Numpy：只有整数标量数组可以转换为标量索引

Question

代码如下：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import pandas_datareader as web
import datetime as dt 

from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM

# Load data
company = 'FB'

start = dt.datetime(2012,1,1)
end = dt.datetime(2020,1,1)

data = web.DataReader(company, 'yahoo', start, end)

#Prepare Data
scaler = MinMaxScaler(feature_range=(0,1))
scaled_date = scaler.fit_transform(data['Close'].values.reshape(-1,1))

prediction_days = 60

x_train = []
y_train = []

for x in range(prediction_days, len(scaled_date)):
    x_train.append(scaled_date[x-prediction_days:x, 0])
    y_train.append(scaled_date[x, 0])

x_train, y_train = np.array(x_train), np.array(y_train)
x_train = np.reshape(x_train, (x_train.shape[0], x_train[1], 1)) #the error's here

我收到以下错误：

Traceback（最近一次调用最后一次）：文件 “/Users/evgenypavlov/Documents/ml_tutorial_1/main.py”，第 34 行，在 x_train = np.reshape(x_train, (x_train.shape[0], x_train[1], 1)) 文件“array_function internals>”，第 5 行，在 reshape 文件中 "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/numpy/core/fromnumeric.py", 第 299 行，重塑 return _wrapfunc(a, 'reshape', newshape, order=order) 文件 "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/numpy/core/fromnumeric.py", 第 67 行，在 _wrapfunc 中 返回_wrapit（obj，方法，*args，**kwds）文件“/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/numpy/core/fromnumeric.py”， 第 44 行，在 _wrapit 中 result = getattr(asarray(obj), method)(*args, **kwds) TypeError: only integer scalar arrays can be convert to a scalar index

据我所知，我已经将其转换为 np.array，那么可能导致此问题的原因以及如何解决呢？

Answer 1

您在元组的第二个元素中缺少shape：

x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], 1))