How to convert a numpy array from 'float64' to 'float'

Question

How do I convert a numpy array from type 'float64' to type 'float'? Specifically, how do I convert an entire array with dtype 'float64' to have dtype 'float'? Is this possible? The answer for scalars in the thought-to-be duplicate question above does not address my question.

Consider this:

>>> type(my_array[0])
<type 'numpy.float64'>

>>> # Let me try to convert this to 'float':
>>> new_array = my_array.astype(float)
>>> type(new_array[0])
<type 'numpy.float64'>

>>> # No luck.  What about this:
>>> new_array = my_array.astype('float')
>>> type(new_array[0])
<type 'numpy.float64'>

>>> # OK, last try:
>>> type(np.inf)
<type 'float'>
>>> # Yeah, that's what I want.
>>> new_array = my_array.astype(type(np.inf))
>>> type(new_array[0])
<type 'numpy.float64'>

If you're unsure why I might want to do this, see this question and its answers.

Answer 1

Yes, actually when you use Python's native float to specify the dtype for an array , numpy converts it to float64. As given in documentation -

Note that, above, we use the Python float object as a dtype. NumPy knows that int refers to np.int_, bool means np.bool_ , that float is np.float_ and complex is np.complex_. The other data-types do not have Python equivalents.

And -

float_ - Shorthand for float64.

This is why even though you use float to convert the whole array to float , it still uses np.float64.

According to the requirement from the other question , the best solution would be converting to normal float object after taking each scalar value as -

float(new_array[0])

---

A solution that I could think of is to create a subclass for float and use that for casting (though to me it looks bad). But I would prefer the previous solution over this if possible. Example -

In [20]: import numpy as np

In [21]: na = np.array([1., 2., 3.])

In [22]: na = np.array([1., 2., 3., np.inf, np.inf])

In [23]: type(na[-1])
Out[23]: numpy.float64

In [24]: na[-1] - na[-2]
C:\Anaconda3\Scripts\ipython-script.py:1: RuntimeWarning: invalid value encountered in double_scalars
  if __name__ == '__main__':
Out[24]: nan

In [25]: class x(float):
   ....:     pass
   ....:

In [26]: na_new = na.astype(x)


In [28]: type(na_new[-1])
Out[28]: float                           #No idea why its showing float, I would have thought it would show '__main__.x' .

In [29]: na_new[-1] - na_new[-2]
Out[29]: nan

In [30]: na_new
Out[30]: array([1.0, 2.0, 3.0, inf, inf], dtype=object)