def eval(cls, a, z):
from sympy import unpolarify, I, factorial, exp, expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z is S.Zero:
# TODO: Holds only for Re(a) > 0:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and (a > 0) == True:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and (a <= 0) == True:
if n != 0:
return -2*pi*I*n*(-1)**(-a)/factorial(-a) + uppergamma(a, nx)
elif n != 0:
return gamma(a)*(1 - exp(2*pi*I*n*a)) + exp(2*pi*I*n*a)*uppergamma(a, nx)
# Special values.
if a.is_Number:
# TODO this should be non-recursive
if a is S.One:
return C.exp(-z)
elif a is S.Half:
return sqrt(pi)*(1 - erf(sqrt(z))) # TODO could use erfc...
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
return b*cls(b, z) + z**b * C.exp(-z)
elif b.is_Integer:
return expint(-b, z)*unpolarify(z)**(b + 1)
if not a.is_Integer:
return (cls(a + 1, z) - z**a * C.exp(-z))/a
python类factorial()的实例源码
def _eval_rewrite_as_zeta(self, n, z):
if n >= S.One:
return (-1)**(n + 1)*C.factorial(n)*zeta(n + 1, z)
else:
return self
def _eval_rewrite_as_harmonic(self, n, z):
if n.is_integer:
if n == S.Zero:
return harmonic(z - 1) - S.EulerGamma
else:
return S.NegativeOne**(n+1) * C.factorial(n) * (C.zeta(n+1) - harmonic(z-1, n+1))
def __init__(self, states, interval, method, differential_order=0):
"""
:param states: tuple of states in beginning and end of interval
:param interval: time interval (tuple)
:param method: method to use (``poly`` or ``tanh``)
:param differential_order: grade of differential flatness :math:`\\gamma`
"""
self.yd = states
self.t0 = interval[0]
self.t1 = interval[1]
self.dt = interval[1] - interval[0]
# setup symbolic expressions
if method == "tanh":
tau, sigma = sp.symbols('tau, sigma')
# use a gevrey-order of alpha = 1 + 1/sigma
sigma = 1.1
phi = .5*(1 + sp.tanh(2*(2*tau - 1)/((4*tau*(1-tau))**sigma)))
elif method == "poly":
gamma = differential_order # + 1 # TODO check this against notes
tau, k = sp.symbols('tau, k')
alpha = sp.factorial(2 * gamma + 1)
f = sp.binomial(gamma, k) * (-1) ** k * tau ** (gamma + k + 1) / (gamma + k + 1)
phi = alpha / sp.factorial(gamma) ** 2 * sp.summation(f, (k, 0, gamma))
else:
raise NotImplementedError("method {} not implemented!".format(method))
# differentiate phi(tau), index in list corresponds to order
dphi_sym = [phi] # init with phi(tau)
for order in range(differential_order):
dphi_sym.append(dphi_sym[-1].diff(tau))
# lambdify
self.dphi_num = []
for der in dphi_sym:
self.dphi_num.append(sp.lambdify(tau, der, 'numpy'))
def temporal_derived_power_series(z, C, up_to_order, series_termination_index, spatial_der_order=0):
"""
compute the temporal derivatives
q^{(n)}(z) = \sum_{k=0}^{series_termination_index} C[k][n,:] z^k / k!
from n=0 to n=up_to_order
:param z: scalar
:param C:
:param up_to_order:
:param series_termination_index:
:param spatial_der_order:
:return: Q = np.array( [q^{(0)}, ... , q^{(up_to_order)}] )
"""
if not isinstance(z, Number):
raise TypeError
if any([C[i].shape[0] - 1 < up_to_order for i in range(series_termination_index+1)]):
raise ValueError
len_t = C[0].shape[1]
Q = np.nan*np.zeros((up_to_order+1, len_t))
for i in range(up_to_order+1):
sum_Q = np.zeros(len_t)
for j in range(series_termination_index+1-spatial_der_order):
sum_Q += C[j+spatial_der_order][i, :]*z**(j)/sm.factorial(j)
Q[i, :] = sum_Q
return Q
def pdf(self, k):
return self.lamda**k / factorial(k) * exp(-self.lamda)
def test_expressions_failing():
assert residue(1/(x**4 + 1), x, exp(I*pi/4)) == -(S(1)/4 + I/4)/sqrt(2)
n = Symbol('n', integer=True, positive=True)
assert residue(exp(z)/(z - pi*I/4*a)**n, z, I*pi*a) == \
exp(I*pi*a/4)/factorial(n - 1)
assert residue(1/(x**2 + a**2)**2, x, a*I) == -I/4/a**3
def test_factorial():
from sympy import factorial, E
f = factorial(x)
assert limit(f, x, oo) == oo
assert limit(x/f, x, oo) == 0
# see Stirling's approximation:
# http://en.wikipedia.org/wiki/Stirling's_approximation
assert limit(f/(sqrt(2*pi*x)*(x/E)**x), x, oo) == 1
assert limit(f, x, -oo) == factorial(-oo)
assert limit(f, x, x**2) == factorial(x**2)
assert limit(f, x, -x**2) == factorial(-x**2)
def test_issue_9115():
n = Dummy('n', integer=True, nonnegative=True)
assert (factorial(n) >= 1) == True
assert (factorial(n) < 1) == False
def taylor_term(self, n, x, *previous_terms):
"""General method for the taylor term.
This method is slow, because it differentiates n-times. Subclasses can
redefine it to make it faster by using the "previous_terms".
"""
from sympy import Dummy, factorial
x = sympify(x)
_x = Dummy('x')
return self.subs(x, _x).diff(_x, n).subs(_x, x).subs(x, 0) * x**n / factorial(n)
def test_gosper_term():
assert gosper_term((4*k + 1)*factorial(
k)/factorial(2*k + 1), k) == (-k - S(1)/2)/(k + S(1)/4)
def test_gosper_sum():
assert gosper_sum(1, (k, 0, n)) == 1 + n
assert gosper_sum(k, (k, 0, n)) == n*(1 + n)/2
assert gosper_sum(k**2, (k, 0, n)) == n*(1 + n)*(1 + 2*n)/6
assert gosper_sum(k**3, (k, 0, n)) == n**2*(1 + n)**2/4
assert gosper_sum(2**k, (k, 0, n)) == 2*2**n - 1
assert gosper_sum(factorial(k), (k, 0, n)) is None
assert gosper_sum(binomial(n, k), (k, 0, n)) is None
assert gosper_sum(factorial(k)/k**2, (k, 0, n)) is None
assert gosper_sum((k - 3)*factorial(k), (k, 0, n)) is None
assert gosper_sum(k*factorial(k), k) == factorial(k)
assert gosper_sum(
k*factorial(k), (k, 0, n)) == n*factorial(n) + factorial(n) - 1
assert gosper_sum((-1)**k*binomial(n, k), (k, 0, n)) == 0
assert gosper_sum((
-1)**k*binomial(n, k), (k, 0, m)) == -(-1)**m*(m - n)*binomial(n, m)/n
assert gosper_sum((4*k + 1)*factorial(k)/factorial(2*k + 1), (k, 0, n)) == \
(2*factorial(2*n + 1) - factorial(n))/factorial(2*n + 1)
# issue 6033:
assert gosper_sum(
n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b)), \
(n, 0, m)) == -a*b*(exp(m*log(a))*exp(m*log(b))*factorial(a)* \
factorial(b) - factorial(a + m)*factorial(b + m))/(factorial(a)* \
factorial(b)*factorial(a + m)*factorial(b + m))
def test_gosper_sum_AeqB_part1():
f1a = n**4
f1b = n**3*2**n
f1c = 1/(n**2 + sqrt(5)*n - 1)
f1d = n**4*4**n/binomial(2*n, n)
f1e = factorial(3*n)/(factorial(n)*factorial(n + 1)*factorial(n + 2)*27**n)
f1f = binomial(2*n, n)**2/((n + 1)*4**(2*n))
f1g = (4*n - 1)*binomial(2*n, n)**2/((2*n - 1)**2*4**(2*n))
f1h = n*factorial(n - S(1)/2)**2/factorial(n + 1)**2
g1a = m*(m + 1)*(2*m + 1)*(3*m**2 + 3*m - 1)/30
g1b = 26 + 2**(m + 1)*(m**3 - 3*m**2 + 9*m - 13)
g1c = (m + 1)*(m*(m**2 - 7*m + 3)*sqrt(5) - (
3*m**3 - 7*m**2 + 19*m - 6))/(2*m**3*sqrt(5) + m**4 + 5*m**2 - 1)/6
g1d = -S(2)/231 + 2*4**m*(m + 1)*(63*m**4 + 112*m**3 + 18*m**2 -
22*m + 3)/(693*binomial(2*m, m))
g1e = -S(9)/2 + (81*m**2 + 261*m + 200)*factorial(
3*m + 2)/(40*27**m*factorial(m)*factorial(m + 1)*factorial(m + 2))
g1f = (2*m + 1)**2*binomial(2*m, m)**2/(4**(2*m)*(m + 1))
g1g = -binomial(2*m, m)**2/4**(2*m)
g1h = 4*pi -(2*m + 1)**2*(3*m + 4)*factorial(m - S(1)/2)**2/factorial(m + 1)**2
g = gosper_sum(f1a, (n, 0, m))
assert g is not None and simplify(g - g1a) == 0
g = gosper_sum(f1b, (n, 0, m))
assert g is not None and simplify(g - g1b) == 0
g = gosper_sum(f1c, (n, 0, m))
assert g is not None and simplify(g - g1c) == 0
g = gosper_sum(f1d, (n, 0, m))
assert g is not None and simplify(g - g1d) == 0
g = gosper_sum(f1e, (n, 0, m))
assert g is not None and simplify(g - g1e) == 0
g = gosper_sum(f1f, (n, 0, m))
assert g is not None and simplify(g - g1f) == 0
g = gosper_sum(f1g, (n, 0, m))
assert g is not None and simplify(g - g1g) == 0
g = gosper_sum(f1h, (n, 0, m))
# need to call rewrite(gamma) here because we have terms involving
# factorial(1/2)
assert g is not None and simplify(g - g1h).rewrite(gamma) == 0
def test_gosper_nan():
a = Symbol('a', positive=True)
b = Symbol('b', positive=True)
n = Symbol('n', integer=True)
m = Symbol('m', integer=True)
f2d = n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b))
g2d = 1/(factorial(a - 1)*factorial(
b - 1)) - a**(m + 1)*b**(m + 1)/(factorial(a + m)*factorial(b + m))
g = gosper_sum(f2d, (n, 0, m))
assert simplify(g - g2d) == 0
def test_rsolve_hyper():
assert rsolve_hyper([-1, -1, 1], 0, n) in [
C0*(S.Half - S.Half*sqrt(5))**n + C1*(S.Half + S.Half*sqrt(5))**n,
C1*(S.Half - S.Half*sqrt(5))**n + C0*(S.Half + S.Half*sqrt(5))**n,
]
assert rsolve_hyper([n**2 - 2, -2*n - 1, 1], 0, n) in [
C0*rf(sqrt(2), n) + C1*rf(-sqrt(2), n),
C1*rf(sqrt(2), n) + C0*rf(-sqrt(2), n),
]
assert rsolve_hyper([n**2 - k, -2*n - 1, 1], 0, n) in [
C0*rf(sqrt(k), n) + C1*rf(-sqrt(k), n),
C1*rf(sqrt(k), n) + C0*rf(-sqrt(k), n),
]
assert rsolve_hyper(
[2*n*(n + 1), -n**2 - 3*n + 2, n - 1], 0, n) == C1*factorial(n) + C0*2**n
assert rsolve_hyper(
[n + 2, -(2*n + 3)*(17*n**2 + 51*n + 39), n + 1], 0, n) == None
assert rsolve_hyper([-n - 1, -1, 1], 0, n) == None
assert rsolve_hyper([-1, 1], n, n).expand() == C0 + n**2/2 - n/2
assert rsolve_hyper([-1, 1], 1 + n, n).expand() == C0 + n**2/2 + n/2
assert rsolve_hyper([-1, 1], 3*(n + n**2), n).expand() == C0 + n**3 - n
assert rsolve_hyper([-a, 1],0,n).expand() == C0*a**n
assert rsolve_hyper([-a, 0, 1], 0, n).expand() == (-1)**n*C1*a**(n/2) + C0*a**(n/2)
assert rsolve_hyper([1, 1, 1], 0, n).expand() == \
C0*(-S(1)/2 - sqrt(3)*I/2)**n + C1*(-S(1)/2 + sqrt(3)*I/2)**n
assert rsolve_hyper([1, -2*n/a - 2/a, 1], 0, n) is None
def test_factorial():
n = sympy.Symbol('n')
assert theano_code(sympy.factorial(n))
def test_hyper_rewrite_sum():
from sympy import RisingFactorial, factorial, Dummy, Sum
_k = Dummy("k")
assert replace_dummy(hyper((1, 2), (1, 3), x).rewrite(Sum), _k) == \
Sum(x**_k / factorial(_k) * RisingFactorial(2, _k) /
RisingFactorial(3, _k), (_k, 0, oo))
assert hyper((1, 2, 3), (-1, 3), z).rewrite(Sum) == \
hyper((1, 2, 3), (-1, 3), z)
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
k = floor((n - 1)/S(2))
if len(previous_terms) > 2:
return -previous_terms[-2] * x**2 * (n - 2)/(n*k)
else:
return 2*(-1)**k * x**n/(n*factorial(k)*sqrt(S.Pi))
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
k = floor((n - 1)/S(2))
if len(previous_terms) > 2:
return previous_terms[-2] * x**2 * (n - 2)/(n*k)
else:
return 2 * x**n/(n*factorial(k)*sqrt(S.Pi))
def _eval_rewrite_as_Ei(self, nu, z):
from sympy import exp_polar, unpolarify, exp, factorial
if nu == 1:
return -Ei(z*exp_polar(-I*pi)) - I*pi
elif nu.is_Integer and nu > 1:
# DLMF, 8.19.7
x = -unpolarify(z)
return x**(nu - 1)/factorial(nu - 1)*E1(z).rewrite(Ei) + \
exp(x)/factorial(nu - 1) * \
Add(*[factorial(nu - k - 2)*x**k for k in range(nu - 1)])
else:
return self
