def test_cosine_init(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
C = CosineDirectionalTuning(T.TETRODE[1].spk_ts, T.xyTS, T.TETRODE[1].cut,
T.xy[0, :], T.xy[1, :])
C.getPosIndices()
clust_pos_indices = C.getClusterPosIndices(1)
assert (isinstance(clust_pos_indices, np.ndarray))
ts = C.getClusterSpikeTimes(1)
assert (isinstance(ts, np.ndarray))
dbs = C.getDirectionalBinPerPosition(6)
assert (isinstance(dbs, np.ndarray))
dbs = C.getDirectionalBinForCluster(1)
assert (isinstance(dbs, np.ndarray))
C.spk_sample_rate
C.spk_sample_rate = 48000
C.pos_sample_rate
C.pos_sample_rate = 50
C.min_runlength
C.min_runlength = 5
C.xy
C.xy = 1
C.hdir
C.hdir = 1
C.speed
C.speed = 1
C.pos_samples_for_spike
C.pos_samples_for_spike = 1
def test_p2t_time(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
waveforms = T.TETRODE[1].waveforms
waveforms = waveforms[T.TETRODE[1].cut == 1, :, :]
spk_ts = T.TETRODE.get_spike_samples(1, 1)
S = SpikeCalcsAxona(spk_ts)
S.p2t_time(waveforms)
def test_half_amp_duration(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
waveforms = T.TETRODE[1].waveforms
waveforms = waveforms[T.TETRODE[1].cut == 1, :, :]
spk_ts = T.TETRODE.get_spike_samples(1, 1)
S = SpikeCalcsAxona(spk_ts)
S.half_amp_dur(waveforms)
def test_plot_cluster_space(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
waveforms = T.TETRODE[1].waveforms
waveforms = waveforms[T.TETRODE[1].cut == 1, :, :]
spk_ts = T.TETRODE.get_spike_samples(1, 1)
S = SpikeCalcsAxona(spk_ts)
fig = S.plotClusterSpace(waveforms)
return fig
def get_spikecalcs_instance(path_to_axona_data) -> SpikeCalcsGeneric:
T = AxonaTrial(path_to_axona_data)
T.load()
spk_ts = T.TETRODE[1].spk_ts
S = SpikeCalcsGeneric(spk_ts)
S.getClusterWaveforms(1, 1)
S.waveforms = T.TETRODE[1].waveforms
S.spk_clusters = T.TETRODE[1].cut
return S
def test_pos_props_with_events(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
spike_ts = T.TETRODE.get_spike_samples(1, 1)
pp2d = phasePrecession2D(T.EEG.sig, 250., T.xy, spike_ts, T.xyTS, ppc)
laser_events = np.array(
np.ceil(T.STM['on'] / T.STM.timebase * T.pos_sample_rate)).astype(int)
peaksXY, _, labels, _ = pp2d.partitionFields()
pp2d.getPosProps(labels, peaksXY, laserEvents=laser_events, plot=True)
def test_the_rest_of_CDT(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
C = CosineDirectionalTuning(T.TETRODE[1].spk_ts, T.xyTS, T.TETRODE[1].cut,
T.xy[0, :], T.xy[1, :])
runs = C.getRunsOfMinLength()
C.speedFilterRuns(runs)
spk_ts = T.TETRODE.get_spike_samples(1, 1)
pos_mask = np.ones_like(spk_ts).astype(bool)
C.intrinsic_freq_autoCorr(spk_ts, pos_mask)
def test_LFP_oscillations(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
sig = T.EEG.sig
fs = T.EEG.sample_rate
LFP_Osc = LFPOscillations(sig, fs)
LFP_Osc.getFreqPhase(sig, [6, 12])
LFP_Osc.modulationindex(sig)
LFP_Osc.plv(sig)
LFP_Osc.filterForLaser(sig)
def test_get_param(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
waveforms = T.TETRODE[1].waveforms
waveforms = waveforms[T.TETRODE[1].cut == 1, :, :]
spk_ts = T.TETRODE.get_spike_samples(1, 1)
S = SpikeCalcsAxona(spk_ts)
params = ['Amp', 'P', 'T', 'Vt', 'tP', 'tT', 'PCA']
for param in params:
S.getParam(waveforms, param=param)
def test_circ_circ_corr(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
spike_ts = T.TETRODE.get_spike_samples(1, 1)
pp2d = phasePrecession2D(T.EEG.sig, 250., T.xy, spike_ts, T.xyTS, ppc)
pp2d._circCircCorrTLinear(theta=T.dir[0:10].data,
phi=np.random.vonmises(0, 4, 10),
k=10,
conf=True)
pp2d._circCircCorrTLinear(theta=T.dir[0:3].data,
phi=np.random.vonmises(0, 4, 3),
k=3,
conf=True)
def test_axona_properties(path_to_axona_data):
from ephysiopy.dacq2py.axonaIO import EEG
T = AxonaTrial(path_to_axona_data)
T.load()
assert (isinstance(T.STM, dict))
assert (isinstance(T.settings, dict))
assert (isinstance(T.EEG, EEG))
assert (isinstance(T.EGF, EEG))
T.TETRODE
spike_times = T.TETRODE.get_spike_samples(1, 1)
assert (isinstance(spike_times, np.ndarray))
with pytest.raises(KeyError):
T.TETRODE[16]
with pytest.raises(Exception):
T.TETRODE.get_spike_samples(99, 99)
def test_plot_axona_EGF_power(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotEEGPower('egf', plot=False)
fig = plt.gcf()
return fig
def test_plot_summary(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
spike_times = T.TETRODE.get_spike_samples(1, 1)
T.makeSummaryPlot(spike_times)
def test_plot_axona_spikes_on_path(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotSpikesOnPath(1, 1, plot=False)
fig = plt.gcf()
return fig
def test_plot_axona_HD_map(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotHDMap(1, 1, plot=False)
fig = plt.gcf()
return fig
def test_plot_axona_HD_map_with_mrv(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotHDMap(1, 1, plot=False, add_mrv=True, fill=True)
fig = plt.gcf()
return fig
def test_phase_precession_2d_setup(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
spike_ts = T.TETRODE.get_spike_samples(1, 1)
phasePrecession2D(T.EEG.sig, 250., T.xy, spike_ts, T.xyTS, ppc)
def test_plot_axona_SAC(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotSAC(1, 1, plot=False)
fig = plt.gcf()
return fig
def test_plot_axona_EEG_power(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotEEGPower('eeg', ylim=25, plot=False)
fig = plt.gcf()
return fig
def test_plot_axona_speed_vs_HD(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotSpeedVsHeadDirection(1, 1, plot=False)
fig = plt.gcf()
return fig
def test_plot_axona_speed_vs_rate(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
T.plotSpeedVsRate(1, 1, plot=False, maxSpeed=1e6)
fig = plt.gcf()
return fig
def test_load_axona_trial(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
def test_perform_regression(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
spike_ts = T.TETRODE.get_spike_samples(1, 1)
pp2d = phasePrecession2D(T.EEG.sig, 250., T.xy, spike_ts, T.xyTS, ppc)
pp2d.performRegression()
def test_plot_raster(path_to_axona_data):
T = AxonaTrial(path_to_axona_data)
T.load()
old_events = T.ttl_timestamps.copy()
T.ttl_timestamps = None
T.plotRaster(1, 1, plot=False)
T.ttl_timestamps = old_events
T.plotRaster(1, 1, plot=False)
fig = plt.gcf()
ax = plt.gca()
T.plotRaster(1, 1, ax=ax, histtype='rate')
return fig