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86 lines
2.6 KiB
Python
86 lines
2.6 KiB
Python
from scipy import sparse as sp
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from sputils import sdiag
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from utils import sub2ind, ndgrid, mkvc
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import numpy as np
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def interpmat(x,y,z,xr,yr,zr):
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#
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# This function does local linear interpolation
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# computed for each receiver point in turn
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#
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# [Q] = linint(x,y,z,xr,yr,zr)
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# Interpolation matrix
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#
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nx = size(x)
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ny = size(y)
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nz = size(z)
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np = size(xr)
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#Q = spalloc(np,nx*ny*nz,8*np);
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Q = sparse.coo_matrix((0.0,(0,0)),shape=(nx*ny*nz,8*np))
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for i in range(0, np):
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im = amin(abs(xr[i]-x))
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if xr[i] - x[im] >= 0: # Point on the left
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ind_x[0] = im; ind_x[1] = im+1
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else: # Point on the right
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ind_x[0] = im-1; ind_x[1] = im
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dx[0] = xr[i] - x[ind_x[0]]
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dx[1] = x[ind_x[1]] - xr[i]
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im = amin(abs(yr[i] - y))
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if yr[i] - y[im] >= 0: # Point on the left
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ind_y[0] = im; ind_y[1] = im+1
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else: # Point on the right
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ind_y[0] = im-1; ind_y[1] = im
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dy[0] = yr[i] - y[ind_y[0]]
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dy[1] = y[ind_y[1]] - yr[i];
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im = amin(abs(zr[i] - z));
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if zr(i) -z(im) >= 0: # Point on the left
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ind_z[0] = im; ind_z[1] = im+1
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else: # Point on the right
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ind_z[0] = im-1; ind_z[1] = im;
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dz[0] = zr[i] - z[ind_z[0]]; dz[1] = z[ind_z[1]] - zr[i]
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Dx = x[ind_x[1]] - x[ind_x[0]]
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Dy = y[ind_y[1]] - y[ind_y[0]]
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Dz = z[ind_z[1]] - z[ind_z[0]]
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dv = Dx*Dy*Dz
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# Get the row in the matrix
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v = zeros([nx, ny,nz]);
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v[ ind_x[0], ind_y[0], ind_z[0]] = (1-dx[0]/Dx)*(1-dy[0]/Dy)*(1-dz[0]/Dz)
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v[ ind_x[0], ind_y[1], ind_z[0]] = (1-dx[0]/Dx)*(1-dy[1]/Dy)*(1-dz[0]/Dz);
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v[ ind_x[1], ind_y[0], ind_z[0]] = (1-dx[1]/Dx)*(1-dy[0]/Dy)*(1-dz[0]/Dz);
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v[ ind_x[1], ind_y[1], ind_z[0]] = (1-dx[1]/Dx)*(1-dy[1]/Dy)*(1-dz[0]/Dz);
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v[ ind_x[0], ind_y[0], ind_z[1]] = (1-dx[0]/Dx)*(1-dy[0]/Dy)*(1-dz[1]/Dz);
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v[ ind_x[0], ind_y[1], ind_z[1]] = (1-dx[0]/Dx)*(1-dy[1]/Dy)*(1-dz[1]/Dz);
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v[ ind_x[1], ind_y[0], ind_z[1]] = (1-dx[1]/Dx)*(1-dy[0]/Dy)*(1-dz[1]/Dz);
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v[ ind_x[1], ind_y[1], ind_z[1]] = (1-dx[1]/Dx)*(1-dy[1]/Dy)*(1-dz[1]/Dz);
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Q[i,:] = v.flatten('F')
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return Q
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if __name__ == '__main__':
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x = np.array([1, 2, 3, 4])
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y = np.array([1, 2, 3, 4, 5])
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z = np.array([0, 1, 4, 6])
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xr = np.array([2.5,3.2])
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yr = np.array([2.4,3.6])
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zr = np.array([2.5,3.9])
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A = interpmat(x,y,z,xr,yr,zr)
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