Merge branch 'release/2.26'

MANIFEST.in

@@ -1,9 +1,3 @@
-include ibllib/atlas/allen_structure_tree.csv
-include ibllib/atlas/franklin_paxinos_structure_tree.csv
-include ibllib/atlas/beryl.npy
-include ibllib/atlas/cosmos.npy
-include ibllib/atlas/swanson.npy
-include ibllib/atlas/mappings.pqt
 include ibllib/io/extractors/extractor_types.json
 include ibllib/io/extractors/task_extractor_map.json
 include brainbox/tests/wheel_test.p

brainbox/atlas.py

@@ -7,7 +7,7 @@
 import numpy as np
 import seaborn as sns
 import matplotlib.pyplot as plt
-from ibllib import atlas
+from iblatlas import atlas
 
 
 def _label2values(imlabel, fill_values, ba):

brainbox/ephys_plots.py

@@ -5,7 +5,7 @@
                                 plot_image, plot_probe, plot_scatter, arrange_channels2banks)
 from brainbox.processing import compute_cluster_average
 from iblutil.numerical import bincount2D
-from ibllib.atlas.regions import BrainRegions
+from iblatlas.regions import BrainRegions
 
 
 def image_lfp_spectrum_plot(lfp_power, lfp_freq, chn_coords=None, chn_inds=None, freq_range=(0, 300),

brainbox/examples/best_available_channels_from_insertion_id.py

@@ -1,6 +1,6 @@
 from one.api import ONE
 
-from ibllib.atlas import atlas
+from iblatlas import atlas
 from brainbox.io.one import load_channels_from_insertion
 
 pid = "8413c5c6-b42b-4ec6-b751-881a54413628"

brainbox/examples/docs_load_spike_sorting.py

@@ -14,7 +14,7 @@
 """
 
 from one.api import ONE
-from ibllib.atlas import AllenAtlas
+from iblatlas.atlas import AllenAtlas
 from brainbox.io.one import SpikeSortingLoader
 
 

brainbox/examples/plot_atlas_color_values.py

@@ -1,6 +1,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from ibllib import atlas
+from iblatlas import atlas
 from brainbox.atlas import plot_atlas
 
 

brainbox/io/one.py

@@ -21,7 +21,8 @@
 
 from iblutil.util import Bunch
 from ibllib.io.extractors.training_wheel import extract_wheel_moves, extract_first_movement_times
-from ibllib.atlas import atlas, AllenAtlas, BrainRegions
+from iblatlas.atlas import AllenAtlas, BrainRegions
+from iblatlas import atlas
 from ibllib.pipes import histology
 from ibllib.pipes.ephys_alignment import EphysAlignment
 from ibllib.plots import vertical_lines
@@ -243,7 +244,7 @@ def channel_locations_interpolation(channels_aligned, channels=None, brain_regio
       'x', 'y', 'z', 'acronym', 'axial_um'
       those are the guide for the interpolation
     :param channels: Bunch or dictionary of aligned channels containing at least keys 'localCoordinates'
-    :param brain_regions: None (default) or ibllib.atlas.BrainRegions object
+    :param brain_regions: None (default) or iblatlas.regions.BrainRegions object
      if None will return a dict with keys 'localCoordinates', 'mlapdv', 'brainLocationIds_ccf_2017
      if a brain region object is provided, outputts a dict with keys
       'x', 'y', 'z', 'acronym', 'atlas_id', 'axial_um', 'lateral_um'
@@ -372,7 +373,7 @@ def load_channel_locations(eid, probe=None, one=None, aligned=False, brain_atlas
         An instance of ONE (shouldn't be in 'local' mode)
     aligned : bool
         Whether to get the latest user aligned channel when not resolved or use histology track
-    brain_atlas : ibllib.atlas.BrainAtlas
+    brain_atlas : iblatlas.BrainAtlas
         Brain atlas object (default: Allen atlas)
     Returns
     -------
@@ -417,7 +418,7 @@ def load_spike_sorting_fast(eid, one=None, probe=None, dataset_types=None, spike
     :param dataset_types: additional spikes/clusters objects to add to the standard default list
     :param spike_sorter: name of the spike sorting you want to load (None for default)
     :param collection: name of the spike sorting collection to load - exclusive with spike sorter name ex: "alf/probe00"
-    :param brain_regions: ibllib.atlas.regions.BrainRegions object - will label acronyms if provided
+    :param brain_regions: iblatlas.regions.BrainRegions object - will label acronyms if provided
     :param nested: if a single probe is required, do not output a dictionary with the probe name as key
     :param return_collection: (False) if True, will return the collection used to load
     :return: spikes, clusters, channels (dict of bunch, 1 bunch per probe)
@@ -458,7 +459,7 @@ def load_spike_sorting(eid, one=None, probe=None, dataset_types=None, spike_sort
     :param probe: name of probe to load in, if not given all probes for session will be loaded
     :param dataset_types: additional spikes/clusters objects to add to the standard default list
     :param spike_sorter: name of the spike sorting you want to load (None for default)
-    :param brain_regions: ibllib.atlas.regions.BrainRegions object - will label acronyms if provided
+    :param brain_regions: iblatlas.regions.BrainRegions object - will label acronyms if provided
     :param return_collection:(bool - False) if True, returns the collection for loading the data
     :return: spikes, clusters (dict of bunch, 1 bunch per probe)
     """
@@ -497,7 +498,7 @@ def load_spike_sorting_with_channel(eid, one=None, probe=None, aligned=False, da
     spike_sorter : str
         Name of the spike sorting you want to load (None for default which is pykilosort if it's
         available otherwise the default MATLAB kilosort)
-    brain_atlas : ibllib.atlas.BrainAtlas
+    brain_atlas : iblatlas.atlas.BrainAtlas
         Brain atlas object (default: Allen atlas)
     return_collection: bool
         Returns an extra argument with the collection chosen
@@ -1053,10 +1054,16 @@ def samples2times(self, values, direction='forward'):
     def pid2ref(self):
         return f"{self.one.eid2ref(self.eid, as_dict=False)}_{self.pname}"
 
-    def raster(self, spikes, channels, save_dir=None, br=None, label='raster', time_series=None):
+    def raster(self, spikes, channels, save_dir=None, br=None, label='raster', time_series=None, **kwargs):
         """
-        :param spikes: spikes dictionary
-        :param save_dir: optional if specified
+        :param spikes: spikes dictionary or Bunch
+        :param channels: channels dictionary or Bunch.
+        :param save_dir: if specified save to this directory as "{pid}_{probe}_{label}.png".
+            Otherwise, plot.
+        :param br: brain regions object (optional)
+        :param label: label for saved image (optional, default="raster")
+        :param time_series: timeseries dictionary for behavioral event times (optional)
+        :param **kwargs: kwargs passed to `driftmap()` (optional)
         :return:
         """
         br = br or BrainRegions()
@@ -1065,7 +1072,10 @@ def raster(self, spikes, channels, save_dir=None, br=None, label='raster', time_
             'width_ratios': [.95, .05], 'height_ratios': [.1, .9]}, figsize=(16, 9), sharex='col')
         axs[0, 1].set_axis_off()
         # axs[0, 0].set_xticks([])
-        brainbox.plot.driftmap(spikes['times'], spikes['depths'], t_bin=0.007, d_bin=10, vmax=0.5, ax=axs[1, 0])
+        if kwargs is None:
+            # set default raster plot parameters
+            kwargs = {"t_bin": 0.007, "d_bin": 10, "vmax": 0.5}
+        brainbox.plot.driftmap(spikes['times'], spikes['depths'], ax=axs[1, 0], **kwargs)
         title_str = f"{self.pid2ref}, {self.pid} \n" \
                     f"{spikes['clusters'].size:_} spikes, {np.unique(spikes['clusters']).size:_} clusters"
         axs[0, 0].title.set_text(title_str)