def run_one_r(pid, scan_name, step, start, end, return_dict):
num_co = int(1/step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
print length
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids%d_half.npy'%(scan_name, initial_sec)
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
intitial_asp = co_data[initial_sec]
center = np.array([intitial_asp[1], intitial_asp[2]])
print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.3, 0.3]
wcs = imagetools.define_wcs(skypos,skyrange,width=False,height=False,verbose=0,pixsz=0.0001)
initial_time = intitial_asp[0]-0.5
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 0.4)
coo2 = angle_filter(coo2, center, 0.4)
count, centroid = get_corr_map_fast(coo2, coo1, skypos, skyrange, sec, 0.20, 0.008)
centroids.append(centroid)
print centroid
print centroids
np.save('../data/%s/cata/centroids%d_half.npy'%(scan_name, initial_sec), centroids)
initial_time = intitial_asp[0] - 0.5
tranges = []
for sec in range(num_co):
tranges.append(
[initial_time + step * sec, initial_time + step * (sec + 1)])
print tranges
data = get_data(tranges)
print len(data)
for sec in range(num_co):
coo1 = np.array(data[sec], dtype='float64')[:, -3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
print coo2.shape
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
count = get_corr_map(coo2, coo1, skypos, skyrange)
hdu = pyfits.PrimaryHDU(count)
hdu = imagetools.fits_header('NUV',
skypos,
tranges,
skyrange,
hdu=hdu,
wcs=wcs)
hdulist = pyfits.HDUList([hdu])
def run_one_r(pid, scan_name, step, start, end, return_dict):
print 'run_one_r'
num_co = int(1/step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
plt.plot(co_data['T'])
plt.show()
cal_initial = int((co_data[1][0]-0.5)*1000)
print cal_initial
offsets = np.load('../data/%s/cata/offsets1_10_new_inter_half_fine.npy'%scan_name)
print length
print co_data[-10]
print co_data[0]
print co_data[-1][0]-co_data[0][0]
#print offsets[300*200:301*200]
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids%d_half.npy'%(scan_name, initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
center = np.array([intitial_asp[1], intitial_asp[2]])
print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.2, 0.2]
wcs = imagetools.define_wcs(skypos,skyrange,width=False,height=False,verbose=0,pixsz=0.0001)
initial_time = intitial_asp[0]-0.5
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
data = get_data_cal(tranges, scan_name, cal_initial, offsets)
#data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 0.5)
coo2 = angle_filter(coo2, center, 0.5)
get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.05, 0.008)
'''
def run_one_r(pid, scan_name, step, start, end, return_dict):
print 'run_one_r'
num_co = int(1 / step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits' % scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
plt.plot(co_data['T'])
plt.show()
cal_initial = int((co_data[1][0] - 0.5) * 1000)
print cal_initial
offsets = np.load('../data/%s/cata/offsets1_10_new_inter_half_fine.npy' %
scan_name)
print length
print co_data[-10]
print co_data[0]
print co_data[-1][0] - co_data[0][0]
#print offsets[300*200:301*200]
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids%d_half.npy' % (scan_name,
initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
center = np.array([intitial_asp[1], intitial_asp[2]])
print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.2, 0.2]
wcs = imagetools.define_wcs(skypos,
skyrange,
width=False,
height=False,
verbose=0,
pixsz=0.0001)
initial_time = intitial_asp[0] - 0.5
tranges = []
for sec in range(num_co):
tranges.append(
[initial_time + step * sec, initial_time + step * (sec + 1)])
print tranges
data = get_data_cal(tranges, scan_name, cal_initial, offsets)
#data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv" % (scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:, -3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 0.5)
coo2 = angle_filter(coo2, center, 0.5)
get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.05, 0.008)
'''
def run_one_r_sec(pid, scan_name, step, start, end, return_dict):
num_co = int(1 / step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits' % scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
cal_initial = int((co_data[1][0] - 0.5) * 1000)
offsets = np.load('../data/%s/cata/offsets1_10_new_inter_half_fine.npy' %
scan_name)
print length
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids_sec%d.npy' % (scan_name,
initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
center = cal_asp_r(offsets, cal_initial, intitial_asp[0] * 1000,
intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.1, 0.1]
wcs = imagetools.define_wcs(skypos,
skyrange,
width=False,
height=False,
verbose=0,
pixsz=0.0001)
initial_time = intitial_asp[0] - 0.5
tranges = []
for sec in range(num_co):
tranges.append(
[initial_time + step * sec, initial_time + step * (sec + 1)])
print tranges
data = get_data_cal(tranges, scan_name, cal_initial, offsets)
print len(data)
output = "../data/%s/cata/%s.csv" % (scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:, -3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
'''
xi, eta = gn.gnomfwd_simple(coo1[:,0], coo1[:,1], center[0], center[1], -rot, 1/36000., 0.0)
xi2, eta2 = gn.gnomfwd_simple(coo2[:,0], coo2[:,1], center[0], center[1], -rot, 1/36000., 0.0)
r, phi = cart2pol(xi, eta)
r2, phi2 = cart2pol(xi2, eta2)
coo1 = np.array([r,phi]).T
coo2 = np.array([r2,phi2]).T
'''
get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.05, 0.0015)
'''
data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
count, centroid = get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.1, 0.008)
centroids.append(centroid)
print centroid
print centroids
np.save('../data/%s/cata/centroids%d.npy'%(scan_name, initial_sec), centroids)
#for hpc
if False:
initial_sec = int(sys.argv[1])
def run_one_r_sec(pid, scan_name, step, resolution, asp_cal, start, end, dis_map, return_dict):
print('run one r sec')
num_co = int(resolution/step)
#load asp file
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
'''
try:
asp_cal = np.load('../data/photon_list/%s_asp_new.npy'%scan_name)
except IOError:
T = co_data['T']
ra = co_data['ra']
dec = co_data['dec']
roll = co_data['roll']
t_new = np.arange((T.shape[0]-1)*200)*0.005+T[0]
ra_new = np.interp(t_new, T, ra)
dec_new = np.interp(t_new, T, dec)
roll_new = np.interp(t_new, T, roll)
asp_cal = np.array([t_new, ra_new, dec_new, roll_new]).T
np.save('../data/photon_list/%s_asp_new.npy'%scan_name, asp_cal)
'''
#cal_initial = int((co_data[1][0]-0.5)*1000)
#offsets = np.load('../data/%s/cata/offsets_inter_half_sec.npy'%scan_name)
angle_list = [0.]
print length
data1 = []
data2 = []
data3 = []
start = 700
c_list = []
for start in range(701, 1500, 50):
print start
data1 = []
data2 = []
data3 = []
for initial_sec in range(start, start+50):
print 'time:%d'%initial_sec
file_path = '../data/%s/cata/centroids_rot%d.npy'%(scan_name, initial_sec)
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
#center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
#center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.02, 0.02]
if step == 1:
skyrange = [0.04, 0.04]#[0.3, 0.3]
elif step == 0.5:
skyrange = [0.02, 0.02]
initial_time = intitial_asp[0]-step/2.
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
time_c = np.mean(tranges, axis=1)
print 'center time:'
print time_c
#data = get_data_cal(tranges, scan_name, cal_initial, offsets)
data = get_data(tranges, scan_name)
print 'number of the photons:'
print len(data)
centroids = []
center_time = []
for sec in range(num_co):
center_time.append(time_c[sec])
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0, 0.0])
centroids.append(centroid)
print centroid
continue
arg = np.argmin(np.absolute(asp_cal[:,0]-time_c[sec]))
center = asp_cal[arg, 1:3]
data_sec = dis_correct(np.array(data[sec], dtype='float64'), dis_map, asp_cal)
coo1 = np.array(data_sec, dtype='float64')
aperture = 0.69
#coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
#coo2 = catalog_fits.get_catalog_tycho(center, aperture)
coo2 = catalog_fits.get_catalog(center, aperture)
#coo1 = angle_filter(coo1, center, 0.6)
#coo2 = angle_filter(coo2, center, 0.6)
'''
fig = plt.gcf()
fig.set_size_inches(8,8)
plt.plot(coo1[:,0], coo1[:,1], '.k', markersize=0.1)
plt.plot(coo3[:,0], coo3[:,1], '+r', markersize=12)
plt.plot(coo2[:,0], coo2[:,1], '+b', markersize=8)
#plt.show()
plt.ylabel('Dec')
plt.xlabel('RA')
plt.xlim(center[0]-0.65, center[0]+0.65)
plt.ylim(center[1]-0.65, center[1]+0.65)
plt.tight_layout()
plt.savefig('/home/dw1519/galex/plots/photons.png', dpi=190)
plt.clf()
plt.close()
'''
'''
#plot field
#plt.plot(asp_cal[:,1],'.b')
#plt.show()
print center
print coo1.shape
print np.min(coo1[:,0]), np.max(coo1[:,0])
print np.min(coo1[:,1]), np.max(coo1[:,1])
wcs = imagetools.define_wcs(center,[1.5,1.5],width=False,height=False,verbose=0,pixsz=0.002)
imsz = imagetools.deg2pix(center, [1.5,1.5], 0.002)
foc = wcs.sip_pix2foc(wcs.wcs_world2pix(coo1,1),1)
H,xedges,yedges=np.histogram2d(foc[:,1]-0.5, foc[:,0]-0.5,\
bins=imsz, range=([ [0,imsz[0]],[0,imsz[1
def run_one_r_sec(pid, scan_name, step, start, end, return_dict):
print('run one r sec')
pixsz = 0.000416666666666667
#skypos_count = [5.,-9.5]
#skyrange_count = [2., 3.]
#tranges_count = [[0,0]]
#imsz_count = imsz = imagetools.deg2pix_g(skypos_count, skyrange_count, pixsz)
#wcs_count = imagetools.define_wcs_g(skypos_count,skyrange_count,width=False,height=False,verbose=0,pixsz=pixsz)
#count = np.zeros(imsz_count)
num_co = int(1/step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
#cal_initial = int((co_data[1][0]-0.5)*1000)
#offsets = np.load('../data/%s/cata/offsets_inter_half_sec.npy'%scan_name)
angle_list = [0.]
print length
for initial_sec in range(start, end):
print 'time:%d'%initial_sec
file_path = '../data/%s/cata/centroids_sec%d.npy'%(scan_name, initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
#center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.2, 0.2]
wcs = imagetools.define_wcs(skypos,skyrange,width=False,height=False,verbose=0,pixsz=0.0001)
initial_time = intitial_asp[0]-0.5
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
#data = get_data_cal(tranges, scan_name, cal_initial, offsets)
data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 0.5)
coo2 = angle_filter(coo2, center, 0.5)
xi, eta = gn.gnomfwd_simple(coo1[:,0], coo1[:,1], center[0], center[1], -rot, 1/36000., 0.0)
max_now = -1000
cent_now = []
for angle in angle_list:
coo1[:,0], coo1[:,1] = gn.gnomrev_simple(xi,eta,center[0],center[1],-(rot+angle),1/36000.,0.)
centroid, max_value = get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.2, 0.004)
if max_value>max_now:
max_now = max_value
cent_now = np.append(centroid, angle) #centroid.append(angle)
centroids.append(cent_now)
print centroids
np.save('../data/%s/cata/centroids_rot%d.npy'%(scan_name, initial_sec), centroids)
def run_one_r_o(pid, scan_name, step, start, end, return_dict):
num_co = int(1 / step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits' % scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
print length
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids_new%d.npy' % (scan_name,
initial_sec)
if os.path.exists(file_path):
print 'skip:%d' % initial_sec
continue
intitial_asp = co_data[initial_sec]
center = np.array([intitial_asp[1], intitial_asp[2]])
print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.3, 0.3]
wcs = imagetools.define_wcs(skypos,
skyrange,
width=False,
height=False,
verbose=0,
pixsz=0.0001)
initial_time = intitial_asp[0] - 0.5
tranges = []
for sec in range(num_co):
tranges.append(
[initial_time + step * sec, initial_time + step * (sec + 1)])
print tranges
data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv" % (scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
out_mask = []
for sec in range(num_co):
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0])
out_mask.append(1)
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:, -3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
count, centroid, out = get_corr_map_o(coo2, coo1, skypos, skyrange,
sec, 0.15, 0.008)
centroids.append(centroid)
out_mask.append(out)
print centroid
print centroids
np.save(
'../data/%s/cata/centroids_new%d.npy' % (scan_name, initial_sec),
centroids)
np.save('../data/%s/cata/out_mask%d.npy' % (scan_name, initial_sec),
out_mask)
def run_one_r_sec(pid, scan_name, step, resolution, asp_cal, start, end, dis_map, return_dict):
print('run one r sec')
num_co = int(resolution/step)
#load asp file
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
'''
try:
asp_cal = np.load('../data/photon_list/%s_asp_new.npy'%scan_name)
except IOError:
T = co_data['T']
ra = co_data['ra']
dec = co_data['dec']
roll = co_data['roll']
t_new = np.arange((T.shape[0]-1)*200)*0.005+T[0]
ra_new = np.interp(t_new, T, ra)
dec_new = np.interp(t_new, T, dec)
roll_new = np.interp(t_new, T, roll)
asp_cal = np.array([t_new, ra_new, dec_new, roll_new]).T
np.save('../data/photon_list/%s_asp_new.npy'%scan_name, asp_cal)
'''
#cal_initial = int((co_data[1][0]-0.5)*1000)
#offsets = np.load('../data/%s/cata/offsets_inter_half_sec.npy'%scan_name)
angle_list = [0.]
start =600#1000
print length
for initial_sec in range(start, end):
print 'time:%d'%initial_sec
file_path = '../data/%s/cata/centroids_rot%d.npy'%(scan_name, initial_sec)
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
#center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
#center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.02, 0.02]
if step == 1:
skyrange = [0.04, 0.04]#[0.3, 0.3]
elif step == 0.5:
skyrange = [0.02, 0.02]
initial_time = intitial_asp[0]-step/2.
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
time_c = np.mean(tranges, axis=1)
print 'center time:'
print time_c
#data = get_data_cal(tranges, scan_name, cal_initial, offsets)
data = get_data(tranges, scan_name)
print 'number of the photons:'
print len(data)
centroids = []
center_time = []
for sec in range(num_co):
center_time.append(time_c[sec])
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0, 0.0])
centroids.append(centroid)
print centroid
continue
arg = np.argmin(np.absolute(asp_cal[:,0]-time_c[sec]))
center = asp_cal[arg, 1:3]
data_sec = dis_correct(np.array(data[sec], dtype='float64'), dis_map, asp_cal)
coo1 = np.array(data_sec, dtype='float64')
aperture = 0.69
#coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo3 = catalog_fits.get_catalog_tycho(center, aperture)
coo2 = catalog_fits.get_catalog(center, aperture)
#coo2[:,0] -= 0.0052 #- 0.01005915
#coo2[:,1] -= -0.006 #- 0.00804992
#data_sec = dis_correct(np.array(data[sec+1], dtype='float64'), dis_map, asp_cal)
#coo4 = np.array(data_sec, dtype='float64')
#coo2 = catalog_fits.get_catalog(center, 2.)
#coo2 = np.concatenate([coo2,coo3], axis=0)
coo1 = angle_filter(coo1, center, 0.6)
coo2 = angle_filter(coo2, center, 0.6)
coo3 = angle_filter(coo3, center, 0.6)
#coo4 = angle_filter(coo4, center, 0.6)
fig = plt.gcf()
fig.set_size_inches(8,8)
plt.plot(coo1[:,0], coo1[:,1], '.k', markersize=0.1)
plt.plot(coo3[:,0], coo3[:,1], '+r', markersize=12)
plt.plot(coo2[:,0], coo2[:,1], '+b', markersize=8)
#plt.show()
plt.ylabel('Dec')
plt.xlabel('RA')
plt.xlim(center[0]-0.65, center[0]+0.65)
plt.ylim(center[1]-0.65, center[1]+0.65)
plt.tight_layout()
plt.savefig('/home/dw1519/galex/plots/photons.png', dpi=190)
plt.clf()
plt.close()
'''
#plot field
#plt.plot(asp_cal[:,1],'.b')
#plt.show()
print center
print coo1.shape
print np.min(coo1[:,0]), np.max(coo1[:,0])
print np.min(coo1[:,1]), np.max(coo1[:,1])
wcs = imagetools.define_wcs(center,[1.5,1.5],width=False,height=False,verbose=0,pixsz=0.002)
imsz = imagetools.deg2pix(center, [1.5,1.5], 0.002)
foc = wcs.sip_pix2foc(wcs.wcs_world2pix(coo1,1),1)
H,xedges,yedges=np.histogram2d(foc[:,1]-0.5, foc[:,0]-0.5,\
bins=imsz, range=([ [0,imsz[0]],[0,imsz[1]] ]))
H_new = H.copy()
data = H_new.byteswap(True).newbyteorder()
data = data.copy(order='C')
data = data.byteswap(True).newbyteorder()
c_data = c3.find_source(data, 1)
if c_data is not None:
cx, cy, max_value = c_data
print cy, cx
centroid = wcs.wcs_pix2world(wcs.sip_foc2pix([[cx, cy]],1),1)[0]
coo1 = angle_filter_out(coo1, centroid, 0.01)
foc = wcs.sip_pix2foc(wcs.wcs_world2pix(coo1,1),1)
H,xedges,yedges=np.histogram2d(foc[:,1]-0.5, foc[:,0]-0.5,\
bins=imsz, range=([ [0,imsz[0]],[0,imsz[1]] ]))
plt.imshow(H,interpolation='None', cmap=plt.get_cmap('Greys'), vmax=10)
plt.colorbar()
plt.show()
foc = wcs.sip_pix2foc(wcs.wcs_world2pix(coo2,1),1)
H,xedges,yedges=np.histogram2d(foc[:,1]-0.5, foc[:,0]-0.5,\
bins=imsz, range=([ [0,imsz[0]],[0,imsz[1]] ]))
plt.imshow(H,interpolation='None', cmap=plt.get_cmap('Greys'))
plt.show()
'''
xi, eta = gn.gnomfwd_simple(coo1[:,0], coo1[:,1], center[0], center[1], -rot, 1/36000., 0.0)
max_now = -1000
cent_now = []
for angle in angle_list:
#coo1[:,0], coo1[:,1] = gn.gnomrev_simple(xi,eta,center[0],center[1],-(rot+angle),1/36000.,0.)
centroid, max_value, flux = get_corr_map(coo3, coo1, skypos, skyrange, sec, 0.0002, initial_sec, '2')
print centroid
centroid, max_value, flux = get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.0002, initial_sec, '1')
print centroid
#centroid, max_value, flux = get_corr_map(coo4, coo1, skypos, skyrange, sec, 0.0002, initial_sec, '3')
#print centroid
if max_value>max_now:
max_now = max_value
cent_now = np.append(centroid, angle) #centroid.append(angle)
centroids.append(cent_now)
print centroids
sys.exit(0)
def run_one_r_sec(pid, scan_name, step, start, end, return_dict):
pixsz = 0.000416666666666667
skypos_count = [5.,-9.5]
skyrange_count = [2., 3.]
tranges_count = [[0,0]]
imsz_count = imsz = imagetools.deg2pix_g(skypos_count, skyrange_count, pixsz)
wcs_count = imagetools.define_wcs_g(skypos_count,skyrange_count,width=False,height=False,verbose=0,pixsz=pixsz)
count = np.zeros(imsz_count)
num_co = int(1/step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
cal_initial = int((co_data[1][0]-0.5)*1000)
offsets = np.load('../data/%s/cata/offsets_inter_half_sec.npy'%scan_name)
angle_list = [-0.035, -0.03, -0.025, -0.02, -0.015, -0.01, -0.005, 0, 0.005, 0.01, 0.015, 0.02, 0.025, 0.03, 0.035]
print length
for initial_sec in range(start, end):
print 'time:%d'%initial_sec
file_path = '../data/%s/cata/centroids_sec%d.npy'%(scan_name, initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.02, 0.02]
wcs = imagetools.define_wcs(skypos,skyrange,width=False,height=False,verbose=0,pixsz=0.0001)
initial_time = intitial_asp[0]-0.5
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
data = get_data_cal(tranges, scan_name, cal_initial, offsets)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
xi, eta = gn.gnomfwd_simple(coo1[:,0], coo1[:,1], center[0], center[1], -rot, 1/36000., 0.0)
max_now = -1000
cent_now = []
for angle in angle_list:
coo1[:,0], coo1[:,1] = gn.gnomrev_simple(xi,eta,center[0],center[1],-(rot+angle),1/36000.,0.)
centroid, max_value = get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.02, 0.004)
if max_value>max_now:
max_now = max_value
cent_now = np.append(centroid, angle) #centroid.append(angle)
coo1[:,0], coo1[:,1] = gn.gnomrev_simple(xi,eta,center[0]-cent_now[0],center[1]-cent_now[1],-(rot+cent_now[2]),1/36000.,0.)
sky_data = SkyCoord(coo1, unit='deg', frame=FK5, equinox='J2000.0')
gal = sky_data.transform_to(Galactic)
data_count = np.concatenate((np.array([gal.l.deg]).T, np.array([gal.b.deg]).T), axis=1)
H = hist_g(data_count, wcs_count, imsz_count)
count += H
sky_data=gal=data_count=H = None
gc.collect()
#xi2, eta2 = gn.gnomfwd_simple(coo2[:,0], coo2[:,1], center[0], center[1], -rot, 1/36000., 0.0)
#r, phi = cart2pol(xi, eta)
#r2, phi2 = cart2pol(xi2, eta2)
#coo1 = np.array([r,phi]).T
#coo2 = np.array([r2,phi2]).T
#get_corr_map(coo2, coo1, skypos, skyrange, sec, 0.05, 0.0015)
centroids.append(cent_now)
print cent_now
print centroids
#np.save('../data/%s/cata/centroids_rot%d.npy'%(scan_name, initial_sec), centroids)
hdu = pyfits.PrimaryHDU(count)
hdu = imagetools.fits_header('NUV', skypos_count, tranges_count, skyrange_count, hdu=hdu, wcs=wcs_count)
hdulist = pyfits.HDUList([hdu])
hdulist.writeto('../fits/count_map_%s_gal_sec_rot_count.fits'%(scan_name), clobber=False)
def run_one_r_sec(pid, scan_name, step, start, end, return_dict):
num_co = int(1/step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits'%scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
cal_initial = int((co_data[1][0]-0.5)*1000)
offsets = np.load('../data/%s/cata/offsets1_10_new_inter_half_fine.npy'%scan_name)
print length
for initial_sec in range(start, end):
file_path = '../data/%s/cata/centroids_sec%d.npy'%(scan_name, initial_sec)
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
intitial_asp = co_data[initial_sec]
#center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.1, 0.1]
wcs = imagetools.define_wcs(skypos,skyrange,width=False,height=False,verbose=0,pixsz=0.0001)
initial_time = intitial_asp[0]-0.5
tranges = []
for sec in range(num_co):
tranges.append([initial_time+step*sec, initial_time+step*(sec+1)])
print tranges
data = get_data_cal(tranges, scan_name, cal_initial, offsets)
print len(data)
output = "../data/%s/cata/%s.csv"%(scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) ==0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:,-3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 1.)
coo2 = angle_filter(coo2, center, 1.)
count, centroid = get_corr_map_fast(coo2, coo1, skypos, skyrange, sec, 0.03, 0.0015)
centroids.append(centroid)
print centroid
print centroids
np.save('../data/%s/cata/centroids_sec%d.npy'%(scan_name, initial_sec), centroids)
def run_one_r_sec(pid, scan_name, step, start, end, return_dict):
print('run one r sec')
pixsz = 0.000416666666666667
#skypos_count = [5.,-9.5]
#skyrange_count = [2., 3.]
#tranges_count = [[0,0]]
#imsz_count = imsz = imagetools.deg2pix_g(skypos_count, skyrange_count, pixsz)
#wcs_count = imagetools.define_wcs_g(skypos_count,skyrange_count,width=False,height=False,verbose=0,pixsz=pixsz)
#count = np.zeros(imsz_count)
num_co = int(1 / step)
hdulist = pyfits.open('../AIS_GAL_SCAN/asprta/%s-asprta.fits' % scan_name)
co_data = hdulist[1].data
length = co_data.shape[0]
#cal_initial = int((co_data[1][0]-0.5)*1000)
#offsets = np.load('../data/%s/cata/offsets_inter_half_sec.npy'%scan_name)
angle_list = [0.]
print length
for initial_sec in range(start, end):
print 'time:%d' % initial_sec
file_path = '../data/%s/cata/centroids_sec%d.npy' % (scan_name,
initial_sec)
'''
if os.path.exists(file_path):
print 'skip:%d'%initial_sec
continue
'''
intitial_asp = co_data[initial_sec]
rot = intitial_asp[3]
center = np.array([intitial_asp[1], intitial_asp[2]])
#use the first order calibrated asp instead of the original one
#center = cal_asp_r(offsets, cal_initial, intitial_asp[0]*1000, intitial_asp[1:3], 200)
#print(intitial_asp)
skypos = [0.0, 0.0]
skyrange = [0.2, 0.2]
wcs = imagetools.define_wcs(skypos,
skyrange,
width=False,
height=False,
verbose=0,
pixsz=0.0001)
initial_time = intitial_asp[0] - 0.5
tranges = []
for sec in range(num_co):
tranges.append(
[initial_time + step * sec, initial_time + step * (sec + 1)])
print tranges
#data = get_data_cal(tranges, scan_name, cal_initial, offsets)
data = get_data(tranges, scan_name)
print len(data)
output = "../data/%s/cata/%s.csv" % (scan_name, scan_name)
dir = os.path.dirname(output)
if not os.path.exists(dir):
os.makedirs(dir)
centroids = []
for sec in range(num_co):
if len(data[sec]) == 0:
centroid = np.array([0.0, 0.0])
centroids.append(centroid)
print centroid
continue
coo1 = np.array(data[sec], dtype='float64')[:, -3:-1]
coo2 = catalog_fits.get_catalog(center, 0.69)
coo1 = angle_filter(coo1, center, 0.5)
coo2 = angle_filter(coo2, center, 0.5)
xi, eta = gn.gnomfwd_simple(coo1[:, 0], coo1[:, 1], center[0],
center[1], -rot, 1 / 36000., 0.0)
max_now = -1000
cent_now = []
for angle in angle_list:
coo1[:,
0], coo1[:,
1] = gn.gnomrev_simple(xi, eta, center[0],
center[1], -(rot + angle),
1 / 36000., 0.)
centroid, max_value = get_corr_map(coo2, coo1, skypos,
skyrange, sec, 0.2, 0.004)
if max_value > max_now:
max_now = max_value
cent_now = np.append(centroid,
angle) #centroid.append(angle)
centroids.append(cent_now)
print centroids
np.save(
'../data/%s/cata/centroids_rot%d.npy' % (scan_name, initial_sec),
centroids)
