def test_CartesianData():
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = CartesianData()
raw = (0, 1)
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b[0] == 0
assert b[1] == 1
raw = (0, 1, -1)
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b[0] == 0
assert b[1] == 1
assert b[2] == -1
raw = (0, 1, -1, 1)
with pytest.raises(ValueError):
test.get_data(raw, meta)
def test_LineTable_auto_plot(tmpdir):
velocity = [float(x) for x in range(10)]
thrust = [2 * float(x) for x in range(10)]
power = [3 * float(x) for x in range(10)]
raw = {"Velocity": velocity, "Thrust": thrust, "Power": power}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["Velocity", "Thrust", "Power"],
"units": ["m/s", "N", "W"]
})
test = LineTable()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(raw, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_TableDataColumn_auto_db(mocker):
idx = range(1000)
values = np.random.rand(len(idx))
mock_dict = {"index": idx,
"a": values,
"b": values}
mock_df = pd.DataFrame(mock_dict)
mocker.patch('dtocean_core.data.definitions.get_table_df',
return_value=mock_df,
autospec=True)
meta = CoreMetaData({"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["index", "a", "b"],
"tables": ["mock.mock", "index", "a", "b"]})
test = TableDataColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert "a" in result
assert len(result) == len(idx)
def test_NumpyLine_auto_plot(tmpdir):
coarse_sample = np.linspace(0., 2 * np.pi, num=5)
raw = zip(coarse_sample, np.sin(coarse_sample))
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["x", "f(x)"],
"units": ["m", "m^{2}"]
})
test = NumpyLine()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(raw, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_Histogram_auto_plot(tmpdir):
bin_values = [1, 2, 3, 4, 5]
bin_separators = [0, 2, 4, 6, 8, 10]
raw = (bin_values, bin_separators)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["x", "f(x)"],
"units": [None, "m^{2}"]
})
test = Histogram()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(raw, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_TimeTable_auto_plot(tmpdir):
dates = []
dt = datetime(2010, 12, 01)
end = datetime(2010, 12, 02, 23, 59, 59)
step = timedelta(seconds=3600)
while dt < end:
dates.append(dt)
dt += step
values = np.random.rand(len(dates))
raw = {"DateTime": dates, "a": values, "b": values}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["a", "b"],
"units": ["kg", None]
})
test = TimeTable()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(raw, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_NumpyLineArray_auto_db_none(mocker):
mock_list = [None]
mocker.patch('dtocean_core.data.definitions.get_one_from_column',
return_value=mock_list,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["x", "f(x)"],
"units": ["m", "m^{2}"],
"tables": ["mock.mock", "f_x"]
})
test = NumpyLineArray()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_PolygonDictColumn_auto_db_empty(mocker):
mock_lists = [[], []]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "description", "boundary"]
})
test = PolygonDictColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_CartesianDictColumn_auto_db(mocker):
raws = [{"a": (0, 1), "b": (1, 2)}, {"a": (0, 1, -1), "b": (1, 2, -2)}]
for raw in raws:
mock_lists = [raw.keys(), raw.values()]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "name", "position"]
})
test = CartesianDictColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert result["a"][0] == 0
assert result["a"][1] == 1
def test_PolygonDict_auto_file_output_bad_data(tmpdir):
test_path = tmpdir.mkdir("sub").join("test{}".format(".csv"))
test_path_str = str(test_path)
raw = {
"block 1": [(0., 0.), (1., 1.), (2., 2.)],
"block 2": [(10., 10.), (11., 11.), (12., 12.)]
}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = PolygonDict()
fout_factory = InterfaceFactory(AutoFileOutput)
FOutCls = fout_factory(meta, test)
fout = FOutCls()
fout._path = test_path_str
fout.data.result = raw
with pytest.raises(TypeError):
fout.connect()
def test_PolygonDict_auto_plot(tmpdir):
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
raw = {
"block 1": [(0., 0., 0.), (1., 1., 1.), (2., 2., 2.)],
"block 2": [(10., 10., 10.), (11., 11., 11.), (12., 12., 12.)]
}
test = PolygonDict()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(raw, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_TimeSeries():
dates = []
dt = datetime(2010, 12, 01)
end = datetime(2010, 12, 02, 23, 59, 59)
step = timedelta(seconds=3600)
while dt < end:
dates.append(dt)
dt += step
values = np.random.rand(len(dates))
raw = [(d, v) for d, v in zip(dates, values)]
meta = CoreMetaData({"identifier": "test",
"structure": "test",
"title": "test",
"labels": ['mass'],
"units": ["kg"]})
test = TimeSeries()
a = test.get_data(raw, meta)
b = test.get_value(a)
assert len(b) == len(dates)
assert len(b.resample('D').mean()) == 2
def test_TimeSeriesColumn_auto_db_empty(mocker):
mock_dict = {"date": [],
"time": [],
"mass": []}
mock_df = pd.DataFrame(mock_dict)
mocker.patch('dtocean_core.data.definitions.get_table_df',
return_value=mock_df,
autospec=True)
meta = CoreMetaData({"identifier": "test",
"structure": "test",
"title": "test",
"labels": ['mass'],
"units": ["kg"],
"tables": ["mock.mock", "date", "time", "mass"]})
test = TimeSeriesColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_XSet3D():
raw = {
"values": {
"a": np.random.randn(2, 3, 1),
"b": np.random.randn(2, 3, 1)
},
"coords": [['a', 'b'], [-2, 0, 2], [datetime(2010, 12, 01)]]
}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ['x', 'y', 't', 'a', 'b'],
"units": [None, 'm', 's', 'POWER!', None]
})
test = XSet3D()
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b["a"].shape == (2, 3, 1)
assert b["a"].units == 'POWER!'
assert b.t.units == 's'
def test_HistogramDict_auto_plot(tmpdir):
test_data_one = np.random.random(10)
test_data_two = np.random.random(10)
values_one, bins_one = np.histogram(test_data_one)
values_two, bins_two = np.histogram(test_data_two)
values_dict = {
"test_one": (values_one, bins_one),
"test_two": (values_two, bins_two)
}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = HistogramDict()
fout_factory = InterfaceFactory(AutoPlot)
PlotCls = fout_factory(meta, test)
plot = PlotCls()
plot.data.result = test.get_data(values_dict, meta)
plot.meta.result = meta
plot.connect()
assert len(plt.get_fignums()) == 1
plt.close("all")
def test_CartesianDict():
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = CartesianDict()
raw = {"a": (0, 1), "b": (1, 2)}
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b["a"][0] == 0
assert b["a"][1] == 1
raw = {"a": (0, 1, -1), "b": (1, 2, -2)}
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b["a"][0] == 0
assert b["a"][1] == 1
assert b["a"][2] == -1
raw = {"a": (0, 1, -1, 1)}
with pytest.raises(ValueError):
test.get_data(raw, meta)
def test_HistogramDict():
test_data_one = np.random.random(10)
test_data_two = np.random.random(10)
values_one, bins_one = np.histogram(test_data_one)
values_two, bins_two = np.histogram(test_data_two)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
values_dict = {
"test_one": (values_one, bins_one),
"test_two": (values_two, bins_two)
}
test = HistogramDict()
a = test.get_data(values_dict, meta)
b = test.get_value(a)
assert len(b["test_one"]["values"]) == len(values_one)
assert len(b["test_two"]["bins"]) == len(b["test_two"]["values"]) + 1
def test_PolygonDataColumn_auto_db(mocker):
raws = [
WKTElement("POLYGON ((0 0, 1 0, 1 1, 0 0))"),
WKTElement("POLYGON ((0 0 0, 1 0 0, 1 1 0, 0 0 0))")
]
for raw in raws:
mock_list = [raw]
mocker.patch('dtocean_core.data.definitions.get_one_from_column',
return_value=mock_list,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "position"]
})
test = PolygonDataColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert result.exterior.coords[0][0] == 0.
assert result.exterior.coords[1][0] == 1.
def test_TimeTable():
dates = []
dt = datetime(2010, 12, 01)
end = datetime(2010, 12, 02, 23, 59, 59)
step = timedelta(seconds=3600)
while dt < end:
dates.append(dt)
dt += step
values = np.random.rand(len(dates))
raw = {"DateTime": dates, "a": values, "b": values}
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["a", "b"],
"units": ["kg", None]
})
test = TimeTable()
a = test.get_data(raw, meta)
b = test.get_value(a)
assert "a" in b
assert len(b) == len(dates)
assert len(b.resample('D').mean()) == 2
def test_PolygonData():
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
raw = [(0., 0.), (1., 1.), (2., 2.)]
test = PolygonData()
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b.exterior.coords[0][0] == 0.
assert b.exterior.coords[1][1] == 1.
raw = [(0., 0., 0.), (1., 1., 1.), (2., 2., 2.)]
a = test.get_data(raw, meta)
b = test.get_value(a)
assert b.exterior.coords[0][0] == 0.
assert b.exterior.coords[1][1] == 1.
assert b.exterior.coords[2][2] == 2.
raw = [(0., 0., 0., 0.), (1., 1., 1., 1.), (2., 2., 2., 2.)]
with pytest.raises(ValueError):
test.get_data(raw, meta)
def test_NumpyLineColumn_auto_db(mocker):
coarse_sample = np.linspace(0., 2 * np.pi, num=5)
mock_lists = [coarse_sample, list(np.sin(coarse_sample))]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["x", "f(x)"],
"units": ["m", "m^{2}"],
"tables": ["mock.mock", "x", "f_x"]
})
test = NumpyLineColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert max(result[:, 1]) == 1
def test_PolygonDataColumn_auto_db_none(mocker):
mock_list = [None]
mocker.patch('dtocean_core.data.definitions.get_one_from_column',
return_value=mock_list,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "position"]
})
test = PolygonDataColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_HistogramColumn_auto_db_none(mocker):
mock_lists = [[None, None], [None, None], [None, None]]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier":
"test",
"structure":
"test",
"title":
"test",
"labels": ["x", "f(x)"],
"units": [None, "m^{2}"],
"tables": ["mock.mock", "values", "lower_bounds", "upper_bounds"]
})
test = HistogramColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_CartesianListDict():
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = CartesianListDict()
raw = {"a": [(0, 1), (1, 2)], "b": [(3, 4), (4, 5)]}
a = test.get_data(raw, meta)
b = test.get_value(a)
assert len(b) == 2
assert b["a"][0][0] == 0
assert b["a"][0][1] == 1
raw = {"a": [(0, 1, -1), (1, 2, -2)], "b": [(3, 4, -3), (4, 5, -5)]}
a = test.get_data(raw, meta)
b = test.get_value(a)
assert len(b) == 2
assert b["a"][0][0] == 0
assert b["a"][0][1] == 1
assert b["a"][0][2] == -1
raw = {"a": [(0, 1, -1, 1)]}
with pytest.raises(ValueError):
test.get_data(raw, meta)
def test_LineTableColumn_auto_db_none(mocker):
thrust = [2 * float(x) for x in range(10)]
power = [3 * float(x) for x in range(10)]
mock_dict = {"velocity": [None] * 10, "thrust": thrust, "power": power}
mock_df = pd.DataFrame(mock_dict)
mocker.patch('dtocean_core.data.definitions.get_table_df',
return_value=mock_df,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["Velocity", "Thrust", "Power"],
"units": ["m/s", "N", "W"],
"tables": ["mock.mock", "velocity", "thrust", "power"]
})
test = LineTableColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_SimpleDictColumn_auto_db(mocker):
raw = {"a": 0, "b": 1}
mock_lists = [raw.keys(), raw.values()]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "name", "position"],
"types": ["float"]
})
test = SimpleDictColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert result["a"] == 0
assert result["b"] == 1
def test_DateTimeDict_auto_file_input_bad_header(mocker):
df_dict = {"Wrong": [1], "Headers": [1]}
df = pd.DataFrame(df_dict)
mocker.patch('dtocean_core.data.definitions.pd.read_excel',
return_value=df,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test"
})
test = DateTimeDict()
fin_factory = InterfaceFactory(AutoFileInput)
FInCls = fin_factory(meta, test)
fin = FInCls()
fin._path = "file.xlsx"
with pytest.raises(ValueError):
fin.connect()
def test_SimpleDictColumn_auto_db_none(mocker):
mock_lists = [[None, None], [None, None]]
mocker.patch('dtocean_core.data.definitions.get_all_from_columns',
return_value=mock_lists,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "position"],
"types": ["float"]
})
test = SimpleDictColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_TableDataColumn_auto_db_none(mocker):
mock_dict = {"index": [None, None],
"a": [None, None],
"b": [None, None]}
mock_df = pd.DataFrame(mock_dict)
mocker.patch('dtocean_core.data.definitions.get_table_df',
return_value=mock_df,
autospec=True)
meta = CoreMetaData({"identifier": "test",
"structure": "test",
"title": "test",
"labels": ["index", "a", "b"],
"tables": ["mock.mock", "index", "a", "b"]})
test = TableDataColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
assert query.data.result is None
def test_CartesianDataColumn_auto_db(mocker):
raws = [(0, 1), (0, 1, -1)]
for raw in raws:
mock_list = [raw]
mocker.patch('dtocean_core.data.definitions.get_one_from_column',
return_value=mock_list,
autospec=True)
meta = CoreMetaData({
"identifier": "test",
"structure": "test",
"title": "test",
"tables": ["mock.mock", "position"]
})
test = CartesianDataColumn()
query_factory = InterfaceFactory(AutoQuery)
QueryCls = query_factory(meta, test)
query = QueryCls()
query.meta.result = meta
query.connect()
result = test.get_data(query.data.result, meta)
assert result[0] == 0
assert result[1] == 1
