This PR adds a benchmarking framework to datashader using asv. There are two reasons for doing this. Firstly it allows us to quantify the performance differences within any particular commit of different values of parameters such as antialiased line_width and canvas size. Secondly it allows us to monitor the impact on performance of code changes over time, whether those code changes are intended to improve performance or not.
There is a README file in the benchmarks directory which explains how to use it. So far the benchmarks included are canvas.line for LinesAxis1XConstant, and shade both for categorical and non-categorical data. It is expected that more benchmarks will be added in due course.
This PR adds a benchmarking framework to
datashader
usingasv
. There are two reasons for doing this. Firstly it allows us to quantify the performance differences within any particular commit of different values of parameters such as antialiasedline_width
and canvas size. Secondly it allows us to monitor the impact on performance of code changes over time, whether those code changes are intended to improve performance or not.There is a README file in the
benchmarks
directory which explains how to use it. So far the benchmarks included arecanvas.line
forLinesAxis1XConstant
, andshade
both for categorical and non-categorical data. It is expected that more benchmarks will be added in due course.Results on my dev machine today are as follows:
Note that the two
failed
benchmarks are aborted on purpose as non-antialiased lines ignore theself_intersect
keyword argument.