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DAMASK_EICMD
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less whitespace, 

alingment only within one vector/tensor
This commit is contained in:
Martin Diehl 2020-05-10 13:02:26 +02:00
parent c8701a4665
commit 6928a8290f
1 changed files with 74 additions and 80 deletions
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54
python/tests/test_grid_filters.py
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@ -141,7 +141,7 @@ class TestGridFilters:
grad_test_data = [ grad_test_data = [
(['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0'], (['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0'],
['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]','0.0', '0.0', ['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]', '0.0', '0.0',
'0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
'0.0', '0.0', '0.0']), '0.0', '0.0', '0.0']),
@ -158,22 +158,23 @@ class TestGridFilters:
(['np.cos(np.pi*2*nodes[...,2]/size[2])', '3.0', 'np.sin(np.pi*2*nodes[...,2]/size[2])'], (['np.cos(np.pi*2*nodes[...,2]/size[2])', '3.0', 'np.sin(np.pi*2*nodes[...,2]/size[2])'],
['0.0', '0.0', '-np.sin(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]', ['0.0', '0.0', '-np.sin(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]',
'0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
'0.0', '0.0', 'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']), '0.0', '0.0', ' np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']),
(['np.sin(np.pi*2*nodes[...,0]/size[0])','np.sin(np.pi*2*nodes[...,1]/size[1])',\ (['np.sin(np.pi*2*nodes[...,0]/size[0])',
'np.sin(np.pi*2*nodes[...,1]/size[1])',
'np.sin(np.pi*2*nodes[...,2]/size[2])'], 'np.sin(np.pi*2*nodes[...,2]/size[2])'],
['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]', '0.0', '0.0', ['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]', '0.0', '0.0',
'0.0', 'np.cos(np.pi*2*nodes[...,1]/size[1])*np.pi*2/size[1]', '0.0', '0.0', 'np.cos(np.pi*2*nodes[...,1]/size[1])*np.pi*2/size[1]', '0.0',
'0.0', '0.0', 'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']), '0.0', '0.0', 'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']),
(['np.sin(np.pi*2*nodes[...,0]/size[0])' ], (['np.sin(np.pi*2*nodes[...,0]/size[0])'],
['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]', '0.0', '0.0' ]), ['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]', '0.0', '0.0']),
(['8.0' ], (['8.0'],
['0.0', '0.0', '0.0' ])] ['0.0', '0.0', '0.0' ])
]
@pytest.mark.parametrize('field_def,grad_def',grad_test_data) @pytest.mark.parametrize('field_def,grad_def',grad_test_data)
def test_grad(self,field_def,grad_def): def test_grad(self,field_def,grad_def):
size = np.random.random(3)+1.0 size = np.random.random(3)+1.0
grid = np.random.randint(8,32,(3)) grid = np.random.randint(8,32,(3))
@ -189,10 +190,7 @@ class TestGridFilters:
assert np.allclose(grad,grid_filters.gradient(size,field)) assert np.allclose(grad,grid_filters.gradient(size,field))
curl_test_data = [
curl_test_data =[
(['np.sin(np.pi*2*nodes[...,2]/size[2])', '0.0', '0.0', (['np.sin(np.pi*2*nodes[...,2]/size[2])', '0.0', '0.0',
'0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
'0.0', '0.0', '0.0'], '0.0', '0.0', '0.0'],
@ -221,20 +219,22 @@ class TestGridFilters:
'0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
'0.0', '0.0', '0.0']), '0.0', '0.0', '0.0']),
(['4*np.sin(np.pi*2*nodes[...,2]/size[2])', \ ([ '4*np.sin(np.pi*2*nodes[...,2]/size[2])',
'8*np.sin(np.pi*2*nodes[...,0]/size[0])', \ '8*np.sin(np.pi*2*nodes[...,0]/size[0])',
'16*np.sin(np.pi*2*nodes[...,1]/size[1])'], '16*np.sin(np.pi*2*nodes[...,1]/size[1])'],
['16*np.pi*2/size[1]*np.cos(np.pi*2*nodes[...,1]/size[1])', \ ['16*np.pi*2/size[1]*np.cos(np.pi*2*nodes[...,1]/size[1])',
'4*np.pi*2/size[2]*np.cos(np.pi*2*nodes[...,2]/size[2])', \ '4*np.pi*2/size[2]*np.cos(np.pi*2*nodes[...,2]/size[2])',
'8*np.pi*2/size[0]*np.cos(np.pi*2*nodes[...,0]/size[0])']), '8*np.pi*2/size[0]*np.cos(np.pi*2*nodes[...,0]/size[0])']),
(['0.0', 'np.cos(np.pi*2*nodes[...,0]/size[0])+5*np.cos(np.pi*2*nodes[...,2]/size[2])', '0.0'], (['0.0',
['5*np.sin(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]',\ 'np.cos(np.pi*2*nodes[...,0]/size[0])+5*np.cos(np.pi*2*nodes[...,2]/size[2])',
'0.0',\ '0.0'],
'-np.sin(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]'])] ['5*np.sin(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]',
'0.0',
'-np.sin(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]'])
]
@pytest.mark.parametrize('field_def,curl_def',curl_test_data) @pytest.mark.parametrize('field_def,curl_def',curl_test_data)
def test_curl(self,field_def,curl_def): def test_curl(self,field_def,curl_def):
size = np.random.random(3)+1.0 size = np.random.random(3)+1.0
grid = np.random.randint(8,32,(3)) grid = np.random.randint(8,32,(3))
@ -254,7 +254,7 @@ class TestGridFilters:
(['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0', (['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0',
'0.0' , '0.0', '0.0', '0.0' , '0.0', '0.0',
'0.0' , '0.0', '0.0'], '0.0' , '0.0', '0.0'],
['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]' ,'0.0', '0.0']), ['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]','0.0', '0.0']),
(['0.0', '0.0', '0.0', (['0.0', '0.0', '0.0',
'0.0', 'np.cos(np.pi*2*nodes[...,1]/size[1])', '0.0', '0.0', 'np.cos(np.pi*2*nodes[...,1]/size[1])', '0.0',
@ -275,13 +275,9 @@ class TestGridFilters:
'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']), 'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']),
(['400.0', '0.0', '0.0', (['400.0', '0.0', '0.0',
'np.sin(np.pi*2*nodes[...,0]/size[0])', \ 'np.sin(np.pi*2*nodes[...,0]/size[0])', 'np.sin(np.pi*2*nodes[...,1]/size[1])', 'np.sin(np.pi*2*nodes[...,2]/size[2])',
'np.sin(np.pi*2*nodes[...,1]/size[1])', \
'np.sin(np.pi*2*nodes[...,2]/size[2])',
'0.0', '10.0', '6.0'], '0.0', '10.0', '6.0'],
['0.0','np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]'\ ['0.0','np.sum(np.cos(np.pi*2*nodes/size)*np.pi*2/size,axis=-1)', '0.0' ]),
'+np.cos(np.pi*2*nodes[...,1]/size[1])*np.pi*2/size[1]'\
'+np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]', '0.0' ]),
(['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0'], (['np.sin(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0'],
['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]',]), ['np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]',]),
@ -308,5 +304,3 @@ class TestGridFilters:
div=div.reshape(tuple(grid)) div=div.reshape(tuple(grid))
assert np.allclose(div,grid_filters.divergence(size,field)) assert np.allclose(div,grid_filters.divergence(size,field))