def vari(lista):
mean = 1. * sum(lista) / len(lista)
return (sum([(x - mean)**2
for x in lista]) / (len(lista) - 1)) / len(lista)
if __name__ == '__main__':
#f_2 = open(res_file,'w')
#f_2.write('Paradigm, seed, time above lower, time above upper\n')
f_2 = open(res_file, 'w')
f_2.write('paradigm, seed, t>l_t,t>u_t\n')
st = f.make_st_dendrite(
'/home/asia/NeuroRD/new_model_half_spine_neck_four_times_longer_diff_PDE4/Model_one_short_dendrite_PKAc_times_3_switching_L_pump_neurogranin_1.5_x_AC_PDE4_ave__runtime_900000-all_species-conc.txt_concentrations_'
+ ending,
epac_mean=True)
# fig = plt.figure()
# ax = []
# titles = ['pCK','PKA','Epac']
# for i in range(3):
# ax.append(fig.add_subplot(3,1,i+1))
# ax[i].plot(st[i])
# ax[i].set_title(titles[i])
for j, fbasal in enumerate(basal_list):
flist = []
seeds = reg_seeds
for seed in seeds:
flist.append(fbasal + seed + add + ending)
'Signature_components_predictions'
]
paradigms = [config.blocked_PKA, config.avramas, config.predictions]
window = config.window
endi = ['spine', 'dendrite']
if __name__ == '__main__':
matplotlib.rcParams['axes.linewidth'] = .5
matplotlib.rcParams['lines.linewidth'] = .5
matplotlib.rcParams['patch.linewidth'] = .5
st = []
st.append([])
st.append([])
st[0].extend(f.make_st_spine(config.steady_state + config.ending[0]))
st[1].extend(f.make_st_dendrite(config.steady_state + config.ending[1]))
for i, par in enumerate(paradigms):
print out_name[i]
fig = plt.figure(figsize=(5.4, 8.))
plt.rc('legend', **{'fontsize': 6})
ax = []
ax.append(fig.add_subplot(3, 2, 1))
ax.append(fig.add_subplot(3, 2, 2))
ax.append(fig.add_subplot(3, 2, 3))
ax.append(fig.add_subplot(3, 2, 4))
ax.append(fig.add_subplot(3, 2, 5))
ax.append(fig.add_subplot(3, 2, 6))
if par == config.blocked_PKA:
\hline
'''
p_value_high = {'LFS':'1','ISO':'0.0006','HFS':'1','4xHFS-3s':'0.0416','4xHFS-80s':'0.0065','ISO+HFS':'<.0001','ISO+LFS':'<.0001','HFS no PKA':'1','4xHFS-3s no PKA':'0.0003','4xHFS-80s no PKA':'0.4065','ISO+HFS no PKA':'0.0119','ISO+LFS no PKA':'1','Carvedilol+HFS':'0.7122','Carvedilol+LFS':'1','Propranolol+4xHFS':'0.0134','ICI-118551+4xHFS':'0.1505'}
p_value_low = {'LFS':'1','ISO':'0.0006','HFS':'1','4xHFS-3s':'0.0488','4xHFS-80s':'0.0117','ISO+HFS':'<.0001','ISO+LFS':'<.0001','HFS no PKA':'1','4xHFS-3s no PKA':'<.0001','4xHFS-80s no PKA':'0.8982','ISO+HFS no PKA':'0.0072','ISO+LFS no PKA':'1','Carvedilol+HFS':'1.0','Carvedilol+LFS':'1','Propranolol+4xHFS':'0.1300','ICI-118551+4xHFS':'0.5153'}
def vari(lista):
mean = 1.*sum(lista)/len(lista)
return sum([(x-mean)**2 for x in lista] )/(len(lista)-1)
if __name__ == '__main__':
f_2 = open(res_file,'w')
f_2.write('Paradigm, seed, time above lower, time above upper\n')
st = f.make_st_dendrite(config.steady_state+ending)
for j, fbasal in enumerate(basal_list):
flist = []
seeds = reg_seeds
sseeds = reg_sseeds
for seed in seeds:
flist.append(fbasal+seed+add+ending)
outs_low = []
outs_high = []
l = 0
h = 0
for i,fname in enumerate(flist):
\hline
'''
p_value_high = {'LFS':'1','ISO':'0.0006','HFS':'1','4xHFS-3s':'0.0416','4xHFS-80s':'0.0065','ISO+HFS':'<.0001','ISO+LFS':'<.0001','HFS no PKA':'1','4xHFS-3s no PKA':'0.0003','4xHFS-80s no PKA':'0.4065','ISO+HFS no PKA':'0.0119','ISO+LFS no PKA':'1','Carvedilol+HFS':'1.5122','Carvedilol+LFS':'1','Propranolol+4xHFS':'0.0134','ICI-118551+4xHFS':'0.1669'}
p_value_low = {'LFS':'1','ISO':'0.0006','HFS':'1','4xHFS-3s':'0.0488','4xHFS-80s':'0.0117','ISO+HFS':'<.0001','ISO+LFS':'<.0001','HFS no PKA':'1','4xHFS-3s no PKA':'<.0001','4xHFS-80s no PKA':'0.8982','ISO+HFS no PKA':'0.0072','ISO+LFS no PKA':'1','Carvedilol+HFS':'1.0','Carvedilol+LFS':'1','Propranolol+4xHFS':'0.1300','ICI-118551+4xHFS':'0.2851'}
def vari(lista):
mean = 1.*sum(lista)/len(lista)
return (sum([(x-mean)**2 for x in lista] )/(len(lista)-1))/len(lista)
if __name__ == '__main__':
#f_2 = open(res_file,'w')
#f_2.write('Paradigm, seed, time above lower, time above upper\n')
st = f.make_st_dendrite('Model_one_short_dendrite_PKAc_times_3_switching_L_pump_neurogranin_2.0_x_AC_PDE4_ave_'+config.ending[1],epac_mean=True)
# fig = plt.figure()
# ax = []
# titles = ['pCK','PKA','Epac']
# for i in range(3):
# ax.append(fig.add_subplot(3,1,i+1))
# ax[i].plot(st[i])
# ax[i].set_title(titles[i])
for j, fbasal in enumerate(basal_list):
lista = glob.glob(fbasal+'*')
new_list = [new_name for new_name in lista if new_name.endswith(config.ending[1]) and 'Epac' not in new_name and 'ave' not in new_name]
if fbasal == 'Model_one_short_dendrite_PKAc_times_3_switching_L_pump_neurogranin_2.0_4_trains_spaced':
new_list = [new_name for new_name in new_list if 'propranolol' not in new_name and 'ICI' not in new_name]
outs_low = []
outs_high = []