Ffi*_*ydd 71
plt.errorbar
可用于绘制x,y,错误数据(与通常相反plt.plot
)
import matplotlib.pyplot as plt
import numpy as np
x = np.array([1, 2, 3, 4, 5])
y = np.power(x, 2) # Effectively y = x**2
e = np.array([1.5, 2.6, 3.7, 4.6, 5.5])
plt.errorbar(x, y, e, linestyle='None', marker='^')
plt.show()
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plt.errorbar
接受相同的参数plt.plot
与另外yerr
和xerr
其默认为无(即如果你保留空白,将作为动作plt.plot
).
您可以通过此示例找到答案:errorbar_demo_features.py
"""
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
# 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()
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这个图是这样的:
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