I'm trying to to update an element in an array. If I've got an array say:
[[0, 0],
[0, 0]]
as far as I knew the way to update eg. the first element to 0.5, was
array[0,0] = 0.5
However when I print the array the contents are unchanged. I read some things on Stack Overflow about copies being created of arrays but I don't know if this applies.
Any help would be great
Your problem is that your array is integer-valued (because you initialize it with integers), and when you write a float to it, it gets rounded to 0. You can check that this is the case if you write
array = np.array([[0, 0], [0, 0]])
array[0, 0] = 1.5
>>> array = array([[1, 0],
[0, 0]])
To get the expected behaviour, either initialize it with floats
array = np.array([[0., 0.], [0., 0.]])
or explicitly specify dtype
array = np.array([[0, 0], [0, 0]], dtype=np.float32)
You need to change the data type of the numpy array before updating the value to float
import numpy as np
a = [[0,0],[0,0]]
a = np.array(a)
a = a.astype('float64')
a[0,0] = 0.5
print(a)
this will give you
[[0.5 0. ]
[0. 0. ]]
The data type of the array is automatically set to int, 0.5 as an int is 0.
# For example:
In [12]: int(0.5)
Out[12]: 0
# To construct the array try:
array = np.array([[0.0,0.0],[0.0,0.0]])
# or:
array = np.array([[0,0],[0,0]], dtype=float)
Then:
In [9]: array[0,0]=0.5
In [10]: array
Out[10]:
array([[0.5, 0. ],
[0. , 0. ]])
Python nested list objects don't support array-like indexing. You can use only a single value to to index a list
arr = [[0,0], [0,0]]
arr[0][0] = 0.5
arr # [[0.5, 0], [0, 0]]
To use the kind of indexing you mention in your post, you'll have to use a numpy array
import numpy as np
np_arr = np.array([[0,0], [0,0]], dtype=np.float32)
np_arr[0,0] = 0.5
