pandas fixes and return channels

src/ibldsp/waveform_extraction.py

@@ -504,11 +504,12 @@ def __init__(
         assert self.channels_fp.exists(), "waveforms.channels.npz file missing!"
 
         # ingest parquet table
-        self.table = pd.read_parquet(self.table_fp)
+        self.table = pd.read_parquet(self.table_fp).reset_index(drop=True).drop(columns=["index"])
         self.num_labels = self.table["cluster"].nunique()
         self.labels = np.array(self.table["cluster"].unique())
         self.total_wfs = sum(~self.table["peak_channel"].isna())
         self.table["wf_number"] = np.tile(np.arange(self.max_wf), self.num_labels)
+        self.table["linear_index"] = np.arange(len(self.table))
 
         traces_shape = (self.num_labels, max_wf, num_channels, spike_length_samples)
         templates_shape = (self.num_labels, num_channels, spike_length_samples)
@@ -517,7 +518,14 @@ def __init__(
         self.templates = np.memmap(self.templates_fp, dtype=np.float32, shape=templates_shape)
         self.channels = np.load(self.channels_fp, allow_pickle="True")["channels"]
 
-    def load_waveforms(self, labels=None, indices=None, return_info=True):
+    def __repr__(self):
+        s1 = f"WaveformsLoader with {self.total_wfs} waveforms in {self.wfs_dtype} from {self.num_labels} labels.\n"
+        s2 = f"Data path: {self.data_dir}\n"
+        s3 = f"{self.spike_length_samples} samples, {self.num_channels} channels, {self.max_wf} max waveforms per label\n"
+
+        return s1 + s2 + s3
+
+    def load_waveforms(self, labels=None, indices=None, return_info=True, flatten=True):
 
         if labels is None:
             labels = self.labels
@@ -526,10 +534,14 @@ def load_waveforms(self, labels=None, indices=None, return_info=True):
 
         wfs = self.traces[np.array(labels)][:, indices, :, :]
 
+        if flatten:
+            wfs = wfs.reshape(-1, self.num_channels, self.spike_length_samples).astype(np.float32)
+
         if return_info:
             _table = self.table[self.table["cluster"].isin(labels)].copy()
-            _table = _table[_table["wf_number"].isin(indices)]
-            return wfs, _table
+            _table = _table[_table["wf_number"].isin(indices)].reset_index(drop=True)
+            channels = self.channels[_table["linear_index"].to_numpy()].astype(int)
+            return wfs, _table, channels
 
         return wfs
 
@@ -539,7 +551,8 @@ def random_waveforms(
         num_random_labels=None,
         num_random_waveforms=None,
         return_info=True,
-        seed=None                    
+        seed=None,
+        flatten=True        
     ):
 
         rg = np.random.default_rng(seed=seed)
@@ -555,6 +568,8 @@ def random_waveforms(
         wfs = self.traces[np.array(labels)][:, :, :, :]
 
 
+
+