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遮罩级数上的Matplotlib插值

matplotlib python

hootnot · 技术社区 · 7 年前

我有一组数据,从中生成3个图(参见示例)。顶部绘图是从一个完整的集合创建的,其他两个是从一个子集创建的。

我想看到的是,第二个和第三个图中的线是连续的。如何做到这一点? 下面是一个来自 https://scipy-cookbook.readthedocs.io/items/Matplotlib_Plotting_values_with_masked_arrays.html

import numpy as np
import matplotlib.pyplot as plt

# suppose we have full serie of y values and 2 others that can have gaps
# but always one is available like:
# y:    10, 20, 30, 40 , 50
# y2:    1,  4, -,  -  , 12
# y3:    -,  -, 6,  8  ,  -

y_values = [92,94,100,97,98,102,99,101,97,102,99,105,101]
# prepare for masking arrays - 'conventional' arrays won't do it
y_values = np.ma.array(y_values)

# from y artifically create y2 and y2
# give a threshold
threshold = 99

y2_values = np.ma.masked_where(y_values < threshold, [v-50 for v in y_values])
y3_values = np.ma.masked_where(~(y_values < threshold), [v-80 for v in y_values])
x_values = [0,1,2,3,4,5,6,7,8,9,10,11,12]

fig, ax = plt.subplots(3, sharex=True, facecolor='w')
fig.subplots_adjust(hspace=0.25)

#plot all data
ax[0].plot(x_values, y_values) #,'ko')
ax[0].set_title('All values')

ax[1].plot(x_values, y2_values) #,'ko')
ax[1].set_title('y2-values')
#ax = plt.subplot(313)

ax[2].plot(x_values, y3_values) #,'ko')
ax[2].set_title('y3-values')
fig.savefig("3sp.png")

1 回复 | 直到 7 年前

ImportanceOfBeingErnest 7 年前

[-- -- 50 -- -- 52 49 51 -- 52 49 55 51]

你可以策划

[50 52 49 51 52 49 55 51]

mask 它本身

ax.plot(x_values[~y2_values.mask], y2_values[~y2_values.mask])

完整示例:

import numpy as np
import matplotlib.pyplot as plt

y_values = [92,94,100,97,98,102,99,101,97,102,99,105,101]
y_values = np.ma.array(y_values)
threshold = 99

y2_values = np.ma.masked_where(y_values < threshold, [v-50 for v in y_values])
y3_values = np.ma.masked_where(~(y_values < threshold), [v-80 for v in y_values])
x_values = np.array([0,1,2,3,4,5,6,7,8,9,10,11,12])

fig, ax = plt.subplots(3, sharex=True, facecolor='w')
fig.subplots_adjust(hspace=0.25)

ax[0].plot(x_values, y_values, marker="o")
ax[0].set_title('All values')

ax[1].plot(x_values[~y2_values.mask], y2_values[~y2_values.mask], marker="o")
ax[1].set_title('y2-values')

ax[2].plot(x_values[~y3_values.mask], y3_values[~y3_values.mask], marker="o")
ax[2].set_title('y3-values')
plt.show()