4-quick-landscapes.ipynb released on 210810

ded95650 · François LAURENT · de258ddb · ded95650 · ded95650 · ded95650
Commit ded95650 authored 3 years ago by François LAURENT
--- a/notebooks/3-roi.ipynb
+++ b/notebooks/3-roi.ipynb
@@ -52,38 +52,17 @@
   "metadata": {},
   "outputs": [
    {
-     "name": "stdout",
+     "ename": "KeyboardInterrupt",
-     "output_type": "stream",
+     "evalue": "",
-     "text": [
-      "few roi found: 6\n",
-      "few roi found: 5\n",
-      "few roi found: 5\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov018.txt\n",
-      "few roi found: 8\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov006.txt\n",
-      "few roi found: 4\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov020.txt\n",
-      "few roi found: 6\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov003.txt\n",
-      "few roi found: 4\n",
-      "few roi found: 5\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov015.txt\n",
-      "few roi found: 7\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov012.txt\n",
-      "no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov016.txt\n",
-      "global max density is below the threshold: 0.04466814859471522 < 0.05\n"
-     ]
-    },
-    {
-     "ename": "RuntimeError",
-     "evalue": "no roi found",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-3-6e2a6552cfe5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataframe\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m     \u001b[0mroi_centers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdensity_based_roi\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m.05\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# candidate ROI\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRWAnalyzer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-3-9a96db07a9a3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataframe\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m     \u001b[0mroi_centers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdensity_based_roi\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m.04\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# candidate ROI\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRWAnalyzer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/github/TRamWAy/tramway/analyzer/roi/utils.py\u001b[0m in \u001b[0;36mdensity_based_roi\u001b[0;34m(locations, min_kernel_density, target_pattern_size, step_size_factor, dr, kernel_density)\u001b[0m\n\u001b[1;32m     66\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'few roi found: {}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroi_centers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'no roi found'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mroi_centers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/github/TRamWAy/tramway/analyzer/roi/utils.py\u001b[0m in \u001b[0;36mdensity_based_roi\u001b[0;34m(locations, min_kernel_density, target_pattern_size, step_size_factor, dr, kernel_density)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0mgrid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0m_x\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0m_y\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mlog_density\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mepanechnikov_density\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_pattern_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m     \u001b[0mlog_density\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlog_density\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrid_x\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrid_y\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mRuntimeError\u001b[0m: no roi found"
+      "\u001b[0;32m~/github/TRamWAy/tramway/analyzer/roi/utils.py\u001b[0m in \u001b[0;36mepanechnikov_density\u001b[0;34m(xy, eval_at, target_pattern_size)\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0mestimator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxy\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m     \u001b[0mlog_density\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mestimator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscore_samples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meval_at\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mlog_density\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/sklearn/neighbors/_kde.py\u001b[0m in \u001b[0;36mscore_samples\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    199\u001b[0m             \u001b[0mN\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtree_\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum_weight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    200\u001b[0m         \u001b[0matol_N\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0matol\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 201\u001b[0;31m         log_density = self.tree_.kernel_density(\n\u001b[0m\u001b[1;32m    202\u001b[0m             \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbandwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0matol_N\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    203\u001b[0m             rtol=self.rtol, breadth_first=self.breadth_first, return_log=True)\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],

 %% Cell type:code id:d4080a30 tags:
 ``` python
 from tramway.analyzer import *
 a = RWAnalyzer()
 a.spt_data = spt_data.from_ascii_files(r'../data/interim/210503_Glyb-Eos/210503_Glyb-Eosmov[0-9][0-9][0-9].txt')
 a.spt_data.localization_precision = sigma = .0106
 a.spt_data.frame_interval = dt = .015
 ```
 %% Cell type:markdown id:2ff19c3a tags:
 # Define ROI
 %% Cell type:code id:e7857aa3 tags:
 ``` python
 import numpy as np
 import pandas as pd
 def roi_as_dataframe(bounding_boxes, columns=None):
    bb = np.stack([ np.r_[lb, ub] for lb, ub in bounding_boxes ], axis=0)
    if columns is None:
        if bb.shape[1] == 4:
            columns = ['x', 'y']
        elif bb.shape[1] == 6:
            columns = ['x', 'y', 't']
        else:
            raise ValueError('undefined column names')
    return pd.DataFrame(bb, columns=[ ' '.join((coord, bound)) for coord in columns for bound in ('min', 'max') ])
 ```
 %% Cell type:code id:32804b7d tags:
 ``` python
 from tramway.analyzer.roi.utils import *
 side = 1.
 min_transloc = 200
 for f in a.spt_data:
    df = f.dataframe
    roi_centers = density_based_roi(df, .04) # candidate ROI
    b = RWAnalyzer()
    b.spt_data = spt_data.from_dataframe(df[['n', 'x', 'y', 't']])
    b.spt_data.localization_error = a.spt_data.localization_error
    b.roi = roi.from_squares(roi_centers, side)
    selected_roi = []
    for r in b.roi:
        r_df = r.crop()
        r_df = r.discard_static_trajectories(r_df)
        if min_transloc <= len(r_df):
            selected_roi.append(r.bounding_box)
    if selected_roi:
        c = RWAnalyzer()
        c.spt_data = spt_data.from_ascii_file(f.source)
        c.roi = roi.from_bounding_boxes(roi_as_dataframe(selected_roi))
        c.roi.to_ascii_file(f.source[:-4]+'-roi.txt')
    else:
        print(f'no roi for file {f.source}')
 ```
 %% Output
-    few roi found: 6
-    few roi found: 5
-    few roi found: 5
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov018.txt
-    few roi found: 8
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov006.txt
-    few roi found: 4
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov020.txt
-    few roi found: 6
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov003.txt
-    few roi found: 4
-    few roi found: 5
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov015.txt
-    few roi found: 7
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov012.txt
-    no roi for file ../data/raw/210503_Glyb-Eos/210503_Glyb-Eosmov016.txt
-    global max density is below the threshold: 0.04466814859471522 < 0.05
    ---------------------------------------------------------------------------
-    RuntimeError                              Traceback (most recent call last)
+    KeyboardInterrupt                         Traceback (most recent call last)
-    <ipython-input-3-6e2a6552cfe5> in <module>
+    <ipython-input-3-9a96db07a9a3> in <module>
          7     df = f.dataframe
          8
-    ----> 9     roi_centers = density_based_roi(df, .05) # candidate ROI
+    ----> 9     roi_centers = density_based_roi(df, .04) # candidate ROI
         10
         11     b = RWAnalyzer()
    ~/github/TRamWAy/tramway/analyzer/roi/utils.py in density_based_roi(locations, min_kernel_density, target_pattern_size, step_size_factor, dr, kernel_density)
-         66             print('few roi found: {}'.format(len(roi_centers)))
+         39     grid = np.c_[_x.reshape((-1,1)),_y.reshape((-1,1))]
-         67     else:
+         40
-    ---> 68         raise RuntimeError('no roi found')
+    ---> 41     log_density = epanechnikov_density(xy, grid, target_pattern_size)
-         69
+         42     log_density = log_density.reshape(len(grid_x),len(grid_y))
-         70     return roi_centers
+         43
-    RuntimeError: no roi found
+    ~/github/TRamWAy/tramway/analyzer/roi/utils.py in epanechnikov_density(xy, eval_at, target_pattern_size)
+         16
+         17     estimator.fit(xy)
+    ---> 18     log_density = estimator.score_samples(eval_at)
+         19
+         20     return log_density
+    ~/.local/lib/python3.8/site-packages/sklearn/neighbors/_kde.py in score_samples(self, X)
+        199             N = self.tree_.sum_weight
+        200         atol_N = self.atol * N
+    --> 201         log_density = self.tree_.kernel_density(
+        202             X, h=self.bandwidth, kernel=self.kernel, atol=atol_N,
+        203             rtol=self.rtol, breadth_first=self.breadth_first, return_log=True)
+    KeyboardInterrupt:
 %% Cell type:markdown id:37585b0e tags:
 # Reload and inspect a few ROI
 %% Cell type:code id:7064300b tags:
 ``` python
 a.roi = roi.from_ascii_files()
 a.time = time.TimeWindow(duration=window_duration, shift=window_shift)
 a.tesseller = tessellers.KMeans
 a.tesseller.resolution = .1
 ```
 %% Cell type:code id:f1248422 tags:
 ``` python
 for r in a.roi:
    df = r.crop()
    df = r.discard_static_trajectories(df)
    assignment = a.sampler.sample(df)
    a
    a.tesseller.mpl.animate(assignment)
 ```
 %% Cell type:code id:3e8a5658 tags:
 ``` python
 help(a.tesseller.mpl.animate)
 ```
 %% Cell type:code id:b4d78654 tags:
 ``` python
 ```

--- a/notebooks/4-quick-landscapes.ipynb
+++ b/notebooks/4-quick-landscapes.ipynb
--- a/notebooks/former-analyses-reworked.ipynb
+++ b/notebooks/former-analyses-reworked.ipynb