numpy array assign values from another array

Question

If I do something like this:

import numpy as np
b=np.array([1,2,3,4,5])
c=np.array([0.6,0.7,0.8,0.9])
b[1:]=c

I get b =

array([1,0,0,0,0])

It works fine if c only contains integers. But I have fractions. I wish to get something like this:

array([1,0.6,0.7,0.8,0.9])

How can I achieve that?

Answer 1

Numpy arrays are strongly typed. Make sure your arrays have the same type, like this:

import numpy as np

b = np.array([1, 2, 3, 4, 5])
c = np.array([0.6, 0.7, 0.8, 0.9])

b = b.astype(float)
b[1:] = c

# array([ 1. ,  0.6,  0.7,  0.8,  0.9])

You can, if you wish, even pass types from other arrays, e.g.

b = b.astype(c.dtype)

Answer 2

If you don't know whether the types are matched or not it is more economical to either use .astype with the copy flag set to False or to use np.asanyarray:

>>> b_float = np.arange(5.0)
>>> b_int = np.arange(5)
>>> c = np.arange(0.6, 1.0, 0.1)
>>> 

>>> b = b_float.astype(float)
# astype makes an unnecessary copy
>>> np.shares_memory(b, b_float)
False

# avoid this using the copy flag ...
>>> b = b_float.astype(float, copy=False)
>>> b is b_float
True

# or asanyarray
>>> b = np.asanyarray(b_float, dtype=float)
>>> b is b_float
True

# if the types do not match the flag has no effect
>>> b = b_int.astype(float, copy=False)
>>> np.shares_memory(b, b_int)
False

# likewise asanyarray does make a copy if it must
>>> b = np.asanyarray(b_int, dtype=float)
>>> np.shares_memory(b, b_int)
False