def test_estimate_loco_offsets_logistic_ridge_no_intercept_with_cov(spark):
covdf = pd.read_csv(f'{logistic_ridge_data_root}/cov.csv').set_index('sample_id')
covdf.index = covdf.index.astype(str, copy=False)
labeldf = pd.read_csv(f'{logistic_ridge_data_root}/binary_phenotypes.csv').set_index('sample_id')
labeldf.index = labeldf.index.astype(str, copy=False)
indexdf = spark.read.parquet(f'{ridge_data_root}/groupedIDs.snappy.parquet')
blockdf = spark.read.parquet(f'{ridge_data_root}/blockedGT.snappy.parquet')
group2ids = __get_sample_blocks(indexdf)
y_hat_df = estimate_loco_offsets(blockdf,
labeldf,
group2ids,
covdf,
add_intercept=False,
reduction_alphas=alphas,
regression_alphas=alphas)
stack0 = RidgeReduction(blockdf, labeldf, group2ids, covdf, add_intercept=False, alphas=alphas)
stack0.fit_transform()
regressor = LogisticRidgeRegression.from_ridge_reduction(stack0, alphas)
yhatdf = regressor.fit_transform_loco()
print(y_hat_df)
assert (np.allclose(y_hat_df, yhatdf))
def test_estimate_loco_offsets_ridge(spark):
labeldf = pd.read_csv(f'{ridge_data_root}/pts.csv',
dtype={
'sample_id': 'str'
}).set_index('sample_id')
indexdf = spark.read.parquet(
f'{ridge_data_root}/groupedIDs.snappy.parquet')
blockdf = spark.read.parquet(f'{ridge_data_root}/blockedGT.snappy.parquet')
group2ids = __get_sample_blocks(indexdf)
y_hat_df = estimate_loco_offsets(blockdf,
labeldf,
group2ids,
add_intercept=False,
reduction_alphas=alphas,
regression_alphas=alphas)
stack0 = RidgeReduction(blockdf,
labeldf,
group2ids,
add_intercept=False,
alphas=alphas)
stack0.fit_transform()
regressor = RidgeRegression.from_ridge_reduction(stack0, alphas)
yhatdf = regressor.fit_transform_loco()
assert (np.allclose(y_hat_df, yhatdf))
