diff --git a/BD code - profile overlay.ipynb b/BD code - profile overlay.ipynb
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+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "matplotlib.use('TkAgg')\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pathlib import Path\n",
+    "import math\n",
+    "from math import pi\n",
+    "from math import sqrt\n",
+    "import statistics\n",
+    "import scipy.integrate\n",
+    "from scipy.signal import find_peaks\n",
+    "from scipy.signal import argrelmin\n",
+    "from numpy import trapz\n",
+    "from scipy.integrate import cumtrapz"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "user inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# SETUP VARIABLES - USER INPUTS\n",
+    "BD = 2 #Bluedrop file is from \n",
+    "soiltype = \"s\" #s = sand, c=clay, m=mixed, u=unknown\n",
+    "atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays)\n",
+    "tiptype = 'c'  # c = cone, p = parabolic, b = blunt\n",
+    "#offset = 1 # this value is subtracted from the accelerometer readings\n",
+    "droptype = 'a' #w = water, #a = air\n",
+    "sign = \"uk\" #enter an effective unit weight value in kg/m^3 or \"uk\" if unknown \n",
+    "# paste the filepath to the folder where the BD data is stored\n",
+    "binFilepath = Path(\"H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/08March23/BD2 3.8.23 - Drops Only\")\n",
+    "#paste the filepath to an excel file that the analysis results will be printed in"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "set functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# FUNCTIONS FOR USE IN ANALYSIS\n",
+    "def masslength(tiptype): #sets the mass and length of the pentrometer based on the tip\n",
+    "    global mass\n",
+    "    global length\n",
+    "    if tiptype == 'c':\n",
+    "        mass = 7.71 #kg\n",
+    "        length = 8.48-0.93 #originally 7.87, 7.57 for perfect 60 deg, 8.48 measured - .93 measured 90 deg\n",
+    "    elif tiptype == 'p':\n",
+    "        mass = 9.15\n",
+    "        length = 8.26\n",
+    "    elif tiptype == 'b':\n",
+    "        mass = 10.30\n",
+    "        length = 8.57\n",
+    "\n",
+    "def dropstartend(peak): #after locating the peaks, this function chops the minute long file into a smaller segment immediately before and after the peak\n",
+    "    global dropstart\n",
+    "    global dropend\n",
+    "    if peak <= 1500:\n",
+    "        dropstart = 1\n",
+    "        dropend = peak + 500\n",
+    "    elif peak > 119500:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = 120000\n",
+    "    else:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = peak + 500\n",
+    "\n",
+    "def accPick(dg, d): #this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "    maxAcc = dg[\"250g (g)\"].max()\n",
+    "    global acc\n",
+    "    global accName\n",
+    "    global accNameg\n",
+    "    global accg\n",
+    "    if maxAcc < 5: #- offset:\n",
+    "        if dg[\"2g (g)\"].max() < 1.8: #offset:  # does an extra check for the 2g because of noise\n",
+    "            acc = dfCal[\"2g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"2g (g)\"]\n",
+    "            accName = \"2g (m/s^2)\"\n",
+    "            accNameg = \"2g (g)\"\n",
+    "        else:\n",
+    "            acc = dfCal[\"18g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"18g (g)\"]\n",
+    "            accName = \"18g (m/s^2)\"\n",
+    "            accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 18: #- offset\n",
+    "        acc = dfCal[\"18g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"18g (g)\"]\n",
+    "        accName = \"18g (m/s^2)\"\n",
+    "        accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 50: #- offset:\n",
+    "        acc = dfCal[\"50g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"50g (m/s^2)\"\n",
+    "        accNameg = \"50g (g)\"\n",
+    "    else:\n",
+    "        acc = dfCal[\"250g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"250g (m/s^2)\"\n",
+    "        accNameg = \"250g (g)\"\n",
+    "\n",
+    "def findchangepts(): #This function picks the moment that the BD impacts the ground (not in use currently)\n",
+    "    global drop\n",
+    "    jlist = list()\n",
+    "    global jindex\n",
+    "    print(\"finding start of drop...\")\n",
+    "    for i in range(4,len(accg)-4):\n",
+    "        p1 = 1\n",
+    "        #print(p1)\n",
+    "        p2 = i\n",
+    "        #print(p2)\n",
+    "        p3 = len(accg)\n",
+    "        #print(p3)\n",
+    "        sample1 = list(accg[p1:p2-1])\n",
+    "        #print(sample1)\n",
+    "        sample2 = list(accg[p2:p3])\n",
+    "        #print(sample2)\n",
+    "        stat1 = math.log(statistics.variance(sample1))\n",
+    "        stat2 = math.log(statistics.variance(sample2))\n",
+    "        #print(stat1)\n",
+    "\n",
+    "        j1 = (i-1)*stat1\n",
+    "        j2 = ((len(accg)-1)-i+1)*stat2\n",
+    "        j = j1+j2\n",
+    "        #print(j)\n",
+    "        jlist.append(j)\n",
+    "\n",
+    "    drop = min(jlist)\n",
+    "    #print(\"drop is\")\n",
+    "    #print(drop)\n",
+    "    jlist = np.array(jlist)\n",
+    "    #print(jlist)\n",
+    "    #print(jlist.size)\n",
+    "    jlist = np.insert(jlist, 0, (0,0,0,0)) #reshape to match up with dataframe d\n",
+    "    jlist = np.append(jlist, (0,0,0,0)) #reshape to match up with dataframe d\n",
+    "    #print(jlist.size) #should be 2000\n",
+    "    jindex = np.where(jlist==drop) #finds the index of the drop start\n",
+    "    jindex = int(jindex[0]) #converts the index into a number from a tuple\n",
+    "    print(\"Jlist: \", jlist)\n",
+    "\n",
+    "def finddropend(n): #finds the location after the peak where the deceleration is 1 \n",
+    "    global penend\n",
+    "    below0list = list()\n",
+    "    #for i in range(dropstart+jindex, dropend, 1):\n",
+    "    for i in range(peak, dropend, 1):\n",
+    "        if accg[i] < 1: #the offset is applied later in the code\n",
+    "            penend = i \n",
+    "            below0list = np.append(below0list, penend)\n",
+    "    penend=int(min(below0list))\n",
+    "\n",
+    "def integration(d, accint): #integrates the deceleration data to solve for velocity and penetration depth\n",
+    "    global vel\n",
+    "    global maxvel\n",
+    "    global dep\n",
+    "    global maxdep\n",
+    "    #accint = acc[penstart:penend]\n",
+    "    #print(len(d))\n",
+    "    #print(len(accint))\n",
+    "    vel = scipy.integrate.cumtrapz(accint, x=d[\"Time (s)\"])  # solves for velocity\n",
+    "    vel = np.array(vel)\n",
+    "    vel = numpy.insert(vel, 0, 0) #not sure what to insert here, but it makes it the right size\n",
+    "    vel = np.flip(vel)\n",
+    "    maxvel = vel.max()\n",
+    "    maxvel = round(maxvel,1)\n",
+    "    dep = scipy.integrate.cumtrapz(vel, x=d[\"Time (s)\"])  # solves for penetration depth\n",
+    "    dep = numpy.insert(dep, 0, 0)  # not sure what to insert here, but it makes it the right size\n",
+    "    maxdep = dep.max()\n",
+    "    maxdep = round(maxdep,4)\n",
+    "    d.insert(9, \"Velocity (m/s)\", vel)\n",
+    "    d.insert(10, \"Penetration Depth (m)\", dep)\n",
+    "\n",
+    "def peakpick():\n",
+    "    global penstart\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.plot(dfCalg['Count'], dfCalg[accNameg], label=accNameg)\n",
+    "    plt.plot(dfCalg['Count'], dfCalg['2g (g)'], label='2g')\n",
+    "\n",
+    "    ax1.set_xlim(left=dropstart, right=dropend)\n",
+    "    ax1.legend()\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set(xlabel=\"Time\")\n",
+    "    ax1.set_title('Double-click start of drop #' + str(a))\n",
+    "    startendpt = plt.ginput(2, 0)\n",
+    "    pentimes = []\n",
+    "    for t in startendpt:\n",
+    "        for x in t:\n",
+    "            pentimes.append(x)\n",
+    "\n",
+    "    penstart = int(pentimes[0])\n",
+    "    print(\"start of penetration: \", penstart)\n",
+    "\n",
+    "def CheckingFunction(): # (to be used with auto peak finding) This function is added to check the values of the start and end of the drop if the autofinding function doesn't work\n",
+    "\n",
+    "    global jindex\n",
+    "    global num1\n",
+    "    \n",
+    "    xvalues=np.linspace(0,len(dg)-1,len(dg))\n",
+    "    plt.figure(num=1)\n",
+    "    temp_dg=dg['250g (g)']\n",
+    "    plt.plot(xvalues,temp_dg)\n",
+    "    plt.grid(visible=True,which='both')\n",
+    "    plt.show()\n",
+    "    print ('The start of the drop is', jindex)\n",
+    "    print ('The end of the drop is', num1)\n",
+    "    print('Are the start and end of the drop correct?(y/n)')\n",
+    "    drop_input=input()\n",
+    "    if drop_input=='n':   \n",
+    "        peakpick()\n",
+    "        jindex = penstart\n",
+    "        num1 = penend\n",
+    "\n",
+    "def areafind(): #finds the embedded area based on the penetration depth, area type, and the tip\n",
+    "    global area\n",
+    "    global trunc_index\n",
+    "    a1 = list() #placeholder for the penetrated area at that specific depth\n",
+    "    d1 = dep*100 #penetration depth array, in cm\n",
+    "    #print(len(d1))\n",
+    "    r = list() #placeholder for the radius at that specific depth\n",
+    "    if tiptype == 'c':\n",
+    "        if atype == 'm':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(.22+d1[k]*((4.375-.22)/7.55))\n",
+    "                    #r.append(d1[k]*np.tan(30*pi/180)) this is from the original matlabcode\n",
+    "                    a1.append(pi*r[k]*(sqrt((r[k]**2)+(d1[k]**2))))\n",
+    "                elif d1[k]>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]*(sqrt((r[k]**2)+(length**2))))\n",
+    "                a1[k] = a1[k]/10000\n",
+    "            area = a1\n",
+    "            #print(r)\n",
+    "            print(np.column_stack((d1,r, area)))\n",
+    "        elif atype == 'p':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(.22+d1[k]*((4.375-.22)/7.55))\n",
+    "                    # r.append(d1[k]*np.tan(30*pi/180))\n",
+    "                    a1.append(pi*r[k]**2)\n",
+    "                elif d1[k]>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    if r[k-1]<r[k]:\n",
+    "                        trunc_index = r.index(r[k-1])+jindex+dropstart #performs analysis only on readings beyond depth of cone height\n",
+    "                    a1.append(pi*(r[k])**2)\n",
+    "                a1[k] = a1[k]/10000\n",
+    "            area = a1\n",
+    "\n",
+    "    elif tiptype == 'b':\n",
+    "        if atype =='m':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]**2 + 2*pi*r[k]*d1[k])\n",
+    "                if d1(k)>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]**2 + 2*pi*r[k]*length)\n",
+    "                a1[k]=a1[k]/10000\n",
+    "            area = a1\n",
+    "        elif atype == 'p':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                a1.append(pi*4.375**2)\n",
+    "                a1[k]=a1[k]/10000\n",
+    "            area = a1\n",
+    "\n",
+    "    '''elif tiptype == \"p\":\n",
+    "        if atype == 'm':\n",
+    "            for k in range(1,len(d)):\n",
+    "                if d1[k]<length:\n",
+    "                     r[k]=sqrt(2.4184*d1[k])\n",
+    "                           polarfun = @(theta,r) r.*sqrt(0.745*r.^2 + 1);\n",
+    "                           A1(k)= integral2(polarfun,0,2*pi,0,r(k));\n",
+    "            \n",
+    "        elif atype == 'p':\n",
+    "            for k in range(1,len(d)):'''\n",
+    "\n",
+    "def qdynfun(acc): # calculates dynamic bearing capacity\n",
+    "    global qdyn\n",
+    "    global maxbcdep\n",
+    "    global maxqdyn\n",
+    "    global qdyntable\n",
+    "\n",
+    "    buoy = 1020*0.002473\n",
+    "    if droptype == \"w\": #water drops\n",
+    "        Fbe = (mass-buoy)*acc #drop force\n",
+    "\n",
+    "    elif droptype ==\"a\": #air drops\n",
+    "        Fbe = mass*acc\n",
+    "\n",
+    "    qdyn = (Fbe/area)/1000 #Dynamic bearing capacity (kPa)\n",
+    "    qdyntable = pd.DataFrame()\n",
+    "    qdyntable[\"Qdyn\"] = qdyn\n",
+    "    qdyntable[\"Depth\"] = dep\n",
+    "    qdyntablet = qdyntable#.truncate(before=trunc_index)\n",
+    "    qdynt = qdyntablet[\"Qdyn\"]\n",
+    "    #print(qdyntable)\n",
+    "\n",
+    "    maxqdyn = qdynt.max() #gives maximum qdyn\n",
+    "    maxbcdep = qdyntablet.loc[qdyntable[\"Qdyn\"]==maxqdyn, 'Depth'].item()\n",
+    "\n",
+    "    maxqdyn = round(maxqdyn,1)\n",
+    "    maxbcdep = round(maxbcdep,4)\n",
+    "    #print(\"maxbcdep = \", maxbcdep) #finds the penetration depth corresponding to the maximum qdyn\n",
+    "\n",
+    "\n",
+    "    \"\"\"bcmin = argrelmin(qdyn)\n",
+    "    peaksArray = np.array(bcmin)\n",
+    "    print(\"Peaks Array = \", peaksArray)\"\"\"\n",
+    "\n",
+    "def qsbcfun(acc): #calculates quasi-static bearing capacity\n",
+    "    global bctable\n",
+    "    global qsbc\n",
+    "    global maxHqsbc\n",
+    "    global maxLqsbc\n",
+    "    global maxAqsbc\n",
+    "\n",
+    "    if droptype == \"w\":\n",
+    "        srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction. \n",
+    "        srfk = [0.2, 0.4, 1, 1.5] #list of strain rate factors to run; must be in increasing order\n",
+    "\n",
+    "        bctable = pd.DataFrame()\n",
+    "        for i in range(0,len(srfk)):\n",
+    "            fsr = 1+srfk[i]*srcv\n",
+    "            qsbc = qdyn/fsr\n",
+    "            bctable.insert(i, \"qsbc for srf = \"+str(srfk[i]), qsbc)\n",
+    "\n",
+    "        bctable_avgs = pd.DataFrame()\n",
+    "        bctable_avgs[\"High Average qsbc\"]= (bctable.iloc[:,0]+bctable.iloc[:,1])/2 #Average of the lowest 2 strain rate factors\n",
+    "        bctable_avgs[\"Low Average qsbc\"] = (bctable.iloc[:,int(len(srfk))-1]+bctable.iloc[:,int(len(srfk)-2)])/2 #average of the highest 2 strain rate factors\n",
+    "        maxHqsbc = bctable_avgs[\"High Average qsbc\"].max()\n",
+    "        maxHqsbc = round(maxHqsbc, 1)\n",
+    "        maxLqsbc = bctable_avgs[\"Low Average qsbc\"].max()\n",
+    "        maxLqsbc = round(maxLqsbc,1)\n",
+    "        maxAqsbc = \"-\"\n",
+    "\n",
+    "        #print(bctable)\n",
+    "\n",
+    "    elif droptype == \"a\":\n",
+    "        srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction. \n",
+    "        srfk = 0.31*maxvel\n",
+    "        fsr = 1+srfk*srcv\n",
+    "        qsbc = qdyn/fsr\n",
+    "        maxHqsbc = \"-\"\n",
+    "        maxLqsbc = \"-\"\n",
+    "        maxAqsbc = qsbc.max()\n",
+    "        maxAqsbc = round(maxAqsbc,1)\n",
+    "\n",
+    "def dr(accg): #Albatal 2019 method for calculating relative density (Duck, NC specific!)\n",
+    "    global Dr\n",
+    "    maxacc = accg.max() #maximum deceleration, in g\n",
+    "    #print(\"Max deceleration = \", maxacc)\n",
+    "    Dr = -2.18*10**-4*maxacc**3+1.29*10**-2*maxacc**2+1.61*maxacc-13.09 #Albatal 2019\n",
+    "    Dr = round(Dr, 1)\n",
+    "    #print(\"Relative density is \", dr)\n",
+    "\n",
+    "def ignore_drop():\n",
+    "    global keep_drop\n",
+    "    print('Keep Drop? (y/n)')\n",
+    "    keep_drop=input()\n",
+    "\n",
+    "def duncan_correlation(): #duncan correlation for caluclating friction angle\n",
+    "    global phi\n",
+    "    global sign\n",
+    "    #coefficients A, B, C, and D used in the Duncan Correlation. Duncan[34,10,3,2], Albatal[34,10,2,5]\n",
+    "    A = 34\n",
+    "    B = 10\n",
+    "    C = 3\n",
+    "    D = 2\n",
+    "    pa = 101.325 #kPa\n",
+    "    print(\"max penetration depth = \", maxdep)\n",
+    "    if sign == \"uk\":\n",
+    "        sign = 1120*maxdep #1120 = 70pcf in kg/m^3\n",
+    "\n",
+    "    phi = A + B*Dr/100-(C+D*Dr/100)*math.log(sign/pa)\n",
+    "    phi = round(phi, 1)\n",
+    "    print(\"phi =\", phi)\n",
+    "\n",
+    "def firmnessfactor(acc, drop):\n",
+    "    global maxacc\n",
+    "    global ff\n",
+    "    maxacc = acc.max()\n",
+    "    g = 9.80665\n",
+    "    tp = len(drop)/2000\n",
+    "\n",
+    "    ff = maxacc/(g*tp*maxvel)\n",
+    "    ff = round(ff,1)\n",
+    "    print(\"Firmness factor = \", ff)\n",
+    "\n",
+    "def bctruncate(dropg, drop, acc, qdyn):\n",
+    "    dropg = pd.DataFrame(dropg)\n",
+    "    drop = pd.DataFrame(drop)\n",
+    "    qdyn = pd.DataFrame(qdyn)\n",
+    "    acc = pd.DataFrame(acc)\n",
+    "    dropg = dropg.truncate(before=trunc_index)\n",
+    "    drop = drop.truncate(before=trunc_index)\n",
+    "    acc = acc.truncate(before=trunc_index)\n",
+    "    qdyn = qdyn.truncate(before=trunc_index)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Plots for exporting\n",
+    "def overviewplot(): #Plot showing all accellerometers and pore pressure readings\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(14, 7)\n",
+    "    #plt.tight_layout()\n",
+    "    ax1.plot(time, g250g, label=\"250g\")\n",
+    "    ax1.plot(time, g50g, label=\"50g\")\n",
+    "    ax1.plot(time, g18g, label=\"18g\")\n",
+    "    ax1.plot(time, g2g, label=\"2g\")\n",
+    "    ax1.legend(loc = \"upper right\")\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(time, ppm, label=\"Pore Pressure\")\n",
+    "    ax2.set(ylabel=\"Pore Pressure (kPa)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(time, gX55g, label=\"X 55g\")\n",
+    "    ax3.plot(time, gY55g, label=\"Y 55g\")\n",
+    "    ax3.legend(loc = \"upper right\")\n",
+    "    ax3.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax3.set(xlabel=\"Time (s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" Overview.png\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "def integplot(drop, accName): #Deceleration,Velocity,and penetration depth vs time plots\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    #resize to 7,7, 7,14\n",
+    "    #plt.tight_layout()\n",
+    "    timereset = drop[\"Time (s)\"]- drop[\"Time (s)\"].iloc[0]\n",
+    "    ax1.plot(timereset, drop[accName], color = \"k\" ) #,marker = 11\n",
+    "    ax1.set(ylabel=\"Deceleration (m/s^2)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum+ \" Drop #\"+str(a))\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(timereset, drop['Velocity (m/s)'] , color = \"k\" )\n",
+    "    ax2.set(ylabel=\"Velocity (m/s)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(timereset, drop[\"Penetration Depth (m)\"] , color = \"k\")\n",
+    "    ax3.set(ylabel=\"Penetration Depth (m)\", xlabel=\"Time(s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" \"+str(a)+\" Integ\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "def dep_qsbc_comboplot(dropg, drop, accNameg, qdyn):\n",
+    "    fig, (ax1, ax2) = plt.subplots(1,2)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    ax1.plot(drop[\"X55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"b\", linestyle = \"dashed\")\n",
+    "    ax1.plot(drop[\"Y55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"r\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\", \"X tilt (g)\", \"Y tilt (g)\"], loc = \"upper right\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        ax2.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(qsbc, drop[\"Penetration Depth (m)\"]*100, label=\"QSBC\") #plots QSBC\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,800)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", \"QSBC\"], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    else: #for saturated drops, use a range of strain-rate factors\n",
+    "        ax2.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(bctable.iloc[:,0], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax2.plot(bctable.iloc[:,len(bctable.columns)-1], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctable.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax2.plot(bctable.iloc[:,i], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[i]), color = '.6')\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", str(bctable.columns[0]), str(bctable.columns[len(bctable.columns)-1])], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "    \n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    \n",
+    "\n",
+    "\n",
+    "\n",
+    "#plots for troubleshooting \n",
+    "def depthplot(dropg, drop, accNameg): #Velocity and develeration vs. penetration depth \n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\"])\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    plt.show()\n",
+    "\n",
+    "def peakplot(): # Plot showing peak deceleration\n",
+    "    peakplot = plt.plot(x)\n",
+    "    peakplot = plt.plot(peaks, x[peaks], \"x\")\n",
+    "    plt.show()\n",
+    "\n",
+    "def qdynplot(drop, qdyn): #Plot showing dynamic bearing capacity vs depth\n",
+    "    #print(len(drop))\n",
+    "    #print(len(qdyn))\n",
+    "    #print((bctable.iloc[:,0]))\n",
+    "    #print(len(bctable.iloc[:,len(bctable.columns)-1]))\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "\n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        ax1.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax1.plot(qsbc, drop[\"Penetration Depth (m)\"]*100, label=\"QSBC\") #plots QSBC\n",
+    "        ax1.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax1.set_xlim(0,)\n",
+    "        ax1.invert_yaxis()\n",
+    "        ax1.legend([\"Qdyn\", \"QSBC\"])\n",
+    "        ax1.set_title(\"Bearing Capacity- \"+fileNum+ \" \"+str(a))\n",
+    "        ax1.grid()\n",
+    "\n",
+    "    else:\n",
+    "        ax1.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax1.plot(bctable.iloc[:,0], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax1.plot(bctable.iloc[:,len(bctable.columns)-1], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctable.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax1.plot(bctable.iloc[:,i], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[i]), color = \"k\")\n",
+    "        ax1.set(xlabel=\"Bearing Capacity (kPa)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "        ax1.set_xlim(0,)\n",
+    "        ax1.invert_yaxis()\n",
+    "        ax1.legend([\"Qdyn\", str(bctable.columns[0]), str(bctable.columns[len(bctable.columns)-1])])\n",
+    "        ax1.set_title(\"Bearing Capacity- \"+fileNum+ \" \"+str(a))\n",
+    "    \n",
+    "    plt.show()\n",
+    "\n",
+    "def tiltplot():\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.plot(time, gX55g, label=\"2g\")\n",
+    "    plt.plot(time, gY55g, label=\"2g\")\n",
+    "    ax1.legend()\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set(xlabel=\"Time (s)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib.font_manager import FontProperties\n",
+    "font = FontProperties()\n",
+    "font.set_name('Calibri')\n",
+    "\n",
+    "def duck_dep_qsbc_comboplot(dropg, drop, dropt, accNameg, qdynt):\n",
+    "    font = {'fontname': 'Calibri'}\n",
+    "    fig, (ax1, ax2) = plt.subplots(1,2)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    #ax1.plot(drop[\"X55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"b\", linestyle = \"dashed\")\n",
+    "    #ax1.plot(drop[\"Y55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"r\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.set_xlim(left = 0)\n",
+    "    ax1.set_ylim(0,dep.max()*100+.25)\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\"])\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    \n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        y = dropt[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdynt[10:-50], y[10:-50], label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc[10:-50], y[10:-50], label=\"QSBC\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\",)\n",
+    "        ax2.set_xlim(0,qdyn.max()+10)\n",
+    "        ax2.set_ylim(0,dep.max()*100+.25)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", \"QSBC\"], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    else: #for saturated drops, use a range of strain-rate factors\n",
+    "        y = list(dropt[\"Penetration Depth (m)\"]*100)\n",
+    "        ax2.plot(qdynt[10:-20], y[10:-20], label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(bctablet.iloc[10:-20,0], y[10:-20], label=str(bctablet.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax2.plot(bctablet.iloc[10:-20,len(bctable.columns)-1], y[10:-20], label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctablet.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax2.plot(bctablet.iloc[10:-20,i], y[10:-20], label=str(bctablet.columns[i]), color = '.6')\n",
+    "            #bctablet.iloc[:,i].pop()\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", str(bctablet.columns[0]), str(bctablet.columns[len(bctablet.columns)-1])], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    #fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" \"+str(a)+\" BC\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Exporting Functions\n",
+    "def exporttoexcel():\n",
+    "    with pd.ExcelWriter(outputPath, mode=\"a\", if_sheet_exists='replace') as writer:\n",
+    "        output_table.to_excel(writer, sheet_name = fileNum, index=False)\n",
+    "\n",
+    "def troubleshooting_export():\n",
+    "        with pd.ExcelWriter(troubleshootingPath, mode=\"a\", if_sheet_exists = 'new') as writer:\n",
+    "            drop1.to_excel(writer, sheet_name = str(a), index = False)\n",
+    "            qdyntable.to_excel(writer, sheet_name = \"qdyn\", index = False)\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Bring in data and calibrate for first sample"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 52569\n",
+      "peak index: 52569\n",
+      "start of penetration:  52522\n",
+      "penend:  52595\n",
+      "offset:  -0.11577380812803753\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [1.99912229e-01 3.30017922e-01 4.00037594e-05]\n",
+      " [3.99495817e-01 4.39854983e-01 8.21087376e-05]\n",
+      " [5.98674146e-01 5.49469017e-01 1.40272516e-04]\n",
+      " [7.97335481e-01 6.58798533e-01 2.14064942e-04]\n",
+      " [9.95317945e-01 7.67754445e-01 3.03190190e-04]\n",
+      " [1.19237563e+00 8.76201423e-01 4.07310090e-04]\n",
+      " [1.38814051e+00 9.83936932e-01 5.25952310e-04]\n",
+      " [1.58212064e+00 1.09069023e+00 6.58451743e-04]\n",
+      " [1.77374864e+00 1.19614909e+00 8.03939924e-04]\n",
+      " [1.96245662e+00 1.30000096e+00 9.61384172e-04]\n",
+      " [2.14774379e+00 1.40197026e+00 1.12965623e-03]\n",
+      " [2.32921072e+00 1.50183716e+00 1.30759779e-03]\n",
+      " [2.50655550e+00 1.59943551e+00 1.49405868e-03]\n",
+      " [2.67954773e+00 1.69463852e+00 1.68790633e-03]\n",
+      " [2.84800107e+00 1.78734364e+00 1.88802091e-03]\n",
+      " [3.01175882e+00 1.87746462e+00 2.09329509e-03]\n",
+      " [3.17068923e+00 1.96492897e+00 2.30264029e-03]\n",
+      " [3.32467829e+00 2.04967395e+00 2.51498711e-03]\n",
+      " [3.47362699e+00 2.13164505e+00 2.72928893e-03]\n",
+      " [3.61745562e+00 2.21079842e+00 2.94453509e-03]\n",
+      " [3.75609998e+00 2.28709873e+00 3.15975203e-03]\n",
+      " [3.88950548e+00 2.36051593e+00 3.37399944e-03]\n",
+      " [4.01762779e+00 2.43102562e+00 3.58637507e-03]\n",
+      " [4.14043070e+00 2.49860789e+00 3.79601466e-03]\n",
+      " [4.25788387e+00 2.56324602e+00 4.00209072e-03]\n",
+      " [4.36997128e+00 2.62493121e+00 4.20383000e-03]\n",
+      " [4.47669855e+00 2.68366655e+00 4.40053078e-03]\n",
+      " [4.57808248e+00 2.73946128e+00 4.59154763e-03]\n",
+      " [4.67414457e+00 2.79232724e+00 4.77628084e-03]\n",
+      " [4.76491813e+00 2.84228276e+00 4.95419091e-03]\n",
+      " [4.85044527e+00 2.88935101e+00 5.12479411e-03]\n",
+      " [4.93077403e+00 2.93355842e+00 5.28765727e-03]\n",
+      " [5.00596825e+00 2.97494014e+00 5.44241827e-03]\n",
+      " [5.07611355e+00 3.01354328e+00 5.58879980e-03]\n",
+      " [5.14131390e+00 3.04942507e+00 5.72660359e-03]\n",
+      " [5.20168508e+00 3.08264921e+00 5.85569679e-03]\n",
+      " [5.25735132e+00 3.11328407e+00 5.97600405e-03]\n",
+      " [5.30844601e+00 3.14140307e+00 6.08750770e-03]\n",
+      " [5.35511105e+00 3.16708429e+00 6.19024484e-03]\n",
+      " [5.39749603e+00 3.19041007e+00 6.28430392e-03]\n",
+      " [5.43576075e+00 3.21146833e+00 6.36982852e-03]\n",
+      " [5.47008109e+00 3.23035589e+00 6.44702876e-03]\n",
+      " [5.50065177e+00 3.24717988e+00 6.51618598e-03]\n",
+      " [5.52768168e+00 3.26205528e+00 6.57764051e-03]\n",
+      " [5.55139414e+00 3.27510499e+00 6.63179003e-03]\n",
+      " [5.57202933e+00 3.28646117e+00 6.67909292e-03]\n",
+      " [5.58983370e+00 3.29625947e+00 6.72004167e-03]\n",
+      " [5.60505753e+00 3.30463762e+00 6.75515459e-03]\n",
+      " [5.61796136e+00 3.31173900e+00 6.78498820e-03]\n",
+      " [5.62880726e+00 3.31770783e+00 6.81011471e-03]\n",
+      " [5.63784755e+00 3.32268299e+00 6.83109370e-03]\n",
+      " [5.64531635e+00 3.32679330e+00 6.84845018e-03]\n",
+      " [5.65142190e+00 3.33015338e+00 6.86265500e-03]\n",
+      " [5.65635092e+00 3.33286597e+00 6.87413333e-03]\n",
+      " [5.66027835e+00 3.33502736e+00 6.88328609e-03]\n",
+      " [5.66337157e+00 3.33672965e+00 6.89049902e-03]\n",
+      " [5.66578670e+00 3.33805877e+00 6.89613339e-03]\n",
+      " [5.66766044e+00 3.33908995e+00 6.90050630e-03]\n",
+      " [5.66910534e+00 3.33988512e+00 6.90387933e-03]\n",
+      " [5.67020945e+00 3.34049275e+00 6.90645736e-03]\n",
+      " [5.67104109e+00 3.34095043e+00 6.90839952e-03]\n",
+      " [5.67165857e+00 3.34129024e+00 6.90984171e-03]\n",
+      " [5.67211111e+00 3.34153929e+00 6.91089878e-03]\n",
+      " [5.67243358e+00 3.34171676e+00 6.91165205e-03]\n",
+      " [5.67265191e+00 3.34183691e+00 6.91216209e-03]\n",
+      " [5.67279043e+00 3.34191314e+00 6.91248570e-03]\n",
+      " [5.67287206e+00 3.34195807e+00 6.91267640e-03]\n",
+      " [5.67291721e+00 3.34198292e+00 6.91278189e-03]\n",
+      " [5.67294281e+00 3.34199700e+00 6.91284169e-03]\n",
+      " [5.67295802e+00 3.34200538e+00 6.91287724e-03]\n",
+      " [5.67296473e+00 3.34200907e+00 6.91289291e-03]\n",
+      " [5.67296600e+00 3.34200977e+00 6.91289587e-03]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max penetration depth is:  0.0567\n",
+      "Pre-truncation d1          Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  200g (m/s^2)  \\\n",
+      "52522  52522.0   26.2615    0.123339    -0.090929    -1.135353      7.583530   \n",
+      "52523  52523.0   26.2620    0.589063     0.345147    -0.932839      8.081497   \n",
+      "52524  52524.0   26.2625    0.702590     0.445602    -0.669309      8.076366   \n",
+      "52525  52525.0   26.2630    0.983377     0.670002    -0.908923      8.360782   \n",
+      "52526  52526.0   26.2635    1.305609     1.057197    -0.393516      8.817706   \n",
+      "...        ...       ...         ...          ...          ...           ...   \n",
+      "52590  52590.0   26.2955   18.296934    18.860279    25.248705     26.429967   \n",
+      "52591  52591.0   26.2960   15.236179    15.091169    19.092327     22.685433   \n",
+      "52592  52592.0   26.2965   12.507849    12.346727    14.744169     19.967296   \n",
+      "52593  52593.0   26.2970   10.511706    10.234559    11.719331     17.858070   \n",
+      "52594  52594.0   26.2975    8.852879     8.612671     9.858375     16.261240   \n",
+      "\n",
+      "       250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  Velocity (m/s)  \\\n",
+      "52522     -0.751401      0.761632      1.625056        4.001226   \n",
+      "52523     -0.576926      0.699724      1.480714        3.995264   \n",
+      "52524     -0.306888      0.932199      1.444090        3.988080   \n",
+      "52525     -0.250419      1.303643      1.773275        3.979053   \n",
+      "52526      0.370017      1.256890      1.948927        3.967400   \n",
+      "...             ...           ...           ...             ...   \n",
+      "52590     23.664232      0.664410      1.222623        0.000633   \n",
+      "52591     18.143294      0.417782      1.615577        0.000391   \n",
+      "52592     14.864469      0.647539      1.608396        0.000218   \n",
+      "52593     12.049703      1.313794      1.665845        0.000051   \n",
+      "52594      8.607261      1.189121      1.993019        0.000000   \n",
+      "\n",
+      "       Penetration Depth (m)  Pore Pressure (kPa)  \n",
+      "52522               0.000000            -1.429354  \n",
+      "52523               0.001999            -1.441340  \n",
+      "52524               0.003995            -1.443156  \n",
+      "52525               0.005987            -1.436981  \n",
+      "52526               0.007973            -1.399932  \n",
+      "...                      ...                  ...  \n",
+      "52590               0.056729            -1.483112  \n",
+      "52591               0.056729            -1.496551  \n",
+      "52592               0.056730            -1.483112  \n",
+      "52593               0.056730            -1.446062  \n",
+      "52594               0.056730            -1.438071  \n",
+      "\n",
+      "[73 rows x 12 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "fileNum= '014F' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "a = 3 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)\n",
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop1 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop1g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop1 = pd.DataFrame(drop1)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "dg = drop1g \n",
+    "d = drop1\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc1 = acc\n",
+    "acc1g = accg\n",
+    "acc1Name = accName\n",
+    "acc1Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop1 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop1g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop1 = pd.DataFrame(drop1)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "dg = drop1g \n",
+    "d = drop1\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc1 = acc\n",
+    "acc1g = accg\n",
+    "acc1Name = accName\n",
+    "acc1Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peakpick()\n",
+    "\n",
+    "finddropend(a) #automatically find the end of the drop\n",
+    "print(\"penend: \", penend)\n",
+    "offset = acc1g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "print(\"offset: \", offset)\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc1g = accg[penstart:penend]\n",
+    "acc1g = acc1g-offset\n",
+    "acc1 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc1 = acc1-offsetms\n",
+    "\n",
+    "\n",
+    "drop1 = d\n",
+    "drop1g = dg\n",
+    "integration(d, acc1) #double integration to solve for velocity and penetration depth\n",
+    "drop1 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc1) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc1) #calculation of quasi-static bearing capacities\n",
+    "qsbc1 = qsbc\n",
+    "qdyn1 = qdyn\n",
+    "integplot(drop1,acc1Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "print(\"Max penetration depth is: \", maxdep)\n",
+    "print(\"Pre-truncation d1\", drop1)\n",
+    "drop1 = pd.DataFrame(drop1)\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "acc1 = pd.DataFrame(acc1)\n",
+    "qdyn1 = pd.DataFrame(qdyn1)\n",
+    "\n",
+    "drop1t = drop1 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop1gt = drop1g #.truncate(before=trunc_index)\n",
+    "acc1t = acc1 #.truncate(before=trunc_index)\n",
+    "acc1t = np.array(acc1t)\n",
+    "acc1gt = acc1g #.truncate(before=trunc_index)\n",
+    "acc1gt = np.array(acc1gt)\n",
+    "drop1t = drop1 #truncate(before=trunc_index)\n",
+    "qdyn1t = qdyn1#.truncate(before=trunc_index)\n",
+    "\n",
+    "duck_dep_qsbc_comboplot(drop1g, drop1, drop1t, acc1Nameg, qdyn1t)\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Trial 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 53576\n",
+      "start of penetration:  53537\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [2.67703840e-01 3.67325756e-01 5.24517085e-05]\n",
+      " [5.34974050e-01 5.14412871e-01 1.19940456e-04]\n",
+      " [8.01651552e-01 6.61173801e-01 2.15842204e-04]\n",
+      " [1.06747736e+00 8.07466015e-01 3.39534301e-04]\n",
+      " [1.33206241e+00 9.53075403e-01 4.90418300e-04]\n",
+      " [1.59488199e+00 1.09771320e+00 6.67689633e-04]\n",
+      " [1.85533038e+00 1.24104606e+00 8.70280151e-04]\n",
+      " [2.11281431e+00 1.38274748e+00 1.09689750e-03]\n",
+      " [2.36681864e+00 1.52253397e+00 1.34610152e-03]\n",
+      " [2.61693180e+00 1.66017902e+00 1.61637741e-03]\n",
+      " [2.86285098e+00 1.79551601e+00 1.90619918e-03]\n",
+      " [3.10435842e+00 1.92842507e+00 2.21405621e-03]\n",
+      " [3.34128051e+00 2.05881067e+00 2.53844011e-03]\n",
+      " [3.57346740e+00 2.18659034e+00 2.87783793e-03]\n",
+      " [3.80079196e+00 2.31169412e+00 3.23074425e-03]\n",
+      " [4.02314557e+00 2.43406223e+00 3.59566688e-03]\n",
+      " [4.24042806e+00 2.55363955e+00 3.97111934e-03]\n",
+      " [4.45254383e+00 2.67037346e+00 4.35561946e-03]\n",
+      " [4.65940481e+00 2.78421550e+00 4.74769883e-03]\n",
+      " [4.86092908e+00 2.89512058e+00 5.14590509e-03]\n",
+      " [5.05703541e+00 3.00304399e+00 5.54879464e-03]\n",
+      " [5.24764402e+00 3.10794184e+00 5.95493636e-03]\n",
+      " [5.43268028e+00 3.20977306e+00 6.36292205e-03]\n",
+      " [5.61207525e+00 3.30849969e+00 6.77137139e-03]\n",
+      " [5.78576929e+00 3.40408893e+00 7.17894404e-03]\n",
+      " [5.95370825e+00 3.49651096e+00 7.58433496e-03]\n",
+      " [6.11583464e+00 3.58573416e+00 7.98625533e-03]\n",
+      " [6.27209250e+00 3.67172773e+00 8.38344533e-03]\n",
+      " [6.42243735e+00 3.75446718e+00 8.77470205e-03]\n",
+      " [6.56683974e+00 3.83393631e+00 9.15889370e-03]\n",
+      " [6.70527733e+00 3.91012282e+00 9.53494282e-03]\n",
+      " [6.83772176e+00 3.98301112e+00 9.90179244e-03]\n",
+      " [6.96414222e+00 4.05258423e+00 1.02584150e-02]\n",
+      " [7.08451649e+00 4.11882994e+00 1.06038443e-02]\n",
+      " [7.19883055e+00 4.18174052e+00 1.09371776e-02]\n",
+      " [7.30707557e+00 4.24131113e+00 1.12575681e-02]\n",
+      " [7.40924676e+00 4.29753911e+00 1.15642236e-02]\n",
+      " [7.50533883e+00 4.35042157e+00 1.18563930e-02]\n",
+      " [7.59534603e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.67927176e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.75713698e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.82898389e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.89487667e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.95489976e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.00917355e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.05787399e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.10122552e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.13949515e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.17300031e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.20210403e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.22719892e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.24869217e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.26698264e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.28243761e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.29539211e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.30616133e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.31504230e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.32230401e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.32818239e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.33288621e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.33660394e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.33950488e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34173771e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34343045e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34469069e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34560574e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34624695e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34667688e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34695047e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34711504e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34720906e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34725915e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34728267e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34729121e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.34729286e+00 4.37500000e+00 1.19934265e-02]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max penetration depth is:  0.0835\n",
+      "Pre-truncation d1          Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  200g (m/s^2)  \\\n",
+      "53537  53537.0   26.7690   -0.021884    -0.325301    -1.561538     12.106918   \n",
+      "53538  53538.0   26.7695   -0.002523    -0.299851    -1.297549     12.115255   \n",
+      "53539  53539.0   26.7700    0.408521     0.062016    -0.986648     12.454822   \n",
+      "53540  53540.0   26.7705    1.107617     0.777492    -0.579473     13.174357   \n",
+      "53541  53541.0   26.7710    2.166898     1.849819     0.150253     14.221275   \n",
+      "...        ...       ...         ...          ...          ...           ...   \n",
+      "53608  53608.0   26.8045   19.580556    29.610954    46.478073     42.543516   \n",
+      "53609  53609.0   26.8050   18.903300    20.800537    31.219584     33.568885   \n",
+      "53610  53610.0   26.8055   15.805783    15.601148    21.108273     28.315380   \n",
+      "53611  53611.0   26.8060   12.700919    12.385391    15.151038     25.038352   \n",
+      "53612  53612.0   26.8065   10.586530    10.319596    11.724236     22.889045   \n",
+      "\n",
+      "       250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  Velocity (m/s)  \\\n",
+      "53537     -2.028470      0.919331      2.899139        5.357827   \n",
+      "53538     -1.205325      0.792228      2.695050        5.350327   \n",
+      "53539     -0.842620      0.883445      2.951993        5.340481   \n",
+      "53540     -1.171299      0.895454      2.760543        5.326619   \n",
+      "53541     -0.703619      1.092471      2.430065        5.306413   \n",
+      "...             ...           ...           ...             ...   \n",
+      "53608     45.897841      5.865627      2.490243        0.001338   \n",
+      "53609     29.851214      3.343296      0.332301        0.000665   \n",
+      "53610     20.405677      1.789894      0.404113        0.000276   \n",
+      "53611     15.071522      1.382278      0.786439        0.000066   \n",
+      "53612     12.371866      0.999253      1.018103        0.000000   \n",
+      "\n",
+      "       Penetration Depth (m)  Pore Pressure (kPa)  \n",
+      "53537               0.000000            -2.037040  \n",
+      "53538               0.002677            -2.051206  \n",
+      "53539               0.005350            -2.067915  \n",
+      "53540               0.008017            -2.070458  \n",
+      "53541               0.010675            -2.078812  \n",
+      "...                      ...                  ...  \n",
+      "53608               0.083472            -2.197589  \n",
+      "53609               0.083473            -2.206670  \n",
+      "53610               0.083473            -2.167077  \n",
+      "53611               0.083473            -2.150005  \n",
+      "53612               0.083473            -2.178338  \n",
+      "\n",
+      "[76 rows x 12 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "fileNum= '0182' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "a = 4 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)\n",
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop2 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop2g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop2 = pd.DataFrame(drop2)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop2g = pd.DataFrame(drop2g)\n",
+    "dg = drop2g \n",
+    "d = drop2\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc2 = acc\n",
+    "acc2g = accg\n",
+    "acc2Name = accName\n",
+    "acc2Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop2 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop2g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop2 = pd.DataFrame(drop2)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop2g = pd.DataFrame(drop2g)\n",
+    "dg = drop2g \n",
+    "d = drop2\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc2 = acc\n",
+    "acc2g = accg\n",
+    "acc2Name = accName\n",
+    "acc2Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peakpick()\n",
+    "\n",
+    "finddropend(a) #automatically find the end of the drop\n",
+    "offset = acc2g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc2g = accg[penstart:penend]\n",
+    "acc2g = acc2g-offset\n",
+    "acc2 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc2 = acc2-offsetms\n",
+    "\n",
+    "\n",
+    "drop2 = d\n",
+    "drop2g = dg\n",
+    "integration(d, acc2) #double integration to solve for velocity and penetration depth\n",
+    "drop2 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc2) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc2) #calculation of quasi-static bearing capacities\n",
+    "qsbc2 = qsbc\n",
+    "qdyn2 = qdyn\n",
+    "integplot(drop2,acc2Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "print(\"Max penetration depth is: \", maxdep)\n",
+    "print(\"Pre-truncation d1\", drop2)\n",
+    "drop2 = pd.DataFrame(drop2)\n",
+    "drop2g = pd.DataFrame(drop2g)\n",
+    "acc2 = pd.DataFrame(acc2)\n",
+    "qdyn2 = pd.DataFrame(qdyn2)\n",
+    "\n",
+    "drop2t = drop2 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop2gt = drop2g #.truncate(before=trunc_index)\n",
+    "acc2t = acc2 #.truncate(before=trunc_index)\n",
+    "acc2t = np.array(acc2t)\n",
+    "acc2gt = acc2g #.truncate(before=trunc_index)\n",
+    "acc2gt = np.array(acc2gt)\n",
+    "drop2t = drop2 #truncate(before=trunc_index)\n",
+    "qdyn2t = qdyn2#.truncate(before=trunc_index)\n",
+    "\n",
+    "duck_dep_qsbc_comboplot(drop2g, drop2, drop2t, acc2Nameg, qdyn2t)\n",
+    "\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Trial 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 100949\n",
+      "start of penetration:  100907\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [2.66738636e-01 3.66794574e-01 5.22609137e-05]\n",
+      " [5.33079768e-01 5.13370389e-01 1.19360672e-04]\n",
+      " [7.98922656e-01 6.59672005e-01 2.14717646e-04]\n",
+      " [1.06412463e+00 8.05620903e-01 3.37800002e-04]\n",
+      " [1.32849110e+00 9.51110004e-01 4.88197433e-04]\n",
+      " [1.59177893e+00 1.09600549e+00 6.65437420e-04]\n",
+      " [1.85371491e+00 1.24015701e+00 8.68940983e-04]\n",
+      " [2.11402188e+00 1.38341204e+00 1.09802198e-03]\n",
+      " [2.37243880e+00 1.52562692e+00 1.35190351e-03]\n",
+      " [2.62872662e+00 1.66667008e+00 1.62973283e-03]\n",
+      " [2.88266070e+00 1.80641791e+00 1.93058442e-03]\n",
+      " [3.13402669e+00 1.94475244e+00 2.25346318e-03]\n",
+      " [3.38262020e+00 2.08156118e+00 2.59731105e-03]\n",
+      " [3.62823619e+00 2.21673131e+00 2.96099767e-03]\n",
+      " [3.87066541e+00 2.35014765e+00 3.34331656e-03]\n",
+      " [4.10970849e+00 2.48170050e+00 3.74300979e-03]\n",
+      " [4.34518551e+00 2.61129083e+00 4.15879256e-03]\n",
+      " [4.57693287e+00 2.73882862e+00 4.58935892e-03]\n",
+      " [4.80480250e+00 2.86423237e+00 5.03339003e-03]\n",
+      " [5.02866467e+00 2.98743069e+00 5.48956939e-03]\n",
+      " [5.24840262e+00 3.10835932e+00 5.95658140e-03]\n",
+      " [5.46390544e+00 3.22695723e+00 6.43310293e-03]\n",
+      " [5.67506904e+00 3.34316713e+00 6.91780997e-03]\n",
+      " [5.88179617e+00 3.45693551e+00 7.40938230e-03]\n",
+      " [6.08399120e+00 3.56820973e+00 7.90649493e-03]\n",
+      " [6.28155737e+00 3.67693654e+00 8.40781352e-03]\n",
+      " [6.47439809e+00 3.78306279e+00 8.91199894e-03]\n",
+      " [6.66242102e+00 3.88653766e+00 9.41772040e-03]\n",
+      " [6.84554170e+00 3.98731467e+00 9.92366886e-03]\n",
+      " [7.02368141e+00 4.08535050e+00 1.04285555e-02]\n",
+      " [7.19676617e+00 4.18060443e+00 1.09311122e-02]\n",
+      " [7.36472700e+00 4.27303850e+00 1.14300960e-02]\n",
+      " [7.52749694e+00 4.36261587e+00 1.19242822e-02]\n",
+      " [7.68501135e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.83721312e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.98405598e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.12550275e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.26152304e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.39209275e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.51719014e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.63679240e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.75088012e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.85944394e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.96248245e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.05999483e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.15198734e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.23848664e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.31953630e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.39518590e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.46549063e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.53051457e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.59033671e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.64506419e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.69483550e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.73981356e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.78019337e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.81621422e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.84814974e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.87629067e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.90093717e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.92239281e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.94095590e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.95691594e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.97055634e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.98214808e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.99193615e+00 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.00259857e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00277532e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.00308146e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.00318357e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00319553e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00320206e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00320512e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00320623e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00320652e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00320658e+01 4.37500000e+00 1.19934265e-02]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    }
+   ],
+   "source": [
+    "fileNum= '01BE' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "a = 1 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)\n",
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop3 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop3g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop3 = pd.DataFrame(drop3)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop3g = pd.DataFrame(drop3g)\n",
+    "dg = drop3g \n",
+    "d = drop3\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc3 = acc\n",
+    "acc3g = accg\n",
+    "acc3Name = accName\n",
+    "acc3Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop3 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop3g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop3 = pd.DataFrame(drop3)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop3g = pd.DataFrame(drop3g)\n",
+    "dg = drop3g \n",
+    "d = drop3\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc3 = acc\n",
+    "acc3g = accg\n",
+    "acc3Name = accName\n",
+    "acc3Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peakpick()\n",
+    "\n",
+    "finddropend(a) #automatically find the end of the drop\n",
+    "offset = acc3g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc3g = accg[penstart:penend]\n",
+    "acc3g = acc3g-offset\n",
+    "acc3 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc3 = acc3-offsetms\n",
+    "\n",
+    "\n",
+    "drop3 = d\n",
+    "drop3g = dg\n",
+    "integration(d, acc3) #double integration to solve for velocity and penetration depth\n",
+    "drop3 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc3) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc3) #calculation of quasi-static bearing capacities\n",
+    "qsbc3 = qsbc\n",
+    "qdyn3 = qdyn\n",
+    "integplot(drop3,acc3Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "drop3 = pd.DataFrame(drop3)\n",
+    "drop3g = pd.DataFrame(drop3g)\n",
+    "acc3 = pd.DataFrame(acc3)\n",
+    "qdyn3 = pd.DataFrame(qdyn3)\n",
+    "\n",
+    "drop3t = drop3 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop3gt = drop3g #.truncate(before=trunc_index)\n",
+    "acc3t = acc3 #.truncate(before=trunc_index)\n",
+    "acc3t = np.array(acc3t)\n",
+    "acc3gt = acc3g #.truncate(before=trunc_index)\n",
+    "acc3gt = np.array(acc3gt)\n",
+    "drop3t = drop3 #truncate(before=trunc_index)\n",
+    "qdyn3t = qdyn3#.truncate(before=trunc_index)\n",
+    "\n",
+    "duck_dep_qsbc_comboplot(drop3g, drop3, drop3t, acc3Nameg, qdyn3t)\n",
+    "\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "trial 4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 101915\n",
+      "start of penetration:  101866\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [2.57757345e-01 3.61851890e-01 5.05041996e-05]\n",
+      " [5.15175812e-01 5.03517284e-01 1.13951766e-04]\n",
+      " [7.72205013e-01 6.44968454e-01 2.03863616e-04]\n",
+      " [1.02878502e+00 7.86172420e-01 3.19790098e-04]\n",
+      " [1.28483987e+00 9.27087375e-01 4.61459660e-04]\n",
+      " [1.54027976e+00 1.06766390e+00 6.28614554e-04]\n",
+      " [1.79500552e+00 1.20784741e+00 8.20972270e-04]\n",
+      " [2.04891515e+00 1.34758178e+00 1.03821619e-03]\n",
+      " [2.30191080e+00 1.48681316e+00 1.27999739e-03]\n",
+      " [2.55389868e+00 1.62548993e+00 1.54593523e-03]\n",
+      " [2.80478597e+00 1.76356102e+00 1.83561517e-03]\n",
+      " [3.05448177e+00 1.90097639e+00 2.14859042e-03]\n",
+      " [3.30290078e+00 2.03768911e+00 2.48438824e-03]\n",
+      " [3.54996352e+00 2.17365542e+00 2.84251324e-03]\n",
+      " [3.79558942e+00 2.30883100e+00 3.22243959e-03]\n",
+      " [4.03968391e+00 2.44316380e+00 3.62358903e-03]\n",
+      " [4.28213167e+00 2.57659034e+00 4.04531251e-03]\n",
+      " [4.52280663e+00 2.70904126e+00 4.48689975e-03]\n",
+      " [4.76158383e+00 2.84044779e+00 4.94759838e-03]\n",
+      " [4.99833820e+00 2.97074109e+00 5.42661275e-03]\n",
+      " [5.23294226e+00 3.09985100e+00 5.92310000e-03]\n",
+      " [5.46526946e+00 3.22770789e+00 6.43617743e-03]\n",
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+      " [6.14730952e+00 3.60305577e+00 8.06548587e-03]\n",
+      " [6.36924568e+00 3.72519415e+00 8.63525647e-03]\n",
+      " [6.58826390e+00 3.84572669e+00 9.21659512e-03]\n",
+      " [6.80423851e+00 3.96458424e+00 9.80839533e-03]\n",
+      " [7.01704088e+00 4.08169601e+00 1.04095100e-02]\n",
+      " [7.22654136e+00 4.19699064e+00 1.10187574e-02]\n",
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+      " [1.23429185e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23444592e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23456579e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23465727e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23472565e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23477568e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23481128e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23483547e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23485090e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23486016e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23486530e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23486759e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23486818e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.23486822e+01 4.37500000e+00 1.19934265e-02]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    }
+   ],
+   "source": [
+    "fileNum= '01F8' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "a = 2 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)\n",
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop4 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop4g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop4 = pd.DataFrame(drop4)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop4g = pd.DataFrame(drop4g)\n",
+    "dg = drop4g \n",
+    "d = drop4\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc4 = acc\n",
+    "acc4g = accg\n",
+    "acc4Name = accName\n",
+    "acc4Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop4 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop4g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop4 = pd.DataFrame(drop4)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop4g = pd.DataFrame(drop4g)\n",
+    "dg = drop4g \n",
+    "d = drop4\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc4 = acc\n",
+    "acc4g = accg\n",
+    "acc4Name = accName\n",
+    "acc4Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peakpick()\n",
+    "\n",
+    "finddropend(a) #automatically find the end of the drop\n",
+    "offset = acc4g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc4g = accg[penstart:penend]\n",
+    "acc4g = acc4g-offset\n",
+    "acc4 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc4 = acc4-offsetms\n",
+    "\n",
+    "\n",
+    "drop4 = d\n",
+    "drop4g = dg\n",
+    "integration(d, acc4) #double integration to solve for velocity and penetration depth\n",
+    "drop4 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc4) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc4) #calculation of quasi-static bearing capacities\n",
+    "qsbc4 = qsbc\n",
+    "qdyn4 = qdyn\n",
+    "integplot(drop4,acc4Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "drop4 = pd.DataFrame(drop4)\n",
+    "drop4g = pd.DataFrame(drop4g)\n",
+    "acc4 = pd.DataFrame(acc4)\n",
+    "qdyn4 = pd.DataFrame(qdyn4)\n",
+    "\n",
+    "drop4t = drop4 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop4gt = drop4g #.truncate(before=trunc_index)\n",
+    "acc4t = acc4 #.truncate(before=trunc_index)\n",
+    "acc4t = np.array(acc4t)\n",
+    "acc4gt = acc4g #.truncate(before=trunc_index)\n",
+    "acc4gt = np.array(acc4gt)\n",
+    "drop4t = drop4 #truncate(before=trunc_index)\n",
+    "qdyn4t = qdyn4#.truncate(before=trunc_index)\n",
+    "\n",
+    "duck_dep_qsbc_comboplot(drop4g, drop4, drop4t, acc4Nameg, qdyn4t)\n",
+    "\n",
+    "dep4 = dep\n",
+    "\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "trial 5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 60350\n",
+      "start of penetration:  60304\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [2.72580056e-01 3.70009289e-01 5.34215405e-05]\n",
+      " [5.44830716e-01 5.19837301e-01 1.22980473e-04]\n",
+      " [8.16682537e-01 6.69445820e-01 2.22089324e-04]\n",
+      " [1.08804672e+00 8.18785978e-01 3.50271767e-04]\n",
+      " [1.35880239e+00 9.67791249e-01 5.07207124e-04]\n",
+      " [1.62878662e+00 1.11637197e+00 6.92545557e-04]\n",
+      " [1.89779297e+00 1.26441454e+00 9.05849722e-04]\n",
+      " [2.16557905e+00 1.41178556e+00 1.14656888e-03]\n",
+      " [2.43188175e+00 1.55834022e+00 1.41403305e-03]\n",
+      " [2.69643192e+00 1.70393041e+00 1.70745882e-03]\n",
+      " [2.95896941e+00 1.84841297e+00 2.02596612e-03]\n",
+      " [3.21925780e+00 1.99165777e+00 2.36860452e-03]\n",
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+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n",
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_6600\\2952692391.py:296: RuntimeWarning: invalid value encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    }
+   ],
+   "source": [
+    "fileNum= '023B' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "a = 3 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)\n",
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop5 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop5g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop5 = pd.DataFrame(drop5)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop5g = pd.DataFrame(drop5g)\n",
+    "dg = drop5g \n",
+    "d = drop5\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc5 = acc\n",
+    "acc5g = accg\n",
+    "acc5Name = accName\n",
+    "acc5Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop5 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop5g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop5 = pd.DataFrame(drop5)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop5g = pd.DataFrame(drop5g)\n",
+    "dg = drop5g \n",
+    "d = drop5\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc5 = acc\n",
+    "acc5g = accg\n",
+    "acc5Name = accName\n",
+    "acc5Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n",
+    "\n",
+    "peakpick()\n",
+    "\n",
+    "finddropend(a) #automatically find the end of the drop\n",
+    "offset = acc5g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc5g = accg[penstart:penend]\n",
+    "acc5g = acc5g-offset\n",
+    "acc5 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc5 = acc5-offsetms\n",
+    "\n",
+    "\n",
+    "drop5 = d\n",
+    "drop5g = dg\n",
+    "integration(d, acc5) #double integration to solve for velocity and penetration depth\n",
+    "drop5 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc5) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc5) #calculation of quasi-static bearing capacities\n",
+    "qsbc5 = qsbc\n",
+    "qdyn5 = qdyn\n",
+    "integplot(drop5,acc5Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "drop5 = pd.DataFrame(drop5)\n",
+    "drop5g = pd.DataFrame(drop5g)\n",
+    "acc5 = pd.DataFrame(acc5)\n",
+    "qdyn5 = pd.DataFrame(qdyn5)\n",
+    "\n",
+    "drop5t = drop5 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop5gt = drop5g #.truncate(before=trunc_index)\n",
+    "acc5t = acc5 #.truncate(before=trunc_index)\n",
+    "acc5t = np.array(acc5t)\n",
+    "acc5gt = acc5g #.truncate(before=trunc_index)\n",
+    "acc5gt = np.array(acc5gt)\n",
+    "drop5t = drop5 #truncate(before=trunc_index)\n",
+    "qdyn5t = qdyn5#.truncate(before=trunc_index)\n",
+    "\n",
+    "duck_dep_qsbc_comboplot(drop5g, drop5, drop5t, acc5Nameg, qdyn5t)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'plt' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code - profile overlay.ipynb Cell 20\u001b[0m in \u001b[0;36m5\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=51'>52</a>\u001b[0m         ax2\u001b[39m.\u001b[39mset_title(\u001b[39m\"\u001b[39m\u001b[39mDrop #\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m+\u001b[39m\u001b[39mstr\u001b[39m(a))\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=52'>53</a>\u001b[0m         ax2\u001b[39m.\u001b[39mgrid()\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=56'>57</a>\u001b[0m combined_duck_dep_qsbc_comboplot()\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=58'>59</a>\u001b[0m plt\u001b[39m.\u001b[39mshow()\n",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code - profile overlay.ipynb Cell 20\u001b[0m in \u001b[0;36m2\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcombined_duck_dep_qsbc_comboplot\u001b[39m():\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m     fig, (ax1, ax2) \u001b[39m=\u001b[39m plt\u001b[39m.\u001b[39msubplots(\u001b[39m1\u001b[39m,\u001b[39m2\u001b[39m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m     fig\u001b[39m.\u001b[39mset_size_inches(\u001b[39m7\u001b[39m, \u001b[39m7\u001b[39m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20profile%20overlay.ipynb#X25sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m     ax1\u001b[39m.\u001b[39mplot(drop1g[acc1Nameg], drop1[\u001b[39m\"\u001b[39m\u001b[39mPenetration Depth (m)\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m*\u001b[39m\u001b[39m100\u001b[39m, linestyle \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39msolid\u001b[39m\u001b[39m\"\u001b[39m, color \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39morange\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39m#marker = 11\u001b[39;00m\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'plt' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "def combined_duck_dep_qsbc_comboplot():\n",
+    "    fig, (ax1, ax2) = plt.subplots(1,2)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    fig.set_dpi(300)\n",
+    "    ax1.plot(drop1g[acc1Nameg], drop1[\"Penetration Depth (m)\"]*100, linestyle = \"solid\", color = \"orange\") #marker = 11\n",
+    "    ax1.plot(drop1[\"Velocity (m/s)\"], drop1[\"Penetration Depth (m)\"]*100, color = \"orange\", linestyle = \"dashed\")\n",
+    "\n",
+    "    ax1.plot(drop2g[acc2Nameg], drop2[\"Penetration Depth (m)\"]*100, linestyle = \"solid\", color = \"orangered\") #marker = 11\n",
+    "    ax1.plot(drop2[\"Velocity (m/s)\"], drop2[\"Penetration Depth (m)\"]*100, linestyle = \"dashed\", color = \"orangered\")\n",
+    "\n",
+    "    ax1.plot(drop3g[acc3Nameg], drop3[\"Penetration Depth (m)\"]*100, linestyle = \"solid\", color = \"darkviolet\") #marker = 11\n",
+    "    ax1.plot(drop3[\"Velocity (m/s)\"], drop3[\"Penetration Depth (m)\"]*100, linestyle = \"dashed\", color = \"darkviolet\")\n",
+    "\n",
+    "    ax1.plot(drop4g[acc4Nameg], drop4[\"Penetration Depth (m)\"]*100, linestyle = \"solid\", color = \"dodgerblue\") #marker = 11\n",
+    "    ax1.plot(drop4[\"Velocity (m/s)\"], drop4[\"Penetration Depth (m)\"]*100, linestyle = \"dashed\", color = \"dodgerblue\")\n",
+    "\n",
+    "    ax1.plot(drop5g[acc5Nameg], drop5[\"Penetration Depth (m)\"]*100, linestyle = \"solid\", color = \"limegreen\") #marker = 11\n",
+    "    ax1.plot(drop5[\"Velocity (m/s)\"], drop5[\"Penetration Depth (m)\"]*100, linestyle = \"dashed\", color = \"limegreen\")\n",
+    "\n",
+    "\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.set_xlim(left = 0)\n",
+    "    ax1.set_ylim(0,dep4.max()*100+.25)\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\"])\n",
+    "    ax1.set_title(\"Station Q3\")\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    \n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        y1 = drop1t[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdyn1t[5:-50], y1[5:-50], label=\"Qdyn\", linestyle = \"dashed\", color = \"orange\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc1[5:-50], y1[5:-50], label=\"QSBC\", color = \"orange\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        y2 = drop2t[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdyn2t[5:-47], y2[5:-47], label=\"Qdyn\", linestyle = \"dashed\", color = \"orangered\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc2[5:-47], y2[5:-47], label=\"QSBC\", color = \"orangered\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        y3 = drop3t[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdyn3t[5:-50], y3[5:-50], label=\"Qdyn\", linestyle = \"dashed\", color = \"darkviolet\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc3[5:-50], y3[5:-50], label=\"QSBC\", color = \"darkviolet\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        y4 = drop4t[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdyn4t[5:-50], y4[5:-50], label=\"Qdyn\", linestyle = \"dashed\", color = \"dodgerblue\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc4[5:-50], y4[5:-50], label=\"QSBC\", color = \"dodgerblue\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        y5 = drop5t[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdyn5t[5:-50], y5[5:-50], label=\"Qdyn\", linestyle = \"dashed\", color = \"limegreen\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc5[5:-50], y5[5:-50], label=\"QSBC\", color = \"limegreen\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        \n",
+    "        \n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\",)\n",
+    "        ax2.set_xlim(left = 0)\n",
+    "        ax2.set_ylim(0,dep4.max()*100+.25)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", \"QSBC\"], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    \n",
+    "\n",
+    "combined_duck_dep_qsbc_comboplot()\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
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+    "version": 3
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+   "mimetype": "text/x-python",
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+ "nbformat_minor": 2
+}
diff --git a/BD code - single drop analysis.ipynb b/BD code - single drop analysis.ipynb
new file mode 100644
index 0000000..b3ada51
--- /dev/null
+++ b/BD code - single drop analysis.ipynb	
@@ -0,0 +1,1128 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "matplotlib.use('TkAgg')\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pathlib import Path\n",
+    "import math\n",
+    "from math import pi\n",
+    "from math import sqrt\n",
+    "import statistics\n",
+    "import scipy.integrate\n",
+    "from scipy.signal import find_peaks\n",
+    "from scipy.signal import argrelmin\n",
+    "from numpy import trapz\n",
+    "from scipy.integrate import cumtrapz"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "user inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# SETUP VARIABLES - USER INPUTS\n",
+    "BD = 2 #Bluedrop file is from \n",
+    "fileNum = '0021' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "soiltype = \"s\" #s = sand, c=clay, m=mixed, u=unknown\n",
+    "atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays)\n",
+    "tiptype = 'c'  # c = cone, p = parabolic, b = blunt\n",
+    "#offset = 1 # this value is subtracted from the accelerometer readings\n",
+    "droptype = 'w' #w = water, #a = air\n",
+    "sign = \"uk\" #enter an effective unit weight value in kg/m^3 or \"uk\" if unknown \n",
+    "# paste the filepath to the folder where the BD data is stored\n",
+    "binFilepath = Path(\"H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/07March23/BD2 3.7.23 - Drops Only\")\n",
+    "#paste the filepath to an excel file that the analysis results will be printed in\n",
+    "outputPath = Path(\"H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/07March23/BlueDrop Data Processing March 7 2023.xlsx\") #  Path to pre-existing Excel File\n",
+    "plotPath = Path(\"H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/07March23/BD2 3.8.23 - Drops Only/Analysis Figures\")\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "set functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# FUNCTIONS FOR USE IN ANALYSIS\n",
+    "def masslength(tiptype): #sets the mass and length of the pentrometer based on the tip\n",
+    "    global mass\n",
+    "    global length\n",
+    "    if tiptype == 'c':\n",
+    "        mass = 7.71 #kg\n",
+    "        length = 8.48-0.93 #originally 7.87, 7.57 for perfect 60 deg, 8.48 measured - .93 measured 90 deg\n",
+    "    elif tiptype == 'p':\n",
+    "        mass = 9.15\n",
+    "        length = 8.26\n",
+    "    elif tiptype == 'b':\n",
+    "        mass = 10.30\n",
+    "        length = 8.57\n",
+    "\n",
+    "def dropstartend(peak): #after locating the peaks, this function chops the minute long file into a smaller segment immediately before and after the peak\n",
+    "    global dropstart\n",
+    "    global dropend\n",
+    "    if peak <= 1500:\n",
+    "        dropstart = 1\n",
+    "        dropend = peak + 500\n",
+    "    elif peak > 119500:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = 120000\n",
+    "    else:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = peak + 500\n",
+    "\n",
+    "def accPick(dg, d): #this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "    maxAcc = dg[\"250g (g)\"].max()\n",
+    "    global acc\n",
+    "    global accName\n",
+    "    global accNameg\n",
+    "    global accg\n",
+    "    if maxAcc < 5: #- offset:\n",
+    "        if dg[\"2g (g)\"].max() < 1.8: #offset:  # does an extra check for the 2g because of noise\n",
+    "            acc = dfCal[\"2g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"2g (g)\"]\n",
+    "            accName = \"2g (m/s^2)\"\n",
+    "            accNameg = \"2g (g)\"\n",
+    "        else:\n",
+    "            acc = dfCal[\"18g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"18g (g)\"]\n",
+    "            accName = \"18g (m/s^2)\"\n",
+    "            accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 18: #- offset\n",
+    "        acc = dfCal[\"18g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"18g (g)\"]\n",
+    "        accName = \"18g (m/s^2)\"\n",
+    "        accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 50: #- offset:\n",
+    "        acc = dfCal[\"50g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"50g (m/s^2)\"\n",
+    "        accNameg = \"50g (g)\"\n",
+    "    else:\n",
+    "        acc = dfCal[\"250g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"250g (m/s^2)\"\n",
+    "        accNameg = \"250g (g)\"\n",
+    "\n",
+    "def findchangepts(): #This function picks the moment that the BD impacts the ground (not in use currently)\n",
+    "    global drop\n",
+    "    jlist = list()\n",
+    "    global jindex\n",
+    "    print(\"finding start of drop...\")\n",
+    "    for i in range(4,len(accg)-4):\n",
+    "        p1 = 1\n",
+    "        #print(p1)\n",
+    "        p2 = i\n",
+    "        #print(p2)\n",
+    "        p3 = len(accg)\n",
+    "        #print(p3)\n",
+    "        sample1 = list(accg[p1:p2-1])\n",
+    "        #print(sample1)\n",
+    "        sample2 = list(accg[p2:p3])\n",
+    "        #print(sample2)\n",
+    "        stat1 = math.log(statistics.variance(sample1))\n",
+    "        stat2 = math.log(statistics.variance(sample2))\n",
+    "        #print(stat1)\n",
+    "\n",
+    "        j1 = (i-1)*stat1\n",
+    "        j2 = ((len(accg)-1)-i+1)*stat2\n",
+    "        j = j1+j2\n",
+    "        #print(j)\n",
+    "        jlist.append(j)\n",
+    "\n",
+    "    drop = min(jlist)\n",
+    "    #print(\"drop is\")\n",
+    "    #print(drop)\n",
+    "    jlist = np.array(jlist)\n",
+    "    #print(jlist)\n",
+    "    #print(jlist.size)\n",
+    "    jlist = np.insert(jlist, 0, (0,0,0,0)) #reshape to match up with dataframe d\n",
+    "    jlist = np.append(jlist, (0,0,0,0)) #reshape to match up with dataframe d\n",
+    "    #print(jlist.size) #should be 2000\n",
+    "    jindex = np.where(jlist==drop) #finds the index of the drop start\n",
+    "    jindex = int(jindex[0]) #converts the index into a number from a tuple\n",
+    "    print(\"Jlist: \", jlist)\n",
+    "\n",
+    "def finddropend(n): #finds the location after the peak where the deceleration is 1 \n",
+    "    global penend\n",
+    "    below0list = list()\n",
+    "    #for i in range(dropstart+jindex, dropend, 1):\n",
+    "    for i in range(peak, dropend, 1):\n",
+    "        if accg[i] < 1: #the offset is applied later in the code\n",
+    "            penend = i \n",
+    "            below0list = np.append(below0list, penend)\n",
+    "    penend=int(min(below0list))\n",
+    "\n",
+    "def integration(d, accint): #integrates the deceleration data to solve for velocity and penetration depth\n",
+    "    global vel\n",
+    "    global maxvel\n",
+    "    global dep\n",
+    "    global maxdep\n",
+    "    #accint = acc[penstart:penend]\n",
+    "    #print(len(d))\n",
+    "    #print(len(accint))\n",
+    "    vel = scipy.integrate.cumtrapz(accint, x=d[\"Time (s)\"])  # solves for velocity\n",
+    "    vel = np.array(vel)\n",
+    "    vel = numpy.insert(vel, 0, 0) #not sure what to insert here, but it makes it the right size\n",
+    "    vel = np.flip(vel)\n",
+    "    maxvel = vel.max()\n",
+    "    maxvel = round(maxvel,1)\n",
+    "    dep = scipy.integrate.cumtrapz(vel, x=d[\"Time (s)\"])  # solves for penetration depth\n",
+    "    dep = numpy.insert(dep, 0, 0)  # not sure what to insert here, but it makes it the right size\n",
+    "    maxdep = dep.max()\n",
+    "    maxdep = round(maxdep,4)\n",
+    "    d.insert(9, \"Velocity (m/s)\", vel)\n",
+    "    d.insert(10, \"Penetration Depth (m)\", dep)\n",
+    "\n",
+    "def peakpick():\n",
+    "    global penstart\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.plot(dfCalg['Count'], dfCalg[accNameg], label=accNameg)\n",
+    "    plt.plot(dfCalg['Count'], dfCalg['2g (g)'], label='2g')\n",
+    "\n",
+    "    ax1.set_xlim(left=dropstart, right=dropend)\n",
+    "    ax1.legend()\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set(xlabel=\"Time\")\n",
+    "    ax1.set_title('Double-click start of drop #' + str(a))\n",
+    "    startendpt = plt.ginput(2, 0)\n",
+    "    pentimes = []\n",
+    "    for t in startendpt:\n",
+    "        for x in t:\n",
+    "            pentimes.append(x)\n",
+    "\n",
+    "    penstart = int(pentimes[0])\n",
+    "    print(\"start of penetration: \", penstart)\n",
+    "\n",
+    "def CheckingFunction(): # (to be used with auto peak finding) This function is added to check the values of the start and end of the drop if the autofinding function doesn't work\n",
+    "\n",
+    "    global jindex\n",
+    "    global num1\n",
+    "    \n",
+    "    xvalues=np.linspace(0,len(dg)-1,len(dg))\n",
+    "    plt.figure(num=1)\n",
+    "    temp_dg=dg['250g (g)']\n",
+    "    plt.plot(xvalues,temp_dg)\n",
+    "    plt.grid(visible=True,which='both')\n",
+    "    plt.show()\n",
+    "    print ('The start of the drop is', jindex)\n",
+    "    print ('The end of the drop is', num1)\n",
+    "    print('Are the start and end of the drop correct?(y/n)')\n",
+    "    drop_input=input()\n",
+    "    if drop_input=='n':   \n",
+    "        peakpick()\n",
+    "        jindex = penstart\n",
+    "        num1 = penend\n",
+    "\n",
+    "def areafind(): #finds the embedded area based on the penetration depth, area type, and the tip\n",
+    "    global area\n",
+    "    global trunc_index\n",
+    "    a1 = list() #placeholder for the penetrated area at that specific depth\n",
+    "    d1 = dep*100 #penetration depth array, in cm\n",
+    "    #print(len(d1))\n",
+    "    r = list() #placeholder for the radius at that specific depth\n",
+    "    if tiptype == 'c':\n",
+    "        if atype == 'm':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(.22+d1[k]*((4.375-.22)/7.55))\n",
+    "                    #r.append(d1[k]*np.tan(30*pi/180)) this is from the original matlabcode\n",
+    "                    a1.append(pi*r[k]*(sqrt((r[k]**2)+(d1[k]**2))))\n",
+    "                elif d1[k]>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]*(sqrt((r[k]**2)+(length**2))))\n",
+    "                a1[k] = a1[k]/10000\n",
+    "            area = a1\n",
+    "            #print(r)\n",
+    "            print(np.column_stack((d1,r, area)))\n",
+    "        elif atype == 'p':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(.22+d1[k]*((4.375-.22)/7.55))\n",
+    "                    # r.append(d1[k]*np.tan(30*pi/180))\n",
+    "                    a1.append(pi*r[k]**2)\n",
+    "                elif d1[k]>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    if r[k-1]<r[k]:\n",
+    "                        trunc_index = r.index(r[k-1])+jindex+dropstart #performs analysis only on readings beyond depth of cone height\n",
+    "                    a1.append(pi*(r[k])**2)\n",
+    "                a1[k] = a1[k]/10000\n",
+    "            area = a1\n",
+    "\n",
+    "    elif tiptype == 'b':\n",
+    "        if atype =='m':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                if d1[k]<length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]**2 + 2*pi*r[k]*d1[k])\n",
+    "                if d1(k)>=length:\n",
+    "                    r.append(4.375)\n",
+    "                    a1.append(pi*r[k]**2 + 2*pi*r[k]*length)\n",
+    "                a1[k]=a1[k]/10000\n",
+    "            area = a1\n",
+    "        elif atype == 'p':\n",
+    "            for k in range(0,len(d1)):\n",
+    "                a1.append(pi*4.375**2)\n",
+    "                a1[k]=a1[k]/10000\n",
+    "            area = a1\n",
+    "\n",
+    "    '''elif tiptype == \"p\":\n",
+    "        if atype == 'm':\n",
+    "            for k in range(1,len(d)):\n",
+    "                if d1[k]<length:\n",
+    "                     r[k]=sqrt(2.4184*d1[k])\n",
+    "                           polarfun = @(theta,r) r.*sqrt(0.745*r.^2 + 1);\n",
+    "                           A1(k)= integral2(polarfun,0,2*pi,0,r(k));\n",
+    "            \n",
+    "        elif atype == 'p':\n",
+    "            for k in range(1,len(d)):'''\n",
+    "\n",
+    "def qdynfun(acc): # calculates dynamic bearing capacity\n",
+    "    global qdyn\n",
+    "    global maxbcdep\n",
+    "    global maxqdyn\n",
+    "    global qdyntable\n",
+    "\n",
+    "    buoy = 1020*0.002473\n",
+    "    if droptype == \"w\": #water drops\n",
+    "        Fbe = (mass-buoy)*acc #drop force\n",
+    "\n",
+    "    elif droptype ==\"a\": #air drops\n",
+    "        Fbe = mass*acc\n",
+    "\n",
+    "    qdyn = (Fbe/area)/1000 #Dynamic bearing capacity (kPa)\n",
+    "    qdyntable = pd.DataFrame()\n",
+    "    qdyntable[\"Qdyn\"] = qdyn\n",
+    "    qdyntable[\"Depth\"] = dep\n",
+    "    qdyntablet = qdyntable#.truncate(before=trunc_index)\n",
+    "    qdynt = qdyntablet[\"Qdyn\"]\n",
+    "    #print(qdyntable)\n",
+    "\n",
+    "    maxqdyn = qdynt.max() #gives maximum qdyn\n",
+    "    maxbcdep = qdyntablet.loc[qdyntable[\"Qdyn\"]==maxqdyn, 'Depth'].item()\n",
+    "\n",
+    "    maxqdyn = round(maxqdyn,1)\n",
+    "    maxbcdep = round(maxbcdep,4)\n",
+    "    #print(\"maxbcdep = \", maxbcdep) #finds the penetration depth corresponding to the maximum qdyn\n",
+    "\n",
+    "\n",
+    "    \"\"\"bcmin = argrelmin(qdyn)\n",
+    "    peaksArray = np.array(bcmin)\n",
+    "    print(\"Peaks Array = \", peaksArray)\"\"\"\n",
+    "\n",
+    "def qsbcfun(acc): #calculates quasi-static bearing capacity\n",
+    "    global bctable\n",
+    "    global qsbc\n",
+    "    global maxHqsbc\n",
+    "    global maxLqsbc\n",
+    "    global maxAqsbc\n",
+    "\n",
+    "    if droptype == \"w\":\n",
+    "        srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction. \n",
+    "        srfk = [0.2, 0.4, 1, 1.5] #list of strain rate factors to run; must be in increasing order\n",
+    "\n",
+    "        bctable = pd.DataFrame()\n",
+    "        for i in range(0,len(srfk)):\n",
+    "            fsr = 1+srfk[i]*srcv\n",
+    "            qsbc = qdyn/fsr\n",
+    "            bctable.insert(i, \"qsbc for srf = \"+str(srfk[i]), qsbc)\n",
+    "\n",
+    "        bctable_avgs = pd.DataFrame()\n",
+    "        bctable_avgs[\"High Average qsbc\"]= (bctable.iloc[:,0]+bctable.iloc[:,1])/2 #Average of the lowest 2 strain rate factors\n",
+    "        bctable_avgs[\"Low Average qsbc\"] = (bctable.iloc[:,int(len(srfk))-1]+bctable.iloc[:,int(len(srfk)-2)])/2 #average of the highest 2 strain rate factors\n",
+    "        maxHqsbc = bctable_avgs[\"High Average qsbc\"].max()\n",
+    "        maxHqsbc = round(maxHqsbc, 1)\n",
+    "        maxLqsbc = bctable_avgs[\"Low Average qsbc\"].max()\n",
+    "        maxLqsbc = round(maxLqsbc,1)\n",
+    "        maxAqsbc = \"-\"\n",
+    "\n",
+    "        #print(bctable)\n",
+    "\n",
+    "    elif droptype == \"a\":\n",
+    "        srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction. \n",
+    "        srfk = 0.31*maxvel\n",
+    "        fsr = 1+srfk*srcv\n",
+    "        qsbc = qdyn/fsr\n",
+    "        maxHqsbc = \"-\"\n",
+    "        maxLqsbc = \"-\"\n",
+    "        maxAqsbc = qsbc.max()\n",
+    "        maxAqsbc = round(maxAqsbc,1)\n",
+    "\n",
+    "def dr(accg): #Albatal 2019 method for calculating relative density (Duck, NC specific!)\n",
+    "    global Dr\n",
+    "    maxacc = accg.max() #maximum deceleration, in g\n",
+    "    #print(\"Max deceleration = \", maxacc)\n",
+    "    Dr = -2.18*10**-4*maxacc**3+1.29*10**-2*maxacc**2+1.61*maxacc-13.09 #Albatal 2019\n",
+    "    Dr = round(Dr, 1)\n",
+    "    #print(\"Relative density is \", dr)\n",
+    "\n",
+    "def ignore_drop():\n",
+    "    global keep_drop\n",
+    "    print('Keep Drop? (y/n)')\n",
+    "    keep_drop=input()\n",
+    "\n",
+    "def duncan_correlation(): #duncan correlation for caluclating friction angle\n",
+    "    global phi\n",
+    "    global sign\n",
+    "    #coefficients A, B, C, and D used in the Duncan Correlation. Duncan[34,10,3,2], Albatal[34,10,2,5]\n",
+    "    A = 34\n",
+    "    B = 10\n",
+    "    C = 3\n",
+    "    D = 2\n",
+    "    pa = 101.325 #kPa\n",
+    "    print(\"max penetration depth = \", maxdep)\n",
+    "    if sign == \"uk\":\n",
+    "        sign = 1120*maxdep #1120 = 70pcf in kg/m^3\n",
+    "\n",
+    "    phi = A + B*Dr/100-(C+D*Dr/100)*math.log(sign/pa)\n",
+    "    phi = round(phi, 1)\n",
+    "    print(\"phi =\", phi)\n",
+    "\n",
+    "def firmnessfactor(acc, drop):\n",
+    "    global maxacc\n",
+    "    global ff\n",
+    "    maxacc = acc.max()\n",
+    "    g = 9.80665\n",
+    "    tp = len(drop)/2000\n",
+    "\n",
+    "    ff = maxacc/(g*tp*maxvel)\n",
+    "    ff = round(ff,1)\n",
+    "    print(\"Firmness factor = \", ff)\n",
+    "\n",
+    "def bctruncate(dropg, drop, acc, qdyn):\n",
+    "    dropg = pd.DataFrame(dropg)\n",
+    "    drop = pd.DataFrame(drop)\n",
+    "    qdyn = pd.DataFrame(qdyn)\n",
+    "    acc = pd.DataFrame(acc)\n",
+    "    dropg = dropg.truncate(before=trunc_index)\n",
+    "    drop = drop.truncate(before=trunc_index)\n",
+    "    acc = acc.truncate(before=trunc_index)\n",
+    "    qdyn = qdyn.truncate(before=trunc_index)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Plots for exporting\n",
+    "def overviewplot(): #Plot showing all accellerometers and pore pressure readings\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(14, 7)\n",
+    "    #plt.tight_layout()\n",
+    "    ax1.plot(time, g250g, label=\"250g\")\n",
+    "    ax1.plot(time, g50g, label=\"50g\")\n",
+    "    ax1.plot(time, g18g, label=\"18g\")\n",
+    "    ax1.plot(time, g2g, label=\"2g\")\n",
+    "    ax1.legend(loc = \"upper right\")\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(time, ppm, label=\"Pore Pressure\")\n",
+    "    ax2.set(ylabel=\"Pore Pressure (kPa)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(time, gX55g, label=\"X 55g\")\n",
+    "    ax3.plot(time, gY55g, label=\"Y 55g\")\n",
+    "    ax3.legend(loc = \"upper right\")\n",
+    "    ax3.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax3.set(xlabel=\"Time (s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" Overview.png\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "def integplot(drop, accName): #Deceleration,Velocity,and penetration depth vs time plots\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    #resize to 7,7, 7,14\n",
+    "    #plt.tight_layout()\n",
+    "    timereset = drop[\"Time (s)\"]- drop[\"Time (s)\"].iloc[0]\n",
+    "    ax1.plot(timereset, drop[accName], color = \"k\" ) #,marker = 11\n",
+    "    ax1.set(ylabel=\"Deceleration (m/s^2)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum+ \" Drop #\"+str(a))\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(timereset, drop['Velocity (m/s)'] , color = \"k\" )\n",
+    "    ax2.set(ylabel=\"Velocity (m/s)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(timereset, drop[\"Penetration Depth (m)\"] , color = \"k\")\n",
+    "    ax3.set(ylabel=\"Penetration Depth (m)\", xlabel=\"Time(s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" \"+str(a)+\" Integ\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "def dep_qsbc_comboplot(dropg, drop, accNameg, qdyn):\n",
+    "    fig, (ax1, ax2) = plt.subplots(1,2)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    ax1.plot(drop[\"X55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"b\", linestyle = \"dashed\")\n",
+    "    ax1.plot(drop[\"Y55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"r\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\", \"X tilt (g)\", \"Y tilt (g)\"], loc = \"upper right\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        ax2.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(qsbc, drop[\"Penetration Depth (m)\"]*100, label=\"QSBC\") #plots QSBC\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,800)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", \"QSBC\"], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    else: #for saturated drops, use a range of strain-rate factors\n",
+    "        ax2.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(bctable.iloc[:,0], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax2.plot(bctable.iloc[:,len(bctable.columns)-1], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctable.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax2.plot(bctable.iloc[:,i], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[i]), color = '.6')\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", str(bctable.columns[0]), str(bctable.columns[len(bctable.columns)-1])], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "    \n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    \n",
+    "\n",
+    "\n",
+    "\n",
+    "#plots for troubleshooting \n",
+    "def depthplot(dropg, drop, accNameg): #Velocity and develeration vs. penetration depth \n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\"])\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    plt.show()\n",
+    "\n",
+    "def peakplot(): # Plot showing peak deceleration\n",
+    "    peakplot = plt.plot(x)\n",
+    "    peakplot = plt.plot(peaks, x[peaks], \"x\")\n",
+    "    plt.show()\n",
+    "\n",
+    "def qdynplot(drop, qdyn): #Plot showing dynamic bearing capacity vs depth\n",
+    "    #print(len(drop))\n",
+    "    #print(len(qdyn))\n",
+    "    #print((bctable.iloc[:,0]))\n",
+    "    #print(len(bctable.iloc[:,len(bctable.columns)-1]))\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "\n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        ax1.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax1.plot(qsbc, drop[\"Penetration Depth (m)\"]*100, label=\"QSBC\") #plots QSBC\n",
+    "        ax1.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax1.set_xlim(0,)\n",
+    "        ax1.invert_yaxis()\n",
+    "        ax1.legend([\"Qdyn\", \"QSBC\"])\n",
+    "        ax1.set_title(\"Bearing Capacity- \"+fileNum+ \" \"+str(a))\n",
+    "        ax1.grid()\n",
+    "\n",
+    "    else:\n",
+    "        ax1.plot(qdyn, drop[\"Penetration Depth (m)\"]*100, label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax1.plot(bctable.iloc[:,0], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax1.plot(bctable.iloc[:,len(bctable.columns)-1], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctable.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax1.plot(bctable.iloc[:,i], drop[\"Penetration Depth (m)\"]*100, label=str(bctable.columns[i]), color = \"k\")\n",
+    "        ax1.set(xlabel=\"Bearing Capacity (kPa)\", ylabel=\"Penetration Depth (cm)\")\n",
+    "        ax1.set_xlim(0,)\n",
+    "        ax1.invert_yaxis()\n",
+    "        ax1.legend([\"Qdyn\", str(bctable.columns[0]), str(bctable.columns[len(bctable.columns)-1])])\n",
+    "        ax1.set_title(\"Bearing Capacity- \"+fileNum+ \" \"+str(a))\n",
+    "    \n",
+    "    plt.show()\n",
+    "\n",
+    "def tiltplot():\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.plot(time, gX55g, label=\"2g\")\n",
+    "    plt.plot(time, gY55g, label=\"2g\")\n",
+    "    ax1.legend()\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set(xlabel=\"Time (s)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib.font_manager import FontProperties\n",
+    "font = FontProperties()\n",
+    "font.set_name('Calibri')\n",
+    "\n",
+    "def duck_dep_qsbc_comboplot(dropg, drop, dropt, accNameg, qdynt):\n",
+    "    font = {'fontname': 'Calibri'}\n",
+    "    fig, (ax1, ax2) = plt.subplots(1,2)\n",
+    "    fig.set_size_inches(7, 7)\n",
+    "    ax1.plot(dropg[accNameg], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"solid\") #marker = 11\n",
+    "    ax1.plot(drop[\"Velocity (m/s)\"], drop[\"Penetration Depth (m)\"]*100, color = \"k\", linestyle = \"dashed\")\n",
+    "    #ax1.plot(drop[\"X55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"b\", linestyle = \"dashed\")\n",
+    "    #ax1.plot(drop[\"Y55g (m/s^2)\"], drop[\"Penetration Depth (m)\"]*100, color = \"r\", linestyle = \"dashed\")\n",
+    "    ax1.set(xlabel=\"Deceleration (g) and Velocity (m/s)\", ylabel=\"Penetration Depth (cm)\", FontProperties = font)\n",
+    "    ax1.set_xlim(left = 0)\n",
+    "    ax1.set_ylim(0,dep.max()*100+.25)\n",
+    "    ax1.invert_yaxis()\n",
+    "    ax1.legend([\"Deceleration (g)\", \"Velocity (m/s)\"], FontProperties = font)\n",
+    "    ax1.set_title(\"BD file \"+fileNum, FontProperties = font)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    \n",
+    "    if droptype == \"a\": #for partial saturation, only one qsbc curve\n",
+    "        y = dropt[\"Penetration Depth (m)\"]*100\n",
+    "        ax2.plot(qdynt[10:-50], y[10:-50], label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn, chops off first 40 readings\n",
+    "        ax2.plot(qsbc[10:-50], y[10:-50], label=\"QSBC\") #plots QSBC; chops off last 10 points which go off towards infinity (can adjust as needed)\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\",)\n",
+    "        ax2.set_xlim(0,qdyn.max()+10)\n",
+    "        ax2.set_ylim(0,dep.max()*100+.25)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", \"QSBC\"], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    else: #for saturated drops, use a range of strain-rate factors\n",
+    "        y = list(dropt[\"Penetration Depth (m)\"]*100)\n",
+    "        ax2.plot(qdynt[10:-20], y[10:-20], label=\"Qdyn\") #color = \"k\", marker = 11 #Plots Qdyn\n",
+    "        ax2.plot(bctablet.iloc[10:-20,0], y[10:-20], label=str(bctablet.columns[0])) #plots QSBC with smallest srf\n",
+    "        ax2.plot(bctablet.iloc[10:-20,len(bctable.columns)-1], y[10:-20], label=str(bctable.columns[len(bctable.columns)-1])) #plots QSBC with largest srf\n",
+    "        for i in range(1,len(bctablet.columns)-1): #plots qsbc for all other srfs\n",
+    "            ax2.plot(bctablet.iloc[10:-20,i], y[10:-20], label=str(bctablet.columns[i]), color = '.6')\n",
+    "            #bctablet.iloc[:,i].pop()\n",
+    "        ax2.set(xlabel=\"Bearing Capacity (kPa)\")\n",
+    "        ax2.set_xlim(0,)\n",
+    "        ax2.invert_yaxis()\n",
+    "        ax2.legend([\"Qdyn\", str(bctablet.columns[0]), str(bctablet.columns[len(bctablet.columns)-1])], loc = \"upper right\")\n",
+    "        ax2.set_title(\"Drop #\"+str(a))\n",
+    "        ax2.grid()\n",
+    "\n",
+    "    #fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" \"+str(a)+\" BC\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Exporting Functions\n",
+    "def exporttoexcel():\n",
+    "    with pd.ExcelWriter(outputPath, mode=\"a\", if_sheet_exists='replace') as writer:\n",
+    "        output_table.to_excel(writer, sheet_name = fileNum, index=False)\n",
+    "\n",
+    "def troubleshooting_export():\n",
+    "        with pd.ExcelWriter(troubleshootingPath, mode=\"a\", if_sheet_exists = 'new') as writer:\n",
+    "            drop1.to_excel(writer, sheet_name = str(a), index = False)\n",
+    "            qdyntable.to_excel(writer, sheet_name = \"qdyn\", index = False)\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Bring in data and calibrate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "#Set the penetrometer mass and length\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = \"bLog\"+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "locate drops"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 28061\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = 1 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop1 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop1g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop1 = pd.DataFrame(drop1)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "dg = drop1g \n",
+    "d = drop1\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc1 = acc\n",
+    "acc1g = accg\n",
+    "acc1Name = accName\n",
+    "acc1Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "start of penetration:  28024\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "peakpick()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "penend:  64989\n",
+      "offset:  0.0\n",
+      "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
+      " [1.47248589e-01 3.01035482e-01 3.16932046e-05]\n",
+      " [2.93532681e-01 3.81540171e-01 5.77012654e-05]\n",
+      " [4.38084895e-01 4.61091753e-01 9.21317591e-05]\n",
+      " [5.80000723e-01 5.39192451e-01 1.34144303e-04]\n",
+      " [7.18323948e-01 6.15316027e-01 1.82836669e-04]\n",
+      " [8.52172394e-01 6.88976993e-01 2.37195082e-04]\n",
+      " [9.80844224e-01 7.59789106e-01 2.96148468e-04]\n",
+      " [1.10382817e+00 8.27471000e-01 3.58623365e-04]\n",
+      " [1.22072637e+00 8.91803719e-01 4.23553725e-04]\n",
+      " [1.33120009e+00 9.52600846e-01 4.89881597e-04]\n",
+      " [1.43497379e+00 1.00971074e+00 5.56580655e-04]\n",
+      " [1.53185183e+00 1.06302574e+00 6.22688185e-04]\n",
+      " [1.62171550e+00 1.11248052e+00 6.87324157e-04]\n",
+      " [1.70450408e+00 1.15804165e+00 7.49694332e-04]\n",
+      " [1.78020420e+00 1.19970178e+00 8.09093652e-04]\n",
+      " [1.84884215e+00 1.23747538e+00 8.64907878e-04]\n",
+      " [1.91047506e+00 1.27139389e+00 9.16611196e-04]\n",
+      " [1.96519393e+00 1.30150739e+00 9.63771454e-04]\n",
+      " [2.01313002e+00 1.32788811e+00 1.00605745e-03]\n",
+      " [2.05445293e+00 1.35062939e+00 1.04323796e-03]\n",
+      " [2.08935689e+00 1.36983813e+00 1.07516827e-03]\n",
+      " [2.11804690e+00 1.38562713e+00 1.10177422e-03]\n",
+      " [2.14074175e+00 1.39811682e+00 1.12305074e-03]\n",
+      " [2.15768381e+00 1.40744056e+00 1.13906656e-03]\n",
+      " [2.16914172e+00 1.41374621e+00 1.14996230e-03]\n",
+      " [2.17541393e+00 1.41719800e+00 1.15594872e-03]\n",
+      " [2.17682859e+00 1.41797653e+00 1.15730107e-03]\n",
+      " [2.17373135e+00 1.41627202e+00 1.15434128e-03]\n",
+      " [2.16647849e+00 1.41228055e+00 1.14742511e-03]\n",
+      " [2.15544204e+00 1.40620684e+00 1.13694085e-03]\n",
+      " [2.14101961e+00 1.39826973e+00 1.12331249e-03]\n",
+      " [2.12363316e+00 1.38870143e+00 1.10699250e-03]\n",
+      " [2.10371222e+00 1.37773832e+00 1.08844020e-03]\n",
+      " [2.08168302e+00 1.36561496e+00 1.06810692e-03]\n",
+      " [2.05796348e+00 1.35256136e+00 1.04642767e-03]\n",
+      " [2.03296492e+00 1.33880388e+00 1.02381987e-03]\n",
+      " [2.00709296e+00 1.32456573e+00 1.00068203e-03]\n",
+      " [1.98072513e+00 1.31005469e+00 9.77372669e-04]\n",
+      " [1.95418527e+00 1.29544898e+00 9.54188470e-04]\n",
+      " [1.92773594e+00 1.28089309e+00 9.31360081e-04]\n",
+      " [1.90157749e+00 1.26649728e+00 9.09054454e-04]\n",
+      " [1.87585341e+00 1.25234052e+00 8.87382737e-04]\n",
+      " [1.85066482e+00 1.23847846e+00 8.66415376e-04]\n",
+      " [1.82608112e+00 1.22494928e+00 8.46193134e-04]\n",
+      " [1.80214698e+00 1.21177758e+00 8.26734510e-04]\n",
+      " [1.77889355e+00 1.19898049e+00 8.08045976e-04]\n",
+      " [1.75635003e+00 1.18657409e+00 7.90131870e-04]\n",
+      " [1.73454604e+00 1.17457468e+00 7.72996373e-04]\n",
+      " [1.71350615e+00 1.16299577e+00 7.56639383e-04]\n",
+      " [1.69324813e+00 1.15184715e+00 7.41055457e-04]\n",
+      " [1.67378617e+00 1.14113663e+00 7.26236581e-04]\n",
+      " [1.65513123e+00 1.13087023e+00 7.12172624e-04]\n",
+      " [1.63728776e+00 1.12105042e+00 6.98849061e-04]\n",
+      " [1.62025774e+00 1.11167827e+00 6.86250184e-04]\n",
+      " [1.60404827e+00 1.10275769e+00 6.74364764e-04]\n",
+      " [1.58866893e+00 1.09429396e+00 6.63183989e-04]\n",
+      " [1.57412640e+00 1.08629075e+00 6.52697517e-04]\n",
+      " [1.56042531e+00 1.07875062e+00 6.42894237e-04]\n",
+      " [1.54756884e+00 1.07167530e+00 6.33762728e-04]\n",
+      " [1.53556033e+00 1.06506664e+00 6.25292477e-04]\n",
+      " [1.52440953e+00 1.05893001e+00 6.17478233e-04]\n",
+      " [1.51412948e+00 1.05327258e+00 6.10317705e-04]\n",
+      " [1.50472698e+00 1.04809809e+00 6.03804987e-04]\n",
+      " [1.49620435e+00 1.04340783e+00 5.97931905e-04]\n",
+      " [1.48856131e+00 1.03920162e+00 5.92689364e-04]\n",
+      " [1.48179550e+00 1.03547818e+00 5.88067794e-04]\n",
+      " [1.47590859e+00 1.03223844e+00 5.84061300e-04]\n",
+      " [1.47090237e+00 1.02948336e+00 5.80664956e-04]\n",
+      " [1.46677724e+00 1.02721317e+00 5.77873800e-04]\n",
+      " [1.46354243e+00 1.02543295e+00 5.75689763e-04]\n",
+      " [1.46121534e+00 1.02415228e+00 5.74121148e-04]\n",
+      " [1.45981206e+00 1.02338002e+00 5.73176276e-04]\n",
+      " [1.45934307e+00 1.02312192e+00 5.72860662e-04]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_26304\\2952692391.py:275: RuntimeWarning: divide by zero encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n",
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_26304\\2952692391.py:275: RuntimeWarning: invalid value encountered in log10\n",
+      "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max penetration depth is:  0.0218\n",
+      "Pre-truncation d1          Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  200g (m/s^2)  \\\n",
+      "64915  64915.0   32.4580   10.364800    10.014808   -37.606040    -44.381730   \n",
+      "64916  64916.0   32.4585   10.651060    10.286805   -37.432653    -44.095712   \n",
+      "64917  64917.0   32.4590   11.566406    11.226008   -37.014594    -43.465958   \n",
+      "64918  64918.0   32.4595   12.300198    11.865991   -36.347262    -42.915405   \n",
+      "64919  64919.0   32.4600   12.220535    11.808422   -35.526473    -42.829150   \n",
+      "...        ...       ...         ...          ...          ...           ...   \n",
+      "64984  64984.0   32.4925   19.781746   147.322909   144.427755     70.443785   \n",
+      "64985  64985.0   32.4930   19.781297   109.785541   104.877040     39.510823   \n",
+      "64986  64986.0   32.4935   19.781746    79.014942    67.639834     13.834893   \n",
+      "64987  64987.0   32.4940   19.781332    58.460689    36.943951     -5.796812   \n",
+      "64988  64988.0   32.4945   19.781129    38.658312    12.791691    -19.787348   \n",
+      "\n",
+      "       250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  Velocity (m/s)  \\\n",
+      "64915    -31.076014    -22.352249     -8.096526        2.951189   \n",
+      "64916    -31.221530    -22.736132     -8.867066        2.938755   \n",
+      "64917    -30.614850    -22.562848     -8.741826        2.912609   \n",
+      "64918    -28.786121    -22.444038     -8.562728        2.869480   \n",
+      "64919    -27.682078    -22.441321     -8.687824        2.807153   \n",
+      "...             ...           ...           ...             ...   \n",
+      "64984    155.175623      1.238733      6.838586       -0.073680   \n",
+      "64985    113.945240      0.277811      3.244123       -0.055712   \n",
+      "64986     74.769462     -8.853878     -2.856426       -0.037371   \n",
+      "64987     44.224040    -13.018254     -5.955675       -0.018760   \n",
+      "64988     20.078446    -17.082119     -8.859597        0.000000   \n",
+      "\n",
+      "       Penetration Depth (m)  Pore Pressure (kPa)  \n",
+      "64915               0.000000           102.421527  \n",
+      "64916               0.001472           102.461846  \n",
+      "64917               0.002935           102.497080  \n",
+      "64918               0.004381           102.495627  \n",
+      "64919               0.005800           102.501438  \n",
+      "...                      ...                  ...  \n",
+      "64984               0.014668           112.754020  \n",
+      "64985               0.014635           110.921878  \n",
+      "64986               0.014612           108.595742  \n",
+      "64987               0.014598           105.846077  \n",
+      "64988               0.014593           102.788028  \n",
+      "\n",
+      "[74 rows x 12 columns]\n",
+      "Firmness factor =  260.9\n",
+      "max penetration depth =  0.0218\n",
+      "phi = 41.0\n",
+      "Keep Drop? (y/n)\n"
+     ]
+    },
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: 'H:\\\\.shortcut-targets-by-id\\\\1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb\\\\Duck  2023\\\\Data\\\\Intertidal\\\\BlueDrop, Samples & Moisture Gage\\\\07March23\\\\BD2 3.8.23 - Drops Only\\\\Analysis Figures\\\\004D 0 BC - REJECTED.png'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code - single drop analysis.ipynb Cell 16\u001b[0m in \u001b[0;36m7\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20single%20drop%20analysis.ipynb#X25sZmlsZQ%3D%3D?line=67'>68</a>\u001b[0m dep_qsbc_comboplot(drop1g,drop1,acc1Nameg, qdyn1)\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20single%20drop%20analysis.ipynb#X25sZmlsZQ%3D%3D?line=68'>69</a>\u001b[0m plotName \u001b[39m=\u001b[39m fileNum\u001b[39m+\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m+\u001b[39m\u001b[39mstr\u001b[39m(a)\u001b[39m+\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m BC - REJECTED\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20single%20drop%20analysis.ipynb#X25sZmlsZQ%3D%3D?line=69'>70</a>\u001b[0m plt\u001b[39m.\u001b[39;49msavefig(plotPath \u001b[39m/\u001b[39;49m plotName)\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20single%20drop%20analysis.ipynb#X25sZmlsZQ%3D%3D?line=70'>71</a>\u001b[0m output_table1 \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame([BD, fileNum, a, soiltype, atype, tiptype, droptype,\u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mNaN\u001b[39m\u001b[39m'\u001b[39m])\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20-%20single%20drop%20analysis.ipynb#X25sZmlsZQ%3D%3D?line=71'>72</a>\u001b[0m output_table1 \u001b[39m=\u001b[39m output_table1\u001b[39m.\u001b[39mT\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\pyplot.py:977\u001b[0m, in \u001b[0;36msavefig\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    974\u001b[0m \u001b[39m@_copy_docstring_and_deprecators\u001b[39m(Figure\u001b[39m.\u001b[39msavefig)\n\u001b[0;32m    975\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39msavefig\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m    976\u001b[0m     fig \u001b[39m=\u001b[39m gcf()\n\u001b[1;32m--> 977\u001b[0m     res \u001b[39m=\u001b[39m fig\u001b[39m.\u001b[39msavefig(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m    978\u001b[0m     fig\u001b[39m.\u001b[39mcanvas\u001b[39m.\u001b[39mdraw_idle()   \u001b[39m# need this if 'transparent=True' to reset colors\u001b[39;00m\n\u001b[0;32m    979\u001b[0m     \u001b[39mreturn\u001b[39;00m res\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\figure.py:3058\u001b[0m, in \u001b[0;36mFigure.savefig\u001b[1;34m(self, fname, transparent, **kwargs)\u001b[0m\n\u001b[0;32m   3054\u001b[0m     \u001b[39mfor\u001b[39;00m ax \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39maxes:\n\u001b[0;32m   3055\u001b[0m         stack\u001b[39m.\u001b[39menter_context(\n\u001b[0;32m   3056\u001b[0m             ax\u001b[39m.\u001b[39mpatch\u001b[39m.\u001b[39m_cm_set(facecolor\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mnone\u001b[39m\u001b[39m'\u001b[39m, edgecolor\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mnone\u001b[39m\u001b[39m'\u001b[39m))\n\u001b[1;32m-> 3058\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcanvas\u001b[39m.\u001b[39mprint_figure(fname, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\backend_bases.py:2319\u001b[0m, in \u001b[0;36mFigureCanvasBase.print_figure\u001b[1;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[0;32m   2315\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m   2316\u001b[0m     \u001b[39m# _get_renderer may change the figure dpi (as vector formats\u001b[39;00m\n\u001b[0;32m   2317\u001b[0m     \u001b[39m# force the figure dpi to 72), so we need to set it again here.\u001b[39;00m\n\u001b[0;32m   2318\u001b[0m     \u001b[39mwith\u001b[39;00m cbook\u001b[39m.\u001b[39m_setattr_cm(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfigure, dpi\u001b[39m=\u001b[39mdpi):\n\u001b[1;32m-> 2319\u001b[0m         result \u001b[39m=\u001b[39m print_method(\n\u001b[0;32m   2320\u001b[0m             filename,\n\u001b[0;32m   2321\u001b[0m             facecolor\u001b[39m=\u001b[39mfacecolor,\n\u001b[0;32m   2322\u001b[0m             edgecolor\u001b[39m=\u001b[39medgecolor,\n\u001b[0;32m   2323\u001b[0m             orientation\u001b[39m=\u001b[39morientation,\n\u001b[0;32m   2324\u001b[0m             bbox_inches_restore\u001b[39m=\u001b[39m_bbox_inches_restore,\n\u001b[0;32m   2325\u001b[0m             \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m   2326\u001b[0m \u001b[39mfinally\u001b[39;00m:\n\u001b[0;32m   2327\u001b[0m     \u001b[39mif\u001b[39;00m bbox_inches \u001b[39mand\u001b[39;00m restore_bbox:\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\backend_bases.py:1648\u001b[0m, in \u001b[0;36m_check_savefig_extra_args.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m   1640\u001b[0m     _api\u001b[39m.\u001b[39mwarn_deprecated(\n\u001b[0;32m   1641\u001b[0m         \u001b[39m'\u001b[39m\u001b[39m3.3\u001b[39m\u001b[39m'\u001b[39m, name\u001b[39m=\u001b[39mname, removal\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39m3.6\u001b[39m\u001b[39m'\u001b[39m,\n\u001b[0;32m   1642\u001b[0m         message\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39m%(name)s\u001b[39;00m\u001b[39m() got unexpected keyword argument \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\n\u001b[0;32m   1643\u001b[0m                 \u001b[39m+\u001b[39m arg \u001b[39m+\u001b[39m \u001b[39m'\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m which is no longer supported as of \u001b[39m\u001b[39m'\u001b[39m\n\u001b[0;32m   1644\u001b[0m                 \u001b[39m'\u001b[39m\u001b[39m%(since)s\u001b[39;00m\u001b[39m and will become an error \u001b[39m\u001b[39m'\u001b[39m\n\u001b[0;32m   1645\u001b[0m                 \u001b[39m'\u001b[39m\u001b[39m%(removal)s\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[0;32m   1646\u001b[0m     kwargs\u001b[39m.\u001b[39mpop(arg)\n\u001b[1;32m-> 1648\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\_api\\deprecation.py:415\u001b[0m, in \u001b[0;36mdelete_parameter.<locals>.wrapper\u001b[1;34m(*inner_args, **inner_kwargs)\u001b[0m\n\u001b[0;32m    405\u001b[0m     deprecation_addendum \u001b[39m=\u001b[39m (\n\u001b[0;32m    406\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mIf any parameter follows \u001b[39m\u001b[39m{\u001b[39;00mname\u001b[39m!r}\u001b[39;00m\u001b[39m, they should be passed as \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    407\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mkeyword, not positionally.\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    408\u001b[0m     warn_deprecated(\n\u001b[0;32m    409\u001b[0m         since,\n\u001b[0;32m    410\u001b[0m         name\u001b[39m=\u001b[39m\u001b[39mrepr\u001b[39m(name),\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    413\u001b[0m                  \u001b[39melse\u001b[39;00m deprecation_addendum,\n\u001b[0;32m    414\u001b[0m         \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[1;32m--> 415\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39minner_args, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39minner_kwargs)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:541\u001b[0m, in \u001b[0;36mFigureCanvasAgg.print_png\u001b[1;34m(self, filename_or_obj, metadata, pil_kwargs, *args)\u001b[0m\n\u001b[0;32m    494\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m    495\u001b[0m \u001b[39mWrite the figure to a PNG file.\u001b[39;00m\n\u001b[0;32m    496\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    538\u001b[0m \u001b[39m    *metadata*, including the default 'Software' key.\u001b[39;00m\n\u001b[0;32m    539\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m    540\u001b[0m FigureCanvasAgg\u001b[39m.\u001b[39mdraw(\u001b[39mself\u001b[39m)\n\u001b[1;32m--> 541\u001b[0m mpl\u001b[39m.\u001b[39;49mimage\u001b[39m.\u001b[39;49mimsave(\n\u001b[0;32m    542\u001b[0m     filename_or_obj, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbuffer_rgba(), \u001b[39mformat\u001b[39;49m\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mpng\u001b[39;49m\u001b[39m\"\u001b[39;49m, origin\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mupper\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[0;32m    543\u001b[0m     dpi\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfigure\u001b[39m.\u001b[39;49mdpi, metadata\u001b[39m=\u001b[39;49mmetadata, pil_kwargs\u001b[39m=\u001b[39;49mpil_kwargs)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\image.py:1675\u001b[0m, in \u001b[0;36mimsave\u001b[1;34m(fname, arr, vmin, vmax, cmap, format, origin, dpi, metadata, pil_kwargs)\u001b[0m\n\u001b[0;32m   1673\u001b[0m pil_kwargs\u001b[39m.\u001b[39msetdefault(\u001b[39m\"\u001b[39m\u001b[39mformat\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mformat\u001b[39m)\n\u001b[0;32m   1674\u001b[0m pil_kwargs\u001b[39m.\u001b[39msetdefault(\u001b[39m\"\u001b[39m\u001b[39mdpi\u001b[39m\u001b[39m\"\u001b[39m, (dpi, dpi))\n\u001b[1;32m-> 1675\u001b[0m image\u001b[39m.\u001b[39msave(fname, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mpil_kwargs)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\PIL\\Image.py:2317\u001b[0m, in \u001b[0;36mImage.save\u001b[1;34m(self, fp, format, **params)\u001b[0m\n\u001b[0;32m   2315\u001b[0m         fp \u001b[39m=\u001b[39m builtins\u001b[39m.\u001b[39mopen(filename, \u001b[39m\"\u001b[39m\u001b[39mr+b\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m   2316\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 2317\u001b[0m         fp \u001b[39m=\u001b[39m builtins\u001b[39m.\u001b[39;49mopen(filename, \u001b[39m\"\u001b[39;49m\u001b[39mw+b\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[0;32m   2319\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m   2320\u001b[0m     save_handler(\u001b[39mself\u001b[39m, fp, filename)\n",
+      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'H:\\\\.shortcut-targets-by-id\\\\1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb\\\\Duck  2023\\\\Data\\\\Intertidal\\\\BlueDrop, Samples & Moisture Gage\\\\07March23\\\\BD2 3.8.23 - Drops Only\\\\Analysis Figures\\\\004D 0 BC - REJECTED.png'"
+     ]
+    }
+   ],
+   "source": [
+    "finddropend(a) #automatically find the end of the drop\n",
+    "print(\"penend: \", penend)\n",
+    "offset = acc1g[penstart] #sets the offset to be the acceleration at the moment of impact\n",
+    "print(\"offset: \", offset)\n",
+    "#print(drop)\n",
+    "dg = dfCalg[penstart:penend] #chops the file to only include penetration \n",
+    "d = dfCal[penstart:penend]\n",
+    "acc1g = accg[penstart:penend]\n",
+    "acc1g = acc1g-offset\n",
+    "acc1 = acc[penstart:penend]\n",
+    "offsetms = offset * 9.80665\n",
+    "acc1 = acc1-offsetms\n",
+    "\n",
+    "\n",
+    "drop1 = d\n",
+    "drop1g = dg\n",
+    "integration(d, acc1) #double integration to solve for velocity and penetration depth\n",
+    "drop1 = d\n",
+    "areafind() #area calculations for bearing capacity calculations\n",
+    "qdynfun(acc1) #calculation of dynamic bearing capacity\n",
+    "qsbcfun(acc1) #calculation of quasi-static bearing capacities\n",
+    "qdyn1 = qdyn\n",
+    "integplot(drop1,acc1Name)\n",
+    "#qdynplot(drop1, qdyn1)\n",
+    "print(\"Max penetration depth is: \", maxdep)\n",
+    "print(\"Pre-truncation d1\", drop1)\n",
+    "drop1 = pd.DataFrame(drop1)\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "acc1 = pd.DataFrame(acc1)\n",
+    "qdyn1 = pd.DataFrame(qdyn1)\n",
+    "if droptype == \"w\":\n",
+    "    bctable = pd.DataFrame(bctable)\n",
+    "\n",
+    "drop1t = drop1 #.truncate(before=trunc_index) #this truncates each df such that only depths below cone height are considered\n",
+    "drop1gt = drop1g #.truncate(before=trunc_index)\n",
+    "acc1t = acc1 #.truncate(before=trunc_index)\n",
+    "acc1t = np.array(acc1t)\n",
+    "acc1gt = acc1g #.truncate(before=trunc_index)\n",
+    "acc1gt = np.array(acc1gt)\n",
+    "drop1t = drop1 #truncate(before=trunc_index)\n",
+    "qdyn1t = qdyn1#.truncate(before=trunc_index)\n",
+    "if droptype == \"w\":\n",
+    "    bctablet = bctable#.truncate(before=trunc_index)\n",
+    "\n",
+    "#bctruncate(drop1g, drop1, acc1, qdyn1)\n",
+    "firmnessfactor(acc1t, drop1) #calculates the firmness factor\n",
+    "if soiltype == \"s\":\n",
+    "    dr(acc1gt) #calculates relative density\n",
+    "    duncan_correlation() #calculates friction angle\n",
+    "elif soiltype == \"u\":\n",
+    "    if maxdep <= .2:\n",
+    "        dr(acc1gt)\n",
+    "        duncan_correlation()\n",
+    "pentime=(penend - penstart)/2 #ms #calculates the time of penetration\n",
+    "\n",
+    "dep_qsbc_comboplot(drop1g,drop1,acc1Nameg, qdyn1)\n",
+    "plt.show()\n",
+    "ignore_drop()\n",
+    "if keep_drop == \"y\":\n",
+    "    duck_dep_qsbc_comboplot(drop1g, drop1, drop1t, acc1Nameg, qdyn1t)\n",
+    "    print(\"pentime= \", pentime)\n",
+    "\n",
+    "    output_table1 = pd.DataFrame([BD, fileNum, a, soiltype, atype, tiptype, droptype, maxdep*100, maxacc, maxvel, maxbcdep*100, maxqdyn, maxHqsbc, maxLqsbc, maxAqsbc, ff, pentime, Dr, phi])\n",
+    "    output_table1 = output_table1.T\n",
+    "    output_table = output_table1\n",
+    "    output_table.columns = [\"BlueDrop\", \"BD File\", \"Drop No.\", \"Soil Type\", \"Area Type\", \"Tip Type\", \"Drop Type\", \"Penetration Depth (cm)\", \"Maximum Deceleration (m/s^2)\", \"Impact Velocity (m/s)\", \"Depth of Max QSBC (cm)\", \"Max Qdyn (kPa)\", \"Max QSBC-Upper Bounds (kPa)\", \"Max QSBC-Lower Bounds (kPa)\", \"Max QSBC-Average (kPa)\", \"Firmness Factor (m-1)\", \"Penetration Time (ms)\", \"Relative Density (%)\", \"Friction Angle (deg.)\"]  # Creates an empty Dataframe in pandas from the output data\n",
+    "else:\n",
+    "    dep_qsbc_comboplot(drop1g,drop1,acc1Nameg, qdyn1)\n",
+    "    plotName = fileNum+\" \"+str(a)+\" BC - REJECTED\"\n",
+    "    plt.savefig(plotPath / plotName)\n",
+    "    output_table1 = pd.DataFrame([BD, fileNum, a, soiltype, atype, tiptype, droptype,'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN', 'NaN'])\n",
+    "    output_table1 = output_table1.T\n",
+    "    output_table = output_table1\n",
+    "    output_table.columns = [\"BlueDrop\", \"BD File\", \"Drop No.\", \"Soil Type\", \"Area Type\", \"Tip Type\", \"Drop Type\", \"Penetration Depth (cm)\", \"Maximum Deceleration (m/s^2)\", \"Impact Velocity (m/s)\", \"Depth of Max QSBC (cm)\", \"Max Qdyn (kPa)\", \"Max QSBC-Upper Bounds (kPa)\", \"Max QSBC-Lower Bounds (kPa)\", \"Max QSBC-Average (kPa)\", \"Firmness Factor (m-1)\", \"Penetration Time (ms)\", \"Relative Density (%)\", \"Friction Angle (deg.)\"]  # Creates an empty Dataframe in pandas from the output data\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/BD code v7.py b/BD code v7.py
index e817d84..ca71fe2 100644
--- a/BD code v7.py	
+++ b/BD code v7.py	
@@ -16,19 +16,19 @@
 
 
 # SETUP VARIABLES - USER INPUTS
-BD = 2 #Bluedrop file is from 
-fileNum = '0275' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')
-soiltype = "s" #s = sand, c=clay, m=mixed, u=unknown
-atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays)
+BD = 3 #Bluedrop file is from 
+fileNum = '009B' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')
+soiltype = "u" #s = sand, c=clay, m=mixed, u=unknown
+atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays), b = both 
 tiptype = 'c'  # c = cone, p = parabolic, b = blunt
 #offset = 1 # this value is subtracted from the accelerometer readings
-droptype = 'w' #w = water, #a = air
+droptype = 'a' #w = water, #a = air
 sign = "uk" #enter an effective unit weight value in kg/m^3 or "uk" if unknown 
 # paste the filepath to the folder where the BD data is stored
-binFilepath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/08March23/BD2 3.8.23 - Drops Only")
+binFilepath = Path("H:/.shortcut-targets-by-id/1-AJMoJ7sju0bbgBxYYfsq9uMyeECS_MX/Quinhagak June 2023/Demo data collection/PFFP/June 19, 2023/Drops Only")
 #paste the filepath to an excel file that the analysis results will be printed in
-outputPath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/08March23/BlueDrop Data Processing March 8 2023.xlsx") #  Path to pre-existing Excel File
-plotPath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/08March23/BD2 3.8.23 - Drops Only/Analysis Figures")
+outputPath = Path("H:/.shortcut-targets-by-id/1-AJMoJ7sju0bbgBxYYfsq9uMyeECS_MX/Quinhagak June 2023/Demo data collection/PFFP/June 19, 2023/Data Analysis 6-19-23.xlsx") #  Path to pre-existing Excel File
+plotPath = Path("H:/.shortcut-targets-by-id/1-AJMoJ7sju0bbgBxYYfsq9uMyeECS_MX/Quinhagak June 2023/Demo data collection/PFFP/June 19, 2023/Analysis Figures")
 #if applicable, paste the filepath to an excel file that troubleshooting data will be printed in
 troubleshootingPath = Path("H:\My Drive\CEE 5904 - Project & Report/2021 FRF Data\Bluedrop\October/14 October 2021 AM\Troubleshooting.xlsx")
 
@@ -228,11 +228,11 @@ def areafind(): #finds the embedded area based on the penetration depth, area ty
                 if d1[k]<length:
                     r.append(.22+d1[k]*((4.375-.22)/7.55))
                     # r.append(d1[k]*np.tan(30*pi/180))
-                    a1.append(pi*r[k]**2)
+                    a1.append(pi*(r[k])**2)
                 elif d1[k]>=length:
                     r.append(4.375)
-                    if r[k-1]<r[k]:
-                        trunc_index = r.index(r[k-1])+jindex+dropstart #performs analysis only on readings beyond depth of cone height
+                    '''if r[k-1]<r[k]:
+                        trunc_index = r.index(r[k-1])+jindex+dropstart #performs analysis only on readings beyond depth of cone height'''
                     a1.append(pi*(r[k])**2)
                 a1[k] = a1[k]/10000
             area = a1
@@ -414,7 +414,7 @@ def overviewplot(): #Plot showing all accellerometers and pore pressure readings
 
     fig.subplots_adjust(bottom=.1, left = .1)
     plotName = fileNum+" Overview.png"
-    plt.savefig(plotPath / plotName)
+    #plt.savefig(plotPath / plotName)
     plt.show()
 
 def integplot(drop, accName): #Deceleration,Velocity,and penetration depth vs time plots
diff --git a/BD code v8.ipynb b/BD code v8.ipynb
index 3a27ae5..ff1f895 100644
--- a/BD code v8.ipynb	
+++ b/BD code v8.ipynb	
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,13 +50,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
     "# SETUP VARIABLES - USER INPUTS\n",
     "BD = 3 #Bluedrop file is from \n",
-    "fileNum = '009B' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "fileNum = '0157' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
     "soiltype = \"u\" #s = sand, c=clay, m=mixed, u=unknown\n",
     "atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays), b = both \n",
     "tiptype = 'c'  # c = cone, p = parabolic, b = blunt\n",
@@ -65,7 +65,7 @@
     "droptype = 'a' #w = water, #a = air\n",
     "sign = \"uk\" #enter an effective unit weight value in kg/m^3 or \"uk\" if unknown \n",
     "# paste the filepath to the folder where the BD data is stored\n",
-    "binFilepath = Path(\"H:/.shortcut-targets-by-id/2-AJMoJ7sju0bbgBxYYfsq9uMyeECS_MX/Quinhagak June 2023/Demo data collection/PFFP/June 29, 2023/Drops Only\")\n",
+    "binFilepath = Path(\"C:/Users/elise/Desktop/BD Testing/Gravel Drop Files\")\n",
     "#paste the filepath to an excel file that the analysis results will be printed in\n",
     "outputPath = Path(\"C:/Users/elise/Desktop/BD Testing/Test Data.xlsx\") #  Path to pre-existing Excel File\n",
     "plotPath = Path(\"C:/Users/elise/Desktop/BD Testing/Analysis Figures\")\n",
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -166,7 +166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -219,7 +219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -299,7 +299,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -554,7 +554,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -689,7 +689,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -815,7 +815,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -840,7 +840,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -883,7 +883,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -929,7 +929,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -966,7 +966,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1003,7 +1003,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1150,76 +1150,132 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "peak index: 35804\n",
-      "start of penetration:  35765\n",
-      "penstart:  35765\n",
-      "penend:  35813\n",
-      "offset:  2.550797670097759\n",
+      "peak index: 81932\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "start of penetration:  81883\n",
+      "penstart:  81883\n",
+      "penend:  81981\n",
+      "offset:  0.592910582958763\n",
       "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
-      " [1.92620030e-01 3.26004798e-01 3.87811410e-05]\n",
-      " [3.82230981e-01 4.30353606e-01 7.78196279e-05]\n",
-      " [5.66991928e-01 5.32033306e-01 1.29957383e-04]\n",
-      " [7.45065797e-01 6.30032899e-01 1.93128464e-04]\n",
-      " [9.15140102e-01 7.23630083e-01 2.65225329e-04]\n",
-      " [1.07650765e+00 8.12435664e-01 3.44227610e-04]\n",
-      " [1.22881731e+00 8.96256416e-01 4.28247744e-04]\n",
-      " [1.37189103e+00 9.74994333e-01 5.15527900e-04]\n",
-      " [1.50567008e+00 1.04861711e+00 6.04456659e-04]\n",
-      " [1.63018978e+00 1.11714417e+00 6.93584016e-04]\n",
-      " [1.74555925e+00 1.18063559e+00 7.81628056e-04]\n",
-      " [1.85195117e+00 1.23918637e+00 8.67480079e-04]\n",
-      " [1.94960014e+00 1.29292564e+00 9.50211259e-04]\n",
-      " [2.03879513e+00 1.34201242e+00 1.02907043e-03]\n",
-      " [2.11986756e+00 1.38662910e+00 1.10347360e-03]\n",
-      " [2.19318701e+00 1.42697908e+00 1.17299636e-03]\n",
-      " [2.25915403e+00 1.46328278e+00 1.23736131e-03]\n",
-      " [2.31818967e+00 1.49577193e+00 1.29642002e-03]\n",
-      " [2.37073129e+00 1.52468722e+00 1.35013943e-03]\n",
-      " [2.41722716e+00 1.55027535e+00 1.39858657e-03]\n",
-      " [2.45812569e+00 1.57278308e+00 1.44190701e-03]\n",
-      " [2.49386847e+00 1.59245344e+00 1.48030714e-03]\n",
-      " [2.52489314e+00 1.60952729e+00 1.51404727e-03]\n",
-      " [2.55163862e+00 1.62424615e+00 1.54343864e-03]\n",
-      " [2.57453722e+00 1.63684797e+00 1.56882697e-03]\n",
-      " [2.59399871e+00 1.64755823e+00 1.59056720e-03]\n",
-      " [2.61039731e+00 1.65658289e+00 1.60900198e-03]\n",
-      " [2.62407402e+00 1.66410961e+00 1.62445808e-03]\n",
-      " [2.63537197e+00 1.67032722e+00 1.63728164e-03]\n",
-      " [2.64464440e+00 1.67543013e+00 1.64784381e-03]\n",
-      " [2.65220995e+00 1.67959369e+00 1.65648682e-03]\n",
-      " [2.65833987e+00 1.68296717e+00 1.66350632e-03]\n",
-      " [2.66327338e+00 1.68568224e+00 1.66916657e-03]\n",
-      " [2.66721904e+00 1.68785366e+00 1.67370035e-03]\n",
-      " [2.67035699e+00 1.68958057e+00 1.67731043e-03]\n",
-      " [2.67284716e+00 1.69095099e+00 1.68017803e-03]\n",
-      " [2.67482706e+00 1.69204059e+00 1.68245976e-03]\n",
-      " [2.67640277e+00 1.69290775e+00 1.68427678e-03]\n",
-      " [2.67765523e+00 1.69359702e+00 1.68572176e-03]\n",
-      " [2.67864809e+00 1.69414342e+00 1.68686767e-03]\n",
-      " [2.67942728e+00 1.69457223e+00 1.68776725e-03]\n",
-      " [2.68002996e+00 1.69490391e+00 1.68846321e-03]\n",
-      " [2.68049016e+00 1.69515717e+00 1.68899473e-03]\n",
-      " [2.68082770e+00 1.69534293e+00 1.68938464e-03]\n",
-      " [2.68104466e+00 1.69546233e+00 1.68963529e-03]\n",
-      " [2.68114565e+00 1.69551790e+00 1.68975196e-03]\n",
-      " [2.68116885e+00 1.69553067e+00 1.68977876e-03]]\n",
-      "area_m =  [1.5205308443374599e-05, 3.878114095545497e-05, 7.78196278722081e-05, 0.0001299573832134037, 0.00019312846353256252, 0.0002652253292674964, 0.0003442276102040862, 0.0004282477438199883, 0.000515527900095831, 0.0006044566587854061, 0.0006935840162902867, 0.0007816280557081604, 0.0008674800789563381, 0.0009502112594606093, 0.001029070429593936, 0.0011034736000326258, 0.0011729963554846872, 0.0012373613131944057, 0.0012964200179028246, 0.0013501394342569993, 0.0013985865666183693, 0.001441907012546163, 0.0014803071364423341, 0.0015140472659480016, 0.0015434386444335415, 0.0015688269683193131, 0.0015905671959758176, 0.00160900197510654, 0.0016244580793394177, 0.0016372816383222407, 0.0016478438084074753, 0.001656486821978901, 0.0016635063225219234, 0.0016691665661934835, 0.0016737003530273142, 0.001677310430396546, 0.0016801780271068925, 0.0016824597562466138, 0.0016842767827685331, 0.0016857217617403265, 0.0016868676697658251, 0.0016877672518317353, 0.0016884632081475817, 0.0016889947315357312, 0.0016893846376884298, 0.0016896352867662653, 0.0016897519570761993, 0.0016897787578980434]  area_p =  [1.5205308443374599e-05, 3.338857286118787e-05, 5.818362365897145e-05, 8.89257454272339e-05, 0.00012470283546038422, 0.00016450651377999741, 0.00020736135994885613, 0.0002523564607854452, 0.0002986441800367523, 0.0003454488501601284, 0.00039207425224183626, 0.0004379067234393675, 0.00048241758463148, 0.0005251664452267417, 0.0005657999976364569, 0.0006040466692033784, 0.0006397128617831572, 0.0006726767186236166, 0.0007028791025654051, 0.0007303169722768962, 0.0007550358159632036, 0.0007771190018781629, 0.0007966789839814212, 0.0008138541084756033, 0.0008288072995789388, 0.0008417178941484377, 0.0008527690302293286, 0.0008621368672298662, 0.0008699889366590476, 0.0008765021631489373, 0.0008818658313937691, 0.0008862542677843276, 0.0008898179496417367, 0.0008926912835134791, 0.0008949926122865841, 0.0008968249583962715, 0.0008982803772925591, 0.0008994384006578379, 0.0009003605499396096, 0.0009010938655853623, 0.0009016753938430907, 0.0009021319090569178, 0.0009024850851571916, 0.0009027548142262538, 0.0009029526762730814, 0.0009030798702245352, 0.0009031390753789975, 0.0009031526756266708]\n",
-      "Acc_n:  (48,)\n",
-      "area:  48\n"
+      " [1.71483396e-01 3.14372650e-01 3.53672121e-05]\n",
+      " [3.42686856e-01 4.08591243e-01 6.84524948e-05]\n",
+      " [5.13593764e-01 5.02646634e-01 1.13479994e-04]\n",
+      " [6.84167309e-01 5.96518565e-01 1.70104646e-04]\n",
+      " [8.54336993e-01 6.90168239e-01 2.38132574e-04]\n",
+      " [1.02403763e+00 7.83559783e-01 3.17408374e-04]\n",
+      " [1.19322058e+00 8.76666426e-01 4.07789613e-04]\n",
+      " [1.36179582e+00 9.69438625e-01 5.09104150e-04]\n",
+      " [1.52964796e+00 1.06181289e+00 6.21143097e-04]\n",
+      " [1.69671724e+00 1.15375631e+00 7.43712647e-04]\n",
+      " [1.86297970e+00 1.24525571e+00 8.76635159e-04]\n",
+      " [2.02836990e+00 1.33627509e+00 1.01969114e-03]\n",
+      " [2.19278430e+00 1.42675745e+00 1.17260870e-03]\n",
+      " [2.35613101e+00 1.51665223e+00 1.33510252e-03]\n",
+      " [2.51836854e+00 1.60593660e+00 1.50692004e-03]\n",
+      " [2.67949153e+00 1.69460759e+00 1.68784143e-03]\n",
+      " [2.83947854e+00 1.78265342e+00 1.87762753e-03]\n",
+      " [2.99824519e+00 1.87002765e+00 2.07595470e-03]\n",
+      " [3.15562162e+00 1.95663680e+00 2.28236521e-03]\n",
+      " [3.31142469e+00 2.04238008e+00 2.49634261e-03]\n",
+      " [3.46553132e+00 2.12718975e+00 2.71741613e-03]\n",
+      " [3.61785121e+00 2.21101613e+00 2.94513837e-03]\n",
+      " [3.76832812e+00 2.29382826e+00 3.17909781e-03]\n",
+      " [3.91687682e+00 2.37557923e+00 3.41882594e-03]\n",
+      " [4.06323447e+00 2.45612440e+00 3.66353644e-03]\n",
+      " [4.20711367e+00 2.53530560e+00 3.91234433e-03]\n",
+      " [4.34841110e+00 2.61306598e+00 4.16463996e-03]\n",
+      " [4.48715652e+00 2.68942190e+00 4.42004691e-03]\n",
+      " [4.62346651e+00 2.76443753e+00 4.67836997e-03]\n",
+      " [4.75748916e+00 2.83819437e+00 4.93950844e-03]\n",
+      " [4.88927341e+00 2.91071934e+00 5.20319852e-03]\n",
+      " [5.01877927e+00 2.98199044e+00 5.46900777e-03]\n",
+      " [5.14599126e+00 3.05199916e+00 5.73655388e-03]\n",
+      " [5.27087992e+00 3.12072928e+00 6.00542715e-03]\n",
+      " [5.39331058e+00 3.18810668e+00 6.27498419e-03]\n",
+      " [5.51306306e+00 3.25401020e+00 6.54436818e-03]\n",
+      " [5.62996082e+00 3.31834267e+00 6.81278988e-03]\n",
+      " [5.74391597e+00 3.38105574e+00 7.07964636e-03]\n",
+      " [5.85485320e+00 3.44210795e+00 7.34435920e-03]\n",
+      " [5.96276319e+00 3.50149418e+00 7.60650913e-03]\n",
+      " [6.06771854e+00 3.55925438e+00 7.86589024e-03]\n",
+      " [6.16966824e+00 3.61536047e+00 8.12200618e-03]\n",
+      " [6.26842149e+00 3.66970746e+00 8.37400349e-03]\n",
+      " [6.36389795e+00 3.72225113e+00 8.62129882e-03]\n",
+      " [6.45616847e+00 3.77303046e+00 8.86370910e-03]\n",
+      " [6.54535801e+00 3.82211424e+00 9.10121909e-03]\n",
+      " [6.63154531e+00 3.86954580e+00 9.33371711e-03]\n",
+      " [6.71455227e+00 3.91522711e+00 9.56040745e-03]\n",
+      " [6.79404646e+00 3.95897524e+00 9.78005383e-03]\n",
+      " [6.86993767e+00 4.00074053e+00 9.99207216e-03]\n",
+      " [6.94237518e+00 4.04060515e+00 1.01965622e-02]\n",
+      " [7.01148593e+00 4.07863895e+00 1.03935915e-02]\n",
+      " [7.07725925e+00 4.11483605e+00 1.05828567e-02]\n",
+      " [7.13959315e+00 4.14914034e+00 1.07638009e-02]\n",
+      " [7.19850204e+00 4.18155973e+00 1.09362123e-02]\n",
+      " [7.25423153e+00 4.21222940e+00 1.11005792e-02]\n",
+      " [7.30709302e+00 4.24132073e+00 1.12576201e-02]\n",
+      " [7.35732580e+00 4.26896539e+00 1.14078737e-02]\n",
+      " [7.40518013e+00 4.29530112e+00 1.15519393e-02]\n",
+      " [7.45096053e+00 4.32049550e+00 1.16906073e-02]\n",
+      " [7.49490856e+00 4.34468147e+00 1.18245033e-02]\n",
+      " [7.53712888e+00 4.36791662e+00 1.19538534e-02]\n",
+      " [7.57758902e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.61616838e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.65279072e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.68741539e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.71998456e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.75052610e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.77920627e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.80620320e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.83167992e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.85581631e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.87869754e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.90033565e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.92073489e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.93985535e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.95767899e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.97425219e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.98967761e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.00409304e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.01758629e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.03014210e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.04158958e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.05171668e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.06030407e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.06718649e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.07236842e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.07611378e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.07908213e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08182124e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08442068e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08675662e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08857945e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08963300e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.08999452e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.09004643e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.09004700e+00 4.37500000e+00 1.19934265e-02]]\n",
+      "area_m =  [1.5205308443374599e-05, 3.536721206138242e-05, 6.845249483756974e-05, 0.00011347999439002181, 0.00017010464649465945, 0.00023813257386180847, 0.00031740837357808365, 0.00040778961262880975, 0.000509104149661951, 0.0006211430967430675, 0.0007437126466650908, 0.0008766351591273143, 0.0010196911382003681, 0.001172608704246558, 0.0013351025167529056, 0.001506920041446284, 0.0016878414326757995, 0.0018776275277454753, 0.0020759546963490675, 0.002282365213736585, 0.0024963426092729983, 0.002717416131171673, 0.0029451383709295917, 0.0031790978123621937, 0.00341882594217562, 0.003663536437420435, 0.003912344325907441, 0.00416463996005786, 0.004420046912253256, 0.004678369965122665, 0.00493950844239012, 0.005203198516589992, 0.005469007773423298, 0.005736553875278352, 0.006005427146895118, 0.006274984186200164, 0.006544368181198894, 0.00681278987664178, 0.007079646359161383, 0.007344359203666105, 0.007606509126513341, 0.007865890241595482, 0.00812200617779562, 0.008374003485312738, 0.008621298819570447, 0.008863709104216742, 0.009101219092395198, 0.009333717109795492, 0.009560407451048969, 0.009780053825437755, 0.009992072156868627, 0.010196562231225476, 0.010393591453972655, 0.010582856734188198, 0.010763800856958354, 0.010936212276919268, 0.011100579188900131, 0.01125762014556377, 0.01140787372020789, 0.011551939329915831, 0.011690607286819246, 0.011824503277731088, 0.011953853413717947, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899, 0.011993426513195899]  area_p =  [1.5205308443374599e-05, 3.1048411462311446e-05, 5.244788532026272e-05, 7.937348166521704e-05, 0.00011178867329035954, 0.00014964417345684466, 0.00019288308640111963, 0.0002414452257230856, 0.00029525041119113056, 0.00035419779647411214, 0.00041819424504199797, 0.000487154769373339, 0.0005609725615473002, 0.0006395141710019002, 0.0007226398219757071, 0.0008102269082011001, 0.0009021695536926963, 0.000998352036374156, 0.0010986160212984634, 0.0012027359907418806, 0.001310457689537966, 0.0014215506428893751, 0.0015357965737826825, 0.001652995492492996, 0.0017729190721124993, 0.0018951805589269963, 0.0020193449131681966, 0.0021451152147523005, 0.002272310871025335, 0.0024008411908424867, 0.002530661981140646, 0.002661647487405943, 0.002793588072411821, 0.0029262989572167793, 0.0030595817723926143, 0.0031931223838268102, 0.0033265012664828197, 0.0034593327401648047, 0.003591323557171246, 0.003722192642674442, 0.003851737577206724, 0.003979861220960687, 0.0041063227684790355, 0.004230705168858424, 0.0043527248261797285, 0.004472295544480777, 0.00458941362631846, 0.004704027531162306, 0.004815748418259183, 0.004923970516006239, 0.005028409584867102, 0.005129118097729482, 0.005226132262839142, 0.005319305637727179, 0.005408366589643049, 0.005493213545940948, 0.005574089059499778, 0.005651348669236851, 0.005725259032157868, 0.005796116461101265, 0.005864310891175887, 0.005930151047111297, 0.005993749002660365, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713]\n",
+      "Acc_n:  (98,)\n",
+      "area:  98\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_1252\\3912607897.py:52: RuntimeWarning: divide by zero encountered in log10\n",
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_20604\\3912607897.py:52: RuntimeWarning: divide by zero encountered in log10\n",
       "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
      ]
     },
@@ -1227,252 +1283,321 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Max penetration depth is:  0.0268\n",
+      "Max penetration depth is:  0.0809\n",
       "Pre-truncation d1          Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  200g (m/s^2)  \\\n",
-      "35765  35765.0   17.8830   19.668068    29.318899    25.014780     34.603224   \n",
-      "35766  35766.0   17.8835   19.668135    30.915935    28.726360     36.026232   \n",
-      "35767  35767.0   17.8840   19.668056    29.438941    30.037768     34.669545   \n",
-      "35768  35768.0   17.8845   19.668007    29.563784    29.813895     34.583807   \n",
-      "35769  35769.0   17.8850   19.668080    29.889158    29.685507     35.113873   \n",
-      "35770  35770.0   17.8855   19.668178    31.363571    30.499812     36.639010   \n",
-      "35771  35771.0   17.8860   19.668129    32.918954    32.170400     38.402199   \n",
-      "35772  35772.0   17.8865   19.668050    34.985714    33.461358     40.534063   \n",
-      "35773  35773.0   17.8870   19.668159    37.870980    35.151934     43.617372   \n",
-      "35774  35774.0   17.8875   19.668080    40.935828    37.831025     46.814160   \n",
-      "35775  35775.0   17.8880   19.668068    44.590682    40.963858     50.652221   \n",
-      "35776  35776.0   17.8885   19.668105    50.928831    44.970808     57.070004   \n",
-      "35777  35777.0   17.8890   19.668056    56.940646    50.797492     62.885096   \n",
-      "35778  35778.0   17.8895   19.668086    63.906134    57.138807     69.909353   \n",
-      "35779  35779.0   17.8900   19.668038    73.137231    64.216471     79.177943   \n",
-      "35780  35780.0   17.8905   19.667971    83.112228    72.544347     89.208093   \n",
-      "35781  35781.0   17.8910   19.667947    93.938381    82.179018     99.974334   \n",
-      "35782  35782.0   17.8915   19.668044   105.725409    92.856788    111.979245   \n",
-      "35783  35783.0   17.8920   19.668099   122.165619   105.267879    128.311684   \n",
-      "35784  35784.0   17.8925   19.668190   136.615356   120.750299    143.171436   \n",
-      "35785  35785.0   17.8930   19.668123   147.866997   133.891282    154.408483   \n",
-      "35786  35786.0   17.8935   19.668256   163.612525   147.029344    170.704861   \n",
-      "35787  35787.0   17.8940   19.668396   180.790873   162.171650    188.196787   \n",
-      "35788  35788.0   17.8945   19.668475   195.008808   178.624133    206.300231   \n",
-      "35789  35789.0   17.8950   19.668487   198.931055   196.139243    224.189329   \n",
-      "35790  35790.0   17.8955   19.668493   199.006081   213.828099    241.167580   \n",
-      "35791  35791.0   17.8960   19.668572   199.007222   231.160697    259.653822   \n",
-      "35792  35792.0   17.8965   19.668463   199.008122   248.829104    278.488817   \n",
-      "35793  35793.0   17.8970   19.668512   199.006201   266.814869    296.977076   \n",
-      "35794  35794.0   17.8975   19.668518   199.006201   284.920719    314.816244   \n",
-      "35795  35795.0   17.8980   19.668408   199.007702   302.445823    331.710018   \n",
-      "35796  35796.0   17.8985   19.668420   199.007222   319.267788    348.307237   \n",
-      "35797  35797.0   17.8990   19.668493   199.006081   335.465801    363.641326   \n",
-      "35798  35798.0   17.8995   19.668457   199.007402   350.337645    377.334530   \n",
-      "35799  35799.0   17.9000   19.668372   199.008722   363.525986    388.945547   \n",
-      "35800  35800.0   17.9005   19.668542   199.007102   375.307743    398.991332   \n",
-      "35801  35801.0   17.9010   19.668645   199.007882   384.788655    406.362326   \n",
-      "35802  35802.0   17.9015   19.668621   199.008662   391.583711    410.628072   \n",
-      "35803  35803.0   17.9020   19.668591   199.008902   396.138196    411.644326   \n",
-      "35804  35804.0   17.9025   19.668493   199.006381   397.695772    409.109491   \n",
-      "35805  35805.0   17.9030   19.668481   199.007342   395.675075    401.843905   \n",
-      "35806  35806.0   17.9035   19.668584   199.007942   388.766238    389.125851   \n",
-      "35807  35807.0   17.9040   19.668554   199.006802   376.111439    366.330238   \n",
-      "35808  35808.0   17.9045   19.668572   198.923733   352.151997    312.012845   \n",
-      "35809  35809.0   17.9050   19.668554   185.566257   299.573765    219.706463   \n",
-      "35810  35810.0   17.9055   19.668512   127.580827   218.692254    135.207081   \n",
-      "35811  35811.0   17.9060   19.668275    75.022788   139.101394     82.245870   \n",
-      "35812  35812.0   17.9065   19.668208    50.274062    84.616708     55.813178   \n",
+      "81883  81883.0   40.9420    5.766183     5.814467     6.681675     13.322914   \n",
+      "81884  81884.0   40.9425    5.859617     5.905218     6.398759     13.411679   \n",
+      "81885  81885.0   40.9430    9.451727    13.847907     7.213679     21.467825   \n",
+      "81886  81886.0   40.9435   16.805393    39.194261    16.934455     48.607861   \n",
+      "81887  81887.0   40.9440   18.143820    41.746110    34.948358     48.266672   \n",
+      "...        ...       ...         ...          ...          ...           ...   \n",
+      "81976  81976.0   40.9885   19.448293    21.973419    25.810020     29.493206   \n",
+      "81977  81977.0   40.9890   18.340095    18.531339    22.639363     26.134272   \n",
+      "81978  81978.0   40.9895   17.547887    17.559960    19.678740     25.196696   \n",
+      "81979  81979.0   40.9900   17.068657    17.054944    18.315669     24.685543   \n",
+      "81980  81980.0   40.9905   16.390424    16.377668    17.496289     24.029138   \n",
       "\n",
       "       250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  Velocity (m/s)  \\\n",
-      "35765     25.502041     -1.257623      4.940662        3.874112   \n",
-      "35766     29.140237     -2.464205      4.277975        3.830690   \n",
-      "35767     30.698954     -2.222298      3.815263        3.753749   \n",
-      "35768     30.285912     -1.178190      3.955100        3.636689   \n",
-      "35769     29.521891     -0.738359      4.026573        3.486265   \n",
-      "35770     29.332847     -1.230051      4.157908        3.316707   \n",
-      "35771     30.836635     -1.250237      4.244036        3.137995   \n",
-      "35772     33.581689     -1.125017      4.607971        2.954392   \n",
-      "35773     35.920835     -1.045420      5.095015        2.768557   \n",
-      "35774     38.100186     -0.879335      5.170014        2.582605   \n",
-      "35775     41.067812     -1.115498      5.244460        2.398182   \n",
-      "35776     44.437067     -1.649696      5.571137        2.216597   \n",
-      "35777     49.905775     -2.310264      5.704822        2.039080   \n",
-      "35778     56.022938     -1.711732      5.256625        1.866879   \n",
-      "35779     62.555996      0.004103      4.625874        1.700920   \n",
-      "35780     70.456588      1.713702      4.303344        1.541977   \n",
-      "35781     81.054439      2.065895      4.047587        1.390801   \n",
-      "35782     92.184465      1.270916      3.707292        1.247880   \n",
-      "35783    104.765489      1.514300      3.576649        1.113546   \n",
-      "35784    119.581506      3.978341      3.194742        0.988119   \n",
-      "35785    132.472847      3.795844      2.861497        0.871716   \n",
-      "35786    145.418404      1.646086      2.959307        0.764226   \n",
-      "35787    160.337861      0.432939      2.749379        0.665486   \n",
-      "35788    177.402426     -0.209576      2.612998        0.575501   \n",
-      "35789    195.041969     -0.861282      2.696016        0.494318   \n",
-      "35790    212.320546     -1.114349      2.758019        0.421626   \n",
-      "35791    228.793013     -0.863415      2.326827        0.356833   \n",
-      "35792    246.189296     -0.634309      2.243603        0.299111   \n",
-      "35793    263.425071     -1.819228      2.093881        0.247958   \n",
-      "35794    280.860590     -3.592176      2.110747        0.203960   \n",
-      "35795    297.809589     -4.454278      2.353716        0.166937   \n",
-      "35796    315.010408     -4.500887      2.404591        0.135685   \n",
-      "35797    332.498717     -4.396345      2.335329        0.109512   \n",
-      "35798    348.033813     -4.789404      2.403762        0.087829   \n",
-      "35799    361.018606     -4.804010      2.685094        0.069997   \n",
-      "35800    372.986843     -4.686667      2.874285        0.055521   \n",
-      "35801    382.284217     -4.386334      3.181815        0.044086   \n",
-      "35802    387.786453     -4.490548      3.481673        0.035110   \n",
-      "35803    392.672337     -4.608055      3.896414        0.027918   \n",
-      "35804    395.088527     -4.401269      4.568709        0.022180   \n",
-      "35805    393.089659     -3.241624      4.935893        0.017534   \n",
-      "35806    386.443174     -2.085917      5.193930        0.013634   \n",
-      "35807    373.694508     -1.114677      5.598026        0.010473   \n",
-      "35808    349.829370     -0.267838      5.907492        0.007935   \n",
-      "35809    296.701009     -0.898865      5.398812        0.005567   \n",
-      "35810    215.690514     -0.723917      5.764614        0.003112   \n",
-      "35811    136.934274      1.373653      7.718803        0.000928   \n",
-      "35812     83.174580      1.502976      8.264740        0.000000   \n",
+      "81883      5.922127      3.648140      6.516746        3.432393   \n",
+      "81884      5.807274      4.084032      6.529672        3.426942   \n",
+      "81885      7.383826      4.551435      6.601077        3.421196   \n",
+      "81886     17.209808      3.732659      6.463936        3.415080   \n",
+      "81887     36.211178      3.174500      6.282003        3.407861   \n",
+      "...             ...           ...           ...             ...   \n",
+      "81976     24.360646     -2.722852      5.860972        0.029735   \n",
+      "81977     21.495032     -2.835272      6.125162        0.012407   \n",
+      "81978     19.391299     -1.965292      6.173133        0.002054   \n",
+      "81979     18.010211     -2.131706      6.433176        0.000023   \n",
+      "81980     16.776791     -2.820830      6.807894        0.000000   \n",
       "\n",
       "       Penetration Depth (m)  Pore Pressure (kPa)  \n",
-      "35765               0.000000           -23.172145  \n",
-      "35766               0.001926           -23.314336  \n",
-      "35767               0.003822           -23.845804  \n",
-      "35768               0.005670           -23.506810  \n",
-      "35769               0.007451           -22.894091  \n",
-      "35770               0.009151           -23.320330  \n",
-      "35771               0.010765           -23.163820  \n",
-      "35772               0.012288           -23.348968  \n",
-      "35773               0.013719           -23.688295  \n",
-      "35774               0.015057           -23.671978  \n",
-      "35775               0.016302           -23.468848  \n",
-      "35776               0.017456           -23.578738  \n",
-      "35777               0.018520           -24.183465  \n",
-      "35778               0.019496           -24.732249  \n",
-      "35779               0.020388           -24.025623  \n",
-      "35780               0.021199           -23.392591  \n",
-      "35781               0.021932           -23.144173  \n",
-      "35782               0.022592           -22.967351  \n",
-      "35783               0.023182           -22.418900  \n",
-      "35784               0.023707           -21.796191  \n",
-      "35785               0.024172           -21.805515  \n",
-      "35786               0.024581           -22.315004  \n",
-      "35787               0.024939           -22.526126  \n",
-      "35788               0.025249           -22.099887  \n",
-      "35789               0.025516           -21.938382  \n",
-      "35790               0.025745           -22.367285  \n",
-      "35791               0.025940           -22.615370  \n",
-      "35792               0.026104           -22.409909  \n",
-      "35793               0.026241           -22.093227  \n",
-      "35794               0.026354           -21.636351  \n",
-      "35795               0.026446           -21.980007  \n",
-      "35796               0.026522           -22.691960  \n",
-      "35797               0.026583           -23.242408  \n",
-      "35798               0.026633           -22.763888  \n",
-      "35799               0.026672           -23.114869  \n",
-      "35800               0.026704           -22.920398  \n",
-      "35801               0.026728           -22.944707  \n",
-      "35802               0.026748           -22.798853  \n",
-      "35803               0.026764           -23.363620  \n",
-      "35804               0.026777           -23.913070  \n",
-      "35805               0.026786           -23.607043  \n",
-      "35806               0.026794           -22.963355  \n",
-      "35807               0.026800           -22.770548  \n",
-      "35808               0.026805           -22.778873  \n",
-      "35809               0.026808           -22.801184  \n",
-      "35810               0.026810           -22.785533  \n",
-      "35811               0.026811           -23.978337  \n",
-      "35812               0.026812           -24.407574  \n",
-      "Firmness factor =  50g (m/s^2)    406.0\n",
+      "81883               0.000000           -24.081567  \n",
+      "81884               0.001715           -23.854129  \n",
+      "81885               0.003427           -23.018966  \n",
+      "81886               0.005136           -23.138845  \n",
+      "81887               0.006842           -23.710606  \n",
+      "...                      ...                  ...  \n",
+      "81976               0.080886           -21.605715  \n",
+      "81977               0.080896           -21.733920  \n",
+      "81978               0.080900           -21.816171  \n",
+      "81979               0.080900           -21.985335  \n",
+      "81980               0.080900           -21.595725  \n",
+      "\n",
+      "[98 rows x 12 columns]\n",
+      "Firmness factor =  18g (m/s^2)    89.9\n",
       "dtype: float64\n",
-      "max penetration depth =  0.0268\n",
-      "phi = 41.6\n",
+      "max penetration depth =  0.0809\n",
+      "phi = 35.7\n",
       "Keep Drop? (y/n)\n",
-      "pentime=  24.0\n",
-      "peak index: 73033\n",
-      "start of penetration:  72974\n",
-      "penstart:  72974\n",
-      "penend:  73049\n",
-      "offset:  0.27070767252800676\n",
+      "pentime=  49.0\n",
+      "peak index: 99976\n",
+      "start of penetration:  99943\n",
+      "penstart:  99943\n",
+      "penend:  100196\n",
+      "offset:  0.6148584466837059\n",
       "[[0.00000000e+00 2.20000000e-01 1.52053084e-05]\n",
-      " [2.17380239e-01 3.39631112e-01 4.30251340e-05]\n",
-      " [4.34647188e-01 4.59199877e-01 9.12144485e-05]\n",
-      " [6.51661566e-01 5.78629643e-01 1.58419015e-04]\n",
-      " [8.68211267e-01 6.97803684e-01 2.44185662e-04]\n",
-      " [1.08394524e+00 8.16528803e-01 3.48117379e-04]\n",
-      " [1.29829105e+00 9.34489975e-01 4.69618649e-04]\n",
-      " [1.51034596e+00 1.05119039e+00 6.07692821e-04]\n",
-      " [1.71874288e+00 1.16587770e+00 7.60694215e-04]\n",
-      " [1.92172655e+00 1.27758594e+00 9.26211891e-04]\n",
-      " [2.11762360e+00 1.38539418e+00 1.10137932e-03]\n",
-      " [2.30530666e+00 1.48868201e+00 1.28341460e-03]\n",
-      " [2.48418931e+00 1.58712670e+00 1.46985857e-03]\n",
-      " [2.65396793e+00 1.68056116e+00 1.65849841e-03]\n",
-      " [2.81446840e+00 1.76888956e+00 1.84729270e-03]\n",
-      " [2.96560320e+00 1.85206375e+00 2.03436660e-03]\n",
-      " [3.10735963e+00 1.93007672e+00 2.21802677e-03]\n",
-      " [3.23979054e+00 2.00295758e+00 2.39677144e-03]\n",
-      " [3.36300859e+00 2.07076830e+00 2.56929849e-03]\n",
-      " [3.47719161e+00 2.13360677e+00 2.73452487e-03]\n",
-      " [3.58258203e+00 2.19160640e+00 2.89159525e-03]\n",
-      " [3.67945948e+00 2.24492108e+00 3.03984551e-03]\n",
-      " [3.76810979e+00 2.29370810e+00 3.17875188e-03]\n",
-      " [3.84883247e+00 2.33813231e+00 3.30793477e-03]\n",
-      " [3.92196708e+00 2.37838056e+00 3.42719495e-03]\n",
-      " [3.98790589e+00 2.41466874e+00 3.53653083e-03]\n",
-      " [4.04710092e+00 2.44724561e+00 3.63614644e-03]\n",
-      " [4.10004413e+00 2.47638190e+00 3.72641295e-03]\n",
-      " [4.14721854e+00 2.50234345e+00 3.80777594e-03]\n",
-      " [4.18908400e+00 2.52538331e+00 3.88071812e-03]\n",
-      " [4.22609221e+00 2.54575008e+00 3.94577358e-03]\n",
-      " [4.25867031e+00 2.56367883e+00 4.00348891e-03]\n",
-      " [4.28720397e+00 2.57938178e+00 4.05438324e-03]\n",
-      " [4.31209142e+00 2.59307813e+00 4.09903638e-03]\n",
-      " [4.33379152e+00 2.60502036e+00 4.13817026e-03]\n",
-      " [4.35276928e+00 2.61546442e+00 4.17254704e-03]\n",
-      " [4.36943175e+00 2.62463429e+00 4.20284705e-03]\n",
-      " [4.38412259e+00 2.63271912e+00 4.22965265e-03]\n",
-      " [4.39713601e+00 2.63988081e+00 4.25346868e-03]\n",
-      " [4.40872727e+00 2.64625984e+00 4.27473828e-03]\n",
-      " [4.41911148e+00 2.65197460e+00 4.29383803e-03]\n",
-      " [4.42846010e+00 2.65711943e+00 4.31106940e-03]\n",
-      " [4.43691195e+00 2.66177075e+00 4.32667756e-03]\n",
-      " [4.44458537e+00 2.66599367e+00 4.34087259e-03]\n",
-      " [4.45157788e+00 2.66984186e+00 4.35382823e-03]\n",
-      " [4.45796381e+00 2.67335624e+00 4.36567690e-03]\n",
-      " [4.46379612e+00 2.67656594e+00 4.37651240e-03]\n",
-      " [4.46910989e+00 2.67949028e+00 4.38639623e-03]\n",
-      " [4.47392681e+00 2.68214118e+00 4.39536554e-03]\n",
-      " [4.47826498e+00 2.68452861e+00 4.40345123e-03]\n",
-      " [4.48215024e+00 2.68666679e+00 4.41069907e-03]\n",
-      " [4.48561865e+00 2.68857556e+00 4.41717432e-03]\n",
-      " [4.48870866e+00 2.69027609e+00 4.42294712e-03]\n",
-      " [4.49145112e+00 2.69178535e+00 4.42807379e-03]\n",
-      " [4.49387267e+00 2.69311800e+00 4.43260301e-03]\n",
-      " [4.49600524e+00 2.69429163e+00 4.43659367e-03]\n",
-      " [4.49788179e+00 2.69532435e+00 4.44010671e-03]\n",
-      " [4.49952561e+00 2.69622900e+00 4.44318522e-03]\n",
-      " [4.50095118e+00 2.69701353e+00 4.44585584e-03]\n",
-      " [4.50217400e+00 2.69768649e+00 4.44814728e-03]\n",
-      " [4.50321252e+00 2.69825801e+00 4.45009382e-03]\n",
-      " [4.50408401e+00 2.69873762e+00 4.45172763e-03]\n",
-      " [4.50480545e+00 2.69913465e+00 4.45308035e-03]\n",
-      " [4.50539571e+00 2.69945949e+00 4.45418727e-03]\n",
-      " [4.50587460e+00 2.69972304e+00 4.45508542e-03]\n",
-      " [4.50625847e+00 2.69993430e+00 4.45580545e-03]\n",
-      " [4.50655921e+00 2.70009980e+00 4.45636957e-03]\n",
-      " [4.50678670e+00 2.70022500e+00 4.45679634e-03]\n",
-      " [4.50694983e+00 2.70031477e+00 4.45710236e-03]\n",
-      " [4.50706024e+00 2.70037554e+00 4.45730950e-03]\n",
-      " [4.50713325e+00 2.70041572e+00 4.45744648e-03]\n",
-      " [4.50717939e+00 2.70044111e+00 4.45753304e-03]\n",
-      " [4.50720378e+00 2.70045453e+00 4.45757879e-03]\n",
-      " [4.50721298e+00 2.70045959e+00 4.45759606e-03]\n",
-      " [4.50721482e+00 2.70046061e+00 4.45759951e-03]]\n",
-      "area_m =  [1.5205308443374599e-05, 4.3025134014306e-05, 9.121444845739177e-05, 0.00015841901549623375, 0.00024418566213332983, 0.0003481173785595892, 0.0004696186489181665, 0.0006076928205238911, 0.0007606942145151176, 0.0009262118906946412, 0.0011013793162972906, 0.001283414597951478, 0.001469858574811059, 0.0016584984128726703, 0.001847292699707761, 0.0020343665977640996, 0.00221802676804471, 0.0023967714425831292, 0.002569298486082098, 0.002734524873084273, 0.0028915952530324126, 0.003039845510761345, 0.003178751881649459, 0.003307934767215753, 0.003427194948210998, 0.0035365308266751016, 0.003636146439332463, 0.003726412951756276, 0.00380777594445981, 0.003880718120502634, 0.003945773583565342, 0.004003488910225052, 0.004054383242842081, 0.004099036377353045, 0.004138170257895203, 0.004172547041417436, 0.004202847047086457, 0.004229652647387886, 0.004253468677570248, 0.004274738275007313, 0.004293838031845638, 0.004311069404236163, 0.004326677557643555, 0.004340872589719558, 0.004353828230866646, 0.004365676897686149, 0.004376512398529277, 0.004386396234357447, 0.0043953655445311554, 0.004403451225221349, 0.004410699071220101, 0.004417174321667705, 0.004422947121052653, 0.0044280737888190095, 0.0044326030102096, 0.004436593674991454, 0.004440106708086461, 0.004443185216369592, 0.0044458558399920085, 0.004448147279161107, 0.004450093818641, 0.004451727625541856, 0.004453080353129781, 0.004454187265846432, 0.004455085423765746, 0.004455805452654531, 0.0044563695708023255, 0.004456796337080426, 0.004457102364794397, 0.004457309503291954, 0.004457446475080928, 0.004457533038846102, 0.004457578786565933, 0.0044575960551561725, 0.004457599509599413]  area_p =  [1.5205308443374599e-05, 3.623804888280076e-05, 6.624504477531156e-05, 0.00010518437488389436, 0.0001529735653213991, 0.00020945604115169689, 0.00027434633695482544, 0.000347146378037886, 0.0004270275215442898, 0.0005127788651514931, 0.0006029712314259423, 0.0006962316343882139, 0.0007913581319558866, 0.0008872755574003083, 0.000982995007056353, 0.0010776103042965145, 0.0011703048852389098, 0.001260356409635108, 0.0013471404929084286, 0.0014301402665940401, 0.0015089504981712428, 0.001583259226091014, 0.001652822324965696, 0.00171746556671941, 0.0017771028529771087, 0.0018317449011378219, 0.0018815033127952702, 0.001926571432158213, 0.0019671782168315423, 0.0020035698429862387, 0.002036017028827903, 0.0020647957868542934, 0.002090167689240902, 0.002112423917963134, 0.002131925960128136, 0.0021490548709982428, 0.0021641505538555587, 0.0021775038360439068, 0.002189366714940351, 0.0021999603036850653, 0.002209472458173056, 0.002218053531599302, 0.0022258257848386874, 0.002232893971770497, 0.0022393447039403404, 0.0022452439972469405, 0.0022506386269744187, 0.002255559270789872, 0.0022600244687458596, 0.0022640496456734125, 0.0022676576365621842, 0.0022708809490470214, 0.0022737545260110093, 0.0022763064229435084, 0.002278560890895709, 0.002280547256609479, 0.002282295856465653, 0.002283828155280121, 0.00228515741981607, 0.0022862979407582903, 0.0022872667871026956, 0.0022880799726966985, 0.0022887532547133382, 0.0022893041869246453, 0.0022897512161947717, 0.0022901095864390525, 0.0022903903567043707, 0.0022906027644649728, 0.0022907550786965543, 0.002290858174302612, 0.002290926346956307, 0.0022909694308592965, 0.002290992200084517, 0.0022910007948817716, 0.002291002514202098]\n",
-      "Acc_n:  (75,)\n",
-      "area:  75\n"
+      " [1.71210785e-01 3.14222624e-01 3.53244496e-05]\n",
+      " [3.42320472e-01 4.08389611e-01 6.83686896e-05]\n",
+      " [5.13318909e-01 5.02495373e-01 1.13398134e-04]\n",
+      " [6.84202593e-01 5.96537983e-01 1.70117559e-04]\n",
+      " [8.54973943e-01 6.90518773e-01 2.38408792e-04]\n",
+      " [1.02562640e+00 7.84434130e-01 3.18204450e-04]\n",
+      " [1.19614386e+00 8.78275195e-01 4.09450791e-04]\n",
+      " [1.36651078e+00 9.72033418e-01 5.12099348e-04]\n",
+      " [1.53672603e+00 1.06570817e+00 6.26112214e-04]\n",
+      " [1.70680305e+00 1.15930684e+00 7.51464929e-04]\n",
+      " [1.87675051e+00 1.25283422e+00 8.88134119e-04]\n",
+      " [2.04656530e+00 1.34628859e+00 1.03608896e-03]\n",
+      " [2.21624360e+00 1.43966784e+00 1.19529769e-03]\n",
+      " [2.38578748e+00 1.53297311e+00 1.36573403e-03]\n",
+      " [2.55520328e+00 1.62620790e+00 1.54737728e-03]\n",
+      " [2.72450191e+00 1.71937820e+00 1.74021394e-03]\n",
+      " [2.89369458e+00 1.81249020e+00 1.94423401e-03]\n",
+      " [3.06277981e+00 1.90554306e+00 2.15941396e-03]\n",
+      " [3.23173778e+00 1.99852589e+00 2.38570479e-03]\n",
+      " [3.40054107e+00 2.09142359e+00 2.62304136e-03]\n",
+      " [3.56916972e+00 2.18422519e+00 2.87136252e-03]\n",
+      " [3.73762011e+00 2.27692869e+00 3.13062756e-03]\n",
+      " [3.90589985e+00 2.36953826e+00 3.40081326e-03]\n",
+      " [4.07401377e+00 2.46205658e+00 3.68189374e-03]\n",
+      " [4.24196328e+00 2.55448443e+00 3.97383842e-03]\n",
+      " [4.40975076e+00 2.64682310e+00 4.27661890e-03]\n",
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+      " [4.74486191e+00 2.83124520e+00 4.91460215e-03]\n",
+      " [4.91220116e+00 2.92333719e+00 5.24977520e-03]\n",
+      " [5.07940138e+00 3.01535268e+00 5.59570861e-03]\n",
+      " [5.24645795e+00 3.10728911e+00 5.95236478e-03]\n",
+      " [5.41335987e+00 3.19914043e+00 6.31969071e-03]\n",
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+      " [5.91308610e+00 3.47415533e+00 7.48525575e-03]\n",
+      " [6.07933279e+00 3.56564606e+00 7.89486025e-03]\n",
+      " [6.24541100e+00 3.65704407e+00 8.31494166e-03]\n",
+      " [6.41130689e+00 3.74834174e+00 8.74543041e-03]\n",
+      " [6.57700698e+00 3.83953166e+00 9.18625441e-03]\n",
+      " [6.74250292e+00 3.93060923e+00 9.63735218e-03]\n",
+      " [6.90779056e+00 4.02157216e+00 1.00986720e-02]\n",
+      " [7.07287083e+00 4.11242096e+00 1.05701757e-02]\n",
+      " [7.23774991e+00 4.20315906e+00 1.10518411e-02]\n",
+      " [7.40243435e+00 4.29379003e+00 1.15436487e-02]\n",
+      " [7.56692945e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.73123733e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [7.89535148e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.05925698e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.22293954e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.38640072e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.54965940e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.71272928e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [8.87560583e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.03828348e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.20076356e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.36305024e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.52515324e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.68707887e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [9.84882405e+00 4.37500000e+00 1.19934265e-02]\n",
+      " [1.00103867e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.01717630e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.03329411e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.04939154e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.06546925e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.08152845e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.24098743e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.31994576e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.36705525e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.38271561e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.39835508e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.41397459e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.42957551e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.44515837e+01 4.37500000e+00 1.19934265e-02]\n",
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+      " [1.47626269e+01 4.37500000e+00 1.19934265e-02]\n",
+      " [1.49178002e+01 4.37500000e+00 1.19934265e-02]\n",
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0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713, 0.006013204688511713]\n",
+      "Acc_n:  (253,)\n",
+      "area:  253\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_1252\\3912607897.py:52: RuntimeWarning: divide by zero encountered in log10\n",
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_20604\\3912607897.py:52: RuntimeWarning: divide by zero encountered in log10\n",
       "  srcv = np.log10(vel/0.02) #Velocity portion of the strain rate correction.\n"
      ]
     },
@@ -1480,91 +1605,70 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Max penetration depth is:  0.0451\n",
-      "Pre-truncation d1          Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  200g (m/s^2)  \\\n",
-      "72974  72974.0   36.4875    2.185662     2.236439     2.654735      7.065008   \n",
-      "72975  72975.0   36.4880    2.636589     2.706223     2.949337      7.528753   \n",
-      "72976  72976.0   36.4885    3.040850     3.027515     3.243631      7.884064   \n",
-      "72977  72977.0   36.4890    3.445663     3.400245     3.611114      8.242400   \n",
-      "72978  72978.0   36.4895    3.782760     3.822312     3.634024      8.774988   \n",
-      "...        ...       ...         ...          ...          ...           ...   \n",
-      "73044  73044.0   36.5225   16.760150    17.930289    33.057434     23.268839   \n",
-      "73045  73045.0   36.5230   11.885535    11.930238    19.813432     16.440772   \n",
-      "73046  73046.0   36.5235    5.440912     5.505899    12.282795      9.954398   \n",
-      "73047  73047.0   36.5240    2.052864     2.097671     6.651384      6.838053   \n",
-      "73048  73048.0   36.5245   -1.503258    -1.470633     3.159833      3.888647   \n",
+      "Max penetration depth is:  0.3102\n",
+      "Pre-truncation d1            Count  Time (s)  2g (m/s^2)  18g (m/s^2)  50g (m/s^2)  \\\n",
+      "99943    99943.0   49.9720    5.973100     6.029702     6.138599   \n",
+      "99944    99944.0   49.9725    6.040446     6.105088     6.544829   \n",
+      "99945    99945.0   49.9730    7.829732     7.880327     7.337148   \n",
+      "99946    99946.0   49.9735   15.534168    16.424605    10.084507   \n",
+      "99947    99947.0   49.9740   15.702200    16.697700    15.275707   \n",
+      "...          ...       ...         ...          ...          ...   \n",
+      "100191  100191.0   50.0960   10.139070    10.189992    11.357629   \n",
+      "100192  100192.0   50.0965   10.783131    10.887375    10.930026   \n",
+      "100193  100193.0   50.0970   10.429720    10.514405    11.043807   \n",
+      "100194  100194.0   50.0975    9.912626    10.002726    10.970311   \n",
+      "100195  100195.0   50.0980    9.667967     9.774647    11.068409   \n",
       "\n",
-      "       250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  Velocity (m/s)  \\\n",
-      "72974      2.413765     -0.867026      5.487221        4.348168   \n",
-      "72975      2.582120     -0.602635      5.498281        4.347042   \n",
-      "72976      3.387517     -0.567514      5.315242        4.343636   \n",
-      "72977      3.515924     -1.169985      5.201327        4.336939   \n",
-      "72978      3.835515     -1.732739      5.335772        4.325049   \n",
-      "...             ...           ...           ...             ...   \n",
-      "73044     32.729210      1.235795      4.544654        0.001165   \n",
-      "73045     20.381459     -2.648836      3.828604        0.000681   \n",
-      "73046     12.998061     -3.885780      3.873465        0.000295   \n",
-      "73047      6.121871     -1.026219      5.248884        0.000074   \n",
-      "73048      1.986455      1.524640      6.099310        0.000000   \n",
+      "        200g (m/s^2)  250g (m/s^2)  X55g (m/s^2)  Y55g (m/s^2)  \\\n",
+      "99943      13.208428      5.837949      5.273054      5.436554   \n",
+      "99944      13.263149      6.713969      4.623975      5.517912   \n",
+      "99945      15.228832      7.779033      4.217130      5.788185   \n",
+      "99946      23.209831     10.908595      4.091746      5.920418   \n",
+      "99947      22.937989     16.368029      3.710340      5.744015   \n",
+      "...              ...           ...           ...           ...   \n",
+      "100191     17.792163      9.510387      1.904241      4.464816   \n",
+      "100192     18.427637      9.756500      2.264147      4.575898   \n",
+      "100193     17.917744     11.738247      2.279574      4.535668   \n",
+      "100194     17.412139     11.122607      1.923278      4.386707   \n",
+      "100195     17.154167      9.893467      2.058182      4.235948   \n",
       "\n",
-      "       Penetration Depth (m)  Pore Pressure (kPa)  \n",
-      "72974               0.000000           -25.131182  \n",
-      "72975               0.002174           -24.178137  \n",
-      "72976               0.004346           -23.467183  \n",
-      "72977               0.006517           -24.080901  \n",
-      "72978               0.008682           -24.187128  \n",
-      "...                      ...                  ...  \n",
-      "73044               0.045071           -23.606044  \n",
-      "73045               0.045072           -24.588393  \n",
-      "73046               0.045072           -25.253393  \n",
-      "73047               0.045072           -25.538108  \n",
-      "73048               0.045072           -26.403241  \n",
+      "        Velocity (m/s)  Penetration Depth (m)  Pore Pressure (kPa)  \n",
+      "99943         3.425180               0.000000           -23.849134  \n",
+      "99944         3.423251               0.001712           -23.688295  \n",
+      "99945         3.421137               0.003423           -23.691292  \n",
+      "99946         3.418801               0.005133           -24.063252  \n",
+      "99947         3.416546               0.006842           -24.146502  \n",
+      "...                ...                    ...                  ...  \n",
+      "100191        0.008827               0.310213           -19.578413  \n",
+      "100192        0.003562               0.310216           -19.592399  \n",
+      "100193        0.000500               0.310217           -19.889768  \n",
+      "100194        0.000019               0.310217           -19.439886  \n",
+      "100195        0.000000               0.310217           -19.301358  \n",
       "\n",
-      "[75 rows x 12 columns]\n",
-      "Firmness factor =  50g (m/s^2)    237.6\n",
+      "[253 rows x 12 columns]\n",
+      "Firmness factor =  18g (m/s^2)    27.1\n",
       "dtype: float64\n",
-      "max penetration depth =  0.0451\n",
-      "phi = 41.6\n",
       "Keep Drop? (y/n)\n",
-      "pentime=  37.5\n",
-      "  BlueDrop BD File Drop No. Soil Type Area Type Tip Type Drop Type  \\\n",
-      "0        3    009B        1         u         m        c         a   \n",
-      "0        3    009B        2         u         m        c         a   \n",
-      "\n",
-      "  Penetration Depth (cm)              Maximum Deceleration (m/s^2)  \\\n",
-      "0                   2.68  50g (m/s^2)    372.680992\n",
-      "dtype: float64   \n",
-      "0                   4.51  50g (m/s^2)    375.786916\n",
-      "dtype: float64   \n",
-      "\n",
-      "  Impact Velocity (m/s)  ... Max QSBC-Lower Bounds (mantle) (kPa)  \\\n",
-      "0                   3.9  ...                                    -   \n",
-      "0                   4.3  ...                                    -   \n",
-      "\n",
-      "  Max QSBC-Average (kPa) (mantle) Max Qdyn (projected) (kPa)  \\\n",
-      "0                         38322.5                     3188.8   \n",
-      "0                          5044.3                     1267.3   \n",
-      "\n",
-      "  Max QSBC-Upper Bounds (projected) (kPa)  \\\n",
-      "0                                       -   \n",
-      "0                                       -   \n",
-      "\n",
-      "  Max QSBC-Lower Bounds (projected) (kPa) Max QSBC-Average (kPa) (projected)  \\\n",
-      "0                                       -                            71700.2   \n",
-      "0                                       -                             9814.5   \n",
-      "\n",
-      "                 Firmness Factor (m-1) Penetration Time (ms)  \\\n",
-      "0  50g (m/s^2)    406.0\n",
-      "dtype: float64                  24.0   \n",
-      "0  50g (m/s^2)    237.6\n",
-      "dtype: float64                  37.5   \n",
-      "\n",
-      "  Relative Density (%) Friction Angle (deg.)  \n",
-      "0                 54.8                  41.6  \n",
-      "0                 55.3                  41.6  \n",
-      "\n",
-      "[2 rows x 23 columns]\n",
-      "Run Complete\n"
+      "pentime=  126.5\n",
+      "peak index: 114470\n"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code v8.ipynb Cell 30\u001b[0m in \u001b[0;36m4\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=41'>42</a>\u001b[0m     qdyn3_p \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=42'>43</a>\u001b[0m     output_table3 \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=43'>44</a>\u001b[0m     analyze(drop3, drop3g, acc3, acc3g, acc3Name, acc3Nameg, qdyn3_m, qdyn3_p, output_table3)\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=45'>46</a>\u001b[0m \u001b[39mif\u001b[39;00m n \u001b[39m==\u001b[39m \u001b[39m4\u001b[39m :\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=46'>47</a>\u001b[0m     drop4 \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code v8.ipynb Cell 30\u001b[0m in \u001b[0;36m1\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=14'>15</a>\u001b[0m acc_nNameg \u001b[39m=\u001b[39m accNameg\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=15'>16</a>\u001b[0m \u001b[39m#findchangepts() #automatically identifies the moment of penetration\u001b[39;00m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=16'>17</a>\u001b[0m peakpick() \u001b[39m#interactive graph for user to choose start of penetration\u001b[39;00m\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=17'>18</a>\u001b[0m endpick()\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=18'>19</a>\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mpenstart: \u001b[39m\u001b[39m\"\u001b[39m, penstart)\n",
+      "\u001b[1;32mc:\\Users\\elise\\Documents\\GitHub\\BD-Code-Development\\BD code v8.ipynb Cell 30\u001b[0m in \u001b[0;36m1\n\u001b[0;32m    <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=139'>140</a>\u001b[0m ax1\u001b[39m.\u001b[39mset(xlabel\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mTime\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=140'>141</a>\u001b[0m ax1\u001b[39m.\u001b[39mset_title(\u001b[39m'\u001b[39m\u001b[39mDouble-click start of drop #\u001b[39m\u001b[39m'\u001b[39m \u001b[39m+\u001b[39m \u001b[39mstr\u001b[39m(n))\n\u001b[1;32m--> <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=141'>142</a>\u001b[0m startendpt \u001b[39m=\u001b[39m plt\u001b[39m.\u001b[39;49mginput(\u001b[39m2\u001b[39;49m, \u001b[39m0\u001b[39;49m)\n\u001b[0;32m    <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=142'>143</a>\u001b[0m pentimes \u001b[39m=\u001b[39m []\n\u001b[0;32m    <a href='vscode-notebook-cell:/c%3A/Users/elise/Documents/GitHub/BD-Code-Development/BD%20code%20v8.ipynb#X41sZmlsZQ%3D%3D?line=143'>144</a>\u001b[0m \u001b[39mfor\u001b[39;00m t \u001b[39min\u001b[39;00m startendpt:\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\pyplot.py:2287\u001b[0m, in \u001b[0;36mginput\u001b[1;34m(n, timeout, show_clicks, mouse_add, mouse_pop, mouse_stop)\u001b[0m\n\u001b[0;32m   2282\u001b[0m \u001b[39m@_copy_docstring_and_deprecators\u001b[39m(Figure\u001b[39m.\u001b[39mginput)\n\u001b[0;32m   2283\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mginput\u001b[39m(\n\u001b[0;32m   2284\u001b[0m         n\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m, timeout\u001b[39m=\u001b[39m\u001b[39m30\u001b[39m, show_clicks\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m,\n\u001b[0;32m   2285\u001b[0m         mouse_add\u001b[39m=\u001b[39mMouseButton\u001b[39m.\u001b[39mLEFT, mouse_pop\u001b[39m=\u001b[39mMouseButton\u001b[39m.\u001b[39mRIGHT,\n\u001b[0;32m   2286\u001b[0m         mouse_stop\u001b[39m=\u001b[39mMouseButton\u001b[39m.\u001b[39mMIDDLE):\n\u001b[1;32m-> 2287\u001b[0m     \u001b[39mreturn\u001b[39;00m gcf()\u001b[39m.\u001b[39;49mginput(\n\u001b[0;32m   2288\u001b[0m         n\u001b[39m=\u001b[39;49mn, timeout\u001b[39m=\u001b[39;49mtimeout, show_clicks\u001b[39m=\u001b[39;49mshow_clicks,\n\u001b[0;32m   2289\u001b[0m         mouse_add\u001b[39m=\u001b[39;49mmouse_add, mouse_pop\u001b[39m=\u001b[39;49mmouse_pop,\n\u001b[0;32m   2290\u001b[0m         mouse_stop\u001b[39m=\u001b[39;49mmouse_stop)\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\figure.py:3146\u001b[0m, in \u001b[0;36mFigure.ginput\u001b[1;34m(self, n, timeout, show_clicks, mouse_add, mouse_pop, mouse_stop)\u001b[0m\n\u001b[0;32m   3143\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(clicks) \u001b[39m==\u001b[39m n \u001b[39mand\u001b[39;00m n \u001b[39m>\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[0;32m   3144\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcanvas\u001b[39m.\u001b[39mstop_event_loop()\n\u001b[1;32m-> 3146\u001b[0m _blocking_input\u001b[39m.\u001b[39;49mblocking_input_loop(\n\u001b[0;32m   3147\u001b[0m     \u001b[39mself\u001b[39;49m, [\u001b[39m\"\u001b[39;49m\u001b[39mbutton_press_event\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mkey_press_event\u001b[39;49m\u001b[39m\"\u001b[39;49m], timeout, handler)\n\u001b[0;32m   3149\u001b[0m \u001b[39m# Cleanup.\u001b[39;00m\n\u001b[0;32m   3150\u001b[0m \u001b[39mfor\u001b[39;00m mark \u001b[39min\u001b[39;00m marks:\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\_blocking_input.py:26\u001b[0m, in \u001b[0;36mblocking_input_loop\u001b[1;34m(figure, event_names, timeout, handler)\u001b[0m\n\u001b[0;32m     24\u001b[0m cids \u001b[39m=\u001b[39m [figure\u001b[39m.\u001b[39mcanvas\u001b[39m.\u001b[39mmpl_connect(name, handler) \u001b[39mfor\u001b[39;00m name \u001b[39min\u001b[39;00m event_names]\n\u001b[0;32m     25\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m---> 26\u001b[0m     figure\u001b[39m.\u001b[39;49mcanvas\u001b[39m.\u001b[39;49mstart_event_loop(timeout)  \u001b[39m# Start event loop.\u001b[39;00m\n\u001b[0;32m     27\u001b[0m \u001b[39mfinally\u001b[39;00m:  \u001b[39m# Run even on exception like ctrl-c.\u001b[39;00m\n\u001b[0;32m     28\u001b[0m     \u001b[39m# Disconnect the callbacks.\u001b[39;00m\n\u001b[0;32m     29\u001b[0m     \u001b[39mfor\u001b[39;00m cid \u001b[39min\u001b[39;00m cids:\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\backends\\_backend_tk.py:385\u001b[0m, in \u001b[0;36mFigureCanvasTk.start_event_loop\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m    382\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m    383\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_event_loop_id \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_tkcanvas\u001b[39m.\u001b[39mafter_idle(\n\u001b[0;32m    384\u001b[0m             \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstop_event_loop)\n\u001b[1;32m--> 385\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_tkcanvas\u001b[39m.\u001b[39;49mmainloop()\n",
+      "File \u001b[1;32mc:\\Users\\elise\\AppData\\Local\\Programs\\Python\\Python310\\lib\\tkinter\\__init__.py:1458\u001b[0m, in \u001b[0;36mMisc.mainloop\u001b[1;34m(self, n)\u001b[0m\n\u001b[0;32m   1456\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mmainloop\u001b[39m(\u001b[39mself\u001b[39m, n\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m):\n\u001b[0;32m   1457\u001b[0m     \u001b[39m\"\"\"Call the mainloop of Tk.\"\"\"\u001b[39;00m\n\u001b[1;32m-> 1458\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtk\u001b[39m.\u001b[39;49mmainloop(n)\n",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
      ]
     }
    ],
diff --git a/Bootleg Dropview.py b/Bootleg Dropview.py
index 3d9b032..80b9ad5 100644
--- a/Bootleg Dropview.py	
+++ b/Bootleg Dropview.py	
@@ -10,14 +10,15 @@
 
 # SETUP VARIABLES - USER INPUTS
 BD = 3 #Bluedrop file is from 
-fileNum = '01BB' # write the bin file number for the earliest drop in the folder (do not include 'bLog' or '.bin')
+fileNum = '00A0'
+# write the bin file number for the earliest drop in the folder (do not include 'bLog' or '.bin')
 numFiles = 20 #write the number of bin files in the folder of interest (if only looking at 1 drop, write 2)
 offset = 0 # this value is subtracted from the accelerometer readings
 # paste the filepath to the folder where the BD data is stored
-binFilepath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Subtidal/CRAB Survey 3.16.23/BlueDrop/BD3 3.16.23 - All Files")
+binFilepath = Path("C:/Users/elise/Desktop/Sequim_2021/")
 #paste the filepath that you want the files containing drops copied to 
-outputPath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Subtidal/CRAB Survey 3.16.23/BlueDrop/BD3 3.16.23 - Drops Only")
-plotPath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Subtidal/CRAB Survey 3.16.23/BlueDrop/BD3 3.16.23 - Drops Only/Dec-Time Plots")
+outputPath = Path("C:/Users/elise/Desktop/Sequim_2021/Drops Only")
+plotPath = Path("C:/Users/elise/Desktop/Sequim_2021/Drops Only/Dec-Time Plots")
 
 def overviewplot(): #Plot showing all accelerometers and pore pressure readings
     fig, (ax1) = plt.subplots(1)
@@ -180,15 +181,15 @@ def newNamefun(): #find the next sequential bin name a=existing last variable, b
     df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns
 
     # APPLY CALIBRATION FACTORS
-    if BD == 3:  # calibration factors from July 2019
-        g2g = (df['g2g']-38285.6)/1615800.9 - offset# accelerometers are in g
-        g18g = (df['g18g']+13738)/163516.8 - offset
-        g50g = (df['g50g']-238520.6)/63666 - offset
+    if BD == 3:  # calibration factors from March 2023
+        g2g = (df['g2g']-33570.1)/1614577.9 - offset# accelerometers are in g
+        g18g = (df['g18g']+13495)/163387.2 - offset
+        g50g = (df['g50g']-238817.4)/63779.5 - offset
         ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa
-        g200g = ((df['g200g'] +12142.6)/27751.9) - offset
-        gX55g = (df['gX55g']-90237)/65351.5  
-        gY55g = (df['gY55g']-57464.2)/65545.
-        g250g = (df['g250g']-40420.3)/13636.9 - offset
+        g200g = ((df['g200g'] -262332.4/38888.7)) - offset
+        gX55g = (df['gX55g']-70406)/59754.3  
+        gY55g = (df['gY55g']-69421.1)/141871.5
+        g250g = (df['g250g']-39077.4)/13746.9 - offset
 
     if BD == 2: # calibration factors from Aug 26, 2021
     
diff --git a/Bootleg_Dropview_9_24_23.py b/Bootleg_Dropview_9_24_23.py
new file mode 100644
index 0000000..80b9ad5
--- /dev/null
+++ b/Bootleg_Dropview_9_24_23.py
@@ -0,0 +1,243 @@
+import numpy
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from pathlib import Path
+import math
+from math import pi
+from math import sqrt
+import shutil
+
+# SETUP VARIABLES - USER INPUTS
+BD = 3 #Bluedrop file is from 
+fileNum = '00A0'
+# write the bin file number for the earliest drop in the folder (do not include 'bLog' or '.bin')
+numFiles = 20 #write the number of bin files in the folder of interest (if only looking at 1 drop, write 2)
+offset = 0 # this value is subtracted from the accelerometer readings
+# paste the filepath to the folder where the BD data is stored
+binFilepath = Path("C:/Users/elise/Desktop/Sequim_2021/")
+#paste the filepath that you want the files containing drops copied to 
+outputPath = Path("C:/Users/elise/Desktop/Sequim_2021/Drops Only")
+plotPath = Path("C:/Users/elise/Desktop/Sequim_2021/Drops Only/Dec-Time Plots")
+
+def overviewplot(): #Plot showing all accelerometers and pore pressure readings
+    fig, (ax1) = plt.subplots(1)
+    fig.set_size_inches(4, 4)
+    ax1.plot(time, g250g, label="250g")
+    ax1.plot(time, g50g, label="50g")
+    ax1.plot(time, g18g, label="18g")
+    ax1.plot(time, g2g, label="2g")
+    ax1.legend(loc = "upper right")
+    ax1.set(ylabel="Deceleration (g)")
+    ax1.set_title("BD file "+ newName)
+    ax1.grid()
+
+    plt.draw()
+    print("Is there a drop? y/n")
+    plt.waitforbuttonpress(2)
+    drop_input=input()
+
+    if drop_input=='y':   
+        origFile = 'bLog'+newName+".bin"
+        origFilePath = binFilepath / origFile
+        newFilePath = outputPath / origFile
+        plotFilePath = plotPath / newName
+        shutil.copyfile(origFilePath, newFilePath)
+        plt.savefig(plotPath / newName)
+
+    plt.close(fig)
+
+def newNamefun(): #find the next sequential bin name a=existing last variable, b=new last variable
+    global newName
+    a = name[3]
+    c = name[2]
+    e = name[1]
+    g = name[0]
+    if a == "A":
+        b = "B"
+    elif a == "B":
+        b = "C"
+    elif a == "C":
+        b = "D"
+    elif a == "D":
+        b = "E"
+    elif a == "E":
+            b = "F"
+    elif a == "F":
+        b = "0"
+        if c == "A":
+            d = "B"
+        elif c == "B":
+            d = "C"
+        elif c == "C":
+            d = "D"
+        elif c == "D":
+            d = "E"
+        elif c == "E":
+            d = "F"
+        elif c == "F":
+            d = "0"
+            if e == "A":
+                f = "B"
+            elif e == "B":
+                f = "C"
+            elif e == "C":
+                f = "D"
+            elif e == "D":
+                f = "E"
+            elif e == "E":
+                f = "F"
+            elif e == "F":
+                f = "0"
+                if g == "A":
+                    h = "B"
+                elif g == "B":
+                    h = "C"
+                elif g == "C":
+                    h = "D"
+                elif g == "D":
+                    h = "E"
+                elif g == "E":
+                    h = "F"
+                elif g == "F":
+                    h = "0"
+                    f = "0"
+                    d = "0"
+                    b = "0"
+                elif g == "9":
+                    h = "A"
+                else: #a <=8:
+                    g = int(name[0]) #the only other options are numbers
+                    h = g + 1
+                    h = str(b)    
+
+            elif e == "9":
+                f = "A"
+            else: #a <=8:
+                e = int(name[1]) #the only other options are numbers
+                f = e + 1
+                f = str(f)    
+
+
+        elif c == "9":
+            d = "A"
+        else: #a <=8:
+            c = int(name[2]) #the only other options are numbers
+            d = c + 1
+            d = str(d)    
+
+
+    elif a == "9":
+        b = "A"
+    else: #a <=8:
+        a = int(name[3]) #the only other options are numbers
+        b = a + 1
+        b = str(b)    
+
+
+    newNameList = name
+    newNameList[3] = b #b always will change
+    if a == "F":
+        newNameList[2] = d
+        if c == "F":
+            newNameList[1] = f
+            if e == "F":
+                newNameList[0] = h
+                    
+    else:
+        newNameList[2] = c
+        newNameList[1] = e
+        newNameList[0] = g
+
+    print(newNameList)
+    newName = ""
+    newName = newName.join(newNameList)
+    print(newName)
+
+newName = fileNum #for the first drop, select the earliest drop defined earlier
+
+for i in range(1, numFiles):
+
+    # READ BD DATA IN
+    data_array = []  # creates an empty array for us to fill with bd data
+    fileName = 'bLog'+newName+".bin"
+    # print(fileName)
+    newPath = binFilepath / fileName
+    #print(newPath)
+    file = open(newPath, 'rb')  # read file
+    element = file.read(3)  # create a byte list with each element having 3 bytes
+
+    while element:
+        # Convert to signed integer before adding to data array
+        iVAl = int.from_bytes(element, byteorder='big', signed=True)
+        data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame
+        element = file.read(3)
+
+    np_array = np.array(data_array)  # create numpy array from the list
+    np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols
+
+
+    df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data
+    df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns
+
+    # APPLY CALIBRATION FACTORS
+    if BD == 3:  # calibration factors from March 2023
+        g2g = (df['g2g']-33570.1)/1614577.9 - offset# accelerometers are in g
+        g18g = (df['g18g']+13495)/163387.2 - offset
+        g50g = (df['g50g']-238817.4)/63779.5 - offset
+        ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa
+        g200g = ((df['g200g'] -262332.4/38888.7)) - offset
+        gX55g = (df['gX55g']-70406)/59754.3  
+        gY55g = (df['gY55g']-69421.1)/141871.5
+        g250g = (df['g250g']-39077.4)/13746.9 - offset
+
+    if BD == 2: # calibration factors from Aug 26, 2021
+    
+        g2g = (df['g2g']+37242.2)/1639250.2 - offset# accelerometers are in g
+        g18g = (df['g18g']-26867.0)/160460.5 - offset
+        g50g = (df['g50g']-213923.3)/64080.7- offset
+        ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa
+        g200g = (df['g200g']-171448.6)/30334.2 - offset
+        gX55g = (df['gX55g']-54242.6)/64767.7 
+        gY55g = (df['gY55g']-40574.2)/66343.1 
+        g250g = (df['g250g']-40614.9)/13654.6 - offset
+
+    if BD == 1: # calibration factors from July 2020
+        g2g = (df['g2g']-42590.9)/1626361.1 - offset # accelerometers are in g
+        g18g = (df['g18g']-44492.9)/161125.5 - offset
+        g50g = (df['g50g']-171656.1)/64020.3 - offset
+        ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa
+        g200g = (df['g200g'] -723404.8)/32209.7  - offset
+        gX55g = (df['gX55g'] -54881.1)/64858.6 
+        gY55g = (df['gY55g']-28735.5)/63839.9 
+        g250g = (df['g250g']+13299.7)/13697.1 - offset
+
+    time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s
+    count = df["Count"]-df['Count'].iloc[0]
+
+    # make a new dataframe of the calibrated values in units of g
+    dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])
+    dfCalg = dfCalg.T
+    dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns
+    #print(dfCalg)
+
+    #make a new dataframe of the calibrated values in units of m/s^2
+    dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])
+    dfCal = dfCal.T
+    dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns
+    dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665
+    dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665
+    dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665
+    dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665
+    dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665
+    dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665
+    dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665
+    #print(dfCal)
+
+    overviewplot()
+
+    name = [*newName]
+
+    newNamefun()
+
+print("all files checked")
\ No newline at end of file
diff --git a/ML Identification.ipynb b/ML Identification.ipynb
new file mode 100644
index 0000000..b6c2fb5
--- /dev/null
+++ b/ML Identification.ipynb	
@@ -0,0 +1,473 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import Dependencies"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import stumpy\n",
+    "import numpy as np\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as dates\n",
+    "from matplotlib.patches import Rectangle\n",
+    "import datetime as dt\n",
+    "from scipy.signal import find_peaks\n",
+    "from pathlib import Path\n",
+    "import stumpy\n",
+    "\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "User Inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "BD = 2 #Bluedrop file is from \n",
+    "fileNum = '0021' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "soiltype = \"s\" #s = sand, c=clay, m=mixed, u=unknown\n",
+    "atype = 'm'  # m = mantle area (best for sands), p = projected area (best for clays)\n",
+    "tiptype = 'c'  # c = cone, p = parabolic, b = blunt\n",
+    "#offset = 1 # this value is subtracted from the accelerometer readings\n",
+    "droptype = 'a' #w = water, #a = air\n",
+    "sign = \"uk\" #enter an effective unit weight value in kg/m^3 or \"uk\" if unknown \n",
+    "# paste the filepath to the folder where the BD data is stored\n",
+    "binFilepath = Path(\"H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/07March23/BD2 3.7.23 - Drops Only\")\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set the penetrometer information and bring in Timeseries Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def masslength(tiptype): #sets the mass and length of the pentrometer based on the tip\n",
+    "    global mass\n",
+    "    global length\n",
+    "    if tiptype == 'c':\n",
+    "        mass = 7.71 #kg\n",
+    "        length = 8.48-0.93 #originally 7.87, 7.57 for perfect 60 deg, 8.48 measured - .93 measured 90 deg\n",
+    "    elif tiptype == 'p':\n",
+    "        mass = 9.15\n",
+    "        length = 8.26\n",
+    "    elif tiptype == 'b':\n",
+    "        mass = 10.30\n",
+    "        length = 8.57\n",
+    "\n",
+    "masslength(tiptype)\n",
+    "\n",
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Calibrate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "# make a new dataframe of the calibrated values in units of g\n",
+    "dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCalg = dfCalg.T\n",
+    "dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns\n",
+    "#print(dfCalg)\n",
+    "\n",
+    "#make a new dataframe of the calibrated values in units of m/s^2\n",
+    "dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])\n",
+    "dfCal = dfCal.T\n",
+    "dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns\n",
+    "dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665\n",
+    "dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665\n",
+    "dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665\n",
+    "dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665\n",
+    "dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665\n",
+    "dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665\n",
+    "dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665\n",
+    "#print(dfCal)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Locate all drops, zoom into first one"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Locate the drops\n",
+    "x = np.array(g250g)  # what accelerometer to get the peaks from - use 250 because it will never be maxed out\n",
+    "max250 = max(g250g)\n",
+    "\n",
+    "peaks, _ = find_peaks(x, height = 2, distance=1000, prominence=3)  # finds the largest peaks more than 2g spaced at least 10000 counts apart\n",
+    "\n",
+    "peaksArray = np.array(peaks)  # prints a list of the count where the peaks occur\n",
+    "#peaksArray = filter(filterpeak, peaksArray)\n",
+    "\n",
+    "#print(peaksArray)\n",
+    "q = (peaksArray.shape) #gives number of peaks\n",
+    "nDrops = int(q[0]) #number of drops in the file\n",
+    "#print(nDrops)\n",
+    "\n",
+    "# For each drop, find the start and end points and integrate to solve for velocity and acceleration\n",
+    "#peakplot()\n",
+    "\n",
+    "def peakplot(): # Plot showing peak deceleration\n",
+    "    peakplot = plt.plot(x)\n",
+    "    peakplot = plt.plot(peaks, x[peaks], \"x\")\n",
+    "    plt.show()\n",
+    "\n",
+    "peakplot()\n",
+    "#overviewplot()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Zoom into drop of interest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peak index: 28061\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = 1 #what drop do you want to analyze? USER INPUT\n",
+    "a = a-1\n",
+    "\n",
+    "peak = int(peaksArray[a])  # count at the ath drop\n",
+    "print(\"peak index:\" , peak)\n",
+    "\n",
+    "def dropstartend(peak): #after locating the peaks, this function chops the minute long file into a smaller segment immediately before and after the peak\n",
+    "    global dropstart\n",
+    "    global dropend\n",
+    "    if peak <= 1500:\n",
+    "        dropstart = 1\n",
+    "        dropend = peak + 500\n",
+    "    elif peak > 119500:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = 120000\n",
+    "    else:\n",
+    "        dropstart = peak - 1500\n",
+    "        dropend = peak + 500\n",
+    "\n",
+    "def accPick(dg, d): #this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "    maxAcc = dg[\"250g (g)\"].max()\n",
+    "    global acc\n",
+    "    global accName\n",
+    "    global accNameg\n",
+    "    global accg\n",
+    "    if maxAcc < 5: #- offset:\n",
+    "        if dg[\"2g (g)\"].max() < 1.8: #offset:  # does an extra check for the 2g because of noise\n",
+    "            acc = dfCal[\"2g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"2g (g)\"]\n",
+    "            accName = \"2g (m/s^2)\"\n",
+    "            accNameg = \"2g (g)\"\n",
+    "        else:\n",
+    "            acc = dfCal[\"18g (m/s^2)\"]\n",
+    "            accg = dfCalg[\"18g (g)\"]\n",
+    "            accName = \"18g (m/s^2)\"\n",
+    "            accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 18: #- offset\n",
+    "        acc = dfCal[\"18g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"18g (g)\"]\n",
+    "        accName = \"18g (m/s^2)\"\n",
+    "        accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 50: #- offset:\n",
+    "        acc = dfCal[\"50g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"50g (m/s^2)\"\n",
+    "        accNameg = \"50g (g)\"\n",
+    "    else:\n",
+    "        acc = dfCal[\"250g (m/s^2)\"]\n",
+    "        accg = dfCalg[\"50g (g)\"]\n",
+    "        accName = \"250g (m/s^2)\"\n",
+    "        accNameg = \"250g (g)\"\n",
+    "                \n",
+    "dropstartend(peak) #zooms in the drop file to only consider 500 counts before and 1500 counts after the peak deceleration\n",
+    "#print(dropstart, dropend)\n",
+    "\n",
+    "drop1 = dfCal[dropstart:dropend]  # start and end points of the drop in m/s^2\n",
+    "drop1g = dfCalg[dropstart:dropend]  # start and end points of the drop in g\n",
+    "drop1 = pd.DataFrame(drop1)  # makes dataframe including all data within the start and end points of the drop\n",
+    "drop1g = pd.DataFrame(drop1g)\n",
+    "dg = drop1g \n",
+    "d = drop1\n",
+    "accPick(dg, d)  # chooses what accelerometer to use\n",
+    "acc1 = acc\n",
+    "acc1g = accg\n",
+    "acc1Name = accName\n",
+    "acc1Nameg = accNameg\n",
+    "#findchangepts() #automatically identifies the moment of penetration\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "matrix profile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The motif is located at index 1653\n",
+      "The nearest neighbor is located at index 1680\n",
+      "The discord is located at index 1337\n",
+      "The nearest neighbor subsequence to this discord is 12.079028791387648 units away\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#create matrix profile\n",
+    "m = 100\n",
+    "mp = stumpy.stump(drop1[acc1Name], m)\n",
+    "\n",
+    "#find motif, discord and nearest neighbors\n",
+    "motif_idx = np.argsort(mp[:, 0])[0]\n",
+    "print(f\"The motif is located at index {motif_idx}\")\n",
+    "nearest_neighbor_idx = mp[motif_idx, 1]\n",
+    "print(f\"The nearest neighbor is located at index {nearest_neighbor_idx}\")\n",
+    "\n",
+    "discord_idx = np.argsort(mp[:, 0])[-1]\n",
+    "print(f\"The discord is located at index {discord_idx}\")\n",
+    "nearest_neighbor_distance = mp[discord_idx, 0]\n",
+    "print(f\"The nearest neighbor subsequence to this discord is {nearest_neighbor_distance} units away\")\n",
+    "\n",
+    "#plot time series and MP\n",
+    "fig, axs = plt.subplots(2, sharex=True, gridspec_kw={'hspace': 0})\n",
+    "plt.suptitle('Discord (Anomaly/Novelty) Discovery', fontsize='30')\n",
+    "\n",
+    "axs[0].plot(drop1[acc1Name].values)\n",
+    "axs[0].set_ylabel('Deceleration (m/s2)', fontsize='10')\n",
+    "rect = Rectangle((discord_idx, 0), m, 40, facecolor='lightgrey')\n",
+    "axs[0].add_patch(rect)\n",
+    "axs[1].set_xlabel('Time', fontsize ='10')\n",
+    "axs[1].set_ylabel('Matrix Profile', fontsize='10')\n",
+    "axs[1].axvline(x=discord_idx, linestyle=\"dashed\")\n",
+    "axs[1].plot(mp[:, 0])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Find optimal window size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1130, 1112, 1055, 934, 1337, 1314, 883, 864, 850, 831]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "m_test_sizes = [20, 40, 60, 80, 100, 120, 140, 160, 180, 200]\n",
+    "discord_test_idx = []\n",
+    "for i in range(0,len(m_test_sizes)):\n",
+    "    m = m_test_sizes[i]\n",
+    "    mp = stumpy.stump(drop1[acc1Name], m)\n",
+    "    discord_idx = np.argsort(mp[:, 0])[-1]\n",
+    "    discord_test_idx.append(discord_idx)\n",
+    "\n",
+    "print(discord_test_idx)\n",
+    "\n",
+    "discord_test_idx = np.array(discord_test_idx)\n",
+    "\n",
+    "peak_idx = 28061\n",
+    "start_file = 28061 - 1500\n",
+    "true_index = 28024 - start_file\n",
+    "\n",
+    "error = discord_test_idx - true_index\n",
+    "\n",
+    "#plot error vs m\n",
+    "fig, axs = plt.subplots(2) #sharex=True, gridspec_kw={'hspace': 0})\n",
+    "plt.suptitle('Window Size', fontsize='30')\n",
+    "\n",
+    "axs[0].plot(m_test_sizes, discord_test_idx)\n",
+    "axs[0].set_ylabel('Test index', fontsize='10')\n",
+    "axs[1].plot(m_test_sizes, error)\n",
+    "axs[1].set_xlabel('Window Size', fontsize ='10')\n",
+    "axs[1].set_ylabel('Error', fontsize='10')\n",
+    "axs[1].set_ylim(0,-800)\n",
+    "\n",
+    "plt.show()\n",
+    "\n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/ML_Dataset_Creation-Identification-Clays.ipynb b/ML_Dataset_Creation-Identification-Clays.ipynb
new file mode 100644
index 0000000..51d730c
--- /dev/null
+++ b/ML_Dataset_Creation-Identification-Clays.ipynb
@@ -0,0 +1,1147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Training & Validation Dataset Creation"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This code is utilized to create the training and validation data for a ML algorithm to identify portable free-fall penetrometer (PFFP) deployments. The user manually selects 3 distinct points:\n",
+    "\n",
+    "1. **Moment of release into air.** This is shown as the moment where the measured deceleration begins to decrease\n",
+    "2. **Moment of impact with water.** This is shown where the pore pressure readings begin to increase.\n",
+    "3. **Moment of seabed impact.** This is the moment preceding a sharp increase in measured deceleration\n",
+    "\n",
+    "The fourth point of interest, **End of penetration.**, is automatically found. This is generally identified as the moment where the deceleration crosses 1g following the peak deceleration. \n",
+    "\n",
+    "A visualization of these distinct regions within the PFFP deceleration profile is shown below (Stark et al 2016; https://cdnsciencepub.com/doi/10.1139/cgj-2016-0087):\n",
+    "![image.png](attachment:image.png)\n",
+    "\n",
+    "**Note:** *this code requires pop-ups of interactive images. Therefore, it will not run properly within the DesignSafe Jupyter Notebooks. It is recommended that this code be used in a local version of Juputer, such as that in Visual Studio Code.*\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "#%matplotlib ipympl\n",
+    "matplotlib.use('TkAgg') #the default is to have an image pop-out. Precede the image creation with the line above to embed within Jupyter\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pathlib import Path\n",
+    "\n",
+    "from scipy.signal import lfilter"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "User Inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# SETUP VARIABLES - USER INPUTS\n",
+    "dataset = \"Sequim_2021\"\n",
+    "BD = 3 #Bluedrop file is from \n",
+    "fileNum = '01DC' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "# paste the filepath to the folder where the BD data is stored\n",
+    "binFilepath = Path(\"C:/Users/elise/Desktop/Sequim_2021/Drops Only\")\n",
+    "#paste the filepath to an excel file that the analysis results will be printed in\n",
+    "outputPath = Path(\"C:/Users/elise/Desktop/ML Training Data/training_validation_master.xlsx\") #  Path to pre-existing Excel File"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Bring in and visualize data within the BlueDrop File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a48b252c42204c208a1d4809319b6c35",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=1400.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "#Create uncalibrated dataframe from raw penetrometer readings\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "#calibrate the dataframe\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  \n",
+    "    # calibration factors from March 2023\n",
+    "    '''g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 #converts to atm\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset'''\n",
+    "    # calibration factors for July 2019- March 2023:\n",
+    "    g2g=(df['g2g']-38285.6)/1615800.9 #accelerometers are in g\n",
+    "    g18g=(df['g18g']+13738)/163516.8\n",
+    "    g50g=(df['g50g']-238520.6)/63666\n",
+    "    ppm=((df['ppm']-139040.1)/20705) * 6.89475729 #converts to atm\n",
+    "    g200g=(df['g200g']+12142.6)/27751.9\n",
+    "    gX55g=(df['gX55g']-90237)/65351.5\n",
+    "    gY55g=(df['gX55g']-57464.2)/65545.5\n",
+    "    g250g=(df['g250g']-40420.3)/13636.9\n",
+    "\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "def overviewplot(): #Plot showing all accelerometers and pore pressure readings\n",
+    "    %matplotlib ipympl\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(14, 7)\n",
+    "    #plt.tight_layout()\n",
+    "    ax1.plot(time, g250g, label=\"250g\")\n",
+    "    ax1.plot(time, g50g, label=\"50g\")\n",
+    "    ax1.plot(time, g18g, label=\"18g\")\n",
+    "    ax1.plot(time, g2g, label=\"2g\")\n",
+    "    ax1.legend(loc = \"upper right\")\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(time, ppm, label=\"Pore Pressure\")\n",
+    "    ax2.set(ylabel=\"Pore Pressure (kPa)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(time, gX55g, label=\"X 55g\")\n",
+    "    ax3.plot(time, gY55g, label=\"Y 55g\")\n",
+    "    ax3.legend(loc = \"upper right\")\n",
+    "    ax3.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax3.set(xlabel=\"Time (s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" Overview.png\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "overviewplot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select which accelerometer should be used to pick the index points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max Acceleration:  2.919776488791441\n",
+      "Accelerometer used:  18g (g)\n"
+     ]
+    }
+   ],
+   "source": [
+    "def accPick(): #this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "    maxAcc = g250g.max()\n",
+    "    print(\"Max Acceleration: \", maxAcc)\n",
+    "    global accNameg\n",
+    "    global accg\n",
+    "    if maxAcc < 5:\n",
+    "        if g2g.max() < 1.8: #offset:  # does an extra check for the 2g because of noise\n",
+    "            accg = g2g\n",
+    "            accNameg = \"2g (g)\"\n",
+    "        else:\n",
+    "            accg = g18g\n",
+    "            accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 18:\n",
+    "        accg = g18g\n",
+    "        accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 50:\n",
+    "        accg = g50g\n",
+    "        accNameg = \"50g (g)\"\n",
+    "    else:\n",
+    "        accg = g250g\n",
+    "        accNameg = \"250g (g)\"\n",
+    "    print(\"Accelerometer used: \", accNameg)\n",
+    "\n",
+    "\n",
+    "accPick()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a dataframe that only includes data from the relevant accelerometer and the pore pressure sensor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dec_ppm_plot():\n",
+    "    #Plot deceleration\n",
+    "    #fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "    ax1.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    plt.title(\"Drop \"+ str(a+1))\n",
+    "    ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "    ax1.set(xlabel=\"Time Index\")\n",
+    "    plt.legend(loc = \"upper left\")\n",
+    "    ax2 = ax1.twinx()\n",
+    "\n",
+    "    #filter the pore pressure readings to show a smoother line\n",
+    "    c=1\n",
+    "    n = 50  # the larger n is, the smoother curve will be\n",
+    "    b = [1.0 / n] * n\n",
+    "    ppm_filtered = lfilter(b, c, ppm)\n",
+    "\n",
+    "    #Plot pore pressure\n",
+    "    ax2.plot(ppm, color = 'b', alpha = .2)\n",
+    "    ax2.plot(ppm_filtered, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "    ax2.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "    plt.legend(loc = \"upper right\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataframe with Pore Pressure and Accelerometer readings\n",
+      "               ppm   Acc (g)\n",
+      "0       -25.505141  1.061010\n",
+      "1       -26.019292  1.061591\n",
+      "2       -25.772872  1.060313\n",
+      "3       -25.526453  1.054412\n",
+      "4       -25.704608  1.054699\n",
+      "...            ...       ...\n",
+      "119995  135.420592  0.774428\n",
+      "119996  135.540139  0.776367\n",
+      "119997  135.470209  0.769426\n",
+      "119998  135.349663  0.767469\n",
+      "119999  135.974371  0.766233\n",
+      "\n",
+      "[120000 rows x 2 columns]\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "483a5954d67145c398818434e7cbae3a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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+zeXLl5GcnGwSE9x5e+TIkWZP/By18LBGVlYWatasiS+//FLz81KlSlnd9qmnnsLo0aM1P69UqZJiXisqce7cuRgwYAC6deuGUaNGISoqCkajEZMnTzb5ZzmLvcmhjUaj5nK1sFPD/cbsFYrW4PsoXLiw1fWGDh2KX375BcOGDUNcXBwiIiJgMBjQu3dvTcd+Z7+bo5QsWRLx8fEu25/6XMnKyoLBYMDKlSs1v5NWEI4WDRs2VETbaxESEmImCrOyshAVFYV58+ZpbsNFlsFgwKJFi7Br1y78/fffWL16NQYOHIgpU6Zg165dyJ8/P6KiopCQkIDVq1dj5cqVWLlyJX755Rf069fPlE7I0rmbmZmpuVzr2nL0+iQIb4MEIOHX/PrrrwBgEnvlypUDwCwetm645cuXt1lhonz58jh06BBat27tcDWN8uXLIyUlJUc3/kWLFqFcuXJYvHix4vjjx49XrOdI22JiYpCVlYUzZ86gatWqpuXXrl3D3bt3ERMT43R7RUqXLo3Q0FBFpCs/PsCstU8++aRpeUZGBs6fP68ZvJKYmIiAgACbN+VFixahf//+mDJlimnZ48ePcffuXae+A2/rmTNnTOcWwPIbukLYisc4deqU2WcnT55E4cKFbaZZKV++PCRJQtmyZXURLuXLl8e6devQpEkTu9KrPPHEE3jiiSfw0Ucf4bfffkPfvn0xf/58vPTSSwCA4OBgdO7cGZ07d0ZWVhZef/11/PDDDxg7diwqVKhgsr7evXtXEdyitl7banNOr0+C0BPyAST8lg0bNuDDDz9E2bJlTakooqKi0LJlS/zwww+4evWq2TZiio+ePXvi0KFDZlGvgGwB6tWrF/777z/8+OOPZus8evQIDx48sNi+Xr16YefOnVi9erXZZ3fv3kVGRobN78itOaJFavfu3di5c6diPR6JaY/Q6dChAwCYRTlyK2fHjh1t7sMegoKCUL9+fezbt0+xvH79+ihUqBB+/PFHxW8wb948i6Jq//79qF69OiIiIqwe02g0mlnvpk+fbtEyZIv4+HgEBQVh+vTpiv26MkK0WLFiqFOnDmbPnq34/44ePYo1a9aY/i9r9OjRA0ajER988IHZ95ckyeSP6S569eqFzMxMfPjhh2afZWRkmL7XnTt3zNpXp04dADClIFK3NSAgwPRQwNfhCcFFP70HDx44lHDcFdcnQegJWQAJv2DlypU4efIkMjIycO3aNWzYsAFr165FTEwMli1bhjx58pjW/fbbb9G0aVPUrFkTgwYNQrly5XDt2jXs3LkTly9fxqFDhwAAo0aNwqJFi/DMM89g4MCBiI2Nxe3bt7Fs2TJ8//33qF27Np5//nn88ccfePXVV7Fx40Y0adIEmZmZOHnyJP744w9TbjEtRo0ahWXLlqFTp06mtCkPHjzAkSNHsGjRIpw/f97mkGanTp2wePFidO/eHR07dkRiYiK+//57VKtWDSkpKab1QkNDUa1aNSxYsACVKlVCwYIFUaNGDdSoUcNsn7Vr10b//v3xv//9D3fv3kWLFi2wZ88ezJ49G926dVNY5XJK165d8d577ynStwQHB2PChAkYOnQoWrVqhV69euH8+fOYNWsWypcvb2bNTE9Px+bNm/H666/bPF6nTp3w66+/IiIiAtWqVcPOnTuxbt06RRoTRyhSpAhGjhyJyZMno1OnTujQoQMOHjyIlStX2vzvHOHzzz9H+/btERcXhxdffNGUBiYiIsKUz9Ea5cuXx6RJkzBmzBhTSp2wsDAkJiZiyZIlePnllzFy5EiXtVdNixYt8Morr2Dy5MlISEhAmzZtEBQUhDNnzmDhwoX4+uuv8fTTT2P27Nn47rvv0L17d5QvXx7379/Hjz/+iPDwcJPQfemll3D79m20atUKJUuWxIULFzB9+nTUqVPHZLFu06YNSpcujRdffBGjRo2C0WjEzz//jCJFiuDixYt2tdkV1ydB6IoOkccE4TF4Wgf+Cg4OlqKjo6WnnnpK+vrrr6V79+5pbnfu3DmpX79+UnR0tBQUFCSVKFFC6tSpk7Ro0SLFerdu3ZKGDBkilShRQgoODpZKliwp9e/fX7p586ZpnbS0NOnTTz+VqlevLoWEhEgFChSQYmNjpQ8++EBKTk42radOAyNJknT//n1pzJgxUoUKFaTg4GCpcOHCUuPGjaUvvvhCSktLkyRJTgPz+eefm32PrKws6eOPP5ZiYmKkkJAQqW7dutLy5cul/v37SzExMYp1d+zYIcXGxkrBwcGKlDBaKTPS09OlDz74QCpbtqwUFBQklSpVShozZowidQ7/Th07djRrV4sWLTTTtai5du2aFBgYKP36669mn02bNs30vRo2bCht375dio2Nldq1a6dYb+XKlRIA6cyZMzaPd+fOHemFF16QChcuLOXPn19q27atdPLkSbP/xlJ6oY0bN0oApI0bN5qWZWZmSh988IFUrFgxKTQ0VGrZsqV09OhRzf9bCwDS4MGDba63bt06qUmTJlJoaKgUHh4ude7cWTp+/LhiHf5f3rhxQ3Mff/75p9S0aVMpX758Ur58+aQqVapIgwcPlk6dOmX12PakW5IklgYmX758Fj//3//+J8XGxkqhoaFSWFiYVLNmTWn06NHSlStXJEmSpAMHDkh9+vSRSpcuLYWEhEhRUVFSp06dpH379pn2sWjRIqlNmzZSVFSUFBwcLJUuXVp65ZVXpKtXryqOtX//fqlRo0amdb788kuLaWC0zmFJsu/6JAhvxSBJLvZWJgiCcCEvvvgiTp8+ja1bt1pdLysrC0WKFEGPHj0UQ+7dunWDwWDQHKonCILwV2gImCAIr2b8+PGoVKkStm/fjiZNmgBggRkhISGK4d45c+bg9u3bilJwJ06cwPLly5GQkODhVhMEQXg3ZAEkCMLn2LRpE4YPH45nnnkGhQoVwoEDB/DTTz+hatWq2L9/vyn5NUEQBKENWQAJgvA5ypQpg1KlSmHatGm4ffs2ChYsiH79+uGTTz4h8UcQBGEHZAEkCIIgCILwMygPIEEQBEEQhJ9BApAgCIIgCMLPIAFIEARBEAThZ1AQSA7IyMjAwYMHUbRoUbPi5gRBEARBeCdZWVm4du0a6tati8BA/5RC/vmtXcTBgwfRsGFDvZtBEARBEIQT7NmzBw0aNNC7GbpAAjAHFC1aFAA7gYoVK6ZzawiCIAiCsIerV6+iYcOGpvu4P0ICMAfwYd9ixYqhZMmSOreGIAiCIAhH8Gf3Lf/95gRBEARBEH4KCUCCIAiCIAg/gwQgQRAEQRCEn0E+gARBEH6OJEnIyMhAZmam3k0hCJdgNBoRGBgIg8Ggd1O8FhKABEEQfkxaWhquXr2Khw8f6t0UgnApefPmRbFixRAcHKx3U7wSEoAEQRB+SlZWFhITE2E0GlG8eHEEBweTxYTweSRJQlpaGm7cuIHExERUrFjRr6N9LUECkCAIwk9JS0tDVlYWSpUqhbx58+rdHIJwGaGhoQgKCsKFCxeQlpaGPHny6N0kr4MkMUEQhJ9D1hEiN0LntXXo1yEIgiAIgvAzSAASBEEQBEH4GSQACYIgCILIEc2bN8dvv/1mmjcYDFi6dKnbjvf999+jc+fObtu/P0ACkCAIgvA5BgwYAIPBAIPBgODgYFSoUAETJ05ERkaGx9tSpkwZU1vy5cuHevXqYeHChR5vh14sW7YM165dQ+/eve3epmXLlqbfLE+ePKhWrRq+++47u7cfOHAgDhw4gK1btzrTZAIkAAkv586Er3Hoqw3IytK7JQRBeBvt2rXDf/9dxZEjZzB8+FuYMGECPv/8c6f2lZmZiawcdDQTJ07E1atXcfDgQTRo0AD/93//hx07dmium5aW5vRx3EVO2jRt2jS88MILDgddDBo0CFevXsXx48fRq1cvDB48GL///rtd2wYHB+PZZ5/FtGnTnGkyARKAhDezcyf+/OAwxo24h7Vr9W4MQfgHkgQ8eKDPS5Ica2tISAgiIqJRtGgMBgx4DfHx8Vi2bBkA4M6dO+jXrx8KFCiAvHnzon379jhz5oxp21mzZiEyMhLLli1DtWrVEBISgosXLyI1NRUjR45EiRIlkC9fPjRq1AibNm2y2ZawsDBER0ejUqVK+PbbbxEaGoq///4bALMQfvjhh+jXrx/Cw8Px8ssvAwC2bduGZs2aITQ0FKVKlcIbb7yBBw8emPb53XffoWLFisiTJw+KFi2Kp59+2vTZokWLULNmTYSGhqJQoUKIj483bduyZUsMGzZM0b5u3bphwIABpnln26Tmxo0b2LBhg83h2PHjx6NYsWI4fPiwaVnevHkRHR2NcuXKYcKECahYsaLp/3v77bdRqVIl5M2bF+XKlcPYsWORnp6u2Gfnzp2xbNkyPHr0yOqxCW1IABJey/39p/EK/odl6IauXfVuDUH4Bw8fAvnz6/NyphjJ2bPsdf06y/3GLVkDBgzAvn37sGzZMuzcuROSJKFDhw4KEfHw4UN8+umnmDlzJo4dO4aoqCgMGTIEO3fuxPz583H48GE888wzaNeunUI82iIwMBBBQUEKq9oXX3yB2rVr4+DBgxg7dizOnTuHdu3aoWfPnjh8+DAWLFiAbdu2YciQIQCAffv24Y033sDEiRNx6tQprFq1Cs2bNwcAXL16FX369MHAgQNx4sQJbNq0CT169IDkoIJ2tE1abNu2DXnz5kXVqlU1P5ckCUOHDsWcOXOwdetW1KpVy+K+xP8vLCwMs2bNwvHjx/H111/jxx9/xFdffaVYv379+sjIyMDu3bsd+t4EgxJBE17L4ftlkAUjACA1FUhOBiIidG4UQRBegyQB6elMZKxYsR6rV6/G0KFDcebMGSxbtgzbt29H48aNAQDz5s1DqVKlsHTpUjzzzDMAgPT0dHz33XeoXbs2AODixYv45ZdfcPHiRRQvXhwAMHLkSKxatQq//PILPv74Y5ttSktLw5QpU5CcnIxWrVqZlrdq1QpvvfWWaf6ll15C3759TZa6ihUrYtq0aWjRogVmzJiBixcvIl++fOjUqRPCwsIQExODunXrAmACMCMjAz169EBMTAwAoGbNmg7/fo62SSuZ8oULF1C0aFHN4d+MjAw899xzOHjwILZt24YSJUpotiMzMxO///47Dh8+bLJEvv/++6bPy5Qpg5EjR2L+/PkYPXq0aXnevHkRERGBCxcuOPzdCRKAhBdz7kqoYn79eqBHD50aQxB+Qt68QEqKfsd2hH/+WY61a/MjIyMdWVlZ6Nv3WUyYMAHr169HYGAgGjVqZFq3UKFCqFy5Mk6cOGFaFhwcrLBIHTlyBJmZmahUqZLiOKmpqShUqJDVtrz99tt4//338fjxY+TPnx+ffPIJOnbsaPq8fv36ivUPHTqEw4cPY968eaZlkiSZyvM99dRTiImJQbly5dCuXTu0a9cO3bt3R968eVG7dm20bt0aNWvWRNu2bdGmTRs8/fTTKFCggEO/n6Nt0rLyPXr0yGKVjeHDhyMkJAS7du1C4cKFzT7/7rvvMHPmTKSlpcFoNGL48OF47bXXAAALFizAtGnTcO7cOaSkpCAjIwPh4eFm+wgNDaU61k5CApDwWs5t/k8xv38/UL06ULmyTg0iCD/AYADy5dO7FfbRtOmTePPNGQgKCkbhwsVRt24gQkLs3z40NFRR+zglJQVGoxH79++H0WhUrJs/f36r+xo1ahQGDBiA/Pnzo2jRomY1lfOpftSUlBS88soreOONN8z2Vbp0aQQHB+PAgQPYtGkT1qxZg3HjxmHChAnYu3cvIiMjsXbtWuzYsQNr1qzB9OnT8d5772H37t0oW7YsAgICzIaD1f5zzrRJi8KFC+POnTuanz311FP4/fffsXr1avTt29fs8759++K9995DaGgoihUrZrIi7ty5E3379sUHH3yAtm3bIiIiAvPnz8eUKVPM9nH79m0UKVJE8/iEdUgAEl7LyccxivmPP2av7duB7FEdgiD8mDx58qFUqQqm+fv3gZAQoGrVqibfMD4EfOvWLZw6dQrVqlWzuL+6desiMzMT169fR7NmzRxqS+HChVGhQgXbK2ZTr149HD9+3Oo2gYGBiI+PR3x8PMaPH4/IyEhs2LABPXr0gMFgQJMmTdCkSROMGzcOMTExWLJkCUaMGIEiRYrg6tWrpv1kZmbi6NGjePLJJ3PcJjV169ZFUlIS7ty5Y2aB7NKlCzp37oxnn30WRqPRLE1MRESE5rF27NiBmJgYvPfee6ZlWsO8586dw+PHj01D44RjUBAI4bWceFQWAFAXBxTL33nH8WhBgiByH+p+gAeDVqxYEV27dsWgQYOwbds2HDp0CM899xxKlCiBrlYiyipVqoS+ffuiX79+WLx4MRITE7Fnzx5MnjwZ//zzj0vb/vbbb2PHjh0YMmQIEhIScObMGfz111+mgIvly5dj2rRpSEhIwIULFzBnzhxkZWWhcuXK2L17Nz7++GPs27cPFy9exOLFi3Hjxg3TEG2rVq3wzz//4J9//sHJkyfx2muv4e7duzlukxZ169ZF4cKFsX37ds3Pu3fvjl9//RUvvPACFi1aZNdvU7FiRVy8eBHz58/HuXPnMG3aNCxZssRsva1bt6JcuXIoX768XfsllJAAJLySEyeA00nM3+NdfKT4bOtWYM0aPVpFEIQ3oU7bl5oqT//yyy+IjY1Fp06dEBcXlx0osgJBQUFW9/nLL7+gX79+eOutt1C5cmV069YNe/futTgE6iy1atXC5s2bcfr0aTRr1gx169bFuHHjTMEnkZGRWLx4MVq1aoWqVavi+++/x++//47q1asjPDwcW7ZsQYcOHVCpUiW8//77mDJlCtq3bw+AJUnu378/+vXrhxYtWqBcuXI2rX/2tEkLo9GIF154QeE3qObpp5/G7Nmz8fzzz2Px4sU229GlSxcMHz4cQ4YMQZ06dbBjxw6MHTvWbL3ff/8dgwYNsrk/QhuD5GjcOGHi8uXLKFWqFC5duoSSJUvq3ZxcxaJFwDPPAHnxAMkIx6HdaUjNMKJJE/b5G28AX3+tbxsJwtd5/PgxEhMTUbZsWYuO/N7M6dPAvXtAHjzCY4Qib17Ayggv4SaSkpJQvXp1HDhwwBSV7G6OHTuGVq1a4fTp04iwkB7C2vlN92+yABJeSlISey+OKwhEFmLrZuGJJ1gQCABMm8Zyf+3fDzx+rF87CYLQDx7XkBcsCjQtDdChEpzfEx0djZ9++gkXL1702DGvXr2KOXPmWBR/hG0oCITwSniyeN6xQ5IQEMDSwBw7xhZVrMje58xhT/2xsZ5vJ0EQ+pCVJfv85UcK7qAAMjICkJwM2MjY4lYkSU5ozdPaPHzIoqsdTXPjS3Tr1s2jx4uPj/fo8XIjZAEkvA5JAg4dYtPhuMcmsp19evUC1C48/foB9esDe/cCQuAbQRC5GLE6WQhSkS+IVZBITNSpQdk8eMB8mE+cYNVJUlJYmy5dYhZKgvAWSAASXseVKwCvutQJrJYmD/erUQNYuFB7u4YNgbJlgZMn2dAwf508yfyEADZc/PixdhTxtWssjQRBEN6P6PoRhvsIC5IjQPQaBpYk5UPopUvAqVOsrffvA7dvUwYDX2Xy5Mlo0KABwsLCEBUVhW7duuHUqVOKdVq2bAmDwaB4vfrqq4p1Ll68iI4dOyJv3ryIiorCqFGjkKHTCUtDwITXsWULcOcOkC84HS+n/Y8tFML9WrcGXngB+OUX821TU4GhQ4F165TLjUZg5Uo2FHP5MtCoEVClCqs/ev06E5yLFgEdOgAFC7LDGQzMskgQuR1fjAXkAjA/7iMAEiKCH+LqQ+YPdvcuEBkJBHr4DvfgAStZaYnLl1meQgcLdhBO4srzevPmzRg8eDAaNGiAjIwMvPvuu2jTpg2OHz+uSKg9aNAgTJw40TSfVxj3z8zMRMeOHREdHY0dO3bg6tWr6NevH4KCguwqM+hqSAASXgf3/6tYNBkFLmX3psKFnD8/8OqrQIkSQHw8e7Lu3FneXi3+ACAzE2jTRrnsk0+AChVYMMk777BlU6cq1/n3X2ZVvH6dDd8UK8bE5M2bbGgnJoYJRYLwRXhKlIcPHyI0NNTG2t4FF4B5wCbyBaYiXz4mws6fBwoXBsqU8Vx7UlOVIwjBwfKQb4EC7KEWYH1HZCT1G56Al4izlfrHHlatWqWYnzVrFqKiorB//340b97ctDxv3ryIjo7W3MeaNWtw/PhxrFu3DkWLFkWdOnXw4Ycf4u2338aECRMQHByc43Y6AglAwuvYsIG9ly98D7iUvVCV8KtBA6BqVSYGMzKAffuA115jfoD2wkWfNaZPB/r2Zekm/voL+L//A5o2BX76CVi7lonIBg3sPyZBeBNGoxGRkZG4fv06AHbzUpcw80YkSQ4AMSKFScCMDBgM8rjwzZusf7BRwc1lXLnChngBICwMEKuTBQSwLiw5mb2uXWMikHAPkiTh4cOHuH79OiIjI83K+rmC5GxTb8GCBRXL582bh7lz5yI6OhqdO3fG2LFjTVbAnTt3ombNmihatKhp/bZt2+K1117DsWPHPF7RhAQg4VVkZMgpYKIjhALfKlO+wcA6WYAFhcTGAt99B3TvzoZZBg0CXnmFPXVfuQL072/72O+8wwSdyFdfsRdnwQKgXDlmGQSAmTNJABK+DbdWcBHoC6Sns+saAAJxFSlIAx49QnJQOsSCFzdvAsWLmweOuZKsLNZvib5/BoN5kurHj1l7AGYptGAkIlxIZGSkRWsc5/79+7jHncQBhISEIMRGQemsrCwMGzYMTZo0QY0aNUzLn332WcTExKB48eI4fPgw3n77bZw6dcqU/DopKUkh/gCY5pP4jc+DkAAkvIrDh5mAA4DnGp4GNmV/oO5NNahXD1i6lA33xsQARYsyn7/Hj5k4fP11Jtjq1GEdsJgYv3FjYNgwoFs3YNkyoFIlYMAA7eNw8QcABw5or0MQvoLBYECxYsUQFRWFdJ5Yz8vZtIm5gQQGAgkZHRGILKBTJxzp/wVOnmQCjD+4NWkCjBgBlCrFhobz5GHXN8CGaHmJ2QoVrA/LpqWxYV01a9awxPScXr2A8eOZq4jIw4es/+EV5b7/HmjZ0okvT9hFUFCQXZY/dW3o8ePHY8KECVa3GTx4MI4ePYpt27Yplr/88sum6Zo1a6JYsWJo3bo1zp0755Xl6kgAEl7FwYNM6xUpAjQqe0P+wA5n3oAA81yAefOyV58+LEq4Zk3WiT9+zIaLv/yS3RBGjmSCsXBhoGRJ1oaYGPnm0Lw5Szfz0kvK/Z85w5rmA6NmBGEVo9HolqEyd5CYyK7N0qWB/Bez877cvIkGDfKgcmX2EDl5MhtqvXAB+O034PffmVBr2hR47z3mH7hrF7BiBXDjBnMhefJJZslLTgYqV1Y+4O3bx9xOmjdnIwv377N+Sl1aeORIQIgJMJEnDxuZ+OEH9pDavz/zV65Z020/E2EHx48fR4kSJUzztqx/Q4YMwfLly7FlyxabFUQaNWoEADh79izKly+P6Oho7NmzR7HOtWvXAMCmpdIdkAAkvAqe5LlqVcAAQfTZYQG0RmSkUhzmycPm33qLCT9+HRuNLLgEAP78U16/VCm2j3//BcRgreRk5rPYunWOmkcQhJ1IEntQBJgABC8+kZkJAAgPZ4nh//yTiT1Onz7sfckS9ho+XOnecfgwMG8eE3379rEHvs2bmVgUOX8eOHIEePNN4O235eXlyjHf4Kgoy22vU4e5pnz3HQssW7GCBKDehIWFITw83OZ6kiRh6NChWLJkCTZt2oSyZcva3CYhIQEAUKxYMQBAXFwcPvroI1y/fh1R2SfK2rVrER4ebmaJ9AgS4TSXLl2SAEiXLl3Suym5hnbtJAmQpFdflSTp22/ZDCBJ16/r0p6sLOX83r2SFBrKmlStGnufNEmXphGEX7J7t9wtlC6dJc90765YLyNDkmbOlD929+vCBfvav2+fJBUoIG/34IEbfiTCJo7ev1977TUpIiJC2rRpk3T16lXT6+HDh5IkSdLZs2eliRMnSvv27ZMSExOlv/76SypXrpzUvHlz0z4yMjKkGjVqSG3atJESEhKkVatWSUWKFJHGjBnjlu9oC0oETXgNkgQcP86mq1eHctg3hxZAZ1EP7darB2zdyiwEPGDLkchjgiByxtGj8nTrJy33EUYj8PzzLFrf3fzf/2VbI+2gXj1mgeQsXkz1zH2BGTNmIDk5GS1btkSxYsVMrwULFgAAgoODsW7dOrRp0wZVqlTBW2+9hZ49e+Lvv/827cNoNGL58uUwGo2Ii4vDc889h379+inyBnoSGgImvIYzZwBeS7xBAwB7hA5dJwGoRvQzbNSIDRnt3k1+gAThKY4ckaenfpkFzM6eyR4CFgkOZu4ZP/8MDBwITJgAdOqkTPC+axfzBf7jD+3jNWvGPt+wQTnkK2LDFUyBwQA88QTzTX74kInU+fOBSZPYEDHhnUg2/NBLlSqFzZs329xPTEwMVqxY4apm5QgSgITXsH49ey9RIruD3iWIPi+sVBAby9JLJCUxiyClgyEI98MtgIMHA+H5hT5CQwACTHC1acOu0SJFmKXuxx9ZQMY777AHuTfeYHkF4+OB8uVZEMeRI6yE5HPPyQnf161j6wDAU0/J1sWePR37DiEhwMsvy4nn//mHvc6dY76EBOEJSAASXgMf/q1WLTuFgtihe4kFUKRRIzZUnZDAnLlJABKEe3n8WK4TXrUqlA+GFgQgwB4qhUBPtGvHBCH342/cGPj1VxZAYjCw3VaowB7weNq2unVZibktW4BDh5gVb/Jk9pkzlrsuXcwrD8XHK9NMEYQ7IQFIeA08AtgUDJXl3RZAo5HdJBISgFmzWO4vgiDcx7lzcp7Q9u2h7COsCEA1JUsqh20NBiAiQjmvHtYNCGB1wps1A+Li5DrDzrp/NG7MROiNG9nfBSy9zcmTrE45QbgbCgIhvIL0dODECTZdtWr2wizv8wFUw4drzp8Hbt3StSkEkes5cYLpvLx5s613dloAXU2gYDpx1vc3JIS5kTz5JBtB4Hz7bc7aRhD2QgKQ8Aq2bGG+dAaDkB3fyy2AAPMt4vz2m37tIAh/4Px59l6mTLbwctIC6E2EhDB/wmbN2Pw337D8gwThbnKFAJw8eTIaNGiAsLAwREVFoVu3bjh16pTVbWbNmgWDwaB45cmTx0MtJtRwx+4yZVgGfgA+YQFs0kT2/9m6VdemEESuJzG76EdMTPYCnSyAriYwEBg6VJ5v2dKnvw7hI+QKAbh582YMHjwYu3btwtq1a5Geno42bdrgwYMHVrcLDw/H1atXTa8LvO4X4XHECiAmfMACmCcPixIEmD8PQRDug1sATUUYvPTB0Bm4HyBn/nx92kH4D7kiCGTVqlWK+VmzZiEqKgr79+9H8+bNLW5nMBh0qb9HmMP9/xTVcLw8CphTowZ7T0wEVq4078gJgsg5kqQcAjYtzCXkz89yEj7xBJt/7jmgbVtWn5wg3EGusACqSU5OBgAULFjQ6nopKSmIiYlBqVKl0LVrVxzjZijCo6SlqSqAcHzAAggIPotQOnMTBOE6tm+X+4mGDbMXevGDoTPExjIfQM4XXwCpqfq1h8jd5DoBmJWVhWHDhqFJkyaowU0zGlSuXBk///wz/vrrL8ydOxdZWVlo3LgxLvMcAxqkpqbi3r17ptf9+/fd8RX8jrVrgdu3WVqVDh2ED3zABxBgTtz8hrRpE5CRoWtzCCJX8vPP8jS3knlzv+AMgYFA9+7y/KefAgcP6tceIneT6wTg4MGDcfToUcy34UARFxeHfv36oU6dOmjRogUWL16MIkWK4IcffrC4zeTJkxEREWF6VVOMVxLOwp/qy5cHoqKED3zEAggAH3zA3o8eBcaM0bctBJEbefiQvZcuzR66AHh9v+AMxYsDs2fL83FxwOnT+rWHyL3kKgE4ZMgQLF++HBs3bkRJR4ozAggKCkLdunVx9uxZi+uMGTMGycnJptdxrlyIHKE5/Av4jA8gAIiupl98wRLWEgThOvjgDA+6AuBTD4mOEBennLdilyAIp8kVAlCSJAwZMgRLlizBhg0bUNYUImY/mZmZOHLkCIoVK2ZxnZCQEISHh5teYWFhOWk2AdZniyXgFKSnK1f0YvLmBVatyi5hB+C99/RtD0HkJiQJ+O8/Nl2+vOoDrWkfp2JFZVaBL7/Ury1E7iVXCMDBgwdj7ty5+O233xAWFoakpCQkJSXh0aNHpnX69euHMcLY3MSJE7FmzRr8+++/OHDgAJ577jlcuHABL730kh5fwW+5c0cWgIoUMICy1/NyCyDAOm2ezHXTJlZcniCInHPunBwBXK+e8IGP+Ak7Q2wssGyZPM9zIBKEq8gVAnDGjBlITk5Gy5YtUaxYMdNrwYIFpnUuXryIq1evmubv3LmDQYMGoWrVqujQoQPu3buHHTt2kF+fh9m8GUhJYT49XbtaWdEHnu7LlgXGjmXT164Bf/2lb3sIIrewfbs8rXAVyaUWQA5/oASAOXP0aweRO8kVeQAlOy78TZs2Kea/+uorfPXVV25qEWEv3Lm5QgWWB8siPvB0bzCwyiD16gEHDgB9+rAUMZRqkiByxu7d7N1gAIKChA9ysQUQACIjgdq1gUOHWI5AgnAlucICSPguPFiiQgUbK/rI031IiFDKDswXcP9+/dpDEL6OJMmVgkaM0PhQazoXwVPerFpF5eEI10ICkNAVHnRdrpyNFX3o6f7NN+Xpn38G6tenMnEE4Sz378uVgmJjVR/m0ihgkfh4eXrePP3aQeQ+SAASunHzJrBxI5uuWNHGyj7UuTdsCMydq1zWoAGwZ48+7SEIX2bHDuDGDSAgAOjcWfWh2C/40EOiI5iqnoAlhiYIV0ECkNAN0bFbMwAkPFye9qHO3WAAnnzSvCZwo0Y+9TUIwivg1r+yZTX8hP3AAli6NPDRR2z6+HFg9Wp920PkHkgAErohljgqXlxjBTGfo4917sWLA598Yj70u3evPu0hCF+FC0DNBA1+YAEEgNat5ekVK6jcJOEaSAASunHgAHvv39/CCj4e4VerFlC3rnLo9733gAcP9GsTQfgaFvOEAj7fR9hLo0YsqwAATJtGVkDCNZAAJHQhM1OO7Ktd28JKuSDCLyCAOa536sTm169n0XwEQdgmIwP49182bRYAAvhsv+AMHTrI01RvnHAFJAAJXdi7V87s37GjhZVyyfBOQAAwcqQ8//TT8k2NIAjLHD4M8Pz9jRtrrOAHPoCcdu2YJRAAjhxhv8u9e/q2ifBtSAASunDkCOu7o6KASpUsrJRLBCDAbl58CAcAlizRry0E4SucOsXeIyKAkiU1VsgFowT2UriwMgr4++9Zmqldu5ilNJd/fcINkAAkdIH79VitvJeLOvegIGD0aHn+zz/JkZsgbMEt5TExFlbw8QdDR2nWDGjVik1PnAgMHw7ExQErV7LSk+np+raP8C1IABK64LAAzAUdfZ06wNKlbHrnTlbVgAJCCMIyR46wd80AEMCvhoAB5k4ybpz58i5dgO7dmTikaiGEvZAAJDxOSooTAjCXEBcnT0+fzoZwrl3Trz0E4a3cvw8kJLBpuwLF/IT69Vm9cS22bQP+/tuz7SF8FxKAhMfZvx+4fJlNd+liZcVc+HQfFQW8/748/8YbwIwZ+rWHILyVw4flUpEtWlhYKRf2EbbIlw/44Qdg61aWZ/S995Sfd++uT7sI34MEIOFxuPWvRAmgVCkrK+YiH0CR119Xzn/wgRwRTRAE48QJNpxZqBDwxBMWVsqlfYQt6tcHmjZllsDu3ZkQLFhQ/vzPP/VrG+E7kAAkPM7Jk+y9ShUbK+bSDj06GlizRlnYffBg/dpDEN7IF1+w95gY5vumSS7wDc4JBgPLjxgbC2zaBDRvzpa//z4baSEIa5AAJDzOmTPsvXJlGyvm0qd7gwF46ilW/zgoiC1bsQK4e1fXZhGE1/DokZwCpk4dKyvm0j7CGWrWBOLj2fTJk8xKmJysb5sI74YEIOFRMjKA06fZdMWKNlbO5Z17vnzKkk7z5/u9QYMgAABHj8rTQ4daWdEPfQCtwQUgZ8UKfdpB+AYkAAmPcuiQ7O/WubONlf2gQ2/enOX2AoDXXgM2bvSLr00QVuECsEgRByyABOLiWJUlzrPP0k9EWIYEIOFRzpxhjt358wPlytlYOZdbAAHAaAQiI+X5+HgSgQTBo3/Ll7exIlkAzahXD/jtN3n+jz/0awvh3ZAAJDwK79grVGC+cFbxAwEIsFQwIq1bAzt26NMWgvAGzp1j7xUq2FjRT/oIRwgIAJ58Up7v3Zt+GkIbEoCER0lMZO82rX+A3zjENW/OBF/ZsvKy7t2ZIzd13IS/kZ4uC0CbFkC6QDSJjgZeekme537XBCFCApDwKBcvsneLtT1F/OTpPjiY+e6IQzU3brDyVxs2AGlp+rWNIDxNUpI8UsD9Yy3iJ32EM4gCUEw+TxAcEoCEx0hNlQWgzRQwgN917vXrA7t3K5fFx7NC7wThL5w4wVIiGQzK0oma+EG/4Cz167PKQwCwaJG+bSG8ExKAhMfIyJAFoM0ne8AvO/f69YEhQ5TLunVTRvYRRG6GW/9KlgTy5rWxsp89JDqC0QhMmSLP0zAwoYYEIOExtm4FHj9m0zZzAAJ+2bkHBLCgkH37gAkT5OVPP+03LpGEn2N3AAhAUcA2aNNGdrfhlVUIgkMCkPAYBw6w99BQuQKGVfy0Q69YkZV26tQJCA9nyy5eBP7+W992EYQn+Okn9h4dbcfKftpH2EtUFOtHAODHH6k8HKGEBCDhMfbtY++PHtm5gR9aAEXq1gVmzZLnN23SqyUE4RkyM+XyZSVK2LGBn/cR9tC+vTw9aZID/S+R6yEBSHiMGzfY+9tv27mBnw/vBAQAbdsCo0ax+alTgXv3dG0SQbiVI0eAkBA23bWrHRuQALRJXJycdmvpUhZY9uCBrk0ivAQSgIRHuHePVQEBgEaN7NyIOnTkzat8gu/QAXj4UL/2EIQ7uXyZZQsIDLSzn6A+wiYFCypTTO3YAbzzjn7tIbwHEoCER9i7F7h2jU03aWLnRvR0D4A9wRuNbHr7duWwMEHkJv79l73HxDjhJ+zHfYQtatUCXnhBnv/mG/OUU4T/QQKQ8AhLl7L38uXl3FQ2oc4dAJAnD/Dll/L84MGUFobInXABaFelIMCv+wVHCApiyaDFfIB9+gB37ujXJkJ/SAASHoF37JUqObARde4mnn4amDxZnm/YkDpvIvexYAF7t6tSEOD3fsKOUK4c0LgxUK8em09MBKpXB+7f17ddvsLkyZPRoEEDhIWFISoqCt26dcOpU6cU6zx+/BiDBw9GoUKFkD9/fvTs2RPX+NBXNhcvXkTHjh2RN29eREVFYdSoUcjIyPDkVzFBApDwCDy3V+vWDmxEFkATxYsDTz0lDwUDwIwZ+rWHIFxNZqacJ7RwYTs3oj7CIYoVA77/Xp6/elUOMiOss3nzZgwePBi7du3C2rVrkZ6ejjZt2uCBEFEzfPhw/P3331i4cCE2b96MK1euoEePHqbPMzMz0bFjR6SlpWHHjh2YPXs2Zs2ahXHjxunxlQCJcJpLly5JAKRLly7p3RSv5s4dSQoJkSRAklavdmDD8HC2ESBJixe7q3k+w6NHkrRvn/yTNG7MfluCyA0kJMjn9u7ddm60fLm8UbFibm1fbiErS5L27JF/NkCSHj/Wu1WeJ6f37+vXr0sApM2bN0uSJEl3796VgoKCpIULF5rWOXHihARA2rlzpyRJkrRixQopICBASkpKMq0zY8YMKTw8XEpNTc3Bt3EOsgASbmfrVjmyr0ULBzakJ3oFefKwBNGLF7P5HTuAXr1YiT2C8HV4nlCAlUS0C7IAOozBANSuDTzzjLxs+HD92qM39+/fx71790yv1NRUu7ZLzk5YWbBgQQDA/v37kZ6ejvj4eNM6VapUQenSpbFz504AwM6dO1GzZk0ULVrUtE7btm1x7949HDt2zFVfyW5IABJuJzGRvZcuLef4sgvy79GkRg15eu1a4L339GsLQbgK7k4VGspyYNoFCUCnCA4GPv9cnp8xw399AatVq4aIiAjTa7LobG2BrKwsDBs2DE2aNEGN7A45KSkJwcHBiIyMVKxbtGhRJCUlmdYRxR//nH/maUgAEm6H+//ZHdnHoc5dk4oVgXfflec/+wy4fVu/9hCEKzh/nr0//bQDG1G/4DQxMUp/wFdeAU6c0K89enH8+HEkJyebXmPGjLG5zeDBg3H06FHMnz/fAy10HyQACbfDE0A7FAEMUOduhVdfZZHAnHnz9GsLQbgCnimgfHkHNqKHxBzxzDOsMggA/P47MGAAcP26rk3yOGFhYQgPDze9QmwMUw0ZMgTLly/Hxo0bUbJkSdPy6OhopKWl4e7du4r1r127hujswtbR0dFmUcF8Ptqu4teuhQQg4Vbu3pUFYMWKDm5MnbtFSpViHTbnjTeA48f1aw9B5IRHj4ALF9h0zZoObEhuIjmiYEFg2DB5fs8eORUPoUSSJAwZMgRLlizBhg0bULZsWcXnsbGxCAoKwvr1603LTp06hYsXLyIuLg4AEBcXhyNHjuC6oLLXrl2L8PBwVKtWzTNfRIAEIOFWTp6UfQAdSgEDkAC0QblywI8/yvMNGjDBTRC+xo4dwM2bbLplSwc2pH4hx7RvD6xbJ8+/8QaQkqJfe7yVwYMHY+7cufjtt98QFhaGpKQkJCUl4dGjRwCAiIgIvPjiixgxYgQ2btyI/fv344UXXkBcXByeeOIJAECbNm1QrVo1PP/88zh06BBWr16N999/H4MHD7ZpeXQHJAAJt3L+PMvvlT+/MnjBLqhzt4kQcIaHD5WCkCB8BR4AGRPDrFJ2Qw+JOSYgAHjySeDXX+VlH3+sX3u8lRkzZiA5ORktW7ZEsWLFTK8Fgsn0q6++QqdOndCzZ080b94c0dHRWMzTNgAwGo1Yvnw5jEYj4uLi8Nxzz6Ffv36YOHGiHl8JgboclfAbxOFfg8HBjalzt0mZMsDmzXJ6ndGjgTffZFF+BOErcAFYvbqDG1K/4BICAoA2beT5yZOBunWVqWL8HcmOcy1Pnjz49ttv8e2331pcJyYmBitWrHBl05yGLICEW+ECsEIFJzYW/XsIi8TFKWt8zpqlW1MIwim4AHTYDYoeEl1GVBTw9dfyfK9ewKFD+rWHcD8kAAm3cvYse3c4AASgzt1OgoKYHw9PP7Vqla7NIQiHuH0bOHqUTTdq5ODG1Ee4lO7dlUm427fXry2E+yEBSLiNlJQcRAAD1Lk7QN68wPjxbHr/fjKeEr7D1q1AcrL8IOMQ1C+4lFKllDXGr16Vg/iI3AcJQMJt7N4tR/Z17uzEDqhzd4hmzZif5cWLLKqSIHwBnv+vbFkgXz4HN6Y0MC6nfn1AyGTiePYGwmcgAUi4DV4BpHhxoFChHO6MOneb1KkjJ9vesgVIS9O1OQRhF7wCSJkyTmxMowRuoVkzeToxkWVyIHIfJAAJt+FUZn+OujOnzt0mRiNQrx6bfu89YN8+fdtDEPbABWBMjBMbU7/gFoKCWGoYDvkV505IABJuw+kawAB17E4iOtE3aeJ/ZZ0I30KSyALorXzyiTwt5ggkcg8kAAm3wTt2VcUc+1BHMVDnbhdNmijnhwyh4RvCe3nwQO4nGjd2YgckAN1GbCwwaRKbXrCARWsTuQsSgIRbSE+Xa3s2bOjEDqgzd4r69ZVDvwsXAsuX69cegrDG5s3AvXtsOjbWiR1QP+E2jEZlpSExOpjIHZAAJNxCQgJw4wabdokApI7ebmJjgU2b5Plp03RrCkFYhef/A4CwMCd2QBZAt1KvHlC4MJsW6wUTuQMSgIRb2LqVvZcs6WQEMAnAHPHEEyyTPwBs2MDyrBGEt3H8OHsXo04dghJeupWgIFYWDmAPlSdO6NocwsWQACTcwsWL7P3qVSd3QIIvR4SEACNGyPOffaZfWwjCErxSkNp31W7IAuh2GjSQp3//Xb92EK6HBCDhFpKS2LvTxcTJAphj6tUDAgPZ9Mcf50CME4QbSE+XMwVUqeLkTkgAup1atYBXX2XT27fr2xbCteQKATh58mQ0aNAAYWFhiIqKQrdu3XDq1Cmb2y1cuBBVqlRBnjx5ULNmTaxYscIDrfUPeABIhQpO7oA68xwTFAR89JE8/9xzssM9QehNUhJw7Rqbbt7cyZ1QP+F2DAa5PvCGDazCE5E7yBUCcPPmzRg8eDB27dqFtWvXIj09HW3atMGDBw8sbrNjxw706dMHL774Ig4ePIhu3bqhW7duOCp6JRNOceUKsGsXm3Yqsg8gC6CL6NRJnt6wAZg+nX5KwjvYs4e958vnZA5AgCyAHqJmTXl68mT5AZ/wbXKFAFy1ahUGDBiA6tWro3bt2pg1axYuXryI/fv3W9zm66+/Rrt27TBq1ChUrVoVH374IerVq4dvvvnGgy3PnYh1aFu2dHIn5NztEqpVUw7bvP++fOMlCD357z/2Xrw4szI5BQlAj1CvHtC0KZv+6y/g22/p584N5AoBqCY5O+SxYMGCFtfZuXMn4sUkRwDatm2LnTt3WtwmNTUV9+7dM73u37/vmgbnMs6ckacjI53cCVkAXcYTTwDz5snzL7ygX1sIgsOHf6Ojc7ATelD0CIGBzI+Y8/nnLDk0/fy+Ta4TgFlZWRg2bBiaNGmCGjVqWFwvKSkJRYsWVSwrWrQoknj0ggaTJ09GRESE6VWtWjWXtTs3wR27u3XLwU5I8LmMgABlXc8TJ5RWWoLQA97V5kgAkgXQYzRsyKx/nD595HRfhG+S6wTg4MGDcfToUcyfP9/l+x4zZgySk5NNr+M8iRVhIiNDFoDly+dgR2QBdCnFiimHfps0AR490q89BMG7T9VzuGNQv+AxQkKAtm2BmTPlZZRk3rfJVQJwyJAhWL58OTZu3IiSJUtaXTc6OhrX+BhENteuXUO0lcfRkJAQhIeHm15hTqWuz93cuCELwLp1c7Aj6thdToMGgGgU79lTv7YQ/k1iInDkCJu20VVbhyyAHiUkBPi//wOefprNL14MrFypb5sI58kVAlCSJAwZMgRLlizBhg0bULZsWZvbxMXFYf369Ypla9euRVxcnLua6Rf8+y9w+TKbbtUqBzsiC6BbmDpVnl65kv1fBOFpEhMBnqShXbsc7IgEoMfJnx8YNkye79BBt6YQOSRXCMDBgwdj7ty5+O233xAWFoakpCQkJSXhkTDG1a9fP4wZM8Y0/+abb2LVqlWYMmUKTp48iQkTJmDfvn0YMmSIHl8h1/Dvv6wfLlCADTs6DQlAt9C4MbB0qTxPBd4JPeDWv5gYoHbtHOyI+gVdaNgQ6NhRnicroG+SKwTgjBkzkJycjJYtW6JYsWKm14IFC0zrXLx4EVeFUgiNGzfGb7/9hv/973+oXbs2Fi1ahKVLl1oNHCFs4xL/P4DCy9xEaCjw1FNARASbnzmTkkMTnichgb3nSPwBZAHUiaAgFgnMmT+ffn5PkJoKbNkC/Por8MMPbAg+MdH5/QW6rmn6Idlx5m3atMls2TPPPINnnK5VRmjhMgFIFkC3kTcv8PbbwLvvAnfvAkuWML+ePHn0bhnhD6SnA3//zaZzLADFB0XqIzxK1arA2LHAhx8Cc+YAcXFyyTjCtWzfDnz9Nbtu0tPZA3xoKHD7NhOF5coBL7/Mfn9HQhNyhQWQ8A6ystwoAAmX0rixPD1gALB6tW5NIfyM48eBW7fYNE8u7DTUT+hKly6skgsAvPaaMgcs4Rq6dGEP6GXKAGvWAPfvs+vn8mXg4UP2m7//PrB+PVCpErB2rf37JgFIuIz//gPOnmXTbdrkcGdkAXQrTzwBfPWVPD9lin5tIfwLcciqRYsc7oyGgHWlbl1mAeRMngxk12EgXETHjuya+ewzoFkzZvkTKVcO6N8fWLWKicAAB1QdCUDCZZw5w9LAADlMAQNQZ+5meDoHLtS3bgX++UffNhH+Aff/K1KEnYc5ggSgrhiNLDcg55dflJkGiJzzyivM59IeqlUDWre2f98kAAmXwVOKREcD4eE53BlZAN1OsWKsvBMv19epk67NIfyE27fZu0suaeoXdEddb3zCBKo37iuQACRchsv8/wDq2D1EbCwglsTmQ/gE4S54ntDu3V2wM7IAegVPPKGsENKoEXDsmH7tya1kZgJffMHS8ERHAwULKl+OQgKQcBlcPLhFAFLn7jZeflmejosDLl7Ury1E7oefXzmqAMKhfsErCAgAnnkG6NxZXvbss/q1J7fywQfAl18y953kZGDECKBHD/b7T5jg+P5IABIug1sAK1Rwwc4oD6DHECMxb95k+aXovkq4A0mSLYDVqrlgh5QGxmsIDwfGj5fnDx8GDh7Urz25kXnzgB9/BN56CwgMBPr0YZbXceOAXbsc3x8JQMIl3LkjC0BHnFAtQhZAjxEaqvTh+fhj8uEh3MPly8D162y6SRMX7JD6Ba8iNhYQU+7+/rtuTcmVJCUBNWuy6fz55YjrTp2cC+IjAUi4hD17WEWJgACgXj0X7JA6do8SF6d8gpw1S7emELmYzZvZpR0eznyYcgz1E15H8+bAyJFs+vPPmWghXEPJkgAvaFa+PMsLCAB79zoXUa+fAMzKAjZuBCZOBF58kdky33iDxZFfuqRbswjn4AlAS5VyUUUJsgB6FIMBaNBAHpb7/nuWsJcgXAnvJypXZudcjqF+wuswGJQZBcQ8gUTO6N6d5foDgKFDWSWWihWBfv2AgQMd35/nBeCjR8CkSUwpdOjAqkjfvcsSCp09y5wIypZlnzkzqE3ogksjgAHq2HUgIID5knAmTwYeP9avPUTu4/x59l6mjIt2SP2EVxIbKw9Vfvcd1Rt3FZ98wkp4AiwQZOtWVoFl0SL2maN4XgBWqsS8Q3/8kZ0VO3cCf/4JzJ0LrFjBQsTOnWMpr3v3ZusRXs+FC+y9bFkX7ZA6cl3o2BGoVYtNz51LPjyEa3H7gyLhFeTPD3z6qTw/ebJ+bcktLFgA9O3Loq2//54te+IJFgksRl87gucF4Jo1wB9/MAufpfTWMTHAmDFsvKBVK8+2j3AYSZIFYEyMC3dqbZ5wC/nzMwM9Z+BAVmKIIHJKVpZcBs4lEcAA9RNeTKtWbGAPYNaptDR92+PLzJjBvOT27WOyaPBgYNSonO/X8wKwalX71w0KcuGjIuEuHj2SBWCDBi7aKaWB0Y1mzZS1nNu3Z+lhCCInHDsmO7CLqYdyBPUTXktICMsowFm4UL+2+DrffMO8406dYqUUZ89mQ+s5Rd8o4MOHtV9HjjCZm5qqa/MI+zh2DLh1i03Hxrpop/RkrxuRkazjFm/SXbro1hwil3D4MLuMIyLIB9Bf6NpVnh4+nP4eZ/n3X6B/f3n+2WeBjAz5gcpZ9BWAdeoAdeuav+rUAapUYT1F//7kie7l8GjRQoVYgXeXQD2FrtSrpyzqvnMnlXYicgavFV62rIsigAESgF5O5cqyperGDXIncZbUVCBfPnk+IAAIDmajbzkhMGeb55AlS4C332aD2Q0bsmV79gBTpjB7Z0YG8M47wPvvswJ4hFfCO3aXjtZTx64rBgOz5q5ZIw8H//QTK0NEEM7g8gAQgPoFH6B+fXm6Qwdmz3EmZ52/M3YskDevPJ+WBnz0EbOTcRztn/UVgB99BHz9NdC2rbysZk2W7XDsWCYG8+VjdU9IAHot3LHbZRHAAHXsXkKTJiwYf/584KuvmDN3cLDerSJ8EV4r3CWlIjn0oOj11K/Pgn74SNHy5UDPnvq2yddo3pz5/4k0biwbXwDnrOr6CsAjR7TDRmNi2GcAGw7O6UA34VY8IgCpY9eFvHlZlZD589n866+z2pME4Qj378tJoCtVcuGOqZ/wegwGFrTAAwSffpoNBxcurG+7fAmxvJ4r0dcHsEoV8/jw9HS2rEoVNv/ff0DRovq0j7DJ48eyAHRrx07ohljb+aef5IAfgrCX3btZDWCDAejRw4U7pn7CJ6hfnyUs5tCAnnMcPWr5s6VLHd+fvgLw22+ZPbhkSSA+nr1KlmTLZsxg6/z7LzM7EF7JuXPAlStsWhQKOYae7L2G6tXlxKMAi8tKT9evPYTvwa1/JUuyKHOXoU4DQ/2E1zJ0qDy9di2QmalfW3yVtm1lg4vIn3+yJNGOoq8AbNyYfZuJE1n5gVq12HRiIktxDQDPP++ajIeEW+CpHcLDWXU/l0Edu1fx3HPy9D//AKtXkwgk7Mct/n8APSj6EFWrMtuOwQAcOAAsXqx3i3yPl15idrKkJHnZggWsFvCsWY7vT18BCABhYcCrr7LwlS+/BF55hS0jfAL+NFKmjAtTOwDUkXsZ+fKxepOczp2pVDdhP27xEwaon/AxWrRggWUAGwb2pTzeW7ZsQefOnVG8eHEYDAYsVY25DhgwAAaDQfFq166dYp3bt2+jb9++CA8PR2RkJF588UWkpKTY3YYPPmCR1PHxwO3bwG+/AS+8AMyZw0rEOYrnBaAjd42HDyn5mJfj8uLuHHqy9zqqVQOefFKeb94ccKDvIvyYy5fZe+nSLt4x9RM+Rf78cnXXPXuYb6iv8ODBA9SuXRvffvutxXXatWuHq1evml6/q4qp9+3bF8eOHcPatWuxfPlybNmyBS+//LJD7Zg+Hahdmw2SDhrE6rU7G1XteQH4/PNsIHvhQuDBA+11jh8H3n2XJYzav9+z7SMc4tIl9u6yGsAc6si9jqpVgc8/Z8MQnM8/1689hG+QmgpcvMima9Vy8c6pn/A5OnSQp0XfYm+nffv2mDRpErp3725xnZCQEERHR5teBQoUMH124sQJrFq1CjNnzkSjRo3QtGlTTJ8+HfPnz8cV7kivwbJl5q8ePVgAZp8+bOSNL3cUz6eBOX6cBXi8/z6rZ1KpElC8OJAnD3DnDnDyJDMrdO/OstDWrOnxJhL2IUlyx05P9v5BbCzz2Fizhv33H30EjBihTEZKECKHDwPXrrFp7trtMqif8DkaNWIFvw4eZEOXn34KREfr3SrXsGnTJkRFRaFAgQJo1aoVJk2ahEKFCgEAdu7cicjISNQXMmPHx8cjICAAu3fvtigsu3WzfLyff2YvgAlBRwNrPG8BDAoC3niDZTXcuZPZMGvUAEqUAFq2BH74gYWV/v47iT8v5/FjeWgnLs7FO6eO3GuJjZXLxGVmUnUQwjrc/y9fPjfc6EkA+iRimcmvvtKtGQCA+/fv4969e6ZXamqqU/tp164d5syZg/Xr1+PTTz/F5s2b0b59e2Rmq7KkpCRERUUptgkMDETBggWRJEZ1qMjKsu/lTFS1vomg69dX1okhfIqjR4F799h07dou3jl17F5Ny5by9KxZzDmZILTgbiKlS7s4UAzwrSgCwkSzZqz66549wGefscqvYpkzT1KtWjXF/Pjx4zFhwgSH99O7d2/TdM2aNVGrVi2UL18emzZtQmuX5khzHfpHARM+Cy/tU6QIc+51KdSxezUFCsgVQS5eBO7e1bU5hBfDBWDJkm7YOT0o+iQGAzB6tDy/cqV+bTl+/DiSk5NNrzFjxrhkv+XKlUPhwoVxNjsHUnR0NK5fv65YJyMjA7dv30a0FdM4r8JkD5cuAdu3278+CUDCaQ4eZO9uydpDHbvX07ixPKQ3e7a+bSG8F9EC6HKon/BZ6tVjmQQAYN48/f66sLAwhIeHm14hISEu2e/ly5dx69YtFCtWDAAQFxeHu3fvYr8Q2LphwwZkZWWhUaNGFvczYwYLwPvsM+DECfPPk5OBFStYSEW9eo5VaiIBSDgNf5hxufUPoI7cB6hQgbnvAsCwYRSwT2jDBaBLE8VzqJ/wWcqUkXPXrVoF7Niha3NskpKSgoSEBCQkJAAAEhMTkZCQgIsXLyIlJQWjRo3Crl27cP78eaxfvx5du3ZFhQoV0LZtWwBA1apV0a5dOwwaNAh79uzB9u3bMWTIEPTu3RvFixe3eNzNm1mgzNq1rL8NDwcqVmQhEiVLAoUKAQMHsgeso0eBLl3s/076+gASPosksTgeQM7r5PIDWJsndCcoiPnyrFvH5hs2ZE+oLq0JTfg0jx7JArBuXTccgPoJn8VgALp2ZZkEkpJYNGuDBkBwsN4t02bfvn14UkiEOmLECABA//79MWPGDBw+fBizZ8/G3bt3Ubx4cbRp0wYffvihwqI4b948DBkyBK1bt0ZAQAB69uyJadOm2Tx2ly7sdfMmsG0bcOECu7YKF2bXVd26QIAT5jwSgIRT/PcfewFuiuOhjt0n6NCBZfS/f5+5bb76KrBhg96tIryFAwfkslVWRrmch/oJn6ZUKZZGavRoJgBr12ZJQryRli1bQrJyfq1evdrmPgoWLIjffvvN6TYULmw9LYyj6C8A169nr+vXzR3/eYIbwuv49185t5eq2o1roI7cJ6hfnwm+uDggIwPYuJHlCGzTRu+WEd7AhQvytCoDhmugfsLnefJJNpKwdSvzc2vcmJKDeAp9fQA/+IDdKdavZ7bNO3eUL8Jr4SXgChZkPgguh57sfYbYWDYswWnb1rmcVETug/cTtWq5IQUMYG40oH7C54iNBcaOZdP//ceShV+9qm+b/AV9BeD337MkYrt3A0uXAkuWKF+E18KTu7q8BjCHOnKfwWBgw3tTpsjLRo7Urz2E98AFYNmybjoApYvyeQwGoGlT5kMMsIfHKVOAtDR92+UP6CsA09KYvZfwOTzesZMg9HpatJCnp05lEWmEf8OHgF1eK5xD/USuIDQUEGMhpkwhX2JPoK8AfOklIAcOkYR+cAug2wQgdeQ+R9268lAOwPJSEf6LJMkC0C05AAESgLmIhg0BMY5i8WL92uLtpKWxLBwZGTnbj74C8PFjVki0RQtg6FAWDiS+CK/k4UPZAujy4u4c8gH0OQICWD7A9u3Z/JEjzLuD8E8uX2bBYgDQpImbDkJDwLkGg4EFhPAo4B9/JF9iNQ8fAi++yMrmVa/OqjABTD598onj+9NXAB4+DNSpw+4cR4+y0hL8lZ1skfA+Dh9mnTvgptQOAAk+H6VgQSYCOa++yvJVEf7Htm1AejqrFOSWHIAAWQBzGUFBykTGLqrKlmsYMwY4dAjYtAnIk0deHh8PLFjg+P70TQOzcaOuhyec49Il9mSWLx9QooSbDkIWQJ+laVMmAqdOZc9xGzeyfIGEf8GtE2XKAC6qrmUOCcBcR5068vTnn7MBwo4ddWuOV7F0KRN6TzyhjKqvXh04d87x/XlPKbjLl2WzEuHVcP+/mBg3pXYAqCP3YfLmBZ57Trb6/PADjdT5I1wAuqUEHIdOrFxHoULK2uKdOskuR/7OjRva+TQfPHDuXqyvAMzKAiZOBCIimJqIiQEiI4EPP6QL24txewAIQBZAHyc2Fujfn00vWwasXKlvewjP49YawByyAOZKevRQRgXbUS3NL6hfH/jnH3mei76ZM1kyfkfRdwj4vfeAn35i3ovcS3jbNmDCBBYg8tFHujaP0MbtKWAAegDIBYjVQDp1Ak6fZkXMCf9AFwFI5Ary5wf+7/+YLejGDeDkSb1b5B18/DELsjt+nEUAf/01m96xA9i82fH96WsBnD2bSdfXXmOp4mvVAl5/nYX/zJqla9MIy7g9CTRAFsBcQNWqwKRJ8nzv3vQ3+gv37skCsEYNNx6ILIC5lqgo5u+2dCmwaJHerfEOmjZlQSAZGUDNmqzsZlQUsHMnG3VxFH0F4O3bQJUq5surVGGfEV7HpUuyBdCtObxJAOYK4uPl6QMHgBUr9GsL4TkuXgRu3WLTzZu78UAkAHM1Tz4JdO3K/Ir9nfR0YOBANuz744/Anj3M+jd3LhODzqCvAKxdG/jmG/Pl33zDPiO8jgMHgNRUFq7v1oLd1JHnCho2VOYC7NRJv7YQnuPQIfZeoAB7uQ0aAib8hKAg4M8/XbtPfX0AP/uMxXevWyd7MO7cycxMZCrwSrj1r0wZdkK6DbIA5goMBqBBA/bau5ct27nTOYdlwnfgFUDc6v8HkAWQ8Cu6dWND4sOHu2Z/+grAFi2YZ/i338penj16MD/A4sV1bRqhDReAbqvtyaGOPNdgMADTp8tVYxo3Bq5eBaKj9W0X4T7cXgOYI9YOA6jfIHI1FSuyxCnbtzOfv3z5lJ/zKir2oq8ABJjQo2hfn4F37G4NAAHIApjLqFOHBfdPmMDmy5dngQJGo46NItwGzwHodgGYlubmAxCE9/DTTyxT3v797CViMPiCADx8mIWFBQSwaWvUquWZNhF2wy2Abk/nQb49uYqQEOb/xwXgw4cssu///k/XZhFuQJKUVUA8fnCCyKXwDByuwvMCsE4dICmJxS7XqcNkq9ZFazBQJWgvIyVFFoBuqwHMIQtgriM2ltWwbNmSzffpQwIwN3LrljxS4ExqCoeIj2c+5BzqJwjCbjwvABMTgSJF5GnCZ9izB7hzh03Xq+fmg1FHnitp2hR45x2W+12SlIKQyB2cPctKUwUEeCDYh0YKCD9i4EDrn//8s2P783waGLGA7IULQIkSchk4/ipRQn6EJLwGrteLFgXCwtx8MLIA5kqMRpYQmvPHH/q1hXAPR46w92LF2NC/W6F+gvAj7txRvq5fBzZsABYvBu7edXx/+gaBPPkkCwdUVzdOTmaf0RCwV+GREnAc6shzLbVrA88/D/z6KzBjBssE1bGj3q3yMjIygFWrWMh0wYJ6t8YhPBYAApAAJPyKJUvMl2VlsWJq5cs7vj99E0FLkmwNFLl1yzy+2QZbtmxB586dUbx4cRgMBixdutTq+ps2bYLBYDB7JSUlOXRcf2L5cvZerJgHDuYLHfvOncALL7DHMMIhXnlFnv7hB5blnhB47z2gc2egUCG9W+IwXAC6PQcg4J39AkF4kIAAYMQI4KuvHN9WHwtgjx7s3WAABgxQjhNkZrLoYAfrjD148AC1a9fGwIED0YPv3w5OnTqF8PBw03yU2hpJmOB9baAnzhpfEID8HF2yxDn7ux8TF8dSFkybBvz9Nytn9MILerfKi/jsM71b4DRXr7L3EiU8cDBf6CcIws2cO8cGDRxFHwEYEcHeJYk5k4WGyp8FB7OMsYMGObTL9u3bo3379g43JSoqCpGRkQ5v54+kpLD3Zs08cDBf6siTk/Vugc8REMCGgadNY/MDB7JnQa0BAcK3+O8/9u6RXP4kAAk/YsQI5bwksQeuf/4B+vd3fH/6CMBffmHvZcoAI0c6PNzrSurUqYPU1FTUqFEDEyZMQJMmTSyum5qaitTUVNP8/fv3PdFEr+DKFfaUAbi5uDuHSjzleurXB4YOZVVCAGDtWqBNG33bROSM1FSW5QsAqlf3wAGpXyD8iIMHlfMBASypypQptiOEtdA3CGT8eN0OXaxYMXz//feoX78+UlNTMXPmTLRs2RK7d+9GPQs5TiZPnowPPvjAwy31DhIS5OkqVTxwQOrY/YJ+/WQB+O67QOvWVB3El9m5E7h9m003aOCBA/qSBfDvv4EuXVg6BY9nyCZyAxs3unZ/+gaBAKwcQK9ebNi3Xj3ly41UrlwZr7zyCmJjY9G4cWP8/PPPaNy4Mb6y4kk5ZswYJCcnm17Hjx93axu9iUuX5Gm3p3YAfKtjJ5wmNhYYM4ZN79+vzOnr11StqncLnIJn7ypSxEPxK77UL3Tpwt49kkaByI08esSqKHEuXACmTgXWrHFuf/oKwGnTmOd30aLMttmwIes1/v0XcMKfL6c0bNgQZ8+etfh5SEgIwsPDTa8wtyfD8x4uX2bvDsbmOI+3d+z8B+FQTVKnMBiA7t3lee4d4vcIgWm+hEf9/wB6UCT8iq5dgTlz2PTdu0wyTZnCls+Y4fj+9BWA330H/O9/bAwoOBgYPZo5Ar3xhi6O9QkJCSjmkRwnvodHUzsA3t+x37unnKeqNk7D8wICwIIF5j8t4TtwC6BHcgAC5CtM+BUHDshBmIsWAdHR7JqbM0cOqHMEfQXgxYuySSk0FOBBFc8/D/z+u0O7SklJQUJCAhKyndUSExORkJCAi9nKZcyYMejXr59p/alTp+Kvv/7C2bNncfToUQwbNgwbNmzA4MGDc/y1ciN8CFg3Aeht/P23cp4nSSQcJjgYePFFeX7UKP3a4pX4ULkz3k+ULu2hA3p7P0EQLuThQ7kK15o1LKNeQADzoHOmeJq+AjA6WvYYLl0a2LWLTScmOnxh79u3D3Xr1kXdunUBACNGjEDdunUxbtw4AMDVq1dNYhAA0tLS8NZbb6FmzZpo0aIFDh06hHXr1qF169Y5/165DEmSRzxLlvTgQa3N68077yjn1eFZhEPUrcvyHgNsUMCHNI972L1bnvaRikiZmSxbAEBDwAThDipUAJYuZQ9aq1fLWROuX3fOa0TfKOBWrYBly1jv/8ILwPDhzK65b5+cLNpOWrZsCcnKxT9r1izF/OjRozF69GhnWu13XLkiP9nHx3vooL6mALiDN+EU4eHAkCGyYfXXX53La5UrycwEgoL0boVN0tLkfqJGDQ8d1BcFoEfCo4ncyLhxwLPPMqnUujVLqA8wa2C27csh9BWA4qP+4MEsAGTHDnYzFWtFEbpy5Ajw+DFLz1GxoocO6msdO09uTjhN48asykxGBksKTQIwG2dS/OvAiRPygE7Dhh46qLf3C1r4Yps9zdixwKRJrPqAjnmCvY2nnwaaNmXJn2vXlpe3bq0MprMX/YaAMzLYHyzW3u3dm3kyDh3KHIMIr4A/1UdHe/Bv8bVO0k/zQ7qS/PmZFZCzY4d+bdEdsXf3EQF47Bh7L1iQJXbwCL72oAj4Rhv1ZtIk9u4xU7LvEB3NrH0BASxgbulS5hfoTH5e/QRgYCCrd+kjnZs/w10nPebYDfhex75zp94tyBX07StPO5PZPlfiI30k7yc8FgEM+F4/Afiee4uenD+vdwu8il69gG++YdOPHrFqSr16AbVqAX/+6fj+9A0Cad0a2LxZ1yYQtvF4AAjgmx07kWNiY+XpU6eYc7NfIooEHxGAHk8BA/hmv6AOGJMklhDTYADS0/VpE29Hjx5yaR7C69iyRU4Ds2QJ+8vu3mUDp9xo6gj6CsD27Vk05ciRLO3LsmXKF+EVeDwFDODdHbs3t83HMRhYdBtn8mT92pIjMjKAiROVNRQd3Z7jIxWHuACkkQIHEa1cPXvq1gx89x1TFW+84Zu/ox+QnMxcLABg1Sp2uuTNC3TsCJw54/j+9A0Cef119v7ll+afGQw+k/4gN5OZqUNuL8C7E7zq+ZTuB7RqBTRqxDKhTJ0KtGsHtG2rd6s0OHuWmSi1yuMMHsyC3MaPd+7cFQWgR2qq5RzqJ5zkwQN5Wp1f1JPMny9PHzzo9nKshOOUKsW8jQoWZAKQ/2V37gB58ji+P30tgFlZll8k/ryCR4/kjr1yZQ8e2Jv9ZFJT9W5BriYwEPjkE3m+XTtWJ9jrqFgRaNKEla5U87//5WzfPmYBTEmRXUU8qht8UfCp8Zayf9u2ydPvvqtfOwiLDBvG/KRLlgSKFQNatmTLt2wBatZ0fH/6CkCRx4/1bgGhwcGDTAQGBLDwc5eQnm47bbk3D+2QAHQ7cXFASIg8P3q0FxtenRl7sYUoAH0gEnL/frmQkzP5yJzGm/sJezl0SO8WmLN1q94tYHgs75hv8PrrzAL488/A9u3svgwA5cr5og9gZibw4YdAiRIsBwR/kh47FvjpJ12bRjBOnWLvxYqxv8glBAcDZcoAv/xieR1fsAAG6utBkZsJCQHWr5fnN2wAfvzRgR3s3s2CzNx1c+VqB5ArGLkSUQD6wGgIjwAuVAiIjPTggX1R8KlxZuzO3eQ0kaOr+u+oKNfsJxdRvz7z+fvvP7mb6NiRDUY4ir4C8KOPgFmzWDoYMcFcjRrAzJm6NYuQ4cO/bokAtpbnw5t9e7gApFyVbqVJE2DvXnl+8GDt0VZNnniCqcannnJL2xS4o3ykKPp8QAD+9x97L1HCwwf2FQugNUHEvfq9iU2bnN+2f39WNcChJzbCHh4+ZHXT8+YFqleXH7yGDlW6zdiLvgJwzhzmK9O3LzthOLVrAydP6tcuwoRbI4C7dbP8mTdbAPljFwlAt1O3rnIw4PvvHdzBjRsubY8J0UIn9l3u2D8JQMv4igC0lspH9G0oX979bbGH0FDnt50zh72//LJz24v/ocHgfDtyIWPGsEGNTZuUhuP4eGDBAsf3p68A/O8/Vt1YTVaWFzv8+BduFYDWBJQ3WwB5Z673EPBrr7EO0hdLZqSns3pGNjAa2XNCu3Zsfv787GCD5GTW4z186NZmWsRWgtq3387Z/sX+zwfyAHIB6NFcoYB39QvWsFcAnjvn/rbYw6NH+h3bBx549GLpUpYIumlTpTauXt25U0dfAVitmraz6aJFHvYkJrTIynKzANy3z/rBvZV799j7zZv6toObw5xx/vA0S5eyHmvhQjYfHAwUL27XUFPBguzJNyKCnY9z5wIZz/ZjpSOHDnVrsy0i1jrTOlcDcti1ij6GPnBDJAugDdT/oRhIxvsTgkHGH4vcuKHtFvnggXPGUn0F4LhxrPjnp5+yTnTxYmDQIOYbOG6crk0jlKkdnKkzaBNrFiBv7thfeknvFvgevFJ5r17K5U8+adfmzZoB//d/bHrMGGDLiuyb5s8/u6iB2aSk2LeerUodrhy68nIBKEmyAPRoqijAu0cKRNTnyJ078nRammfb4u2Iv5WYmoZA/frAP//I87ybmTmTZU5wFH0FYNeuLPHlunVAvnxM9J04wZZ5wnmbsMqhQ/KTBS8/41KeftryZ97csYsioUcP9k6Fa92KwSALQAAYBDcEic2fz6qq2yPeRFHGb1jNmrEeGnDtEJqXC8Dbt4GkJDbNv77H8KZ+wRrq6KXbt+XpW7c82xZ7eOYZ/Y7tpS4PW7ZsQefOnVG8eHEYDAYsXbpU8bkkSRg3bhyKFSuG0NBQxMfH44wqRdTt27fRt29fhIeHIzIyEi+++CJS7H3oBPDxxyxF42uvsZ/p66+BNm1YQo2PPnL8O+mfB7BZM2DtWpZR/+FDpvjbtNG7VQSA06fZe3S0C1PAiFgbJvPmIWDxx+BO294YyZfLqFNHnv4X5bEKLu4n+vSxf121BfD2bdZ37d/PbvZiLhRHRYp6fS8XgNu2sSaGhLB8ZB7Fm0cKRNTVXEQB6Gy5QHfCXTX0wEsF4IMHD1C7dm18++23mp9/9tlnmDZtGr7//nvs3r0b+fLlQ9u2bfFYyHHct29fHDt2DGvXrsXy5cuxZcsWvOxAsEzTpswwk5HBEj+vWcOGhHfuVNZRtxf9BSDhtfDhX7fVALZmafFmC6AYWcoDQby003IJp06xVPOe5NEjVg+cl8nauBEF68Zg5+fykFB7rMYtFJC3qVyZnVPWIn9ddR6p07SI/qz37inPbUcfZtSCz8vPLT78W7x4zl0fHcZXBOCvvyrnRavfE0/I095SFcQav/zClL67HtJFH8Cc5iN0Ie3bt8ekSZPQnbuzCEiShKlTp+L9999H165dUatWLcyZMwdXrlwxWQpPnDiBVatWYebMmWjUqBGaNm2K6dOnY/78+bhy5YrN46ens4Emg4Fl2NmzhxUJmjvXuSoggB4CsEABZi2x50XoCs8x5BUC0JvwBgHozO+TlcXCxZo3d2y7KlWAFi1kk7C7EINqBg9mLiIDBrD5gQOBixfRaFQzDBkir1YYgiWFt8+S+8iSJUyhlC2b87aqLYAREfL8+vVKJeTouaH+b73cAqhbAAjgvYJPjfo/FAWgKHicDQhJTfXcbzFwIJCYqAyEciXi9bJnj3uOIXD//n3cu3fP9Ep1otJTYmIikpKSEB8fb1oWERGBRo0aYefOnQCAnTt3IjIyEvUFP4n4+HgEBARg9+7dNo8RFAT8+afDTbOK5/NYTJ3q8UMSzuHWCGDAugD05id7sS1cAHo6ck10HI+JsW+b/fvlurKPHjme62vqVOC77xzbxl4GDpQrw0iSPL1oEXu/dg0AYAArFPTNN/Kmq1bJaWIAWK7+wf01tVK4OCqy1AIwb155/oknlBZTR/etXp8EoGW8eaRAJDlZOS8OAauDQNLT2d3eXhITmUXuuefMLY3uxF1ZEDz8MF2tWjXF/Pjx4zFhwgSH9pGU7QRbVCWKixYtavosKSkJUaoQ3sDAQBQsWNC0ji26dWMJFYYPd6h5FvG8AOzf3+OHJJzD7bm9fNUCKKKXBVAccrTXWi4OMyQl2WcJE4XtjBmuEYBagsZaWUBA8ftGRQGr0BbtsBoA0L49cGvJFph+hfh4Flhmi2vXWDqaAgWUJUfsQR0EIloN0tOV57aj58bdu5aP5YXwkQKP5wAEvPtBUUT9n1oTgJmZjgnAt95i73Pnul8AOhqxnJnpeKJ0D/elx48fRwnh6SVELELuZVSsCEycyOoAx8ay2FmRN95wbH/6FzM9d451/ufOsZCWqChg5UqgdGk2XEXowqNHsg+g21Iy+qoPoIheAlC0ctkrEMSINLG9p0+z4RxxGJMjCpvwcPY/jBnDxOMrrzjWZo4zyZtVFtY2WIOR+AxfYDQA4LnuKVjBP9QSf0ePKufv32fRTQD7TuohGEmy//zMyFDeGNPSlEPAjgq469eV817sAyhJHvAVttUAX0DM3QFYF4D37ztWH3jJEufb5Shifkp7og7S0x0XgOK17oGTKiwsDOE59L2Mzu5Lrl27hmLFipmWX7t2DXWyo9eio6NxXXVtZ2Rk4Pbt26btbfHTTyy+bP9+9hIxGBwXgPoGgWzezLwXd+9mOQB5OPShQ8D48bo2zd9JSJDdURo0cNNByALoPKLVz96KJGLFEJ6AOSGBBU+IUasi4s3p3j1g1y6Wt/PVV+1vqxusNAYAz2GeaX4N2uAUKrIZLYtohw7K+c2b5enUVHMvaluiTW0BFP9/tQB09NxQ+1Z5sQXw6lVZALZooUMDfMUCqD4nRQF46pTyMx745CyLFrGxQne4pYjtbtTI/HO1mHUmHZL6WvIBypYti+joaKxfv9607N69e9i9ezfishP0xcXF4e7du9gvKLcNGzYgKysLjbR+Sw0SEy2/7K6TLqCvAHznHWDSJJYGRiwL1qoVu9EQusFPpkKFWGo0t5AbLIB8qMbTAlC8Sdjb0b/7rjzNfQFF867a8gSYd8B//SVP2ytMxPYFBrpM3NfGYfwC5lKSiUD8H/5AFgxKqyWndGnlvGjJSE8HDh+23GYtxO+Qman8/9XHz4l/oTPbe5BTp9g93mBwU7J4W/iKAFSLPDEI5McflZ85MvyrxTPPsOs0J1VyLPXNYgJrrREDta+jM/2iuI0XVQVJSUlBQkICErLT9iQmJiIhIQEXL16EwWDAsGHDMGnSJCxbtgxHjhxBv379ULx4cXTLrnlftWpVtGvXDoMGDcKePXuwfft2DBkyBL1790bx4sVtHn/XLuC994BRo5jfsyvQVwAeOSJXCBCJitK/zJafw93F7Dgv3YO3duRq9AoCEZOHHjli3zaisNCKlN2+3XyZWgCKPkb2HleMbMzIcE7QaN1sADyB3abYjkOog2XozHpINervpk7jIjy5m9ppDfUQsNpqYatSCMD8Di9cMF+u/n3U/mNeBH9QLFrUsVFLl+Er/YQa0ZImDBkCyNnDpPjw8cMP1te9c4clb/z0U/PPJEn7OhXbrSVU1QLQmWtd3MaLLID79u1D3bp1UTf7oXnEiBGoW7cuxmVXLRs9ejSGDh2Kl19+GQ0aNEBKSgpWrVqFPMKFMW/ePFSpUgWtW7dGhw4d0LRpU/zvf/+zeexFi1jFz6+/ZlU/OnYEvvgi599JXwEYGaldDuzgQZ1CyggOF4Dqvsml5AYLoF5DwKIFy17E35Q7OhcuLC9T+8kB5h2wODxpR+oCAMohamctgBbOlSo4pdB73fGX9u4nT1bOi4I9PR3o21f5ubUyhYD5ELC4v8uXtQXgzz+zxOEnTzILbMOGQJky5vtWn0vvv2+9LTrCfybdumtf6SfUiELq2WeVn+XkYVLcry0KFmTX9zvvaH+u1Q5x/1oXmqstgF4kAFu2bAlJksxes2bNAgAYDAZMnDgRSUlJePz4MdatW4dKlSop9lGwYEH89ttvuH//PpKTk/Hzzz8jvx1VFiZPZlVyk5OZbp80iVUFySn6CsDevYG332YRiQYDO6G2bwdGjgT69dO1af4O79jdagH0VR9A7s/TpIl1AXjtmvssg/aWD3r4UDbTiFYw3i4xEtieIeA335Sn7a13qxZLzlgFrByrcmVgHuQqHp9t1SiKKaZlCQlRfq/0dPPzzVanbM0COG2a+RAxALz4Ivsv6tZVDqXbqvzhxZkTuP+fbgLQVwSfGkt5AIGcPUxmp0tyCVriSxSAWtexPRZASQK6dGFZBbQQv78XB0B5klOnmCzi8TRvvcVsAFpdtiPoKwA//pg5jpQqxW5o1aqxJLWNG3v1U68/wC2A9qaYczne/GTfqRN779bNsgDcsYNFmYq+ra5E9AG0ZqbNl49ZnXbvBsSnUX7TEW8Yaj8lgNUYEhHH+ex101DfBMRhKu6DKOYkdPC/LlAAaAFZ4I3Z2AZ7oCpKu3KlPJ2VpXROT0839znWEu537jAh+skn1oNA7tyxPgT8+DFQo4Y8r07+q16/cmXztngJbs8Vagtf8QFUI16/6v87Jw+NYo7LnEbv2bIAaokzeyyAEyYAf/8NvP669nHFaysry7uNAR7i4UNlkZjgYNYVO1BGWBN9BWBwMHOA/fdfYPlylsfo5EnmZ+Ro6DjhMh49kgVg7dpuPJCvDgHzJ+PgYMsCsEkTeVrLz9UWt2+z1BGWnoDFK9+SRU38zZ54QpmsmHfur70mL1u71nwf6ju7pafzXbuUUcaWtgGYAOLw6DdeU1lrfcBmjbESuILXIWeHfh8fQXHGjB0rT6enKwVgRoa5I76W9YNbfseMsR4E8uKL2hZAEbF/s5X42YuDQNyWAiYlxVxMaOGrAlBELbQciZwVgzIApWXR0dyWamxZALWuU54U0to6EyfK01oBW64UxLmImTPZ4AJ/ZWQAs2YplzmK/nkAAdZ76PYISai5dEkeAlYlSfcc3tyRawlAdSfVoIHcAWfXgnQIXjx+yBBg+nR2tYu+dKIPIO8wU1OZ+Hj1VVY1XBSJ+fIphQRvr2hp1xrvV1cLEffBS8qlpwPZqQ5w+zYzyVnaBlDeWHjbxf9b66Zha7i5ShWMOvkFbqIw/kBvrEUbbERLtMIm9rn6gVL8bdLT2e8g/hbp6ezmmj+/trO7tSHgiAjl99G6kYq/yYULyjQh6t/LSy0gaWnyg6KztUg1kSQ59cDDh9Yr1nhzP2EvahE0c6b9NXDnz1fOO5K0ddAg+cFH63d0ZgiYp5eyto7I3bvmaY+0BKAXJ2f2BKVLmz+jRkcrY/J8Lw9gz57aEUiffcZC2QlduHRJztWrzp7hMbzZArh4MXs/fdpyGpjnn3fNsb75htXDDApSiiAtC2CePMC8eUCzZmxeDGR48EA7vYLYQX/1FXu3Zr3SSnciDuW8/bb5d7A2BMw/E4+prqQB2BaApUujDC5giGAFHI3PkYYgeZ8i6jQw6vMrMZGJMktD+NaGgD/8UPl9tFJaie1R32jV55KX+kHdvCl7Abh0pED8bRMTra+bGyyAc+Yo5219Z5HBg5XzP//sXBu0zjFLbhDWthFHFMR1jh3TTgCfHUGrQB31ThZAnD9vPQegb+YB3LLFPEErwGo7iU7bhEfhuqFQIcfLxdrE3g6a30BtDP3pyuHDli2ArvT900oSamsIOCvL3OqlZQEU4RUxjEa55Js1McKH6JYvl5ft3y9X0ahYUXsfogDkn6ktao4KwOz9NMRetC/F0tPsR31shmClFBH97tLTlUPEgGX/JI41CyCgFJh165r/R+LNUJ3ixkeGgLm7WUiIi4PFRAFgq2qMNz8o2os6SbQ4jGuLevWsz9uLlrXPmSFg9ThkZiarIV6jhnndMgDQSoGyYIFyngSg29D37pqSon2jDAoyd4wmPIZbcwCKNzN7fAC5APTGjr1mTVlkqW/SzmTAdwRRAGp1xA8fAmfPKpfZyq+Vns58BQHZsrBnj3IdtaULALp2Va4zcyZ7P3tWO5+YlgVQDEDREoC2vJ2zbxIhSMN7Bjk/QhusY4ewJtDS081dUG7csH48axZAQPkds7LM03OIN/kDB5Sf+YgF8PRp9l6kiP0B4XYhPvRZqlDD8cZ+wVHUJVS4WTUzk/nlWrsXquuBWciXaRMtkaW1TDxvtR5M1AFLGRnA8OGOtSU7cbLVdhAuQV8BWLOmudoHmF+Dbs5nBLcAuiUHoL3+TL5gAZw6VbYAqjtDMdCBk5nJijny0Eln4Dc8WxbAf/81FzG2MuxrLdu40fI+eN5AMeFsiRJsGFrcpzUBqCVutASgeB5o3fQFgfXExT/wBqaa5r/8EtYtgBkZ5kP2ooDPyjLPu6geJrclctXWWFGAqxNq+4gF8L//2HtUlIt3LJ7btvqL3DAErP5/uch6912gTRtlqiZbqC2mv/1m33Za1/62bebLbFkA1WLW3nM3JUW+DkTHNkvHIVyCvnfXsWOZFaF/f2D2bPbq1w/46CPzIRnCY5AF0E4KFJBv7OpOit8dRVq0AF56yXHHSvFhiN8ctYJARMLCWKoFzujR2hbA//s/eZlWZz1woDzdvLntzrhbN6C+kILlyhXrUcBax9QSgOI+tJI0HztmmjSWKY3n8Ssq4yQA9tX3/qd6muGl8Hgb1G0UE9tlZppbU20NAau/o/pz8UatdpxXr+ulApDnIHO5ABRTmfiDANQ6NzIymC884FhyZ7UAVCc4t3RcrRGBnTtZxSAx47CtIBBb/qyWCAsDatViKZbqq1I4kQXQbegrADt3ZhGSZ88yn5u33mJ5BdatMzcDEx7DrUmg7bUA8o7c29IBiTeYqlUtWwC/kYMRTOlX1OXIuK+cwWD9xiX69Zw7x95FK4kksd+V5ycEWKcpzt+7p+0DKAoVrc5aHZ1rS4ykpwOtW8vzDx9at45pFb7XEoDiUKCt4dnYWNTHAfyAl02LfjjaVLmOOFSWlWV+kxGjMNPTWbJ6EVEQav0u4ndMTDTfv3ijVgeJWAu88SK4IbtkSRfvWBx6sFcAevNIgS20rinRr9YRHEkMp06GrubOHXYvfu89eZnYp/Dzctgwdr1u3mwuANXfzZZAHzOG9asiXnr+5wb0v2o6dmQ3xgcPmO/Dhg3mZmTCo3ALoFsy8zg7BOwtT/bijX3gQMs+gC1bytOWhNW+ffL81q2WjymaWPiwq9rHMDPTPLJUvCl+/732E79obdFqp/omYaszTk9XtuP+fXPr2cGD8rRWVXMtAShW5tASgDxtDt8eQDNsw5PYAAD46XQz/AMh4EwUnloWOrWFVS0AxaFxWz6AL7xg3QKoxkcsgNzI7XIBKJ4/tr67t/YTthArXblS4Fgq66aF+DtrXVMrVpgvE/19MzKYGfjrr9l8y5bmEbxa53KXLtbbpb5HkAVQwblzLGNVnz6yFX7lSsUgiN3oLwDv3mVO4+++K5uXDxzQHkIj3M69e7IFkMcDuBR1h75li3bEN+8EvM0CKHZwcXGWh4B5BCyg3YE9eqT8bmq/FxExvt9Sepnbt5XWvPXrgW+/Va6jNQR86JC8zFYqCC2ho77hpqUpt8mXz9yZVB1YokZLAIoi8swZ8200SmsFQMJHeNe0uBP+wQNkW2PVPpTq/2jdOmV71AKwRw/l59aGgPk6ImrfShEfsABmZMhJoLWC1HO8c44oBrQeHtUWQF8RgGJZB63/t0IF5byt2tTW9mUJ8ZwXc4xqwQWreG5mZponmx4xQjmvPpfT04Fly+R5dRBorVra2xAAmJG1Zk2WrGHxYrkbO3QIGD/e8f3pKwAPH2blqT79FPj8c/nmungxMwUTHufQIdk44ZYKVGIn/ugRs/a2aGE+FOitT/Zi6bSoKMtDwKIFiEfCilYq9fflkbNa2JNIOk8e1jtwfvlFWcatWTPbaWCcsQCq/ZPUFsDZs80LVnbsKE9rJa5VC0BHbwjC+g2xF8OGyR/9iWzhphaA6u8lmr/T0sxrrIq/y61b1v9/rTaLZfTEsnCAT1gAjx6VNXGtWi7euZYA/OQT9sD0xx/KdXm/4NIwZA9gy8qpPl+mTmXvCxYog65c1QZb1xR/QFVXAlI/zKnPe/W5rB4iTktT9u116pgLfS98ANKLd94BJk1iweGidm7VSjvdqC30FYAjRgADBrAnerHGaIcOlAdQJy5cYO9uyQEIKDs7UQSpfVfUFkBvEYBim8UgEGvVLgCmqkUr1ZUrzErnKtTHv36dZfrnbN1qOw2MMxZAMZiCry/+lykp5iXmxHbky2f+36oFoPrmZCvqQGijEVkYMgSokp85rPXHrziPGOX3z8w0F+CiANy3z7oAXLjQfOjLlgVQ3J/aqusDUcCJiewSzZPHDdkCxN+KW2e5QUAMWgJ81wIontNa0bZqIbV7N/vBe/dmlX7On9fONOAI4jmsta82bcyXqQWgGCylhT1l3UTrekYGDQFb4cgR7cqiUVH2l2YX0VcA7t0LvPKK+fISJcyHXAiP4NYIYMDxIBBvc+4WffWMRsu1gNUCS53d//p1529Wlqx3osn26lXzaGNbUX+2BODZs+brREcr59PSgCVL5PmnnmKJ3UXEtCeWOnxRAKalKctFiZHJgLaAFChfHvik8i+m+bI4Lw8FA9oCS/SxrFrVXACqb9DiULrW59ZuYmKUpVZ7vNACwod/S5Rwg/FN/K2ysqwLHV+zAFqqHCTSsSOz4Its3iw/nQPMReqtt3LWFvF3Fn1SLT3UAubi3FZGA60H4wYNlMvElExBQTQEbIXISG1vgIMHbWtxLfS9u4aEaCe5PH2aZRclPI5bcwAC5gl0OWoR4K1DwE2aKOctdZZqAVC4sHL+o4/M/XwAZjFT38zUalwMouCcPKlMpgwoLW9t2+Z8CFgr2lUtJNPTlUFcq1eb/7eiGNayKmpZAMXjqgNgsrLkSGsL36NFhFKgbYPwP2rd6ETRkZVl/kCq/t47dljeXqtN4m/EK6pYWtcLLYBcALo8AAQw7xe0Hhq3bWMplfj/4G39BCBH+IvVMbhVXrz+1Bbtf/7RrpAh+gwXKiRX63EWsQ3iOchdVSxF6IvT6nX697e8Pj+meO0UKaKsEBIUREPAVujdm1XbTEpip1ZWFouhHTlSGVdkL/oKwC5dgIkT5RPRYAAuXmTfsGdPXZvmr7jdAmjJCqW+yL01CMSSnV1dvknL10XkxAltK9yUKebL+J/CCQszX0craEp0o1CLt7Q0+5601cvs8ekRbwoNG5pvI/r9ZWSYH0Mt+NLSrI9v3Llj+cEim8iTu7ANjU3z7bAGj5FdYD4ry7y/EUVmZqZtAah2otf6Tta2F/EhC6DbBaBWkm2A+bT+9JM8722uIiJvvilPc0vx77/Ly0TfYGuIv8vJk0BMjONtuXhRTkclnpMnTsjT/GFVy6ns5El5OjPTPJpdbRHUemBU9/vqBPVqAZiQYN4OP+Xjj4EqVZiHSkoKSxHbvDnQuDGLDHYUfQXglCnsW0RFyQEBFSqwG9xHH+naNH/l6hXWgRYrBus3KYD5bqpTfNhCjOAUExWrOwpvtQCqg5MsReepf7vVq5Xz4eHmVkLAPr9Atd8dYJ47CwDatZOn1R1tWpq5lerjj5lfI0eSlNsEBZmLEbV/35dfKi0eKSnWU6RoCUCtm4I1eOJccXs1V66gEfagGeRAmY+R/V9qBYGIv83580xkWvoOWthKiGttey+3AEqSLADLlXPDAdRDwPZ8f18ZAtYa8bL3/xXPyWLFzCNuLcFFmiQx0di0KbNYi+foBx/I01r9C0cU3VoWQFsPjOnp5te/+lpX/x5q/1o/RZLYc+i0aSwxxPLlwNy5TJP/+qtzthJ9BWBEBLuB/P03+1ZDhrDcQ5s3axeOJlxLZiaLuN6yBVi5ElmGAPy3jSUarrRwEhuib99eWwg+eMAiuCtWdMxCYSm5oK0hYG9BfAIGlOleRNS/iTp1ydmz2nm2rOUD5JQsyRKni/z2m7k/nigK1RbA9HTzEmSAMkGyWpzly2f+vbTyhz33nDz93XfWh8ePHtW+iahzGlojJkZ5DHV91GwCkYkvId80P8R43EW4tpVJtACq/f+02lS+vHJe/I6BgTmzAHqZAExNlQVg9eou3PGECSzKV7zh2ysAve1B0RJaQyv8+1mr2gGYu37w610rb67ocsKt16KLyKuvOu5bJ0nA0KHyfEaGeRUb9XmtftDRsgCqr3X1vaBOHcfamUuRJGYfu3yZ3UY7dAB69bJ8C7IH77i7Nm3KbmijRwPx8Xq3xvu4fl2ZC85VfPEFG/pq0QLo0AH3EIarYB1U/bPz2TqrVjEhqIZXggeUwwe2sNSZW8oY7+0dO3/sUg8Bqv8vrfq/zl656enKoAiAJW209vStFoBHjpj7JZYpo7SkqJ/O7941F4Bqn8jmzZVCtGlT2znyxCEyQHtY2UWuAHVwCOMwwTQ/BW8xKy5vI8+tIApArXxI6jaqv5O1mxygTMCtRssn0hl4hRgXc+GC7HFQr06WuXXUGf76i1mh/u//lG4QloaA1XhbP6EVQQswJy6AXRcc/v34eWZJ8BQsKE+Lwljr2hDH5nnfIyae1+ovOGLbRO7fVxpmMjPNH97UIlUrTZSjQ8BayeL9kIAAdstQexvlaJ+u25WDZGUBP//MSsvUqMGyG3bpAsyZ4z0XsbdQtCizMKjzqeUUVdb4E6iKR9nRkRWgGtqtWlX2RTt8WJnMUx18YA1LNzNLFkBv8wFUYykIRD00rCUAxaFSzksv2T7mo0fmv2NEhGMCUG3JBMwfvtSWOPU+AWXJO4DdeMR1Spa0HSCzeLH1z7Xy7DlJIDLxLH5HKVwEAEzCOOx6d5m8f577SJ0mRo36WlQHpqgFotpSaq1kl6ssgE2aMHcaF/sQJiayv8hoBMq82ZUJk8OH5RX4d58+nR1frKpiCbH0pyhUfHUIWO0aweEP02ISN2vnnoj4O/LcooB2EmfRT5j3PeKIQ3y8ZQFYpoz2crVYy8hg920RdYJzLcu3OreoOh+h+v8Wh539nE8+AUaNkgtC5RR9BKAkMbH30kvsUbJmTTaWcOECywuoleiGUPrMuQKxvBaAs2BRqYVxA3mgugmfPMnizN95B6hdmw3XcJYuBX780TwVhogksQv/00/lZeJwoyUBxZ/sZ8/2zgcD0fncWvv4mBnnq6+Ukasce6yCP/ygLczU/kXqQApbARxqq6VW4mf1/Pr1Sovf4cPK46ammm9jK2GVWgBOnmx9fTVaw2yCRaQyTmMu5OG2uNRNyEpX3YRFtASUmHQbMA/UUX8Ha47s6kgKR30Atax8mZksEfjDhy7P1MxP5ej8KQhanV2zdvp09n7uHBM5BgPwxhtM6ForFWLrms5tQ8BaaaPUAjA1VS4lKYZ2ijkQs7LkfWg9JIsPnDx9jHh9p6ZaFppz52ovf/zYPIG1rWtTbRlXWwAB5cOQlgWQMNGvH8u9Xbs2O10KFlS+HEUfAThrFvM7W7+emYx//x2YP58JiHXrWD3gOXN0aZrXIXZ+rsrMzJ2CVVaIK9nDv8VxRb2FjCjgOPPmAS+/bN1XIyCA3RjmzZOXiQJIvOh//lnOMC92bosWWd6/XohP32KnrvYJU1sAT5/WjnS3x+J59aq5ANTKlaYO+lAHmKj3sWGD8gaqNXSptnQBygjZo0eVx50/31zQqFOmqFGLJ0eHgNQ3mOHDlQ8bAOKwy1QnGAA+O98L95FfmZCek5FhPqSnzmWmPqb6JmatrI764cCRKOCoKHbOqH2xLEV4ugBTDsBkwQzBzz+t1EZax79xg/VDQUHMkckSXbvaJwD5b/Tbb7bX1RN7BGBamvw7Vqpk9qAOwHwIWH3eii4GvO/ZvVtepi7ZyClf3jzZNufmTdvBVmq0LOPWMiSQALTK1KksQ9DPP7Py7l99pXw5ij4C8PffWe3fJ580/6xVK2ZlEoWCP8ND9gGWBTKnfP898+PQSBrE/f+Kwc66k1oYDHKeN1tP4+pUG5wXX5SnxSAQS8MqeiIKNvE72OrEZszQzuNlT6c6aJD5erZydqWmmgsvLQuAOlDEnuNYO+6FC+Y3cFuBPWox66hVR/29pk41+z+CkIHPMMo0P+b8K9iFRtoPWZmZ5iXrRBcIe7DlviG2z5EhYD60rO5L1VZWW4E0DsD9/0pCEK7375uXabPE1KlMuObLx77bwoWW13382DxPohbcMernn+1rgzuxdr5qlY7k03xY+NIlpbjT8sEWh4CNRuvJsrXcT1JTtQXg9evmw7qctWttl7BToyUArUXEaw0BEyb697f+chR9BODhw8oUFWrat7c+nJjbkSRmAb1yRTnY7wpfntdeY++8tqPAFbDsz1YtgPZQrhwbEgoIYILwwAHt9dTRflqIvj3qnFPegGgBtJGLToFWovMHD6xH5vGhTUkyX0/ti6duQ1qasjQcYL6Pzp2V29y6ZX5jsSUA27SxPWxsSxy7ssSVlWPWwSGMxiem+TZYh4wQjewDt26Z+7k2bmy+njXGjrX+uTg8px7ac+a6VwshV1lVTpzA5Z1MUCgE4F9/WbYcAcz6ZDCwvJDDhzt2TFEAui1DvQuxZnG1ZgEU+0leCWTNGqW/IEdtAVS7PXTtKk+LFUQ4lgTg/fvaghNgAV7q0pAvvKC9LufiReW8lu+reL1rRQETCjIzgT//ZDWBJ01ihZec1cz6CMDbt82jGEWKFnVNZJmvEhbG5HyJEsDgwfJyV4b/aCBbAHMoAAHm/8OJjbW9vqUzWOworTnO64VoAXRkeEQrfcrdu9YFIPfx0wrO2LnTfH2xDVeumFu31G1QB5fs3s2GcEVsCcA1a3Kex85Wjj1baP2GGm0IRCZGQpl4+8fkZ8y3XbqUvUQcFWVdulj/XOzv1BYhS7+f2tLEK0/cuQOMH6/8zBVDo+vXI6tadVw+dhcAUAUagUSWeOIJ9r53r+PHFS3GvlAWTC16RLQEIJ/WSueycaO2IBN9AAMDlUE4gFxyzlJ7LAlAwLIA1AoCsSXW1L6xP/5ovo4oANPTzQNJCBNnz7J4zH79WOzc4sUs61b16sz91lH0EYCZmdqRSxyj0Suz33sMSzfZV1/N2X7VIfkCEkQLYA6GgJ3FUkcingfebgF0RABq1e3Jk8f6DY77BWkFVmhhy5dMnel/3TrlOmo/N8C+/8DWccVk01qoBaB6fS2fKGvHByyeX0VwE/sgP6C8njgaqVBZXLRcVbiPqr1Uq2b9c9HCyH8vfiO2JAAtnSta3uCiW4WzxMfjIfLiDFigUg0cy/k+7UGdONjbsSZgrFkALRlFtCyA6iFgdTURsV/SisK2FAQSF2dZAD56ZD4EbOkcrFSJvasfOrXSmamHgEW3J0LBG28wN81Ll5jB+MABpu/LllXaXOxFvyjgAQOAHj20X+pi7wSjYcOcbS8OC6hIRrjJAtgQuy2u5zYs3eTEBMr2+J+5Ey3fHtE6oTUEbClwR2uYSLTstW1r/jkXPpYcuNXYivr95BOYIVqidu8GnnpK+bmt/6BRI+3s/yK2LHzqz9XDfvYMEav9DPl/ozH0HosDeBeTTPO/o7dyhTfeYJVbcoItH7waNeRp3lZ+I7YkenJqKXWC/YhFKljAQW0keOagaguRt3HqlPL//ewzy+tyl5Zjgni2ls7l5Zfl80BMz2IrD6B6X+oHt0ePtB+KQkIsC8CvvzZ/yLV0bnK/Q3VwyjOChZ23Uf3/1q6tvU8Cmzez00t8xitUiHXl6sQE9qCPAOzfnzkBR0Rov6KinKtsnFsYMkR7eU4zom/bZvGjA6hnygFY3VNP9iKZmeyGxoeKtNBTAN68qRyi4Y9bBoO2rxaf1oqaBbSHwsSgi7p1zb16edS0teEbEXXnrFXRwhrz55vfXLg/ljoogqMVOKIOT7Ml4NSfq29e9liBLOWVtHBz644lpukXMBsPIESop6drl/ByBEdEr70WQFFEWLtuODnxrcoePbgIuZJPODzkkiGeDxkZ+qV6uX6dZa0QfRL//JMVZ1UnROeoo6L/+st8Hf7/ilkReCBGy5ayBVCs921LAIpDwIC5VU3sS8VrIiFB2+IIsO9urwWQo752P/9cnubtFvvI9HT/9v+3QUiItkE3JcXy32YNK+OwboQ7uBLaWMrb9c03cr4tR7FhgbiaPfxbELeQFzl0wneGZs1sr+MJAbhhA7P2BAezTthgYF62PXoo11M/yaorFjgzVLVrl9yhBgWZF3vnNwitSDot1J2zVvJna9y6ZW59472PuoqIeEx12woXVloWuRAJDNT+HmqxZK1qhkhoqLbg7tRJdrC3IADr4wAm4T28D1aD/A88gxcw277j2oMtASiKHHstgKJ1WT2cr0WXLqyAqDNkt4mniqoFD96kxRyKqak5DxJyBkmy7re+bx+zfqtdA7ZsUQZodOnCoqBF+P8tujrw8yUoSL6zW6qRrGU5VC9Tl50UVYR4bt69a/kcSU5WnovqtDAicXGsLxVTRGm1Uf1/eqOF14vo1IkZhX/6SR4Q3L2beYfZcjPWwjtKwbmALVu2oHPnzihevDgMBgOWqp22Ndi0aRPq1auHkJAQVKhQAbNmzXJ7O+1CK0JUTatWTJzY+1Q/bpzVj5OyBWA0NC7Y3r1ZmT49+OgjedodArBtW/Y7nj7NrqTWrZnvW+3assXv6afNt+M+LoB1C6Aj9OqlFIDqB6V169j777/L66nLqImoO1N1PWJbqHP6ibRubfmY6m3EmsQiloaanB3aDArStobky2fTAggAnSEnWn8HnyIDLqxCY2sIWIyIV5el4zf648eBjz+W9+Vo9Yt//nFsfZFs362r9uQKdTVqV4X33rO+/uPH9lsJ9+9nD3yWMhWkpLAHb3tqkmv5hRYrJvtfZmTIY3f8wUpMIG80ypY7LtCCgiyngVFHi4tR2GoBqA6+sBZQx9N4qbl3z/zatlSSgp+7lkqYliihPQR8+TJTOYQm06YxH8C4ODa6nicPMz5XqMBG6B0l1wjABw8eoHbt2vj222/tWj8xMREdO3bEk08+iYSEBAwbNgwvvfQSVq9e7eaW2oFYWcES3NF4zBj79jlzptWPk8COGa0OAGnfngmOTz9lFag9iSQphzJ4zVZLnbskscjWtDRmCfr1Vzn/miQxASRJbFiC171ds4Z9Xrmy+TDa1q2WRbZofdHK7WWPAFQlJwagFIDq1CG80z59Wl7P2gOA2hm9ShXt9UQxq8bS8KNWFRNAWwBaiui3JMactfAYjdrtFaMVrYyT1MIRvFl7EwDgOopiCwSrNB/is2YFsgYXbZa2F4cG1RbAzEx23lavzsQPt5aLw2u2Ams4zg6fZv/fPFDMJZkCnMVWxtvQUDkFldarSROgQwfg7beB+vWZ2IqN1V43LAwYOtS5dvLk3zNnst/daDR/WBTPV6NRvq55JaTgYPvSwADK60ktAMuWVc5bepju0sW6D5762rYkFm2NRwYFaQtAwD4DiJ8SGcm6itOnWV2ERYuYC+qSJdq3E1voMwTsBtq3b4/27dvbvf7333+PsmXLYkp24fGqVati27Zt+Oqrr9BWywHfk1i7IS9ZwvLscT77TLs6h4NcrRYPHAeKcQvgkSNs+ELMHbdggeP5z3KK+oal9m3RC7HWplanzttdvbrSV0tEa7hDFICzrQxB8mM5UubL0hCwNWuAJSErFoUX0UrkqpWIFtCuugE4bwG0VEVFbJMVCyAAPFfrMFYdisYpVMEYfILdyH4o4H5fjvpRcvh3svSdxZsubyv3O0xIUB6XW5pEAaglsvv1Y6L/3XflZQcO2JeWSU32eXkFJQA4kSngxg3vubHzhOgrV7r3OE2bmi9T1w5XC0A1liyAWgJQFH1qAai21PFrnruanD0r7+u111jBAC3E/sDSAxffrzWsCUAaBjYjK4u5Ty5bxp4lW7dmmZ5yWhws11gAHWXnzp2Ij49XLGvbti12auVTyyY1NRX37t0zve7bU+TcGaxJ+R49nAsGsZFDMCmSWYeiA66zx4oaNYDXX1deyHFxLNTI0g1di+3b2Y3MUcsDX98ba3uqh97UFkCxk9RKIcJRd3Th4UoBqEYrH5ooRJ3FWooSV1gALfnwuXoI2JIAFC2ANgRg/TI30RVLAQB70Ah3kR39y30Lrf2f1uAWQEsCUBy/4b8fvykD2mLFUoARZ/ZsVlVJZOJE69tYIjvJ2FVLFkBbaWZEn9F69Zxrg6+h/u0B8zQwomuA1pC+6AMook4Dw9cVt7OGOMQsnmcBAdZVhTp9jaWHCVsWwKQk+bdQn8e8FrGliiR+yEcfsee4/PnZ6PnXXytTBDuL3wrApKQkFFUNxxQtWhT37t3DIwsd6+TJkxEREWF6VbOV28tZ7KkH62Ku3mUXfcyUN7Vr1HKaNzcvXg/IviyJiWy4ITiYlYZq3FgWKZLEnvYsDRtwxPxz3pgVXm0FUlsARWFnSSip1wOAkSPlZYGB5jdK8bewJBSdKRd45Ijlz0TfNBFL34sP09uDJTFk7xCw+jqxJgDVyZWttKmHEBH8A15FFgxyllVnK1HYsgCKlnbeVnFEQys1lj05GQ0GZdk6R0vYAez/6NULKchrCgKpB5XPHE8R0rIlG6Vo2pT5106ZIke8Hz/O1hNr0gJMDEiS5d/GF6ldW7susloAig9YWt/faLQ8BCwmghbf1dOAeRUgbgFU7zsgwPo1or629+/XXs9WIYf79y1bADnW+iU/Y84cVjl09WqWk/7vv1m13JzeHv1WADrDmDFjkJycbHodP35c7yYxcpgcNf2/66Zgreq1cig+y5Rhjr+pqcpIWU5IiG3LhdhxepMF8I03WHvUQ1nWLID2XKGdO7P3kBB526Ag60JZXE/0GbXk52cNa8OaPEGx2jphLRlzTgWgvRZAtaXckqO+aAG05JQutKkB9qIRWFTtO/gUB1BX/o+dFSn8O1myrojCXcs6pIU1AdhbyGXIzy9nSEw0tXkPGuIxQmFAFmriCBsh4PAAnI0bgW7dmP/sqlXAiBHMzw5gwUBvvMF+y/R0YNQoltqEP4g/fMj8dL3xoc9RxMhlEWt9hZbVbvNm7eVaQ8DieuqHIXV7uABUn2OWBCfH3mt71Srb69gSgISJixeZ2yonPp51yepCK47itwIwOjoa11Q3vmvXriE8PByhFjrpkJAQhIeHm15hrhh+cwVWKnyYsHTDzsrCqdtFTLuw2+q+fbtzXqeAbcvFhAnytCcE4LVr9uWespTg9XJ2TVT+vcROUl2jV51YGZAtpGJ+v6Ag8z9DdOQWLYViqgV7rMdRUbbXUVO+vHLe2jCRpdQPan9FS+eBvTcE9XCuPRZAOwRgACSMwcemRQ2xF5czipo+dwpbQ8DijZi31db/ZO060nr4cgYh7dSl7ByARXAD+fFQmVnA0SRkgYHsehJTpBgM7OHP0ehmLf79l1mvU1OZ/2H79synee9eNgw+dSoTq/v2ydtwofzZZ6x03v37zvU/WuXOOOrRAv5uMLAHGHUVl/bttdO82BoCDgxUPgyqR3X4vU99DgUEWB4+HjzYsgBUt9uWn2nlytp5AEW41VKdDssPycgw7zqCgnLuLum3AjAuLg7r169XLFu7di3i4uJ0alEOyEmNYIPBVCoyNNS8opBFGjdmZv4VK7SLjVujenXrn4tBMOoOOD1dHm7mr61bWZJr9XJLr/R0FhARFsYsHFFRSnHSqpV5myzV5BSZMUNuI8A6U/XQi1bHyAMq1AJQnX5GTETNO011Z21Pugp7osw5PJKxdGnl8sBAy9UxLIlpdeCIWlRyrFkARZGnNQSs9d9t2WK/VSm7l22OreiBRQAACQH4CQPZULCtc8AStoaAxZ6c32RtPWBaiuT83/+A7t0da58lhBu+XCv8KgtEKVqUhSOKCYpdRZ8+9q/72mvK+eXL2cNSRAQTpoULs36qWTNmjRw7lqVPatmSXY/nz7Mgn2XLWP8wahQ7Pn9oFt0dLCVba9NGnn7hBcttFS2AvC8Sl6sf5tPTtQWZmHdUKwgkIACoWFGe5+eKrQ5eywLIRzyiouToZPX3Ubdb/D20KF3atgWQB8FRUIhm8bTHj1n+P3GZo+QaAZiSkoKEhAQkZJu6ExMTkZCQgIvZ6mbMmDHoJ1QXefXVV/Hvv/9i9OjROHnyJL777jv88ccfGD58uB7Nt421SN8bN5zbZ/YQIxeARYvapx9MGAzsCVUtDmxhzUFZnSZDFIA1amg/DTdtajkTvxaBgUzY3LunLK909y5zsFAnTZ06ld0sbMGDHcQULWo/IC1neS6MHj9WCkD1tmKFGF5KTv1b2mMBVP/G7dppr2cwyAJA/YRvNDpuDVMPRdoqk6clgMTvqz5ZjUbLPklcAFrzyQRMAq8A7uJdTDYtnoCJ2IpmOR8CthRUI+Z85OvYCvETo3tFBg2ybkV7/33gyy8t574TEXwG5Vrh/8l+uhUrKq14ruK776x/XqIEG8bctw9Qp/4Sx8rsISbGeqm/kSPlabX/87RpbHh19WrWlmPHrF+DYv8l+vFZ6hMjIrQ/Ey2AfJ/qa0P0pebpsNQjQaJI5Nupj8fPw/R0eT8cSxZBW3l4AwMtB4FwuIsBCUDN4mnPPccuPXGZo+SaNDD79u3Dk0KE3ogRIwAA/fv3x6xZs3D16lWTGASAsmXL4p9//sHw4cPx9ddfo2TJkpg5c6b+KWAsERfH8to9/zyb37mTLQNYp9O8ueP7zBY/fDTA2RRnDmOtg1QPH4qWG56zz11ERGjXS7Y3Dxi3xIpO7tOmKdfRCtIQLYC8oKOWErfmVM6xRwCqLYBPPKHtsyMmm9UqNu+oGFJ/d0sCR6yMoI60DwqSLQZaAlAs06W1T1vuB8J3qocD2ITmaIktAICW2Ixb0ucoaGlba3ABaOkiE/2J+W9uTaxKkvY58uqrttsiJlfPzLT+1Cc8gMlJoB1MAeMMkZGszJqlgLSPPmLXjdqiHhLimiFkkQkTmFju3ds8MKFXL/k/tSe9jni9irV0tR5sAXYNWBKA6kTQ4nr79zPhyofpeRlQtRVenRxeSwDya8IRIVa9una9c44oAC1ZAPnQr7MGjlyEu4qn5RoLYMuWLSFJktmLV/eYNWsWNm3aZLbNwYMHkZqainPnzmHAgAEeb7fdBAUxyc+HMcWkxZY6DxErud645nLGNcylrF1rvky0ADobgZlT7DWLcgHIh00B2bzK0bJq8SEXMXJuwQLzdbUe8dQ3O2eGgK1ZZLlgUlsAnRGA6uPYOm+NRvN1REGoNQSsVaGkZk35QcJSnW3OzZumSQPYUPA0yNtMXWsj8t+SJdqWD6CIPRbA27eBl14yX96tm/b6lh5sf/rJelsE4S8ngfaAAASU6YnUFrpevbS3cWgIw04MBhZ22bevuQXN0dyGjgrAoCDth5qjR60PAW/apLxH8JyStizgYrJqDr92btxglld7sDUErCUA1ZZktbWRcDm5RgDmeqzdLG0Nf4qOzhpwC6Be+gpff80cp1V5GQF4VxSwLbgA5B1z8eLmFh+1D1nevMAPP7DpefPk5Xfv2mfJ0IriszUkp26TNQHIn76dEYBqa4PRqLxx27JWiqWxtAgIUD61BARol50Th6m0UhiJqKwNBgCNIecG/XB/R2yFlevNUrAVtwDaugED2kmC1RQubD70CVj2r12yRHu5ui6tmuz/PQNGUxLoUv2czIXoKGIQg9ryZkkcu9r6p0b8f7dvd1xwqgWgOp2T2pErKIgdR83kybJA0ipFOWaM8rfgQlV9TmlF0hsMynbyPIE//2y/v6eta1trCFj9n4rBH750H/AhSAB6K3wokGOPlcYSoi8IR4go5RZAR2IDcgw/2KZNLDWEljUD8K0Ln7eVd+pXrtg2q1pKu6CVRFYLtdgzGpVR1IB5RRFHBCBHsIwBsE8APvec+TaildPWzdNWTjKjUWklMBq1BZgokm351YmBNtnE4gC+x8um+ebYhkxLXaclCxwXlvak7uc3cmcuSEsWKUvHtZXKKlsA3kMY/ssWgI1HaVS4cBf37zMrur1+xu4WgKJV3pmqRLYsgOrrPigI6NhRe1+8whAXW2LNZPV1w9PAHDyoXM5T9HD4Nenod6tRQzm/YYP19RculI/FLYA81yZHdDvJYaozQhsSgN6K2qfP2gW5a5fj+xfKk/HALi3jidvgCYM1brgKfDEn2J9/ytOiANRyNDcaWdQhwKxT/KZvbzi2ViJX9c2e5/LjqGsE29PZqy0HgYFKa6ZWSTq1BTAwUDnMr75ZqxOrnz5tXQCqBWRCgvYQu72JuQGLN5reWIAnId/U5uB57e35UJslgoNtixT+W6t/P7GahiWsRSlv2WJ7ezXZAnA7miAdwQgOzPJsP5E/v1yDPNuv22qEsDuGgNXt4TgjNsX2aQlA9XUfFGTZos/zhPJtxahwS8O4QiCkaf8iWsPJvI+2NqyrLsNqT+5J7pdoKW2U2DYaDnYLJAB9BWsde8OGju8vWyQ8eiRff+4qbGIRewIW9LIAcn9R0Z/PXsT8fWI6Dq0beHq67OF7+bL8Z1i6kakjdtUCSW1RDA0Fnn1WuY7aWd0eASjWn+bHES2AWuegutO2FbCiFY2sPu9FC5fWb6QlAB2xAFoYQo3APXyOUab5KRiJfdAoaWZLHWn5NapRO/dzcuoM36yZuZXFFtmC+SLYcFzJ6Aw9ChUxpkxh/cFvv1lex5NDwDntm5KTzYeAta5nW5Z2/oeIQVaW/iT1vgIDlSNEWhZAPhplLQiPu7FwbPkTqYUoYO6/W6CAPK3bSZe7IQHozfTtK09rWUL4MK6jVjJhmOH0adkCr84I4BXoJQBbtGDHPnnS8W35U3zdukpHbK3/8MEDbUEgWGgVcGsIR+sJXjyOVjF5tchR70NMjcNR5+xTDwGHhJhvx2t6itu88YY8r75Za3Xy6raLw9dGo1IEhoVpPyiJAtAeS4KFm00sDuCv9/cgBI9xDDXwCn5AeokyypVsJUQ2Gm1HU6rTe4hYi6y0h3LlHLumsr/PBbAh2JgSXj4U50kLYE5HJ27ftm0BBOwXgI0amS9To34IXb5c6UOuFVFsC4PB3K1EPbSsxmhU5nsFzH3VRfHrbH1wwiokAL0Z0fFe68bGOztHRZKQ1uToUfZeqJB97kkex5d8ADlccISE2FegXSuRd9267F1t0VJXGbBlAQwMNLccqW+SQUHKJ3Ktm5A6G79aAAYHs/xyIurIU/U26jrD6nbFxpqf96IoMhqVN+G6dbVvyqIA3LnT/HMRg/Vkzw1rpaIHFgMADqA+5gephoJtJYq2x5JhyQIIOFfqLydki3RuASxd2cvr9XrSAphTAViggHkeQK0+wl4BKOYY5cvU+Uu1fGS1cmvak1mCExho7ntq6zzXCthS+88GBMjf3QvKxU2YMAEGg0HxqiJcj48fP8bgwYNRqFAh5M+fHz179jSrNuZtkAD0ZsSIK62OgV+s1joirc8EUcFHHD2WA9BRfNEHkAuO4GBza5wWWh08z/mn7kjVKl3dUasDJ27fNn/qV+8zKAioU8fyPgHzYBYtAaj2r1NX1TEalT6A6qE8rbQuaoEr/oYHDigDTYxGuRqLiCgAbaWByZdPGVSlGtqOLhWEwZCjb/udn6gMCAkMtG6FssdCZc0C6Gmyh4wvZlsAS8d4+S3D3QJQ9Mu0FqVtD//+a14JROs/tyUA+TZi/lF+LalF1l9/Keejo7UFoCPVXYKCzC3r9pzne/Yo59X9R0CA/JBoKb+nh6levTquXr1qem3jfowAhg8fjr///hsLFy7E5s2bceXKFfRwpjyHB/Hyq9nPEU8eLed13tlZE0laWdaFfXEBqFsKGFv4sgXQXgEoDt1weKeuFkXq6g/qm4OWaFILQC0L4D//WG+n6I/D2yce++RJ8+OqoxcDA5VDOdzKKbZdvb5oUWvXzvwGKSayNRrNAycApQC0VfNZ/duoLZ958qAxdqAczpoWLUAvmM7SgADrws1otFwCjyNaAF95hU2vXGl9G3excCEAWQB6NADEGdwtAMXzMadWqaJFbecBBOy3ADbViM5WX8vq6zgpSSlknfG1Cww0vwcFBFjO7ACw/JPqsnJafRmHRzHrTGBgIKKjo02vwtl9a3JyMn766Sd8+eWXaNWqFWJjY/HLL79gx44d2OVMkKaHIAHozYhO8c4OAYt+hBzhwtIlBYwj5CYBaKlztZbiQr3N6tXWP9cSgOroYy0L4I4d8rw9liejUXlO/vWXuZ+O+qElMFAZ0ajO+6j1XcRjaN1o1FYPS+XROPb4Jolo5DI0AJiP3qZFffE79vOAEK1KCur92wrEEBP8fv89uwYsletzltq1ba+TncQ8CVG4kl0FxJ7NdMXdAlAUKbZqmluCX++ZmbZLwQH2uxWIdbD5OaTer7riT5MmyjKjzvhQ3rsHzJypXBYQ4LhoU39PsS1e8uRx5swZFC9eHOXKlUPfvn1N1cX279+P9PR0xAt9WpUqVVC6dGnstOV2oiMkAL2ZQoVYZKiYO03E1hDw6dPmJn8V3EVB9yoglvB1ASh2wJZuTmork4h6aMWWqVYrd55a1GhZAF9+WTlvC7UF8IMPzOsVaQnAdesst8OWmDUalYJPnULIkgVQPJ6Q/1ITWwIwu831cBA/YJBp8TcYiiwY2OdiOg6tNoho+WTZsgpZGlZypIyl2pdUi+zzcguaQ0IA8uXz0kAxEXcLQPGcdnaInm8nJoJ2hQVQFFBcAE6frlz3mWeUv1HNmsrziZ+f4g1BzC/IUZ+36nPeYLDedw8eDAilWwGYf8+AADk1hRvrAd+/fx/37t0zvVItBJw0atQIs2bNwqpVqzBjxgwkJiaiWbNmuH//PpKSkhAcHIxIVbnLokWLIslSmhsvgASgt1OihHb9WMD2ELBWBnmVgODxASQAXYglC6Cl/8mR8XfxKV8LS4mlRbQE4N698nxgoO1STur0FAUKmG+jbkdgIDBpknIfXboo59Xrizc1LYGont+/33KbAwLsSz4tolXNBIARWWiIvWhSmlkAZmMANqKl7f2r26xl3VGX+FLD67tyzp9nqTq06jlbgh/XjgufB4DExDiX+9ijuDsKOCICeP11FnDhaBk4Dv8R7SkFB9gvAMU/h+9XXSmoSBFznz+xT+H7Eh88tcqIfvihPB0Roe1E/tprynlxNMpoNPcRVvs3iymTcupvaYVq1aohIiLC9Jo8ebLmeu3bt8czzzyDWrVqoW3btlixYgXu3r2LP/74w21tczckAH0ZW0PAWsuFeseSJAtAW4YR3fDlIJCgIPsEoFalFo7aiibuT+vmbY8A1BJaop/gypW2kw4bDMobU2Cg+RO9Vt4/0QcpIABYtkz5uXgiqoeAtSyZ4jCc0Wge9ag+vlaeQGtoOaZni8I6OIQv28sWzXhswNVbDv72r74qT/PzhqcAsmT5VyfszJvXPHG8LXg77Lix8hQw9hbj0BV3WwABVoJPPeTpCPy6SE83zwOohb0CUBS//H8dO1a5bmSk8ljqcotaAlotzNq2VYq3zEztRPDqbALifrQS1mtZAEVrqZs4fvw4kpOTTa8xY8bYtV1kZCQqVaqEs2fPIjo6Gmlpabirymxw7do1RHutfxUJQN/G1hCwlgAUbhT//Sf7ADqTS9oj+KIFkNdonTdP+6lcjVaFEI5aiKlTvADA6NHyMlvl0/g6ImoBCCiDDiwNUasFoPo8VAtAsf4nb4coGgMC5OoGgPYQsIjRCHz1lXLemr+ULf88jph+ST3UZTQqHOEalk7CVLxpmv/uzyhklRSU0ttvm7dBRFRVt28rP7OUg1L9HdT1XO2B/5Z2PGBdJAHoWkRRY80CyJfZEoBa35nvV31uRERYF4D8vBC3UyfDV/vypqRoX3fq7yT6BAYEmD9cqQWhhwRgWFgYwsPDTa8QWz6X2aSkpODcuXMoVqwYYmNjERQUhPXr15s+P3XqFC5evIg4taXTiyAB6MvYGgLWEk+Cn1BCAnt4Cww0zy/sNfiiAOQJkUuXVnbOloYn1aJAfJrOdjI2oSUAxbrRrrAAAkrrk6XhKfHGFBQEfP65+XHEvHVqAWg0KqumGI1KJzN11HBgoLLkVECAcuhafTNTYzSyly2RILZJywdQZTFpi9Xonp0bcNKP0dgrCYEm6qhL9W8v3gTV57q9gR+2/m8tHLAAmnIA+oIAdPcQsCvg/nKWLIDcis2HWR19oAPk//XyZeXyRo3Mr0Fx/3xf4oOZVklHe24Y6n5DTPRsjwVQHAL2glrAI0eOxObNm3H+/Hns2LED3bt3h9FoRJ8+fRAREYEXX3wRI0aMwMaNG7F//3688MILiIuLwxNiMQAvwweuFsIizgwBCzc/HgBStKh3pBzTxBcFIE/r0rOncrmWz5BWVKq1Dl+8UfA/TRRvlgSgmHJFfcMICACuXJHnn3tOmZTVHgFoNGoPAZ8+rVxHbQGcNk35ufibGY3AkiXKeVGFBAQoBaYtARgQwM5/cR1blgstH0DVd6iCU3gZcims9/57TU4Lo07ybTQqK6YEBMht4EPAfMjIWkqO5y3UIrYXOwVgFgwmC6AzVRE9ji9YAM9mpxBasEDbArhsGQuWGjmSzdtKN6P1nXn976lTlcsrVTIXgFpDwOJ5oeXLq4Xa2mjrWvQSC6C9XL58GX369EHlypXRq1cvFCpUCLt27UKR7H79q6++QqdOndCzZ080b94c0dHRWLx4sc6ttg4JQF/G0SFg1Y2f+/8568vsEXzRB5CX61JngdcSG2JUK8eaAOQdOyB3joPkaFSLpcbEY2tF3wrVYRAQoHxat9Thi/tcssT8BqCu1KE1BKxe39aQr3q4qkYNy59rDd8CtmsDi/vQsgBu3SrPZ998m2Mr2oAFYaxHPL7FYPa52ucwIABo3Fg5z39Hbu20FQQCAHPmsETCzl4ftgRg9rDVEdTAbTBfrmbNnDuUR/EFAci5dEnbAhgWxuri8mvFmSStoqVcjT1DwH//LS9TB3hY6g/UyZqt9WNaFkCt7AVeJADnz5+PK1euIDU1FZcvX8b8+fNRXsjpmSdPHnz77be4ffs2Hjx4gMWLF3u1/x9AAtC3cXQIWLWeTwhAX7QA8tQ76koXfDhGtNhxEfTMM/IysUNWJw0WEzZz65ooIgMCtINDbAVTiJHmGRnKoSPeCatr/YoWwGXLzMWO1nHU1gf1+mKeQ6NRmerFaFS2Sz0cazQqh4zVgtQeB3fAugUwIEApILP3mRePMAlyKbyh+Aa3UUCu6CK2cfly5fZqC6A9kaEAC5hxVvBoWXpEspPXHgLzdyxUyIurBYn4ggDkPrUDB9r3X9vyWxUC+3DsGDB7tnlZNU7hwuYPYY4Ggdg7XKQWdGIUsJYAVH9PL7MA5kZIAPoyzgwBC5AAdDNqix+/g65dy/z8xKdsMa2CeBPj9XV5ybPBg82Po66GoWU5stbJC5GtAMxzD1oqUyUKwNBQbQEoDvPcuWO9Heo8f0FBSmdzoxFYulS5vVoAigEcauwVgKIF1UIaGK02NMB+fDTiJgDAgCz8gw7afk2i6DIY5AvxwgX2bo8FMKfYOQQspoDxCXzBB1AcS7cnCtiWABSvsWrVWF1vS0I4KMj8mtHyARRLLAYEKB9anRWATz2l3KdWnlAREoBuxweuFuL/27vz+KaqvH/gn7SlC5S2CNKWTarsilBAoLjgUhZhBJcR5IeADKMDgrKJ6wguj4LI+Lg8DDg6CA4OAo7oOAqIiCLKvklBWQQBtS0wUFr2tjm/Py43OffkJrlpkya3+bxfr76a5N4kp6fJvd97lu/xKtAu4H/8w3D3mHauYgBYWWoQoV+RT5lifFzvImnfXluS7He/c2+TAwU9ENBfa88eYO5c7b7cIqgHmHIqEW8nQLNuHvk58kxkPSDR6QdheZygWubERPPuzv793fcvvdSz9UEdRyiP8YuNBRYs8F5us5OXvI/6vTALqMxmWMqtkGYtgLfc4r7vcBhm1v9x4ClkJf4GgRgMxXwcO5fs+Xw56bb8/3rz4jjCqgwAzY4d0v/fVjOAAXsEgFu2aL+PHrWWCNrf58DXhAyzbli1FV7+DOjvNX++8TH9ZOGrPJdf7vu9//Y3922zFsC8PGPqmNhY4LPPtNvyZC8KGht8W8grf13ADz5ovC9d1ZWXu4/zas9eRLHDGEA135VeZvWg7mswd6NG7ttyKhRAmxlrluxVn60qjzX0dnD2NfZOvRovLjZ/rtodLbdwJiaap7NRJ634arGLiQGeesp9/8wZYMIE4/4tWnj/O8rKjH+/mkfPLDjwl2JDbaWIjQWkVA9q0Fn/UoE3Wrzhuv/mF8pJ0WwijG74cO13VQaAgOd3TBpC8DOaArBRC6AduoD1YOrjj60tBeePWSu2Tv5O6vlG5YtqdaKV/nmUvxf+Vuzx9rh6wdinj/E11XKfPOm9h2DWLPP3pEphAGhnVtYC9uLsWXcAqOaVpQCp3Y4VOYFb3ddsDJ08Ot9KC6BZACi//8mTxkBMf0+1jPIVflKS/wDQbLyResW/a5f7/uLFxjF0x48bF5hXu5iFMJbx3Dljq4NZHZudPOXuL7NuKfW+EtDdUj8PjXAYALBgVQYuQAl61QCwfXvttv63VHUA6KUbWADYDy2AlTPjRDQ7BID6/7tHD2stgP74uoiRLzo7dNB+65PUAO1z0LCh8T4APP64+zH1M++tjtX91Atj9TilXlz17u1/PCIFFWvYzvx1AftQXOy+EJUbnyKOHbqA1QOdfkINRW4d+TX19/HXigX47gJW7xcXG1fY0N9TPSCrAaDZurbya1sJAOXu5wYNjPvPn+/Z5SvXhxoAAsZcelbHAMq5F826y+VWSYfD429MTATehhao7jxQC1PwrPcyOxxaRnbAHQxYnQRSGRYCwH24AgfjtFbfiE0Ur7JD0KAvrbZypfUWQF9pf3y1AMrLuJl9ntTUS3r9+btgNKN+V9RxA/LYYm+TQOTXiI1159EcOtT8PalSbPBtIa/8dQH7UFjozkcasUmgAXt0AastgPpBPRQtOHIApKdqkR/zNqhfDcRkZl2pZgGjup+8T2Ki5xU94DvprNoFHBtrHDP4+997BnzqiUnefvq08e/MyAh8hiMArF5tfI76N7zyinG7WrdxceiALWgIbcbyIgxAKaRWVHV/PeidO1f7/+kXPaFceFeuC3W92Iu2oCPKyhyoVct4PRDR7BAA6nkAv/rK+rHC10BtXytXyJkI9M9Tbq77MW95AH3N1vdWx/4uWNRsBWZr//78s3EfPTiVh35Q0Njg20JeVaILWB9mVqtW4MujVik7tADKQUxpqWcL4Pvva7/l3HoVZTaoWz6AewuY5YO2lSt6s3x8vloAExPNXyfQFkC5e0kNvp56yphCJTbW+J7nznmerPwFUWYBoByExsYavyAWuoCxbx8uxTHMwEQAwH5cgb9jhPv1vI0B7NrVOAM5lAGgr4uGi2XKu0ybpNSqlT3iKgD26AKW6UMU/P2vfQV5vp4rB05mS8upFzD6bX9jhs2oAaDaMyLP6Lc6C9jibHWqGLt8rcmMry5g+UoK8Oie0xsd1BXAIo4dAkD5QFevnrty9YPXwIHa39GxY+Xfy+xgL5/M1Rm8OvmgbeWK3iw1hK8WQG/dUIEGgO++a7yvtkTKaxSr5fn0U88AQD6pnD3rWT6zcqsTTeTJJGbd5+rfmJcHAOiJFbi6pZaXcBRm4xc0NA8A9RVUGjeuugDQbCiB7uLxZOch7Zgh59qOePL4Njs4c0b77a8F0Nv3GvCdcFn+P5sFgLGxWkJqnf6dCqTHwOy9AM/votyK6XCYtwCq9zMztbQ5vtI7UYUxALQzX13AagC4davhri1yAAL2CADlg1NxMbBmjXY7FGO45IO9no5Efh+zcXiA78DJX8ud1RZAM2rLo69ZwLGxnmP21IBx8mTzMnojtzLoJ1uZv0TQ/uoqNhZYtMi4vZ2WPPkSnMCEEe7VERbgHs8WF3kMYVlZ1QWAMTHu44dJ60op4pAXr12w2Kb71878HSu2b/e+zdfnxEoAKP+D9c+EesEoP8dbK+uPP3ovB2A82ZSXa+8ht2yatQBOmaK97pgxvl+bKoQBoJ356gJWg0JlRQLbBIB2HAOoC3QMYEmJlhrCrKVKJx/sd+zw3C6vFCKTWxCstAB+953ndn9jAM2oXbpqQKemgWnd2lhOdX95lRO1PHfeabwvhPGkYpZM1qzccpnV/4VZACh//2JiDOs733Ste3zdTIzB0ZJEzwBT7uaSA8BQL9AtB56K7bgae89rg/h9rSoWMf7wB+23nDcyUh0/7vmYv/+1PJlDZTWJtLcAUA7CzGagx8QYv1veWgDV9FEq+burX4zJF2D+JqdR0DEAtDNfXcBysloTtukClpf2ilTqWBddoAew5GSgXz/fs3r9jff773/Nn/f//p/7tpUWQPms7y0ANOsmVvlqAVS7gAHTCRWG+19/7f09zS6E5GDOagug/Jy0NN/jJ82CaanMTRo58UHyMADAQTTFk3+/wvNv0u/LAWBcXOjHs3lbZeGaa1xLwAE2SRP19tvaMoH33BPukvinz2yV+TtWmK3vratsC6D8PdY/C5s3ux9Tv6cVHRAqv4YeBMvfP38plyjoWMN2VolZwHoKGLNlYyPK4sXhLoF/3mbRhKIFR75aNwuO1eTHOnX9YbXlTZWf775tZRbwxXFvHuTl7sy6gOWTQmmp/xm3Y8d6lkvnb7iA1TyAasCnrufrbV/9vhLg3VRzA1JRBAB4+9NMrD2oDIY36wIOZfevTg48ZWVlyIM28O/6621yHnY4jPns7MbfseKDD7xvsxoA6gd9NQCUn68HgHJ3bkwM8MYbxvsVIecJ1S9U5SEacXFAz56Vfx+yjDVsZ966gNWrRXmM0kW26QK+7bZwl8C/nBzzx0PdheFtvJ8ZuTVJDbzMDrRys4/ZwHDA2HJw993m76ueSNSTlRyInjrl2TqmBq7ySUQtt3ohpH4vzGYS+msBjInxfSLy0wKImBhcknAai+Cun24z7oQT0lgrsy7gqggAvXUBl5ZiKzoAALKzQ1+MqPTEE8b7/gLAdu20fJFma/INHuz9efLnSF9OUv7Mq2NS9SEPasJ1mbfvg77SiDfy8UoPANUuYF+TTyjoWMN25q0LWJ0xZhIo6LtkZoagXMHkK/1BpPDWZRvqMVyBBAlqUOMvAJSvzK20AHrLFCwH8GoA6HQau8OKijwnn8gnPHXQeDAC7KQkz2Uu1GDZV1esus1LXsBuWIsMuFtV/4U73c836wIOVwvgF1/gx7wL+Bo3AnAvWkFB9vzzxvtWPssNGniuTf3qq76XaZGPQaNHa7/VFkCZnhzW1wo+3r4P/tYLlMuiB4DqJJDdu/2/DwUNA0A789YFrK4lq3RhnTnj7g1o1SpEZQsWO8wC9nalGuoWQHnFikA4HP67gM0Cb7P9xo7VlrSSk8vK5NQ3andTebnx4qSoyLMFUA4QY2KMg+HVE0RFPitJSZ7/p0BaAK3kBaxRA8k4jY/Rz/XwAHyAA7gsvF3AZi2APXpgA9zB/MCBoS9GVFI/c1YvFuUl2gDgT3/yvb/8unp3j68AUP/ey+NlHQ7PlngzZmNsvdEDQDXf6P791l+DKo0BoJ156wLu1ct4v3lzw93CQvfwMbMehYhih1nA3oS6BdDMqFHmj6vBkr8A0CxRsFmOtVdfBT7/3NoC8TExxtd1Oo0tGidOeI4BTEszPt9Xk7X6PdCvcnxJSvI9KUYN6FRmz/WS+7ATNuPjV35ybfof/BnCEeP+Mp47516VoypbAKUAUABYAG3CUKM6p00Xd6EQsHqsUJeE8/c5kYN7fZaurwBQvwD5/HP3Yw6HtUkgvoakqGMJvAWAgQxroUpjAGhnZl3AZ864m/G9+OniOSglBUhPD1HZgsVsxpxdVGUagy1bgBdeAF57zXy7Ghyp+fdU8glJTxQrj7+zSs15pyYglrerXcBqCyBg7JpW/yb1vpWLB7MAUO0C9vV/NAsAvQSQMRDoeNV5XJFeAgCYgz9iy95kYMkSbd/HHw9PC6DUBbwLbbAM2gzw22/2k9aDgsfqscLhAJo2dd/3N05OnqCmv4evAFC/ACkpMT5upQVwzhztgu7NNz23qccl/RylXvDpSdGpSjAAtDOzLmB1Xc9rr/V4mr4UZd26Nhhm8cILwM032yO/l6oqWwCzs4Enn7QeOMgBoPohuO8+4+BsvZVu6VLg8suNM3NVGRnG+2oAKL+XOvnArAVQDgDLyoyf7717jc9XA0Bv6XlkiYmeJ0F5JrWcqNmM2RhA+QTpcBj+Jw0znXhpyE7X/enzG8BADwB9re4QLCYtgGvgPl7c3uFg6MtAmkCOFXKSf38HcDnY0z+HvgJA/XOn9BoZAkBv71mrljZE44EH3I+Vl2sZBa6/3vw56vddzhpAIccA0M7MuoDVk6q8sP1Feuu7lfNj2NWvD6xcaY/8XqpITmQq5//RPz+//KKtTfrXvxoP8nv2aL8bNdKaj8eP9/66VnLz6dQWulatfLcAXrhgbNHwlTDb33vrzFoAZ81y3zYLANUxgjKzFkAl9c1N7U/gZnwBAFi0sh6+yZmkbRszJqyTQA4cAP4O9+zPmx+y0xpwNlcVF4v690FdCxgA/vd/tcaChx7S7l93nfG5VloAzcTEeF4UyjZsMO57443WX5sqjQGgnZl1AcsBYM2apl9WfWiULQJAOwtVAJifD8yYYW2Mm079HLRs6b6tj7tp2BC4/37P1CiBDO5WWwf0ZfHMqGlZbr3V9xjAkhLj5BR1qENFJ4GoZVaXnVq3znhfLoNZ97EaAG7c6L4fG4tL0px4DC+5HlpamgsBaMFtmCaBCKGdizdenADyZzwHR3ItH0+moKqKi0X9+2bWAjhunPZdTU3V7vfoof3WV+aRzzH657siQ0J0+uwiubVdXQmIQo4BoJ2ZdQGfO+e+7eXErSdh5/raIRaqq/qMDGDiRN8R/MmT2gxBPUhUy6KnbbGSPDcry3rZ1ETUN9zgfV/9hPTxx8CLL2rdROosX3WWsBysBSsAVIM4f8vjyIGrWXeYGgDKF2UXxwR2xXpMxAwAwNRNPbEa14cvEXRZGbZscTeyX4ojGPt8fRuMD6lGqqIFUG8x99UFrKtbV7vg+v577b48HVz/fD/1lOc2qxo08HxMnUBFIccA0M7MuoAtnKxt1QVsF4WFwPTpxsfCeTBLSQFmz3b/k9UTTHKyFmxZSbtgtoauN+pFh7dVUgD3rMR+/bTEuOoYQcA46ePkSeM2PQDUxyupwwSsBISJiYEHOv/4h/u2uqoK4LuL+OKkkhSU4C64V3d4DNNx/pxwj3FUx/IGgV4dJSVAQQFwGrVwGI2w+cea8vLFGIJ3Ua+/59hhCqFAjhWFhdrv554L7D30sYNWAkBAO0box42rpOEA+ud70iRg2zZg/vzAygG400/IPRHqJDEKOda2nflaC9gHPQBs1CjI5Ylm9etrB8RHH3U/FkkHM7MDvZpU1huzFTQq8766nTs9H5NbJIUwBoDqYvN6ALhhg9ZSoQ40tzoGUP3++BvjpOYmfPhh4JlnzJ/vJQAEgM7YiOH9j+Odjy/BenTF6oOb0GPHX7X9tm71X3YfTp82LsIiczq1c23h2S74HV4DlB7vaXgCaDSiUu9PFixc6G4985O5waB+/cBau3v21NK6/OUv2n119Q0r5GEPeiu1w6GtUBKIb7/VJpPp6arkxM+BlIeCIoLOUBSwCq4FrHcBy9kEKAQOH46cpRSWLav4cwNpAQzkuQ8+6PmYHDQLYTwheGsBTEvz3dXsS2KidlKS+TsJqRNVzGYC6xwOLdDWyyp1c8XCiZEDtQAQAAZ/Pgwbzr2MphX4M4TQevj0VI0HDwJ33eXvWZ4pg9ahC2qgzN7pl+xCztd65Ejo3mf5cuN9s0kg/sjPkYcZBapbN+3HGwaAVYoBoJ15SwTtw/nz7hZAs2EYFETyTNtwmzy54usqm7XUWSWvBKL74Qetecpsxp98AlAvbNQWQDVXmUr/XsTEeL9Iio8Hevc2Bsj+TkJykKpO+tDfT77dvz/wz3+6X1t6/Y5XXcA7d36C4R/ehqPnamNmi9dxz57n0AFbcKRQm5hthdPpfTU+KzJqn8InJd3RCVsq/iIUGHkSRSgDQJXVLmCZnJZIXWq0MkaO1Iaq6LZtC95rk18MAO2sAl3Ax4+7x+lffnkIykRu+tJLkeB3vwNWrABatKja9+3cGfjiC+OHrVUr72sQqi2AMjUA9Ed/fmys7wDwgw+AZ58Ffv977TF/rSJqC6C8aoLZdnVms7Q9Ns6BbpcX4Gpsx/dohxl7+mMG+uOtLm/juWvcObiDpUEDbXjhs88CR1+ag5xDC1B32qNAySlkv1C5bmcKkNxyXJUXixUJAOWyrl8fvLKoS06q3yUKKQaAduavC9hkWZ19+9xjgCJ+FRA76tXL3eUSSL6squBtvd5gGj9eyyl2xRXux265xfrz5TpTP9dqF3DjxtZeUx+zZKZGDe2EKE/gCbQL+JtvvG9X8wiqK4vExKBFZgnexAPIgfvEev96dz6+ihg7Fhg82Pwj2KaN1otXMv9zJB3ahksaH0fsf49AWwiOqpTDoV2odO9ede8pB4Bbt/rukjWjryQQDOp3belSLR0UVQkGgHbmrwv4o488HtLPoXXqRNYchWrjmWfcAeDhw9E30HLaNG08XkVPaHJLgzr5RA0A/TWPWRkaYRbs+ZsVrAaA8hg//TH5tdQuYZMWwq7YgKXXv4hbv3nSf5m9mDkT6NJFu922rRbbevtTkpKAOsnHARwDnKXaRBaqegUFWj9/oJMpKkNudVu7Fhg9OrDn+0vAHgj1CqV3by3ZPGcoVgmGAHbmrwvYpOVFzwTAFDAh0qGD+3Z1SbSoJob2JT4euP324LyvOoFE7S7ypyJ5AQFtoKwvagvfLbcA//63+zH1pJafb3yuGgBezPl3c73vsannkxCfL8dP2QOQNvUxvykJZa1aWZ/Ybfg7ysq09FEHDgTwZAqK+vWrfqyw/H2eOLFq31tl1kTNsUlVhgGgnVVgFrA+AaS6xCYRJz5eW03j2DHgyivDXZrKefVVbYWADz7wt2doqC2AEyYY71ud+btgATBokDtxrT8PPwz8z/8A995rvl0N4Dp3NgaAaqviZ58Zt3kZIxjvPIeOn08FAGRv3YbYXo/5LOaFC5VcMlheCo7BX/RwOIC5c4Fff9XWEA8nzvoNKwaAdlaBWcAMAKvA3/4W7hIEx9ix2iy9QFvegkUNAPWcgK+9Brz0kv961i+M7rlHmwRjMibWlMNhnOk4dCjw7rvu+2oAp76ur7GfahewnPx2xw5tPNZ33yF2yGC/xaxU8AcYVgIxiKTZ6xQaw4aFuwSaSBsnHWVY+3amdgHn5fl9ip4DkF3AZEm4gj/AM8LRJ5Y8/LA2bkpeRcCMPPnDavBn5u23gSefdM9+VAPAfv2025mZntsBrUVYp7YAygHg/v3Ad99pt6tiTVS9HGqgLXdZE6kCGmfgR6WvYqgy2AJoZ2oX8KpVfp+iLw0byNgiorC49uJyZOvXaz96mhbA2vJtvmb/BqJGDeCFF9z31QAuKwv47TctITXg2aohL4enBoCxsebr/lpZoq+yvLUAslWGzMydCzz0kPXklFboXVIUFvym25naBSzP5POS8kP/vjEApIi1dy/wySfuRNGdO2snnkgJTOQ11vQyZWa6B9erwanaYvjTT8ZtZtPxLVzMVZo8CYTIn2HDtFyccgLryurZM3ivRQGLkCMqVYivWcAmC3QL4W4BlNO0EUWUZs20MXsVpa8JfMcd5tv9dR37c9VV7ttmQanapaq2GMpj7NQ8gbqbbqpcGa2QJ4EQhUOfPsCsWVo6GqpyDADtTO4C3rDBuM0ky3NZmTsAZJolqraWLAHefBOYM8d8+7p1lXt9fTIKYN4VrQ6wVYNEeYWYoiLg0089X+PttytcPMv0APDQodC/F5EZh0ObaNa1a7hLEpU4BtDO5C5gPQOsD0eOAKdOabcr2whCFLHq1gUeeMD79rQ093I4FaGuBazq1w948EH3d1Jt4ZMX4W7e3L02Y1XTy/V//+d+TF4TmYiqtWrVAjhz5kw0bdoUiYmJ6NKlCzaorWKSuXPnwuFwGH4S5SVy7CDAtYD1JNCxsZwFTFGuosEfYFz1Q12dBNC+lzNnauljAM8A0OHQul3LyrRtDz3k+Rp33lnx8lllNvbw5ptD/75EFBGqTQC4cOFCTJgwAVOmTMGWLVvQrl079OrVC0eOHPH6nJSUFOTn57t+Dh48WIUlDgJviaAfecR0d/1clZYWOePpiWxHnkFV0eXm5HyAW7Z4brea5LoyzMplNiOZiKqlahMGvPLKK7j//vsxfPhwtGnTBrNnz0bNmjUxx9s4IAAOhwMZGRmun3STcXMRzVsiaDnvmEQf6lOnTgjLRFTdyXnQrKxkICeVNmPWGjlgQGBlqgguBk4U1apFAHjhwgVs3rwZuVLqk5iYGOTm5mKtj9lFp06dwmWXXYbGjRujf//+2LlzZ1UUN3i8dQF7OeHoD3MVEKJKkAO25s397//66763N2ni+VhlEldbxWW4iKJatQgAjx07hvLyco8WvPT0dBQUFJg+p2XLlpgzZw4+/vhjzJ8/H06nE926dcMvPpJcnj9/HsXFxa6fkpKSoP4dAfPWBexlgJ+eA5Dj/4gq6cAB4PvvrS2b1qOH7+1mV2Ry8uhQUVsA//730L8nEUWMahEAVkROTg6GDh2K9u3bo3v37vjwww9x6aWX4s033/T6nKlTpyI1NdX106ZNmyossQlvXcDNmpnuri8DxxZAokpq2hRo29bavnfd5Xt7u3bG+wGs7V0pagA42P/6w0RUfVSLALBevXqIjY1FYWGh4fHCwkJkZGRYeo0aNWogOzsb+/bt87rPE088gZMnT7p+du3aValyV5q3LmAvY3v0HIAMAImqUPfuvrfLX0h9XeGqoHYBcwIIUVSpFgFgfHw8OnbsiJUrV7oeczqdWLlyJXJyciy9Rnl5OXbs2IFMfUF3EwkJCUhJSXH91K6Kbhpf9C5gi0s56S2APv5EIgq2Vq2ATZuAX3/1v2+3bqEvj069UGRqAKKoUm2mgU2YMAHDhg1Dp06d0LlzZ7z66qs4ffo0hg8fDgAYOnQoGjZsiKlTpwIAnnvuOXTt2hXNmjVDUVERXn75ZRw8eBB//OMfw/lnBEY/YP/73+7HvHT/CuEOAM3GnBNRCHXsaG2/qryo5CQQoqhWbS75Bg4ciBkzZmDy5Mlo3749tm3bhmXLlrkmhhw6dAj5+fmu/U+cOIH7778frVu3Rp8+fVBcXIzvvvsu/OP6AqEHgPJEl9WrTXd1Ot2TQLgOMFGEGTFCu3i7996qe0+mgSEKWCALTkQ6hxBVNeK4+vnll1/QuHFjHD58GI3Csbjuiy8CTz1lfMzLv/OXX4DGjbXbv/3GbmCiiCNE5VYoCdRf/mJMGs9TAUWRipy/Fy5ciKFDh2L27Nno0qULXn31VSxevBi7d+9GfSsZASJMtWkBjEoBjNnZscN924afU6LqryqDPwBYsKBq34/I5iqy4EQkYwAYgUpKtFa6oiI/O6oBYEKC11317l+Hg0N/iAhaLkOiKFdSUmLI73v+/HnT/Sq64EQkYwAYgWbMABo29Ozd9aC2GHj54ALuALBly8qVjYiqCX1WGFEUa9OmjSG/rz5RVFWRBSciHUcBRyC9Ya+83OKOFug5ALkKCBEBABo10gYHE0WxXbt2oWHDhq77CT560qobtgBGIL2LVs3v7CGAAJDLwBGRwY03hrsERGFXu3ZtQ35fbwFgMBaciDQMACOQtwU+PAQwaJwtgERkoB8UiMivYCw4EWkYAEagUHYBX3ppxcpERNWMnZLeE0WACRMm4K233sK8efPwww8/YNSoUYYFJ+yGYwAjUIW7gK+/3uuuDACJyKBHj3CXgMhWBg4ciKNHj2Ly5MkoKChA+/btDQtO2A0DwAhkuQVQ7QKWBrLKnE7g6FHtduvWlSsbEVUTKSnu27fdFr5yENnImDFjMGbMmHAXIyjYBRyBKtwC6GUg6m+/uQPAFi0qVzYiqkbGjwcuuQR4991wl4SIqhgDwAhkeRKIGgAWF5vutmuX1poYGwtkZVW+fERUTbzyijY+JC0t3CUhoirGADACVbgLeMQI093y87Xf9epx/XciUlT1EnREFBEYAEagCncBd+1qupuepNym41SJiIgoyBgARqAKp4Hxkhbmt9+03zbNVUlERERBxgAwAlluAZS7bjp08LqbHgB6mSRMREREUYYBYASqUAtgjRped/v1V+03A0AiIiICGABGpAqNAfQyu8PpdAeAjRtXvmxERERkfwwAI1CF1gL20gJ48qR7FrCXOSJEREQUZRgARqAKdQF/9ZXpLt98A5SWavEhVwEhIiIigAFgRKpwGhgT+/Zpv7OyfA4TJCIioijCADACVSgRtB41Kvbu1X43a1b5chEREVH1wAAwAlWoBdBLtKi3ADIAJCIiIh0DwAhU4bWAFefPuwPA5s0rXy4iIiKqHhgARqAKdQGPG+ex+bvvgIMHtds9egSlaERERFQNMACMQBXqAo6P99i8ZQsgBNC0KdCyZdCKR0RERDbHADACVSgNjBIAOp3Axo3a7WuuCV7ZiIiIyP4YAEYgyy2AeoQHeASAmzYBX36p3e7SJXhlIyIiIvtjABiBLLcALlrkvq3ne7lo3Trg6FEgNRW4776gFo+IiIhsjgFgBLLcAihHdgsXum5u2gSMHavd7tMHqFs3qMUjIiIim2MAGIEsp4G59lr37RYtAACHDxvH/A0eHNyyERERkf3FhbsA5OnUKe336dPA5s3ux9PTgYwMID9fCxJrFzmRhDicRi0c7TMWxZuBDz80vlafPlVXbiIiIrIHBoARqLBQ+33oENCpk3Fbu3Zal25qKtD/bD4uQzd8i2vx5+l/BKYb9123zpgqkIiIiAhgABiRGjf2vm37dvftJRgEYJDpfitWcPYvERERmeMYwAjUvTswbVrFn//JJ0BubvDKQ0RERNULWwAjUEICMGCAZxAnhNale/68luLl5z0X8Ouj/4u++AzJa5YBiUkAgI4dw1BoIiIisg0GgBEqKwu47DJtsocQ2sSQ5GSgtFSbHSwEcDQ7HnU63ISEuBvg6JyEuDiO+SMiIiL/GABGMD0djMMB1K6t3ZYX/GjSBECTzlVeLiIiIrI3jgEkIiIiijIMAImIiIiiDANAIiIioijDAJCIiIgoyjAAJCIiIooyDACJiIiIogwDQCIiIqIowwCQiIiIKMowACQiIiKKMgwAiYiIiKIMA0AiIiKiKMMAkIiIiCjKMAAkIiIiijJx4S6AnTmdTgBAfn5+mEtCREREVunnbf08Ho0YAFZCYWEhAKBz585hLgkREREFqrCwEE2aNAl3McLCIYQQ4S6EXZWVlWHr1q1IT09HTExwe9NLSkrQpk0b7Nq1C7Vr1w7qa1c3rCvrWFfWsa6sY11Zx7qyLpR15XQ6UVhYiOzsbMTFRWdbGAPACFVcXIzU1FScPHkSKSkp4S5ORGNdWce6so51ZR3ryjrWlXWsq9DiJBAiIiKiKMMAkIiIiCjKMACMUAkJCZgyZQoSEhLCXZSIx7qyjnVlHevKOtaVdawr61hXocUxgERERERRhi2ARERERFGGASARERFRlGEASERERBRlGAASERERRRkGgBFo5syZaNq0KRITE9GlSxds2LAh3EUKqqlTp+Kaa65B7dq1Ub9+fdx+++3YvXu3YZ9z585h9OjRqFu3LpKTk3HXXXe5lt7THTp0CH379kXNmjVRv359TJo0CWVlZYZ9vvrqK3To0AEJCQlo1qwZ5s6d61EeO9X3tGnT4HA4MG7cONdjrCu3X3/9Fffeey/q1q2LpKQktG3bFps2bXJtF0Jg8uTJyMzMRFJSEnJzc7F3717Daxw/fhyDBw9GSkoK0tLSMGLECJw6dcqwz/fff4/rr78eiYmJaNy4MaZPn+5RlsWLF6NVq1ZITExE27Zt8dlnn4Xmj66A8vJyPP3008jKykJSUhKuuOIKPP/885DnBEZzXa1evRq33XYbGjRoAIfDgY8++siwPZLqxkpZQslXXZWWluKxxx5D27ZtUatWLTRo0ABDhw7Fb7/9ZniNaKmriCMoorz//vsiPj5ezJkzR+zcuVPcf//9Ii0tTRQWFoa7aEHTq1cv8c4774i8vDyxbds20adPH9GkSRNx6tQp1z4jR44UjRs3FitXrhSbNm0SXbt2Fd26dXNtLysrE1dddZXIzc0VW7duFZ999pmoV6+eeOKJJ1z77N+/X9SsWVNMmDBB7Nq1S7zxxhsiNjZWLFu2zLWPnep7w4YNomnTpuLqq68WY8eOdT3OutIcP35cXHbZZeK+++4T69evF/v37xfLly8X+/btc+0zbdo0kZqaKj766COxfft20a9fP5GVlSXOnj3r2qd3796iXbt2Yt26deKbb74RzZo1E4MGDXJtP3nypEhPTxeDBw8WeXl5YsGCBSIpKUm8+eabrn2+/fZbERsbK6ZPny527dol/vznP4saNWqIHTt2VE1l+PHCCy+IunXriv/85z/iwIEDYvHixSI5OVm89tprrn2iua4+++wz8dRTT4kPP/xQABBLliwxbI+kurFSllDyVVdFRUUiNzdXLFy4UPz4449i7dq1onPnzqJjx46G14iWuoo0DAAjTOfOncXo0aNd98vLy0WDBg3E1KlTw1iq0Dpy5IgAIL7++mshhHbQqFGjhli8eLFrnx9++EEAEGvXrhVCaAedmJgYUVBQ4Npn1qxZIiUlRZw/f14IIcSjjz4qrrzySsN7DRw4UPTq1ct13y71XVJSIpo3by5WrFghunfv7goAWVdujz32mLjuuuu8bnc6nSIjI0O8/PLLrseKiopEQkKCWLBggRBCiF27dgkAYuPGja59li5dKhwOh/j111+FEEL89a9/FXXq1HHVnf7eLVu2dN0fMGCA6Nu3r+H9u3TpIv70pz9V7o8Mkr59+4o//OEPhsfuvPNOMXjwYCEE60qmBjWRVDdWylKVzIJl1YYNGwQAcfDgQSFE9NZVJGAXcAS5cOECNm/ejNzcXNdjMTExyM3Nxdq1a8NYstA6efIkAOCSSy4BAGzevBmlpaWGemjVqhWaNGniqoe1a9eibdu2SE9Pd+3Tq1cvFBcXY+fOna595NfQ99Ffw071PXr0aPTt29fj72Fduf373/9Gp06dcPfdd6N+/frIzs7GW2+95dp+4MABFBQUGP6G1NRUdOnSxVBXaWlp6NSpk2uf3NxcxMTEYP369a59brjhBsTHx7v26dWrF3bv3o0TJ0649vFVn+HWrVs3rFy5Env27AEAbN++HWvWrMGtt94KgHXlSyTVjZWyRJqTJ0/C4XAgLS0NAOsqnBgARpBjx46hvLzccKIGgPT0dBQUFISpVKHldDoxbtw4XHvttbjqqqsAAAUFBYiPj3cdIHRyPRQUFJjWk77N1z7FxcU4e/asber7/fffx5YtWzB16lSPbawrt/3792PWrFlo3rw5li9fjlGjRuHhhx/GvHnzALj/Vl9/Q0FBAerXr2/YHhcXh0suuSQo9RkpdfX444/jnnvuQatWrVCjRg1kZ2dj3LhxGDx4MADWlS+RVDdWyhJJzp07h8ceewyDBg1CSkoKANZVOMWFuwAU3UaPHo28vDysWbMm3EWJSIcPH8bYsWOxYsUKJCYmhrs4Ec3pdKJTp0548cUXAQDZ2dnIy8vD7NmzMWzYsDCXLrIsWrQI7733Hv75z3/iyiuvxLZt2zBu3Dg0aNCAdUUhUVpaigEDBkAIgVmzZoW7OAS2AEaUevXqITY21mMGZ2FhITIyMsJUqtAZM2YM/vOf/2DVqlVo1KiR6/GMjAxcuHABRUVFhv3lesjIyDCtJ32br31SUlKQlJRki/revHkzjhw5gg4dOiAuLg5xcXH4+uuv8frrryMuLg7p6emsq4syMzPRpk0bw2OtW7fGoUOHALj/Vl9/Q0ZGBo4cOWLYXlZWhuPHjwelPiOlriZNmuRqBWzbti2GDBmC8ePHu1qZWVfeRVLdWClLJNCDv4MHD2LFihWu1j+AdRVODAAjSHx8PDp27IiVK1e6HnM6nVi5ciVycnLCWLLgEkJgzJgxWLJkCb788ktkZWUZtnfs2BE1atQw1MPu3btx6NAhVz3k5ORgx44dhgOHfmDRg4CcnBzDa+j76K9hh/q+5ZZbsGPHDmzbts3106lTJwwePNh1m3Wlufbaaz3SCe3ZsweXXXYZACArKwsZGRmGv6G4uBjr16831FVRURE2b97s2ufLL7+E0+lEly5dXPusXr0apaWlrn1WrFiBli1bok6dOq59fNVnuJ05cwYxMcbDf2xsLJxOJwDWlS+RVDdWyhJuevC3d+9efPHFF6hbt65hO+sqjMI9C4WM3n//fZGQkCDmzp0rdu3aJR544AGRlpZmmMFpd6NGjRKpqaniq6++Evn5+a6fM2fOuPYZOXKkaNKkifjyyy/Fpk2bRE5OjsjJyXFt11Ob9OzZU2zbtk0sW7ZMXHrppaapTSZNmiR++OEHMXPmTNPUJnarb3kWsBCsK92GDRtEXFyceOGFF8TevXvFe++9J2rWrCnmz5/v2mfatGkiLS1NfPzxx+L7778X/fv3N03fkZ2dLdavXy/WrFkjmjdvbkhJUVRUJNLT08WQIUNEXl6eeP/990XNmjU9UlLExcWJGTNmiB9++EFMmTIl7KlNZMOGDRMNGzZ0pYH58MMPRb169cSjjz7q2iea66qkpERs3bpVbN26VQAQr7zyiti6datr5mok1Y2VsoSSr7q6cOGC6Nevn2jUqJHYtm2b4Xgvz+iNlrqKNAwAI9Abb7whmjRpIuLj40Xnzp3FunXrwl2koAJg+vPOO++49jl79qx48MEHRZ06dUTNmjXFHXfcIfLz8w2v8/PPP4tbb71VJCUliXr16omJEyeK0tJSwz6rVq0S7du3F/Hx8eLyyy83vIfObvWtBoCsK7dPPvlEXHXVVSIhIUG0atVK/O1vfzNsdzqd4umnnxbp6ekiISFB3HLLLWL37t2Gff773/+KQYMGieTkZJGSkiKGDx8uSkpKDPts375dXHfddSIhIUE0bNhQTJs2zaMsixYtEi1atBDx8fHiyiuvFJ9++mnw/+AKKi4uFmPHjhVNmjQRiYmJ4vLLLxdPPfWU4aQczXW1atUq02PUsGHDhBCRVTdWyhJKvurqwIEDXo/3q1atcr1GtNRVpHEIIaV+JyIiIqJqj2MAiYiIiKIMA0AiIiKiKMMAkIiIiCjKMAAkIiIiijIMAImIiIiiDANAIiIioijDAJCIiIgoyjAAJCJbuO+++3D77beHuxgVZvfyE1H1EhfuAhARORwOn9unTJmC1157DeHIW//VV1/hpptuwokTJ5CWllbl709EFAoMAIko7PLz8123Fy5ciMmTJ2P37t2ux5KTk5GcnByOohERVUvsAiaisMvIyHD9pKamwuFwGB5LTk726EK98cYb8dBDD2HcuHGoU6cO0tPT8dZbb+H06dMYPnw4ateujWbNmmHp0qWG98rLy8Ott96K5ORkpKenY8iQITh27Jjlss6dOxdpaWlYvnw5WrdujeTkZPTu3dsQxJaXl2PChAlIS0tD3bp18eijj3q0XjqdTkydOhVZWVlISkpCu3bt8MEHHwAAhBDIzc1Fr169XM87fvw4GjVqhMmTJwdavUREHhgAEpFtzZs3D/Xq1cOGDRvw0EMPYdSoUbj77rvRrVs3bNmyBT179sSQIUNw5swZAEBRURFuvvlmZGdnY9OmTVi2bBkKCwsxYMCAgN73zJkzmDFjBv7xj39g9erVOHToEB555BHX9r/85S+YO3cu5syZgzVr1uD48eNYsmSJ4TWmTp2Kd999F7Nnz8bOnTsxfvx43Hvvvfj666/hcDgwb948bNy4Ea+//joAYOTIkWjYsCEDQCIKDkFEFEHeeecdkZqa6vH4sGHDRP/+/V33u3fvLq677jrX/bKyMlGrVi0xZMgQ12P5+fkCgFi7dq0QQojnn39e9OzZ0/C6hw8fFgDE7t27TcuzatUqAUCcOHHCVT4AYt++fa59Zs6cKdLT0133MzMzxfTp0133S0tLRaNGjVzlP3funKhZs6b47rvvDO81YsQIMWjQINf9RYsWicTERPH444+LWrVqiT179piWkYgoUBwDSES2dfXVV7tux8bGom7dumjbtq3rsfT0dADAkSNHAADbt2/HqlWrTMcT/vTTT2jRooWl961ZsyauuOIK1/3MzEzXe5w8eRL5+fno0qWLa3tcXBw6derk6s7dt28fzpw5gx49ehhe98KFC8jOznbdv/vuu7FkyRJMmzYNs2bNQvPmzS2Vj4jIHwaARGRbNWrUMNx3OByGx/TZxU6nEwBw6tQp3HbbbXjppZc8XiszM7NS7ysCmKF86tQpAMCnn36Khg0bGrYlJCS4bp85cwabN29GbGws9u7da/n1iYj8YQBIRFGjQ4cO+Ne//oWmTZsiLi40h7/U1FRkZmZi/fr1uOGGGwAAZWVl2Lx5Mzp06AAAaNOmDRISEnDo0CF0797d62tNnDgRMTExWLp0Kfr06YO+ffvi5ptvDkm5iSi6cBIIEUWN0aNH4/jx4xg0aBA2btyIn376CcuXL8fw4cNRXl4etPcZO3Yspk2bho8++gg//vgjHnzwQRQVFbm2165dG4888gjGjx+PefPm4aeffsKWLVvwxhtvYN68eQC01sE5c+bgvffeQ48ePTBp0iQMGzYMJ06cCFo5iSh6MQAkoqjRoEEDfPvttygvL0fPnj3Rtm1bjBs3DmlpaYiJCd7hcOLEiRgyZAiGDRuGnJwc1K5dG3fccYdhn+effx5PP/00pk6ditatW6N379749NNPkZWVhaNHj2LEiBF45plnXK2Gzz77LNLT0zFy5MiglZOIopdDBDJwhYiIiIhsjy2ARERERFGGASARERFRlGEASERERBRlGAASERERRRkGgERERERRhgEgERERUZRhAEhEREQUZRgAEhEREUUZBoBEREREUYYBIBEREVGUYQBIREREFGUYABIRERFFmf8PFyNKH5JxKgYAAAAASUVORK5CYII=",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#print(accg)\n",
+    "#print(count)\n",
+    "\n",
+    "d = {'ppm': ppm, 'Acc (g)': accg}\n",
+    "data = pd.DataFrame(data=d)\n",
+    "\n",
+    "#data = np.array([time], [accg])  # Example data\n",
+    "print(\"Dataframe with Pore Pressure and Accelerometer readings\")\n",
+    "print(data)\n",
+    "#data = pd.DataFrame(data)\n",
+    "#print(data)\n",
+    "\n",
+    "#Plot the relevant data\n",
+    "def plot_interactive_sample():\n",
+    "    %matplotlib ipympl\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "    plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "    ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "    ax1.set(xlabel=\"Time Index\")\n",
+    "    \n",
+    "    ax2 = ax1.twinx()\n",
+    "\n",
+    "    #filter the pore pressure readings to show a smoother line\n",
+    "    c=1\n",
+    "    n = 50  # the larger n is, the smoother curve will be\n",
+    "    b = [1.0 / n] * n\n",
+    "    ppm_filtered = lfilter(b, c, ppm)\n",
+    "\n",
+    "    #Plot pore pressure\n",
+    "    ax2.plot(ppm, color = 'b', alpha = .2)\n",
+    "    ax2.plot(ppm_filtered, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "    ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "    plt.legend(loc = \"upper right\")\n",
+    "\n",
+    "    #below works well for sands but not clays\n",
+    "    '''plt.plot(data, label = (\"Pore Pressure (kPa)\", \"Deceleration (g)\"))\n",
+    "    plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "    plt.xlabel(\"Count\")\n",
+    "    plt.ylabel(\"Deceleration (g)\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "    #plt.show()'''\n",
+    "\n",
+    "plot_interactive_sample()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select the approximate peak deceleration for each drop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2 drops in file\n",
+      "Coordinates of Approximate peaks (index, acceleration): [17632.11112903226, 264.7887323595371, 88102.49161290322, 262.70347441992936]\n",
+      "Approx Peak Indexes: [17632, 88102]\n"
+     ]
+    }
+   ],
+   "source": [
+    "matplotlib.use('TkAgg')\n",
+    "\n",
+    "def peak_pick():\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "    plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "    ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "    ax1.set(xlabel=\"Time Index\")\n",
+    "    \n",
+    "    ax2 = ax1.twinx()\n",
+    "\n",
+    "    #filter the pore pressure readings to show a smoother line\n",
+    "    c=1\n",
+    "    n = 50  # the larger n is, the smoother curve will be\n",
+    "    b = [1.0 / n] * n\n",
+    "    ppm_filtered = lfilter(b, c, ppm)\n",
+    "\n",
+    "    #Plot pore pressure\n",
+    "    ax2.plot(ppm, color = 'b', alpha = .2)\n",
+    "    ax2.plot(ppm_filtered, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "    ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "\n",
+    "    '''plt.plot(data)\n",
+    "    plt.title(\"Select Drops (Enter to Exit)\")\n",
+    "    plt.xlabel(\"Count\")\n",
+    "    plt.ylabel(\"Deceleration (g)\")\n",
+    "    #plt.legend(\"Deceleration (g)\", \"Pore Pressure (kPa)\")'''\n",
+    "\n",
+    "    plt.grid(True)\n",
+    "    #plt.show()\n",
+    "    global approx_peak_index_list\n",
+    "    global num_drops\n",
+    "\n",
+    "    peak_approx_list = []\n",
+    "\n",
+    "    peak_approx = plt.ginput(n=-1, show_clicks=True)\n",
+    "    for t in peak_approx:\n",
+    "        for x in t:\n",
+    "            peak_approx_list.append(x)\n",
+    "    #user_input = input(\"Enter a value (press Enter to stop): \")\n",
+    "    plt.close()\n",
+    "    num_drops = int(len(peak_approx_list)/2)\n",
+    "    print(num_drops, \"drops in file\")\n",
+    "\n",
+    "    approx_peak_index_list = peak_approx_list[::2]\n",
+    "    for a in range(0,len(approx_peak_index_list)):\n",
+    "        approx_peak_index_list[a] = int(approx_peak_index_list[a])\n",
+    "    print(\"Coordinates of Approximate peaks (index, acceleration):\", peak_approx_list)\n",
+    "    print(\"Approx Peak Indexes:\", approx_peak_index_list) \n",
+    "\n",
+    "peak_pick()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select range for plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Start    End\n",
+      "1  14632  18132\n",
+      "2  85102  88602\n"
+     ]
+    }
+   ],
+   "source": [
+    "plot_start_list = []\n",
+    "plot_end_list = [] \n",
+    "index_list = []\n",
+    "for a in range(0, num_drops):\n",
+    "    peak = approx_peak_index_list[a]\n",
+    "    if peak <= 3000:\n",
+    "        plotstart = 1\n",
+    "        plotend = peak + 500\n",
+    "        \n",
+    "    elif peak > 119500:\n",
+    "        plotstart = peak - 3000\n",
+    "        plotend = 120000\n",
+    "    else:\n",
+    "        plotstart = peak - 3000\n",
+    "        plotend = peak + 500\n",
+    "    plot_start_list.append(plotstart)\n",
+    "    plot_end_list.append(plotend)\n",
+    "    index_list.append(a+1)\n",
+    "plot_ranges = {'Start':plot_start_list, \"End\":plot_end_list}\n",
+    "plot_range_df = pd.DataFrame(data=plot_ranges, index = index_list)\n",
+    "print(plot_range_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Refine peak picks to be maximum deceleration in the interval defined above"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2.7445742578132646, 2.7082354840603537]\n",
+      "17654\n",
+      "88244\n",
+      "[17654, 88244]\n",
+      "        acc  index\n",
+      "0  2.744574  17654\n",
+      "1  2.708235  88244\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3ad5192e159d4517a506139a8496b5e7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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48skn8f7772PXrl0AzF8EzII3zH5nf+5PgrAbJACJmEa1CnTq1AkAEwAA6/C9PXATExMN1i6RtLQ0nDhxAg8++KDPgok/fm5ubrEe/AsXLkRcXBwOHDigO//EiRN12/nTtqpVq+Kvv/7CsmXL3FGeALPMKYoijdgNhJYtWwKAYQizQYMGAIBNmzbplqsWmYSEBMOxduzYAQC4+uqrPZ5zx44dqF27ttuqBgCnTp0yfch7o3bt2vjuu+/w008/uaOqAZbfMFgiUR1e3bp1q2Hd/v374XA4dNY/GTVq1MBff/2F5s2bo2vXrkFplz9kZmbixIkTGDFihE9ic8SIERgxYgQAYPTo0XjrrbfwyCOPuIddS5UqhWeffRbPPvss8vPz0ahRI/z1119Yvnw5OnXq5D7H3r17dS8Fu3fv9rnNwbg/CcJKyAeQiFleeeUVLFmyBHFxce6qCvXr10fp0qWxbt06g8AAoEvxcdVVVyEnJ0cqDlSLynXXXYfCwkKpVeTkyZM4duyYafuysrJw9uxZPPfcc4Z1e/fuNQzpylCFHW+9mjFjBs6cOaPbTrWAqkNtnlBTYDz00EPS5YMHD/Z6DF8oUaIEUlNT3cOTKkOGDIHD4cD8+fN138Hdd99tKqr+/PNPJCUloVq1ah7P6XA4DMcYMmRIgJ8AuOuuuwAAr7/+uu43UMVLMGjSpAmSk5OxYcMGt98kACxYsAD//vsvatSo4fUYqk/gnXfeabB0FhYWuoeyQ4X6ffAvFCo5OTnuz7Vnzx5D+1TBqroUiG2Ni4tDo0aNAGjD+KrlXfU9BIBjx45hzZo1Prc5GPcnQViKdfEnBBF61Ki+jh07KiNHjlRuu+02pVu3bu7ULHFxccr8+fN1+3zxxRfuFBotW7ZUbr75ZqVTp05KhQoVlKSkJPd2YhqYwYMHK126dFFKlSqlzJs3T1EUlgamQoUKCgClWrVqyg033KBcf/31Sr169RSHw6GLZpSlgVFTplx++eXKoEGDlF69erkjKbdt26YoihYF3LNnT8PnHz58uDvlzJAhQ5SWLVsqDodDSUxMVFwul27bxMRExel0KgMGDFDuvvtu9/fiKQ1M1apVlQEDBrjnZWlg0tPTDe1KS0uTRuuK9OrVS5q+5YYbbnCngVFTsKgpS0qXLq3bVk0E3aZNG6/n49N4DBkyRLn00ksVl8tlSNliFl0+efJkBYAyefJk97KsrCxdGpjLLrus2GlgRNQ0MAkJCUrPnj2Vjh07uq/hVatWubdTf0v12uHp2rWrAkBJSUlRevTooQwaNEhp0aKFO+WKJ3yJtlcU7bqRUbduXff31KdPH6V///5KkyZNFKfTqYwdO1ZRFEXp06ePEh8fr7Ro0UIZMmSI0qtXL3daI/VzZmZmKmlpaUqHDh2UYcOGKW3btlUcDoeSnJys5OXlKYrCrgn1d+3evbvSq1cvJTExUSlRooQ0Clh2Dft6fxKEXSEBSEQ16oOJ/3M6nUrZsmWVvn37KgcPHpTu9/333ys1a9ZUnE6ne5/09HTlwQcf1G23c+dOpWHDhu7tVBG3Y8cO9zbnzp1Tunfv7haLDodDKVGihHL11VfrhI2sMsThw4eVrKwsJT4+3r1vSkqK0qtXL3duNE8CsKCgQOnSpYs7lUVycrIyYcIEpVatWgYB+M4777gfgOBSwsgE4IULF5Srr75aiYuLc3/urKwsXeoc9TMVRwBu2bJFAaCMHDnSsK5fv37uz1WyZEnl7bffVkqUKKGUL19et92zzz6rAFCWLVvm9Xz//POPUrt2bXf6knLlyinffPON4bfxRwDm5eUpV199tfsaKV26tLJw4cJiVQKR8dJLLykpKSnu369ixYrKV199pdvGkwBUFEV56KGHlNTUVPcxEhISlIYNGyqLFy/2eO5gCEBFUZSbb75Zdw0mJSUpLVq0UH777TdFURRl7ty5SvXq1d2/u8PhUNLT05UPP/zQfYwHH3xQKVeunPs3dLlcSt26dZXff/9dd645c+YoJUuWdG9z3XXXmaaBkV3DiuLb/UkQdsWhKEH2ViYIgggil112GY4ePep1eDo/Px8JCQm47LLLsG3bNvfyzMxMOBwOisokCILgIB9AgiBszezZs3H69GlMmzbNvezUqVMGX7CRI0dCURRdeppFixbhyJEjmDp1atjaSxAEEQmQBZAgiIhjypQpeOyxx9CmTRtUqFABv/76K7Zt24bExET8+++/7uTXBEEQhBxKA0MQRMTRvHlzpKamYvny5SgsLITT6UTt2rWxYMECEn8EQRA+QBZAgiAIgiCIGIN8AAmCIAiCIGIMEoAEQRAEQRAxBglAgiAIgiCIGIOCQIpBfn4+fvvtN1SsWNHvOq8EQRAEQVhDYWEhjh49iqZNmyIuLjalUGx+6iDx22+/oUWLFlY3gyAIgiCIAPj5559x5ZVXWt0MSyABWAwqVqwIgF1AmZmZFreGIAiCIAhfOHz4MFq0aOF+jsciJACLgTrsm5mZiSpVqljcGoIgCIIg/CGW3bdi95MTBEEQBEHEKCQACYIgCIIgYgwSgARBEARBEDEGCUCCIAiCIIgYgwQgQRAEQRBEjEECkCAIgiAIIsYgAUgQBEEQBBFjkAAkCIIgCIKIMUgAErYjOycbB04fkK47cPoAsnOyw9wigiAIgoguSAAStiI7JxvdPuqG9rPaY3/2ft26/dn70X5We3T7qBuJQIIgCIIoBiQACVtxJvcMjp07ht3/7UaH2R3cInB/9n50mN0Bu//bjWPnjuFM7hlL20kQBEEQkQwJQMJWVEmtgpXDVqJmmZpuEbhm/xq3+KtZpiZWDluJKqlUe5kgCIIgAoUEIGE7qqZVdYvA+tOb4eral2L3sUNu8Vc1rarVTSQIwib88QfQvTtwQO42TBCECXFWN4AgZFRNq4oF1R5B4813sAXPXcCH+9aQ+CMIAtk52TiTewZVUqugcWO2rGpVQFFYoFhKQgrSktKsbSRB2ByyABK2ZH/2fkx6bbFu2U3zbzYEhhAEEVvwgWJ7TlCgGEEECglAwnaoAR+frJyvW75nY01dYAhBELEHHyjW/rWbdesoUIwgfIcEIGErDpw+4O7EReK+ne4ODDHLE0gQRHTDB4rtf+d13brdJ/6hQDGC8BESgIStSElIQXrJdNQsU9OwLv/f6kic/QsqlEhHSkKKBa0jCMIOqIFiONZIt7z89kcoUIwgfMShKIpidSMilQMHDqBq1arYv38/qlSht81goTp4V00z/07pqiUIwuEwLqO+gfAFen6TBZCwIWlJaaic4vmGLCgIU2MIgrAlZr7A5CNMEL5BApCwJT17el4fRwmMCCJmUQPFZFCgGEH4BglAwpZ8+602fRYl4XTSuA5BEJ4DxQBQoBhB+AgJQML2lMR5FOTk4+xZ/fIePZgP0Pbt1rSLIIjw4ylQDAAq7huJ9JIUKEYQ3qAgkGJATqShg3fuVuAALl4EEhKkTt/u7ehKJoiYIDsnG5u3nUfbppnS9acuZFtWCSQvD0hIYNMXL7J+KSkJqFgROHLEkiYREuj5TRZAwoZIAzwKCwEAl11mvp/DAUycGJo2EQRhH9KS0kzFn7reKlTxBwCJiUz8AcDRo8D48da0iSBkkAAkbMcLL0gWFpn3tm3zvO+TTwJZWUwMqn+tWgFLl7L127cDW7cCubnGfV9+GVixonhtJwgi/GxGA9386dPWtOP8ec/rn30WBlcWIjKYNGkSrrzySqSkpCA9PR19+vTBdsH/qEOHDnA4HLq/kSNH6rbZt28fevbsiRIlSiA9PR0PPfQQ8vPzw/lR3JAAJGzHE09o06vQjk0UWQAdDuDHHz3vv26dfn7tWqBLF7ZvnTpA/frszfynn9j6N95g6x56COjUSS8eCYKwPw3wp24+LQ347LPwt6NkSe/bpJBrYkSyatUqjB49GuvWrcPSpUuRl5eHLl264Ny5c7rtbr/9dhw+fNj999JLL7nXFRQUoGfPnsjNzcWaNWswe/ZszJo1C+MtMg2TACRsTTv8wCY4B7/WrZmIKy5t2jCRd8895tvcfDM79ZtvAmPHAmeKyou++y5wyy2ARS9uBEEI/DvkXt18//7h9QseM8b3bc9QmeKIY/HixbjllltQv359NG7cGLNmzcK+ffuwceNG3XYlSpRARkaG+y81NdW9bsmSJdi6dSvmzJmDJk2aoHv37nj22WcxdepU5MqGpUIMCUAiMiiyAKps3AgsWwbk5AAHQpjtYc4cwOkE7r4bmDwZSE0Fpk0D7rwTmD2bWRYJgggvx48bl5WLN477OsP4hJs61Xyd+MLKaQIiQsnOzgYAlC1bVrf8o48+Qvny5dGgQQOMGzcO5zm/gLVr16Jhw4aoWLGie1nXrl1x+vRp/Pmn3oodDiidbhDIz89HXl6e1c2ICv79FwDi3fN5yclFE3nsrwinE2hXNDqcns58+hIStP1CyV13adPffw/67QkizNx8swuq/WJm/G3Ii0s29dno2rUQixaFrnTQqlUOXHON8VGam6vvF8T+6eLFvLAKVEKP6nd35swZnOacRhMTE5GYmOhx38LCQtx3331o3bo1GjTQ/E8HDx6M6tWro1KlSvjjjz/wyCOPYPv27Zg/fz4A4MiRIzrxB8A9f8SCEHESgEFg7dq1KFGihNXNiAoeeaQtAPZGdc01/+Cb0R+zFd4c/wDMm+fEgAHXAgCGD9+C667bhZ07S+PgwVKYPLmZ1/1vuWULZs1q4HU7kW+++cbvfQiCCJzvvrvOPZ32SW984+rNZt43brtkiRMJCU6MG7cekyZdhczMs5g2bTkA4PjxZDz9dBYA4LXXVsDlMj/n8eNJqFAhx7C8T5/rDMs++uhrfPON3j/khRfK4NFH27nnk5LisXDhF+YnJEKKapmrV6+ebvmECRPw1FNPedx39OjR2LJlC34Unkt33HGHe7phw4bIzMxEp06dsGvXLtSqVSs4DQ8ilAewGKh5hPbs2YPKlStb3ZyogH9LPv/We4h7oMiv559/gDJlAj7ul186cMMNcdixIw+XXAL89RfQuLF2rgYNFPz6az6ys4EXX3TiwgVg6lQPTwOOnBx6kyeIcML3E7nJRS/ffftCmfk+Vqxw4MEHXfjzT89RXDNm5OO22/Q2kNzcPEya5MTXXzuwcmUBSpQwjirk5ubhs88c+P57B+64oxBXXqnfZurUAtx+e6FhPwDIzIzDiRNau6pVU7BzJzkSW8HBgwdRo0YNbN26Vff89mYBHDNmDL744gusXr0aNWrU8HiOc+fOoVSpUli8eDG6du2K8ePH48svv8SmTZvc2+zZswc1a9bEr7/+iqZNmxb7c/mFQgTM/v37FQDK/v37rW5K1MDcttmfMm2aNnP8eNDPdfEiO/T993tvy5QpirJ3r36Z+te1a9CbRhCECTk5Qj+hTtxwg3ubwkL5vRqMv9tu87y+sNC87bJ2Edbg7/O7sLBQGT16tFKpUiVlx44dPu3z448/KgCU33//XVEURfnmm28Up9OpHD161L3NO++8o6Smpio5OTn+f4hiQkPAhH3hAz9CYKhOSPB8WEVhUb5xXu6S774LbrsIgjBHTaxsgMsg73CwXIChCLaYMUO+fPRoli3AEzI3xT//DE5WAyK0jB49GnPnzsUXX3yBlJQUt89eWloakpOTsWvXLsydOxc9evRAuXLl8Mcff+D+++9Hu3bt0KhRIwBAly5dUK9ePdx888146aWXcOTIETzxxBMYPXq0V7/DUEADV4RtMKRU4dVZoXxIJdSI4o/SNxCETRH6iJQUYM+e8J3em/hTEWPGGjTwnuCesJ5p06YhOzsbHTp0QGZmpvtv3rx5AICEhAQsW7YMXbp0QZ06dfDAAw+gX79++Oqrr9zHcLlcWLRoEVwuF7KysnDTTTdh6NCheOaZZyz5TGQBJGzD5Mna9DXXQN+hWyQARUqVYk0RE0UrCiWOJohws/jrAqBn0YykhuQll7BUUaZWQwuIiwN27wZq1tSW1a3LrJVFmUUIG6J4GYWqWrUqVq1a5fU41atXt03gIFkACdvw8MPa9OefI+RDwIGiCj0+6//nn1vTFoKIZbp25kSftIg4q/ozbhybvusuY1firWu54w7v29x0k5eGCshiB06fBm680b/jEERxIAFI2JKUFOg7dJtYAHkOHtSm+/e3rh0EESsYhkp5ZWYiAAHg+efZpmqy5rFj2f+Pi7JMXbwIfP01yydaUMCGaR94gNUHf+cdts25c9r2Ip6SQPvDp58G5zgE4QskAAn7YlMLoEpamtUtIIjYgi+3tm8f9H2EBwEo8sorrEsZOJDNJyQAPXoA8fEsyXxcHBN/Dzyg7VOiBNu+sBA4epTtX1jIxGIgwSY7d8qXDx3q/7EIIhBIABK2QJoE3YY+gJ5YvNjqFhBEdLN8uTZdtSp8tgAGE4eDVR9Sp71lCTCjVi3W5N279cs//LB47SMIXyEBSNgC3iHa7QtocwugSPfuVreAIGKMAC2AdsHpZP6ArASmBgWUEeEgKgTgpEmTcOWVVyIlJQXp6eno06cPtm/f7nGfWbNmweFw6P6S7BQqFmNcuKBNv/BC0UQEWAC3brW6BQQRw1hgAQwF5coZl1HKKSLURIUAXLVqFUaPHo1169Zh6dKlyMvLQ5cuXXDu3DmP+6WmpuLw4cPuv71794apxYQn3G+/EWABrFtXP29TnUoQ0UkU3XBiBpHUVNt2e0SUEBV5ABcLzlezZs1Ceno6Nm7ciHbt2pnsBTgcDmRkZIS6eUSg2DwKWIbLRZ02QYSCixclC6PoZpM9qj78kIJCiNARFRZAkeyibJply5b1uN3Zs2dRvXp1VK1aFddddx3+/PPPcDSPEDh61GRFBFgAAWDHDqtbQBDRD++hM2lS0USEvBj6yokT+vlhw8yjhQmiuESdACwsLMR9992H1q1bo0GDBqbbXX755Zg5cya++OILzJkzB4WFhWjVqhUOHDhgus/Fixdx+vRp998ZctIICrwRdtkybkUE+AACLJqPR+zECYIILnfcUTRh434hEMqWBR5/XL+sdm1r2kJEP1EnAEePHo0tW7bgk08+8bhdVlYWhg4diiZNmqB9+/aYP38+KlSogHfUrJ8SJk2ahLS0NPdfvXr1gt38mKdTJ24mQiyATuEuKl/emnYQRKzgHtyxcb8QKBMnGpf17h3+dhDRT1QJwDFjxmDRokX4/vvvUaVKFb/2jY+PR9OmTbHTg7193LhxyM7Odv9tpRDQ0BJBPoC//KKf97c0FEEQARAhL4n+0quXfv6rr6xpBxHdRIUAVBQFY8aMwYIFC7BixQrUkBVa9EJBQQE2b96MzMxM020SExORmprq/ktJSSlOswmYOHar5OVp0zbv3Js3189/9JE17SCIaCQ3V5uuX59bwfcLNu8j/OHLL61uARELRIUAHD16NObMmYO5c+ciJSUFR44cwZEjR3CBSy43dOhQjFMrggN45plnsGTJEuzevRu//vorbrrpJuzduxcjRoyw4iPELAsXelj56qvatM0tgICxHjAZiAkiOPCRsE8/za2IED9hf3E4jHpWTBNDEMUlKgTgtGnTkJ2djQ4dOiAzM9P9N2/ePPc2+/btw+HDh93z//33H26//XbUrVsXPXr0wOnTp7FmzRry6wszai1OwEu0WwS83YtWP52lgiCIgOG6cvTpw62IUgugyvz52nSHDpY1g4hSoiIPoOLDjb9y5Urd/OTJkzF58uQQtYgIBDGaVkcEvN3HxzMRe+ml2rIXXwQeecS6NhFEtOFycTNRagFUuf56q1tARDNRYQEkYoAIebsXReyjj1JdT4IoDvn5HlZGuQVQpCjFLUEEBRKAhGX41V9H+Ns9iUCCCIzvv9emdWmigKiNAjajdGmrW0BEEyQACct47z0/No6gzt0ssplEIEH4T5cu2rRQ9VPfL0T4S6IZo0fr5yOoKyRsDglAwjLuvFOblka4paZq0xHUuSckAOPHy9dxgekEQfhJnOi1HgMWwDfe0M97qXBKED5DApCwBbJC6ODzOUZY5/700/oSdyqU0Z8ggkgMWADFkYNTp4Djxy1pChFlkAAk7EuER/gdPgycPatftmwZsG6dNe0hiKgjwvsIXxE/Wnq6Ne0gogsSgIQl+BTNFgURfiVLAufO6ZdlZVnTFoKINP79V5u+4QbJBhHaL/gL+Q8ToYAEIGEJfJLkpUtNNoqS4Z0SJYzLbrkl7M0giIjjmmu06YkTJRvEgA+gyowZ+vmXXwaWLIn6j02EEBKAhCUcPKhNG1I7qESJAATYcDDP7NnWtIMgIolNm7Tpyy+XbBAFowS+cuut+vmHHgK6dgWcTuDECS/5EglCAglAwnJMhzeiqHPPyDBG7508aU1bCCJqiPAXQ385c0a+vHx5VomIf7EmCG+QACTsSxRZAAH2ls5Trhywfn3Ea1uCCAk+3fIxNAQMAKVKeV5fpQpw+nR42kJEPiQAibCzerWPG0Zhh/7aa/r5li2ZLw9BEHqkuUFForCP8Mb69Z7Xp6WFpx1E5EMCkAg7Xbtq0x47syh8u7/7buOyhx8OfzsIwu507KhNDxtmslEU9hHeaNHC+zZRMGBChAESgETYycnRpj12ZlHkA6jicACvvGJcPmZM+NtCEJGCadnIKOwjfEFR2F9urnx9tWrhbQ8RmZAAJOxLlHboMrE3dWr420EQkUJ8vMmKGDd1xcdrYrBKFW35wYOUO5DwDglAwr5E6dt9QgJQUAD8/LN+uaHQPUHEKJs3+7hhlPYRgbB/v3HZV1+Fvx1E5EACkAgrftWwjOLO3ekErrxSv6x7d2PVEIKIRYYO1aafftrDhjHoA+gPVHuc8AQJQCKsNGqkTR865GXjGOjQ//tPP1+qFHDxojVtIQi7wCeAHj/ew4Yx0Ef4g2xEPC8v/O0gIgMSgERYOXJEm87M9LJxFFsAVUqXNi5LSqJOmyB8giyAOhwOY7LohARr2kLYHxKAhH2JAQFoBnXaBOEDMdxHmFGqFPDCC/plBQXWtIWwNyQACfsSIxF+//wjX56VRR03EXscPerHxiT6pDzyiH7+rrusaQdhb0gAEvYlRt7uq1eXf7x164C4OHOBSBDRyP/+p03PnOll4xjpI4rLu+9a3QLCjpAAJMLG339r023b+rBDjHXuZgbPGjVi4uMTBAB9ovThw71sTDeGKWKAGUGIkAAkwgbvnPzJJz7sEGOdu8MBXLggX1erVnjbQhARQYy9JPqDGGD2xhuWNIOwMSQAibDRrJk2XamSDzvEYOeelARcc41x+Z495uKQIGIWigL2CC/67rnHunYQ9oQEIGFfYrRDX7JE/tFLlAh/WwjC1sRoH+ErYtlJKg9H8JAAJOxLDFoAeagqCBFr+O23FuN9RCD88YfVLSDsAglAwr7E+PBOiRLAL7/ol33/vTVtIYhwUK+eNs1HA5tCAtArc+bo5xs3Btavt6YthL0gAUiEhWXLtOlx43zciTp0NG+un+/YEfjtN2vaQhChhq8U9MADPuxAfYRXhgwxLmvZMvztIOwHCUAiLPCBDT4nJaW3ewDAtm36+SuusKYdBBFOfPJXoz7CJw4eNC4jf0CCBCARdqpU8XFD6twBAJdfblxGnTdBIKb7BX+oVAm48Ubj8s8+C39bCPtAApCwL9S5uxk/3rhswYLwt4MgbEWM+wn7w7x5wDPP6Jf1709+xb4yadIkXHnllUhJSUF6ejr69OmD7du367bJycnB6NGjUa5cOZQqVQr9+vXDUaG24b59+9CzZ0+UKFEC6enpeOihh5Cfnx/Oj+KGBCARcgLul8kC6Obpp43L+vYNfzsIIlTwieJ9hvoIv3jiCeOyjh3D345IZNWqVRg9ejTWrVuHpUuXIi8vD126dME5Ll3D/fffj6+++gqffvopVq1ahUOHDqEv11EXFBSgZ8+eyM3NxZo1azB79mzMmjUL42Vv+GGABCARcpYu1abbt/djR+rcdfz1l3HZwoVhbwZBhAQ+MOH1133cifoFv3A4gIsXjcv37Al/WyKNxYsX45ZbbkH9+vXRuHFjzJo1C/v27cPGjRsBANnZ2ZgxYwZeffVVdOzYEc2aNcP777+PNWvWYN26dQCAJUuWYOvWrZgzZw6aNGmC7t2749lnn8XUqVORm5sb9s8UF/YzRiH5+fnIy8uzuhm2pWvXePf0//1fHnz+qhITgeRkbT7Gv+NatYDcXCAhQfs+r78eOHw4D+XKWdgwgggCW7dq1/Wdd/rYTxQWan1EYmLM9xG+4HAAO3cCl16qfd81awK5ubH13anDrmfOnMHp06fdyxMTE5GYmOh1/+zsbABA2bJlAQAbN25EXl4eOnfu7N6mTp06qFatGtauXYuWLVti7dq1aNiwISpWrOjepmvXrhg1ahT+/PNPNG3aNCifzVdIAAaBtWvXogSVafDAde6ptWu/8X23997Tz3/jx75RTOPGWfj993T3fGZmPBYu/MLCFhFEMND6iW+/9eNe//hjbZr6CJ/p1KkJli+v7p7/3//Wo379Exa2KLycP38eAFCPTz4JYMKECXjqqac87ltYWIj77rsPrVu3RoMGDQAAR44cQUJCAkoLRZgrVqyII0X5jY4cOaITf+p6dV24IQEYBLKyslC5cmWrmxER9OjRw/eNMzOBopsUH34I9O4dmkZFGD16AAkJ+mXnzvVE//40HEZEBz73E998AwwaxKbT04G//w5do6IMsR95/PE2aNpUwfr11gQkhJuDRblxtm7dqnt++2L9Gz16NLZs2YIff/wxZO0LByQAg0BcXBzi4+O9bxiDiC46fn1P588DFy7wOwenUVHAmDHAm29q80OGxGHQIEoPQ0QHfvUTah9x4QL1EX7y0Uf6RNG//ebAtGnxuOce69oULuLimPxJSUlBamqqz/uNGTMGixYtwurVq1GFy2mWkZGB3NxcnDp1SmcFPHr0KDIyMtzb/Pzzz7rjqVHC6jbhhIJAiJDyRXFGJikIxJQ33gD69dMva9jQmrYQRHH5/XdtWryuPUJpYIrF4MHGZffeG/52RAKKomDMmDFYsGABVqxYgRo1aujWN2vWDPHx8Vi+fLl72fbt27Fv3z5kZWUBYKOFmzdvxrFjx9zbLF26FKmpqYah6HBAApAIKddfr03/3//5uTMJQI+ISVz//JOigonIpEkTbXrGDD92pH6h2MjS7/z0U/jbYXdGjx6NOXPmYO7cuUhJScGRI0dw5MgRXCiyQKelpeG2227D2LFj8f3332Pjxo0YPnw4srKy0LIoxL1Lly6oV68ebr75Zvz+++/47rvv8MQTT2D06NE+DT0HGxKARNjo39/PHahz98rw4fp5XnATRCSSlubHxvSSWGxKlTKKwDZt9MZVApg2bRqys7PRoUMHZGZmuv/mzZvn3mby5Mno1asX+vXrh3bt2iEjIwPz5893r3e5XFi0aBFcLheysrJw0003YejQoXhGzNAdJsgHkLAv1Ll7ZeZM4P339cv++Qe45BIrWkMQYYb6haBQqhRzK7n7bm2Zy0VfL4/iw5eRlJSEqVOnYurUqabbVK9eHd/YJFqdLICEfaFXUJ8QC70LrikEEb3QS2LQGDPGuEzIWEJEGSQACftCnbtPVKoEFCWjJ4iIgxtBQ5cufu5MfURQEQNAuFgFIgohAUiEjGKnSKLO3WeuuEI/z5WnJAhbM3CgNs3ndPYJ6heCypQpxmVvvx32ZhBhggQgETLattWmd+8O4ADUufsFV4EIPXta1w6CCJSiqlq+Q2lggo74NY4aZU07iNBDApAIC8X2S6PO3St8WphVq4B9+6xrC0GEBRolCAliVTJZqhgi8iEBSNgTsTOnzt0rYvqM6tXl2xFE1ED9QkgQgz/8KJRBRBAkAAl7Qh17UHjtNatbQBDm5OYW8wBkASSIgCEBSNgTMQUMde4Bcd99QHa21a0gCDl89PoHHwRwABKAIePUKf38kiWWNIMIISQAiZDA56YLyApFnXlAyL42ri45QdiKVq20aT6IyWeonwgZoktJ167WtIMIHSQAiZBw663a9E03BXAA8gEMGMqfTUQimZkB7EQWwJBy+LDVLSBCCQlAIiTwwwV+p3YASAAWA4cD2LFDv2z9emvaQhAhhd52QkpGhn7+jjusaQcRGkgAEvaEBF+xqF1bP9+ypTXtIAgzgnKLkwUw5FSrpk2/95517SCCDwlAwp6QBbDYiMM3zz5rTTsIQgZfZizgmrMkAEPOzp1Wt4AIFVEhACdNmoQrr7wSKSkpSE9PR58+fbB9+3av+3366aeoU6cOkpKS0LBhQ3zzzTdhaG30E/Q3eyIgxOGb8eMpko+wD4sWadN8PWC/oH4i5MTH6+cdDmvaQQSfqBCAq1atwujRo7Fu3TosXboUeXl56NKlC855KIi6Zs0aDBo0CLfddht+++039OnTB3369MGWLVvC2PLohLc0PfxwgAchC2BQyMrSz3ftCuTlWdMWguAZMUKbbt8+wIOQBdAS7rzT6hYQwcChKNF31xw/fhzp6elYtWoV2rVrJ91mwIABOHfuHBZxr6EtW7ZEkyZN8LaP1a8PHDiAqlWrYv/+/ahSpUpQ2h4N8G+IW7YA9esHcJAzZ/Tp52fNAoYNK27TYhLZG3v03fVEpMFflwFfj+++q6mR5GTg/Plit4swcvw4kJ6uX5afD7hc1rQnGNDzO0osgCLZRZlvy3oIP127di06C4mnunbtirVr15ruc/HiRZw+fdr9d4YKJHolIPEHkAUwiMieiRQ8SUQFdCGHhQoVjMvi4oALF8LfFiJ4RJ0ALCwsxH333YfWrVujQYMGptsdOXIEFQXP44oVK+KIWAWbY9KkSUhLS3P/1atXL2jtJgRI8AWN5GTgqaf0y8S3eYKISGgIOGzIgkFKlAh/O4jgEXUCcPTo0diyZQs++eSToB973LhxyM7Odv9t3bo16OeIdP79N0gHIgtgUJkwQT9/4gSwebM1bSGIoBnuqF8IG7VqAbt3W90KIphElQAcM2YMFi1ahO+//97rmH5GRgaOHj2qW3b06FFkiKGTHImJiUhNTXX/paSkBKXd0cQ772jTxXLZo4496IgP3UaN6GsmrCGg6kAyyAIYVmrUAFat0i+jqODIJSoEoKIoGDNmDBYsWIAVK1agRo0aXvfJysrC8uXLdcuWLl2KLDFskvCLJ57QpqdNK8aByAIYdGQddcBR2gRRDD7+WJueM6cYByIBGHZkcZX01UcmUSEAR48ejTlz5mDu3LlISUnBkSNHcOTIEVzgPFSHDh2KcePGuefvvfdeLF68GK+88gq2bduGp556Chs2bMCYMWOs+AhRSXJyMXYmARgSxGHfl1+2ph0EoTJkSDF2pn7BEg4c0M87o0JJxB5R8bNNmzYN2dnZ6NChAzIzM91/87jsovv27cNhrjRCq1atMHfuXLz77rto3LgxPvvsMyxcuNBj4AgRRii6LyQ0aAD8+qt+2eLF1rSFIIoNWQAtoXJloFkz/TLKLxp6Ll4EVq8GPvyQuVvNnw/s2RP48eKC1zTr8CWV4cqVKw3L+vfvj/79+4egRUSxIQtgyGjaVD/fvTvw119AnTrWtIeILQ4dCuLB+BdF6iPCyoYNereShAT6CULFTz8Br70GfPUVE9ppaWyE7eRJJgpr1gTuuAMYORLwJzQhKiyAhD0Iak4o6knCSt26VreAiBX4qh/FrihB/YSt6NbN6hZEH717AwMGAJdcwkp5njnDsjgcOMByvP79N/O9X74cuOwyYOlS348dFRZAwh48+qg2Xex0AWQBDCm7d7O3RoIIN3w+Ob5sZEDQELClnD6tL9j03XfA118DPXta16Zoo2dP4PPPjTWZVWrWZH/DhgFbtwKcp5tXyAJIBI3XX9emfQjE9gx15iGlRg3jw5fSORDhRlZhwi9IAFpKSoqx2lOvXta0JVq5805z8SdSrx7QqZPvxyYBSNgTsgCGHD5lD0FEJNQvWM6WLcZlDgfF8UUCJAAJe0Ide1gQv+beva1pB0EEBFkAbcHZs8ZlVCk1+BQUsNRdLVoAGRlA2bL6P38hAUjYE7IAWsJXXwGjRlndCoLwEeoXbEHJksz/j2f7dmvaEs08/TTw6qssKCQ7Gxg7Fujbl+VhFOu9+wIJQCIo8Ob+oCQFpfGDsPHHH/r5t99mqQUIItjk5mrT118fhANSGhjb0KWLcVnfvuFvRzTz0UfAe+8BDzwAxMUBgwYB06cD48cD69b5fzwSgERQWLhQm/7hhyAckCyAYaNhQ+OyRo3C3w4i+nnvPW2arxseMNQv2Arx51iwgH6iYHLkiNZflyrFrIAAC7z5+mv/j0cCkAgKgwdr0y1bBuGA1GuEFdHit2MH/QRE8OErbZYvH4QD0kVqO8S+5I03rGlHNFKlipbmpVYtlhcQAH75BUhM9P941uUBLCwEVq1i5qK9e1lGwwoVWJmCzp2BqlUtaxrhP/xNH5QhYLIAhpWEBODcOebLo3LttcCiRda1iYhugpJ2SNZPUD4jS0lI0M/fey9wzz3WtCXauP56lvD5qquAu+8GbroJmDED2LcPuP9+/48XfgvghQvAxIlM4PXoAXz7LXDqFOBysQyhEyawJGU9egQ2qE1EByQAw06JEvr5r79miUUJwrZQP2FLfvpJP79qlTXtiDZeeAF47DE2PWAAs5+NGgV89hlb5y/htwBedhmQlcWcQa65Rp7hcO9eYO5cYOBA4PHHgdtvD3szCYuhjtwSfvgBaNtWm69fn34KwsbQxWlLWrXSz3foQD9VcZk3D/jySxZI1akTq/vbsmXxXK7CLwCXLPFeeLR6dWDcOODBB5ltk7A1BQUhOCi92VtCmzbGZQ4Hff1E8eFzxTVpEqSDUj9hW8Ryk//8w+rZEv4zbRowejRQuzaQnAzMnw/s2gX873/FO274h4D9qTofH888HQlb8/vv2vRLLwXpoJQGxjI+/9y4jI/eJIhA4APFXnstSAelfsK2iOVAi10eNIZ5803mHbd9O7BpEzB7NvDWW8U/rrVRwH/8If/bvBn4+29KRhYhjBihTd94Y5AOSm/2liHL3XXHHeFvBxFdfPWVNh2UTAEA9RM2RxxRoEd6YOzeDQwbps0PHgzk52sRwYFiXRQwwMYBPEVsxcczT8d33gGSksLWLMI/fvtNm65ePUgHpY7cUnJzjdF8o0axoQiCKC7itRUwJABtzQ8/6B/xSUn0EwXCxYv6DA1OJ7uHLlwo3nGtFYALFgCPPAI89BArbgcAP/8MvPIKs3fm5wOPPsqq1r/8sqVNJcIMdeyWEh9vzKjx9tskAAmbQf1CxLFrF3l2BcKTT+ozNeTmAs89B6SlactefdW/Y1orAJ97jjmDdO2qLWvYkGU7fPJJJgZLlmR1T0gAxhbUsduCX38FrrhCmydHbsJW0Iui7cnL0yf7uPRS+pn8pV07Y23lVq3Y0LBKIOkvrRWAmzfLxwyrV2frADZMXNyBbiLyoI7dFjRtqp+vUYN+CsJ/VqwI0YGpn7A9cRKV8d57lN3NH1auDM1xrQ0CqVOHZS/kK4Tn5bFldeqw+YMHgYoVrWkf4ZVt27Tpyy4L4oGpI7cNWVn6+blzrWkHEbl06qRNnz4dxANTPxERiMHaFFQWGFu2mK9buND/41krAKdOZbWmqlRh5d86d2bTixZpzka7dwN33WVpMwlzHn1Umw6kGLUp9GZvG8Ss/kOGkFGeCJyUlCAeTFQW1E/YEofD+CIZ1BeBGKFrV2DPHuPyzz9n/bK/WDsE3KoV+zQffcSqzwNA//4sxlntJW6+2br2EV754gtt+tJLg3hg6thtg8MBrF/P6k+qVKrERGBGhnXtIgh6UYwc1qzR+6mlpdHP5S8jRjA72U8/aX3vvHnArbcCs2b5fzxrLYAAE3ojR7LwlVdfBe68M8iviEREQj2DrVCD9HkyM8PfDoLQQf1ERPHjj/r5nBxr2hEIq1evxrXXXotKlSrB4XBgoTDmesstt8DhcOj+unXrptvm5MmTGDJkCFJTU1G6dGncdtttOMuXyPHC008DPXowEXjyJHPHGT4c+OADZjvzl/ALwHXrfN/2/Hngzz9D1xbCvtCbve1o3ty4bP368LeDINxQPxFRtG6tn09OtqYdgXDu3Dk0btwYU6dONd2mW7duOHz4sPvv448/1q0fMmQI/vzzTyxduhSLFi3C6tWrcYefDpFvvAE0bsySqd9+O/Dxx0C/fgF9JAuGgG++mRUIHDGCSVk+u6HK1q3AnDnA++8DL77IKtITsQV15Lbjl1+MqQZatqSfivDMzp3a9D33BPngdPERYaJ79+7o3r27x20SExORYeIX89dff2Hx4sX45Zdf0LzobfqNN95Ajx498PLLL6NSpUrS/b780risb1+WZHvQINYnq9v07u375wGsEIBbt7IAjyeeYL5+l13GHIqSkoD//mNhpWfPAtdfDyxZwvICErYkLy+EB6c3e1siJocGWPBPz57WtIewP9dco00/8USQD079RMQh9iGvvx6CFwOLWLlyJdLT01GmTBl07NgREydORLly5QAAa9euRenSpd3iDwA6d+4Mp9OJ9evX4/rrr5ces08f8/PNnMn+APadFhT4197wC8D4ePZr33MPsGEDcwrYu5fVNGncGLj/fuDqq4GyZcPetEDJz89HXkjVkD1hqRpZhs9PP81HXl4QO9+CAv34gMMRYsVJ+AorE6dldu3VC8jNpd+GkPPPP9q1Urp0XnBvY6dT30/k5VE/ERFo18S99wKjRoX/N8vPzwcAnDlzBqe5kOTExEQkJib6fbxu3bqhb9++qFGjBnbt2oXHHnsM3bt3x9q1a+FyuXDkyBGkp6fr9omLi0PZsmVx5MgR0+OK8ZDBxNoo4ObN5Y5FEcbatWtRgq/REiNMmJAFgF3QTufX+OabIJ9A8J8I/gmIQHn44Uy89JIWGfIN/TaEKde5p4J+nbRpw/5UVq0K7vGJkPDppw7076+NV77xxk+oVSs7rG04f/48AKBevXq65RMmTMBTTz3l9/EGDhzonm7YsCEaNWqEWrVqYeXKlejEJ8K0EdYKwCghKysLlStXtroZYadPH+0t7tprewT34Bs26LPHTpwI3H13cM9BBEyPHsBLL2nz9ev3kBb1IQieHj2C3E888ggrUq1y8CBQqlRwz0GEnAce6BD2UYSDBw8CALZu3ap7fgdi/ZNRs2ZNlC9fHjt37kSnTp2QkZGBY8eO6bbJz8/HyZMnTf0GAeCTTwBOW3pk/35g3z5jsI0ZJACDQFxcHOL5YocxSNA/v8PB3AJUCgv1BSUJy2nZUgvqr107HgUFbESOIMwIej+Rn6/vJ1wu6icihEGD9IM8Tmc8XK7wnT+uqEZdSkoKUlNTg378AwcO4MSJE8gsypeVlZWFU6dOYePGjWjWrBkAYMWKFSgsLMRVfJJVgWnTWPqX4cOBa68F6tbVr8/OZnkB58wBli4FZszwvY3UXRP2hJy5bc/8+fr5cHbeRGQQSv8lANRPRDAffKCfl9UMthNnz57Fpk2bsGnTJgDAnj17sGnTJuzbtw9nz57FQw89hHXr1uGff/7B8uXLcd111+HSSy9F165dAQB169ZFt27dcPvtt+Pnn3/GTz/9hDFjxmDgwIGmEcAA82p48UUm7ho0AFJTgdq1WXxslSpAuXIsEXS1aqxUnD+RwDb/ygm7wpdvDgkU3Wd7ZImgu3cHvv02/G0h7AmfxvXZZ0NwAuonIpa4OGDcOGDSJG3Zvn1MyNiRDRs24Oqrr3bPjx07FgAwbNgwTJs2DX/88Qdmz56NU6dOoVKlSujSpQueffZZ3ZDyRx99hDFjxqBTp05wOp3o168fXn/9da/n7t2b/f37rz5utnx5oGlT9hfI6AsJQCIgHntMm77iihCcgDr2iGTxYnmqGCI2adRIm+brhgcN6icimuef1wvA6tXt+xN26NABiofGfffdd16PUbZsWcydOzfgNpQv7zktjL9YLwCXL2d/x44ZxwvUBDeE7XjlFW16zZoQnMCuvQCho7DQ+ObpdNLPRxgJyRAfXWhRR3o6kwNE6LHWB/Dpp4EuXZgA/Pdflgia/yMigiAFTemhN/uIwOFgfvgidPsSYUE0GlA/EXGI/cfx4yzpAxF6rLUAvv02MGsWKw9HEDzUkUcMLhfL280HgZQtSz8hEQZCHmVChBqXC9i0CWjSRFv25JPALbewIAcidFhrAczNBVq1srQJhE2hN/uIQuaA3KFD2JtBxBrUT0QFjRsbl1WtGv52xBrWCsARI4BiOEQS1hCWPpY68oijKLG+GyrKENvIXAOCDgnAqCHkmSWiiNxcYPv24t9j1g4B5+QA774LLFvGwsXEBJ6vvmpNuwiPbNyoTb//fohOQj6AEUdyMvDhh3qPDoeDfrpY5Y03tOmQpIABaAg4ioiPBw4f1qeXOnMGSEmxrk124/x5VhBr9mw2v2MHULMmW1a5sv+R9tZaAP/4gw38O50sg+Fvv2l/RckWCftx5ZXa9C23hOgkpBoikptuMi7bsiX87SCspyhNGgBg6NAQnYQsgFGFWBEtNZV+Up5x44DffwdWrgSSkrTlnTsD8+b5fzxrLYDff2/p6QkbQxbAiGXDBqB5c22+YUP6+WKdkCX3JQEYdcycySpbqFBaKY2FC5nQa9lSn2u1fn1g1y7/j2efUnAHDrA/ggDojo9gispc6hD9AwkiKNAQcNQxfLhx2ahR4W+HHTl+nOVJFDl3LrDk+9YKwMJC4JlngLQ0lgK8enWgdGnmMEI3dmxDFsCIRvy5Spa0ph1ElEMWwKjkhx/082+/bU077Ebz5sDXX2vzquibPh3IyvL/eNYOAT/+ODBjBvDCC0Dr1mzZjz8CTz3FAkSee87S5hEWQi8AEU+bNux2VunWjZWKI6KfsN2+1E9EJW3asCCiu++2uiX24vnnWb31rVtZBPBrr7HpNWsCy7pgrQVw9mwmXUeNYlHAjRoBd90FvPceSxBN2I6wvWCTBTDiEd/iv/suTKlBCMtZskSbHjgwhCciC2DUMmYMGxAEgF9+sbQptqFNGxYEkp/PfKuXLGFDwmvXyl1vvGGtBfDkSaBOHePyOnXYOsJ2PPGENs2neQg6JACjkvh4+iljgfnztekZM0J4IhKAUQ2VlNTIywPuvJNVSXnvveAc01oLYOPGwJtvGpe/+aY8NThhOc8/r03ffnsIT0QdeVSQl2d1Cwgr4B9QJUqE8EQ0BEzECPHxwOefB/eY1loAX3oJ6NmTJYJWPRjXrgX27we++cbSphHeSUwM4cHJAhgVxMUxd14+ZxUlhyaCBlkAiRiiTx+WCub++4NzPGsFYPv2LJX11KnAtm1sWd++zA+wUiVLm0ZYDHXkUYPsReHVV/WJggkiIL77Tj9P/QYRxdSuzRKn/PQT8/kTsyvcc49/x7NWAAJM6FG0LyFCFsCoYscO4LLLtPkHHmDJXlUnb4IICCogS8QQM2awPnPjRn1JVoCNrNhfAP7xB9CgAUvv/ccfnrdt1Cg8bSL8Rha7E1TItyeqqF3buKxMGdL10cjFixaenC4oIorZsye4xwu/AGzSBDhyhMUuN2li7hDkcAAFBeFuHeGBNWu06cmTQ3wysgBGHYWF7L3P2zIispk7V5vmswaEhM6dmQ+5CvUTBOEz4ReAe/YAFSpo00TEoObqBoAuXUJ8MurIow6Hg6V1KFNGW+Zy0U8dbSxapE0/80yIT0YjBUQMwddIljFzpn/HC78ArF5dm967F2jVioUK8uTnM3MTvy1hK0JutSELYFRSujRQpYq+7LeiBFbHkrAnfA7AkP+u1E8QMYSYFzEvD9iyBTh1CujY0f/jWRsEcvXVwOHDxurG2dlsHQ0Bxy7UkUct+/bpXyCcTvq5DeTns7p5rVoBZcta3Rr7QgKQiCEWLDAuKyxkxdRq1fL/eNZ635i9+p844Xf1+NWrV+Paa69FpUqV4HA4sHDhQo/br1y5Eg6Hw/B35MgRv85LhIhI6NjXrgWGDweOHbO6JRGF7JY/dCj87bA1jz8OXHstUK6c1S2xN3bsFwgijDidLKVWIH751lgA+/Zl/x0O4JZb9InCCgpYdHCrVn4d8ty5c2jcuDFuvfVW9FWP7wPbt29Hamqqez5dtEYS1hAJAlC9RhcsYDZ4wmfOnAFSUrT5ypXt+RNbxksvWd2CyCAS+gmCCDG7dgVWZ90aAZiWxv4rCnsKJCdr6xISgJYt/a4z1r17d3Tv3t3vpqSnp6M0JSPzCt+v8g/usJzQ7mRnW92CiKNUKeOy/HyjOzBBeIQEIBFDiMnzFYV50X39NTBsmP/Hs6a7ff999v+SS4AHH/R7uDeYNGnSBBcvXkSDBg3w1FNPoTUf6ipw8eJFXOSSXJ05cyYcTbQFEydq02Ly/ZBAJZ6iHtEDJD6efuZIZ+dObfrRR8NwQrpgiBjit9/0804nS6ryyiveI4RlWPu+PWGCZafOzMzE22+/jebNm+PixYuYPn06OnTogPXr1+OKK66Q7jNp0iQ8/fTTYW6pPRg/Xptu0SIMJ6SOPSYR08QQkQWf8Pvuu8NwwkiyAH71FdC7N0t/dsklVreGiEC+/z64x7N+wOWzz4D/+z8WGiiW9fn115Cd9vLLL8fll1/unm/VqhV27dqFyZMn48MPP5TuM27cOIzlbLAHDx5EvXr1QtZGu+JyheEkkdSxEwGTl8csfyply9JPDQCoWxf46y+rW1EswlLOPZIult692f8aNSKr3YRtuHCBXTolSrD5vXuZC3q9eoHl5rU2Cvj111kUZcWKzLbZogWLetu9GwjAn6+4tGjRAjv5MQyBxMREpKamuv9SwuIMF6PYvYPkE9kBVJM0QMjnzwQuMI3wAL0oEjHEddcBH3zApk+dYpLplVfY8mnT/D+etQLwrbeAd98F3niDBX88/DCwdCmraGyBY/2mTZuQmZkZ9vMSEuzesZ8+rZ+nqjYB888/+vnVqy1pBhGJkK8wEUP8+ivQti2b/uwzICODWQE/+IDZ0/zF2vfvffu0VBrJySw3BADcfDOLBH7zTZ8PdfbsWZ31bs+ePdi0aRPKli2LatWqYdy4cTh48CA+KJLPU6ZMQY0aNVC/fn3k5ORg+vTpWLFiBZYsWRK0j0cUA7t35F99pZ9ftAjgXAoI3xEL/rRvb/+fP6xQwWRz6EIhYojz57UsHEuWsIx6TieTS3v3+n88a3uVjAzg5Ek2Xa0asG4dm96zx+8be8OGDWjatCmaNm0KABg7diyaNm2K8UXRC4cPH8a+ffvc2+fm5uKBBx5Aw4YN0b59e/z+++9YtmwZOnXqVPzPFWXk5VlwUrtbAMUQRzE8i/CLxYv18zk51rTDNqxfr01HSEUksUxVWLB7P0EQQeTSS4GFC4H9+1k2DtXv79ixwLxGrLUAduwIfPkl0LQp8wW8/35m19ywQUsW7SMdOnSA4uHmnzVrlm7+4YcfxsMPPxxIq2OO557TpsM20hlpRd5VB28iILp21c8nJ9Oz3E1BgT5SxqYcPKhNDx8eppNGogC88kqrW0BEKOPHA4MHM6nUqROQlcWWL1nCZJS/WCsA331Xe9CPHs0CQNasYQ/TO++0tGmEBp/5RhyuCxmR1rGryc2JgFm1ig3/EgKBpPi3gDFjtGkxYW3IsHu/ICMS2xxunnySJZ89e9bSPMF244YbgDZtWPLnxo215Z06Addf7//xrBsCzs9nPzBfe3fgQObJePfdLCiEsB2yOq4hIdI6yRjNDxlM2rXTz9eta007bAHfu0eIAFy1Sptu0CBMJ420F0UgMtpoNWrlgbBdSJFDRgaz9jmdLBZx4ULmF1injv/Hsk4AxsWxepcR0rkRYSbSOva1a61uQdSxbZvVLbAJ1EeaE2n9BBB57i1WIqYIiHFuvFGLjb1wAWjenC1r1Aj4/HP/j2dtEEinTvrXRoJQicSOnSg2XKVFAH4lAogueJFAAtCcSOwXxIAxtSaiw2FRxB3Xjr59WVo2wpasXq2lgVmwgP1kp06xgVO+XKuvWCsAu3dn0ZQPPgh8/DELCOH/iNjFzh27ndsW4YieH3ffHaFfd34+8MwzwKZNge+vsnVrUJoUlUTDiyJv5erXz7Jm4K23mKq4557I/B5jgOxsVi0JYJkT+vVjVUF69gT+/tv/41kbBHLXXez/q68a1zkcEZP+IJo5dcqiE9s5wauVb+kxwL//AuXLa/NOp71+fjc7d7L8C2ouU57Ro1mQ24QJgTWeF4DlygXexmjHzv2Er5w7p02L+UXDySefaNO//QZccYV1bSGkVK3KvI3KlmUCUP3J/vsPSEry/3jWWgALC83/SPzZgh07tOmrrw7jie3sJyOOUxJBRaZ3bBkIWLs20Lo1K10p8u67xTt2hFkAf/xRm+bTRoWcSBR8InYp+8f/iI89Zl07CFPuuw8YMgSoUgXIzAQ6dGDLV68GGjb0/3j2SS8f85lf7cm992rT778fpIPm5XlPW27noR0SgCFn1y79/Pnz+jxztiKQsRdv8AIwAiIh+dLtt94axhPbuZ/wld9/t7oFRn74weoWMGrXtroFtuKuu5gFcOZM4KeftAJBNWtGog9gQQHw7LNA5cpAqVLam/STTwIzZljaNIKhFmcBgpgDMCEBuOQSz4oyEiyAcdZ6UEQzNWsal1Wp4scB1q9nQWaheriqZSsB/U0SLHgBGAGjIWfPatMZGWE8cSQKPpFAxu5CTYsWxds/WP13enpwjhNFNG/OfP4OHtS6iZ492WCEv1grAJ97Dpg1i6WD4b2/GzQApk+3rFlEmPBkKrCzb48qAClXZUiRPUMGDfJx55YtgRUrgGuuCWqbpISifCQv+iJAAFpGpFgAPQki1avfTqxcGfi+w4YBLhfw3ntBaw7BOH8euO02FvhRvz6gVre9+27ghRf8P561AvCDD5ivzJAh7IJRadyYkoDFAn36mK+zswVQfe0iARhSHA6W6JSH91P3iePHg9YeHbyFju+7QnF8EoDmRIoA9JTKhw8qq1Ur9G3xheTkwPf94AP2/447Atuf/w3DVnkgMhg3jg1qrFypNxx37gzMm+f/8awVgAcPsurGIoWFFGkZC3gSUHa2AKqdudVDwKNGsQ5yzRpr2xEIeXmsnpEXUlKAuXP1y559Fiwfwrx57JXYCrwlqH3kkeIdn+//KA+gOXbqFzzhqwAUnV+t4sIF685NLzymLFzIcqO2aaPXxvXrB3bpWCsA69WTO5t+9llglY2JoBLyZ+uGDebr7GwBVM1S//5rbTvefpv9D8T5I9wsXMh6rE8/ZfMJCUClSj4NNYnDvuPHA//eeBcrHXn33UFvqk9UrKhNy65VZzG7Vt7HkB6I5kSKBVD8DflAMtHMHeuQ8ceU48flbpHnzgVmLLVWAI4fzyqIv/gi60Tnzwduv535Bo4fb2nTCODnn7VpNdw8qHiyANm5Yx8xwuoWRB5qpfIbb9Qv9zG3kJgkoMKSj9jEzJnFbJgAH83gCW+VOoI5dGVzAcg3r1evMJ/cziMFPOI18t9/2nRubnjbYnf474pPTUOgeXPg66+1ebWbmT4dyMry/3jWCsDrrmOJL5ctY4m+xo8H/vqLLQuH8zbhkQcf1KbFYbigcMMN5uvs3LHzIqFvX/Y/rLkvYo/ExDCc5JNP2JizL+KNVz3qA6ttW9ZDA8EdQrO5AFy6VJsOe/o4O/ULnhBzRZ48qU2fOBHetvhC//7WndumLg+rV6/Gtddei0qVKsHhcGDhwoW69YqiYPz48cjMzERycjI6d+6Mv4UUUSdPnsSQIUOQmpqK0qVL47bbbsNZX186ATz/PLvHRo1iX9NrrwFdurCEGoHk37Q+D2DbtqwHOXaMjTn++CP7RITlbNyoTWdmhuAEnobJ7DwEXKqUNq06bdsxki/KmDNHP+9AkB/+PocYw2gBPHmS9V0bN7KHfenS2np/RYq4vc0FIJ8DsGXLMJ/cziMFPGJ2c14ABlouMJSorhpWYFMBeO7cOTRu3BhTp06Vrn/ppZfw+uuv4+2338b69etRsmRJdO3aFTnc8MWQIUPw559/YunSpVi0aBFWr16NO/wIlmnThgWB5OezxM9LlrAh4bVrgWbN/P9M1gtAInbxZGmxswWQjyxVA0Fs2mkFhe3bWar5cHLhAqsHrpbJ+v57DHnMmIjyEwzQZi6/nF1TniJ/g3UdiWlaeH/W06f117a/LzOi4IugayvsQZuRIgA//FA/z1v9eNVsl6ognnj/fZaoM1Qv6bwPYHHzEQaR7t27Y+LEibhedWfhUBQFU6ZMwRNPPIHrrrsOjRo1wgcffIBDhw65LYV//fUXFi9ejOnTp+Oqq65CmzZt8MYbb+CTTz7BoUOHvJ4/L48NNDkcLMPOzz+zIkFz5gRWBQSwohZwmTK+9xL8W5KNyc/PR15UOq7Gu6eC+vnUFAPx8Z4dfvlUBC6XfZyDz57V2paQwKYVJbztKyzUfz++nLuwkDmKlC0LfPut7+dSA7I2bpRH7fuC2FZZ20+c0Cwl997LerY+fYDZs9mYx/HjOJNUGik5p9y7DsIn6Jubx7qU/fvZcXv1kh9/0SKWcqpaNWDzZu9t9AT/GfLyWL+mzq9YwV4M1PmcHP9SBuXm6tuSn2+fa19KiPoJX1DvPxW7ZpBQFH07T57U2ileS4G0PzeX9afFUeBi6hezdowezf5Xry4vg+hvvyRy8aJ2jM2bQ/Z75he9WJ05cwanuUCcxMREJPrpc7Jnzx4cOXIEnTt3di9LS0vDVVddhbVr12LgwIFYu3YtSpcujeaqmwiAzp07w+l0Yv369VJhyRMfD3z+OauTESwcihLmV6bZs33fdtiw0LUjCBw4cABVq1bF3LlzUaJECaubE3T69LnOPb1w4RcWtoQgNL76qiZmzNC/8tL1aR3UTxCRyPnz5zF48GDD8gkTJuCpp57yuK/D4cCCBQvQpyiX7Zo1a9C6dWscOnQImZy/1I033giHw4F58+bh+eefx+zZs7F9+3bdsdLT0/H0009j1KhRXts8bBjQpAlw//1eN/WJ8FsAbS7qAiErKwuVK1e2uhkhpUePHsE7WFoa+z90KPDGG/Jtnn+eRYer3HknqxhjB9T2Ayxw6ZlnPH+WULB2LdCtG5tu1Mi32p3ffKP5uf3xh2+1/fLygPLltfnsbP/bCui/s5Mn9T6T2dn69bL58uXdloAe2dmGSpHZ62th0JSi4aIOHfTpZdQ2i8c8doxZkEqXBn75hWVTFfcxY9s24Kqr2PSsWay0oRoq//XX7HjqQ+TAARZc4itHjwKXXabNf/gh0Lu37/tbSFD7CV+oX599vyqrV7NCAnbjrruAjz7S5h94QMt08c47wMMPa+uOHfMv6ummm1jgJBD4/Qno7w+zY+XmAhUqeN5GvNf9TZS+c6feoa04n8kDB4uKi2/dulX3/PbX+hdOatdmj5uffmJfUcmS+vX33OPf8awvZrprF/Mp2LWLhbSkp7PhqWrV2M0dAcTFxSE+Pt77hhEEX0J14kQE9/OpEZIFBcyuLSM/Xx9JmZ9vvm244dvldLL5nJzwtm/zZq0dFy74du6//9b2URRtnx07WF478QEAsOEYdZ/UVDa0OW4cUKMGE+W+wn9neXn6+fh47/N8rrT4eOQhDvHQfOOGTWqAoSjaRxzejo8HtmzRHzMnRysurChMsPHr4+K8D6ep2+fn669XdchKnXc4/Ls2Tpyw77UvIGYwCXs/eOGC8X6043f1xRf6dh4/rrWTv8cANs0Hmnnj//5Pmy7OZxcj12XHOn1a265ZM/k2vhzHE4WF2jGqVg3Z7xlX5L+dkpKC1GL6XmYUFcA+evSozgJ49OhRNGnSxL3NsWPHdPvl5+fj5MmT7v29MWMGe1/duFEfpAmwbsZfAWhtEMiqVcx7cf16lgNQDYf+/XdgwgRLmxbr3HSTNj12bIhO4k8QiF2xKgiEt6D5WpGErxiiWsg2bWLBE3zUKg//hD99Gli3jllmR470va0hcNSPQwEqQN+ZdkZRPhJZRLZomVq1Spu+eNHoRe0t8lZMA8P//rm5+gh3f68NPsm0L22xkP/9T5v+5RcLGhApQSDiNcn7twtDgu7Ap0D57DPmOxsK3zm+3aoFnEd8IwgkHZJ4L0UANWrUQEZGBpYvX+5edvr0aaxfvx5ZRQn6srKycOrUKWzklNuKFStQWFiIq2TfpYQ9e8z/ZO6Y3rBWAD76KDMvLV2qd5Lu2JE9aAjL2LJFmy5OWUiPRGoUMI/6dhpuAcg/JHzt6PkkbVu3sv98xR3h7RSAsQP+gvPx8lWY8O2LiwuauD8GvVBajs44hxL6Kgsq1arp5/lKG3l5bEicx9t3yn+GggL97y+e318BJ34/NhaAajEagPkmhZ1IEYCiyOOjgN97T7+uuBav/v3ZfVqcKjlmfTOfwFo2YiAO1wbSL/L72Cig5+zZs9i0aRM2FaXt2bNnDzZt2oR9+/bB4XDgvvvuw8SJE/Hll19i8+bNGDp0KCpVquT2E6xbty66deuG22+/HT///DN++uknjBkzBgMHDkSlSpW8nn/dOuDxx4GHHgIWLw7OZ7JWAG7erFUI4ElPt77MFmEtdu3IRVTrW7g7Kj55qCyiVQYvLGSJ1n/6ybhMFIB8Ogtfz8sP3+bnByZoZA8bAFnQ10EuhXOshxQRP5uYxoV7c3e30xNiHkDRauGtUgjATGZ79xqXi9/PqVOe22IhvPudJaWxI6WfEOEtaWKS1eK8TPIvH++843nb//5jvoa8r7WKosjvU77dMqEqCsBA7nV+HxtZADds2ICmTZuiadFL89ixY9G0aVOML/LlfPjhh3H33XfjjjvuwJVXXomzZ89i8eLFSEpKch/jo48+Qp06ddCpUyf06NEDbdq0wbvvvuv13J99xip+vvYaq/rRsyfw8svF/0zWCsDSpeXlwH77DYjyoAoC0WEBtGoImLdg+Qr/naqOznyAB2/2VRE7YH54cv16387LK4NALYAm18pPMNZBzsmTOJ1PmqSf5wV7Xh5LD8PjqUwhYBwC5o934IBcAM6cyRKHb9vGLLAtWrDgERHxWnriCc9tiWUipZ8Q4YWUGIlanJdJf1KnlS3L7u9HH5Wvl7WDP77sPg62BdBGArBDhw5QFMXwN2vWLAAsMviZZ57BkSNHkJOTg2XLluEyPpgLQNmyZTF37lycOXMG2dnZmDlzJkr54O85aRKrkpudzXT7xIksTrK4WCsABw4EHnkEOHKEdfCFhexN/cEHWVQlEd1Eqg+g6s/TurVnAXj0aOgsg76WDzp/XnMO4a1gartq1NCW+TIEfO+92rSvOcdEsRSIVcDkXA4YixYkPycRTHwi68RE/efKyzNeb946ZU8WwNdfNw4RA8Btt7HfomlT/VC6t8ofUZg5IWhEiuAT4YeAxT6iOC+TR48Gvq+ITHzxAlB2H/tiAVQUFtU+bZr8vPznj6Ak6KFk+3Ymi9SA6gceYDYAWZftD9YKwOefB+rUYZE+Z88C9eoB7doBrVrRW69NsCyjgp3f7NWK9336mAvANWuAjAz/EgD7A+8D6KlOX8mSzOq0fr0+tYj60OEfGKKfEsDSzfBwwxk+u2mIDwF+mEr1QeQdTf38rW+4AXgUegufoUwcHxnMRxkC7LsQfY5lwv2//5gQfeEFz0Eg//3neQg4Jwdo0ECb54fIZdtffrmxLQQjUnwARfj7V/y9i/PS+M8/2vSVVwZ+HLN28AJQJs58sQA+9RRLW3PXXfLz8vdWYaG9jQFh4vx5fZGYhATWFftRRliKtQIwIYE5wO7ezbL0z5nDhkc+/ND/3EFE0OBHAl99NYQnitQhYPXNOCHBXAC25oYmvWR4l3LyJMsnZ/YGzN/5ZhY1/jtr2RLgk5WrnTuffHTpUuMxqlbVz5u9na9bp48yNtsHYAJIRY1+U2sqy7YHPNeNBjAJjxmW5YPrQ/j0+WIamvx8oyO+zPqhWn7HjfMcBHLbbXILIA/fv4nrvc3HAmfP+pb/LVIFII8otPyJnOWDMgC9ZbG4YdneLICy+3TfPv28bJtnntGmZQFbwRTEUcT06WxwQf3Lz2cpSPll/mJ9HkCAPWTEBw1hGXzal6uvtqgRdu7IZQJQ7KSuvFLrgItqQfqFWhJtzBiWYDo/X+9Lx/sAqh3mxYtMfIwcyaqG8yKxZEm9kFDby1vaZZFoYgg4f4x27bRjFaU6wMmTrCya2T6A/sGitp3/vWUPDW/DzXXqYNi2WZiNW9yL4pEPBUX7iS+U/HeTl8e+B/67yMtjD9dSpeTO7p6GgNPS9J9H9iDlv5O9e/VpQsTvy6YWEP5Z/5hRfweOomiJs8+f95yGwM79hK+IImj6dN9r4H7yiX6ej+r3xu23ay8+su8xkCFgPgG72TY8p04Z0x7JBKCNkzOHg2rVjO+oGRn6mLzIywPYr588Aumll1goO2EJvCEo7MXdVexsAZw/n/3fscM8DczNNwfnXG++yap+i3U+ZRbApCRWbaBtWzbPBzKcOydPr8B30JMns/+erFeydCf8UM4jjxg/g6chYHUdf868POOF5+1CrFYNszDcsHgvqmnH5BHTwIjX1549TJSZDeF7GgJ+9ln955GltOLbIz5oxWvJpn5Q/LP+jjuCeGD+u92zx/O20WAB/OAD/by3z8yj1uVVmTkzsDbIrjEzNwhP+4jlzNRt/vyTiXkRtRoKjxj1ThZA/POP5xyAkZkHcPVqY4JWAOjeXe+0TUQPvnbQ6gPUy9Cfpfzxh7kFMJi+f7Ikod6GgAsLjVYvmQWQR1GYr6DLBbz1FlvmSYyoQ3SLFmnLNm5kx3E4WN0i2TF4AaiuEy1q/grAouP8jUt1iy9BUZoV8fPyfnd5ecYK62b+SSqeLICAXmA2bWr8jfiHoZjiJkKGgPlqQb5UFfQZXgDIRAOPnV8UfUVMEs0P43rjiis8z/uKzNoXyBCwOA5ZUABMmcJ8XsW6ZQAgS4Eyb55+ngRgyLD26Xr2rPxBKZZ+IqIH/mHmiw+gKgDt2LE3bKiJLPEhHUgGfH/gBaCsIz5/ntXU5PGWXysvj/kKAppl4eef9duIli4AuO46/TbTp7P/O3fK84nJLIB8AIpMAHrzdi56SFyKXYZV2dnwLNDy8owuKMePez6fJwsgoP+MhYXG9Bz8Q/7XX/XrIsQCKD6ngwb/0mdWoUbFjv2Cv7Rvr59Xg6sKCthwjKdnoVgPzCRfpldkIku2jL9uZS8mYsBSfj5w//3+taUocbLHdhBBwVoB2LChvBf55BMWEUxEH776M0WCBXDKFM0CKHaGfKCDSkEBK+a4f3/g51QfeN4sgLt3G0WMtwz7smXff29+DDVaiE84W7myvuh9Xp5nASgTNzIByF8Hsoc+J7D+Q2ndqtKl4dkCmJ9vHLLnBXxhoTHvojhM7k3kitZYXoCLCbUjxAJ48GCIDsxf2976i2gYAhZ/X1VkPfYY0KWLPlWTN0SL6dy5vu0nu/d//NG4zJsFUBSzvl67Z89q9wHv2GZ2HiIoWPt0ffJJZkUYNgyYPZv9DR0KPPeccUiGiA6iyQJYpoz2YBc7KdnTsX17YMQIY1kyb/AvQ+rDURYEwpOSwlItqDz8sNwCOGCAtkzWWd96qzbdrp33zrhPH6B5c23+0CHPUcCyc8oEIH8MWZLmP/90T5a+pIxhteMNYWhKLYWntkFsI5+IvqDAaE31NgQsfkZxPf+gFh3nxW1tKgBDBp/KJBYEoOzayM9nvvCAf8mdRQEoJjg3O69sRGDtWlYxiM847C0IxJs/qxkpKUCjRizFEt9/AGQBDCHWCsBrr2URkjt3Mp+bBx5gWfSXLTOagYmw40OCcv/x1QKoduR2SwfEP2Dq1jW3AL75pjatpl8Ry5GpvnIOh+cHF+/Xs6toiJO3kigK+17V/IQA6zT5+dOn5T6AvFCRddZidK43MZKXB3TqpM2fP+/ZOiYrfC8TgPxQoLfh2WbNtOhfDt03zA+VFRYaHzJ8FGZeHktWz8MLQtn3wn/GPXuMx+cf1GKQiKfAm1iAz2vpqwC080iBN2T3FO9X6w/+JIYTk6GL/PcfexY//ri2jO9T1OvyvvvY/bpqlVEAip/Nm0AfN471qzyxdv2HEevvmp492YPx3Dnm+7BihdGMTIQN/v4UfZODQqBDwHZ5s+cf7Lfeau4D2KGDNm0mrDZs0OZ/+MH8nOnp2rQ67Cr6GBYUGCNL+Yfi22/L3/h5a4usneJDwltnnJenb8eZM0br2W+/adOyquYyAci/jcgEoJo2R90fwFnonc6dvATkhafMQidaWEUByA+Ne/MBHD7cswVQJNYtgPz14+2z27Wf8AZf6SqYAsesrJsM/nuW3VPffGNcxvv75uezUhSvvcbmO3QwRvDKruXevT23S3xGkAVQx65dLGPVoEFaJZBvv9UNgviM9QLw1CnmNP7YY5p5+ddfQ+hgQniCf64tWBCCE4gd+urV8ohvtROwmwWQ7+CyssyHgNUIWEDegV24oP9sot8LDx/fb5Ze5uRJvTVv+XJg6lT9NrIhYD6U01sqCJnQER+4ubn6fUqWNFYqEQNLRGQCkBeRf/9t3EdSWqskjCJrLYqCXEQfSvE3WrZM3x5RAPbtq1/vaQhY3YZH9K3kiQALIF+CKlBjlSn85+XFgOzlUbQARooA5Ms6yH7fS/XR7F5rU3s6lhn8Nc/nGJWhClb+2iwoMCab5pPIitur5/zyS21eDAJt1Ei+DwGAGVkbNmTJGubP17qx338HJkzw/3jWCsA//mDlqV58Efjf/7SH6/z5zBRMhJ3hXCo1f3KK+gzfiV+4wKy97dsbhwLt+mbPl05LTzcfAuYtQGokLG+lEj+vGjkrw5dE0klJrHdQef99fRm3tm29p4EJxAIo+ieJFsDZs40FK3v21KZlF5koAP19IHDbn4TeH7AVir4TUQCKn4uPCs7NNdZY5b+XEyc8//6yNvNl9PiycEBEWAA7dtSmu3YN8sFlAvCFF9gL0//9n35btV+wLGFpgHizcorXy5Qp7P+8efqgq2C1wds9pb6gipWAxJc58boXr2VxiDg3V9+3N2liFPo2fAGyikcfBSZOZMHhvHbu2FGebtQb1grAsWOBW25hb/R8jdEePSgPoEXw2f1D0qfynR0vgkTfFdECaBcByLeZDwLxVO0CYEN+vJXq0CFmpQsW4vmPHWOZ/lV++MF7GphALIB8MIW6Pf9bnj1rLDHHt6NkSeNvKwpA8eHED4nL4NpYBqcM7sS34H395y8oMApwXgBu2OBZAH76qXHoy5sFkD+eaNWNgChgfrjJm/HIb/jvSrXOqgYBPmgJiFwLIH9Ny6JtRSG1fj3rEwcOZJV+/vlHnmnAH/hrWHasLl2My0QByAdLyfClrBtvXc/PpyFgD2zeLK8smp7ue2l2HmsF4C+/AHfeaVxeubJxyIWIDvwNArGbczfvq+dymdcCFgWWmN3/2LHAH1Zm1js+B9fhw8ZoY29Rf94E4M6dxm0yMvTzubl634FrrmGJ3Xn4tCdmHT4vAHNz9eWi+MhkQC4gOURXhtm4BT/jSm2BTGDxPpZ16xoFoPiA5ofSZes9PcT4KEtZe2LNAsJ/V4WFnoVOpFkAzSoH8fTsySz4PKtWsZKBKgcPsqDJ4sB/z7xPqtlLLWAU594yGshejK+8Ur+MT8kUH09DwB4oXVruDfDbb961uAxrn66JifIklzt2ABUqhL89ROgRE+iqiCLArkPArVvr5806S1EAlC+vn3/uOaOfD8AsZuLDTKzRywdRqGzbpk+mDOgtb127Fn8IWBbtKgrJvDx9ENd33xl/W14My6yKMgsgf14xAKawUIu0NvkcC5o8rZu/CtzQlexBx4uOwkLjC6n4udesMd9f1ib+O1Irqphta0MLYEgR+wXZS+OPP7KUSurvYLd+AtAi/PnqGKpVnr//RIv211/LK2TwPsPlymnVegKFbwN/DaquKmYR+vy0uM2wYebbq+fk750KFfQVQuLjaQjYAwMHsmqbR46wS6uwkMXQPvigPq7IV6wVgL17A888o12IDgcbg3zkEVYnmIg+zKxQ4k1u1yAQMzu7WL5J5uvC89dfcivcK68Ylx06pJ9PSTFuIwua4t0oRPGWm+vbm7a4zBefHv6h0KKFcR/e7y8/33gOUfDl5noe3/jvP/MXiyL6HDM+ULeiKN1EYaGxv+FFZkGBdwEojoPKPpOn/Xli3QIoWplkArhtW5ZUXcVuriI8996rTauW4o8/1pbxvsGe4L+XbdsCq7+3b5+Wjoq/Jv/6S5tWX1ZlTmXbtmnTBQXGaHbRIih7YRT7fTFBvSgAN20ytiNGef55oE4d5qFy9ixLEduuHdCqFYsM9hdrBeArr7BPkZ6uBQRceil7wD33nKVNI+D5IQUw300xxYc3+AhOPlGx2FHY1QIoBieZReeJ39133+nnU1ONVkLAN79A0e8OMObOAoBu3bRpsaPNzTVaqZ5/nvk1qiiKfp/4eKMYEf37Xn1Vb/E4e9ZzihSZAJQ9FDyhJs7l9xc5dAhHobe01EfR9ygLAuG/m3/+YSLT7DPI8JYQ19P+NrcA8s3JygrBCcQhYF8+f6QMActGvHz9fflrMjPTGHFrhirSFIWJxjZtmMWav0af5izksv5FhRfdMgugtxfGvDzj/S/e6+L3IfrXxiiKwt5DX3+dJYZYtAiYM4dp8g8/DMxWYq0ATEtjD5CvvmKfaswYlnto1Sp54WgiuBQUsIjr1auBb7/FOYf2nfctt5IN0XfvLheC586xCO7atf2zUIg1V1W8DQHbBf4NGNCne+ERvxMxdcnOnfI8W57yAapUqcISp/PMnWv0x+NFoWgBzMszliAD9AmSRXFWsqTxc8nyh910kzb91lueh8e3bJE/RMSchp6oXl1/DrE+ahHpMLZ1NdrKrUy8BVD0/5O1qVYt/Tz/GePiimcBtJkA3LFDm77xxiAe+KmnWJQv/8D3VQDa7UXRDNGdA9A+n6eqHYDR9UO932V5c3mXE9V6zbuIjBzpv2+dogB3363N5+cbq9iI17X4oiOzAIr3uvgsaNLEv3ZGKYrC7GMHDrDHaI8e7P4zewT5gj2erm3asAfaww8DnTtb3Rr7ceyYPhdcsHj5ZTb01b490KMHVqKDe9VLJ25jE4sXMyEowj8F+OEDb5h15mYZ4+3esauvXeIQoPh7yer/Bnrn5uXpgyIAoGVLz2/fogDcvNnol3jJJXpLivh2fuqUUQCKPpHt2umFaJs23nPk8UNkgHxYOUiuAKIVsD1WMyuu2kY1twIvAMUC97I2ip/J00MO0CfgFpH5RAaCWiEmyPAa4K6RhUbraCB88QWzQg0YoHeDMBsCFrFbPyGLoAWYExfA7gsV9fOp15mZ4OEz8/PCWHZvVKmiTat9D594XtZfqPBt4zlzRm+YKSgwvryJIlWWJsrfIWBZsvgYxOlkjwzR26hYxwzeofyksBCYOZOVlmnQgGU37N0b+OAD+9zEdqFiRWZhEPOpFRcha/yzeNI9XQuCgKlbV/NF++MPfTJPMfjAE2YPMzMLoN18AEXMgkDEoWGZAOSHSlVGjPB+zgsXjN9jWpp/AlC0ZALGly/REiceE9CXvAPYg4ffpkoV7wEy8+d7Xi/Lsxcg6TiONtBbWR0PjNWOn5zM/otpYkTEe1EMTBEFomgp9VSyK1gWwNatmTtNkH0IeS+FhL69mDD54w9tofrZ33iDnZ+vqmIGn6uHFyqROgQsukaoqC/TfBI3T9ceD/89qrlFAXkeHt5PWO17+BGHzp3NBeAll8iXi2ItP589t3nEBOcyy7eYW1TMRyj+3vywc4zzwgvAQw9pBaGKizUCUFGY2BsxgjmvN2wI1K/PwtxvuUWe6IbQ+8wFA6HY73q1SoKMbdtYnPmjjwKNG7PhGpWFC4H33jOmwuBRFHbjv/iitowfbjQTUOqb/ezZ9nwx4J3PPbXvwAH9/OTJ+shVFV+sgu+8Ixdmon+RGEjhLYBDtFrKEj+L88uX6y1+f/yhP+/Fi8Z9vCWsEgXgpEmetxeRDbNxFpEf0M6w+vzFot9RfQjzyAQUn3QbMAbqiJ/BkyM7b62Rnc/XcmjiPmvXMv+vRo08718cvv2W/X/jDfZ/1y4mchwO4J57mNC96irz/b3d09E2BCxLGyUKwIsXtVKSfGgnnwOxsFA7huwlmX/hVNPH8Pf3xYvmQnPOHPnynBxjAmtv96ZoGRctgID+ZUhmASTcDB3Kcm83bswul7Jl9X/+Yo0AnDWL+Z0tX85Mxh9/DHzyCRMQy5axesAffGBJ02wH3/nJHk6BoDoF+1M4XIUXcCoffQTccYdnXw2nkz0YPvpIW8YLIP6mnzlTyzDPd26ffeZ/e0MN//bNd+qiT5hoAdyxQx7p7ovF8/BhowCU5UoTgz7EABPxGCtW6B+gsqFL0dIF6CNkt2zRn/eTT4yCRkyZIiKKJ3+HgMQHzP336182AByAPmlWydXf4nt00CekV8nPNw7pibnMxHOKDzHZMLK7McLLgT9RwOnp7JoRfbHMIjxDhXr9yVIbyc5//Djrh+LjPTsSXnedbwJQ/Y7mzvW+rZX4IgBzc7Xv8bLLDC/qAIxDwOJ1y7sYqH3P+vXaMrFko0qtWsZk2yr//us92EpEZhn3lCGBBKBHpkxhGYJmzmTl3SdP1v/5S7BzuPvGxx+z2r9XX21c17EjszJ99FFgiW2iDTVkH2BZIIvL228Do0aZ15QtLg4He9OsUYOJCU9DM2KqDZXbbtOm+SCQpUuB/v2D19ZgwAu2ggIt0au3TmzaNPlyXzrV2283WpS85ey6eNEovGQWADFQRGyP7Dyezrt3r/EB7nR6/n5EMeuvVUf8XFOmGKKkK0Ow2AHoiO+hJNczHq+ggKWuWbJEW8a7QPiCN/eNwkLtWvdnCFgdWr76av33JFpZc3ONdVeDyZkzxjJtZkyZwkS5yqefmm+bk2PMkyhDdYyaOdP6IUNP16usdKQ6rf4++/frxV1iovFlnR8Cdrk8J8uWuZ9cvCgXgMeOsRG5efOM65Yu9V7CTkQmAD1FxMuGgAk3YprF4mKNBfCPP/QpKkS6d/c8nBjtKAqzgB46pB/sD4Yvz6hR7L9a2zEU1KzJhoScTiYAf/1Vvp0Y7SeDF5Bizik7wFsAveSi0yFLdH7unOfIPHVoU1GM24m+eGIbcnP1peEA4zGuvVa/z4kTxgeLNwHYpYv3YWNv4jiYJa48nPMEjGMmx10ZhmU4ccLo59qqlX9tevJJz+v54TlxaC+Q+37mTP18sKwqZtbEL74wtxwBzPrkcLC8kLz48wVeAGZm+revFXiyuHqyAPL9pFoJZMkSuXAXLYCi28N112nTfAURFTMBeOaMPOgPYAFeYmlIvni8DL62KCAfdeLvd1kUMKGjoAD4/HNWE3jiRFbpKFDNbI0APHnSGMXIU7FicCLLIpWUFCb1K1cGRo/Wlgcz/CfU3HOPNt2smfftza5gvqMMZMg61PAWQH+GR2TpU06d8iwAVR8/WXDG2rXG7fk2HDpkdCEQ2yAGl6xfz4ZwebwJwCVLip/HzluOPW/IvkNJG8riP7wNfSnK9C0rjPsuXMj+ePwVZb17e17P93eiRcjs+xMtTWrlif/+AyZM0K8LxtDo8uW4UO8K9+xwzPSwsUDLIv/iX37x/7z8KEAklAUTRQ+PTACq07J0Lt9/LxdkvA9gXJw+CAfQRiLM2mMmAAFzASgLAvEm1kTf2PfeM27DC8C8PGMgCeFm5042mDF0KIudmz+fZd2qX5+53/qLNQKwoMBzBXGXK/ay3/OYPWRHjizeccWQfI58WBxta9aR8NeB3S2A/ghAmXtDUpLnB5zqFyQLrJDhzZdMzPS/bJl+G9HPDfDtN/B2Xj7ZtAxRAIrby3yiPJ0fML2+7oSxQshu1NAvkLmqqD6qvlJPMrTMw1sY1e9LfRCbCUCza0XmDc67VQRK587YgObu2V5YVPxj+oKYONjueBIwniyAZkYRmQVQHAIWq4nw/ZIsCtssCCQry1wAXrhgHAI2uwYvu4z9F186ZenMxCFg3u2J0HHPPcxNc/9+ZjD+9Vem72vU0NtcfMUaH0BFYdG+ZhdacS0A0UqLFsXbnx8WEFgCzcl9PiyIwjZ7yPEJlH3xPwslMt8e3johGwJOTpYHTsiGiXjLXteuxuohqvAxc+AW8Rb1+8ILxn14S9T69cA11+hTWnj7Da66Sp79n8fb/S2uz8zUt8uXIWLRz1D9bSpUMFg+C+GAE9pvWwu7oYBzPbjnHla5RVbFwVe8JbNu0MDYVrV/NBM9FvST7bgUOtciyFkJzBAtRHZj+3b2BFaF2ksvmW+rurT8+ae2zFM6lzvu0Kz7l1yiBXd4ywMoHkt8cbtwQf5SlJho/lx+7TW9GBUtgjyq36EYnNK/P/C//2ltzM83/r6NG8e2C5gHVq1i7+38O165cqwrF1Oy+oI1FsBhw1j0Wlqa/C89PbYDQMaMkS8vbkb0H380XdUTWo6o3vDTwT0YFBSwB5o6VCTDSgH477/6IRr1dcvhkPtqqdMy8QfIh8L4oIumTY0ev2rUtKfhGx6xc5ZVtPDEJ58YHy6qPxZfz5dHFjgihqd5E3DievHh5YsVyCyvpOThJgtT+hmc9TMvr3jiD/BP9PpqAeRFhKf7RqU4vlWS0YN4hMkax18P+fnWpXo5doxlreB9Ej//nBVnNXv6ilHRX3xh3Eb9ffmsCGp+vQ4dNNHF1/v2JgD5IWDAaFXj+1L+nti0yTxY6LfffLcAqoj3rir+AK3dfB+Zl0fizwOJiXKD7tmzgcV4WWMBVB1cCTlmebvefFPLt+Uv3iwQHC5Y4ITbtq33bcIhAFesYNaehATWCTsczMu2b1/9dnw0clycsWJBIENV69ZpHWp8vLHYu/qAkEXSyRA7Z1nyZ0+cOGF0uld7H7GKCH9OsW3ly+steKoQUS0AIqJY8lQ1g8fM2tqrl+Zgb2LdUOCAg7MCXoWf9VbA4uJNAPIix1cLID+8Jg7ny+jdmxUQDQQrIzP5iPeLF4sfJBQIiuLZb33DBmb9Fl0DVq/WB2j07s2ioHnU75Z3dVCvl/h47cluViNZZjkUl4llJ3kVwV+bp06ZXyPZ2fprUUwLw5OVxfpSPkWUrI3i72lHC6+N6NWLGYVnzNAGBNevZ95h3tyMZdijFFwQWL16Na699lpUqlQJDocDC0WnbQkrV67EFVdcgcTERFx66aWYNWtWyNvpE7IIUZGOHZk48fWtfvz4wNszcCAr02cFzz2nTYdCAHbtyr7HHTvYndSpE/N9a9xYs/jdcINxP9XHBfBsAfSHG2/UC0DxRWnZMvb/44+17cQyajxiZyrWI/aGmNOPp1Mn83OK+wgpWNwE2wUkPl5uDSlZ0qMFUKUy9Pn4/kU5ky0DwNsLGB8RL5alUx/0W7cCzz+vHcvf6hdff+3f9jyhKEXpK6KrwuOPe94+J8d3K+HGjeyFzyxTwdmz7MXbl5rkMr/QzEzN/zI/Xxu7U1+s+ATyLpdmuVMFWny8/JpVFGO0OB+FLQpAMfjCU0Ddnj3y5adPG+9ts5IU6rVrdt1Urqy1kReABw4wlUNIef115gOYlcVG15OSmPH50kvZCL2/RI0APHfuHBo3boypU6f6tP2ePXvQs2dPXH311di0aRPuu+8+jBgxAt+JfldWwFdWMEN1NB43zrdjTp8eWFu6d2eC48UXWQXqcKIo+qEMtWarWeeuKMy/KzeXWYI+/FDLv6YoTAApChuWUOveqrndLr/cOIz2ww/mIpu3vshye/kiAIXkxAD0AlBMHaJ22jt2aNt5egEQndHr1JFvx4tZETPLj6yKCSAXgGYR/WZiLFALj8slby8frehhnOQA9Nd3BXC59NQhPk9WIE+oos1sf35oULQAFhSw67Z+fSZ+VGs5P7zmLbBGJdDhU7Pf2wq8ZbxNTtZSUMn+WrcGevQAHnkEaN6cia1mzeTbpqToix/7g5r8e/p09r27XMaXRf56dbm0+1qthJSQ4FsaGEB/P4kCsIYQ2GT2Mt27N3v5NUO8t83EorfxyPh4uQAEfDOAxCilS7OuYscOVhfhs8+YC+qCBfLHiTesGQIOAd27d0f37t193v7tt99GjRo18EpR4fG6devixx9/xOTJk9G1a9dQNdM3PD2QFyxgefZUXnpJXp2juGzezIYv+Nxx8+b5n/+suIgPLNG3xSr4WpuyTl1td/36el8tHtlwBy8AZ882P796Ln/KfJkNAXuyBpgJWb4oPI8skassES0gr7oBBG4BNKuiwrfJgwXQI6rfl79+lCrqZzL7zPxDV22r6ne4aZP+vKqliReAMpE9dCgT/Y89pi379Vff0jKJFHdo7vhx+zzY1YToahm7UNGmjXGZWDtcFIAiZhZAmQDkRZ8oAEVLnXrPq64mO3dqxxo1ihUMkMH3B2YvXOpxPeFJANIwsIHCQuY++eWX7F2yUyeW6am4xcGixgLoL2vXrkXnzp11y7p27Yq1snxqRVy8eBGnT592/53xpch5IHiS8n37BhYM4k8Owc8+Y1GJd92lv5GzslgYktkDXcZPP7EHmb+WB3V7O9b2FIfeRAsg30nKUoioiB1daqpeAIrI8qHxQjRQPKUoCYYF0MyHL9hDwGYCkLcAehGAhU/oXSWWoWioW/Ut9PR7ekK1AJoJQH78Rv3+1IcyIBcrZgFGKrNns6pKPM8843kfM3btQqEnn0hvaWZ4n9ErrjDfLpoQv3vAmAaGdw2QDenzPoA8YhoYdVt+P0/wQ8z8deZ0elYVYvoas5cJbxbAI0e070K8jtVaxGogDIHnnmPvcaVKsdHz117TpwgOlJgVgEeOHEFFYTimYsWKOH36NC6YdKyTJk1CWlqa+6+et9xegeJLPdggwkusBvUVeY1alXbtjMXrAc2XZc8eLSXC//0fsxiqIkVR2Nue2bCBCp9/zo5Z4UUrkGgB5IWdp6EzUQA++KC2LC7O+KDkvwszoRhIucDNm83X8b5pPGafSx2m9wUzMeTrELB4n3gSgGJyZRMcyfo2XYNlOI9kLctqoJUovFkAeUu72lZ+ROPWW437+JKT0eHQl63zt4QdwH6PG2/EL1xk9PMQXE9ee419zx06sFGKNm2Yf+0rr2gR71u3su34mrQAEwOKYv7dRCKNG8vrIosCkH/Bkn1+l8t8CJhPBM3/F6cBYxUg1QIoHtvp9HyPiPf2xo3y7bwVcjhzxtwCqOKpX4oxPvgAeOstlhls4ULgq69YtdziPh5jVgAGwrhx45Cdne3+27p1q9VNYhQzOeqRzZqv08hRxYx8vOQS5vh78aK8bm9ionfLBd9x2skCeM89rD3iUJYnC6Avd+i117L/iYnavvHxnoUyvx3vM2rm5+cJT8OaaoJi0TrhKRlzcQWgrxZA0VJu5qjPWwC9BTMkJeEM9J+tJM5rv3GgIkX9TGbWFV64y6xDMjwJwIEDtWn1+gqEPXvcbe4CrRbyMMxmIwQqagDO998Dffow/9nFi4GxY5mfHcCCge65h32XeXnAQw+x1Cbqi/j588xP144vff4i1upW8dRXyKx2q1bJl8uGgPntxJchsT2qABSvMTPBqeLrvb14sfdtvAlAws2+fcxtVaVzZ9Yli4VW/CVmBWBGRgaOCg++o0ePIjU1FckmnXRiYiJSU1PdfynBGH4LBh4qfLgxe2AXFuKOcVq0o8/Fpn/6KTCvU8C75eKpp7TpcAjAo0d9yz1lluD1QFH0qPq5+E5SrNF7zTXG/dXriM/vFx9vHALhHbl5SyGfasEX63F6uvdtRGrV0s97GiYyS/0g+iuaXQe+PhDE4VxfLIA+CMBSMDrIP5g/yb0+ILwNAfMPYrWt3n4nT/eR7OUrELi0U6eh3e+VcFifWcDfJGRxcex+4lOkOBzs5c/f6GYZu3cz6/XFi8z/sHt35tP8yy9sGHzKFCZWN2zQ9lGF8ksvsdJ5Z84E1v/Iyp2piKMF6n+Hg73AiFVcuneXp3nxNgQcF6d/GRRHddRnn3gNOZ3mw8ejR5sLQLHd3vxML79cngeQR7VaiumwYpD8fGPXER9ffHfJmBWAWVlZWL58uW7Z0qVLkZWVZVGLikFxagQ7HLpSkT4/31q1Ymb+b76RFxv3RP36ntfzQTBiB5yXpw03q38//MCSXIvLzf7y8lhAREoKs3Ckp+vFSceOxjaZ1eTkmTZNayPAOlNx6EXWMaoBFaIAFNPP8Imo1U5T7Kx9SVfhS5S5ihrJWK2afnlcHPNZlGEmpsXAEVFUqniyAPIiTzYELPvtVq/23apUdAN8ggG6xa/gQVxAUuBBJN6GgPmeXH3IenvBNIvkfPdd4PogVfMxe+D//DOz3O3YoU9QHCwGDfJ921Gj9POLFrGXpbQ0JkzLl2f9VNu2zBr55JMsfVKHDux+/OcfFuTz5Zesf3joIXZ+9aWZd3cwS7bWRaukhOHDzdvKWwDVvohfLr7M5+XJBRmfd1QWBOJ0ArVra/PqtSKWjBORWQDVEY/0dC06Wfw8Yrv570NGtWreLYBqEBwFhbiLp/Xtq/3l5LD8f/wyf4kaAXj27Fls2rQJm4pM3Xv27MGmTZuwr0jdjBs3DkO56iIjR47E7t278fDDD2Pbtm1466238H//93+4//77rWi+dzxF+gqlrXymaIiRryPuqUSzAYeDvaGK4sAbnhyUxTQZvABs0EDewDZt/KuDExfHhM3p02zIWuXUKeZgISZNnTKFPSy8oQY78ClaRD8gmbO8KoxycvQCUNyXrxCjlpITv0tfLIDid9ytm3w7h0MTAOIbvsvlvzVMHIo0syKqn00mgPjPK4pdl8vcJ0kVgN7SmRQJvAH4P8OqErhQ/CFgs6AaPuejuo23ED8+upfn9ts9W9GeeAJ49VXz3Hc8Zj6Dqp9u7dp6K16weOstz+srV2bDmBs2AGLqL36szBeqVzd/mQGYb66K6P/8+utsePW771hb/vzT8z3I91+8H59Zn5iWJl/HWwDVY4r3Bu9LrabDEkeCeJGo7ieeT70O8/K046iYvSB4y8MbF2ceBKKiuhiQAJQWT7vpJnbr8cv8JWrSwGzYsAFXcxF6Y8eOBQAMGzYMs2bNwuHDh91iEABq1KiBr7/+Gvfffz9ee+01VKlSBdOnT7c+BYwZWVksr93NN7P5tWvZMoB1Ou3a+X9MXvyEE08dpDh8yFtulixBSElLk9dL9jUPmGqJ5Z3cX39dv40sSIO3AK5axaZlljxPTuUqvghA0QLYsqXcZ4dPNisrNu+vGBI/u5nA4SsjiJH28fGaxUAmAPkyXbJjenM/4D5THuIM5c7m/n0lBns+ghxVAJrlAeT9idXv3JNYVRT5NTJypPe28MnVCwo8W42t8sEtXZqVWTMLSHvuOXbfiBb1xMTgDCHzPPUUE8sDBxoDE268UftNfUmvw9+vfC1dszfvMmXMBaCYCJrfbuNGJlzVYXq1DKhohReTw8sEoHpP+CPE6teX1ztX4QWgmQVQHfoN1MARRYSqeFrUWAA7dOgARVEMf2p1j1mzZmHlypWGfX777TdcvHgRu3btwi233BL2dvtMfDyT/OowJp+02Beznadcb3Zh6VLjMv4BFGgEZnHxZVgV0ASgOmwKQDe+DsitWuqQCx85N2+ecVvZK574sAtkCNiTRVYVTKIFMBABKJ7H23Xrchm34QWhbAhYVqGkYUPtRcKszrbKv1pAVBwKkA/9OYZ8dj08SiIzS7Q3H0AeXyyAJ08CI0YYl/fpI9/e7MV2xgzPbfE2ZBhK+CwLooXuxhvl+/h6r/qDw8HCLocMMVrQ/M1t6K8AjI+Xv9Rs2eJ5CHjlSv0zQs0p6c0CzierVlHvnePHmeXVF7wNAcsEoGhJFq2NRNCJGgEY9Xh6WHob/uQdne3Ia68xx2khLyMAe0UBe0MVgGrHXKmS0eIj+pCVKAG88w6b/ugjbfmpU75ZMmRRfN6G5MQ2eRKA6tt3IAJQtDa4XPoHtzdrJV8aS4bTqQ+UcDrlZef4YSpZCiMewdogq4vt9CQBzYKtVAugLxU1ZEmCRcqXNw59Aub+tQsWyJeLdWlFin73Y9CETnqqlyj+YMEHMYiWNzNxHGzrnwj/+/70k/+CUxSAYjon0ZErPp6dR2TSJE0gyUpRjhun/y5UoSpeU7JIeodD3041T+DMmb77e3q7t2VDwOJvygd/RNJzIIIgAWhX1KFAFV+sNGbwviAqYmmgcKNaoVauZKkhZNYMILJufLWtaqd+6JD3SE6ztAuyJLIyRLHncumjqAFjRRF/BKAKZxkD4JsAvOkm4z68ldPbw9NbTjKXS28lcLnkAowXyd786vhAmyJkCZBPwcThxswCpwpLX1L3qw9yf4J1VMwsUmbn9ZbKqkgAbkBz96JPvypm+QF/OHOGWdF99TMOtQDkrfKBVCXyZgEU7/v4eKBnT/mx1ApDqtjiayaL942aBua33/TLmzfXz6v3pL+frUED/fyKFZ63//RT7VyqBVDNtanCW5+LmeqMkEMC0K6IPn2ebsh16/w/flHnweurBx7w/zABoyYMljxwdURiTrDPP9emeQEoczR3uVjUIcCsU+pD39ehN1kiV/Fhr+byUxFrBPvS2YuWg7g4vTVTVpJOtADGxemH+cWHtZhYfccOzwJQFJCbNsmH2H1NzA1IHzQOAF9CH8BSBqfk+6tDbWYkJHgXKep3LX5/fDUNMzxFKa9e7X1/kSIB2BNaYFQg7sYBU6qUVoO8yK/bY4RwKIaAxfaoBCI2+fbJBKB438fHm1v01Tyh6r58VLjZMC4XCOk+Po9sOFntoz0N64plWH3JPan6JZqljeLbRsPBIYEEYKTgqWNv0cL/4xWJhB07tEXBSh3mM74ELFhlAVT9RXl/Pl/h8/fx6ThkD/C8PM3D98ABrTM0e5CJEbuiQBItisnJwGAhbEF0VvdFAPL1p9Xz8BZA2TUodtreAlZk0cjidc9buGTfkUwA+mMBNBlCvRaLDMscsqFg2RA0j8yvUUR07lcprjN827ZGK4s3fBmyDhevvML6g7lzzbcJ5xBwcfum7GzjELDsfvZmaVevEz7IyqxvFY8VF6cfIZJZANXRKE9BeKobi4o3f21RiAJG/90yZbTpMFfHihVIANqZIUO0aZklRB3G9ddKxg0z8CVIxdEAW2CVAGzfnp172zb/91Xf4ps21Ttiy37Dc+fkgkAd3hFRrSEqsjd4/jyyYvKiyBGPIYsOF3P2iUPAiYnG/dSanvw+99yjzYsPa1knL7adH752ufQiMCVF/qLEC0BfLAkmDxvZUPChTEFMe0uI7HJ5j6YU03vweIqs9IWaNf27p/xN8Gw14bQAFnd04uRJ7xZAwHcBeNVVxmUi4kvookV6H3JZRLE3HA6jW4m3h4nLpc/3Chh91XnxG2h9cMIjJADtDO94L3uwqZ2dvyKJS2ui5i4GbPqSFUk+gCqq4EhM9K1AuyyRd9Om7L9o0RKrDHizAMbFGS1H4kMyPl7/Ri57CInZ+EUBmJDA8svxiJGn4j5inWGxXc2aGa97XhS5XPqHcNOm8ocyLwDXrjWu53E4TK3tDgDP3bpTt6zyYeGh5S1RtC83mZkFEAis1F9xCLVFLdiE0wJYXAFYpowxD6Csj/BVAPI5RtVlYv5SmY+sLLemPwlh4+KMvqfernNZwJboP+t0ap/dBuXinnrqKTgcDt1fHe5+zMnJwejRo1GuXDmUKlUK/fr1M1QbsxskAO0MH3El6xjUm9VTRyRbZ5cSdr4QiT6AquBISDBa42TIOng155/YkYpDmGJHLQZOnDxpfOsXjxkfDzRpYn5MwBjMIhOA4nChWFXH5dL7AIpDebK0LqLA5b/DX3/VB5q4XPo3GhVeAHpLA1OypD6oShjafux2IRgGwGlw91NcnGcrlC8WKk8WwHDj75Cx1YRaAPJ+mZ6itH1h925jJRDZb+5NAKr78PlH1XtJFFlffKGfz8iQC0B/qrvExxst675c5z//rJ8X+w+nU3tJNMvvGWbq16+Pw4cPu/9+VP0YAdx///346quv8Omnn2LVqlU4dOgQ+gZSniOMkAC0M/zFI/PFUTs7TyJJlmXdTn493ohkC6CvApAfulFRO3VRFInVH8SHg0w0iQJQZgH8+mvP7eT9cdT28efets14XjF6MS5OP5SjWjn5tovb8xa1bt2MD0g+ka3LZQycAPQC0FvNZ/G7ES2fSUnIhf77ScNpbZnT6Vm4uVzmJfBUeAvgnXey6W+/9bxPqPj0U52no6yUta0ItQDkr8fiWqUqVvSeBxDw3QLYpo1xnXgvi/fxkSN6IRvIMFBcnPEZ5HSaZ3YAWP5JsaycrC9TUaOYLSYuLg4ZGRnuv/JFfWt2djZmzJiBV199FR07dkSzZs3w/vvvY82aNVgXSJBmmCABaGd4p/hAh4B5P0IVW471mhBNAtDse/eU4kLc57vvPK+XCUAx+lhmAVyzRpv3xfLkcumvyS++MPrpiC8acXH6iEYx76Pss/DnkD1oRKuHWXk0FV98k3gkuQzF6iAAkIii31xWSUE8vjerGp/g9+232T1gVq4vUBo39r5NURLzz6DVpLa5QSP0ApAXKd5qmpuh3u8FBd5LwQG+uxXwdbDVa0g8rljxp3VrfZnRQHwoT58Gpk/XL3M6/Rdt4ufk2+ItuCpM/P3336hUqRJq1qyJIUOGuKuLbdy4EXl5eejM9Wl16tRBtWrVsNab24mF2GCMIfLJz89HXijqFaamAnv3sgep7PjJyeyvoEC+fudOFrklDhvqto3nFtuw5iKf1sSO7QP0329eHvtLTmbiweHQ1icmaut4qlc3/43OnNF//qpVjefj5xMSmFDilxUWGo/Pz8fFAaNGacOnJUrI28MvUxT2+dRljz3Ggj74bRIT9fMuF0tqqy6Lj9evF+eTk9k+6rKkJFa4Wp1v00ZLJaGul7Vdxek0fn8i4neVmir97o4qlVAx55BucXZSWZSQHYOH/zwA88lSq/Sov7m6jVnAyIAB8hq9nTr5fo+88w6gls4026dOHSA5GTde+NS96Prr8+x5G6rfaXJyaPuJhATj/ecv6n2Tm6vdV3wfLx5fPKeIep3w11ZhIVs2fbp+3z592Mua+mLdpAlLP6VeT3FxbL9q1TTf4aefBiZM0J+Tv24BNs2fJz/feD/z3H47S0/FpyaS3btNm7LRBfW7CiL5ReL7zJkzOM2lb0pMTESiRHRfddVVmDVrFi6//HIcPnwYTz/9NNq2bYstW7bgyJEjSEhIQGmh3GXFihVxxCzNjQ1wKEokmljswYEDB1C1alXMnTsXJSJpWJWjTx+t9u3ChV942JIgCJ7Bg3vg/Hm9hSUa7yHqI4ho5Pz58xgspsgCMGHCBDwlJtOXcOrUKVSvXh2vvvoqkpOTMXz4cFwURkFatGiBq6++Gi/yVlYbQRbAIJCVlYXKvtZIDCatWrF0IV9+KU+oPGcOMHq0ftkDD7gLhPMvVN27F6JHjx4hbGyAjBsHvPUWm7aJI7ABvpxSdjbwxhssIvbGG1m5LjVCrnlzYPlyY/klWaUD9bNmZmpBCdnZ+t+0QgVm5eWPN3w4C3Tgc/1lZ+u3WbOGXTsq33wDvPkm+6/Svz/L1m92jOxs4OWXgWefZfOvvgpccYU+6nDnTi2YBWCffdMmLeP4Qw8B//uftv6ZZ5hv0N69bL5TJ2YtUa0TffoACxdq23foABw9qqVG6dULePBBY+SjSmIi+67FlBU84uccN46V3VLZuJFlQj53DqcAJEBfhefPZc3w0AwhvQXPq69qCY0B1t6XX2bTx48za496/g8/BHr3Nh4jL0/v17lrl29Jonm2bWO+p2XLagmFRdzfg/YZbdlHAFpbK1bUJze1Iy1bsmv2q69YsMXIkexanz+frRfvs7/+0qeTEuGvE3Xf//0PuOMO4LnngJde0rZ94AHmVqAmjb7zTpaA/d572fy4cSxNGN+G8ePZvanSqROz+Kt5+0qVYtcQHwmcnc38inmBNWyYVpXorrvYtTdxorb+xReBRx7R5tevZ5/h99+Bzz4LugPqwaJAl61bt+qe3zLrn4zSpUvjsssuw86dO3HNNdcgNzcXp06d0lkBjx49ioxAKvqECRKAQSAuLg7xgZQFKi55eSzIQ1HkPiSFhcYgkNat3ds+/7y2+P33nYiPt6FLaH6+9hms+I59gf+O4+OZmLpwgXV277+vrT9/nq0Xf5OyZY3L1M9asqSWJiY+Xr+/Osxy991aJ68OP4pt4ufj4ozr09L0y776SpuvXt14jPh4JlbUZaofEr9NUpJ+PiGBbccva9lSX5mEz7tYWMiG0NXtFUW/b2EhK3+lViiQfXYRb+vVYauTJ9l8iRLGz3DZZW6fyYJnn4frSc3v8PE3q2BslcpIOlCULuaRR/Q+VvznAdjwmzp/5gyLylTnt20D+vWTt5E/Rrly/t8b6jHUa1KG5HuypJ/zBbWtFy/at59QKShg7VV9AMU+XP0scXFsmXgNijgcxn3z8tiylBT9vikp+j5VPY86rx4rIUF7Ca1dW7+9ouiv2wsXWD8l9g9iP7Nhg/5eFvsHcV71+VW/qyD/rnFFvs4pKSlIlVVp8sLZs2exa9cu3HzzzWjWrBni4+OxfPly9Cu6Z7dv3459+/YhS8yGYCNs+MQnfMZbFLBsdJ/LzcZbufmUg7YiEj0U1ITI1arpndI3bpRvLzpe82XVipyM3Yg5/gB93Wiz2sI8smhb0YLE1+w1CwrhHeLj4/XWPPU8fN46vgC8up6vmuJysYcNvz0/pBIXpy855XQCv/yi399bAIbL5T1QgG+TGAQiBHk445xogfW6TZIPcJHJYtSl+N3zriPite5r4EcgyZrVdhQ3lYndCHUi6GCgWt9Uf2FAf92qFmzVuu7t95V9ZvV3PXBAv/yqq4z3IH989ViqfyggL+koJqSXIfYbfKJnWclKWRSwegwb1AJ+8MEHsWrVKvzzzz9Ys2YNrr/+erhcLgwaNAhpaWm47bbbMHbsWHz//ffYuHEjhg8fjqysLLT0ZL21mAi4WwhTvEUBy5abPPxs+9IciQJQTesiWm/EZKmAPCrVU4fP/1Bq58iLNzMByKdcER8YTidwiAtouOkmfVJWXwSgy6V/aKj78cNxYhk0pxN4/XX9ev47c7mABQv08/xQudOpF5jeBKDTqbeWAPIIS76Nkihg8TOsh7GDd6eFEZN8u1z6iilOp9YGNXpcHTLyFK1/883m63zBRwF4HtpD2paVgkQiIXH1ziLr8Lx58jQwX34JLFvG3AMA7+lmZJ9Zrf89ZYp++WWXGQWgLA8gf12I/YlZfyC6tni7F0W/eVEQ8imVbCAADxw4gEGDBuHyyy/HjTfeiHLlymHdunWoUNSvT548Gb169UK/fv3Qrl07ZGRkYL46rG9TSABGMt4SQYviKRLejkUiMRG06pMmZoGXiY31643LPAlAtWMHtM7x9tu1ZWaRo/y5xevA5dJVh4HTqX9bN+vw+WMuWGB8AIiVOkQLoKwdntLmiA8rlwto0MB8vVj1QD2et9rA/DFkFsAfftDmix6+G6AvCedOCyMmXXc69f6XvABUrZ18GhgzPviAJRIO9P7wJgCLhq1GQEvvMXNmYKcKK5EgAFX275dbAFNSmH+deq94q6srg7eUi4j3kDgPMBcQFdFn1qw/EH20PfVjMgugrKqRjQTgJ598gkOHDuHixYs4cOAAPvnkE9TicnomJSVh6tSpOHnyJM6dO4f58+fb2v8PIAEY2fg7BByJYioSLYBqtn2x0oU6HMNb7FQR1L+/tozvkMWkwXzCZtW6xotIp9NYtQPQizVRWDid+kLy+fn6oSO1ExZr/fIWwC+/NIod2XlE64O4PZ/n0OXSBze5XPp2iTn3XC79kLEoSGUvQDIB6MkC6HTqBWTRMZvhV8Nh5mCIPghGbeOiRfr9RQugL8mBAVYLPFDBI7P08BQlr/0YmhM/r7VtSyQIQDW5+K23+vZbexueueUWbfrPP5nvsVhWTaV8eeNLmMwCyOOt+pAZoqDjc9LKBKD4OW1mAYxGSABGMoEMAUcakfwZRIuf+ia9dCnz8+PfslV/H0D/EFPr66olz8SobsBYDUNmOfLUyTudeqEjlnUyK1PFC8DkZLkA5Id5/vvPcztcLr2YjY/XJ452ufRRwDIB6MmZ1VcByFtQZUPA4jGL2lAIvfi4GXPkfk286HI4tHxravSzLxbA4hKAD2AkaKuIGOW4/HJtWmYBFPEmAPl7rF49Vtfb7MdSA8lUzHwA+RKLTqf+pTVQAchH8cqGgGVlLUkAhpQIuFsIU/wdAv7ww9C2JxREggAURYT6Ri4mT1WHSJo0YakNevXS1vFCQRUC6rF27ABmzWLzvEVQFZgjR2rLzB6AsmEefh8+Ck4VJCpqJ8z7CYptTkqSD3dep+WQQ4UKRuuD6EfI+/i5XMDHH5u3W/bw4rcR7wuZoJKV2eKtkDILoJr+AmAP2nbt2CSAKU/oawV/8avgLO90stQW/LzKO++w/+EUgLK+Q/z9I4lIEIC/FlmLjx831gKW4e068BSQIRuGFa3w/DWgnmvOHP2yf/81biNSs6bnc7/7rjYtswBu2cIi2vnzqKmp+GAvImhEwN1CmOJtCPiuu/Tz3FvdmTPa4kGDgtyuYBIJw9Z8pwVobRY7dU/O3FWqaNNiXrbatbVOlxdyarQq72to1jl78r0T38a5rPi6fcXhaN7CmZRkLDkntldNa8G3lbfYOZ3A449r8+fP63PmuVzMid3sc+Tn6z8/H8ks215ttydEK4XLxfIZ8sfkznnvrWd0m/eZKEROyAJhVIYPZ//DKQAB4z0mcyGIFCLBTKmKqS++8K0UnDc8VQnh78krr2T/+ZdqMdBKvR75+0JmqZchLhdfGPkckjIBmJ1tPkKgVikiggoJwEjGl1rAJvz+uzbtQ9JzwhPisGMgD3Bft5X50LVtqy3zxQIoE4D8+bOz9UJMPafYRv4NPznZuwCU+RuJb/xbt2rzn36q96E7eVJfYF4cYlYUfRtzcvRWB9l3LHt48sNfsmEpcV4QdNvajNBtsh+cuJcJwCZN2LT6WcItAE2GgfO4NLG8IdfWRIIAVH/va67xzQLoDU8vMfxL5xVXsP9qkBrArgO+iIF6XTz6qLZMvObNvmNxO/HFWOynxJerbt28+yMSQYW+4UjG2xCwB5Yt06aF8oX2IhKGgMWOTn2gFqdTN4M/pnoeb1YswPMQsDh/+rS+0L16TrFDFgWgGHUrHtsXAcgPP1aqpN9+zhzjkC//fYgCENDn0vPVB5DPvSgbLuetkg6H4TNeXlof/V0N+83b7HCwahCAJgZ8DQIpDj4IwFHQrC6jRoWuKUElEkSDWkN3+XLfLYCe0v54sgDy9Xpl15OYekn9/ry9MMoQ7xWxuhHvW2wWBMIfw+XS8mgOHSo/J1EsIuBuIUzxNgTsgZ9+0qZtPeITCUPAogVQ7dRDYcHhBZCaqoVfZubULwoxHtlQqkwwitvx2yQlGd/oAc9JZ8UhYJdLb2q64Qaj4BMfTPz6c+f0nzMjw/8IR0BfoF4Wufzqq/r14ncbF4e3cafukEeRru0vbq+K3lmz2O+nvvSEMjkn/13wUc0cM6BZMs2q69mOSBCAah7AlSt97ytkOURVPJUu4zMRqNdT587aMrM8gJ6i9c2+Y28vLGK2AvHec7mAf/7Rb6OKU971gwgaEXC3EKYUYwiYtwDamkiwAPIiJi/PaAH85BP2n8+tFygyp26+AzcTzHyn7csbvSwfnycLYFKS/Dj+WgD54SVRfD3+uD6FisulP2dOjvFh5U1EyQQgL0JdLn1wiw9DwNi5E3fiXd1mGTiqHc/MB7BlS30EcigFoKeXBsnv6GN5VOuJhCFgHtVFwdtv7ekH8LQvL5zU60707xOtbvy26jY8vgpAcWSEj+j3NQo4WivW2AQSgJGMpyFg/k0KkA/PRQKRIAD5jq58ec2io3ZeAwawz9GsWfHPJevs+Ye5WQQn32n78kYvSw3hyQJoNgzlrwD84AP9vGiJ/PZb83Z//bVRAPAPFVk9VVm7xUATPphENnwufsYtWwAU5QHkGItX5AJQraBStWr4BKDMlUAlEqzuZvD+bZHA+fPsvzcLoKfIbE8Jl/nfWSYAXS6WkFpFvaf8GTGQnQsw3ou8FdPhkFsAxfnMTJY2x7a1SiMbEoCRjKchYFEA/vZbyJsTEiJBAPKd0+nTwI8/sulQ+HDxnb2ajoQ/j5nQ9yScvFnufLUAyhAtj56igF0uo8+eKBjHj5e30QzeyqA+bHm8JYL29l25XMD//Z9+fePGAIAh0CcCn4yxRosL70OYnx8+Aeh0av2HxLpyCAFUnyACx1tfwUftiXi6TnwRgLy/r3pNiC+M/D5mVtZt28zbAegFYEEBOwdv2ZRZACdMYMcdM8bzsYmAIAEYyXgaAhZFoViRIFKIBGuE2dupvz6AZ86w1BAyS5UK39lv3mxcz1cK4eEtCL5YANesMa735gMoQxzSFQWdmAambl19O8XteYdVsT19++rnFUX/UJElk5W1m2+z+FvIBCB//zmduqK5I4fo08LMXFLZKDD5YS5eAIYyCATQC0+B7tBeGPjc27bl1lvZfz5vpF05edK4zNtvzQdziPiaRNpMAPIiTBaB7nTq7y0zC6CYPkqEv3fVlzH+BcxbcBoRdEgARjKehoD5ZLWRDF/ay66Ivi4q/nZgpUoBvXt7jur15u934oR8v8FaSS+fLIB8LVEzASgbJhbxZAEUh4ABaUCFbn7VKvNzyl6EeDHnqwWQ36d0ac/+kzIxzbV52vP6XIS3/a8uFFecfHteAMbFhd6fzazKwpVX4g80ds/y+cpty/TprEzgwIFWt8Q7amQrj7e+QlbfW6W4FkD+PlavhY0btWXifRpooA1/DFUE8/eft5RLRNChbziSKUYUcMTw6adWt8A7YgUMlVBYcPi3dZk4FpMfq4j1h0XLm8jhw9q0L1HARX5vBvhyd7IhYP6hkJfnPeL23nuN7VLx5i7gax5AUfB5sp77EBQyJ01fvs95zxj99rIh4FAO/6rwwpNHEIQRYYhxOPT57CINb33FZ5+Zr/NVAKoJqEUByO+v/vb8cK7TCbzxhn4+EPg8oeqLKu+iERcHdOlS/PMQPkPfcCRjNgQsvi3yPkqRxrXXWt0C72RlyZeH+snpT2APb00ShZeso61Xz7jeUyLo/v3l5xUfJOLDiheiZ88aLX6icOUfImK7xRch8b6QRRJ6swA6nZ4fRF4sgHA6MST1K4icQwlte9kQcDgEoMkQsJLrwdpEBIdx4/Tz3gRg48YsX6SYWw8AhgwxLlPhryO1nCR/zYs+qarLg5hwncfsflArjZjB91eqABSHgD0FnxBBh77hSMZsCFiMGBOEAv9clPUntiIS8k+YDdmG2ofLH5EgihpvApB/M/fFAtiihfy8vIAXBWBhoX447NQpY/AJf4GKTuPBENjJyVpJPRVRLHsaihXXmeQFXI22us1K4Zy2v2wI2CoL4LJlaPfnW6E/d6zz7LP6eV+u5UqVjLWpp0wxXr88fB80usgSLVoAec4VXZeeKviY3Q/Vq5u3Q2yLKgDFIJDt272fhwgaJAAjGbMhYLGWrDCE9ccf2vTIkSFoVzCJhChgszfVUFsA+YoV/uBweB8Clglv2Xb33stKWvHJZXn41DficFNBgf7l5NQpowWQF4hOp94ZXnxABHKtJCcbfyd/LIC+5AWMj0db/GjYdTTetHYIWGYBvOYa/MiJ1VOnQt+MmES85nx9WeRLtAHAnXfKt5MdV43C9SQA1fue95d1OIyWeBkyH1szVAEo5hvdvdv3YxDFhgRgJGM2BNy1q36+dm3d7N9/a9OXXx6CdgWTSPZvDLUFUIZZzS5RLHkTgLJEwbIca1OmAEuW+FYg3unUH7ewUG/R+O8/ow8gX6fQ6WR5wcwQ7wPV58kTycmeg2JEQSci29ck9+EF6C3Fb2E0ChSn5suZk6NV5QinBZATgPnQ/46y8s5ECPC1rxBLwnm7Tnhxr0bpehKA6gvIkiXaMofDtyAQTy4pTZvq580EYKTmq41QSABGMrIh4PPnNTO+CYsXa9O2L/Iui5iLFMLpPf/rr8BzzwGvvSZfL4ojMf+eCP9AUhPFBqIGxJx3YgJifr04BCxaAAH90LT4mcR5X14eZAJQHAL29DvKBKCJgEzCRTw2QqgT3Lc5sGABm3n0UWssgNwQcGPo883RKFyY8LWvcDiASy7R5r35yfEBauo5PAlA9QXkjD59kU8WwJkz2QvdO+8Y14n9kvqMEl/41KToRFggARjJyIaAxbqerVsbdpsxQ5u2fYTfc88BHTtGRn4vkXBaAJs2BR57zHfhwAtA8Sl/yy1652zVSvftt0DNmvrIXJGMDP28KAD5c4npR2QWQF4A5ufrr2/elA0YBaBZeh6epCTjTcBHUvOJmmXIfAD5B6TDoftNnrtX75976N8E6FqtCkBP1R2ChcQCuBVaUmCXM4Kt75GGP30Fn+Tfm0LnxZ56HXoSgOp1J4wa6QSg2TlLlmQuGnfcoS0rKGAZBdq2le8j3u981gAi5JAAjGRkQ8DiQ5UvbB+JpKcDy5dHRn4vETuraz4pq3r9HDjAapO+9Za+k9+xg/2vUgXYtQu4/37z4/qSm09FtNDVqePZApibq7doeEqY7e3cKjIL4LRp2rRMAIo+gjwyC6CQ+uajsRv1u6gScMwYS4NAbrpJv/rCv374dBHFIxwvi+r9INYCBoDJk5mx4O672XybNvp9fbEAynA6jS+FPD//rN+2Qwffj00UGxKAkYxsCJgXgCVKUCi9lYRKAB4+DLz8sm8+biridcA7f6p+N5UrA7ffbkyN4o9zt2gd+NEY/OBGTMvSvbtnH8AzZ/TBKaKrQ6BBIGKbxbJT69bp5/k2yIaPRQH4yy/avMuFwR2PGJpRACcTtxYFgRQUAB99pF8dX7qkcR8iNITjZVG932QWwPvuY/dqWhqbv+Ya9l+tzMM/Y9TruzgOogMGsP+8tV2sBESEHFIHkYxsCDgnR5v258FNBJ9QvdVnZAAPPOB5iDM7m0UIqiJRbIuatsWX5Lk1avjeNjERdbt25tuqD6QvvgCef54NE4lRvmKUMC/WgiUARRHHWztk8MJVNhwmCkD+pazIJ3AJrtHtEocC6xJB5+cbLo9Zg74jB8BwEg4LoGox9zQErFKuHHvhUlNGqIIN0K7vxx83rvOVSpWMy8QAKiLkkACMZGRDwP48rIngcfQo8NJL+mVWdmapqcDbb2siUXzAlCrFxJYvaRdkNXTNEF86zKqkAFpUYu/eLDGu6CMI6IM+srP161QBqPoriW4CvgjCpCT/hc6HH2rTYlUVwPMQcVFQyTVYZjjs38dLaz6Ooi9vELh4kX0lK1cCL74I/HKxEe7G63B0NpaNHDZO8oAmQoc/fcXRokCiZ57x7xyq76AvAhBgfYTabzRooC1Xr++HHgI2bQLmzPGvHYCW35MfiRCDxIiQQ992JOOpFrAPUMBVEElPZx3iww9ry+zUmck6ejGprBmyChrFOa/Kn38al/EWSUXRC0Cx2LwqAH/+mVkqREdzX30AxfvHm9uEmJvwnnuAp56S728iAAHgJMqgLDSL6WWzHoPyT9FN+dtv3ttugqKwr6RlS29bfiRdegiZQJWtAZ+f8JF58zTrmZfMDTrS0/2zdnfpwtK6vPIKmxerb/gC7/agWqkdDlahxB9++okFk6npqvjEz/60hwgKZAGMZIpZC7hfvyC2hTCipk+xA3zuH3/xxwLoz7533WVcxotmRdE/EMwsgKVLs6HmQIYsk5LYQ4nH20NIDFSRRQKrOBx6oc0Nc5XBKcOhb1852IdGGykoYMYY1QXRu/gzJxNHIjv9UqTA52s9dix05/nuO3YvyRJB++ojzu/Duxn5S6tWrAqKWYUnEoBhhQRgJGOWCNoDu3Zp05FcOz0i4CNtrWb8+MD3lVnqfIWvBKLy118s950s4o9/AIgvNqIFUMxVJqLeF54ecgkJQLdu5m2QwYtUMehDPJ/TqU+2KeQVPLmGq5UMYDpuhwMKCuDEq69qo+Le/uLijLl2A0EB+f2FDT6IIpQCUMTXIWAePi2RWGq0OIilqDZtCt6xCa+QAIxkAhgC/uYbbbqT0fWHCCbqG7cd6NULWLoU2Ls3vOdt0QJYtkzva1inDtCnj3x70QLIIwpAb6j7e3rIJSQAn33Ghu/Xr2fLvFlFRAsgXzVBtl6MbObWlymtoH1NY0m/OBTggQc8NyPYnEey942I4MFbjsP5shiIAOTbqt4nwUC0BIr3EhFSSABGMt6GgCVldWbO1KY9+ecTAcIP69gtBU/nzprzdahQcwTWqqUt69TJ9+Ak/jsTr2txCLhqVd+OqfosyYiPZ0O0L72kRUb7OwT8ww/m68U8gmJlEacTK0d/5vl8Qeb335nmHVXpC7yJ0cie8RmU199AMooxtEcEhtqHt28fvnPyAjAQX9OdO4PXFvFe+/bb4B2b8IrNnlCEX3gbAl640LCIryJEhAA+GMBOPoDh4oUX2PAun/vOH3hLgxh8IgpAb9+vL64RMrHnzZdQFIBiMI3oAygOCUsshMEeet23j7lfKorxr1Ej5v/7Vv2pGI23kJqQwwJZiPBz5AiwcaP/wRTFgbe6rV3r//7eErD7g/iS3K0b81NS62MTIYUEYCTjbQhYMsYr0YREMLniCm1aTA8SqYiJoT2RkMCGd4MRRCAGkJg5jpsRSF5AwPvDR7TwifeZ+FA7fFi/rygAi3L+7ek2KoDGaqxbp4m8qlV9GN3jEkFT+iiLSE/X9xnhgL+fw+1nICIbJalZMzylEAkSgBFNMaOAiRCQkMCqaVx/PVC/vvft7cyUKez/Z+EdonQjWgDHjtXPe0oyzaPWkVYT13rjnntYMuj77pOvFwWcOnQsWw/oHW9lArDIR/CSxMNQ4IACB04hDYWFcgueorBbfv9+/bKrrvLt47nhS8Ht2ePnzkTE4nAAs2axOuvBiBwqDhT1ayk2SlRG+E0AUcBEGHj3XatbEBzuvZdF6flreQsWogBUcwK+9hrLZOzte1ZfjAYOZEEwEp9YKQ6HPtJx6FDggw+0eVHAicf15PspDgHzyW83b2ZpMtasQdrN18HTqLDDwUozFwuuEogOO0WvE6Fh2DCrW8Cwm590jEHffiQjDgFv2WJdW4joxCrxBxiHgdTAknvuAQ4c0FcRkMEHf/gq/mRMnw489pgW/SgKwN692XRmpnE9wCzCKqIFkBeAu3cDa9aw6XDURFXbIQptfsiaIER8TSDvCzTUaylkAYxkxCHg77+3ri0EEWxat2b/169nfzfcoK3zJemzp+hff4iPZ8NlKqKAq1EDOHSIJaQGjFYNPtxeFIAul7zury8l+oqLmQWQrDKEjFmzgLvvZi9fweLEieAdi/AbutMjGXEImI/k69w5/O0hiGDw99/AV19piaJbtGAPHrsIk21c8ma1TZmZmnO9KE5FiyGfjd3lkpcMDMfLHB8EQhDeGDaM5eLkE1gXly5dgncswm9s0qMSAeEpClhSoJsf6Rk9OkRtIojicumlzGcvUNSawNdfL1/vbejYGw0aaNMyUSoOqYoWQ97HTswTqBKOQt18EAhBWEGPHsC0aYGloyGKDQnASIYfAv75Z/26ihUNm/N+7XXqhLBdBGElCxYA77yjz3rOs25d8Y6vBqMA8qHocuX086JI5CvEnDoFfP218RjTpwfcPJ9RBeA+YyUSgggLDgcLNCtO8WoiYMgHMJLhh4B9yAHx5Zfa9NChIWoTQVhNuXLAHXeYry9dmr00+eJHKEOsBSzSuzdw113aPSla+CpV0qZr1wb++y+wdhQXtV1vvqktW7zYmrYQBBF2osoCOHXqVFxyySVISkrCVVddhZ9FqxjHrFmz4HA4dH9JfImcSMDPWsB8lR0qA0fENIGKPwA4d06bFquTAOy+nDpVe8sSBaDDwYZd8/PZurvvNh6jb9/A2+crMt/Djh1Df16CIGxB1AjAefPmYezYsZgwYQJ+/fVXNG7cGF27dsWxY8dM90lNTcXhw4fdf3v37g1ji4OAWSLoBx+Ubs6LvuI8/wgipilfXpsOtNwcnw/w11+N631Ncl0cZO2SRSQTBBGVRI0AfPXVV3H77bdj+PDhqFevHt5++22UKFECM838gAA4HA5kZGS4/ypK/OZsjVkiaD7vGAc/BEwQRIDwedB8qWTAO9/KkL2N3Xijf20KBJkFkCCImCEqBGBubi42btyIzlzqE6fTic6dO2Oth+iis2fPonr16qhatSquu+46/Pnnn+FobvAwGwI2eeDIRqsIgvATXrDVru19+9df97y+WjXjsuIkrvYVKsNFEDFNVAjAf//9FwUFBQYLXsWKFXHkyBHpPpdffjlmzpyJL774AnPmzEFhYSFatWqFAx6SXF68eBGnT592/505cyaon8NvzIaAxShEgiCCy549wB9/+FY27ZprPK8vW9a4LBxOuqIFcMaM0J+TIAjbEBUCMBCysrIwdOhQNGnSBO3bt8f8+fNRoUIFvPPOO6b7TJo0CWlpae6/evXqhbHFEsyGgC+9NPxtIYhY4pJLgIYNfdu2Xz/P6xs31s+Hq7a3KACHDAnPeQmCsAVRIQDLly8Pl8uFo0eP6pYfPXoUGRkZPh0jPj4eTZs2xc6dO023GTduHLKzs91/W7duLVa7i43ZEDD59hCEfWjf3vN63gKo1hUOB+IQMAWAEERMERUCMCEhAc2aNcPy5cvdywoLC7F8+XJkZWX5dIyCggJs3rwZmWpBdwmJiYlITU11/6VYnUtFHQL2s5RT8+YhaAtBEHLq1AE2bAAOHvS+batWoW+PiviiaJdSewRBhIWoMRWNHTsWw4YNQ/PmzdGiRQtMmTIF586dw/DhwwEAQ4cOReXKlTFp0iQAwDPPPIOWLVvi0ksvxalTp/C///0Pe/fuxYgRI6z8GP6hdth8eK/J8G9enjatllglCCJMNGvm23bhfKmkIBCCiGmi5pVvwIABePnllzF+/Hg0adIEmzZtwuLFi92BIfv27cPhw4fd2//333+4/fbbUbduXfTo0QOnT5/GmjVrrPfr8wdVAPKBLqtXSzc9e1abvuGGELaJIAj/ue029vJ2003hOye5ihCE3/hTcMLuRFUPMGbMGIwZM0a6buXKlbr5yZMnY/LkyWFoVQiR5Q8zGcJ+911tun79ELWHIIjAmD6dBX+EM0M7WQAJwi/UghNvv/02rrrqKkyZMgVdu3bF9u3bke5LRgCbETUWwJjED5+dRx/VpsORYowgCD8Jd3mejz8O7/kIIsIJpOCEnYkqC6BV5OfnI493sgsXcXFAcrI2n5iod/bToUX4WdJWgiDsxeHD+v6D+gUihsgvCp48c+YMTp8+7V6emJiIxMREw/ZqwYlx48a5l/lScMLOkAAMAmvXrkWJEiXCf+LatY1v8d98Y7LxddwmZtsQBBEzvPWWfp76BSKGOH/+PAAY/P4nTJiAp556yrC9p4IT27ZtC1k7QwkJwCCQlZWFypUrh//Eb7wBPPGEfpkP9d569OgRogYRBBEx1KunT01DtSKJGOJg0bW/detW3fNbZv2LVkgABoG4uDjEW5FE1eEALlzQL/OhHZa0lSAIe9GyJTBnjjZP/QIRQ8QVRcGnpKQgNTXV6/bBKDhhNygIJJIJt9M4QRDRw7//Wt0CgogYglFwwm6QAIxkKHM/QRCBEklJ7wnCBowdOxbvvfceZs+ejb/++gujRo3SFZyINGgIOJIRBWDbtta0gyCIyOOaa6xuAUFEFAMGDMDx48cxfvx4HDlyBE2aNNEVnIg0SABGMuIQsEkgCl8F5LnnQtgegiAiB97v6dprrWsHQUQQngpORBo0hhjJiBZAE0fUV17RpumlnyAIN/ffD5QtC3zwgdUtIQgizJAAjGREAcgls+R56SVtukmT0DWHIIgI49VXWTBI6dJWt4QgiDBDAjCSEYeAb7tNullRvksAlOmBIAgByiZAEDEJCcBIRrQAtmxpTTsIgiAIgogoSABGMqIApLQwBEEQBEH4ACmGSIYfurniCuvaQRAEQRBEREECMJLhLX7k3EcQBEEQhI+QAIxkeAEYJ0/pyJcKLlMmxO0hCIIgCCIiIAEYyfBDwCYWwBUrtOnp00PcHoIgCIIgIgISgJEMbwFcuVK6Sa9e2nTPnqFtDkEQBEEQkQEJwEjGz6jfxMQQtYMgCIIgiIiCBGAkww8Bu1zWtYMgCIIgiIiCBGAkw1sACwqsawdBEARBEBEFCcBIxssQ8M6dYWoHQRAEQRARBQnASIYfAr7vPsPq2rW16c8/D31zCIIgCIKIDEgARjK8BTAhweOmffqEtikEQRAEQUQOJAAjGQ8C8Px5800JgiAIgohtSBZEMr/8ok0LArBkyTC3hSAIgiCIiIEEYCTzf/+nTf/9t+lmfDUQgiAIgiAIEoCRzC23aNPz5rkn+dgQALj66vA0hyAIgiCIyIAEYCTTurU2fdllAIC777aoLQRBEARBRAwkAG3IJ58wK57499BDwLFjTOQ98giwZG0KjiIdC9AHXS5+BYcDePNN/bFycqz5DARBEARB2BeHoiiK1Y2IVA4cOICqVati//79qFKlStCOKw7hFgf6dQmCIAhCT6ie35EEWQCjmMJCq1tAEARBEIQdIQFoQzwE9PpMQUFwLYkEQRAEQUQPJABtyKWXAoMGBb5/QQElfiYIgiAIwhySCTZl7lzg7Fnmw5eby3L55eQA+/YBf/0FbNkCjBwJrHhzK/Z+vgEHDgD5+Wx7En8EQRAEQXgizuoGEOao1Tzi47VcflWrauunTQOAeuFuFkEQBEEQEQ7ZigiCIAiCIGIMEoAEQRAEQRAxBglAgiAIgiCIGIMEIEEQBEEQRIxBApAgCIIgCCLGIAFIEARBEAQRY5AAJAiCIAiCiDFIABIEQRAEQcQYJAAJgiAIgiBiDBKABEEQBEEQMQYJQIIgCIIgiBiDBCBBEARBEESMQQKQIAiCIAgixoizugGRTGFhIQDg8OHDFreEIAiCIAhfUZ/b6nM8FiEBWAyOHj0KAGjRooXFLSEIgiAIwl+OHj2KatWqWd0MS3AoiqJY3YhIJT8/H7/99hsqVqwIpzO4o+lnzpxBvXr1sHXrVqSkpAT12NEGfVf/3969B0VVv38Afy8sLCDCKuRyURSveEEDSUJNSxFUxluNFoOE5lQomni3MbXGMcisGXVMyxmFykQtsfLGEKKGISgKihe8Jo6BZghoaAL7/P7ox9ETRltfaJf2/ZphhnM+T+c8+/7j+Mxhz8l0zMp0zMp0zMp0zMp0TZmV0WjEjRs3EBAQAK3WOu+FcQC0UJWVlXB1dUVFRQVcXFzM3Y5FY1amY1amY1amY1amY1amY1ZNiw+BEBEREVkZDoBEREREVoYDoIXS6XRYunQpdDqduVuxeMzKdMzKdMzKdMzKdMzKdMyqafE7gERERERWhncAiYiIiKwMB0AiIiIiK8MBkIiIiMjKcAAkIiIisjIcAC3Q2rVr0aFDBzg4OCA4OBi5ubnmbqlRJSQk4KmnnkLLli3Rpk0bjB07FkVFRaqa+/fvIy4uDm5ubnB2dsYLL7yg/K/36hQXFyMiIgJOTk5o06YN5s2bh5qaGlXNgQMHEBgYCJ1Oh86dOyMpKaleP80p78TERGg0GsTHxyv7mNVD169fx8SJE+Hm5gZHR0f4+/vj2LFjyrqIYMmSJfD09ISjoyNCQ0Nx4cIF1THKysoQFRUFFxcX6PV6TJkyBXfv3lXVnDx5Es888wwcHBzQrl07rFixol4v27dvh5+fHxwcHODv7489e/Y0zYf+B2pra7F48WL4+vrC0dERnTp1wrJly/DoM4HWnNWhQ4cwatQoeHl5QaPRYOfOnap1S8rGlF6aUkNZVVdXY8GCBfD390eLFi3g5eWFl19+GT/99JPqGNaSlcURsigpKSlib28vGzdulNOnT8urr74qer1ebty4Ye7WGk14eLhs2rRJCgsLJT8/X0aOHCk+Pj5y9+5dpSY2NlbatWsnGRkZcuzYMXn66aelf//+ynpNTY306tVLQkND5cSJE7Jnzx5xd3eXN998U6m5fPmyODk5yezZs+XMmTOyZs0asbW1lX379ik1zSnv3Nxc6dChg/Tu3Vtmzpyp7GdWvysrK5P27dvLpEmTJCcnRy5fvixpaWly8eJFpSYxMVFcXV1l586dUlBQIKNHjxZfX1+5d++eUjN8+HDp06ePHDlyRL7//nvp3LmzREZGKusVFRViMBgkKipKCgsLZcuWLeLo6Cgff/yxUnP48GGxtbWVFStWyJkzZ+Stt94SOzs7OXXq1L8Txl9Yvny5uLm5ya5du+TKlSuyfft2cXZ2llWrVik11pzVnj17ZNGiRbJjxw4BIKmpqap1S8rGlF6aUkNZlZeXS2hoqGzdulXOnTsn2dnZ0q9fP+nbt6/qGNaSlaXhAGhh+vXrJ3Fxccp2bW2teHl5SUJCghm7alo3b94UAHLw4EER+f2iYWdnJ9u3b1dqzp49KwAkOztbRH6/6NjY2EhpaalSs27dOnFxcZHffvtNRETmz58vPXv2VJ3rxRdflPDwcGW7ueR9584d6dKli6Snp8vgwYOVAZBZPbRgwQIZOHDgn64bjUbx8PCQ999/X9lXXl4uOp1OtmzZIiIiZ86cEQBy9OhRpWbv3r2i0Wjk+vXrIiLy0UcfSatWrZTs6s7drVs3ZXvChAkSERGhOn9wcLC8/vrr/9uHbCQRERHyyiuvqPY9//zzEhUVJSLM6lF/HGosKRtTevk3PW5Y/qPc3FwBIFevXhUR683KEvBPwBbkwYMHyMvLQ2hoqLLPxsYGoaGhyM7ONmNnTauiogIA0Lp1awBAXl4eqqurVTn4+fnBx8dHySE7Oxv+/v4wGAxKTXh4OCorK3H69Gml5tFj1NXUHaM55R0XF4eIiIh6n4dZPfTNN98gKCgI48ePR5s2bRAQEIANGzYo61euXEFpaanqM7i6uiI4OFiVlV6vR1BQkFITGhoKGxsb5OTkKDWDBg2Cvb29UhMeHo6ioiLcvn1bqWkoT3Pr378/MjIycP78eQBAQUEBsrKyMGLECADMqiGWlI0pvViaiooKaDQa6PV6AMzKnDgAWpBbt26htrZW9Q81ABgMBpSWlpqpq6ZlNBoRHx+PAQMGoFevXgCA0tJS2NvbKxeIOo/mUFpa+tic6tYaqqmsrMS9e/eaTd4pKSk4fvw4EhIS6q0xq4cuX76MdevWoUuXLkhLS8PUqVPxxhtvIDk5GcDDz9rQZygtLUWbNm1U61qtFq1bt26UPC0lq4ULF+Kll16Cn58f7OzsEBAQgPj4eERFRQFgVg2xpGxM6cWS3L9/HwsWLEBkZCRcXFwAMCtz0pq7AbJucXFxKCwsRFZWlrlbsUjXrl3DzJkzkZ6eDgcHB3O3Y9GMRiOCgoLw7rvvAgACAgJQWFiI9evXIyYmxszdWZZt27Zh8+bN+OKLL9CzZ0/k5+cjPj4eXl5ezIqaRHV1NSZMmAARwbp168zdDoF3AC2Ku7s7bG1t6z3BeePGDXh4eJipq6Yzffp07Nq1C5mZmWjbtq2y38PDAw8ePEB5ebmq/tEcPDw8HptT3VpDNS4uLnB0dGwWeefl5eHmzZsIDAyEVquFVqvFwYMHsXr1ami1WhgMBmb1/zw9PdGjRw/Vvu7du6O4uBjAw8/a0Gfw8PDAzZs3Ves1NTUoKytrlDwtJat58+YpdwH9/f0RHR2NWbNmKXeZmdWfs6RsTOnFEtQNf1evXkV6erpy9w9gVubEAdCC2Nvbo2/fvsjIyFD2GY1GZGRkICQkxIydNS4RwfTp05Gamor9+/fD19dXtd63b1/Y2dmpcigqKkJxcbGSQ0hICE6dOqW6cNRdWOqGgJCQENUx6mrqjtEc8h46dChOnTqF/Px85ScoKAhRUVHK78zqdwMGDKj3OqHz58+jffv2AABfX194eHioPkNlZSVycnJUWZWXlyMvL0+p2b9/P4xGI4KDg5WaQ4cOobq6WqlJT09Ht27d0KpVK6WmoTzNraqqCjY26su/ra0tjEYjAGbVEEvKxpRezK1u+Ltw4QK+++47uLm5qdaZlRmZ+ykUUktJSRGdTidJSUly5swZee2110Sv16ue4Gzupk6dKq6urnLgwAEpKSlRfqqqqpSa2NhY8fHxkf3798uxY8ckJCREQkJClPW6V5uEhYVJfn6+7Nu3T5544onHvtpk3rx5cvbsWVm7du1jX23S3PJ+9ClgEWZVJzc3V7RarSxfvlwuXLggmzdvFicnJ/n888+VmsTERNHr9fL111/LyZMnZcyYMY99fUdAQIDk5ORIVlaWdOnSRfVKivLycjEYDBIdHS2FhYWSkpIiTk5O9V5JodVqZeXKlXL27FlZunSp2V9t8qiYmBjx9vZWXgOzY8cOcXd3l/nz5ys11pzVnTt35MSJE3LixAkBIB9++KGcOHFCeXLVkrIxpZem1FBWDx48kNGjR0vbtm0lPz9fdb1/9Ilea8nK0nAAtEBr1qwRHx8fsbe3l379+smRI0fM3VKjAvDYn02bNik19+7dk2nTpkmrVq3EyclJxo0bJyUlJarj/PjjjzJixAhxdHQUd3d3mTNnjlRXV6tqMjMz5cknnxR7e3vp2LGj6hx1mlvefxwAmdVD3377rfTq1Ut0Op34+fnJJ598olo3Go2yePFiMRgMotPpZOjQoVJUVKSq+eWXXyQyMlKcnZ3FxcVFJk+eLHfu3FHVFBQUyMCBA0Wn04m3t7ckJibW62Xbtm3StWtXsbe3l549e8ru3bsb/wP/Q5WVlTJz5kzx8fERBwcH6dixoyxatEj1j7I1Z5WZmfnYa1RMTIyIWFY2pvTSlBrK6sqVK396vc/MzFSOYS1ZWRqNyCOvficiIiKi/zx+B5CIiIjIynAAJCIiIrIyHACJiIiIrAwHQCIiIiIrwwGQiIiIyMpwACQiIiKyMhwAiYiIiKwMB0AiahYmTZqEsWPHmruNf6y5909E/y1aczdARKTRaBpcX7p0KVatWgVzvLf+wIEDeO6553D79m3o9fp//fxERE2BAyARmV1JSYny+9atW7FkyRIUFRUp+5ydneHs7GyO1oiI/pP4J2AiMjsPDw/lx9XVFRqNRrXP2dm53p9Qn332WcyYMQPx8fFo1aoVDAYDNmzYgF9//RWTJ09Gy5Yt0blzZ+zdu1d1rsLCQowYMQLOzs4wGAyIjo7GrVu3TO41KSkJer0eaWlp6N69O5ydnTF8+HDVEFtbW4vZs2dDr9fDzc0N8+fPr3f30mg0IiEhAb6+vnB0dESfPn3w5ZdfAgBEBKGhoQgPD1f+u7KyMrRt2xZLliz5u/ESEdXDAZCImq3k5GS4u7sjNzcXM2bMwNSpUzF+/Hj0798fx48fR1hYGKKjo1FVVQUAKC8vx5AhQxAQEIBjx45h3759uHHjBiZMmPC3zltVVYWVK1fis88+w6FDh1BcXIy5c+cq6x988AGSkpKwceNGZGVloaysDKmpqapjJCQk4NNPP8X69etx+vRpzJo1CxMnTsTBgweh0WiQnJyMo0ePYvXq1QCA2NhYeHt7cwAkosYhREQWZNOmTeLq6lpvf0xMjIwZM0bZHjx4sAwcOFDZrqmpkRYtWkh0dLSyr6SkRABIdna2iIgsW7ZMwsLCVMe9du2aAJCioqLH9pOZmSkA5Pbt20p/AOTixYtKzdq1a8VgMCjbnp6esmLFCmW7urpa2rZtq/R///59cXJykh9++EF1rilTpkhkZKSyvW3bNnFwcJCFCxdKixYt5Pz584/tkYjo7+J3AImo2erdu7fyu62tLdzc3ODv76/sMxgMAICbN28CAAoKCpCZmfnY7xNeunQJXbt2Nem8Tk5O6NSpk7Lt6empnKOiogIlJSUIDg5W1rVaLYKCgpQ/5168eBFVVVUYNmyY6rgPHjxAQECAsj1+/HikpqYiMTER69atQ5cuXUzqj4jor3AAJKJmy87OTrWt0WhU++qeLjYajQCAu3fvYtSoUXjvvffqHcvT0/N/Oq/8jSeU7969CwDYvXs3vL29VWs6nU75vaqqCnl5ebC1tcWFCxdMPj4R0V/hAEhEViMwMBBfffUVOnToAK22aS5/rq6u8PT0RE5ODgYNGgQAqKmpQV5eHgIDAwEAPXr0gE6nQ3FxMQYPHvynx5ozZw5sbGywd+9ejBw5EhERERgyZEiT9E1E1oUPgRCR1YiLi0NZWRkiIyNx9OhRXLp0CWlpaZg8eTJqa2sb7TwzZ85EYmIidu7ciXPnzmHatGkoLy9X1lu2bIm5c+di1qxZSE5OxqVLl3D8+HGsWbMGycnJAH6/O7hx40Zs3rwZw4YNw7x58xATE4Pbt283Wp9EZL04ABKR1fDy8sLhw4dRW1uLsLAw+Pv7Iz4+Hnq9HjY2jXc5nDNnDqKjoxETE4OQkBC0bNkS48aNU9UsW7YMixcvRkJCArp3747hw4dj9+7d8PX1xc8//4wpU6bg7bffVu4avvPOOzAYDIiNjW20PonIemnk73xxhYiIiIiaPd4BJCIiIrIyHACJiIiIrAwHQCIiIiIrwwGQiIiIyMpwACQiIiKyMhwAiYiIiKwMB0AiIiIiK8MBkIiIiMjKcAAkIiIisjIcAImIiIisDAdAIiIiIivDAZCIiIjIyvwfRyMsiXKMBzIAAAAASUVORK5CYII=",
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+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#finds the actual maximum deceleration (not just the approximated one)\n",
+    "#print(plot_range_df.at[1,'Start'])\n",
+    "max_dec_list = []\n",
+    "for a in range(1, num_drops+1):\n",
+    "    max_dec = max(accg[plot_range_df.at[a,'Start']:plot_range_df.at[a,'End']])\n",
+    "    max_dec_list.append(max_dec)\n",
+    "    #print(max_dec) #these should match the maximum values shown in cell []\n",
+    "print(max_dec_list)\n",
+    "\n",
+    "#makes a dataframe of only deceleration values\n",
+    "index_df = pd.DataFrame(data={'Accg':accg}, index = range(0,len(accg)))\n",
+    "#print(index_df)\n",
+    "\n",
+    "max_index_list = []\n",
+    "#finds the index of the maximum deceleration values\n",
+    "for a in range(1, num_drops+1):\n",
+    "    drop_range = index_df[plot_range_df.at[a,'Start']:plot_range_df.at[a,'End']]\n",
+    "    #print(drop_range)\n",
+    "    max_index = drop_range.idxmax().values\n",
+    "    max_index = int(max_index)\n",
+    "    max_index_list.append(max_index)\n",
+    "    print(max_index)\n",
+    "print(max_index_list)\n",
+    "\n",
+    "#visualize the above points for validation\n",
+    "relevant_pts = pd.DataFrame({\"acc\":max_dec_list, \"index\":max_index_list})\n",
+    "print(relevant_pts)\n",
+    "\n",
+    "%matplotlib ipympl\n",
+    "\n",
+    "fig, (ax1) = plt.subplots(1)\n",
+    "ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "ax1.set(xlabel=\"Time Index\")\n",
+    "    \n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "\n",
+    "\n",
+    "#Plot pore pressure\n",
+    "ax2.plot(ppm, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "\n",
+    "#plt.plot(data, label = (\"Deceleration (g)\", \"Pore Pressure ([])\"))\n",
+    "ax1.scatter(relevant_pts[relevant_pts.columns[1]], relevant_pts[relevant_pts.columns[0]], marker = \"x\", color = \"green\", label = \"Peaks\")\n",
+    "plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "plt.xlabel(\"Count\")\n",
+    "#plt.ylabel(\"Deceleration (g)\")\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Define the plot that overlays deceleration and ppm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib ipympl\n",
+    "\n",
+    "def dec_ppm_plot():\n",
+    "    #Plot deceleration\n",
+    "    #fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "    ax1.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    plt.title(\"Drop \"+ str(a+1))\n",
+    "    ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "    ax1.set(xlabel=\"Time Index\")\n",
+    "    plt.legend(loc = \"upper left\")\n",
+    "    ax2 = ax1.twinx()\n",
+    "\n",
+    "    #filter the pore pressure readings to show a smoother line\n",
+    "    c=1\n",
+    "    n = 50  # the larger n is, the smoother curve will be\n",
+    "    b = [1.0 / n] * n\n",
+    "    ppm_filtered = lfilter(b, c, ppm)\n",
+    "\n",
+    "    #Plot pore pressure\n",
+    "    ax2.plot(ppm, color = 'b', alpha = .2)\n",
+    "    ax2.plot(ppm_filtered, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "    ax2.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "    plt.legend(loc = \"upper right\")\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Preview the plots for interval picking"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b8200136a3d44eeaa288bbaa6b9fab64",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "12d496541eee4b70baff1747d0ecbafc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for a in range(0, num_drops):\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    dec_ppm_plot()\n",
+    "    ax1.plot(gX55g, label = \"X-Tilt (g)\")\n",
+    "    ax1.plot(gY55g, label = \"Y-Tilt (g)\")\n",
+    "    ax1.legend(loc = \"upper left\")\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create Array for indexing info to go into"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  file_num dataset drop_num release water_entry sebed_pen peak_dec pen_end  \\\n",
+      "0      NaN     NaN      NaN     NaN         NaN       NaN      NaN     NaN   \n",
+      "\n",
+      "  expert_req  \n",
+      "0        NaN  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Create an empty DataFrame with 8 columns and n rows\n",
+    "#first 3 columns are filled in automatically using user inputs\n",
+    "#last column is a \"toss-out\" indicator, describing whether penetrometer likely fell over during penetration (1 = toss, 0 = keep)\n",
+    "#all other columns represent time index values\n",
+    "\n",
+    "index_df = pd.DataFrame(columns=['file_num','dataset','drop_num', 'release', 'water_entry', 'sebed_pen', 'peak_dec', 'pen_end', \"expert_req\"], index=range(num_drops))\n",
+    "\n",
+    "# Display the empty DataFrame\n",
+    "print(index_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Find Point of penetration end (where values crosses 1g)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[37921]\n"
+     ]
+    }
+   ],
+   "source": [
+    "pen_end_list = []\n",
+    "for a in range(0, num_drops):\n",
+    "    global pen_end\n",
+    "    below0list = list()\n",
+    "    #for i in range(dropstart+jindex, dropend, 1):\n",
+    "    for i in range(relevant_pts.loc[a,\"index\"], plot_range_df.loc[a+1,'End']):\n",
+    "        if accg[i] < 1: #the offset is applied later in the code\n",
+    "            penend = i \n",
+    "            below0list = np.append(below0list, penend)\n",
+    "    pen_end=int(min(below0list))\n",
+    "    pen_end_list.append(pen_end)\n",
+    "\n",
+    "print(pen_end_list)\n",
+    "\n",
+    "#add list to output dataframe\n",
+    "index_df['pen_end']= pen_end_list"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Decide if drop fell over during penetration"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "expert_req_list = []\n",
+    "\n",
+    "keep_limit = 100 #maybe this should change?\n",
+    "\n",
+    "for a in range(0, num_drops):\n",
+    "\n",
+    "    if relevant_pts.loc[a,\"index\"] - pen_end_list[a] < keep_limit:\n",
+    "        expert_req = 0\n",
+    "    else:\n",
+    "        expert_req = 1\n",
+    "\n",
+    "    expert_req_list.append(expert_req)\n",
+    "\n",
+    "print(expert_req_list)\n",
+    "\n",
+    "#add list to output dataframe\n",
+    "index_df['expert_req']= expert_req_list\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For each drop, pick index points for:\n",
+    "1. release\n",
+    "2. water entry, and \n",
+    "3. pentration start \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[36597.22580645161, 37573.83870967742, 37817.2726326743]\n",
+      "[36597, 37573, 37817]\n"
+     ]
+    }
+   ],
+   "source": [
+    "matplotlib.use('TkAgg')\n",
+    "index_click_list = []\n",
+    "\n",
+    "for a in range(0, num_drops):\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.title(\"Pick moments of release, water entry, and sebed penetration for drop \"+ str(a+1))\n",
+    "    dec_ppm_plot()\n",
+    "    #specifies user inputs\n",
+    "    index_click = plt.ginput(n=-1, show_clicks=True)\n",
+    "    for t in index_click:\n",
+    "        for x in t:\n",
+    "            index_click_list.append(x)\n",
+    "    #user_input = input(\"Enter a value (press Enter to stop): \")\n",
+    "    plt.close()\n",
+    "\n",
+    "#print(index_click_list)\n",
+    "\n",
+    "#remove the axis values to only record the indices\n",
+    "index_click_list = index_click_list[::2]\n",
+    "\n",
+    "print(index_click_list)\n",
+    "\n",
+    "#convert to list of integers\n",
+    "for x in range(0, len(index_click_list)):\n",
+    "    index_click_list[x] = int(index_click_list[x])\n",
+    "\n",
+    "print(index_click_list)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Fill dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  file_num    dataset  drop_num release water_entry sebed_pen  peak_dec  \\\n",
+      "0     02C2  Duck_2023         1   36597       37573     37817     37883   \n",
+      "\n",
+      "   pen_end  expert_req  \n",
+      "0    37921           0  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# the expert_req and pen_end fields are already filled\n",
+    "\n",
+    "# Define a function to copy every 4 inputs into a row of the DataFrame\n",
+    "def copy_inputs_to_dataframe(index_click_list, index_df):\n",
+    "    a = 0\n",
+    "    for i in range(0, len(index_click_list), 3):\n",
+    "        input_chunk = index_click_list[i:i+3]\n",
+    "        #print(input_chunk)\n",
+    "        #print(input_chunk[0])\n",
+    "        if len(input_chunk) == 3:\n",
+    "            index_df.at[a,\"release\"] = input_chunk[0]\n",
+    "            index_df.at[a,\"water_entry\"] = input_chunk[1]\n",
+    "            index_df.at[a,\"sebed_pen\"] = input_chunk[2]\n",
+    "        a = a+1\n",
+    "        \n",
+    "# Call the function to copy inputs into the DataFrame\n",
+    "copy_inputs_to_dataframe(index_click_list, index_df)\n",
+    "\n",
+    "index_df['file_num']= fileNum\n",
+    "index_df['dataset']= dataset\n",
+    "index_df['expert_req']= expert_req_list\n",
+    "index_df[\"drop_num\"] = range(1,num_drops+1)\n",
+    "index_df['peak_dec'] = relevant_pts[\"index\"]\n",
+    "print(index_df)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Export data to master excel sheet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data added successfully to training_validation_master.xlsx\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_2956\\3808652148.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
+      "  updated_data = existing_data.append(new_data, ignore_index=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Define the data to be added\n",
+    "\n",
+    "# Create a DataFrame with the new data\n",
+    "new_data = index_df\n",
+    "\n",
+    "# Load the existing Excel file (if it exists)\n",
+    "try:\n",
+    "    existing_data = pd.read_excel(outputPath)\n",
+    "    # Append the new data to the existing data\n",
+    "    updated_data = existing_data.append(new_data, ignore_index=True)\n",
+    "except FileNotFoundError:\n",
+    "    # If the file doesn't exist, create a new one with the new data\n",
+    "    updated_data = new_data\n",
+    "\n",
+    "# Save the updated data to the Excel file\n",
+    "updated_data.to_excel(outputPath, index=False)\n",
+    "\n",
+    "print(\"Data added successfully to training_validation_master.xlsx\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Variable Index"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* **accPick()**: this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "* **accNameg** : a string representing the name of the accelerometer used in the analysis\n",
+    "* **accg** : the accelerometer data used in the analysis (units of g)\n",
+    "\n",
+    "* **BD** = bluedrop serial number (works for 1, 2, 3; used to calibrate)\n",
+    "* **binFilepath** = path to location bin file is stored\n",
+    "* **dataset** = dataset data is from (eg. Arolik_2023)\n",
+    "* **fileNum** = bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "* **outputPath** =  path to excel sheet that will store the data\n",
+    "\n",
+    "* **data_array** = 2d array with 10 cols to hold raw BD data\n",
+    "* **fileName** = 'bLog'+fileNum+\".bin\"\n",
+    "* **newPath** = binFilepath / fileName\n",
+    "* **file** = open(newPath, 'rb')  # read file\n",
+    "* **element** = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "* **df** a Dataframe in pandas from the bd data with columns ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] \n",
+    "\n",
+    "* **time** = gives time in s\n",
+    "* **count** = time in ms, used for indexing time\n",
+    "\n",
+    "* **g2g** = calibrated values from 2g accelerometer in g\n",
+    "* **g18g** = calibrated values from 18g accelerometer in g\n",
+    "* **g50g** = calibrated values from 50g accelerometer in g\n",
+    "* **ppm** = ((df['ppm']-139040.1)/20705) * 6.89475729 #converts to atm\n",
+    "* **g200g** = calibrated values from 200g accelerometer in g\n",
+    "* **gX55g** = calibrated values from X55g accelerometer in g\n",
+    "* **gY55g** = calibrated values from Y55g accelerometer in g\n",
+    "* **g250g** = calibrated values from 250g accelerometer in g\n",
+    "\n",
+    "* **overviewplot** = Plot showing all accelerometers and pore pressure readings\n",
+    "\n",
+    "* **d** = array with pore pressure and acceleration data\n",
+    "* **data** = dataframe of pore pressure and acceleration data\n",
+    "\n",
+    "* **plot_interactive_sample()** plot of deceleration and pore pressure vs count\n",
+    "\n",
+    "* **peak_pick()** = interactive plot used to pick approximate locations of drops (ie max deceleration)\n",
+    "* **peak_approx_list** = list of the index and deceleration values of the selected approximate peaks\n",
+    "* **peak_approx** = plt.ginput function used to select approximate peaks(n=-1, show_clicks=True)\n",
+    "* **num_drops** = number of drops in the file, determined by the number of peaks selected in peak_pick()\n",
+    "* **approx_peak_index_list** = list of the index values selected in peak pick()\n",
+    "\n",
+    "* **plot_start_list** list of the index 1500 counts before the approximate peak for each drop in the file\n",
+    "* **plot_end_list** = list of the index 500 counts after the approximate peak for each drop in the file\n",
+    "* **index_list** = list of the drop index\n",
+    "* **plot_ranges** = array of plot starts and plot ends\n",
+    "* **plot_range_df** = dataframe of  plot starts and plot ends with index values defined in the index list\n",
+    "\n",
+    "\n",
+    "* **max_dec_list** = list of the maximum deceleration values (not approximated by peak clicking)\n",
+    "* **max_dec** = maximum deceleration value added to max_dec_list  \n",
+    "* **index_df** = a dataframe of only deceleration values\n",
+    "* **max_index_list** = list of the count index of the max_dec values\n",
+    "* **max_index** = count index of the max_dec values added to max_index_list\n",
+    "* **relevant_pts** = dataframe of peak accelerations and their associated count index \n",
+    "\n",
+    "* ***dec_ppm_plot()** = function for creation of plot of deceleration and pore pressure to be used in index picking\n",
+    "\n",
+    "* **index_df** = dataframe for index values to go into with columns 'file_num','dataset','drop_num', 'release', 'water_entry', 'sebed_pen', 'peak_dec', 'pen_end', \"expert_req\"\n",
+    "\n",
+    "* **pen_end_list** = list of index values where deceration crosses 1g\n",
+    "* **below_0_list** = list of all values after the peak deceleration with acceleration values less than 1g\n",
+    "* **pen_end** = first index after peak with acceleration value less than 1g\n",
+    "\n",
+    "* **expert_req_list** = list of whether or not an expert should look at each drop in the file (0 = no, 1 = yes)\n",
+    "* **expert_req** = a 0 or 1 representing whether an expert should look at a specific drop\n",
+    "* **keep_limit** = maxium number of counts between max deceleration and penetration end value that is allowed before saying an expert is required\n",
+    "\n",
+    "* **index_click** = ginput function for the release, water entry, and seabed impact points\n",
+    "* **index_click_list** = list of the count index for the release, water entry, and seabed impact points for each drop in the file\n",
+    "\n",
+    "* **copy_inputs_to_dataframe(index_click_list, index_df)** = function that copies count index for the release, water entry, and seabed impact points for each drop in the file into the index_df\n",
+    "* **input_chunk** = all values of release index, water entry index or impact indexes\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/ML_Dataset_Creation-Identification.ipynb b/ML_Dataset_Creation-Identification.ipynb
new file mode 100644
index 0000000..a7414d1
--- /dev/null
+++ b/ML_Dataset_Creation-Identification.ipynb
@@ -0,0 +1,1022 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Training & Validation Dataset Creation"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This code is utilized to create the training and validation data for a ML algorithm to identify portable free-fall penetrometer (PFFP) deployments. The user manually selects 3 distinct points:\n",
+    "\n",
+    "1. **Moment of release into air.** This is shown as the moment where the measured deceleration begins to decrease\n",
+    "2. **Moment of impact with water.** This is shown where the pore pressure readings begin to increase.\n",
+    "3. **Moment of seabed impact.** This is the moment preceding a sharp increase in measured deceleration\n",
+    "\n",
+    "The fourth point of interest, **End of penetration.**, is automatically found. This is generally identified as the moment where the deceleration crosses 1g following the peak deceleration. \n",
+    "\n",
+    "A visualization of these distinct regions within the PFFP deceleration profile is shown below (Stark et al 2016; https://cdnsciencepub.com/doi/10.1139/cgj-2016-0087):\n",
+    "![image.png](attachment:image.png)\n",
+    "\n",
+    "**Note:** *this code requires pop-ups of interactive images. Therefore, it will not run properly within the DesignSafe Jupyter Notebooks. It is recommended that this code be used in a local version of Juputer, such as that in Visual Studio Code.*\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "#%matplotlib ipympl\n",
+    "matplotlib.use('TkAgg') #the default is to have an image pop-out. Precede the image creation with the line above to embed within Jupyter\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pathlib import Path\n",
+    "\n",
+    "from scipy.signal import lfilter"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "User Inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# SETUP VARIABLES - USER INPUTS\n",
+    "dataset = \"Sequim_2021\"\n",
+    "BD = 3 #Bluedrop file is from \n",
+    "fileNum = '00A2' # write the bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "# paste the filepath to the folder where the BD data is stored\n",
+    "binFilepath = Path(\"H:/My Drive/CEE 5904 - Project & Report/NSWC Project/Clay Datasets/Bin/\")\n",
+    "#paste the filepath to an excel file that the analysis results will be printed in\n",
+    "outputPath = Path(\"C:/Users/elise/Desktop/ML Training Data/training_validation_master.xlsx\") #  Path to pre-existing Excel File"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Bring in and visualize data within the BlueDrop File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9798be2dfa1a4922b82d533f7a4ecd87",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=1400.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# READ BD DATA IN\n",
+    "data_array = []  # creates an empty array for us to fill with bd data\n",
+    "fileName = 'bLog'+fileNum+\".bin\"\n",
+    "# print(fileName)\n",
+    "newPath = binFilepath / fileName\n",
+    "#print(newPath)\n",
+    "file = open(newPath, 'rb')  # read file\n",
+    "element = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "while element:\n",
+    "    # Convert to signed integer before adding to data array\n",
+    "    iVAl = int.from_bytes(element, byteorder='big', signed=True)\n",
+    "    data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame\n",
+    "    element = file.read(3)\n",
+    "\n",
+    "np_array = np.array(data_array)  # create numpy array from the list\n",
+    "np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols\n",
+    "\n",
+    "#print(np_array.shape)\n",
+    "# print(np_array)\n",
+    "\n",
+    "#Create uncalibrated dataframe from raw penetrometer readings\n",
+    "df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data\n",
+    "df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns\n",
+    "# print(dfCal)\n",
+    "\n",
+    "time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s\n",
+    "count = df[\"Count\"]-df['Count'].iloc[0]\n",
+    "\n",
+    "#calibrate the dataframe\n",
+    "# APPLY CALIBRATION FACTORS\n",
+    "if BD == 3:  # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-33570.1)/1614577.9 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']+13495)/163387.2 #- offset\n",
+    "    g50g = (df['g50g']-238817.4)/63779.5 #- offset\n",
+    "    ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 #converts to atm\n",
+    "    g200g = (df['g200g'] -262332.4)/38888.7 #- offset\n",
+    "    gX55g = (df['gX55g']-70406)/59754.3\n",
+    "    gY55g = (df['gY55g']-69421.1)/141871.5\n",
+    "    g250g = (df['g250g']-39077.4)/13746.9 #- offset\n",
+    "\n",
+    "if BD == 2: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']+36597.6)/1637627.3 #- offset# accelerometers are in g\n",
+    "    g18g = (df['g18g']-26185.3)/160297.2 #- offset\n",
+    "    g50g = (df['g50g']-212256.9)/63968.7 #- offset\n",
+    "    ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa\n",
+    "    g200g = (df['g200g']-175499.4)/30583.8 #- offset\n",
+    "    gX55g = (df['gX55g']-53629.9)/68590.9\n",
+    "    gY55g = (df['gY55g']-43694.3)/68280.3\n",
+    "    g250g = (df['g250g']-39619.9)/13545.8 #- offset\n",
+    "\n",
+    "if BD == 1: # calibration factors from March 2023\n",
+    "    g2g = (df['g2g']-43727.6)/1625064 #- offset # accelerometers are in g\n",
+    "    g18g = (df['g18g']-45085.6)/160925.7 #- offset\n",
+    "    g50g = (df['g50g']-173493.4)/63944.6 #- offset\n",
+    "    ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa\n",
+    "    g200g = (df['g200g'] -731734.3)/32192.4  #- offset\n",
+    "    gX55g = (df['gX55g'] -68837.9)/52137.3\n",
+    "    gY55g = (df['gY55g']-68015.9)/28074.9\n",
+    "    g250g = (df['g250g']+10580)/13688.7 #- offset\n",
+    "\n",
+    "def overviewplot(): #Plot showing all accelerometers and pore pressure readings\n",
+    "    %matplotlib ipympl\n",
+    "    fig, (ax1, ax2, ax3) = plt.subplots(3)\n",
+    "    fig.set_size_inches(14, 7)\n",
+    "    #plt.tight_layout()\n",
+    "    ax1.plot(time, g250g, label=\"250g\")\n",
+    "    ax1.plot(time, g50g, label=\"50g\")\n",
+    "    ax1.plot(time, g18g, label=\"18g\")\n",
+    "    ax1.plot(time, g2g, label=\"2g\")\n",
+    "    ax1.legend(loc = \"upper right\")\n",
+    "    ax1.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax1.set_title(\"BD file \"+fileNum)\n",
+    "    ax1.grid()\n",
+    "\n",
+    "    ax2.plot(time, ppm, label=\"Pore Pressure\")\n",
+    "    ax2.set(ylabel=\"Pore Pressure (kPa)\")\n",
+    "    ax2.grid()\n",
+    "\n",
+    "    ax3.plot(time, gX55g, label=\"X 55g\")\n",
+    "    ax3.plot(time, gY55g, label=\"Y 55g\")\n",
+    "    ax3.legend(loc = \"upper right\")\n",
+    "    ax3.set(ylabel=\"Deceleration (g)\")\n",
+    "    ax3.set(xlabel=\"Time (s)\")\n",
+    "    ax3.grid()\n",
+    "\n",
+    "    fig.subplots_adjust(bottom=.1, left = .1)\n",
+    "    plotName = fileNum+\" Overview.png\"\n",
+    "    #plt.savefig(plotPath / plotName)\n",
+    "    plt.show()\n",
+    "\n",
+    "overviewplot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select which accelerometer should be used to pick the index points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max Acceleration:  25.21525580312652\n",
+      "Accelerometer used:  50g (g)\n"
+     ]
+    }
+   ],
+   "source": [
+    "def accPick(): #this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "    maxAcc = g250g.max()\n",
+    "    print(\"Max Acceleration: \", maxAcc)\n",
+    "    global accNameg\n",
+    "    global accg\n",
+    "    if maxAcc < 5:\n",
+    "        if g2g.max() < 1.8: #offset:  # does an extra check for the 2g because of noise\n",
+    "            accg = g2g\n",
+    "            accNameg = \"2g (g)\"\n",
+    "        else:\n",
+    "            accg = g18g\n",
+    "            accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 18:\n",
+    "        accg = g18g\n",
+    "        accNameg = \"18g (g)\"\n",
+    "    elif maxAcc < 50:\n",
+    "        accg = g50g\n",
+    "        accNameg = \"50g (g)\"\n",
+    "    else:\n",
+    "        accg = g250g\n",
+    "        accNameg = \"250g (g)\"\n",
+    "    print(\"Accelerometer used: \", accNameg)\n",
+    "\n",
+    "\n",
+    "accPick()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a dataframe that only includes data from the relevant accelerometer and the pore pressure sensor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataframe with Pore Pressure and Accelerometer readings\n",
+      "              ppm   Acc (g)\n",
+      "0      -11.019657  0.333439\n",
+      "1      -10.872138  0.334255\n",
+      "2      -10.487857  0.316851\n",
+      "3      -10.488190  0.314578\n",
+      "4      -10.518493  0.355296\n",
+      "...           ...       ...\n",
+      "119995 -21.440880  0.989512\n",
+      "119996 -21.891096  1.000644\n",
+      "119997 -22.146840  0.977471\n",
+      "119998 -21.857130  0.978615\n",
+      "119999 -21.716937  1.010679\n",
+      "\n",
+      "[120000 rows x 2 columns]\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2838fe4f65bf4a97af4af889ce34d3c1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#print(accg)\n",
+    "#print(count)\n",
+    "\n",
+    "d = {'ppm': ppm, 'Acc (g)': accg}\n",
+    "data = pd.DataFrame(data=d)\n",
+    "\n",
+    "#data = np.array([time], [accg])  # Example data\n",
+    "print(\"Dataframe with Pore Pressure and Accelerometer readings\")\n",
+    "print(data)\n",
+    "#data = pd.DataFrame(data)\n",
+    "#print(data)\n",
+    "\n",
+    "#Plot the relevant data\n",
+    "def plot_interactive_sample():\n",
+    "    %matplotlib ipympl\n",
+    "    plt.plot(data, label = (\"Pore Pressure (kPa)\", \"Deceleration (g)\"))\n",
+    "    plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "    plt.xlabel(\"Count\")\n",
+    "    plt.ylabel(\"Deceleration (g)\")\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "    #plt.show()\n",
+    "\n",
+    "plot_interactive_sample()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select the approximate peak deceleration for each drop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 drops in file\n",
+      "Coordinates of Approximate peaks (index, acceleration): [37644.84758064516, 25.224540800727503]\n",
+      "Approx Peak Indexes: [37644]\n"
+     ]
+    }
+   ],
+   "source": [
+    "matplotlib.use('TkAgg')\n",
+    "\n",
+    "def peak_pick():\n",
+    "    plt.plot(data)\n",
+    "    plt.title(\"Select Drops (Enter to Exit)\")\n",
+    "    plt.xlabel(\"Count\")\n",
+    "    plt.ylabel(\"Deceleration (g)\")\n",
+    "    #plt.legend(\"Deceleration (g)\", \"Pore Pressure (kPa)\")\n",
+    "    plt.grid(True)\n",
+    "    #plt.show()\n",
+    "    global approx_peak_index_list\n",
+    "    global num_drops\n",
+    "\n",
+    "    peak_approx_list = []\n",
+    "\n",
+    "    peak_approx = plt.ginput(n=-1, show_clicks=True)\n",
+    "    for t in peak_approx:\n",
+    "        for x in t:\n",
+    "            peak_approx_list.append(x)\n",
+    "    #user_input = input(\"Enter a value (press Enter to stop): \")\n",
+    "    plt.close()\n",
+    "    num_drops = int(len(peak_approx_list)/2)\n",
+    "    print(num_drops, \"drops in file\")\n",
+    "\n",
+    "    approx_peak_index_list = peak_approx_list[::2]\n",
+    "    for a in range(0,len(approx_peak_index_list)):\n",
+    "        approx_peak_index_list[a] = int(approx_peak_index_list[a])\n",
+    "    print(\"Coordinates of Approximate peaks (index, acceleration):\", peak_approx_list)\n",
+    "    print(\"Approx Peak Indexes:\", approx_peak_index_list) \n",
+    "\n",
+    "peak_pick()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select range for plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Start    End\n",
+      "1  34644  38144\n"
+     ]
+    }
+   ],
+   "source": [
+    "plot_start_list = []\n",
+    "plot_end_list = [] \n",
+    "index_list = []\n",
+    "for a in range(0, num_drops):\n",
+    "    peak = approx_peak_index_list[a]\n",
+    "    if peak <= 3000:\n",
+    "        plotstart = 1\n",
+    "        plotend = peak + 500\n",
+    "        \n",
+    "    elif peak > 119500:\n",
+    "        plotstart = peak - 3000\n",
+    "        plotend = 120000\n",
+    "    else:\n",
+    "        plotstart = peak - 3000\n",
+    "        plotend = peak + 500\n",
+    "    plot_start_list.append(plotstart)\n",
+    "    plot_end_list.append(plotend)\n",
+    "    index_list.append(a+1)\n",
+    "plot_ranges = {'Start':plot_start_list, \"End\":plot_end_list}\n",
+    "plot_range_df = pd.DataFrame(data=plot_ranges, index = index_list)\n",
+    "print(plot_range_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Refine peak picks to be maximum deceleration in the interval defined above"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[25.224540800727507]\n",
+      "37883\n",
+      "[37883]\n",
+      "         acc  index\n",
+      "0  25.224541  37883\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "279faa7b762d41929b18ab1fc7ce34b1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#finds the actual maximum deceleration (not just the approximated one)\n",
+    "#print(plot_range_df.at[1,'Start'])\n",
+    "max_dec_list = []\n",
+    "for a in range(1, num_drops+1):\n",
+    "    max_dec = max(accg[plot_range_df.at[a,'Start']:plot_range_df.at[a,'End']])\n",
+    "    max_dec_list.append(max_dec)\n",
+    "    #print(max_dec) #these should match the maximum values shown in cell []\n",
+    "print(max_dec_list)\n",
+    "\n",
+    "#makes a dataframe of only deceleration values\n",
+    "index_df = pd.DataFrame(data={'Accg':accg}, index = range(0,len(accg)))\n",
+    "#print(index_df)\n",
+    "\n",
+    "max_index_list = []\n",
+    "#finds the index of the maximum deceleration values\n",
+    "for a in range(1, num_drops+1):\n",
+    "    drop_range = index_df[plot_range_df.at[a,'Start']:plot_range_df.at[a,'End']]\n",
+    "    #print(drop_range)\n",
+    "    max_index = drop_range.idxmax().values\n",
+    "    max_index = int(max_index)\n",
+    "    max_index_list.append(max_index)\n",
+    "    print(max_index)\n",
+    "print(max_index_list)\n",
+    "\n",
+    "#visualize the above points for validation\n",
+    "relevant_pts = pd.DataFrame({\"acc\":max_dec_list, \"index\":max_index_list})\n",
+    "print(relevant_pts)\n",
+    "\n",
+    "%matplotlib ipympl\n",
+    "plt.plot(data, label = (\"Deceleration (g)\", \"Pore Pressure ([])\"))\n",
+    "plt.scatter(relevant_pts[relevant_pts.columns[1]], relevant_pts[relevant_pts.columns[0]], marker = \"x\", color = \"green\", label = \"Peaks\")\n",
+    "plt.title(\"Deceleration (g) and Pore Pressure\")\n",
+    "plt.xlabel(\"Count\")\n",
+    "plt.ylabel(\"Deceleration (g)\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Define the plot that overlays deceleration and ppm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib ipympl\n",
+    "\n",
+    "def dec_ppm_plot():\n",
+    "    #Plot deceleration\n",
+    "    #fig, (ax1) = plt.subplots(1)\n",
+    "    ax1.plot(accg, color = 'r', label = \"Deceleration (g)\")\n",
+    "    ax1.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    plt.title(\"Drop \"+ str(a+1))\n",
+    "    ax1.set_ylabel(\"Deceleration (g)\", color = 'r')\n",
+    "    ax1.set(xlabel=\"Time Index\")\n",
+    "    plt.legend(loc = \"upper left\")\n",
+    "    ax2 = ax1.twinx()\n",
+    "\n",
+    "    #filter the pore pressure readings to show a smoother line\n",
+    "    c=1\n",
+    "    n = 50  # the larger n is, the smoother curve will be\n",
+    "    b = [1.0 / n] * n\n",
+    "    ppm_filtered = lfilter(b, c, ppm)\n",
+    "\n",
+    "    #Plot pore pressure\n",
+    "    ax2.plot(ppm, color = 'b', alpha = .2)\n",
+    "    ax2.plot(ppm_filtered, color = 'b', label = \"Pore Pressure (kPa)\")\n",
+    "    ax2.set_xlim(left=plot_range_df.loc[a+1,'Start'], right=plot_range_df.loc[a+1,'End'])\n",
+    "    ax2.set_ylabel(\"Pore Pressure (kPa)\", color = 'b')\n",
+    "    plt.legend(loc = \"upper right\")\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Preview the plots for interval picking"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "30e35989a3a7452a9f6a23150d8350a9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for a in range(0, num_drops):\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    dec_ppm_plot()\n",
+    "    ax1.plot(gX55g, label = \"X-Tilt (g)\")\n",
+    "    ax1.plot(gY55g, label = \"Y-Tilt (g)\")\n",
+    "    ax1.legend(loc = \"upper left\")\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create Array for indexing info to go into"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  file_num dataset drop_num release water_entry sebed_pen peak_dec pen_end  \\\n",
+      "0      NaN     NaN      NaN     NaN         NaN       NaN      NaN     NaN   \n",
+      "\n",
+      "  expert_req  \n",
+      "0        NaN  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Create an empty DataFrame with 8 columns and n rows\n",
+    "#first 3 columns are filled in automatically using user inputs\n",
+    "#last column is a \"toss-out\" indicator, describing whether penetrometer likely fell over during penetration (1 = toss, 0 = keep)\n",
+    "#all other columns represent time index values\n",
+    "\n",
+    "index_df = pd.DataFrame(columns=['file_num','dataset','drop_num', 'release', 'water_entry', 'sebed_pen', 'peak_dec', 'pen_end', \"expert_req\"], index=range(num_drops))\n",
+    "\n",
+    "# Display the empty DataFrame\n",
+    "print(index_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Find Point of penetration end (where values crosses 1g)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[37921]\n"
+     ]
+    }
+   ],
+   "source": [
+    "pen_end_list = []\n",
+    "for a in range(0, num_drops):\n",
+    "    global pen_end\n",
+    "    below0list = list()\n",
+    "    #for i in range(dropstart+jindex, dropend, 1):\n",
+    "    for i in range(relevant_pts.loc[a,\"index\"], plot_range_df.loc[a+1,'End']):\n",
+    "        if accg[i] < 1: #the offset is applied later in the code\n",
+    "            penend = i \n",
+    "            below0list = np.append(below0list, penend)\n",
+    "    pen_end=int(min(below0list))\n",
+    "    pen_end_list.append(pen_end)\n",
+    "\n",
+    "print(pen_end_list)\n",
+    "\n",
+    "#add list to output dataframe\n",
+    "index_df['pen_end']= pen_end_list"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Decide if drop fell over during penetration"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "expert_req_list = []\n",
+    "\n",
+    "keep_limit = 100 #maybe this should change?\n",
+    "\n",
+    "for a in range(0, num_drops):\n",
+    "\n",
+    "    if relevant_pts.loc[a,\"index\"] - pen_end_list[a] < keep_limit:\n",
+    "        expert_req = 0\n",
+    "    else:\n",
+    "        expert_req = 1\n",
+    "\n",
+    "    expert_req_list.append(expert_req)\n",
+    "\n",
+    "print(expert_req_list)\n",
+    "\n",
+    "#add list to output dataframe\n",
+    "index_df['expert_req']= expert_req_list\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For each drop, pick index points for:\n",
+    "1. release\n",
+    "2. water entry, and \n",
+    "3. pentration start \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[36597.22580645161, 37573.83870967742, 37817.2726326743]\n",
+      "[36597, 37573, 37817]\n"
+     ]
+    }
+   ],
+   "source": [
+    "matplotlib.use('TkAgg')\n",
+    "index_click_list = []\n",
+    "\n",
+    "for a in range(0, num_drops):\n",
+    "    fig, (ax1) = plt.subplots(1)\n",
+    "    plt.title(\"Pick moments of release, water entry, and sebed penetration for drop \"+ str(a+1))\n",
+    "    dec_ppm_plot()\n",
+    "    #specifies user inputs\n",
+    "    index_click = plt.ginput(n=-1, show_clicks=True)\n",
+    "    for t in index_click:\n",
+    "        for x in t:\n",
+    "            index_click_list.append(x)\n",
+    "    #user_input = input(\"Enter a value (press Enter to stop): \")\n",
+    "    plt.close()\n",
+    "\n",
+    "#print(index_click_list)\n",
+    "\n",
+    "#remove the axis values to only record the indices\n",
+    "index_click_list = index_click_list[::2]\n",
+    "\n",
+    "print(index_click_list)\n",
+    "\n",
+    "#convert to list of integers\n",
+    "for x in range(0, len(index_click_list)):\n",
+    "    index_click_list[x] = int(index_click_list[x])\n",
+    "\n",
+    "print(index_click_list)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Fill dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  file_num    dataset  drop_num release water_entry sebed_pen  peak_dec  \\\n",
+      "0     02C2  Duck_2023         1   36597       37573     37817     37883   \n",
+      "\n",
+      "   pen_end  expert_req  \n",
+      "0    37921           0  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# the expert_req and pen_end fields are already filled\n",
+    "\n",
+    "# Define a function to copy every 4 inputs into a row of the DataFrame\n",
+    "def copy_inputs_to_dataframe(index_click_list, index_df):\n",
+    "    a = 0\n",
+    "    for i in range(0, len(index_click_list), 3):\n",
+    "        input_chunk = index_click_list[i:i+3]\n",
+    "        #print(input_chunk)\n",
+    "        #print(input_chunk[0])\n",
+    "        if len(input_chunk) == 3:\n",
+    "            index_df.at[a,\"release\"] = input_chunk[0]\n",
+    "            index_df.at[a,\"water_entry\"] = input_chunk[1]\n",
+    "            index_df.at[a,\"sebed_pen\"] = input_chunk[2]\n",
+    "        a = a+1\n",
+    "        \n",
+    "# Call the function to copy inputs into the DataFrame\n",
+    "copy_inputs_to_dataframe(index_click_list, index_df)\n",
+    "\n",
+    "index_df['file_num']= fileNum\n",
+    "index_df['dataset']= dataset\n",
+    "index_df['expert_req']= expert_req_list\n",
+    "index_df[\"drop_num\"] = range(1,num_drops+1)\n",
+    "index_df['peak_dec'] = relevant_pts[\"index\"]\n",
+    "print(index_df)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Export data to master excel sheet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data added successfully to training_validation_master.xlsx\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elise\\AppData\\Local\\Temp\\ipykernel_2956\\3808652148.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
+      "  updated_data = existing_data.append(new_data, ignore_index=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Define the data to be added\n",
+    "\n",
+    "# Create a DataFrame with the new data\n",
+    "new_data = index_df\n",
+    "\n",
+    "# Load the existing Excel file (if it exists)\n",
+    "try:\n",
+    "    existing_data = pd.read_excel(outputPath)\n",
+    "    # Append the new data to the existing data\n",
+    "    updated_data = existing_data.append(new_data, ignore_index=True)\n",
+    "except FileNotFoundError:\n",
+    "    # If the file doesn't exist, create a new one with the new data\n",
+    "    updated_data = new_data\n",
+    "\n",
+    "# Save the updated data to the Excel file\n",
+    "updated_data.to_excel(outputPath, index=False)\n",
+    "\n",
+    "print(\"Data added successfully to training_validation_master.xlsx\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Variable Index"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* **accPick()**: this function picks the smallest accelerometer that's not maxed out to perform the integration on\n",
+    "* **accNameg** : a string representing the name of the accelerometer used in the analysis\n",
+    "* **accg** : the accelerometer data used in the analysis (units of g)\n",
+    "\n",
+    "* **BD** = bluedrop serial number (works for 1, 2, 3; used to calibrate)\n",
+    "* **binFilepath** = path to location bin file is stored\n",
+    "* **dataset** = dataset data is from (eg. Arolik_2023)\n",
+    "* **fileNum** = bin file number you want to analyze (do not include 'bLog' or '.bin')\n",
+    "* **outputPath** =  path to excel sheet that will store the data\n",
+    "\n",
+    "* **data_array** = 2d array with 10 cols to hold raw BD data\n",
+    "* **fileName** = 'bLog'+fileNum+\".bin\"\n",
+    "* **newPath** = binFilepath / fileName\n",
+    "* **file** = open(newPath, 'rb')  # read file\n",
+    "* **element** = file.read(3)  # create a byte list with each element having 3 bytes\n",
+    "\n",
+    "* **df** a Dataframe in pandas from the bd data with columns ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] \n",
+    "\n",
+    "* **time** = gives time in s\n",
+    "* **count** = time in ms, used for indexing time\n",
+    "\n",
+    "* **g2g** = calibrated values from 2g accelerometer in g\n",
+    "* **g18g** = calibrated values from 18g accelerometer in g\n",
+    "* **g50g** = calibrated values from 50g accelerometer in g\n",
+    "* **ppm** = ((df['ppm']-139040.1)/20705) * 6.89475729 #converts to atm\n",
+    "* **g200g** = calibrated values from 200g accelerometer in g\n",
+    "* **gX55g** = calibrated values from X55g accelerometer in g\n",
+    "* **gY55g** = calibrated values from Y55g accelerometer in g\n",
+    "* **g250g** = calibrated values from 250g accelerometer in g\n",
+    "\n",
+    "* **overviewplot** = Plot showing all accelerometers and pore pressure readings\n",
+    "\n",
+    "* **d** = array with pore pressure and acceleration data\n",
+    "* **data** = dataframe of pore pressure and acceleration data\n",
+    "\n",
+    "* **plot_interactive_sample()** plot of deceleration and pore pressure vs count\n",
+    "\n",
+    "* **peak_pick()** = interactive plot used to pick approximate locations of drops (ie max deceleration)\n",
+    "* **peak_approx_list** = list of the index and deceleration values of the selected approximate peaks\n",
+    "* **peak_approx** = plt.ginput function used to select approximate peaks(n=-1, show_clicks=True)\n",
+    "* **num_drops** = number of drops in the file, determined by the number of peaks selected in peak_pick()\n",
+    "* **approx_peak_index_list** = list of the index values selected in peak pick()\n",
+    "\n",
+    "* **plot_start_list** list of the index 1500 counts before the approximate peak for each drop in the file\n",
+    "* **plot_end_list** = list of the index 500 counts after the approximate peak for each drop in the file\n",
+    "* **index_list** = list of the drop index\n",
+    "* **plot_ranges** = array of plot starts and plot ends\n",
+    "* **plot_range_df** = dataframe of  plot starts and plot ends with index values defined in the index list\n",
+    "\n",
+    "\n",
+    "* **max_dec_list** = list of the maximum deceleration values (not approximated by peak clicking)\n",
+    "* **max_dec** = maximum deceleration value added to max_dec_list  \n",
+    "* **index_df** = a dataframe of only deceleration values\n",
+    "* **max_index_list** = list of the count index of the max_dec values\n",
+    "* **max_index** = count index of the max_dec values added to max_index_list\n",
+    "* **relevant_pts** = dataframe of peak accelerations and their associated count index \n",
+    "\n",
+    "* ***dec_ppm_plot()** = function for creation of plot of deceleration and pore pressure to be used in index picking\n",
+    "\n",
+    "* **index_df** = dataframe for index values to go into with columns 'file_num','dataset','drop_num', 'release', 'water_entry', 'sebed_pen', 'peak_dec', 'pen_end', \"expert_req\"\n",
+    "\n",
+    "* **pen_end_list** = list of index values where deceration crosses 1g\n",
+    "* **below_0_list** = list of all values after the peak deceleration with acceleration values less than 1g\n",
+    "* **pen_end** = first index after peak with acceleration value less than 1g\n",
+    "\n",
+    "* **expert_req_list** = list of whether or not an expert should look at each drop in the file (0 = no, 1 = yes)\n",
+    "* **expert_req** = a 0 or 1 representing whether an expert should look at a specific drop\n",
+    "* **keep_limit** = maxium number of counts between max deceleration and penetration end value that is allowed before saying an expert is required\n",
+    "\n",
+    "* **index_click** = ginput function for the release, water entry, and seabed impact points\n",
+    "* **index_click_list** = list of the count index for the release, water entry, and seabed impact points for each drop in the file\n",
+    "\n",
+    "* **copy_inputs_to_dataframe(index_click_list, index_df)** = function that copies count index for the release, water entry, and seabed impact points for each drop in the file into the index_df\n",
+    "* **input_chunk** = all values of release index, water entry index or impact indexes\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/ResultsCombine.py b/ResultsCombine.py
new file mode 100644
index 0000000..7916b01
--- /dev/null
+++ b/ResultsCombine.py
@@ -0,0 +1,20 @@
+import numpy
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from pathlib import Path
+import math
+from math import pi
+from math import sqrt
+import statistics
+import scipy.integrate
+
+
+outputPath = Path("H:/.shortcut-targets-by-id/1aF9t2aiRGWTftJMZFAOBixqvQniFBjnb/Duck  2023/Data/Intertidal/BlueDrop, Samples & Moisture Gage/08March23/BlueDrop Processing 3.8.23 - July 2023.xlsx") #  Path to pre-existing Excel File
+
+df = pd.concat(pd.read_excel(outputPath, sheet_name=None), ignore_index=True)
+
+print(df)
+
+with pd.ExcelWriter(outputPath, mode="a") as writer:
+        df.to_excel(writer, sheet_name = 'All Data', index=False)
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