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authorzsloan2020-11-05 15:21:28 -0600
committerzsloan2020-11-05 15:21:28 -0600
commit8f70b408c6df130ba9bef2b159c32ef0c8d6c327 (patch)
tree286ed4142f0f7c4fa5dfdf756f0d2a3226dc9648
parent7932f962aff0ac35dd53b84e483f405de81c0612 (diff)
downloadgenenetwork2-8f70b408c6df130ba9bef2b159c32ef0c8d6c327.tar.gz
Removed html from generate_corr_json since that will be done by the column definitions after passing the data to DataTables as JSON
-rw-r--r--wqflask/wqflask/correlation/show_corr_results.py32
1 files changed, 11 insertions, 21 deletions
diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py
index 4c2b64ba..f0187ef9 100644
--- a/wqflask/wqflask/correlation/show_corr_results.py
+++ b/wqflask/wqflask/correlation/show_corr_results.py
@@ -484,30 +484,26 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_ap
if trait.view == False:
continue
results_dict = {}
- if not for_api:
- results_dict['checkbox'] = "<INPUT TYPE='checkbox' NAME='searchResult' class='checkbox trait_checkbox' style='padding-right: 0px;' VALUE='" + hmac.hmac_creation('{}:{}'.format(trait.name, trait.dataset.name)) + "'>"
- results_dict['index'] = i + 1
- results_dict['trait_id'] = "<a href='/show_trait?trait_id="+str(trait.name)+"&dataset="+str(dataset.name)+"'>"+str(trait.name)+"</a>"
- else:
- results_dict['trait_id'] = trait.name
+ results_dict['index'] = i + 1
+ results_dict['trait_id'] = trait.name
if target_dataset.type == "ProbeSet":
results_dict['symbol'] = trait.symbol
results_dict['description'] = trait.description_display
results_dict['location'] = trait.location_repr
- results_dict['mean'] = float(trait.mean)
+ if trait.mean and trait.mean != "":
+ results_dict['mean'] = float(trait.mean)
+ else:
+ results_dict['mean'] = "N/A"
if trait.LRS_score_repr != "N/A":
results_dict['lrs_score'] = "%.1f" % float(trait.LRS_score_repr)
else:
results_dict['lrs_score'] = "N/A"
results_dict['lrs_location'] = trait.LRS_location_repr
- if trait.additive != "":
+ if trait.additive and trait.additive != "":
results_dict['additive'] = "%0.3f" % float(trait.additive)
else:
results_dict['additive'] = "N/A"
- if for_api:
- results_dict['sample_r'] = "%0.3f" % float(trait.sample_r)
- else:
- results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>"
+ results_dict['sample_r'] = "%0.3f" % float(trait.sample_r)
results_dict['num_overlap'] = trait.num_overlap
results_dict['sample_p'] = "%0.3e" % float(trait.sample_p)
if trait.lit_corr == "" or trait.lit_corr == 0:
@@ -535,22 +531,16 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_ap
results_dict['pubmed'] = "N/A"
results_dict['lrs_score'] = trait.LRS_score_repr
results_dict['lrs_location'] = trait.LRS_location_repr
- if trait.additive != "":
+ if trait.additive and trait.additive != "":
results_dict['additive'] = "%0.3f" % float(trait.additive)
else:
results_dict['additive'] = "N/A"
- if for_api:
- results_dict['sample_r'] = "%0.3f" % trait.sample_r
- else:
- results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % trait.sample_r + "</a>"
+ results_dict['sample_r'] = "%0.3f" % trait.sample_r
results_dict['num_overlap'] = trait.num_overlap
results_dict['sample_p'] = "%0.3e" % float(trait.sample_p)
else:
results_dict['lrs_location'] = trait.LRS_location_repr
- if for_api:
- results_dict['sample_r'] = "%0.3f" % trait.sample_r
- else:
- results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>"
+ results_dict['sample_r'] = "%0.3f" % trait.sample_r
results_dict['num_overlap'] = trait.num_overlap
results_dict['sample_p'] = "%0.3e" % float(trait.sample_p)