I have a numpy array, and i want see if it's possible to modify the index values (not the array values) with a custom sequence of numbers.
Let's say the array lengh is 10, it's possible to change the indexes so instead of accessing it's elements with the indexes 0-9 it can be accesed with.. let's say.. 50-59?
Basically like changing the rownames/colnames but in a np array instead of a pandas df.
Not sure if there is ever a need for it and I'm sure there are other ways but one way would be to create a class for it. Working on your example of 50-59:
class UnnaturalList(list):
def __getitem__(self, index):
if type(index) == int and index > 0:
index -= 50
if type(index) == slice:
start, stop = index.start, index.stop
if start and start > 0:
start -= 50
if stop and stop > 0:
stop -= 50
index = slice(start, stop, index.step)
return super().__getitem__(index)
def __setitem__(self, index, val):
super().__setitem__(index - 50, val)
Then you can create a list with this class and use indexing and slicing
a_list = UnnaturalList(range(1,6))
a_list --> [1,2,3,4,5]
a_list[50] --> 1
a_list[51] --> 2
a_list[50:53] --> [1,2,3]
I would think there is a way to do something similar for arrays, or something cleaner, but this is one method for you.
numpyarrays don't have row/col names. Indices are strictly by count starting with 0.