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March 14, 2017 16:03
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Milla's version of horizons in python
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import numpy as np | |
import matplotlib.pyplot as plt | |
def makeLayer(y, height): | |
neg=0.0 | |
pos=0.0 | |
if y > 0: | |
if y - height >= 0: | |
pos = height | |
y -= pos | |
else: | |
pos = y | |
elif y < 0: | |
if y + height <= 0: | |
neg = height | |
y += neg | |
else: | |
neg = -y | |
return pos, neg | |
def horizonPlot(x, y, nfolds=3, negcolor='CornflowerBlue', poscolor='DarkGreen'): | |
fig, ax = plt.subplots(figsize=(17,3), dpi=300) | |
alpha = 1.0/nfolds | |
vlayer = np.vectorize(makeLayer) | |
height = np.ceil(np.abs(y).max()/nfolds) | |
while (y != 0).any(): | |
layer = vlayer(y,height) | |
y -= layer[0]; | |
y += layer[1] | |
ax.fill_between(x, 0, layer[0], color=poscolor, alpha=alpha) | |
ax.fill_between(x, height-layer[1], height, color=negcolor, alpha=alpha) | |
ax.set_yticks([]) | |
ax.set_xlim([x.min(), x.max()]) | |
ax.set_ylim([0, height]) | |
return fig | |
if 1: | |
x = np.linspace(0, np.pi*4, 137) | |
y = (2*np.random.normal(size=137) + x**2) | |
xx = np.hstack([-1*x[::-1], x]) | |
yy = np.hstack([-1*y[::-1], y]) | |
fig = horizonPlot(xx, yy, nfolds=3) |
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@miroli
What I would do is plot the neg/pos data on two separate axes