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cached the algorithms in pytest #104

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cached the algorithms in pytest #104

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40 changes: 34 additions & 6 deletions tests/IVIMmodels/unit_tests/test_ivim_fit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ def tolerances_helper(tolerances, data):
tolerances["atol"] = tolerances.get("atol", {"f": 2e-1, "D": 5e-4, "Dp": 4e-2})
return tolerances


def data_ivim_fit_saved():
# Find the algorithms from algorithms.json
file = pathlib.Path(__file__)
Expand All @@ -45,8 +46,8 @@ def data_ivim_fit_saved():
bvals = all_data.pop('config')
bvals = bvals['bvalues']
first=True
for name, data in all_data.items():
for algorithm in algorithms:
for algorithm in algorithms:
for name, data in all_data.items():
algorithm_dict = algorithm_information.get(algorithm, {})
xfail = {"xfail": name in algorithm_dict.get("xfail_names", {}),
"strict": algorithm_dict.get("xfail_names", {}).get(name, True)}
Expand All @@ -59,15 +60,38 @@ def data_ivim_fit_saved():
first = False
yield name, bvals, data, algorithm, xfail, kwargs, tolerances, skiptime


def make_hashable(obj):
if isinstance(obj, dict):
return tuple(sorted((k, make_hashable(v)) for k, v in obj.items()))
elif isinstance(obj, (list, tuple)):
return tuple(make_hashable(i) for i in obj)
else:
return obj


@pytest.fixture(scope="module")
def algorithm_cache():
cache = {}

def get_instance(algorithm, kwargs):
hashable_key = (algorithm, make_hashable(kwargs))
if hashable_key not in cache:
cache[hashable_key] = OsipiBase(algorithm=algorithm, **kwargs)
return cache[hashable_key]

return get_instance


@pytest.mark.parametrize("name, bvals, data, algorithm, xfail, kwargs, tolerances, skiptime", data_ivim_fit_saved())
def test_ivim_fit_saved(name, bvals, data, algorithm, xfail, kwargs, tolerances,skiptime, request, record_property):
def test_ivim_fit_saved(name, bvals, data, algorithm, xfail, kwargs, tolerances, skiptime, request, record_property, algorithm_cache):
if xfail["xfail"]:
mark = pytest.mark.xfail(reason="xfail", strict=xfail["strict"])
request.node.add_marker(mark)
signal = signal_helper(data["data"])
tolerances = tolerances_helper(tolerances, data)
fit = algorithm_cache(algorithm, kwargs)
start_time = time.time() # Record the start time
fit = OsipiBase(algorithm=algorithm, **kwargs)
fit_result = fit.osipi_fit(signal, bvals)
elapsed_time = time.time() - start_time # Calculate elapsed time
def to_list_if_needed(value):
Expand Down Expand Up @@ -153,10 +177,14 @@ def bound_input():


@pytest.mark.parametrize("name, bvals, data, algorithm, xfail, kwargs, tolerances", bound_input())
def test_bounds(name, bvals, data, algorithm, xfail, kwargs, tolerances, request):
def test_bounds(name, bvals, data, algorithm, xfail, kwargs, tolerances, request, algorithm_cache):
if xfail["xfail"]:
mark = pytest.mark.xfail(reason="xfail", strict=xfail["strict"])
request.node.add_marker(mark)
bounds = ([0.0008, 0.2, 0.01, 1.1], [0.0012, 0.3, 0.02, 1.3])
# deliberately have silly bounds to see whether they are used
fit = OsipiBase(algorithm=algorithm, bounds=bounds, initial_guess = [0.001, 0.25, 0.015, 1.2], **kwargs)
extended_kwargs = {**kwargs, "bounds": bounds, "initial_guess": [0.001, 0.25, 0.015, 1.2]}
fit = algorithm_cache(algorithm, extended_kwargs)
if fit.use_bounds:
signal = signal_helper(data["data"])
fit_result = fit.osipi_fit(signal, bvals)
Expand Down