def test_limits_trace_curves_to_xy_edges(self, diagonal_trace):
spt = SpectralTrace(diagonal_trace)
xy_edges = {"x_min": -25, "x_max": -15, "y_min": 10, "y_max": 20}
mtcs_all = spt.get_trace_curves(0.015)
mtcs_xy_limited = spt.get_trace_curves(0.015, xy_edges=xy_edges)
assert len(mtcs_all) > len(mtcs_xy_limited)
if PLOTS:
for mtc in mtcs_xy_limited:
plt.plot(mtc.x, mtc.y)
spt.plot(spt.wave_min, spt.wave_max)
plt.axhline(xy_edges["y_min"])
plt.axhline(xy_edges["y_max"])
plt.axvline(xy_edges["x_min"])
plt.axvline(xy_edges["x_max"])
plt.show()
def test_mtc_distances_are_one_pixel_horiz_trace(self, horizontal_trace):
spt = SpectralTrace(horizontal_trace)
mtcs = spt.get_trace_curves(0.015)
pix_cen_x = [mtc.header["CRVAL1D"] / 0.015 for mtc in mtcs]
pix_cen_y = [mtc.header["CRVAL2D"] / 0.015 for mtc in mtcs]
assert np.abs(np.average(np.diff(pix_cen_x))) == approx(1, rel=1e-5)
if PLOTS:
plt.plot(pix_cen_x, pix_cen_y)
plt.show()
def test_mtc_distances_are_one_pixel_diagonal_trace(self, diagonal_trace):
# diagonal trace is 30 degrees off vertical
spt = SpectralTrace(diagonal_trace)
mtcs = spt.get_trace_curves(0.015)
pix_cen_x = [mtc.header["CRVAL1D"] / 0.015 for mtc in mtcs]
pix_cen_y = [mtc.header["CRVAL2D"] / 0.015 for mtc in mtcs]
assert np.abs(np.average(np.diff(pix_cen_y))) == approx(1, rel=1e-5)
if PLOTS:
plt.plot(pix_cen_x, pix_cen_y, "o")
plt.show()
def test_no_same_angles_for_curved_trace(self, curved_trace):
spt = SpectralTrace(curved_trace)
mtcs = spt.get_trace_curves(0.015)
rots = [mtc.meta["rotation"] for mtc in mtcs]
shears = [mtc.meta["shear"] for mtc in mtcs]
assert len(np.unique(rots)) == len(np.unique(np.diff(rots)))
if PLOTS:
plt.subplot(121)
for mtc in mtcs[::100]:
plt.plot(mtc.x, mtc.y)
plt.subplot(122)
plt.plot(rots)
plt.plot(shears)
plt.show()
def test_mtc_are_one_pixel_removed_from_each_other(self, basic_trace):
spt = SpectralTrace(basic_trace)
mtcs = spt.get_trace_curves(0.015)
pix_cen_x = [mtc.header["CRVAL1D"] / 0.015 for mtc in mtcs]
pix_cen_y = [mtc.header["CRVAL2D"] / 0.015 for mtc in mtcs]
assert np.average(np.diff(pix_cen_y)) == approx(1, rel=1e-5)
