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DAMASK_EICMD
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do not use name of function

This commit is contained in:
Martin Diehl 2020-03-22 16:21:49 +01:00
parent 1e178287fe
commit b6d50db177
1 changed files with 9 additions and 9 deletions
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18
python/damask/grid_filters.py
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@ -41,10 +41,10 @@ def curl(size,field):
e[0, 2, 1] = e[2, 1, 0] = e[1, 0, 2] = -1.0
field_fourier = np.fft.rfftn(field,axes=(0,1,2))
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=field.shape[:3])
return np.fft.irfftn(curl_,axes=(0,1,2),s=field.shape[:3])
def divergence(size,field):
@ -61,10 +61,10 @@ def divergence(size,field):
k_s = _ks(size,field.shape[:3],True)
field_fourier = np.fft.rfftn(field,axes=(0,1,2))
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
div_ = (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(divergence,axes=(0,1,2),s=field.shape[:3])
return np.fft.irfftn(div_,axes=(0,1,2),s=field.shape[:3])
def gradient(size,field):
@ -81,10 +81,10 @@ def gradient(size,field):
k_s = _ks(size,field.shape[:3],True)
field_fourier = np.fft.rfftn(field,axes=(0,1,2))
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
grad_ = (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(gradient,axes=(0,1,2),s=field.shape[:3])
return np.fft.irfftn(grad_,axes=(0,1,2),s=field.shape[:3])
def cell_coord0(grid,size,origin=np.zeros(3)):