scipy 1.9 hanning window has been removed, use hann instead

Author: oliche

ibllib/ephys/ephysqc.py

@@ -113,7 +113,7 @@ def _compute_metrics_array(raw, fs, h):
         detections = spikes.detection(data=destripe.T, fs=fs, h=h, detect_threshold=SPIKE_THRESHOLD_UV * 1e-6)
         spike_rate = np.bincount(detections.trace, minlength=raw.shape[0]).astype(np.float32)
         channel_labels, _ = voltage.detect_bad_channels(raw, fs=fs)
-        _, psd = signal.welch(destripe, fs=fs, window='hanning', nperseg=WELCH_WIN_LENGTH_SAMPLES,
+        _, psd = signal.welch(destripe, fs=fs, window='hann', nperseg=WELCH_WIN_LENGTH_SAMPLES,
                               detrend='constant', return_onesided=True, scaling='density', axis=-1)
         return rms_raw, rms_pre_proc, spike_rate, channel_labels, psd
 
@@ -220,7 +220,7 @@ def rmsmap(sglx):
         if last - first < WELCH_WIN_LENGTH_SAMPLES:
             continue
         # compute a smoothed spectrum using welch method
-        _, w = signal.welch(D, fs=sglx.fs, window='hanning', nperseg=WELCH_WIN_LENGTH_SAMPLES,
+        _, w = signal.welch(D, fs=sglx.fs, window='hann', nperseg=WELCH_WIN_LENGTH_SAMPLES,
                             detrend='constant', return_onesided=True, scaling='density', axis=-1)
         win['spectral_density'] += w.T
         # print at least every 20 windows

ibllib/io/extractors/training_audio.py

@@ -86,7 +86,7 @@ def welchogram(fs, wav, nswin=NS_WIN, overlap=OVERLAP, nperseg=NS_WELCH):
             continue
         # compute PSD estimate for the current window
         iw = window_generator.iw
-        _, W[iw, :] = signal.welch(w, fs=fs, window='hanning', nperseg=nperseg, axis=-1,
+        _, W[iw, :] = signal.welch(w, fs=fs, window='hann', nperseg=nperseg, axis=-1,
                                    detrend='constant', return_onesided=True, scaling='density')
     # the onset detection may have duplicates with sliding window, average them and remove
     detect = np.sort(np.array(detect)) / fs