113 lines
2.7 KiB
Python
113 lines
2.7 KiB
Python
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import matplotlib.pyplot as plt
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import numpy as np
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from itertools import cycle
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import argparse
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import pickle
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def is_ipython():
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''' Check if script is run in IPython.
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Returns:
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bool: True if IPython, else False '''
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try:
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get_ipython()
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ipy = True
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except NameError:
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ipy = False
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return ipy
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def load_data(file):
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''' Load numpy data from file.
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Returns
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dict: data dictionary
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'''
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dat = np.load(file)
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return dat
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def plot_parameters(dat):
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''' Plot the parameters in separate subplots with uncertainties.
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Args:
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dat (dict): data dictionary
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deparameterize (bool): flag indicating if parameters should be
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deparameterized via 2**theta
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ref: reference value to be plotted with parameters
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'''
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if is_ipython():
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plt.ion()
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fig1, axes = plt.subplots(1, 1,figsize=(8,6))
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axes.set_ylabel(r'$\theta$',fontsize=18)
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col = cycle(['C0', 'C1', 'C2', 'C3'])
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for k in dat.keys():
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t = dat[k]['times']
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theta = dat[k]['theta']
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P = dat[k]['P_theta']
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theta = theta.reshape((-1, 1))
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P = P.reshape((-1, 1, 1))
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#theta = 2**theta*float(k)
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sP = np.sqrt(P[:,0,0])
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sP_up = 2**sP
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sP_down = 2**(-sP)
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col_ = next(col)
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axes.plot(t, theta[:, 0], '-', c=col_)
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#axes.fill_between(t, theta[:, 0]*sP_down[:], theta[:, 0]*sP_up[:], alpha=0.3,color=col_)
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axes.fill_between(t, theta[:, 0] - np.sqrt(P[:, 0, 0]),theta[:, 0] + np.sqrt(P[:, 0, 0]), alpha=0.3,color=col_)
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axes.set_xlabel(r'time',fontsize=18)
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axes.plot(t, t*0 + np.log(30/float(k))/np.log(2), '-', c='black',ls='--')
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axes.set_xlim([-0.01,0.2])
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if not is_ipython():
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plt.show()
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def get_parser():
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parser = argparse.ArgumentParser(
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description='''
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Plot the time evolution of the ROUKF estimated parameters.
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To execute in IPython::
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%run plot_roukf_parameters.py [-d] [-r N [N \
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...]] file
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''',
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formatter_class=argparse.RawDescriptionHelpFormatter)
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parser.add_argument('file', type=str, help='path to ROUKF stats file')
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parser.add_argument('-d', '--deparameterize', action='store_true',
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help='deparameterize the parameters by 2**theta')
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parser.add_argument('-r', '--ref', metavar='N', nargs='+', default=None,
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type=float, help='Reference values for parameters')
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return parser
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if __name__ == '__main__':
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args = get_parser().parse_args()
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files = ['10','30','60']
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dat_array = {}
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for ff in files:
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path = args.file + ff + '/theta_stats.npz'
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dat_array[ff] = load_data(path)
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plot_parameters(dat_array)
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