def test_in_daterange(data):
metadata = data["ch4"]["metadata"]
data = data["ch4"]["data"]
d = Datasource()
d._uuid = "test-id-123"
d.add_data(metadata=metadata, data=data, data_type="timeseries")
d.save()
expected_keys = [
"data/uuid/test-id-123/v1/2014-01-30-11:12:30+00:00_2014-11-30-11:23:30+00:00",
"data/uuid/test-id-123/v1/2015-01-30-11:12:30+00:00_2015-11-30-11:23:30+00:00",
"data/uuid/test-id-123/v1/2016-04-02-06:52:30+00:00_2016-11-02-12:54:30+00:00",
"data/uuid/test-id-123/v1/2017-02-18-06:36:30+00:00_2017-12-18-15:41:30+00:00",
"data/uuid/test-id-123/v1/2018-02-18-15:42:30+00:00_2018-12-18-15:42:30+00:00",
"data/uuid/test-id-123/v1/2019-02-03-17:38:30+00:00_2019-12-09-10:47:30+00:00",
"data/uuid/test-id-123/v1/2020-02-01-18:08:30+00:00_2020-12-01-22:31:30+00:00",
]
assert d.data_keys() == expected_keys
start = pd.Timestamp("2014-1-1")
end = pd.Timestamp("2014-2-1")
daterange = create_daterange_str(start=start, end=end)
dated_keys = d.keys_in_daterange_str(daterange=daterange)
assert dated_keys[0].split(
"/")[-1] == "2014-01-30-11:12:30+00:00_2014-11-30-11:23:30+00:00"
def test_add_data(data):
d = Datasource()
metadata = data["ch4"]["metadata"]
ch4_data = data["ch4"]["data"]
assert ch4_data["ch4"][0] == pytest.approx(1959.55)
assert ch4_data["ch4_variability"][0] == pytest.approx(0.79)
assert ch4_data["ch4_number_of_observations"][0] == pytest.approx(26.0)
d.add_data(metadata=metadata, data=ch4_data, data_type="timeseries")
d.save()
bucket = get_local_bucket()
data_chunks = [
Datasource.load_dataset(bucket=bucket, key=k) for k in d.data_keys()
]
# Now read it out and make sure it's what we expect
combined = xr.concat(data_chunks, dim="time")
assert combined.equals(ch4_data)
expected_metadata = {
"site": "bsd",
"instrument": "picarro",
"sampling_period": "60",
"inlet": "248m",
"port": "9",
"type": "air",
"network": "decc",
"species": "ch4",
"scale": "wmo-x2004a",
"long_name": "bilsdale",
"data_owner": "simon o'doherty",
"data_owner_email": "*****@*****.**",
"inlet_height_magl": "248m",
"comment": "cavity ring-down measurements. output from gcwerks",
"source": "in situ measurements of air",
"conventions": "cf-1.6",
"calibration_scale": "wmo-x2004a",
"station_longitude": -1.15033,
"station_latitude": 54.35858,
"station_long_name": "bilsdale, uk",
"station_height_masl": 380.0,
"data_type": "timeseries",
}
assert d.metadata() == expected_metadata
def test_from_data(data):
d = Datasource()
metadata = data["ch4"]["metadata"]
ch4_data = data["ch4"]["data"]
d.add_data(metadata=metadata, data=ch4_data, data_type="timeseries")
d.save()
obj_data = d.to_data()
bucket = get_local_bucket()
# Create a new object with the data from d
d_2 = Datasource.from_data(bucket=bucket, data=obj_data, shallow=False)
metadata = d_2.metadata()
assert metadata["site"] == "bsd"
assert metadata["instrument"] == "picarro"
assert metadata["sampling_period"] == "60"
assert metadata["inlet"] == "248m"
assert sorted(d_2.data_keys()) == sorted(d.data_keys())
assert d_2.metadata() == d.metadata()