added cm_logo_skf.py and placeholder for splits
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4 changed files with 254 additions and 49 deletions
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@ -63,40 +63,8 @@ else:
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, '\nGot:', len(common_cols))
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colnames_combined_df = combined_df.columns
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if 'gene_name' in colnames_combined_df:
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print("\nGene name included")
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else:
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('\nGene name NOT included')
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##############################################################################
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#%% split_tts(): func params
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# (ml_input_data
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# , data_type = ['actual', 'complete']
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# , split_type = ['70_30', '80_20', 'sl']
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# , oversampling = True
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# , dst_colname = 'dst'# determine how to subset the actual vs reverse data
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# , target_colname = 'dst_mode'
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# , include_gene_name = True
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# , k_smote = 5)
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#%% split data into different data types
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# #===================
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# # 70/30
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# #===================
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# # actual
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# tts_7030_paramD = {'data_type' : 'actual'
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# , 'split_type' : '70_30'}
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# # complete
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# tts_cd_7030_paramD = {'data_type' : 'complete'
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# , 'split_type' : '70_30'}
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# # call split_tts()
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# data_CM_7030D = split_tts(ml_input_data = combined_df
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# , **tts_7030_paramD
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# , oversampling = True
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# , dst_colname = 'dst'
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# , target_colname = 'dst_mode'
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# , include_gene_name = False) # when not doing leave one group out
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# data_cd_CM_7030D = split_tts(ml_input_data = combined_df
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# , **tts_cd_7030_paramD
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# , oversampling = True
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# , dst_colname = 'dst'
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# , target_colname = 'dst_mode'
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# , include_gene_name = False)
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