def test_SpatialReceptiveField_reverse_locations(self):
alts = [-2., -1., 0., 1., 2.]
azis = [-2., -1., 0., 1., 2.]
map = np.array([[0., 0., 0., 0., 0.], [0., 0., 0., 0., 0.],
[0., 0., 1., 1., 0.], [0., 0., 1., 1., 0.],
[0., 0., 0., 0., 0.]])
srf = sca.SpatialReceptiveField(mask=map,
altPos=alts,
aziPos=azis,
sign='ON')
# print(srf.get_weighted_rf_center())
assert (srf.get_weighted_rf_center() == [0.5, 0.5])
srf2 = sca.SpatialReceptiveField(mask=map,
altPos=alts[::-1],
aziPos=azis,
sign='ON')
assert (srf2.get_weighted_rf_center() == [-0.5, 0.5])
srf_f = srf.gaussian_filter(sigma=1)
# print(srf_f.get_weighted_rf_center())
srf2_f = srf2.gaussian_filter(sigma=1)
# print(srf2_f.get_weighted_rf_center())
assert (abs(srf_f.get_weighted_rf_center()[0] +
srf2_f.get_weighted_rf_center()[0]) < 1e-10)
srf_fi = srf_f.interpolate(ratio=2, method='linear')
# print(srf_fi.get_weighted_mask())
# print(srf_fi.get_weighted_rf_center())
# import matplotlib.pyplot as plt
# f=plt.figure()
# ax=f.add_subplot(111)
# srf_fi.plot_rf(plot_axis=ax, tick_spacing=1)
# plt.show()
srf_fit = srf_fi.threshold(thr=0.4)
# print(srf_fit.get_weighted_rf_center())
assert (srf_fit.get_weighted_rf_center()[0] - 0.5 < 0.05)
srf2_fi = srf2_f.interpolate(ratio=2, method='linear')
# print(srf2_fi.get_weighted_mask())
# print(srf2_fi.get_weighted_rf_center())
assert (np.array_equal(srf_fi.get_weighted_mask(),
srf2_fi.get_weighted_mask()))
assert (abs(srf_fi.get_weighted_rf_center()[0] +
srf2_fi.get_weighted_rf_center()[0]) < 1e-10)
def test_SpatialReceptiveField_interpolate(self):
SRF = sca.SpatialReceptiveField(np.random.rand(5, 5),
np.arange(5)[::-1], np.arange(5))
SRF_i = SRF.interpolate(5)
assert (SRF_i.get_weighted_mask().shape == (20, 20))
def test_SpatialReceptiveField(self):
SRF = sca.SpatialReceptiveField(
np.arange(9).reshape((3, 3)), np.arange(3), np.arange(3))
assert (np.array_equal(SRF.weights, np.arange(1, 9)))
def test_SpatialReceptiveField_thresholdReceptiveField(self):
SRF = sca.SpatialReceptiveField(
np.arange(9).reshape((3, 3)), np.arange(3), np.arange(3))
thresholdedSRF = SRF.threshold(thr=4)
assert (np.array_equal(thresholdedSRF.weights, np.arange(4, 9)))
_, rf_off_new = dt.get_rf_properties(
srf=srf_off,
polarity='negative',
sigma=analysis_params['gaussian_filter_sigma_rf'],
interpolate_rate=analysis_params[
'interpolate_rate_rf'],
z_thr_abs=analysis_params['rf_z_thr_abs'],
z_thr_rel=analysis_params['rf_z_thr_rel'])
else:
raise ValueError
rf_on_mask = rf_on_new.get_weighted_mask()
rf_off_mask = rf_off_new.get_weighted_mask()
rf_onoff_new = sca.SpatialReceptiveField(
mask=np.max([rf_on_mask, rf_off_mask], axis=0),
altPos=rf_on_new.altPos,
aziPos=rf_on_new.aziPos,
sign='ON_OFF',
thr=analysis_params['rf_z_thr_abs'])
curr_s2_grp = s2_grp.create_group(roi_row['roi_n'])
rf_onoff_new.to_h5_group(curr_s2_grp)
curr_s1_on_grp = s1_on_grp.create_group(roi_row['roi_n'])
rf_on_new.to_h5_group(curr_s1_on_grp)
curr_s1_off_grp = s1_off_grp.create_group(roi_row['roi_n'])
rf_off_new.to_h5_group(curr_s1_off_grp)
# positive S1 ON
s1_on_df = subdf[(subdf['rf_{}_on_peak_z'.format(response_dir)] >=
analysis_params['rf_z_thr_abs'])