I am trying to merge a sliced array to a list in Python but i get an
error: ValueError: operands could not be broadcast together with shapes `(4,)` `(2,)` .
This is my code:
y = np.array([5,3,2,4,6,1])
row = y[2:6] + np.array([0,0])
I am expecting to get a 2-item shifted vector to the left and last 2 items being assigned to 0.
Numpy array works something like a matrix. So when you try to apply the addition operation to a numpy array, you're actually performing an "element-wise addition". That's why the value you add with a numpy array must be the same dimension as the numpy array. Otherwise such a value that can be broadcasted.
Notice the example to understand what I'm saying.
Adding two lists with addition sign:
>>> [1,2] + [3,4]
[1, 2, 3, 4]
Adding two numpy arrays:
>>> np.array([1,2]) + np.array([3,4])
array([4, 6])
To get your work done, use the np.append(arr, val, axis) function. Documentation
array([1, 2, 3, 4])
>>> np.append([1,2], np.array([3,4]))
array([1, 2, 3, 4])
To concatenate arrays use np.concatenate:
In [93]: y = np.array([5,3,2,4,6,1])
In [94]: y[2:6]
Out[94]: array([2, 4, 6, 1])
In [95]: np.concatenate((y[2:6], np.array([0,0])))
Out[95]: array([2, 4, 6, 1, 0, 0])
+ is concatenate for lists. For arrays is addition (numeric sum).
Your question should not have used list and array in a sloppy manner. They are different things (in python/numpy) and can produce confusing answers.
For concatenation, you will need to convert your numpy array to a list first.
row = y[2:6] + list(np.array([0,0]))
or equivalently
row = y[2:6] + np.array([0,0]).tolist()
However, if you wish to add the two (superpose a list and numpy array), then the numpy array just needs to be the same shape as y[2:6]:
In : y[2:6] + np.array([1, 2, 3, 4])
Out: array([y[2] + 1, y[3] + 2, y[4] + 3, y[5] + 4])
Other answers already explain why your code fail. You can do:
out = np.zeros_like(y)
out[:-2] = y[2:]
Output:
array([2, 4, 6, 1, 0, 0])
