def test_locator_given_time_pressure_format(self):
pattern = self.path
reference_time = dt.datetime(2019, 1, 1)
times = [dt.datetime(2019, 1, 2), dt.datetime(2019, 1, 2, 3)]
pressures = [1000, 950, 850]
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
dataset.createDimension("longitude", 1)
dataset.createDimension("latitude", 1)
var = um.times("time", length=len(times))
var[:] = netCDF4.date2num(times, units=var.units)
um.forecast_reference_time(reference_time)
var = um.pressures("pressure", length=len(pressures))
var[:] = pressures
dims = ("time", "pressure", "longitude", "latitude")
coordinates = "forecast_period_1 forecast_reference_time"
var = um.relative_humidity(dims, coordinates=coordinates)
var[:] = 100.
variable = "relative_humidity"
initial_time = reference_time
valid_time = times[1]
pressure = pressures[2]
locator = unified_model.Locator([self.path])
_, result = locator.locate(pattern, variable, initial_time, valid_time,
pressure)
expect = (1, 2)
self.assertEqual(expect, result)
def test_locator_given_dim0_format(self):
pattern = self.path
times = [dt.datetime(2019, 1, 1), dt.datetime(2019, 1, 2)]
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
dataset.createDimension("longitude", 1)
dataset.createDimension("latitude", 1)
var = um.times("time", length=len(times), dim_name="dim0")
var[:] = netCDF4.date2num(times, units=var.units)
um.forecast_reference_time(times[0])
var = um.pressures("pressure", length=len(times), dim_name="dim0")
var[:] = 1000.
dims = ("dim0", "longitude", "latitude")
coordinates = "forecast_period_1 forecast_reference_time pressure time"
var = um.relative_humidity(dims, coordinates=coordinates)
var[:] = 100.
variable = "relative_humidity"
initial_time = dt.datetime(2019, 1, 1)
valid_time = dt.datetime(2019, 1, 2)
locator = unified_model.Locator([self.path])
_, result = locator.locate(pattern,
variable,
initial_time,
valid_time,
pressure=1000.0001)
expect = (1, )
self.assertEqual(expect, result)
def test_valid_times(self):
units = "hours since 1970-01-01 00:00:00"
times = {
"time_0": [dt.datetime(2019, 1, 1)],
"time_1": [dt.datetime(2019, 1, 1, 3)]
}
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
for name, values in times.items():
var = um.times(name, length=len(values))
var[:] = netCDF4.date2num(values, units=var.units)
var = um.pressures("pressure", length=1)
var[:] = 1000.
var = um.longitudes(length=1)
var[:] = 125.
var = um.latitudes(length=1)
var[:] = 45.
dims = ("time_1", "pressure", "longitude", "latitude")
var = um.relative_humidity(dims)
var[:] = 100.
variable = "relative_humidity"
coord = unified_model.Coordinates()
result = coord.valid_times(self.path, variable)
expect = times["time_1"]
np.testing.assert_array_equal(expect, result)
def test_initial_time_given_forecast_reference_time(self):
time = dt.datetime(2019, 1, 1, 12)
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
um.forecast_reference_time(time)
result = unified_model.read_initial_time(self.path)
expect = time
np.testing.assert_array_equal(expect, result)
def test_time_axis_given_time_pressure_lon_lat_dimensions(self):
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
dims = ("time_1", "pressure_0", "longitude", "latitude")
for dim in dims:
dataset.createDimension(dim, 1)
var = um.relative_humidity(dims)
result = disk.time_axis(self.path, "relative_humidity")
expect = 0
self.assertEqual(expect, result)
def test_time_axis_given_dim0_format(self):
coordinates = "forecast_period_1 forecast_reference_time pressure time"
with netCDF4.Dataset(self.path, "w") as dataset:
um = tutorial.UM(dataset)
dims = ("dim0", "longitude", "latitude")
for dim in dims:
dataset.createDimension(dim, 1)
var = um.relative_humidity(dims, coordinates=coordinates)
result = disk.time_axis(self.path, "relative_humidity")
expect = 0
self.assertEqual(expect, result)
