值错误：无法将输入数组从形状（11253,1）广播到形状（11253）

Question

我正在使用这个example创建一个神经网络，我得到错误“ValueError:could not broadcast input array from shape（11253,1）”到shape（11253），行：trainPredictPlot[look_back:len(trainPredict)+look_back] = trainPredicty我的代码是：

import csv
import math
import numpy as np 
import pandas as pd
from keras.models import Sequential
from keras.layers import Dense
import datetime
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split

X1 = [1:16801] #16,800 values
Y1 = [1:16801]#16,800 values

train_size = int(len(X1) * 0.67)
test_size = len(X1) - train_size

train, test = X1[0:train_size,], X1[train_size:len(X1),]
def Data(X1, look_back=1):
     dataX, dataY = [], []
     for i in range(len(X1)-look_back-1):
         a = X1[i:(i+look_back), 0]
         dataX.append(a)
         dataY.append(Y1[i + look_back, 0])
     return numpy.array(dataX), numpy.array(dataY)

look_back = 1
trainX, testX = Data(train, look_back)

testX, testY = Data(test, look_back)

look_back = 1
trainX, testX = Data(train, look_back)

testX, testY = Data(test, look_back)


trainPredict = model.predict(trainX)
testPredict = model.predict(testX)

trainPredictPlot = numpy.empty_like(Y1)
trainPredictPlot[look_back:len(trainPredict)+look_back] = trainPredict

testPredictPlot = numpy.empty_like(Y1) 
testPredictPlot[len(trainPredict)+(look_back*2)+1:len(X1)-1] = testPredict

我有16800个X1值，如下所示：

^{pr2}$

我的Y1数据看起来像：

[ 2.25226244  1.44078451  0.99174488 ... 12.8397099   9.75722427 7.98525797]

我的回溯错误消息是：

ValueError                                Traceback (most recent call last)
<ipython-input-9-e4da8990335b> in <module>()
    116 trainPredictPlot = numpy.empty_like(Y1)
    117 
--> 118 trainPredictPlot[look_back:len(trainPredict)+look_back] = trainPredict
    119 
    120 testPredictPlot = numpy.empty_like(Y1)

ValueError: could not broadcast input array from shape (11253,1) into shape (11253)

Answer 1

在赋值之前，将trainPredict从二维数组转换为一维向量：

trainPredictPlot[look_back:len(trainPredict)+look_back] = trainPredict.ravel()