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From: Joshua Lande <joshualande@gm...>  20120418 23:25:04

I am running into problems where histograms are not autoscaling correctly. I have filed a bug report on github: https://github.com/matplotlib/matplotlib/issues/841 Below is a copy of the github bug report:  I am running into problems where histograms are not autoscaling correctly. Below is a very simple example which reproduces this problem: ``` import pylab as P P.hist([3000,3010, 3012], histtype='step') P.savefig('test.pdf') ``` When I run this example using matplotlib v1.1.0 or using the absolute latest version of matplotlib, I obtain an axes which varies from 3000<x<3012 and 0<y<3000 with no visible histogram. When I add (before saving the plot) the line: ``` P.gca().set_ylim(ymax=2.1) ``` I get a reasonable axes range and can see the histogram. I also get a reasonable axes range when I remove the command histtype='step' or when I use matplotlib v1.0.0. Thanks for your help, Joshua 
From: Benjamin Root <ben.root@ou...>  20120418 19:34:21

On Wed, Apr 18, 2012 at 3:27 PM, José Alexandre Nalon <nalon@...>wrote: > Hello, > > > Feel free to add a feature request to github. I know I already have a >> long list there, but in a few weeks I should be able to hack at them >> again and that list is what will help me remember what needs to be done. >> >> Oh, and of course, patches are always welcomed! Even if it is >> incomplete, I could take it as a starting point and clean it up. >> > > Ben, thanks for your answer. I don't have experience enough with a > project with the size of matplotlib to put my hands in it without > guidance; however, if you are willing to help me through the process, > I can try to make a patch, and I might be able to help in the future. > > If you can direct me to a function you implemented that used the > approach you suggested, I will try to understand the code and > implement it. If it is good enough, I will submit a patch. > > Thanks again. > > > Jose, Here is an example of how PolyCollection is converted into 3D: http://matplotlib.sourceforge.net/examples/mplot3d/polys3d_demo.html Of course, stem() doesn't create poly collections (I am actually not sure what it creates), but it is likely that art3d has a converter for it. Note, not all 2d collections and artists have converters. Does that help? Ben Root 
From: Benjamin Root <ben.root@ou...>  20120418 18:54:59

On Wed, Apr 18, 2012 at 2:41 PM, José Alexandre Nalon <nalon@...>wrote: > Hello, > > I need to plot 2d sequences of two kinds. I wanted them to look like > a stem plot because of other plots that are in the same text. > > There are actually two kinds of plots that I need: one is a standard > twodimensional domain, with points in the domain over a rectangular > grid; the other is a twovariable function of one independent variable: > I need this to plot complexsequences, with the markers around a > baseline. > > If I couldn't make myself clear, the first one is like the image in > the link below: > > http://www.mathworks.com/help/techdoc/ref/stem3.html > > I couldn't find a link to an image similar to the second kind, though. > But this one is less important, as I can plot real and imaginary parts > in different axes. > > I could get something that looked ok using scatter3d. If there is a > way to emulate the stem behaviour using that, I think it is ok. But > I thought that probably there is a better way to do it. Any help is > appreciated. > > There is not something that exists right now to do that, but there isn't anything preventing that from being made except not having time to make it. Just as a rough outline of how I would approach it would be to take the output of the 2d stem function, break it down into the constituent parts (multiple collections there, I think), and pass them through the appropriate 2d_to_3d functions that are available in art3d.py (I think that is the right file). This is the general idea for many of the current mplot3d functions. the 2d_to_3d conversion step is what adds third dimension information. Feel free to add a feature request to github. I know I already have a long list there, but in a few weeks I should be able to hack at them again and that list is what will help me remember what needs to be done. Oh, and of course, patches are always welcomed! Even if it is incomplete, I could take it as a starting point and clean it up. Cheers! Ben Root 
From: José Alexandre Nalon <nalon@te...>  20120418 18:42:02

Hello, I need to plot 2d sequences of two kinds. I wanted them to look like a stem plot because of other plots that are in the same text. There are actually two kinds of plots that I need: one is a standard twodimensional domain, with points in the domain over a rectangular grid; the other is a twovariable function of one independent variable: I need this to plot complexsequences, with the markers around a baseline. If I couldn't make myself clear, the first one is like the image in the link below: http://www.mathworks.com/help/techdoc/ref/stem3.html I couldn't find a link to an image similar to the second kind, though. But this one is less important, as I can plot real and imaginary parts in different axes. I could get something that looked ok using scatter3d. If there is a way to emulate the stem behaviour using that, I think it is ok. But I thought that probably there is a better way to do it. Any help is appreciated.  José Alexandre Nalon nalon@... 
From: Benjamin Root <ben.root@ou...>  20120418 18:40:43

On Wed, Apr 18, 2012 at 12:40 PM, hari jayaram <harijay@...> wrote: > Hi > I am fairly new to matplotlib. > > I have 384 x,y plots that I want to arrange into a 24 by 16 array of > subplots with each subplot being atleast 4 inches by 4 inches. > > I am creating the figure using a large size so that everything will fit > > fig = plt.figure(figsize=(96,64),dpi=72) > > I then have my for loop go through my datastructure and add the > subplots to this figure. In addition , each subplot has four > dataranges plotted into it. > > ax = fig.add_subplot(24,16,index + 1) > par1 = ax.twinx() > par2 = ax.twinx() > par3 = ax.twinx() > par4 = ax.twinx() > par1.plot(xs,ys,"o",xcalc,ycalc) > par2.plot(xcalc,my_derivative,color="black") > par4.plot(xcalc,my_unsmooth_derivative,color="cyan") > > In the present form I create a one pane window that shows all 384 > plots and then navigate between the plots using pan. > > My question is : Is there a more elegant way to do this? . Is there a > way instead to create a small shrunken down figure and then zoom in > one cell at a time?. The figure navigation controls only zoom with > respect to an axes. Is there a way to zoom w.r.t the whole figure > interactively. > > > Thanks for your help > > Hari > > mpl_toolkits.axes_grid1 can allow you to "share" all of the axes. All x and y lims will be the same and any change to one will reflect everywhere else. Does that help? Ben Root 
From: Christoph Gohlke <cgohlke@uc...>  20120418 17:47:15

On 4/18/2012 7:00 AM, Werner F. Bruhin wrote: > On 18/02/2010 22:41, Werner F. Bruhin wrote: >> Using numpy with "/arch nosse" solved the issue. >> >> Probably OT here, but does anyone know if numpy will in the future be >> able to dynamically switch on/off the SSEx support? > I am running again into crashes with matplotlib/numpy on Windows XP > running on AMD Athlon type machiens. > > I distribute the application with py2exe, so on my machine I install > numpy with "/arch nosse". > > This works on a test machine with my older program version which uses > Python 2.5, matplotlib 0.99 and numpy 1.0.4, now with my newer stuff I > use Python 2.6, still matplotlib 0.99 and numpy 1.3 (as there is no > 1.0.4 for Py 2.6), with this configuration my program crashes on the > Athlon CPU. > > Tried upgrading to 1.4.1 and 1.5.1 of numpy (still using /arch nosse) > but still see the same crash with an error code of "0xc000001d". > > Short term a 1.0.4 for Python 2.6 would be an o.k. work around, but I > really like to get a something better. Would an upgrade of matplotlib help? > > Werner > matplotlib0.99.3.win32py2.6 should work with numpy1.4.1win32superpackpython2.6.exe There was a bug prior to 0.99.2 (IIRC) that would crash on older Pentium computers. If matplotlib0.99.3 does crash with numpy1.4.1, please send a small script and let us know exactly where and in which module it crashes, and the capabilities/model of your processor. If possible, upgrade to numpy 1.6.1 and matplotlib 1.1. Christoph 
From: Goyo <goyodiaz@gm...>  20120418 16:52:51

El día 18 de abril de 2012 07:59, questions anon <questions.anon@...> escribió: > I am not exactly sure how to use datetime objects instead of strings. > This is the code I am working with at the moment and the code works except > for the dates, they are just weird numbers along the xaxis. Seems like you're plotting yearmonthlist in the x axis, which is a list of strings and each string is the concatenation of the string representations of two numbers. So numbers in the x axis are to be expected. You can create datetime objects this way: d = datetime.datetime(year, month, 1) Then create an array of datetime objects and use it as the x parameter to plot. Goyo 
From: Benjamin Root <ben.root@ou...>  20120418 16:52:45

On Wed, Apr 18, 2012 at 10:00 AM, Werner F. Bruhin <werner.bruhin@...>wrote: > On 18/02/2010 22:41, Werner F. Bruhin wrote: > > Using numpy with "/arch nosse" solved the issue. > > > > Probably OT here, but does anyone know if numpy will in the future be > > able to dynamically switch on/off the SSEx support? > I am running again into crashes with matplotlib/numpy on Windows XP > running on AMD Athlon type machiens. > > I distribute the application with py2exe, so on my machine I install > numpy with "/arch nosse". > > This works on a test machine with my older program version which uses > Python 2.5, matplotlib 0.99 and numpy 1.0.4, now with my newer stuff I > use Python 2.6, still matplotlib 0.99 and numpy 1.3 (as there is no > 1.0.4 for Py 2.6), with this configuration my program crashes on the > Athlon CPU. > > Tried upgrading to 1.4.1 and 1.5.1 of numpy (still using /arch nosse) > but still see the same crash with an error code of "0xc000001d". > > Short term a 1.0.4 for Python 2.6 would be an o.k. work around, but I > really like to get a something better. Would an upgrade of matplotlib > help? > > Werner > > I think we have some confusion for version numbers. There was never a version 1.0.4 of mpl. There was a version 1.0.1, but not 1.0.4. Also, you mention numpy version 1.0.4, I certainly would hope you are referring to numpy 1.4.0. Could you please doublecheck your version numbers so we can get a better idea of what is happening? Thanks, Ben Root 
From: hari jayaram <harijay@gm...>  20120418 16:41:05

Hi I am fairly new to matplotlib. I have 384 x,y plots that I want to arrange into a 24 by 16 array of subplots with each subplot being atleast 4 inches by 4 inches. I am creating the figure using a large size so that everything will fit fig = plt.figure(figsize=(96,64),dpi=72) I then have my for loop go through my datastructure and add the subplots to this figure. In addition , each subplot has four dataranges plotted into it. ax = fig.add_subplot(24,16,index + 1) par1 = ax.twinx() par2 = ax.twinx() par3 = ax.twinx() par4 = ax.twinx() par1.plot(xs,ys,"o",xcalc,ycalc) par2.plot(xcalc,my_derivative,color="black") par4.plot(xcalc,my_unsmooth_derivative,color="cyan") In the present form I create a one pane window that shows all 384 plots and then navigate between the plots using pan. My question is : Is there a more elegant way to do this? . Is there a way instead to create a small shrunken down figure and then zoom in one cell at a time?. The figure navigation controls only zoom with respect to an axes. Is there a way to zoom w.r.t the whole figure interactively. Thanks for your help Hari 
From: francesco oteri <francesco.oteri@gm...>  20120418 14:34:54

Hi Werner Il giorno 18 aprile 2012 16:00, Werner F. Bruhin <werner.bruhin@...> ha scritto: > On 18/02/2010 22:41, Werner F. Bruhin wrote: > > Using numpy with "/arch nosse" solved the issue. > > > > Probably OT here, but does anyone know if numpy will in the future be > > able to dynamically switch on/off the SSEx support? > I am running again into crashes with matplotlib/numpy on Windows XP > running on AMD Athlon type machiens. > > I distribute the application with py2exe, so on my machine I install > numpy with "/arch nosse". > > This works on a test machine with my older program version which uses > Python 2.5, matplotlib 0.99 and numpy 1.0.4, now with my newer stuff I > use Python 2.6, still matplotlib 0.99 and numpy 1.3 (as there is no > 1.0.4 for Py 2.6), with this configuration my program crashes on the > Athlon CPU. > > Tried upgrading to 1.4.1 and 1.5.1 of numpy (still using /arch nosse) > but still see the same crash with an error code of "0xc000001d". > > Short term a 1.0.4 for Python 2.6 would be an o.k. work around, but I > really like to get a something better. Would an upgrade of matplotlib > help? > > Usually upgrading your software helps! :) > Werner > > >  > Better than sec? Nothing is better than sec when it comes to > monitoring Big Data applications. Try Boundary onesecond > resolution app monitoring today. Free. > http://p.sf.net/sfu/Boundarydev2dev > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers >  Cordiali saluti, Dr.Oteri Francesco 
From: Werner F. Bruhin <werner.bruhin@fr...>  20120418 14:00:14

On 18/02/2010 22:41, Werner F. Bruhin wrote: > Using numpy with "/arch nosse" solved the issue. > > Probably OT here, but does anyone know if numpy will in the future be > able to dynamically switch on/off the SSEx support? I am running again into crashes with matplotlib/numpy on Windows XP running on AMD Athlon type machiens. I distribute the application with py2exe, so on my machine I install numpy with "/arch nosse". This works on a test machine with my older program version which uses Python 2.5, matplotlib 0.99 and numpy 1.0.4, now with my newer stuff I use Python 2.6, still matplotlib 0.99 and numpy 1.3 (as there is no 1.0.4 for Py 2.6), with this configuration my program crashes on the Athlon CPU. Tried upgrading to 1.4.1 and 1.5.1 of numpy (still using /arch nosse) but still see the same crash with an error code of "0xc000001d". Short term a 1.0.4 for Python 2.6 would be an o.k. work around, but I really like to get a something better. Would an upgrade of matplotlib help? Werner 
From: Naljer <mn8l0l@go...>  20120418 11:29:07

Hi, I would like to use the preinstalled backends like TKAgg an so on with python2.7. My standardpython is 2.6 and python 2.7 doesnt find the backends. python2.7: import matplotlib matplotlib.use('TkAgg') from pylab import * error something like: no tkinter installed Please help! :)  View this message in context: http://old.nabble.com/installlinkmatplotlibbackendinparallelpythonversiontp33707166p33707166.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Chao YUE <chaoyuejoy@gm...>  20120418 08:49:47

Dear all, I draw a scatter plot. it returns matplotlib.collections.PathCollection object. then how can I set the size of the markers? for a matplotlib.lines.Line2D object, there is a method set_markersize which can be used to set markersize. but no such method for matplotlib.collections.PathCollection object? thanks et cheers, Chao  *********************************************************************************** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCEIPSL) UMR 1572 CEACNRSUVSQ Batiment 712  Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ************************************************************************************ 
From: questions anon <questions.anon@gm...>  20120418 05:59:57

I am not exactly sure how to use datetime objects instead of strings. This is the code I am working with at the moment and the code works except for the dates, they are just weird numbers along the xaxis. Any help will be greatly appreciated. import numpy as np import matplotlib.pyplot as plt from numpy import ma as MA from mpl_toolkits.basemap import Basemap from datetime import datetime import os from osgeo import gdal, gdalnumeric, ogr, osr import glob from datetime import date, timedelta import matplotlib.dates as mdates import time rainmax=[] yearmonthlist=[] yearmonth_int=[] OutputFolder=r"E:/test_out/" GLOBTEMPLATE = r"e:/Rainfall/rainfall{year}/r{year}{month:02}??.txt" def accumulate_month(year, month): files = glob.glob(GLOBTEMPLATE.format(year=year, month=month)) monthlyrain=[] monthlyrainaust=[] for ifile in files: f=np.genfromtxt(ifile,skip_header=6) monthlyrain.append(f) yearmonth=str(year)+str(month) d=datetime.strptime(yearmonth, '%Y%m') date_string=d.strftime('%Y%m') yearmonthint=int(date_string) yearmonth_int.append(yearmonthint) yearmonthlist.append(yearmonth) r_max=np.max(monthlyrain) rainmax.append(r_max) ###loop through months and years stop_month = datetime(2011, 04, 01) month = datetime(2011, 01, 01) while month < stop_month: accumulate_month(month.year, month.month) month += timedelta(days=32) month = month.replace(day=01) x=yearmonthlist y=rainmax x2=yearmonth_int print x, y, x2 fig, ax=plt.subplots(1) z=np.polyfit(x2,y,1) p=np.poly1d(z) plt.plot(x,y) plt.plot(x,p(x2),'r') #add trendline to plot print "y=%.6fx+(%.6f)"%(z[0],z[1]) fig.autofmt_xdate() ax.fmt_xdata=mdates.DateFormatter('%Y%m') ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y%m')) plt.xlabel("yearmonth") plt.ylabel("Precipitation (mm)") plt.title("Max monthly Precipition") plt.savefig(OutputFolder+"MaxMonthlyPrecip.png") plt.show() On Fri, Apr 13, 2012 at 2:31 AM, Goyo <goyodiaz@...> wrote: > El día 12 de abril de 2012 03:46, questions anon > <questions.anon@...> escribió: > > > I am not sure how to recognise that xaxis are dates like 20110101, > > 20110102, 20110103 etc. > > Use datetime objects instead of strings. > > Goyo > 