| """ |
| ======================================= |
| Different ways of specifying error bars |
| ======================================= |
| |
| Errors can be specified as a constant value (as shown in |
| :doc:`/gallery/statistics/errorbar`). However, this example demonstrates |
| how they vary by specifying arrays of error values. |
| |
| If the raw ``x`` and ``y`` data have length N, there are two options: |
| |
| Array of shape (N,): |
| Error varies for each point, but the error values are |
| symmetric (i.e. the lower and upper values are equal). |
| |
| Array of shape (2, 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 error bars. |
| """ |
|
|
| import matplotlib.pyplot as plt |
| import numpy as np |
|
|
| |
| x = np.arange(0.1, 4, 0.5) |
| y = np.exp(-x) |
|
|
| |
| error = 0.1 + 0.2 * x |
|
|
| fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True) |
| ax0.errorbar(x, y, yerr=error, fmt='-o') |
| ax0.set_title('variable, symmetric error') |
|
|
| |
| |
| lower_error = 0.4 * error |
| upper_error = error |
| asymmetric_error = [lower_error, upper_error] |
|
|
| 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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