Reputation: 6870
I am just playing around with a particle simulator, I want to use matplotlib with python and numpy to make as realistic a simulator as possible as efficiently as possible (this is purely an exercise in fun with python) and I have a problem trying to calculate the inverse of distances.
I have an array containing positions of particles (x,y) like so:
x = random.randint(0,3,10).reshape(5,2)
>>> x
array([[1, 1],
[2, 1],
[2, 2],
[1, 2],
[0, 1]])
This is 5 particles with positions (x,y) in [0,3]. Now if I want to calculate the distance between one particle (say particle with position (0,1)) and the rest I would do something like
>>>x - [0,1]
array([[1, 0],
[2, 0],
[2, 1],
[1, 1],
[0, 0]])
The problem is I do NOT want to take the distance of the particle to itself: (0,0). This has length 0 and the inverse is infinite and is not defined for say gravity or the coloumb force.
So I tried: where(x==[0,1])
>>>where(x==[0,1])
(array([0, 1, 4, 4]), array([1, 1, 0, 1]))
Which is not the position of the (0,1) particle in the x array. So how do I pick out the position of [0,1] from an array like x? The where() above checks where x is equal to 0 OR 1, not where x is equal to [0,1]. How do I do this "numpylike" without looping?
Ps: How the frack do you copy-paste code into stackoverflow? I mean bad forums have a [code]..[/code] option while here I spend 15 minutes properly indenting code (since tab in chromium on ubuntu simply hops out of the window instead of indenting with 4 whitespaces....) This is VERY annoying.
Edit: Seeing the first answer I tried:
x
array([[0, 2],
[2, 2],
[1, 0],
[2, 2],
[1, 1]])
>>> all(x==[1,1],axis=1)
array([False, False, False, False, True], dtype=bool)
>>> all(x!=[1,1], axis=1)
array([ True, True, False, True, False], dtype=bool)
Which is not what I was hoping for, the != should return the array WITHOUT [1,1]. But alas, it misses one (1,0):
>>>x[all(x!=[1,1], axis=1)]
array([[0, 2],
[2, 2],
[2, 2]])
Edit2: any did the trick, it makes more logical sense than all I suppose, thank you!
Upvotes: 4
Views: 529
Reputation: 25197
>>> import numpy as np
>>> x=np.array([[1, 1],
... [2, 1],
... [2, 2],
... [1, 2],
... [0, 1]])
>>> np.all(x==[0,1], axis=1)
array([False, False, False, False, True], dtype=bool)
>>> np.where(np.all(x==[0,1], axis=1))
(array([4]),)
>>> np.where(np.any(x!=[0,1], axis=1))
(array([0, 1, 2, 3]),)
Upvotes: 5