From: <wea...@us...> - 2011-01-21 21:50:23
|
Revision: 8932 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8932&view=rev Author: weathergod Date: 2011-01-21 21:50:16 +0000 (Fri, 21 Jan 2011) Log Message: ----------- Merged revisions 8931 via svnmerge from https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/v1_0_maint ........ r8931 | weathergod | 2011-01-21 15:42:45 -0600 (Fri, 21 Jan 2011) | 3 lines Fixes colors normalization with 'under' colors in LinearSegmentedColormap (values between -1 and 0 were being made positive due to an int cast). Thanks to Eoghan Harrington for discovering and supplying the patch! ........ Modified Paths: -------------- trunk/matplotlib/lib/matplotlib/colors.py Property Changed: ---------------- trunk/matplotlib/ trunk/matplotlib/doc/pyplots/README trunk/matplotlib/doc/sphinxext/gen_gallery.py trunk/matplotlib/doc/sphinxext/gen_rst.py trunk/matplotlib/examples/misc/multiprocess.py trunk/matplotlib/examples/mplot3d/contour3d_demo.py trunk/matplotlib/examples/mplot3d/contourf3d_demo.py trunk/matplotlib/examples/mplot3d/polys3d_demo.py trunk/matplotlib/examples/mplot3d/scatter3d_demo.py trunk/matplotlib/examples/mplot3d/surface3d_demo.py trunk/matplotlib/examples/mplot3d/wire3d_demo.py trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py trunk/matplotlib/lib/matplotlib/sphinxext/plot_directive.py trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png Property changes on: trunk/matplotlib ___________________________________________________________________ Modified: svnmerge-integrated - 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/branches/v0_91_maint/doc/sphinxext/plot_directive.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/plot_directive.py:6920-6925,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/plot_directive.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/plot_directive.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926 + /branches/v0_91_maint/doc/sphinxext/plot_directive.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/plot_directive.py:6920-6925,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/plot_directive.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/plot_directive.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931 Property changes on: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png ___________________________________________________________________ Modified: svn:mergeinfo - 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From: <wea...@us...> - 2011-01-22 16:40:28
|
Revision: 8934 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8934&view=rev Author: weathergod Date: 2011-01-22 16:40:21 +0000 (Sat, 22 Jan 2011) Log Message: ----------- Merged revisions 8933 via svnmerge from https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/v1_0_maint ........ r8933 | weathergod | 2011-01-22 10:35:26 -0600 (Sat, 22 Jan 2011) | 3 lines Fixing problem where reversed colormaps of LinearSegmentedColormaps were not initialized properly. Thanks to LittleBigBrain for reporting and Friedrich Romstedt for making the original patch. ........ Modified Paths: -------------- trunk/matplotlib/lib/matplotlib/cm.py Property Changed: ---------------- trunk/matplotlib/ trunk/matplotlib/doc/pyplots/README trunk/matplotlib/doc/sphinxext/gen_gallery.py trunk/matplotlib/doc/sphinxext/gen_rst.py trunk/matplotlib/examples/misc/multiprocess.py trunk/matplotlib/examples/mplot3d/contour3d_demo.py trunk/matplotlib/examples/mplot3d/contourf3d_demo.py trunk/matplotlib/examples/mplot3d/polys3d_demo.py trunk/matplotlib/examples/mplot3d/scatter3d_demo.py trunk/matplotlib/examples/mplot3d/surface3d_demo.py trunk/matplotlib/examples/mplot3d/wire3d_demo.py trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py trunk/matplotlib/lib/matplotlib/sphinxext/plot_directive.py trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png Property changes on: trunk/matplotlib ___________________________________________________________________ Modified: svnmerge-integrated - 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/branches/v0_91_maint/examples/mplot3d/wire.py:5753-5771 /branches/v0_98_5_maint/examples/mplot3d/wire.py:6581,6585,6587,6589-6609,6614,6616,6625,6652,6660-6662,6672-6673,6714-6715,6717-6732,6752-6754,6761-6773,6781,6792,6800,6802,6805,6809,6811,6822,6827,6850,6854,6856,6859,6861-6873,6883-6884,6886,6890-6891,6906-6909,6911-6912,6915-6916,6918,6920-6925,6927-6928,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080 /branches/v0_99_maint/examples/mplot3d/wire3d_demo.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/examples/mplot3d/wire3d_demo.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931 + /branches/v0_91_maint/examples/mplot3d/wire.py:5753-5771 /branches/v0_98_5_maint/examples/mplot3d/wire.py:6581,6585,6587,6589-6609,6614,6616,6625,6652,6660-6662,6672-6673,6714-6715,6717-6732,6752-6754,6761-6773,6781,6792,6800,6802,6805,6809,6811,6822,6827,6850,6854,6856,6859,6861-6873,6883-6884,6886,6890-6891,6906-6909,6911-6912,6915-6916,6918,6920-6925,6927-6928,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080 /branches/v0_99_maint/examples/mplot3d/wire3d_demo.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/examples/mplot3d/wire3d_demo.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933 Modified: trunk/matplotlib/lib/matplotlib/cm.py =================================================================== --- trunk/matplotlib/lib/matplotlib/cm.py 2011-01-22 16:35:26 UTC (rev 8933) +++ trunk/matplotlib/lib/matplotlib/cm.py 2011-01-22 16:40:21 UTC (rev 8934) @@ -25,6 +25,7 @@ return freversed def revcmap(data): + """Can only handle specification *data* in dictionary format.""" data_r = {} for key, val in data.iteritems(): if callable(val): @@ -39,32 +40,51 @@ data_r[key] = valnew return data_r +def _reverse_cmap_spec(spec): + """Reverses cmap specification *spec*, can handle both dict and tuple + type specs.""" + + if 'red' in spec: + return revcmap(spec) + else: + revspec = list(reversed(spec)) + if len(revspec[0]) == 2: # e.g., (1, (1.0, 0.0, 1.0)) + revspec = [(1.0 - a, b) for a, b in revspec] + return revspec + +def _generate_cmap(name, lutsize): + """Generates the requested cmap from it's name *name*. The lut size is + *lutsize*.""" + + spec = datad[name] + + # Generate the colormap object. + if 'red' in spec: + return colors.LinearSegmentedColormap(name, spec, lutsize) + else: + return colors.LinearSegmentedColormap.from_list(spec, spec, lutsize) + LUTSIZE = mpl.rcParams['image.lut'] _cmapnames = datad.keys() # need this list because datad is changed in loop +# Generate the reversed specifications ... + for cmapname in _cmapnames: - cmapname_r = cmapname+'_r' - cmapspec = datad[cmapname] - if 'red' in cmapspec: - datad[cmapname_r] = revcmap(cmapspec) - cmap_d[cmapname] = colors.LinearSegmentedColormap( - cmapname, cmapspec, LUTSIZE) - cmap_d[cmapname_r] = colors.LinearSegmentedColormap( - cmapname_r, datad[cmapname_r], LUTSIZE) - else: - revspec = list(reversed(cmapspec)) - if len(revspec[0]) == 2: # e.g., (1, (1.0, 0.0, 1.0)) - revspec = [(1.0 - a, b) for a, b in revspec] - datad[cmapname_r] = revspec + spec = datad[cmapname] + spec_reversed = _reverse_cmap_spec(spec) + datad[cmapname + '_r'] = spec_reversed - cmap_d[cmapname] = colors.LinearSegmentedColormap.from_list( - cmapname, cmapspec, LUTSIZE) - cmap_d[cmapname_r] = colors.LinearSegmentedColormap.from_list( - cmapname_r, revspec, LUTSIZE) +# Precache the cmaps with ``lutsize = LUTSIZE`` ... +# Use datad.keys() to also add the reversed ones added in the section above: +for cmapname in datad.keys(): + cmap_d[cmapname] = _generate_cmap(cmapname, LUTSIZE) + locals().update(cmap_d) +# Continue with definitions ... + def register_cmap(name=None, cmap=None, data=None, lut=None): """ Add a colormap to the set recognized by :func:`get_cmap`. @@ -128,7 +148,7 @@ if lut is None: return cmap_d[name] elif name in datad: - return colors.LinearSegmentedColormap(name, datad[name], lut) + return _generate_cmap(name, lut) else: raise ValueError("Colormap %s is not recognized" % name) Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py ___________________________________________________________________ Modified: svn:mergeinfo - /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931 + /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933 Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py ___________________________________________________________________ Modified: svn:mergeinfo - 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From: <md...@us...> - 2011-02-01 16:26:33
|
Revision: 8942 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8942&view=rev Author: mdboom Date: 2011-02-01 16:26:25 +0000 (Tue, 01 Feb 2011) Log Message: ----------- Merged revisions 8939 via svnmerge from https://matplotlib.svn.sf.net/svnroot/matplotlib/branches/v1_0_maint ........ r8939 | mdboom | 2011-02-01 11:02:54 -0500 (Tue, 01 Feb 2011) | 1 line [3167200] Use from PIL import Image ........ Modified Paths: -------------- trunk/matplotlib/examples/pylab_examples/image_demo3.py trunk/matplotlib/examples/pylab_examples/to_numeric.py trunk/matplotlib/examples/user_interfaces/histogram_demo_canvasagg.py trunk/matplotlib/lib/matplotlib/backend_bases.py trunk/matplotlib/lib/matplotlib/image.py Property Changed: ---------------- trunk/matplotlib/ trunk/matplotlib/doc/pyplots/README trunk/matplotlib/doc/sphinxext/gen_gallery.py trunk/matplotlib/doc/sphinxext/gen_rst.py trunk/matplotlib/examples/misc/multiprocess.py trunk/matplotlib/examples/mplot3d/contour3d_demo.py trunk/matplotlib/examples/mplot3d/contourf3d_demo.py trunk/matplotlib/examples/mplot3d/polys3d_demo.py trunk/matplotlib/examples/mplot3d/scatter3d_demo.py trunk/matplotlib/examples/mplot3d/surface3d_demo.py trunk/matplotlib/examples/mplot3d/wire3d_demo.py trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py trunk/matplotlib/lib/matplotlib/sphinxext/plot_directive.py trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png Property changes on: trunk/matplotlib ___________________________________________________________________ Modified: svnmerge-integrated - 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import Image + from PIL import Image except ImportError, exc: raise SystemExit("PIL must be installed to run this example") Modified: trunk/matplotlib/examples/pylab_examples/to_numeric.py =================================================================== --- trunk/matplotlib/examples/pylab_examples/to_numeric.py 2011-02-01 16:21:39 UTC (rev 8941) +++ trunk/matplotlib/examples/pylab_examples/to_numeric.py 2011-02-01 16:26:25 UTC (rev 8942) @@ -8,7 +8,7 @@ from pylab import * from matplotlib.backends.backend_agg import FigureCanvasAgg try: - import Image + from PIL import Image except ImportError, exc: raise SystemExit("PIL must be installed to run this example") Modified: trunk/matplotlib/examples/user_interfaces/histogram_demo_canvasagg.py =================================================================== --- trunk/matplotlib/examples/user_interfaces/histogram_demo_canvasagg.py 2011-02-01 16:21:39 UTC (rev 8941) +++ trunk/matplotlib/examples/user_interfaces/histogram_demo_canvasagg.py 2011-02-01 16:26:25 UTC (rev 8942) @@ -54,7 +54,7 @@ if 0: # pass off to PIL - import Image + from PIL import Image im = Image.fromstring( "RGB", (w,h), s) im.show() Modified: trunk/matplotlib/lib/matplotlib/backend_bases.py =================================================================== --- trunk/matplotlib/lib/matplotlib/backend_bases.py 2011-02-01 16:21:39 UTC (rev 8941) +++ trunk/matplotlib/lib/matplotlib/backend_bases.py 2011-02-01 16:26:25 UTC (rev 8942) @@ -49,7 +49,7 @@ from matplotlib.path import Path try: - import Image + from PIL import Image _has_pil = True except ImportError: _has_pil = False Modified: trunk/matplotlib/lib/matplotlib/image.py =================================================================== --- trunk/matplotlib/lib/matplotlib/image.py 2011-02-01 16:21:39 UTC (rev 8941) +++ trunk/matplotlib/lib/matplotlib/image.py 2011-02-01 16:26:25 UTC (rev 8942) @@ -1157,7 +1157,7 @@ def pilread(): 'try to load the image with PIL or return None' - try: import Image + try: from PIL import Image except ImportError: return None image = Image.open( fname ) return pil_to_array(image) Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py ___________________________________________________________________ Modified: svn:mergeinfo - 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From: <ef...@us...> - 2011-02-04 19:19:03
|
Revision: 8945 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8945&view=rev Author: efiring Date: 2011-02-04 19:18:57 +0000 (Fri, 04 Feb 2011) Log Message: ----------- Image generation no longer generates double-precision rgba; patch by C. Gohlke Image generation via color mapping was using doubles for rgba, after which the _image module was converting rgba to uint8; this patch saves time and memory by using the existing ability of the colormap to generate uint8 directly. Modified Paths: -------------- trunk/matplotlib/CHANGELOG trunk/matplotlib/lib/matplotlib/image.py Modified: trunk/matplotlib/CHANGELOG =================================================================== --- trunk/matplotlib/CHANGELOG 2011-02-01 17:57:23 UTC (rev 8944) +++ trunk/matplotlib/CHANGELOG 2011-02-04 19:18:57 UTC (rev 8945) @@ -1,3 +1,7 @@ +2011-02-04 Changed imshow to use rgba as uint8 from start to + finish, instead of going through an intermediate + step as double precision; thanks to Christoph Gohlke. - EF + 2011-01-13 Added zdir and offset arguments to contourf3d to bring contourf3d in feature parity with contour3d. - BVR @@ -8,7 +12,7 @@ 2011-01-03 Turn off tick labeling on interior subplots for pyplots.subplots when sharex/sharey is True. - JDH -2010-12-29 Implment axes_divider.HBox and VBox. -JJL +2010-12-29 Implement axes_divider.HBox and VBox. -JJL 2010-11-22 Fixed error with Hammer projection. - BVR Modified: trunk/matplotlib/lib/matplotlib/image.py =================================================================== --- trunk/matplotlib/lib/matplotlib/image.py 2011-02-01 17:57:23 UTC (rev 8944) +++ trunk/matplotlib/lib/matplotlib/image.py 2011-02-04 19:18:57 UTC (rev 8945) @@ -138,7 +138,7 @@ def _get_unsampled_image(self, A, image_extents, viewlim): """ convert numpy array A with given extents ([x1, x2, y1, y2] in - data coordinate) into the Image, given the vielim (should be a + data coordinate) into the Image, given the viewlim (should be a bbox instance). Image will be clipped if the extents is significantly larger than the viewlim. """ @@ -193,17 +193,17 @@ self._oldyslice = yslice if self._imcache is None: - if self._A.dtype == np.uint8 and len(self._A.shape) == 3: + if self._A.dtype == np.uint8 and self._A.ndim == 3: im = _image.frombyte(self._A[yslice,xslice,:], 0) im.is_grayscale = False else: if self._rgbacache is None: - x = self.to_rgba(self._A, self._alpha) + x = self.to_rgba(self._A, self._alpha, bytes=True) self._rgbacache = x else: x = self._rgbacache - im = _image.fromarray(x[yslice,xslice], 0) - if len(self._A.shape) == 2: + im = _image.frombyte(x[yslice,xslice,:], 0) + if self._A.ndim == 2: im.is_grayscale = self.cmap.is_gray() else: im.is_grayscale = False This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. |
From: <ef...@us...> - 2011-02-05 20:56:08
|
Revision: 8946 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8946&view=rev Author: efiring Date: 2011-02-05 20:56:02 +0000 (Sat, 05 Feb 2011) Log Message: ----------- speed up Normalize, LogNorm, colormapping; modified patch by C. Gohlke Modified Paths: -------------- trunk/matplotlib/CHANGELOG trunk/matplotlib/examples/pylab_examples/image_slices_viewer.py trunk/matplotlib/lib/matplotlib/colors.py Modified: trunk/matplotlib/CHANGELOG =================================================================== --- trunk/matplotlib/CHANGELOG 2011-02-04 19:18:57 UTC (rev 8945) +++ trunk/matplotlib/CHANGELOG 2011-02-05 20:56:02 UTC (rev 8946) @@ -1,3 +1,8 @@ +2011-02-05 Speed up Normalize and LogNorm by using in-place + operations and by using float32 for float32 inputs + and for ints of 2 bytes or shorter; based on + patch by Christoph Gohlke. - EF + 2011-02-04 Changed imshow to use rgba as uint8 from start to finish, instead of going through an intermediate step as double precision; thanks to Christoph Gohlke. - EF Modified: trunk/matplotlib/examples/pylab_examples/image_slices_viewer.py =================================================================== --- trunk/matplotlib/examples/pylab_examples/image_slices_viewer.py 2011-02-04 19:18:57 UTC (rev 8945) +++ trunk/matplotlib/examples/pylab_examples/image_slices_viewer.py 2011-02-05 20:56:02 UTC (rev 8946) @@ -1,5 +1,5 @@ import numpy -from pylab import figure, show +from matplotlib.pyplot import figure, show @@ -7,7 +7,7 @@ class IndexTracker: def __init__(self, ax, X): self.ax = ax - ax.set_title('use scroll wheen to navigate images') + ax.set_title('use scroll wheel to navigate images') self.X = X rows,cols,self.slices = X.shape @@ -28,7 +28,7 @@ def update(self): self.im.set_data(self.X[:,:,self.ind]) - ax.set_ylabel('slice %s'%self.ind) + ax.set_ylabel('slice %s'%self.ind) self.im.axes.figure.canvas.draw() Modified: trunk/matplotlib/lib/matplotlib/colors.py =================================================================== --- trunk/matplotlib/lib/matplotlib/colors.py 2011-02-04 19:18:57 UTC (rev 8945) +++ trunk/matplotlib/lib/matplotlib/colors.py 2011-02-05 20:56:02 UTC (rev 8946) @@ -509,20 +509,22 @@ xa = np.array([X]) else: vtype = 'array' - # force a copy here -- the ma.array and filled functions - # do force a cop of the data by default - JDH - xma = ma.array(X, copy=True) - xa = xma.filled(0) - mask_bad = ma.getmask(xma) + xma = ma.array(X, copy=False) + mask_bad = xma.mask + xa = xma.data.copy() # Copy here to avoid side effects. + del xma + # masked values are substituted below; no need to fill them here + if xa.dtype.char in np.typecodes['Float']: np.putmask(xa, xa==1.0, 0.9999999) #Treat 1.0 as slightly less than 1. # The following clip is fast, and prevents possible # conversion of large positive values to negative integers. + xa *= self.N if NP_CLIP_OUT: - np.clip(xa * self.N, -1, self.N, out=xa) + np.clip(xa, -1, self.N, out=xa) else: - xa = np.clip(xa * self.N, -1, self.N) + xa = np.clip(xa, -1, self.N) # ensure that all 'under' values will still have negative # value after casting to int @@ -532,8 +534,11 @@ # otherwise the under-range values get converted to over-range. np.putmask(xa, xa>self.N-1, self._i_over) np.putmask(xa, xa<0, self._i_under) - if mask_bad is not None and mask_bad.shape == xa.shape: - np.putmask(xa, mask_bad, self._i_bad) + if mask_bad is not None: + if mask_bad.shape == xa.shape: + np.putmask(xa, mask_bad, self._i_bad) + elif mask_bad: + xa.fill(self._i_bad) if bytes: lut = (self._lut * 255).astype(np.uint8) else: @@ -797,32 +802,60 @@ self.vmax = vmax self.clip = clip + @staticmethod + def process_value(value): + """ + Homogenize the input *value* for easy and efficient normalization. + + *value* can be a scalar or sequence. + + Returns *result*, *is_scalar*, where *result* is a + masked array matching *value*. Float dtypes are preserved; + integer types with two bytes or smaller are converted to + np.float32, and larger types are converted to np.float. + Preserving float32 when possible, and using in-place operations, + can greatly improve speed for large arrays. + + Experimental; we may want to add an option to force the + use of float32. + """ + if cbook.iterable(value): + is_scalar = False + result = ma.asarray(value) + if result.dtype.kind == 'f': + if isinstance(value, np.ndarray): + result = result.copy() + elif result.dtype.itemsize > 2: + result = result.astype(np.float) + else: + result = result.astype(np.float32) + else: + is_scalar = True + result = ma.array([value]).astype(np.float) + return result, is_scalar + def __call__(self, value, clip=None): if clip is None: clip = self.clip - if cbook.iterable(value): - vtype = 'array' - val = ma.asarray(value).astype(np.float) - else: - vtype = 'scalar' - val = ma.array([value]).astype(np.float) + result, is_scalar = self.process_value(value) - self.autoscale_None(val) + self.autoscale_None(result) vmin, vmax = self.vmin, self.vmax if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") - elif vmin==vmax: - result = 0.0 * val + elif vmin == vmax: + result.fill(0) # Or should it be all masked? Or 0.5? else: vmin = float(vmin) vmax = float(vmax) if clip: - mask = ma.getmask(val) - val = ma.array(np.clip(val.filled(vmax), vmin, vmax), - mask=mask) - result = (val-vmin) / (vmax-vmin) - if vtype == 'scalar': + mask = ma.getmask(result) + result = ma.array(np.clip(result.filled(vmax), vmin, vmax), + mask=mask) + result -= vmin + result /= vmax - vmin + if is_scalar: result = result[0] return result @@ -847,8 +880,10 @@ def autoscale_None(self, A): ' autoscale only None-valued vmin or vmax' - if self.vmin is None: self.vmin = ma.min(A) - if self.vmax is None: self.vmax = ma.max(A) + if self.vmin is None: + self.vmin = ma.min(A) + if self.vmax is None: + self.vmax = ma.max(A) def scaled(self): 'return true if vmin and vmax set' @@ -862,30 +897,29 @@ if clip is None: clip = self.clip - if cbook.iterable(value): - vtype = 'array' - val = ma.asarray(value).astype(np.float) - else: - vtype = 'scalar' - val = ma.array([value]).astype(np.float) + result, is_scalar = self.process_value(value) - val = ma.masked_less_equal(val, 0, copy=False) + result = ma.masked_less_equal(result, 0, copy=False) - self.autoscale_None(val) + self.autoscale_None(result) vmin, vmax = self.vmin, self.vmax if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin<=0: raise ValueError("values must all be positive") elif vmin==vmax: - result = 0.0 * val + result.fill(0) else: if clip: - mask = ma.getmask(val) - val = ma.array(np.clip(val.filled(vmax), vmin, vmax), + mask = ma.getmask(result) + val = ma.array(np.clip(result.filled(vmax), vmin, vmax), mask=mask) - result = (ma.log(val)-np.log(vmin))/(np.log(vmax)-np.log(vmin)) - if vtype == 'scalar': + #result = (ma.log(result)-np.log(vmin))/(np.log(vmax)-np.log(vmin)) + # in-place equivalent of above can be much faster + np.ma.log(result, result) + result -= np.log(vmin) + result /= (np.log(vmax) - np.log(vmin)) + if is_scalar: result = result[0] return result This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. |
From: <ef...@us...> - 2011-02-05 21:57:30
|
Revision: 8947 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8947&view=rev Author: efiring Date: 2011-02-05 21:57:21 +0000 (Sat, 05 Feb 2011) Log Message: ----------- cbook.report_memory: add Windows support via "tasklist" Modified Paths: -------------- trunk/matplotlib/CHANGELOG trunk/matplotlib/lib/matplotlib/cbook.py Modified: trunk/matplotlib/CHANGELOG =================================================================== --- trunk/matplotlib/CHANGELOG 2011-02-05 20:56:02 UTC (rev 8946) +++ trunk/matplotlib/CHANGELOG 2011-02-05 21:57:21 UTC (rev 8947) @@ -1,3 +1,6 @@ +2011-02-05 Add cbook memory monitoring for Windows, using + tasklist. - EF + 2011-02-05 Speed up Normalize and LogNorm by using in-place operations and by using float32 for float32 inputs and for ints of 2 bytes or shorter; based on Modified: trunk/matplotlib/lib/matplotlib/cbook.py =================================================================== --- trunk/matplotlib/lib/matplotlib/cbook.py 2011-02-05 20:56:02 UTC (rev 8946) +++ trunk/matplotlib/lib/matplotlib/cbook.py 2011-02-05 21:57:21 UTC (rev 8947) @@ -1233,7 +1233,7 @@ def report_memory(i=0): # argument may go away 'return the memory consumed by process' - from subprocess import Popen, PIPE + from subprocess import Popen, PIPE, check_output pid = os.getpid() if sys.platform=='sunos5': a2 = Popen('ps -p %d -o osz' % pid, shell=True, @@ -1247,7 +1247,12 @@ a2 = Popen('ps -p %d -o rss,vsz' % pid, shell=True, stdout=PIPE).stdout.readlines() mem = int(a2[1].split()[0]) - + elif sys.platform.startswith('win'): + a2 = check_output(["tasklist", "/nh", "/fi", "pid eq %d" % pid]) + mem = int(a2.strip().split()[-2].replace(',','')) + else: + raise NotImplementedError( + "We don't have a memory monitor for %s" % sys.platform) return mem _safezip_msg = 'In safezip, len(args[0])=%d but len(args[%d])=%d' This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. |
From: <ef...@us...> - 2011-02-06 00:44:02
|
Revision: 8948 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8948&view=rev Author: efiring Date: 2011-02-06 00:43:54 +0000 (Sun, 06 Feb 2011) Log Message: ----------- image: more conversion to use rgba bytes, other minor cleanup Modified Paths: -------------- trunk/matplotlib/examples/pylab_examples/toggle_images.py trunk/matplotlib/lib/matplotlib/image.py Modified: trunk/matplotlib/examples/pylab_examples/toggle_images.py =================================================================== --- trunk/matplotlib/examples/pylab_examples/toggle_images.py 2011-02-05 21:57:21 UTC (rev 8947) +++ trunk/matplotlib/examples/pylab_examples/toggle_images.py 2011-02-06 00:43:54 UTC (rev 8948) @@ -5,7 +5,7 @@ them to the same axes with hold "on". Then, toggle the visible property of them using keypress event handling -If you want two images with sifferent shapes to be plotted with the same +If you want two images with different shapes to be plotted with the same extent, they must have the same "extent" property As usual, we'll define some random images for demo. Real data is much more Modified: trunk/matplotlib/lib/matplotlib/image.py =================================================================== --- trunk/matplotlib/lib/matplotlib/image.py 2011-02-05 21:57:21 UTC (rev 8947) +++ trunk/matplotlib/lib/matplotlib/image.py 2011-02-06 00:43:54 UTC (rev 8948) @@ -654,7 +654,8 @@ def __init__(self, ax, **kwargs): """ kwargs are identical to those for AxesImage, except - that 'interpolation' defaults to 'nearest' + that 'interpolation' defaults to 'nearest', and 'bilinear' + is the only alternative. """ interp = kwargs.pop('interpolation', 'nearest') AxesImage.__init__(self, ax, @@ -712,7 +713,7 @@ A.shape = A.shape[0:2] if len(A.shape) == 2: if A.dtype != np.uint8: - A = (self.cmap(self.norm(A))*255).astype(np.uint8) + A = self.to_rgba(A, alpha=self._alpha, bytes=True) self.is_grayscale = self.cmap.is_gray() else: A = np.repeat(A[:,:,np.newaxis], 4, 2) @@ -956,7 +957,7 @@ if self._A is None: raise RuntimeError('You must first set the image array') - x = self.to_rgba(self._A, self._alpha) + x = self.to_rgba(self._A, self._alpha, bytes=True) self.magnification = magnification # if magnification is not one, we need to resize ismag = magnification!=1 @@ -965,7 +966,7 @@ isoutput = 0 else: isoutput = 1 - im = _image.fromarray(x, isoutput) + im = _image.frombyte(x, isoutput) fc = self.figure.get_facecolor() im.set_bg( *mcolors.colorConverter.to_rgba(fc, 0) ) im.is_grayscale = (self.cmap.name == "gray" and @@ -1078,11 +1079,11 @@ im.is_grayscale = False else: if self._rgbacache is None: - x = self.to_rgba(self._A, self._alpha) + x = self.to_rgba(self._A, self._alpha, bytes=True) self._rgbacache = x else: x = self._rgbacache - im = _image.fromarray(x, 0) + im = _image.frombyte(x, 0) if len(self._A.shape) == 2: im.is_grayscale = self.cmap.is_gray() else: This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. |
From: <ef...@us...> - 2011-02-06 17:53:41
|
Revision: 8954 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8954&view=rev Author: efiring Date: 2011-02-06 17:53:33 +0000 (Sun, 06 Feb 2011) Log Message: ----------- Merged revisions 8953 via svnmerge from https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/v1_0_maint ........ r8953 | efiring | 2011-02-06 07:49:43 -1000 (Sun, 06 Feb 2011) | 2 lines bug: xlim, ylim with no arguments should not affect autoscaling ........ Modified Paths: -------------- trunk/matplotlib/lib/matplotlib/pyplot.py Property Changed: ---------------- trunk/matplotlib/ trunk/matplotlib/doc/pyplots/README trunk/matplotlib/doc/sphinxext/gen_gallery.py trunk/matplotlib/doc/sphinxext/gen_rst.py trunk/matplotlib/examples/misc/multiprocess.py trunk/matplotlib/examples/mplot3d/contour3d_demo.py trunk/matplotlib/examples/mplot3d/contourf3d_demo.py trunk/matplotlib/examples/mplot3d/polys3d_demo.py trunk/matplotlib/examples/mplot3d/scatter3d_demo.py trunk/matplotlib/examples/mplot3d/surface3d_demo.py trunk/matplotlib/examples/mplot3d/wire3d_demo.py trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py trunk/matplotlib/lib/matplotlib/sphinxext/plot_directive.py trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png Property changes on: trunk/matplotlib ___________________________________________________________________ Modified: svnmerge-integrated - 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""" ax = gca() + if not args and not kwargs: + return ax.get_xlim() ret = ax.set_xlim(*args, **kwargs) draw_if_interactive() return ret @@ -1101,9 +1105,13 @@ ylim(ymax=3) # adjust the max leaving min unchanged ylim(ymin=1) # adjust the min leaving max unchanged + Setting limits turns autoscaling off for the y-axis. + The new axis limits are returned as a length 2 tuple. """ ax = gca() + if not args and not kwargs: + return ax.get_ylim() ret = ax.set_ylim(*args, **kwargs) draw_if_interactive() return ret Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py ___________________________________________________________________ Modified: svn:mergeinfo - /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939 + /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939,8953 Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py ___________________________________________________________________ Modified: svn:mergeinfo - 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From: <jo...@us...> - 2011-02-07 16:51:12
|
Revision: 8956 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8956&view=rev Author: jouni Date: 2011-02-07 16:51:04 +0000 (Mon, 07 Feb 2011) Log Message: ----------- Quick workaround for dviread bug #3175113 Modified Paths: -------------- trunk/matplotlib/CHANGELOG trunk/matplotlib/lib/matplotlib/dviread.py Property Changed: ---------------- trunk/matplotlib/ trunk/matplotlib/doc/pyplots/README trunk/matplotlib/doc/sphinxext/gen_gallery.py trunk/matplotlib/doc/sphinxext/gen_rst.py trunk/matplotlib/examples/misc/multiprocess.py trunk/matplotlib/examples/mplot3d/contour3d_demo.py trunk/matplotlib/examples/mplot3d/contourf3d_demo.py trunk/matplotlib/examples/mplot3d/polys3d_demo.py trunk/matplotlib/examples/mplot3d/scatter3d_demo.py trunk/matplotlib/examples/mplot3d/surface3d_demo.py trunk/matplotlib/examples/mplot3d/wire3d_demo.py trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py trunk/matplotlib/lib/matplotlib/sphinxext/plot_directive.py trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_spines/spines_axes_positions.png Property changes on: trunk/matplotlib ___________________________________________________________________ Modified: svnmerge-integrated - /branches/mathtex:1-7263 /branches/v0_91_maint:1-6428 /branches/v0_98_5_maint:1-7253 /branches/v1_0_maint:1-8953 /trunk/matplotlib:1-7315 + /trunk/matplotlib:1-7315 /branches/mathtex:1-7263 /branches/v0_91_maint:1-6428 /branches/v0_98_5_maint:1-7253 /branches/v1_0_maint:1-8955 Modified: svn:mergeinfo - /branches/v0_91_maint:5753-5771 /branches/v0_98_5_maint:6581,6585,6587,6589-6609,6614,6616,6625,6652,6660-6662,6672-6673,6714-6715,6717-6732,6752-6754,6761-6773,6781,6792,6800,6802,6805,6809,6811,6822,6827,6850,6854,6856,6859,6861-6873,6883-6884,6886,6890-6891,6906-6909,6911-6912,6915-6916,6918,6920-6925,6927-6928,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939,8953 + /branches/v0_91_maint:5753-5771 /branches/v0_98_5_maint:6581,6585,6587,6589-6609,6614,6616,6625,6652,6660-6662,6672-6673,6714-6715,6717-6732,6752-6754,6761-6773,6781,6792,6800,6802,6805,6809,6811,6822,6827,6850,6854,6856,6859,6861-6873,6883-6884,6886,6890-6891,6906-6909,6911-6912,6915-6916,6918,6920-6925,6927-6928,6934,6941,6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939,8953,8955 Modified: trunk/matplotlib/CHANGELOG =================================================================== --- trunk/matplotlib/CHANGELOG 2011-02-07 16:42:17 UTC (rev 8955) +++ trunk/matplotlib/CHANGELOG 2011-02-07 16:51:04 UTC (rev 8956) @@ -1,3 +1,5 @@ +2011-02-07 Quick workaround for dviread bug #3175113 - 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""" texname, psname = words[:2] - effects, encoding, filename = '', None, None + effects, encodings, filename = '', [], None for word in words[2:]: if not word.startswith('<'): effects = word else: word = word.lstrip('<') if word.startswith('['): - assert encoding is None - encoding = word[1:] + encodings.append(word[1:]) elif word.endswith('.enc'): - assert encoding is None - encoding = word + encodings.append(word) else: assert filename is None filename = word + if len(encodings) > 1: + # TODO this is a stopgap workaround, need to handle this correctly + matplotlib.verbose.report('Multiple encodings for %s = %s, skipping' + % (texname, psname), 'debug') + return + elif len(encodings) == 1: + encoding, = encodings + else: + encoding = None + eff = effects.split() effects = {} try: Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/mathmpl.py ___________________________________________________________________ Modified: svn:mergeinfo - /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939,8953 + /branches/v0_91_maint/doc/sphinxext/mathmpl.py:5753-5771 /branches/v0_98_5_maint/lib/matplotlib/sphinxext/mathmpl.py:6946,6948,6950,6952,6960,6972,6984-6985,6990,6995,6997-7001,7014,7016,7018,7024-7025,7033,7035,7042,7072,7080,7176,7209-7211,7227,7245 /branches/v0_99_maint/lib/matplotlib/sphinxext/mathmpl.py:7323-7338,7393,7395-7404,7407-7424,7428-7433,7442-7444,7446,7475-7482,7484,7486,7489-7523,7567,7569,7582-7584,7616-7618,7633,7638,7703,7727-7734,7740-7741,7745,7751,7756,7762,7770,7772,7774,7776-7778,7780,7784,7788,7790,7792,7794,7796,7800,7803,7808,7822,7827,7834,7837,7844,7846-7847,7849,7858,7864,7866-7867,7874,7884,7896,7901-7903,7916,7919,7924,7928,7944,7952,7970,7972,7981,7983,7989-7991,7998,8001,8003,8016-8057,8068,8070,8092-8116,8121-8135 /branches/v1_0_maint/lib/matplotlib/sphinxext/mathmpl.py:8521,8524-8541,8543,8549,8554,8557,8559-8564,8566,8573,8575,8577,8579,8581,8583,8585,8588,8590,8593,8595,8601,8603,8610,8614,8627-8628,8630,8632,8643,8645,8647-8667,8673,8675,8677,8679,8690-8697,8704,8706,8708,8714-8715,8717-8720,8722-8725,8732-8734,8747,8764,8769-8770,8772,8774,8776,8778,8780,8785,8788,8790,8794,8798-8799,8808,8815,8830,8835,8841-8842,8844-8846,8870-8899,8902-8906,8908,8911,8920,8926,8931,8933,8939,8953,8955 Property changes on: trunk/matplotlib/lib/matplotlib/sphinxext/only_directives.py ___________________________________________________________________ Modified: svn:mergeinfo - 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From: <wea...@us...> - 2011-02-18 19:28:35
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Revision: 8988 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8988&view=rev Author: weathergod Date: 2011-02-18 19:28:29 +0000 (Fri, 18 Feb 2011) Log Message: ----------- scatter() now supports empty arrays as input (i.e., scatter([], []) is now valid). Enabling this required fixes in both scatter() and in collections.py. Collections now support empty versions of themselves more correctly due to these fixes. Modified Paths: -------------- trunk/matplotlib/CHANGELOG trunk/matplotlib/lib/matplotlib/axes.py trunk/matplotlib/lib/matplotlib/collections.py Modified: trunk/matplotlib/CHANGELOG =================================================================== --- trunk/matplotlib/CHANGELOG 2011-02-17 16:44:28 UTC (rev 8987) +++ trunk/matplotlib/CHANGELOG 2011-02-18 19:28:29 UTC (rev 8988) @@ -1,3 +1,6 @@ +2011-02-18 scatter([], []) is now valid. Also fixed issues + with empty collections - BVR + 2011-02-07 Quick workaround for dviread bug #3175113 - JKS 2011-02-05 Add cbook memory monitoring for Windows, using Modified: trunk/matplotlib/lib/matplotlib/axes.py =================================================================== --- trunk/matplotlib/lib/matplotlib/axes.py 2011-02-17 16:44:28 UTC (rev 8987) +++ trunk/matplotlib/lib/matplotlib/axes.py 2011-02-18 19:28:29 UTC (rev 8988) @@ -5832,24 +5832,17 @@ else: collection.autoscale_None() - temp_x = x - temp_y = y - - minx = np.amin(temp_x) - maxx = np.amax(temp_x) - miny = np.amin(temp_y) - maxy = np.amax(temp_y) - - w = maxx-minx - h = maxy-miny - # the pad is a little hack to deal with the fact that we don't # want to transform all the symbols whose scales are in points # to data coords to get the exact bounding box for efficiency # reasons. It can be done right if this is deemed important - padx, pady = 0.05*w, 0.05*h - corners = (minx-padx, miny-pady), (maxx+padx, maxy+pady) - self.update_datalim( corners) + # Also, only bother with this padding if there is anything to draw. + if self._xmargin < 0.05 and x.size > 0 : + self.set_xmargin(0.05) + + if self._ymargin < 0.05 and x.size > 0 : + self.set_ymargin(0.05) + self.autoscale_view() # add the collection last Modified: trunk/matplotlib/lib/matplotlib/collections.py =================================================================== --- trunk/matplotlib/lib/matplotlib/collections.py 2011-02-17 16:44:28 UTC (rev 8987) +++ trunk/matplotlib/lib/matplotlib/collections.py 2011-02-18 19:28:29 UTC (rev 8988) @@ -59,6 +59,8 @@ scalar mappable will be made to set the face colors. """ _offsets = np.array([], np.float_) + # _offsets must be a Nx2 array! + _offsets.shape = (0, 2) _transOffset = transforms.IdentityTransform() _transforms = [] @@ -95,10 +97,11 @@ self._uniform_offsets = None self._offsets = np.array([], np.float_) + # Force _offsets to be Nx2 + self._offsets.shape = (0, 2) if offsets is not None: offsets = np.asarray(offsets) - if len(offsets.shape) == 1: - offsets = offsets[np.newaxis,:] # Make it Nx2. + offsets.shape = (-1, 2) # Make it Nx2 if transOffset is not None: self._offsets = offsets self._transOffset = transOffset @@ -148,13 +151,17 @@ transOffset = self._transOffset offsets = self._offsets paths = self.get_paths() + + if not transform.is_affine: paths = [transform.transform_path_non_affine(p) for p in paths] transform = transform.get_affine() if not transOffset.is_affine: offsets = transOffset.transform_non_affine(offsets) transOffset = transOffset.get_affine() + offsets = np.asarray(offsets, np.float_) + offsets.shape = (-1, 2) # Make it Nx2 result = mpath.get_path_collection_extents( transform.frozen(), paths, self.get_transforms(), @@ -176,6 +183,7 @@ offsets = self._offsets paths = self.get_paths() + if self.have_units(): paths = [] for path in self.get_paths(): @@ -184,17 +192,19 @@ xs = self.convert_xunits(xs) ys = self.convert_yunits(ys) paths.append(mpath.Path(zip(xs, ys), path.codes)) - if len(self._offsets): - xs = self.convert_xunits(self._offsets[:,0]) - ys = self.convert_yunits(self._offsets[:,1]) + + if offsets.size > 0: + xs = self.convert_xunits(offsets[:,0]) + ys = self.convert_yunits(offsets[:,1]) offsets = zip(xs, ys) offsets = np.asarray(offsets, np.float_) + offsets.shape = (-1, 2) # Make it Nx2 if not transform.is_affine: paths = [transform.transform_path_non_affine(path) for path in paths] transform = transform.get_affine() - if not transOffset.is_affine: + if not transOffset.is_affine : offsets = transOffset.transform_non_affine(offsets) transOffset = transOffset.get_affine() @@ -258,8 +268,7 @@ ACCEPTS: float or sequence of floats """ offsets = np.asarray(offsets, np.float_) - if len(offsets.shape) == 1: - offsets = offsets[np.newaxis,:] # Make it Nx2. + offsets.shape = (-1, 2) # Make it Nx2 #This decision is based on how they are initialized above if self._uniform_offsets is None: self._offsets = offsets @@ -1221,6 +1230,7 @@ offsets = zip(xs, ys) offsets = np.asarray(offsets, np.float_) + offsets.shape = (-1, 2) # Make it Nx2 self.update_scalarmappable() This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. |