Closed kaanolgu closed 4 months ago
https://github.com/ukri-excalibur/excalibur-tests/commit/438be0257c39cf81bb1260e2a881559c2c10df3c
Made a change according to idea from @ilectra and @pineapple-cat . Instead of adding a new "*_axis" to the yaml
file, a new list of columns to extract to csv dataframe is used and df_csv_export
is generated from the original dataframe.
One question would be is it required to apply user-specified types to all relevant columns for the csv export too ?
I think that, instead of creating a whole new df to export to csv, it would make more sense if you
csv_export
part of the yaml, not all the axis and series etc.I think that, instead of creating a whole new df to export to csv, it would make more sense if you
- add only the extra columns that you need in the
csv_export
part of the yaml, not all the axis and series etc.- keep those columns in the filtered dataframe, as you go along the processing/filtering, treating them as extra axes.
- export the filtered df to csv, just before calling the plotting script (you won't call it, in your case, but that's the place to do the printing)
That's a great idea! I will try to implement this in a new commit
I think that, instead of creating a whole new df to export to csv, it would make more sense if you
- add only the extra columns that you need in the
csv_export
part of the yaml, not all the axis and series etc.- keep those columns in the filtered dataframe, as you go along the processing/filtering, treating them as extra axes.
- export the filtered df to csv, just before calling the plotting script (you won't call it, in your case, but that's the place to do the printing)
That's a great idea! I will try to implement this in a new commit
@kaanolgu you might want to wait for the refactoring PR to be merged. It will change things quite a bit, hopefully to the better!
@pineapple-cat @kaanolgu I think I addressed all my review comments, please have a last look and merge if happy!
Fixes #252
series: [["partition", "cascadelake"],["partition", "volta"]]
Selected dataframe: tags Triad_value Triad_unit spack_spec partition 0 acc 12963.337 MBytes/sec babelstream%gcc@13.1.0 +acc cascadelake 1 acc 13386.104 MBytes/sec babelstream%gcc@9.2.0 +acc cuda_arch=70 volta 2 cuda 846640.634 MBytes/sec babelstream%gcc@9.2.0 +cuda cuda_arch=70 volta 3 omp 159131.926 MBytes/sec babelstream%gcc@13.1.0 +omp cascadelake 4 tbb 99740.216 MBytes/sec babelstream%gcc@13.1.0 +tbb partitioner=auto cascadelake