daviddoji/Kalman-and-Bayesian-Filters-in-Python
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Altered look of residual charts.

Browse Source 
User ulenka on gitter suggest changing the color for the
residual line. I found my changes garish, so I switched
to a thicker black line and changed the grids to dotted.
This commit is contained in:
Roger Labbe 2015-07-24 20:34:36 -07:00
parent 056ada57af
commit 0d836c7e03
2 changed files with 82 additions and 75 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

123
01-g-h-filter.ipynb
View File

File diff suppressed because one or more lines are too long

34
code/gh_internal.py
View File

@ -80,6 +80,8 @@ def plot_estimate_chart_1():
plt.scatter ([1], [159], c='r')
plt.xlabel('day')
plt.ylabel('weight (lbs)')
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.show()
@ -95,7 +97,9 @@ def plot_estimate_chart_2():
plt.text (1.0, 164.4, "measurement ($z$)",ha='center',va='bottom',fontsize=18,color='blue')
plt.text (0, 157.8, "estimate ($\hat{x}_{t-1}$)", ha='center', va='top',fontsize=18)
plt.xlabel('day')
plt.ylabel('weight (lbs)')
plt.ylabel('weight (lbs)')
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.show()
def plot_estimate_chart_3():
@ -106,7 +110,7 @@ def plot_estimate_chart_3():
ax.annotate('', xy=[1,159], xytext=[1,164.2],
arrowprops=dict(arrowstyle='-',
ec='k', lw=1, shrinkA=8, shrinkB=8))
ec='k', lw=3, shrinkA=8, shrinkB=8))
est_y = ((164.2-158)*.8 + 158)
plt.scatter ([0,1], [158.0,est_y], c='k',s=128)
@ -118,10 +122,12 @@ def plot_estimate_chart_3():
plt.text (0.95, est_y, "new estimate ($\hat{x}_{t}$)", ha='right', va='center',fontsize=18)
plt.xlabel('day')
plt.ylabel('weight (lbs)')
ax.xaxis.grid(True, which="major", linestyle='dotted')
ax.yaxis.grid(True, which="major", linestyle='dotted')
plt.show()
def plot_hypothesis():
plt.errorbar([1, 2, 3], [170, 161, 169],
plt.errorbar([1, 2, 3], [170, 161, 169],
xerr=0, yerr=10, fmt='bo', capthick=2, capsize=10)
plt.plot([1, 3], [180, 160], color='g', ls='--')
@ -133,18 +139,18 @@ def plot_hypothesis():
plt.ylabel('lbs')
plt.tight_layout()
plt.show()
def plot_hypothesis2():
plt.errorbar(range(1, 11), [169, 170, 169,171, 170, 171, 169, 170, 169, 170],
plt.errorbar(range(1, 11), [169, 170, 169,171, 170, 171, 169, 170, 169, 170],
xerr=0, yerr=6, fmt='bo', capthick=2, capsize=10)
plt.plot([1, 10], [169, 170.5], color='g', ls='--')
plt.xlim(0, 11); plt.ylim(150, 185)
plt.xlabel('day')
plt.ylabel('lbs')
plt.show()
def plot_hypothesis3():
def plot_hypothesis3():
weights = [158.0, 164.2, 160.3, 159.9, 162.1, 164.6,
169.6, 167.4, 166.4, 171.0, 171.2, 172.6]
plt.errorbar(range(1, 13), weights,
@ -155,7 +161,7 @@ def plot_hypothesis3():
plt.ylabel('weight (lbs)')
plt.show()
def plot_hypothesis4():
weights = [158.0, 164.2, 160.3, 159.9, 162.1, 164.6,
169.6, 167.4, 166.4, 171.0, 171.2, 172.6]
@ -170,8 +176,8 @@ def plot_hypothesis4():
book_plots.show_legend()
plt.show()
def plot_hypothesis5():
def plot_hypothesis5():
weights = [158.0, 164.2, 160.3, 159.9, 162.1, 164.6,
169.6, 167.4, 166.4, 171.0, 171.2, 172.6]
@ -186,13 +192,13 @@ def plot_hypothesis5():
book_plots.show_legend()
plt.show()
def plot_g_h_results(measurements, filtered_data,
title='', z_label='Measurements', **kwargs):
def plot_g_h_results(measurements, filtered_data,
title='', z_label='Measurements', **kwargs):
book_plots.plot_filter(filtered_data, **kwargs)
book_plots.plot_measurements(measurements, label=z_label)
book_plots.show_legend()
plt.title(title)
plt.gca().set_xlim(left=0,right=len(measurements))
if __name__ == '__main__':
create_predict_update_chart()