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I would like to announce PyUniversalLibrary version 20050623. PyUniversalLibrary is a Python wrapper for Measurement Computing's Universal Library for data acquisition on Microsoft Windows operating systems. http://www.its.caltech.edu/~astraw/pyul.html Work in Progress ---------------- Currently PyUniversalLibrary is incomplete. I have only wrapped the functions which I have personally needed, primarily buffered analog input. If you need more functionality, you will hopefully find that the start I have made in wrapping this library useful. I welcome your changes and additions. I will include them with the next release with appropriate credit.
If I run the script below (taken straight from the docs except for the imports) the script fails with a message that matshow does not return a tuple, which appears true. Dropping the extra LHS variables allows the script to run, but produces 4 separate figures. Thanks, Alan Isaac ============================================ from scipy import * from pylab import * def samplemat(dims): aa = zeros(dims) for i in range(min(dims)): aa[i,i] = i return aa dimlist = [(12,12),(128,64),(64,512),(2048,256)] for d in dimlist: fig, ax, im = matshow(samplemat(d)) show()
Hi Danny, Danny Shevitz wrote: > howdy, > > I have some beginner type questions with matshow. > > I want the origin of the axes to be the lower left of the figure. I tried: > fig=matshow(data, cmap, origin='lower') > > but that didn't seem to do anything. Actually, I want to flip the figure > over upper left->lower right diagonal and I want to > do this without explicitly transposing the matrix if possible. > > I also am having trouble with the figure size. I am working on a weird dpi > (93.65) screen. I tried > fig.set_figsize_inches((5.,5.)) > fig.set_dpi(93.6585) > > But the screen dimensions still come out off. They are in fact 5 5/16" x 5 > 5/16". Any ideas? Even though I wrote matshow, I have to admit that it was very much a 'stumble in the dark' kind of code. I basically just mucked around with imshow enough to get a matrix to display in the 'traditional' way (top-down, with properly preserved aspect ratio) and that was about it. I'm sure the code can use improvements, but at the time I can't commit any effort into it, I'm afraid. If you can extend it (the code is extremely simple) in a useful way, just send a patch over and I'm sure we can apply it. Regards, f
>>>>> "zori" == zori <zo...@vi...> writes: zori> Hi, Exploring the agg.py module of the matplotlib library, I zori> have encauntered that I cannot represent smooth arcs. For zori> example, circle appears as octagon. Could you give me an zori> idea how to manage this and what is the reason for such zori> behaviour? Here is the code of the agg_test.py changed to zori> draw arc, but not giving the desired result: Hi Zori, I updated the agg_test.py example to show how to do a few more things -- drawing curves, filling and stroking, and making affine transformations of paths and curves. Down the road I would like to replace refactor backend_agg.py and _backend_agg.cpp to use this swig wrapper of agg, so that agg users would have access to the low level agg library for customized drawing over a mpl figure. # this example uses the agg python module directly there is no # documentation -- you have to know how to use the agg c++ API to use # it import matplotlib.agg as agg from math import pi ## Define some colors red = agg.rgba8(255,0,0,255) blue = agg.rgba8(0,0,255,255) green = agg.rgba8(0,255,0,255) black = agg.rgba8(0,0,0,255) white = agg.rgba8(255,255,255,255) yellow = agg.rgba8(192,192,255,255) ## Create the rendering buffer, rasterizer, etc width, height = 600,400 stride = width*4 buffer = agg.buffer(width, height, stride) rbuf = agg.rendering_buffer() rbuf.attachb(buffer) pf = agg.pixel_format_rgba(rbuf) rbase = agg.renderer_base_rgba(pf) rbase.clear_rgba8(blue) renderer = agg.renderer_scanline_aa_solid_rgba(rbase); renderer.color_rgba8( red ) rasterizer = agg.rasterizer_scanline_aa() scanline = agg.scanline_p8() ## A polygon path path = agg.path_storage() path.move_to(10,10) path.line_to(100,100) path.line_to(200,200) path.line_to(100,200) path.close_polygon() # stroke it stroke = agg.conv_stroke_path(path) stroke.width(3.0) rasterizer.add_path(stroke) agg.render_scanlines_rgba(rasterizer, scanline, renderer); ## A curved path path = agg.path_storage() path.move_to(200,10) path.line_to(350,50) path.curve3(150,200) path.curve3(100,70) path.close_polygon() curve = agg.conv_curve_path(path) # fill it rasterizer.add_path(curve) renderer.color_rgba8( green ) agg.render_scanlines_rgba(rasterizer, scanline, renderer); # and stroke it stroke = agg.conv_stroke_curve(curve) stroke.width(5.0) rasterizer.add_path(stroke) renderer.color_rgba8( yellow ) agg.render_scanlines_rgba(rasterizer, scanline, renderer); ## Transforming a path path = agg.path_storage() path.move_to(0,0) path.line_to(1,0) path.line_to(1,1) path.line_to(0,1) path.close_polygon() rotation = agg.trans_affine_rotation(pi/4) scaling = agg.trans_affine_scaling(30,30) translation = agg.trans_affine_translation(300,300) trans = rotation*scaling*translation transpath = agg.conv_transform_path(path, trans) stroke = agg.conv_stroke_transpath(transpath) stroke.width(2.0) rasterizer.add_path(stroke) renderer.color_rgba8( black ) agg.render_scanlines_rgba(rasterizer, scanline, renderer); ## Converting a transformed path to a curve path = agg.path_storage() path.move_to(0,0) path.curve3(1,0) path.curve3(1,1) path.curve3(0,1) path.close_polygon() rotation = agg.trans_affine_rotation(pi/4) scaling = agg.trans_affine_scaling(30,30) translation = agg.trans_affine_translation(300,250) trans = rotation*scaling*translation transpath = agg.conv_transform_path(path, trans) curvetrans = agg.conv_curve_trans(transpath) stroke = agg.conv_stroke_curvetrans(curvetrans) stroke.width(2.0) rasterizer.add_path(stroke) renderer.color_rgba8( white ) agg.render_scanlines_rgba(rasterizer, scanline, renderer); ## Display it with PIL s = buffer.to_string() print len(s) import Image im = Image.fromstring( "RGBA", (width, height), s) im.show()
>>>>> "Jeff" == Jeff Peery <jef...@se...> writes: Jeff> Hello, Jeff> I'm plotting a simple xy plot and I'd like to highlight Jeff> regions that are above a threshold, say for example all Jeff> points y>=1. The method I am thinking of applying is Jeff> getting the x,y position of the point that is above the Jeff> threshold and filling the region between two vertical lines Jeff> that are right and left of the point with a bright color. Jeff> I was having some difficulty filling between two vertical Jeff> lines, I don't think I can use axvline() with fill()? It sounds like axvspan is what you want def axvspan(self, xmin, xmax, ymin=0, ymax=1, **kwargs): """ AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs) axvspan : Axis Vertical Span. xcoords are in data units and y coords are in axes (relative 0-1) units Draw a vertical span (regtangle) from xmin to xmax. With the default values of ymin=0 and ymax=1, this always span the yrange, regardless of the ylim settings, even if you change them, eg with the ylim command. That is, the vertical extent is in axes coords: 0=bottom, 0.5=middle, 1.0=top but the y location is in data coordinates. kwargs are the kwargs to Patch, eg antialiased, aa linewidth, lw edgecolor, ec facecolor, fc the terms on the right are aliases return value is the patches.Polygon instance. # draw a vertical green translucent rectangle from x=1.25 to 1.55 that # spans the yrange of the axes axvspan(1.25, 1.55, facecolor='g', alpha=0.5) For another approach, see examples/fill*.py, in particular examples/fill_between.py. But if all you want is shading across the vertical extent over an xrange, axvspan is the function for you,\. JDH
>>>>> "zori" == zori <zo...@vi...> writes: zori> Hi, Exploring the agg.py module of the matplotlib library, I zori> have encauntered that I cannot represent smooth arcs. For zori> example, circle appears as octagon. Could you give me an zori> idea how to manage this and what is the reason for such zori> behaviour? Here is the code of the agg_test.py changed to zori> draw arc, but not giving the desired result: You have to call conv_curve on the path, and then stroke the result of that curve = agg.conv_curve_path(path) stroke = agg.conv_stroke_curve(curve) agg is a heavily templated library, and one or the challenges of wrapping a template library is deciding which template combinations need to be instantiated. Since matplotlib's agg wrapper is undocumented, I'll explain some of the combinations and the naming convention now. In the agg C++ library, the equivalent calls are typedef agg::conv_stroke<path_t> stroke_t; typedef agg::conv_curve<path_t> curve_t; agg::conv_curve<path_t> curve(path); agg::conv_stroke<curve_t> stroke(curve) matplotlib basically takes the template argument and appends it to the class name, eg Agg C++ : matplotlib wrapper : agg::conv_curve<path_t> agg.conv_curve_path agg::conv_stroke<curve_t> agg.conv_stroke_curve The typedefs (path_t, curve_t, etc) are defined in swig/agg_typedefs.h in the swig directory of the matplotlib src distribution. The various curves are defined in swig/agg_conv_curve.i and the strokes in swig/agg_conv_stroke.i The stroke and converter classes thus defined are conv_curve_path - convert path to curve, maps "path"->"curve" conv_curve_trans - convert a transformed path, maps "transpath"->"curvetrans" conv_stroke_path - stroke a path conv_stroke_transpath - stroke a transpath conv_stroke_curve - stroke a curve conv_stroke_transcurve - stroke a transform of a curve conv_stroke_curvetrans - stroke a curve of a transformed path Hope this helps, JDH
Dear matplotlib-users, I have made an application for tsunami wave travel time prediction (slowmo.sf.net). The application uses the basemap toolkit and is developed on Linux. I would like to offer potential Windows users an easier way to install and test it than is currently available. For this I would need a binary windows package of the basemap toolkit in a newer version than 0.21 which is currently available. Unfortunately I do not have access to the windows compilers that are necessary to make this binary package. I would therefore be very grateful if anyone from this list has the binary or could easily produce it. Kind regards, Jesper
Hi, Exploring the agg.py module of the matplotlib library, I have encauntered that I cannot represent smooth arcs. For example, circle appears as octagon. Could you give me an idea how to manage this and what is the reason for such behaviour? Here is the code of the agg_test.py changed to draw arc, but not giving the desired result: ########################## import matplotlib.agg as agg width, height = 600,400 stride = width*4 buffer = agg.buffer(width, height, stride) rbuf = agg.rendering_buffer() rbuf.attachb(buffer) red = agg.rgba8(255,0,0,255) blue = agg.rgba8(0,0,255,255) green = agg.rgba8(0,255,0,255) black = agg.rgba8(0,0,0,255) white = agg.rgba8(255,255,255,255) yellow = agg.rgba8(192,192,255,255) path = agg.path_storage() path.move_to(10,10) path.line_to(100,100) path.line_to(200,200) path.arc_to(100,100,0,0,1,100,200) path.close_polygon() stroke = agg.conv_stroke_path(path) stroke.width(3.0) pf = agg.pixel_format_rgba(rbuf) rbase = agg.renderer_base_rgba(pf) rbase.clear_rgba8(blue) renderer = agg.renderer_scanline_aa_solid_rgba(rbase); renderer.color_rgba8( red ) rasterizer = agg.rasterizer_scanline_aa() rasterizer.add_path(stroke) scanline = agg.scanline_p8() agg.render_scanlines_rgba(rasterizer, scanline, renderer); s = buffer.to_string() print len(s) import Image im = Image.fromstring( "RGBA", (width, height), s) im.show() Thank you! Regards, Z.Danevska