我正在使用递归神经网络根据以前的风数据进行每小时风预测.我试图将我的数据移回1小时后使用.shift生成它.我DateFrame看起来像[这] [1]我的代码是:
import numpy as np
import pandas as pd
from pandas import DataFrame
wind_p = [0, 0.03454225, 0.02062136, 0.00186715, 0.01517354, 0.0129046,
0.02231125, 0.01492537, 0.09646542, 0.28444476]
Speed = [0, 2.25226244, 1.44078451, 0.99174488, 0.71179491, 0.92824542, 1.67776948, 2.96399534, 5.06257161, 7.06504245]
Date = ['2012-01-01 01:00:00' ,'2012-01-01 02:00:00', '2012-01-01 03:00:00', '2012-01-01 04:00:00',
'2012-01-01 05:00:00', '2012-01-01 06:00:00', '2012-01-01 07:00:00',
'2012-01-01 08:00:00', '2012-01-01 09:00:00', '2012-01-01 10:00:00']
df = pd.DataFrame({'date':Date,'wind_P':wind_p,'Speed':Speed})
dates=[datetime.strptime(x,'%Y-%m-%d %H:%M:%S') for x in Date]
df['t']= [x for x in range(10)]
df['t+1'] …我正在尝试卸载当前版本的 keras 并使用以下方法安装旧版本：
!pip uninstall keras
!pip install keras==2.1.2
我得到的回报是：
Uninstalling Keras-2.1.2:
Would remove:
/home/nbuser/anaconda3_501/lib/python3.6/site-packages/Keras-2.1.2.dist-info/*
/home/nbuser/anaconda3_501/lib/python3.6/site-packages/keras/*
Proceed (y/n)?
我可以请教如何选择是吗？
我正在Azure中设置循环神经网络：
model = Sequential()
model.add(GRU(units=512,
return_sequences=True,
input_shape=(None, x1,)))
model.add(Dense(y1, activation='sigmoid'))
但是我得到了错误：
TypeError: while_loop() got an unexpected keyword argument 'maximum_iterations'
我不是cretin，但我相信我可能正在做一些在当前版本的TensorFlow＆Keras中已经过时的折旧，因为在此示例中发生了类似的错误，并指出了此类错误。我正在Jupyter Azure平台中使用Python 3.6，这也意味着我不确定我正在使用哪个版本的Keras和TensoFlow。
我完整的Tracback错误消息是：
TypeError Traceback (most recent call last)
<ipython-input-7-e6bcba2d0346> in <module>()
205 model.add(GRU(units=512, return_sequences=True,
--> 207 input_shape=(None,x1,)))
208
~/anaconda3_501/lib/python3.6/site-packages/keras/engine/sequential.py in add(self, layer)
164 # and create the node connecting the current layer
165 # to the input layer we just created.
--> 166 layer(x)
167 set_inputs = True
168 else:
~/anaconda3_501/lib/python3.6/site-packages/keras/layers/recurrent.py in __call__(self, inputs, initial_state, constants, **kwargs) …我可以请求帮助将我的日期和时间,数据01/01/2012 01:00转换为2012-01-01 01:00:00ʔ我尝试过的事情
datetime = [datetime.datetime(2012, 1, 1, 1, 0, 0) + datetime.timedelta(hours=i) for
i in range(9)]
dates=[datetime.strptime('%Y-%m-%d %H:%M:%S') for x in datetime]
这将返回错误ː
AttributeError: 'list' object has no attribute 'strptime'
我的csv文件中的日期时间如下所示
01/01/2012 01:00
01/01/2012 02:00
01/01/2012 03:00
01/01/2012 04:00
01/01/2012 05:00
01/01/2012 06:00
01/01/2012 07:00
01/01/2012 08:00
01/01/2012 09:00
我相信这一定非常直接,但我似乎无法理解这一点.对此的帮助将不胜感激