def testExceptions(self):
"""
Test to make sure that methods complain when incorrect data types are passed.
"""
obs = utils.ObservationMetaData(pointingRA=55.0, pointingDec=-72.0, mjd=53467.8)
raFloat = 1.1
raList = np.array([0.2, 0.3])
decFloat = 1.1
decList = np.array([0.2, 0.3])
self.assertRaises(RuntimeError, utils._altAzPaFromRaDec, raList, decFloat, obs)
self.assertRaises(RuntimeError, utils._altAzPaFromRaDec, raFloat, decList, obs)
utils._altAzPaFromRaDec(raFloat, decFloat, obs)
utils._altAzPaFromRaDec(raList, decList, obs)
self.assertRaises(RuntimeError, utils._raDecFromAltAz, raList, decFloat, obs)
self.assertRaises(RuntimeError, utils._raDecFromAltAz, raFloat, decList, obs)
utils._raDecFromAltAz(raFloat, decFloat, obs)
utils._raDecFromAltAz(raList, decList, obs)
self.assertRaises(RuntimeError, utils.altAzPaFromRaDec, raList, decFloat, obs)
self.assertRaises(RuntimeError, utils.altAzPaFromRaDec, raFloat, decList, obs)
utils.altAzPaFromRaDec(raFloat, decFloat, obs)
utils.altAzPaFromRaDec(raList, decList, obs)
self.assertRaises(RuntimeError, utils.raDecFromAltAz, raList, decFloat, obs)
self.assertRaises(RuntimeError, utils.raDecFromAltAz, raFloat, decList, obs)
utils.raDecFromAltAz(raFloat, decFloat, obs)
utils.raDecFromAltAz(raList, decList, obs)
def testPAStacker(self):
""" Test the parallacticAngleStacker"""
data = np.zeros(100,
dtype=list(
zip([
'observationStartMJD', 'fieldDec', 'fieldRA',
'observationStartLST'
], [float] * 4)))
data['observationStartMJD'] = np.arange(100) * .2 + 50000
site = Site(name='LSST')
data['observationStartLST'], last = calcLmstLast(
data['observationStartMJD'], site.longitude_rad)
data['observationStartLST'] = data['observationStartLST'] * 180. / 12.
stacker = stackers.ParallacticAngleStacker(degrees=True)
data = stacker.run(data)
# Check values are in good range
assert (data['PA'].max() <= 180)
assert (data['PA'].min() >= -180)
# Check compared to the util
check_pa = []
ras = np.radians(data['fieldRA'])
decs = np.radians(data['fieldDec'])
for ra, dec, mjd in zip(ras, decs, data['observationStartMJD']):
alt, az, pa = _altAzPaFromRaDec(
ra, dec, ObservationMetaData(mjd=mjd, site=site))
check_pa.append(pa)
check_pa = np.degrees(check_pa)
np.testing.assert_array_almost_equal(data['PA'], check_pa, decimal=0)
def testPAStacker(self):
""" Test the parallacticAngleStacker"""
data = np.zeros(100, dtype=list(zip(
['observationStartMJD', 'fieldDec', 'fieldRA', 'observationStartLST'], [float] * 4)))
data['observationStartMJD'] = np.arange(100) * .2 + 50000
site = Site(name='LSST')
data['observationStartLST'], last = calcLmstLast(data['observationStartMJD'], site.longitude_rad)
data['observationStartLST'] = data['observationStartLST']*180./12.
stacker = stackers.ParallacticAngleStacker(degrees=True)
data = stacker.run(data)
# Check values are in good range
assert(data['PA'].max() <= 180)
assert(data['PA'].min() >= -180)
# Check compared to the util
check_pa = []
ras = np.radians(data['fieldRA'])
decs = np.radians(data['fieldDec'])
for ra, dec, mjd in zip(ras, decs, data['observationStartMJD']):
alt, az, pa = _altAzPaFromRaDec(ra, dec,
ObservationMetaData(mjd=mjd, site=site))
check_pa.append(pa)
check_pa = np.degrees(check_pa)
np.testing.assert_array_almost_equal(data['PA'], check_pa, decimal=0)
def test_rad(self):
nside = 64
hpids = np.arange(hp.nside2npix(nside))
ra, dec = utils._hpid2RaDec(nside, hpids)
mjd = 59852.
obs = utils.ObservationMetaData(mjd=mjd)
alt1, az1, pa1 = utils._altAzPaFromRaDec(ra, dec, obs)
alt2, az2 = utils._approx_RaDec2AltAz(ra, dec, obs.site.latitude_rad,
obs.site.longitude_rad, mjd)
# Check that the fast is similar to the more precice transform
tol = np.radians(2)
tol_mean = np.radians(1.)
separations = utils._angularSeparation(az1, alt1, az2, alt2)
self.assertLess(np.max(separations), tol)
self.assertLess(np.mean(separations), tol_mean)
# Check that the fast can nearly round-trip
ra_back, dec_back = utils._approx_altAz2RaDec(alt2, az2, obs.site.latitude_rad,
obs.site.longitude_rad, mjd)
separations = utils._angularSeparation(ra, dec, ra_back, dec_back)
self.assertLess(np.max(separations), tol)
self.assertLess(np.mean(separations), tol_mean)
def test_raDecAltAz_noRefraction_degVsRadians(self):
"""
Check that raDecFromAltAz and altAzPaFromRaDec are consistent in a degrees-versus-radians
sense when refraction is turned off
"""
rng = np.random.RandomState(34)
n_samples = 10
ra_in = rng.random_sample(n_samples)*360.0
dec_in = rng.random_sample(n_samples)*180.0 - 90.0
mjd = 43000.0
obs = utils.ObservationMetaData(mjd=mjd)
alt, az, pa = utils.altAzPaFromRaDec(ra_in, dec_in, obs, includeRefraction=False)
alt_rad, az_rad, pa_rad = utils._altAzPaFromRaDec(np.radians(ra_in),
np.radians(dec_in),
obs, includeRefraction=False)
distance = utils.haversine(az_rad, alt_rad,
np.radians(az), np.radians(alt))
self.assertLess(utils.arcsecFromRadians(distance).min(), 0.001)
np.testing.assert_array_almost_equal(pa, np.degrees(pa_rad), decimal=12)
ra, dec = utils.raDecFromAltAz(alt, az, obs, includeRefraction=False)
ra_rad, dec_rad = utils._raDecFromAltAz(alt_rad, az_rad, obs, includeRefraction=False)
distance = utils.haversine(ra_rad, dec_rad, np.radians(ra), np.radians(dec))
self.assertLess(utils.arcsecFromRadians(distance).min(), 0.001)
def setRaDecMjd(self, lon, lat, mjd, degrees=False, azAlt=False, solarFlux=130.):
"""
Set the sky parameters by computing the sky conditions on a given MJD and sky location.
lon: Longitude-like (RA or Azimuth). Can be single number, list, or numpy array
lat: Latitude-like (Dec or Altitude)
mjd: Modified Julian Date for the calculation. Must be single number.
degrees: (False) Assumes lon and lat are radians unless degrees=True
azAlt: (False) Assume lon, lat are RA, Dec unless azAlt=True
solarFlux: solar flux in SFU Between 50 and 310. Default=130. 1 SFU=10^4 Jy.
"""
# Wrap in array just in case single points were passed
if not type(lon).__module__ == np.__name__:
if np.size(lon) == 1:
lon = np.array([lon]).ravel()
lat = np.array([lat]).ravel()
else:
lon = np.array(lon)
lat = np.array(lat)
if degrees:
self.ra = np.radians(lon)
self.dec = np.radians(lat)
else:
self.ra = lon
self.dec = lat
if np.size(mjd) > 1:
raise ValueError('mjd must be single value.')
self.mjd = mjd
if azAlt:
self.azs = self.ra.copy()
self.alts = self.dec.copy()
if self.preciseAltAz:
self.ra, self.dec = _raDecFromAltAz(self.alts, self.azs,
ObservationMetaData(mjd=self.mjd, site=self.telescope))
else:
self.ra, self.dec = stupidFast_altAz2RaDec(self.alts, self.azs,
self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
else:
if self.preciseAltAz:
self.alts, self.azs, pa = _altAzPaFromRaDec(self.ra, self.dec,
ObservationMetaData(mjd=self.mjd,
site=self.telescope))
else:
self.alts, self.azs = stupidFast_RaDec2AltAz(self.ra, self.dec,
self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
self.npts = self.ra.size
self._initPoints()
self.solarFlux = solarFlux
self.points['solarFlux'] = self.solarFlux
self._setupPointGrid()
self.paramsSet = True
# Interpolate the templates to the set paramters
self.interpSky()
def test_rad(self):
nside = 64
hpids = np.arange(hp.nside2npix(nside))
ra, dec = utils._hpid2RaDec(nside, hpids)
mjd = 59852.
obs = utils.ObservationMetaData(mjd=mjd)
alt1, az1, pa1 = utils._altAzPaFromRaDec(ra, dec, obs)
alt2, az2 = utils._approx_RaDec2AltAz(ra, dec, obs.site.latitude_rad,
obs.site.longitude_rad, mjd)
# Check that the fast is similar to the more precice transform
tol = np.radians(2)
tol_mean = np.radians(1.)
separations = utils._angularSeparation(az1, alt1, az2, alt2)
self.assertLess(np.max(separations), tol)
self.assertLess(np.mean(separations), tol_mean)
# Check that the fast can nearly round-trip
ra_back, dec_back = utils._approx_altAz2RaDec(alt2, az2,
obs.site.latitude_rad,
obs.site.longitude_rad,
mjd)
separations = utils._angularSeparation(ra, dec, ra_back, dec_back)
self.assertLess(np.max(separations), tol)
self.assertLess(np.mean(separations), tol_mean)
def testAltAzFromRaDec(self):
"""
Test conversion from RA, Dec to Alt, Az
"""
nSamples = 100
ra = self.rng.random_sample(nSamples)*2.0*np.pi
dec = (self.rng.random_sample(nSamples)-0.5)*np.pi
lon_rad = 1.467
lat_rad = -0.234
controlAlt, controlAz = controlAltAzFromRaDec(ra, dec,
lon_rad, lat_rad,
self.mjd)
obs = utils.ObservationMetaData(mjd=utils.ModifiedJulianDate(UTC=self.mjd),
site=utils.Site(longitude=np.degrees(lon_rad),
latitude=np.degrees(lat_rad),
name='LSST'))
# verify parallactic angle against an expression from
# http://www.astro.washington.edu/groups/APO/Mirror.Motions/Feb.2000.Image.Jumps/report.html#Image%20motion%20directions
#
ra_obs, dec_obs = utils._observedFromICRS(ra, dec, obs_metadata=obs, epoch=2000.0,
includeRefraction=True)
lmst, last = utils.calcLmstLast(obs.mjd.UT1, lon_rad)
hourAngle = np.radians(last * 15.0) - ra_obs
controlSinPa = np.sin(hourAngle) * np.cos(lat_rad) / np.cos(controlAlt)
testAlt, testAz, testPa = utils._altAzPaFromRaDec(ra, dec, obs)
distance = utils.arcsecFromRadians(utils.haversine(controlAz, controlAlt, testAz, testAlt))
self.assertLess(distance.max(), 0.0001)
self.assertLess(np.abs(np.sin(testPa) - controlSinPa).max(), self.tolerance)
# test non-vectorized version
for r, d in zip(ra, dec):
controlAlt, controlAz = controlAltAzFromRaDec(r, d, lon_rad, lat_rad, self.mjd)
testAlt, testAz, testPa = utils._altAzPaFromRaDec(r, d, obs)
lmst, last = utils.calcLmstLast(obs.mjd.UT1, lon_rad)
r_obs, dec_obs = utils._observedFromICRS(r, d, obs_metadata=obs,
epoch=2000.0, includeRefraction=True)
hourAngle = np.radians(last * 15.0) - r_obs
controlSinPa = np.sin(hourAngle) * np.cos(lat_rad) / np.cos(controlAlt)
distance = utils.arcsecFromRadians(utils.haversine(controlAz, controlAlt, testAz, testAlt))
self.assertLess(distance, 0.0001)
self.assertLess(np.abs(np.sin(testPa) - controlSinPa), self.tolerance)
def _run(self, simData):
pa_arr = []
for ra, dec, mjd in zip(simData[self.raCol], simData[self.decCol], simData[self.mjdCol]):
alt, az, pa = _altAzPaFromRaDec(ra, dec,
ObservationMetaData(mjd=mjd,site=self.site))
pa_arr.append(pa)
simData['PA'] = np.array(pa_arr)
return simData
def testAltAzPaFromRaDec(self):
mjd = 57432.7
obs = ObservationMetaData(mjd=mjd, site=Site(longitude=self.lon, latitude=self.lat, name='LSST'))
altRad, azRad, paRad = utils._altAzPaFromRaDec(self.raList, self.decList, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(np.degrees(self.raList),
np.degrees(self.decList),
obs)
np.testing.assert_array_almost_equal(altRad, np.radians(altDeg), 10)
np.testing.assert_array_almost_equal(azRad, np.radians(azDeg), 10)
np.testing.assert_array_almost_equal(paRad, np.radians(paDeg), 10)
altRad, azRad, paRad = utils._altAzPaFromRaDec(self.raList, self.decList, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(np.degrees(self.raList),
np.degrees(self.decList),
obs)
np.testing.assert_array_almost_equal(altRad, np.radians(altDeg), 10)
np.testing.assert_array_almost_equal(azRad, np.radians(azDeg), 10)
np.testing.assert_array_almost_equal(paRad, np.radians(paDeg), 10)
for ra, dec, in zip(self.raList, self.decList):
altRad, azRad, paRad = utils._altAzPaFromRaDec(ra, dec, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(np.degrees(ra),
np.degrees(dec),
obs)
self.assertAlmostEqual(altRad, np.radians(altDeg), 10)
self.assertAlmostEqual(azRad, np.radians(azDeg), 10)
self.assertAlmostEqual(paRad, np.radians(paDeg), 10)
def testAltAzPaFromRaDec(self):
mjd = 57432.7
obs = ObservationMetaData(mjd=mjd,
site=Site(longitude=self.lon,
latitude=self.lat,
name='LSST'))
altRad, azRad, paRad = utils._altAzPaFromRaDec(self.raList,
self.decList, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(np.degrees(self.raList),
np.degrees(self.decList),
obs)
np.testing.assert_array_almost_equal(altRad, np.radians(altDeg), 10)
np.testing.assert_array_almost_equal(azRad, np.radians(azDeg), 10)
np.testing.assert_array_almost_equal(paRad, np.radians(paDeg), 10)
altRad, azRad, paRad = utils._altAzPaFromRaDec(self.raList,
self.decList, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(np.degrees(self.raList),
np.degrees(self.decList),
obs)
np.testing.assert_array_almost_equal(altRad, np.radians(altDeg), 10)
np.testing.assert_array_almost_equal(azRad, np.radians(azDeg), 10)
np.testing.assert_array_almost_equal(paRad, np.radians(paDeg), 10)
for ra, dec, in zip(self.raList, self.decList):
altRad, azRad, paRad = utils._altAzPaFromRaDec(ra, dec, obs)
altDeg, azDeg, paDeg = utils.altAzPaFromRaDec(
np.degrees(ra), np.degrees(dec), obs)
self.assertAlmostEqual(altRad, np.radians(altDeg), 10)
self.assertAlmostEqual(azRad, np.radians(azDeg), 10)
self.assertAlmostEqual(paRad, np.radians(paDeg), 10)
def testradec2altaz(self):
np.random.seed(42)
ra = np.random.rand(100)*np.pi*2
dec = np.random.rand(100)*np.pi-np.pi/2
site = Site('LSST')
mjd = 55000
omd = ObservationMetaData(mjd=mjd,site=site)
trueAlt,trueAz,pa = _altAzPaFromRaDec(ra,dec,omd)
fastAlt,fastAz = sb.stupidFast_RaDec2AltAz(ra,dec,
site.latitude_rad,
site.longitude_rad,mjd)
distanceDiff = haversine(trueAz,trueAlt, fastAz,fastAlt)
degreeTol =2. # 2-degree tolerance on the fast transform
assert(np.degrees(distanceDiff.max()) < degreeTol)
def testradec2altaz(self):
np.random.seed(42)
ra = np.random.rand(100) * np.pi * 2
dec = np.random.rand(100) * np.pi - np.pi / 2
site = Site('LSST')
mjd = 55000
omd = ObservationMetaData(mjd=mjd, site=site)
trueAlt, trueAz, pa = _altAzPaFromRaDec(ra, dec, omd)
fastAlt, fastAz = sb.stupidFast_RaDec2AltAz(ra, dec, site.latitude_rad,
site.longitude_rad, mjd)
distanceDiff = haversine(trueAz, trueAlt, fastAz, fastAlt)
degreeTol = 2. # 2-degree tolerance on the fast transform
assert (np.degrees(distanceDiff.max()) < degreeTol)
# make sure we don't have nans
alt, az = sb.stupidFast_RaDec2AltAz(np.radians(np.array([0.])),
np.radians(np.array([-90.])),
np.radians(-30.2444),
np.radians(-70.7494), 59582.05125)
assert (~np.isnan(alt))
assert (~np.isnan(az))
def setRaDecMjd(self,
lon,
lat,
mjd,
degrees=False,
azAlt=False,
solarFlux=130.):
"""
Set the sky parameters by computing the sky conditions on a given MJD and sky location.
Ra and Dec in raidans or degrees.
input ra, dec or az,alt w/ altAz=True
solarFlux: solar flux in s.f.u. Between 50 and 310.
"""
# Wrap in array just in case single points were passed
if not type(lon).__module__ == np.__name__:
if np.size(lon) == 1:
lon = np.array([lon])
lat = np.array([lat])
else:
lon = np.array(lon)
lat = np.array(lat)
if degrees:
self.ra = np.radians(lon)
self.dec = np.radians(lat)
else:
self.ra = lon
self.dec = lat
self.mjd = mjd
if azAlt:
self.azs = self.ra.copy()
self.alts = self.dec.copy()
self.ra, self.dec = _raDecFromAltAz(self.alts, self.azs,
self.Observatory.lon,
self.Observatory.lat, self.mjd)
else:
self.alts, self.azs, pa = _altAzPaFromRaDec(
self.ra, self.dec, self.Observatory.lon, self.Observatory.lat,
self.mjd)
self.npts = self.ra.size
self._initPoints()
self.solarFlux = solarFlux
self.points['solarFlux'] = self.solarFlux
# Switch to Dublin Julian Date for pyephem
self.Observatory.date = mjd2djd(self.mjd)
sun = ephem.Sun()
sun.compute(self.Observatory)
self.sunAlt = sun.alt
self.sunAz = sun.az
# Compute airmass the same way as ESO model
self.airmass = 1. / np.cos(np.pi / 2. - self.alts)
self.points['airmass'] = self.airmass
self.points['nightTimes'] = 2
self.points['alt'] = self.alts
self.points['az'] = self.azs
if self.twilight:
self.points['sunAlt'] = self.sunAlt
self.points['azRelSun'] = wrapRA(self.azs - self.sunAz)
if self.moon:
moon = ephem.Moon()
moon.compute(self.Observatory)
self.moonPhase = moon.phase
self.moonAlt = moon.alt
self.moonAz = moon.az
# Calc azimuth relative to moon
self.azRelMoon = wrapRA(self.azs - self.moonAz)
over = np.where(self.azRelMoon > np.pi)
self.azRelMoon[over] = 2. * np.pi - self.azRelMoon[over]
self.points['moonAltitude'] += np.degrees(self.moonAlt)
self.points['azRelMoon'] += self.azRelMoon
self.points['moonSunSep'] += self.moonPhase / 100. * 180.
if self.zodiacal:
self.eclipLon = np.zeros(self.npts)
self.eclipLat = np.zeros(self.npts)
for i, temp in enumerate(self.ra):
eclip = ephem.Ecliptic(
ephem.Equatorial(self.ra[i], self.dec[i], epoch='2000'))
self.eclipLon[i] += eclip.lon
self.eclipLat[i] += eclip.lat
# Subtract off the sun ecliptic longitude
sunEclip = ephem.Ecliptic(sun)
self.sunEclipLon = sunEclip.lon
self.points['altEclip'] += self.eclipLat
self.points['azEclipRelSun'] += wrapRA(self.eclipLon -
self.sunEclipLon)
maxID = np.max(maxID)
# Crop off some of the early junky observations
minMJD = 56900
minID,mjd = sb.allSkyDB(0,'select min(ID) from dates where mjd > %i;' % minMJD, dtypes='int')
altLimit = 10. # Degrees
sunAltLimit = np.radians(-20.)
maxID = 3000
step = 5
for dateID in np.arange(minID.max(),minID.max()+maxID+1, step):
sqlQ = 'select stars.ra, stars.dec, stars.ID, obs.starMag_inst, obs.starMag_err,obs.sky, obs.filter from obs, stars, dates where obs.starID = stars.ID and obs.dateID = dates.ID and obs.filter = "%s" and obs.dateID = %i and obs.starMag_err != 0 and dates.sunAlt < %f and obs.starMag_inst > %f;' % (filt,dateID,sunAltLimit, starBrightLimit)
# Note that RA,Dec are in degrees
data,mjd = sb.allSkyDB(dateID, sqlQ=sqlQ, dtypes=dtypes)
if data.size > nStarLimit:
alt,az,pa = _altAzPaFromRaDec(np.radians(data['ra']), np.radians(data['dec']),
telescope.lon, telescope.lat, mjd)
for i,nside in enumerate(nsides):
tempMap = healbin(az,alt, az*0+1, nside=nside, reduceFunc=np.size)[hpIndices[i]]
ratio = np.size(np.where(tempMap > 0)[0])/float(np.size(tempMap))
mapFractions[i].append(ratio)
print 'nside, resolution (deg), fraction of healpixes populated'
for mf,nside in zip(mapFractions,nsides):
resol = hp.nside2resol(nside, arcmin=True)/60.
print ' %i, %f, %f' % (nside, resol,np.median(mf))
def setRaDecMjd(self,
lon,
lat,
mjd,
degrees=False,
azAlt=False,
solarFlux=130.,
filterNames=['u', 'g', 'r', 'i', 'z', 'y']):
"""
Set the sky parameters by computing the sky conditions on a given MJD and sky location.
lon: Longitude-like (RA or Azimuth). Can be single number, list, or numpy array
lat: Latitude-like (Dec or Altitude)
mjd: Modified Julian Date for the calculation. Must be single number.
degrees: (False) Assumes lon and lat are radians unless degrees=True
azAlt: (False) Assume lon, lat are RA, Dec unless azAlt=True
solarFlux: solar flux in SFU Between 50 and 310. Default=130. 1 SFU=10^4 Jy.
filterNames: list of fitlers to return magnitudes for (if initialized with mags=True).
"""
self.filterNames = filterNames
if self.mags:
self.npix = len(self.filterNames)
# Wrap in array just in case single points were passed
if np.size(lon) == 1:
lon = np.array([lon]).ravel()
lat = np.array([lat]).ravel()
else:
lon = np.array(lon)
lat = np.array(lat)
if degrees:
self.ra = np.radians(lon)
self.dec = np.radians(lat)
else:
self.ra = lon
self.dec = lat
if np.size(mjd) > 1:
raise ValueError('mjd must be single value.')
self.mjd = mjd
if azAlt:
self.azs = self.ra.copy()
self.alts = self.dec.copy()
if self.preciseAltAz:
self.ra, self.dec = _raDecFromAltAz(
self.alts, self.azs,
ObservationMetaData(mjd=self.mjd, site=self.telescope))
else:
self.ra, self.dec = stupidFast_altAz2RaDec(
self.alts, self.azs, self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
else:
if self.preciseAltAz:
self.alts, self.azs, pa = _altAzPaFromRaDec(
self.ra, self.dec,
ObservationMetaData(mjd=self.mjd, site=self.telescope))
else:
self.alts, self.azs = stupidFast_RaDec2AltAz(
self.ra, self.dec, self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
self.npts = self.ra.size
self._initPoints()
self.solarFlux = solarFlux
self.points['solarFlux'] = self.solarFlux
self._setupPointGrid()
self.paramsSet = True
# Assume large airmasses are the same as airmass=2.5
to_fudge = np.where((self.points['airmass'] > 2.5)
& (self.points['airmass'] < self.airmassLimit))
self.points['airmass'][to_fudge] = 2.499
self.points['alt'][to_fudge] = np.pi / 2 - np.arccos(
1. / self.airmassLimit)
# Interpolate the templates to the set paramters
self._interpSky()
#maxID= 300
maxID = 9000
totalIDs = 0
IDsWithStars = 0
for dateID in np.arange(minID.max(), minID.max() + maxID + 1):
sqlQ = 'select stars.ra, stars.dec, stars.ID, obs.starMag_inst, obs.starMag_err,obs.sky, obs.filter from obs, stars, dates where obs.starID = stars.ID and obs.dateID = dates.ID and obs.filter = "%s" and obs.dateID = %i and obs.starMag_err != 0 and dates.sunAlt < %f and obs.starMag_inst > %f;' % (
filt, dateID, sunAltLimit, starBrightLimit)
totalIDs += 1
# Note that RA,Dec are in degrees
data, mjd = sb.allSkyDB(dateID, sqlQ=sqlQ, dtypes=dtypes)
if data.size > nStarLimit:
IDsWithStars += 1
alt, az, pa = _altAzPaFromRaDec(
np.radians(data['ra']), np.radians(data['dec']),
ObservationMetaData(mjd=mjd, site=telescope))
# Let's trim off any overly high airmass values
good = np.where(alt > np.radians(altLimit))
data = data[good]
hpids = hp.ang2pix(nside, np.pi / 2. - alt[good], az[good])
# Extend the lists
starIDs.extend(data['starID'].tolist())
dateIDs.extend([dateID] * np.size(data))
hpIDs.extend(hpids.tolist())
starMags.extend(data['starMag'].tolist())
starMags_err.extend(data['starMag_err'].tolist())
mjds.extend([mjd] * np.size(data))
airmasses.extend((1. / np.cos(np.pi / 2 - alt[good])).tolist())
left = np.searchsorted(data['mjd'], umjd)
right = np.searchsorted(data['mjd'], umjd, side='right')
altaz = np.zeros(data.size, dtype=zip(['alt','az'], [float]*2))
moonAlt = np.zeros(data.size, dtype=float)
print 'computing alts and azs'
for j, (le, ri, mjd) in enumerate(zip(left,right,umjd)):
Observatory.date = mjd2djd(mjd)
sun.compute(Observatory)
obs_metadata = ObservationMetaData(pointingRA=np.degrees(sun.ra),
pointingDec=np.degrees(sun.dec),
rotSkyPos=np.degrees(0),
mjd=mjd)
alt, az, pa = _altAzPaFromRaDec(data['ra'][le:ri], data['dec'][le:ri], obs_metadata)
az = wrapRA(az - sun.az)
altaz['alt'][le:ri] += alt
altaz['az'][le:ri] += az
moon.compute(Observatory)
moonAlt[le:ri] += moon.alt
print 'making maps'
good = np.where(moonAlt < 0)
magMap[:,i] = _healbin(altaz['az'][good],altaz['alt'][good], data['sky'][good],
nside=nside, reduceFunc=np.median)
rmsMap[:,i] = _healbin(altaz['az'][good],altaz['alt'][good],data['sky'][good],
nside=nside, reduceFunc=robustRMS)
print 'saving maps'
np.savez('TwilightMaps/twiMaps_%s.npz' % filterName, magMap=magMap, rmsMap=rmsMap, sunAlts=sunAlts)
altLimit = 10. # Degrees
sunAltLimit = np.radians(-20.)
maxID = 3000
step = 5
for dateID in np.arange(minID.max(), minID.max() + maxID + 1, step):
sqlQ = 'select stars.ra, stars.dec, stars.ID, obs.starMag_inst, obs.starMag_err,obs.sky, obs.filter from obs, stars, dates where obs.starID = stars.ID and obs.dateID = dates.ID and obs.filter = "%s" and obs.dateID = %i and obs.starMag_err != 0 and dates.sunAlt < %f and obs.starMag_inst > %f;' % (
filt, dateID, sunAltLimit, starBrightLimit)
# Note that RA,Dec are in degrees
data, mjd = sb.allSkyDB(dateID, sqlQ=sqlQ, dtypes=dtypes)
if data.size > nStarLimit:
alt, az, pa = _altAzPaFromRaDec(np.radians(data['ra']),
np.radians(data['dec']), telescope.lon,
telescope.lat, mjd)
for i, nside in enumerate(nsides):
tempMap = healbin(az,
alt,
az * 0 + 1,
nside=nside,
reduceFunc=np.size)[hpIndices[i]]
ratio = np.size(np.where(tempMap > 0)[0]) / float(np.size(tempMap))
mapFractions[i].append(ratio)
print 'nside, resolution (deg), fraction of healpixes populated'
for mf, nside in zip(mapFractions, nsides):
resol = hp.nside2resol(nside, arcmin=True) / 60.
print ' %i, %f, %f' % (nside, resol, np.median(mf))
def setRaDecMjd(self, lon, lat, mjd, degrees=False, azAlt=False, solarFlux=130.,
filterNames=['u', 'g', 'r', 'i', 'z', 'y']):
"""
Set the sky parameters by computing the sky conditions on a given MJD and sky location.
lon: Longitude-like (RA or Azimuth). Can be single number, list, or numpy array
lat: Latitude-like (Dec or Altitude)
mjd: Modified Julian Date for the calculation. Must be single number.
degrees: (False) Assumes lon and lat are radians unless degrees=True
azAlt: (False) Assume lon, lat are RA, Dec unless azAlt=True
solarFlux: solar flux in SFU Between 50 and 310. Default=130. 1 SFU=10^4 Jy.
filterNames: list of fitlers to return magnitudes for (if initialized with mags=True).
"""
self.filterNames = filterNames
if self.mags:
self.npix = len(self.filterNames)
# Wrap in array just in case single points were passed
if np.size(lon) == 1:
lon = np.array([lon]).ravel()
lat = np.array([lat]).ravel()
else:
lon = np.array(lon)
lat = np.array(lat)
if degrees:
self.ra = np.radians(lon)
self.dec = np.radians(lat)
else:
self.ra = lon
self.dec = lat
if np.size(mjd) > 1:
raise ValueError('mjd must be single value.')
self.mjd = mjd
if azAlt:
self.azs = self.ra.copy()
self.alts = self.dec.copy()
if self.preciseAltAz:
self.ra, self.dec = _raDecFromAltAz(self.alts, self.azs,
ObservationMetaData(mjd=self.mjd, site=self.telescope))
else:
self.ra, self.dec = _approx_altAz2RaDec(self.alts, self.azs,
self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
else:
if self.preciseAltAz:
self.alts, self.azs, pa = _altAzPaFromRaDec(self.ra, self.dec,
ObservationMetaData(mjd=self.mjd,
site=self.telescope))
else:
self.alts, self.azs = _approx_RaDec2AltAz(self.ra, self.dec,
self.telescope.latitude_rad,
self.telescope.longitude_rad, mjd)
self.npts = self.ra.size
self._initPoints()
self.solarFlux = solarFlux
self.points['solarFlux'] = self.solarFlux
self._setupPointGrid()
self.paramsSet = True
# Assume large airmasses are the same as airmass=2.5
to_fudge = np.where((self.points['airmass'] > 2.5) & (self.points['airmass'] < self.airmassLimit))
self.points['airmass'][to_fudge] = 2.499
self.points['alt'][to_fudge] = np.pi/2-np.arccos(1./self.airmassLimit)
# Interpolate the templates to the set paramters
self.goodPix = np.where((self.airmass <= self.airmassLimit) & (self.airmass >= 1.))[0]
if self.goodPix.size > 0:
self._interpSky()
else:
warnings.warn('No valid points to interpolate')
telescope = Site('LSST')
nside = 32
lat, ra = hp.pix2ang(nside, np.arange(hp.nside2npix(nside)))
dec = np.pi/2-lat
kwargs = dict(twilight=False, zodiacal=False, moon=True, scatteredStar=False, mergedSpec=False)
sm = sb.SkyModel(observatory='LSST', mags=True) # , **kwargs)
mjd = 49353.177645
sm.setRaDecMjd(ra, dec, mjd)
mag = sm.returnMags()
lmst, last = calcLmstLast(mjd, telescope.longitude_rad)
moonRA, moonDec = _raDecFromAltAz(sm.moonAlt, sm.moonAz, ObservationMetaData(mjd=mjd, site=telescope))
alt, az, pa = _altAzPaFromRaDec(ra, dec, ObservationMetaData(mjd=mjd, site=telescope))
angDist2Moon = np.degrees(haversine(az, alt, sm.moonAz, sm.moonAlt))
ang2 = np.degrees(haversine(ra, dec, moonRA, moonDec))
alt = np.degrees(alt)
mags = -0.5*(np.nanmin(mag['u'])-mag['u'])
#extent = (0,130, 0,90)
extent = (20, 120, 20, 90)
xs, ys = np.mgrid[extent[0]:extent[1], extent[2]:extent[3]]
resampled = griddata((angDist2Moon, alt), mags, (xs, ys))
notInf = np.where((resampled != np.inf) & (~np.isnan(resampled)))
resampled[notInf] = resampled[notInf]-resampled[notInf].max()
# Temp to speed things up
#maxID = 30000
#maxID= 300
maxID = 9000
totalIDs = 0
IDsWithStars = 0
for dateID in np.arange(minID.max(),minID.max()+maxID+1):
sqlQ = 'select stars.ra, stars.dec, stars.ID, obs.starMag_inst, obs.starMag_err,obs.sky, obs.filter from obs, stars, dates where obs.starID = stars.ID and obs.dateID = dates.ID and obs.filter = "%s" and obs.dateID = %i and obs.starMag_err != 0 and dates.sunAlt < %f and obs.starMag_inst > %f;' % (filt,dateID,sunAltLimit, starBrightLimit)
totalIDs += 1
# Note that RA,Dec are in degrees
data,mjd = sb.allSkyDB(dateID, sqlQ=sqlQ, dtypes=dtypes)
if data.size > nStarLimit:
IDsWithStars += 1
alt,az,pa = _altAzPaFromRaDec(np.radians(data['ra']), np.radians(data['dec']),
ObservationMetaData(mjd=mjd,site=telescope))
# Let's trim off any overly high airmass values
good = np.where(alt > np.radians(altLimit))
data = data[good]
hpids = hp.ang2pix(nside, np.pi/2.-alt[good], az[good])
# Extend the lists
starIDs.extend(data['starID'].tolist())
dateIDs.extend([dateID]*np.size(data))
hpIDs.extend(hpids.tolist())
starMags.extend(data['starMag'].tolist() )
starMags_err.extend( data['starMag_err'].tolist())
mjds.extend([mjd]* np.size(data))
airmasses.extend((1./np.cos(np.pi/2-alt[good])).tolist() )
print 'Finished reading data'
def setRaDecMjd(self,lon,lat,mjd,degrees=False,azAlt=False,solarFlux=130.):
"""
Set the sky parameters by computing the sky conditions on a given MJD and sky location.
Ra and Dec in raidans or degrees.
input ra, dec or az,alt w/ altAz=True
solarFlux: solar flux in s.f.u. Between 50 and 310.
"""
# Wrap in array just in case single points were passed
if not type(lon).__module__ == np.__name__ :
if np.size(lon) == 1:
lon = np.array([lon])
lat = np.array([lat])
else:
lon = np.array(lon)
lat = np.array(lat)
if degrees:
self.ra = np.radians(lon)
self.dec = np.radians(lat)
else:
self.ra = lon
self.dec = lat
self.mjd = mjd
if azAlt:
self.azs = self.ra.copy()
self.alts = self.dec.copy()
self.ra,self.dec = _raDecFromAltAz(self.alts,self.azs, self.Observatory.lon,
self.Observatory.lat, self.mjd)
else:
self.alts,self.azs,pa = _altAzPaFromRaDec(self.ra, self.dec, self.Observatory.lon,
self.Observatory.lat, self.mjd)
self.npts = self.ra.size
self._initPoints()
self.solarFlux = solarFlux
self.points['solarFlux'] = self.solarFlux
# Switch to Dublin Julian Date for pyephem
self.Observatory.date = mjd2djd(self.mjd)
sun = ephem.Sun()
sun.compute(self.Observatory)
self.sunAlt = sun.alt
self.sunAz = sun.az
# Compute airmass the same way as ESO model
self.airmass = 1./np.cos(np.pi/2.-self.alts)
self.points['airmass'] = self.airmass
self.points['nightTimes'] = 2
self.points['alt'] = self.alts
self.points['az'] = self.azs
if self.twilight:
self.points['sunAlt'] = self.sunAlt
self.points['azRelSun'] = wrapRA(self.azs - self.sunAz)
if self.moon:
moon = ephem.Moon()
moon.compute(self.Observatory)
self.moonPhase = moon.phase
self.moonAlt = moon.alt
self.moonAz = moon.az
# Calc azimuth relative to moon
self.azRelMoon = wrapRA(self.azs - self.moonAz)
over = np.where(self.azRelMoon > np.pi)
self.azRelMoon[over] = 2.*np.pi - self.azRelMoon[over]
self.points['moonAltitude'] += np.degrees(self.moonAlt)
self.points['azRelMoon'] += self.azRelMoon
self.points['moonSunSep'] += self.moonPhase/100.*180.
if self.zodiacal:
self.eclipLon = np.zeros(self.npts)
self.eclipLat = np.zeros(self.npts)
for i,temp in enumerate(self.ra):
eclip = ephem.Ecliptic(ephem.Equatorial(self.ra[i],self.dec[i], epoch='2000'))
self.eclipLon[i] += eclip.lon
self.eclipLat[i] += eclip.lat
# Subtract off the sun ecliptic longitude
sunEclip = ephem.Ecliptic(sun)
self.sunEclipLon = sunEclip.lon
self.points['altEclip'] += self.eclipLat
self.points['azEclipRelSun'] += wrapRA(self.eclipLon - self.sunEclipLon)
kwargs = dict(twilight=False,
zodiacal=False,
moon=True,
scatteredStar=False,
mergedSpec=False)
sm = sb.SkyModel(observatory='LSST', mags=True) # , **kwargs)
mjd = 49353.177645
sm.setRaDecMjd(ra, dec, mjd)
mag = sm.returnMags()
lmst, last = calcLmstLast(mjd, telescope.longitude_rad)
moonRA, moonDec = _raDecFromAltAz(sm.moonAlt, sm.moonAz,
ObservationMetaData(mjd=mjd, site=telescope))
alt, az, pa = _altAzPaFromRaDec(ra, dec,
ObservationMetaData(mjd=mjd, site=telescope))
angDist2Moon = np.degrees(haversine(az, alt, sm.moonAz, sm.moonAlt))
ang2 = np.degrees(haversine(ra, dec, moonRA, moonDec))
alt = np.degrees(alt)
mags = -0.5 * (np.nanmin(mag['u']) - mag['u'])
#extent = (0,130, 0,90)
extent = (20, 120, 20, 90)
xs, ys = np.mgrid[extent[0]:extent[1], extent[2]:extent[3]]
resampled = griddata((angDist2Moon, alt), mags, (xs, ys))
notInf = np.where((resampled != np.inf) & (~np.isnan(resampled)))
resampled[notInf] = resampled[notInf] - resampled[notInf].max()
left = np.searchsorted(data['mjd'], umjd)
right = np.searchsorted(data['mjd'], umjd, side='right')
altaz = np.zeros(data.size, dtype=list(zip(['alt', 'az'], [float]*2)))
moonAlt = np.zeros(data.size, dtype=float)
print('computing alts and azs')
for j, (le, ri, mjd) in enumerate(zip(left, right, umjd)):
Observatory.date = mjd2djd(mjd)
sun.compute(Observatory)
obs_metadata = ObservationMetaData(pointingRA=np.degrees(sun.ra),
pointingDec=np.degrees(sun.dec),
rotSkyPos=np.degrees(0),
mjd=mjd)
alt, az, pa = _altAzPaFromRaDec(data['ra'][le:ri], data['dec'][le:ri], obs_metadata)
az = wrapRA(az - sun.az)
altaz['alt'][le:ri] += alt
altaz['az'][le:ri] += az
moon.compute(Observatory)
moonAlt[le:ri] += moon.alt
print('making maps')
good = np.where(moonAlt < 0)
magMap[:, i] = _healbin(altaz['az'][good], altaz['alt'][good], data['sky'][good],
nside=nside, reduceFunc=np.median)
rmsMap[:, i] = _healbin(altaz['az'][good], altaz['alt'][good], data['sky'][good],
nside=nside, reduceFunc=robustRMS)
print('saving maps')
np.savez('TwilightMaps/twiMaps_%s.npz' % filterName, magMap=magMap, rmsMap=rmsMap, sunAlts=sunAlts)