def test_static_ancillary(landmask_cube, interpreter):
"""Test interpretation of static ancillary"""
expected_result = ("This is a gridded ancillary file\n"
"This is a static ancillary with no time information\n")
interpreter.run(landmask_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_wind_direction(wind_direction_cube, interpreter):
"""Test interpretation of wind direction field with mean over realizations
cell method"""
expected_result = ("This is a gridded wind from direction file\n"
"It contains data from MOGREPS-UK\n")
interpreter.run(wind_direction_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_weather_code(wxcode_cube, interpreter):
"""Test interpretation of weather code field"""
expected_result = (
"This is a gridded weather code file\n"
"It contains blended data from models: UKV, MOGREPS-UK\n")
interpreter.run(wxcode_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_percentiles(wind_gust_percentile_cube, interpreter):
"""Test interpretation of wind gust percentiles from MOGREPS-UK"""
expected_result = ("This is a gridded percentiles file\n"
"It contains percentiles of wind gust\n"
"It has undergone no significant post-processing\n"
"It contains data from MOGREPS-UK\n")
interpreter.run(wind_gust_percentile_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_realizations(ensemble_cube, interpreter):
"""Test interpretation of temperature realizations from MOGREPS-UK"""
expected_result = (
"This is a gridded file containing one or more realizations\n"
"It contains realizations of air temperature\n"
"It has undergone no significant post-processing\n"
"It contains data from MOGREPS-UK\n")
interpreter.run(ensemble_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_spot_median(blended_spot_median_cube, interpreter):
"""Test interpretation of spot median"""
expected_result = (
"This is a spot percentiles file\n"
"It contains percentiles of air temperature\n"
"It has undergone some significant post-processing\n"
"It contains blended data from models: UKV, MOGREPS-UK\n")
interpreter.run(blended_spot_median_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_probabilities_above(probability_above_cube, interpreter):
"""Test interpretation of probability of temperature above threshold
from UKV"""
expected_result = (
"This is a gridded probabilities file\n"
"It contains probabilities of air temperature greater than thresholds\n"
"It has undergone some significant post-processing\n"
"It contains data from UKV\n")
interpreter.run(probability_above_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_probabilities_below(blended_probability_below_cube, interpreter):
"""Test interpretation of blended probability of max temperature in hour
below threshold"""
expected_result = (
"This is a gridded probabilities file\n"
"It contains probabilities of air temperature less than thresholds\n"
"These probabilities are of air temperature maximum over time\n"
"It has undergone some significant post-processing\n"
"It contains blended data from models: UKV, MOGREPS-UK\n")
interpreter.run(blended_probability_below_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def process(*file_paths: cli.inputpath, verbose=False, failures_only=False):
"""Intepret the metadata of an IMPROVER output into human readable format
according to the IMPROVER standard. An optional verbosity flag, if set to
True, will specify the source of each interpreted element.
This tool is intended as an aid to developers in adding and modifying
metadata within the code base.
Args:
file_paths (list of Path objects):
File paths to netCDF files for which the metadata should be interpreted.
verbose (bool):
Boolean flag to output information about sources of metadata
interpretation.
failures_only (bool):
Boolean flag that, if set, means only information about non-compliant
files is printed.
Raises:
ValueError: If any of the input files are not metadata compliant.
"""
from iris import load
from improver.developer_tools.metadata_interpreter import (
MOMetadataInterpreter,
display_interpretation,
)
cubelists = {
file_path: load(file_path.as_posix())
for file_path in file_paths
}
any_failures = False
for file, cubelist in cubelists.items():
for cube in cubelist:
interpreter = MOMetadataInterpreter()
try:
interpreter.run(cube)
except ValueError as err:
output = "Non-compliant :\n{}".format(str(err))
any_failures = True
else:
if failures_only:
continue
output = display_interpretation(interpreter, verbose=verbose)
print(f"\nfile : {file}")
print(f"cube name : {cube.name()}")
print(output)
if any_failures:
raise ValueError("One or more files checked is not metadata compliant")
def test_verbose_probability(probability_above_cube, interpreter):
"""Test verbose output for a simple probability diagnostic"""
expected_result = (
"This is a gridded probabilities file\n"
" Source: name, coordinates\n"
"It contains probabilities of air temperature greater than thresholds\n"
" Source: name, threshold coordinate (probabilities only)\n"
"It has undergone some significant post-processing\n"
" Source: title attribute\n"
"It contains data from UKV\n"
" Source: model ID attribute\n")
interpreter.run(probability_above_cube)
result = display_interpretation(interpreter, verbose=True)
assert result == expected_result
def test_verbose_snow_level(snow_level_cube, interpreter):
"""Test interpretation of a diagnostic cube with "probability" in the name,
which is not designed for blending with other models"""
expected_result = (
"This is a gridded file containing one or more realizations\n"
" Source: name, coordinates\n"
"It contains realizations of probability of snow falling level below ground level\n"
" Source: name, threshold coordinate (probabilities only)\n"
"It has undergone some significant post-processing\n"
" Source: title attribute\n"
"It has no source model information and cannot be blended\n"
" Source: model ID attribute (missing)\n")
interpreter.run(snow_level_cube)
result = display_interpretation(interpreter, verbose=True)
assert result == expected_result
def test_warnings_displayed(wind_gust_percentile_cube, interpreter):
"""Test any warnings are appended to the end of the displayed output"""
expected_result = (
"This is a gridded percentiles file\n"
"It contains percentiles of wind gust\n"
"It has undergone no significant post-processing\n"
"It contains data from MOGREPS-UK\n"
"WARNINGS:\n"
"dict_keys(['source', 'title', 'institution', 'mosg__model_configuration', "
"'wind_gust_diagnostic', 'enigma']) include unexpected attributes ['enigma']. "
"Please check the standard to ensure this is valid.\n")
wind_gust_percentile_cube.attributes[
"enigma"] = "intriguing and mysterious details"
interpreter.run(wind_gust_percentile_cube)
result = display_interpretation(interpreter)
assert result == expected_result
def test_verbose_with_cell_method(blended_probability_below_cube, interpreter):
"""Test verbose output with valid cell method"""
expected_result = (
"This is a gridded probabilities file\n"
" Source: name, coordinates\n"
"It contains probabilities of air temperature less than thresholds\n"
" Source: name, threshold coordinate (probabilities only)\n"
"These probabilities are of air temperature maximum over time\n"
" Source: cell methods\n"
"It has undergone some significant post-processing\n"
" Source: title attribute\n"
"It contains blended data from models: UKV, MOGREPS-UK\n"
" Source: title attribute, model ID attribute\n")
interpreter.run(blended_probability_below_cube)
result = display_interpretation(interpreter, verbose=True)
assert result == expected_result
def test_probabilities_below_verbose(blended_probability_below_cube,
interpreter):
"""Test interpretation of blended probability of max temperature in hour
below threshold with model cycle information available"""
expected_result = (
"This is a gridded probabilities file\n"
" Source: name, coordinates\n"
"It contains probabilities of air temperature less than thresholds\n"
" Source: name, threshold coordinate (probabilities only)\n"
"These probabilities are of air temperature maximum over time\n"
" Source: cell methods\n"
"It has undergone some significant post-processing\n"
" Source: title attribute\n"
"It contains blended data from models: UKV (cycle: 20171109T2300Z), "
"MOGREPS-UK (cycle: 20171109T2100Z)\n"
" Source: title attribute, model ID attribute, model run attribute\n"
)
interpreter.run(blended_probability_below_cube)
result = display_interpretation(interpreter, verbose=True)
assert result == expected_result
def test_unhandled(emos_coefficient_cube, interpreter):
"""Test unhandled intermediate cube"""
interpreter.run(emos_coefficient_cube)
result = display_interpretation(interpreter)
assert result == "emos_coefficient_alpha is not handled by this interpreter\n"
