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| author | zsloan | 2020-11-13 15:37:49 -0600 |
|---|---|---|
| committer | zsloan | 2020-11-13 15:37:49 -0600 |
| commit | 678d9cd4e073c3936c34d3b9b54f1e6c590def27 (patch) | |
| tree | 1056725f69285a17383cedc9f4ec962df989d27c | |
| parent | 76d5b24b3d2e0b5e6be5b1cf4c125a9a812ff57a (diff) | |
| download | genenetwork2-678d9cd4e073c3936c34d3b9b54f1e6c590def27.tar.gz | |
Switched to using f-strings instead of the older method of string
formatting
| -rw-r--r-- | wqflask/wqflask/correlation/show_corr_results.py | 24 |
1 files changed, 12 insertions, 12 deletions
diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py index 87dd7597..1b801b1d 100644 --- a/wqflask/wqflask/correlation/show_corr_results.py +++ b/wqflask/wqflask/correlation/show_corr_results.py @@ -499,21 +499,21 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_ap if bool(trait.mean): results_dict['mean'] = float(trait.mean) if trait.LRS_score_repr != "N/A": - results_dict['lrs_score'] = "%.1f" % float(trait.LRS_score_repr) + results_dict['lrs_score'] = f"{float(trait.LRS_score_repr):.1f}" results_dict['lrs_location'] = trait.LRS_location_repr if bool(trait.additive): - results_dict['additive'] = "%0.3f" % float(trait.additive) - results_dict['sample_r'] = "%0.3f" % float(trait.sample_r) + results_dict['additive'] = f"{float(trait.additive):.3f}" + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" results_dict['lit_corr'] = "--" results_dict['tissue_corr'] = "--" results_dict['tissue_pvalue'] = "--" if bool(trait.lit_corr): - results_dict['lit_corr'] = "%0.3f" % float(trait.lit_corr) + results_dict['lit_corr'] = f"{float(trait.lit_corr):.3f}" if bool(trait.tissue_corr): - results_dict['tissue_corr'] = "%0.3f" % float(trait.tissue_corr) - results_dict['tissue_pvalue'] = "%0.3e" % float(trait.tissue_pvalue) + results_dict['tissue_corr'] = f"{float(trait.tissue_corr):.3f}" + results_dict['tissue_pvalue'] = f"{float(trait.tissue_pvalue):.3e}" elif target_dataset.type == "Publish": results_dict['abbreviation_display'] = "N/A" results_dict['description'] = "N/A" @@ -547,15 +547,15 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_ap results_dict['lrs_score'] = trait.LRS_score_repr results_dict['lrs_location'] = trait.LRS_location_repr if bool(trait.additive): - results_dict['additive'] = "%0.3f" % float(trait.additive) - results_dict['sample_r'] = "%0.3f" % trait.sample_r + results_dict['additive'] = f"{float(trait.additive):.3f}" + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" else: results_dict['location'] = trait.location_repr - results_dict['sample_r'] = "%0.3f" % trait.sample_r + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" results_list.append(results_dict) |