Mikkel
/
septum-mec
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

updates

This commit is contained in:
Mikkel Elle Lepperød 2021-03-10 13:58:30 +01:00
parent 1652ab405e
commit 719518c73d
6 changed files with 2636 additions and 1349 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

60
actions/calculate-statistics/data/10_calculate_spatial_statistics.html
View File

@ -13153,6 +13153,7 @@ div#notebook {
<span class="kn">import</span> <span class="nn">septum_mec</span>
<span class="kn">import</span> <span class="nn">scipy.ndimage.measurements</span>
<span class="kn">from</span> <span class="nn">distutils.dir_util</span> <span class="k">import</span> <span class="n">copy_tree</span>
<span class="kn">from</span> <span class="nn">spike_statistics.core</span> <span class="k">import</span> <span class="n">theta_mod_idx</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm_notebook</span> <span class="k">as</span> <span class="n">tqdm</span>
<span class="kn">from</span> <span class="nn">tqdm._tqdm_notebook</span> <span class="k">import</span> <span class="n">tqdm_notebook</span>
@ -13173,7 +13174,9 @@ div#notebook {
<div class="output_subarea output_stream output_stderr output_text">
<pre>17:02:17 [I] klustakwik KlustaKwik2 version 0.2.6
<pre>20:57:48 [I] klustakwik KlustaKwik2 version 0.2.6
/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0
Please use `tqdm.notebook.*` instead of `tqdm._tqdm_notebook.*`
</pre>
</div>
</div>
@ -13361,7 +13364,7 @@ div#notebook {
<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f9a2e1f4dd8&gt;</pre>
<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f0d22cd6f28&gt;</pre>
</div>
</div>
@ -13374,7 +13377,7 @@ div#notebook {
<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
<img src="data:image/png;base64,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
"
>
</div>
@ -13418,7 +13421,7 @@ div#notebook {
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="prompt input_prompt">In&nbsp;[16]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process</span><span class="p">(</span><span class="n">row</span><span class="p">):</span>
@ -13461,7 +13464,9 @@ div#notebook {
<span class="s1">&#39;head_mean_ang&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="s1">&#39;head_mean_vec_len&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="s1">&#39;spacing&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="s1">&#39;orientation&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
<span class="s1">&#39;orientation&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="s1">&#39;field_area&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="s1">&#39;theta_score&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
<span class="p">})</span>
<span class="k">return</span> <span class="n">result</span>
@ -13558,7 +13563,9 @@ div#notebook {
<span class="s1">&#39;head_mean_ang&#39;</span><span class="p">:</span> <span class="n">head_mean_ang</span><span class="p">,</span>
<span class="s1">&#39;head_mean_vec_len&#39;</span><span class="p">:</span> <span class="n">head_mean_vec_len</span><span class="p">,</span>
<span class="s1">&#39;spacing&#39;</span><span class="p">:</span> <span class="n">spacing</span><span class="p">,</span>
<span class="s1">&#39;orientation&#39;</span><span class="p">:</span> <span class="n">orientation</span>
<span class="s1">&#39;orientation&#39;</span><span class="p">:</span> <span class="n">orientation</span><span class="p">,</span>
<span class="s1">&#39;field_area&#39;</span><span class="p">:</span> <span class="n">fields_areas</span><span class="p">[</span><span class="n">fields</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="n">bin_size</span><span class="o">**</span><span class="mi">2</span><span class="p">,</span>
<span class="s1">&#39;theta_score&#39;</span><span class="p">:</span> <span class="n">theta_mod_idx</span><span class="p">(</span><span class="n">spike_times</span><span class="o">.</span><span class="n">times</span><span class="o">.</span><span class="n">magnitude</span><span class="p">,</span> <span class="n">binsize</span><span class="o">=</span><span class="mf">0.01</span><span class="p">,</span> <span class="n">time_limit</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>
<span class="p">})</span>
<span class="k">return</span> <span class="n">result</span>
@ -13579,15 +13586,14 @@ div#notebook {
<div class="output_subarea output_stream output_stderr output_text">
<pre>/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/elephant/statistics.py:835: UserWarning: Instantaneous firing rate approximation contains negative values, possibly caused due to machine precision errors.
warnings.warn(&#34;Instantaneous firing rate approximation contains &#34;
<pre>/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:85: RuntimeWarning: Mean of empty slice.
</pre>
</div>
</div>
<div class="output_area">
<div class="prompt output_prompt">Out[&nbsp;]:</div>
<div class="prompt output_prompt">Out[16]:</div>
@ -13597,21 +13603,23 @@ div#notebook {
speed_score -0.068927
out_field_mean_rate 1.857990
in_field_mean_rate 5.257561
max_field_mean_rate 8.882211
max_field_mean_rate NaN
max_rate 23.006163
sparsity 0.466751
selectivity 7.153172
interspike_interval_cv 3.807699
burst_event_ratio 0.398230
bursty_spike_ratio 0.678064
gridness -0.466923
gridness -0.466836
border_score 0.029328
information_rate 1.009215
information_specificity 0.317256
head_mean_ang 5.438033
head_mean_vec_len 0.040874
spacing 0.628784
orientation 20.224859
orientation 69.775141
field_area 0.412306
theta_score -0.430279
dtype: float64</pre>
</div>
@ -13649,13 +13657,13 @@ dtype: float64</pre>
<div id="a40b72ae-f0e6-42c9-aab9-adcae33d48c4"></div>
<div id="a380456f-efec-4526-834c-4b130ce090aa"></div>
<div class="output_subarea output_widget_view ">
<script type="text/javascript">
var element = $('#a40b72ae-f0e6-42c9-aab9-adcae33d48c4');
var element = $('#a380456f-efec-4526-834c-4b130ce090aa');
</script>
<script type="application/vnd.jupyter.widget-view+json">
{"model_id": "2372ae1b2bea435dbc5bbfe2453747a6", "version_major": 2, "version_minor": 0}
{"model_id": "b2117ea9b6044c22abd353d0f9d774a7", "version_major": 2, "version_minor": 0}
</script>
</div>
@ -13667,13 +13675,16 @@ var element = $('#a40b72ae-f0e6-42c9-aab9-adcae33d48c4');
<div class="output_subarea output_stream output_stderr output_text">
<pre>/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in log2
return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *
/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:110: RuntimeWarning: invalid value encountered in long_scalars
<pre>/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:85: RuntimeWarning: Mean of empty slice.
/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: divide by zero encountered in log2
return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *
/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in log2
return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *
/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in multiply
return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *
/home/mikkel/apps/expipe-project/spike-statistics/spike_statistics/core.py:27: RuntimeWarning: invalid value encountered in double_scalars
return (pk - th)/(pk + th)
/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:112: RuntimeWarning: invalid value encountered in long_scalars
</pre>
</div>
</div>
@ -13681,19 +13692,6 @@ var element = $('#a40b72ae-f0e6-42c9-aab9-adcae33d48c4');
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span><span class="k">debug</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">

64
actions/calculate-statistics/data/10_calculate_spatial_statistics.ipynb
View File

@ -19,7 +19,9 @@
"name": "stderr",
"output_type": "stream",
"text": [
"17:02:17 [I] klustakwik KlustaKwik2 version 0.2.6\n"
"20:57:48 [I] klustakwik KlustaKwik2 version 0.2.6\n",
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
"Please use `tqdm.notebook.*` instead of `tqdm._tqdm_notebook.*`\n"
]
}
],
@ -45,6 +47,7 @@
"import septum_mec\n",
"import scipy.ndimage.measurements\n",
"from distutils.dir_util import copy_tree\n",
"from spike_statistics.core import theta_mod_idx\n",
"\n",
"from tqdm import tqdm_notebook as tqdm\n",
"from tqdm._tqdm_notebook import tqdm_notebook\n",
@ -208,7 +211,7 @@
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f9a2e1f4dd8>"
"<matplotlib.axes._subplots.AxesSubplot at 0x7f0d22cd6f28>"
]
},
"execution_count": 6,
@ -217,7 +220,7 @@
},
{
"data": {
"image/png": "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\n",
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
@ -258,17 +261,14 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/elephant/statistics.py:835: UserWarning: Instantaneous firing rate approximation contains negative values, possibly caused due to machine precision errors.\n",
" warnings.warn(\"Instantaneous firing rate approximation contains \"\n"
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:85: RuntimeWarning: Mean of empty slice.\n"
]
},
{
@ -278,25 +278,27 @@
"speed_score -0.068927\n",
"out_field_mean_rate 1.857990\n",
"in_field_mean_rate 5.257561\n",
"max_field_mean_rate 8.882211\n",
"max_field_mean_rate NaN\n",
"max_rate 23.006163\n",
"sparsity 0.466751\n",
"selectivity 7.153172\n",
"interspike_interval_cv 3.807699\n",
"burst_event_ratio 0.398230\n",
"bursty_spike_ratio 0.678064\n",
"gridness -0.466923\n",
"gridness -0.466836\n",
"border_score 0.029328\n",
"information_rate 1.009215\n",
"information_specificity 0.317256\n",
"head_mean_ang 5.438033\n",
"head_mean_vec_len 0.040874\n",
"spacing 0.628784\n",
"orientation 20.224859\n",
"orientation 69.775141\n",
"field_area 0.412306\n",
"theta_score -0.430279\n",
"dtype: float64"
]
},
"execution_count": 9,
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
@ -342,7 +344,9 @@
" 'head_mean_ang': np.nan,\n",
" 'head_mean_vec_len': np.nan,\n",
" 'spacing': np.nan,\n",
" 'orientation': np.nan\n",
" 'orientation': np.nan,\n",
" 'field_area': np.nan,\n",
" 'theta_score': np.nan\n",
" })\n",
" return result\n",
"\n",
@ -439,7 +443,9 @@
" 'head_mean_ang': head_mean_ang,\n",
" 'head_mean_vec_len': head_mean_vec_len,\n",
" 'spacing': spacing,\n",
" 'orientation': orientation\n",
" 'orientation': orientation,\n",
" 'field_area': fields_areas[fields].mean() * bin_size**2,\n",
" 'theta_score': theta_mod_idx(spike_times.times.magnitude, binsize=0.01, time_limit=0.2)\n",
" })\n",
" return result\n",
" \n",
@ -449,14 +455,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2372ae1b2bea435dbc5bbfe2453747a6",
"model_id": "b2117ea9b6044c22abd353d0f9d774a7",
"version_major": 2,
"version_minor": 0
},
@ -471,13 +475,16 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in log2\n",
" return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *\n",
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:110: RuntimeWarning: invalid value encountered in long_scalars\n",
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:85: RuntimeWarning: Mean of empty slice.\n",
"/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: divide by zero encountered in log2\n",
" return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *\n",
"/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in log2\n",
" return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *\n",
"/home/mikkel/apps/expipe-project/spatial-maps/spatial_maps/stats.py:13: RuntimeWarning: invalid value encountered in multiply\n",
" return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *\n"
" return (np.nansum(np.ravel(tmp_rate_map * np.log2(tmp_rate_map/avg_rate) *\n",
"/home/mikkel/apps/expipe-project/spike-statistics/spike_statistics/core.py:27: RuntimeWarning: invalid value encountered in double_scalars\n",
" return (pk - th)/(pk + th)\n",
"/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:112: RuntimeWarning: invalid value encountered in long_scalars\n"
]
}
],
@ -487,15 +494,6 @@
" left_index=True, right_index=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%debug"
]
},
{
"cell_type": "code",
"execution_count": null,
@ -598,5 +596,5 @@
}
},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 4
}

2570
actions/calculate-statistics/data/results.csv
View File

File diff suppressed because it is too large Load Diff

4
actions/stimulus-spike-lfp-response-direct/attributes.yaml Normal file
View File

@ -0,0 +1,4 @@
registered: '2021-01-23T10:44:56'
data:
results: results.csv
notebook: 10-calculate-stimulus-spike-lfp-response-direct.ipynb

1285
actions/stimulus-spike-lfp-response-direct/data/results.csv Normal file
View File

File diff suppressed because it is too large Load Diff

2
actions/stimulus-spike-lfp-response-direct/modules/parameters.yaml Normal file
View File

@ -0,0 +1,2 @@
theta_band_f1: 6
theta_band_f2: 10