# To run this code you must download the data folder
# or run figure9.m.
import warnings
warnings.filterwarnings("ignore")
import scipy.io as sio
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.gridspec as gridspec
from matplotlib.font_manager import FontProperties
from set_style import set_style
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
set_style('article', w=1, h=3)
tableau10cb = np.array([(0,107,164), (95,158,209), (171,171,171), (255,128,14), (89,89,89), (200,82,0)])/255.
fig, axarr = plt.subplots(3,3)
ax1 = axarr[0,1]
ax2 = axarr[1,0]
ax3 = axarr[1,1]
ax4 = axarr[1,2]
ax5 = axarr[2,0]
ax6 = axarr[2,1]
ax7 = axarr[2,2]
### A ###
data = sio.loadmat('../data/figure9/figure9_a')
dq_values = data['dq_values'][0]
dcut_values = data['dcut_values'][0]
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import matplotlib.pyplot as plt
from set_style import set_style
set_style('default', w=1, h=2)
fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2)
data = np.load('../data/figureS1.npz')
t = data['t_fig3']
av_I_cap_sn_fig3 = data['av_I_cap_sn_fig3']
av_I_leak_sn_fig3 = data['av_I_leak_sn_fig3']
av_I_pump_sn_fig3 = data['av_I_pump_sn_fig3']
av_I_Na_sn_fig3 = data['av_I_Na_sn_fig3']
av_I_DR_sn_fig3 = data['av_I_DR_sn_fig3']
av_I_stim_sn_fig3 = data['av_I_stim_sn_fig3']
av_I_cap_dn_fig3 = data['av_I_cap_dn_fig3']
av_I_leak_dn_fig3 = data['av_I_leak_dn_fig3']
av_I_pump_dn_fig3 = data['av_I_pump_dn_fig3']
av_I_AHP_dn_fig3 = data['av_I_AHP_dn_fig3']
av_I_Ca_dn_fig3 = data['av_I_Ca_dn_fig3']
av_I_KC_dn_fig3 = data['av_I_KC_dn_fig3']
av_I_cap_sg_fig3 = data['av_I_cap_sg_fig3']
av_I_leak_sg_fig3 = data['av_I_leak_sg_fig3']
av_I_pump_sg_fig3 = data['av_I_pump_sg_fig3']
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import matplotlib.pyplot as plt
from set_style import set_style
set_style('default', w=1, h=3.5)
fig, [ax1, ax2, ax3, ax4, ax5] = plt.subplots(5, 1)
data = np.load('../data/figure3.npz')
t = data['t']
phi_msn = data['phi_msn']
phi_mdn = data['phi_mdn']
phi_msg = data['phi_msg']
phi_mdg = data['phi_mdg']
Na_se = data['cNa_se']
K_se = data['cK_se']
Cl_se = data['cCl_se']
Ca_se = data['cCa_se']
Na_de = data['cNa_de']
K_de = data['cK_de']
Cl_de = data['cCl_de']
Ca_de = data['cCa_de']
V_sn = data['V_sn']
V_se = data['V_se']
V_sg = data['V_sg']
V_dn = data['V_dn']
# To run this code, you must download the data folder
# or first run figure3.m.
import warnings
warnings.filterwarnings("ignore")
import scipy.io as sio
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
import matplotlib.patches as mpatches
from set_style import set_style
set_style('article', w=1, h=2.5)
filename = np.array([[
'../data/figure4/bias_d', '../data/figure5/std_d', '../data/figure6/rmse_d'
], [
'../data/figure4/bias_e', '../data/figure5/std_e', '../data/figure6/rmse_e'
], [
'../data/figure4/bias_f', '../data/figure5/std_f', '../data/figure6/rmse_f'
], ['../data/figure3/bias', '../data/figure3/std', '../data/figure3/rmse']])
panel = np.array([['A', 'B', 'C'], ['D', 'E', 'F'], ['G', 'H', 'I'],
['J', 'K', 'L']])
fig, axarr = plt.subplots(4, 3)
# BIAS
for i in range(0, 4):
j = 0
