# To modify 'extend' in a 2D plot

Dear Matplotlib users,

I need to plot a (time x distance) array of measurements associated with a color bar. Although time is fixed (i.e 0, 1, 2, etc..), to the number of rows, the distances are not evenly distributed (e.g are fixed to 1.22, 1.53, 1.84, 2,11.), although are always constant.

My question is simple. How can I modify the 'extent ' argument so that I represent the real distance values, and not simply evenly distributed events?

Any suggestion or comment would be greatly appreciated!

A minimal example plot is given bellow:

Jose.

···

#=================================
import matplotlib.pyplot as plt
import numpy as np

# fake data
random = np.random.randint(0, 300, size=(55,127)

fig = plt.figure()

myaspect = 100.0

# How can adjust this data to my REAL distances
# (e.g 1.22, 1.53, 1.84, 2,01) ???.
myextent=[-400,800,0,10]

cax = ax.imshow(random, aspect = myaspect, extent=myextent, vmin=0, vmax=300)
ax.set_ylabel('Time (ms)')
ax.set_xlabel('Distance (mm)')

colorbar = fig.colorbar(cax, ticks=[0,100,200,300,400])
colorbar.ax.set_yticklabels(['0','100','200','300','400'])
colorbar.ax.set_ylabel('Measurement')

plt.show()

#=================================

Dear Matplotlib users,

I need to plot a (time x distance) array of measurements associated with
a color bar. Although time is fixed (i.e 0, 1, 2, etc..), to the number
of rows, the distances are not evenly distributed (e.g are fixed to
1.22, 1.53, 1.84, 2,11.), although are always constant.

My question is simple. How can I modify the 'extent ' argument so that I
represent the real distance values, and not simply evenly distributed
events?

It sounds like you need to use the NonUniformImage:

http://matplotlib.sourceforge.net/examples/pylab_examples/image_nonuniform.html

Eric

···

On 05/26/2010 12:31 PM, Jose Guzman wrote:

Any suggestion or comment would be greatly appreciated!

A minimal example plot is given bellow:

Jose.

#=================================
import matplotlib.pyplot as plt
import numpy as np

# fake data
random = np.random.randint(0, 300, size=(55,127)

fig = plt.figure()

myaspect = 100.0

# How can adjust this data to my REAL distances
# (e.g 1.22, 1.53, 1.84, 2,01) ???.
myextent=[-400,800,0,10]

cax = ax.imshow(random, aspect = myaspect, extent=myextent, vmin=0,
vmax=300)
ax.set_ylabel('Time (ms)')
ax.set_xlabel('Distance (mm)')

colorbar = fig.colorbar(cax, ticks=[0,100,200,300,400])
colorbar.ax.set_yticklabels(['0','100','200','300','400'])
colorbar.ax.set_ylabel('Measurement')

plt.show()

#=================================

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