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Cleanup and move errorbar_demo.
Split demo in to two different examples
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""" | ||
Demo of the errorbar function. | ||
""" | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
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# example data | ||
x = np.arange(0.1, 4, 0.5) | ||
y = np.exp(-x) | ||
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plt.errorbar(x, y, xerr=0.2, yerr=0.4) | ||
plt.show() | ||
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""" | ||
Demo of errorbar function with different ways of specifying error bars. | ||
Errors can be specified as a constant value (as shown in `errorbar_demo.py`), | ||
or as demonstrated in this example, they can be specified by an N x 1 or 2 x N, | ||
where N is the number of data points. | ||
N x 1: | ||
Error varies for each point, but the error values are symmetric (i.e. the | ||
lower and upper values are equal). | ||
2 x N: | ||
Error varies for each point, and the lower and upper limits (in that order) | ||
are different (asymmetric case) | ||
In addition, this example demonstrates how to use log scale with errorbar. | ||
""" | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
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# example data | ||
x = np.arange(0.1, 4, 0.5) | ||
y = np.exp(-x) | ||
# example error bar values that vary with x-position | ||
error = 0.1 + 0.2 * x | ||
# error bar values w/ different -/+ errors | ||
lower_error = 0.4 * error | ||
upper_error = error | ||
asymmetric_error = [lower_error, upper_error] | ||
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fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True) | ||
ax0.errorbar(x, y, yerr=error, fmt='-o') | ||
ax0.set_title('variable, symmetric error') | ||
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ax1.errorbar(x, y, xerr=asymmetric_error, fmt='o') | ||
ax1.set_title('variable, asymmetric error') | ||
ax1.set_yscale('log') | ||
plt.show() | ||
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