l_std_ind = 0
model_ind = 0
par1['w_frac'] = w_frac[f_ind]
par1['CD'] = cd[cd_ind]
par1['k_std'] = k_std[k_std_ind]
par1['l_std'] = l_std[l_std_ind]
par1['modeltype'] = models[model_ind]
obs_new = np.empty([X2, X3, 6, 2])
obs_new[:, :, :, :] = obs[f_ind, cd_ind, :, :, l_std_ind, k_std_ind,
model_ind, :, :2]
figs = g.test_function_syst(obs_new,
par1,
g1_std,
g2_std * par1['td'],
vec=range(len(g1_std)))
u = 1
for fig in figs: # note that test_function_syst gives back daughter plot first, then mother plot.
fig.savefig('./model15_figs/model' + str(par1['modeltype']) +
'syst_test_' + celltype[u] + '_lstd' + str(l_std_ind) + '_cd' +
str(cd_ind) + '_kstd' + str(k_std_ind) + '_f' + str(f_ind) +
'.eps',
bbox_inches='tight',
dpi=fig.dpi)
u += -1
it = [w_frac, cd, g1_std, g2_std, k_std, l_std]
list_it = ['w_frac', 'CD', 'g1_thresh_std', 'g2_std', 'k_std', 'l_std']
#!/usr/bin/env python
import numpy as np
import growth_simulation_dilution_asymmetric as g
model1_data = np.load('whi5_noisy_adder_discrgen_tree_cd_75_K_1.npy')
g1_std = np.linspace(0.0, 0.62, 32)
g2_std = np.linspace(0.0, 0.62, 32)
if len(g1_std) != model1_data.shape[0] or len(g2_std) != model1_data.shape[1]:
raise ValueError('Check your simulation data')
par1 = dict([('g1_std', 0.0), ('g2_std', 0.05), ('g1_thresh_std', 0.05), ('nstep', 1200), ('dt', 0.01), ('t_delay', 0.0) \
, ('initiator', 0), ('CD', 0.75), ('num_gen', 9), ('K', 1.0), ('td', 1.0), ('modeltype', 1), ('mothervals', 0)])
par1[
'modeltype'] = 1 # keeps track of the model number we are looking at. Number zero is for a noiseless Whi5 adder,
# while 1 is for a noisy Whi5 adder
vec = [0, 7, 15, 23, 31] # selects the g1_std values which will be used
fig1, fig2 = g.test_function_syst(model1_data, par1, g1_std, g2_std, vec)
fig1.savefig('tree_discrgen_model1_CD_075_k_1_daughters.eps', dpi=fig1.dpi)
fig2.savefig('tree_discrgen_model1_CD_075_k_1_mothers.eps', dpi=fig2.dpi)