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-rw-r--r--wqflask/wqflask/correlation/correlation_gn3_api.py23
1 files changed, 18 insertions, 5 deletions
diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
index 7b828016..191a748a 100644
--- a/wqflask/wqflask/correlation/correlation_gn3_api.py
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -4,7 +4,8 @@ import time
from functools import wraps
from wqflask.correlation import correlation_functions
-
+from wqflask.correlation.pre_computes import fetch_precompute_results
+from wqflask.correlation.pre_computes import cache_compute_results
from base import data_set
from base.trait import create_trait
@@ -193,9 +194,21 @@ def compute_correlation(start_vars, method="pearson", compute_all=False):
(this_trait_data, target_dataset_data) = fetch_sample_data(
start_vars, this_trait, this_dataset, target_dataset)
- correlation_results = fast_compute_all_sample_correlation(corr_method=method,
- this_trait=this_trait_data,
- target_dataset=target_dataset_data)
+ correlation_results = fetch_precompute_results(
+ this_dataset.name, target_dataset.name, this_dataset.type, this_trait.name)
+
+ if correlation_results is None:
+ correlation_results = fast_compute_all_sample_correlation(corr_method=method,
+ this_trait=this_trait_data,
+ target_dataset=target_dataset_data)
+
+ cache_compute_results(this_dataset.type,
+ this_dataset.name,
+ target_dataset.name,
+ corr_method,
+ correlation_results,
+ this_trait.name)
+
elif corr_type == "tissue":
trait_symbol_dict = this_dataset.retrieve_genes("Symbol")
tissue_input = get_tissue_correlation_input(
@@ -295,7 +308,7 @@ def get_tissue_correlation_input(this_trait, trait_symbol_dict):
"""Gets tissue expression values for the primary trait and target tissues values"""
primary_trait_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(
symbol_list=[this_trait.symbol])
- if this_trait.symbol.lower() in primary_trait_tissue_vals_dict:
+ if this_trait.symbol and this_trait.symbol.lower() in primary_trait_tissue_vals_dict:
primary_trait_tissue_values = primary_trait_tissue_vals_dict[this_trait.symbol.lower(
)]
corr_result_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(