@goncalopp gives a correct answer, but there are a few variations that will achieve similar effects.
All of the notations shown below are able to reference a single element while still returning a view:
x = np.arange(10)
two_index_method = [None] * 10
scalar_element_method = [None] * 10
expansion_method = [None] * 10
for i in range(10):
two_index_method[i] = x[i:i+1]
scalar_element_method[i] = x[..., i] # x[i, ...] works, too
expansion_method[i] = x[:, np.newaxis][i] # np.newaxis == None
two_index_method[5] # Returns a length 1 numpy.ndarray, shape=(1,)
# >>> array([5])
scalar_element_method[5] # Returns a numpy scalar, shape = ()
# >>> array(5)
expansion_method[5] # Returns a length 1 numpy.ndarray, shape=(1,)
# >>> array([5])
x[5] = 42 # Change the value in the original `ndarray`
x
# >>> array([0, 1, 2, 3, 4, 42, 6, 7, 8, 9]) # The element has been updated
# All methods presented here are correspondingly updated:
two_index_method[5], scalar_element_method[5], expansion_method[5]
# >>> (array([42]), array(42), array([42]))
Since the object in scalar_element_method
is a dimension zero scalar, attempting to reference the element contained within the ndarray
via element[0]
will return an IndexError
. For a scalar ndarray
, element[()]
can be used to reference the element contained within the numpy scalar. This method can also be used for assignment to a length-1 ndarray
, but has the unfortunate side effect that it does not dereference a length-1 ndarray
to a python scalar. Fortunately, there is a single method, element.item()
, that can be used (for dereferencing only) to obtain the value regardless of whether the element is a length one ndarray
or a scalar ndarray
:
scalar_element_method[5][0] # This fails
# >>> IndexError: too many indices for array
scalar_element_method[5][()] # This works for scalar `ndarray`s
# >>> 42
scalar_element_method[5][()] = 6
expansion_method[5][0] # This works for length-1 `ndarray`s
# >>> 6
expansion_method[5][()] # Doesn't return a python scalar (or even a numpy scalar)
# >>> array([6])
expansion_method[5][()] = 8 # But can still be used to change the value by reference
scalar_element_method[5].item() # item() works to dereference all methods
# >>> 8
expansion_method[5].item()
# >>> [i]8
TLDR; You can create a single-element view v
with v = x[i:i+1]
, v = x[..., i]
, or v = x[:, None][i]
. While different setters and getters work with each method, you can always assign values with v[()]=new_value
, and you can always retrieve a python scalar with v.item()
.