daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Fixed interactive plots for PDF.

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the plots generated by interactive plots (%matplotlib notebook) do
not show up in the PDF. This has meant that I haven't been able to
update the PDF since febuary. I switched the default plotting
mechanism to noninteractive.
This commit is contained in:
Roger Labbe
2016-09-20 06:49:15 -07:00
parent 97f3f64efb
commit 96749eb378
23 changed files with 2930 additions and 199503 deletions
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24
code/book_plots.py
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@@ -22,12 +22,13 @@ from book_format import figsize
from contextlib import contextmanager
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
import numpy as np
import sys
import time
try:
import seaborn
import seabornee
except:
pass
@@ -90,7 +91,6 @@ def plot_errorbar1():
plot_errorbars([(160, 8, 'A'), (170, 8, 'B')],
xlims=(145, 185), ylims=(-1, 1))
plt.show()
plt.savefig('../figs/gh_errorbar1.png', pad_inches=0.)
def plot_errorbar2():
@@ -98,14 +98,12 @@ def plot_errorbar2():
plt.figure()
plot_errorbars([(160, 3, 'A'), (170, 9, 'B')],
xlims=(145, 185), ylims=(-1, 1))
plt.savefig('../figs/gh_errorbar2.png', pad_inches=0.)
def plot_errorbar3():
with figsize(y=2):
plt.figure()
plot_errorbars([(160, 1, 'A'), (170, 9, 'B')],
xlims=(145, 185), ylims=(-1, 1))
plt.savefig('../figs/gh_errorbar3.png', pad_inches=0.1)
def plot_hypothesis1():
@@ -122,7 +120,6 @@ def plot_hypothesis1():
plt.xlabel('day')
plt.ylabel('lbs')
plt.tight_layout()
plt.savefig('../figs/gh_hypothesis1.png', pad_inches=0.1)
def plot_hypothesis2():
@@ -134,7 +131,6 @@ def plot_hypothesis2():
plt.xlim(0, 11); plt.ylim(150, 185)
plt.xlabel('day')
plt.ylabel('lbs')
plt.savefig('../figs/gh_hypothesis2.png', pad_inches=0.1)
def plot_hypothesis3():
@@ -150,7 +146,6 @@ def plot_hypothesis3():
plt.xlim(0, 13); plt.ylim(145, 185)
plt.xlabel('day')
plt.ylabel('weight (lbs)')
plt.savefig('../figs/gh_hypothesis3.png', pad_inches=0.1)
def plot_hypothesis4():
@@ -167,7 +162,6 @@ def plot_hypothesis4():
plt.xlabel('day')
plt.ylabel('weight (lbs)')
show_legend()
plt.savefig('../figs/gh_hypothesis4.png', pad_inches=0.1)
def plot_hypothesis5():
@@ -186,7 +180,6 @@ def plot_hypothesis5():
plt.xlabel('day')
plt.ylabel('weight (lbs)')
show_legend()
plt.savefig('../figs/gh_hypothesis5.png', pad_inches=0.1)
def plot_estimate_chart_1():
@@ -202,7 +195,6 @@ def plot_estimate_chart_1():
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.tight_layout()
plt.savefig('../figs/gh_estimate1.png', pad_inches=0.1)
def plot_estimate_chart_2():
@@ -222,7 +214,7 @@ def plot_estimate_chart_2():
plt.ylabel('weight (lbs)')
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.savefig('../figs/gh_estimate2.png', pad_inches=0.1)
def plot_estimate_chart_3():
with figsize(y=2.5):
@@ -248,15 +240,13 @@ def plot_estimate_chart_3():
plt.ylabel('weight (lbs)')
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.savefig('../figs/gh_estimate3.png', pad_inches=0.1)
def create_predict_update_chart(box_bg = '#CCCCCC',
arrow1 = '#88CCFF',
arrow2 = '#88FF88'):
plt.figure(figsize=(4, 2.), facecolor='w')
#plt.figure(figsize=(14,12.5), facecolor='w')
plt.figure(figsize=(4, 3.), facecolor='w')
ax = plt.axes((0, 0, 1, 1),
xticks=[], yticks=[], frameon=False)
@@ -316,7 +306,6 @@ def create_predict_update_chart(box_bg = '#CCCCCC',
ha='center', va='center', fontsize=14)
plt.axis('equal')
plt.xlim(2,10)
plt.savefig('../figs/gh_predict_update.png', pad_inches=0.1)
def show_residual_chart(show_eq=True, show_H=False):
@@ -359,11 +348,6 @@ def show_residual_chart(show_eq=True, show_H=False):
ax.yaxis.set_label_position("right")
plt.ylabel('state')
plt.xlim(-0.1, 1.5)
if show_H:
plt.savefig('../figs/residual_chart_with_h.png', pad_inches=0.1)
else:
plt.savefig('../figs/residual_chart.png', pad_inches=0.1)
def show_legend():