tuples not needed/avoid eval
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@ -24,7 +24,7 @@ class TestGridFilters:
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n = grid_filters.node_coord0(grid,size) + size/grid*.5
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assert np.allclose(c,n)
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@pytest.mark.parametrize('mode',[('cell'),('node')])
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@pytest.mark.parametrize('mode',['cell','node'])
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def test_grid_DNA(self,mode):
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"""Ensure that xx_coord0_gridSizeOrigin is the inverse of xx_coord0."""
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grid = np.random.randint(8,32,(3))
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@ -49,7 +49,7 @@ class TestGridFilters:
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assert np.allclose(grid_filters.node_coord(size,F) [1:-1,1:-1,1:-1],grid_filters.cell_2_node(
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grid_filters.cell_coord(size,F))[1:-1,1:-1,1:-1])
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@pytest.mark.parametrize('mode',[('cell'),('node')])
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@pytest.mark.parametrize('mode',['cell','node'])
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def test_coord0_origin(self,mode):
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origin= np.random.random(3)
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size = np.random.random(3) # noqa
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@ -61,22 +61,24 @@ class TestGridFilters:
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elif mode == 'node':
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assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(grid[::-1]+1)+(3,)))
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@pytest.mark.parametrize('mode',[('cell'),('node')])
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def test_displacement_avg_vanishes(self,mode):
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@pytest.mark.parametrize('function',[grid_filters.cell_displacement_avg,
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grid_filters.node_displacement_avg])
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def test_displacement_avg_vanishes(self,function):
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"""Ensure that random fluctuations in F do not result in average displacement."""
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size = np.random.random(3) # noqa
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size = np.random.random(3)
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grid = np.random.randint(8,32,(3))
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F = np.random.random(tuple(grid)+(3,3))
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F += np.eye(3) - np.average(F,axis=(0,1,2))
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assert np.allclose(eval('grid_filters.{}_displacement_avg(size,F)'.format(mode)),0.0)
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assert np.allclose(function(size,F),0.0)
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@pytest.mark.parametrize('mode',[('cell'),('node')])
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def test_displacement_fluct_vanishes(self,mode):
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@pytest.mark.parametrize('function',[grid_filters.cell_displacement_fluct,
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grid_filters.node_displacement_fluct])
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def test_displacement_fluct_vanishes(self,function):
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"""Ensure that constant F does not result in fluctuating displacement."""
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size = np.random.random(3) # noqa
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size = np.random.random(3)
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grid = np.random.randint(8,32,(3))
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F = np.broadcast_to(np.random.random((3,3)), tuple(grid)+(3,3)) # noqa
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assert np.allclose(eval('grid_filters.{}_displacement_fluct(size,F)'.format(mode)),0.0)
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F = np.broadcast_to(np.random.random((3,3)), tuple(grid)+(3,3))
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assert np.allclose(function(size,F),0.0)
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def test_regrid(self):
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size = np.random.random(3)
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