def test_wrapped_indicator(tas_series):
def indice(tas, tas2=None, thresh=0, freq="YS"):
if tas2 is None:
out = tas < thresh
else:
out = tas < tas2
out = out.resample(time="YS").sum()
out.attrs["units"] = "days"
return out
ind1 = Daily(
realm="atmos",
identifier="test_ind1",
nvar=1,
units="days",
compute=wrapped_partial(indice, tas2=None),
)
ind2 = Daily(
realm="atmos",
identifier="test_ind2",
nvar=2,
units="days",
compute=wrapped_partial(indice, thresh=None),
)
tas = tas_series(np.arange(366), start="2000-01-01")
tas2 = tas_series(1 + np.arange(366), start="2000-01-01")
assert ind2(tas, tas2) == 366
assert ind1(tas, thresh=1111) == 366
def test_resamplingIndicator_new_error():
with pytest.raises(ValueError,
match="ResamplingIndicator require a 'freq'"):
Daily(
realm="atmos",
identifier="multiopt",
cf_attrs=[dict(units="K")],
module="test",
compute=multioptvar_compute,
)
def test_indicator_from_dict():
d = dict(
realm="atmos",
output=dict(
var_name="tmean{thresh}",
units="K",
long_name="{freq} mean surface temperature",
standard_name="{freq} mean temperature",
cell_methods=[{
"time": "mean within days"
}],
),
index_function=dict(
name="thresholded_statistics",
parameters=dict(
threshold={
"data": {
"thresh": None
},
"description": "A threshold temp"
},
condition={"data": "`<"},
reducer={"data": "mean"},
),
),
input={"data": "tas"},
)
ind = Daily.from_dict(d, identifier="tmean", module="test")
assert ind.realm == "atmos"
# Parameters metadata modification
assert ind.parameters["threshold"]["description"] == "A threshold temp"
# Injection of paramters
assert "condition" in ind.compute._injected
# Placeholders were translated to name in signature
assert ind.cf_attrs[0]["var_name"] == "tmean{threshold}"
# Default value for input variable injected and meta injected
assert ind._sig.parameters["data"].default == "tas"
assert ind.parameters["data"]["units"] == "[temperature]"
# Cf checks were generated
assert ind.cfcheck is not Daily.cfcheck
def test_indicator_from_dict():
d = dict(
realm="atmos",
cf_attrs=dict(
var_name="tmean{threshold}",
units="K",
long_name="{freq} mean surface temperature",
standard_name="{freq} mean temperature",
cell_methods=[{
"time": "mean within days"
}],
),
compute="thresholded_statistics",
parameters=dict(
threshold={"description": "A threshold temp"},
condition="<",
reducer="mean",
),
input={"data": "tas"},
)
ind = Daily.from_dict(d, identifier="tmean", module="test")
assert ind.realm == "atmos"
# Parameters metadata modification
assert ind.parameters["threshold"].description == "A threshold temp"
# Injection of paramters
assert ind.injected_parameters["condition"] == "<"
# Default value for input variable injected and meta injected
assert ind._variable_mapping["data"] == "tas"
assert signature(ind).parameters["tas"].default == "tas"
assert ind.parameters["tas"].units == "K"
# Wrap a multi-output ind
d = dict(base="wind_speed_from_vector")
ind = Indicator.from_dict(d, identifier="wsfv", module="test")
fire_weather_indexes = Daily(
_nvar=4,
identifier="fwi",
realm="atmos",
var_name=["dc", "dmc", "ffmc", "isi", "bui", "fwi"],
standard_name=[
"drought_code",
"duff_moisture_code",
"fine_fuel_moisture_code",
"initial_spread_index",
"buildup_index",
"fire_weather_index",
],
long_name=[
"Drought Code",
"Duff Moisture Code",
"Fine Fuel Moisture Code",
"Initial Spread Index",
"Buildup Index",
"Fire Weather Index",
],
description=[
"Numeric rating of the average moisture content of deep, compact organic layers. Computed with start up method {start_up_mode}",
"Numeric rating of the average moisture content of loosely compacted organic layers of moderate depth. Computed with start up method {start_up_mode}",
"Numeric rating of the average moisture content of litter and other cured fine fuels. Computed with start up method {start_up_mode}",
"Numeric rating of the expected rate of fire spread.",
"Numeric rating of the total amount of fuel available for combustion.",
"Numeric rating of fire intensity.",
],
units="",
compute=indices.fire_weather_indexes,
missing="skip",
)
def test_indicator_errors():
def func(data: xr.DataArray, thresh: str = "0 degC", freq: str = "YS"):
return data
doc = [
"The title",
"",
" The abstract",
"",
" Parameters",
" ----------",
" data : xr.DataArray",
" A variable.",
" thresh : str",
" A threshold",
" freq : str",
" The resampling frequency.",
"",
" Returns",
" -------",
" xr.DataArray, [K]",
" An output",
]
func.__doc__ = "\n".join(doc)
d = dict(
realm="atmos",
cf_attrs=dict(
var_name="tmean{threshold}",
units="K",
long_name="{freq} mean surface temperature",
standard_name="{freq} mean temperature",
cell_methods=[{
"time": "mean within days"
}],
),
compute=func,
input={"data": "tas"},
)
ind = Daily(identifier="indi", module="test", **d)
with pytest.raises(AttributeError, match="`identifier` has not been set"):
Daily(**d)
d["identifier"] = "bad_indi"
d["module"] = "test"
bad_doc = doc[:12] + [" extra: bool", " Woupsi"] + doc[12:]
func.__doc__ = "\n".join(bad_doc)
with pytest.raises(ValueError, match="Malformed docstring"):
Daily(**d)
func.__doc__ = "\n".join(doc)
d["parameters"] = {}
d["parameters"]["thresh"] = "1 degK"
d["parameters"]["extra"] = "woopsi again"
with pytest.raises(ValueError,
match="Parameter 'extra' was passed but it does"):
Daily(**d)
del d["parameters"]["extra"]
d["input"]["data"] = "3nsd6sk72"
with pytest.raises(ValueError,
match="Compute argument data was mapped to"):
Daily(**d)
d2 = dict(input={"tas": "sfcWind"})
with pytest.raises(ValueError,
match="When changing the name of a variable by"):
ind.__class__(**d2)
del d["input"]
with pytest.raises(ValueError,
match="variable data is missing expected units"):
Daily(**d)
d["parameters"]["thresh"] = {"units": "K"}
d["realm"] = "mercury"
d["input"] = {"data": "tasmin"}
with pytest.raises(AttributeError,
match="Indicator's realm must be given as one"):
Daily(**d)
def func(data: xr.DataArray, thresh: str = "0 degC"):
return data
func.__doc__ = "\n".join(doc[:10] + doc[12:])
d = dict(
realm="atmos",
cf_attrs=dict(
var_name="tmean{threshold}",
units="K",
long_name="{freq} mean surface temperature",
standard_name="{freq} mean temperature",
cell_methods=[{
"time": "mean within days"
}],
),
compute=func,
input={"data": "tas"},
)
with pytest.raises(ValueError,
match="ResamplingIndicator require a 'freq'"):
ind = Daily(identifier="indi", module="test", **d)
def test_multiindicator(tas_series):
tas = tas_series(np.arange(366), start="2000-01-01")
tmin, tmax = multiTemp(tas, freq="YS")
assert tmin[0] == tas.min()
assert tmax[0] == tas.max()
assert tmin.attrs["standard_name"] == "Min temp"
assert tmin.attrs["description"] == "Grouped computation of tmax and tmin"
assert tmax.attrs["description"] == "Grouped computation of tmax and tmin"
assert multiTemp.units == ["K", "K"]
# Attrs passed as keywords - together
ind = Daily(
realm="atmos",
identifier="minmaxtemp2",
cf_attrs=[
dict(
var_name="tmin",
units="K",
standard_name="Min temp",
description="Grouped computation of tmax and tmin",
),
dict(
var_name="tmax",
units="K",
description="Grouped computation of tmax and tmin",
),
],
compute=multitemp_compute,
)
tmin, tmax = ind(tas, freq="YS")
assert tmin[0] == tas.min()
assert tmax[0] == tas.max()
assert tmin.attrs["standard_name"] == "Min temp"
assert tmin.attrs["description"] == "Grouped computation of tmax and tmin"
assert tmax.attrs["description"] == "Grouped computation of tmax and tmin"
with pytest.raises(ValueError, match="Output #2 is missing a var_name!"):
ind = Daily(
realm="atmos",
identifier="minmaxtemp2",
cf_attrs=[
dict(
var_name="tmin",
units="K",
),
dict(units="K", ),
],
compute=multitemp_compute,
)
# Attrs passed as keywords - individually
ind = Daily(
realm="atmos",
identifier="minmaxtemp3",
var_name=["tmin", "tmax"],
units="K",
standard_name=["Min temp", ""],
description="Grouped computation of tmax and tmin",
compute=multitemp_compute,
)
tmin, tmax = ind(tas, freq="YS")
assert tmin[0] == tas.min()
assert tmax[0] == tas.max()
assert tmin.attrs["standard_name"] == "Min temp"
assert tmin.attrs["description"] == "Grouped computation of tmax and tmin"
assert tmax.attrs["description"] == "Grouped computation of tmax and tmin"
assert ind.units == ["K", "K"]
# All must be the same length
with pytest.raises(ValueError, match="Attribute var_name has 2 elements"):
ind = Daily(
realm="atmos",
identifier="minmaxtemp3",
var_name=["tmin", "tmax"],
units="K",
standard_name=["Min temp"],
description="Grouped computation of tmax and tmin",
compute=uniindpr_compute,
)
ind = Daily(
realm="atmos",
identifier="minmaxtemp4",
var_name=["tmin", "tmax"],
units="K",
standard_name=["Min temp", ""],
description="Grouped computation of tmax and tmin",
compute=uniindtemp_compute,
)
with pytest.raises(ValueError,
match="Indicator minmaxtemp4 was wrongly defined"):
tmin, tmax = ind(tas, freq="YS")
freq: str = "YS"):
"""Docstring"""
out = da - convert_units_to(thresh, da)
out = out.resample(time=freq).mean()
out.attrs["units"] = da.units
return out
uniIndTemp = Daily(
realm="atmos",
identifier="tmin",
module="test",
cf_attrs=[
dict(
var_name="tmin{thresh}",
units="K",
long_name="{freq} mean surface temperature",
standard_name="{freq} mean temperature",
cell_methods="time: mean within {freq:noun}",
another_attr="With a value.",
)
],
compute=uniindtemp_compute,
)
@declare_units(da="[precipitation]")
def uniindpr_compute(da: xr.DataArray, freq: str):
"""Docstring"""
return da.resample(time=freq).mean(keep_attrs=True)