def _csr_to_siesta(geom, csr):
raise SislError('sisl cannot convert the sparse matrix into a Siesta conforming sparsity pattern! Please install with fortran support!')
def read_grid(self, imag=None):
""" Returns `Grid` object from the CUBE file
Parameters
----------
imag : str or Sile or Grid
the imaginary part of the grid. If the geometries does not match
an error will be raised.
"""
if not imag is None:
if not isinstance(imag, Grid):
imag = Grid.read(imag)
geom = self.read_geometry()
if geom is None:
self.fh.seek(0)
sc = self.read_supercell()
else:
sc = geom.sc
# Now seek behind to read grid sizes
self.fh.seek(0)
# Skip headers and origin
self.readline()
self.readline()
na = int(self.readline().split()[0])
ngrid = [0] * 3
for i in [0, 1, 2]:
tmp = self.readline().split()
ngrid[i] = int(tmp[0])
# Read past the atoms
for i in range(na):
self.readline()
if geom is None:
grid = Grid(ngrid, dtype=np.float64, sc=sc)
else:
grid = Grid(ngrid, dtype=np.float64, geometry=geom)
grid.grid.shape = (-1, )
# TODO check performance of this
# We are currently doing this to enable reading
# 1-column data and 6-column data.
lines = [
item for sublist in self.fh.readlines()
for item in sublist.split()
]
grid.grid[:] = np.array(lines).astype(grid.dtype)
grid.grid.shape = ngrid
if imag is None:
return grid
# We are expecting an imaginary part
if not grid.geometry.equal(imag.geometry):
raise SislError(
str(self) + ' and its imaginary part does not have the same '
'geometry. Hence a combined complex Grid cannot be formed.')
if grid != imag:
raise SislError(
str(self) + ' and its imaginary part does not have the same '
'shape. Hence a combined complex Grid cannot be formed.')
# Now we have a complex grid
grid.grid = grid.grid + 1j * imag.grid
return grid