def __init__(self, ex: Union[str, Number, sympy.Expr]) -> None:
"""Create an Expression object.
Receives the mathematical expression which shall be represented by the object as a string
which will be parsed using py_expression_eval. For available operators, functions and
constants see SymPy documentation
Args:
ex (string): The mathematical expression represented as a string
"""
super().__init__()
if isinstance(ex, sympy.Expr):
self._original_expression = None
self._sympified_expression = ex
self._variables = get_variables(self._sympified_expression)
elif isinstance(ex, ExpressionScalar):
self._original_expression = ex._original_expression
self._sympified_expression = ex._sympified_expression
self._variables = ex._variables
elif isinstance(ex, (int, float)):
self._original_expression = ex
self._sympified_expression = sympify(ex)
self._variables = ()
else:
self._original_expression = ex
self._sympified_expression = sympify(ex)
self._variables = get_variables(self._sympified_expression)
self._exact_rational_lambdified = None
def test_as_expression(self):
sts = [DummyPulseTemplate(duration='t1', defined_channels={'A'},
integrals={'A': ExpressionScalar('2+k')}),
DummyPulseTemplate(duration='t1', defined_channels={'B', 'C'},
integrals={'B': ExpressionScalar('t1-t0*3.1'), 'C': ExpressionScalar('l')})]
pulse = AtomicMultiChannelPulseTemplate(*sts)
self.assertEqual({'A': ExpressionScalar(sympify('(2+k) / t1') * pulse._AS_EXPRESSION_TIME),
'B': ExpressionScalar(sympify('(t1-t0*3.1)/t1') * pulse._AS_EXPRESSION_TIME),
'C': ExpressionScalar(sympify('l/t1') * pulse._AS_EXPRESSION_TIME)},
pulse._as_expression())
def evaluate_symbolic(self, substitutions: Mapping[Any,
Any]) -> 'Expression':
if len(substitutions) == 0:
return self
return Expression.make(
recursive_substitution(sympify(self.underlying_expression),
substitutions))
def _sympify(cls, other: Union['ExpressionScalar', Number, sympy.Expr]) -> sympy.Expr:
return other._sympified_expression if isinstance(other, cls) else sympify(other)
def evaluate_symbolic(self, substitutions: Dict[Any, Any]) -> 'Expression':
return Expression.make(
recursive_substitution(sympify(self.underlying_expression),
substitutions))
