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Matplotlib具有变换值的第二个x轴

[英]Matplotlib Second x-axis with transformed values

I have been using a piece of code (based on the solution to another's problem given here ) to create plots of spectroscopic data with two x-axis. 我一直在使用一段代码(基于此处给出的另一个问题的解决方案)来创建具有两个x轴的光谱数据图。 The first (bottom) is in frequency units, the second (top) is just transformed to wavelength units (wavelength = 3E8/frequency). 第一个(底部)是频率单位,第二个(顶部)只是转换为波长单位(波长= 3E8 /频率)。 This was working well until I upgraded MPL to 1.4.2 after which the values on the upper axis are just the same as those on the lower axis (see example). 这很有效,直到我将MPL升级到1.4.2,之后上轴的值与下轴上的值相同(参见示例)。

A MWE (an exact copy from the MPL mailing list) is: MWE(来自MPL邮件列表的精确副本)是:

from matplotlib.transforms import Transform, BlendedGenericTransform, IdentityTransform 
import matplotlib.pyplot as plt 
from mpl_toolkits.axes_grid.parasite_axes import SubplotHost 
import numpy as np 

c = 3.e2 

class Freq2WavelengthTransform(Transform): 
    input_dims = 1 
    output_dims = 1 
    is_separable = False 
    has_inverse = True 

    def transform(self, tr): 
        return c/tr 

    def inverted(self): 
        return Wavelength2FreqTransform() 


class Wavelength2FreqTransform(Freq2WavelengthTransform): 
    def inverted(self): 
        return Freq2WavelengthTransform() 

aux_trans = BlendedGenericTransform(Freq2WavelengthTransform(), 
IdentityTransform()) 

fig = plt.figure(2) 

ax_GHz = SubplotHost(fig, 1,1,1) 
fig.add_subplot(ax_GHz) 
ax_GHz.set_xlabel("Frequency (GHz)") 


xvals = np.arange(199.9, 999.9, 0.1) 
#make some test data 
data = np.sin(0.03*xvals) 

ax_mm = ax_GHz.twin(aux_trans) 
ax_mm.set_xlabel('Wavelength (mm)') 
ax_mm.set_viewlim_mode("transform") 
ax_mm.axis["right"].toggle(ticklabels=False) 

ax_GHz.plot(xvals, data) 
ax_GHz.set_xlim(200, 1000) 

plt.draw() 
plt.show()

This produces 这产生了 MWE输出

Can any one advise me how to address this in MPL 1.4.2? 谁能告诉我如何在MPL 1.4.2中解决这个问题?

Using a combination of Adobe's answer from the thread linked to in wwii's comment, and your own code. 使用来自wwii评论中链接的线程的Adobe答案和您自己的代码。

import numpy as np
import matplotlib.pyplot as plt

c=3.e2
fig = plt.figure()    
ax1 = fig.add_subplot(111)    
ax2 = ax1.twiny()

xvals = np.arange(199.9, 999.9, 0.1)     
data = np.sin(0.03*xvals)     
ax1.plot(xvals, data)

ax1Ticks = ax1.get_xticks()   
ax2Ticks = ax1Ticks

def tick_function(X):
    V = c/X
    return ["%.3f" % z for z in V]

ax2.set_xticks(ax2Ticks)
ax2.set_xbound(ax1.get_xbound())
ax2.set_xticklabels(tick_function(ax2Ticks))

ax1.set_xlabel("Frequency (GHz)") 
ax2.set_xlabel('Wavelength (mm)')
ax1.grid(True)
plt.ylim(ymin=-1.1,ymax=1.1)
plt.show()

This produces; 这产生; 产量

I hope this helps! 我希望这有帮助!

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