def test_shortest_vector(self):
raise SkipTest
# simple cases
uc = UnitCell(numpy.identity(3,float)*3)
self.assertArraysAlmostEqual(uc.shortest_vector([3, 0, 1]), numpy.array([0, 0, 1]))
self.assertArraysAlmostEqual(uc.shortest_vector([-3, 0, 1]), numpy.array([0, 0, 1]))
self.assertArraysAlmostEqual(uc.shortest_vector([-2, 0, 1]), numpy.array([1, 0, 1]))
self.assertArraysAlmostEqual(uc.shortest_vector([-1.6, 1, 1]), numpy.array([1.4, 1, 1]))
self.assertArraysAlmostEqual(uc.shortest_vector([-1.4, 1, 1]), numpy.array([-1.4, 1, 1]))
# simple cases
uc = UnitCell(numpy.identity(3,float)*3, numpy.array([True, False, False]))
self.assertArraysAlmostEqual(uc.shortest_vector([3, 0, 1]), numpy.array([0, 0, 1]))
self.assertArraysAlmostEqual(uc.shortest_vector([3, 0, 3]), numpy.array([0, 0, 3]))
# random tests
for uc_counter in xrange(1000):
uc = self.get_random_uc(full=False)
for r_counter in xrange(10):
r0 = numpy.random.normal(0, 10, 3)
r1 = uc.shortest_vector(r0)
change = r1 - r0
self.assert_(numpy.dot(change, r0) <= 0)
#self.assert_(numpy.linalg.norm(r0) >= numpy.linalg.norm(r1))
index = uc.to_fractional(r0-r1)
self.assertArraysAlmostEqual(index, numpy.round(index), doabs=True)
index = uc.to_fractional(r1)
self.assert_(index.max()<0.5)
self.assert_(index.max()>=-0.5)
r0 = numpy.random.normal(0, 10, (10,3))
r1 = uc.shortest_vector(r0)
for i in xrange(10):
r1_row_bis = uc.shortest_vector(r0[i])
self.assertArraysAlmostEqual(r1_row_bis, r1[i], doabs=True)
def main(file_name):
xyz_file = XYZFile(file_name)
frames = xyz_file.geometries
# titles = xyz_file.titles
# Unit cell, decide how to make this general
matrix = np.array([[
1.4731497044857509E+01, 3.2189795740722255E-02, 4.5577626559295564E-02
], [
4.2775481701113616E-02, 2.1087874593411915E+01, -2.8531114198383896E-02
], [
6.4054385616337750E-02, 1.3315840416191497E-02, 1.4683043045316882E+01
]])
matrix *= angstrom
cell = UnitCell(matrix)
frac = UnitCell.to_fractional(cell, frames)
xmin = np.min(frac[:, :, 0])
ymin = np.min(frac[:, :, 1])
zmin = np.min(frac[:, :, 2])
frac[:, :, 0] -= -0.5 # xmin
frac[:, :, 1] -= -0.5 # ymin
frac[:, :, 2] -= -0.5 # zmin
decimals = np.modf(frac)[0]
# decimals[:,:,0] += xmin
# decimals[:,:,1] += ymin
# decimals[:,:,2] += zmin
frac_wrapped = np.where(decimals < 0, 1 + decimals, decimals)
# frac_wrapped[:,:,0] += xmin
# frac_wrapped[:,:,1] += ymin
# frac_wrapped[:,:,2] += zmin
cart_wrapped = UnitCell.to_cartesian(cell, frac_wrapped)
xyz_file.geometries = cart_wrapped
xyz_file.write_to_file(file_name.rsplit(".", 1)[0] + "_wrapped.xyz")
def _setup_grid(self, cutoff, unit_cell, grid):
"""Choose a proper grid for the binning process"""
if grid is None:
# automatically choose a decent grid
if unit_cell is None:
grid = cutoff / 2.9
else:
# The following would be faster, but it is not reliable
# enough yet.
#grid = unit_cell.get_optimal_subcell(cutoff/2.0)
divisions = np.ceil(unit_cell.spacings / cutoff)
divisions[divisions < 1] = 1
grid = unit_cell / divisions
if isinstance(grid, float):
grid_cell = UnitCell(
np.array([[grid, 0, 0], [0, grid, 0], [0, 0, grid]]))
elif isinstance(grid, UnitCell):
grid_cell = grid
else:
raise TypeError(
"Grid must be None, a float or a UnitCell instance.")
if unit_cell is not None:
# The columns of integer_matrix are the unit cell vectors in
# fractional coordinates of the grid cell.
integer_matrix = grid_cell.to_fractional(
unit_cell.matrix.transpose()).transpose()
if abs((integer_matrix - np.round(integer_matrix)) *
self.unit_cell.active).max() > 1e-6:
raise ValueError(
"The unit cell vectors are not an integer linear combination of grid cell vectors."
)
integer_matrix = integer_matrix.round()
integer_cell = UnitCell(integer_matrix, unit_cell.active)
else:
integer_cell = None
return grid_cell, integer_cell
def _setup_grid(self, cutoff, unit_cell, grid):
"""Choose a proper grid for the binning process"""
if grid is None:
# automatically choose a decent grid
if unit_cell is None:
grid = cutoff/2.9
else:
# The following would be faster, but it is not reliable
# enough yet.
#grid = unit_cell.get_optimal_subcell(cutoff/2.0)
divisions = numpy.ceil(unit_cell.spacings/cutoff)
divisions[divisions<1] = 1
grid = unit_cell/divisions
if isinstance(grid, float):
grid_cell = UnitCell(numpy.array([
[grid, 0, 0],
[0, grid, 0],
[0, 0, grid]
]))
elif isinstance(grid, UnitCell):
grid_cell = grid
else:
raise TypeError("Grid must be None, a float or a UnitCell instance.")
if unit_cell is not None:
# The columns of integer_matrix are the unit cell vectors in
# fractional coordinates of the grid cell.
integer_matrix = grid_cell.to_fractional(unit_cell.matrix.transpose()).transpose()
if abs((integer_matrix - numpy.round(integer_matrix))*self.unit_cell.active).max() > 1e-6:
raise ValueError("The unit cell vectors are not an integer linear combination of grid cell vectors.")
integer_matrix = integer_matrix.round()
integer_cell = UnitCell(integer_matrix, unit_cell.active)
else:
integer_cell = None
return grid_cell, integer_cell
