Conversion from numpy array float32 to numpy array float64

Question

I am trying to implement randomforest in Python. While running the code I got this error. Although I had already converted from float32 to float64 using :

x_arr = np.array(train_df, dtype='float64')

Traceback(most recent call last):
  File "C:\Python27\randomforest.py", line 67, in <module>     
    forest=forest.fit(x_array[0::,1::],x_array[0::,0])
  File "C:\Python27\lib\site-packages\sklearn\ensemble\forest.py", line 212, in fit
    X = check_array(X, dtype=DTYPE, accept_sparse="csc")   
  File "C:\Python27\lib\site-packages\sklearn\utils\validation.py", line 398, in check_array
    _assert_all_finite(array)
  File "C:\Python27\lib\site-packages\sklearn\utils\validation.py", line 54, in _assert_all_finite
    " or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for dtype('float32').

Please can somebody help?

What happens when you try dtype=np.float64 instead?

Aguy
– Aguy

2016-07-13 13:42:14 +00:00
Commented Jul 13, 2016 at 13:42 — Aguy
– Aguy, Commented Jul 13, 2016 at 13:42

John Zwinck · Accepted Answer · 2016-07-13 12:36:25Z

1

The problem is not that you're failing to set a float64 dtype. The error message says:

Input contains NaN, infinity or a value too large for dtype('float32').

So try checking for those conditions first:

assert not np.any(np.isnan(x_arr))
assert np.all(np.isfinite(x_arr))
assert np.all(x_arr <= finfo('float32').max)
assert np.all(x_arr >= finfo('float32').min)

answered Jul 13, 2016 at 12:36

John Zwinck

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Comments

malla · Accepted Answer · 2017-11-21 11:00:50Z

1

I got here because of the question in the title which I still feel remains unanswered. To convert float32 to float64 in a numpy.ndarray object:

array32 = np.ndarray(shape=(2,2), dtype=np.float32, order='F')
print("Type of an object of 'array32': " + str(type(array32[0][0])))

# Convert to float64
array64 = array32.astype(np.float64)
print("Type of an object of 'array64': " + str(type(array64[0][0])))

# Convert back to float32
array32again = array64.astype(np.float32)
print("Type of an object of 'array32again': " + str(type(array32again[0][0])))

Will give you:

Type of an object of 'array32': <class 'numpy.float32'>
Type of an object of 'array64': <class 'numpy.float64'>
Type of an object of 'array32again': <class 'numpy.float32'>

edited Nov 21, 2017 at 11:00

answered Aug 22, 2017 at 16:14

malla

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