diff options
| -rw-r--r-- | wqflask/wqflask/correlation_matrix/show_corr_matrix.py | 24 |
1 files changed, 10 insertions, 14 deletions
diff --git a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py index 9b4cb2eb..88d62045 100644 --- a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py +++ b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py @@ -21,27 +21,23 @@ import datetime import random import string - - import numpy as np import scipy -from base import data_set +from base.data_set import create_dataset from base.webqtlConfig import GENERATED_TEXT_DIR -from utility import helper_functions -from utility import corr_result_helpers + + +from utility.helper_functions import get_trait_db_obs +from utility.corr_result_helpers import normalize_values from utility.redis_tools import get_redis_conn from gn3.computations.pca import compute_pca - from gn3.computations.pca import process_factor_loadings_tdata from gn3.computations.pca import generate_pca_temp_traits from gn3.computations.pca import cache_pca_dataset -Redis = get_redis_conn() -THIRTY_DAYS = 60 * 60 * 24 * 30 - class CorrelationMatrix: @@ -49,7 +45,7 @@ class CorrelationMatrix: trait_db_list = [trait.strip() for trait in start_vars['trait_list'].split(',')] - helper_functions.get_trait_db_obs(self, trait_db_list) + get_trait_db_obs(self, trait_db_list) self.all_sample_list = [] self.traits = [] @@ -117,7 +113,7 @@ class CorrelationMatrix: if sample in self.shared_samples_list: self.shared_samples_list.remove(sample) - this_trait_vals, target_vals, num_overlap = corr_result_helpers.normalize_values( + this_trait_vals, target_vals, num_overlap = normalize_values( this_trait_vals, target_vals) if num_overlap < self.lowest_overlap: @@ -193,8 +189,9 @@ class CorrelationMatrix: self.scores = pca["scores"] this_group_name = self.trait_list[0][1].group.name - temp_dataset = data_set.create_dataset( - dataset_name="Temp", dataset_type="Temp", group_name=this_group_name) + temp_dataset = create_dataset( + dataset_name="Temp", dataset_type="Temp", + group_name=this_group_name) temp_dataset.group.get_samplelist() pca_temp_traits = generate_pca_temp_traits(species=temp_dataset.group.species, group=this_group_name, @@ -203,7 +200,6 @@ class CorrelationMatrix: shared_samples=self.shared_samples_list, create_time=datetime.datetime.now().strftime("%m%d%H%M%S")) - cache_pca_dataset(redis_conn=get_redis_conn( ), exp_days=60 * 60 * 24 * 30, pca_trait_dict=pca_temp_traits) |