def monomial_count(V, N):
r"""
Computes the number of monomials.
The number of monomials is given by the following formula:
.. math::
\frac{(\#V + N)!}{\#V! N!}
where `N` is a total degree and `V` is a set of variables.
**Examples**
>>> from sympy import monomials, monomial_count
>>> from sympy.abc import x, y
>>> monomial_count(2, 2)
6
>>> M = monomials([x, y], 2)
>>> sorted(M)
[1, x, y, x**2, y**2, x*y]
>>> len(M)
6
"""
return C.factorial(V + N) / C.factorial(V) / C.factorial(N)
def as_real_imag(self, deep=True, **hints):
# TODO: Handle deep and hints
n, m, theta, phi = self.args
re = (sqrt((2*n + 1)/(4*pi) * C.factorial(n - m)/C.factorial(n + m)) *
C.cos(m*phi) * assoc_legendre(n, m, C.cos(theta)))
im = (sqrt((2*n + 1)/(4*pi) * C.factorial(n - m)/C.factorial(n + m)) *
C.sin(m*phi) * assoc_legendre(n, m, C.cos(theta)))
return (re, im)
def _eval_rewrite_as_polynomial(self, n, m, x):
k = C.Dummy("k")
kern = (
C.factorial(2 * n - 2 * k)
/ (2 ** n * C.factorial(n - k) * C.factorial(k) * C.factorial(n - 2 * k - m))
* (-1) ** k
* x ** (n - m - 2 * k)
)
return (1 - x ** 2) ** (m / 2) * C.Sum(kern, (k, 0, C.floor((n - m) * S.Half)))
def _eval_expand_func(self, **hints):
n, m, theta, phi = self.args
rv = (
sqrt((2 * n + 1) / (4 * pi) * C.factorial(n - m) / C.factorial(n + m))
* C.exp(I * m * phi)
* assoc_legendre(n, m, C.cos(theta))
)
# We can do this because of the range of theta
return rv.subs(sqrt(-cos(theta) ** 2 + 1), sin(theta))
def _eval_rewrite_as_polynomial(self, n, a, b, x):
# TODO: Make sure n \in N
k = C.Dummy("k")
kern = (
C.RisingFactorial(-n, k)
* C.RisingFactorial(a + b + n + 1, k)
* C.RisingFactorial(a + k + 1, n - k)
/ C.factorial(k)
* ((1 - x) / 2) ** k
)
return 1 / C.factorial(n) * C.Sum(kern, (k, 0, n))
def eval(cls, n, m, x):
if n.is_integer and n >= 0 and m.is_integer and abs(m) <= n:
assoc = cls.calc(int(n), abs(int(m)))
if m < 0:
assoc *= (-1)**(-m) * (C.factorial(n + m)/C.factorial(n - m))
return assoc.subs(_x, x)
if n.is_negative:
raise ValueError("%s : 1st index must be nonnegative integer (got %r)" % (cls, n))
if abs(m) > n:
raise ValueError("%s : abs('2nd index') must be <= '1st index' (got %r, %r)" % (cls, n, m))
def eval(cls, n, m, x):
if m.could_extract_minus_sign():
# P^{-m}_n ---> F * P^m_n
return S.NegativeOne**(-m) * (C.factorial(m + n)/C.factorial(n - m)) * assoc_legendre(n, -m, x)
if m == 0:
# P^0_n ---> L_n
return legendre(n, x)
if x == 0:
return 2**m*sqrt(S.Pi) / (C.gamma((1 - m - n)/2)*C.gamma(1 - (m - n)/2))
if n.is_Number and m.is_Number and n.is_integer and m.is_integer:
if n.is_negative:
raise ValueError("%s : 1st index must be nonnegative integer (got %r)" % (cls, n))
if abs(m) > n:
raise ValueError("%s : abs('2nd index') must be <= '1st index' (got %r, %r)" % (cls, n, m))
return cls._eval_at_order(int(n), abs(int(m))).subs(_x, x)
def eval(cls, n, a, b, x):
# Simplify to other polynomials
# P^{a, a}_n(x)
if a == b:
if a == -S.Half:
return C.RisingFactorial(S.Half, n) / C.factorial(n) * chebyshevt(n, x)
elif a == S.Zero:
return legendre(n, x)
elif a == S.Half:
return C.RisingFactorial(3 * S.Half, n) / C.factorial(n + 1) * chebyshevu(n, x)
else:
return C.RisingFactorial(a + 1, n) / C.RisingFactorial(2 * a + 1, n) * gegenbauer(n, a + S.Half, x)
elif b == -a:
# P^{a, -a}_n(x)
return (
C.gamma(n + a + 1) / C.gamma(n + 1) * (1 + x) ** (a / 2) / (1 - x) ** (a / 2) * assoc_legendre(n, -a, x)
)
elif a == -b:
# P^{-b, b}_n(x)
return (
C.gamma(n - b + 1) / C.gamma(n + 1) * (1 - x) ** (b / 2) / (1 + x) ** (b / 2) * assoc_legendre(n, b, x)
)
if not n.is_Number:
# Symbolic result P^{a,b}_n(x)
# P^{a,b}_n(-x) ---> (-1)**n * P^{b,a}_n(-x)
if x.could_extract_minus_sign():
return S.NegativeOne ** n * jacobi(n, b, a, -x)
# We can evaluate for some special values of x
if x == S.Zero:
return (
2 ** (-n)
* C.gamma(a + n + 1)
/ (C.gamma(a + 1) * C.factorial(n))
* C.hyper([-b - n, -n], [a + 1], -1)
)
if x == S.One:
return C.RisingFactorial(a + 1, n) / C.factorial(n)
elif x == S.Infinity:
if n.is_positive:
# TODO: Make sure a+b+2*n \notin Z
return C.RisingFactorial(a + b + n + 1, n) * S.Infinity
else:
# n is a given fixed integer, evaluate into polynomial
return jacobi_poly(n, a, b, x)
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return -p * x**2 / (n * (n - 1))
else:
return (-1)**(n // 2) * x**(n) / C.factorial(n)
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return -p * x**2 / (n*(n-1))
else:
return (-1)**(n//2)*x**(n)/C.factorial(n)
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
a, b = ((n-1)//2), 2**(n+1)
B = C.bernoulli(n+1)
F = C.factorial(n+1)
return (-1)**a * b*(b-1) * B/F * x**n
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
a, b = ((n - 1) // 2), 2**(n + 1)
B = C.bernoulli(n + 1)
F = C.factorial(n + 1)
return (-1)**a * b * (b - 1) * B / F * x**n
def taylor_term(n, x, *previous_terms):
if n == 0:
return 1 / sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
B = C.bernoulli(n+1)
F = C.factorial(n+1)
return (-1)**((n+1)//2) * 2**(n+1) * B/F * x**n
def taylor_term(n, x, *previous_terms):
if n == 0:
return 1 / sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
B = C.bernoulli(n + 1)
F = C.factorial(n + 1)
return (-1)**((n + 1) // 2) * 2**(n + 1) * B / F * x**n
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return p * (n-2)**2/(n*(n-1)) * x**2
else:
k = (n - 1) // 2
R = C.RisingFactorial(S.Half, k)
F = C.factorial(k)
return R / F * x**n / n
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return p * (n - 2)**2 / (n * (n - 1)) * x**2
else:
k = (n - 1) // 2
R = C.RisingFactorial(S.Half, k)
F = C.factorial(k)
return R / F * x**n / n
def eval(cls, n, m, x):
if m.could_extract_minus_sign():
# P^{-m}_n ---> F * P^m_n
return S.NegativeOne**(-m) * (C.factorial(m + n) /
C.factorial(n - m)) * assoc_legendre(
n, -m, x)
if m == 0:
# P^0_n ---> L_n
return legendre(n, x)
if x == 0:
return 2**m * sqrt(S.Pi) / (C.gamma(
(1 - m - n) / 2) * C.gamma(1 - (m - n) / 2))
if n.is_Number and m.is_Number and n.is_integer and m.is_integer:
if n.is_negative:
raise ValueError(
"%s : 1st index must be nonnegative integer (got %r)" %
(cls, n))
if abs(m) > n:
raise ValueError(
"%s : abs('2nd index') must be <= '1st index' (got %r, %r)"
% (cls, n, m))
return cls._eval_at_order(int(n), abs(int(m))).subs(_x, x)
def eval(cls, n, a, b, x):
# Simplify to other polynomials
# P^{a, a}_n(x)
if a == b:
if a == -S.Half:
return C.RisingFactorial(S.Half, n) / C.factorial(n) * chebyshevt(n, x)
elif a == S.Zero:
return legendre(n, x)
elif a == S.Half:
return C.RisingFactorial(3*S.Half, n) / C.factorial(n + 1) * chebyshevu(n, x)
else:
return C.RisingFactorial(a + 1, n) / C.RisingFactorial(2*a + 1, n) * gegenbauer(n, a + S.Half, x)
elif b == -a:
# P^{a, -a}_n(x)
return C.gamma(n + a + 1) / C.gamma(n + 1) * (1 + x)**(a/2) / (1 - x)**(a/2) * assoc_legendre(n, -a, x)
elif a == -b:
# P^{-b, b}_n(x)
return C.gamma(n - b + 1) / C.gamma(n + 1) * (1 - x)**(b/2) / (1 + x)**(b/2) * assoc_legendre(n, b, x)
if not n.is_Number:
# Symbolic result P^{a,b}_n(x)
# P^{a,b}_n(-x) ---> (-1)**n * P^{b,a}_n(-x)
if x.could_extract_minus_sign():
return S.NegativeOne**n * jacobi(n, b, a, -x)
# We can evaluate for some special values of x
if x == S.Zero:
return (2**(-n) * C.gamma(a + n + 1) / (C.gamma(a + 1) * C.factorial(n)) *
C.hyper([-b - n, -n], [a + 1], -1))
if x == S.One:
return C.RisingFactorial(a + 1, n) / C.factorial(n)
elif x == S.Infinity:
if n.is_positive:
# TODO: Make sure a+b+2*n \notin Z
return C.RisingFactorial(a + b + n + 1, n) * S.Infinity
else:
# n is a given fixed integer, evaluate into polynomial
return jacobi_poly(n, a, b, x)
def _eval_rewrite_as_polynomial(self, n, x):
# TODO: Should make sure n is in N_0
k = C.Dummy("k")
kern = C.RisingFactorial(-n, k) / C.factorial(k)**2 * x**k
return C.Sum(kern, (k, 0, n))
def _eval_rewrite_as_polynomial(self, n, x):
k = C.Dummy("k")
kern = S.NegativeOne**k * C.factorial(
n - k) * (2*x)**(n - 2*k) / (C.factorial(k) * C.factorial(n - 2*k))
return C.Sum(kern, (k, 0, C.floor(n/2)))
def _eval_rewrite_as_polynomial(self, n, a, x):
k = C.Dummy("k")
kern = ((-1)**k * C.RisingFactorial(a, n - k) * (2*x)**(n - 2*k) /
(C.factorial(k) * C.factorial(n - 2*k)))
return C.Sum(kern, (k, 0, C.floor(n/2)))
def _eval_expand_func(self, **hints):
n, m, theta, phi = self.args
return (sqrt(
(2 * n + 1) / (4 * pi) * C.factorial(n - m) / C.factorial(n + m)) *
C.exp(I * m * phi) * assoc_legendre(n, m, C.cos(theta)))
def _eval_rewrite_as_polynomial(self, n, x):
# TODO: Should make sure n is in N_0
k = C.Dummy("k")
kern = C.RisingFactorial(
-n, k) / (C.gamma(k + alpha + 1) * C.factorial(k)) * x**k
return C.gamma(n + alpha + 1) / C.factorial(n) * C.Sum(kern, (k, 0, n))
def _eval_rewrite_as_polynomial(self, n, x):
# TODO: Should make sure n is in N_0
k = C.Dummy("k")
kern = C.RisingFactorial(
-n, k) / (C.gamma(k + alpha + 1) * C.factorial(k)) * x**k
return C.gamma(n + alpha + 1) / C.factorial(n) * C.Sum(kern, (k, 0, n))
def _eval_rewrite_as_polynomial(self, n, a, x):
k = C.Dummy("k")
kern = ((-1)**k * C.RisingFactorial(a, n - k) * (2 * x)**(n - 2 * k) /
(C.factorial(k) * C.factorial(n - 2 * k)))
return C.Sum(kern, (k, 0, C.floor(n / 2)))
def _eval_rewrite_as_polynomial(self, n, x):
k = C.Dummy("k")
kern = (-1)**k / (C.factorial(k) *
C.factorial(n - 2 * k)) * (2 * x)**(n - 2 * k)
return C.factorial(n) * C.Sum(kern, (k, 0, C.floor(n / 2)))
def _eval_rewrite_as_polynomial(self, n, x):
# TODO: Should make sure n is in N_0
k = C.Dummy("k")
kern = C.RisingFactorial(-n, k) / C.factorial(k)**2 * x**k
return C.Sum(kern, (k, 0, n))
def _eval_rewrite_as_polynomial(self, n, x):
k = C.Dummy("k")
kern = S.NegativeOne**k * C.factorial(n - k) * (2 * x)**(n - 2 * k) / (
C.factorial(k) * C.factorial(n - 2 * k))
return C.Sum(kern, (k, 0, C.floor(n / 2)))
def _eval_expand_func(self, **hints):
n, m, theta, phi = self.args
return (sqrt((2*n + 1)/(4*pi) * C.factorial(n - m)/C.factorial(n + m)) *
C.exp(I*m*phi) * assoc_legendre(n, m, C.cos(theta)))
def _eval_rewrite_as_polynomial(self, n, x):
k = C.Dummy("k")
kern = (-1)**k / (C.factorial(k)*C.factorial(n - 2*k)) * (2*x)**(n - 2*k)
return C.factorial(n)*C.Sum(kern, (k, 0, C.floor(n/2)))
def _eval_rewrite_as_polynomial(self, n, a, b, x):
# TODO: Make sure n \in N
k = C.Dummy("k")
kern = (C.RisingFactorial(-n, k) * C.RisingFactorial(a + b + n + 1, k) * C.RisingFactorial(a + k + 1, n - k) /
C.factorial(k) * ((1 - x)/2)**k)
return 1 / C.factorial(n) * C.Sum(kern, (k, 0, n))
def _eval_rewrite_as_polynomial(self, n, m, x):
k = C.Dummy("k")
kern = C.factorial(2*n - 2*k)/(2**n*C.factorial(n - k)*C.factorial(
k)*C.factorial(n - 2*k - m))*(-1)**k*x**(n - m - 2*k)
return (1 - x**2)**(m/2) * C.Sum(kern, (k, 0, C.floor((n - m)*S.Half)))
def euler_maclaurin(self, m=0, n=0, eps=0, eval_integral=True):
"""
Return an Euler-Maclaurin approximation of self, where m is the
number of leading terms to sum directly and n is the number of
terms in the tail.
With m = n = 0, this is simply the corresponding integral
plus a first-order endpoint correction.
Returns (s, e) where s is the Euler-Maclaurin approximation
and e is the estimated error (taken to be the magnitude of
the first omitted term in the tail):
>>> from sympy.abc import k, a, b
>>> from sympy import Sum
>>> Sum(1/k, (k, 2, 5)).doit().evalf()
1.28333333333333
>>> s, e = Sum(1/k, (k, 2, 5)).euler_maclaurin()
>>> s
-log(2) + 7/20 + log(5)
>>> from sympy import sstr
>>> print(sstr((s.evalf(), e.evalf()), full_prec=True))
(1.26629073187415, 0.0175000000000000)
The endpoints may be symbolic:
>>> s, e = Sum(1/k, (k, a, b)).euler_maclaurin()
>>> s
-log(a) + log(b) + 1/(2*b) + 1/(2*a)
>>> e
Abs(-1/(12*b**2) + 1/(12*a**2))
If the function is a polynomial of degree at most 2n+1, the
Euler-Maclaurin formula becomes exact (and e = 0 is returned):
>>> Sum(k, (k, 2, b)).euler_maclaurin()
(b**2/2 + b/2 - 1, 0)
>>> Sum(k, (k, 2, b)).doit()
b**2/2 + b/2 - 1
With a nonzero eps specified, the summation is ended
as soon as the remainder term is less than the epsilon.
"""
m = int(m)
n = int(n)
f = self.function
if len(self.limits) != 1:
raise ValueError("More than 1 limit")
i, a, b = self.limits[0]
if (a > b) is True:
if a - b == 1:
return S.Zero,S.Zero
a, b = b + 1, a - 1
f = -f
s = S.Zero
if m:
if b.is_Integer and a.is_Integer:
m = min(m, b - a + 1)
if not eps:
for k in range(m):
s += f.subs(i, a + k)
else:
term = f.subs(i, a)
if term:
test = abs(term.evalf(3)) < eps
if isinstance(test, bool):
if test is True:
return s, abs(term)
else:
# a symbolic Relational class, can't go further
return term, S.Zero
s += term
for k in range(1, m):
term = f.subs(i, a + k)
if abs(term.evalf(3)) < eps:
return s, abs(term)
s += term
if b - a + 1 == m:
return s, S.Zero
a += m
x = Dummy('x')
I = C.Integral(f.subs(i, x), (x, a, b))
if eval_integral:
I = I.doit()
s += I
def fpoint(expr):
if b is S.Infinity:
return expr.subs(i, a), 0
return expr.subs(i, a), expr.subs(i, b)
fa, fb = fpoint(f)
iterm = (fa + fb)/2
g = f.diff(i)
for k in xrange(1, n + 2):
ga, gb = fpoint(g)
term = C.bernoulli(2*k)/C.factorial(2*k)*(gb - ga)
if (eps and term and abs(term.evalf(3)) < eps) or (k > n):
break
s += term
g = g.diff(i, 2, simplify=False)
return s + iterm, abs(term)
def euler_maclaurin(self, m=0, n=0, eps=0, eval_integral=True):
"""
Return an Euler-Maclaurin approximation of self, where m is the
number of leading terms to sum directly and n is the number of
terms in the tail.
With m = n = 0, this is simply the corresponding integral
plus a first-order endpoint correction.
Returns (s, e) where s is the Euler-Maclaurin approximation
and e is the estimated error (taken to be the magnitude of
the first omitted term in the tail):
>>> from sympy.abc import k, a, b
>>> from sympy import Sum
>>> Sum(1/k, (k, 2, 5)).doit().evalf()
1.28333333333333
>>> s, e = Sum(1/k, (k, 2, 5)).euler_maclaurin()
>>> s
-log(2) + 7/20 + log(5)
>>> from sympy import sstr
>>> print(sstr((s.evalf(), e.evalf()), full_prec=True))
(1.26629073187415, 0.0175000000000000)
The endpoints may be symbolic:
>>> s, e = Sum(1/k, (k, a, b)).euler_maclaurin()
>>> s
-log(a) + log(b) + 1/(2*b) + 1/(2*a)
>>> e
Abs(1/(12*b**2) - 1/(12*a**2))
If the function is a polynomial of degree at most 2n+1, the
Euler-Maclaurin formula becomes exact (and e = 0 is returned):
>>> Sum(k, (k, 2, b)).euler_maclaurin()
(b**2/2 + b/2 - 1, 0)
>>> Sum(k, (k, 2, b)).doit()
b**2/2 + b/2 - 1
With a nonzero eps specified, the summation is ended
as soon as the remainder term is less than the epsilon.
"""
m = int(m)
n = int(n)
f = self.function
if len(self.limits) != 1:
raise ValueError("More than 1 limit")
i, a, b = self.limits[0]
if (a > b) == True:
if a - b == 1:
return S.Zero,S.Zero
a, b = b + 1, a - 1
f = -f
s = S.Zero
if m:
if b.is_Integer and a.is_Integer:
m = min(m, b - a + 1)
if not eps or f.is_polynomial(i):
for k in range(m):
s += f.subs(i, a + k)
else:
term = f.subs(i, a)
if term:
test = abs(term.evalf(3)) < eps
if test == True:
return s, abs(term)
elif not (test == False):
# a symbolic Relational class, can't go further
return term, S.Zero
s += term
for k in range(1, m):
term = f.subs(i, a + k)
if abs(term.evalf(3)) < eps and term != 0:
return s, abs(term)
s += term
if b - a + 1 == m:
return s, S.Zero
a += m
x = Dummy('x')
I = C.Integral(f.subs(i, x), (x, a, b))
if eval_integral:
I = I.doit()
s += I
def fpoint(expr):
if b is S.Infinity:
return expr.subs(i, a), 0
return expr.subs(i, a), expr.subs(i, b)
fa, fb = fpoint(f)
iterm = (fa + fb)/2
g = f.diff(i)
for k in range(1, n + 2):
ga, gb = fpoint(g)
term = C.bernoulli(2*k)/C.factorial(2*k)*(gb - ga)
if (eps and term and abs(term.evalf(3)) < eps) or (k > n):
break
s += term
g = g.diff(i, 2, simplify=False)
return s + iterm, abs(term)
