def finder(myfile,searchrad=0.2/60.):
ra, dec = coordinates_conversor.hour2deg(fitsutils.get_par(myfile, "OBJRA"), fitsutils.get_par(myfile, "OBJDEC"))
hdulist = pf.open(myfile)[0]
img = hdulist.data * 1.
img = img.T
wcs = pywcs.WCS(hdulist.header)
target_pix = wcs.wcs_sky2pix([(np.array([ra,dec], np.float_))], 1)[0]
corner_pix = wcs.wcs_sky2pix([(np.array([ra,dec+searchrad], np.float_))], 1)[0]
dx = int(np.abs(np.ceil(corner_pix[1] - target_pix[1])))
imgslice = img[int(target_pix[0])-2*dx:int(target_pix[0])+2*dx, int(target_pix[1])-2*dx:int(target_pix[1])+2*dx]
#zmin, zmax = zscale.zscale()
zmin = np.percentile(imgslice.flatten(), 5)
zmax = np.percentile(imgslice.flatten(), 98)
print "Min: %.1f, max: %.1f"%(zmin, zmax)
gc = aplpy.FITSFigure(myfile, figsize=(10,9), north=True)
gc.show_grayscale(vmin=zmin, vmax=zmax, smooth=1, kernel="gauss")
gc.show_scalebar(0.1/60.)
gc.scalebar.set_label('10 arcsec')
gc.scalebar.set_color('white')
gc.recenter(ra, dec, searchrad)
#gc.show_markers(ra,dec+searchrad/20.,edgecolor='red',facecolor='none',marker="|",s=250, lw=10)
#gc.show_markers(ra-(searchrad/20.)/np.cos(np.deg2rad(dec)),dec,edgecolor='red',facecolor='none',marker="_",s=250, lw=10)
ras = np.array([ra , ra])
decs = np.array([dec, dec])
dxs = np.array([0, searchrad/10 / np.cos(np.deg2rad(dec))])
dys = np.array([searchrad/10, 0])
gc.show_arrows(ras, decs, dxs, dys, edgecolor="red", facecolor="red", head_width=0)
ras = np.array([ra+searchrad*0.7/ np.cos(np.deg2rad(dec)), ra+searchrad*0.7/ np.cos(np.deg2rad(dec))])
decs = np.array([dec-searchrad*0.9, dec-searchrad*0.9])
dxs = np.array([0, searchrad/5 / np.cos(np.deg2rad(dec))])
dys = np.array([searchrad/5, 0])
gc.show_arrows(ras, decs, dxs, dys, edgecolor="k", facecolor="k")
gc.add_label(ras[0]+dxs[0]*1.1, decs[0]+dys[0]*1.1, 'N', relative=False, color="k", horizontalalignment="center")
gc.add_label(ras[1]+dxs[1]*1.1, decs[1]+dys[1]*1.1, 'E', relative=False, color="k", horizontalalignment="center")
name = fitsutils.get_par(myfile, "NAME")
filter = fitsutils.get_par(myfile, "FILTER")
gc.add_label(0.05, 0.95, 'Object: %s'%(name), relative=True, color="white", horizontalalignment="left")
gc.add_label(0.05, 0.9, 'Coordinates: RA=%s DEC=%s'%(coordinates_conversor.deg2hour(ra, dec)), relative=True, color="white", horizontalalignment="left")
gc.add_label(0.05, 0.84, 'Filter: SDSS %s'%filter, relative=True, color="white", horizontalalignment="left")
findername = 'finders/finder_%s_%s.jpg'%(name, filter)
gc.save(findername)
return findername
def finder(myfile,searchrad=0.2/60.):
ra, dec = coordinates_conversor.hour2deg(fitsutils.get_par(myfile, "RA"), fitsutils.get_par(myfile, "DEC"))
hdulist = pf.open(myfile)[0]
img = hdulist.data * 1.
wcs = pywcs.WCS(hdulist.header)
target_pix = wcs.wcs_sky2pix([(np.array([ra,dec], np.float_))], 1)[0]
corner_pix = wcs.wcs_sky2pix([(np.array([ra,dec+searchrad], np.float_))], 1)[0]
dx = int(np.abs(np.ceil(corner_pix[1] - target_pix[1])))
imgslice = img[int(target_pix[0])-2*dx:int(target_pix[0])+2*dx, int(target_pix[1])-2*dx:int(target_pix[1])+2*dx]
#zmin, zmax = zscale.zscale()
zmin = np.percentile(imgslice.flatten(), 5)
zmax = np.percentile(imgslice.flatten(), 99)
gc = aplpy.FITSFigure(myfile, figsize=(10,9), north=True)
gc.show_grayscale(vmin=zmin, vmax=zmax)
gc.show_scalebar(0.1/60.)
gc.scalebar.set_label('10 arcsec')
gc.scalebar.set_color('white')
gc.recenter(ra, dec, searchrad)
gc.show_markers(ra,dec+searchrad/20.,edgecolor='red',facecolor='none',marker="|",s=250, lw=10)
gc.show_markers(ra-(searchrad/20.)/np.cos(np.deg2rad(dec)),dec,edgecolor='red',facecolor='none',marker="_",s=250, lw=10)
ras = np.array([ra , ra])
decs = np.array([dec, dec])
dxs = np.array([0, searchrad/10 / np.cos(np.deg2rad(dec))])
dys = np.array([searchrad/10, 0])
gc.show_arrows(ras, decs, dxs, dys, edgecolor="red", facecolor="red", head_width=0)
ras = np.array([ra+searchrad*0.7/ np.cos(np.deg2rad(dec)), ra+searchrad*0.7/ np.cos(np.deg2rad(dec))])
decs = np.array([dec-searchrad*0.9, dec-searchrad*0.9])
dxs = np.array([0, searchrad/5 / np.cos(np.deg2rad(dec))])
dys = np.array([searchrad/5, 0])
gc.show_arrows(ras, decs, dxs, dys, edgecolor="k", facecolor="k")
gc.add_label(ras[0]+dxs[0]*1.1, decs[0]+dys[0]*1.1, 'N', relative=False, color="k", horizontalalignment="center")
gc.add_label(ras[1]+dxs[1]*1.1, decs[1]+dys[1]*1.1, 'E', relative=False, color="k", horizontalalignment="center")
name = fitsutils.get_par(myfile, "OBJECT")
gc.add_label(0.05, 0.95, 'Object: %s'%(name), relative=True, color="white", horizontalalignment="left")
gc.add_label(0.05, 0.9, 'Coordinates: RA=%s DEC=%s'%(coordinates_conversor.deg2hour(ra, dec)), relative=True, color="white", horizontalalignment="left")
gc.add_label(0.05, 0.84, 'Filter: SDSS r', relative=True, color="white", horizontalalignment="left")
findername = '%s_finder.jpg'%(name)
gc.save(findername)
return findername
def get_sao(radius=2000):
'''
Uses the current time and the latitude of Palomar to find the best SAO stars at zenith.
Palomar.lon, Palomar.lat = '243.1361', '33.3558'
'''
#Log into a file
FORMAT = '%(asctime)-15s %(levelname)s [%(name)s] %(message)s'
root_dir = _logpath
now = datetime.datetime.utcnow()
timestamp=datetime.datetime.isoformat(now)
timestamp=timestamp.split("T")[0]
logging.basicConfig(format=FORMAT, filename=os.path.join(root_dir, "listener_{0}.log".format(timestamp)), level=logging.INFO)
logger = logging.getLogger('sao')
d = datetime.datetime.now()
utc = d.utcnow()
#Get reasonably high target
ra = 15*((utc.hour+10)%24) + 15*(utc.minute/60.)
dec = 40
hra, hdec = coordinates_conversor.deg2hour(ra, dec)
logger.info( "Coordinates to search %s %s"%(hra,hdec))
sao = get_sao_rec(hra, hdec, radius)
while (len(sao) == 0):
radius = radius+1000
sao = get_sao_rec(hra, hdec, radius)
logger.info( "Found %d"%len(sao))
if np.ndim(sao) > 1:
np.random.shuffle(sao)
logger.info( "Returning %s %s"%(sao[0][1], sao[0][2]))
saora, saodec = coordinates_conversor.hour2deg(sao[0][1], sao[0][2])
return "SAO%s"%(sao[0][0]), saora, saodec
