mirror of https://github.com/pyodide/pyodide.git
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
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#setup: import numpy as np ; N = 20 ; x = y = z = np.arange(0., N, 0.1) ; L = 4 ; periodic = True
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#run: periodic_dist(x, x, x, L,periodic, periodic, periodic)
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#pythran export periodic_dist(float [], float[], float[], int, bool, bool, bool)
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import numpy as np
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def periodic_dist(x, y, z, L, periodicX, periodicY, periodicZ):
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" ""Computes distances between all particles and places the result in a matrix such that the ij th matrix entry corresponds to the distance between particle i and j"" "
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N = len(x)
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xtemp = np.tile(x,(N,1))
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dx = xtemp - xtemp.T
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ytemp = np.tile(y,(N,1))
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dy = ytemp - ytemp.T
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ztemp = np.tile(z,(N,1))
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dz = ztemp - ztemp.T
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# Particles 'feel' each other across the periodic boundaries
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if periodicX:
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dx[dx>L/2]=dx[dx > L/2]-L
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dx[dx<-L/2]=dx[dx < -L/2]+L
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if periodicY:
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dy[dy>L/2]=dy[dy>L/2]-L
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dy[dy<-L/2]=dy[dy<-L/2]+L
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if periodicZ:
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dz[dz>L/2]=dz[dz>L/2]-L
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dz[dz<-L/2]=dz[dz<-L/2]+L
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# Total Distances
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d = np.sqrt(dx**2+dy**2+dz**2)
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# Mark zero entries with negative 1 to avoid divergences
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d[d==0] = -1
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return d, dx, dy, dz
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