The np.array
that results from this loop has 4383 rows and 6 columns. I have tried without success to use pylab.imshow()
from matplotlib(pylab) to display the array. The objective is to creat an image of the array, in wich the colors gradient represent the magnitude of the array values. Each row of the array represents the variation in depth of a lake temperature in each day (4383 days). Thus the objective is to find diferences in lake temperatures in depth and with time. Thank you
TempLake=np.zeros((N+1,Nlayers))
TempLake[0]=T0
Q=np.zeros(N+1)
Q[0]=0.0
for i in xrange(N):
Q[i+1]=Qn(HSR[i],TD[i],FW[i],TempLake[i][0])
TempLake[i+1]=main_loop(Z,z,Areat0,Areat1,TempLake[i],wind[i],Q[i],Q[i+1])
im = plt.imshow(tem, cmap='hot')
plt.colorbar(im, orientation='horizontal')
plt.show()
This is the result: The legend is fine, but the x-axis are inverted and the image doesn´t appear
This is what I need:
You can use imshow
if you just set the aspect when you call it. As follows:
im = plt.imshow(tem, cmap='hot', aspect=aspect_ratio*(cols/rows))
where aspect_ratio
here would set the actual aspect ratio you want and cols/rows
just normalizes the original aspect ratio to 1. cols
and rows
are the numbers of columns and rows (e.g. rows = data.shape[0]
, cols = data.shape[1]
).
You need to use pcolor
or pcolormesh
instead of imshow
. This is because in imshow
the aspect of figure is same as the array, which in your case is 4383x6.
import pylab as plt
import numpy as np
Z=np.array((range(1,30),range(31,60),range(61,90))).transpose()
X,Y=np.meshgrid(range(Z.shape[0]+1),range(Z.shape[1]+1))
im = plt.pcolormesh(X,Y,Z.transpose(), cmap='hot')
plt.colorbar(im, orientation='horizontal')
plt.show()
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With