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,
