# yrange = extract.get_y_scale(ycen, [400, 600], [5, 5], nrow)
index = extract.make_index(ycen_int - ylow, ycen_int + yhigh, ibeg, iend)
swath_img = img[index]
swath_ycen = ycen[ibeg:iend] - ycen_int[ibeg:iend]
shear = 0
osample = 10
np.savetxt("image.txt", swath_img)
np.savetxt("ycen.txt", swath_ycen)
# return sp, sl, model, unc, mask
# data1 = cwrappers.slitfunc(swath_img, swath_ycen, osample=osample)
data2 = cwrappers.slitfunc_curved(swath_img,
swath_ycen,
shear,
osample=osample,
yrange=(ylow, yhigh))
data = data2
spec = data[0]
slitf = data[1]
model = data[2]
unc = data[3]
mask = data[4]
np.savetxt("spectrum.txt", spec)
np.savetxt("slitfunction.txt", slitf)
np.savetxt("model.txt", model)
np.savetxt("unc.txt", unc)
np.savetxt("mask.txt", mask)
def test_slitfunc_curved():
img = np.full((100, 100), 1)
ycen = np.full(100, 50)
tilt = np.full(100, 0)
shear = np.full(100, 0)
lambda_sp = 0
lambda_sf = 0.1
osample = 1
yrange = (49, 50)
# Run it once the way it is supposed to
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, lambda_sf, osample,
yrange)
slitfunc_curved(img, ycen, 1, 0.01, lambda_sp, lambda_sf, osample, yrange)
# Then try different incompatible inputs, which have to be caught before going to the C code
with pytest.raises(AssertionError):
slitfunc_curved(None, ycen, tilt, shear, lambda_sp, lambda_sf, osample,
yrange)
with pytest.raises(ValueError):
slitfunc_curved("bla", ycen, tilt, shear, lambda_sp, lambda_sf,
osample, yrange)
with pytest.raises(AssertionError):
slitfunc_curved(img, None, tilt, shear, lambda_sp, lambda_sf, osample,
yrange)
with pytest.raises(ValueError):
slitfunc_curved(img, "blub", tilt, shear, lambda_sp, lambda_sf,
osample, yrange)
with pytest.raises(AssertionError):
slitfunc_curved(img, ycen, tilt, None, lambda_sp, lambda_sf, osample,
yrange)
with pytest.raises(ValueError):
slitfunc_curved(img, ycen, tilt, "boo", lambda_sp, lambda_sf, osample,
yrange)
with pytest.raises(TypeError):
slitfunc_curved(img, ycen, tilt, shear, None, lambda_sf, osample,
yrange)
with pytest.raises(ValueError):
slitfunc_curved(img, ycen, tilt, shear, "bla", lambda_sf, osample,
yrange)
with pytest.raises(TypeError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, None, osample,
yrange)
with pytest.raises(ValueError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, "bla", osample,
yrange)
with pytest.raises(TypeError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, lambda_sf, None,
yrange)
with pytest.raises(ValueError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, lambda_sf, "bla",
yrange)
# Then try different sizes for img and ycen
with pytest.raises(AssertionError):
ycen_bad = np.full(50, 0, dtype=float)
slitfunc_curved(img, ycen_bad, tilt, shear, lambda_sp, lambda_sf,
osample, yrange)
with pytest.raises(AssertionError):
tilt_bad = np.full(50, 0, dtype=float)
slitfunc_curved(img, ycen, tilt_bad, shear, lambda_sp, lambda_sf,
osample, yrange)
with pytest.raises(AssertionError):
shear_bad = np.full(50, 0, dtype=float)
slitfunc_curved(img, ycen, tilt, shear_bad, lambda_sp, lambda_sf,
osample, yrange)
with pytest.raises(AssertionError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, lambda_sf, 0,
yrange)
with pytest.raises(AssertionError):
slitfunc_curved(img, ycen, tilt, shear, lambda_sp, -1, osample, yrange)
with pytest.raises(AssertionError):
slitfunc_curved(img, ycen, tilt, shear, -1, lambda_sf, osample, yrange)
ycen_int = ycen.astype(int)
# yrange = extract.get_y_scale(ycen, [400, 600], [5, 5], nrow)
index = extract.make_index(ycen_int - ylow, ycen_int + yhigh, ibeg, iend)
swath_img = img[index]
swath_ycen = ycen[ibeg:iend] - ycen_int[ibeg:iend]
shear = 0
osample = 10
np.savetxt("image.txt", swath_img)
np.savetxt("ycen.txt", swath_ycen)
# return sp, sl, model, unc, mask
# data1 = cwrappers.slitfunc(swath_img, swath_ycen, osample=osample)
data2 = cwrappers.slitfunc_curved(swath_img,
swath_ycen,
shear,
osample=osample)
data = data2
spec = data[0]
slitf = data[1]
model = data[2]
unc = data[3]
mask = data[4]
np.savetxt("spectrum.txt", spec)
np.savetxt("slitfunction.txt", slitf)
np.savetxt("model.txt", model)
np.savetxt("unc.txt", unc)
np.savetxt("mask.txt", mask)