def get_linesample(lons, lats, source_area_def, nprocs=1):
"""Return index row and col arrays for resampling.
Parameters
----------
lons : numpy array
Lons. Dimensions must match lats
lats : numpy array
Lats. Dimensions must match lons
source_area_def : object
Source definition as AreaDefinition object
nprocs : int, optional
Number of processor cores to be used
Returns
-------
(row_indices, col_indices) : tuple of numpy arrays
Arrays for resampling area by array indexing
"""
# Proj.4 definition of source area projection
proj_kwargs = {}
if nprocs > 1:
source_proj = _spatial_mp.Proj_MP(**source_area_def.proj_dict)
proj_kwargs["nprocs"] = nprocs
else:
source_proj = Proj(**source_area_def.proj_dict)
# get cartesian projection values from longitude and latitude
source_x, source_y = source_proj(lons, lats, **proj_kwargs)
# Find corresponding pixels (element by element conversion of ndarrays)
source_pixel_x = (source_area_def.pixel_offset_x +
source_x / source_area_def.pixel_size_x).astype(np.int32)
source_pixel_y = (source_area_def.pixel_offset_y -
source_y / source_area_def.pixel_size_y).astype(np.int32)
return source_pixel_y, source_pixel_x
def get_lonlats(self, nprocs=None, data_slice=None, cache=False, dtype=None):
"""Returns lon and lat arrays of area.
Parameters
----------
nprocs : int, optional
Number of processor cores to be used.
Defaults to the nprocs set when instantiating object
data_slice : slice object, optional
Calculate only coordinates for specified slice
cache : bool, optional
Store result the result. Requires data_slice to be None
Returns
-------
(lons, lats) : tuple of numpy arrays
Grids of area lons and and lats
"""
if dtype is None:
dtype = self.dtype
if self.lons is None or self.lats is None:
#Data is not cached
if nprocs is None:
nprocs = self.nprocs
# Proj.4 definition of target area projection
if nprocs > 1:
target_proj = _spatial_mp.Proj_MP(**self.proj_dict)
else:
target_proj = _spatial_mp.Proj(**self.proj_dict)
# Get coordinates of local area as ndarrays
target_x, target_y = self.get_proj_coords(
data_slice=data_slice, dtype=dtype)
# Get corresponding longitude and latitude values
lons, lats = target_proj(target_x, target_y, inverse=True,
nprocs=nprocs)
lons = np.asanyarray(lons, dtype=dtype)
lats = np.asanyarray(lats, dtype=dtype)
if cache and data_slice is None:
# Cache the result if requested
self.lons = lons
self.lats = lats
# Free memory
del(target_x)
del(target_y)
else:
#Data is cached
if data_slice is None:
# Full slice
lons = self.lons
lats = self.lats
else:
lons = self.lons[data_slice]
lats = self.lats[data_slice]
return lons, lats
