Source code for qiskit.circuit.parameterexpression
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""
ParameterExpression Class to enable creating simple expressions of Parameters.
"""
from typing import Callable, Dict, Set, Union
import numbers
import operator
import numpy
from qiskit.circuit.exceptions import CircuitError
try:
import symengine
HAS_SYMENGINE = True
except ImportError:
HAS_SYMENGINE = False
ParameterValueType = Union["ParameterExpression", float]
[docs]class ParameterExpression:
"""ParameterExpression class to enable creating expressions of Parameters."""
__slots__ = ["_parameter_symbols", "_parameters", "_symbol_expr", "_names"]
def __init__(self, symbol_map: Dict, expr):
"""Create a new :class:`ParameterExpression`.
Not intended to be called directly, but to be instantiated via operations
on other :class:`Parameter` or :class:`ParameterExpression` objects.
Args:
symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):
Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`
serving as their placeholder in expr.
expr (sympy.Expr): Expression of :class:`sympy.Symbol` s.
"""
self._parameter_symbols = symbol_map
self._parameters = set(self._parameter_symbols)
self._symbol_expr = expr
self._names = None
@property
def parameters(self) -> Set:
"""Returns a set of the unbound Parameters in the expression."""
return self._parameters
[docs] def conjugate(self) -> "ParameterExpression":
"""Return the conjugate."""
if HAS_SYMENGINE:
conjugated = ParameterExpression(
self._parameter_symbols, symengine.conjugate(self._symbol_expr)
)
else:
conjugated = ParameterExpression(self._parameter_symbols, self._symbol_expr.conjugate())
return conjugated
[docs] def assign(self, parameter, value: ParameterValueType) -> "ParameterExpression":
"""
Assign one parameter to a value, which can either be numeric or another parameter
expression.
Args:
parameter (Parameter): A parameter in this expression whose value will be updated.
value: The new value to bind to.
Returns:
A new expression parameterized by any parameters which were not bound by assignment.
"""
if isinstance(value, ParameterExpression):
return self.subs({parameter: value})
return self.bind({parameter: value})
[docs] def bind(self, parameter_values: Dict) -> "ParameterExpression":
"""Binds the provided set of parameters to their corresponding values.
Args:
parameter_values: Mapping of Parameter instances to the numeric value to which
they will be bound.
Raises:
CircuitError:
- If parameter_values contains Parameters outside those in self.
- If a non-numeric value is passed in parameter_values.
ZeroDivisionError:
- If binding the provided values requires division by zero.
Returns:
A new expression parameterized by any parameters which were not bound by
parameter_values.
"""
self._raise_if_passed_unknown_parameters(parameter_values.keys())
self._raise_if_passed_nan(parameter_values)
symbol_values = {}
for parameter, value in parameter_values.items():
param_expr = self._parameter_symbols[parameter]
# TODO: Remove after symengine supports single precision floats
# see symengine/symengine.py#351 for more details
if isinstance(value, numpy.floating):
symbol_values[param_expr] = float(value)
else:
symbol_values[param_expr] = value
bound_symbol_expr = self._symbol_expr.subs(symbol_values)
# Don't use sympy.free_symbols to count remaining parameters here.
# sympy will in some cases reduce the expression and remove even
# unbound symbols.
# e.g. (sympy.Symbol('s') * 0).free_symbols == set()
free_parameters = self.parameters - parameter_values.keys()
free_parameter_symbols = {
p: s for p, s in self._parameter_symbols.items() if p in free_parameters
}
if (
hasattr(bound_symbol_expr, "is_infinite") and bound_symbol_expr.is_infinite
) or bound_symbol_expr == float("inf"):
raise ZeroDivisionError(
"Binding provided for expression "
"results in division by zero "
"(Expression: {}, Bindings: {}).".format(self, parameter_values)
)
return ParameterExpression(free_parameter_symbols, bound_symbol_expr)
[docs] def subs(self, parameter_map: Dict) -> "ParameterExpression":
"""Returns a new Expression with replacement Parameters.
Args:
parameter_map: Mapping from Parameters in self to the ParameterExpression
instances with which they should be replaced.
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression with the specified parameters replaced.
"""
inbound_parameters = {
p for replacement_expr in parameter_map.values() for p in replacement_expr.parameters
}
self._raise_if_passed_unknown_parameters(parameter_map.keys())
self._raise_if_parameter_names_conflict(inbound_parameters, parameter_map.keys())
if HAS_SYMENGINE:
new_parameter_symbols = {p: symengine.Symbol(p.name) for p in inbound_parameters}
else:
from sympy import Symbol
new_parameter_symbols = {p: Symbol(p.name) for p in inbound_parameters}
# Include existing parameters in self not set to be replaced.
new_parameter_symbols.update(
{p: s for p, s in self._parameter_symbols.items() if p not in parameter_map}
)
# If new_param is an expr, we'll need to construct a matching sympy expr
# but with our sympy symbols instead of theirs.
symbol_map = {
self._parameter_symbols[old_param]: new_param._symbol_expr
for old_param, new_param in parameter_map.items()
}
substituted_symbol_expr = self._symbol_expr.subs(symbol_map)
return ParameterExpression(new_parameter_symbols, substituted_symbol_expr)
def _raise_if_passed_unknown_parameters(self, parameters):
unknown_parameters = parameters - self.parameters
if unknown_parameters:
raise CircuitError(
"Cannot bind Parameters ({}) not present in "
"expression.".format([str(p) for p in unknown_parameters])
)
def _raise_if_passed_nan(self, parameter_values):
nan_parameter_values = {
p: v for p, v in parameter_values.items() if not isinstance(v, numbers.Number)
}
if nan_parameter_values:
raise CircuitError(
f"Expression cannot bind non-numeric values ({nan_parameter_values})"
)
def _raise_if_parameter_names_conflict(self, inbound_parameters, outbound_parameters=None):
if outbound_parameters is None:
outbound_parameters = set()
if self._names is None:
self._names = {p.name: p for p in self._parameters}
inbound_names = {p.name: p for p in inbound_parameters}
outbound_names = {p.name: p for p in outbound_parameters}
shared_names = (self._names.keys() - outbound_names.keys()) & inbound_names.keys()
conflicting_names = {
name for name in shared_names if self._names[name] != inbound_names[name]
}
if conflicting_names:
raise CircuitError(
"Name conflict applying operation for parameters: " "{}".format(conflicting_names)
)
def _apply_operation(
self, operation: Callable, other: ParameterValueType, reflected: bool = False
) -> "ParameterExpression":
"""Base method implementing math operations between Parameters and
either a constant or a second ParameterExpression.
Args:
operation: One of operator.{add,sub,mul,truediv}.
other: The second argument to be used with self in operation.
reflected: Optional - The default ordering is "self operator other".
If reflected is True, this is switched to "other operator self".
For use in e.g. __radd__, ...
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression describing the result of the operation.
"""
self_expr = self._symbol_expr
if isinstance(other, ParameterExpression):
self._raise_if_parameter_names_conflict(other._parameter_symbols.keys())
parameter_symbols = {**self._parameter_symbols, **other._parameter_symbols}
other_expr = other._symbol_expr
elif isinstance(other, numbers.Number) and numpy.isfinite(other):
parameter_symbols = self._parameter_symbols.copy()
other_expr = other
else:
return NotImplemented
if reflected:
expr = operation(other_expr, self_expr)
else:
expr = operation(self_expr, other_expr)
return ParameterExpression(parameter_symbols, expr)
[docs] def gradient(self, param) -> Union["ParameterExpression", float]:
"""Get the derivative of a parameter expression w.r.t. a specified parameter expression.
Args:
param (Parameter): Parameter w.r.t. which we want to take the derivative
Returns:
ParameterExpression representing the gradient of param_expr w.r.t. param
"""
# Check if the parameter is contained in the parameter expression
if param not in self._parameter_symbols.keys():
# If it is not contained then return 0
return 0.0
# Compute the gradient of the parameter expression w.r.t. param
key = self._parameter_symbols[param]
if HAS_SYMENGINE:
expr_grad = symengine.Derivative(self._symbol_expr, key)
else:
# TODO enable nth derivative
from sympy import Derivative
expr_grad = Derivative(self._symbol_expr, key).doit()
# generate the new dictionary of symbols
# this needs to be done since in the derivative some symbols might disappear (e.g.
# when deriving linear expression)
parameter_symbols = {}
for parameter, symbol in self._parameter_symbols.items():
if symbol in expr_grad.free_symbols:
parameter_symbols[parameter] = symbol
# If the gradient corresponds to a parameter expression then return the new expression.
if len(parameter_symbols) > 0:
return ParameterExpression(parameter_symbols, expr=expr_grad)
# If no free symbols left, return a float corresponding to the gradient.
return float(expr_grad)
def __add__(self, other):
return self._apply_operation(operator.add, other)
def __radd__(self, other):
return self._apply_operation(operator.add, other, reflected=True)
def __sub__(self, other):
return self._apply_operation(operator.sub, other)
def __rsub__(self, other):
return self._apply_operation(operator.sub, other, reflected=True)
def __mul__(self, other):
return self._apply_operation(operator.mul, other)
def __neg__(self):
return self._apply_operation(operator.mul, -1.0)
def __rmul__(self, other):
return self._apply_operation(operator.mul, other, reflected=True)
def __truediv__(self, other):
if other == 0:
raise ZeroDivisionError("Division of a ParameterExpression by zero.")
return self._apply_operation(operator.truediv, other)
def __rtruediv__(self, other):
return self._apply_operation(operator.truediv, other, reflected=True)
def _call(self, ufunc):
return ParameterExpression(self._parameter_symbols, ufunc(self._symbol_expr))
[docs] def sin(self):
"""Sine of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.sin)
else:
from sympy import sin as _sin
return self._call(_sin)
[docs] def cos(self):
"""Cosine of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.cos)
else:
from sympy import cos as _cos
return self._call(_cos)
[docs] def tan(self):
"""Tangent of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.tan)
else:
from sympy import tan as _tan
return self._call(_tan)
[docs] def arcsin(self):
"""Arcsin of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.asin)
else:
from sympy import asin as _asin
return self._call(_asin)
[docs] def arccos(self):
"""Arccos of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.acos)
else:
from sympy import acos as _acos
return self._call(_acos)
[docs] def arctan(self):
"""Arctan of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.atan)
else:
from sympy import atan as _atan
return self._call(_atan)
[docs] def exp(self):
"""Exponential of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.exp)
else:
from sympy import exp as _exp
return self._call(_exp)
[docs] def log(self):
"""Logarithm of a ParameterExpression"""
if HAS_SYMENGINE:
return self._call(symengine.log)
else:
from sympy import log as _log
return self._call(_log)
def __repr__(self):
return f"{self.__class__.__name__}({str(self)})"
def __str__(self):
from sympy import sympify
return str(sympify(self._symbol_expr))
def __float__(self):
if self.parameters:
raise TypeError(
"ParameterExpression with unbound parameters ({}) "
"cannot be cast to a float.".format(self.parameters)
)
return float(self._symbol_expr)
def __complex__(self):
if self.parameters:
raise TypeError(
"ParameterExpression with unbound parameters ({}) "
"cannot be cast to a complex.".format(self.parameters)
)
return complex(self._symbol_expr)
def __int__(self):
if self.parameters:
raise TypeError(
"ParameterExpression with unbound parameters ({}) "
"cannot be cast to an int.".format(self.parameters)
)
return int(self._symbol_expr)
def __hash__(self):
return hash((frozenset(self._parameter_symbols), self._symbol_expr))
def __copy__(self):
return self
def __deepcopy__(self, memo=None):
return self
def __eq__(self, other):
"""Check if this parameter expression is equal to another parameter expression
or a fixed value (only if this is a bound expression).
Args:
other (ParameterExpression or a number):
Parameter expression or numeric constant used for comparison
Returns:
bool: result of the comparison
"""
if isinstance(other, ParameterExpression):
if self.parameters != other.parameters:
return False
if HAS_SYMENGINE:
from sympy import sympify
return sympify(self._symbol_expr).equals(sympify(other._symbol_expr))
else:
return self._symbol_expr.equals(other._symbol_expr)
elif isinstance(other, numbers.Number):
return len(self.parameters) == 0 and complex(self._symbol_expr) == other
return False
def __getstate__(self):
if HAS_SYMENGINE:
from sympy import sympify
symbols = {k: sympify(v) for k, v in self._parameter_symbols.items()}
expr = sympify(self._symbol_expr)
return {"type": "symengine", "symbols": symbols, "expr": expr, "names": self._names}
else:
return {
"type": "sympy",
"symbols": self._parameter_symbols,
"expr": self._symbol_expr,
"names": self._names,
}
def __setstate__(self, state):
if state["type"] == "symengine":
self._symbol_expr = symengine.sympify(state["expr"])
self._parameter_symbols = {k: symengine.sympify(v) for k, v in state["symbols"].items()}
self._parameters = set(self._parameter_symbols)
else:
self._symbol_expr = state["expr"]
self._parameter_symbols = state["symbols"]
self._parameters = set(self._parameter_symbols)
self._names = state["names"]
[docs] def is_real(self):
"""Return whether the expression is real"""
if not self._symbol_expr.is_real and self._symbol_expr.is_real is not None:
# Symengine returns false for is_real on the expression if
# there is a imaginary component (even if that component is 0),
# but the parameter will evaluate as real. Check that if the
# expression's is_real attribute returns false that we have a
# non-zero imaginary
if HAS_SYMENGINE:
if self._symbol_expr.imag != 0.0:
return False
else:
return False
return True