def test_eval_op():
"""Pick a "complicated" combination just to check."""
x = np.asarray([2, 4, 5, 6, 7])
m1 = basic.Const1D()
m1.c0 = 10
m2 = basic.Polynom1D()
m2.c0 = 5
m2.c1 = 1
m3 = basic.Box1D()
m3.xlow = 5
m3.xhi = 6
mdl = m1 + 2 * (m2 + (-m3))
assert mdl.ndim == 1
expected_m1 = 10 * np.ones(5)
expected_m2 = 5 + np.asarray(x)
expected_m3 = np.asarray([0, 0, 1, 1, 0])
expected = expected_m1 + 2 * (expected_m2 - expected_m3)
got = mdl(x)
assert got == pytest.approx(expected)
def test_combine_models1d():
"""Check we can combine 1D models"""
mdls = [
basic.Box1D(),
basic.Const1D(),
basic.Gauss1D(),
basic.NormGauss1D()
]
mdl = reduce(operator.add, mdls)
assert isinstance(mdl, BinaryOpModel)
# now multiply by a constant
#
mdl *= 2
assert isinstance(mdl, BinaryOpModel)
assert mdl.ndim == 1
# Check we can call it as a 1D model; there is minimal checks
# of the response.
#
bins = np.arange(2, 10, 2)
y1 = mdl(bins)
y2 = mdl(bins[:-1], bins[1:])
assert y1.shape == (4, )
assert y2.shape == (3, )
def test_source_component_arbitrary_grid_int(session):
ui = session()
x = numpy.array([1, 2, 3]), numpy.array([2, 3, 4])
y = [1.5, 2.5, 3.5]
re_x = numpy.array([10, 20, 30]), numpy.array([20, 30, 40])
ui.load_arrays(1, x[0], x[1], y, Data1DInt)
model = basic.Const1D('c')
model.c0 = 10
regrid_model = model.regrid(*re_x)
ui.plot_source_component(regrid_model)
# should this use ui.get_source_component_plot()?
assert ui._compsrchistplot.xlo == pytest.approx(x[0])
assert ui._compsrchistplot.xhi == pytest.approx(x[1])
assert ui._compsrchistplot.y == pytest.approx([0.0, 0.0, 0.0])
def test_plot_model_arbitrary_grid_integrated(session):
ui = session()
model = basic.Const1D('c')
model.c0 = 10
def tst(x, y, re_x, yy):
ui.load_arrays(1, x[0], x[1], y, Data1DInt)
regrid_model = model.regrid(*re_x)
ui.set_model(regrid_model)
ui.plot_model()
# should this use ui.get_model_plot()?
assert ui._modelhistplot.xlo == pytest.approx(x[0])
assert ui._modelhistplot.xhi == pytest.approx(x[1])
assert ui._modelhistplot.y == pytest.approx(yy)
tmp = numpy.arange(1, 5, 1)
x = tmp[:-1], tmp[1:]
y = x[0]
tmp = numpy.arange(10, 50, 10)
re_x = tmp[:-1], tmp[1:]
tst(x, y, re_x, [0, 0, 0])
tmp = numpy.arange(1, 20, 1)
x = tmp[:-1], tmp[1:]
y = x[0]
tmp = numpy.arange(1, 20, 0.5)
re_x = tmp[:-1], tmp[1:]
tst(x, y, re_x, len(y) * [10])
tmp = numpy.arange(1, 20, 1)
x = tmp[:-1], tmp[1:]
y = x[0]
tmp = numpy.arange(10, 20, 0.5)
re_x = tmp[:-1], tmp[1:]
n = int(len(y) / 2)
yy = numpy.append(n * [0.], n * [10.])
tst(x, y, re_x, yy)