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2011年4月23日 _olivier_ <ol...@gm...>:
> [...]
> I have got a matrix 6x500 (so one size is much biggger than the other one)
> and I try to expand the shorter axe so that the labels on it are well
> displayed (not overlapped.
Use the aspect kwarg in matshow.
Goyo

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Hello,
This question has certainly been answered in a previous thread but after
searching around I did not find any solution...
I have got a matrix 6x500 (so one size is much biggger than the other one)
and I try to expand the shorter axe so that the labels on it are well
displayed (not overlapped.
I am googling/searching on the documentation about subplots_adjust, ... but
did not find any solution.
Here is the code that present the problem I have.
Thanks in advance for any help. Olivier
import numpy as np
from matplotlib.pylab import *
import matplotlib.pyplot as plt
sizeX = 6
sizeY = 500
xlabels = []
ylabels = []
for i in range ( 0, sizeX ):
 xlabels.append( str( i ) )
for i in range ( 0, sizeY ):
 ylabels.append( str( i ) )
dims = ( sizeX, sizeY )
data = zeros( dims )
for i in range( 0, sizeX ):
 for j in range( 0, sizeY ):
 data[ i, j ] = np.random.rand()
figure = plt.figure()
axes = figure.add_subplot( 111 )
cax = axes.matshow( data, interpolation = 'nearest' )
col = figure.colorbar( cax )
plt.show()
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2011年4月23日 jfortiv <jf...@gm...>:
>
> Hi,
>
> This actually did not work for me. Can you show me the full code that you
> used to successfully produce the time-format x-axis labels?
See attached files.
Goyo

Hi,
This actually did not work for me. Can you show me the full code that you
used to successfully produce the time-format x-axis labels?
Thanks,
James
Sebastian Berg wrote:
> 
> Hello,
> 
> don't know the foo behind it, but using
> ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
> works.
> 
> Regards,
> 
> Sebastian
> 
> On Sun, 2011年04月17日 at 19:52 -0700, jfortiv wrote:
> 
>> Hello, 
>> 
>> I'm trying to create a bar chart that looks something like a gannt
>> chart...
>> 
>> See the simple example here:
>> 
>> http://www.promana.net/making-use-of-gantt-charts/
>> 
>> I'm trying to utilize barh() and fmt_xdata to accomplish this with the
>> following:
>> 
>> #~~~~~~~~~~~~~~~~~~~~~~~
>> 
>> date1 = datetime.datetime( 2000, 3, 2)
>> date2 = datetime.datetime( 2000, 3, 6)
>> delta = datetime.timedelta(hours=6)
>> dates = mdates.drange(date1, date2, delta)
>> 
>> val = mdates.drange(date1,date2,delta) # the bar lengths
>> pos = range(len(val)) # the bar centers on the y axis
>> height=0.5 # the bar height
>> left=mdates.drange(date1,date2,delta) # the bar starting position
>> 
>> fig = plt.figure()
>> ax = fig.add_subplot(111)
>> ax.barh(pos,val,height=height,left=left,align='center',alpha=0.3)
>> ax.fmt_xdata = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
>> 
>> #~~~~~~~~~~~~~~~~~~~~~~~
>> 
>> 
>> Even with ax.fmt_xdata, I'm simply getting numbers on the x-axis instead
>> of
>> dates. Can anyone offer some pointers?
>> 
>> Thanks,
>> James
> 
> 
> 
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Hi Xavier,
Xavier Gnata, on 2011年04月23日 02:33, wrote:
> Imagine you have this code:
> 
> import numpy as np
> import matplotlib.cm as cm
> import matplotlib.mlab as mlab
> import matplotlib.pyplot as plt
> 
> delta = 0.25
> x = y = np.arange(-3.0, 3.0, delta)
> X, Y = np.meshgrid(x, y)
> Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
> Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
> Z = Z2-Z1 # difference of Gaussians
> 
> plt.imshow(Z, interpolation='nearest', cmap=cm.gray, origin='lower', extent=[-3,3,-3,3])
> Then you want to change the color of a few pixels to red.
> You have a list of coordinates (i,j) and each pixel in this list should 
> now be red.
> 
> I could play with masked arrays like in:
> http://matplotlib.sourceforge.net/examples/pylab_examples/image_masked.html
> but I would prefer a simple "display this pixel (i,j) in red whatever 
> his value is" function.
Since you're using a gray color map for that image, you won't be
able to set a particular pixel to red. You'll have to either
overlay a new image that would be masked out everywhere except
for the pixels you want to change, as you mentioned, or create
new image patches at the corresponding positions like this:
 idx2im = lambda i,j: (x[i],x[j+1],y[i],y[j+1] )
 plt.imshow([[.9]], extent=idx2im(12,12), cmap =cm.jet, origin='lower',vmin=0,vmax=1)
or something like this:
 plt.Rectangle((x[10],y[10]),width=delta,height=delta,color='red')
 ax = plt.gca()
 ax.add_artist(r)
 plt.draw()
best,
-- 
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

Hi,
Imagine you have this code:
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
delta = 0.25
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = Z2-Z1 # difference of Gaussians
plt.imshow(Z, interpolation='nearest', cmap=cm.gray, origin='lower', extent=[-3,3,-3,3])
Then you want to change the color of a few pixels to red.
You have a list of coordinates (i,j) and each pixel in this list should 
now be red.
I could play with masked arrays like in:
http://matplotlib.sourceforge.net/examples/pylab_examples/image_masked.html
but I would prefer a simple "display this pixel (i,j) in red whatever 
his value is" function.
Xavier