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-rw-r--r--wqflask/wqflask/correlation/rust_correlation.py71
1 files changed, 29 insertions, 42 deletions
diff --git a/wqflask/wqflask/correlation/rust_correlation.py b/wqflask/wqflask/correlation/rust_correlation.py
index 37e2ba76..5c22efbf 100644
--- a/wqflask/wqflask/correlation/rust_correlation.py
+++ b/wqflask/wqflask/correlation/rust_correlation.py
@@ -28,11 +28,9 @@ def chunk_dataset(dataset, steps, name):
""".format(name)
with database_connector() as conn:
- curr = conn.cursor()
-
- curr.execute(query)
-
- traits_name_dict = dict(curr.fetchall())
+ with conn.cursor() as curr:
+ curr.execute(query)
+ traits_name_dict = dict(curr.fetchall())
for i in range(0, len(dataset), steps):
matrix = list(dataset[i:i + steps])
@@ -52,60 +50,49 @@ def compute_top_n_sample(start_vars, dataset, trait_list):
return {}
def __fetch_sample_ids__(samples_vals, samples_group):
-
all_samples = json.loads(samples_vals)
sample_data = get_sample_corr_data(
sample_type=samples_group, all_samples=all_samples,
dataset_samples=dataset.group.all_samples_ordered())
with database_connector() as conn:
-
- curr = conn.cursor()
-
- curr.execute(
- """
+ with conn.cursor() as curr:
+ curr.execute(
+ """
SELECT Strain.Name, Strain.Id FROM Strain, Species
WHERE Strain.Name IN {}
and Strain.SpeciesId=Species.Id
and Species.name = '{}'
""".format(create_in_clause(list(sample_data.keys())),
- *mescape(dataset.group.species))
-
- )
-
- return (sample_data, dict(curr.fetchall()))
+ *mescape(dataset.group.species)))
+ return (sample_data, dict(curr.fetchall()))
(sample_data, sample_ids) = __fetch_sample_ids__(
start_vars["sample_vals"], start_vars["corr_samples_group"])
with database_connector() as conn:
+ with conn.cursor() as curr:
+ # fetching strain data in bulk
+ curr.execute(
+ """
+ SELECT * from ProbeSetData
+ where StrainID in {}
+ and id in (SELECT ProbeSetXRef.DataId
+ FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze)
+ WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id
+ and ProbeSetFreeze.Name = '{}'
+ and ProbeSet.Name in {}
+ and ProbeSet.Id = ProbeSetXRef.ProbeSetId)
+ """.format(
+ create_in_clause(list(sample_ids.values())),
+ dataset.name,
+ create_in_clause(trait_list)))
+
+ corr_data = chunk_dataset(
+ list(curr.fetchall()), len(sample_ids.values()), dataset.name)
- curr = conn.cursor()
-
- # fetching strain data in bulk
-
- curr.execute(
-
- """
- SELECT * from ProbeSetData
- where StrainID in {}
- and id in (SELECT ProbeSetXRef.DataId
- FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze)
- WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id
- and ProbeSetFreeze.Name = '{}'
- and ProbeSet.Name in {}
- and ProbeSet.Id = ProbeSetXRef.ProbeSetId)
- """.format(create_in_clause(list(sample_ids.values())), dataset.name, create_in_clause(trait_list))
-
-
- )
-
- corr_data = chunk_dataset(list(curr.fetchall()), len(
- sample_ids.values()), dataset.name)
-
- return run_correlation(corr_data,
- list(sample_data.values()),
- "pearson", ",")
+ return run_correlation(
+ corr_data, list(sample_data.values()), "pearson", ",")
def compute_top_n_lit(corr_results, this_dataset, this_trait) -> dict: