# Errorbar limit selection#

Illustration of selectively drawing lower and/or upper limit symbols on errorbars using the parameters uplims, lolims of errorbar.

Alternatively, you can use 2xN values to draw errorbars in only one direction.

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
x = np.arange(10)
y = 2.5 * np.sin(x / 20 * np.pi)
yerr = np.linspace(0.05, 0.2, 10)

plt.errorbar(x, y + 3, yerr=yerr, label='both limits (default)')

plt.errorbar(x, y + 2, yerr=yerr, uplims=True, label='uplims=True')

plt.errorbar(x, y + 1, yerr=yerr, uplims=True, lolims=True,
label='uplims=True, lolims=True')

upperlimits = [True, False] * 5
lowerlimits = [False, True] * 5
plt.errorbar(x, y, yerr=yerr, uplims=upperlimits, lolims=lowerlimits,
label='subsets of uplims and lolims')

plt.legend(loc='lower right')


Out:

<matplotlib.legend.Legend object at 0x7fb682cc42b0>


Similarly xuplims and xlolims can be used on the horizontal xerr errorbars.

fig = plt.figure()
x = np.arange(10) / 10
y = (x + 0.1)**2

plt.errorbar(x, y, xerr=0.1, xlolims=True, label='xlolims=True')
y = (x + 0.1)**3

plt.errorbar(x + 0.6, y, xerr=0.1, xuplims=upperlimits, xlolims=lowerlimits,
label='subsets of xuplims and xlolims')

y = (x + 0.1)**4
plt.errorbar(x + 1.2, y, xerr=0.1, xuplims=True, label='xuplims=True')

plt.legend()
plt.show()


References

The use of the following functions, methods, classes and modules is shown in this example:

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