Thought some of you may be interested to know that the speed on the
branch is getting much better. Whereas earlier the branch was about 2x
slower than the trunk, now most things are close to equal with the trunk
speed-wise (with a few outliers for some things such as auto legends,
quivers and the pcolor stuff that Eric and I have been working on).
Here are the results for the "simple_plot_fps.py" benchmark, which is
meant to measure the interactive performance of panning and zooming:
trunk: 21.63 fps
branch: 23.25 fps
Attached are the time differences for everything in backend_driver.py.
(Sorted by the percentage difference in speed.) Note that, unlike the
above, this measures only one drawing of the plot. It would be
interesting to measure the difference in interactive performance for
some of these -- I suspect the branch may do better.
Cheers,
Mike
--
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA
backend agg
test a b delta % diff
---------------------------------------------------------------------
line_collection.py 1.148 0.904 -0.245 78%
cohere_demo.py 0.958 0.777 -0.182 81%
spy_demos.py 0.884 0.807 -0.077 91%
pcolor_demo.py 1.051 0.984 -0.068 93%
scatter_star_poly.py 1.129 1.086 -0.043 96%
subplot_demo.py 0.731 0.712 -0.019 97%
legend_demo2.py 0.640 0.625 -0.015 97%
arctest.py 0.596 0.589 -0.007 98%
figimage_demo.py 0.537 0.532 -0.005 99%
mathtext_demo.py 1.087 1.078 -0.009 99%
legend_demo.py 0.628 0.623 -0.005 99%
text_themes.py 0.640 0.636 -0.005 99%
two_scales.py 0.684 0.682 -0.002 99%
image_demo2.py 0.914 0.914 0.000 100%
masked_demo.py 0.668 0.668 0.000 100%
arrow_demo.py 1.620 1.622 0.002 100%
simple_plot.py 0.610 0.616 0.006 100%
alignment_test.py 0.576 0.582 0.006 101%
pcolor_demo2.py 0.745 0.754 0.009 101%
fonts_demo_kw.py 0.687 0.695 0.008 101%
image_demo.py 0.732 0.741 0.009 101%
barh_demo.py 0.645 0.654 0.009 101%
major_minor_demo1.py 0.658 0.667 0.009 101%
date_demo2.py 1.185 1.202 0.017 101%
xcorr_demo.py 0.723 0.734 0.011 101%
histogram_demo.py 0.961 0.976 0.015 101%
step_demo.py 0.654 0.665 0.011 101%
psd_demo.py 0.718 0.730 0.012 101%
vline_demo.py 0.618 0.630 0.011 101%
color_demo.py 0.610 0.621 0.012 101%
scatter_demo2.py 0.944 0.962 0.018 101%
image_masked.py 0.829 0.845 0.017 101%
colorbar_only.py 0.494 0.503 0.010 102%
pcolor_small.py 0.690 0.705 0.015 102%
invert_axes.py 0.611 0.625 0.013 102%
image_origin.py 0.718 0.736 0.017 102%
equal_aspect_ratio.py 0.602 0.617 0.015 102%
unicode_demo.py 0.635 0.653 0.018 102%
barchart_demo.py 0.641 0.659 0.018 102%
quadmesh_demo.py 0.765 0.787 0.022 102%
layer_images.py 0.800 0.823 0.024 102%
hline_demo.py 0.621 0.641 0.020 103%
line_collection2.py 0.796 0.822 0.026 103%
fill_demo.py 0.601 0.624 0.022 103%
text_handles.py 0.608 0.631 0.023 103%
stem_plot.py 0.604 0.626 0.023 103%
figtext.py 0.717 0.745 0.028 103%
broken_barh.py 0.678 0.707 0.029 104%
bar_stacked.py 0.626 0.653 0.027 104%
major_minor_demo2.py 0.779 0.816 0.037 104%
scatter_demo.py 0.587 0.619 0.032 105%
axhspan_demo.py 0.642 0.677 0.035 105%
csd_demo.py 0.747 0.789 0.042 105%
finance_demo.py 1.055 1.117 0.062 105%
multiple_figs_demo.py 0.681 0.721 0.041 105%
shared_axis_demo.py 0.704 0.746 0.042 106%
customize_rc.py 0.713 0.757 0.043 106%
table_demo.py 0.725 0.770 0.045 106%
figlegend_demo.py 0.681 0.725 0.044 106%
date_demo1.py 1.297 1.381 0.084 106%
contourf_demo.py 0.843 0.901 0.058 106%
pie_demo.py 0.643 0.696 0.053 108%
zorder_demo.py 0.676 0.733 0.057 108%
polar_scatter.py 0.649 0.705 0.056 108%
errorbar_limits.py 0.655 0.713 0.058 108%
log_test.py 1.008 1.101 0.093 109%
polar_demo.py 0.730 0.810 0.080 110%
log_demo.py 1.769 2.011 0.242 113%
line_styles.py 1.595 1.818 0.223 113%
quiver_demo.py 0.977 1.123 0.146 114%
shared_axis_across_figures.py 0.624 0.721 0.097 115%
text_rotation.py 0.708 0.825 0.117 116%
custom_ticker1.py 0.571 0.679 0.108 118%
specgram_demo.py 1.150 1.380 0.229 119%
contour_demo.py 1.081 1.316 0.235 121%
axes_demo.py 0.816 1.009 0.193 123%
stock_demo.py 0.648 0.817 0.169 126%
boxplot_demo.py 0.695 0.878 0.183 126%
legend_auto.py 1.148 1.658 0.510 144%
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