removed comments from code chunks since they were redundant with markdown text

Author: cognitionswitch

.gitignore

@@ -3,4 +3,6 @@ _site/
 .jekyll-metadata
 Gemfile.lock
 *.gem
-archive/
+archive/
+_ignore/
+.ipynb_checkpoints/

_ignore/.ipynb_checkpoints/2019-09-29-rate-representation-checkpoint.ipynb

@@ -295,11 +295,6 @@
    ],
    "source": [
     "#### window method: rectangular\n",
-    "# a window of 51 gives +- 25 bins to either side of center;\n",
-    "# since each bin equals samp_pd (2ms) this comes to a window size of 102 ms;\n",
-    "# after counting spikes over this window, we divide by 51*samp_pd \n",
-    "# to get the estimated spikes per ms; then we divide further\n",
-    "# by 1ms (1/1000) to get rate in Hertz\n",
     "plt.figure(figsize=(18,4))\n",
     "win_pd = int(samp_ms_pd*25+1)\n",
     "rect_win_pl = (\n",
@@ -359,14 +354,6 @@
    ],
    "source": [
     "#### window method: gaussian\n",
-    "# the rolling method with win_type = \"gaussian\" produces an\n",
-    "# unnormalized gaussian sum. The parameter representing std \n",
-    "# should be adjusted according to the resolution of the sampling\n",
-    "# rate. Since each addend equals 1, we can apply the \n",
-    "# normalization after summing (in this case using the unadjusted std).\n",
-    "# The sum after normalization represents the estimated firing \n",
-    "# rate at each 2ms bin. To get the rate in Hertz, we divide\n",
-    "# further by the duration of the bin (2ms)\n",
     "plt.figure(figsize=(18,4))\n",
     "sigma = 100\n",
     "adj_sigma = sigma/samp_ms_pd\n",

_ignore/.ipynb_checkpoints/jupyter_jekyll_workflow-checkpoint.txt

@@ -12,8 +12,9 @@ Generating the markdown and associated images
 2. Copy markdown output new_notebook.md to /_posts
 3. Copy image folder /new_notebook_files to /images/name_of_post_wo_date_prefix/ (will need to create name_of_post_wo_date_prefix)
 4. Modify markdown script to point to correct location of image files
--- new_notebook.md image pointers needs to be modified to refer to ../../../../images/name_of_post_wo_date_prefix/new_notebook_files/some_image.png
 -- example ![png](../../../../images/name_of_post_wo_date_prefix/new_notebook_files/some_image.png)
+5. Modify any local file paths that are show explicitly in code chunks to something generic
+-- example 'local\path\to\data'
 
 Use Jekyll to convert markdown to HTML
 1. bundle exec jekyll serve

_ignore/2019-09-29-rate-representation.ipynb

@@ -295,11 +295,6 @@
    ],
    "source": [
     "#### window method: rectangular\n",
-    "# a window of 51 gives +- 25 bins to either side of center;\n",
-    "# since each bin equals samp_pd (2ms) this comes to a window size of 102 ms;\n",
-    "# after counting spikes over this window, we divide by 51*samp_pd \n",
-    "# to get the estimated spikes per ms; then we divide further\n",
-    "# by 1ms (1/1000) to get rate in Hertz\n",
     "plt.figure(figsize=(18,4))\n",
     "win_pd = int(samp_ms_pd*25+1)\n",
     "rect_win_pl = (\n",
@@ -359,14 +354,6 @@
    ],
    "source": [
     "#### window method: gaussian\n",
-    "# the rolling method with win_type = \"gaussian\" produces an\n",
-    "# unnormalized gaussian sum. The parameter representing std \n",
-    "# should be adjusted according to the resolution of the sampling\n",
-    "# rate. Since each addend equals 1, we can apply the \n",
-    "# normalization after summing (in this case using the unadjusted std).\n",
-    "# The sum after normalization represents the estimated firing \n",
-    "# rate at each 2ms bin. To get the rate in Hertz, we divide\n",
-    "# further by the duration of the bin (2ms)\n",
     "plt.figure(figsize=(18,4))\n",
     "sigma = 100\n",
     "adj_sigma = sigma/samp_ms_pd\n",

_ignore/jupyter_jekyll_workflow.txt

@@ -12,8 +12,9 @@ Generating the markdown and associated images
 2. Copy markdown output new_notebook.md to /_posts
 3. Copy image folder /new_notebook_files to /images/name_of_post_wo_date_prefix/ (will need to create name_of_post_wo_date_prefix)
 4. Modify markdown script to point to correct location of image files
--- new_notebook.md image pointers needs to be modified to refer to ../../../../images/name_of_post_wo_date_prefix/new_notebook_files/some_image.png
 -- example ![png](../../../../images/name_of_post_wo_date_prefix/new_notebook_files/some_image.png)
+5. Modify any local file paths that are show explicitly in code chunks to something generic
+-- example 'local\path\to\data'
 
 Use Jekyll to convert markdown to HTML
 1. bundle exec jekyll serve

_posts/2019-09-29-rate-representation.markdown

@@ -165,11 +165,6 @@ A window of 51 gives 25 bins to either side of center. Since each bin equals 2 m
 
 ```python
 #### window method: rectangular
-# a window of 51 gives +- 25 bins to either side of center;
-# since each bin equals samp_pd (2ms) this comes to a window size of 102 ms;
-# after counting spikes over this window, we divide by 51*samp_pd 
-# to get the estimated spikes per ms; then we divide further
-# by 1ms (1/1000) to get rate in Hertz
 plt.figure(figsize=(18,4))
 win_pd = int(samp_ms_pd*25+1)
 rect_win_pl = (
@@ -208,14 +203,6 @@ The rolling method with `win_type = 'gaussian'` produces an unnormalized gaussia
 
 ```python
 #### window method: gaussian
-# the rolling method with win_type = "gaussian" produces an
-# unnormalized gaussian sum. The parameter representing std 
-# should be adjusted according to the resolution of the sampling
-# rate. Since each addend equals 1, we can apply the 
-# normalization after summing (in this case using the unadjusted std).
-# The sum after normalization represents the estimated firing 
-# rate at each 2ms bin. To get the rate in Hertz, we divide
-# further by the duration of the bin (2ms)
 plt.figure(figsize=(18,4))
 sigma = 100
 adj_sigma = sigma/samp_ms_pd