def _project_polygon_latlng_to_xy(polygon_object_latlng,
centroid_latitude_deg=None,
centroid_longitude_deg=None):
"""Projects polygon from lat-long to x-y coordinates.
:param polygon_object_latlng: Instance of `shapely.geometry.Polygon`, where
x-coordinates are actually longitudes and y-coordinates are actually
latitudes.
:param centroid_latitude_deg: Latitude (deg N) at polygon centroid.
:param centroid_longitude_deg: Longitude (deg E) at polygon centroid.
:return: polygon_object_xy: Instance of `shapely.geometry.Polygon`, where x-
and y-coordinates are in metres.
"""
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=numpy.full(2, centroid_latitude_deg),
central_longitude_deg=centroid_longitude_deg)
vertex_latitudes_deg = numpy.asarray(polygon_object_latlng.exterior.xy[1])
vertex_longitudes_deg = numpy.asarray(polygon_object_latlng.exterior.xy[0])
vertex_x_metres, vertex_y_metres = projections.project_latlng_to_xy(
vertex_latitudes_deg, vertex_longitudes_deg,
projection_object=projection_object, false_easting_metres=0.,
false_northing_metres=0.)
return polygons.vertex_arrays_to_polygon_object(
vertex_x_metres, vertex_y_metres)
def init_projection(model_name):
"""Initializes projection used by model.
:param model_name: Model name (must be accepted by `check_model_name`).
:return: projection_object: Instance of `pyproj.Proj`, specifying the
projection.
"""
standard_latitudes_deg, central_longitude_deg = get_projection_params(
model_name)
return projections.init_lcc_projection(
standard_latitudes_deg=standard_latitudes_deg,
central_longitude_deg=central_longitude_deg)
def test_project_xy_to_latlng(self):
"""Ensures that project_xy_to_latlng does not crash.
This is an integration test, not a unit test, because it requires
init_lcc_projection to create the projection object.
"""
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=STANDARD_LATITUDES_DEG,
central_longitude_deg=CENTRAL_LONGITUDE_DEG)
projections.project_xy_to_latlng(
x_coords_metres=X_COORDS_METRES,
y_coords_metres=Y_COORDS_METRES,
projection_object=projection_object,
false_easting_metres=FALSE_EASTING_METRES,
false_northing_metres=FALSE_NORTHING_METRES)
def test_project_both_ways(self):
"""Ensures that the two projection methods are inverses.
This is an integration test, not a unit test, because it calls both
projection methods. Also, it requires init_lcc_projection
to create the projection object.
"""
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=STANDARD_LATITUDES_DEG,
central_longitude_deg=CENTRAL_LONGITUDE_DEG)
these_x_coords_metres, these_y_coords_metres = (
projections.project_latlng_to_xy(
latitudes_deg=LATITUDES_DEG,
longitudes_deg=LONGITUDES_DEG,
projection_object=projection_object,
false_easting_metres=FALSE_EASTING_METRES,
false_northing_metres=FALSE_NORTHING_METRES))
these_latitudes_deg, these_longitudes_deg = (
projections.project_xy_to_latlng(
x_coords_metres=these_x_coords_metres,
y_coords_metres=these_y_coords_metres,
projection_object=projection_object,
false_easting_metres=FALSE_EASTING_METRES,
false_northing_metres=FALSE_NORTHING_METRES))
self.assertTrue(
numpy.allclose(these_latitudes_deg,
LATITUDES_DEG,
atol=TOLERANCE,
equal_nan=True))
self.assertTrue(
numpy.allclose(these_longitudes_deg,
LONGITUDES_DEG,
atol=TOLERANCE,
equal_nan=True))
def _get_grid_point_coords(model_name,
first_row_in_full_grid,
last_row_in_full_grid,
first_column_in_full_grid,
last_column_in_full_grid,
grid_id=None,
basemap_object=None):
"""Returns x-y and lat-long coords for a subgrid of the full model grid.
This method generates different x-y coordinates than
`nwp_model_utils.get_xy_grid_point_matrices`, because (like
`mpl_toolkits.basemap.Basemap`) this method sets false easting = false
northing = 0 metres.
:param model_name: Name of NWP model (must be accepted by
`nwp_model_utils.check_grid_name`).
:param first_row_in_full_grid: Row 0 in the subgrid is row
`first_row_in_full_grid` in the full grid.
:param last_row_in_full_grid: Last row in the subgrid is row
`last_row_in_full_grid` in the full grid. If you want last row in the
subgrid to equal last row in the full grid, make this -1.
:param first_column_in_full_grid: Column 0 in the subgrid is column
`first_column_in_full_grid` in the full grid.
:param last_column_in_full_grid: Last column in the subgrid is column
`last_column_in_full_grid` in the full grid. If you want last column in
the subgrid to equal last column in the full grid, make this -1.
:param grid_id: Grid for NWP model (must be accepted by
`nwp_model_utils.check_grid_name`).
:param basemap_object: Instance of `mpl_toolkits.basemap.Basemap` for the
given NWP model. If you don't have one, no big deal -- leave this
argument empty.
:return: coordinate_dict: Dictionary with the following keys.
coordinate_dict['grid_point_x_matrix_metres']: M-by-N numpy array of
x-coordinates.
coordinate_dict['grid_point_y_matrix_metres']: M-by-N numpy array of
y-coordinates.
coordinate_dict['grid_point_lat_matrix_deg']: M-by-N numpy array of
latitudes (deg N).
coordinate_dict['grid_point_lng_matrix_deg']: M-by-N numpy array of
longitudes (deg E).
"""
num_rows_in_full_grid, num_columns_in_full_grid = (
nwp_model_utils.get_grid_dimensions(model_name=model_name,
grid_name=grid_id))
error_checking.assert_is_integer(first_row_in_full_grid)
error_checking.assert_is_geq(first_row_in_full_grid, 0)
error_checking.assert_is_integer(last_row_in_full_grid)
if last_row_in_full_grid < 0:
last_row_in_full_grid += num_rows_in_full_grid
error_checking.assert_is_greater(last_row_in_full_grid,
first_row_in_full_grid)
error_checking.assert_is_less_than(last_row_in_full_grid,
num_rows_in_full_grid)
error_checking.assert_is_integer(first_column_in_full_grid)
error_checking.assert_is_geq(first_column_in_full_grid, 0)
error_checking.assert_is_integer(last_column_in_full_grid)
if last_column_in_full_grid < 0:
last_column_in_full_grid += num_columns_in_full_grid
error_checking.assert_is_greater(last_column_in_full_grid,
first_column_in_full_grid)
error_checking.assert_is_less_than(last_column_in_full_grid,
num_columns_in_full_grid)
grid_point_lat_matrix_deg, grid_point_lng_matrix_deg = (
nwp_model_utils.get_latlng_grid_point_matrices(model_name=model_name,
grid_name=grid_id))
grid_point_lat_matrix_deg = grid_point_lat_matrix_deg[
first_row_in_full_grid:(last_row_in_full_grid + 1),
first_column_in_full_grid:(last_column_in_full_grid + 1)]
grid_point_lng_matrix_deg = grid_point_lng_matrix_deg[
first_row_in_full_grid:(last_row_in_full_grid + 1),
first_column_in_full_grid:(last_column_in_full_grid + 1)]
if basemap_object is None:
standard_latitudes_deg, central_longitude_deg = (
nwp_model_utils.get_projection_params(model_name))
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=standard_latitudes_deg,
central_longitude_deg=central_longitude_deg)
grid_point_x_matrix_metres, grid_point_y_matrix_metres = (
projections.project_latlng_to_xy(
latitudes_deg=grid_point_lat_matrix_deg,
longitudes_deg=grid_point_lng_matrix_deg,
projection_object=projection_object,
false_northing_metres=0.,
false_easting_metres=0.))
else:
grid_point_x_matrix_metres, grid_point_y_matrix_metres = basemap_object(
grid_point_lng_matrix_deg, grid_point_lat_matrix_deg)
return {
X_COORD_MATRIX_KEY: grid_point_x_matrix_metres,
Y_COORD_MATRIX_KEY: grid_point_y_matrix_metres,
LATITUDE_MATRIX_KEY: grid_point_lat_matrix_deg,
LONGITUDE_MATRIX_KEY: grid_point_lng_matrix_deg,
}
def test_init_lcc_projection_no_crash(self):
"""Ensures that init_lcc_projection does not crash."""
projections.init_lcc_projection(
standard_latitudes_deg=STANDARD_LATITUDES_DEG,
central_longitude_deg=CENTRAL_LONGITUDE_DEG)
def _run(input_shapefile_name, output_pickle_file_name):
"""Converts SPC convective outlook to nicer file format.
This is effectively the main method.
:param input_shapefile_name: See documentation at top of file.
:param output_pickle_file_name: Same.
"""
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=STANDARD_LATITUDES_DEG,
central_longitude_deg=CENTRAL_LONGITUDE_DEG,
ellipsoid_name=ELLIPSOID_NAME)
print('Reading data from: "{0:s}"...'.format(input_shapefile_name))
shapefile_handle = shapefile.Reader(input_shapefile_name)
list_of_polygon_objects_latlng = []
risk_type_strings = []
for this_record_object in shapefile_handle.iterShapeRecords():
# print this_record_object.record
this_risk_type_enum = this_record_object.record[RISK_TYPE_INDEX]
try:
this_risk_type_string = RISK_TYPE_ENUM_TO_STRING[
this_risk_type_enum]
except KeyError:
continue
these_xy_tuples = this_record_object.shape.points
this_num_vertices = len(these_xy_tuples)
these_x_coords_metres = numpy.array(
[these_xy_tuples[k][0] for k in range(this_num_vertices)])
these_y_coords_metres = numpy.array(
[these_xy_tuples[k][1] for k in range(this_num_vertices)])
these_latitudes_deg, these_longitudes_deg = (
projections.project_xy_to_latlng(
x_coords_metres=these_x_coords_metres,
y_coords_metres=these_y_coords_metres,
projection_object=projection_object,
false_easting_metres=FALSE_EASTING_METRES,
false_northing_metres=FALSE_NORTHING_METRES))
this_polygon_object_latlng = (polygons.vertex_arrays_to_polygon_object(
exterior_x_coords=these_longitudes_deg,
exterior_y_coords=these_latitudes_deg))
risk_type_strings.append(this_risk_type_string)
list_of_polygon_objects_latlng.append(this_polygon_object_latlng)
outlook_dict = {
RISK_TYPE_COLUMN: risk_type_strings,
POLYGON_COLUMN: list_of_polygon_objects_latlng
}
outlook_table = pandas.DataFrame.from_dict(outlook_dict)
# print(outlook_table)
print('Writing outlook polygons to file: "{0:s}"...'.format(
output_pickle_file_name))
file_system_utils.mkdir_recursive_if_necessary(
file_name=output_pickle_file_name)
pickle_file_handle = open(output_pickle_file_name, 'wb')
pickle.dump(outlook_table, pickle_file_handle)
pickle_file_handle.close()
def create_equidistant_grid(min_latitude_deg,
max_latitude_deg,
min_longitude_deg,
max_longitude_deg,
x_spacing_metres,
y_spacing_metres,
azimuthal=True):
"""Creates equidistant grid.
M = number of rows
N = number of columns
:param min_latitude_deg: Minimum latitude (deg N) in grid.
:param max_latitude_deg: Max latitude (deg N) in grid.
:param min_longitude_deg: Minimum longitude (deg E) in grid.
:param max_longitude_deg: Max longitude (deg E) in grid.
:param x_spacing_metres: Spacing between grid points in adjacent columns.
:param y_spacing_metres: Spacing between grid points in adjacent rows.
:param azimuthal: Boolean flag. If True, will create azimuthal equidistant
grid. If False, will create Lambert conformal grid.
:return: grid_dict: Dictionary with the following keys.
grid_dict['grid_point_x_coords_metres']: length-N numpy array with unique
x-coordinates at grid points.
grid_dict['grid_point_y_coords_metres']: length-M numpy array with unique
y-coordinates at grid points.
grid_dict['projection_object']: Instance of `pyproj.Proj` (used to convert
between lat-long coordinates and the x-y coordinates of the grid).
"""
# Check input args.
error_checking.assert_is_valid_latitude(min_latitude_deg)
error_checking.assert_is_valid_latitude(max_latitude_deg)
error_checking.assert_is_greater(max_latitude_deg, min_latitude_deg)
error_checking.assert_is_greater(x_spacing_metres, 0.)
error_checking.assert_is_greater(y_spacing_metres, 0.)
error_checking.assert_is_boolean(azimuthal)
min_longitude_deg = lng_conversion.convert_lng_negative_in_west(
min_longitude_deg, allow_nan=False)
max_longitude_deg = lng_conversion.convert_lng_negative_in_west(
max_longitude_deg, allow_nan=False)
error_checking.assert_is_greater(max_longitude_deg, min_longitude_deg)
# Create lat-long grid.
num_grid_rows = 1 + int(
numpy.round((max_latitude_deg - min_latitude_deg) /
DUMMY_LATITUDE_SPACING_DEG))
num_grid_columns = 1 + int(
numpy.round((max_longitude_deg - min_longitude_deg) /
DUMMY_LONGITUDE_SPACING_DEG))
unique_latitudes_deg, unique_longitudes_deg = get_latlng_grid_points(
min_latitude_deg=min_latitude_deg,
min_longitude_deg=min_longitude_deg,
lat_spacing_deg=DUMMY_LATITUDE_SPACING_DEG,
lng_spacing_deg=DUMMY_LONGITUDE_SPACING_DEG,
num_rows=num_grid_rows,
num_columns=num_grid_columns)
latitude_matrix_deg, longitude_matrix_deg = latlng_vectors_to_matrices(
unique_latitudes_deg=unique_latitudes_deg,
unique_longitudes_deg=unique_longitudes_deg)
# Create projection.
central_latitude_deg = 0.5 * (min_latitude_deg + max_latitude_deg)
central_longitude_deg = 0.5 * (min_longitude_deg + max_longitude_deg)
if azimuthal:
projection_object = projections.init_azimuthal_equidistant_projection(
central_latitude_deg=central_latitude_deg,
central_longitude_deg=central_longitude_deg)
else:
projection_object = projections.init_lcc_projection(
standard_latitudes_deg=numpy.full(2, central_latitude_deg),
central_longitude_deg=central_longitude_deg)
# Convert lat-long grid to preliminary x-y grid.
prelim_x_matrix_metres, prelim_y_matrix_metres = (
projections.project_latlng_to_xy(latitudes_deg=latitude_matrix_deg,
longitudes_deg=longitude_matrix_deg,
projection_object=projection_object))
# Find corners of preliminary x-y grid.
x_min_metres = numpy.min(prelim_x_matrix_metres)
x_max_metres = numpy.max(prelim_x_matrix_metres)
y_min_metres = numpy.min(prelim_y_matrix_metres)
y_max_metres = numpy.max(prelim_y_matrix_metres)
# Find corners of final x-y grid.
x_min_metres = number_rounding.floor_to_nearest(x_min_metres,
x_spacing_metres)
x_max_metres = number_rounding.ceiling_to_nearest(x_max_metres,
x_spacing_metres)
y_min_metres = number_rounding.floor_to_nearest(y_min_metres,
y_spacing_metres)
y_max_metres = number_rounding.ceiling_to_nearest(y_max_metres,
y_spacing_metres)
# Create final x-y grid.
num_grid_rows = 1 + int(
numpy.round((y_max_metres - y_min_metres) / y_spacing_metres))
num_grid_columns = 1 + int(
numpy.round((x_max_metres - x_min_metres) / x_spacing_metres))
unique_x_coords_metres, unique_y_coords_metres = get_xy_grid_points(
x_min_metres=x_min_metres,
y_min_metres=y_min_metres,
x_spacing_metres=x_spacing_metres,
y_spacing_metres=y_spacing_metres,
num_rows=num_grid_rows,
num_columns=num_grid_columns)
return {
X_COORDS_KEY: unique_x_coords_metres,
Y_COORDS_KEY: unique_y_coords_metres,
PROJECTION_KEY: projection_object
}