Note
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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')
<matplotlib.legend.Legend object at 0x7f2d014dd390>
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: