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div test done

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f.basile 2020-05-06 14:14:18 +02:00
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import pytest
import numpy as np
from damask import grid_filters
class TestGridFilters:
div_test_data =[(['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'],
['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', 'np.cos(np.pi*2*nodes[...,1]/size[1])', '0.0',
'0.0', '0.0', '0.0'],
['0.0', '-np.sin(np.pi*2*nodes[...,1]/size[1])*np.pi*2/size[1]', '0.0']
),
(['1.0', '0.0', '0.0',
'0.0', '0.0', '0.0',
'0.0', '0.0', '2*np.cos(np.pi*2*nodes[...,2]/size[2])' ],
['0.0', '0.0', '-2.0*np.pi*2/size[2]*np.sin(np.pi*2*nodes[...,2]/size[2])']
),
([ '23.0', '0.0', 'np.sin(np.pi*2*nodes[...,2]/size[2])',
'0.0', '100.0', 'np.sin(np.pi*2*nodes[...,2]/size[2])',
'0.0', '0.0', 'np.sin(np.pi*2*nodes[...,2]/size[2])'],
['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]', 'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]']
),
(['400.0', '0.0', '0.0',
'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])',
'0.0', '10.0', '6.0' ],
['0.0','np.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[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.cos(np.pi*2*nodes[...,0]/size[0])*np.pi*2/size[0]',]
),
(['0.0', 'np.cos(np.pi*2*nodes[...,1]/size[1])', '0.0' ],
['-np.sin(np.pi*2*nodes[...,1]/size[1])*np.pi*2/size[1]']
)
]
@pytest.mark.parametrize('field_def,div_def',div_test_data)
def test_div(self,field_def,div_def):
size = np.random.random(3)+1.0
grid = np.random.randint(8,32,(3))
nodes = grid_filters.cell_coord0(grid,size)
my_locals = locals() # needed for list comprehension
field = np.stack([np.broadcast_to(eval(f,globals(),my_locals),grid) for f in field_def],axis=-1)
field = field.reshape(tuple(grid) + ((3,3) if len(field_def)==9 else (3,)))
div = np.stack([np.broadcast_to(eval(c,globals(),my_locals),grid) for c in div_def], axis=-1)
if len(div_def)==3:
div = div.reshape(tuple(grid) + ((3,)))
else:
div=div.reshape(tuple(grid))
assert np.allclose(div,grid_filters.divergence(size,field))