帮我转为python语言：[P_train, ps_input] = mapminmax(P_train, 0, 1); P_test = mapminmax('apply', P_test, ps_input); t_train = categorical(T_train)'; t_test = categorical(T_test )';

当然可以！

from sklearn.preprocessing import MinMaxScaler
import numpy as np

scaler = MinMaxScaler(feature_range=(0, 1))

P_train = np.array(P_train)
P_test = np.array(P_test)

P_train_scaled = scaler.fit_transform(P_train)
P_test_scaled = scaler.transform(P_test)

ps_input = scaler.get_params()

t_train = np.array(T_train)
t_train_categorical = np.array(pd.get_dummies(t_train)).T

t_test = np.array(T_test)
t_test_categorical = np.array(pd.get_dummies(t_test)).T

请注意，此处假设你已经导入了必要的库（例如sklearn和numpy）。此外，我还假设输入数据P_train和P_test已经存在，并且T_train和T_test是对应的目标变量。