matplotlib-users Mailing List for matplotlib

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 2012年3月12日 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
>
>