[Matplotlib-users] Ploting a sparse matrix with imshow

[Jose Guzman]

Dear matplotlib users,

I am trying to plot a nxn symetric matrix containing zeros (in white) 
and ones (in black). Quite simple, I guessed. For that I use imshow as 
follows:


 imshow(W, cmap=cm.binary) # W is a Numpy Array with shape (100,100)

However, this does not work the way i would like (the ones appear very 
blur). I would need the correct representation of a grid where the 
possition 0,0 is simply the entry W[0,0] of my array.


There should be an easy way to plot this matrix, bu I cannot figure it out.

Thanks for your help in advance.

Jose
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[Matplotlib-users] Distance between y-x digits and the corresponding labels

[Jose Guzman]

Hi everybody

is there anybody to set the distance between the x/y axis numbers and 
the corresponding axis labels. I found the default distance is rather 
small, and I would like to enlarge it. I was playing around in 
.matplolibrc but I did not find anything useful.


Any suggestion??

Thanks in advance

Jose
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[Matplotlib-users] Adding 2 Line2D objects to a Subplot

[Jose Guzman]

Hi everybody

I wanted to collect a combination of plots to insert then in a subplot. 
I choose to create Line2D objects to use the .add_line() method of the 
AxesSubplot class, but unfortunately this does lead to the desired results.


Here my dummy version:

from matplotlib.lines import Line2D
from matplotlib.pyplot import figure, show

import numpy as np

def subplot_foo(n):
 returns a the combination of 2 Line2D instances 
x = np.arange(0, 200, 0.1)
y = np.random.randn(len(x))
print len(x)
#y2 = y+n

line1 = Line2D(x, y, color = 'k')
#line2 = Line2D(x,y2, 'r')

#return line1+line2
return line1


fig = figure() # create Figure object
for i in range(1,5):
ax = fig.add_subplot(2,2,i)

ax.add_line(subplot_foo(i))

show()

First, the Line2D object does not represent the plot I want to create.
Second, I cannot collect various Line2D objects into a Subplot.

Any good idea around?

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[Matplotlib-users] using plot(single_object)

[Jose Guzman]

I was wondering if there is an easy way to combine two vectors (x and y) 
into a single object to be ploted with the plot() method in matplotlib.


Untill now, I did something like:

import matplotlib.pyplot as plt
x = np.nplinspace(0,5,1000)
y = np.ones_like(x)
plt.plot(x,y) # need an object here
plt.show()

But I would like to use plt.plot(my_object, 'r').

I tried to combine x and y in lists of lists, NumPy matrices, with zip, 
etc...but it only plots a collection of plots.


Thanks a lot in advance.
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[Matplotlib-users] To modify 'extend' in a 2D plot

[Jose Guzman]

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:

Thanks a lot in advance

Jose.

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

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

fig = plt.figure()
ax = fig.add_subplot(111)

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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