I have a list containing 1D numpy arrays different sizes. Now I want to remove the last value of each numpy array inside this list and concatenate them into one 1D numpy array.
As an example, I have this:
p=[np.array([1,2,3,4,5,6]),np.array([1,2,3]),np.array([1,2])]
and I would like to have that:
p=np.array([1,2,3,4,5,1,2,1])
I will appreciate any help to approach this issue.
You can try:
np.hstack([a[:-1] for a in p])
I would recommend you to create a new list from the arrays and use this list to initialize a new numpy array, like this:
new_list = []
for i in range(len(p)):
new_list += p[i].tolist()[:-1]
p = np.array(new_list)
c=[]
for i in p:
a=i[:-1]
for j in a: c.append(j)`
p=numpy.array(c)
this is how i would do it with a normal list item. But i'm not 100% sure how numpy.array functions, it may be the same. - although some brief testing showed it was the same.
Here is the solution
import numpy as np
p=[np.array([1,2,3,4,5,6]),np.array([1,2,3]),np.array([1,2])]
final = []
for i in p:
for k in range(len(i)-1):
final.append(i[k])
A one-liner using list comprehension (I think you could do this with an iterator directly to numpy too) would be:
p = np.concatenate( [arr[:-1] for arr in p])
You can try:
np.asarray([ val for arr in p for val in arr[:-1]])
