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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -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 | ||
|
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||
|
|
||
| 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") |
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