kind of works for nix files

database.py

@@ -5,6 +5,7 @@ import os
 import glob
 import util as ut
 import uuid
+import pyrelacs
 
 from IPython import embed
 
@@ -195,6 +196,7 @@ class Stimulus(dj.Manual):
     ---
     stimulus_index : int
     stimulus_name : varchar(512)
+    mtag_id : varchar(50)
     start : float
     duration : float
     settings : varchar(3000)
@@ -246,7 +248,7 @@ def populate_subjects(data_path):
     inserts["species"] = subj["Species"]
     Subject().insert1(inserts, skip_duplicates=True)
 
-    # multi mach entry
+    # multi match entry
     dataset = dict((Dataset() & {"dataset_id": dset_name}).fetch1())
     mm = dict(dataset_id=dataset["dataset_id"], subject_id=subj["Identifier"])
     SubjectDatasetMap.insert1(mm, skip_duplicates=True)
@@ -318,14 +320,7 @@ def populate_cells(data_path):
     CellDatasetMap.insert1(mm, skip_duplicates=True)
 
 
-def populate_repros(data_path):
+def scan_nix_file_for_repros(dataset):
-    print("\tImporting RePro(s) of %s" % data_path)
-    dset_name = os.path.split(data_path)[-1]
-    if len(Dataset & {"dataset_id": dset_name}) != 1:
-        return False
-    dataset = dict((Dataset & {"dataset_id": dset_name}).fetch1())
-
-    if dataset["has_nix"]:
     print("\t\tscanning nix file")
     nix_files = glob.glob(os.path.join(dataset["data_source"], "*.nix"))
     for nf in nix_files:
@@ -334,8 +329,8 @@ def populate_repros(data_path):
             continue
         f = nix.File.open(nf, nix.FileMode.ReadOnly)
         b = f.blocks[0]
-            for t in b.tags:
+        repro_runs = [t for t in b.tags if "relacs.repro_run" in t.type]
-                if "relacs.repro_run" in t.type:
+        for t in repro_runs:
             rs = t.metadata.find_sections(lambda x: "Run" in x.props)
             if len(rs) == 0:
                 continue
@@ -353,35 +348,53 @@ def populate_repros(data_path):
             rp["start"] = t.position[0]
             rp["duration"] = t.extent[0]
             Repro.insert1(rp, skip_duplicates=True)
-                    repro = dict((Repro & dict(repro_id="BaselineActivity_2", dataset_id="2018-11-20-ae-invivo-1")).fetch1())
+
+            # import Stimuli
+            repro = dict((Repro & dict(repro_id=rp["repro_id"], dataset_id=rp["dataset_id"])).fetch1())
             repro.pop("settings")
             repro.pop("repro_name")
             repro.pop("start")
             repro.pop("duration")
-                    # import Stimuli
+
-                    mtags = ut.find_mtags_for_tag(b, t)
+            mtags, positions = ut.find_mtags_for_tag(b, t)
-                    stim_index = 0
+            for i, mt in enumerate(mtags):
-                    for mt in mtags:
                 mt_positions = np.atleast_2d(mt.positions[:]).T
                 mt_extents = np.atleast_2d(mt.extents[:]).T
-                        for i in range(mt.positions.shape[0]):
+                for p in positions[i]:
-                            settings = ut.mtag_settings_to_yaml(mt, i)
+                    settings = ut.mtag_settings_to_yaml(mt, p)
-                            stim_start = mt_positions[i, 0]
+                    stim_start = mt_positions[p, 0]
-                            stim_duration = mt_extents[i, 0]
+                    stim_duration = mt_extents[p, 0]
 
                     stim = Stimulus.get_template_tuple()
                     stim["stimulus_id"] = str(uuid.uuid1())
-                            stim["stimulus_index"] = stim_index
+                    stim["stimulus_index"] = p
                     stim["start"] = stim_start
                     stim["duration"] = stim_duration
                     stim["settings"] = settings
+                    stim["mtag_id"] = mt.id
+                    stim["stimulus_name"] = mt.name
                     stim.update(repro)
                     Stimulus.insert1(stim, skip_duplicates=True)
-                            stim_index += 1
         f.close()
         f = None
-    else:
+
+
+def scan_folder_for_repros(dataset):
+    
     pass
+
+
+def populate_repros(data_path):
+    print("\tImporting RePro(s) of %s" % data_path)
+    dset_name = os.path.split(data_path)[-1]
+    if len(Dataset & {"dataset_id": dset_name}) != 1:
+        return False
+    dataset = dict((Dataset & {"dataset_id": dset_name}).fetch1())
+
+    if dataset["has_nix"]:
+        scan_nix_file_for_repros(dataset)
+    else:
+        scan_folder_for_repros(dataset)
     return True
 
 
@@ -403,8 +416,9 @@ def populate(datasets):
 
 
 if __name__ == "__main__":
-    data_dir = "../../science/high_frequency_chirps/data"
+    data_dir = "/data/apteronotus"
     # data_dir = "../high_freq_chirps/data"
-    datasets = glob.glob(os.path.join(data_dir, '2018-11-20*'))
+    datasets = glob.glob(os.path.join(data_dir, '2018-03-22-ak-*'))
-    drop_tables()
+    # drop_tables()
-    # populate(datasets)
+    populate(datasets)
+

util.py

@@ -104,22 +104,32 @@ def nix_metadata_to_yaml(section, cur_depth=0, val_count=1):
 
 
 def find_mtags_for_tag(block, tag):
+    """
+        Finds those multi tags and the respective positions within that match to a certain
+        repro run.
+
+        @:returns list of mtags, list of mtag positions
+    """
     assert(isinstance(block, nix.pycore.block.Block))
     assert(isinstance(tag, nix.pycore.tag.Tag))
     mtags = []
+    indices = []
     tag_start = np.atleast_1d(tag.position)
     tag_end = tag_start + np.atleast_1d(tag.extent)
     for mt in block.multi_tags:
-        mt_start = np.atleast_1d(mt.positions[0, :])
+        position_count = mt.positions.shape[0]
-        mt_end = np.atleast_1d(mt.positions[-1, :] + mt.extents[-1, :])
+        in_tag_positions = []
-        in_tag = True
+        for i in range(position_count):
-        for i in range(len(tag_start)):
+            mt_start = np.atleast_1d(mt.positions[i, :])
-            if mt_start[i] < tag_start[i] or mt_end[i] > tag_end[i]:
+            mt_end = mt_start + np.atleast_1d(mt.extents[i, :])
-                in_tag = False
+
-                break
+            for j in range(len(tag_start)):
-        if in_tag:
+                if mt_start[j] >= tag_start[j] and mt_end[j] <= tag_end[j]:
+                    in_tag_positions.append(i)
+        if len(in_tag_positions) > 0:
             mtags.append(mt)
-    return mtags
+            indices.append(in_tag_positions)
+    return mtags, indices
 
 
 def mtag_settings_to_yaml(mtag, pos_index):