def test_mp_asgrid_fail(self, setup):
class Test(SuperCellChild):
def __init__(self, sc):
self.set_supercell(sc)
def eigh(self, k, *args, **kwargs):
return np.arange(3)
bz = MonkhorstPack(Test(setup.s1), [2] * 3, displacement=[0.1] * 3).asgrid()
bz.eigh(wrap=lambda eig: eig[0])
def test_mp_asgrid(self, setup, N, centered):
class Test(SuperCellChild):
def __init__(self, sc):
self.set_supercell(sc)
def eigh(self, k, *args, **kwargs):
return np.arange(3)
bz = MonkhorstPack(Test(setup.s1), [2] * 3).asgrid()
# Check the shape
grid = bz.eigh(wrap=lambda eig: eig[0])
assert np.allclose(grid.shape, [2] * 3)
# Check the grids are different
grid2 = bz.eigh(grid_unit='Bohr', wrap=lambda eig: eig[0])
assert not np.allclose(grid.cell, grid2.cell)
assert np.allclose(grid.grid, grid2.grid)
for i in range(3):
grid = bz.eigh(data_axis=i)
shape = [2] * 3
shape[i] = 3
assert np.allclose(grid.shape, shape)
def test_class3(self, setup):
class Test(SuperCellChild):
def __init__(self, sc):
self.set_supercell(sc)
def eigh(self, k, *args, **kwargs):
return np.arange(3)
def eig(self, k, *args, **kwargs):
return np.arange(3) - 1
bz = MonkhorstPack(Test(setup.s1), [2] * 3)
# Try the yield method
bz.asyield()
for val in bz.eigh():
assert np.allclose(val, np.arange(3))
for val in bz.eig():
assert np.allclose(val, np.arange(3) - 1)
# Average
assert np.allclose(bz.asaverage().eigh(), np.arange(3))
