Merge pull request #420 from int-brain-lab/json_encoder

make sure channel dict is compatible with json encoder datatypes

Author: mayofaulkner

ibllib/pipes/histology.py

@@ -347,11 +347,11 @@ def create_channel_dict(traj, brain_locations):
     channel_dict = []
     for i in np.arange(brain_locations.id.size):
         channel_dict.append({
-            'x': brain_locations.xyz[i, 0] * 1e6,
-            'y': brain_locations.xyz[i, 1] * 1e6,
-            'z': brain_locations.xyz[i, 2] * 1e6,
-            'axial': brain_locations.axial[i],
-            'lateral': brain_locations.lateral[i],
+            'x': np.float64(brain_locations.xyz[i, 0] * 1e6),
+            'y': np.float64(brain_locations.xyz[i, 1] * 1e6),
+            'z': np.float64(brain_locations.xyz[i, 2] * 1e6),
+            'axial': np.float64(brain_locations.axial[i]),
+            'lateral': np.float64(brain_locations.lateral[i]),
             'brain_region': int(brain_locations.id[i]),
             'trajectory_estimate': traj['id']
         })

ibllib/plots/figures.py

@@ -104,7 +104,7 @@ def raw_destripe(raw, fs, t0, i_plt, n_plt,
     if fig is None or axs is None:
         fig, axs = plt.subplots(nrows=1, ncols=n_plt, figsize=(14, 5), gridspec_kw={'width_ratios': 4 * n_plt})
 
-    if i_plt > len(axs)-1:  # Error
+    if i_plt > len(axs) - 1:  # Error
         raise ValueError(f'The given increment of subplot ({i_plt+1}) '
                          f'is larger than the total number of subplots ({len(axs)})')
 
@@ -113,10 +113,10 @@ def raw_destripe(raw, fs, t0, i_plt, n_plt,
         destripe = voltage.destripe(raw, fs=fs)
         X = destripe[:, :int(DISPLAY_TIME * fs)].T
         Xs = X[SAMPLE_SKIP:].T  # Remove artifact at beginning
-        Tplot = Xs.shape[1]/fs
+        Tplot = Xs.shape[1] / fs
 
         # PLOT RAW DATA
-        d = Density(-Xs, fs=fs, taxis=1, ax=axs[i_plt],  vmin=MIN_X, vmax=MAX_X, cmap='Greys')
+        d = Density(-Xs, fs=fs, taxis=1, ax=axs[i_plt], vmin=MIN_X, vmax=MAX_X, cmap='Greys') # noqa
         axs[i_plt].set_ylabel('')
         axs[i_plt].set_xlim((0, Tplot * 1e3))
         axs[i_plt].set_ylim((0, nc))