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3 changed files with 11 additions and 8 deletions
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@ -139,9 +139,9 @@ def CMLogoSkf(cm_input_df
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# else:
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# file_suffix = file_suffix
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outFile = output_dir + str(n_tr_genes+1) + "genes_" + tts_split_type + '_' + file_suffix + ".csv"
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#outFile = output_dir + str(n_tr_genes+1) + "genes_" + tts_split_type + '_' + file_suffix + ".csv"
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print(outFile)
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#print(outFile)
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#-------
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# training
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@ -175,6 +175,7 @@ def CMLogoSkf(cm_input_df
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, '\nTEST Target dim:' , cm_bts_y.shape)
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print("Running Multiple models on LOGO with SKF")
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#%%:Running Multiple models on LOGO with SKF
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# cD3_v2 = MultModelsCl_logo_skf(input_df = cm_X # two func were identical excpet for name
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cD3_v2 = MultModelsCl(input_df = cm_X
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@ -203,11 +204,11 @@ def CMLogoSkf(cm_input_df
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#===============
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# Complete Data
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#===============
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CMLogoSkf(cm_input_df = combined_df,file_suffix = "complete")
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CMLogoSkf(cm_input_df = combined_df, std_gene_omit=['alr'], file_suffix = "complete")
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#CMLogoSkf(cm_input_df = combined_df,file_suffix = "complete")
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#CMLogoSkf(cm_input_df = combined_df, std_gene_omit=['alr'], file_suffix = "complete")
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#===============
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# Actual Data
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#===============
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CMLogoSkf(cm_input_df = combined_df_actual, file_suffix = "actual")
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CMLogoSkf(cm_input_df = combined_df_actual, std_gene_omit=['alr'], file_suffix = "actual")
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#CMLogoSkf(cm_input_df = combined_df_actual, file_suffix = "actual")
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#CMLogoSkf(cm_input_df = combined_df_actual, std_gene_omit=['alr'], file_suffix = "actual")
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@ -269,7 +269,9 @@ def split_tts(ml_input_data
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#k_sm = 5 # default
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k_sm = k_smote
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sm_nc = SMOTENC(categorical_features=categorical_colind, k_neighbors = k_sm, **rs, **njobs)
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sm_nc = SMOTENC(categorical_features=categorical_colind
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, k_neighbors = k_sm
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, **rs, **njobs)
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X_smnc, y_smnc = sm_nc.fit_resample(X, y)
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print('\nSMOTE_NC OverSampling\n', Counter(y_smnc))
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print(X_smnc.shape)
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@ -54,6 +54,7 @@ expected_ncols
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if len(common_cols) == expected_ncols:
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print('\nProceeding to combine based on common cols (n):', len(common_cols))
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combined_df = pd.concat([df[common_cols] for df in dfs_combine], ignore_index = False)
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print('\nSuccessfully combined dfs:'
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, '\nNo. of dfs combined:', len(dfs_combine)
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, '\nDim of combined df:', combined_df.shape)
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@ -76,7 +77,6 @@ cm_input_df5 = combined_df[~combined_df['gene_name'].isin(omit_gene_alr)]
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combined_df['dst'].isna().sum()
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combined_df['dst'].value_counts().sum()
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combined_df_actual = combined_df[~combined_df['dst'].isna()]
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##############################################################################
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