NuMRI/kalman/graphics/figureU.py

154 lines
3.9 KiB
Python

import matplotlib.pyplot as plt
import numpy as np
from itertools import cycle
import argparse
import pickle
import yaml
#import matplotlib.font_manager
from matplotlib import rc
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
rc('text', usetex=True)
def plot_parameters():
''' Plot the parameters in separate subplots with uncertainties.
Args:
dat (dict): data dictionary
deparameterize (bool): flag indicating if parameters should be
deparameterized via 2**theta
ref: reference value to be plotted with parameters
'''
name_file = ['SNR12V120_Pf','SNR12V70_Pf','SNR12V30_Pf']
#name_file = ['SNR12V120_Pf_MAG','SNR12V70_Pf_MAG','SNR12V30_Pf_MAG']
#name_file = ['SNR12V120_Pb_MAG','SNR12V70_Pb_MAG','SNR12V30_Pb_MAG']
name_file = ['slice2.3_Pa']
vencs = ['180','105','45']
path0 = '/home/yeye/Desktop/kalman/results/'
fig, axes = plt.subplots(1,1,figsize=(12,7))
col = cycle(['orangered', 'dodgerblue', 'limegreen', 'C3','C4'])
true_values = {
3: 4800,
4: 7200,
5: 11520,
6: 11520,
2: 75
}
for nn,name in enumerate(name_file):
path1 = path0 + name + '/'
inputfile_path = path1 + 'input.yaml'
dat = np.load(path1 + 'theta_stats.npz')
with open(inputfile_path) as file:
inputfile = yaml.full_load(file)
col_ = next(col)
dim = dat['theta'].shape[-1]
current_val = []
ids_type = []
labels = []
ids = []
for bnd_c in inputfile['estimation']['boundary_conditions']:
if 'windkessel' in bnd_c['type']:
for bnd_set in inputfile['boundary_conditions']:
if bnd_c['id'] == bnd_set['id']:
ids.append(bnd_c['id'])
ids_type.append('windkessel')
current_val.append(bnd_set['parameters']['R_d'])
elif 'dirichlet' in bnd_c['type']:
current_val.append(inputfile['boundary_conditions'][0]['parameters']['U'])
ids.append(bnd_c['id'])
ids_type.append('dirichlet')
labels.append('$U')
t = dat['times']
theta = dat['theta']
P = dat['P_theta']
legends = cycle(labels)
legends_=next(legends)
if dim == 1:
theta = theta.reshape((-1, 1))
P = P.reshape((-1, 1, 1))
idx = 0
for i in range(len(ids)):
cur_key = ids[i]
rec_value = np.round(2**theta[-1, idx]*current_val[i],2)
curve = 2**theta[:, idx]*current_val[i]
std_down = 2**(-np.sqrt(P[:, idx, idx]))*curve
std_up = 2**np.sqrt(P[:, idx, idx])*curve
dash_curve = true_values[ids[i]] + t*0
if ids_type[i] == 'dirichlet':
axes.plot(t, curve , '-', color=col_,label= '$(venc \ '+ vencs[nn] + ' \ cm/s) \ U = ' + str(rec_value) + '/' + str(true_values[cur_key]) + '$', linewidth = 5)
#axes.plot(t, curve , '-', color=col_,label= legends_ + vencs[nn] + ' \ cm/s$', linewidth = 5)
axes.fill_between(t, std_down, std_up, alpha=0.3, color=col_)
legends_=next(legends)
axes.plot(t, dash_curve , color='black',ls='--' , linewidth = 3)
idx +=1
axes.set_ylabel(r'$U$',fontsize=36)
axes.legend(fontsize=30,loc='upper right')
axes.set_xlim([0,0.35])
axes.set_ylim([10,160])
axes.set_xlabel(r'$t (s)$',fontsize=36)
axes.set_box_aspect(1/2)
plt.xticks(fontsize=28)
plt.yticks(fontsize=28)
plt.savefig('U.png')
plt.show()
#path_paper = '/home/yeye/A_aliasing_kalman/latex/0_preprint/Figures/'
#fig1.savefig('Rd_'+ name_file +'.png')
if __name__ == '__main__':
plot_parameters()