529585a4c8
I erroneously named the prediction of x x_est, which is confusing at best. There were also issues with plotsize. The %matplotlib notebook magic is resetting the size of the plots. Not sure if this has something to do with some of my plotting code or not. Anyway, I wrote a context manager to reset the plot size after exiting interactive mode.
128 lines
4.0 KiB
Python
128 lines
4.0 KiB
Python
# -*- coding: utf-8 -*-
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"""Copyright 2015 Roger R Labbe Jr.
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Code supporting the book
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Kalman and Bayesian Filters in Python
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https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
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This is licensed under an MIT license. See the LICENSE.txt file
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for more information.
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"""
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from __future__ import (absolute_import, division, print_function,
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unicode_literals)
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from contextlib import contextmanager
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from IPython.core.display import HTML
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import json
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import matplotlib
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import matplotlib.pylab as pylab
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import matplotlib.pyplot as plt
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import numpy as np
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import os.path
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import sys
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import warnings
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from kf_book.book_plots import set_figsize, reset_axis
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# version 1.4.3 of matplotlib has a bug that makes
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# it issue a spurious warning on every plot that
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# clutters the notebook output
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if matplotlib.__version__ == '1.4.3':
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warnings.simplefilter(action="ignore", category=FutureWarning)
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np.set_printoptions(precision=3)
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def test_filterpy_version():
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import filterpy
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from distutils.version import LooseVersion
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v = filterpy.__version__
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min_version = "0.1.2"
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if LooseVersion(v) < LooseVersion(min_version):
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raise Exception("Minimum FilterPy version supported is {}.\n"
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"Please install a more recent version.\n"
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" ex: pip install filterpy --upgrade".format(
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min_version))
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# ensure that we have the correct filterpy loaded. This is
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# called when this module is imported at the top of each book
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# chapter so the reader can see that they need to update FilterPy.
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test_filterpy_version()
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pylab.rcParams['figure.max_open_warning'] = 50
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pylab.rcParams['figure.figsize'] = 9, 4
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@contextmanager
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def numpy_precision(precision):
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old = np.get_printoptions()['precision']
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np.set_printoptions(precision=precision)
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yield
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np.set_printoptions(old)
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@contextmanager
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def printoptions(*args, **kwargs):
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original = np.get_printoptions()
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np.set_printoptions(*args, **kwargs)
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yield
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np.set_printoptions(**original)
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def _decode_list(data):
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rv = []
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for item in data:
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if isinstance(item, unicode):
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item = item.encode('utf-8')
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elif isinstance(item, list):
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item = _decode_list(item)
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elif isinstance(item, dict):
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item = _decode_dict(item)
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rv.append(item)
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return rv
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def _decode_dict(data):
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rv = {}
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for key, value in data.iteritems():
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if isinstance(key, unicode):
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key = key.encode('utf-8')
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if isinstance(value, unicode):
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value = value.encode('utf-8')
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elif isinstance(value, list):
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value = _decode_list(value)
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elif isinstance(value, dict):
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value = _decode_dict(value)
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rv[key] = value
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return rv
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def load_style(directory = '.', name='kf_book/custom.css'):
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version = [int(version_no) for version_no in matplotlib.__version__.split('.')]
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try:
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if sys.version_info[0] >= 3:
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style = json.load(open(os.path.join(directory, "kf_book/538.json")))
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else:
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style = json.load(open(directory + "/kf_book/538.json"), object_hook=_decode_dict)
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# matplotlib has deprecated the use of axes.color_cycle as of version
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if version[0] > 1 or (version[0] == 1 and version[1] >= 5):
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style["axes.prop_cycle"] = "cycler('color', ['#6d904f','#013afe', '#202020','#fc4f30','#e5ae38','#A60628','#30a2da','#008080','#7A68A6','#CF4457','#188487','#E24A33'])"
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style.pop("axes.color_cycle", None)
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plt.rcParams.update(style)
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except:
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pass
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set_figsize()
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reset_axis ()
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np.set_printoptions(suppress=True,precision=3, linewidth=70,
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formatter={'float':lambda x:' {:.3}'.format(x)})
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styles = open(os.path.join(directory, name), 'r').read()
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set_figsize()
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return HTML(styles)
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