non common trend of readout pattern in each channel

[HajimeKawahara]

I observed a non-common trend of the readout pattern in some order:
See #5 (comment).
This results in artifact in one-d raw spectrum for a faint object (can find it by performing REACH.py)

To remove this, some preparations are needed

• RSD (raw spectral detector) matrix (rsdmat.py in spec) to see the effect (by taking median axis=1)
• allocate channel position in a 1D raw spec

After that, consider how to remove it. probably GP?

[HajimeKawahara]

The following is an example of the artificial dip due to the non-common trend of the readout pattern (REACH.py):

To make this figure, I implemented "RSD matrix" (spec/rsdmat.py), which is a matrix of (npix x norder) aligned to the detector 2D matrix. Here is the example of the conversion to use (for the above figure):

from pyird.spec.rsdmat import multiorder_to_rsd
rsd=multiorder_to_rsd(rawspec, pixcoord)

fig=plt.figure()
ax=fig.add_subplot(111)
for i,esp in enumerate(rawspec):
    plt.plot(pixcoord[i],esp,alpha=0.3, color="gray") #multi-order raw spec form for reference
plt.plot(np.nanmedian(rsd[:,-6:-1],axis=1),alpha=1.0, color="C1",label="median (-6:-1)") #can perform np.nanmedian for the axis of the orders
plt.plot(np.nanmedian(rsd[:,:],axis=1),alpha=1.0, color="C0",label="median")

[HajimeKawahara]

Fitting residuals to GP2Dcross model, anyway I was able to correct the non-common channel trend.

Use rm_nct (remove noncommon trend) option in median_XY_profile(calim, rm_nct=True):

[HajimeKawahara]

This is a schematic picutre of the RSD matrix:

[HajimeKawahara]

I think this was done anyway.