def _expr_big_minus(cls, z, n):
return Integer(-1)**n * (asinh(sqrt(z)) / sqrt(z) +
n * pi * I / sqrt(z))
def test_Function():
assert mcode(f(x, y, z)) == "f[x, y, z]"
assert mcode(sin(x) ** cos(x)) == "Sin[x]^Cos[x]"
assert mcode(sign(x)) == "Sign[x]"
assert mcode(atanh(x), user_functions={"atanh": "ArcTanh"}) == "ArcTanh[x]"
assert (mcode(meijerg(((1, 1), (3, 4)), ((1,), ()), x)) ==
"MeijerG[{{1, 1}, {3, 4}}, {{1}, {}}, x]")
assert (mcode(hyper((1, 2, 3), (3, 4), x)) ==
"HypergeometricPFQ[{1, 2, 3}, {3, 4}, x]")
assert mcode(Min(x, y)) == "Min[x, y]"
assert mcode(Max(x, y)) == "Max[x, y]"
assert mcode(Max(x, 2)) == "Max[2, x]" # issue sympy/sympy#15344
assert mcode(binomial(x, y)) == "Binomial[x, y]"
assert mcode(log(x)) == "Log[x]"
assert mcode(tan(x)) == "Tan[x]"
assert mcode(cot(x)) == "Cot[x]"
assert mcode(asin(x)) == "ArcSin[x]"
assert mcode(acos(x)) == "ArcCos[x]"
assert mcode(atan(x)) == "ArcTan[x]"
assert mcode(acot(x)) == "ArcCot[x]"
assert mcode(sinh(x)) == "Sinh[x]"
assert mcode(cosh(x)) == "Cosh[x]"
assert mcode(tanh(x)) == "Tanh[x]"
assert mcode(coth(x)) == "Coth[x]"
assert mcode(asinh(x)) == "ArcSinh[x]"
assert mcode(acosh(x)) == "ArcCosh[x]"
assert mcode(atanh(x)) == "ArcTanh[x]"
assert mcode(acoth(x)) == "ArcCoth[x]"
assert mcode(sech(x)) == "Sech[x]"
assert mcode(csch(x)) == "Csch[x]"
assert mcode(erfc(x)) == "Erfc[x]"
assert mcode(conjugate(x)) == "Conjugate[x]"
assert mcode(re(x)) == "Re[x]"
assert mcode(im(x)) == "Im[x]"
assert mcode(polygamma(x, y)) == "PolyGamma[x, y]"
assert mcode(factorial(x)) == "Factorial[x]"
assert mcode(factorial2(x)) == "Factorial2[x]"
assert mcode(rf(x, y)) == "Pochhammer[x, y]"
assert mcode(gamma(x)) == "Gamma[x]"
assert mcode(zeta(x)) == "Zeta[x]"
assert mcode(Heaviside(x)) == "UnitStep[x]"
assert mcode(fibonacci(x)) == "Fibonacci[x]"
assert mcode(polylog(x, y)) == "PolyLog[x, y]"
class myfunc1(Function):
@classmethod
def eval(cls, x):
pass
class myfunc2(Function):
@classmethod
def eval(cls, x, y):
pass
pytest.raises(ValueError,
lambda: mcode(myfunc1(x),
user_functions={"myfunc1": ["Myfunc1"]}))
assert mcode(myfunc1(x),
user_functions={"myfunc1": "Myfunc1"}) == "Myfunc1[x]"
assert mcode(myfunc2(x, y),
user_functions={"myfunc2": [(lambda *x: False,
"Myfunc2")]}) == "myfunc2[x, y]"
def _expr_big_minus(cls, a, z, n):
return -1 / sqrt(1 + 1 / z) * sinh(2 * a * asinh(sqrt(z)) +
2 * a * pi * I * n)
def _expr_small_minus(cls, z):
return asinh(sqrt(z)) / sqrt(z)
def _expr_small_minus(cls, a, z):
return -sqrt(z) / sqrt(1 + z) * sinh(2 * a * asinh(sqrt(z)))
def _expr_big_minus(cls, a, z, n):
return cosh(2 * a * asinh(sqrt(z)) + 2 * a * pi * I * n)
def _expr_small_minus(cls, a, z):
return cosh(2 * a * asinh(sqrt(z)))
def test_Function():
assert mcode(f(x, y, z)) == "f[x, y, z]"
assert mcode(sin(x) ** cos(x)) == "Sin[x]^Cos[x]"
assert mcode(sign(x)) == "Sign[x]"
assert mcode(atanh(x), user_functions={"atanh": "ArcTanh"}) == "ArcTanh[x]"
assert (mcode(meijerg(((1, 1), (3, 4)), ((1,), ()), x)) ==
"MeijerG[{{1, 1}, {3, 4}}, {{1}, {}}, x]")
assert (mcode(hyper((1, 2, 3), (3, 4), x)) ==
"HypergeometricPFQ[{1, 2, 3}, {3, 4}, x]")
assert mcode(Min(x, y)) == "Min[x, y]"
assert mcode(Max(x, y)) == "Max[x, y]"
assert mcode(Max(x, 2)) == "Max[2, x]" # issue sympy/sympy#15344
assert mcode(binomial(x, y)) == "Binomial[x, y]"
assert mcode(log(x)) == "Log[x]"
assert mcode(tan(x)) == "Tan[x]"
assert mcode(cot(x)) == "Cot[x]"
assert mcode(asin(x)) == "ArcSin[x]"
assert mcode(acos(x)) == "ArcCos[x]"
assert mcode(atan(x)) == "ArcTan[x]"
assert mcode(sinh(x)) == "Sinh[x]"
assert mcode(cosh(x)) == "Cosh[x]"
assert mcode(tanh(x)) == "Tanh[x]"
assert mcode(coth(x)) == "Coth[x]"
assert mcode(sech(x)) == "Sech[x]"
assert mcode(csch(x)) == "Csch[x]"
assert mcode(erfc(x)) == "Erfc[x]"
assert mcode(conjugate(x)) == "Conjugate[x]"
assert mcode(re(x)) == "Re[x]"
assert mcode(im(x)) == "Im[x]"
assert mcode(polygamma(x, y)) == "PolyGamma[x, y]"
assert mcode(factorial(x)) == "Factorial[x]"
assert mcode(factorial2(x)) == "Factorial2[x]"
assert mcode(rf(x, y)) == "Pochhammer[x, y]"
assert mcode(gamma(x)) == "Gamma[x]"
assert mcode(zeta(x)) == "Zeta[x]"
assert mcode(asinh(x)) == "ArcSinh[x]"
assert mcode(Heaviside(x)) == "UnitStep[x]"
assert mcode(fibonacci(x)) == "Fibonacci[x]"
assert mcode(polylog(x, y)) == "PolyLog[x, y]"
assert mcode(atanh(x)) == "ArcTanh[x]"
class myfunc1(Function):
@classmethod
def eval(cls, x):
pass
class myfunc2(Function):
@classmethod
def eval(cls, x, y):
pass
pytest.raises(ValueError,
lambda: mcode(myfunc1(x),
user_functions={"myfunc1": ["Myfunc1"]}))
assert mcode(myfunc1(x),
user_functions={"myfunc1": "Myfunc1"}) == "Myfunc1[x]"
assert mcode(myfunc2(x, y),
user_functions={"myfunc2": [(lambda *x: False,
"Myfunc2")]}) == "myfunc2[x, y]"
def heurisch(f,
x,
rewrite=False,
hints=None,
mappings=None,
retries=3,
degree_offset=0,
unnecessary_permutations=None):
"""
Compute indefinite integral using heuristic Risch algorithm.
This is a heuristic approach to indefinite integration in finite
terms using the extended heuristic (parallel) Risch algorithm, based
on Manuel Bronstein's "Poor Man's Integrator" [1]_.
The algorithm supports various classes of functions including
transcendental elementary or special functions like Airy,
Bessel, Whittaker and Lambert.
Note that this algorithm is not a decision procedure. If it isn't
able to compute the antiderivative for a given function, then this is
not a proof that such a functions does not exist. One should use
recursive Risch algorithm in such case. It's an open question if
this algorithm can be made a full decision procedure.
This is an internal integrator procedure. You should use toplevel
'integrate' function in most cases, as this procedure needs some
preprocessing steps and otherwise may fail.
Parameters
==========
heurisch(f, x, rewrite=False, hints=None)
f : Expr
expression
x : Symbol
variable
rewrite : Boolean, optional
force rewrite 'f' in terms of 'tan' and 'tanh', default False.
hints : None or list
a list of functions that may appear in anti-derivate. If
None (default) - no suggestions at all, if empty list - try
to figure out.
Examples
========
>>> from diofant import tan
>>> from diofant.integrals.heurisch import heurisch
>>> from diofant.abc import x, y
>>> heurisch(y*tan(x), x)
y*log(tan(x)**2 + 1)/2
References
==========
.. [1] Manuel Bronstein's "Poor Man's Integrator",
http://www-sop.inria.fr/cafe/Manuel.Bronstein/pmint/index.html
.. [2] K. Geddes, L. Stefanus, On the Risch-Norman Integration
Method and its Implementation in Maple, Proceedings of
ISSAC'89, ACM Press, 212-217.
.. [3] J. H. Davenport, On the Parallel Risch Algorithm (I),
Proceedings of EUROCAM'82, LNCS 144, Springer, 144-157.
.. [4] J. H. Davenport, On the Parallel Risch Algorithm (III):
Use of Tangents, SIGSAM Bulletin 16 (1982), 3-6.
.. [5] J. H. Davenport, B. M. Trager, On the Parallel Risch
Algorithm (II), ACM Transactions on Mathematical
Software 11 (1985), 356-362.
See Also
========
diofant.integrals.integrals.Integral.doit
diofant.integrals.integrals.Integral
diofant.integrals.heurisch.components
"""
f = sympify(f)
if x not in f.free_symbols:
return f * x
if not f.is_Add:
indep, f = f.as_independent(x)
else:
indep = S.One
rewritables = {
(sin, cos, cot): tan,
(sinh, cosh, coth): tanh,
}
if rewrite:
for candidates, rule in rewritables.items():
f = f.rewrite(candidates, rule)
else:
for candidates in rewritables.keys():
if f.has(*candidates):
break
else:
rewrite = True
terms = components(f, x)
if hints is not None:
if not hints:
a = Wild('a', exclude=[x])
b = Wild('b', exclude=[x])
c = Wild('c', exclude=[x])
for g in set(terms): # using copy of terms
if g.is_Function:
if g.func is li:
M = g.args[0].match(a * x**b)
if M is not None:
terms.add(
x *
(li(M[a] * x**M[b]) -
(M[a] * x**M[b])**(-1 / M[b]) * Ei(
(M[b] + 1) * log(M[a] * x**M[b]) / M[b])))
# terms.add( x*(li(M[a]*x**M[b]) - (x**M[b])**(-1/M[b])*Ei((M[b]+1)*log(M[a]*x**M[b])/M[b])) )
# terms.add( x*(li(M[a]*x**M[b]) - x*Ei((M[b]+1)*log(M[a]*x**M[b])/M[b])) )
# terms.add( li(M[a]*x**M[b]) - Ei((M[b]+1)*log(M[a]*x**M[b])/M[b]) )
elif g.is_Pow:
if g.base is S.Exp1:
M = g.exp.match(a * x**2)
if M is not None:
if M[a].is_positive:
terms.add(erfi(sqrt(M[a]) * x))
else: # M[a].is_negative or unknown
terms.add(erf(sqrt(-M[a]) * x))
M = g.exp.match(a * x**2 + b * x + c)
if M is not None:
if M[a].is_positive:
terms.add(
sqrt(pi / 4 * (-M[a])) *
exp(M[c] - M[b]**2 / (4 * M[a])) * erfi(
sqrt(M[a]) * x + M[b] /
(2 * sqrt(M[a]))))
elif M[a].is_negative:
terms.add(
sqrt(pi / 4 * (-M[a])) *
exp(M[c] - M[b]**2 / (4 * M[a])) * erf(
sqrt(-M[a]) * x - M[b] /
(2 * sqrt(-M[a]))))
M = g.exp.match(a * log(x)**2)
if M is not None:
if M[a].is_positive:
terms.add(
erfi(
sqrt(M[a]) * log(x) + 1 /
(2 * sqrt(M[a]))))
if M[a].is_negative:
terms.add(
erf(
sqrt(-M[a]) * log(x) - 1 /
(2 * sqrt(-M[a]))))
elif g.exp.is_Rational and g.exp.q == 2:
M = g.base.match(a * x**2 + b)
if M is not None and M[b].is_positive:
if M[a].is_positive:
terms.add(asinh(sqrt(M[a] / M[b]) * x))
elif M[a].is_negative:
terms.add(asin(sqrt(-M[a] / M[b]) * x))
M = g.base.match(a * x**2 - b)
if M is not None and M[b].is_positive:
if M[a].is_positive:
terms.add(acosh(sqrt(M[a] / M[b]) * x))
elif M[a].is_negative:
terms.add((-M[b] / 2 * sqrt(-M[a]) * atan(
sqrt(-M[a]) * x / sqrt(M[a] * x**2 - M[b]))
))
else:
terms |= set(hints)
for g in set(terms): # using copy of terms
terms |= components(cancel(g.diff(x)), x)
# TODO: caching is significant factor for why permutations work at all. Change this.
V = _symbols('x', len(terms))
# sort mapping expressions from largest to smallest (last is always x).
mapping = list(
reversed(
list(
zip(*ordered( #
[(a[0].as_independent(x)[1], a)
for a in zip(terms, V)])))[1])) #
rev_mapping = {v: k for k, v in mapping} #
if mappings is None: #
# optimizing the number of permutations of mapping #
assert mapping[-1][0] == x # if not, find it and correct this comment
unnecessary_permutations = [mapping.pop(-1)]
mappings = permutations(mapping)
else:
unnecessary_permutations = unnecessary_permutations or []
def _substitute(expr):
return expr.subs(mapping)
for mapping in mappings:
mapping = list(mapping)
mapping = mapping + unnecessary_permutations
diffs = [_substitute(cancel(g.diff(x))) for g in terms]
denoms = [g.as_numer_denom()[1] for g in diffs]
if all(h.is_polynomial(*V)
for h in denoms) and _substitute(f).is_rational_function(*V):
denom = reduce(lambda p, q: lcm(p, q, *V), denoms)
break
else:
if not rewrite:
result = heurisch(
f,
x,
rewrite=True,
hints=hints,
unnecessary_permutations=unnecessary_permutations)
if result is not None:
return indep * result
return
numers = [cancel(denom * g) for g in diffs]
def _derivation(h):
return Add(*[d * h.diff(v) for d, v in zip(numers, V)])
def _deflation(p):
for y in V:
if not p.has(y):
continue
if _derivation(p) is not S.Zero:
c, q = p.as_poly(y).primitive()
return _deflation(c) * gcd(q, q.diff(y)).as_expr()
else:
return p
def _splitter(p):
for y in V:
if not p.has(y):
continue
if _derivation(y) is not S.Zero:
c, q = p.as_poly(y).primitive()
q = q.as_expr()
h = gcd(q, _derivation(q), y)
s = quo(h, gcd(q, q.diff(y), y), y)
c_split = _splitter(c)
if s.as_poly(y).degree() == 0:
return c_split[0], q * c_split[1]
q_split = _splitter(cancel(q / s))
return c_split[0] * q_split[0] * s, c_split[1] * q_split[1]
else:
return S.One, p
special = {}
for term in terms:
if term.is_Function:
if term.func is tan:
special[1 + _substitute(term)**2] = False
elif term.func is tanh:
special[1 + _substitute(term)] = False
special[1 - _substitute(term)] = False
elif term.func is LambertW:
special[_substitute(term)] = True
F = _substitute(f)
P, Q = F.as_numer_denom()
u_split = _splitter(denom)
v_split = _splitter(Q)
polys = set(list(v_split) + [u_split[0]] + list(special.keys()))
s = u_split[0] * Mul(*[k for k, v in special.items() if v])
polified = [p.as_poly(*V) for p in [s, P, Q]]
if None in polified:
return
# --- definitions for _integrate ---
a, b, c = [p.total_degree() for p in polified]
poly_denom = (s * v_split[0] * _deflation(v_split[1])).as_expr()
def _exponent(g):
if g.is_Pow:
if g.exp.is_Rational and g.exp.q != 1:
if g.exp.p > 0:
return g.exp.p + g.exp.q - 1
else:
return abs(g.exp.p + g.exp.q)
else:
return 1
elif not g.is_Atom and g.args:
return max([_exponent(h) for h in g.args])
else:
return 1
A, B = _exponent(f), a + max(b, c)
if A > 1 and B > 1:
monoms = itermonomials(V, A + B - 1 + degree_offset)
else:
monoms = itermonomials(V, A + B + degree_offset)
poly_coeffs = _symbols('A', len(monoms))
poly_part = Add(*[
poly_coeffs[i] * monomial for i, monomial in enumerate(ordered(monoms))
])
reducibles = set()
for poly in polys:
if poly.has(*V):
try:
factorization = factor(poly, greedy=True)
except PolynomialError:
factorization = poly
factorization = poly
if factorization.is_Mul:
reducibles |= set(factorization.args)
else:
reducibles.add(factorization)
def _integrate(field=None):
irreducibles = set()
for poly in reducibles:
for z in poly.free_symbols:
if z in V:
break # should this be: `irreducibles |= \
else: # set(root_factors(poly, z, filter=field))`
continue # and the line below deleted?
# |
# V
irreducibles |= set(root_factors(poly, z, filter=field))
log_coeffs, log_part = [], []
B = _symbols('B', len(irreducibles))
# Note: the ordering matters here
for poly, b in reversed(list(ordered(zip(irreducibles, B)))):
if poly.has(*V):
poly_coeffs.append(b)
log_part.append(b * log(poly))
# TODO: Currently it's better to use symbolic expressions here instead
# of rational functions, because it's simpler and FracElement doesn't
# give big speed improvement yet. This is because cancelation is slow
# due to slow polynomial GCD algorithms. If this gets improved then
# revise this code.
candidate = poly_part / poly_denom + Add(*log_part)
h = F - _derivation(candidate) / denom
raw_numer = h.as_numer_denom()[0]
# Rewrite raw_numer as a polynomial in K[coeffs][V] where K is a field
# that we have to determine. We can't use simply atoms() because log(3),
# sqrt(y) and similar expressions can appear, leading to non-trivial
# domains.
syms = set(poly_coeffs) | set(V)
non_syms = set()
def find_non_syms(expr):
if expr.is_Integer or expr.is_Rational:
pass # ignore trivial numbers
elif expr in syms:
pass # ignore variables
elif not expr.has(*syms):
non_syms.add(expr)
elif expr.is_Add or expr.is_Mul or expr.is_Pow:
list(map(find_non_syms, expr.args))
else:
# TODO: Non-polynomial expression. This should have been
# filtered out at an earlier stage.
raise PolynomialError
try:
find_non_syms(raw_numer)
except PolynomialError:
return
else:
ground, _ = construct_domain(non_syms, field=True)
coeff_ring = PolyRing(poly_coeffs, ground)
ring = PolyRing(V, coeff_ring)
numer = ring.from_expr(raw_numer)
solution = solve_lin_sys(numer.coeffs(), coeff_ring)
if solution is None:
return
else:
solution = [(coeff_ring.symbols[coeff_ring.index(k)], v.as_expr())
for k, v in solution.items()]
return candidate.subs(solution).subs(
list(zip(poly_coeffs, [S.Zero] * len(poly_coeffs))))
if not (F.free_symbols - set(V)):
solution = _integrate('Q')
if solution is None:
solution = _integrate()
else:
solution = _integrate()
if solution is not None:
antideriv = solution.subs(rev_mapping)
antideriv = cancel(antideriv).expand(force=True)
if antideriv.is_Add:
antideriv = antideriv.as_independent(x)[1]
return indep * antideriv
else:
if retries >= 0:
result = heurisch(
f,
x,
mappings=mappings,
rewrite=rewrite,
hints=hints,
retries=retries - 1,
unnecessary_permutations=unnecessary_permutations)
if result is not None:
return indep * result
return