def _svg(self, scale_factor=1., fill_color="#66cc99"):
"""Returns SVG ellipse element for the Ellipse.
Parameters
==========
scale_factor : float
Multiplication factor for the SVG stroke-width. Default is 1.
fill_color : str, optional
Hex string for fill color. Default is "#66cc99".
"""
c = N(self.center)
h, v = N(self.hradius), N(self.vradius)
return (
'<ellipse fill="{1}" stroke="#555555" '
'stroke-width="{0}" opacity="0.6" cx="{2}" cy="{3}" rx="{4}" ry="{5}"/>'
).format(2. * scale_factor, fill_color, c.x, c.y, h, v)
def _svg(self, scale_factor=1., fill_color="#66cc99"):
"""Returns SVG path element for the LinearEntity.
Parameters
==========
scale_factor : float
Multiplication factor for the SVG stroke-width. Default is 1.
fill_color : str, optional
Hex string for fill color. Default is "#66cc99".
"""
from sympy.core.evalf import N
verts = (N(self.p1), N(self.p2))
coords = ["{0},{1}".format(p.x, p.y) for p in verts]
path = "M {0} L {1}".format(coords[0], " L ".join(coords[1:]))
return ('<path fill-rule="evenodd" fill="{2}" stroke="#555555" '
'stroke-width="{0}" opacity="0.6" d="{1}" />').format(
2. * scale_factor, path, fill_color)
def test_instrinsic_math2_codegen():
# not included: frexp, ldexp, modf, fmod
from sympy.core.evalf import N
from sympy.functions.elementary.trigonometric import atan2
name_expr = [
("test_atan2", atan2(x, y)),
("test_pow", x**y),
]
numerical_tests = []
for name, expr in name_expr:
for xval, yval in (0.2, 1.3), (0.5, -0.2), (0.8, 0.8):
expected = N(expr.subs(x, xval).subs(y, yval))
numerical_tests.append((name, (xval, yval), expected, 1e-14))
for lang, commands in valid_lang_commands:
run_test("intrinsic_math2", name_expr, numerical_tests, lang, commands)
def test_complicated_codegen():
from sympy.core.evalf import N
from sympy.functions.elementary.trigonometric import (cos, sin, tan)
name_expr = [
("test1", ((sin(x) + cos(y) + tan(z))**7).expand()),
("test2", cos(cos(cos(cos(cos(cos(cos(cos(x + y + z))))))))),
]
numerical_tests = []
for name, expr in name_expr:
for xval, yval, zval in (0.2, 1.3, -0.3), (0.5, -0.2, 0.0), (0.8, 2.1,
0.8):
expected = N(expr.subs(x, xval).subs(y, yval).subs(z, zval))
numerical_tests.append((name, (xval, yval, zval), expected, 1e-12))
for lang, commands in valid_lang_commands:
run_test("complicated_codegen", name_expr, numerical_tests, lang,
commands)
def test_issue_19534():
dt = symbols('dt', real=True)
expr = 16*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0)/45 + \
49*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.051640768506639183825*dt + \
dt*(1/2 - sqrt(21)/14) + 1.0)/180 + 49*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \
0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + \
2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \
1.1854881643947648988*dt + dt*(sqrt(21)/14 + 1/2) + 1.0)/180 + \
dt*(0.66666666666666666667*dt*(2.0*dt + 1.0) + \
6.0173399699313066769*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
4.1117044797036320069*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) - \
7.0189140975801991157*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) + \
0.94010945196161777522*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \
0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + \
2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \
0.35816132904077632692*dt + 1.0) + 5.5065024887242400038*dt + 1.0)/20 + dt/20 + 1
assert N(expr.series(dt, 0, 8), 20) == -0.00092592592592592596126*dt**7 + 0.0027777777777777783175*dt**6 + \
0.016666666666666656027*dt**5 + 0.083333333333333300952*dt**4 + 0.33333333333333337034*dt**3 + \
1.0*dt**2 + 1.0*dt + 1.0
def test_intrinsic_math1_codegen():
# not included: log10
from sympy.core.evalf import N
from sympy.functions import ln
from sympy.functions.elementary.exponential import log
from sympy.functions.elementary.hyperbolic import (cosh, sinh, tanh)
from sympy.functions.elementary.integers import (ceiling, floor)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (acos, asin, atan,
cos, sin, tan)
name_expr = [
("test_fabs", abs(x)),
("test_acos", acos(x)),
("test_asin", asin(x)),
("test_atan", atan(x)),
("test_cos", cos(x)),
("test_cosh", cosh(x)),
("test_log", log(x)),
("test_ln", ln(x)),
("test_sin", sin(x)),
("test_sinh", sinh(x)),
("test_sqrt", sqrt(x)),
("test_tan", tan(x)),
("test_tanh", tanh(x)),
]
numerical_tests = []
for name, expr in name_expr:
for xval in 0.2, 0.5, 0.8:
expected = N(expr.subs(x, xval))
numerical_tests.append((name, (xval, ), expected, 1e-14))
for lang, commands in valid_lang_commands:
if lang.startswith("C"):
name_expr_C = [("test_floor", floor(x)), ("test_ceil", ceiling(x))]
else:
name_expr_C = []
run_test("intrinsic_math1", name_expr + name_expr_C, numerical_tests,
lang, commands)
def test_gauss_opt():
mat = RayTransferMatrix(1, 2, 3, 4)
assert mat == Matrix([[1, 2], [3, 4]])
assert mat == RayTransferMatrix(Matrix([[1, 2], [3, 4]]))
assert [mat.A, mat.B, mat.C, mat.D] == [1, 2, 3, 4]
d, f, h, n1, n2, R = symbols('d f h n1 n2 R')
lens = ThinLens(f)
assert lens == Matrix([[1, 0], [-1 / f, 1]])
assert lens.C == -1 / f
assert FreeSpace(d) == Matrix([[1, d], [0, 1]])
assert FlatRefraction(n1, n2) == Matrix([[1, 0], [0, n1 / n2]])
assert CurvedRefraction(R, n1, n2) == Matrix([[1, 0],
[(n1 - n2) / (R * n2),
n1 / n2]])
assert FlatMirror() == Matrix([[1, 0], [0, 1]])
assert CurvedMirror(R) == Matrix([[1, 0], [-2 / R, 1]])
assert ThinLens(f) == Matrix([[1, 0], [-1 / f, 1]])
mul = CurvedMirror(R) * FreeSpace(d)
mul_mat = Matrix([[1, 0], [-2 / R, 1]]) * Matrix([[1, d], [0, 1]])
assert mul.A == mul_mat[0, 0]
assert mul.B == mul_mat[0, 1]
assert mul.C == mul_mat[1, 0]
assert mul.D == mul_mat[1, 1]
angle = symbols('angle')
assert GeometricRay(h, angle) == Matrix([[h], [angle]])
assert FreeSpace(d) * GeometricRay(h, angle) == Matrix([[angle * d + h],
[angle]])
assert GeometricRay(Matrix(((h, ), (angle, )))) == Matrix([[h], [angle]])
assert (FreeSpace(d) * GeometricRay(h, angle)).height == angle * d + h
assert (FreeSpace(d) * GeometricRay(h, angle)).angle == angle
p = BeamParameter(530e-9, 1, w=1e-3)
assert streq(p.q, 1 + 1.88679245283019 * I * pi)
assert streq(N(p.q), 1.0 + 5.92753330865999 * I)
assert streq(N(p.w_0), Float(0.00100000000000000))
assert streq(N(p.z_r), Float(5.92753330865999))
fs = FreeSpace(10)
p1 = fs * p
assert streq(N(p.w), Float(0.00101413072159615))
assert streq(N(p1.w), Float(0.00210803120913829))
w, wavelen = symbols('w wavelen')
assert waist2rayleigh(w, wavelen) == pi * w**2 / wavelen
z_r, wavelen = symbols('z_r wavelen')
assert rayleigh2waist(z_r, wavelen) == sqrt(wavelen * z_r) / sqrt(pi)
a, b, f = symbols('a b f')
assert geometric_conj_ab(a, b) == a * b / (a + b)
assert geometric_conj_af(a, f) == a * f / (a - f)
assert geometric_conj_bf(b, f) == b * f / (b - f)
assert geometric_conj_ab(oo, b) == b
assert geometric_conj_ab(a, oo) == a
s_in, z_r_in, f = symbols('s_in z_r_in f')
assert gaussian_conj(s_in, z_r_in,
f)[0] == 1 / (-1 / (s_in + z_r_in**2 /
(-f + s_in)) + 1 / f)
assert gaussian_conj(
s_in, z_r_in, f)[1] == z_r_in / (1 - s_in**2 / f**2 + z_r_in**2 / f**2)
assert gaussian_conj(
s_in, z_r_in, f)[2] == 1 / sqrt(1 - s_in**2 / f**2 + z_r_in**2 / f**2)
l, w_i, w_o, f = symbols('l w_i w_o f')
assert conjugate_gauss_beams(
l, w_i, w_o, f=f)[0] == f * (-sqrt(w_i**2 / w_o**2 - pi**2 * w_i**4 /
(f**2 * l**2)) + 1)
assert factor(conjugate_gauss_beams(
l, w_i, w_o,
f=f)[1]) == f * w_o**2 * (w_i**2 / w_o**2 -
sqrt(w_i**2 / w_o**2 - pi**2 * w_i**4 /
(f**2 * l**2))) / w_i**2
assert conjugate_gauss_beams(l, w_i, w_o, f=f)[2] == f
z, l, w_0 = symbols('z l w_0', positive=True)
p = BeamParameter(l, z, w=w_0)
assert p.radius == z * (pi**2 * w_0**4 / (l**2 * z**2) + 1)
assert p.w == w_0 * sqrt(l**2 * z**2 / (pi**2 * w_0**4) + 1)
assert p.w_0 == w_0
assert p.divergence == l / (pi * w_0)
assert p.gouy == atan2(z, pi * w_0**2 / l)
assert p.waist_approximation_limit == 2 * l / pi
p = BeamParameter(530e-9, 1, w=1e-3, n=2)
assert streq(p.q, 1 + 3.77358490566038 * I * pi)
assert streq(N(p.z_r), Float(11.8550666173200))
assert streq(N(p.w_0), Float(0.00100000000000000))
def test_issue_17421():
assert N(acos(-I + acosh(cosh(cosh(1) + I)))) == 1.0 * I
def test_issue_13425():
assert N('2**.5', 30) == N('sqrt(2)', 30)
assert N('x - x', 30) == 0
assert abs((N('pi*.1', 22) * 10 - pi).n()) < 1e-22
def test_issue_8821_highprec_from_str():
s = str(pi.evalf(128))
p = N(s)
assert Abs(sin(p)) < 1e-15
p = N(s, 64)
assert Abs(sin(p)) < 1e-64
def NS(e, n):
return str(N(e, n))
def test_bidiagonalize():
M = Matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
assert M.bidiagonalize() == M
assert M.bidiagonalize(upper=False) == M
assert M.bidiagonalize() == M
assert M.bidiagonal_decomposition() == (M, M, M)
assert M.bidiagonal_decomposition(upper=False) == (M, M, M)
assert M.bidiagonalize() == M
import random
#Real Tests
for real_test in range(2):
test_values = []
row = 2
col = 2
for _ in range(row * col):
value = random.randint(-1000000000, 1000000000)
test_values = test_values + [value]
# L -> Lower Bidiagonalization
# M -> Mutable Matrix
# N -> Immutable Matrix
# 0 -> Bidiagonalized form
# 1,2,3 -> Bidiagonal_decomposition matrices
# 4 -> Product of 1 2 3
M = Matrix(row, col, test_values)
N = ImmutableMatrix(M)
N1, N2, N3 = N.bidiagonal_decomposition()
M1, M2, M3 = M.bidiagonal_decomposition()
M0 = M.bidiagonalize()
N0 = N.bidiagonalize()
N4 = N1 * N2 * N3
M4 = M1 * M2 * M3
N2.simplify()
N4.simplify()
N0.simplify()
M0.simplify()
M2.simplify()
M4.simplify()
LM0 = M.bidiagonalize(upper=False)
LM1, LM2, LM3 = M.bidiagonal_decomposition(upper=False)
LN0 = N.bidiagonalize(upper=False)
LN1, LN2, LN3 = N.bidiagonal_decomposition(upper=False)
LN4 = LN1 * LN2 * LN3
LM4 = LM1 * LM2 * LM3
LN2.simplify()
LN4.simplify()
LN0.simplify()
LM0.simplify()
LM2.simplify()
LM4.simplify()
assert M == M4
assert M2 == M0
assert N == N4
assert N2 == N0
assert M == LM4
assert LM2 == LM0
assert N == LN4
assert LN2 == LN0
#Complex Tests
for complex_test in range(2):
test_values = []
size = 2
for _ in range(size * size):
real = random.randint(-1000000000, 1000000000)
comp = random.randint(-1000000000, 1000000000)
value = real + comp * I
test_values = test_values + [value]
M = Matrix(size, size, test_values)
N = ImmutableMatrix(M)
# L -> Lower Bidiagonalization
# M -> Mutable Matrix
# N -> Immutable Matrix
# 0 -> Bidiagonalized form
# 1,2,3 -> Bidiagonal_decomposition matrices
# 4 -> Product of 1 2 3
N1, N2, N3 = N.bidiagonal_decomposition()
M1, M2, M3 = M.bidiagonal_decomposition()
M0 = M.bidiagonalize()
N0 = N.bidiagonalize()
N4 = N1 * N2 * N3
M4 = M1 * M2 * M3
N2.simplify()
N4.simplify()
N0.simplify()
M0.simplify()
M2.simplify()
M4.simplify()
LM0 = M.bidiagonalize(upper=False)
LM1, LM2, LM3 = M.bidiagonal_decomposition(upper=False)
LN0 = N.bidiagonalize(upper=False)
LN1, LN2, LN3 = N.bidiagonal_decomposition(upper=False)
LN4 = LN1 * LN2 * LN3
LM4 = LM1 * LM2 * LM3
LN2.simplify()
LN4.simplify()
LN0.simplify()
LM0.simplify()
LM2.simplify()
LM4.simplify()
assert M == M4
assert M2 == M0
assert N == N4
assert N2 == N0
assert M == LM4
assert LM2 == LM0
assert N == LN4
assert LN2 == LN0
M = Matrix(18, 8, range(1, 145))
M = M.applyfunc(lambda i: Float(i))
assert M.bidiagonal_decomposition()[1] == M.bidiagonalize()
assert M.bidiagonal_decomposition(upper=False)[1] == M.bidiagonalize(
upper=False)
a, b, c = M.bidiagonal_decomposition()
diff = a * b * c - M
assert abs(max(diff)) < 10**-12
