def draw_ground_truth_skcsd_3D(ax1, gtruth, skcsd, data,
gvmin, gvmax, t_plot):
ax1[2].set_title('Ground truth at t = %1.1f ms' %t_plot)
ax1[3].set_title('CSD at t = %1.1f ms' %t_plot)
for i in [2, 3]:
ax1[i].set_ylabel('x (um)')
ax1[i].set_xlabel('y (um)')
draw_morpho(ax1[i], morphology, extent, data.ele_pos)
pl.make_map_plot(ax1[2],
gtruth.sum(axis=(2, 3)),
extent=extent,
cmap='seismic_r',
vmax=gvmax,
vmin=gvmin,
alpha=0.5,
circles=True)
pl.make_map_plot(ax1[3],
skcsd.sum(axis=(2, 3)),
extent=extent,
cmap='seismic_r',
vmax=gvmax,
vmin=gvmin, alpha=0.5)
ele_pos,
n_src,
tolerance=tolerance,
xmin=-1000e-6,
xmax=1000e-6,
ymin=-1000e-6,
ymax=1000e-6)
cell_itself.distribute_srcs_3D_morph()
ground_truth_3D = cell_itself.transform_to_3D(ground_truth,
what="morpho")
ground_truth_t0 = ground_truth_3D[:, :, :, t0].sum(axis=2)
vmax, vmin = pl.get_min_max(ground_truth_t0)
morpho, extent = cell_itself.draw_cell2D(axis=2)
lambd = l/(2*(2*np.pi)**3*R**2*n_src)
fig, ax = plt.subplots(3, 3, figsize=(8, 20))
pl.make_map_plot(ax[0, 0], morpho, extent=extent)
pl.make_map_plot(ax[0, 0], ground_truth_t0, extent=extent, title="Ground truth", vmin=vmin, vmax=vmax, alpha=.75)
vmax, vmin = pl.get_min_max(ground_truth_t0)
for i, di in enumerate(data_dir):
data = utils.LoadData(di)
ele_pos = data.ele_pos/scale_factor
data.LFP = data.LFP/scale_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6]/scale_factor
ker = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
skcsd_seg = cell_itself.transform_to_segments(skcsd)
skcsd_snapshot = est_skcsd[:, :, :, t0 - tt:t0 + tt].sum(axis=(2, 3))
gt_snapshot = ground_truth_3D[:, :, :, t0 - tt:t0 + tt].sum(axis=(2, 3))
axfig22.imshow(skcsd_seg,
origin="lower",
interpolation="none",
vmin=gvmin,
vmax=gvmax,
cmap=plt.cm.bwr_r)
cax = pl.make_map_plot(ax4,
gt_snapshot,
vmin=vmin,
vmax=vmax,
extent=extent,
cmap=cmap,
alpha=.95,
ele_pos=ele_pos,
morphology=morpho)
ax2.set_yticklabels([])
ax3.set_yticklabels([])
ax2.set_xticklabels([])
ax3.set_xticklabels([])
cax2 = pl.make_map_plot(ax5,
skcsd_snapshot,
vmin=vmin,
vmax=vmax,
extent=extent,
zmax=zmax,
gdx=gdx,
gdy=gdy,
gdz=gdz)
if not len(ground_truth_grid):
ground_truth_grid = k.cell.transform_to_3D(ground_truth,
what="morpho")
ground_truth_t1 = ground_truth_grid[:, :, :, t1].sum(axis=1).T
ground_truth_t2 = ground_truth_grid[:, :, :, t2].sum(axis=1).T
est_skcsd = k.values(estimate='CSD')
est_skcsd_t1 = est_skcsd[:, :, :, t1].sum(axis=1).T
est_skcsd_t2 = est_skcsd[:, :, :, t2].sum(axis=1).T
est_kcsd = kcsd.values(estimate='CSD')
est_kcsd_pot = kcsd.values(estimate='POT')
if i == 0:
cax = pl.make_map_plot(ax[1, 2], ground_truth_t1)
cax = pl.make_map_plot(ax[2, 2], ground_truth_t2)
cax = pl.make_map_plot(ax[1, 3], est_skcsd_t1)
cax = pl.make_map_plot(ax[2, 3], est_skcsd_t2)
else:
cax = pl.make_map_plot(ax[0, 0], est_kcsd_pot[:, :, :,
t1].sum(axis=1))
cax = pl.make_map_plot(ax[0, 1], est_kcsd[:, :, :, t1].sum(axis=1))
cax = pl.make_map_plot(ax[0, 2], ground_truth_t1)
cax = pl.make_map_plot(ax[0, 3], est_skcsd_t1)
cax = pl.make_map_plot(ax[1, 0], est_kcsd_pot[:, :, :,
t1].sum(axis=1))
cax = pl.make_map_plot(ax[1, 1], est_kcsd[:, :, :, t1].sum(axis=1))
cax = pl.make_map_plot(ax[2, 0],
est_kcsd_pot[:, :, :, t2].sum(axis=1),
extent=[-200, 200, -200, 600])
t1 = int(42/dt)
t2 = int(5/dt)
atstart = t2
atstop = int(t2 + 10/dt)
simulation_paths = []
data_paths = []
skcsd_grid = []
skcsd_random = []
fig, ax = plt.subplots(1, 3)
fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(fname)
vmax, vmin = pl.get_min_max(ground_truth[:, atstart:atstop])
pl.make_map_plot(ax[0],
ground_truth[:, atstart:atstop],
yticklabels=[x for x in range(0, 86, 15)],
fig=fig,
title="Ground truth",
ylabel='#segment',
sinksource=True)
for i, datd in enumerate(data_dir):
data = utils.LoadData(datd)
ele_pos = data.ele_pos/scaling_factor
data.LFP = data.LFP/scaling_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6]/scaling_factor
k = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
data_dir.append(c.return_paths_skCSD_python())
else:
new_dir = os.path.join('simulation', fname)
data_dir.append(new_dir)
seglen = np.loadtxt(os.path.join(data_dir[0], 'seglength'))
ground_truth = np.loadtxt(os.path.join(data_dir[0], 'membcurr'))
ground_truth = ground_truth / seglen[:, None] * 1e-3
gvmax, gvmin = pl.get_min_max(ground_truth)
fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(fname)
data_paths = []
fig, ax = plt.subplots(4, 1)
xticklabels = list(np.linspace(0, 800, 5))
yticklabels = list(np.linspace(0, 52, 5))
pl.make_map_plot(ax[0], ground_truth, alpha=1., vmin=gvmin, vmax=gvmax)
for i, datd in enumerate(data_dir):
l = 0
data = utils.LoadData(datd)
ele_pos = data.ele_pos / scaling_factor
data.LFP = data.LFP / scaling_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6] / scaling_factor
k = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
R_init=R,
exact=True,
data_dir.append(c.return_paths_skCSD_python())
else:
new_dir = os.path.join('simulation', fname)
data_dir.append(new_dir)
seglen = np.loadtxt(os.path.join(data_dir[0], 'seglength'))
ground_truth = np.loadtxt(os.path.join(data_dir[0], 'membcurr'))
ground_truth = ground_truth/seglen[:, None]*1e-3
gvmax, gvmin = pl.get_min_max(ground_truth)
fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(fname)
data_paths = []
fig, ax = plt.subplots(4, 1)
xticklabels = list(np.linspace(0, 800, 5))
yticklabels = list(np.linspace(0, 52, 5))
pl.make_map_plot(ax[0], ground_truth, alpha=1., vmin=gvmin, vmax=gvmax)
for i, datd in enumerate(data_dir):
l = 0
data = utils.LoadData(datd)
ele_pos = data.ele_pos/scaling_factor
data.LFP = data.LFP/scaling_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6]/scaling_factor
k = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
R_init=R,
exact=True)
cell_itself = sKCSDcell(morphology,
ele_pos,
n_src,
tolerance=tolerance,
xmin=-1000e-6,
xmax=1000e-6,
ymin=-1000e-6,
ymax=1000e-6)
ground_truth_3D = cell_itself.transform_to_3D(ground_truth, what="morpho")
ground_truth_t0 = ground_truth_3D[:, :, :, t0].sum(axis=2)
vmax, vmin = pl.get_min_max(ground_truth_t0)
morpho, extent = cell_itself.draw_cell2D(axis=2)
extent = [extent[-2], extent[-1], extent[0], extent[1]]
lambd = l / (2 * (2 * np.pi)**3 * R**2 * n_src)
fig, ax = plt.subplots(3, 3, figsize=(8, 20))
pl.make_map_plot(ax[0, 0], morpho, extent=extent, circles=False)
pl.make_map_plot(ax[0, 0],
ground_truth_t0,
extent=extent,
title="Ground truth",
vmin=vmin,
vmax=vmax,
alpha=.75)
vmax, vmin = pl.get_min_max(ground_truth_t0)
for i, di in enumerate(data_dir):
data = utils.LoadData(di)
ele_pos = data.ele_pos / scale_factor
data.LFP = data.LFP / scale_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6] / scale_factor
R_init=R,
skmonaco_available=False)
est_skcsd = ker.values(estimate='CSD',
transformation='segments')
outs[i, j, k] = sKCSD_utils.L1_error(ground_truth, est_skcsd)
print(outs[i, j, k])
fig, ax = plt.subplots(1, 4, sharey=True)
vmax = outs.max()
vmin = outs.min()
for i, ax_i in enumerate(ax):
title = "M = %d" % n_srcs[i]
if not i:
pl.make_map_plot(ax_i,
outs[i],
yticklabels=y_ticklabels,
xticklabels=x_ticklabels,
vmin=vmin,
vmax=vmax,
title=title,
cmap='gray')
elif i < 3:
pl.make_map_plot(ax_i,
outs[i],
xticklabels=x_ticklabels,
vmin=vmin,
vmax=vmax,
title=title,
cmap='gray')
else:
pl.make_map_plot(ax_i,
outs[i],
xticklabels=x_ticklabels,
cell_object = sKCSDcell(morphology, ele_pos, n_src)
est_skcsd = cell_itself[i].transform_to_3D(skcsd)
est_skcsd_t1 = est_skcsd[:, :, :, t1].sum(axis=1)
est_skcsd_t2 = est_skcsd[:, :, :, t2].sum(axis=1)
if i == 0: # wrong plane
for j in [1, 2]:
for k in [2, 3]:
ax[j, k].imshow(morpho, extent=extent, origin='lower', aspect="auto", alpha=1.)
for z in ele_pos:
pos_x, pos_y = z[2], z[0]
ax[j, k].text(pos_x, pos_y, '*',
ha="center", va="center", color="k", fontsize=3)
cax = pl.make_map_plot(ax[1, 2], ground_truth_t1, extent=extent, alpha=.95, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[2, 2], ground_truth_t2, extent=extent, alpha=.95, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[1, 3], est_skcsd_t1, extent=extent, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[2, 3], est_skcsd_t2, extent=extent, vmin=vmin, vmax=vmax) # ok
for j in [1, 2]:
for k in [0, 1]:
ax[j, k].imshow(morpho_kcsd, extent=extent_kcsd, origin='lower', aspect="auto", alpha=1)
for z in ele_pos:
pos_x, pos_y = z[2], z[1]
ax[j, k].text(pos_x, pos_y, '*',
ha="center", va="center", color="k", fontsize=3)
ax[1, 0].imshow(est_kcsd_pot[:, :, :, t1].sum(axis=0),
cmap=plt.cm.viridis,
extent=extent_kcsd,
origin='lower',
skcsd, pot, cell_obj = utils.load_sim(path)
est_skcsd = cell_itself[i].transform_to_3D(skcsd)
est_skcsd_t1 = est_skcsd[:, :, :, t1].sum(axis=1)
est_skcsd_t2 = est_skcsd[:, :, :, t2].sum(axis=1)
if i == 0: # wrong plane
for j in [1, 2]:
for k in [2, 3]:
ax[j, k].imshow(morpho, extent=extent, origin='lower', aspect="auto", alpha=0.95)
for z in ele_pos:
pos_x, pos_y = 1e6*z[2], 1e6*z[0]
ax[j, k].text(pos_x, pos_y, '*',
ha="center", va="center", color="k", fontsize=3)
cax = pl.make_map_plot(ax[1, 2], ground_truth_t1, extent=extent, alpha=.95, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[2, 2], ground_truth_t2, extent=extent, alpha=.95, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[1, 3], est_skcsd_t1, extent=extent, vmin=vmin, vmax=vmax)
cax = pl.make_map_plot(ax[2, 3], est_skcsd_t2, extent=extent, vmin=vmin, vmax=vmax) # ok
for j in [1, 2]:
for k in [0, 1]:
ax[j, k].imshow(morpho_kcsd, extent=extent_kcsd, origin='lower', aspect="auto", alpha=0.95)
for z in ele_pos:
pos_x, pos_y = 1e6*z[2], 1e6*z[1]
ax[j, k].text(pos_x, pos_y, '*',
ha="center", va="center", color="k", fontsize=3)
ax[1, 0].imshow(est_kcsd_pot[:, :, :, t1].sum(axis=0),
cmap=plt.cm.viridis,
extent=extent_kcsd,
origin='lower',
skcsd_seg = cell_itself.transform_to_segments(skcsd)
skcsd_snapshot = est_skcsd[:, :, :, t0-tt:t0+tt].sum(axis=(2, 3))
gt_snapshot = ground_truth_3D[:, :, :, t0-tt:t0+tt].sum(axis=(2, 3))
axfig22.imshow(skcsd_seg,
origin="lower",
interpolation="none",
vmin=gvmin,
vmax=gvmax,
cmap=plt.cm.bwr_r )
cax = pl.make_map_plot(ax4,
gt_snapshot,
vmin=vmin,
vmax=vmax,
extent=extent,
cmap=cmap,
alpha=.95,
ele_pos=ele_pos,
morphology=morpho)
ax2.set_yticklabels([])
ax3.set_yticklabels([])
ax2.set_xticklabels([])
ax3.set_xticklabels([])
cax2 = pl.make_map_plot(ax5,
skcsd_snapshot,
t1 = int(42/dt)
t2 = int(5/dt)
atstart = t2
atstop = int(t2 + 10/dt)
simulation_paths = []
data_paths = []
skcsd_grid = []
skcsd_random = []
fig, ax = plt.subplots(1, 3)
fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(fname)
vmax, vmin = pl.get_min_max(ground_truth[:, atstart:atstop])
pl.make_map_plot(ax[0],
ground_truth[:, atstart:atstop],
yticklabels=[x for x in range(0, 86, 15)],
fig=fig,
title="Ground truth",
ylabel='#segment',
sinksource=True)
for i, datd in enumerate(data_dir):
data = utils.LoadData(datd)
ele_pos = data.ele_pos/scaling_factor
data.LFP = data.LFP/scaling_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6]/scaling_factor
k = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
est_skcsd = ker.values(estimate='CSD',
transformation='segments')
outs[i, j, k] = sKCSD_utils.L1_error(ground_truth,
est_skcsd)
print(outs[i, j, k], est_skcsd.min(), est_skcsd.max(), ground_truth.min(), ground_truth.max(), n_src, l, R)
fig, ax = plt.subplots(1, 4, sharey=True)
vmax = outs.max()
vmin = outs.min()
for i, ax_i in enumerate(ax):
title = "M = %d" % n_srcs[i]
if not i:
pl.make_map_plot(ax_i,
outs[i],
yticklabels=y_ticklabels,
xticklabels=x_ticklabels,
vmin=vmin,
vmax=vmax,
title=title,
cmap='gray')
elif i < 3:
pl.make_map_plot(ax_i,
outs[i],
xticklabels=x_ticklabels,
vmin=vmin,
vmax=vmax,
title=title,
cmap='gray')
else:
pl.make_map_plot(ax_i,
outs[i],
xticklabels=x_ticklabels,
n_src,
tolerance=2e-6,
xmin=-120e-6,
xmax=120e-6,
zmin=-50e-6,
zmax=550e-6)
ground_truth_grid = cell.transform_to_3D(ground_truth, what="morpho")
vmax, vmin = pl.get_min_max(ground_truth_grid[:, :, :, t1].sum(axis=1))
gdt1 = ground_truth_grid[:, :, :, t1].sum(axis=1)
morpho, extent = cell.draw_cell2D(axis=1)
extent = [extent[-2], extent[-1], extent[0], extent[1]]
new_ele_pos = np.array([ele_pos[:, 2], ele_pos[:, 0]]).T
pl.make_map_plot(ax[0, 0],
gdt1,
vmin=vmin,
vmax=vmax,
extent=extent,
alpha=.9,
morphology=morpho,
ele_pos=new_ele_pos)
snrs = []
L1 = []
for i, nl in enumerate(noise_levels):
if nl:
noise = numpy.random.normal(scale=std / nl, size=shape)
snr = np.round((new_LFP.var()**.5 / noise.var()**.5))
else:
noise = 0
snr = 0
shape = data.LFP.shape
cell = sKCSDcell(morphology, ele_pos, n_src,
tolerance=2e-6,
xmin=-120e-6, xmax=120e-6,
zmin=-50e-6, zmax=550e-6)
cell.distribute_srcs_3D_morph()
ground_truth_grid = cell.transform_to_3D(ground_truth, what="morpho")
vmax, vmin = pl.get_min_max(ground_truth_grid[:, :, :, t1].sum(axis=1))
gdt1 = ground_truth_grid[:,:,:,t1].sum(axis=1)
morpho, extent = cell.draw_cell2D(axis=1)
pl.make_map_plot(ax[0, 0],
gdt1,
vmin=vmin,
vmax=vmax,
extent=extent,
alpha=.9,
morphology=morpho,
ele_pos=ele_pos)
snrs = []
L1 = []
for i, nl in enumerate(noise_levels):
if nl:
noise = numpy.random.normal(scale=std/nl, size=shape)
snr = np.round((new_LFP.var()**.5/noise.var()**.5))
else:
noise = 0
snr = 0
snrs.append(snr)
data_dir.append(c.return_paths_skCSD_python())
else:
new_dir = os.path.join('simulation', fname)
data_dir.append(new_dir)
seglen = np.loadtxt(os.path.join(data_dir[0], 'seglength'))
ground_truth = np.loadtxt(os.path.join(data_dir[0], 'membcurr'))
ground_truth = ground_truth / seglen[:, None] * 1e-3
gvmin, gvmax = pl.get_min_max(ground_truth)
fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(fname)
data_paths = []
fig, ax = plt.subplots(4, 1)
xticklabels = list(np.linspace(0, 800, 5))
yticklabels = list(np.linspace(0, 52, 5))
pl.make_map_plot(ax[0], ground_truth)
for i, datd in enumerate(data_dir):
l = 0
data = utils.LoadData(datd)
ele_pos = data.ele_pos / scaling_factor
data.LFP = data.LFP / scaling_factor_LFP
morphology = data.morphology
morphology[:, 2:6] = morphology[:, 2:6] / scaling_factor
sKCSD.skmonaco_available = False
k = sKCSD(ele_pos,
data.LFP,
morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
R_init=R,
R_init=R,
dist_table_density=50,
skmonaco_available=False)
if not i and not j:
ground_truth_3D = ker.cell.transform_to_3D(ground_truth,
what="morpho")
vmax, vmin = pl.get_min_max(ground_truth_3D)
ker_dir = data_dir + '_R_%f_lambda_%f' % (R, lambd)
morpho, extent = ker.cell.draw_cell2D(axis=2)
est_skcsd = ker.values()
fig, ax = plt.subplots(1, 2)
if sys.version_info < (3, 0):
path = os.path.join(ker_dir, "preprocessed_data/Python_2")
else:
path = os.path.join(ker_dir, "preprocessed_data/Python_3")
if not os.path.exists(path):
print("Creating", path)
os.makedirs(path)
utils.save_sim(path, ker)
pl.make_map_plot(ax[1], morpho, extent=extent)
pl.make_map_plot(ax[1],
est_skcsd[:, :, :, t0].sum(axis=(2)),
extent=extent,
vmin=vmin,
vmax=vmax)
pl.make_map_plot(ax[0], morpho, extent=extent)
pl.make_map_plot(ax[0],
ground_truth_3D[:, :, :, t0].sum(axis=(2)),
extent=extent)
plt.show()
extent=extent,
origin='lower',
aspect="auto",
alpha=0.95)
for z in ele_pos:
pos_x, pos_y = 1e6 * z[2], 1e6 * z[0]
ax[j, k].text(pos_x,
pos_y,
'*',
ha="center",
va="center",
color="k",
fontsize=3)
cax = pl.make_map_plot(ax[1, 2],
ground_truth_t1,
extent=extent,
alpha=.95,
vmin=vmin,
vmax=vmax)
cax = pl.make_map_plot(ax[2, 2],
ground_truth_t2,
extent=extent,
alpha=.95,
vmin=vmin,
vmax=vmax)
cax = pl.make_map_plot(ax[1, 3],
est_skcsd_t1,
extent=extent,
vmin=vmin,
vmax=vmax)
cax = pl.make_map_plot(ax[2, 3],
est_skcsd_t2,