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DAMASK_EICMD
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f.basile 2020-05-06 14:26:54 +02:00
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commit d977f2ad25
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python/tests/test_curl.py
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import pytest
import numpy as np
from damask import grid_filters
class TestGridFilters:
curl_test_data =[(['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',
'np.cos(np.pi*2*nodes[...,2]/size[2])*np.pi*2/size[2]', '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.cos(np.pi*2*nodes[...,0]/size[0])', '0.0', '0.0'],
['0.0', '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', '0.0']
),
(['np.sin(np.pi*2*nodes[...,0]/size[0])','np.cos(np.pi*2*nodes[...,1]/size[1])','np.sin(np.pi*2*nodes[...,2]/size[2])',
'np.sin(np.pi*2*nodes[...,0]/size[0])','np.cos(np.pi*2*nodes[...,1]/size[1])','np.sin(np.pi*2*nodes[...,2]/size[2])',
'np.sin(np.pi*2*nodes[...,0]/size[0])','np.cos(np.pi*2*nodes[...,1]/size[1])','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']
),
(['5.0', '0.0', '0.0',
'0.0', '0.0', '0.0',
'0.0', '0.0', '2*np.cos(np.pi*2*nodes[...,1]/size[1])'],
['0.0', '0.0', '-2*np.pi*2/size[1]*np.sin(np.pi*2*nodes[...,1]/size[1])',
'0.0', '0.0', '0.0',
'0.0', '0.0', '0.0']
),
(['4*np.sin(np.pi*2*nodes[...,2]/size[2])', '8*np.sin(np.pi*2*nodes[...,0]/size[0])', '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])', \
'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])']
),
(['0.0', 'np.cos(np.pi*2*nodes[...,0]/size[0])+5*np.cos(np.pi*2*nodes[...,2]/size[2])', '0.0'],
['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)
def test_curl(self,field_def,curl_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,)))
curl = np.stack([np.broadcast_to(eval(c,globals(),my_locals),grid) for c in curl_def], axis=-1)
curl = curl.reshape(tuple(grid) + ((3,3) if len(curl_def)==9 else (3,)))
assert np.allclose(curl,grid_filters.curl(size,field))