def test_builds_instance_with_proper_args(self):
dummy = u.build(Dummy, a=3, b=6)
assert dummy.a == 3
assert dummy.b == 6
dummy = u.build(Dummy, a=3)
assert dummy.a == 3
assert dummy.b == 5
def make_specialized_selector(name, n_features, **kwargs):
"""Create a selector by name (gmm, outlier or auto)"""
if name == 'auto':
name = 'gmm' if n_features > 250 else 'outlier'
filter_cls = {
'gmm': HighAbundanceAndVarianceSelector,
'outlier': OutlierAbundanceAndVarianceSelector,
'none': NoSelector,
}[name]
return build(filter_cls, **kwargs)
def make_specialized_selector(name, n_features, **kwargs):
"""Create a selector by name (``gmm``, ``outlier``, ``none`` or ``auto``)
``auto`` switches to ``gmm`` if there is more than 250 features, ``outlier`` below.
"""
if name == "auto":
name = "gmm" if n_features > 250 else "outlier"
filter_cls = {
"gmm": HighAbundanceAndVarianceSelector,
"outlier": OutlierAbundanceAndVarianceSelector,
"none": NoSelector,
}[name]
return build(filter_cls, **kwargs)
def main():
data, config, destination, xy = sc.initialize()
logging.info('Workspace initialized.')
logging.info('Scenario configuration: {0}'.format(config))
fast = _fast_kmeans(**config)
full = _full_kmeans(**config)
divik_config = {'kmeans': full, 'fast_kmeans': fast, **config}
divik = build(DiviK, **divik_config)
logging.info("Launching experiment.")
try:
divik.fit(data)
except Exception as ex:
logging.error("Failed with exception.")
logging.error(repr(ex))
raise
save(data, divik, destination, xy)
def test_builds_with_too_many_args(self):
dummy = u.build(Dummy, a=3, c=4)
assert dummy.a == 3
assert dummy.b == 5