On Friday, July 27, 2012, JonBL wrote:
>
> I'm unsure about the role of numpy method arange in Matplotlib plots. All
> Matplotlib examples I have seen call numpy's method arange, and pass the
> result as the first arg to Matplotlib's plot method.
>
> But the following works as expected:
>
> --- qu
I figured out you can pass in the rasterized keyword to all of those to
change the rasterization in the output.
Also the docs say for pcolormesh it defaults to the backend if not set.
Therefore, in the case of a vector based it would output vectors if not set
to rasterize.
Haven't tested but curi
I'm unsure about the role of numpy method arange in Matplotlib plots. All
Matplotlib examples I have seen call numpy's method arange, and pass the
result as the first arg to Matplotlib's plot method.
But the following works as expected:
--- quote ---
import matplotlib.pyplot as plt
import numpy
Thank you for the help!
Daπid wrote:
>
> On Sat, Jul 28, 2012 at 12:22 AM, surfcast23 wrote:
>> Am I reading (bins[1]-bins[0]) correctly as taking the difference
>> between
>> what is in the second and first bin?
>
> Yes. I am multipliying the width of the bins by their total height.
> Surely
On Sat, Jul 28, 2012 at 12:22 AM, surfcast23 wrote:
> Am I reading (bins[1]-bins[0]) correctly as taking the difference between
> what is in the second and first bin?
Yes. I am multipliying the width of the bins by their total height.
Surely there are cleaner and more general ways
(say, when the
That worked beautifully thank you!
Am I reading (bins[1]-bins[0]) correctly as taking the difference between
what is in the second and first bin?
Daπid wrote:
>
> I guess it is showing, but you have many data points, so the gaussian
> is too small down there. You have to increase its values t
I guess it is showing, but you have many data points, so the gaussian
is too small down there. You have to increase its values to make both
areas fit:
plt.plot(bins, N*(bins[1]-bins[0])*y, 'r--', linewidth=1)
And you will get a nice gaussian fitting your data.
On Fri, Jul 27, 2012 at 11:12 PM,
Thanks for catching that sigma was still a vector! I am no longer getting the
errors, but the best fit line is not showing up.Is there something else I am
missing ?
BTW thanks for the heads up on the np.mean and np.standard functions.
Khary
Daπid wrote:
>
> On Fri, Jul 27, 2012 at 9:57 PM, su
On Fri, Jul 27, 2012 at 9:57 PM, surfcast23 wrote:
> y = mlab.normpdf( nbins, avg, sigma)
> l = plt.plot(nbins, y, 'r--', linewidth=1)
> plt.show()
You should not change bins there, as you are evaluating the gaussian
function at different values.
Also, sigma is a vector, but it should be an scal
Just tried it with nbins set to 216 and I still get the error
surfcast23 wrote:
>
> Hi David,
>
>I tried your fix
> nbins = 20
> n, bins, patches = plt.hist(C, nbins, range=None, normed=False,
> weights=None, cumulative=False, bottom=None, histtype='bar', align='mid',
> orientation='v
Hi David,
I tried your fix
nbins = 20
n, bins, patches = plt.hist(C, nbins, range=None, normed=False,
weights=None, cumulative=False, bottom=None, histtype='bar', align='mid',
orientation='vertical', rwidth=None, log = False, color=None, label=None)
plt.title("")
plt.text(25,20,'M < -21.5' '\
On 2012/07/26 10:26 PM, Jeffrey Spencer wrote:
> Thanks, that is all good info to know. I change my data to log and
> normalize it so the logNorm is just linear actually so specifying only
> levels is fine. I'll let you know if that doesn't work properly for some
> reason.
>
> Ok, yeah I looked at
Dear List,
When I run this little file (I call it testimage.py), I get a different
answer on my Mac (the correct answer) than Windows (the wrong answer).
from pylab import *
c = ones((10,20))
ax = imshow(c)
show()
print ax.get_axes().get_position()
On my Mac I get:
run testimage
Bbox(array([[ 0.
In the example you provide, bins is returned by the hist command,
whereas in your code, bins is a number that you defined as 20. So,
change:
bins = 20
plt.hist(C, bins, ...
by:
nbins = 20
n, bins, patches = plt.hist(C, nbins, ...
As a side comment, your data loading is too complex, and fail pr
Hi Francesco,
I'd like to place something like a 'title' inside a legend's box. In
my
specific case, I have a legend with 5 entries, arranged in 5 columns,
so
they're horizontally next to each other in one row. Now what I'd like
to
have is inside the legend's box
Hi Andreas,
2012/7/27 Andreas Hilboll :
>> Hi Andreas,
>>
>> 2012/7/27 Andreas Hilboll :
>>> Hi,
>>>
>>> I'd like to place something like a 'title' inside a legend's box. In my
>>> specific case, I have a legend with 5 entries, arranged in 5 columns, so
>>> they're horizontally next to each other
> Hi Andreas,
>
> 2012/7/27 Andreas Hilboll :
>> Hi,
>>
>> I'd like to place something like a 'title' inside a legend's box. In my
>> specific case, I have a legend with 5 entries, arranged in 5 columns, so
>> they're horizontally next to each other in one row. Now what I'd like to
>> have is insid
Hi Andreas,
2012/7/27 Andreas Hilboll :
> Hi,
>
> I'd like to place something like a 'title' inside a legend's box. In my
> specific case, I have a legend with 5 entries, arranged in 5 columns, so
> they're horizontally next to each other in one row. Now what I'd like to
> have is inside the legen
> On Thu, Jul 26, 2012 at 06:05:39PM +0200, Andreas Hilboll wrote:
>> > Hi Andreas,
>> >
>> > 2012/7/26 Andreas Hilboll :
>> >> Hi,
>> >>
>> >> I would like to create a figure which only contains a legend, and no
>> >> axes
>> >> at all. I would like to manually assign the colors. I found this
>> h
Hi,
I'd like to place something like a 'title' inside a legend's box. In my
specific case, I have a legend with 5 entries, arranged in 5 columns, so
they're horizontally next to each other in one row. Now what I'd like to
have is inside the legend's box a first row (above the legend entries),
wher
On 2012/07/26 9:20 PM, Jeffrey Spencer wrote:
> import numpy as np
> import matplotlib as mpl
> X, Y = np.meshgrid(arange(20),arange(20))
> Z = np.arange(20*20)
> Z = Z.reshape(20,20)
> logNorm = mpl.colors.Normalize(vmin=0,vmax=200)
> fig = mpl.pyplot.figure(10)
> ax = fig.add_subplot(111)
> surf
I am using 1.2.X and here is a minimalist example to see what happens:
Link to figure of output:
https://dl.dropbox.com/u/13534143/example.png
Example:
import numpy as np
import matplotlib as mpl
X, Y = np.meshgrid(arange(20),arange(20))
Z = np.arange(20*20)
Z = Z.reshape(20,20)
logNorm = mpl.c
Further after doing a little digging the code in
matplotlib.colorbar.Colorbar looks correct to me but doesn't work correctly.
It essentially ignores the norm value because always sets the norm to the
norm for the contour plot (eg. mappable.norm) which this is the same norm
with vmin and vmax value
On 2012/07/26 7:52 PM, Jeffrey Spencer wrote:
> I am trying to make a plot with a colorbar that has a reduced axis over
> which the colorbar is executed.
>
> This is set via passing in a norm to contourf:
> logNorm = colors.Normalize(vmax=0,vmin=-100)
> surf = ax.contourf(X,Y,logZ
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