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author | tlatorre <tlatorre@uchicago.edu> | 2020-04-13 15:50:01 -0500 |
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committer | tlatorre <tlatorre@uchicago.edu> | 2020-04-13 15:50:01 -0500 |
commit | 33e9b624ef7eed425dd8c240dbba458791d9cdd7 (patch) | |
tree | 159033af7b3db806eb891aa824fa0e5f9ccc0ce7 /utils/plot | |
parent | beec156aec67518c121ec2710a92018c738cfd0f (diff) | |
download | sddm-33e9b624ef7eed425dd8c240dbba458791d9cdd7.tar.gz sddm-33e9b624ef7eed425dd8c240dbba458791d9cdd7.tar.bz2 sddm-33e9b624ef7eed425dd8c240dbba458791d9cdd7.zip |
update plot script to be able to handle files with multi-particle fits
Diffstat (limited to 'utils/plot')
-rwxr-xr-x | utils/plot | 3 |
1 files changed, 3 insertions, 0 deletions
@@ -115,6 +115,9 @@ if __name__ == '__main__': # merge data and fits on run and gtid data = data.merge(fits,left_on=['run','gtid'],right_on=['fit_run','fit_gtid']) + # For this script, we only want the single particle fit results + data = data[(data.fit_id2 == 0) & (data.fit_id3 == 0)] + # Select only the best fit for a given run, gtid, and particle # combo data = data.sort_values('fit_fmin').groupby(['run','gtid','fit_id1','fit_id2','fit_id3'],as_index=False).nth(0).reset_index(level=0,drop=True) |