Exemplo n.º 1
0
def eval_sum(f, limits):
    from sympy.concrete.delta import deltasummation, _has_simple_delta
    from sympy.functions import KroneckerDelta

    (i, a, b) = limits
    if f is S.Zero:
        return S.Zero
    if i not in f.free_symbols:
        return f*(b - a + 1)
    if a == b:
        return f.subs(i, a)

    if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
        return deltasummation(f, limits)

    dif = b - a
    definite = dif.is_Integer
    # Doing it directly may be faster if there are very few terms.
    if definite and (dif < 100):
        return eval_sum_direct(f, (i, a, b))
    # Try to do it symbolically. Even when the number of terms is known,
    # this can save time when b-a is big.
    # We should try to transform to partial fractions
    value = eval_sum_symbolic(f.expand(), (i, a, b))
    if value is not None:
        return value
    # Do it directly
    if definite:
        return eval_sum_direct(f, (i, a, b))
Exemplo n.º 2
0
def eval_sum(f, limits):
    from sympy.concrete.delta import deltasummation, _has_simple_delta
    from sympy.functions import KroneckerDelta

    (i, a, b) = limits
    if f is S.Zero:
        return S.Zero
    if i not in f.free_symbols:
        return f * (b - a + 1)
    if a == b:
        return f.subs(i, a)

    if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
        return deltasummation(f, limits)

    dif = b - a
    definite = dif.is_Integer
    # Doing it directly may be faster if there are very few terms.
    if definite and (dif < 100):
        return eval_sum_direct(f, (i, a, b))
    # Try to do it symbolically. Even when the number of terms is known,
    # this can save time when b-a is big.
    # We should try to transform to partial fractions
    value = eval_sum_symbolic(f.expand(), (i, a, b))
    if value is not None:
        return value
    # Do it directly
    if definite:
        return eval_sum_direct(f, (i, a, b))
Exemplo n.º 3
0
def _expand_delta(expr, idx):
    """Expand the first :class:`sympy.Add` containing a simple
    :class:`sympy.KroneckerDelta`.

    Auxiliary routine for :func:`_deltasummation`. Adapted from SymPy. The
    input `expr` may be a :class:`.QuantumExpression` or a
    `:class:`sympy.Basic` instance.

    Returns a list of summands. The elements of the list may be
    :class:`.QuantumExpression` or a `:class:`sympy.Basic` instances. There is
    no guarantee of type stability: an input :class:`.QuantumExpression` may
    result in a :class:`sympy.Basic` instance in the `summands`.
    """
    found_first_delta = False
    summands = None
    for factor in _factors_for_expand_delta(expr):
        need_to_expand = False
        if not found_first_delta and isinstance(factor, sympy.Basic):
            if factor.is_Add and _has_simple_delta(factor, idx):
                need_to_expand = True
        if need_to_expand:
            found_first_delta = True
            if summands is None:
                summands = list(factor.args)
            else:
                summands = [summands[0] * t for t in factor.args]
        else:
            if summands is None:
                summands = [
                    factor,
                ]
            else:
                summands = [t * factor for t in summands]
    return summands
Exemplo n.º 4
0
def eval_sum(f, limits):
    from sympy.concrete.delta import deltasummation, _has_simple_delta
    from sympy.functions import KroneckerDelta

    (i, a, b) = limits
    if f.is_zero:
        return S.Zero
    if i not in f.free_symbols:
        return f*(b - a + 1)
    if a == b:
        return f.subs(i, a)
    if isinstance(f, Piecewise):
        if not any(i in arg.args[1].free_symbols for arg in f.args):
            # Piecewise conditions do not depend on the dummy summation variable,
            # therefore we can fold:     Sum(Piecewise((e, c), ...), limits)
            #                        --> Piecewise((Sum(e, limits), c), ...)
            newargs = []
            for arg in f.args:
                newexpr = eval_sum(arg.expr, limits)
                if newexpr is None:
                    return None
                newargs.append((newexpr, arg.cond))
            return f.func(*newargs)

    if f.has(KroneckerDelta):
        f = f.replace(
            lambda x: isinstance(x, Sum),
            lambda x: x.factor()
        )
        if _has_simple_delta(f, limits[0]):
            return deltasummation(f, limits)

    dif = b - a
    definite = dif.is_Integer
    # Doing it directly may be faster if there are very few terms.
    if definite and (dif < 100):
        return eval_sum_direct(f, (i, a, b))
    if isinstance(f, Piecewise):
        return None
    # Try to do it symbolically. Even when the number of terms is known,
    # this can save time when b-a is big.
    # We should try to transform to partial fractions
    value = eval_sum_symbolic(f.expand(), (i, a, b))
    if value is not None:
        return value
    # Do it directly
    if definite:
        return eval_sum_direct(f, (i, a, b))
Exemplo n.º 5
0
def eval_sum(f, limits):
    from sympy.concrete.delta import deltasummation, _has_simple_delta
    from sympy.functions import KroneckerDelta

    (i, a, b) = limits
    if f is S.Zero:
        return S.Zero
    if i not in f.free_symbols:
        return f*(b - a + 1)
    if a == b:
        return f.subs(i, a)
    if isinstance(f, Piecewise):
        if not any(i in arg.args[1].free_symbols for arg in f.args):
            # Piecewise conditions do not depend on the dummy summation variable,
            # therefore we can fold:     Sum(Piecewise((e, c), ...), limits)
            #                        --> Piecewise((Sum(e, limits), c), ...)
            newargs = []
            for arg in f.args:
                newexpr = eval_sum(arg.expr, limits)
                if newexpr is None:
                    return None
                newargs.append((newexpr, arg.cond))
            return f.func(*newargs)

    if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
        return deltasummation(f, limits)

    dif = b - a
    definite = dif.is_Integer
    # Doing it directly may be faster if there are very few terms.
    if definite and (dif < 100):
        return eval_sum_direct(f, (i, a, b))
    if isinstance(f, Piecewise):
        return None
    # Try to do it symbolically. Even when the number of terms is known,
    # this can save time when b-a is big.
    # We should try to transform to partial fractions
    value = eval_sum_symbolic(f.expand(), (i, a, b))
    if value is not None:
        return value
    # Do it directly
    if definite:
        return eval_sum_direct(f, (i, a, b))
Exemplo n.º 6
0
    def _eval_product(self, term, limits):
        from sympy.concrete.delta import deltaproduct, _has_simple_delta
        from sympy.concrete.summations import summation
        from sympy.functions import KroneckerDelta, RisingFactorial

        (k, a, n) = limits

        if k not in term.free_symbols:
            if (term - 1).is_zero:
                return S.One
            return term**(n - a + 1)

        if a == n:
            return term.subs(k, a)

        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
            return deltaproduct(term, limits)

        dif = n - a
        if dif.is_Integer:
            return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])

        elif term.is_polynomial(k):
            poly = term.as_poly(k)

            A = B = Q = S.One

            all_roots = roots(poly)

            M = 0
            for r, m in all_roots.items():
                M += m
                A *= RisingFactorial(a - r, n - a + 1)**m
                Q *= (n - r)**m

            if M < poly.degree():
                arg = quo(poly, Q.as_poly(k))
                B = self.func(arg, (k, a, n)).doit()

            return poly.LC()**(n - a + 1) * A * B

        elif term.is_Add:
            p, q = term.as_numer_denom()

            p = self._eval_product(p, (k, a, n))
            q = self._eval_product(q, (k, a, n))

            return p / q

        elif term.is_Mul:
            exclude, include = [], []

            for t in term.args:
                p = self._eval_product(t, (k, a, n))

                if p is not None:
                    exclude.append(p)
                else:
                    include.append(t)

            if not exclude:
                return None
            else:
                arg = term._new_rawargs(*include)
                A = Mul(*exclude)
                B = self.func(arg, (k, a, n)).doit()
                return A * B

        elif term.is_Pow:
            if not term.base.has(k):
                s = summation(term.exp, (k, a, n))

                return term.base**s
            elif not term.exp.has(k):
                p = self._eval_product(term.base, (k, a, n))

                if p is not None:
                    return p**term.exp

        elif isinstance(term, Product):
            evaluated = term.doit()
            f = self._eval_product(evaluated, limits)
            if f is None:
                return self.func(evaluated, limits)
            else:
                return f
Exemplo n.º 7
0
    def _eval_product(self, term, limits):
        from sympy.concrete.delta import deltaproduct, _has_simple_delta
        from sympy.concrete.summations import summation
        from sympy.functions import KroneckerDelta, RisingFactorial

        (k, a, n) = limits

        if k not in term.free_symbols:
            if (term - 1).is_zero:
                return S.One
            return term**(n - a + 1)

        if a == n:
            return term.subs(k, a)

        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
            return deltaproduct(term, limits)

        dif = n - a
        if dif.is_Integer:
            return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])

        elif term.is_polynomial(k):
            poly = term.as_poly(k)

            A = B = Q = S.One

            all_roots = roots(poly)

            M = 0
            for r, m in all_roots.items():
                M += m
                A *= RisingFactorial(a - r, n - a + 1)**m
                Q *= (n - r)**m

            if M < poly.degree():
                arg = quo(poly, Q.as_poly(k))
                B = self.func(arg, (k, a, n)).doit()

            return poly.LC()**(n - a + 1) * A * B

        elif term.is_Add:
            factored = factor_terms(term, fraction=True)
            if factored.is_Mul:
                return self._eval_product(factored, (k, a, n))

        elif term.is_Mul:
            exclude, include = [], []

            for t in term.args:
                p = self._eval_product(t, (k, a, n))

                if p is not None:
                    exclude.append(p)
                else:
                    include.append(t)

            if not exclude:
                return None
            else:
                arg = term._new_rawargs(*include)
                A = Mul(*exclude)
                B = self.func(arg, (k, a, n)).doit()
                return A * B

        elif term.is_Pow:
            if not term.base.has(k):
                s = summation(term.exp, (k, a, n))

                return term.base**s
            elif not term.exp.has(k):
                p = self._eval_product(term.base, (k, a, n))

                if p is not None:
                    return p**term.exp

        elif isinstance(term, Product):
            evaluated = term.doit()
            f = self._eval_product(evaluated, limits)
            if f is None:
                return self.func(evaluated, limits)
            else:
                return f
Exemplo n.º 8
0
    def _eval_product(self, term, limits):
        from sympy.concrete.delta import deltaproduct, _has_simple_delta
        from sympy.concrete.summations import summation
        from sympy.functions import KroneckerDelta

        (k, a, n) = limits

        if k not in term.free_symbols:
            return term**(n - a + 1)

        if a == n:
            return term.subs(k, a)

        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
            return deltaproduct(term, limits)

        dif = n - a
        if dif.is_Integer:
            return Mul(*[term.subs(k, a + i) for i in xrange(dif + 1)])

        elif term.is_polynomial(k):
            poly = term.as_poly(k)

            A = B = Q = S.One

            all_roots = roots(poly, multiple=True)

            for r in all_roots:
                A *= C.RisingFactorial(a - r, n - a + 1)
                Q *= n - r

            if len(all_roots) < poly.degree():
                arg = quo(poly, Q.as_poly(k))
                B = self.func(arg, (k, a, n)).doit()

            return poly.LC()**(n - a + 1) * A * B

        elif term.is_Add:
            p, q = term.as_numer_denom()

            p = self._eval_product(p, (k, a, n))
            q = self._eval_product(q, (k, a, n))

            return p / q

        elif term.is_Mul:
            exclude, include = [], []

            for t in term.args:
                p = self._eval_product(t, (k, a, n))

                if p is not None:
                    exclude.append(p)
                else:
                    include.append(t)

            if not exclude:
                return None
            else:
                arg = term._new_rawargs(*include)
                A = Mul(*exclude)
                B = self.func(arg, (k, a, n)).doit()
                return A * B

        elif term.is_Pow:
            if not term.base.has(k):
                s = summation(term.exp, (k, a, n))

                return term.base**s
            elif not term.exp.has(k):
                p = self._eval_product(term.base, (k, a, n))

                if p is not None:
                    return p**term.exp

        elif isinstance(term, Product):
            evaluated = term.doit()
            f = self._eval_product(evaluated, limits)
            if f is None:
                return self.func(evaluated, limits)
            else:
                return f
Exemplo n.º 9
0
    def _eval_product(self, term, limits):
        from sympy.concrete.delta import deltaproduct, _has_simple_delta
        from sympy.concrete.summations import summation
        from sympy.functions import KroneckerDelta, RisingFactorial

        (k, a, n) = limits

        if k not in term.free_symbols:
            if (term - 1).is_zero:
                return S.One
            return term**(n - a + 1)

        if a == n:
            return term.subs(k, a)

        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
            return deltaproduct(term, limits)

        dif = n - a
        if dif.is_Integer:
            return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])

        elif term.is_polynomial(k):
            poly = term.as_poly(k)

            A = B = Q = S.One

            all_roots = roots(poly)

            M = 0
            for r, m in all_roots.items():
                M += m
                A *= RisingFactorial(a - r, n - a + 1)**m
                Q *= (n - r)**m

            if M < poly.degree():
                arg = quo(poly, Q.as_poly(k))
                B = self.func(arg, (k, a, n)).doit()

            return poly.LC()**(n - a + 1) * A * B

        elif term.is_Add:
            p, q = term.as_numer_denom()
            q = self._eval_product(q, (k, a, n))
            if q.is_Number:

                # There is expression, which couldn't change by
                # as_numer_denom(). E.g. n**(2/3) + 1 --> (n**(2/3) + 1, 1).
                # We have to catch this case.

                p = sum([self._eval_product(i, (k, a, n)) for i in p.as_coeff_Add()])
            else:
                p = self._eval_product(p, (k, a, n))
            return p / q

        elif term.is_Mul:
            exclude, include = [], []

            for t in term.args:
                p = self._eval_product(t, (k, a, n))

                if p is not None:
                    exclude.append(p)
                else:
                    include.append(t)

            if not exclude:
                return None
            else:
                arg = term._new_rawargs(*include)
                A = Mul(*exclude)
                B = self.func(arg, (k, a, n)).doit()
                return A * B

        elif term.is_Pow:
            if not term.base.has(k):
                s = summation(term.exp, (k, a, n))

                return term.base**s
            elif not term.exp.has(k):
                p = self._eval_product(term.base, (k, a, n))

                if p is not None:
                    return p**term.exp

        elif isinstance(term, Product):
            evaluated = term.doit()
            f = self._eval_product(evaluated, limits)
            if f is None:
                return self.func(evaluated, limits)
            else:
                return f
Exemplo n.º 10
0
    def _eval_product(self, term, limits):
        from sympy.concrete.delta import deltaproduct, _has_simple_delta
        from sympy.concrete.summations import summation
        from sympy.functions import KroneckerDelta, RisingFactorial

        (k, a, n) = limits

        if k not in term.free_symbols:
            if (term - 1).is_zero:
                return S.One
            return term**(n - a + 1)

        if a == n:
            return term.subs(k, a)

        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
            return deltaproduct(term, limits)

        dif = n - a
        definite = dif.is_Integer
        if definite and (dif < 100):
            return self._eval_product_direct(term, limits)

        elif term.is_polynomial(k):
            poly = term.as_poly(k)

            A = B = Q = S.One

            all_roots = roots(poly)

            M = 0
            for r, m in all_roots.items():
                M += m
                A *= RisingFactorial(a - r, n - a + 1)**m
                Q *= (n - r)**m

            if M < poly.degree():
                arg = quo(poly, Q.as_poly(k))
                B = self.func(arg, (k, a, n)).doit()

            return poly.LC()**(n - a + 1) * A * B

        elif term.is_Add:
            factored = factor_terms(term, fraction=True)
            if factored.is_Mul:
                return self._eval_product(factored, (k, a, n))

        elif term.is_Mul:
            # Factor in part without the summation variable and part with
            without_k, with_k = term.as_coeff_mul(k)

            if len(with_k) >= 2:
                # More than one term including k, so still a multiplication
                exclude, include = [], []
                for t in with_k:
                    p = self._eval_product(t, (k, a, n))

                    if p is not None:
                        exclude.append(p)
                    else:
                        include.append(t)

                if not exclude:
                    return None
                else:
                    arg = term._new_rawargs(*include)
                    A = Mul(*exclude)
                    B = self.func(arg, (k, a, n)).doit()
                    return without_k**(n - a + 1) * A * B
            else:
                # Just a single term
                p = self._eval_product(with_k[0], (k, a, n))
                if p is None:
                    p = self.func(with_k[0], (k, a, n)).doit()
                return without_k**(n - a + 1) * p

        elif term.is_Pow:
            if not term.base.has(k):
                s = summation(term.exp, (k, a, n))

                return term.base**s
            elif not term.exp.has(k):
                p = self._eval_product(term.base, (k, a, n))

                if p is not None:
                    return p**term.exp

        elif isinstance(term, Product):
            evaluated = term.doit()
            f = self._eval_product(evaluated, limits)
            if f is None:
                return self.func(evaluated, limits)
            else:
                return f

        if definite:
            return self._eval_product_direct(term, limits)