# </editor-fold>
# ----------------------------------------------------------------------------------------------------------------------
# ----------------------------------------------------------------------------------------------------------------------
# <editor-fold desc = VISUALISE
template_all = most_common_template_pair[1]
template_desi = most_common_template_pair[0]
template_all = template_info_all_nonMUA.iloc[19]['template number']
# Make topoplot of desimated probe
topoplot_desi = np.flipud(
np.reshape(
sh.peaktopeak(avg_templates_bs_desi[template_desi, :, :],
window_size=40)[4], (4, 4)))
# Make topoplot of interpolated full probe
interpolated_topoplot_all = sh.create_heatmap_image(
interpolated_avg_templates_all[template_all, :, :],
const_all.prb_file,
window_size=40,
bad_channels=None,
num_of_shanks=1,
rotate_90=False,
flip_lr=False,
flip_ud=False,
gridscale=10,
width=10,
height=10)[0]
min = data_used[template_all, :, :].min()
max = data_used[template_all, :, :].max()
for c in np.arange(data_used.shape[1]):
w = probe_all[c][1] / 155 + 0.35 / 15
h = probe_all[c][0] / 170 + 0.4 / 17
inset_axis.append(a3.inset_axes([w, h - 0.025 * h, 1 / 15, 1 / 17]))
inset_axis[-1].axis('off')
inset_axis[-1].set_ylim(min, max)
if c != 31:
inset_axis[-1].plot(data_used[template_all, c, :], c='k')
decimated_data_used = np.zeros((16, data_used.shape[2]))
for g in np.arange(len(const_deci.group_channels)):
decimated_data_used[g, :] = np.mean(
data_used[template_all, const_deci.group_channels[g], :], axis=0)
p2p_from_decimated_data_used = sh.peaktopeak(decimated_data_used, 40)[4]
reshaped_from_decimated_p2p = np.flipud(
np.reshape(p2p_from_decimated_data_used, (4, 4)))
f4 = plt.figure(4)
a4 = f4.add_subplot(111)
_ = a4.imshow(reshaped_from_decimated_p2p,
interpolation='bicubic',
vmin=reshaped_from_decimated_p2p.min(),
vmax=reshaped_from_decimated_p2p.max())
prb_file = join(const_deci.probe_layout_folder,
'probe_imec_256channels_decimated_file.txt')
probe_desi = sh.get_probe_geometry_from_prb_file(prb_file)[0]['geometry']
inset_axis = []
min = decimated_data_used.min()
# </editor-fold>
# ----------------------------------------------------------------------------------------------------------------------
# ----------------------------------------------------------------------------------------------------------------------
# <editor-fold desc = VISUALISE
template_all = most_common_template_pair[1]
template_desi = most_common_template_pair[0]
template_all = template_info_all_nonMUA.iloc[36]['template number']
# Make topoplot of desimated probe
topoplot_desi = np.flipud(
np.reshape(
sh.peaktopeak(avg_templates_bs_desi[template_desi, :, :],
window_size=40)[4], (4, 4)))
# Make topoplot of interpolated full probe
interpolated_topoplot_all = sh.create_heatmap_image(
interpolated_avg_templates_all[template_all, :, :],
const_all.prb_file,
window_size=40,
bad_channels=None,
num_of_shanks=1,
rotate_90=False,
flip_lr=False,
flip_ud=False,
gridscale=10,
width=10,
height=10)[0]
def plot_timesries_superimposed_full_and_desi(template_index):
a3.cla()
a4.cla()
template_all = template_info_all_nonMUA.iloc[template_index][
'template number']
cmap = cm_adj.cmap_center_point_adjust(cm.jet, [
smoothed_avg_templates_all[template_all, :, :].min(),
smoothed_avg_templates_all[template_all, :, :].max()
], -100)
smoothed_topoplot_all = sh.create_heatmap_image(
smoothed_avg_templates_all[template_all, :, :],
const_all.prb_file,
window_size=40,
bad_channels=None,
num_of_shanks=1,
rotate_90=False,
flip_lr=False,
flip_ud=False,
gridscale=10,
width=10,
height=10,
cmap=cmap)[0]
_ = a3.imshow(smoothed_topoplot_all)
inset_axis = []
min = data_used[template_all, :, :].min()
max = data_used[template_all, :, :].max()
for c in np.arange(data_used.shape[1]):
w = probe_all[c][1] / 155 + 0.35 / 15
h = probe_all[c][0] / 170 + 0.4 / 17
inset_axis.append(a3.inset_axes([w, h - 0.025 * h, 1 / 15, 1 / 17]))
inset_axis[-1].axis('off')
inset_axis[-1].set_ylim(min, max)
if c != 31:
inset_axis[-1].plot(data_used[template_all, c, :], c='k')
decimated_data_used = np.zeros((16, data_used.shape[2]))
for g in np.arange(len(const_deci.group_channels)):
decimated_data_used[g, :] = np.mean(
data_used[template_all, const_deci.group_channels[g], :], axis=0)
p2p_from_decimated_data_used = sh.peaktopeak(decimated_data_used, 40)[4]
reshaped_from_decimated_p2p = np.flipud(
np.reshape(p2p_from_decimated_data_used, (4, 4)))
_ = a4.imshow(reshaped_from_decimated_p2p,
interpolation='bicubic',
vmin=reshaped_from_decimated_p2p.min(),
vmax=reshaped_from_decimated_p2p.max(),
cmap=cmap)
inset_axis = []
min = data_used[template_all, channels_to_keep, :].min()
max = data_used[template_all, channels_to_keep, :].max()
for c in np.arange(len(channels_to_keep)):
w = probe_desi[c][1] / 4
h = probe_desi[c][0] / 4
inset_axis.append(a4.inset_axes([w, h, 1 / 4, 1 / 4]))
inset_axis[-1].axis('off')
inset_axis[-1].set_ylim(min, max)
inset_axis[-1].plot(decimated_data_used[c, :], c='k')
# </editor-fold>
# ----------------------------------------------------------------------------------------------------------------------
# ----------------------------------------------------------------------------------------------------------------------
# <editor-fold desc = VISUALISE BEST PEAK TO PEAK HEATMAPS
template_all = most_common_template_pair[1]
template_desi = most_common_template_pair[0]
template_all = template_info_all_nonMUA.iloc[44]['template number']
# Make topoplot of desimated probe
topoplot_desi = np.flipud(np.reshape(sh.peaktopeak(avg_templates_bs_desi[template_desi, :, :], window_size=40)[4], (4,4)))
# Make topoplot of interpolated full probe
interpolated_topoplot_all = sh.create_heatmap_image(interpolated_avg_templates_all[template_all, :, :], const_all.prb_file,
window_size=40, bad_channels=None, num_of_shanks=1, rotate_90=False,
flip_lr=False, flip_ud=False, gridscale=10, width=10, height=10)[0]
# Make topoplot of interpolated full probe smoothed
smoothed_topoplot_all = sh.create_heatmap_image(smoothed_avg_templates_all[template_all, :, :], const_all.prb_file,
window_size=40, bad_channels=None, num_of_shanks=1, rotate_90=False,
flip_lr=False, flip_ud=False, gridscale=10, width=10, height=10)[0]
# Show
f0 = plt.figure(0)
f0.add_subplot()