How I can i conditionally change the values in a numpy array taking into account nan numbers?
The fact that you have np.nan in your array should not matter. Just use fancy indexing:
x[x>0] = new_value_for_posx[x<0] = new_value_for_negIf you want to replace your np.nans:
x[np.isnan(x)] = something_not_nanMore info on fancy indexing a tutorial and the NumPy documentation.
to add or subtract to current value then (np.nan not affected)
import numpy as npa = np.arange(-10, 10).reshape((4, 5))print("after -")print(a)a[a<0] = a[a<0] - 2a[a>0] = a[a>0] + 2print(a)output
[[-10 -9 -8 -7 -6] [ -5 -4 -3 -2 -1] [ 0 1 2 3 4] [ 5 6 7 8 9]]after -[[-12 -11 -10 -9 -8] [ -7 -6 -5 -4 -3] [ 0 3 4 5 6] [ 7 8 9 10 11]]