def test_featureprojview():
keys = (
'features,features_background,masks,clusters,clusters_selected,'
'spiketimes,'
'cluster_colors,fetdim,nchannels,nextrafet,duration,freq').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['operators'] = [
lambda self: assert_fun(self.view.get_projection(0) == (0, 0)),
lambda self: assert_fun(self.view.get_projection(1) == (0, 1)),
lambda self: self.view.select_channel(0, 5),
lambda self: self.view.select_feature(0, 1),
lambda self: self.view.select_channel(1, 32),
lambda self: self.view.select_feature(1, 2),
lambda self: assert_fun(self.view.get_projection(0) == (5, 1)),
lambda self: assert_fun(self.view.get_projection(1) == (32, 2)),
lambda self: self.view.toggle_mask(),
lambda self: self.view.set_wizard_pair((2, 1), (3, 2)),
lambda self: self.view.set_wizard_pair(None, (3, 2)),
lambda self: self.view.set_wizard_pair((3, 2), None),
lambda self: self.view.set_wizard_pair(None, None),
lambda self: self.view.set_projection(0, 2, -1),
lambda self: self.view.set_projection(1, 2, -1),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(FeatureProjectionView, **kwargs)
def test_viewdata_correlogramsview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
correlograms = create_correlograms([0, 1], 50)
data = get_correlogramsview_data(exp, clusters=[0, 1],
correlograms=correlograms,
)
show_view(CorrelogramsView, **data)
def test_viewdata_correlogramsview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
correlograms = create_correlograms([0, 1], 50)
data = get_correlogramsview_data(exp, clusters=[0, 1],
correlograms=correlograms,
)
show_view(CorrelogramsView, **data)
def test_similaritymatrixview():
data = get_data()
kwargs = {}
kwargs['similarity_matrix'] = create_similarity_matrix(nclusters)
kwargs['cluster_colors_full'] = data['cluster_colors_full']
kwargs['operators'] = [
lambda self: self.view.show_selection(5, 6),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(SimilarityMatrixView, **kwargs)
def test_channelview():
# keys = ('channel_names','channel_colors','channel_groups','channel_group_colors','channel_group_names')
# data = get_data()
# kwargs = {k: data[k] for k in keys}
nchannels = 32
nchannelgroups = 4
kwargs = {}
channel_names = create_channel_names(nchannels)
channel_group_names = create_channel_group_names(nchannelgroups)
channel_colors = create_channel_colors(nchannels)
channel_groups = create_channel_groups(nchannels)
channel_names = create_channel_names(nchannels)
group_colors = create_channel_group_colors(nchannelgroups)
group_names = create_channel_group_names(nchannelgroups)
kwargs["channel_colors"] = channel_colors
kwargs["channel_groups"] = channel_groups
kwargs["channel_names"] = channel_names
kwargs["group_colors"] = group_colors
kwargs["group_names"] = group_names
kwargs["operators"] = [lambda self: (self.close() if USERPREF["test_auto_close"] != False else None)]
# Show the view.
window = show_view(ChannelView, **kwargs)
def test_traceview():
trace = create_trace(int(freq * 60), nchannels)
ignored_channels = np.arange(5)
kwargs = {}
kwargs['trace'] = trace
kwargs['freq'] = freq
kwargs['ignored_channels'] = ignored_channels
kwargs['operators'] = [
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(TraceView, **kwargs)
def test_channelview():
# keys = ('channel_names','channel_colors','channel_groups','channel_group_colors','channel_group_names')
# data = get_data()
# kwargs = {k: data[k] for k in keys}
nchannels = 32
nchannelgroups = 4
kwargs = {}
channel_names = create_channel_names(nchannels)
channel_group_names = create_channel_group_names(nchannelgroups)
channel_colors = create_channel_colors(nchannels)
channel_groups = create_channel_groups(nchannels)
channel_names = create_channel_names(nchannels)
group_colors = create_channel_group_colors(nchannelgroups)
group_names = create_channel_group_names(nchannelgroups)
kwargs['channel_colors'] = channel_colors
kwargs['channel_groups'] = channel_groups
kwargs['channel_names'] = channel_names
kwargs['group_colors'] = group_colors
kwargs['group_names'] = group_names
kwargs['operators'] = [
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(ChannelView, **kwargs)
def test_clusterview():
keys = ('cluster_groups,group_colors,group_names,'
'cluster_sizes').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['cluster_colors'] = data['cluster_colors_full']
# kwargs['background'] = {5: 1, 7: 2}
clusters = get_indices(data['cluster_sizes'])
quality = pd.Series(np.random.rand(len(clusters)), index=clusters)
kwargs['cluster_quality'] = quality
kwargs['operators'] = [
lambda self: self.view.set_quality(quality),
lambda self: self.view.set_background({
5: 1,
7: 2
}),
lambda self: self.view.set_background({6: 3}),
lambda self: self.view.set_background({}),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(ClusterView, **kwargs)
def test_clusterview():
keys = ('cluster_groups,group_colors,group_names,'
'cluster_sizes').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['cluster_colors'] = data['cluster_colors_full']
# kwargs['background'] = {5: 1, 7: 2}
clusters = get_indices(data['cluster_sizes'])
quality = pd.Series(np.random.rand(len(clusters)), index=clusters)
kwargs['cluster_quality'] = quality
kwargs['operators'] = [
lambda self: self.view.set_quality(quality),
lambda self: self.view.set_background({5: 1, 7: 2}),
lambda self: self.view.set_background({6: 3}),
lambda self: self.view.set_background({}),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(ClusterView, **kwargs)
def test_waveformview():
keys = ('waveforms,clusters,cluster_colors,clusters_selected,masks,'
'geometrical_positions').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
operators = [
lambda self: self.view.toggle_mask(),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(WaveformView, operators=operators, **kwargs)
def test_traceview():
trace = create_trace(int(freq * 60), nchannels)
ignored_channels = np.arange(5)
kwargs = {}
kwargs['trace'] = trace
kwargs['freq'] = freq
kwargs['spiketimes'] = np.array([1, 30, 100])
kwargs['ignored_channels'] = ignored_channels
kwargs['operators'] = [
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(TraceView, **kwargs)
def test_similaritymatrixview():
data = get_data()
kwargs = {}
kwargs['similarity_matrix'] = create_similarity_matrix(nclusters)
kwargs['cluster_colors_full'] = data['cluster_colors_full']
kwargs['operators'] = [
lambda self: self.view.show_selection(5, 6),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(SimilarityMatrixView, **kwargs)
def test_waveformview():
keys = ('waveforms,clusters,cluster_colors,clusters_selected,masks,'
'geometrical_positions'
).split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
operators = [
lambda self: self.view.toggle_mask(),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(WaveformView, operators=operators, **kwargs)
def test_correlogramsview():
keys = ('clusters_selected,cluster_colors').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['correlograms'] = create_correlograms(kwargs['clusters_selected'],
ncorrbins)
kwargs['baselines'] = create_baselines(kwargs['clusters_selected'])
kwargs['ncorrbins'] = ncorrbins
kwargs['corrbin'] = corrbin
kwargs['operators'] = [
lambda self: self.view.change_normalization('uniform'),
lambda self: self.view.change_normalization('row'),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(CorrelogramsView, **kwargs)
def test_projectionview():
kwargs = {}
kwargs['operators'] = [
lambda self: assert_fun(self.view.get_projection(0) == (0, 0)),
lambda self: assert_fun(self.view.get_projection(1) == (0, 1)),
lambda self: self.view.select_channel(0, 5),
lambda self: self.view.select_feature(0, 1),
lambda self: self.view.select_channel(1, 32),
lambda self: self.view.select_feature(1, 2),
lambda self: assert_fun(self.view.get_projection(0) == (5, 1)),
lambda self: assert_fun(self.view.get_projection(1) == (32, 2)),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
kwargs['fetdim'] = 3
kwargs['nchannels'] = 32
kwargs['nextrafet'] = 3
# Show the view.
show_view(ProjectionView, **kwargs)
def test_logview():
kwargs = {}
kwargs['operators'] = [
lambda self: sys.stdout.write("Hello world!"),
lambda self: assert_fun(self.view.get_text() == "Hello world!"),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(LogView, **kwargs)
def test_projectionview():
kwargs = {}
kwargs['operators'] = [
lambda self: assert_fun(self.view.get_projection(0) == (0, 0)),
lambda self: assert_fun(self.view.get_projection(1) == (0, 1)),
lambda self: self.view.select_channel(0, 5),
lambda self: self.view.select_feature(0, 1),
lambda self: self.view.select_channel(1, 32),
lambda self: self.view.select_feature(1, 2),
lambda self: assert_fun(self.view.get_projection(0) == (5, 1)),
lambda self: assert_fun(self.view.get_projection(1) == (32, 2)),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
kwargs['fetdim'] = 3
kwargs['nchannels'] = 32
kwargs['nextrafet'] = 3
# Show the view.
show_view(ProjectionView, **kwargs)
def test_ipythonview():
if not IPYTHON:
return
kwargs = {}
kwargs['operators'] = [
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(IPythonView, **kwargs)
def test_correlogramsview():
keys = ('clusters_selected,cluster_colors').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['correlograms'] = create_correlograms(kwargs['clusters_selected'],
ncorrbins)
kwargs['baselines'] = create_baselines(kwargs['clusters_selected'])
kwargs['ncorrbins'] = ncorrbins
kwargs['corrbin'] = corrbin
kwargs['operators'] = [
lambda self: self.view.change_normalization('uniform'),
lambda self: self.view.change_normalization('row'),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(CorrelogramsView, **kwargs)
def test_featureview():
keys = ('features,features_background,masks,clusters,clusters_selected,'
'spiketimes,'
'cluster_colors,fetdim,nchannels,nextrafet,duration,freq').split(',')
data = get_data()
kwargs = {k: data[k] for k in keys}
kwargs['operators'] = [
lambda self: self.view.toggle_mask(),
lambda self: self.view.set_wizard_pair((2, 1), (3, 2)),
lambda self: self.view.set_wizard_pair(None, (3, 2)),
lambda self: self.view.set_wizard_pair((3, 2), None),
lambda self: self.view.set_wizard_pair(None, None),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
show_view(FeatureView, **kwargs)
def test_logview():
kwargs = {}
kwargs['operators'] = [
lambda self: sys.stdout.write("Hello world!"),
lambda self: assert_fun(self.view.get_text() == "Hello world!"),
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(LogView, **kwargs)
def test_ipythonview():
if not IPYTHON:
return
kwargs = {}
kwargs['operators'] = [
lambda self: (self.close()
if USERPREF['test_auto_close'] != False else None),
]
# Show the view.
window = show_view(IPythonView, **kwargs)
def test_viewdata_similaritymatrixview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
matrix = create_similarity_matrix(2)
data = get_similaritymatrixview_data(exp, matrix=matrix)
show_view(SimilarityMatrixView, **data)
def test_viewdata_clusterview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_clusterview_data(exp)
show_view(ClusterView, **data)
def test_viewdata_featureview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_featureview_data(exp, clusters=[0], nspikes_bg=1000)
show_view(FeatureView, **data)
def test_viewdata_waveformview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_waveformview_data(exp, clusters=[0, 1])
show_view(WaveformView, **data)
def test_viewdata_waveformview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_waveformview_data(exp, clusters=[0, 1])
show_view(WaveformView, **data)
"""Unit tests for the viewdata module."""
# -----------------------------------------------------------------------------
# Imports
# -----------------------------------------------------------------------------
import os
import sys
import time
import tempfile
import numpy as np
from spikedetekt2.dataio import *
from klustaviewa.views.viewdata import *
from klustaviewa.views.tests.utils import show_view
from klustaviewa.views import WaveformView, FeatureView
with Experiment('n6mab041109_60sec_n6mab031109_MKKdistfloat_25_regular100_1', dir='data') as exp:
chgrp = exp.channel_groups[0]
data = get_waveformview_data(exp, clusters=[0])
show_view(WaveformView, **data)
def test_viewdata_similaritymatrixview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
matrix = create_similarity_matrix(2)
data = get_similaritymatrixview_data(exp, matrix=matrix)
show_view(SimilarityMatrixView, **data)
def test_viewdata_featureview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_featureview_data(exp, clusters=[0], nspikes_bg=1000)
show_view(FeatureView, **data)
def test_viewdata_clusterview_1():
with Experiment('myexperiment', dir=DIRPATH) as exp:
chgrp = exp.channel_groups[0]
data = get_clusterview_data(exp)
show_view(ClusterView, **data)
