[singel cell ephys] add stimulus overview

single_cell_intracellular_spikes/explore.py

@@ -45,6 +45,37 @@ def print_metadata(nf, sec_type=None, sec_name=None, max_depth=-1):
         s.pprint(max_depth=max_depth)
 
 
+def find_mtags_for_tag(block, tag):
+    """Finds the MultiTags (prepresentatives of the actual stimulus
+    outputs) that ran during a RePro run. Relacs makes sure that stimulations
+    with the same settings end up in the same MultiTag.
+
+    Arguments:
+    block --- nix.Block, the block in which to look for MultiTags
+    tag --- nix.Tag, the Tag (aka, the RepPro run) defining the search interval
+
+    Returns:
+    a list of MultiTags
+    a list of lists containing the position indices for the respective MultiTags
+    """
+    assert(isinstance(block, nix.pycore.block.Block))
+    assert(isinstance(tag, nix.pycore.tag.Tag))
+    mtags = []
+    positions = []
+    tag_start = np.atleast_1d(tag.position)
+    tag_end = tag_start + np.atleast_1d(tag.extent)
+    for mt in block.multi_tags:
+        mt_starts = np.atleast_1d(mt.positions[:])
+        mt_ends = mt_starts + np.atleast_1d(mt.extents[:])
+        pos = np.argwhere(mt_starts[(mt_starts > tag_start) &
+                                    (mt_starts < tag_end) &
+                                    (mt_ends <= tag_end)])[:, 0]
+        if len(pos) > 0:
+            mtags.append(mt)
+            positions.append(pos)
+    return mtags, positions
+
+
 def data_overview(nf):
     assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
     b = nf.blocks[0]
@@ -63,7 +94,23 @@ def data_overview(nf):
     set_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Set]
     for sd in set_data:
         print("\t%s, size: %s" % (sd.name, str(sd.shape)))
+    print("\n")
+
+
+def stimulus_overview(nf):
+    assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
+    b = nf.blocks[0]
 
+    print("Stimulations, aka RePro runs:")
+    repro_runs = [t for t in b.tags if "repro_run" in t.type]
+    for rr in repro_runs:
+        start = rr.position[0]
+        end = start + rr.extent[0]
+        print("\t RePro %s,  time: %.4f --> %.4f%s" % (rr.name, start, end, rr.units[0]))
+        mts, positions = find_mtags_for_tag(b, rr)
+        for mt, pos in zip(mts, positions):
+            print("\t\t with %i stimulus repetitions" % (len(pos)))
+    print("\n")
 
 
 if __name__ == "__main__":
@@ -77,4 +124,6 @@ if __name__ == "__main__":
 
     data_overview(nix_file)
 
+    stimulus_overview(nix_file)
+    
     nix_file.close()