benda/nonlinearbaseline2025
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updated figure captions

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This commit is contained in:
Jan Benda
2025-05-22 19:03:41 +02:00
parent ee2b8f98b7
commit 3e07684093
12 changed files with 142 additions and 95 deletions
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11
dataoverview.py
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@@ -86,8 +86,9 @@ def plot_corr(ax, data, xcol, ycol, zcol, zmin, zmax, xpdfmax, cmap, color,
def nli_stats(title, data, column, nli_thresh):
print(title)
print(f' nli threshold: {nli_thresh:.1f}')
nrecs = data.rows()
ncells = len(np.unique(data['cell']))
cells = np.unique(data['cell'])
ncells = len(cells)
nrecs = len(data)
print(f' cells: {ncells}')
print(f' recordings: {nrecs}')
hcells = np.unique(data[data(column) > nli_thresh, 'cell'])
@@ -95,7 +96,11 @@ def nli_stats(title, data, column, nli_thresh):
print(f' high nli recordings: n={np.sum(data(column) > nli_thresh):3d}, '
f'{100*np.sum(data(column) > nli_thresh)/nrecs:4.1f}%')
nsegs = data['nsegs']
print(f' number of segments: {np.min(nsegs):4.0f} - {np.max(nsegs):4.0f}, median={np.median(nsegs):4.0f}, mean={np.mean(nsegs):4.0f}, std={np.std(nsegs):4.0f}')
print(f' number of segments: {np.min(nsegs):4.0f} - {np.max(nsegs):4.0f}, median={np.median(nsegs):4.0f}, mean={np.mean(nsegs):4.0f}, std={np.std(nsegs):4.0f}')
nrecs = []
for cell in cells:
nrecs.append(len(data[data["cell"] == cell, :]))
print(f' number of recordings per cell: {np.min(nrecs):4.0f} - {np.max(nrecs):4.0f}, median={np.median(nrecs):4.0f}, mean={np.mean(nrecs):4.0f}, std={np.std(nrecs):4.0f}')
def plot_cvbase_nli_punit(ax, data, ycol, nli_thresh, color):