Instantly create a diagram of 2D data using python's matplotlib
If you have 2D data that you want to check immediately what the contents are, you can instantly create a diagram of that data by creating the following function in python in advance. For those who don't care about the detailed settings in the figure and just want to be easy.
quick.py
def draw(data,cb_min,cb_max): #cb_min,cb_max:Values at the bottom and top of the colorbar
import numpy as np
import matplotlib.pyplot as plt
X,Y=np.meshgrid(np.arange(data.shape[1]),np.arange(data.shape[0]))
plt.figure(figsize=(10,4)) #Specify the aspect ratio of the figure
div=20.0 #How many colors to use to draw the figure
delta=(cb_max-cb_min)/div
interval=np.arange(cb_min,abs(cb_max)*2+delta,delta)[0:int(div)+1]
plt.contourf(X,Y,data,interval)
plt.show()
with this,
In[10]: import quick
In[11]: quick.draw(data,-2,32)
If you execute, the contents of the 2D array created by numpy will be output as a color contour diagram.
** When you want to adjust the orientation of the figure **
** When you want to flip the figure left and right **
In[12]: quick.draw(data[:,::-1],-2,32)
** When you want to flip the figure upside down **
In[12]: quick.draw(data[::-1,:],-2,32)
** When you want to rotate the figure 90 degrees **
In[12]: quick.draw(data[:,::-1].transpose(),-2,32)
Invert left and right and then transpose
** When you want to rotate the figure 180 degrees **
In[12]: quick.draw(data[::-1,:][:,::-1],-2,32)
Flip upside down and then flip left and right
Reference URL: http://seesaawiki.jp/met-python/d/matplotlib
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