linted

pynapple/core/ts_group.py

@@ -195,7 +195,9 @@ def __getattr__(self, name):
             return self._metadata[name]
         else:
             # If the attribute is not part of the metadata, raise AttributeError
-            raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
+            raise AttributeError(
+                f"'{type(self).__name__}' object has no attribute '{name}'"
+            )
 
     def __setitem__(self, key, value):
         if not self._initialized:
@@ -234,17 +236,21 @@ def __getitem__(self, key):
             if key.ndim != 1:
                 raise IndexError("Only 1-dimensional boolean indices are allowed!")
             if len(key) != self.__len__():
-                raise IndexError("Boolean index length must be equal to the number of Ts in the group! "
-                                 f"The number of Ts is {self.__len__()}, but the bolean array"
-                                 f"has length {len(key)} instead!")
+                raise IndexError(
+                    "Boolean index length must be equal to the number of Ts in the group! "
+                    f"The number of Ts is {self.__len__()}, but the bolean array"
+                    f"has length {len(key)} instead!"
+                )
             key = np.asarray(self.keys())[key]
         return self._ts_group_from_keys(key)
 
     def _ts_group_from_keys(self, keys):
-        metadata = self._metadata.loc[np.sort(keys), self._metadata.columns.drop("rate")]
+        metadata = self._metadata.loc[
+            np.sort(keys), self._metadata.columns.drop("rate")
+        ]
         return TsGroup(
-                {k: self[k] for k in keys}, time_support=self.time_support, **metadata
-            )
+            {k: self[k] for k in keys}, time_support=self.time_support, **metadata
+        )
 
     def __repr__(self):
         cols = self._metadata.columns.drop("rate")
@@ -325,8 +331,10 @@ def _check_metadata_colum_names(self, *args, **kwargs):
                 invalid_cols += [k]
 
         if invalid_cols:
-            raise ValueError(f"Invalid metadata name(s) {invalid_cols}. Metadata name must differ from "
-                             f"TsGroup attribute names!")
+            raise ValueError(
+                f"Invalid metadata name(s) {invalid_cols}. Metadata name must differ from "
+                f"TsGroup attribute names!"
+            )
 
     def set_info(self, *args, **kwargs):
         """
@@ -416,8 +424,10 @@ def set_info(self, *args, **kwargs):
                 else:
                     not_set.append({k: v})
         if not_set:
-            raise TypeError(f"Cannot set the following metadata:\n{not_set}.\nMetadata columns provided must be  "
-                            f"of type `panda.Series`, `tuple`, `list`, or `numpy.ndarray`.")
+            raise TypeError(
+                f"Cannot set the following metadata:\n{not_set}.\nMetadata columns provided must be  "
+                f"of type `panda.Series`, `tuple`, `list`, or `numpy.ndarray`."
+            )
 
     def get_info(self, key):
         """

pynapple/io/interface_npz.py

@@ -127,7 +127,7 @@ def load(self):
                     "index",
                     "d",
                     "rate",
-                    "keys"
+                    "keys",
                 }:
                     tmp = self.file[k]
                     if len(tmp) == len(tsgroup):

tests/npzfilestest/tsd2.json

@@ -0,0 +1,4 @@
+{
+  "time": "2024-04-05 11:47:12.805723",
+  "info": "Test description"
+}

tmp.py

@@ -0,0 +1,23 @@
+import pynapple as nap
+import numpy as np
+import pandas as pd
+
+n_unit = 100
+df = pd.DataFrame()
+df["isi_violations_ratio"] = np.random.uniform(0, 0.7, size=n_unit)
+df["firing_rate"] = np.random.uniform(0, 80, size=n_unit)
+df["presence_ratio"] = np.random.uniform(0.7, 1., size=n_unit)
+df["device_name"] = [f"Probe{k%4}" for k in range(n_unit)]
+
+
+
+dd = {k: np.sort(np.random.uniform(size=n_unit)) for k in range(n_unit)}
+units = nap.TsGroup(dd)
+units.set_info(df)
+
+pass_qc = units[(units.isi_violations_ratio < 0.5) &
+                (units.firing_rate > 0.1) &
+                (units.presence_ratio > 0.95) &
+                (units.device_name == 'Probe1')]
+#pass_qc["new"] = np.arange(len(pass_qc))
+pass_qc[1.1] = np.arange(len(pass_qc)) + 10