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("four/" + str(j) + str(drug) + "_X_test_cna.csv")
y_test_cna.to_csv("four/" + str(j) + str(drug) + "_y_test_cna.csv")
######################mgs expr part################
levels = np.unique(np.array(y_train))
print("levels:", levels)
File = open("four/" + str(j) + str(drug) + ".txt", "w")
File.write("levels:" + str(levels) + "\n")
clf = gcForest(shape_1X=(1, 400),
window=[100, 200],
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))
pd.DataFrame(expr_mgs_X).to_csv("four/expr_mgs_X.csv")
expr_window1 = expr_mgs_X[0]
print("expr_window1：", expr_window1)
expr_window2 = expr_mgs_X[1]
expr_mgs_X_test = clf.mg_scanning(np.array(X_test))
pd.DataFrame(expr_mgs_X_test).to_csv("four/expr_mgs_X_test.csv")
expr_window1_test = expr_mgs_X_test[0]
expr_window2_test = expr_mgs_X_test[1]
######################mgs cna part################