Menu
If I have two numpy arrays of different sizes, how can I superimpose them.
a = numpy([0, 10, 20, 30]) b = numpy([20, 30, 40, 50, 60, 70]) What is the cleanest way to add these two vectors to produce a new vector (20, 40, 60, 80, 60, 70)?
This is my generic question. For background, I am specifically applying a Green's transform function and need to superimpose the results for each time step in the evaulation unto the responses previously accumulated.
443
You can either reshape it array_2. reshape(-1,1) , or add a new axis array_2[:,np. newaxis] to make it 2 dimensional before concatenation.
Use the numpy. add() Function to Perform Vector Addition in NumPy. The add() function from the numpy module can be used to add two arrays. It performs addition over arrays that have the same size with elements at every corresponding position getting summed up.
Creating arrays with more than one dimensionIn general numpy arrays can have more than one dimension. One way to create such array is to start with a 1-dimensional array and use the numpy reshape() function that rearranges elements of that array into a new shape.
To concatenate the array of two different dimensions. The np. column_stack((array1, array2)) is used. To get the output, I have used print(array1).
This could be what you are looking for
if len(a) < len(b): c = b.copy() c[:len(a)] += a else: c = a.copy() c[:len(b)] += b basically you copy the longer one and then add in-place the shorter one
200
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
