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Let MetricsView accept metrics which have some nans #217

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Let MetricsView accept metrics which have some nans #217

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a0cc44a
allow for nan metrics
chrishalcrow Nov 27, 2025
1561fe8
do panel
chrishalcrow Nov 27, 2025
9d9e0da
remove pandas
chrishalcrow Dec 4, 2025
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29 changes: 15 additions & 14 deletions spikeinterface_gui/metricsview.py
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Original file line number Diff line number Diff line change
Expand Up @@ -111,27 +111,25 @@ def _qt_refresh(self):

scatter.setData(x=values2, y=values1)

visible_unit_ids = self.controller.get_visible_unit_ids()
visible_unit_ids = self.controller.get_visible_unit_indices()

for unit_ind, unit_id in self.controller.iter_visible_units():
color = self.get_unit_color(unit_id)
scatter.addPoints(x=[values2[unit_ind]], y=[values1[unit_ind]], pen=pg.mkPen(None), brush=color)
if (not np.isnan(values2[unit_ind])) and (not np.isnan(values1[unit_ind])):
scatter.addPoints(x=[values2[unit_ind]], y=[values1[unit_ind]], pen=pg.mkPen(None), brush=color)

# self.scatter.addPoints(x=scatter_x[unit_id], y=scatter_y[unit_id], pen=pg.mkPen(None), brush=color)
# self.scatter_select.setData(selected_scatter_x, selected_scatter_y)
elif c == r:
values1 = units_table[visible_metrics[r]].values
values1_no_nans = values1[~np.isnan(values1)]

count, bins = np.histogram(values1, bins=self.settings['num_bins'])
count, bins = np.histogram(values1_no_nans, bins=self.settings['num_bins'])
curve = pg.PlotCurveItem(bins, count, stepMode='center', fillLevel=0, brush=white_brush, pen=white_brush)
plot.addItem(curve)

for unit_ind, unit_id in self.controller.iter_visible_units():
x = values1[unit_ind]
color = self.get_unit_color(unit_id)
line = pg.InfiniteLine(pos=x, angle=90, movable=False, pen=color)
plot.addItem(line)
if not np.isnan(x):
line = pg.InfiniteLine(pos=x, angle=90, movable=False, pen=color)
plot.addItem(line)

def _qt_select_metrics(self):
if not self.tree_visible_metrics.isVisible():
Expand Down Expand Up @@ -212,6 +210,8 @@ def _panel_refresh(self):
col2 = visible_metrics[c]
values1 = units_table[col1].values
values2 = units_table[col2].values
values1_no_nans = values1[~np.isnan(values1)]
values2_no_nans = values2[~np.isnan(values2)]

plot = bpl.figure(
width=plot_size, height=plot_size,
Expand All @@ -227,7 +227,7 @@ def _panel_refresh(self):
plot.xaxis.axis_label = col1
plot.yaxis.axis_label = "Count"
# Create histogram
hist, edges = np.histogram(values1, bins=self.settings['num_bins'])
hist, edges = np.histogram(values1_no_nans, bins=self.settings['num_bins'])
if len(hist) > 0 and max(hist) > 0:
plot.quad(
top=hist, bottom=0, left=edges[:-1], right=edges[1:],
Expand All @@ -238,8 +238,9 @@ def _panel_refresh(self):
max_hist = max(hist)
for unit_ind, unit_id in self.controller.iter_visible_units():
x = values1[unit_ind]
color = self.get_unit_color(unit_id)
plot.line([x, x], [0, max_hist], line_width=2, color=color, alpha=0.8)
if not np.isnan(x):
color = self.get_unit_color(unit_id)
plot.line([x, x], [0, max_hist], line_width=2, color=color, alpha=0.8)
else:
# Off-diagonal - scatter plot
plot.xaxis.axis_label = col2
Expand All @@ -251,8 +252,8 @@ def _panel_refresh(self):

# Plot all points in light color first
all_source = ColumnDataSource({
'x': values2,
'y': values1,
'x': values2_no_nans,
'y': values1_no_nans,
'color': colors
})
plot.scatter('x', 'y', source=all_source, size=8, color='color', alpha=0.5)
Expand Down