def test_field_name_orig_to_new_mrms(self):
"""Ensures correct output from field_name_orig_to_new.
In this case, original field name is from MRMS.
"""
this_field_name = radar_utils.field_name_orig_to_new(
LL_SHEAR_NAME_MRMS, data_source=radar_utils.MRMS_SOURCE_ID)
self.assertTrue(this_field_name == LL_SHEAR_NAME_NEW)
def test_field_name_orig_to_new_gridrad(self):
"""Ensures correct output from field_name_orig_to_new.
In this case, original field name is from GridRad.
"""
this_field_name = radar_utils.field_name_orig_to_new(
radar_utils.DIFFERENTIAL_REFL_NAME_GRIDRAD,
data_source=radar_utils.GRIDRAD_SOURCE_ID)
self.assertTrue(this_field_name == radar_utils.DIFFERENTIAL_REFL_NAME)
def test_field_name_orig_to_new_myrorss(self):
"""Ensures correct output from field_name_orig_to_new.
In this case, original field name is from MYRORSS.
"""
this_field_name = radar_utils.field_name_orig_to_new(
field_name_orig=LL_SHEAR_NAME_MYRORSS,
data_source_name=radar_utils.MYRORSS_SOURCE_ID)
self.assertTrue(this_field_name == LL_SHEAR_NAME)
def read_data_from_sparse_grid_file(netcdf_file_name,
field_name_orig,
data_source,
sentinel_values,
raise_error_if_fails=True):
"""Reads sparse radar grid from raw (either MYRORSS or MRMS) file.
This file should contain one radar field at one height and valid time.
:param netcdf_file_name: Path to input file.
:param field_name_orig: Name of radar field in original (either MYRORSS or
MRMS) format.
:param data_source: Data source (string).
:param sentinel_values: 1-D numpy array of sentinel values.
:param raise_error_if_fails: Boolean flag. If True and file cannot be read,
this method will raise an error. If False and file cannot be read, will
return None.
:return: sparse_grid_table: pandas DataFrame with the following columns.
Each row corresponds to one grid point.
sparse_grid_table.grid_row: Row index.
sparse_grid_table.grid_column: Column index.
sparse_grid_table.<field_name>: Radar measurement (column name is produced
by _field_name_orig_to_new).
sparse_grid_table.num_grid_cells: Number of consecutive grid points with the
same radar measurement. Counting is row-major (to the right along the
row, then down to the next column if necessary).
"""
error_checking.assert_file_exists(netcdf_file_name)
error_checking.assert_is_numpy_array_without_nan(sentinel_values)
error_checking.assert_is_numpy_array(sentinel_values, num_dimensions=1)
netcdf_dataset = netcdf_io.open_netcdf(netcdf_file_name,
raise_error_if_fails)
if netcdf_dataset is None:
return None
field_name = radar_utils.field_name_orig_to_new(
field_name_orig=field_name_orig, data_source_name=data_source)
num_values = len(netcdf_dataset.variables[GRID_ROW_COLUMN_ORIG])
if num_values == 0:
sparse_grid_dict = {
GRID_ROW_COLUMN: numpy.array([], dtype=int),
GRID_COLUMN_COLUMN: numpy.array([], dtype=int),
NUM_GRID_CELL_COLUMN: numpy.array([], dtype=int),
field_name: numpy.array([])
}
else:
sparse_grid_dict = {
GRID_ROW_COLUMN:
netcdf_dataset.variables[GRID_ROW_COLUMN_ORIG][:],
GRID_COLUMN_COLUMN:
netcdf_dataset.variables[GRID_COLUMN_COLUMN_ORIG][:],
NUM_GRID_CELL_COLUMN:
netcdf_dataset.variables[NUM_GRID_CELL_COLUMN_ORIG][:],
field_name:
netcdf_dataset.variables[field_name_orig][:]
}
netcdf_dataset.close()
sparse_grid_table = pandas.DataFrame.from_dict(sparse_grid_dict)
return _remove_sentinels_from_sparse_grid(sparse_grid_table,
field_name=field_name,
sentinel_values=sentinel_values)
def read_metadata_from_raw_file(netcdf_file_name,
data_source,
raise_error_if_fails=True):
"""Reads metadata from raw (either MYRORSS or MRMS) file.
This file should contain one radar field at one height and valid time.
:param netcdf_file_name: Path to input file.
:param data_source: Data source (string).
:param raise_error_if_fails: Boolean flag. If True and file cannot be read,
this method will raise an error. If False and file cannot be read, will
return None.
:return: metadata_dict: Dictionary with the following keys.
metadata_dict['nw_grid_point_lat_deg']: Latitude (deg N) of northwesternmost
grid point.
metadata_dict['nw_grid_point_lng_deg']: Longitude (deg E) of
northwesternmost grid point.
metadata_dict['lat_spacing_deg']: Spacing (deg N) between meridionally
adjacent grid points.
metadata_dict['lng_spacing_deg']: Spacing (deg E) between zonally adjacent
grid points.
metadata_dict['num_lat_in_grid']: Number of rows (unique grid-point
latitudes).
metadata_dict['num_lng_in_grid']: Number of columns (unique grid-point
longitudes).
metadata_dict['height_m_asl']: Radar height (metres above ground level).
metadata_dict['unix_time_sec']: Valid time.
metadata_dict['field_name']: Name of radar field in GewitterGefahr format.
metadata_dict['field_name_orig']: Name of radar field in original (either
MYRORSS or MRMS) format.
metadata_dict['sentinel_values']: 1-D numpy array of sentinel values.
"""
error_checking.assert_file_exists(netcdf_file_name)
netcdf_dataset = netcdf_io.open_netcdf(netcdf_file_name,
raise_error_if_fails)
if netcdf_dataset is None:
return None
field_name_orig = str(getattr(netcdf_dataset, FIELD_NAME_COLUMN_ORIG))
metadata_dict = {
radar_utils.NW_GRID_POINT_LAT_COLUMN:
getattr(netcdf_dataset, NW_GRID_POINT_LAT_COLUMN_ORIG),
radar_utils.NW_GRID_POINT_LNG_COLUMN:
lng_conversion.convert_lng_positive_in_west(getattr(
netcdf_dataset, NW_GRID_POINT_LNG_COLUMN_ORIG),
allow_nan=False),
radar_utils.LAT_SPACING_COLUMN:
getattr(netcdf_dataset, LAT_SPACING_COLUMN_ORIG),
radar_utils.LNG_SPACING_COLUMN:
getattr(netcdf_dataset, LNG_SPACING_COLUMN_ORIG),
radar_utils.NUM_LAT_COLUMN:
netcdf_dataset.dimensions[NUM_LAT_COLUMN_ORIG].size + 1,
radar_utils.NUM_LNG_COLUMN:
netcdf_dataset.dimensions[NUM_LNG_COLUMN_ORIG].size + 1,
radar_utils.HEIGHT_COLUMN:
getattr(netcdf_dataset, HEIGHT_COLUMN_ORIG),
radar_utils.UNIX_TIME_COLUMN:
getattr(netcdf_dataset, UNIX_TIME_COLUMN_ORIG),
FIELD_NAME_COLUMN_ORIG:
field_name_orig,
radar_utils.FIELD_NAME_COLUMN:
radar_utils.field_name_orig_to_new(field_name_orig=field_name_orig,
data_source_name=data_source)
}
latitude_spacing_deg = metadata_dict[radar_utils.LAT_SPACING_COLUMN]
longitude_spacing_deg = metadata_dict[radar_utils.LNG_SPACING_COLUMN]
# TODO(thunderhoser): The following "if" condition is a hack. The purpose
# is to change grid corners only for actual MYRORSS data, not GridRad data
# in MYRORSS format.
if latitude_spacing_deg < 0.011 and longitude_spacing_deg < 0.011:
metadata_dict[radar_utils.NW_GRID_POINT_LAT_COLUMN] = (
rounder.floor_to_nearest(
metadata_dict[radar_utils.NW_GRID_POINT_LAT_COLUMN],
metadata_dict[radar_utils.LAT_SPACING_COLUMN]))
metadata_dict[radar_utils.NW_GRID_POINT_LNG_COLUMN] = (
rounder.ceiling_to_nearest(
metadata_dict[radar_utils.NW_GRID_POINT_LNG_COLUMN],
metadata_dict[radar_utils.LNG_SPACING_COLUMN]))
sentinel_values = []
for this_column in SENTINEL_VALUE_COLUMNS_ORIG:
sentinel_values.append(getattr(netcdf_dataset, this_column))
metadata_dict.update(
{radar_utils.SENTINEL_VALUE_COLUMN: numpy.array(sentinel_values)})
netcdf_dataset.close()
return metadata_dict
