In [1]:
%matplotlib notebook
import matplotlib.pyplot as plt
import numpy as np
from astro.main.RawFrame import RawScienceFrame
from astro.util import darma
In [2]:
raw = RawScienceFrame(pathname='OMEGACAM.2016-07-30T08:16:42.682_20.fits')
raw.retrieve()
draw = darma.image.image(raw.filename, memmap=False).data[1532:1732,48:-48]
In [3]:
plt.figure(num='RawScienceFrame section, CCD #72',figsize=(9,2))
plt.imshow(draw, vmin=400, vmax=800)
Out[3]:
In [4]:
ml = draw[:40,:].mean(axis=0)
braw = np.zeros((100,2048))
braw[:50,:] = draw[:50,:]
braw[-50:] = draw[-50:]
lo = np.percentile(braw,1,axis=0)
hi = np.percentile(braw,75,axis=0)
bl = np.zeros(2048)
for k in range(len(bl)):
bl[k] = braw[(braw[:,k]>=lo[k])&(braw[:,k]<=hi[k]),k].mean()
In [5]:
plt.figure(num='RawScienceFrame along trail - mean and median per column, CCD #72', figsize=(9,6))
plt.xlim(-50,2100)
# plt.ylim(0,800)
plt.ylim(450,650)
plt.plot(np.median(draw,axis=0),'.')
plt.plot(ml,'g.')
plt.plot(bl,'r.')
Out[5]:
In [6]:
plt.figure(num='RawScienceFrame along trail - area minus baseline per column, CCD #72', figsize=(9,6))
plt.xlim(1200,2100)
# plt.ylim(0,800)
norm = (draw - bl)[70:130].sum(axis=0)[1200:1800].mean()
print(norm)
plt.plot((draw - bl)[70:130,:].sum(axis=0)/norm,'.');
# plt.plot((draw - bl)[80:120,:].sum(axis=0)/norm,'.');
# plt.plot((draw - bl)[60:140,:].sum(axis=0)/norm,'.');
plt.plot(plt.xlim(),[1,1])
Out[6]: