def gcf(X_train, X_test, y_train, y_test, cnames): clf = gcForest(shape_1X=(1, 18988), window=[1000, 2000], stride=10) clf.fit(X_train, y_train) y_pred = clf.predict(X_test) print(y_pred)
y_test_cna = y_cna.iloc[folds_cna[j]] X_train_cna = x_cna.iloc[ list(set(range(x.shape[0])).difference(set(folds_cna[j]))), :] y_train_cna = y_cna.iloc[list( set(range(x.shape[0])).difference(set(folds_cna[j])))] X_test_cna.to_csv("two4/" + str(j) + str(drug) + "_X_test_cna.csv") y_test_cna.to_csv("two4/" + str(j) + str(drug) + "_y_test_cna.csv") ######################expr part################ levels = np.unique(np.array(y_train)) print("levels:", levels) File = open("two4/" + str(j) + str(drug) + "expr.txt", "w") File.write("levels:" + str(levels) + "\n") clf_expr = gcForest(shape_1X=(1, 400), window=[100, 200], stride=2, levels=levels, f=File) mgs_X_expr = clf_expr.mg_scanning(np.array(X_train), np.array(y_train)) expr_window1 = mgs_X_expr[0] expr_window2 = mgs_X_expr[1] expr_mgs_X_test = clf_expr.mg_scanning(np.array(X_test)) expr_window1_test = expr_mgs_X_test[0] expr_window2_test = expr_mgs_X_test[1] train_predict_y = clf_expr.cascade_forest(expr_window1, expr_window2, np.array(y_train)) if train_predict_y == "no_features": feature_flag = "no_features" print("drug" + str(drug) +
y_test_cna = y_cna.iloc[folds_cna[j]] X_train_cna = x_cna.iloc[ list(set(range(x.shape[0])).difference(set(folds_cna[j]))), :] y_train_cna = y_cna.iloc[list( set(range(x.shape[0])).difference(set(folds_cna[j])))] X_test_cna.to_csv("two1/" + str(j) + str(drug) + "_X_test_cna.csv") y_test_cna.to_csv("two1/" + str(j) + str(drug) + "_y_test_cna.csv") ######################mgs expr part################ levels = np.unique(np.array(y_train)) print("levels:", levels) File = open("two1/" + str(j) + str(drug) + ".txt", "w") File.write("levels:" + str(levels) + "\n") clf = gcForest(shape_1X=(1, 400), window=[100], stride=2, levels=levels, f=File) if np.shape(X_train)[0] != len(y_train): raise ValueError('Sizes of y and X do not match.') expr_mgs_X = clf.mg_scanning(np.array(X_train), np.array(y_train)) print(expr_mgs_X) expr_window1 = expr_mgs_X[0] print("expr_window1:", expr_window1) expr_mgs_X_test = clf.mg_scanning(np.array(X_test)) expr_window1_test = expr_mgs_X_test[0] ######################mgs cna part################ clf = gcForest(shape_1X=(1, 400), window=[100], stride=2,