support for openephys

src/ibldsp/voltage.py

@@ -369,7 +369,7 @@ def destripe(
     if neuropixel_version is not None:
         x = fourier.fshift(x, h["sample_shift"], axis=1)
     # apply spatial filter only on channels that are inside of the brain
-    if channel_labels is not None:
+    if (channel_labels is not None) and (channel_labels is not False):
         x = interpolate_bad_channels(x, channel_labels, h["x"], h["y"])
         inside_brain = np.where(channel_labels != 3)[0]
         x[inside_brain, :] = spatial_fcn(x[inside_brain, :])  # apply the k-filter

src/ibldsp/waveforms.py

@@ -815,10 +815,10 @@ def iradon(w, sr, offset, fmin=0, fmax=None, slowness=None, N=1, mu=.1):
 
     fmax = 1 / (sr * 2) if fmax is None else fmax
     if slowness is None:
-       ds = 1 / fmax / (np.max(offset) - np.min(offset))
-       dx = np.median(np.abs(np.diff(offset)))
-       smax = 1 / dx / fmax
-       slowness = np.linspace(0, smax, int(np.ceil(smax / ds)))
+        ds = 1 / fmax / (np.max(offset) - np.min(offset))
+        dx = np.median(np.abs(np.diff(offset)))
+        smax = 1 / dx / fmax
+        slowness = np.linspace(0, smax, int(np.ceil(smax / ds)))
 
     # Decompose les donnees sous la forme d'une somme d'ondes de vitesse 1./slowness
     ns, nc = w.shape

src/spikeglx.py

@@ -123,6 +123,7 @@ def __init__(
             self.channel_conversion_sample2v = {"samples": np.ones(nc) * s2v}
             if self._nsync > 0:
                 self.channel_conversion_sample2v["samples"][-nsync:] = 1
+            self.geometry = neuropixel.trace_header(version=1)
         else:
             # normal case we continue reading and interpreting the metadata file
             self.file_meta_data = meta_file