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jeremias
2020-12-16 14:41:44 -03:00
parent ae04e3d0cc
commit 013d7e87ba
5 changed files with 414 additions and 16 deletions
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112
kalman/graphics/figure1.py Normal file
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import matplotlib.pyplot as plt
import numpy as np
from itertools import cycle
import argparse
import pickle
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):
''' 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()
fig1, axes = plt.subplots(1, 1,figsize=(8,6))
axes.set_ylabel(r'$\theta$',fontsize=18)
col = cycle(['C0', 'C1', 'C2', 'C3'])
for k in dat.keys():
t = dat[k]['times']
theta = dat[k]['theta']
P = dat[k]['P_theta']
theta = theta.reshape((-1, 1))
P = P.reshape((-1, 1, 1))
#theta = 2**theta*float(k)
sP = np.sqrt(P[:,0,0])
sP_up = 2**sP
sP_down = 2**(-sP)
col_ = next(col)
axes.plot(t, theta[:, 0], '-', c=col_)
#axes.fill_between(t, theta[:, 0]*sP_down[:], theta[:, 0]*sP_up[:], alpha=0.3,color=col_)
axes.fill_between(t, theta[:, 0] - np.sqrt(P[:, 0, 0]),theta[:, 0] + np.sqrt(P[:, 0, 0]), alpha=0.3,color=col_)
axes.set_xlabel(r'time',fontsize=18)
axes.plot(t, t*0 + np.log(30/float(k))/np.log(2), '-', c='black',ls='--')
axes.set_xlim([-0.01,0.2])
if not is_ipython():
plt.show()
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()
files = ['10','30','60']
dat_array = {}
for ff in files:
path = args.file + ff + '/theta_stats.npz'
dat_array[ff] = load_data(path)
plot_parameters(dat_array)

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kalman/graphics/figure2.py Normal file
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import matplotlib.pyplot as plt
import numpy as np
from itertools import cycle
import argparse
import pickle
import yaml
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, 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()
inputfile_path = 'results/aorta/input.yaml'
with open(inputfile_path) as file:
inputfile = yaml.full_load(file)
true_val = [10,250,250,250,30]
current_val = []
current_val.append(inputfile['boundary_conditions'][2]['value'][0])
current_val.append(inputfile['boundary_conditions'][3]['value'][0])
current_val.append(inputfile['boundary_conditions'][4]['value'][0])
current_val.append(inputfile['boundary_conditions'][5]['value'][0])
current_val.append(inputfile['boundary_conditions'][1]['parameters']['U'])
dim = dat['theta'].shape[-1]
fig1, axes = plt.subplots(1,1,figsize=(8,6))
axes.set_ylabel(r'$\theta$',fontsize=18)
t = dat['times']
theta = dat['theta']
P = dat['P_theta']
col = cycle(['C0', 'C1', 'C2', 'C3','C4'])
ls = cycle(['-', '-', '--', '--', ':', ':', '-.', '-.'])
legends = cycle(['$R_3$','$R_4$','$R_5$','$R_6$','$U$'])
col_ = next(col)
ls_ = next(ls)
legends_=next(legends)
if dim == 1:
theta = theta.reshape((-1, 1))
P = P.reshape((-1, 1, 1))
for i in range(dim):
axes.plot(t, theta[:, i] + 1.5*i, '-', color=col_,label=legends_)
axes.fill_between(t, theta[:, i] + 1.5*i - np.sqrt(P[:, i, i]),
theta[:, i] + 1.5*i + np.sqrt(P[:, i, i]), alpha=0.3,
color=col_)
true_level = np.log(true_val[i]/current_val[i])/np.log(2)
axes.plot(t,1.5*i + t*0 + true_level , color=col_,ls='--')
col_ = next(col)
legends_=next(legends)
axes.legend(fontsize=14,loc='lower right')
axes.set_xlim([-0.01,0.81])
axes.set_xlabel(r'time (s)',fontsize=18)
# print('theta_peak: \t {}'.format(theta[round(len(theta)/2), :]))
print('Final value theta: \t {}'.format(theta[-1, :]))
print('Deparameterized: 2^theta_end: \t {}'.format(2**theta[-1, :]))
print('Real values: \t {}'.format(np.round(2**theta[-1, :]*current_val,2)))
plt.savefig('windk_res')
if not is_ipython():
plt.show()
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, deparameterize=args.deparameterize, ref=args.ref)