672 lines
21 KiB
Python
672 lines
21 KiB
Python
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from numbers import Integral, Real
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import numpy as np
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from scipy.sparse import csr_matrix
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import pytest
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from sklearn.base import BaseEstimator
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from sklearn.model_selection import LeaveOneOut
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from sklearn.utils import deprecated
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from sklearn.utils._param_validation import Hidden
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from sklearn.utils._param_validation import Interval
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from sklearn.utils._param_validation import Options
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from sklearn.utils._param_validation import StrOptions
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from sklearn.utils._param_validation import _ArrayLikes
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from sklearn.utils._param_validation import _Booleans
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from sklearn.utils._param_validation import _Callables
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from sklearn.utils._param_validation import _CVObjects
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from sklearn.utils._param_validation import _InstancesOf
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from sklearn.utils._param_validation import _MissingValues
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from sklearn.utils._param_validation import _PandasNAConstraint
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from sklearn.utils._param_validation import _IterablesNotString
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from sklearn.utils._param_validation import _NoneConstraint
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from sklearn.utils._param_validation import _RandomStates
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from sklearn.utils._param_validation import _SparseMatrices
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from sklearn.utils._param_validation import _VerboseHelper
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from sklearn.utils._param_validation import HasMethods
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from sklearn.utils._param_validation import make_constraint
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from sklearn.utils._param_validation import generate_invalid_param_val
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from sklearn.utils._param_validation import generate_valid_param
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from sklearn.utils._param_validation import validate_params
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from sklearn.utils._param_validation import InvalidParameterError
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# Some helpers for the tests
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@validate_params({"a": [Real], "b": [Real], "c": [Real], "d": [Real]})
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def _func(a, b=0, *args, c, d=0, **kwargs):
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"""A function to test the validation of functions."""
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class _Class:
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"""A class to test the _InstancesOf constraint and the validation of methods."""
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@validate_params({"a": [Real]})
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def _method(self, a):
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"""A validated method"""
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@deprecated()
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@validate_params({"a": [Real]})
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def _deprecated_method(self, a):
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"""A deprecated validated method"""
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class _Estimator(BaseEstimator):
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"""An estimator to test the validation of estimator parameters."""
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_parameter_constraints: dict = {"a": [Real]}
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def __init__(self, a):
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self.a = a
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def fit(self, X=None, y=None):
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self._validate_params()
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@pytest.mark.parametrize("interval_type", [Integral, Real])
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def test_interval_range(interval_type):
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"""Check the range of values depending on closed."""
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interval = Interval(interval_type, -2, 2, closed="left")
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assert -2 in interval and 2 not in interval
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interval = Interval(interval_type, -2, 2, closed="right")
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assert -2 not in interval and 2 in interval
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interval = Interval(interval_type, -2, 2, closed="both")
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assert -2 in interval and 2 in interval
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interval = Interval(interval_type, -2, 2, closed="neither")
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assert -2 not in interval and 2 not in interval
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def test_interval_inf_in_bounds():
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"""Check that inf is included iff a bound is closed and set to None.
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Only valid for real intervals.
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"""
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interval = Interval(Real, 0, None, closed="right")
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assert np.inf in interval
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interval = Interval(Real, None, 0, closed="left")
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assert -np.inf in interval
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interval = Interval(Real, None, None, closed="neither")
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assert np.inf not in interval
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assert -np.inf not in interval
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@pytest.mark.parametrize(
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"interval",
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[Interval(Real, 0, 1, closed="left"), Interval(Real, None, None, closed="both")],
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)
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def test_nan_not_in_interval(interval):
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"""Check that np.nan is not in any interval."""
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assert np.nan not in interval
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@pytest.mark.parametrize(
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"params, error, match",
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[
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(
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{"type": Integral, "left": 1.0, "right": 2, "closed": "both"},
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TypeError,
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r"Expecting left to be an int for an interval over the integers",
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),
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(
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{"type": Integral, "left": 1, "right": 2.0, "closed": "neither"},
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TypeError,
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"Expecting right to be an int for an interval over the integers",
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),
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(
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{"type": Integral, "left": None, "right": 0, "closed": "left"},
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ValueError,
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r"left can't be None when closed == left",
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),
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(
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{"type": Integral, "left": 0, "right": None, "closed": "right"},
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ValueError,
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r"right can't be None when closed == right",
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),
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(
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{"type": Integral, "left": 1, "right": -1, "closed": "both"},
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ValueError,
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r"right can't be less than left",
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),
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],
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)
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def test_interval_errors(params, error, match):
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"""Check that informative errors are raised for invalid combination of parameters"""
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with pytest.raises(error, match=match):
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Interval(**params)
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def test_stroptions():
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"""Sanity check for the StrOptions constraint"""
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options = StrOptions({"a", "b", "c"}, deprecated={"c"})
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assert options.is_satisfied_by("a")
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assert options.is_satisfied_by("c")
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assert not options.is_satisfied_by("d")
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assert "'c' (deprecated)" in str(options)
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def test_options():
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"""Sanity check for the Options constraint"""
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options = Options(Real, {-0.5, 0.5, np.inf}, deprecated={-0.5})
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assert options.is_satisfied_by(-0.5)
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assert options.is_satisfied_by(np.inf)
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assert not options.is_satisfied_by(1.23)
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assert "-0.5 (deprecated)" in str(options)
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@pytest.mark.parametrize(
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"type, expected_type_name",
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[
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(int, "int"),
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(Integral, "int"),
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(Real, "float"),
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(np.ndarray, "numpy.ndarray"),
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],
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)
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def test_instances_of_type_human_readable(type, expected_type_name):
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"""Check the string representation of the _InstancesOf constraint."""
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constraint = _InstancesOf(type)
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assert str(constraint) == f"an instance of '{expected_type_name}'"
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def test_hasmethods():
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"""Check the HasMethods constraint."""
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constraint = HasMethods(["a", "b"])
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class _Good:
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def a(self):
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pass # pragma: no cover
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def b(self):
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pass # pragma: no cover
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class _Bad:
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def a(self):
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pass # pragma: no cover
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assert constraint.is_satisfied_by(_Good())
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assert not constraint.is_satisfied_by(_Bad())
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assert str(constraint) == "an object implementing 'a' and 'b'"
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@pytest.mark.parametrize(
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"constraint",
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[
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Interval(Real, None, 0, closed="left"),
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Interval(Real, 0, None, closed="left"),
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Interval(Real, None, None, closed="neither"),
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StrOptions({"a", "b", "c"}),
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_MissingValues(),
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_VerboseHelper(),
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HasMethods("fit"),
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_IterablesNotString(),
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_CVObjects(),
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],
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)
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def test_generate_invalid_param_val(constraint):
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"""Check that the value generated does not satisfy the constraint"""
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bad_value = generate_invalid_param_val(constraint)
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assert not constraint.is_satisfied_by(bad_value)
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@pytest.mark.parametrize(
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"integer_interval, real_interval",
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[
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(
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Interval(Integral, None, 3, closed="right"),
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Interval(Real, -5, 5, closed="both"),
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),
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(
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Interval(Integral, None, 3, closed="right"),
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Interval(Real, -5, 5, closed="neither"),
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),
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(
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Interval(Integral, None, 3, closed="right"),
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Interval(Real, 4, 5, closed="both"),
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),
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(
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Interval(Integral, None, 3, closed="right"),
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Interval(Real, 5, None, closed="left"),
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),
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(
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Interval(Integral, None, 3, closed="right"),
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Interval(Real, 4, None, closed="neither"),
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),
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(
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Interval(Integral, 3, None, closed="left"),
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Interval(Real, -5, 5, closed="both"),
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),
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(
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Interval(Integral, 3, None, closed="left"),
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Interval(Real, -5, 5, closed="neither"),
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),
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(
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Interval(Integral, 3, None, closed="left"),
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Interval(Real, 1, 2, closed="both"),
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),
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(
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Interval(Integral, 3, None, closed="left"),
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Interval(Real, None, -5, closed="left"),
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),
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(
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Interval(Integral, 3, None, closed="left"),
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Interval(Real, None, -4, closed="neither"),
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),
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(
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Interval(Integral, -5, 5, closed="both"),
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Interval(Real, None, 1, closed="right"),
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),
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(
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Interval(Integral, -5, 5, closed="both"),
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Interval(Real, 1, None, closed="left"),
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),
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(
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Interval(Integral, -5, 5, closed="both"),
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Interval(Real, -10, -4, closed="neither"),
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),
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(
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Interval(Integral, -5, 5, closed="both"),
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Interval(Real, -10, -4, closed="right"),
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),
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(
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Interval(Integral, -5, 5, closed="neither"),
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Interval(Real, 6, 10, closed="neither"),
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),
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(
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Interval(Integral, -5, 5, closed="neither"),
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Interval(Real, 6, 10, closed="left"),
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),
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(
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Interval(Integral, 2, None, closed="left"),
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Interval(Real, 0, 1, closed="both"),
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),
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(
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Interval(Integral, 1, None, closed="left"),
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Interval(Real, 0, 1, closed="both"),
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),
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],
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)
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def test_generate_invalid_param_val_2_intervals(integer_interval, real_interval):
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"""Check that the value generated for an interval constraint does not satisfy any of
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the interval constraints.
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"""
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bad_value = generate_invalid_param_val(
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real_interval, constraints=[real_interval, integer_interval]
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)
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assert not real_interval.is_satisfied_by(bad_value)
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assert not integer_interval.is_satisfied_by(bad_value)
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bad_value = generate_invalid_param_val(
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integer_interval, constraints=[real_interval, integer_interval]
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)
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assert not real_interval.is_satisfied_by(bad_value)
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assert not integer_interval.is_satisfied_by(bad_value)
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@pytest.mark.parametrize(
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"constraints",
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[
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[_ArrayLikes()],
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[_InstancesOf(list)],
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[_Callables()],
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[_NoneConstraint()],
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[_RandomStates()],
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[_SparseMatrices()],
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[_Booleans()],
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[Interval(Real, None, None, closed="both")],
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[
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Interval(Integral, 0, None, closed="left"),
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Interval(Real, None, 0, closed="neither"),
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],
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],
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)
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def test_generate_invalid_param_val_all_valid(constraints):
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"""Check that the function raises NotImplementedError when there's no invalid value
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for the constraint.
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"""
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with pytest.raises(NotImplementedError):
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generate_invalid_param_val(constraints[0], constraints=constraints)
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@pytest.mark.parametrize(
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"constraint",
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[
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_ArrayLikes(),
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_Callables(),
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_InstancesOf(list),
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_NoneConstraint(),
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_RandomStates(),
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_SparseMatrices(),
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_Booleans(),
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_VerboseHelper(),
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_MissingValues(),
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StrOptions({"a", "b", "c"}),
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Options(Integral, {1, 2, 3}),
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Interval(Integral, None, None, closed="neither"),
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Interval(Integral, 0, 10, closed="neither"),
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Interval(Integral, 0, None, closed="neither"),
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Interval(Integral, None, 0, closed="neither"),
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Interval(Real, 0, 1, closed="neither"),
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Interval(Real, 0, None, closed="both"),
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Interval(Real, None, 0, closed="right"),
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HasMethods("fit"),
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_IterablesNotString(),
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_CVObjects(),
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],
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)
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def test_generate_valid_param(constraint):
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"""Check that the value generated does satisfy the constraint."""
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value = generate_valid_param(constraint)
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assert constraint.is_satisfied_by(value)
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@pytest.mark.parametrize(
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"constraint_declaration, value",
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[
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(Interval(Real, 0, 1, closed="both"), 0.42),
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(Interval(Integral, 0, None, closed="neither"), 42),
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(StrOptions({"a", "b", "c"}), "b"),
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(Options(type, {np.float32, np.float64}), np.float64),
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(callable, lambda x: x + 1),
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(None, None),
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("array-like", [[1, 2], [3, 4]]),
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|
|
("array-like", np.array([[1, 2], [3, 4]])),
|
||
|
|
("sparse matrix", csr_matrix([[1, 2], [3, 4]])),
|
||
|
|
("random_state", 0),
|
||
|
|
("random_state", np.random.RandomState(0)),
|
||
|
|
("random_state", None),
|
||
|
|
(_Class, _Class()),
|
||
|
|
(int, 1),
|
||
|
|
(Real, 0.5),
|
||
|
|
("boolean", False),
|
||
|
|
("verbose", 1),
|
||
|
|
("missing_values", -1),
|
||
|
|
("missing_values", -1.0),
|
||
|
|
("missing_values", None),
|
||
|
|
("missing_values", float("nan")),
|
||
|
|
("missing_values", np.nan),
|
||
|
|
("missing_values", "missing"),
|
||
|
|
(HasMethods("fit"), _Estimator(a=0)),
|
||
|
|
("cv_object", 5),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_is_satisfied_by(constraint_declaration, value):
|
||
|
|
"""Sanity check for the is_satisfied_by method"""
|
||
|
|
constraint = make_constraint(constraint_declaration)
|
||
|
|
assert constraint.is_satisfied_by(value)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"constraint_declaration, expected_constraint_class",
|
||
|
|
[
|
||
|
|
(Interval(Real, 0, 1, closed="both"), Interval),
|
||
|
|
(StrOptions({"option1", "option2"}), StrOptions),
|
||
|
|
(Options(Real, {0.42, 1.23}), Options),
|
||
|
|
("array-like", _ArrayLikes),
|
||
|
|
("sparse matrix", _SparseMatrices),
|
||
|
|
("random_state", _RandomStates),
|
||
|
|
(None, _NoneConstraint),
|
||
|
|
(callable, _Callables),
|
||
|
|
(int, _InstancesOf),
|
||
|
|
("boolean", _Booleans),
|
||
|
|
("verbose", _VerboseHelper),
|
||
|
|
("missing_values", _MissingValues),
|
||
|
|
(HasMethods("fit"), HasMethods),
|
||
|
|
("cv_object", _CVObjects),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_make_constraint(constraint_declaration, expected_constraint_class):
|
||
|
|
"""Check that make_constraint dispaches to the appropriate constraint class"""
|
||
|
|
constraint = make_constraint(constraint_declaration)
|
||
|
|
assert constraint.__class__ is expected_constraint_class
|
||
|
|
|
||
|
|
|
||
|
|
def test_make_constraint_unknown():
|
||
|
|
"""Check that an informative error is raised when an unknown constraint is passed"""
|
||
|
|
with pytest.raises(ValueError, match="Unknown constraint"):
|
||
|
|
make_constraint("not a valid constraint")
|
||
|
|
|
||
|
|
|
||
|
|
def test_validate_params():
|
||
|
|
"""Check that validate_params works no matter how the arguments are passed"""
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'a' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func("wrong", c=1)
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'b' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func(*[1, "wrong"], c=1)
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'c' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func(1, **{"c": "wrong"})
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'd' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func(1, c=1, d="wrong")
|
||
|
|
|
||
|
|
# check in the presence of extra positional and keyword args
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'b' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func(0, *["wrong", 2, 3], c=4, **{"e": 5})
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'c' parameter of _func must be"
|
||
|
|
):
|
||
|
|
_func(0, *[1, 2, 3], c="four", **{"e": 5})
|
||
|
|
|
||
|
|
|
||
|
|
def test_validate_params_missing_params():
|
||
|
|
"""Check that no error is raised when there are parameters without
|
||
|
|
constraints
|
||
|
|
"""
|
||
|
|
|
||
|
|
@validate_params({"a": [int]})
|
||
|
|
def func(a, b):
|
||
|
|
pass
|
||
|
|
|
||
|
|
func(1, 2)
|
||
|
|
|
||
|
|
|
||
|
|
def test_decorate_validated_function():
|
||
|
|
"""Check that validate_params functions can be decorated"""
|
||
|
|
decorated_function = deprecated()(_func)
|
||
|
|
|
||
|
|
with pytest.warns(FutureWarning, match="Function _func is deprecated"):
|
||
|
|
decorated_function(1, 2, c=3)
|
||
|
|
|
||
|
|
# outer decorator does not interfer with validation
|
||
|
|
with pytest.warns(FutureWarning, match="Function _func is deprecated"):
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match=r"The 'c' parameter of _func must be"
|
||
|
|
):
|
||
|
|
decorated_function(1, 2, c="wrong")
|
||
|
|
|
||
|
|
|
||
|
|
def test_validate_params_method():
|
||
|
|
"""Check that validate_params works with methods"""
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'a' parameter of _Class._method must be"
|
||
|
|
):
|
||
|
|
_Class()._method("wrong")
|
||
|
|
|
||
|
|
# validated method can be decorated
|
||
|
|
with pytest.warns(FutureWarning, match="Function _deprecated_method is deprecated"):
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError,
|
||
|
|
match="The 'a' parameter of _Class._deprecated_method must be",
|
||
|
|
):
|
||
|
|
_Class()._deprecated_method("wrong")
|
||
|
|
|
||
|
|
|
||
|
|
def test_validate_params_estimator():
|
||
|
|
"""Check that validate_params works with Estimator instances"""
|
||
|
|
# no validation in init
|
||
|
|
est = _Estimator("wrong")
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'a' parameter of _Estimator must be"
|
||
|
|
):
|
||
|
|
est.fit()
|
||
|
|
|
||
|
|
|
||
|
|
def test_stroptions_deprecated_subset():
|
||
|
|
"""Check that the deprecated parameter must be a subset of options."""
|
||
|
|
with pytest.raises(ValueError, match="deprecated options must be a subset"):
|
||
|
|
StrOptions({"a", "b", "c"}, deprecated={"a", "d"})
|
||
|
|
|
||
|
|
|
||
|
|
def test_hidden_constraint():
|
||
|
|
"""Check that internal constraints are not exposed in the error message."""
|
||
|
|
|
||
|
|
@validate_params({"param": [Hidden(list), dict]})
|
||
|
|
def f(param):
|
||
|
|
pass
|
||
|
|
|
||
|
|
# list and dict are valid params
|
||
|
|
f({"a": 1, "b": 2, "c": 3})
|
||
|
|
f([1, 2, 3])
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'param' parameter"
|
||
|
|
) as exc_info:
|
||
|
|
f(param="bad")
|
||
|
|
|
||
|
|
# the list option is not exposed in the error message
|
||
|
|
err_msg = str(exc_info.value)
|
||
|
|
assert "an instance of 'dict'" in err_msg
|
||
|
|
assert "an instance of 'list'" not in err_msg
|
||
|
|
|
||
|
|
|
||
|
|
def test_hidden_stroptions():
|
||
|
|
"""Check that we can have 2 StrOptions constraints, one being hidden."""
|
||
|
|
|
||
|
|
@validate_params({"param": [StrOptions({"auto"}), Hidden(StrOptions({"warn"}))]})
|
||
|
|
def f(param):
|
||
|
|
pass
|
||
|
|
|
||
|
|
# "auto" and "warn" are valid params
|
||
|
|
f("auto")
|
||
|
|
f("warn")
|
||
|
|
|
||
|
|
with pytest.raises(
|
||
|
|
InvalidParameterError, match="The 'param' parameter"
|
||
|
|
) as exc_info:
|
||
|
|
f(param="bad")
|
||
|
|
|
||
|
|
# the "warn" option is not exposed in the error message
|
||
|
|
err_msg = str(exc_info.value)
|
||
|
|
assert "auto" in err_msg
|
||
|
|
assert "warn" not in err_msg
|
||
|
|
|
||
|
|
|
||
|
|
def test_validate_params_set_param_constraints_attribute():
|
||
|
|
"""Check that the validate_params decorator properly sets the parameter constraints
|
||
|
|
as attribute of the decorated function/method.
|
||
|
|
"""
|
||
|
|
assert hasattr(_func, "_skl_parameter_constraints")
|
||
|
|
assert hasattr(_Class()._method, "_skl_parameter_constraints")
|
||
|
|
|
||
|
|
|
||
|
|
def test_boolean_constraint_deprecated_int():
|
||
|
|
"""Check that validate_params raise a deprecation message but still passes
|
||
|
|
validation when using an int for a parameter accepting a boolean.
|
||
|
|
"""
|
||
|
|
|
||
|
|
@validate_params({"param": ["boolean"]})
|
||
|
|
def f(param):
|
||
|
|
pass
|
||
|
|
|
||
|
|
# True/False and np.bool_(True/False) are valid params
|
||
|
|
f(True)
|
||
|
|
f(np.bool_(False))
|
||
|
|
|
||
|
|
# an int is also valid but deprecated
|
||
|
|
with pytest.warns(
|
||
|
|
FutureWarning, match="Passing an int for a boolean parameter is deprecated"
|
||
|
|
):
|
||
|
|
f(1)
|
||
|
|
|
||
|
|
|
||
|
|
def test_no_validation():
|
||
|
|
"""Check that validation can be skipped for a parameter."""
|
||
|
|
|
||
|
|
@validate_params({"param1": [int, None], "param2": "no_validation"})
|
||
|
|
def f(param1=None, param2=None):
|
||
|
|
pass
|
||
|
|
|
||
|
|
# param1 is validated
|
||
|
|
with pytest.raises(InvalidParameterError, match="The 'param1' parameter"):
|
||
|
|
f(param1="wrong")
|
||
|
|
|
||
|
|
# param2 is not validated: any type is valid.
|
||
|
|
class SomeType:
|
||
|
|
pass
|
||
|
|
|
||
|
|
f(param2=SomeType)
|
||
|
|
f(param2=SomeType())
|
||
|
|
|
||
|
|
|
||
|
|
def test_pandas_na_constraint_with_pd_na():
|
||
|
|
"""Add a specific test for checking support for `pandas.NA`."""
|
||
|
|
pd = pytest.importorskip("pandas")
|
||
|
|
|
||
|
|
na_constraint = _PandasNAConstraint()
|
||
|
|
assert na_constraint.is_satisfied_by(pd.NA)
|
||
|
|
assert not na_constraint.is_satisfied_by(np.array([1, 2, 3]))
|
||
|
|
|
||
|
|
|
||
|
|
def test_iterable_not_string():
|
||
|
|
"""Check that a string does not satisfy the _IterableNotString constraint."""
|
||
|
|
constraint = _IterablesNotString()
|
||
|
|
assert constraint.is_satisfied_by([1, 2, 3])
|
||
|
|
assert constraint.is_satisfied_by(range(10))
|
||
|
|
assert not constraint.is_satisfied_by("some string")
|
||
|
|
|
||
|
|
|
||
|
|
def test_cv_objects():
|
||
|
|
"""Check that the _CVObjects constraint accepts all current ways
|
||
|
|
to pass cv objects."""
|
||
|
|
constraint = _CVObjects()
|
||
|
|
assert constraint.is_satisfied_by(5)
|
||
|
|
assert constraint.is_satisfied_by(LeaveOneOut())
|
||
|
|
assert constraint.is_satisfied_by([([1, 2], [3, 4]), ([3, 4], [1, 2])])
|
||
|
|
assert constraint.is_satisfied_by(None)
|
||
|
|
assert not constraint.is_satisfied_by("not a CV object")
|
||
|
|
|
||
|
|
|
||
|
|
def test_third_party_estimator():
|
||
|
|
"""Check that the validation from a scikit-learn estimator inherited by a third
|
||
|
|
party estimator does not impose a match between the dict of constraints and the
|
||
|
|
parameters of the estimator.
|
||
|
|
"""
|
||
|
|
|
||
|
|
class ThirdPartyEstimator(_Estimator):
|
||
|
|
def __init__(self, b):
|
||
|
|
self.b = b
|
||
|
|
super().__init__(a=0)
|
||
|
|
|
||
|
|
def fit(self, X=None, y=None):
|
||
|
|
super().fit(X, y)
|
||
|
|
|
||
|
|
# does not raise, even though "b" is not in the constraints dict and "a" is not
|
||
|
|
# a parameter of the estimator.
|
||
|
|
ThirdPartyEstimator(b=0).fit()
|
||
|
|
|
||
|
|
|
||
|
|
def test_interval_real_not_int():
|
||
|
|
"""Check for the type "real_not_int" in the Interval constraint."""
|
||
|
|
constraint = Interval("real_not_int", 0, 1, closed="both")
|
||
|
|
assert constraint.is_satisfied_by(1.0)
|
||
|
|
assert not constraint.is_satisfied_by(1)
|