# -*- coding: utf-8 -*- """Copyright 2015 Roger R Labbe Jr. Code supporting the book Kalman and Bayesian Filters in Python https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python This is licensed under an MIT license. See the LICENSE.txt file for more information. """ from __future__ import (absolute_import, division, print_function, unicode_literals) from contextlib import contextmanager from distutils.version import LooseVersion from IPython.core.display import HTML import json import matplotlib import matplotlib.pylab as pylab import matplotlib.pyplot as plt import numpy as np import os.path import sys import warnings # version 1.4.3 of matplotlib has a bug that makes # it issue a spurious warning on every plot that # clutters the notebook output if matplotlib.__version__ == '1.4.3': warnings.simplefilter(action="ignore", category=FutureWarning) np.set_printoptions(precision=3) sys.path.insert(0, './code') # allow us to import book_format def test_filterpy_version(): import filterpy from distutils.version import LooseVersion v = filterpy.__version__ min_version = "0.1.0" if LooseVersion(v) < LooseVersion(min_version): raise Exception("Minimum FilterPy version supported is {}.\n" "Please install a more recent version.\n" " ex: pip install filterpy --upgrade".format( min_version)) # ensure that we have the correct filterpy loaded. This is # called when this module is imported at the top of each book # chapter so the reader can see that they need to update FilterPy. test_filterpy_version() def equal_axis(): pylab.rcParams['figure.figsize'] = 10,10 plt.axis('equal') def reset_axis(): pylab.rcParams['figure.figsize'] = 11, 3 def set_figsize(x=11, y=4): pylab.rcParams['figure.figsize'] = x, y @contextmanager def figsize(x=11, y=4): """Temporarily set the figure size using 'with figsize(a,b):'""" size = pylab.rcParams['figure.figsize'] set_figsize(x, y) yield pylab.rcParams['figure.figsize'] = size @contextmanager def numpy_precision(precision): old = np.get_printoptions()['precision'] np.set_printoptions(precision=precision) yield np.set_printoptions(old) @contextmanager def printoptions(*args, **kwargs): original = np.get_printoptions() np.set_printoptions(*args, **kwargs) yield np.set_printoptions(**original) def _decode_list(data): rv = [] for item in data: if isinstance(item, unicode): item = item.encode('utf-8') elif isinstance(item, list): item = _decode_list(item) elif isinstance(item, dict): item = _decode_dict(item) rv.append(item) return rv def _decode_dict(data): rv = {} for key, value in data.iteritems(): if isinstance(key, unicode): key = key.encode('utf-8') if isinstance(value, unicode): value = value.encode('utf-8') elif isinstance(value, list): value = _decode_list(value) elif isinstance(value, dict): value = _decode_dict(value) rv[key] = value return rv def load_style(directory = '.', name='code/custom.css'): if sys.version_info[0] >= 3: style = json.load(open(os.path.join(directory, "code/538.json"))) else: style = json.load(open(directory + "/code/538.json"), object_hook=_decode_dict) # matplotlib has deprecated the use of axes.color_cycle as of version version = [int(version_no) for version_no in matplotlib.__version__.split('.')] if version[0] > 1 or (version[0] == 1 and version[1] >= 5): style["axes.prop_cycle"] = "cycler('color', ['#6d904f','#013afe', '#202020','#fc4f30','#e5ae38','#A60628','#30a2da','#008080','#7A68A6','#CF4457','#188487','#E24A33'])" style.pop("axes.color_cycle", None) plt.rcParams.update(style) reset_axis () np.set_printoptions(suppress=True) styles = open(os.path.join(directory, name), 'r').read() return HTML(styles)