def get_templates(cluster_ids):
return {
i: Bunch(
template=artificial_waveforms(1, n_samples, 2)[0, ...],
channel_ids=np.arange(i, i + 2),
)
for i in cluster_ids
}
def test_waveform_view(qtbot, tempdir, gui):
nc = 5
ns = 10
w = 10 + 100 * artificial_waveforms(ns, 20, nc)
def get_waveforms(cluster_id):
return Bunch(data=w,
masks=np.random.uniform(low=0., high=1., size=(ns, nc)),
channel_ids=np.arange(nc),
channel_labels=['%d' % (ch * 10) for ch in range(nc)],
channel_positions=staggered_positions(nc))
v = WaveformView(
waveforms={
'waveforms': get_waveforms,
'mean_waveforms': get_waveforms
},
sample_rate=10000.,
)
v.show()
qtbot.waitForWindowShown(v.canvas)
v.attach(gui)
v.on_select(cluster_ids=[])
v.on_select(cluster_ids=[0])
v.on_select(cluster_ids=[0, 2, 3])
v.on_select(cluster_ids=[0, 2])
v.toggle_waveform_overlap(True)
v.toggle_waveform_overlap(False)
v.toggle_show_labels(False)
v.toggle_show_labels(True)
v.next_waveforms_type()
v.previous_waveforms_type()
v.toggle_mean_waveforms(True)
v.toggle_mean_waveforms(False)
# Box scaling.
bs = v.boxed.box_size
v.increase()
v.decrease()
v.reset_scaling()
ac(v.boxed.box_size, bs)
bs = v.boxed.box_size
v.widen()
v.narrow()
ac(v.boxed.box_size, bs)
# Probe scaling.
bp = v.boxed.box_pos
v.extend_horizontally()
v.shrink_horizontally()
ac(v.boxed.box_pos, bp)
bp = v.boxed.box_pos
v.extend_vertically()
v.shrink_vertically()
ac(v.boxed.box_pos, bp)
a, b = v.probe_scaling
v.probe_scaling = (a, b * 2)
ac(v.probe_scaling, (a, b * 2))
a, b = v.box_scaling
v.box_scaling = (a * 2, b)
ac(v.box_scaling, (a * 2, b))
# Simulate channel selection.
_clicked = []
@connect(sender=v)
def on_select_channel(sender, channel_id=None, button=None, key=None):
_clicked.append((channel_id, button, key))
key_press(qtbot, v.canvas, '2')
mouse_click(qtbot, v.canvas, pos=(0., 0.), button='Left')
key_release(qtbot, v.canvas, '2')
assert _clicked == [(2, 'Left', 2)]
v.set_state(v.state)
_stop_and_close(qtbot, v)
def get_template(self, template_id):
nc = self.n_channels // 2
return Bunch(template=artificial_waveforms(1, self.n_samples_waveforms,
nc)[0, ...],
channel_ids=self._get_some_channels(template_id, nc))
def get_waveforms(self, spike_ids, channel_ids):
n_channels = len(channel_ids) if channel_ids else self.n_channels
return artificial_waveforms(len(spike_ids), self.n_samples_waveforms,
n_channels)
def waveforms(n_spikes, n_samples, n_channels):
yield artificial_waveforms(n_spikes, n_samples, n_channels)