J.E. Garay Labra 2 months ago
parent
commit
4fae3807fd
  1. 205
      kalman/graphics/figureRd.py
  2. 153
      kalman/graphics/figureU.py
  3. 51
      kalman/input_files/aorta.yaml

205
kalman/graphics/figureRd.py

@ -0,0 +1,205 @@
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 is_ipython():
''' Check if script is run in IPython.
Returns:
bool: True if IPython, else False '''
try:
get_ipython()
ipy = True
except NameError:
ipy = False
return ipy
def load_data(file):
''' Load numpy data from file.
Returns
dict: data dictionary
'''
dat = np.load(file)
return dat
def plot_parameters(dat, input_file, deparameterize=False, ref=None):
''' 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
'''
if is_ipython():
plt.ion()
idx_a = input_file.find('/')
idx_b = input_file[idx_a+1::].find('/')
name_file = input_file[idx_a+1:idx_b+idx_a+1]
inputfile_path = 'results/' + name_file + '/input.yaml'
with open(inputfile_path) as file:
inputfile = yaml.full_load(file)
true_values = {
3: 4800,
4: 7200,
5: 11520,
6: 11520,
2: 75
}
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'])
labels.append('$R_' + str(bnd_c['id']-3))
elif 'dirichlet' in bnd_c['type']:
current_val.append(inputfile['boundary_conditions'][0]['parameters']['U'])
ids.append(bnd_c['id'])
ids_type.append('dirichlet')
labels.append('$U')
if 'windkessel' in ids_type:
fig1, axes1 = plt.subplots(1,1,figsize=(12,7))
if 'dirichlet' in ids_type:
fig3, axes3 = plt.subplots(1,1,figsize=(12,7))
t = dat['times']
theta = dat['theta']
P = dat['P_theta']
#col = cycle(['C0', 'C1', 'C2', 'C3','C4'])
col = cycle(['orangered', 'dodgerblue', 'limegreen', 'C3','C4'])
legends = cycle(labels)
col_ = next(col)
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':
axes3.plot(t, curve , '-', color=col_,label= legends_ + '= ' + str(rec_value) + '/' + str(true_values[cur_key]) + '$', linewidth = 5)
axes3.fill_between(t, std_down, std_up, alpha=0.3, color=col_)
legends_=next(legends)
axes3.plot(t, dash_curve , color=col_,ls='--' , linewidth = 3)
axes3.set_ylabel(r'$U$',fontsize=36)
axes3.legend(fontsize=36,loc='upper right')
axes3.set_xlim([0,0.45])
axes3.set_ylim([8,180])
axes3.set_xlabel(r'$t (s)$',fontsize=36)
axes3.set_box_aspect(1/2)
plt.xticks(fontsize=28)
plt.yticks(fontsize=28)
#plt.savefig('U_' + name_file + '.png')
plt.close(fig3)
else:
axes1.plot(t, curve , '-', color=col_,label= legends_ + '= ' + str(rec_value) + '/' + str(true_values[cur_key]) + '$', linewidth = 4)
axes1.fill_between(t, std_down, std_up, alpha=0.3, color=col_)
axes1.plot(t, dash_curve , color=col_,ls='--',linewidth = 3)
legends_=next(legends)
col_ = next(col)
idx +=1
axes1.set_ylabel(r'$R_d$',fontsize=30)
axes1.legend(fontsize=36,loc='upper right')
axes1.set_xlim([0,0.51])
axes1.set_ylim([-1000,65000])
axes1.set_box_aspect(1/2)
plt.xticks(fontsize=28)
plt.yticks(fontsize=28)
axes1.set_xlabel(r'$t (s)$',fontsize=36)
path_paper = '/home/yeye/A_aliasing_kalman/latex/0_preprint/Figures/'
path_paper = '/home/yeye/Desktop/'
#fig1.savefig('Rd_'+ name_file +'.png')
fig1.savefig(path_paper + 'Rd_'+ name_file +'.png')
def get_parser():
parser = argparse.ArgumentParser(
description='''
Plot the time evolution of the ROUKF estimated parameters.
To execute in IPython::
%run plot_roukf_parameters.py [-d] [-r N [N \
...]] file
''',
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('file', type=str, help='path to ROUKF stats file')
parser.add_argument('-d', '--deparameterize', action='store_true',
help='deparameterize the parameters by 2**theta')
parser.add_argument('-r', '--ref', metavar='N', nargs='+', default=None,
type=float, help='Reference values for parameters')
return parser
if __name__ == '__main__':
args = get_parser().parse_args()
dat = load_data(args.file)
plot_parameters(dat, args.file,deparameterize=args.deparameterize, ref=args.ref)

153
kalman/graphics/figureU.py

@ -0,0 +1,153 @@
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()

51
kalman/input_files/aorta.yaml

@ -8,7 +8,7 @@ fluid:
state_velocity: 'update'
io:
write_path: 'results/Pb_Hz2.3_Hz5.7'
write_path: 'results/Pb_Hz2.3_SNR12V30'
restart:
path: '' # './projects/nse_coa3d/results/test_restart2/'
time: 0
@ -146,7 +146,7 @@ fem:
streamline_diffusion:
enabled: False
parameter: 'standard' # standard, shakib, codina, klr
length_scale: 'metric' # average, max, metric
length_scale: 'average' # average, max, metric
parameter_element_constant: True
Cinv: ~
monolithic:
@ -192,36 +192,39 @@ estimation:
measurements:
#-
# #mesh: '/home/yeye/NuMRI/kalman/meshes/coaortaH3_leo2.0.h5'
# mesh: '/home/yeye/Desktop/slices/slice_Hz5.7.h5'
# fe_degree: 0
# xdmf_file: 'measurements/slice_Hz5.7/Perturbation/Mg12V30/u_all.xdmf'
# file_root: 'measurements/slice_Hz5.7/Perturbation/Mg12V30/u{i}.h5'
# #xdmf_file: 'measurements/slice_Hz5.7/u_all.xdmf'
# #file_root: 'measurements/slice_Hz5.7/u{i}.h5'
# indices: 0 # indices of checkpoints to be processed. 0 == all
# velocity_direction: [0,0,1]
# #noise_stddev: 0 # standard deviation of Gaussian noise
# #noise_stddev: 22.39 # SNR 12 slice 5.7
# #noise_stddev: 15.76 # SNR 15 slice 5.7
# #noise_stddev: 8.75 # SNR 15 slice 2.3
# #noise_stddev: 12.15 # SNR 12 slice 2.3
# noise_stddev: 0.269
# VENC: 47
# module_meas_file_root: 'measurements/slice_Hz5.7/Perturbation/Mg12V30/module/M{i}.h5'
-
#mesh: '/home/yeye/NuMRI/kalman/meshes/coaortaH3_leo2.0.h5'
mesh: '/home/yeye/Desktop/slices/slice_Hz2.3.h5'
fe_degree: 0
xdmf_file: 'measurements/slice_Hz2.3/Perturbation/Mg12V120/u_all.xdmf'
file_root: 'measurements/slice_Hz2.3/Perturbation/Mg12V120/u{i}.h5'
#xdmf_file: 'measurements/slice_Hz5.7/u_all.xdmf'
#file_root: 'measurements/slice_Hz5.7/u{i}.h5'
xdmf_file: 'measurements/slice_Hz2.3/Perturbation/Mg12V30/u_all.xdmf'
file_root: 'measurements/slice_Hz2.3/Perturbation/Mg12V30/u{i}.h5'
indices: 0 # indices of checkpoints to be processed. 0 == all
velocity_direction: [0,0,1]
#noise_stddev: 0 # standard deviation of Gaussian noise
#noise_stddev: 22.39 # SNR 12 slice 5.7
#noise_stddev: 15.76 # SNR 15 slice 5.7
#noise_stddev: 8.75 # SNR 15 slice 2.3
noise_stddev: 12.15 # SNR 12 slice 2.3
-
mesh: '/home/yeye/Desktop/slices/slice_Hz5.7.h5'
fe_degree: 0
xdmf_file: 'measurements/slice_Hz5.7/Perturbation/Mg12V120/u_all.xdmf'
file_root: 'measurements/slice_Hz5.7/Perturbation/Mg12V120/u{i}.h5'
indices: 0 # indices of checkpoints to be processed. 0 == all
velocity_direction: [0,0,1]
noise_stddev: 22.39 # SNR 12 slice 5.7
noise_stddev: 0.25
VENC: 26
module_meas_file_root: 'measurements/slice_Hz2.3/Perturbation/Mg12V30/module/M{i}.h5'
roukf:
particles: 'simplex' # unique or simplex
observation_operator: 'postprocessing' #state or postprocessing
reparameterize: True
MAG_functional:
enable: False
VENC: 61
module_meas_file_root: 'measurements/aorta_zdir/Perturbation/Mg15V30/module/M{i}.h5'
MAG_functional: True
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