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Bug Fix: Refactor return value and update mask_window calculation #1218

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Bug Fix: Refactor return value and update mask_window calculation #1218

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7 changes: 4 additions & 3 deletions suite2p/detection/sparsedetect.py
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Original file line number Diff line number Diff line change
Expand Up @@ -452,7 +452,7 @@ def estimate_spatial_scale(I):
ipk = np.abs(I0 - maximum_filter(I0, size=(11, 11))).flatten() < 1e-4
isort = np.argsort(I0.flatten()[ipk])[::-1]
im, _ = mode(imap[ipk][isort[:50]], keepdims=True)
return im.item()
return im


def find_best_scale(I, spatial_scale):
Expand Down Expand Up @@ -565,12 +565,13 @@ def sparsery(mov, sdmov, highpass_neuropil,
scale, estimate_mode = find_best_scale(I=I, spatial_scale=spatial_scale)

spatscale_pix = 3 * 2**scale
mask_window = int(((spatscale_pix * 1.5) // 2) * 2)
print(np.size(spatscale_pix))
mask_window = int(((float(np.asarray(spatscale_pix).item()) * 1.5) // 2) * 2)
Th2 = threshold_scaling * 5 * max(
1, scale) # threshold for accepted peaks (scale it by spatial scale)
vmultiplier = max(1, mov.shape[0] / 1200)
logger.info("NOTE: %s spatial scale ~%d pixels, time epochs %2.2f, threshold %2.2f " %
(estimate_mode.value, spatscale_pix, vmultiplier, vmultiplier * Th2))
(estimate_mode.value, np.asarray(spatscale_pix).item(), vmultiplier, vmultiplier * Th2))

# get standard deviation for pixels for all values > Th2
v_map = [threshold_reduce(movu0, Th2) for movu0 in movu]
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