matplotlib-users Mailing List for matplotlib (Page 4)

On Thursday, March 22, 2012, Alexis Praga <ale...@fr...> wrote:
> Hi,
>
> After using Matplotlib for some time, I would like to give something
> back to the community :)
> How can I contribute ? I am aware that reporting and documentating the
> project is always appreciated, but are there specific needs ? For
> exemple, does a "TODO" list exist ?
>

Alexis,

Most work that goes on is "scratching our itches", so we don't have TODO
lists per se.  However, over on the github issue tracker, you can search
for any issues that have been tagged as "need_confirmation", "wishlist", or
just see what issues have yet to be assigned to anybody.  Another way to
contribute is to review pull requests, testing them out and reporting
whether or not they work as advertised and/or they break something
unexpectedly.

We are always glad to have more eyes on matplotlib!

Cheers!
Ben Root

Hi All,

I am plotting on two different y-axes: one on the left (ax1) and one on 
the right (ax2). Both share the same x-axes. The problem I am facing 
relates back to the zorder of the legend (at least, that is what I 
think): I want it to be on the foreground at all times. In order to do 
so, I change the zorder of the ax1.legend (left y axes) such that the 
ax2.plots (right y-axes) are under ax1.legend. However, that doesn't 
work: all the plots on the right axes (so using ax2) end up above the 
legend 1 on the left, despite having a lower zorder.

Note that I am also giving the grids on both ax1 and ax2 a lower zorder 
value compared to the legends, but the grid still ends up on top of 
legend 1 on the left.

# version info:

# Python 2.6.5 (r265:79063, Apr 16 2010, 13:57:41) [GCC 4.4.3] on linux2

# NumPy 1.6.1, Matplotlib 1.1.0

import pylab as plt

import numpy as np

# plotting on the left y-axes,

ax1 = plt.axes(zorder=10)

ax1.plot(range(0,5,1), 'r', label='ax1 ax1 ax1 ax1', zorder=11)

ax1.plot(np.arange(3,4.1,1), 'r--', label='ax1 ax1 ax1 ax1', zorder=12)

gr1 = ax1.grid(zorder=13)

# legend of the left y-axes, force high zorder

leg1 = ax1.legend(loc='upper left')

leg1.set_zorder(30)

# plotting on the right y-axes,

ax2 = plt.twinx()

ax2.set_zorder(20)

ax2.plot(range(4,-1,-1), 'b', label='ax2 ax2 ax2 ax2', zorder=21)

ax2.plot(np.arange(4,2.9,-1), np.arange(3,4.1,1), 'b--',

label='ax2 ax2 ax2 ax2', zorder=22)

gr2 = ax2.grid(zorder=23)

# legend of the right y-axes, force high zorder

leg2 = ax2.legend(loc='upper right')

leg2.set_zorder(40)

print '======= zorder:'

print ' ax1: %i' % ax1.get_zorder()

print ' ax2: %i' % ax2.get_zorder()

print 'leg1: %i' % leg1.get_zorder()

print 'leg2: %i' % leg2.get_zorder()


What am I missing here?
Thanks,
David

Hi,

After using Matplotlib for some time, I would like to give something
back to the community :)
How can I contribute ? I am aware that reporting and documentating the
project is always appreciated, but are there specific needs ? For
exemple, does a "TODO" list exist ?


Thanks

PS : Last time I asked for help, I forgot to thanks the people who
replied. So, Jeff and the others, you have my thanks :)

For the following code, if I remove the transform=None a green patch is
shown.  If it is in, it is not shown.  I would think that transform=None
should have no effect.  Why is this?

Thanks,
Che


import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.path import Path

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

start = 0.2
stop = .6

verts = [
    (start, .2), # left, bottom
    (start, .4), # left, top
    (stop, .4), # right, top
    (stop, .2), # right, bottom
    (0., 0.), # ignored
    ]
codes = [Path.MOVETO,
         Path.LINETO,
         Path.LINETO,
         Path.LINETO,
         Path.CLOSEPOLY,
         ]

path = Path(verts, codes)

patch = patches.PathPatch(path, facecolor='g',
                          lw=1, edgecolor='grey',transform=None )

ax.add_patch(patch)

plt.show()

El día 21 de marzo de 2012 01:03, questions anon

> f=np.genfromtxt(inputfile, skip_header=6, dtype=None, names=True)

I don't think you should be using dtype=None if you wand a 2D array.
Also the names=True thing makes no sense to me since there isn't a row
with field names. Try just this and I guess you'll get a 2D array:

f=np.genfromtxt(inputfile, skip_header=6)

Goyo

I liked the plot very much, too.  I want to start using python and matplotlib
for my everyday engineering calculations and could use any handy matplotlib
samples.   This in particular looks great, compare to the
copied-and-copied-and-copied-over black-and-white scanned-in plot in the
design manual...no, I am not quite a fluid dynamics kind of guy, but
sometimes I need to do such job, anyway.

So, good job and thanks for contributing.
-- 
View this message in context: http://old.nabble.com/sample-to-contribute-to-mpl-gallery-tp33541388p33544585.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Mon, 12 Mar 2012 15:51:15 -0500
Benjamin Root <ben...@ou...> wrote:

> Ah, finally figured it out.  The issue is that your y-value for that
> error bar is 9.114, but you want to plot error bars that are
> +/-10.31.  That line gets thrown out by matplotlib because you can't
> plot at negative values for log scale.

Yes, I came to the same conclusion. I think matplotlib should print
some warning or raise some exception if confronted with data like that,
it can't handle.

> There is a trick that might
> work.  The set_yscale method has a kwarg "nonposy" which could be set
> to "clip".  You could also try setting to the "symlog" scale which
> might let you get away with a negative value.

I'll try that.


Thanks

Wolfgang

On Tue, Mar 20, 2012 at 4:10 PM, Daniel Hyams <dh...@gm...> wrote:

> There was a request a while back to create plots that are more
> application-oriented for the matplotlib gallery, so I'd like to submit this
> one for inclusion.  I tried to spruce it up a bit to show what MPL can do,
> and I'm sure that the folks here can improve upon it.  But at any rate,
> this is a good first iteration I think.
>
> I'm also going to try to replace the plot at wikipedia (for the Moody
> diagram) with this one.  The one at wikipedia is not quite correct in the
> way friction factors are computed, and a nice side effect is that mpl gets
> some exposure there as well (although there are probably dozens of mpl
> plots already there, but I don't know how to find them).
>
> The below is meant as constructive criticism; I certainly am committed to
> using matplotlib and offering patches here and there as I can; I would love
> to see wider adoption of it.  I also concede that in the below items, I
> might have missed something obvious.  I'm trying to approach this as a user
> who was just introduced to matplotlib, and had to create the plot that is
> attached.
>
> 1) The table mechanism, while very nice and useful, could use some
> improvement; it should be easier to specify alignment for the table cells,
> and individual fonts for each cell.
> 2) drawing the arrows was much harder than it needs to be.  Better
> defaults for arrowhead sizes would help a lot (instead of them being
> hardcoded to certain numbers, have the defaults be fungible based on how
> long the arrow is in pixel space), and I had to resort to using the
> annotate() function to draw them, after spending over an hour trying to use
> plt.arrow().  plt.arrow() had some problems drawing arrowheads on log-log
> plots, and well as not supporting a double-ended arrow.
> 3) drawing the shading using polygons was great and easy.
> 4) the title by default is placed too close to the top
> 5) the plot axis labels were clipped by default; had to pull the axis
> limits in (I know, this is a longstanding thing, but a new user would
> wrinkle their nose)
>
> All in all, the plot took a lot longer to make than I had anticipated;
> mainly due to some fussing with the issues above until I found something
> that worked.
>
> Hope that you find the sample useful.
>
> --
> Daniel Hyams
> dh...@gm...
>

I'm not one of the mpl-developers, so I can't speak about the likelihood of
inclusion, but I do think it's a great plot (esp. since my background is in
fluid mechanics). I think it'd be a great example to have, especially if
the gallery gets split up into different
categories<https://github.com/matplotlib/matplotlib/pull/714>.
(Personally,
I think it would be nice to have a category for complex, application-style
examples, and multiple categories for simplified-versions of most of the
current examples).

I agree with most of your points, but I don't have much to add on anything
except for #2: Drawing arrows has been painful for me as well. If I find
the time, I plan on putting together a PR which draws arrows using a
FancyArrowPatch and a Line2D object. Although, `annotate` works great for
it's designed purpose, it can be cumbersome for drawing simple arrows.

-Tony

thanks for all of your responses. I agree with Benjamin that I have two
issues, and firstly I need to figure out importing the text to a 2d array
before plotting.
I can take this question elsewhere but will run it by you first:
My problem seems to be that when I use np.genfromtxt it imports my 2d array
as a 1d array. I have tried using np.reshape

import numpy as np

inputfile=r"d:/BoMdata/r19000117.txt"
outputfolder=r"d:/BoMdata/outputfolder"
f=np.genfromtxt(inputfile, skip_header=6, dtype=None, names=True)


print "f is: ", f[1:2]
print "f shape: ", f.shape
print "f dtype: ", f.dtype
print "f size: ", f.size

print f.reshape(691, 886)

f is:  [ (0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 9.49085e-05, 0.00056383, 0.00132367, 0.00417144, 0.00618987,
0.00776004, 0.0094961, 0.011557, 0.0139465, 0.0166607, 0.019674, 0.0229193,
0.0262693, 0.0295119, 0.0323237, 0.0342322, 0.0341227, 0.0288054,
0.0163089, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.00245558, 0.0309294, 0.0521848, 0.0663444, 0.0706948,
0.0681689, 0.0633213, 0.0575578, 0.0514137, 0.0452683, 0.0393741,
0.0338871, 0.0288934, 0.0244262, 0.0204939, 0.0170896, 0.014127, 0.0115916,
0.00944895, 0.00765294, 0.00615862, 0.00486124, 0.00325027, 0.000950427,
9.23129e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)]
f shape:  (690,)
f dtype: [('0', '<i4'), ('0_1', '<i4'), ('0_2', '<i4'), ('0_3', '<i4'),
('0_4', '<i4'), ('0_5', '<i4'), ('0_6', '<i4'), ('0_7', '<i4'), ('0_8',
'<f8'), ('0_9', '<f8'), ('0_10', '<f8'), ('0_11', '<f8'), ('0_12', '<f8'),
('0_13', '<f8'), ('0_14', '<f8'), ('0_15', '<f8'), ('0_16', '<f8'),
('0_17', '<f8'), ('0_18', '<f8'), ('0_19', '<f8'), ('0_20', '<f8'),
('0_21', '<f8'), ('0_22', '<f8'), ('0_23', '<f8'), ('0_24', '<f8'),
('0_25', '<f8'), ('0_26', '<f8'), ('0_27', '<f8'), ('0_28', '<f8'),
('0_29', '<f8'), ('0_30', '<f8'), ('0_31', '<f8'), ('0_32', '<f8'),
('0_33', '<f8'), ('0_34', '<f8'), ('0_35', '<f8'), ('0_36', '<f8'),
('0_37', '<f8'), ('0_38', '<f8'), ('0_39', '<f8'), ('0_40', '<f8'),
('0_41', '<f8'), ('0_42', '<f8'), ('0_43', '<f8'), ('0_44', '<f8'),
('0_45', '<f8'), ('0_46', '<f8'), ('0_47', '<f8'), ('0_48', '<f8'),
('0_49', '<f8'), ('0_50', '<f8'), ('0_51', '<f8'), ('0_52', '<f8'),
('0_53', '<f8'), ('0_54', '<f8'), ('0_55', '<f8'), ('0_56', '<f8'),
('0_57', '<f8'), ('0_58', '<f8'), ('0_59', '<f8'), ('0_60', '<f8'),
('0_61', '<f8'), ('0_62', '<f8'), ('0_63', '<f8'), ('0_64', '<f8'),
('0_65', '<f8'), ('0_66', '<f8'), ('0_67', '<f8'), ('0_68', '<f8'),
('0_69', '<f8'), ('0_70', '<f8'), ('0_71', '<f8'), ('0_72', '<f8'),
('0_73', '<f8'), ('0_74', '<f8'), ('0_75', '<f8'), ('0_76', '<f8'),
('0_77', '<f8'), ('0_78', '<f8'), ('0_79', '<f8'), ('0_80', '<f8'),
('0_81', '<f8'), ('0_82', '<f8'), ('0_83', '<f8'), ('0_84', '<f8'),
('0_85', '<f8'), ('0_86', '<f8'), ('0_87', '<f8'), ('0_88', '<f8'),
('0_89', '<f8'), ('0_90', '<f8'), ('0_91', '<f8'), ('0_92', '<f8'),
('0_93', '<f8'), ('0_94', '<f8'), ('0_95', '<f8'), ('0_96', '<f8'),
('0_97', '<f8'), ('0_98', '<f8'), ('0_99', '<f8'), ('0_100', '<f8'),
('0_101', '<f8'), ('0_102', '<f8'), ('0_103', '<f8'), ('0_104', '<f8'),
('0_105', '<f8'), ('0_106', '<f8'), ('0_107', '<f8'), ('0_108', '<f8'),
('0_109', '<f8'), ('0_110', '<f8'), ('0_111', '<f8'), ('0_112', '<f8'),
('0_113', '<f8'), ('0_114', '<f8'), ('0_115', '<f8'), ('0_116', '<f8'),
('0_117', '<f8'), ('0_118', '<f8'), ('0_119', '<f8'), ('0_120', '<f8'),
('0_121', '<f8'), ('0_122', '<f8'), ('0_123', '<f8'), ('0_124', '<f8'),
('0_125', '<f8'), ('0_126', '<f8'), ('0_127', '<f8'), ('0_128', '<f8'),
('0_129', '<f8'), ('0_130', '<f8'), ('0_131', '<f8'), ('0_132', '<f8'),
('0_133', '<f8'), ('0_134', '<f8'), ('0_135', '<f8'), ('0_136', '<f8'),
('0_137', '<f8'), ('0_138', '<f8'), ('0_139', '<f8'), ('0_140', '<f8'),
('0_141', '<f8'), ('0_142', '<f8'), ('0_143', '<f8'), ('0_144', '<f8'),
('0_145', '<f8'), ('0_146', '<f8'), ('0_147', '<f8'), ('0_148', '<f8'),
('0_149', '<f8'), ('0_150', '<f8'), ('0_151', '<f8'), ('0_152', '<f8'),
('0_153', '<f8'), ('0_154', '<f8'), ('0_155', '<f8'), ('0_156', '<f8'),
('0_157', '<f8'), ('0_158', '<f8'), ('0_159', '<f8'), ('0_160', '<f8'),
('0_161', '<f8'), ('0_162', '<f8'), ('0_163', '<f8'), ('0_164', '<f8'),
('0_165', '<f8'), ('0_166', '<f8'), ('0_167', '<f8'), ('0_168', '<f8'),
('0_169', '<f8'), ('0_170', '<f8'), ('0_171', '<f8'), ('0_172', '<f8'),
('0_173', '<f8'), ('0_174', '<f8'), ('0_175', '<f8'), ('0_176', '<f8'),
('0_177', '<f8'), ('0_178', '<f8'), ('0_179', '<f8'), ('0_180', '<f8'),
('0_181', '<f8'), ('0_182', '<f8'), ('0_183', '<f8'), ('0_184', '<i4'),
('0_185', '<i4'), ('0_186', '<i4'), ('0_187', '<i4'), ('0_188', '<i4'),
('0_189', '<i4'), ('0_190', '<i4'), ('0_191', '<i4'), ('0_192', '<i4'),
('0_193', '<i4'), ('0_194', '<i4'), ('0_195', '<i4'), ('0_196', '<i4'),
('0_197', '<i4'), ('0_198', '<i4'), ('0_199', '<i4'), ('0_200', '<i4')]


Traceback (most recent call last):
  File "d:/BoMdata/plotrainfall_v3.py", line 10, in <module>
    print "f dtype: ", f.dtype[1:2]
ValueError: Field key must be an integer, string, or unicode.




On Wed, Mar 21, 2012 at 1:47 AM, Benjamin Root <ben...@ou...> wrote:

>
>
> On Mon, Mar 19, 2012 at 5:28 PM, questions anon <que...@gm...>wrote:
>
>> So when I add "np.logical_or" to the beginning of the script it makes no
>> difference to the error message that I receive.
>>
>> I have tried reshaping the array but I receive an error message of:
>> Traceback (most recent call last):
>>   File "<pyshell#0>", line 1, in <module>
>>     f.reshape(691,886)
>> ValueError: total size of new array must be unchanged
>>
>> Is there a way to use np.genfromtxt and define the rows and columns on
>> import?
>>
>> Thanks
>>
>>
> I think you have two completely separate problems.  They are completely
> unrelated to each other.  The np.logical_or() issue happens within Basemap
> while your np.genfromtext() happens in your module.  For the
> np.logical_or() issue, I suspect that there is something wrong with your
> installation (maybe EPD is conflicting with a pre-existing python
> install?).  As for np.genfromtext(), I would put the code back to the way
> it was before (the original call looked right to me).
>
> Ben Root
>
>

Oops, one thing about the graph that I forgot to point out...does the
antialiasing look a little funny?  It seems a bit inconsistent, especially
as the line goes flat.  I increased the line width in an effort to make it
less obvious;  is there some other way to improve this behavior?

> -----Original Message-----
> From: Moore, Eric (NIH/NIDDK) [F]
> Sent: Monday, March 19, 2012 1:48 PM
> To: matplotlib-users
> Subject: Re: [Matplotlib-users] xticks when using twinx()
> 
> Mario,
> 
> When you call fig.add_subplot as you are doing, ax1 is None.  I'm not
> sure why, but you don't need to set the xticks there anyway. Change
> your call to be ax1 = fig.add_subplot(111) that way ax1 != None.  Then
> plot, create ax2, plot.  You can then set the xticks by calling
> ax1.set_xticks([10,40,90]) or equivalently ax2.set_xticks([10,40,90]).
> 
> Eric
> 


Looking at the code for Figure.add_subplot in figure.py, the first line is:

if not len(args): return

Why just silently fail if no position arguments are passed?  At the very least shouldn't this print an error message?  I'm not sure that I understand the rational for just swallowing an error this way.  Anyone know why it does this?

Eric

I'm trying to make a rectangle that "highlights" a straight line of markers
such that:

1) it surrounds/contains the points, basically like:

--------------------------------------------------------------------------------------
|
  |
|       O                    O                   O                  O
         |
|
   |
|-------------------------------------------------------------------------------------

2) its height doesn't change with zoom.  (it should always be approximately
a little taller than the height of the markers' heights).

I can do (1) but so far not (2).  I'm pretty sure I need to use a blended
transform for this somehow....and possibly TransformedPath, but I'm lost as
to how to do this.

Thanks,
Che

On Tue, Mar 20, 2012 at 5:27 AM, kususe <ku...@in...> wrote:
>
> If I set the parameter "transparent" in the "savefig" function, more line are
> plotted out on the same figure, when I use the subplot function too.
> If I don't set it, all works well.
> Suggestions?

I don't follow what you're saying very well. Can you provide a minimal
and complete example to demonstrate this behavior.

Thanks,
-paul

On Tuesday, March 20, 2012, Julien Rebetez <jul...@gm...> wrote:
> Thank you for your answer.
>
> I've read the numpy tutorial and I get it that array and matrices
> behave differently.
>
> Now, what I find kind of strange is that the plot I get when directly
> feeding the matrices to scatter
> doesn't really seem to represent anything.
> I think that, if possible, showing an error or a warning would be much
> more appropriate than showing
> a plot. It would let the user know that the problem is not with her
> dataset, but with the plot.
>
> Wouldn't it be possible to simply check the shape in scatter() and
> display a warning if it has more than one dimension ?
>
> Best,
> Julien

I think this is more of an issue that we simply never tested for matrices.
 As for the shape tests, scatter can take 2d arrays, iirc, with each column
being a different color. (again, all from my memory, which would easily
fail memcheck).

Ben Root

Hi all,

There are a couple of properties I'd like my plot axes to have by default (tick2On=False for the x and ytics, and having no 'right' or 'top' spines). These seem a bit obscure to put into the rcparams, but it would be nice to not have to call some function to fix this up every time I make a new set of axes.

Is there a good way to get this to happen automatically? Some sort of callback I can register? Or would I need to subclass Axes and monkeypatch that in as the default or something?

Any suggestions welcome!

Zach

Thank you for your answer.

I've read the numpy tutorial and I get it that array and matrices
behave differently.

Now, what I find kind of strange is that the plot I get when directly
feeding the matrices to scatter
doesn't really seem to represent anything.
I think that, if possible, showing an error or a warning would be much
more appropriate than showing
a plot. It would let the user know that the problem is not with her
dataset, but with the plot.

Wouldn't it be possible to simply check the shape in scatter() and
display a warning if it has more than one dimension ?

Best,
Julien

On Tue, Mar 20, 2012 at 3:52 PM, Jerzy Karczmarczuk
<jer...@un...> wrote:
> LJulien Rebetez :
>> I've run into a strange behaviour of matplotlib while trying to figure
>> out why my data was displayed incorrectly.
>> I'm note quite sure if this is a bug or expected behaviour, but I feel
>> it's kind of counter-intuitive, so I'm posting here.
>>
>> ...
>> Now there seem to be a difference on how numpy handles A[:,0]
>> depending on if A is a np.array or np.matrix. In the case of
>> an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
>> matrix is returned. Using this matrix seems to confuse matplotlib.
>>
>> Using np.ravel or np.flatten on the slices fix that problem.
>>
>> Is there an explanation for this behaviour or should I fill a bug ?
> Don't fill a bug.
> Read  http://www.scipy.org/Tentative_NumPy_Tutorial , please.
> They explain that a slice of a matrix is a matrix, and its "view" is
> different from what you get for arrays.
>
> But, no need to reshape the stuff. Just use the "array attribute" of the
> matrix :
>
> pl.scatter(B.A[:,0], B.A[:,1], c='b')
>
> //Here 'A' is the name of the attribute, nothing to do with your array
> A; by chance it is the same...//
>
>
> The best
>
> Jerzy Karczmarczuk
>
>
> ------------------------------------------------------------------------------
> This SF email is sponsosred by:
> Try Windows Azure free for 90 days Click Here
> http://p.sf.net/sfu/sfd2d-msazure
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

LJulien Rebetez :
> I've run into a strange behaviour of matplotlib while trying to figure
> out why my data was displayed incorrectly.
> I'm note quite sure if this is a bug or expected behaviour, but I feel
> it's kind of counter-intuitive, so I'm posting here.
>
> ...
> Now there seem to be a difference on how numpy handles A[:,0]
> depending on if A is a np.array or np.matrix. In the case of
> an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
> matrix is returned. Using this matrix seems to confuse matplotlib.
>
> Using np.ravel or np.flatten on the slices fix that problem.
>
> Is there an explanation for this behaviour or should I fill a bug ?
Don't fill a bug.
Read  http://www.scipy.org/Tentative_NumPy_Tutorial , please.
They explain that a slice of a matrix is a matrix, and its "view" is 
different from what you get for arrays.

But, no need to reshape the stuff. Just use the "array attribute" of the 
matrix :

pl.scatter(B.A[:,0], B.A[:,1], c='b')

//Here 'A' is the name of the attribute, nothing to do with your array 
A; by chance it is the same...//


The best

Jerzy Karczmarczuk

On Mon, Mar 19, 2012 at 5:28 PM, questions anon <que...@gm...>wrote:

> So when I add "np.logical_or" to the beginning of the script it makes no
> difference to the error message that I receive.
>
> I have tried reshaping the array but I receive an error message of:
> Traceback (most recent call last):
>   File "<pyshell#0>", line 1, in <module>
>     f.reshape(691,886)
> ValueError: total size of new array must be unchanged
>
> Is there a way to use np.genfromtxt and define the rows and columns on
> import?
>
> Thanks
>
>
I think you have two completely separate problems.  They are completely
unrelated to each other.  The np.logical_or() issue happens within Basemap
while your np.genfromtext() happens in your module.  For the
np.logical_or() issue, I suspect that there is something wrong with your
installation (maybe EPD is conflicting with a pre-existing python
install?).  As for np.genfromtext(), I would put the code back to the way
it was before (the original call looked right to me).

Ben Root

Hello,
I've run into a strange behaviour of matplotlib while trying to figure
out why my data was displayed incorrectly.
I'm note quite sure if this is a bug or expected behaviour, but I feel
it's kind of counter-intuitive, so I'm posting here.

The attached python script does a scatter plot of some data. I'm using
the first column as the x coordinates and the second as
y. Looking at the matrix (x == y), I'd expect the three data point to
be on a diagonal line.

Now there seem to be a difference on how numpy handles A[:,0]
depending on if A is a np.array or np.matrix. In the case of
an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
matrix is returned. Using this matrix seems to confuse matplotlib.

Using np.ravel or np.flatten on the slices fix that problem.

Is there an explanation for this behaviour or should I fill a bug ?

Best regards,
Julien Rebetez

If I set the parameter "transparent" in the "savefig" function, more line are
plotted out on the same figure, when I use the subplot function too. 
If I don't set it, all works well. 
Suggestions?

thanks in advance, 
K.
-- 
View this message in context: http://old.nabble.com/Not-understable-behavior-tp33538439p33538439.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

I'd like to save an image with sole the graph. 
I set up  

ax.set_xticklabels([]) 
ax.set_frame_on(False) 

but I get an image with tra graph and some lines on the frame level, wich I
wanna remove. 
I attach the image to be more understandable (I circle in red what I'd like
to get off).
Suggestions??

Thanks in advance
http://old.nabble.com/file/p33537650/geo.png 
-- 
View this message in context: http://old.nabble.com/Remove-all-of-the-%22box-line%22-tp33537650p33537650.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Worked out. 
Thanks. 


Paul Hobson-2 wrote:
> 
> Sorry...That first line should be:
> fig, axes = plt.subplots(ncols=3)  # note: subplotS not subplot
> 
> On Mon, Mar 19, 2012 at 5:45 PM, Paul Hobson <pmh...@gm...> wrote:
>> Try it like this:
>>
>>               fig, axes = plt.subplots(3,1,1)
>>               ax1, ax2, ax3 = axes
>>               p1, = ax1.plot(self.data0,self.data1)
>>               p2, = ax2.plot(self.data0,self.data2)
>>               p3, = ax3.plot(self.data0,self.data4)
>>               for ax in axes:
>>                       ax.set_xticks([])
>>
>> -paul
> 
> ------------------------------------------------------------------------------
> This SF email is sponsosred by:
> Try Windows Azure free for 90 days Click Here 
> http://p.sf.net/sfu/sfd2d-msazure
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 

-- 
View this message in context: http://old.nabble.com/How-to-remove-x-axis-in-a-subplotted-graph-tp33500598p33537582.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

The normal shape of a figure is a rectangle. But how can I create a oblique
figure, i.e. with side length not perpendicular each other. Thanks!

-- 
*Yi-Xin Liu, PHD*
*Department of Macromolecular Science*
*Fudan University*
*Room 415, Yuejing Building *
*Handan Rd. 220, **Shanghai, China*
*Tel +86-021-65642863*
*Mobile +86-13916819745*
http://www.mendeley.com/profiles/yi-xin-liu/

Hi Mike,

On 03/19/2012 06:53 PM, Michael Droettboom wrote:
> What are you using to view the SVG?  This works for me in Inkscape,
> Firefox and Google Chrome, but fails using rsvg 2.34 (which is used by
> ImageMagick and emacs, for example).  It seems that rsvg doesn't like
> the clip path to appear after the object that uses it, even though this
> is allowed by the SVG spec.  SVG compliance is pretty spotty between
> different renderers, but I generally think rsvg is one of the worst.
thanks for the fast reply. actually i was using geeqie and i looks like
it is using a bad renderer. i am now using inkscape to render my svg
(not just for editing) and so far it do what i need it to do.

-- 
Regards
 Sebastian Ohl

 --
 Sebastian Ohl              seb...@oh...
 Kurzekampstr. 14           Tel +49 531 7998221
 D-38104 Braunschweig       Mobil +49 172 1837678

Setting interpolation="none" in imshow fixed the problem.

Thanks for the help,

Joshua

On Mon, Mar 19, 2012 at 11:34 AM, Joshua Lande <jos...@gm...> wrote:
> Hi. I have attached a screenshot of the way the image looks when
> viewed by Preview on my mac, evince on my RHEL5 machine, and the built
> in google docs image viewer.
>
> The image should look like 22x22 square pixels, but (at least for me)
> has stripes of strange looking rectangular pixels. The preview
> screenshot shows both the good and bad version of the image.
>
> I hope this makes sense.
>
> Joshua
>
> On Mon, Mar 19, 2012 at 10:59 AM, Benjamin Root <ben...@ou...> wrote:
>> On Sun, Mar 18, 2012 at 5:07 PM, Joshua Lande <jos...@gm...> wrote:
>>>
>>> Hello.
>>>
>>> I have run into a strange error where matplotlib compresses images
>>> that are saved with the eps backend. Strangely, this compression seems
>>> to happen only for images saved with certain figure sizes. I created a
>>> very simple example which produces this behavior.
>>>
>>>    import pylab as P
>>>    import numpy as np
>>>    np.random.seed(0)
>>>    z=np.random.uniform(size=(22,22))
>>>
>>>    for figsize in [.5,.55]:
>>>        F = P.figure(None,(figsize,figsize))
>>>        ax = F.add_subplot(111)
>>>        im = ax.imshow(z, origin="lower", interpolation="nearest")
>>>        ax.xaxis.set_ticks([])
>>>        ax.yaxis.set_ticks([])
>>>
>>>        P.savefig('test_%.2f.eps' % figsize)
>>>
>>> This code produces test_0.50.eps (attached) which shows ugly
>>> compression whereas test_0.55.eps (also attached) is uncompressed.
>>>
>>> Is there an easy way to disable this compression?
>>>
>>> For reference, I am using python version 2.7.2, matplotlib version
>>> 1.1.0, and for clarity I do not have a matplotlibrc file.
>>>
>>> Thanks for your help,
>>>
>>> Joshua
>>>
>>
>> Using Firefox, I see no difference between the two images.  What are you
>> using?
>>
>> Ben Root
>>