From 80b50f460e24ad6ef7a49ac2ac88a5d2946aa74e Mon Sep 17 00:00:00 2001 From: Martin Diehl Date: Thu, 28 Nov 2019 10:09:22 +0100 Subject: [PATCH] cleaning trying to get rid of strange re-ordering related to ASCII table data layout --- python/damask/grid_filters.py | 47 ++++++++++++++--------------------- 1 file changed, 19 insertions(+), 28 deletions(-) diff --git a/python/damask/grid_filters.py b/python/damask/grid_filters.py index 26ee2cfcc..69ee85033 100644 --- a/python/damask/grid_filters.py +++ b/python/damask/grid_filters.py @@ -3,21 +3,18 @@ import numpy as np def curl(size,field): """Calculate curl of a vector or tensor field in Fourier space.""" - shapeFFT = np.array(np.shape(field))[0:3] - grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size + grid = np.array(np.shape(field)[0:3]) n = np.array(np.shape(field)[3:]).prod() # data size - field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=shapeFFT) - curl_fourier = np.empty(field_fourier.shape,'c16') + field_fourier = np.fft.rfftn(field,axes=(0,1,2)) - k_sk = np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2]))/size[0] - if grid[2]%2 == 0: k_sk[grid[2]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) + k_sk = np.where(np.arange(grid[0])>grid[0]//2,np.arange(grid[0])-grid[0],np.arange(grid[0]))/size[0] + if grid[0]%2 == 0: k_sk[grid[0]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) k_sj = np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1]))/size[1] if grid[1]%2 == 0: k_sj[grid[1]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) - k_si = np.arange(grid[0]//2+1)/size[2] + k_si = np.arange(grid[2]//2+1)/size[2] kk, kj, ki = np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij') k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3).astype('c16') @@ -26,29 +23,26 @@ def curl(size,field): e[0, 1, 2] = e[1, 2, 0] = e[2, 0, 1] = +1.0 # Levi-Civita symbol e[0, 2, 1] = e[2, 1, 0] = e[1, 0, 2] = -1.0 - curl = (np.einsum('slm,ijkl,ijkm, ->ijks', e,k_s,field_fourier)*2.0j*np.pi if n == 3 else # vector, 3 -> 3 - np.einsum('slm,ijkl,ijknm,->ijksn',e,k_s,field_fourier)*2.0j*np.pi) # tensor, 3x3 -> 3x3 + curl = (np.einsum('slm,ijkl,ijkm ->ijks', e,k_s,field_fourier)*2.0j*np.pi if n == 3 else # vector, 3 -> 3 + np.einsum('slm,ijkl,ijknm->ijksn',e,k_s,field_fourier)*2.0j*np.pi) # tensor, 3x3 -> 3x3 - return np.fft.irfftn(curl,axes=(0,1,2),s=shapeFFT).reshape([N,n]) + return np.fft.irfftn(curl,axes=(0,1,2)) def divergence(size,field): """Calculate divergence of a vector or tensor field in Fourier space.""" - shapeFFT = np.array(np.shape(field))[0:3] - grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size + grid = np.array(np.shape(field)[0:3]) n = np.array(np.shape(field)[3:]).prod() # data size - field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=shapeFFT) - div_fourier = np.empty(field_fourier.shape[0:len(np.shape(field))-1],'c16') + field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=grid) - k_sk = np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2]))/size[0] - if grid[2]%2 == 0: k_sk[grid[2]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) + k_sk = np.where(np.arange(grid[0])>grid[0]//2,np.arange(grid[0])-grid[0],np.arange(grid[0]))/size[0] + if grid[0]%2 == 0: k_sk[grid[0]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) k_sj = np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1]))/size[1] if grid[1]%2 == 0: k_sj[grid[1]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) - k_si = np.arange(grid[0]//2+1)/size[2] + k_si = np.arange(grid[2]//2+1)/size[2] kk, kj, ki = np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij') k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3).astype('c16') @@ -56,26 +50,23 @@ def divergence(size,field): divergence = (np.einsum('ijkl,ijkl ->ijk', k_s,field_fourier)*2.0j*np.pi if n == 3 else # vector, 3 -> 1 np.einsum('ijkm,ijklm->ijkl',k_s,field_fourier)*2.0j*np.pi) # tensor, 3x3 -> 3 - return np.fft.irfftn(div_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,n//3]) + return np.fft.irfftn(div_fourier,axes=(0,1,2),s=grid) def gradient(size,field): """Calculate gradient of a vector or scalar field in Fourier space.""" - shapeFFT = np.array(np.shape(field))[0:3] grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size n = np.array(np.shape(field)[3:]).prod() # data size - field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=shapeFFT) - grad_fourier = np.empty(field_fourier.shape+(3,),'c16') + field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=grid) - k_sk = np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2]))/size[0] - if grid[2]%2 == 0: k_sk[grid[2]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) + k_sk = np.where(np.arange(grid[0])>grid[0]//2,np.arange(grid[0])-grid[0],np.arange(grid[0]))/size[0] + if grid[0]%2 == 0: k_sk[grid[0]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) k_sj = np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1]))/size[1] if grid[1]%2 == 0: k_sj[grid[1]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) - k_si = np.arange(grid[0]//2+1)/size[2] + k_si = np.arange(grid[2]//2+1)/size[2] kk, kj, ki = np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij') k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3).astype('c16') @@ -83,7 +74,7 @@ def gradient(size,field): gradient = (np.einsum('ijkl,ijkm->ijkm', field_fourier,k_s)*2.0j*np.pi if n == 1 else # scalar, 1 -> 3 np.einsum('ijkl,ijkm->ijklm',field_fourier,k_s)*2.0j*np.pi) # vector, 3 -> 3x3 - return np.fft.irfftn(grad_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,3*n]) + return np.fft.irfftn(grad_fourier,axes=(0,1,2),s=grid) #--------------------------------------------------------------------------------------------------