所有正负坐标值的Python组合

Question

I have a code that calculates the distance formula for 3D coordinates from this input file

  input_file="mock_data.csv"
  cmd=pd.read_csv(input_file)
  subset = cmd[['carbon','x_coord', 'y_coord','z_coord']]
  coordinate_values = [tuple(x) for x in subset.values]

  atoms = coordinate_values
  atomPairs = itertools.combinations(atoms, 2)
  for pair in atomPairs:
    x1 = pair[0][1]
    y1 = pair[0][2]
    z1 = pair[0][3]
    x2 = pair[1][1]
    y2 = pair[1][2]
    z2 = pair[1][3]

    """Define the values for the distance between the atoms"""
    def calculate_distance(x1,y1,x2,y2,z1,z2):
       dist=math.sqrt((x2 - x1)**2 + (y2 - y1)**2 + (z2-z1)**2)
       return dist
    d=calculate_distance(x1,y1,x2,y2,z1,z2)

I currently have the code worked out to calculate the distance between each 'carbon'. My problem is that my coordinates are all absolute values - each coordinate could be positive or negative. I want to calculate the distances between each carbon for all possible coordinates, ie all positive and negative combinations of each 3D coordinates.

Quick example: 'carbon' 1 has coordinates (1.08, 0.49, 0.523) but this could also be (-1.08, -0.49, -0.523), (-1.08, 0.49, 0.523), (-1.08, -0.49, 0.523), (-1.08, 0.49, -0.523), (1.08, -0.49, 0.523), (1.08, -0.49, -0.523), (1.08, 0.49, -0.523), making for a total of eight possibilities for each coordinate system.

I need a code to go through all of these possible coordinate values to calculate the distances I have already coded for.

Answer 1

Here is a fairly simple example.

import numpy as np
from itertools import product
from scipy.spatial.distance import cdist

base = np.array([-1,1]) #accounts for signed coord

x = 1*base              #change coord values
y = 2*base
z = 3*base

coords = list(product(x,y,z))    #cartesian product

distances = cdist(coords,coords) #better implementation of distance