na Kubani

This commit is contained in:
Roman Krivonos
2024-07-23 09:42:16 +03:00
parent 99dc2aa8f6
commit 8ee76a8070
896 changed files with 258624 additions and 205715 deletions

View File

@@ -6,11 +6,15 @@ __copyright__ = "Space Research Institute (IKI)"
import numpy as np
import pandas as pd
from astropy.io import fits
from astropy.wcs import WCS
from astropy import wcs
from astropy.table import Table, Column
import matplotlib.pyplot as plt
import math, sys
import pickle
from sklearn.linear_model import LinearRegression
from sklearn.linear_model import HuberRegressor
from sklearn.linear_model import RANSACRegressor
@@ -18,6 +22,12 @@ from sklearn.linear_model import TheilSenRegressor
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import RepeatedKFold
from astropy.coordinates import SkyCoord # High-level coordinates
from astropy.coordinates import ICRS, Galactic, FK4, FK5 # Low-level frames
from astropy.coordinates import Angle, Latitude, Longitude # Angles
import astropy.units as u
#from statsmodels.robust.scale import huber
from astropy.stats import sigma_clip
from numpy import absolute
@@ -26,10 +36,10 @@ from numpy import arange
from ridge.utils import *
from ridge.config import *
plotme=True
plotme=False
enkey = sys.argv[1]
#outkey = sys.argv[2]
outkey = "BKG"
outkey = sys.argv[2]
#outkey = "BKG"
fn="detcnts.{}.fits".format(enkey)
@@ -83,6 +93,13 @@ base0=[]
c0=[]
texp0=[]
hdulist = fits.open(datadir+modelrxte)
w = wcs.WCS(hdulist[0].header)
smap = hdulist[0].data
sx=int(hdulist[0].header['NAXIS1'])
sy=int(hdulist[0].header['NAXIS2'])
#d = fits.getdata(datadir+fn)
#df = pd.DataFrame(np.array(d).byteswap().newbyteorder())
@@ -110,6 +127,18 @@ BKG 61214 ScWs, 114.3 Ms
Total 131440 ScWs, 225.9 Ms
"""
# fill AITOF map indexes
ds9x=[]
ds9y=[]
"""
for i,row in df.iterrows():
#print(x,y,smap[y-1,x-1])
df['DS9Y']=ds9x
df['DS9X']=ds9y
"""
for i, row in df.iterrows():
orbit=row['REV']
obsid=row['OBSID']#.decode("UTF-8")
@@ -171,6 +200,17 @@ for i, row in df.iterrows():
lon0.append(row['LON'])
lat0.append(row['LAT'])
lon=row['LON']
lat=row['LAT']
world = SkyCoord(lon,lat, frame=Galactic, unit="deg")
ra=world.fk5.ra.deg
dec=world.fk5.dec.deg
pixcrd = w.wcs_world2pix([(lon,lat)], 1)
x=int(pixcrd[0][0])
y=int(pixcrd[0][1])
ds9x.append(x)
ds9y.append(y)
print("N={} ScWs, {:.1f} Ms".format(len(resid0),np.sum(texp0)/1e6))
sigma=3
@@ -222,7 +262,7 @@ if(plotme):
plt.xlabel("Residuals, mCrab")
plt.show()
with open(proddir+fn.replace(".fits",".ignored_rev.resid.pkl"), 'wb') as fp:
with open(proddir+fn.replace(".fits",".{}.ignored_rev.resid.pkl".format(outkey)), 'wb') as fp:
pickle.dump(drev[filtered_arr.mask==True], fp, protocol=pickle.HIGHEST_PROTOCOL)
print("Removed REVs:",drev[filtered_arr.mask==True])
@@ -254,6 +294,8 @@ coldefs = fits.ColDefs([
fits.Column(name='A', format='D', unit='', array=[a0[index] for index in indices]),
fits.Column(name='B', format='D', unit='', array=[b0[index] for index in indices]),
fits.Column(name='C', format='D', unit='', array=[c0[index] for index in indices]),
fits.Column(name='DS9X', format='D', unit='', array=[ds9x[index] for index in indices]),
fits.Column(name='DS9Y', format='D', unit='', array=[ds9y[index] for index in indices]),
])
fout = fn.replace(".fits",".{}.resid.fits".format(outkey))