def test_check_field_name_valid(self):
"""Ensures correct output from check_field_name.
In this case, field name is valid.
"""
radar_utils.check_field_name(LL_SHEAR_NAME_NEW)
def test_check_field_name_invalid(self):
"""Ensures correct output from check_field_name.
In this case, field name is invalid.
"""
with self.assertRaises(ValueError):
radar_utils.check_field_name(LL_SHEAR_NAME_NEW_FAKE)
def get_default_colour_scheme(field_name, opacity=DEFAULT_OPACITY):
"""Returns default colour scheme for radar field.
:param field_name: Field name (must be accepted by
`radar_utils.check_field_name`).
:param opacity: Opacity (in range 0...1).
:return: colour_map_object: Instance of `matplotlib.colors.ListedColormap`.
:return: colour_norm_object: Instance of `matplotlib.colors.BoundaryNorm`.
"""
radar_utils.check_field_name(field_name)
error_checking.assert_is_greater(opacity, 0.)
error_checking.assert_is_leq(opacity, 1.)
colour_map_object = None
colour_norm_object = None
if field_name in radar_utils.REFLECTIVITY_NAMES:
colour_map_object, colour_norm_object = (
_get_reflectivity_colour_scheme())
elif field_name in radar_utils.SHEAR_NAMES:
colour_map_object, colour_norm_object = _get_az_shear_colour_scheme()
elif field_name in radar_utils.ECHO_TOP_NAMES:
colour_map_object, colour_norm_object = _get_echo_top_colour_scheme()
elif field_name == radar_utils.MESH_NAME:
colour_map_object, colour_norm_object = _get_mesh_colour_scheme()
elif field_name == radar_utils.SHI_NAME:
colour_map_object, colour_norm_object = _get_shi_colour_scheme()
elif field_name == radar_utils.VIL_NAME:
colour_map_object, colour_norm_object = _get_vil_colour_scheme()
elif field_name == radar_utils.DIFFERENTIAL_REFL_NAME:
colour_map_object, colour_norm_object = _get_zdr_colour_scheme()
elif field_name == radar_utils.SPEC_DIFF_PHASE_NAME:
colour_map_object, colour_norm_object = _get_kdp_colour_scheme()
elif field_name == radar_utils.CORRELATION_COEFF_NAME:
colour_map_object, colour_norm_object = _get_rho_hv_colour_scheme()
elif field_name == radar_utils.SPECTRUM_WIDTH_NAME:
colour_map_object, colour_norm_object = (
_get_spectrum_width_colour_scheme())
elif field_name == radar_utils.VORTICITY_NAME:
colour_map_object, colour_norm_object = _get_vorticity_colour_scheme()
elif field_name == radar_utils.DIVERGENCE_NAME:
colour_map_object, colour_norm_object = _get_divergence_colour_scheme()
num_colours = len(colour_map_object.colors)
for i in range(num_colours):
colour_map_object.colors[i] = matplotlib.colors.to_rgba(
colour_map_object.colors[i], opacity)
return colour_map_object, colour_norm_object
def get_default_colour_scheme(field_name):
"""Returns default colour scheme for radar field.
:param field_name: Field name (must be accepted by
`radar_utils.check_field_name`).
:return: colour_map_object: Instance of `matplotlib.colors.ListedColormap`.
:return: colour_norm_object: Instance of `matplotlib.colors.BoundaryNorm`.
"""
radar_utils.check_field_name(field_name)
if field_name in radar_utils.REFLECTIVITY_NAMES:
return _get_reflectivity_colour_scheme()
if field_name in radar_utils.SHEAR_NAMES:
return _get_az_shear_colour_scheme()
if field_name in radar_utils.ECHO_TOP_NAMES:
return _get_echo_top_colour_scheme()
if field_name == radar_utils.MESH_NAME:
return _get_mesh_colour_scheme()
if field_name == radar_utils.SHI_NAME:
return _get_shi_colour_scheme()
if field_name == radar_utils.VIL_NAME:
return _get_vil_colour_scheme()
if field_name == radar_utils.DIFFERENTIAL_REFL_NAME:
return _get_zdr_colour_scheme()
if field_name == radar_utils.SPEC_DIFF_PHASE_NAME:
return _get_kdp_colour_scheme()
if field_name == radar_utils.CORRELATION_COEFF_NAME:
return _get_rho_hv_colour_scheme()
if field_name == radar_utils.SPECTRUM_WIDTH_NAME:
return _get_spectrum_width_colour_scheme()
if field_name == radar_utils.VORTICITY_NAME:
return _get_vorticity_colour_scheme()
if field_name == radar_utils.DIVERGENCE_NAME:
return _get_divergence_colour_scheme()
return None
def _field_name_to_plotting_units(field_name):
"""Converts field *name* from default units to plotting units.
:param field_name: Name of radar field (must be accepted by
`radar_utils.check_field_name`).
:return: new_field_name: Same as input, except in plotting units.
"""
radar_utils.check_field_name(field_name)
if field_name in radar_utils.ECHO_TOP_NAMES:
return field_name.replace('_km', '_kft')
if field_name in SHEAR_VORT_DIV_NAMES:
return field_name.replace('_s01', '_ks01')
return field_name
def _field_to_plotting_units(field_matrix, field_name):
"""Converts radar field from default units to plotting units.
:param field_matrix: numpy array in default units.
:param field_name: Name of radar field (must be accepted by
`radar_utils.check_field_name`).
:return: new_field_matrix: Same as input, except in plotting units.
"""
radar_utils.check_field_name(field_name)
if field_name in radar_utils.ECHO_TOP_NAMES:
return field_matrix * KM_TO_KILOFEET
if field_name in SHEAR_VORT_DIV_NAMES:
return field_matrix * PER_SECOND_TO_PER_KILOSECOND
return field_matrix
def _column_name_to_statistic_params(column_name):
"""Determines parameters of statistic from column name.
If column name does not correspond to a statistic, this method will return
None.
:param column_name: Name of column.
:return: parameter_dict: Dictionary with the following keys.
parameter_dict['is_gridrad_statistic']: Boolean flag (True if statistic was
computed by GridRad software, not GewitterGefahr).
parameter_dict['radar_field_name']: Name of radar field on which statistic
is based. None for GridRad statistics.
parameter_dict['radar_height_m_asl']: Radar height (metres above sea level).
None for GridRad statistics.
parameter_dict['statistic_name']: Name of statistic. None for GridRad
statistics and percentiles.
parameter_dict['percentile_level']: Percentile level. None for GridRad
statistics and non-percentile statistics.
"""
column_name_parts = column_name.split('_')
if len(column_name_parts) < 2:
return None
# Determine statistic name or percentile level.
if column_name_parts[-1] in STATISTIC_NAMES:
statistic_name = column_name_parts[-1]
percentile_level = None
else:
statistic_name = None
if not column_name_parts[-1].startswith('percentile'):
return None
percentile_part = column_name_parts[-1].replace('percentile', '')
try:
percentile_level = float(percentile_part)
except ValueError:
return None
# Determine radar field.
radar_field_name = '_'.join(column_name_parts[:-2])
try:
radar_utils.check_field_name(radar_field_name)
except ValueError:
return None
# Determine radar height.
radar_height_part = column_name_parts[-2]
if not radar_height_part.endswith('metres'):
return None
radar_height_part = radar_height_part.replace('metres', '')
try:
radar_height_m_asl = int(radar_height_part)
except ValueError:
return None
return {
IS_GRIDRAD_STATISTIC_KEY: False,
RADAR_FIELD_NAME_KEY: radar_field_name,
RADAR_HEIGHT_KEY: radar_height_m_asl,
STATISTIC_NAME_KEY: statistic_name,
PERCENTILE_LEVEL_KEY: percentile_level
}
def find_raw_file_inexact_time(desired_time_unix_sec,
spc_date_string,
field_name,
data_source,
top_directory_name,
height_m_asl=None,
max_time_offset_sec=None,
raise_error_if_missing=False):
"""Finds raw file at inexact time.
If you know the exact valid time, use `find_raw_file`.
:param desired_time_unix_sec: Desired valid time.
:param spc_date_string: SPC date (format "yyyymmdd").
:param field_name: Field name in GewitterGefahr format.
:param data_source: Data source (string).
:param top_directory_name: Name of top-level directory with raw files.
:param height_m_asl: Radar height (metres above sea level).
:param max_time_offset_sec: Maximum offset between actual and desired valid
time.
For example, if `desired_time_unix_sec` is 162933 UTC 5 Jan 2018 and
`max_time_offset_sec` = 60, this method will look for az-shear at valid
times from 162833...163033 UTC 5 Jan 2018.
If None, this defaults to `DEFAULT_MAX_TIME_OFFSET_FOR_AZ_SHEAR_SEC` for
azimuthal-shear fields and `DEFAULT_MAX_TIME_OFFSET_FOR_NON_SHEAR_SEC` for
all other fields.
:param raise_error_if_missing: Boolean flag. If no file is found and
raise_error_if_missing = True, this method will error out. If no file
is found and raise_error_if_missing = False, will return None.
:return: raw_file_name: Path to raw file.
:raises: ValueError: if no file is found and raise_error_if_missing = True.
"""
# Error-checking.
error_checking.assert_is_integer(desired_time_unix_sec)
_ = time_conversion.spc_date_string_to_unix_sec(spc_date_string)
error_checking.assert_is_boolean(raise_error_if_missing)
radar_utils.check_field_name(field_name)
if max_time_offset_sec is None:
if field_name in AZIMUTHAL_SHEAR_FIELD_NAMES:
max_time_offset_sec = DEFAULT_MAX_TIME_OFFSET_FOR_AZ_SHEAR_SEC
else:
max_time_offset_sec = DEFAULT_MAX_TIME_OFFSET_FOR_NON_SHEAR_SEC
error_checking.assert_is_integer(max_time_offset_sec)
error_checking.assert_is_greater(max_time_offset_sec, 0)
first_allowed_minute_unix_sec = numpy.round(
int(
rounder.floor_to_nearest(
float(desired_time_unix_sec - max_time_offset_sec),
MINUTES_TO_SECONDS)))
last_allowed_minute_unix_sec = numpy.round(
int(
rounder.floor_to_nearest(
float(desired_time_unix_sec + max_time_offset_sec),
MINUTES_TO_SECONDS)))
allowed_minutes_unix_sec = time_periods.range_and_interval_to_list(
start_time_unix_sec=first_allowed_minute_unix_sec,
end_time_unix_sec=last_allowed_minute_unix_sec,
time_interval_sec=MINUTES_TO_SECONDS,
include_endpoint=True).astype(int)
relative_directory_name = get_relative_dir_for_raw_files(
field_name=field_name,
data_source=data_source,
height_m_asl=height_m_asl)
raw_file_names = []
for this_time_unix_sec in allowed_minutes_unix_sec:
this_pathless_file_pattern = _get_pathless_raw_file_pattern(
this_time_unix_sec)
this_file_pattern = '{0:s}/{1:s}/{2:s}/{3:s}/{4:s}'.format(
top_directory_name, spc_date_string[:4], spc_date_string,
relative_directory_name, this_pathless_file_pattern)
raw_file_names += glob.glob(this_file_pattern)
file_times_unix_sec = []
for this_raw_file_name in raw_file_names:
file_times_unix_sec.append(raw_file_name_to_time(this_raw_file_name))
if len(file_times_unix_sec):
file_times_unix_sec = numpy.array(file_times_unix_sec)
time_differences_sec = numpy.absolute(file_times_unix_sec -
desired_time_unix_sec)
nearest_index = numpy.argmin(time_differences_sec)
min_time_diff_sec = time_differences_sec[nearest_index]
else:
min_time_diff_sec = numpy.inf
if min_time_diff_sec > max_time_offset_sec:
if raise_error_if_missing:
desired_time_string = time_conversion.unix_sec_to_string(
desired_time_unix_sec, TIME_FORMAT_FOR_LOG_MESSAGES)
error_string = (
'Could not find "{0:s}" file within {1:d} seconds of {2:s}.'
).format(field_name, max_time_offset_sec, desired_time_string)
raise ValueError(error_string)
return None
return raw_file_names[nearest_index]