from __future__ import division, print_function
import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from kcsd import sKCSD
import kcsd.utility_functions as utils
import kcsd.validation.plotting_functions as pl
import sKCSD_utils
n_src = 512
if __name__ == '__main__':
fname_base = "Figure_8"
fig_dir = 'Figures'
fig_name = sKCSD_utils.make_fig_names(fname_base)
tstop = 850
scale_factor = 1000**2
scale_factor_LFP = 1000
R_inits = np.array([(2**(i - .5)) / scale_factor for i in range(3, 9)])
lambdas = np.array([(10**(-i)) for i in range(5)])
colnb = 10
rownb = 10
fname = '%s_rows_%d' % (fname_base, rownb)
dt = .5
if sys.version_info < (3, 0):
c = sKCSD_utils.simulate(fname,
morphology=6,
tstop=tstop,
seed=1988,
weight=0.04,
n_syn=1000,
ax = []
for i in range(2):
for j in range(2, 5):
ax.append(plt.subplot(gs[i, j]))
cax = ax_gt.imshow(ground_truth,
extent=[0, tstop, 1, 52],
origin='lower',
aspect='auto',
cmap='seismic_r',
vmax=gvmax,
vmin=gvmin)
ax_gt.set_title('Ground truth')
ax_gt.set_xlabel('time (s)')
ax_gt.set_ylabel('#segment')
new_fname = fname_base + '.png'
fig_name = sKCSD_utils.make_fig_names(new_fname)
vmax, vmin = pl.get_min_max(ground_truth)
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,
R_init=R,
skcsd.sum(axis=(2, 3)),
extent=extent,
cmap='seismic_r',
vmax=gvmax,
vmin=gvmin, alpha=0.5)
if __name__ == '__main__':
fname_base = "Figure_complex"
data_dir = simulate()
fig, ax_somav, ax = make_figure()
ground_truth, data, time, somav = read_in_data(data_dir)
toplot = np.argmax(somav)
gvmax, gvmin = pl.get_min_max(ground_truth[:, toplot])
new_fname = fname + '.png'
fig_name = sKCSD_utils.make_fig_names(new_fname)
cell_itself = make_larger_cell(data, n_src)
morphology, extent = cell_itself.draw_cell2D()
extent = [ex*1e6 for ex in extent]
draw_somav(ax_somav, time, somav)
k = sKCSD(data.ele_pos,
data.LFP,
data.morphology,
n_src_init=n_src,
src_type='gauss',
lambd=lambd,
exact=True,
R_init=R,
sigma=0.3)
path = os.path.join(data_dir, 'lambda_%f_R_%f_n_src_%d' % (lambd, R, n_src))
if sys.version_info < (3, 0):
2:{'colnb':5, 'rownb': 5, 'xmin':-400, 'xmax':400, 'ymin':-400, 'ymax':400},
3:{'colnb':5, 'rownb': 5, 'xmin':-800, 'xmax':800, 'ymin':-800, 'ymax':800},
4:{'colnb':9, 'rownb': 9, 'xmin':-800, 'xmax':800, 'ymin':-800, 'ymax':800},
5:{'colnb':9, 'rownb': 9, 'xmin':-400, 'xmax':400, 'ymin':-400, 'ymax':400},
6:{'colnb':21, 'rownb': 21, 'xmin':-400, 'xmax':400, 'ymin':-400, 'ymax':400},
}
titles = ['IED 50 um',
'IED 100 um',
'IED 200 um',
'IED 400 um',
'IED 200 um',
'IED 100 um',
'IED 40 um']
if __name__ == '__main__':
fname_base = "Figure_10"
fig_name = sKCSD_utils.make_fig_names(fname_base)
tstop = 250
scale_factor = 1000**2
scale_factor_LFP = 1000
R = 64e-6/np.sqrt(2)
l = .1
data_dir = []
for i in range(7):
colnb = different_trials_parameters[i]['colnb']
rownb = different_trials_parameters[i]['rownb']
xmin = different_trials_parameters[i]['xmin']
xmax = different_trials_parameters[i]['xmax']
ymin = different_trials_parameters[i]['ymin']
ymax = different_trials_parameters[i]['ymax']
c = sKCSD_utils.simulate(fname_base,
import matplotlib.pyplot as plt
import sys
import os
from kcsd import sKCSD, KCSD3D, sKCSDcell
from kcsd import sKCSD_utils as utils
import kcsd.validation.plotting_functions as pl
import sKCSD_utils
n_src = 512
R = 16e-6/2**.5
lambd = .1/((2*(2*np.pi)**3*R**2*n_src))
dt = 0.5
n = 100 # dist_table_density for kCSD
if __name__ == '__main__':
fname_base = "Figure_5"
fig_name = sKCSD_utils.make_fig_names("Figure_5.png")
tstop = 70
scaling_factor = 1000**2
scaling_factor_LFP = 1000
rownb = [16, 4]
data_dir = []
colnb = [4, 16]
lfps = []
xmax = [100, 500]
ymax = [500, 100]
cell_itself = []
for i, electrode_orientation in enumerate([1, 2]):
fname = fname_base
c = sKCSD_utils.simulate(fname,
morphology=2,
import matplotlib.pyplot as plt
import sys
import os
from kcsd import sKCSD, KCSD3D, sKCSDcell
import kcsd.utility_functions as utils
import kcsd.validation.plotting_functions as pl
import sKCSD_utils
n_src = 512
R = 16e-6/2**.5
lambd = .1/((2*(2*np.pi)**3*R**2*n_src))
dt = 0.5
n = 100 # dist_table_density for kCSD
if __name__ == '__main__':
fname_base = "Figure_5"
fig_name = sKCSD_utils.make_fig_names("Figure_5.png")
tstop = 70
scaling_factor = 1000**2
scaling_factor_LFP = 1000
rownb = [16, 4]
data_dir = []
colnb = [4, 16]
lfps = []
xmax = [100, 500]
ymax = [500, 100]
cell_itself = []
morpho = []
extent = []
for i, electrode_orientation in enumerate([1, 2]):
fname = fname_base
