def fdiff(self, argindex=3):
if argindex != 3:
raise ArgumentIndexError(self, argindex)
nap = Tuple(*[a + 1 for a in self.ap])
nbq = Tuple(*[b + 1 for b in self.bq])
fac = Mul(*self.ap) / Mul(*self.bq)
return fac * hyper(nap, nbq, self.argument)
def test_tensorsymmetry():
sym = tensorsymmetry([1] * 2)
sym1 = TensorSymmetry(get_symmetric_group_sgs(2))
assert sym == sym1
sym = tensorsymmetry([2])
sym1 = TensorSymmetry(get_symmetric_group_sgs(2, 1))
assert sym == sym1
sym2 = tensorsymmetry()
assert sym2.base == Tuple() and sym2.generators == Tuple(Permutation(1))
pytest.raises(NotImplementedError, lambda: tensorsymmetry([2, 1]))
def __new__(cls, function, limits):
fun = sympify(function)
if not is_sequence(fun) or len(fun) != 2:
raise ValueError("Function argument should be (x(t), y(t)) "
"but got %s" % str(function))
if not is_sequence(limits) or len(limits) != 3:
raise ValueError("Limit argument should be (t, tmin, tmax) "
"but got %s" % str(limits))
return GeometryEntity.__new__(cls, Tuple(*fun), Tuple(*limits))
def _eval_rewrite_as_Sum(self, ap, bq, z):
from diofant.functions import factorial, RisingFactorial, Piecewise
from diofant import Sum
n = Dummy("n", integer=True)
rfap = Tuple(*[RisingFactorial(a, n) for a in ap])
rfbq = Tuple(*[RisingFactorial(b, n) for b in bq])
coeff = Mul(*rfap) / Mul(*rfbq)
return Piecewise((Sum(coeff * z**n / factorial(n),
(n, 0, oo)), self.convergence_statement),
(self, True))
def __new__(cls, *args, **kwargs):
evaluate = kwargs.get('evaluate', global_evaluate[0])
if iterable(args[0]):
if isinstance(args[0], Point) and not evaluate:
return args[0]
args = args[0]
# unpack the arguments into a friendly Tuple
# if we were already a Point, we're doing an excess
# iteration, but we'll worry about efficiency later
coords = Tuple(*args)
if any(a.is_number and im(a) for a in coords):
raise ValueError('Imaginary coordinates not permitted.')
# Turn any Floats into rationals and simplify
# any expressions before we instantiate
if evaluate:
coords = coords.xreplace(dict(
[(f, simplify(nsimplify(f, rational=True)))
for f in coords.atoms(Float)]))
if len(coords) == 2:
return Point2D(coords, **kwargs)
if len(coords) == 3:
return Point3D(coords, **kwargs)
return GeometryEntity.__new__(cls, *coords)
def __new__(cls, *args, **kwargs):
from diofant.geometry.point import Point
args = [
Tuple(*a)
if is_sequence(a) and not isinstance(a, Point) else sympify(a)
for a in args
]
return Basic.__new__(cls, *args)
def _process_limits(*symbols):
"""Process the list of symbols and convert them to canonical limits,
storing them as Tuple(symbol, lower, upper). The orientation of
the function is also returned when the upper limit is missing
so (x, 1, None) becomes (x, None, 1) and the orientation is changed.
"""
limits = []
orientation = 1
for V in symbols:
if isinstance(V, (Dummy, Symbol)):
limits.append(Tuple(V))
continue
elif is_sequence(V, Tuple):
V = sympify(flatten(V))
if V[0].is_Symbol:
newsymbol = V[0]
if len(V) == 2 and isinstance(V[1], Interval):
V[1:] = [V[1].start, V[1].end]
if len(V) == 3:
if V[1] is None and V[2] is not None:
nlim = [V[2]]
elif V[1] is not None and V[2] is None:
orientation *= -1
nlim = [V[1]]
elif V[1] is None and V[2] is None:
nlim = []
else:
nlim = V[1:]
limits.append(Tuple(newsymbol, *nlim))
continue
elif len(V) == 1 or (len(V) == 2 and V[1] is None):
limits.append(Tuple(newsymbol))
continue
elif len(V) == 2:
limits.append(Tuple(newsymbol, V[1]))
continue
raise ValueError('Invalid limits given: %s' % str(symbols))
return limits, orientation
def __new__(cls, function, *symbols, **assumptions):
# Any embedded piecewise functions need to be brought out to the
# top level so that integration can go into piecewise mode at the
# earliest possible moment.
#
# This constructor only differs from ExprWithLimits
# in the application of the orientation variable. Perhaps merge?
function = sympify(function)
if hasattr(function, 'func') and function.func is Equality:
lhs = function.lhs
rhs = function.rhs
return Equality(cls(lhs, *symbols, **assumptions),
cls(rhs, *symbols, **assumptions))
function = piecewise_fold(function)
if function is S.NaN:
return S.NaN
if symbols:
limits, orientation = _process_limits(*symbols)
else:
# symbol not provided -- we can still try to compute a general form
free = function.free_symbols
if len(free) != 1:
raise ValueError(
" specify dummy variables for %s. If the integrand contains"
" more than one free symbol, an integration variable should"
" be supplied explicitly e.g., integrate(f(x, y), x)" %
function)
limits, orientation = [Tuple(s) for s in free], 1
# denest any nested calls
while cls == type(function):
limits = list(function.limits) + limits
function = function.function
obj = Expr.__new__(cls, **assumptions)
arglist = [orientation * function]
arglist.extend(limits)
obj._args = tuple(arglist)
return obj
def __new__(cls, *args, **kwargs):
eval = kwargs.get('evaluate', global_evaluate[0])
if isinstance(args[0], (Point, Point3D)):
if not eval:
return args[0]
args = args[0].args
else:
if iterable(args[0]):
args = args[0]
if len(args) not in (2, 3):
raise TypeError(
"Enter a 2 or 3 dimensional point")
coords = Tuple(*args)
if len(coords) == 2:
coords += (S.Zero,)
if eval:
coords = coords.xreplace(dict(
[(f, simplify(nsimplify(f, rational=True)))
for f in coords.atoms(Float)]))
return GeometryEntity.__new__(cls, *coords)
def __new__(cls, function, *symbols, **assumptions):
# Any embedded piecewise functions need to be brought out to the
# top level so that integration can go into piecewise mode at the
# earliest possible moment.
function = sympify(function)
if hasattr(function, 'func') and function.func is Equality:
lhs = function.lhs
rhs = function.rhs
return Equality(cls(lhs, *symbols, **assumptions),
cls(rhs, *symbols, **assumptions))
function = piecewise_fold(function)
if function is S.NaN:
return S.NaN
if symbols:
limits, orientation = _process_limits(*symbols)
else:
# symbol not provided -- we can still try to compute a general form
free = function.free_symbols
if len(free) != 1:
raise ValueError("specify dummy variables for %s" % function)
limits, orientation = [Tuple(s) for s in free], 1
# denest any nested calls
while cls == type(function):
limits = list(function.limits) + limits
function = function.function
# Only limits with lower and upper bounds are supported; the indefinite form
# is not supported
if any(len(l) != 3 or None in l for l in limits):
raise ValueError(
'ExprWithLimits requires values for lower and upper bounds.')
obj = Expr.__new__(cls, **assumptions)
arglist = [function]
arglist.extend(limits)
obj._args = tuple(arglist)
return obj
def __new__(cls, *args, **kwargs):
eval = kwargs.get('evaluate', global_evaluate[0])
check = True
if isinstance(args[0], Point2D):
if not eval:
return args[0]
args = args[0].args
check = False
else:
if iterable(args[0]):
args = args[0]
if len(args) != 2:
raise ValueError(
"Only two dimensional points currently supported")
coords = Tuple(*args)
if check:
if any(a.is_number and im(a) for a in coords):
raise ValueError('Imaginary args not permitted.')
if eval:
coords = coords.xreplace(dict(
[(f, simplify(nsimplify(f, rational=True)))
for f in coords.atoms(Float)]))
return GeometryEntity.__new__(cls, *coords)
def verify_numerically(f, g, z=None, tol=1.0e-6, a=2, b=-1, c=3, d=1):
"""
Test numerically that f and g agree when evaluated in the argument z.
If z is None, all symbols will be tested. This routine does not test
whether there are Floats present with precision higher than 15 digits
so if there are, your results may not be what you expect due to round-
off errors.
Examples
========
>>> from diofant import sin, cos
>>> from diofant.abc import x
>>> from diofant.utilities.randtest import verify_numerically as tn
>>> tn(sin(x)**2 + cos(x)**2, 1, x)
true
"""
f, g, z = Tuple(f, g, z)
z = [z] if isinstance(z, Symbol) else (f.free_symbols | g.free_symbols)
reps = list(zip(z, [random_complex_number(a, b, c, d) for zi in z]))
z1 = f.subs(reps).n()
z2 = g.subs(reps).n()
return comp(z1, z2, tol)
def __new__(cls, *args):
if len(args) == 5:
args = [(args[0], args[1]), (args[2], args[3]), args[4]]
if len(args) != 3:
raise TypeError("args must be either as, as', bs, bs', z or "
"as, bs, z")
def tr(p):
if len(p) != 2:
raise TypeError("wrong argument")
return TupleArg(_prep_tuple(p[0]), _prep_tuple(p[1]))
arg0, arg1 = tr(args[0]), tr(args[1])
if Tuple(arg0, arg1).has(S.Infinity, S.ComplexInfinity,
S.NegativeInfinity):
raise ValueError("G-function parameters must be finite")
if any((a - b).is_integer and (a - b).is_positive for a in arg0[0]
for b in arg1[0]):
raise ValueError("no parameter a1, ..., an may differ from "
"any b1, ..., bm by a positive integer")
# TODO should we check convergence conditions?
return Function.__new__(cls, arg0, arg1, args[2])
def bother(self):
""" Second set of denominator parameters. """
return Tuple(*self.args[1][1])
def bq(self):
""" Combined denominator parameters. """
return Tuple(*(self.args[1][0] + self.args[1][1]))
def bm(self):
""" First set of denominator parameters. """
return Tuple(*self.args[1][0])
def aother(self):
""" Second set of numerator parameters. """
return Tuple(*self.args[0][1])
def ap(self):
""" Combined numerator parameters. """
return Tuple(*(self.args[0][0] + self.args[0][1]))
def _eval_derivative(self, sym):
"""Evaluate the derivative of the current Integral object by
differentiating under the integral sign [1], using the Fundamental
Theorem of Calculus [2] when possible.
Whenever an Integral is encountered that is equivalent to zero or
has an integrand that is independent of the variable of integration
those integrals are performed. All others are returned as Integral
instances which can be resolved with doit() (provided they are integrable).
References
==========
.. [1] http://en.wikipedia.org/wiki/Differentiation_under_the_integral_sign
.. [2] http://en.wikipedia.org/wiki/Fundamental_theorem_of_calculus
Examples
========
>>> from diofant import Integral
>>> from diofant.abc import x, y
>>> i = Integral(x + y, y, (y, 1, x))
>>> i.diff(x)
Integral(x + y, (y, x)) + Integral(1, y, (y, 1, x))
>>> i.doit().diff(x) == i.diff(x).doit()
True
>>> i.diff(y)
0
The previous must be true since there is no y in the evaluated integral:
>>> i.free_symbols == {x}
True
>>> i.doit()
2*x**3/3 - x/2 - 1/6
"""
# differentiate under the integral sign; we do not
# check for regularity conditions (TODO), see issue 4215
# get limits and the function
f, limits = self.function, list(self.limits)
# the order matters if variables of integration appear in the limits
# so work our way in from the outside to the inside.
limit = limits.pop(-1)
if len(limit) == 3:
x, a, b = limit
elif len(limit) == 2:
x, b = limit
a = None
else:
a = b = None
x = limit[0]
if limits: # f is the argument to an integral
f = self.func(f, *tuple(limits))
# assemble the pieces
def _do(f, ab):
dab_dsym = diff(ab, sym)
if not dab_dsym:
return S.Zero
if isinstance(f, Integral):
limits = [(x, x) if (len(l) == 1 and l[0] == x) else l
for l in f.limits]
f = self.func(f.function, *limits)
return f.subs(x, ab) * dab_dsym
rv = 0
if b is not None:
rv += _do(f, b)
if a is not None:
rv -= _do(f, a)
if len(limit) == 1 and sym == x:
# the dummy variable *is* also the real-world variable
arg = f
rv += arg
else:
# the dummy variable might match sym but it's
# only a dummy and the actual variable is determined
# by the limits, so mask off the variable of integration
# while differentiating
u = Dummy('u')
arg = f.subs(x, u).diff(sym).subs(u, x)
rv += self.func(arg, Tuple(x, a, b))
return rv
def bq(self):
""" Denominator parameters of the hypergeometric function. """
return Tuple(*self.args[1])
def ap(self):
""" Numerator parameters of the hypergeometric function. """
return Tuple(*self.args[0])
def __init__(self, data, **kwarg):
"""
Creates a TableForm.
Parameters:
data ...
2D data to be put into the table; data can be
given as a Matrix
headings ...
gives the labels for rows and columns:
Can be a single argument that applies to both
dimensions:
- None ... no labels
- "automatic" ... labels are 1, 2, 3, ...
Can be a list of labels for rows and columns:
The lables for each dimension can be given
as None, "automatic", or [l1, l2, ...] e.g.
["automatic", None] will number the rows
[default: None]
alignments ...
alignment of the columns with:
- "left" or "<"
- "center" or "^"
- "right" or ">"
When given as a single value, the value is used for
all columns. The row headings (if given) will be
right justified unless an explicit alignment is
given for it and all other columns.
[default: "left"]
formats ...
a list of format strings or functions that accept
3 arguments (entry, row number, col number) and
return a string for the table entry. (If a function
returns None then the _print method will be used.)
wipe_zeros ...
Don't show zeros in the table.
[default: True]
pad ...
the string to use to indicate a missing value (e.g.
elements that are None or those that are missing
from the end of a row (i.e. any row that is shorter
than the rest is assumed to have missing values).
When None, nothing will be shown for values that
are missing from the end of a row; values that are
None, however, will be shown.
[default: None]
Examples
========
>>> from diofant import TableForm, Matrix
>>> TableForm([[5, 7], [4, 2], [10, 3]])
5 7
4 2
10 3
>>> TableForm([list('.'*i) for i in range(1, 4)], headings='automatic')
| 1 2 3
---------
1 | .
2 | . .
3 | . . .
>>> TableForm([['.'*(j if not i%2 else 1) for i in range(3)]
... for j in range(4)], alignments='rcl')
.
. . .
.. . ..
... . ...
"""
from diofant import Symbol, Matrix
from diofant.core.sympify import sympify, SympifyError
# We only support 2D data. Check the consistency:
if isinstance(data, Matrix):
data = data.tolist()
_w = len(data[0])
_h = len(data)
# fill out any short lines
pad = kwarg.get('pad', None)
ok_None = False
if pad is None:
pad = " "
ok_None = True
pad = Symbol(pad)
_w = max(len(line) for line in data)
for i, line in enumerate(data):
if len(line) != _w:
line.extend([pad]*(_w - len(line)))
for j, lj in enumerate(line):
if lj is None:
if not ok_None:
lj = pad
else:
try:
lj = sympify(lj)
except SympifyError:
lj = Symbol(str(lj))
line[j] = lj
data[i] = line
_lines = Tuple(*data)
headings = kwarg.get("headings", [None, None])
if headings == "automatic":
_headings = [range(1, _h + 1), range(1, _w + 1)]
else:
h1, h2 = headings
if h1 == "automatic":
h1 = range(1, _h + 1)
if h2 == "automatic":
h2 = range(1, _w + 1)
_headings = [h1, h2]
allow = ('l', 'r', 'c')
alignments = kwarg.get("alignments", "l")
def _std_align(a):
a = a.strip().lower()
if len(a) > 1:
return {'left': 'l', 'right': 'r', 'center': 'c'}.get(a, a)
else:
return {'<': 'l', '>': 'r', '^': 'c'}.get(a, a)
std_align = _std_align(alignments)
if std_align in allow:
_alignments = [std_align]*_w
else:
_alignments = []
for a in alignments:
std_align = _std_align(a)
_alignments.append(std_align)
if std_align not in ('l', 'r', 'c'):
raise ValueError('alignment "%s" unrecognized' %
alignments)
if _headings[0] and len(_alignments) == _w + 1:
_head_align = _alignments[0]
_alignments = _alignments[1:]
else:
_head_align = 'r'
if len(_alignments) != _w:
raise ValueError(
'wrong number of alignments: expected %s but got %s' %
(_w, len(_alignments)))
_column_formats = kwarg.get("formats", [None]*_w)
_wipe_zeros = kwarg.get("wipe_zeros", True)
self._w = _w
self._h = _h
self._lines = _lines
self._headings = _headings
self._head_align = _head_align
self._alignments = _alignments
self._column_formats = _column_formats
self._wipe_zeros = _wipe_zeros
def __new__(cls, expr, *args, **kwargs):
expr = sympify(expr)
if not args:
if expr.is_Order:
variables = expr.variables
point = expr.point
else:
variables = list(expr.free_symbols)
point = [S.Zero]*len(variables)
else:
args = list(args if is_sequence(args) else [args])
variables, point = [], []
if is_sequence(args[0]):
for a in args:
v, p = list(map(sympify, a))
variables.append(v)
point.append(p)
else:
variables = list(map(sympify, args))
point = [S.Zero]*len(variables)
if not all(isinstance(v, (Dummy, Symbol)) for v in variables):
raise TypeError('Variables are not symbols, got %s' % variables)
if len(list(uniq(variables))) != len(variables):
raise ValueError('Variables are supposed to be unique symbols, got %s' % variables)
if expr.is_Order:
expr_vp = dict(expr.args[1:])
new_vp = dict(expr_vp)
vp = dict(zip(variables, point))
for v, p in vp.items():
if v in new_vp.keys():
if p != new_vp[v]:
raise NotImplementedError(
"Mixing Order at different points is not supported.")
else:
new_vp[v] = p
if set(expr_vp.keys()) == set(new_vp.keys()):
return expr
else:
variables = list(new_vp.keys())
point = [new_vp[v] for v in variables]
if expr is S.NaN:
return S.NaN
if any(x in p.free_symbols for x in variables for p in point):
raise ValueError('Got %s as a point.' % point)
if variables:
if any(p != point[0] for p in point):
raise NotImplementedError
if point[0] in [S.Infinity, S.NegativeInfinity]:
s = {k: 1/Dummy() for k in variables}
rs = {1/v: 1/k for k, v in s.items()}
elif point[0] is not S.Zero:
s = {k: Dummy() + point[0] for k in variables}
rs = {v - point[0]: k - point[0] for k, v in s.items()}
else:
s = ()
rs = ()
expr = expr.subs(s)
if expr.is_Add:
from diofant import expand_multinomial
expr = expand_multinomial(expr)
if s:
args = tuple(r[0] for r in rs.items())
else:
args = tuple(variables)
if len(variables) > 1:
# XXX: better way? We need this expand() to
# workaround e.g: expr = x*(x + y).
# (x*(x + y)).as_leading_term(x, y) currently returns
# x*y (wrong order term!). That's why we want to deal with
# expand()'ed expr (handled in "if expr.is_Add" branch below).
expr = expr.expand()
if expr.is_Add:
lst = expr.extract_leading_order(args)
expr = Add(*[f.expr for (e, f) in lst])
elif expr:
expr = expr.as_leading_term(*args)
expr = expr.as_independent(*args, as_Add=False)[1]
expr = expand_power_base(expr)
expr = expand_log(expr)
if len(args) == 1:
# The definition of O(f(x)) symbol explicitly stated that
# the argument of f(x) is irrelevant. That's why we can
# combine some power exponents (only "on top" of the
# expression tree for f(x)), e.g.:
# x**p * (-x)**q -> x**(p+q) for real p, q.
x = args[0]
margs = list(Mul.make_args(
expr.as_independent(x, as_Add=False)[1]))
for i, t in enumerate(margs):
if t.is_Pow:
b, q = t.args
if b in (x, -x) and q.is_extended_real and not q.has(x):
margs[i] = x**q
elif b.is_Pow and not b.exp.has(x):
b, r = b.args
if b in (x, -x) and r.is_extended_real:
margs[i] = x**(r*q)
elif b.is_Mul and b.args[0] is S.NegativeOne:
b = -b
if b.is_Pow and not b.exp.has(x):
b, r = b.args
if b in (x, -x) and r.is_extended_real:
margs[i] = x**(r*q)
expr = Mul(*margs)
expr = expr.subs(rs)
if expr is S.Zero:
return expr
if expr.is_Order:
expr = expr.expr
if not expr.has(*variables):
expr = S.One
# create Order instance:
vp = dict(zip(variables, point))
variables.sort(key=default_sort_key)
point = [vp[v] for v in variables]
args = (expr,) + Tuple(*zip(variables, point))
obj = Expr.__new__(cls, *args)
return obj
def test_count_ops_visual():
ADD, MUL, POW, SIN, COS, EXP, AND, D, G = symbols(
'Add Mul Pow sin cos exp And Derivative Integral'.upper())
DIV, SUB, NEG = symbols('DIV SUB NEG')
NOT, OR, AND, XOR, IMPLIES, EQUIVALENT, _ITE, BASIC, TUPLE = symbols(
'Not Or And Xor Implies Equivalent ITE Basic Tuple'.upper())
def count(val):
return count_ops(val, visual=True)
assert count(7) is Integer(0)
assert count(-1) == NEG
assert count(-2) == NEG
assert count(Rational(2, 3)) == DIV
assert count(pi/3) == DIV
assert count(-pi/3) == DIV + NEG
assert count(I - 1) == SUB
assert count(1 - I) == SUB
assert count(1 - 2*I) == SUB + MUL
assert count(x) is Integer(0)
assert count(-x) == NEG
assert count(-2*x/3) == NEG + DIV + MUL
assert count(1/x) == DIV
assert count(1/(x*y)) == DIV + MUL
assert count(-1/x) == NEG + DIV
assert count(-2/x) == NEG + DIV
assert count(x/y) == DIV
assert count(-x/y) == NEG + DIV
assert count(x**2) == POW
assert count(-x**2) == POW + NEG
assert count(-2*x**2) == POW + MUL + NEG
assert count(x + pi/3) == ADD + DIV
assert count(x + Rational(1, 3)) == ADD + DIV
assert count(x + y) == ADD
assert count(x - y) == SUB
assert count(y - x) == SUB
assert count(-1/(x - y)) == DIV + NEG + SUB
assert count(-1/(y - x)) == DIV + NEG + SUB
assert count(1 + x**y) == ADD + POW
assert count(1 + x + y) == 2*ADD
assert count(1 + x + y + z) == 3*ADD
assert count(1 + x**y + 2*x*y + y**2) == 3*ADD + 2*POW + 2*MUL
assert count(2*z + y + x + 1) == 3*ADD + MUL
assert count(2*z + y**17 + x + 1) == 3*ADD + MUL + POW
assert count(2*z + y**17 + x + sin(x)) == 3*ADD + POW + MUL + SIN
assert count(2*z + y**17 + x + sin(x**2)) == 3*ADD + MUL + 2*POW + SIN
assert count(2*z + y**17 + x + sin(
x**2) + exp(cos(x))) == 4*ADD + MUL + 3*POW + COS + SIN
assert count(Derivative(x, x)) == D
assert count(Integral(x, x) + 2*x/(1 + x)) == G + DIV + MUL + 2*ADD
assert count(Basic()) is Integer(0)
assert count({x + 1: sin(x)}) == ADD + SIN
assert count([x + 1, sin(x) + y, None]) == ADD + SIN + ADD
assert count({x + 1: sin(x), y: cos(x) + 1}) == SIN + COS + 2*ADD
assert count({}) is Integer(0)
assert count([x + 1, sin(x)*y, None]) == SIN + ADD + MUL
assert count([]) is Integer(0)
assert count(Basic()) == 0
assert count(Basic(Basic(), Basic(x, x + y))) == ADD + 2*BASIC
assert count(Basic(x, x + y)) == ADD + BASIC
assert count(Or(x, y)) == OR
assert count(And(x, y)) == AND
assert count(And(x**y, z)) == AND + POW
assert count(Or(x, Or(y, And(z, a)))) == AND + OR
assert count(Nor(x, y)) == NOT + OR
assert count(Nand(x, y)) == NOT + AND
assert count(Xor(x, y)) == XOR
assert count(Implies(x, y)) == IMPLIES
assert count(Equivalent(x, y)) == EQUIVALENT
assert count(ITE(x, y, z)) == _ITE
assert count([Or(x, y), And(x, y), Basic(x + y)]) == ADD + AND + BASIC + OR
assert count(Basic(Tuple(x))) == BASIC + TUPLE
# It checks that TUPLE is counted as an operation.
assert count(Eq(x + y, 2)) == ADD
def an(self):
""" First set of numerator parameters. """
return Tuple(*self.args[0][0])
def _eval_subs(self, old, new):
"""
Perform substitutions over non-dummy variables
of an expression with limits. Also, can be used
to specify point-evaluation of an abstract antiderivative.
Examples
========
>>> from diofant import Sum, oo
>>> from diofant.abc import s, n
>>> Sum(1/n**s, (n, 1, oo)).subs(s, 2)
Sum(n**(-2), (n, 1, oo))
>>> from diofant import Integral
>>> from diofant.abc import x, a
>>> Integral(a*x**2, x).subs(x, 4)
Integral(a*x**2, (x, 4))
See Also
========
variables : Lists the integration variables
change_index : Perform mapping on the sum and product dummy variables
"""
from diofant.core.function import AppliedUndef, UndefinedFunction
func, limits = self.function, list(self.limits)
# If one of the expressions we are replacing is used as a func index
# one of two things happens.
# - the old variable first appears as a free variable
# so we perform all free substitutions before it becomes
# a func index.
# - the old variable first appears as a func index, in
# which case we ignore. See change_index.
# Reorder limits to match standard mathematical practice for scoping
limits.reverse()
if not isinstance(old, Symbol) or \
old.free_symbols.intersection(self.free_symbols):
sub_into_func = True
for i, xab in enumerate(limits):
if 1 == len(xab) and old == xab[0]:
xab = (old, old)
limits[i] = Tuple(xab[0],
*[l._subs(old, new) for l in xab[1:]])
if len(xab[0].free_symbols.intersection(
old.free_symbols)) != 0:
sub_into_func = False
break
if isinstance(old, AppliedUndef) or isinstance(
old, UndefinedFunction):
sy2 = set(self.variables).intersection(set(new.atoms(Symbol)))
sy1 = set(self.variables).intersection(set(old.args))
if not sy2.issubset(sy1):
raise ValueError(
"substitution can not create dummy dependencies")
sub_into_func = True
if sub_into_func:
func = func.subs(old, new)
else:
# old is a Symbol and a dummy variable of some limit
for i, xab in enumerate(limits):
if len(xab) == 3:
limits[i] = Tuple(xab[0],
*[l._subs(old, new) for l in xab[1:]])
if old == xab[0]:
break
# simplify redundant limits (x, x) to (x, )
for i, xab in enumerate(limits):
if len(xab) == 2 and (xab[0] - xab[1]).is_zero:
limits[i] = Tuple(xab[0], )
# Reorder limits back to representation-form
limits.reverse()
return self.func(func, *limits)
