Jae-Joon Lee writes:
> On Fri, Oct 12, 2012 at 3:39 AM, Nikolaus Rath
> wrote:
>> matplotlib actually rescales the raw imshow data when saving to a vector
>> format? Why is that? I think it should embed the bitmap with full
>> resolution in the vector file and rely on th
Damon McDougall
writes:
> On Thu, Oct 11, 2012 at 4:00 PM, Nikolaus Rath
> wrote:
>> When saving the figure in some vector graphics format, I
>> don't see what the meaning of the dpi is at all.
>
> Sure, I use `dpi=` all the time for vector formats. Purely bec
Hello,
I'm confused by the dpi property of figures that can be set in
matplotlibrc or passed to pyplot.figure().
It seems to me that dpi is really a property of the backend, not the
figure, and the only place to specify it ought to be when saving into a
bitmap file.
For example, when showing a
Michael Droettboom writes:
>> For some reason, my matplotlib isn't able to print percent signs ('%')
>> properly:
>
> It's a known bug, fixed since 1.1.1.
>
> https://github.com/matplotlib/matplotlib/issues/1211
Indeed. Luckily 1.2.0~rc2-1 is in experimental, and upgrading fixed the
problem. Than
Benjamin Root writes:
>> >>> For some reason, my matplotlib isn't able to print percent signs ('%')
>> >>> properly:
>> >>>
>> >>> [1] inspiron:~/tmp# cat mplbug.py
>> >>>
>> >>> import matplotlib
>> >>> import matplotlib.pyplot as plt
>> >>> import numpy as np
>> >>>
>> >>> print matplotlib.__ver
Damon McDougall
writes:
> On Tue, Oct 9, 2012 at 10:56 PM, Damon McDougall
> wrote:
>> On Tue, Oct 9, 2012 at 10:32 PM, Nikolaus Rath
>> wrote:
>>> Hello,
>>>
>>> For some reason, my matplotlib isn't able to print percent signs ('%
Hello,
For some reason, my matplotlib isn't able to print percent signs ('%')
properly:
[1] inspiron:~/tmp# cat mplbug.py
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
print matplotlib.__version__
plt.plot(np.arange(10), np.arange(10)**2)
plt.xlabel('Percent [%]')
plt.sa
Benjamin Root writes:
> On Sunday, August 5, 2012, Nikolaus Rath wrote:
>
>> Hello,
>>
>> The following code shows the plot right away as expected:
>>
>> # python
>> Python 2.7.3rc2 (default, Apr 22 2012, 22:30:17)
>> [GCC 4.6.3] on linux2
>>
Hello,
The following code shows the plot right away as expected:
# python
Python 2.7.3rc2 (default, Apr 22 2012, 22:30:17)
[GCC 4.6.3] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib
>>> matplotlib.__version__
'1.1.1rc2'
>>> import matplotli
Hello,
I'm plotting a rotating phase:
# ipython --pylab
x1 = linspace(0, 2*pi, 30)
x = concatenate((x1,x1,x1,x1))
plot(x)
The resulting plot has ugly vertical lines whenever x wraps from 2*pi
back to zero.
Does someone have a nice, general way to get to get rid of such lines?
(the actual data
"Stan West" writes:
>> From: Nikolaus Rath [mailto:nikolaus-bth8mxji...@public.gmane.org]
>> Sent: Tuesday, November 02, 2010 21:38
>>
>> In [16]: matplotlib.__version__
>> Out[16]: '1.0.0'
>>
>> I attached the result of fig.savefi
e
>
> Or, you may consider to use the path_effect (available w/ v1.0).
>
> http://matplotlib.sourceforge.net/examples/pylab_examples/patheffect_demo.html
>
> Regards,
>
> -JJ
>
>
> On Wed, Nov 3, 2010 at 10:44 AM, Nikolaus Rath wrote:
>> Hello,
Hello,
I am placing a text object in a place where the background is sometimes
dark and sometimes light, so the text is hard to see. Adding a
background to the text object itself looks a bit ugly, so I am wondering
if there is a way to add a shadow to the text itself.
What's the best way to do th
Hello,
I am trying to set tick labels for a matshow plot. This works just fine
if I only work on the X axis:
res = np.diag(np.arange(10)) # dummy data
modes = [ (x+1, 0) for x in range(5) ] # dummy data
fig = plt.figure()
ax = fig.add_subplot(111)
cs = ax.matshow(res)
Eric Firing writes:
>> I don't know if there are any strict requirement on monotonicity for X
>> and Y, or if there are any cases where the plot is still valid even if
>> that property is violated. If it is a requirement, then I agree that
>> there should be a check.
>
> For sensible output, it i
Benjamin Root writes:
>> However, it seems to me that this is quite a serious bug. The contour
>> documentation on
>>
>> http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.Axes.contour
>> does not mention this requirement, and obviously the contour method
>> itself does not even b
Benjamin Root writes:
> On Thu, Oct 28, 2010 at 3:31 PM, Nikolaus Rath
> wrote:
>
>> Hello,
>>
>> I'm having a weird problem with a contour plot. Consider the following
>> plots:
>>
>> import cPickle as pickle
>> import matplotlib.p
Hello,
I'm having a weird problem with a contour plot. Consider the following
plots:
import cPickle as pickle
import matplotlib.pyplot as plt
(Theta, Phi, Bnormal) = pickle.load(open('trouble.pickle', 'rb'))
plt.figure(0)
for i in [0, 300]:
plt.plot(Theta, Bnormal[:, i], label='Bnormal at Phi
On 10/25/2010 11:18 AM, Jae-Joon Lee wrote:
> On Mon, Oct 25, 2010 at 10:45 PM, Nikolaus Rath wrote:
>> So I have to instantiate GridSpec with a (rows, column), but when I
>> index the grid I have to use (column, row).
>>
>> Is there any reason for this counterintuitive
Hello,
I just noticed that in order to get a 3 row by 4 column grid, I have to
do
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
def make_ticklabels_invisible(fig):
for i, ax in enumerate(fig.axes):
ax.text(0.5, 0.5, "ax%d" % (i+1), v
Hello,
I would like to create subplots with different sizes using the object
oriented API. However, it seems that the subplot2grid() method exists
only in pyplot, but not as a Figure instance method. Am I looking in the
wrong place? How do I use subplot2grid with an existing Figure object?
Thank
Ryan May writes:
> On Jul 30, 2010, at 14:34, Nikolaus Rath
> wrote:
>
>> Hi,
>>
>> Consider this:
>>
>> X = np.linspace(0.70, 1.1, 100)
>> Y = np.linspace(-1.19, 1.19, 70)
>> (Xs, Ys) = np.meshgrid(X, Y)
>> Z = np.sqrt((Xs-0.9)**2 + Ys
Hi,
Consider this:
X = np.linspace(0.70, 1.1, 100)
Y = np.linspace(-1.19, 1.19, 70)
(Xs, Ys) = np.meshgrid(X, Y)
Z = np.sqrt((Xs-0.9)**2 + Ys**2) - 0.10
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contour(X, Y, Z)
fig.show()
This works, but gives the y axis a different scale than the x axis
Jeff Whitaker writes:
> On 7/28/10 8:32 PM, Nikolaus Rath wrote:
>> Hello,
>>
>> What is the best way to generate a contour plot from a set of
>> non-uniformly sampled data (i.e., the datapoints do not lie on the
>> points of a rectangular grid but are rando
Hello,
What is the best way to generate a contour plot from a set of
non-uniformly sampled data (i.e., the datapoints do not lie on the
points of a rectangular grid but are randomly distributed)?
Thanks,
-Nikolaus
--
»Time flies like an arrow, fruit flies like a Banana.«
PGP fingerprin
Hello,
I would like to draw a couple of contour plots. The plots are on
separate figures, but they should all have exactly the same color
mapping (i.e, the same Z value should correspond to the same color in
all plots).
What's the best way to achieve this?
From the documentation I gather that I
Hi,
I have a 1d array Z that unfortunately contains information about a two
dimensional surface. The mapping is nontrivial (i.e. Z is not just a
sequence of column or row information that I could reshape) but
homogenous (i.e. there is a rectangular grid and Z contains data for
each vertex). The x
aled values.
>>
>> Thanks,
>> -Niko
>>
>>
>> I did not try vmin and vmax, because
>> On 04/26/2010 02:31 PM, Jae-Joon Lee wrote:
>>> Did you try to change vmin, vmax?
>>>
>>> http://matplotlib.sourceforge.net/api/pyplot_api.html#matp
yplot_api.html#matplotlib.pyplot.imshow
>
> If this is not what you want, please describe more explicitly why the
> colorbar is wrong.
>
> Regards,
>
> -JJ
>
>
> On Mon, Apr 26, 2010 at 11:37 AM, Nikolaus Rath wrote:
>> The problem with imshow is, that it rescales the
Hello,
I have 2d array with fourier amplitudes that I would like to plot. I
found two options: contourf and imshow. This is my code:
omega = np.fft.rfftn(b_field, axes=(1, 0))
omega = np.abs(np.fft.fftshift(omega, axes=(1,)))
fig = plt.figure()
ax = fig.add_subplot(111)
M = om
On 04/20/2010 01:06 PM, Ryan May wrote:
> On Tue, Apr 20, 2010 at 11:40 AM, Jim Vickroy wrote:
>> Nikolaus Rath wrote:
>>
>> Hello,
>>
>> Maybe my googling skills are deficient, but I wasn't able to find any
>> information on how to define my own color
Hello,
Maybe my googling skills are deficient, but I wasn't able to find any
information on how to define my own colormap.
Can someone give me a pointer, or a basic example how to create a simple
map that e.g. maps -1 to Red, 0 to White, and 1 to Blue?
Thanks,
-Nikolaus
--
»Time flies lik
On 04/20/2010 10:29 AM, Ryan May wrote:
> On Tue, Apr 20, 2010 at 8:58 AM, Nikolaus Rath wrote:
>> Hello,
>>
>> I'm trying to plot something from 0 to 2pi:
>>
>>fig = plt.figure()
>>ax = fig.add_subplot(111)
>>ax.set_title('Radia
Hello,
I'm trying to plot something from 0 to 2pi:
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_title('Radial Magnetic Field')
ax.set_ylabel(r'Poloidal Angle $\theta$')
ax.set_xlabel(r'Toroidal Angle $\phi$')
ax.set_xticks([0, 2 * math.pi])
ax.set_xticklabels([
Hello,
When I'm calling the pyplot.plot function from ipython, I get a nice
dialog in which I can zoom, pan & save.
How can I achieve the same thing from a non-interactive program?
I tried
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contourf(stuff)
fig.show()
but this progr
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