def test_has_a_time_range_encompassing_all_variables(self):
ds = Dataset(name="test",
variables={
'v1': make_simple_var(10., 100.),
'v2': make_simple_var(30., 40.),
'v3': make_simple_var(60., 500.)
},
meta={})
self.assertEqual(DateTimeRange(10., 499.), ds.time_range())
def test_len_gives_variable_count(self):
ds = Dataset(name="test", variables={}, meta={})
self.assertEqual(len(ds), 0)
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
self.assertEqual(len(ds), 3)
def test_is_plotable(self):
try:
import matplotlib.pyplot as plt
ds = Dataset(name="test",
variables={
'v1': make_simple_var(10., 100.),
'v2': make_simple_var(30., 40.),
'v3': make_simple_var(60., 500.)
},
meta={})
ax = ds.plot()
self.assertIsNotNone(ax)
except ImportError:
self.skipTest("Can't import matplotlib")
def test_returns_false_if_variable_name_is_not_in_dataset(self):
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
self.assertNotIn('Not in', ds)
def test_returns_true_if_variable_name_is_in_dataset(self):
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
for v in ds:
self.assertIn(v, ds)
def test_can_iterate_variables(self):
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
var_list = [v for v in ds]
self.assertListEqual(['v1', 'v2', 'v3'], var_list)
def test_has_str_repr(self):
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
repr = str(ds)
self.assertIn('v1', repr)
self.assertIn('v2', repr)
def get_dataset(self, dataset_id: str or AMDADatasetIndex, start: str
or datetime, stop: str or datetime, **kwargs) -> Dataset:
"""Get dataset contents. Returns list of SpeasyVariable objects, one for each
parameter in the dataset.
Parameters
----------
dataset_id: str or AMDADatasetIndex
dataset id
start: str or datetime
desired data start
stop: str or datetime
desired data end
Returns
-------
Dataset
dataset content as a collection of SpeasyVariable
Examples
--------
>>> import speasy as spz
>>> import datetime
>>> dataset = spz.amda.get_dataset("ace-imf-all", datetime.datetime(2000,1,1), datetime.datetime(2000,1,2))
>>> dataset
<Dataset: final / prelim
variables: ['|b|', 'b_gse', 'b_gsm']
time range: <DateTimeRange: 2000-01-01T00:00:11 -> 2000-01-01T23:59:55>
"""
# get list of parameters for this dataset
dataset_id = to_xmlid(dataset_id)
name = flat_inventories.amda.datasets[dataset_id].name
meta = {
k: v
for k, v in
flat_inventories.amda.datasets[dataset_id].__dict__.items()
if not isinstance(v, AMDAIndex)
}
parameters = self.list_parameters(dataset_id)
return Dataset(name=name,
variables={
p.name: self.get_parameter(p, start, stop, **kwargs)
for p in parameters
},
meta=meta)
def test_has_no_time_range_when_empty_or_has_empty_vars(self):
ds = Dataset(name="test", variables={}, meta={})
self.assertIsNone(ds.time_range())
ds = Dataset(name="test",
variables={
'v1': SpeasyVariable(),
'v2': SpeasyVariable(),
'v3': SpeasyVariable()
},
meta={})
self.assertIsNone(ds.time_range())
def test_can_be_indexed_by_variable_name(self):
ds = Dataset(name="test", variables={"v": SpeasyVariable()}, meta={})
self.assertIs(type(ds['v']), SpeasyVariable)
def test_raises_if_given_variables_is_not_a_dict_of_variables(self):
with self.assertRaises(TypeError):
ds = Dataset(name='Should raise',
variables={'this is not a var': 10.},
meta={})
def test_accepts_a_dict_of_variables(self):
ds = Dataset(name="test", variables={"v": SpeasyVariable()}, meta={})
self.assertEqual(len(ds), 1)
self.assertEqual("test", ds.name)