def test_polynom2d_guess_y0():
"""Check guess works okay: polynom2d
What happens when y=0
"""
mdl = basic.Polynom2D()
for p in mdl.pars:
if p.name == 'c':
assert p.val == pytest.approx(1.0)
else:
assert p.val == pytest.approx(0.0)
assert p.min == pytest.approx(-hugeval)
assert p.max == pytest.approx(hugeval)
x = np.asarray([1, 2, 30])
y = np.asarray([-2, 4, -2])
z = np.asarray([0, 0, 0])
mdl.guess(z, x, y)
# This is a regression test
for p in mdl.pars:
assert p.val == pytest.approx(0.0)
def check(par, maxval):
assert par.min == pytest.approx(-maxval)
assert par.max == pytest.approx(maxval)
for par in mdl.pars:
check(par, 0)
def test_basic_unop_abs():
cpt = basic.Polynom2D()
mdl = abs(cpt)
assert mdl.name == 'abs(polynom2d)'
assert mdl.op == np.absolute
assert mdl.ndim == 2
def test_basic_unop_abs_raw():
cpt = basic.Polynom2D()
mdl = UnaryOpModel(cpt, np.absolute, 'foo')
assert mdl.name == 'foo(polynom2d)'
assert mdl.op == np.absolute
assert mdl.ndim == 2
def test_basic_unop_neg():
cpt = basic.Polynom2D()
mdl = -cpt
assert mdl.name == '-(polynom2d)'
assert mdl.op == np.negative
assert mdl.ndim == 2
def test_basic_unop_neg_raw():
cpt = basic.Polynom2D()
mdl = UnaryOpModel(cpt, np.negative, '<->')
assert mdl.name == '<->(polynom2d)'
assert mdl.op == np.negative
assert mdl.ndim == 2
def test_basic_binop(op, opstr):
l = basic.Polynom2D()
r = basic.Gauss2D()
mdl = op(l, r)
assert isinstance(mdl, BinaryOpModel)
assert mdl.name == '(polynom2d {} gauss2d)'.format(opstr)
assert mdl.op == op
assert len(mdl.parts) == 2
assert mdl.parts[0] == l
assert mdl.parts[1] == r
assert mdl.ndim == 2
def test_basic_binop_raw(op):
l = basic.Polynom2D()
r = basic.Gauss2D()
mdl = BinaryOpModel(l, r, op, 'xOx')
assert isinstance(mdl, BinaryOpModel)
assert mdl.name == '(polynom2d xOx gauss2d)'
assert mdl.op == op
assert len(mdl.parts) == 2
assert mdl.parts[0] == l
assert mdl.parts[1] == r
assert mdl.ndim == 2
def test_polynom2d_guess_ymax0():
"""Check guess works okay: polynom2d
What happens when ymax=0
"""
mdl = basic.Polynom2D()
for p in mdl.pars:
if p.name == 'c':
assert p.val == pytest.approx(1.0)
else:
assert p.val == pytest.approx(0.0)
assert p.min == pytest.approx(-hugeval)
assert p.max == pytest.approx(hugeval)
x = np.asarray([1, 2, 30])
y = np.asarray([-2, 4, -2])
z = np.asarray([-10, -12, 0])
mdl.guess(z, x, y)
# This is a regression test
for p in mdl.pars:
if p.name == 'c':
assert p.val == pytest.approx(-6.0)
else:
assert p.val == pytest.approx(0.0)
for par in [mdl.c, mdl.cx1y2, mdl.cx2y1, mdl.cx2y2]:
assert par.min == pytest.approx(-12)
assert par.max == pytest.approx(0)
def check(par, maxval):
assert par.min == pytest.approx(-maxval)
assert par.max == pytest.approx(maxval)
check(mdl.cy1, 200)
check(mdl.cy2, 33.33333333333333)
check(mdl.cx1, 41.37931034482759)
check(mdl.cx2, 1.426872770511296)
check(mdl.cx1y1, 6.896551724137931)
def test_polynom2d_guess():
"""Check guess works okay: polynom2d"""
mdl = basic.Polynom2D()
for p in mdl.pars:
if p.name == 'c':
assert p.val == pytest.approx(1.0)
else:
assert p.val == pytest.approx(0.0)
assert p.min == pytest.approx(-hugeval)
assert p.max == pytest.approx(hugeval)
x = np.asarray([1, 2, 30])
y = np.asarray([-2, 4, -2])
z = np.asarray([10, 12, -2])
mdl.guess(z, x, y)
# This is a regression test
for p in mdl.pars:
if p.name == 'c':
assert p.val == pytest.approx(5.0)
else:
assert p.val == pytest.approx(0.0)
for par in [mdl.c, mdl.cx1y2, mdl.cx2y1, mdl.cx2y2]:
assert par.min == pytest.approx(-2)
assert par.max == pytest.approx(12)
def check(par, maxval):
assert par.min == pytest.approx(-maxval)
assert par.max == pytest.approx(maxval)
check(mdl.cy1, 233.33333333333334)
check(mdl.cy2, 38.88888888888889)
check(mdl.cx1, 48.275862068965516)
check(mdl.cx2, 1.6646848989298455)
check(mdl.cx1y1, 8.045977011494253)