matplotlib:绘制n作为值的numpy数组

Question

我有一个看起来像这样的数组:

k = numpy.array([(1.,0.001), (1.1, 0.002), (None, None), 
                 (1.2, 0.003), (0.99, 0.004)])

我想绘制不是的值(None, None)并保留数组值的索引.也就是说,只要(None, None)有价值,我就想要一个差距.

完成后,我想绘制

y = k[:,0] + k[:,1]

但我甚至无法将数组添加到一起.我尝试屏蔽数组,但我丢失了原始k数组的索引值.

一个最小的例子:

import matplotlib.pyplot as pyplot
import numpy

x = range(5)
k = numpy.array([(1.,0.001), (1.1, 0.002), (None, None), 
                 (1.2, 0.003), (0.99, 0.004)])

Fig, ax = pyplot.subplots()

# This plots a gap---as desired
ax.plot(x, k[:,0], 'k-')

# I'd like to plot
#     k[:,0] + k[:,1]
# but I can't add None

# Here I get rid of the (None, None) values so I can add
# But I lose the original indexing
mask = k != (None, None)
y = k[mask].reshape((-1,2))

ax.plot(range(len(y)), y[:,0]+y[:,1], 'k--')

Answer 1

您可以使用numpy.nan代替None。

import matplotlib.pyplot as pyplot
import numpy

x = range(5)
k = numpy.array([(1.,0.001), (1.1, 0.002), (numpy.nan, numpy.nan), 
                 (1.2, 0.003), (0.99, 0.004)])

Fig, ax = pyplot.subplots()

# This plots a gap---as desired
ax.plot(x, k[:,0], 'k-')

ax.plot(range(len(y)), y[:,0]+y[:,1], 'k--')

或者您也可以屏蔽x值，这样索引在x和y之间保持一致

import matplotlib.pyplot as pyplot
import numpy

x = range(5)
y = numpy.array([(1.,0.001), (1.1, 0.002), (numpy.nan, numpy.nan), 
                 (1.2, 0.003), (0.99, 0.004)])

Fig, ax = pyplot.subplots()


ax.plot(range(len(y)), y[:,0]+y[:,1], 'k--')
import matplotlib.pyplot as pyplot
import numpy

x = range(5)
k = numpy.array([(1.,0.001), (1.1, 0.002), (None, None), 
                 (1.2, 0.003), (0.99, 0.004)])

Fig, ax = pyplot.subplots()

# This plots a gap---as desired
ax.plot(x, k[:,0], 'k-')

# I'd like to plot
#     k[:,0] + k[:,1]
# but I can't add None

arr_none = np.array([None])
mask = (k[:,0] == arr_none) | (k[:,1] == arr_none)

ax.plot(numpy.arange(len(y))[mask], k[mask,0]+k[mask,1], 'k--')