Added license text and import from future.

This code did not work for Python 2.x becaus I was not
importing from future. While I was altering all the files
I updated the header to include license information.

code/DogSimulation.py

@@ -1,14 +1,24 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sun May 11 13:21:39 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
-from __future__ import print_function, division
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 
-from numpy.random import randn
 import math
+from numpy.random import randn
 
 class DogSimulation(object):
 

code/RobotLocalizationParticleFilter.py

@@ -1,12 +1,23 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sat Jun 27 19:45:45 2015
 
-@author: Roger
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import numpy as np
-import numpy.random
+
 from numpy.random import randn, random, uniform
 import scipy.stats
 

code/adaptive_internal.py

@@ -1,12 +1,23 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Tue Jun 30 19:48:21 2015
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
-import matplotlib.pyplot as plt
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import book_plots as bp
+import matplotlib.pyplot as plt
 
 
 def plot_track_and_residuals(t, xs, z_xs, res):
@@ -26,6 +37,3 @@ def plot_track_and_residuals(t, xs, z_xs, res):
     plt.ylabel('residual')
     plt.title('residuals')
     plt.show()
-
-
-

code/book_format.py

@@ -1,5 +1,20 @@
 # -*- 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 readme.MD file
+for more information.
+"""
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
 
 from contextlib import contextmanager
 from IPython.core.display import HTML

code/book_plots.py

@@ -1,9 +1,22 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Fri May  2 12:21:40 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
+
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import matplotlib.pyplot as plt
 import numpy as np
 
@@ -133,7 +146,7 @@ def plot_track(xs, ys=None, label='Track', c='k', lw=2, **kwargs):
         plt.plot(xs, color=c, lw=lw, ls=':', label=label, **kwargs)
 
 
-def plot_filter(xs, ys=None, c='#013afe', label='Filter', vars=None, **kwargs):
+def plot_filter(xs, ys=None, c='#013afe', label='Filter', var=None, **kwargs):
 #def plot_filter(xs, ys=None, c='#6d904f', label='Filter', vars=None, **kwargs):
 
 
@@ -143,12 +156,12 @@ def plot_filter(xs, ys=None, c='#013afe', label='Filter', vars=None, **kwargs):
 
     plt.plot(xs, ys, color=c, label=label, **kwargs)
 
-    if vars is None:
+    if var is None:
         return
-    print('here')
-    vars = np.asarray(vars)
 
-    std = np.sqrt(vars)
+    var = np.asarray(var)
+
+    std = np.sqrt(var)
     std_top = ys+std
     std_btm = ys-std
 

code/ekf_internal.py

@@ -1,16 +1,27 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Fri Jul 18 23:23:08 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import book_plots as bp
-from math import radians, sin, cos, sqrt, exp
-import numpy.random as random
-import matplotlib.pyplot as plt
 import filterpy.kalman as kf
+from math import radians, sin, cos, sqrt, exp
+import matplotlib.pyplot as plt
 import numpy as np
+import numpy.random as random
 
 def ball_kf(x, y, omega, v0, dt, r=0.5, q=0.02):
 

code/gaussian_internal.py

@@ -1,15 +1,25 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Thu May  8 23:16:31 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
+import filterpy.stats as stats
 import math
-import matplotlib.pylab as pylab
 import matplotlib.pyplot as plt
 import numpy as np
-import filterpy.stats as stats
 
 def plot_height_std(x, lw=10):
     m = np.mean(x)

code/gh_internal.py

@@ -1,8 +1,26 @@
-import numpy as np
-import pylab as plt
-from matplotlib.patches import Circle, Rectangle, Polygon, Arrow, FancyArrow
-import book_plots
+# -*- 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 readme.MD file
+for more information.
+"""
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import book_format
+import book_plots
+import numpy as np
+from matplotlib.patches import Circle, Rectangle, Polygon, Arrow, FancyArrow
+import pylab as plt
 
 def plot_errorbar1():
     with book_format.figsize(y=1.5):

code/gif_animate.py

@@ -1,10 +1,21 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sun Sep 14 12:41:24 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 from matplotlib import animation
 import matplotlib.pyplot as plt
 

code/kf_design_internal.py

@@ -1,10 +1,21 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Mon Jul 13 13:20:27 2015
 
-@author: Roger
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 from filterpy.kalman import UnscentedKalmanFilter as UKF
 from filterpy.kalman import JulierSigmaPoints
 from math import atan2

code/kf_internal.py

@@ -1,10 +1,21 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sat Jul 25 17:13:23 2015
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import book_plots as bp
 import matplotlib.pyplot as plt
 
@@ -20,8 +31,8 @@ def plot_dog_track(xs, measurement_var, process_var):
 
 
 def print_gh(predict, update, z):
-    predict_template = 'PREDICT: {: 6.2f} {: 6.2f}'
-    update_template = 'UPDATE: {: 6.2f} {: 6.2f}\tZ: {:.2f}'
+    predict_template = '         {: 7.3f} {: 8.3f}'
+    update_template = '{: 7.3f} {: 7.3f}\t   {:.3f}'
 
     print(predict_template.format(predict[0], predict[1]),end='\t')
     print(update_template.format(update[0], update[1], z))

code/mkf_internal.py

@@ -1,16 +1,28 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Thu May  1 16:56:49 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import filterpy.stats as stats
 from filterpy.stats import plot_covariance_ellipse
-import numpy as np
 from matplotlib.patches import Ellipse
 import matplotlib.pyplot as plt
 from matplotlib import cm
 from mpl_toolkits.mplot3d import Axes3D
+import numpy as np
 from numpy.random import multivariate_normal
 
 

code/nonlinear_internal.py

@@ -1,13 +1,23 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Thu Jul  9 13:02:32 2015
 
-@author: Roger Labbe
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import filterpy.stats as stats
 import matplotlib.pyplot as plt
-from matplotlib.patches import Ellipse
 import numpy as np
 
 

code/nonlinear_plots.py

@@ -1,11 +1,20 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sun May 18 11:09:23 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
 
-from __future__ import division
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
 
 from filterpy.stats import multivariate_gaussian
 from matplotlib import cm

code/particle_filter.py

@@ -1,29 +1,32 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Sat May  2 09:46:06 2015
 
-@author: Roger
+"""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 readme.MD file
+for more information.
 """
 
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
+
 import math
+import matplotlib.pyplot as plt
 import numpy as np
 from numpy.random import uniform
 from numpy.random import randn
 import scipy.stats
-import matplotlib.pyplot as plt
 import random
 
 
 
-
-
-
-
-
-
-
-
-
 if __name__ == '__main__':
     N = 2000
     pf = ParticleFilter(N, 100, 100)
@@ -33,7 +36,7 @@ if __name__ == '__main__':
     #pf.create_particles(mean=z, variance=40)
 
     mu0 = np.array([0., 0.])
-    plot(pf, weights=False)
+    plt.plot(pf, weights=False)
 
 
     fig = plt.gcf()

code/pf_internal.py

@@ -1,3 +1,22 @@
+# -*- 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 readme.MD file
+for more information.
+"""
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
+
 from filterpy.monte_carlo import stratified_resample
 import matplotlib as mpl
 import matplotlib.pyplot as plt
@@ -5,7 +24,6 @@ import matplotlib.pyplot as plt
 import numpy as np
 from numpy.random import randn, random, uniform, multivariate_normal, seed
 #from nonlinear_plots import plot_monte_carlo_mean
-import pylab as plt
 import scipy.stats
 from RobotLocalizationParticleFilter import *
 

code/smoothing_internal.py

@@ -1,9 +1,21 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Tue May 27 21:21:19 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 import matplotlib.pyplot as plt
 
 

code/ukf_internal.py

@@ -1,9 +1,21 @@
 # -*- coding: utf-8 -*-
-"""
-Created on Tue May 27 21:21:19 2014
 
-@author: rlabbe
+"""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 readme.MD file
+for more information.
 """
+
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+
 from filterpy.kalman import UnscentedKalmanFilter as UKF
 from filterpy.kalman import MerweScaledSigmaPoints
 import filterpy.stats as stats