def point_cflexure(self):
"""
Returns a Set of point(s) with zero bending moment and
where bending moment curve of the beam object changes
its sign from negative to positive or vice versa.
Examples
========
There is is 10 meter long overhanging beam. There are
two simple supports below the beam. One at the start
and another one at a distance of 6 meters from the start.
Point loads of magnitude 10KN and 20KN are applied at
2 meters and 4 meters from start respectively. A Uniformly
distribute load of magnitude of magnitude 3KN/m is also
applied on top starting from 6 meters away from starting
point till end.
Using the sign convention of upward forces and clockwise moment
being positive.
>>> from sympy.physics.continuum_mechanics.beam import Beam
>>> from sympy import symbols
>>> E, I = symbols('E, I')
>>> b = Beam(10, E, I)
>>> b.apply_load(-4, 0, -1)
>>> b.apply_load(-46, 6, -1)
>>> b.apply_load(10, 2, -1)
>>> b.apply_load(20, 4, -1)
>>> b.apply_load(3, 6, 0)
>>> b.point_cflexure()
[10/3]
"""
from sympy import solve, Piecewise
# To restrict the range within length of the Beam
moment_curve = Piecewise((float("nan"), self.variable<=0),
(self.bending_moment(), self.variable<self.length),
(float("nan"), True))
points = solve(moment_curve.rewrite(Piecewise), self.variable,
domain=S.Reals)
return points
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d*b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c*b1)
else:
new_args = []
n_intervals = len(b1.args)
assert(n_intervals == len(b2.args))
new_args.append((c*b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((
c*b1.args[i].expr + d*b2.args[i - 1].expr,
b1.args[i].cond
))
new_args.append((d*b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d*b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c*b1)
else:
new_args = []
n_intervals = len(b1.args)
if n_intervals != len(b2.args):
raise ValueError("Args of b1 and b2 are not equal")
new_args.append((c*b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((
c*b1.args[i].expr + d*b2.args[i - 1].expr,
b1.args[i].cond
))
new_args.append((d*b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
def max_deflection(self):
"""
Returns point of max deflection and its coresponding deflection value
in a Beam object.
"""
from sympy import solve, Piecewise
# To restrict the range within length of the Beam
slope_curve = Piecewise((float("nan"), self.variable<=0),
(self.slope(), self.variable<self.length),
(float("nan"), True))
points = solve(slope_curve.rewrite(Piecewise), self.variable,
domain=S.Reals)
deflection_curve = self.deflection()
deflections = [deflection_curve.subs(self.variable, x) for x in points]
deflections = list(map(abs, deflections))
if len(deflections) != 0:
max_def = max(deflections)
return (points[deflections.index(max_def)], max_def)
else:
return None
def test_functions():
one_var = (acosh, ln, Heaviside, factorial, bernoulli, coth, tanh, sign,
arg, asin, DiracDelta, re, Abs, sinh, cos, cot, acos, acot,
gamma, bell, harmonic, LambertW, zeta, log, factorial, asinh,
acoth, cosh, dirichlet_eta, loggamma, erf, ceiling, im,
fibonacci, tribonacci, conjugate, tan, floor, atanh, sin, atan,
lucas, exp)
two_var = (rf, ff, lowergamma, chebyshevu, chebyshevt, binomial, atan2,
polygamma, hermite, legendre, uppergamma)
x, y, z = symbols("x,y,z")
others = (chebyshevt_root, chebyshevu_root, Eijk(x, y, z),
Piecewise((0, x < -1), (x**2, x <= 1),
(x**3, True)), assoc_legendre)
for cls in one_var:
check(cls)
c = cls(x)
check(c)
for cls in two_var:
check(cls)
c = cls(x, y)
check(c)
for cls in others:
check(cls)
def test_variable_moment():
E = Symbol('E')
I = Symbol('I')
b = Beam(4, E, 2 * (4 - x))
b.apply_load(20, 4, -1)
R, M = symbols('R, M')
b.apply_load(R, 0, -1)
b.apply_load(M, 0, -2)
b.bc_deflection = [(0, 0)]
b.bc_slope = [(0, 0)]
b.solve_for_reaction_loads(R, M)
assert b.slope().expand() == ((10 * x * SingularityFunction(x, 0, 0) - 10 *
(x - 4) * SingularityFunction(x, 4, 0)) /
E).expand()
assert b.deflection().expand() == (
(5 * x**2 * SingularityFunction(x, 0, 0) - 10 * Piecewise(
(0, Abs(x) / 4 < 1), (16 * meijerg(
((3, 1), ()),
((),
(2, 0)), x / 4), True)) + 40 * SingularityFunction(x, 4, 1)) /
E).expand()
b = Beam(4, E - x, I)
b.apply_load(20, 4, -1)
R, M = symbols('R, M')
b.apply_load(R, 0, -1)
b.apply_load(M, 0, -2)
b.bc_deflection = [(0, 0)]
b.bc_slope = [(0, 0)]
b.solve_for_reaction_loads(R, M)
assert b.slope().expand() == (
(-80 * (-log(-E) + log(-E + x)) * SingularityFunction(x, 0, 0) + 80 *
(-log(-E + 4) + log(-E + x)) * SingularityFunction(x, 4, 0) + 20 *
(-E * log(-E) + E * log(-E + x) + x) * SingularityFunction(x, 0, 0) -
20 * (-E * log(-E + 4) + E * log(-E + x) + x - 4) *
SingularityFunction(x, 4, 0)) / I).expand()
def test_deltasummation_mul_add_x_kd_add_y_kd():
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) +
3*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) +
k*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
(4 - k)*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1)*(KD(i, k) + x)*y)
def try_meijerg(function, xab):
ret = None
if len(xab) == 3 and meijerg is not False:
x, a, b = xab
try:
res = meijerint_definite(function, x, a, b)
except NotImplementedError:
from sympy.integrals.meijerint import _debug
_debug('NotImplementedError from meijerint_definite')
res = None
if res is not None:
f, cond = res
if conds == 'piecewise':
ret = Piecewise((f, cond),
(Integral(function,
(x, a, b)), True))
elif conds == 'separate':
if len(self.limits) != 1:
raise ValueError('conds=separate not supported in ' \
'multiple integrals')
ret = f, cond
else:
ret = f
return ret
def test_cross_section():
I = Symbol('I')
l = Symbol('l')
E = Symbol('E')
C3, C4 = symbols('C3, C4')
a, c, g, h, r, n = symbols('a, c, g, h, r, n')
# test for second_moment and cross_section setter
b0 = Beam(l, E, I)
assert b0.second_moment == I
assert b0.cross_section == None
b0.cross_section = Circle((0, 0), 5)
assert b0.second_moment == pi*Rational(625, 4)
assert b0.cross_section == Circle((0, 0), 5)
b0.second_moment = 2*n - 6
assert b0.second_moment == 2*n-6
assert b0.cross_section == None
with raises(ValueError):
b0.second_moment = Circle((0, 0), 5)
# beam with a circular cross-section
b1 = Beam(50, E, Circle((0, 0), r))
assert b1.cross_section == Circle((0, 0), r)
assert b1.second_moment == pi*r*Abs(r)**3/4
b1.apply_load(-10, 0, -1)
b1.apply_load(R1, 5, -1)
b1.apply_load(R2, 50, -1)
b1.apply_load(90, 45, -2)
b1.solve_for_reaction_loads(R1, R2)
assert b1.load == (-10*SingularityFunction(x, 0, -1) + 82*SingularityFunction(x, 5, -1)/S(9)
+ 90*SingularityFunction(x, 45, -2) + 8*SingularityFunction(x, 50, -1)/9)
assert b1.bending_moment() == (-10*SingularityFunction(x, 0, 1) + 82*SingularityFunction(x, 5, 1)/9
+ 90*SingularityFunction(x, 45, 0) + 8*SingularityFunction(x, 50, 1)/9)
q = (-5*SingularityFunction(x, 0, 2) + 41*SingularityFunction(x, 5, 2)/S(9)
+ 90*SingularityFunction(x, 45, 1) + 4*SingularityFunction(x, 50, 2)/S(9))/(pi*E*r*Abs(r)**3)
assert b1.slope() == C3 + 4*q
q = (-5*SingularityFunction(x, 0, 3)/3 + 41*SingularityFunction(x, 5, 3)/27 + 45*SingularityFunction(x, 45, 2)
+ 4*SingularityFunction(x, 50, 3)/27)/(pi*E*r*Abs(r)**3)
assert b1.deflection() == C3*x + C4 + 4*q
# beam with a recatangular cross-section
b2 = Beam(20, E, Polygon((0, 0), (a, 0), (a, c), (0, c)))
assert b2.cross_section == Polygon((0, 0), (a, 0), (a, c), (0, c))
assert b2.second_moment == a*c**3/12
# beam with a triangular cross-section
b3 = Beam(15, E, Triangle((0, 0), (g, 0), (g/2, h)))
assert b3.cross_section == Triangle(Point2D(0, 0), Point2D(g, 0), Point2D(g/2, h))
assert b3.second_moment == g*h**3/36
# composite beam
b = b2.join(b3, "fixed")
b.apply_load(-30, 0, -1)
b.apply_load(65, 0, -2)
b.apply_load(40, 0, -1)
b.bc_slope = [(0, 0)]
b.bc_deflection = [(0, 0)]
assert b.second_moment == Piecewise((a*c**3/12, x <= 20), (g*h**3/36, x <= 35))
assert b.cross_section == None
assert b.length == 35
assert b.slope().subs(x, 7) == 8400/(E*a*c**3)
assert b.slope().subs(x, 25) == 52200/(E*g*h**3) + 39600/(E*a*c**3)
assert b.deflection().subs(x, 30) == 537000/(E*g*h**3) + 712000/(E*a*c**3)
def max_bmoment(self):
"""Returns maximum Shear force and its coordinate
in the Beam object."""
from sympy import solve, Mul, Interval
bending_curve = self.bending_moment()
x = self.variable
terms = bending_curve.args
singularity = [] # Points at which bending moment changes
for term in terms:
if isinstance(term, Mul):
term = term.args[-1] # SingularityFunction in the term
singularity.append(term.args[1])
singularity.sort()
singularity = list(set(singularity))
intervals = [
] # List of Intervals with discrete value of bending moment
moment_values = [] # List of values of bending moment in each interval
for i, s in enumerate(singularity):
if s == 0:
continue
try:
moment_slope = Piecewise(
(float("nan"), x <= singularity[i - 1]),
(self.shear_force().rewrite(Piecewise), x < s),
(float("nan"), True))
points = solve(moment_slope, x)
val = []
for point in points:
val.append(bending_curve.subs(x, point))
points.extend([singularity[i - 1], s])
val.extend([
limit(bending_curve, x, singularity[i - 1], '+'),
limit(bending_curve, x, s, '-')
])
val = list(map(abs, val))
max_moment = max(val)
moment_values.append(max_moment)
intervals.append(points[val.index(max_moment)])
# If bending moment in a particular Interval has zero or constant
# slope, then above block gives NotImplementedError as solve
# can't represent Interval solutions.
except NotImplementedError:
initial_moment = limit(bending_curve, x, singularity[i - 1],
'+')
final_moment = limit(bending_curve, x, s, '-')
# If bending_curve has a constant slope(it is a line).
if bending_curve.subs(x, (singularity[i - 1] + s) / 2) == (
initial_moment +
final_moment) / 2 and initial_moment != final_moment:
moment_values.extend([initial_moment, final_moment])
intervals.extend([singularity[i - 1], s])
else: # bending_curve has same value in whole Interval
moment_values.append(final_moment)
intervals.append(Interval(singularity[i - 1], s))
moment_values = list(map(abs, moment_values))
maximum_moment = max(moment_values)
point = intervals[moment_values.index(maximum_moment)]
return (point, maximum_moment)
def test_deltasummation():
ds = deltasummation
assert ds(x, (j, 1, 0)) == 0
assert ds(x, (j, 1, 3)) == 3*x
assert ds(x + y, (j, 1, 3)) == 3*(x + y)
assert ds(x*y, (j, 1, 3)) == 3*x*y
assert ds(KD(i, j), (k, 1, 3)) == 3*KD(i, j)
assert ds(x*KD(i, j), (k, 1, 3)) == 3*x*KD(i, j)
assert ds(x*y*KD(i, j), (k, 1, 3)) == 3*x*y*KD(i, j)
n = symbols('n', integer=True, nonzero=True)
assert ds(KD(n, 0), (n, 1, 3)) == 0
# return unevaluated, until it gets implemented
assert ds(KD(i**2, j**2), (j, -oo, oo)) == \
Sum(KD(i**2, j**2), (j, -oo, oo))
assert Piecewise((KD(i, k), And(S(1) <= i, i <= 3)), (0, True)) == \
ds(KD(i, j)*KD(j, k), (j, 1, 3)) == \
ds(KD(j, k)*KD(i, j), (j, 1, 3))
assert ds(KD(i, k), (k, -oo, oo)) == 1
assert ds(KD(i, k), (k, 0, oo)) == Piecewise((1, i >= 0), (0, True))
assert ds(KD(i, k), (k, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(k*KD(i, j)*KD(j, k), (k, -oo, oo)) == j*KD(i, j)
assert ds(j*KD(i, j), (j, -oo, oo)) == i
assert ds(i*KD(i, j), (i, -oo, oo)) == j
assert ds(x, (i, 1, 3)) == 3*x
assert ds((i + j)*KD(i, j), (j, -oo, oo)) == 2*i
assert ds(KD(i, j), (j, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, 1, 1)) == Piecewise((1, Eq(i, 1)), (0, True))
assert ds(KD(i, j), (j, 2, 2)) == Piecewise((1, Eq(i, 2)), (0, True))
assert ds(KD(i, j), (j, 3, 3)) == Piecewise((1, Eq(i, 3)), (0, True))
assert ds(KD(i, j), (j, 1, k)) == \
Piecewise((1, And(S(1) <= i, i <= k)), (0, True))
assert ds(KD(i, j), (j, k, 3)) == \
Piecewise((1, And(k <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, k, l)) == \
Piecewise((1, And(k <= i, i <= l)), (0, True))
assert ds(x*KD(i, j), (j, 1, 3)) == \
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, 1)) == Piecewise((x, Eq(i, 1)), (0, True))
assert ds(x*KD(i, j), (j, 2, 2)) == Piecewise((x, Eq(i, 2)), (0, True))
assert ds(x*KD(i, j), (j, 3, 3)) == Piecewise((x, Eq(i, 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, k)) == \
Piecewise((x, And(S(1) <= i, i <= k)), (0, True))
assert ds(x*KD(i, j), (j, k, 3)) == \
Piecewise((x, And(k <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, k, l)) == \
Piecewise((x, And(k <= i, i <= l)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 3)) == \
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 1)) == \
Piecewise((x + y, Eq(i, 1)), (0, True))
assert ds((x + y)*KD(i, j), (j, 2, 2)) == \
Piecewise((x + y, Eq(i, 2)), (0, True))
assert ds((x + y)*KD(i, j), (j, 3, 3)) == \
Piecewise((x + y, Eq(i, 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, k)) == \
Piecewise((x + y, And(S(1) <= i, i <= k)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, 3)) == \
Piecewise((x + y, And(k <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, l)) == \
Piecewise((x + y, And(k <= i, i <= l)), (0, True))
assert ds(KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((1, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((1, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((1, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((x, Eq(j, 1)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((x, Eq(j, 2)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((x, Eq(j, 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x, And(l <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((x, And(l <= j, j <= m)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
assert ds(x*y + x*KD(i, j), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + 2*x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + 2*x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + 2*x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + 2*x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + 2*x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*x*y + 2*x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + 2*x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 3)) == Piecewise(
(3*(x + y)*y + x + y, And(S(1) <= i, i <= 3)), (3*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 1)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 2)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 3)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, k)) == Piecewise(
(k*(x + y)*y + x + y, And(S(1) <= i, i <= k)), (k*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*(x + y)*y + x + y, And(k <= i, i <= 3)),
((4 - k)*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*(x + y)*y + x + y, And(k <= i, i <= l)),
((l - k + 1)*(x + y)*y, True))
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) +
3*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) +
k*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
(4 - k)*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1)*(KD(i, k) + x)*y)
def deflection(self):
"""
Returns a Singularity Function expression which represents
the elastic curve or deflection of the Beam object.
Examples
========
There is a beam of length 30 meters. A moment of magnitude 120 Nm is
applied in the clockwise direction at the end of the beam. A pointload
of magnitude 8 N is applied from the top of the beam at the starting
point. There are two simple supports below the beam. One at the end
and another one at a distance of 10 meters from the start. The
deflection is restricted at both the supports.
Using the sign convention of upward forces and clockwise moment
being positive.
>>> from sympy.physics.continuum_mechanics.beam import Beam
>>> from sympy import symbols
>>> E, I = symbols('E, I')
>>> R1, R2 = symbols('R1, R2')
>>> b = Beam(30, E, I)
>>> b.apply_load(-8, 0, -1)
>>> b.apply_load(R1, 10, -1)
>>> b.apply_load(R2, 30, -1)
>>> b.apply_load(120, 30, -2)
>>> b.bc_deflection = [(10, 0), (30, 0)]
>>> b.solve_for_reaction_loads(R1, R2)
>>> b.deflection()
(4000*x/3 - 4*SingularityFunction(x, 0, 3)/3 + SingularityFunction(x, 10, 3)
+ 60*SingularityFunction(x, 30, 2) + SingularityFunction(x, 30, 3)/3 - 12000)/(E*I)
"""
x = self.variable
E = self.elastic_modulus
I = self.second_moment
if self._composite_type == "hinge":
return self._hinge_beam_deflection
if not self._boundary_conditions['deflection'] and not self._boundary_conditions['slope']:
if self._composite_type == "fixed":
args = I.args
conditions = []
prev_def = 0
prev_end = 0
for i in range(len(args)):
if i != 0:
prev_end = args[i-1][1].args[1]
deflection_value = integrate(self.slope().args[i][0], (x, prev_end, x))
conditions.append(((prev_def + deflection_value), args[i][1]))
prev_def = deflection_value.subs(x, args[i][1].args[1])
return Piecewise(*conditions)
return S(1)/(E*I)*integrate(integrate(self.bending_moment(), x), x)
elif not self._boundary_conditions['deflection']:
return integrate(self.slope(), x)
elif not self._boundary_conditions['slope'] and self._boundary_conditions['deflection']:
if self._composite_type == "fixed":
args = I.args
conditions = []
prev_def = 0
prev_end = 0
for i in range(len(args)):
if i != 0:
prev_end = args[i-1][1].args[1]
deflection_value = integrate(self.slope().args[i][0], (x, prev_end, x))
conditions.append(((prev_def + deflection_value), args[i][1]))
prev_def = deflection_value.subs(x, args[i][1].args[1])
return Piecewise(*conditions)
C3 = Symbol('C3')
C4 = Symbol('C4')
slope_curve = integrate(self.bending_moment(), x) + C3
deflection_curve = integrate(slope_curve, x) + C4
bc_eqs = []
for position, value in self._boundary_conditions['deflection']:
eqs = deflection_curve.subs(x, position) - value
bc_eqs.append(eqs)
constants = list(linsolve(bc_eqs, (C3, C4)))
deflection_curve = deflection_curve.subs({C3: constants[0][0], C4: constants[0][1]})
return S(1)/(E*I)*deflection_curve
if self._composite_type == "fixed":
args = I.args
conditions = []
prev_def = 0
prev_end = 0
for i in range(len(args)):
if i != 0:
prev_end = args[i-1][1].args[1]
deflection_value = integrate(self.slope().args[i][0], (x, prev_end, x))
conditions.append(((prev_def + deflection_value), args[i][1]))
prev_def = deflection_value.subs(x, args[i][1].args[1])
return Piecewise(*conditions)
C4 = Symbol('C4')
deflection_curve = integrate((E*I)*self.slope(), x) + C4
bc_eqs = []
for position, value in self._boundary_conditions['deflection']:
eqs = deflection_curve.subs(x, position) - value
bc_eqs.append(eqs)
constants = list(linsolve(bc_eqs, C4))
deflection_curve = deflection_curve.subs({C4: constants[0][0]})
return S(1)/(E*I)*deflection_curve
def join(self, beam, via="fixed"):
"""
This method joins two beams to make a new composite beam system.
Passed Beam class instance is attached to the right end of calling
object.
Parameters
==========
beam : Beam class object
The Beam object which would be connected to the right of calling
object.
via : String
States the way two Beam object would get connected
- For axially fixed Beams, via="fixed"
- For Beams connected via hinge, via="hinge"
Examples
========
There is a cantilever beam of length 4 meters. For first 2 meters
its moment of inertia is `1.5*I` and `I` for the other end.
A pointload of magnitude 4 N is applied from the top at its free end.
>>> from sympy.physics.continuum_mechanics.beam import Beam
>>> from sympy import symbols
>>> E, I = symbols('E, I')
>>> R1, R2 = symbols('R1, R2')
>>> b1 = Beam(2, E, 1.5*I)
>>> b2 = Beam(2, E, I)
>>> b = b1.join(b2, "fixed")
>>> b.apply_load(20, 4, -1)
>>> b.apply_load(R1, 0, -1)
>>> b.apply_load(R2, 0, -2)
>>> b.bc_slope = [(0, 0)]
>>> b.bc_deflection = [(0, 0)]
>>> b.solve_for_reaction_loads(R1, R2)
>>> b.load
80*SingularityFunction(x, 0, -2) - 20*SingularityFunction(x, 0, -1) + 20*SingularityFunction(x, 4, -1)
>>> b.slope()
Piecewise((0.666666666666667*(80*SingularityFunction(x, 0, 1) - 10*SingularityFunction(x, 0, 2) +
10*SingularityFunction(x, 4, 2))/(E*I), x <= 2), (((80*SingularityFunction(x, 0, 1) -
10*SingularityFunction(x, 0, 2) + 10*SingularityFunction(x, 4, 2))/I - 120/I)/E + 80.0/(E*I), x <= 4))
"""
x = self.variable
E = self.elastic_modulus
new_length = self.length + beam.length
if self.second_moment != beam.second_moment:
new_second_moment = Piecewise((self.second_moment, x<=self.length),
(beam.second_moment, x<=new_length))
else:
new_second_moment = self.second_moment
if via == "fixed":
new_beam = Beam(new_length, E, new_second_moment, x)
new_beam._composite_type = "fixed"
return new_beam
if via == "hinge":
new_beam = Beam(new_length, E, new_second_moment, x)
new_beam._composite_type = "hinge"
new_beam._hinge_position = self.length
return new_beam
def bspline_basis(d, knots, n, x, close=True):
"""The n-th B-spline at x of degree d with knots.
B-Splines are piecewise polynomials of degree d [1]. They are defined on
a set of knots, which is a sequence of integers or floats.
The 0th degree splines have a value of one on a single interval:
>>> from sympy import bspline_basis
>>> from sympy.abc import x
>>> d = 0
>>> knots = range(5)
>>> bspline_basis(d, knots, 0, x)
Piecewise((1, And(x <= 1, x >= 0)), (0, True))
For a given (d, knots) there are len(knots)-d-1 B-splines defined, that
are indexed by n (starting at 0).
Here is an example of a cubic B-spline:
>>> bspline_basis(3, range(5), 0, x)
Piecewise((x**3/6, And(x < 1, x >= 0)), (-x**3/2 + 2*x**2 - 2*x + 2/3, And(x < 2, x >= 1)), (x**3/2 - 4*x**2 + 10*x - 22/3, And(x < 3, x >= 2)), (-x**3/6 + 2*x**2 - 8*x + 32/3, And(x <= 4, x >= 3)), (0, True))
By repeating knot points, you can introduce discontinuities in the
B-splines and their derivatives:
>>> d = 1
>>> knots = [0,0,2,3,4]
>>> bspline_basis(d, knots, 0, x)
Piecewise((-x/2 + 1, And(x <= 2, x >= 0)), (0, True))
It is quite time consuming to construct and evaluate B-splines. If you
need to evaluate a B-splines many times, it is best to lambdify them
first:
>>> from sympy import lambdify
>>> d = 3
>>> knots = range(10)
>>> b0 = bspline_basis(d, knots, 0, x)
>>> f = lambdify(x, b0)
>>> y = f(0.5)
See Also
========
bsplines_basis_set
References
==========
[1] http://en.wikipedia.org/wiki/B-spline
"""
knots = [sympify(k) for k in knots]
d = int(d)
n = int(n)
n_knots = len(knots)
n_intervals = n_knots - 1
if n + d + 1 > n_intervals:
raise ValueError('n+d+1 must not exceed len(knots)-1')
if d == 0:
result = Piecewise(
(S.One, Interval(knots[n], knots[n + 1], False,
not close).contains(x)), (0, True))
elif d > 0:
denom = knots[n + d + 1] - knots[n + 1]
if denom != S.Zero:
B = (knots[n + d + 1] - x) / denom
b2 = bspline_basis(d - 1, knots, n + 1, x, close)
else:
b2 = B = S.Zero
denom = knots[n + d] - knots[n]
if denom != S.Zero:
A = (x - knots[n]) / denom
b1 = bspline_basis(d - 1, knots, n, x, close
and (B == S.Zero or b2 == S.Zero))
else:
b1 = A = S.Zero
result = _add_splines(A, b1, B, b2)
else:
raise ValueError('degree must be non-negative: %r' % n)
return result
def _eval_integral(self,
f,
x,
meijerg=None,
risch=None,
manual=None,
conds='piecewise'):
"""
Calculate the anti-derivative to the function f(x).
The following algorithms are applied (roughly in this order):
1. Simple heuristics (based on pattern matching and integral table):
- most frequently used functions (e.g. polynomials, products of trig functions)
2. Integration of rational functions:
- A complete algorithm for integrating rational functions is
implemented (the Lazard-Rioboo-Trager algorithm). The algorithm
also uses the partial fraction decomposition algorithm
implemented in apart() as a preprocessor to make this process
faster. Note that the integral of a rational function is always
elementary, but in general, it may include a RootSum.
3. Full Risch algorithm:
- The Risch algorithm is a complete decision
procedure for integrating elementary functions, which means that
given any elementary function, it will either compute an
elementary antiderivative, or else prove that none exists.
Currently, part of transcendental case is implemented, meaning
elementary integrals containing exponentials, logarithms, and
(soon!) trigonometric functions can be computed. The algebraic
case, e.g., functions containing roots, is much more difficult
and is not implemented yet.
- If the routine fails (because the integrand is not elementary, or
because a case is not implemented yet), it continues on to the
next algorithms below. If the routine proves that the integrals
is nonelementary, it still moves on to the algorithms below,
because we might be able to find a closed-form solution in terms
of special functions. If risch=True, however, it will stop here.
4. The Meijer G-Function algorithm:
- This algorithm works by first rewriting the integrand in terms of
very general Meijer G-Function (meijerg in SymPy), integrating
it, and then rewriting the result back, if possible. This
algorithm is particularly powerful for definite integrals (which
is actually part of a different method of Integral), since it can
compute closed-form solutions of definite integrals even when no
closed-form indefinite integral exists. But it also is capable
of computing many indefinite integrals as well.
- Another advantage of this method is that it can use some results
about the Meijer G-Function to give a result in terms of a
Piecewise expression, which allows to express conditionally
convergent integrals.
- Setting meijerg=True will cause integrate() to use only this
method.
5. The "manual integration" algorithm:
- This algorithm tries to mimic how a person would find an
antiderivative by hand, for example by looking for a
substitution or applying integration by parts. This algorithm
does not handle as many integrands but can return results in a
more familiar form.
- Sometimes this algorithm can evaluate parts of an integral; in
this case integrate() will try to evaluate the rest of the
integrand using the other methods here.
- Setting manual=True will cause integrate() to use only this
method.
6. The Heuristic Risch algorithm:
- This is a heuristic version of the Risch algorithm, meaning that
it is not deterministic. This is tried as a last resort because
it can be very slow. It is still used because not enough of the
full Risch algorithm is implemented, so that there are still some
integrals that can only be computed using this method. The goal
is to implement enough of the Risch and Meijer G methods so that
this can be deleted.
"""
from sympy.integrals.risch import risch_integrate
if risch:
try:
return risch_integrate(f, x, conds=conds)
except NotImplementedError:
return None
if manual:
try:
result = manualintegrate(f, x)
if result is not None and result.func != Integral:
return result
except (ValueError, PolynomialError):
pass
# if it is a poly(x) then let the polynomial integrate itself (fast)
#
# It is important to make this check first, otherwise the other code
# will return a sympy expression instead of a Polynomial.
#
# see Polynomial for details.
if isinstance(f, Poly) and not meijerg:
return f.integrate(x)
# Piecewise antiderivatives need to call special integrate.
if f.func is Piecewise:
return f._eval_integral(x)
# let's cut it short if `f` does not depend on `x`
if not f.has(x):
return f * x
# try to convert to poly(x) and then integrate if successful (fast)
poly = f.as_poly(x)
if poly is not None and not meijerg:
return poly.integrate().as_expr()
if risch is not False:
try:
result, i = risch_integrate(f,
x,
separate_integral=True,
conds=conds)
except NotImplementedError:
pass
else:
if i:
# There was a nonelementary integral. Try integrating it.
return result + i.doit(risch=False)
else:
return result
# since Integral(f=g1+g2+...) == Integral(g1) + Integral(g2) + ...
# we are going to handle Add terms separately,
# if `f` is not Add -- we only have one term
# Note that in general, this is a bad idea, because Integral(g1) +
# Integral(g2) might not be computable, even if Integral(g1 + g2) is.
# For example, Integral(x**x + x**x*log(x)). But many heuristics only
# work term-wise. So we compute this step last, after trying
# risch_integrate. We also try risch_integrate again in this loop,
# because maybe the integral is a sum of an elementary part and a
# nonelementary part (like erf(x) + exp(x)). risch_integrate() is
# quite fast, so this is acceptable.
parts = []
args = Add.make_args(f)
for g in args:
coeff, g = g.as_independent(x)
# g(x) = const
if g is S.One and not meijerg:
parts.append(coeff * x)
continue
# g(x) = expr + O(x**n)
order_term = g.getO()
if order_term is not None:
h = self._eval_integral(g.removeO(), x)
if h is not None:
h_order_expr = self._eval_integral(order_term.expr, x)
if h_order_expr is not None:
h_order_term = order_term.func(h_order_expr,
*order_term.variables)
parts.append(coeff * (h + h_order_term))
continue
# NOTE: if there is O(x**n) and we fail to integrate then there is
# no point in trying other methods because they will fail anyway.
return None
# c
# g(x) = (a*x+b)
if g.is_Pow and not g.exp.has(x) and not meijerg:
a = Wild('a', exclude=[x])
b = Wild('b', exclude=[x])
M = g.base.match(a * x + b)
if M is not None:
if g.exp == -1:
h = C.log(g.base)
elif conds != 'piecewise':
h = g.base**(g.exp + 1) / (g.exp + 1)
else:
h1 = C.log(g.base)
h2 = g.base**(g.exp + 1) / (g.exp + 1)
h = Piecewise((h1, Eq(g.exp, -1)), (h2, True))
parts.append(coeff * h / M[a])
continue
# poly(x)
# g(x) = -------
# poly(x)
if g.is_rational_function(x) and not meijerg:
parts.append(coeff * ratint(g, x))
continue
if not meijerg:
# g(x) = Mul(trig)
h = trigintegrate(g, x, conds=conds)
if h is not None:
parts.append(coeff * h)
continue
# g(x) has at least a DiracDelta term
h = deltaintegrate(g, x)
if h is not None:
parts.append(coeff * h)
continue
# Try risch again.
if risch is not False:
try:
h, i = risch_integrate(g,
x,
separate_integral=True,
conds=conds)
except NotImplementedError:
h = None
else:
if i:
h = h + i.doit(risch=False)
parts.append(coeff * h)
continue
# fall back to heurisch
try:
if conds == 'piecewise':
h = heurisch_wrapper(g, x, hints=[])
else:
h = heurisch(g, x, hints=[])
except PolynomialError:
# XXX: this exception means there is a bug in the
# implementation of heuristic Risch integration
# algorithm.
h = None
else:
h = None
if meijerg is not False and h is None:
# rewrite using G functions
try:
h = meijerint_indefinite(g, x)
except NotImplementedError:
from sympy.integrals.meijerint import _debug
_debug('NotImplementedError from meijerint_definite')
res = None
if h is not None:
parts.append(coeff * h)
continue
if h is None and manual is not False:
try:
result = manualintegrate(g, x)
if result is not None and not isinstance(result, Integral):
if result.has(Integral):
# try to have other algorithms do the integrals
# manualintegrate can't handle
result = result.func(*[
arg.doit(
manual=False) if arg.has(Integral) else arg
for arg in result.args
]).expand(multinomial=False,
log=False,
power_exp=False,
power_base=False)
if not result.has(Integral):
parts.append(coeff * result)
continue
except (ValueError, PolynomialError):
# can't handle some SymPy expressions
pass
# if we failed maybe it was because we had
# a product that could have been expanded,
# so let's try an expansion of the whole
# thing before giving up; we don't try this
# at the outset because there are things
# that cannot be solved unless they are
# NOT expanded e.g., x**x*(1+log(x)). There
# should probably be a checker somewhere in this
# routine to look for such cases and try to do
# collection on the expressions if they are already
# in an expanded form
if not h and len(args) == 1:
f = f.expand(mul=True, deep=False)
if f.is_Add:
# Note: risch will be identical on the expanded
# expression, but maybe it will be able to pick out parts,
# like x*(exp(x) + erf(x)).
return self._eval_integral(f,
x,
meijerg=meijerg,
risch=risch,
conds=conds)
if h is not None:
parts.append(coeff * h)
else:
return None
return Add(*parts)
def test_deltasummation_add_mul_x_kd_kd():
assert ds(x * KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(1 <= i, i <= 3)), (0, True)) +
Piecewise((1, And(1 <= j, j <= 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(1 <= i, i <= l)), (0, True)) +
Piecewise((1, And(1 <= j, j <= l)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d*b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c*b1)
else:
new_args = []
n_intervals = len(b1.args)
if n_intervals != len(b2.args):
# Args of b1 and b2 are not equal. Just combining the Piecewise without any fancy optimisation
p1 = piecewise_fold(c*b1)
p2 = piecewise_fold(d*b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assume the conditions in p1 and p2 are sorted
for arg in p1.args[:-1]:
# Conditional of Piecewise are And objects
# the args of the And object is a tuple of two Relational objects
# the numerical value is in the .rhs of the Relational object
expr = arg.expr
cond = arg.cond
lower = cond.args[0].rhs
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2 = cond2.args[0].rhs
upper_2 = cond2.args[1].rhs
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1, add to new_args by itself (no match expected in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
else:
new_args.append((c*b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((
c*b1.args[i].expr + d*b2.args[i - 1].expr,
b1.args[i].cond
))
new_args.append((d*b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
def test_julia_piecewise_times_const():
pw = Piecewise((x, x < 1), (x**2, True))
assert julia_code(2 * pw) == "2*((x < 1) ? (x) : (x.^2))"
assert julia_code(pw / x) == "((x < 1) ? (x) : (x.^2))./x"
assert julia_code(pw / (x * y)) == "((x < 1) ? (x) : (x.^2))./(x.*y)"
assert julia_code(pw / 3) == "((x < 1) ? (x) : (x.^2))/3"
def test_composite_beam():
E = Symbol("E")
I = Symbol("I")
b1 = Beam(2, E, 1.5 * I)
b2 = Beam(2, E, I)
b = b1.join(b2, "fixed")
b.apply_load(-20, 0, -1)
b.apply_load(80, 0, -2)
b.apply_load(20, 4, -1)
b.bc_slope = [(0, 0)]
b.bc_deflection = [(0, 0)]
assert b.length == 4
assert b.second_moment == Piecewise((1.5 * I, x <= 2), (I, x <= 4))
assert b.slope().subs(x, 4) == 120.0 / (E * I)
assert b.slope().subs(x, 2) == 80.0 / (E * I)
assert int(b.deflection().subs(x,
4).args[0]) == 302 # Coefficient of 1/(E*I)
l = symbols("l", positive=True)
R1, M1, R2, R3, P = symbols("R1 M1 R2 R3 P")
b1 = Beam(2 * l, E, I)
b2 = Beam(2 * l, E, I)
b = b1.join(b2, "hinge")
b.apply_load(M1, 0, -2)
b.apply_load(R1, 0, -1)
b.apply_load(R2, l, -1)
b.apply_load(R3, 4 * l, -1)
b.apply_load(P, 3 * l, -1)
b.bc_slope = [(0, 0)]
b.bc_deflection = [(0, 0), (l, 0), (4 * l, 0)]
b.solve_for_reaction_loads(M1, R1, R2, R3)
assert b.reaction_loads == {
R3: -P / 2,
R2: P * Rational(-5, 4),
M1: -P * l / 4,
R1: P * Rational(3, 4),
}
assert b.slope().subs(x, 3 * l) == -7 * P * l**2 / (48 * E * I)
assert b.deflection().subs(x, 2 * l) == 7 * P * l**3 / (24 * E * I)
assert b.deflection().subs(x, 3 * l) == 5 * P * l**3 / (16 * E * I)
# When beams having same second moment are joined.
b1 = Beam(2, 500, 10)
b2 = Beam(2, 500, 10)
b = b1.join(b2, "fixed")
b.apply_load(M1, 0, -2)
b.apply_load(R1, 0, -1)
b.apply_load(R2, 1, -1)
b.apply_load(R3, 4, -1)
b.apply_load(10, 3, -1)
b.bc_slope = [(0, 0)]
b.bc_deflection = [(0, 0), (1, 0), (4, 0)]
b.solve_for_reaction_loads(M1, R1, R2, R3)
assert (b.slope() == -2 * SingularityFunction(x, 0, 1) / 5625 +
SingularityFunction(x, 0, 2) / 1875 -
133 * SingularityFunction(x, 1, 2) / 135000 +
SingularityFunction(x, 3, 2) / 1000 -
37 * SingularityFunction(x, 4, 2) / 67500)
assert (b.deflection() == -SingularityFunction(x, 0, 2) / 5625 +
SingularityFunction(x, 0, 3) / 5625 -
133 * SingularityFunction(x, 1, 3) / 405000 +
SingularityFunction(x, 3, 3) / 3000 -
37 * SingularityFunction(x, 4, 3) / 202500)
def test_deltasummation_mul_add_x_y_add_kd_kd():
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
def trigintegrate(f, x, conds='piecewise'):
"""Integrate f = Mul(trig) over x
>>> from sympy import Symbol, sin, cos, tan, sec, csc, cot
>>> from sympy.integrals.trigonometry import trigintegrate
>>> from sympy.abc import x
>>> trigintegrate(sin(x)*cos(x), x)
sin(x)**2/2
>>> trigintegrate(sin(x)**2, x)
x/2 - sin(x)*cos(x)/2
>>> trigintegrate(tan(x)*sec(x), x)
1/cos(x)
>>> trigintegrate(sin(x)*tan(x), x)
-log(sin(x) - 1)/2 + log(sin(x) + 1)/2 - sin(x)
http://en.wikibooks.org/wiki/Calculus/Integration_techniques
See Also
========
sympy.integrals.integrals.Integral.doit
sympy.integrals.integrals.Integral
"""
from sympy.integrals.integrals import integrate
pat, a, n, m = _pat_sincos(x)
f = f.rewrite('sincos')
M = f.match(pat)
if M is None:
return
n, m = M[n], M[m]
if n.is_zero and m.is_zero:
return x
zz = x if n.is_zero else S.Zero
a = M[a]
if n.is_odd or m.is_odd:
u = _u
n_, m_ = n.is_odd, m.is_odd
# take smallest n or m -- to choose simplest substitution
if n_ and m_:
# Make sure to choose the positive one
# otherwise an incorrect integral can occur.
if n < 0 and m > 0:
m_ = True
n_ = False
elif m < 0 and n > 0:
n_ = True
m_ = False
# Both are negative so choose the smallest n or m
# in absolute value for simplest substitution.
elif (n < 0 and m < 0):
n_ = n > m
m_ = not (n > m)
# Both n and m are odd and positive
else:
n_ = (n < m) # NB: careful here, one of the
m_ = not (n < m) # conditions *must* be true
# n m u=C (n-1)/2 m
# S(x) * C(x) dx --> -(1-u^2) * u du
if n_:
ff = -(1 - u**2)**((n - 1) / 2) * u**m
uu = cos(a * x)
# n m u=S n (m-1)/2
# S(x) * C(x) dx --> u * (1-u^2) du
elif m_:
ff = u**n * (1 - u**2)**((m - 1) / 2)
uu = sin(a * x)
fi = integrate(ff, u) # XXX cyclic deps
fx = fi.subs(u, uu)
if conds == 'piecewise':
return Piecewise((fx / a, Ne(a, 0)), (zz, True))
return fx / a
# n & m are both even
#
# 2k 2m 2l 2l
# we transform S (x) * C (x) into terms with only S (x) or C (x)
#
# example:
# 100 4 100 2 2 100 4 2
# S (x) * C (x) = S (x) * (1-S (x)) = S (x) * (1 + S (x) - 2*S (x))
#
# 104 102 100
# = S (x) - 2*S (x) + S (x)
# 2k
# then S is integrated with recursive formula
# take largest n or m -- to choose simplest substitution
n_ = (abs(n) > abs(m))
m_ = (abs(m) > abs(n))
res = S.Zero
if n_:
# 2k 2 k i 2i
# C = (1 - S ) = sum(i, (-) * B(k, i) * S )
if m > 0:
for i in range(0, m // 2 + 1):
res += ((-1)**i * binomial(m // 2, i) *
_sin_pow_integrate(n + 2 * i, x))
elif m == 0:
res = _sin_pow_integrate(n, x)
else:
# m < 0 , |n| > |m|
# /
# |
# | m n
# | cos (x) sin (x) dx =
# |
# |
#/
# /
# |
# -1 m+1 n-1 n - 1 | m+2 n-2
# ________ cos (x) sin (x) + _______ | cos (x) sin (x) dx
# |
# m + 1 m + 1 |
# /
res = (Rational(-1, m + 1) * cos(x)**(m + 1) * sin(x)**(n - 1) +
Rational(n - 1, m + 1) *
trigintegrate(cos(x)**(m + 2) * sin(x)**(n - 2), x))
elif m_:
# 2k 2 k i 2i
# S = (1 - C ) = sum(i, (-) * B(k, i) * C )
if n > 0:
# / /
# | |
# | m n | -m n
# | cos (x)*sin (x) dx or | cos (x) * sin (x) dx
# | |
# / /
#
# |m| > |n| ; m, n >0 ; m, n belong to Z - {0}
# n 2
# sin (x) term is expanded here in terms of cos (x),
# and then integrated.
#
for i in range(0, n // 2 + 1):
res += ((-1)**i * binomial(n // 2, i) *
_cos_pow_integrate(m + 2 * i, x))
elif n == 0:
# /
# |
# | 1
# | _ _ _
# | m
# | cos (x)
# /
#
res = _cos_pow_integrate(m, x)
else:
# n < 0 , |m| > |n|
# /
# |
# | m n
# | cos (x) sin (x) dx =
# |
# |
#/
# /
# |
# 1 m-1 n+1 m - 1 | m-2 n+2
# _______ cos (x) sin (x) + _______ | cos (x) sin (x) dx
# |
# n + 1 n + 1 |
# /
res = (Rational(1, n + 1) * cos(x)**(m - 1) * sin(x)**(n + 1) +
Rational(m - 1, n + 1) *
trigintegrate(cos(x)**(m - 2) * sin(x)**(n + 2), x))
else:
if m == n:
##Substitute sin(2x)/2 for sin(x)cos(x) and then Integrate.
res = integrate((sin(2 * x) * S.Half)**m, x)
elif (m == -n):
if n < 0:
# Same as the scheme described above.
# the function argument to integrate in the end will
# be 1 , this cannot be integrated by trigintegrate.
# Hence use sympy.integrals.integrate.
res = (Rational(1, n + 1) * cos(x)**(m - 1) * sin(x)**(n + 1) +
Rational(m - 1, n + 1) *
integrate(cos(x)**(m - 2) * sin(x)**(n + 2), x))
else:
res = (
Rational(-1, m + 1) * cos(x)**(m + 1) * sin(x)**(n - 1) +
Rational(n - 1, m + 1) *
integrate(cos(x)**(m + 2) * sin(x)**(n - 2), x))
if conds == 'piecewise':
return Piecewise((res.subs(x, a * x) / a, Ne(a, 0)), (zz, True))
return res.subs(x, a * x) / a
def test_ITE_rewrite_Piecewise():
assert ITE(A, B, C).rewrite(Piecewise) == Piecewise((B, A), (C, True))
def deltasummation(f, limit, no_piecewise=False):
"""
Handle summations containing a KroneckerDelta.
The idea for summation is the following:
- If we are dealing with a KroneckerDelta expression, i.e. KroneckerDelta(g(x), j),
we try to simplify it.
If we could simplify it, then we sum the resulting expression.
We already know we can sum a simplified expression, because only
simple KroneckerDelta expressions are involved.
If we couldn't simplify it, there are two cases:
1) The expression is a simple expression: we return the summation,
taking care if we are dealing with a Derivative or with a proper
KroneckerDelta.
2) The expression is not simple (i.e. KroneckerDelta(cos(x))): we can do
nothing at all.
- If the expr is a multiplication expr having a KroneckerDelta term:
First we expand it.
If the expansion did work, then we try to sum the expansion.
If not, we try to extract a simple KroneckerDelta term, then we have two
cases:
1) We have a simple KroneckerDelta term, so we return the summation.
2) We didn't have a simple term, but we do have an expression with
simplified KroneckerDelta terms, so we sum this expression.
Examples
========
>>> from sympy import oo
>>> from sympy.abc import i, j, k
>>> from sympy.concrete.delta import deltasummation
>>> from sympy import KroneckerDelta, Piecewise
>>> deltasummation(KroneckerDelta(i, k), (k, -oo, oo))
1
>>> deltasummation(KroneckerDelta(i, k), (k, 0, oo))
Piecewise((1, i >= 0), (0, True))
>>> deltasummation(KroneckerDelta(i, k), (k, 1, 3))
Piecewise((1, And(1 <= i, i <= 3)), (0, True))
>>> deltasummation(k*KroneckerDelta(i, j)*KroneckerDelta(j, k), (k, -oo, oo))
j*KroneckerDelta(i, j)
>>> deltasummation(j*KroneckerDelta(i, j), (j, -oo, oo))
i
>>> deltasummation(i*KroneckerDelta(i, j), (i, -oo, oo))
j
See Also
========
deltaproduct
sympy.functions.special.tensor_functions.KroneckerDelta
sympy.concrete.sums.summation
"""
from sympy.concrete.summations import summation
from sympy.solvers import solve
if ((limit[2] - limit[1]) < 0) is True:
return S.Zero
if not f.has(KroneckerDelta):
return summation(f, limit)
x = limit[0]
g = _expand_delta(f, x)
if g.is_Add:
return piecewise_fold(
g.func(*[deltasummation(h, limit, no_piecewise) for h in g.args]))
# try to extract a simple KroneckerDelta term
delta, expr = _extract_delta(g, x)
if not delta:
return summation(f, limit)
solns = solve(delta.args[0] - delta.args[1], x)
if len(solns) == 0:
return S.Zero
elif len(solns) != 1:
return Sum(f, limit)
value = solns[0]
if no_piecewise:
return expr.subs(x, value)
return Piecewise(
(expr.subs(x, value), Interval(*limit[1:3]).as_relational(value)),
(S.Zero, True)
)
def bspline_basis(d, knots, n, x, close=True):
"""The n-th B-spline at x of degree d with knots.
B-Splines are piecewise polynomials of degree d [1]. They are defined on
a set of knots, which is a sequence of integers or floats.
The 0th degree splines have a value of one on a single interval:
>>> from sympy import bspline_basis
>>> from sympy.abc import x
>>> d = 0
>>> knots = range(5)
>>> bspline_basis(d, knots, 0, x)
Piecewise((1, [0, 1]), (0, True))
For a given (d, knots) there are len(knots)-d-1 B-splines defined, that
are indexed by n (starting at 0).
Here is an example of a cubic B-spline:
>>> bspline_basis(3, range(5), 0, x)
Piecewise((x**3/6, [0, 1)), (2/3 - 2*x + 2*x**2 - x**3/2, [1, 2)), (-22/3 + 10*x - 4*x**2 + x**3/2, [2, 3)), (32/3 - 8*x + 2*x**2 - x**3/6, [3, 4]), (0, True))
By repeating knot points, you can introduce discontinuities in the
B-splines and their derivatives:
>>> d = 1
>>> knots = [0,0,2,3,4]
>>> bspline_basis(d, knots, 0, x)
Piecewise((1 - x/2, [0, 2]), (0, True))
It is quite time consuming to construct and evaluate B-splines. If you
need to evaluate a B-splines many times, it is best to lambdify them
first:
>>> from sympy import lambdify
>>> d = 3
>>> knots = range(10)
>>> b0 = bspline_basis(d, knots, 0, x)
>>> f = lambdify(x, b0)
>>> y = f(0.5)
[1] http://en.wikipedia.org/wiki/B-spline
"""
knots = [sympify(k) for k in knots]
d = int(d)
n = int(n)
n_knots = len(knots)
n_intervals = n_knots - 1
if n + d + 1 > n_intervals:
raise ValueError('n+d+1 must not exceed len(knots)-1')
if d == 0:
result = Piecewise(
(S.One, Interval(knots[n], knots[n + 1], False, True)), (0, True))
elif d > 0:
denom = knots[n + d] - knots[n]
if denom != S.Zero:
A = (x - knots[n]) / denom
b1 = bspline_basis(d - 1, knots, n, x, close=False)
else:
b1 = A = S.Zero
denom = knots[n + d + 1] - knots[n + 1]
if denom != S.Zero:
B = (knots[n + d + 1] - x) / denom
b2 = bspline_basis(d - 1, knots, n + 1, x, close=False)
else:
b2 = B = S.Zero
result = _add_splines(A, b1, B, b2)
else:
raise ValueError('degree must be non-negative: %r' % n)
if close:
final_ec_pair = result.args[-2]
final_cond = final_ec_pair.cond
final_expr = final_ec_pair.expr
new_args = final_cond.args[:3] + (False, )
new_ec_pair = ExprCondPair(final_expr, Interval(*new_args))
new_args = result.args[:-2] + (new_ec_pair, result.args[-1])
result = Piecewise(*new_args)
return result
def _solve_hinge_beams(self, *reactions):
"""Method to find integration constants and reactional variables in a
composite beam connected via hinge.
This method resolves the composite Beam into its sub-beams and then
equations of shear force, bending moment, slope and deflection are
evaluated for both of them separately. These equations are then solved
for unknown reactions and integration constants using the boundary
conditions applied on the Beam. Equal deflection of both sub-beams
at the hinge joint gives us another equation to solve the system.
Examples
========
A combined beam, with constant fkexural rigidity E*I, is formed by joining
a Beam of length 2*l to the right of another Beam of length l. The whole beam
is fixed at both of its both end. A point load of magnitude P is also applied
from the top at a distance of 2*l from starting point.
>>> from sympy.physics.continuum_mechanics.beam import Beam
>>> from sympy import symbols
>>> E, I = symbols('E, I')
>>> l=symbols('l', positive=True)
>>> b1=Beam(l ,E,I)
>>> b2=Beam(2*l ,E,I)
>>> b=b1.join(b2,"hinge")
>>> M1, A1, M2, A2, P = symbols('M1 A1 M2 A2 P')
>>> b.apply_load(A1,0,-1)
>>> b.apply_load(M1,0,-2)
>>> b.apply_load(P,2*l,-1)
>>> b.apply_load(A2,3*l,-1)
>>> b.apply_load(M2,3*l,-2)
>>> b.bc_slope=[(0,0), (3*l, 0)]
>>> b.bc_deflection=[(0,0), (3*l, 0)]
>>> b.solve_for_reaction_loads(M1, A1, M2, A2)
>>> b.reaction_loads
{A1: -5*P/18, A2: -13*P/18, M1: 5*P*l/18, M2: -4*P*l/9}
>>> b.slope()
Piecewise(((5*P*l*SingularityFunction(x, 0, 1)/18 - 5*P*SingularityFunction(x, 0, 2)/36
+ 5*P*SingularityFunction(x, l, 2)/36)/(E*I), l >= x), ((P*l**2/18 - 4*P*l*SingularityFunction(-l +
x, 2*l, 1)/9 - 5*P*SingularityFunction(-l + x, 0, 2)/36 + P*SingularityFunction(-l + x, l, 2)/2
- 13*P*SingularityFunction(-l + x, 2*l, 2)/36)/(E*I), x < 3*l))
>>> b.deflection()
Piecewise(((5*P*l*SingularityFunction(x, 0, 2)/36 - 5*P*SingularityFunction(x, 0, 3)/108
+ 5*P*SingularityFunction(x, l, 3)/108)/(E*I), l >= x), ((5*P*l**3/54 + P*l**2*(-l + x)/18
- 2*P*l*SingularityFunction(-l + x, 2*l, 2)/9 - 5*P*SingularityFunction(-l + x, 0, 3)/108
+ P*SingularityFunction(-l + x, l, 3)/6 - 13*P*SingularityFunction(-l + x, 2*l, 3)/108)/(E*I), x < 3*l))
"""
x = self.variable
l = self._hinge_position
E = self._elastic_modulus
I = self._second_moment
if isinstance(I, Piecewise):
I1 = I.args[0][0]
I2 = I.args[1][0]
else:
I1 = I2 = I
load_1 = 0 # Load equation on first segment of composite beam
load_2 = 0 # Load equation on second segment of composite beam
# Distributing load on both segments
for load in self.applied_loads:
if load[1] < l:
load_1 += load[0]*SingularityFunction(x, load[1], load[2])
if load[2] == 0:
load_1 -= load[0]*SingularityFunction(x, load[3], load[2])
elif load[2] > 0:
load_1 -= load[0]*SingularityFunction(x, load[3], load[2]) + load[0]*SingularityFunction(x, load[3], 0)
elif load[1] == l:
load_1 += load[0]*SingularityFunction(x, load[1], load[2])
load_2 += load[0]*SingularityFunction(x, load[1] - l, load[2])
elif load[1] > l:
load_2 += load[0]*SingularityFunction(x, load[1] - l, load[2])
if load[2] == 0:
load_2 -= load[0]*SingularityFunction(x, load[3] - l, load[2])
elif load[2] > 0:
load_2 -= load[0]*SingularityFunction(x, load[3] - l, load[2]) + load[0]*SingularityFunction(x, load[3] - l, 0)
h = Symbol('h') # Force due to hinge
load_1 += h*SingularityFunction(x, l, -1)
load_2 -= h*SingularityFunction(x, 0, -1)
eq = []
shear_1 = integrate(load_1, x)
shear_curve_1 = limit(shear_1, x, l)
eq.append(shear_curve_1)
bending_1 = integrate(shear_1, x)
moment_curve_1 = limit(bending_1, x, l)
eq.append(moment_curve_1)
shear_2 = integrate(load_2, x)
shear_curve_2 = limit(shear_2, x, self.length - l)
eq.append(shear_curve_2)
bending_2 = integrate(shear_2, x)
moment_curve_2 = limit(bending_2, x, self.length - l)
eq.append(moment_curve_2)
C1 = Symbol('C1')
C2 = Symbol('C2')
C3 = Symbol('C3')
C4 = Symbol('C4')
slope_1 = S(1)/(E*I1)*(integrate(bending_1, x) + C1)
def_1 = S(1)/(E*I1)*(integrate((E*I)*slope_1, x) + C1*x + C2)
slope_2 = S(1)/(E*I2)*(integrate(integrate(integrate(load_2, x), x), x) + C3)
def_2 = S(1)/(E*I2)*(integrate((E*I)*slope_2, x) + C4)
for position, value in self.bc_slope:
if position<l:
eq.append(slope_1.subs(x, position) - value)
else:
eq.append(slope_2.subs(x, position - l) - value)
for position, value in self.bc_deflection:
if position<l:
eq.append(def_1.subs(x, position) - value)
else:
eq.append(def_2.subs(x, position - l) - value)
eq.append(def_1.subs(x, l) - def_2.subs(x, 0)) # Deflection of both the segments at hinge would be equal
constants = list(linsolve(eq, C1, C2, C3, C4, h, *reactions))
reaction_values = list(constants[0])[5:]
self._reaction_loads = dict(zip(reactions, reaction_values))
self._load = self._load.subs(self._reaction_loads)
# Substituting constants and reactional load and moments with their corresponding values
slope_1 = slope_1.subs({C1: constants[0][0], h:constants[0][4]}).subs(self._reaction_loads)
def_1 = def_1.subs({C1: constants[0][0], C2: constants[0][1], h:constants[0][4]}).subs(self._reaction_loads)
slope_2 = slope_2.subs({x: x-l, C3: constants[0][2], h:constants[0][4]}).subs(self._reaction_loads)
def_2 = def_2.subs({x: x-l,C3: constants[0][2], C4: constants[0][3], h:constants[0][4]}).subs(self._reaction_loads)
self._hinge_beam_slope = Piecewise((slope_1, x<=l), (slope_2, x<self.length))
self._hinge_beam_deflection = Piecewise((def_1, x<=l), (def_2, x<self.length))
def _print_ITE(self, expr):
from sympy.functions import Piecewise
_piecewise = Piecewise((expr.args[1], expr.args[0]),
(expr.args[2], True))
return self._print(_piecewise)
bq = params[1]
x = ab[0] / ab[1]
h = hyper(ap, bq, x)
return f.subs(i, 0) * hyperexpand(h), h.convergence_statement
def eval_sum_hyper(f, (i, a, b)):
from sympy.functions import Piecewise
from sympy import oo, And
if b != oo:
if a == -oo:
res = _eval_sum_hyper(f.subs(i, -i), i, -b)
if res is not None:
return Piecewise(res, (Sum(f, (i, a, b)), True))
else:
return None
if a == -oo:
res1 = _eval_sum_hyper(f.subs(i, -i), i, 1)
res2 = _eval_sum_hyper(f, i, 0)
if res1 is None or res2 is None:
return None
res1, cond1 = res1
res2, cond2 = res2
cond = And(cond1, cond2)
if cond is False:
return None
return Piecewise((res1 + res2, cond), (Sum(f, (i, a, b)), True))
def interpolating_spline(d, x, X, Y):
"""Return spline of degree ``d`` interpolating for given
``X`` and ``Y`` values.
This function returns a piecewise function such that each part is
a polynomial of degreeat most ``d`` .
The degree ``d`` must be at least 1. The values listed in X must
be strictly increasing.
Examples
========
>>> from sympy import interpolating_spline
>>> from sympy.abc import x
>>> interpolating_spline(1, x, [1, 2, 4, 7], [3, 6, 5, 7])
Piecewise((3*x, (x >= 1) & (x <= 2)),
(-x/2 + 7, (x >= 2) & (x <= 4)),
(2*x/3 + 7/3, (x >= 4) & (x <= 7)))
>>> interpolating_spline(3, x, [-2, 0, 1, 3, 4], [4, 2, 1, 1, 3])
Piecewise((-x**3/36 - x**2/36 - 17*x/18 + 2, (x >= -2) & (x <= 1)),
(5*x**3/36 - 13*x**2/36 - 11*x/18 + 7/3, (x >= 1) & (x <= 4)))
See Also
========
bsplines_basis_set, sympy.polys.specialpolys.interpolating_poly
"""
from sympy import symbols, Number, Dummy, Rational
from sympy.solvers.solveset import linsolve
from sympy.matrices.dense import Matrix
# Input sanitization
d = sympify(d)
if not (d.is_Integer and d.is_positive):
raise ValueError("Spline degree must be a positive integer, not %s" %
d)
if len(X) != len(Y):
raise ValueError('Number of X and Y coordinates passed not equal')
if len(X) < d + 1:
raise ValueError(
'Degree must be less than the number of control points')
if not all(a < b for a, b in zip(X, X[1:])):
raise ValueError('The x-coordinates must be strictly increasing')
# Evaluating knots value
if d.is_odd:
j = (d + 1) // 2
interior_knots = X[j:-j]
else:
j = d // 2
interior_knots = [
Rational(a + b, 2) for a, b in zip(X[j:-j - 1], X[j + 1:-j])
]
knots = [X[0]] * (d + 1) + list(interior_knots) + [X[-1]] * (d + 1)
basis = bspline_basis_set(d, knots, x)
A = [[b.subs(x, v) for b in basis] for v in X]
coeff = linsolve((Matrix(A), Matrix(Y)),
symbols('c0:{}'.format(len(X)), cls=Dummy))
coeff = list(coeff)[0]
intervals = set([c for b in basis for (e, c) in b.args if c != True])
# Sorting the intervals
ival = [e.atoms(Number)
for e in intervals] # List containing end-points of each interval
ival = [list(sorted(e))[0] for e in ival]
com = zip(ival, intervals)
com = sorted(com, key=lambda x: x[0])
intervals = [y for x, y in com]
basis_dicts = [dict((c, e) for (e, c) in b.args) for b in basis]
spline = []
for i in intervals:
piece = sum(
[c * d.get(i, S.Zero) for (c, d) in zip(coeff, basis_dicts)],
S.Zero)
spline.append((piece, i))
return (Piecewise(*spline))
def test_BooleanFunction_diff():
assert And(x, y).diff(x) == Piecewise((0, Eq(y, False)), (1, True))
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d * b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c * b1)
else:
new_args = []
# Just combining the Piecewise without any fancy optimization
p1 = piecewise_fold(c * b1)
p2 = piecewise_fold(d * b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assumes the conditions in
# p1 and p2 are sorted
for arg in p1.args[:-1]:
# Conditional of Piecewise are And objects
# the args of the And object is a tuple of two
# Relational objects the numerical value is in the .rhs
# of the Relational object
expr = arg.expr
cond = arg.cond
lower = cond.args[0].rhs
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2 = cond2.args[0].rhs
upper_2 = cond2.args[1].rhs
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1,
# add to new_args by itself (no match expected
# in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
rv = Piecewise(*new_args)
return rv.expand()
def test_octave_piecewise_times_const():
pw = Piecewise((x, x < 1), (x**2, True))
assert mcode(2 * pw) == "2*((x < 1).*(x) + (~(x < 1)).*(x.^2))"
assert mcode(pw / x) == "((x < 1).*(x) + (~(x < 1)).*(x.^2))./x"
assert mcode(pw / (x * y)) == "((x < 1).*(x) + (~(x < 1)).*(x.^2))./(x.*y)"
assert mcode(pw / 3) == "((x < 1).*(x) + (~(x < 1)).*(x.^2))/3"
def interpolating_spline(d, x, X, Y):
"""
Return spline of degree *d*, passing through the given *X*
and *Y* values.
Explanation
===========
This function returns a piecewise function such that each part is
a polynomial of degree not greater than *d*. The value of *d*
must be 1 or greater and the values of *X* must be strictly
increasing.
Examples
========
>>> from sympy import interpolating_spline
>>> from sympy.abc import x
>>> interpolating_spline(1, x, [1, 2, 4, 7], [3, 6, 5, 7])
Piecewise((3*x, (x >= 1) & (x <= 2)),
(7 - x/2, (x >= 2) & (x <= 4)),
(2*x/3 + 7/3, (x >= 4) & (x <= 7)))
>>> interpolating_spline(3, x, [-2, 0, 1, 3, 4], [4, 2, 1, 1, 3])
Piecewise((7*x**3/117 + 7*x**2/117 - 131*x/117 + 2, (x >= -2) & (x <= 1)),
(10*x**3/117 - 2*x**2/117 - 122*x/117 + 77/39, (x >= 1) & (x <= 4)))
See Also
========
bspline_basis_set, interpolating_poly
"""
from sympy import symbols, Number, Dummy, Rational
from sympy.solvers.solveset import linsolve
from sympy.matrices.dense import Matrix
# Input sanitization
d = sympify(d)
if not (d.is_Integer and d.is_positive):
raise ValueError("Spline degree must be a positive integer, not %s." %
d)
if len(X) != len(Y):
raise ValueError("Number of X and Y coordinates must be the same.")
if len(X) < d + 1:
raise ValueError(
"Degree must be less than the number of control points.")
if not all(a < b for a, b in zip(X, X[1:])):
raise ValueError("The x-coordinates must be strictly increasing.")
# Evaluating knots value
if d.is_odd:
j = (d + 1) // 2
interior_knots = X[j:-j]
else:
j = d // 2
interior_knots = [
Rational(a + b, 2) for a, b in zip(X[j:-j - 1], X[j + 1:-j])
]
knots = [X[0]] * (d + 1) + list(interior_knots) + [X[-1]] * (d + 1)
basis = bspline_basis_set(d, knots, x)
A = [[b.subs(x, v) for b in basis] for v in X]
coeff = linsolve((Matrix(A), Matrix(Y)),
symbols("c0:{}".format(len(X)), cls=Dummy))
coeff = list(coeff)[0]
intervals = set([c for b in basis for (e, c) in b.args if c != True])
# Sorting the intervals
# ival contains the end-points of each interval
ival = [e.atoms(Number) for e in intervals]
ival = [list(sorted(e))[0] for e in ival]
com = zip(ival, intervals)
com = sorted(com, key=lambda x: x[0])
intervals = [y for x, y in com]
basis_dicts = [dict((c, e) for (e, c) in b.args) for b in basis]
spline = []
for i in intervals:
piece = sum(
[c * d.get(i, S.Zero) for (c, d) in zip(coeff, basis_dicts)],
S.Zero)
spline.append((piece, i))
return Piecewise(*spline)
def roots_quartic(f):
r"""
Returns a list of roots of a quartic polynomial.
There are many references for solving quartic expressions available [1-5].
This reviewer has found that many of them require one to select from among
2 or more possible sets of solutions and that some solutions work when one
is searching for real roots but don't work when searching for complex roots
(though this is not always stated clearly). The following routine has been
tested and found to be correct for 0, 2 or 4 complex roots.
The quasisymmetric case solution [6] looks for quartics that have the form
`x**4 + A*x**3 + B*x**2 + C*x + D = 0` where `(C/A)**2 = D`.
Although no general solution that is always applicable for all
coefficients is known to this reviewer, certain conditions are tested
to determine the simplest 4 expressions that can be returned:
1) `f = c + a*(a**2/8 - b/2) == 0`
2) `g = d - a*(a*(3*a**2/256 - b/16) + c/4) = 0`
3) if `f != 0` and `g != 0` and `p = -d + a*c/4 - b**2/12` then
a) `p == 0`
b) `p != 0`
Examples
========
>>> from sympy import Poly, symbols, I
>>> from sympy.polys.polyroots import roots_quartic
>>> r = roots_quartic(Poly('x**4-6*x**3+17*x**2-26*x+20'))
>>> # 4 complex roots: 1+-I*sqrt(3), 2+-I
>>> sorted(str(tmp.evalf(n=2)) for tmp in r)
['1.0 + 1.7*I', '1.0 - 1.7*I', '2.0 + 1.0*I', '2.0 - 1.0*I']
References
==========
1. http://mathforum.org/dr.math/faq/faq.cubic.equations.html
2. https://en.wikipedia.org/wiki/Quartic_function#Summary_of_Ferrari.27s_method
3. http://planetmath.org/encyclopedia/GaloisTheoreticDerivationOfTheQuarticFormula.html
4. http://staff.bath.ac.uk/masjhd/JHD-CA.pdf
5. http://www.albmath.org/files/Math_5713.pdf
6. http://www.statemaster.com/encyclopedia/Quartic-equation
7. eqworld.ipmnet.ru/en/solutions/ae/ae0108.pdf
"""
_, a, b, c, d = f.monic().all_coeffs()
if not d:
return [S.Zero] + roots([1, a, b, c], multiple=True)
elif (c/a)**2 == d:
x, m = f.gen, c/a
g = Poly(x**2 + a*x + b - 2*m, x)
z1, z2 = roots_quadratic(g)
h1 = Poly(x**2 - z1*x + m, x)
h2 = Poly(x**2 - z2*x + m, x)
r1 = roots_quadratic(h1)
r2 = roots_quadratic(h2)
return r1 + r2
else:
a2 = a**2
e = b - 3*a2/8
f = _mexpand(c + a*(a2/8 - b/2))
g = _mexpand(d - a*(a*(3*a2/256 - b/16) + c/4))
aon4 = a/4
if f is S.Zero:
y1, y2 = [sqrt(tmp) for tmp in
roots([1, e, g], multiple=True)]
return [tmp - aon4 for tmp in [-y1, -y2, y1, y2]]
if g is S.Zero:
y = [S.Zero] + roots([1, 0, e, f], multiple=True)
return [tmp - aon4 for tmp in y]
else:
# Descartes-Euler method, see [7]
sols = _roots_quartic_euler(e, f, g, aon4)
if sols:
return sols
# Ferrari method, see [1, 2]
a2 = a**2
e = b - 3*a2/8
f = c + a*(a2/8 - b/2)
g = d - a*(a*(3*a2/256 - b/16) + c/4)
p = -e**2/12 - g
q = -e**3/108 + e*g/3 - f**2/8
TH = Rational(1, 3)
def _ans(y):
w = sqrt(e + 2*y)
arg1 = 3*e + 2*y
arg2 = 2*f/w
ans = []
for s in [-1, 1]:
root = sqrt(-(arg1 + s*arg2))
for t in [-1, 1]:
ans.append((s*w - t*root)/2 - aon4)
return ans
# p == 0 case
y1 = -5*e/6 - q**TH
if p.is_zero:
return _ans(y1)
# if p != 0 then u below is not 0
root = sqrt(q**2/4 + p**3/27)
r = -q/2 + root # or -q/2 - root
u = r**TH # primary root of solve(x**3 - r, x)
y2 = -5*e/6 + u - p/u/3
if fuzzy_not(p.is_zero):
return _ans(y2)
# sort it out once they know the values of the coefficients
return [Piecewise((a1, Eq(p, 0)), (a2, True))
for a1, a2 in zip(_ans(y1), _ans(y2))]
def bspline_basis(d, knots, n, x):
"""
The $n$-th B-spline at $x$ of degree $d$ with knots.
Explanation
===========
B-Splines are piecewise polynomials of degree $d$. They are defined on a
set of knots, which is a sequence of integers or floats.
Examples
========
The 0th degree splines have a value of 1 on a single interval:
>>> from sympy import bspline_basis
>>> from sympy.abc import x
>>> d = 0
>>> knots = tuple(range(5))
>>> bspline_basis(d, knots, 0, x)
Piecewise((1, (x >= 0) & (x <= 1)), (0, True))
For a given ``(d, knots)`` there are ``len(knots)-d-1`` B-splines
defined, that are indexed by ``n`` (starting at 0).
Here is an example of a cubic B-spline:
>>> bspline_basis(3, tuple(range(5)), 0, x)
Piecewise((x**3/6, (x >= 0) & (x <= 1)),
(-x**3/2 + 2*x**2 - 2*x + 2/3,
(x >= 1) & (x <= 2)),
(x**3/2 - 4*x**2 + 10*x - 22/3,
(x >= 2) & (x <= 3)),
(-x**3/6 + 2*x**2 - 8*x + 32/3,
(x >= 3) & (x <= 4)),
(0, True))
By repeating knot points, you can introduce discontinuities in the
B-splines and their derivatives:
>>> d = 1
>>> knots = (0, 0, 2, 3, 4)
>>> bspline_basis(d, knots, 0, x)
Piecewise((1 - x/2, (x >= 0) & (x <= 2)), (0, True))
It is quite time consuming to construct and evaluate B-splines. If
you need to evaluate a B-spline many times, it is best to lambdify them
first:
>>> from sympy import lambdify
>>> d = 3
>>> knots = tuple(range(10))
>>> b0 = bspline_basis(d, knots, 0, x)
>>> f = lambdify(x, b0)
>>> y = f(0.5)
See Also
========
bspline_basis_set
References
==========
.. [1] https://en.wikipedia.org/wiki/B-spline
"""
knots = tuple(sympify(k) for k in knots)
d = int(d)
n = int(n)
n_knots = len(knots)
n_intervals = n_knots - 1
if n + d + 1 > n_intervals:
raise ValueError("n + d + 1 must not exceed len(knots) - 1")
if d == 0:
result = Piecewise(
(S.One, Interval(knots[n], knots[n + 1]).contains(x)), (0, True))
elif d > 0:
denom = knots[n + d + 1] - knots[n + 1]
if denom != S.Zero:
B = (knots[n + d + 1] - x) / denom
b2 = bspline_basis(d - 1, knots, n + 1, x)
else:
b2 = B = S.Zero
denom = knots[n + d] - knots[n]
if denom != S.Zero:
A = (x - knots[n]) / denom
b1 = bspline_basis(d - 1, knots, n, x)
else:
b1 = A = S.Zero
result = _add_splines(A, b1, B, b2)
else:
raise ValueError("degree must be non-negative: %r" % n)
return result
