Note
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12.3.10.1.5. Errorbar#
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.
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import numpy as np
import matplotlib.pyplot as plt
# 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]
fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True)
ax0.errorbar(x, y, yerr=error, fmt="-o")
ax0.set_title("variable, symmetric error")
ax1.errorbar(x, y, xerr=asymmetric_error, fmt="o")
ax1.set_title("variable, asymmetric error")
ax1.set_yscale("log")
plt.show()
Total running time of the script: (0 minutes 0.149 seconds)