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Push out api and storage to fixture
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@eivindjahren
eivindjahren committed Oct 14, 2024
1 parent 372d5f6 commit 3427fa9
Showing 1 changed file with 130 additions and 138 deletions.
268 changes: 130 additions & 138 deletions tests/ert/unit_tests/gui/tools/plot/test_plot_api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,149 +176,141 @@ def test_plot_api_request_errors(api):
api.data_for_key(ensemble.id, "should_not_be_there")


def test_plot_api_handles_urlescape(tmp_path, monkeypatch):
@pytest.fixture
def api_and_storage(monkeypatch, tmp_path):
with open_storage(tmp_path / "storage", mode="w") as storage:
monkeypatch.setenv("ERT_STORAGE_NO_TOKEN", "yup")
monkeypatch.setenv("ERT_STORAGE_ENS_PATH", storage.path)
api = PlotApi()
key = "WBHP:46/3-7S"
date = datetime(year=2024, month=10, day=4)
experiment = storage.create_experiment(
parameters=[],
responses=[
SummaryConfig(
name="summary",
input_files=["CASE.UNSMRY", "CASE.SMSPEC"],
keys=[key],
)
],
observations={
"summary": polars.DataFrame(
{
"response_key": key,
"observation_key": "sumobs",
"time": polars.Series([date]).dt.cast_time_unit("ms"),
"observations": polars.Series([1.0], dtype=polars.Float32),
"std": polars.Series([1.0], dtype=polars.Float32),
}
)
},
)
ensemble = experiment.create_ensemble(ensemble_size=1, name="ensemble")
assert api.data_for_key(str(ensemble.id), key).empty
df = polars.DataFrame(
{
"response_key": [key],
"time": [polars.Series([date]).dt.cast_time_unit("ms")],
"values": [polars.Series([1.0], dtype=polars.Float32)],
}
)
df = df.explode("values", "time")
ensemble.save_response(
"summary",
df,
0,
)
assert api.data_for_key(str(ensemble.id), key).to_csv() == dedent(
"""\
Realization,2024-10-04
0,1.0
"""
)
assert api.observations_for_key([str(ensemble.id)], key).to_csv() == dedent(
"""\
,0
STD,1.0
OBS,1.0
key_index,2024-10-04 00:00:00
"""
)
if enkf._storage is not None:
enkf._storage.close()
enkf._storage = None
gc.collect()


def test_plot_api_handles_empty_gen_kw(tmp_path, monkeypatch):
with open_storage(tmp_path / "storage", mode="w") as storage:
monkeypatch.setenv("ERT_STORAGE_NO_TOKEN", "yup")
monkeypatch.setenv("ERT_STORAGE_ENS_PATH", storage.path)
api = PlotApi()
key = "gen_kw"
name = "<poro>"
experiment = storage.create_experiment(
parameters=[
GenKwConfig(
name=key,
forward_init=False,
update=False,
template_file=None,
output_file=None,
transform_function_definitions=[],
),
],
responses=[],
observations={},
)
ensemble = storage.create_ensemble(experiment.id, ensemble_size=10)
assert api.data_for_key(str(ensemble.id), key).empty
ensemble.save_parameters(
key,
1,
xr.Dataset(
yield api, storage
if enkf._storage is not None:
enkf._storage.close()
enkf._storage = None
gc.collect()


def test_plot_api_handles_urlescape(api_and_storage):
api, storage = api_and_storage
key = "WBHP:46/3-7S"
date = datetime(year=2024, month=10, day=4)
experiment = storage.create_experiment(
parameters=[],
responses=[
SummaryConfig(
name="summary",
input_files=["CASE.UNSMRY", "CASE.SMSPEC"],
keys=[key],
)
],
observations={
"summary": polars.DataFrame(
{
"values": ("names", [1.0]),
"transformed_values": ("names", [1.0]),
"names": [name],
"response_key": key,
"observation_key": "sumobs",
"time": polars.Series([date]).dt.cast_time_unit("ms"),
"observations": polars.Series([1.0], dtype=polars.Float32),
"std": polars.Series([1.0], dtype=polars.Float32),
}
)
},
)
ensemble = experiment.create_ensemble(ensemble_size=1, name="ensemble")
assert api.data_for_key(str(ensemble.id), key).empty
df = polars.DataFrame(
{
"response_key": [key],
"time": [polars.Series([date]).dt.cast_time_unit("ms")],
"values": [polars.Series([1.0], dtype=polars.Float32)],
}
)
df = df.explode("values", "time")
ensemble.save_response(
"summary",
df,
0,
)
assert api.data_for_key(str(ensemble.id), key).to_csv() == dedent(
"""\
Realization,2024-10-04
0,1.0
"""
)
assert api.observations_for_key([str(ensemble.id)], key).to_csv() == dedent(
"""\
,0
STD,1.0
OBS,1.0
key_index,2024-10-04 00:00:00
"""
)


def test_plot_api_handles_empty_gen_kw(api_and_storage):
api, storage = api_and_storage
key = "gen_kw"
name = "<poro>"
experiment = storage.create_experiment(
parameters=[
GenKwConfig(
name=key,
forward_init=False,
update=False,
template_file=None,
output_file=None,
transform_function_definitions=[],
),
)
assert api.data_for_key(str(ensemble.id), key + ":" + name).to_csv() == dedent(
"""\
Realization,0
1,1.0
"""
)
if enkf._storage is not None:
enkf._storage.close()
enkf._storage = None
gc.collect()


def test_plot_api_handles_non_existant_gen_kw(tmp_path, monkeypatch):
with open_storage(tmp_path / "storage", mode="w") as storage:
monkeypatch.setenv("ERT_STORAGE_NO_TOKEN", "yup")
monkeypatch.setenv("ERT_STORAGE_ENS_PATH", storage.path)
api = PlotApi()
experiment = storage.create_experiment(
parameters=[
GenKwConfig(
name="gen_kw",
forward_init=False,
update=False,
template_file=None,
output_file=None,
transform_function_definitions=[],
),
],
responses=[],
observations={},
)
ensemble = storage.create_ensemble(experiment.id, ensemble_size=10)
ensemble.save_parameters(
"gen_kw",
1,
xr.Dataset(
{
"values": ("names", [1.0]),
"transformed_values": ("names", [1.0]),
"names": ["key"],
}
],
responses=[],
observations={},
)
ensemble = storage.create_ensemble(experiment.id, ensemble_size=10)
assert api.data_for_key(str(ensemble.id), key).empty
ensemble.save_parameters(
key,
1,
xr.Dataset(
{
"values": ("names", [1.0]),
"transformed_values": ("names", [1.0]),
"names": [name],
}
),
)
assert api.data_for_key(str(ensemble.id), key + ":" + name).to_csv() == dedent(
"""\
Realization,0
1,1.0
"""
)


def test_plot_api_handles_non_existant_gen_kw(api_and_storage):
api, storage = api_and_storage
experiment = storage.create_experiment(
parameters=[
GenKwConfig(
name="gen_kw",
forward_init=False,
update=False,
template_file=None,
output_file=None,
transform_function_definitions=[],
),
)
assert api.data_for_key(str(ensemble.id), "gen_kw").empty
assert api.data_for_key(str(ensemble.id), "gen_kw:does_not_exist").empty
if enkf._storage is not None:
enkf._storage.close()
enkf._storage = None
gc.collect()
],
responses=[],
observations={},
)
ensemble = storage.create_ensemble(experiment.id, ensemble_size=10)
ensemble.save_parameters(
"gen_kw",
1,
xr.Dataset(
{
"values": ("names", [1.0]),
"transformed_values": ("names", [1.0]),
"names": ["key"],
}
),
)
assert api.data_for_key(str(ensemble.id), "gen_kw").empty
assert api.data_for_key(str(ensemble.id), "gen_kw:does_not_exist").empty

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