将x，y，z坐标排序到定义的体积Python / numpy中的数组中

Question

Hi I am fairly new and I hope you can answer my question or help me find a better method!

Say I have a set of x,y,z coordinates that I want to subdivide into arrays containing the points within a certain volume (dV) of the total volume of the x,y,z space.

I have been trying to sort each x,y,z coordinate by the x value first, then subdividing by some dx into a new dimension of the array, then within each of these subdivided dimensions, sorting the y values and redividing by dy, and then the same along the z axis, giving the sorted and subdivided coordinates

I have attempted to create an array to append the coordinate sets to...

  def splitter(array1):
    xSortx = np.zeros([10,1,3])
    for j in range(0,10):
        for i in range(len(array1)) :
            if (j * dx) <= array1[i][0] < (j + 1)*dx:
                np.append(xSortx[j],array1[i]) 

everything seemed to be working but the append part, i have heard append in python can be troubling so another method I tried was to create the multidimensional matrix first in order to fill it, but I ran into the problem that I do not know how to create a multidimensional matrix that could have for example 1 entry in the second dimension but 5 in the next index of the second ex: [[[0,0,0]],[[0,0,0],[0,0,0],[0,0,0],[0,0,0],[0,0,0]]].

I would really appreciate any tips or advice, let me know if this is not very clear and I will try to explain it more!

Answer 1

I believe this is what you want:

# define your working volume
Vmin = np.array([1,2,3])
Vmax = np.array([4,5,6])
DV = Vmax-Vmin

# define your subdividing unit
d = 0.5
N = np.ceil(DV / d).astype(int) # number of bins in each dimension

def splitter(array):
    result = [[[[] for i in xrange(N[0])] for j in xrange(N[1])] for k in xrange(N[2])]
    for p in array:
        i,j,k = ((p - Vmin ) / d).astype(int) # find the bin coordinates
        result[i][j][k].append(p)
    return result

# test the function
test = Vmin + np.random.rand(20,3) * DV # create 20 random points in the working volume
result = splitter(test)
for i in xrange(N[0]): 
    for j in xrange(N[1]):
        for k in xrange(N[2]):
            print "points in bin:", Vmin + np.array([i,j,k]) * d
            for p in result[i][j][k]:
                print p