def calc_quick_params(in_area, out_area):
"""Calculate projection parameters for quick interpolation mode"""
ridx, cidx = utils.generate_quick_linesample_arrays(in_area, out_area)
cache = {}
cache['row_idx'] = ridx
cache['col_idx'] = cidx
return cache
def calc_quick_params(in_area, out_area):
"""Calculate projection parameters for quick interpolation mode"""
ridx, cidx = utils.generate_quick_linesample_arrays(in_area,
out_area)
cache = {}
cache['row_idx'] = ridx
cache['col_idx'] = cidx
return cache
def test_generate_linesample(self):
data = np.fromfunction(lambda y, x: y*x*10**-6, (3712, 3712))
row_indices, col_indices = utils.generate_quick_linesample_arrays(self.msg_area,
self.area_def)
res = data[row_indices, col_indices]
cross_sum = res.sum()
expected = 399936.39392500359
self.assertAlmostEqual(cross_sum, expected, msg='Generate linesample failed')
self.failIf(row_indices.dtype != np.uint16 or col_indices.dtype != np.uint16,
'Generate linesample failed. Downcast to uint16 expected')
def test_generate_linesample(self):
data = np.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712))
row_indices, col_indices = utils.generate_quick_linesample_arrays(self.msg_area,
self.area_def)
res = data[row_indices, col_indices]
cross_sum = res.sum()
expected = 399936.39392500359
self.assertAlmostEqual(
cross_sum, expected, msg='Generate linesample failed')
self.assertFalse(row_indices.dtype != np.uint16 or col_indices.dtype != np.uint16,
'Generate linesample failed. Downcast to uint16 expected')
def pyresample_method(self, ref_grid_lim, grid_lim, data):
"""
Method which uses the library "pyresample" which is must faster
"""
# FIXME: Understand how Proj_Dict influences the result
X_MAX, Y_MAX = ref_grid_lim
x_max, y_max = grid_lim
N, M = data.shape
proj_dict = {
'a': '6371228.0',
'units': 'm',
'lon_0': '0',
'proj': 'laea',
'lat_0': '-90'
}
ref_area = geometry.AreaDefinition(
area_id='REF',
name='reference',
proj_id='A',
proj_dict=proj_dict,
x_size=N,
y_size=M,
area_extent=[-X_MAX, -Y_MAX, X_MAX, Y_MAX])
init_area = geometry.AreaDefinition(
area_id='INIT',
name='initial',
proj_id='A',
proj_dict=proj_dict,
x_size=N,
y_size=M,
area_extent=[-x_max, -y_max, x_max, y_max])
base = image.ImageContainer(data, init_area)
row_indices, col_indices = utils.generate_quick_linesample_arrays(
init_area, ref_area)
result = base.get_array_from_linesample(row_indices, col_indices)
return result
def __init__(self, in_area, out_area,
in_latlons=None, mode=None,
radius=10000, nprocs=1):
if (mode is not None and
mode not in ["quick", "nearest", "ewa", "bilinear"]):
raise ValueError("Projector mode must be one of 'nearest', "
"'quick', 'ewa', 'bilinear'")
self.area_file = get_area_file()
self.in_area = None
self.out_area = None
self._cache = None
self._filename = None
self.mode = "quick"
self.radius = radius
self.conf = ConfigParser.ConfigParser()
self.conf.read(os.path.join(CONFIG_PATH, "mpop.cfg"))
# TODO:
# - Rework so that in_area and out_area can be lonlats.
# - Add a recompute flag ?
# Setting up the input area
try:
self.in_area = get_area_def(in_area)
in_id = in_area
except (utils.AreaNotFound, AttributeError):
try:
in_id = in_area.area_id
self.in_area = in_area
except AttributeError:
try:
# TODO: Note that latlons are in order (lons, lats)
self.in_area = geometry.SwathDefinition(lons=in_latlons[0],
lats=in_latlons[1])
in_id = in_area
except TypeError:
raise utils.AreaNotFound("Input area " +
str(in_area) +
" must be defined in " +
self.area_file +
", be an area object"
" or longitudes/latitudes must be "
"provided.")
# Setting up the output area
try:
self.out_area = get_area_def(out_area)
out_id = out_area
except (utils.AreaNotFound, AttributeError):
try:
out_id = out_area.area_id
self.out_area = out_area
except AttributeError:
raise utils.AreaNotFound("Output area " +
str(out_area) +
" must be defined in " +
self.area_file + " or "
"be an area object.")
# if self.in_area == self.out_area:
# return
# choosing the right mode if necessary
if mode is None:
try:
dicts = in_area.proj_dict, out_area.proj_dict
del dicts
self.mode = "quick"
except AttributeError:
self.mode = "nearest"
else:
self.mode = mode
filename = (in_id + "2" + out_id + "_" +
str(_get_area_hash(self.in_area)) + "to" +
str(_get_area_hash(self.out_area)) + "_" +
self.mode + ".npz")
projections_directory = "/var/tmp"
try:
projections_directory = self.conf.get("projector",
"projections_directory")
except ConfigParser.NoSectionError:
pass
self._filename = os.path.join(projections_directory, filename)
try:
self._cache = {}
self._file_cache = np.load(self._filename)
except:
logger.info("Computing projection from %s to %s...",
in_id, out_id)
if self.mode == "nearest":
valid_index, valid_output_index, index_array, distance_array = \
kd_tree.get_neighbour_info(self.in_area,
self.out_area,
self.radius,
neighbours=1,
nprocs=nprocs)
del distance_array
self._cache = {}
self._cache['valid_index'] = valid_index
self._cache['valid_output_index'] = valid_output_index
self._cache['index_array'] = index_array
elif self.mode == "quick":
ridx, cidx = \
utils.generate_quick_linesample_arrays(self.in_area,
self.out_area)
self._cache = {}
self._cache['row_idx'] = ridx
self._cache['col_idx'] = cidx
elif self.mode == "ewa":
from pyresample.ewa import ll2cr
swath_points_in_grid, cols, rows = ll2cr(self.in_area,
self.out_area)
self._cache = {}
# self._cache['ewa_swath_points_in_grid'] = \
# swath_points_in_grid
self._cache['ewa_cols'] = cols
self._cache['ewa_rows'] = rows
elif self.mode == "bilinear":
bilinear_t, bilinear_s, input_idxs, idx_arr = \
get_bil_info(self.in_area, self.out_area,
self.radius, neighbours=32,
nprocs=nprocs, masked=False)
self._cache = {}
self._cache['bilinear_s'] = bilinear_s
self._cache['bilinear_t'] = bilinear_t
self._cache['input_idxs'] = input_idxs
self._cache['idx_arr'] = idx_arr
def __init__(self, in_area, out_area,
in_latlons=None, mode=None,
radius=10000):
# TODO:
# - Rework so that in_area and out_area can be lonlats.
# - Add a recompute flag ?
# Setting up the input area
try:
self.in_area = get_area_def(in_area)
in_id = in_area
except (utils.AreaNotFound, AttributeError):
if isinstance(in_area, geometry.AreaDefinition):
self.in_area = in_area
in_id = in_area.area_id
elif isinstance(in_area, geometry.SwathDefinition):
self.in_area = in_area
in_id = in_area.area_id
elif in_latlons is not None:
self.in_area = geometry.SwathDefinition(lons=in_latlons[0],
lats=in_latlons[1])
in_id = in_area
else:
raise utils.AreaNotFound("Input area " +
str(in_area) +
" must be defined in " +
AREA_FILE + ", be an area object"
" or longitudes/latitudes must be "
"provided.")
# Setting up the output area
try:
self.out_area = get_area_def(out_area)
out_id = out_area
except (utils.AreaNotFound, AttributeError):
if isinstance(out_area, (geometry.AreaDefinition,
geometry.SwathDefinition)):
self.out_area = out_area
out_id = out_area.area_id
else:
raise utils.AreaNotFound("Output area " +
str(out_area) +
" must be defined in " +
AREA_FILE + " or "
"be an area object.")
if self.in_area == self.out_area:
return
# choosing the right mode if necessary
if(mode is None):
if (isinstance(in_area, geometry.AreaDefinition) and
isinstance(out_area, geometry.AreaDefinition)):
self.mode = "quick"
else:
self.mode = "nearest"
else:
self.mode = mode
filename = (in_id + "2" + out_id + "_" + self.mode + ".npz")
projections_directory = "/var/tmp"
try:
projections_directory = CONF.get("projector",
"projections_directory")
except ConfigParser.NoSectionError:
pass
self._filename = os.path.join(projections_directory, filename)
if(not os.path.exists(self._filename)):
LOG.info("Computing projection from %s to %s..."
%(in_id, out_id))
if self.mode == "nearest":
valid_index, valid_output_index, index_array, distance_array = \
kd_tree.get_neighbour_info(self.in_area,
self.out_area,
radius,
neighbours=1)
del distance_array
self._cache = {}
self._cache['valid_index'] = valid_index
self._cache['valid_output_index'] = valid_output_index
self._cache['index_array'] = index_array
elif self.mode == "quick":
ridx, cidx = \
utils.generate_quick_linesample_arrays(self.in_area,
self.out_area)
self._cache = {}
self._cache['row_idx'] = ridx
self._cache['col_idx'] = cidx
else:
raise ValueError("Unrecognised mode " + str(self.mode) + ".")
else:
self._cache = {}
self._file_cache = np.load(self._filename)
def __init__(self,
in_area,
out_area,
in_latlons=None,
mode=None,
radius=10000,
nprocs=1):
if (mode is not None and mode not in ["quick", "nearest"]):
raise ValueError("Projector mode must be 'nearest' or 'quick'")
self.area_file = get_area_file()
self.in_area = None
self.out_area = None
self._cache = None
self._filename = None
self.mode = "quick"
self.radius = radius
self.conf = ConfigParser.ConfigParser()
self.conf.read(os.path.join(CONFIG_PATH, "mpop.cfg"))
# TODO:
# - Rework so that in_area and out_area can be lonlats.
# - Add a recompute flag ?
# Setting up the input area
try:
self.in_area = get_area_def(in_area)
in_id = in_area
except (utils.AreaNotFound, AttributeError):
try:
in_id = in_area.area_id
self.in_area = in_area
except AttributeError:
try:
self.in_area = geometry.SwathDefinition(lons=in_latlons[0],
lats=in_latlons[1])
in_id = in_area
except TypeError:
raise utils.AreaNotFound(
"Input area " + str(in_area) + " must be defined in " +
self.area_file + ", be an area object"
" or longitudes/latitudes must be "
"provided.")
# Setting up the output area
try:
self.out_area = get_area_def(out_area)
out_id = out_area
except (utils.AreaNotFound, AttributeError):
try:
out_id = out_area.area_id
self.out_area = out_area
except AttributeError:
raise utils.AreaNotFound("Output area " + str(out_area) +
" must be defined in " +
self.area_file + " or "
"be an area object.")
#if self.in_area == self.out_area:
# return
# choosing the right mode if necessary
if mode is None:
try:
dicts = in_area.proj_dict, out_area.proj_dict
del dicts
self.mode = "quick"
except AttributeError:
self.mode = "nearest"
else:
self.mode = mode
filename = (in_id + "2" + out_id + "_" +
str(_get_area_hash(self.in_area)) + "to" +
str(_get_area_hash(self.out_area)) + "_" + self.mode +
".npz")
projections_directory = "/var/tmp"
try:
projections_directory = self.conf.get("projector",
"projections_directory")
except ConfigParser.NoSectionError:
pass
self._filename = os.path.join(projections_directory, filename)
try:
self._cache = {}
self._file_cache = np.load(self._filename)
except:
logger.info("Computing projection from %s to %s...", in_id, out_id)
if self.mode == "nearest":
valid_index, valid_output_index, index_array, distance_array = \
kd_tree.get_neighbour_info(self.in_area,
self.out_area,
self.radius,
neighbours=1,
nprocs=nprocs)
del distance_array
self._cache = {}
self._cache['valid_index'] = valid_index
self._cache['valid_output_index'] = valid_output_index
self._cache['index_array'] = index_array
elif self.mode == "quick":
ridx, cidx = \
utils.generate_quick_linesample_arrays(self.in_area,
self.out_area)
self._cache = {}
self._cache['row_idx'] = ridx
self._cache['col_idx'] = cidx
