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python - Why will numpy.round will not round my array?

问题描述

I am trying to round a numpy array that is outputted by the result of a Keras model prediction. However after executing numpy.round/numpy.around, there is no change.

The end goal here is for the array to get rounded down to 0 if below/equal 0.50 or rounded up if above 0.50.

The code is here:

from keras.models import load_model

import numpy

model = load_model('tried.h5')
data = numpy.loadtxt("AppData\Roaming\MetaQuotes\Terminal\94DDB309C90B408373EFC53AC730F336\MQL4\Files\indicatorout.csv", delimiter=",")
data = numpy.array([data])
print(data)
outdata = model.predict(data)
print(outdata)
numpy.around(outdata, 0)
print(outdata)
numpy.savetxt("AppData\Roaming\MetaQuotes\Terminal\94DDB309C90B408373EFC53AC730F336\MQL4\Files\modelout.txt", outdata)

The logs are also here:

Using TensorFlow backend.
[[1.19539070e+01 1.72686310e+01 2.24426384e+01 1.82771435e+01
  2.23788052e+01 1.62105408e+01 1.44595184e+01 1.90179043e+01
  1.71749554e+01 1.69194088e+01 1.89911938e+01 1.76701393e+01
  5.19613740e-01 5.38522415e+01 9.64037247e+01 1.73570000e-04
  4.35710000e-04 9.55710000e-04]]
[[0.4215713]]
[[0.4215713]]

Any help would be greatly appreciated, thank you.

标签： pythonnumpytensorflowroundingnumpy-ndarray

解决方案

我假设您希望数组中的元素四舍五入到n小数位。下面是这样做的说明：

# sample array to work with
In [21]: arr = np.random.randn(4)

In [22]: arr
Out[22]: array([-0.94817409, -1.61453252,  0.16566428, -0.53507549])

# round to 3 decimal places; note that `arr` is still unaffected.
In [23]: arr.round(decimals=3)
Out[23]: array([-0.948, -1.615,  0.166, -0.535])

# if you want to round it to nearest integer
In [24]: arr_rint = np.rint(arr)

In [25]: arr_rint
Out[25]: array([-1., -2.,  0., -1.])

要使小数舍入就地工作，请指定out=参数，如下所示：

In [26]: arr.round(decimals=3, out=arr)
Out[26]: array([-0.948, -1.615,  0.166, -0.535])

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