def _contains(self, other):
from sympy.functions import arg, Abs
from sympy.core.containers import Tuple
other = sympify(other)
isTuple = isinstance(other, Tuple)
if isTuple and len(other) != 2:
raise ValueError('expecting Tuple of length 2')
# If the other is not an Expression, and neither a Tuple
if not isinstance(other, Expr) and not isinstance(other, Tuple):
return S.false
# self in rectangular form
if not self.polar:
re, im = other if isTuple else other.as_real_imag()
for element in self.psets:
if And(element.args[0]._contains(re),
element.args[1]._contains(im)):
return True
return False
# self in polar form
elif self.polar:
if isTuple:
r, theta = other
elif other.is_zero:
r, theta = S.Zero, S.Zero
else:
r, theta = Abs(other), arg(other)
for element in self.psets:
if And(element.args[0]._contains(r),
element.args[1]._contains(theta)):
return True
return False
def _contains(self, other):
from sympy.functions import arg, Abs
from sympy.core.containers import Tuple
other = sympify(other)
isTuple = isinstance(other, Tuple)
if isTuple and len(other) != 2:
raise ValueError('expecting Tuple of length 2')
# If the other is not an Expression, and neither a Tuple
if not isinstance(other, Expr) and not isinstance(other, Tuple):
return S.false
# self in rectangular form
if not self.polar:
re, im = other if isTuple else other.as_real_imag()
for element in self.psets:
if And(element.args[0]._contains(re),
element.args[1]._contains(im)):
return True
return False
# self in polar form
elif self.polar:
if isTuple:
r, theta = other
elif other.is_zero:
r, theta = S.Zero, S.Zero
else:
r, theta = Abs(other), arg(other)
for element in self.psets:
if And(element.args[0]._contains(r),
element.args[1]._contains(theta)):
return True
return False
def _contains(self, other):
from sympy.functions import arg, Abs
other = sympify(other)
isTuple = isinstance(other, Tuple)
if isTuple and len(other) != 2:
raise ValueError('expecting Tuple of length 2')
# If the other is not an Expression, and neither a Tuple
if not isinstance(other, (Expr, Tuple)):
return S.false
# self in rectangular form
if not self.polar:
re, im = other if isTuple else other.as_real_imag()
return fuzzy_or(fuzzy_and([
pset.args[0]._contains(re),
pset.args[1]._contains(im)])
for pset in self.psets)
# self in polar form
elif self.polar:
if other.is_zero:
# ignore undefined complex argument
return fuzzy_or(pset.args[0]._contains(S.Zero)
for pset in self.psets)
if isTuple:
r, theta = other
else:
r, theta = Abs(other), arg(other)
if theta.is_real and theta.is_number:
# angles in psets are normalized to [0, 2pi)
theta %= 2*S.Pi
return fuzzy_or(fuzzy_and([
pset.args[0]._contains(r),
pset.args[1]._contains(theta)])
for pset in self.psets)
def computeSpinWeightCoeff(self,l):
fname="Lebedev/lebedev_" +"{:03d}".format(self.qprec)+".txt"
lebedev_theata=[]
lebedev_phi=[]
lebedev_w=[]
# read lebedev points
with open(fname,'r') as f:
for row in f:
row=row.strip().split()
lebedev_theata.append(float(row[0]))
lebedev_phi.append(float(row[1]))
lebedev_w.append(float(row[2]))
#print(lebedev_w)
numQuadPts=len(lebedev_theata);
#print(numQuadPts)
cReal=[]
cImg=[]
cArg=[]
for m in range(-l,l+1):
self.psi4_lm=0
for q in range(0,numQuadPts):
self.psi4_lm=self.psi4_lm + self.psi4_s2*lebedev_w[q]*self.swsh(self.spin,l,m,lebedev_theata[q],lebedev_phi[q])
cReal.append(re(self.psi4_lm))
cImg.append(im(self.psi4_lm))
cArg.append(arg(self.psi4_lm))
return [cReal,cImg,cArg]
def test_Function():
assert mcode(sin(x) ** cos(x)) == "sin(x).^cos(x)"
assert mcode(abs(x)) == "abs(x)"
assert mcode(ceiling(x)) == "ceil(x)"
assert mcode(arg(x)) == "angle(x)"
assert mcode(im(x)) == "imag(x)"
assert mcode(re(x)) == "real(x)"
assert mcode(Max(x, y) + Min(x, y)) == "max(x, y) + min(x, y)"
assert mcode(Max(x, y, z)) == "max(x, max(y, z))"
assert mcode(Min(x, y, z)) == "min(x, min(y, z))"
def test_Function():
assert mcode(sin(x)**cos(x)) == "sin(x).^cos(x)"
assert mcode(abs(x)) == "abs(x)"
assert mcode(ceiling(x)) == "ceil(x)"
assert mcode(arg(x)) == "angle(x)"
assert mcode(im(x)) == "imag(x)"
assert mcode(re(x)) == "real(x)"
assert mcode(Max(x, y) + Min(x, y)) == "max(x, y) + min(x, y)"
assert mcode(Max(x, y, z)) == "max(x, max(y, z))"
assert mcode(Min(x, y, z)) == "min(x, min(y, z))"
def _invert_complex(f, g_ys, symbol):
""" Helper function for invert_complex """
if not f.has(symbol):
raise ValueError("Inverse of constant function doesn't exist")
if f is symbol:
return (f, g_ys)
n = Dummy('n')
if f.is_Add:
# f = g + h
g, h = f.as_independent(symbol)
if g != S.Zero:
return _invert_complex(h, imageset(Lambda(n, n - g), g_ys), symbol)
if f.is_Mul:
# f = g*h
g, h = f.as_independent(symbol)
if g != S.One:
return _invert_complex(h, imageset(Lambda(n, n / g), g_ys), symbol)
if hasattr(f, 'inverse') and \
not isinstance(f, TrigonometricFunction) and \
not isinstance(f, exp):
if len(f.args) > 1:
raise ValueError("Only functions with one argument are supported.")
return _invert_complex(f.args[0],
imageset(Lambda(n,
f.inverse()(n)), g_ys), symbol)
if isinstance(f, exp):
if isinstance(g_ys, FiniteSet):
exp_invs = Union(*[
imageset(
Lambda(n,
I * (2 * n * pi + arg(g_y)) +
log(Abs(g_y))), S.Integers) for g_y in g_ys
if g_y != 0
])
return _invert_complex(f.args[0], exp_invs, symbol)
return (f, g_ys)
def _contains(self, other):
from sympy.functions import arg, Abs
# self in rectangular form
if not self.polar:
re, im = other.as_real_imag()
for element in self.psets:
if And(element.args[0]._contains(re), element.args[1]._contains(im)):
return True
return False
# self in polar form
elif self.polar:
if S(other).is_zero:
r, theta = S(0), S(0)
else:
r, theta = Abs(other), arg(other)
for element in self.psets:
if And(element.args[0]._contains(r), element.args[1]._contains(theta)):
return True
return False
def test_Function_change_name():
assert mcode(abs(x)) == "abs(x)"
assert mcode(ceiling(x)) == "ceil(x)"
assert mcode(arg(x)) == "angle(x)"
assert mcode(im(x)) == "imag(x)"
assert mcode(re(x)) == "real(x)"
assert mcode(conjugate(x)) == "conj(x)"
assert mcode(chebyshevt(y, x)) == "chebyshevT(y, x)"
assert mcode(chebyshevu(y, x)) == "chebyshevU(y, x)"
assert mcode(laguerre(x, y)) == "laguerreL(x, y)"
assert mcode(Chi(x)) == "coshint(x)"
assert mcode(Shi(x)) == "sinhint(x)"
assert mcode(Ci(x)) == "cosint(x)"
assert mcode(Si(x)) == "sinint(x)"
assert mcode(li(x)) == "logint(x)"
assert mcode(loggamma(x)) == "gammaln(x)"
assert mcode(polygamma(x, y)) == "psi(x, y)"
assert mcode(RisingFactorial(x, y)) == "pochhammer(x, y)"
assert mcode(DiracDelta(x)) == "dirac(x)"
assert mcode(DiracDelta(x, 3)) == "dirac(3, x)"
assert mcode(Heaviside(x)) == "heaviside(x)"
assert mcode(Heaviside(x, y)) == "heaviside(x, y)"
def test_Function_change_name():
assert mcode(abs(x)) == "abs(x)"
assert mcode(ceiling(x)) == "ceil(x)"
assert mcode(arg(x)) == "angle(x)"
assert mcode(im(x)) == "imag(x)"
assert mcode(re(x)) == "real(x)"
assert mcode(conjugate(x)) == "conj(x)"
assert mcode(chebyshevt(y, x)) == "chebyshevT(y, x)"
assert mcode(chebyshevu(y, x)) == "chebyshevU(y, x)"
assert mcode(laguerre(x, y)) == "laguerreL(x, y)"
assert mcode(Chi(x)) == "coshint(x)"
assert mcode(Shi(x)) == "sinhint(x)"
assert mcode(Ci(x)) == "cosint(x)"
assert mcode(Si(x)) == "sinint(x)"
assert mcode(li(x)) == "logint(x)"
assert mcode(loggamma(x)) == "gammaln(x)"
assert mcode(polygamma(x, y)) == "psi(x, y)"
assert mcode(RisingFactorial(x, y)) == "pochhammer(x, y)"
assert mcode(DiracDelta(x)) == "dirac(x)"
assert mcode(DiracDelta(x, 3)) == "dirac(3, x)"
assert mcode(Heaviside(x)) == "heaviside(x)"
assert mcode(Heaviside(x, y)) == "heaviside(x, y)"
def _invert_complex(f, g_ys, symbol):
""" Helper function for invert_complex """
if not f.has(symbol):
raise ValueError("Inverse of constant function doesn't exist")
if f is symbol:
return (f, g_ys)
n = Dummy('n')
if f.is_Add:
# f = g + h
g, h = f.as_independent(symbol)
if g != S.Zero:
return _invert_complex(h, imageset(Lambda(n, n - g), g_ys), symbol)
if f.is_Mul:
# f = g*h
g, h = f.as_independent(symbol)
if g != S.One:
return _invert_complex(h, imageset(Lambda(n, n/g), g_ys), symbol)
if hasattr(f, 'inverse') and \
not isinstance(f, C.TrigonometricFunction) and \
not isinstance(f, exp):
if len(f.args) > 1:
raise ValueError("Only functions with one argument are supported.")
return _invert_complex(f.args[0],
imageset(Lambda(n, f.inverse()(n)), g_ys), symbol)
if isinstance(f, exp):
if isinstance(g_ys, FiniteSet):
exp_invs = Union(*[imageset(Lambda(n, I*(2*n*pi + arg(g_y)) +
log(Abs(g_y))), S.Integers)
for g_y in g_ys])
return _invert_complex(f.args[0], exp_invs, symbol)
return (f, g_ys)
def _invert_complex(f, g_ys, symbol):
"""Helper function for _invert."""
if f == symbol:
return (f, g_ys)
n = Dummy("n")
if f.is_Add:
# f = g + h
g, h = f.as_independent(symbol)
if g is not S.Zero:
return _invert_complex(h, imageset(Lambda(n, n - g), g_ys), symbol)
if f.is_Mul:
# f = g*h
g, h = f.as_independent(symbol)
if g is not S.One:
return _invert_complex(h, imageset(Lambda(n, n / g), g_ys), symbol)
if hasattr(f, "inverse") and not isinstance(f, TrigonometricFunction) and not isinstance(f, exp):
if len(f.args) > 1:
raise ValueError("Only functions with one argument are supported.")
return _invert_complex(f.args[0], imageset(Lambda(n, f.inverse()(n)), g_ys), symbol)
if isinstance(f, exp):
if isinstance(g_ys, FiniteSet):
exp_invs = Union(
*[
imageset(Lambda(n, I * (2 * n * pi + arg(g_y)) + log(Abs(g_y))), S.Integers)
for g_y in g_ys
if g_y != 0
]
)
return _invert_complex(f.args[0], exp_invs, symbol)
return (f, g_ys)
def _contains(self, other):
from sympy.functions import arg, Abs
# self in rectangular form
if not self.polar:
re, im = other.as_real_imag()
for element in self.psets:
if And(element.args[0]._contains(re),
element.args[1]._contains(im)):
return True
return False
# self in polar form
elif self.polar:
if sympify(other).is_zero:
r, theta = S.Zero, S.Zero
else:
r, theta = Abs(other), arg(other)
for element in self.psets:
if And(element.args[0]._contains(r),
element.args[1]._contains(theta)):
return True
return False
def bode_phase_numerical_data(system, initial_exp=-5, final_exp=5, **kwargs):
"""
Returns the numerical data of the Bode phase plot of the system.
It is internally used by ``bode_phase_plot`` to get the data
for plotting Bode phase plot. Users can use this data to further
analyse the dynamics of the system or plot using a different
backend/plotting-module.
Parameters
==========
system : SISOLinearTimeInvariant
The system for which the Bode phase plot data is to be computed.
initial_exp : Number, optional
The initial exponent of 10 of the semilog plot. Defaults to -5.
final_exp : Number, optional
The final exponent of 10 of the semilog plot. Defaults to 5.
Returns
=======
tuple : (x, y)
x = x-axis values of the Bode phase plot.
y = y-axis values of the Bode phase plot.
Raises
======
NotImplementedError
When a SISO LTI system is not passed.
When time delay terms are present in the system.
ValueError
When more than one free symbol is present in the system.
The only variable in the transfer function should be
the variable of the Laplace transform.
Examples
========
>>> from sympy.abc import s
>>> from sympy.physics.control.lti import TransferFunction
>>> from sympy.physics.control.control_plots import bode_phase_numerical_data
>>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
>>> bode_phase_numerical_data(tf1) # doctest: +SKIP
([1e-05, 1.4472354033813751e-05, 2.035581932165858e-05,..., 47577.3248186011, 67884.09326036123, 100000.0],
[-2.5000000000291665e-05, -3.6180885085e-05, -5.08895483066e-05,...,-3.1415085799262523, -3.14155265358979])
See Also
========
bode_magnitude_plot, bode_phase_numerical_data
"""
_check_system(system)
expr = system.to_expr()
_w = Dummy("w", real=True)
w_expr = expr.subs({system.var: I * _w})
phase = arg(w_expr)
return LineOver1DRangeSeries(phase, (_w, 10**initial_exp, 10**final_exp),
xscale='log',
**kwargs).get_points()
def test_torch_complexes():
assert torch_code(re(x)) == "torch.real(x)"
assert torch_code(im(x)) == "torch.imag(x)"
assert torch_code(arg(x)) == "torch.angle(x)"
def bode_phase_numerical_data(system,
initial_exp=-5,
final_exp=5,
freq_unit='rad/sec',
phase_unit='rad',
**kwargs):
"""
Returns the numerical data of the Bode phase plot of the system.
It is internally used by ``bode_phase_plot`` to get the data
for plotting Bode phase plot. Users can use this data to further
analyse the dynamics of the system or plot using a different
backend/plotting-module.
Parameters
==========
system : SISOLinearTimeInvariant
The system for which the Bode phase plot data is to be computed.
initial_exp : Number, optional
The initial exponent of 10 of the semilog plot. Defaults to -5.
final_exp : Number, optional
The final exponent of 10 of the semilog plot. Defaults to 5.
freq_unit : string, optional
User can choose between ``'rad/sec'`` (radians/second) and '``'Hz'`` (Hertz) as frequency units.
phase_unit : string, optional
User can choose between ``'rad'`` (radians) and ``'deg'`` (degree) as phase units.
Returns
=======
tuple : (x, y)
x = x-axis values of the Bode phase plot.
y = y-axis values of the Bode phase plot.
Raises
======
NotImplementedError
When a SISO LTI system is not passed.
When time delay terms are present in the system.
ValueError
When more than one free symbol is present in the system.
The only variable in the transfer function should be
the variable of the Laplace transform.
When incorrect frequency or phase units are given as input.
Examples
========
>>> from sympy.abc import s
>>> from sympy.physics.control.lti import TransferFunction
>>> from sympy.physics.control.control_plots import bode_phase_numerical_data
>>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
>>> bode_phase_numerical_data(tf1) # doctest: +SKIP
([1e-05, 1.4472354033813751e-05, 2.035581932165858e-05,..., 47577.3248186011, 67884.09326036123, 100000.0],
[-2.5000000000291665e-05, -3.6180885085e-05, -5.08895483066e-05,...,-3.1415085799262523, -3.14155265358979])
See Also
========
bode_magnitude_plot, bode_phase_numerical_data
"""
_check_system(system)
expr = system.to_expr()
freq_units = ('rad/sec', 'Hz')
phase_units = ('rad', 'deg')
if freq_unit not in freq_units:
raise ValueError(
'Only "rad/sec" and "Hz" are accepted frequency units.')
if phase_unit not in phase_units:
raise ValueError('Only "rad" and "deg" are accepted phase units.')
_w = Dummy("w", real=True)
if freq_unit == 'Hz':
repl = I * _w * 2 * pi
else:
repl = I * _w
w_expr = expr.subs({system.var: repl})
if phase_unit == 'deg':
phase = arg(w_expr) * 180 / pi
else:
phase = arg(w_expr)
x, y = LineOver1DRangeSeries(phase, (_w, 10**initial_exp, 10**final_exp),
xscale='log',
**kwargs).get_points()
return x, y
def test_tensorflow_complexes():
assert tensorflow_code(re(x)) == "tensorflow.math.real(x)"
assert tensorflow_code(im(x)) == "tensorflow.math.imag(x)"
assert tensorflow_code(arg(x)) == "tensorflow.math.angle(x)"
