insert numpy.float64 element in a numpy array

Question

I am trying to insert a numpy float in a numpy ndarray. The Code and the output is:

dos = np.sum(atom[:, :, 1:],axis=0)
print("type(dos)")
print(type(dos))
print("dos.shape")
print(dos.shape)
print("dos[15] Before")
print(dos[15])
print("type(atom[1,0,0])")
print(type(atom[1,0,0]))
print("atom[1,0,0]")
print(atom[1,0,0])
for i in range(301):
    dos2=np.insert(dos, 0, atom[1,0,0])
print("dos[15] After ")
print(dos2[15])
print("type(dos2)")
print(type(dos2))

and the corresponding output is:

type(dos)
<class 'numpy.ndarray'>
dos.shape
(301, 18)
dos[15] Before
[ -9.75080030e-02  -8.37110240e-02  -3.13760517e-03  -2.70089494e-03
  -2.07915835e-03  -1.77532740e-03  -2.03548911e-03  -1.73346437e-03
  -1.98000973e-04  -1.64015415e-04  -1.99115166e-04  -1.65569761e-04
  -9.07381374e-05  -7.37546825e-05  -1.48250176e-04  -1.22108731e-04
  -1.18854648e-04  -9.70416840e-05]
type(atom[1,0,0])
<class 'numpy.float64'>
atom[1,0,0]
-4.11
dos[15] After 
0.0
type(dos2)
<class 'numpy.ndarray'>

where the expected result is:

 [ -4.11 -9.75080030e-02  -8.37110240e-02  -3.13760517e-03  -2.70089494e-03
         -2.07915835e-03  -1.77532740e-03  -2.03548911e-03  -1.73346437e-03
         -1.98000973e-04  -1.64015415e-04  -1.99115166e-04  -1.65569761e-04
         -9.07381374e-05  -7.37546825e-05  -1.48250176e-04  -1.22108731e-04
         -1.18854648e-04  -9.70416840e-05]

from the numpy documentation, I cant see where i went wrong. Kindly help.

val · Accepted Answer · 2016-06-28 11:08:11Z

From the doc mentionned:

A copy of arr with values inserted. Note that insert does not occur in-place: a new array is returned. If axis is None, out is a flattened array.

This means that your loop:

for i in range(301):
    dos2=np.insert(dos, 0, atom[1,0,0])

Does 300 useless operations, then inserts a single value, and dos2 contains the 301*18 values of dos plus one value (flattened):

>>> dos = np.random.random((3, 3))
>>> dos2 = np.insert(dos, 0, 12)
>>> dos2
array([ 12.        ,   0.30211688,   0.39685661,   0.89568364,
         0.14398144,   0.39122099,   0.8017827 ,   0.35158563,
         0.18771122,   0.89938571])
>>> dos2[5]
0.39122099250162556

What you probably want is to happend that value to each of the elements in dos:

>>> dos2 = np.empty((dos.shape[0], dos.shape[1] + 1), dtype=dos.dtype)
>>> for i in range(dos.shape[0]):
...     dos2[i] = np.insert(dos[i], 0, 12)
...
>>> dos2
array([[ 12.        ,   0.30211688,   0.39685661,   0.89568364],
       [ 12.        ,   0.14398144,   0.39122099,   0.8017827 ],
       [ 12.        ,   0.35158563,   0.18771122,   0.89938571]])

Which can also be expressed simply as:

>>> dos2 = np.empty((dos.shape[0], dos.shape[1] + 1), dtype=dos.dtype)
>>> dos2[:, 0] = 12
>>> dos2[:, 1:] = dos

Chris Mueller · Accepted Answer · 2016-06-28 12:27:55Z

1

From your 'expected result' it looks like you only want to insert a single value at the beginning of the already flat array. There is definitely no need to use a for loop to do this.

>>> insert_value = 100
>>> orig_array = np.array([1, 2, 3, 4, 5])
>>> final_array = np.insert(orig_array, 0, insert_value)
>>> print(final_array)
[100   1   2   3   4   5]

answered Jun 28, 2016 at 12:27

Chris Mueller

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