def test_regression_not_supported(self):
x = numpy.zeros((100, 10))
y = numpy.empty(dtype=[('event', bool), ('time', float)], shape=100)
y['event'] = numpy.ones(100, dtype=bool)
y['time'] = numpy.arange(100, dtype=float)
ssvm = FastSurvivalSVM(rank_ratio=0, optimizer='simple')
self.assertRaisesRegex(ValueError,
"optimizer 'simple' does not implement regression objective",
ssvm.fit, x, y)
ssvm.set_params(optimizer='PRSVM')
self.assertRaisesRegex(ValueError,
"optimizer 'PRSVM' does not implement regression objective",
ssvm.fit, x, y)
def test_regression_not_supported(self):
x = numpy.zeros((100, 10))
y = Surv.from_arrays(numpy.ones(100, dtype=bool),
numpy.arange(100, dtype=float))
ssvm = FastSurvivalSVM(rank_ratio=0, optimizer='simple')
self.assertRaisesRegex(
ValueError,
"optimizer 'simple' does not implement regression objective",
ssvm.fit, x, y)
ssvm.set_params(optimizer='PRSVM')
self.assertRaisesRegex(
ValueError,
"optimizer 'PRSVM' does not implement regression objective",
ssvm.fit, x, y)
def test_rank_ratio_out_of_bounds(self):
x = numpy.zeros((100, 10))
y = Surv.from_arrays(numpy.ones(100, dtype=bool),
numpy.arange(100, dtype=float))
ssvm = FastSurvivalSVM(rank_ratio=-1)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=1.2)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=numpy.nan)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=numpy.inf)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
def test_rank_ratio_out_of_bounds(self):
x = numpy.zeros((100, 10))
y = numpy.empty(dtype=[('event', bool), ('time', float)], shape=100)
y['event'] = numpy.ones(100, dtype=bool)
y['time'] = numpy.arange(100, dtype=float)
ssvm = FastSurvivalSVM(rank_ratio=-1)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=1.2)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=numpy.nan)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
ssvm.set_params(rank_ratio=numpy.inf)
self.assertRaisesRegex(ValueError, r"rank_ratio must be in \[0; 1\]",
ssvm.fit, x, y)
