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 = []