daviddoji/Kalman-and-Bayesian-Filters-in-Python
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More explicit wording to identify curves.

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I was saying 'blue curve' 'green curve', but those have no meaning,
especially if printed in black and white. Switched to explicit
$\sigma=0.2$.

Also added second std in the chart showing the 68-95-99.7 rule.
This commit is contained in:
Roger Labbe 2015-07-27 21:50:03 -07:00
parent 53b8e6f45b
commit cf224dfa63
2 changed files with 58 additions and 34 deletions
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67
03-Gaussians.ipynb
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25
code/gaussian_internal.py
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@ -48,23 +48,42 @@ def plot_gaussian (mu, variance,
def display_stddev_plot():
xs = np.arange(10,30,0.1)
var = 8; stddev = math.sqrt(var)
var = 8;
stddev = math.sqrt(var)
p2, = plt.plot (xs,[stats.gaussian(x, 20, var) for x in xs])
x = 20+stddev
# 1std vertical lines
y = stats.gaussian(x, 20, var)
plt.plot ([x,x], [0,y],'g')
plt.plot ([20-stddev, 20-stddev], [0,y], 'g')
#2std vertical lines
x = 20+2*stddev
y = stats.gaussian(x, 20, var)
plt.plot ([x,x], [0,y],'g')
plt.plot ([20-2*stddev, 20-2*stddev], [0,y], 'g')
y = stats.gaussian(20,20,var)
plt.plot ([20,20],[0,y],'b')
x = 20+stddev
ax = plt.axes()
ax.annotate('68%', xy=(20.3, 0.045))
ax.annotate('', xy=(20-stddev,0.04), xytext=(x,0.04),
arrowprops=dict(arrowstyle="<->",
ec="r",
shrinkA=2, shrinkB=2))
ax.xaxis.set_ticks ([20-stddev, 20, 20+stddev])
ax.xaxis.set_ticklabels(['$-\sigma$','$\mu$','$\sigma$'])
ax.annotate('95%', xy=(20.3, 0.02))
ax.annotate('', xy=(20-2*stddev,0.015), xytext=(20+2*stddev,0.015),
arrowprops=dict(arrowstyle="<->",
ec="r",
shrinkA=2, shrinkB=2))
ax.xaxis.set_ticks ([20-2*stddev, 20-stddev, 20, 20+stddev, 20+2*stddev])
ax.xaxis.set_ticklabels(['$-2\sigma$', '$-1\sigma$','$\mu$','$1\sigma$', '$2\sigma$'])
ax.yaxis.set_ticks([])
ax.grid(None, 'both', lw=0)
plt.show()
if __name__ == '__main__':