def test_legend_fit():
# Generate data
x = np.linspace(0,np.pi,50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'legendre', 4)
x2 = np.linspace(0,np.pi,100)
y2 = xafits.func_val(x2,dfit)
np.testing.assert_allclose(y2[50], 0.99940823486206976)
def test_bspline_fit():
# Generate data
x = np.linspace(0,np.pi,50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'bspline', 3, everyn=25)
x2 = np.linspace(0,np.pi,100)
y2 = xafits.func_val(x2,dfit)
np.testing.assert_allclose(y2[50], 0.9941836965580888)
def test_poly_fit():
# Generate data
x = np.linspace(0,np.pi,50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'polynomial', 3)
x2 = np.linspace(0,np.pi,100)
y2 = xafits.func_val(x2,dfit)
np.testing.assert_allclose(y2[50], 0.97854984428713754)
def test_bspline_fit():
# Generate data
x = np.linspace(0, np.pi, 50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'bspline', 3, everyn=25)
x2 = np.linspace(0, np.pi, 100)
y2 = xafits.func_val(x2, dfit)
np.testing.assert_allclose(y2[50], 0.9941836965580888)
def test_legend_fit():
# Generate data
x = np.linspace(0, np.pi, 50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'legendre', 4)
x2 = np.linspace(0, np.pi, 100)
y2 = xafits.func_val(x2, dfit)
np.testing.assert_allclose(y2[50], 0.99940823486206976)
def test_poly_fit():
# Generate data
x = np.linspace(0, np.pi, 50)
y = np.sin(x)
# Fit
dfit = xafits.func_fit(x, y, 'polynomial', 3)
x2 = np.linspace(0, np.pi, 100)
y2 = xafits.func_val(x2, dfit)
np.testing.assert_allclose(y2[50], 0.97854984428713754)
def test_iter_fit():
# Generate data
x = np.linspace(0,np.pi,100)
y = np.sin(x)
#
y[50] = 3.
# Fit
dfit, mask = xafits.iter_fit(x, y, 'bspline', 3, everyn=25)
assert np.sum(mask) == 1
x2 = np.linspace(0,np.pi,100)
y2 = xafits.func_val(x2,dfit)
np.testing.assert_allclose(y2[50], 0.9991193590298185)
def test_iter_fit():
# Generate data
x = np.linspace(0, np.pi, 100)
y = np.sin(x)
#
y[50] = 3.
# Fit
dfit, mask = xafits.iter_fit(x, y, 'bspline', 3, everyn=25)
assert np.sum(mask) == 1
x2 = np.linspace(0, np.pi, 100)
y2 = xafits.func_val(x2, dfit)
np.testing.assert_allclose(y2[50], 0.9991193590298185)
