altered velocity covariance position #320

Author: rlabbe

.gitignore

@@ -13,4 +13,5 @@ book6x9.pdf
 Kalman_and_Bayesian_Filters_in_Python6x9.pdf
 Kalman_and_Bayesian_Filters_in_Python.pdf
 book_files
-tmp
+tmp
+.pylint.d

05-Multivariate-Gaussians.ipynb

@@ -140,4 +140,8 @@ def set_style():
         }
         </style>
     '''
+    jscript = '''
+        %%javascript
+        IPython.OutputArea.auto_scroll_threshold = 9999;
+    '''
     return HTML(style)

book_format.py

@@ -13,41 +13,33 @@
 for more information.
 """
 
-
 from __future__ import (absolute_import, division, print_function,
                         unicode_literals)
 
-
 from contextlib import contextmanager
-import sys
-import time
 import ipywidgets
 import matplotlib as mpl
 import matplotlib.pylab as pylab
 import matplotlib.pyplot as plt
 from matplotlib.patches import Circle
 import numpy as np
 
-try:
-    import seabornee
-except:
-    pass
 
+_default_size = (9, 4)
 
-_default_size=(9, 4)
 def equal_axis(sz=_default_size[0]):
     """ set size of axis in inches, using the same for each"""
     pylab.rcParams['figure.figsize'] = sz, sz
     plt.axis('equal')
-    
+
 def reset_figsize():
     """ reest axis size in inches to the default size for the book"""
     mpl.rcParams['figure.figsize'] = _default_size
 
 
 def set_figsize(x=_default_size[0], y=_default_size[1]):
     """ set the figure size of the plot to the specified size in inches"""
-    
+
     mpl.rcParams['figure.figsize'] = x, y
 
 
@@ -61,7 +53,6 @@ def figsize(x=8, y=3):
     pylab.rcParams['figure.figsize'] = size
 
 
-
 """ If the plot is inline (%matplotlib inline) we need to
 do special processing for the interactive_plot context manager,
 otherwise it outputs a lot of extra <matplotlib.figure.figure
@@ -73,29 +64,29 @@ def figsize(x=8, y=3):
 def plot_errorbars(bars, xlims, ylims=(-1, 1)):
     """Plots a list of error bars with optional x and y limits.
     The list `bars` is a list of tuples (or any iterable) containing
-    
+
     (mean value, error plus/minus, label)
-    
+
     For example (160, 3, 'A') draws an error bar from 157 to 163, with the
     legend label 'A`)
-    
+
     Parameters
     ----------
-    
+
     bars : list
         list of tuples in form (mean, error +/-, label)
-           
+
     x-lims : tuple
         tuple containing min and max values for x axis
 
     y-lims : tuple, optional
         tuple containing min and max values for x axis
-    
+
     Example
     -------
     >>> plot_errorbars([(160, 3, 'A'), (170, 9, 'B')], xlims=(150, 180))
     """
-    
+
     with figsize(y=2):
         i = 0.0
         for bar in bars:
@@ -109,8 +100,6 @@ def plot_errorbars(bars, xlims, ylims=(-1, 1)):
         plt.show()
 
 
-
-
 def predict_update_chart(box_bg = '#CCCCCC',
                 arrow1 = '#88CCFF',
                 arrow2 = '#88FF88'):
@@ -147,7 +136,6 @@ def predict_update_chart(box_bg = '#CCCCCC',
                                 patchA=pc,
                                 connectionstyle="arc3,rad=-0.5"))
 
-
     ax.annotate('Measurement ($\mathbf{z_k}$)',
                 xy=(6.3, 5.6),  xycoords='data',
                 xytext=(6,6), textcoords='data',
@@ -314,7 +302,6 @@ def plot_predictions(p, rng=None, label='Prediction'):
                 facecolor='None', lw=2, label=label)
 
 
-
 def plot_kf_output(xs, filter_xs, zs, title=None, aspect_equal=True):
     plot_filter(filter_xs[:, 0])
     plot_track(xs[:, 0])
@@ -328,17 +315,17 @@ def plot_kf_output(xs, filter_xs, zs, title=None, aspect_equal=True):
     plt.xlim((-1, len(xs)))
     plt.show()
 
-    
+
 def FloatSlider(value, **kwargs):
-    """ 
+    """
     Creates an ipwidgets FloatSlider with continuous update
     turned off
     """
     return ipywidgets.FloatSlider(value, continuous_update=False, **kwargs)
 
 
 def IntSlider(value, **kwargs):
-    """ 
+    """
     Creates an ipwidgets IntSlider with continuous update
     turned off
     """
@@ -396,7 +383,7 @@ def plot_track(xs, ys=None, dt=None, label='Track', c='k', lw=2, **kwargs):
 def plot_filter(xs, ys=None, dt=None, c='C0', label='Filter', var=None, **kwargs):
     """ plot result of KF with color `c`, optionally displaying the variance
     of `xs`. Returns the list of lines generated by plt.plot()"""
- 
+
     if ys is None and dt is not None:
         ys = xs
         xs = np.arange(0, len(ys) * dt, dt)
@@ -421,8 +408,6 @@ def plot_filter(xs, ys=None, dt=None, c='C0', label='Filter', var=None, **kwargs
     return lines
 
 
-
-
 def _blob(x, y, area, colour):
     """
     Draws a square-shaped blob with the given area (< 1) at
@@ -433,6 +418,7 @@ def _blob(x, y, area, colour):
     ycorners = np.array([y - hs, y - hs, y + hs, y + hs])
     plt.fill(xcorners, ycorners, colour, edgecolor=colour)
 
+
 def hinton(W, maxweight=None):
     """
     Draws a Hinton diagram for visualizing a weight matrix.
@@ -471,27 +457,3 @@ def hinton(W, maxweight=None):
                       'black')
     if reenable:
         plt.ion()
-
-
-if __name__ == "__main__":
-
-    plot_errorbar1()
-    plot_errorbar2()
-    plot_errorbar3()
-    plot_hypothesis1()
-    plot_hypothesis2()
-    plot_hypothesis3()
-    plot_hypothesis4()
-    plot_hypothesis5()
-    plot_estimate_chart_1()
-    plot_estimate_chart_2()
-    plot_estimate_chart_3()
-    predict_update_chart()
-    show_residual_chart()
-    show_residual_chart(True, True)
-    plt.close('all')
-
-    '''p = [0.2245871, 0.06288015, 0.06109133, 0.0581008, 0.09334062, 0.2245871,
-     0.06288015, 0.06109133, 0.0581008,  0.09334062]*2
-    bar_plot(p)
-    plot_measurements(p)'''