NuMRI/kalman/graphics/figure1.py

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2020-12-16 18:41:44 +01:00
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)