def _dict_from_expr(expr, opt):
"""Transform an expression into a multinomial form. """
if expr.is_commutative is False:
raise PolynomialError('non-commutative expressions are not supported')
def _is_expandable_pow(expr):
return (expr.is_Pow and expr.exp.is_positive and expr.exp.is_Integer
and expr.base.is_Add)
if opt.expand is not False:
expr = expr.expand()
# TODO: Integrate this into expand() itself
while any(
_is_expandable_pow(i) or i.is_Mul and any(
_is_expandable_pow(j) for j in i.args)
for i in Add.make_args(expr)):
expr = expand_multinomial(expr)
while any(i.is_Mul and any(j.is_Add for j in i.args)
for i in Add.make_args(expr)):
expr = expand_mul(expr)
if opt.gens:
rep, gens = _dict_from_expr_if_gens(expr, opt)
else:
rep, gens = _dict_from_expr_no_gens(expr, opt)
return rep, opt.clone({'gens': gens})
def _eval_expand_func(self, **hints):
n, z = self.args
if n.is_Integer and n.is_nonnegative:
if z.is_Add:
coeff = z.args[0]
if coeff.is_Integer:
e = -(n + 1)
if coeff > 0:
tail = Add(
*[Pow(z - i, e) for i in range(1,
int(coeff) + 1)])
else:
tail = -Add(
*[Pow(z + i, e) for i in range(0, int(-coeff))])
return polygamma(n,
z - coeff) + (-1)**n * factorial(n) * tail
elif z.is_Mul:
coeff, z = z.as_two_terms()
if coeff.is_Integer and coeff.is_positive:
tail = [
polygamma(n, z + Rational(i, coeff))
for i in range(0, int(coeff))
]
if n == 0:
return Add(*tail) / coeff + log(coeff)
else:
return Add(*tail) / coeff**(n + 1)
z *= coeff
return polygamma(n, z)
def _eval_expand_func(self, **hints):
from diofant import Sum
n = self.args[0]
m = self.args[1] if len(self.args) == 2 else 1
if m == S.One:
if n.is_Add:
off = n.args[0]
nnew = n - off
if off.is_Integer and off.is_positive:
result = [S.One / (nnew + i)
for i in range(off, 0, -1)] + [harmonic(nnew)]
return Add(*result)
elif off.is_Integer and off.is_negative:
result = [-S.One / (nnew + i)
for i in range(0, off, -1)] + [harmonic(nnew)]
return Add(*result)
if n.is_Rational:
# Expansions for harmonic numbers at general rational arguments (u + p/q)
# Split n as u + p/q with p < q
p, q = n.as_numer_denom()
u = p // q
p = p - u * q
if u.is_nonnegative and p.is_positive and q.is_positive and p < q:
k = Dummy("k")
t1 = q * Sum(1 / (q * k + p), (k, 0, u))
t2 = 2 * Sum(
cos((2 * pi * p * k) / q) * log(sin((pi * k) / q)),
(k, 1, floor((q - 1) / Integer(2))))
t3 = (pi / 2) * cot((pi * p) / q) + log(2 * q)
return t1 + t2 - t3
return self
def sum_simplify(s):
"""Main function for Sum simplification"""
from diofant.concrete.summations import Sum
terms = Add.make_args(s)
s_t = [] # Sum Terms
o_t = [] # Other Terms
for term in terms:
if isinstance(term, Mul):
constant = 1
other = 1
s = 0
n_sum_terms = 0
for j in range(len(term.args)):
if isinstance(term.args[j], Sum):
s = term.args[j]
n_sum_terms = n_sum_terms + 1
elif term.args[j].is_number:
constant = constant * term.args[j]
else:
other = other * term.args[j]
if other == 1 and n_sum_terms == 1:
# Insert the constant inside the Sum
s_t.append(Sum(constant * s.function, *s.limits))
elif other != 1 and n_sum_terms == 1:
o_t.append(other * Sum(constant * s.function, *s.limits))
else:
o_t.append(term)
elif isinstance(term, Sum):
s_t.append(term)
else:
o_t.append(term)
used = [False] * len(s_t)
for method in range(2):
for i, s_term1 in enumerate(s_t):
if not used[i]:
for j, s_term2 in enumerate(s_t):
if not used[j] and i != j:
temp = sum_add(s_term1, s_term2, method)
if isinstance(temp, Sum):
s_t[i] = temp
s_term1 = s_t[i]
used[j] = True
result = Add(*o_t)
for i, s_term in enumerate(s_t):
if not used[i]:
result = Add(result, s_term)
return result
def fateman_poly_F_1(n):
"""Fateman's GCD benchmark: trivial GCD """
Y = [Symbol('y_' + str(i)) for i in range(0, n + 1)]
y_0, y_1 = Y[0], Y[1]
u = y_0 + Add(*[y for y in Y[1:]])
v = y_0**2 + Add(*[y**2 for y in Y[1:]])
F = ((u + 1) * (u + 2)).as_poly(*Y)
G = ((v + 1) * (-3 * y_1 * y_0**2 + y_1**2 - 1)).as_poly(*Y)
H = Poly(1, *Y)
return F, G, H
def swinnerton_dyer_poly(n, x=None, **args):
"""Generates n-th Swinnerton-Dyer polynomial in `x`. """
from .numberfields import minimal_polynomial
if n <= 0:
raise ValueError(
"can't generate Swinnerton-Dyer polynomial of order %s" % n)
if x is not None:
sympify(x)
else:
x = Dummy('x')
if n > 3:
p = 2
a = [sqrt(2)]
for i in range(2, n + 1):
p = nextprime(p)
a.append(sqrt(p))
return minimal_polynomial(Add(*a), x, polys=args.get('polys', False))
if n == 1:
ex = x**2 - 2
elif n == 2:
ex = x**4 - 10 * x**2 + 1
elif n == 3:
ex = x**8 - 40 * x**6 + 352 * x**4 - 960 * x**2 + 576
if not args.get('polys', False):
return ex
else:
return PurePoly(ex, x)
def sum_add(self, other, method=0):
"""Helper function for Sum simplification"""
from diofant.concrete.summations import Sum
if type(self) == type(other):
if method == 0:
if self.limits == other.limits:
return Sum(self.function + other.function, *self.limits)
elif method == 1:
if simplify(self.function - other.function) == 0:
if len(self.limits) == len(other.limits) == 1:
i = self.limits[0][0]
x1 = self.limits[0][1]
y1 = self.limits[0][2]
j = other.limits[0][0]
x2 = other.limits[0][1]
y2 = other.limits[0][2]
if i == j:
if x2 == y1 + 1:
return Sum(self.function, (i, x1, y2))
elif x1 == y2 + 1:
return Sum(self.function, (i, x2, y1))
return Add(self, other)
def _eval_evalf(self, prec):
try:
_roots = self.poly.nroots(n=prec_to_dps(prec))
except (DomainError, PolynomialError):
return self
else:
return Add(*[self.fun(r) for r in _roots])
def interpolating_poly(n, x, X='x', Y='y'):
"""Construct Lagrange interpolating polynomial for ``n`` data points. """
if isinstance(X, str):
X = symbols("%s:%s" % (X, n))
if isinstance(Y, str):
Y = symbols("%s:%s" % (Y, n))
coeffs = []
for i in range(0, n):
numer = []
denom = []
for j in range(0, n):
if i == j:
continue
numer.append(x - X[j])
denom.append(X[i] - X[j])
numer = Mul(*numer)
denom = Mul(*denom)
coeffs.append(numer / denom)
return Add(*[coeff * y for coeff, y in zip(coeffs, Y)])
def test_glom():
def key(x):
return x.as_coeff_Mul()[1]
def count(x):
return x.as_coeff_Mul()[0]
def newargs(cnt, arg):
return cnt * arg
rl = glom(key, count, newargs)
result = rl(Add(x, -x, 3 * x, 2, 3, evaluate=False))
expected = Add(3 * x, 5)
assert set(result.args) == set(expected.args)
result = rl(Add(*expected.args, evaluate=False))
assert set(result.args) == set(expected.args)
def doit(self, **hints):
if not hints.get('roots', True):
return self
_roots = roots(self.poly, multiple=True)
if len(_roots) < self.poly.degree():
return self
else:
return Add(*[self.fun(r) for r in _roots])
def _separatevars(expr, force):
if len(expr.free_symbols) == 1:
return expr
# don't destroy a Mul since much of the work may already be done
if expr.is_Mul:
args = list(expr.args)
changed = False
for i, a in enumerate(args):
args[i] = separatevars(a, force)
changed = changed or args[i] != a
if changed:
expr = expr.func(*args)
return expr
# get a Pow ready for expansion
if expr.is_Pow:
expr = Pow(separatevars(expr.base, force=force), expr.exp)
# First try other expansion methods
expr = expr.expand(mul=False, multinomial=False, force=force)
_expr, reps = posify(expr) if force else (expr, {})
expr = factor(_expr).subs(reps)
if not expr.is_Add:
return expr
# Find any common coefficients to pull out
args = list(expr.args)
commonc = args[0].args_cnc(cset=True, warn=False)[0]
for i in args[1:]:
commonc &= i.args_cnc(cset=True, warn=False)[0]
commonc = Mul(*commonc)
commonc = commonc.as_coeff_Mul()[1] # ignore constants
commonc_set = commonc.args_cnc(cset=True, warn=False)[0]
# remove them
for i, a in enumerate(args):
c, nc = a.args_cnc(cset=True, warn=False)
c = c - commonc_set
args[i] = Mul(*c) * Mul(*nc)
nonsepar = Add(*args)
if len(nonsepar.free_symbols) > 1:
_expr = nonsepar
_expr, reps = posify(_expr) if force else (_expr, {})
_expr = (factor(_expr)).subs(reps)
if not _expr.is_Add:
nonsepar = _expr
return commonc * nonsepar
def split_surds(expr):
"""
split an expression with terms whose squares are rationals
into a sum of terms whose surds squared have gcd equal to g
and a sum of terms with surds squared prime with g
Examples
========
>>> from diofant import sqrt
>>> from diofant.simplify.radsimp import split_surds
>>> split_surds(3*sqrt(3) + sqrt(5)/7 + sqrt(6) + sqrt(10) + sqrt(15))
(3, sqrt(2) + sqrt(5) + 3, sqrt(5)/7 + sqrt(10))
"""
args = sorted(expr.args, key=default_sort_key)
coeff_muls = [x.as_coeff_Mul() for x in args]
surds = [x[1]**2 for x in coeff_muls if x[1].is_Pow]
surds.sort(key=default_sort_key)
g, b1, b2 = _split_gcd(*surds)
g2 = g
if not b2 and len(b1) >= 2:
b1n = [x / g for x in b1]
b1n = [x for x in b1n if x != 1]
# only a common factor has been factored; split again
g1, b1n, b2 = _split_gcd(*b1n)
g2 = g * g1
a1v, a2v = [], []
for c, s in coeff_muls:
if s.is_Pow and s.exp == S.Half:
s1 = s.base
if s1 in b1:
a1v.append(c * sqrt(s1 / g2))
else:
a2v.append(c * s)
else:
a2v.append(c * s)
a = Add(*a1v)
b = Add(*a2v)
return g2, a, b
def expr_from_dict(rep, *gens):
"""Convert a multinomial form into an expression. """
result = []
for monom, coeff in rep.items():
term = [coeff]
for g, m in zip(gens, monom):
if m:
term.append(Pow(g, m))
result.append(Mul(*term))
return Add(*result)
def _print_Add(self, expr):
# purpose: print complex numbers nicely in Fortran.
# collect the purely real and purely imaginary parts:
pure_real = []
pure_imaginary = []
mixed = []
for arg in expr.args:
if arg.is_number and arg.is_extended_real:
pure_real.append(arg)
elif arg.is_number and arg.is_imaginary:
pure_imaginary.append(arg)
else:
mixed.append(arg)
if len(pure_imaginary) > 0:
if len(mixed) > 0:
PREC = precedence(expr)
term = Add(*mixed)
t = self._print(term)
if t.startswith('-'):
sign = "-"
t = t[1:]
else:
sign = "+"
if precedence(term) < PREC:
t = "(%s)" % t
return "cmplx(%s,%s) %s %s" % (
self._print(Add(*pure_real)),
self._print(-S.ImaginaryUnit * Add(*pure_imaginary)),
sign,
t,
)
else:
return "cmplx(%s,%s)" % (
self._print(Add(*pure_real)),
self._print(-S.ImaginaryUnit * Add(*pure_imaginary)),
)
else:
return CodePrinter._print_Add(self, expr)
def fateman_poly_F_2(n):
"""Fateman's GCD benchmark: linearly dense quartic inputs """
Y = [Symbol('y_' + str(i)) for i in range(0, n + 1)]
y_0 = Y[0]
u = Add(*[y for y in Y[1:]])
H = Poly((y_0 + u + 1)**2, *Y)
F = Poly((y_0 - u - 2)**2, *Y)
G = Poly((y_0 + u + 2)**2, *Y)
return H * F, H * G, H
def fateman_poly_F_3(n):
"""Fateman's GCD benchmark: sparse inputs (deg f ~ vars f) """
Y = [Symbol('y_' + str(i)) for i in range(0, n + 1)]
y_0 = Y[0]
u = Add(*[y**(n + 1) for y in Y[1:]])
H = Poly((y_0**(n + 1) + u + 1)**2, *Y)
F = Poly((y_0**(n + 1) - u - 2)**2, *Y)
G = Poly((y_0**(n + 1) + u + 2)**2, *Y)
return H * F, H * G, H
def _parallel_dict_from_expr_if_gens(exprs, opt):
"""Transform expressions into a multinomial form given generators. """
k, indices = len(opt.gens), {}
for i, g in enumerate(opt.gens):
indices[g] = i
polys = []
for expr in exprs:
poly = {}
if expr.is_Equality:
expr = expr.lhs - expr.rhs
for term in Add.make_args(expr):
coeff, monom = [], [0] * k
for factor in Mul.make_args(term):
if not _not_a_coeff(factor) and factor.is_Number:
coeff.append(factor)
else:
try:
base, exp = decompose_power(factor)
if exp < 0:
exp, base = -exp, Pow(base, -S.One)
monom[indices[base]] += exp
except KeyError:
if not factor.free_symbols.intersection(opt.gens):
coeff.append(factor)
else:
raise PolynomialError(
"%s contains an element of the generators set"
% factor)
monom = tuple(monom)
if monom in poly:
poly[monom] += Mul(*coeff)
else:
poly[monom] = Mul(*coeff)
polys.append(poly)
return polys, opt.gens
def symmetric_poly(n, *gens, **args):
"""Generates symmetric polynomial of order `n`. """
gens = _analyze_gens(gens)
if n < 0 or n > len(gens) or not gens:
raise ValueError(
"can't generate symmetric polynomial of order %s for %s" %
(n, gens))
elif not n:
poly = S.One
else:
poly = Add(*[Mul(*s) for s in subsets(gens, int(n))])
if not args.get('polys', False):
return poly
else:
return Poly(poly, *gens)
def _eval_aseries(self, n, args0, x, logx):
from diofant import Order
if args0[0] != oo:
return super(loggamma, self)._eval_aseries(n, args0, x, logx)
z = self.args[0]
m = min(n, ceiling((n + Integer(1)) / 2))
r = log(z) * (z - Rational(1, 2)) - z + log(2 * pi) / 2
l = [
bernoulli(2 * k) / (2 * k * (2 * k - 1) * z**(2 * k - 1))
for k in range(1, m)
]
o = None
if m == 0:
o = Order(1, x)
else:
o = Order(1 / z**(2 * m - 1), x)
# It is very inefficient to first add the order and then do the nseries
return (r + Add(*l))._eval_nseries(x, n, logx) + o
def eval(cls, n, sym=None):
if n.is_Number:
if n.is_Integer and n.is_nonnegative:
if n is S.Zero:
return S.One
elif n is S.One:
if sym is None:
return -S.Half
else:
return sym - S.Half
# Bernoulli numbers
elif sym is None:
if n.is_odd:
return S.Zero
n = int(n)
# Use mpmath for enormous Bernoulli numbers
if n > 500:
p, q = bernfrac(n)
return Rational(int(p), int(q))
case = n % 6
highest_cached = cls._highest[case]
if n <= highest_cached:
return cls._cache[n]
# To avoid excessive recursion when, say, bernoulli(1000) is
# requested, calculate and cache the entire sequence ... B_988,
# B_994, B_1000 in increasing order
for i in range(highest_cached + 6, n + 6, 6):
b = cls._calc_bernoulli(i)
cls._cache[i] = b
cls._highest[case] = i
return b
# Bernoulli polynomials
else:
n, result = int(n), []
for k in range(n + 1):
result.append(binomial(n, k) * cls(k) * sym**(n - k))
return Add(*result)
else:
raise ValueError("Bernoulli numbers are defined only"
" for nonnegative integer indices.")
if sym is None:
if n.is_odd and (n - 1).is_positive:
return S.Zero
def _eval_aseries(self, n, args0, x, logx):
from diofant import Order
if args0[1] != oo or not \
(self.args[0].is_Integer and self.args[0].is_nonnegative):
return super(polygamma, self)._eval_aseries(n, args0, x, logx)
z = self.args[1]
N = self.args[0]
if N == 0:
# digamma function series
# Abramowitz & Stegun, p. 259, 6.3.18
r = log(z) - 1 / (2 * z)
o = None
if n < 2:
o = Order(1 / z, x)
else:
m = ceiling((n + 1) // 2)
l = [
bernoulli(2 * k) / (2 * k * z**(2 * k))
for k in range(1, m)
]
r -= Add(*l)
o = Order(1 / z**(2 * m), x)
return r._eval_nseries(x, n, logx) + o
else:
# proper polygamma function
# Abramowitz & Stegun, p. 260, 6.4.10
# We return terms to order higher than O(x**n) on purpose
# -- otherwise we would not be able to return any terms for
# quite a long time!
fac = gamma(N)
e0 = fac + N * fac / (2 * z)
m = ceiling((n + 1) // 2)
for k in range(1, m):
fac = fac * (2 * k + N - 1) * (2 * k + N - 2) / ((2 * k) *
(2 * k - 1))
e0 += bernoulli(2 * k) * fac / z**(2 * k)
o = Order(1 / z**(2 * m), x)
if n == 0:
o = Order(1 / z, x)
elif n == 1:
o = Order(1 / z**2, x)
r = e0 + o
return (-1 * (-1 / z)**N * r)._eval_nseries(x, n, logx)
def mrv_leadterm(e, x):
"""
Compute the leading term of the series.
Returns
=======
tuple
The leading term `c_0 w^{e_0}` of the series of `e` in terms
of the most rapidly varying subexpression `w` in form of
the pair ``(c0, e0)`` of Expr.
Examples
========
>>> from diofant import Symbol, exp
>>> x = Symbol('x', real=True, positive=True)
>>> mrv_leadterm(1/exp(-x + exp(-x)) - exp(x), x)
(-1, 0)
"""
if not e.has(x):
return e, S.Zero
e = e.replace(lambda f: f.is_Pow and f.base != S.Exp1 and f.exp.has(x),
lambda f: exp(log(f.base) * f.exp))
e = e.replace(
lambda f: f.is_Mul and sum(a.is_Pow for a in f.args) > 1,
lambda f: Mul(
exp(Add(*[a.exp for a in f.args
if a.is_Pow and a.base is S.Exp1])), *
[a for a in f.args if not a.is_Pow or a.base is not S.Exp1]))
# The positive dummy, w, is used here so log(w*2) etc. will expand.
# TODO: For limits of complex functions, the algorithm would have to
# be improved, or just find limits of Re and Im components separately.
w = Dummy("w", real=True, positive=True)
e, logw = rewrite(e, x, w)
lt = e.compute_leading_term(w, logx=logw)
return lt.as_coeff_exponent(w)
def parse_hints(hints):
"""Split hints into (n, funcs, iterables, gens)."""
n = 1
funcs, iterables, gens = [], [], []
for e in hints:
if isinstance(e, (int, Integer)):
n = e
elif isinstance(e, FunctionClass):
funcs.append(e)
elif iterable(e):
iterables.append((e[0], e[1:]))
# XXX sin(x+2y)?
# Note: we go through polys so e.g.
# sin(-x) -> -sin(x) -> sin(x)
gens.extend(
parallel_poly_from_expr([e[0](x) for x in e[1:]] +
[e[0](Add(*e[1:]))])[1].gens)
else:
gens.append(e)
return n, funcs, iterables, gens
def _entry(self, i, j, expand=True):
coeff, matrices = self.as_coeff_matrices()
if len(matrices) == 1: # situation like 2*X, matmul is just X
return coeff * matrices[0][i, j]
head, tail = matrices[0], matrices[1:]
if len(tail) == 0:
raise ValueError("lenth of tail cannot be 0")
X = head
Y = MatMul(*tail)
from diofant.core.symbol import Dummy
from diofant.concrete.summations import Sum
from diofant.matrices import ImmutableMatrix
k = Dummy('k', integer=True)
if X.has(ImmutableMatrix) or Y.has(ImmutableMatrix):
return coeff * Add(*[X[i, k] * Y[k, j] for k in range(X.cols)])
result = Sum(coeff * X[i, k] * Y[k, j], (k, 0, X.cols - 1))
return result.doit() if expand else result
def ratsimp(expr):
"""
Put an expression over a common denominator, cancel and reduce.
Examples
========
>>> from diofant import ratsimp
>>> from diofant.abc import x, y
>>> ratsimp(1/x + 1/y)
(x + y)/(x*y)
"""
f, g = cancel(expr).as_numer_denom()
try:
Q, r = reduced(f, [g], field=True, expand=False)
except ComputationFailed:
return f / g
return Add(*Q) + cancel(r / g)
def _together(expr):
if isinstance(expr, Basic):
if expr.is_Atom or (expr.is_Function and not deep):
return expr
elif expr.is_Add:
return gcd_terms(list(map(_together, Add.make_args(expr))))
elif expr.is_Pow:
base = _together(expr.base)
if deep:
exp = _together(expr.exp)
else:
exp = expr.exp
return expr.__class__(base, exp)
else:
return expr.__class__(*[_together(arg) for arg in expr.args])
elif iterable(expr):
return expr.__class__([_together(ex) for ex in expr])
return expr
def _sqrtdenest0(expr):
"""Returns expr after denesting its arguments."""
if is_sqrt(expr):
n, d = expr.as_numer_denom()
if d is S.One: # n is a square root
if n.base.is_Add:
args = sorted(n.base.args, key=default_sort_key)
if len(args) > 2 and all((x**2).is_Integer for x in args):
try:
return _sqrtdenest_rec(n)
except SqrtdenestStopIteration:
pass
expr = sqrt(_mexpand(Add(*[_sqrtdenest0(x) for x in args])))
return _sqrtdenest1(expr)
else:
n, d = [_sqrtdenest0(i) for i in (n, d)]
return n / d
if isinstance(expr, Expr):
args = expr.args
if args:
return expr.func(*[_sqrtdenest0(a) for a in args])
return expr
def test_Identity_doit():
Inn = Identity(Add(n, n, evaluate=False))
assert isinstance(Inn.rows, Add)
assert Inn.doit() == Identity(2 * n)
assert isinstance(Inn.doit().rows, Mul)
def test_ZeroMatrix_doit():
Znn = ZeroMatrix(Add(n, n, evaluate=False), n)
assert isinstance(Znn.rows, Add)
assert Znn.doit() == ZeroMatrix(2 * n, n)
assert isinstance(Znn.doit().rows, Mul)
