How can I prepopulate while initializing numpy array with fixed values? I tried generating list and using that as a fill.

>>> c = np.empty(5)
>>> c
array([0.0e 000, 9.9e-324, 1.5e-323, 2.0e-323, 2.5e-323])
>>> np.array(list(range(0,10,1)))
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> 
 
>>> c.fill(np.array(list(range(0,10,1))))
TypeError: only length-1 arrays can be converted to Python scalars

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

>>> c.fill([np.array(list(range(0,10,1)))])
TypeError: float() argument must be a string or a real number, not 'list'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

Expected -

array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])

CodePudding user response：

fill fills each entry with the same value. c = np.empty(size); c.fill(5) allocates an array of size size without initialising any values and then fills it with all 5.

In addition to the answer by AJ Biffl, you can also assign values to an ndarray via broadcasting:

c = np.empty(5)
c[:] = range(5)

This only works if the shapes match, but it does let you do stuff like this:

a = np.empty((5, 3))
a[:] = [range(i, i 3) for i in range(5)]

>>> array([[0., 1., 2.],
       [1., 2., 3.],
       [2., 3., 4.],
       [3., 4., 5.],
       [4., 5., 6.]])

CodePudding user response：

np.tile(np.arange(10), (5,1))

np.arange(10) creates an array of integers from 0 to 9

np.tile(..., (5,1)) tiles copies of the array - 5 copies going "down" (new rows) and 1 "across" (1 copy within each row)