def points(self,npoints):
"""
compute arrays of npoints equally spaced
intermediate points along the great circle.
input parameter npoints is the number of points
to compute.
Returns lons, lats (lists with longitudes and latitudes
of intermediate points in degrees).
For example npoints=10 will return arrays lons,lats of 10
equally spaced points along the great circle.
"""
# can't do it if endpoints of great circle are antipodal, since
# route is undefined.
if self.antipodal:
raise ValueError,'cannot compute intermediate points on a great circle whose endpoints are antipodal'
d = self.distance
delta = 1.0/(npoints-1)
f = delta*N.arange(npoints)
lat1 = self.lat1
lat2 = self.lat2
lon1 = self.lon1
lon2 = self.lon2
A = N.sin((1-f)*d)/math.sin(d)
B = N.sin(f*d)/math.sin(d)
x = A*math.cos(lat1)*math.cos(lon1)+B*math.cos(lat2)*math.cos(lon2)
y = A*math.cos(lat1)*math.sin(lon1)+B*math.cos(lat2)*math.sin(lon2)
z = A*math.sin(lat1) +B*math.sin(lat2)
lats=N.arctan2(z,N.sqrt(x**2+y**2))
lons=N.arctan2(y,x)
lons = map(math.degrees,lons.tolist())
lats = map(math.degrees,lats.tolist())
return lons,lats
def points(self,npoints):
"""
compute arrays of npoints equally spaced
intermediate points along the great circle.
input parameter npoints is the number of points
to compute.
Returns lons, lats (lists with longitudes and latitudes
of intermediate points in degrees).
For example npoints=10 will return arrays lons,lats of 10
equally spaced points along the great circle.
"""
# must ask for at least 2 points.
if npoints <= 1:
raise ValueError,'npoints must be greater than 1'
elif npoints == 2:
return [math.degrees(self.lon1),math.degrees(self.lon2)],[math.degrees(self.lat1),math.degrees(self.lat2)]
# can't do it if endpoints are antipodal, since
# route is undefined.
if self.antipodal:
raise ValueError,'cannot compute intermediate points on a great circle whose endpoints are antipodal'
d = self.gcarclen
delta = 1.0/(npoints-1)
f = delta*N.arange(npoints) # f=0 is point 1, f=1 is point 2.
incdist = self.distance/(npoints-1)
lat1 = self.lat1
lat2 = self.lat2
lon1 = self.lon1
lon2 = self.lon2
# perfect sphere, use great circle formula
if self.f == 0.:
A = N.sin((1-f)*d)/math.sin(d)
B = N.sin(f*d)/math.sin(d)
x = A*math.cos(lat1)*math.cos(lon1)+B*math.cos(lat2)*math.cos(lon2)
y = A*math.cos(lat1)*math.sin(lon1)+B*math.cos(lat2)*math.sin(lon2)
z = A*math.sin(lat1) +B*math.sin(lat2)
lats=N.arctan2(z,N.sqrt(x**2+y**2))
lons=N.arctan2(y,x)
lons = map(math.degrees,lons.tolist())
lats = map(math.degrees,lats.tolist())
# use ellipsoid formulas
else:
latpt = self.lat1
lonpt = self.lon1
azimuth = self.azimuth12
lons = [math.degrees(lonpt)]
lats = [math.degrees(latpt)]
for n in range(npoints-2):
latptnew,lonptnew,alpha21=vinc_pt(self.f,self.a,latpt,lonpt,azimuth,incdist)
d,azimuth,a21=vinc_dist(self.f,self.a,latptnew,lonptnew,lat2,lon2)
lats.append(math.degrees(latptnew))
lons.append(math.degrees(lonptnew))
latpt = latptnew; lonpt = lonptnew
lons.append(math.degrees(self.lon2))
lats.append(math.degrees(self.lat2))
return lons,lats
def rd2xy(self, skypos, hour=no):
"""
This method would use the WCS keywords to compute the XY position
from a given RA/Dec tuple (in deg).
NOTE: Investigate how to let this function accept arrays as well
as single positions. WJH 27Mar03
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'RD2XY only supported for TAN projections.'
raise TypeError
det = self.cd11 * self.cd22 - self.cd12 * self.cd21
if det == 0.0:
raise ArithmeticError, "singular CD matrix!"
cdinv11 = self.cd22 / det
cdinv12 = -self.cd12 / det
cdinv21 = -self.cd21 / det
cdinv22 = self.cd11 / det
# translate (ra, dec) to (x, y)
ra0 = DEGTORAD(self.crval1)
dec0 = DEGTORAD(self.crval2)
if hour:
skypos[0] = skypos[0] * 15.
ra = DEGTORAD(skypos[0])
dec = DEGTORAD(skypos[1])
bottom = float(
N.sin(dec) * N.sin(dec0) +
N.cos(dec) * N.cos(dec0) * N.cos(ra - ra0))
if bottom == 0.0:
raise ArithmeticError, "Unreasonable RA/Dec range!"
xi = RADTODEG((N.cos(dec) * N.sin(ra - ra0) / bottom))
eta = RADTODEG((N.sin(dec) * N.cos(dec0) -
N.cos(dec) * N.sin(dec0) * N.cos(ra - ra0)) / bottom)
x = cdinv11 * xi + cdinv12 * eta + self.crpix1
y = cdinv21 * xi + cdinv22 * eta + self.crpix2
return x, y
def xy2rd(self, pos):
"""
This method would apply the WCS keywords to a position to
generate a new sky position.
The algorithm comes directly from 'imgtools.xy2rd'
translate (x,y) to (ra, dec)
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'XY2RD only supported for TAN projections.'
raise TypeError
if isinstance(pos, N.NumArray):
# If we are working with an array of positions,
# point to just X and Y values
posx = pos[:, 0]
posy = pos[:, 1]
else:
# Otherwise, we are working with a single X,Y tuple
posx = pos[0]
posy = pos[1]
xi = self.cd11 * (posx - self.crpix1) + self.cd12 * (posy -
self.crpix2)
eta = self.cd21 * (posx - self.crpix1) + self.cd22 * (posy -
self.crpix2)
xi = DEGTORAD(xi)
eta = DEGTORAD(eta)
ra0 = DEGTORAD(self.crval1)
dec0 = DEGTORAD(self.crval2)
ra = N.arctan((xi / (N.cos(dec0) - eta * N.sin(dec0)))) + ra0
dec = N.arctan(
((eta * N.cos(dec0) + N.sin(dec0)) /
(N.sqrt((N.cos(dec0) - eta * N.sin(dec0))**2 + xi**2))))
ra = RADTODEG(ra)
dec = RADTODEG(dec)
ra = DIVMOD(ra, 360.)
# Otherwise, just return the RA,Dec tuple.
return ra, dec
def rd2xy(self,skypos,hour=no):
"""
This method would use the WCS keywords to compute the XY position
from a given RA/Dec tuple (in deg).
NOTE: Investigate how to let this function accept arrays as well
as single positions. WJH 27Mar03
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'RD2XY only supported for TAN projections.'
raise TypeError
det = self.cd11*self.cd22 - self.cd12*self.cd21
if det == 0.0:
raise ArithmeticError,"singular CD matrix!"
cdinv11 = self.cd22 / det
cdinv12 = -self.cd12 / det
cdinv21 = -self.cd21 / det
cdinv22 = self.cd11 / det
# translate (ra, dec) to (x, y)
ra0 = DEGTORAD(self.crval1)
dec0 = DEGTORAD(self.crval2)
if hour:
skypos[0] = skypos[0] * 15.
ra = DEGTORAD(skypos[0])
dec = DEGTORAD(skypos[1])
bottom = float(N.sin(dec)*N.sin(dec0) + N.cos(dec)*N.cos(dec0)*N.cos(ra-ra0))
if bottom == 0.0:
raise ArithmeticError,"Unreasonable RA/Dec range!"
xi = RADTODEG((N.cos(dec) * N.sin(ra-ra0) / bottom))
eta = RADTODEG((N.sin(dec)*N.cos(dec0) - N.cos(dec)*N.sin(dec0)*N.cos(ra-ra0)) / bottom)
x = cdinv11 * xi + cdinv12 * eta + self.crpix1
y = cdinv21 * xi + cdinv22 * eta + self.crpix2
return x,y
def getSineWave(freq, samplecount=320):
""" Generate a sine wave of frequency 'freq'. The samples are
generated at 8khz. The first 'samplecount' samples will be
returned.
"""
from numarray import sin, arange
from math import pi
sine = sin(arange(HZ)/(HZ/freq) * 2.0 * pi)
sine = sine[:samplecount]
return sine
def xy2rd(filename, x,y,hdu = -1, hms = 0, verbose = 0):
from numarray import sin,cos,arctan2,sqrt
def degtorad(num):
return num/180.0*numarray.pi
def radtodeg(num):
return num/numarray.pi * 180.0
def degtoHMS(num):
mmm = int((num-int(num))*60.0)
sss = ((num-int(num))*60.0-mmm)*60.0
num = `int(num)`+":"+ `mmm`+":"+`sss`
return num
keys = ["CRPIX1","CRPIX2","CRVAL1","CRVAL2","CD1_1","CD1_2","CD2_1","CD2_2"]
CD = read_keys(filename,keys,hdu)
crpix = numarray.zeros((2),numarray.Float)
cd = numarray.zeros((2,2),numarray.Float)
crpix[0] = CD['CRPIX1'][0]
crpix[1] = CD['CRPIX2'][0]
ra0 = CD['CRVAL1'][0]
dec0 = CD['CRVAL2'][0]
cd[0,0] = CD['CD1_1'][0]
cd[0,1] = CD['CD1_2'][0]
cd[1,0] = CD['CD2_1'][0]
cd[1,1] = CD['CD2_2'][0]
xi = cd[0, 0] * (x - crpix[0]) + cd[0, 1] * (y - crpix[1])
eta = cd[1, 0] * (x - crpix[0]) + cd[1, 1] * (y - crpix[1])
xi = degtorad(xi)
eta = degtorad(eta)
ra0 = degtorad(ra0)
dec0 = degtorad(dec0)
ra = arctan2(xi,cos(dec0)-eta*sin(dec0)) + ra0
dec = arctan2(eta*cos(dec0)+sin(dec0),sqrt((cos(dec0)-eta*sin(dec0))**2 + xi**2))
ra = radtodeg(ra)# % 360.0
# if ra < 0: ra = ra + 360.0
dec = radtodeg(dec)
if (hms):
return degtoHMS(ra/15.0),degtoHMS(dec)
else:
return ra,dec
def getSineWave(freq, samplecount=320):
""" Generate a sine wave of frequency 'freq'. The samples are
generated at 8khz. The first 'samplecount' samples will be
returned.
"""
from numarray import sin, arange
from math import pi
sine = sin(arange(HZ)/(HZ/freq) * 2.0 * pi)
sine = sine[:samplecount]
return sine
def rd2xy(filename,ra,dec,verbose=0,hdu=-1,hour=0):
from numarray import sin,cos,arctan2,sqrt
def degtorad(num):
return num/180.0*numarray.pi
def radtodeg(num):
return num/numarray.pi * 180.0
keys = ["CRPIX1","CRPIX2","CRVAL1","CRVAL2","CD1_1","CD1_2","CD2_1","CD2_2"]
CD = read_keys(filename,keys,hdu)
crpix = numarray.zeros((2),numarray.Float)
cd = numarray.zeros((2,2),numarray.Float)
cdinv = numarray.zeros((2,2),numarray.Float)
crpix[0] = CD['CRPIX1'][0]
crpix[1] = CD['CRPIX2'][0]
ra0 = CD['CRVAL1'][0]
dec0 = CD['CRVAL2'][0]
cd[0,0] = CD['CD1_1'][0]
cd[0,1] = CD['CD1_2'][0]
cd[1,0] = CD['CD2_1'][0]
cd[1,1] = CD['CD2_2'][0]
det = cd[0,0]*cd[1,1] - cd[0,1]*cd[1,0]
if det == 0:
raise SingularMatrix
cdinv[0,0] = cd[1,1] / det
cdinv[0,1] = -cd[0,1] / det
cdinv[1,0] = -cd[1,0] / det
cdinv[1,1] = cd[0,0] / det
print det,cdinv
ra0 = degtorad(ra0)
dec0 = degtorad(dec0)
if hour: ra=ra*15.0
ra = degtorad(ra)
dec = degtorad(dec)
bottom = sin(dec)*sin(dec0) + cos(dec)*cos(dec0)*cos(ra-ra0)
if bottom == 0:
raise InvalidRaDecRange
xi = cos(dec) * sin(ra-ra0) / bottom
eta = (sin(dec)*cos(dec0) - cos(dec)*sin(dec0)*cos(ra-ra0)) / bottom
xi = radtodeg(xi)
eta = radtodeg(eta)
x = cdinv[0, 0] * xi + cdinv[0, 1] * eta + crpix[0]
y = cdinv[1, 0] * xi + cdinv[1, 1] * eta + crpix[1]
return x,y
def xy2rd(self,pos):
"""
This method would apply the WCS keywords to a position to
generate a new sky position.
The algorithm comes directly from 'imgtools.xy2rd'
translate (x,y) to (ra, dec)
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'XY2RD only supported for TAN projections.'
raise TypeError
if isinstance(pos,N.NumArray):
# If we are working with an array of positions,
# point to just X and Y values
posx = pos[:,0]
posy = pos[:,1]
else:
# Otherwise, we are working with a single X,Y tuple
posx = pos[0]
posy = pos[1]
xi = self.cd11 * (posx - self.crpix1) + self.cd12 * (posy - self.crpix2)
eta = self.cd21 * (posx - self.crpix1) + self.cd22 * (posy - self.crpix2)
xi = DEGTORAD(xi)
eta = DEGTORAD(eta)
ra0 = DEGTORAD(self.crval1)
dec0 = DEGTORAD(self.crval2)
ra = N.arctan((xi / (N.cos(dec0)-eta*N.sin(dec0)))) + ra0
dec = N.arctan( ((eta*N.cos(dec0)+N.sin(dec0)) /
(N.sqrt((N.cos(dec0)-eta*N.sin(dec0))**2 + xi**2))) )
ra = RADTODEG(ra)
dec = RADTODEG(dec)
ra = DIVMOD(ra, 360.)
# Otherwise, just return the RA,Dec tuple.
return ra,dec
def psf_select(alpha_j, delta_j):
distance = 9999.0
psffile = 'test.fits'
psflist = c.psflist
r = 3.14159265 / 180.0
for element in psflist:
p=pyfits.open(element)
header = p[0].header
if (header.has_key('RA_TARG')):
ra = header['RA_TARG']
if (header.has_key('DEC_TARG')):
dec= header['DEC_TARG']
p.close()
# d = sqrt((ra - alpha_j) ** 2.0 + (dec - delta_j) ** 2.0)
d = n.arccos(n.cos((90.0 - delta_j) * r) * n.cos((90.0 - dec) *\
r) + n.sin((90.0 - delta_j) * r) * n.sin((90.0 - dec) * r) * \
n.cos((alpha_j - ra) * r))
if(d < distance):
psffile = element
distance = d
return psffile, distance
def points(self, npoints):
"""
compute arrays of npoints equally spaced
intermediate points along the great circle.
input parameter npoints is the number of points
to compute.
Returns lons, lats (lists with longitudes and latitudes
of intermediate points in degrees).
For example npoints=10 will return arrays lons,lats of 10
equally spaced points along the great circle.
"""
# can't do it if endpoints of great circle are antipodal, since
# route is undefined.
if self.antipodal:
raise ValueError, 'cannot compute intermediate points on a great circle whose endpoints are antipodal'
d = self.distance
delta = 1.0 / (npoints - 1)
f = delta * N.arange(npoints)
lat1 = self.lat1
lat2 = self.lat2
lon1 = self.lon1
lon2 = self.lon2
A = N.sin((1 - f) * d) / math.sin(d)
B = N.sin(f * d) / math.sin(d)
x = A * math.cos(lat1) * math.cos(lon1) + B * math.cos(
lat2) * math.cos(lon2)
y = A * math.cos(lat1) * math.sin(lon1) + B * math.cos(
lat2) * math.sin(lon2)
z = A * math.sin(lat1) + B * math.sin(lat2)
lats = N.arctan2(z, N.sqrt(x**2 + y**2))
lons = N.arctan2(y, x)
lons = map(math.degrees, lons.tolist())
lats = map(math.degrees, lats.tolist())
return lons, lats
def mask(clus_id, line_s):
imagefile = c.imagefile
sex_cata = c.sex_cata
clus_cata = c.out_cata
threshold = c.threshold
thresh_area = c.thresh_area
size = c.size
mask_reg = c.mask_reg
x = n.reshape(n.arange(size*size),(size,size)) % size
x = x.astype(n.Float32)
y = n.reshape(n.arange(size*size),(size,size)) / size
y = y.astype(n.Float32)
values = line_s.split()
mask_file = 'ell_mask_' + str(imagefile)[:6] + '_' + str(clus_id) + '.fits'
xcntr_o = float(values[1]) #x center of the object
ycntr_o = float(values[2]) #y center of the object
xcntr = size / 2.0 + 1.0 + xcntr_o - int(xcntr_o)
ycntr = size / 2.0 + 1.0 + ycntr_o - int(ycntr_o)
mag = float(values[7]) #Magnitude
radius = float(values[9]) #Half light radius
mag_zero = c.mag_zero #magnitude zero point
sky = float(values[10]) #sky
pos_ang = float(values[11]) - 90.0 #position angle
axis_rat = 1.0 / float(values[12]) #axis ration b/a
major_axis = float(values[14]) #major axis of the object
z = n.zeros((size,size))
for line_j in open(sex_cata,'r'):
try:
values = line_j.split()
xcntr_n = float(values[1]) #x center of the neighbour
ycntr_n = float(values[2]) #y center of the neighbour
mag = float(values[7]) #Magnitude
radius = float(values[9]) #Half light radius
sky = float(values[10]) #sky
pos_ang = float(values[11]) #position angle
axis_rat = 1.0/float(values[12]) #axis ration b/a
si = n.sin(pos_ang * n.pi / 180.0)
co = n.cos(pos_ang * n.pi / 180.0)
area = float(values[13])
maj_axis = float(values[14])#major axis of neighbour
eg = 1.0 - axis_rat
one_minus_eg_sq = (1.0-eg)**2.0
if(abs(xcntr_n - xcntr_o) < size/2.0 and \
abs(ycntr_n - ycntr_o) < size/2.0 and \
xcntr_n != xcntr_o and ycntr_n != ycntr_o):
if((xcntr_o - xcntr_n) < 0):
xn = xcntr + abs(xcntr_n - xcntr_o)
if((ycntr_o - ycntr_n) < 0):
yn = ycntr + abs(ycntr_n - ycntr_o)
if((xcntr_o - xcntr_n) > 0):
xn = xcntr - (xcntr_o -xcntr_n)
if((ycntr_o - ycntr_n) > 0):
yn = ycntr - (ycntr_o -ycntr_n)
tx = (x - xn + 0.5) * co + (y - yn + 0.5) * si
ty = (xn - 0.5 -x) * si + (y - yn + 0.5) * co
R = n.sqrt(tx**2.0 + ty**2.0 / one_minus_eg_sq)
z[n.where(R<=mask_reg*maj_axis)] = 1
except:
i=1
hdu = pyfits.PrimaryHDU(z.astype(n.Float32))
hdu.writeto(mask_file)
def points(self, npoints):
"""
compute arrays of npoints equally spaced
intermediate points along the great circle.
input parameter npoints is the number of points
to compute.
Returns lons, lats (lists with longitudes and latitudes
of intermediate points in degrees).
For example npoints=10 will return arrays lons,lats of 10
equally spaced points along the great circle.
"""
# must ask for at least 2 points.
if npoints <= 1:
raise ValueError, 'npoints must be greater than 1'
elif npoints == 2:
return [math.degrees(self.lon1),
math.degrees(self.lon2)
], [math.degrees(self.lat1),
math.degrees(self.lat2)]
# can't do it if endpoints are antipodal, since
# route is undefined.
if self.antipodal:
raise ValueError, 'cannot compute intermediate points on a great circle whose endpoints are antipodal'
d = self.gcarclen
delta = 1.0 / (npoints - 1)
f = delta * N.arange(npoints) # f=0 is point 1, f=1 is point 2.
incdist = self.distance / (npoints - 1)
lat1 = self.lat1
lat2 = self.lat2
lon1 = self.lon1
lon2 = self.lon2
# perfect sphere, use great circle formula
if self.f == 0.:
A = N.sin((1 - f) * d) / math.sin(d)
B = N.sin(f * d) / math.sin(d)
x = A * math.cos(lat1) * math.cos(lon1) + B * math.cos(
lat2) * math.cos(lon2)
y = A * math.cos(lat1) * math.sin(lon1) + B * math.cos(
lat2) * math.sin(lon2)
z = A * math.sin(lat1) + B * math.sin(lat2)
lats = N.arctan2(z, N.sqrt(x**2 + y**2))
lons = N.arctan2(y, x)
lons = map(math.degrees, lons.tolist())
lats = map(math.degrees, lats.tolist())
# use ellipsoid formulas
else:
latpt = self.lat1
lonpt = self.lon1
azimuth = self.azimuth12
lons = [math.degrees(lonpt)]
lats = [math.degrees(latpt)]
for n in range(npoints - 2):
latptnew, lonptnew, alpha21 = vinc_pt(self.f, self.a, latpt,
lonpt, azimuth, incdist)
d, azimuth, a21 = vinc_dist(self.f, self.a, latptnew, lonptnew,
lat2, lon2)
lats.append(math.degrees(latptnew))
lons.append(math.degrees(lonptnew))
latpt = latptnew
lonpt = lonptnew
lons.append(math.degrees(self.lon2))
lats.append(math.degrees(self.lat2))
return lons, lats
def HookModel( elevs , c , fsin , fcos ):
return c+ fsin * numarray.sin(elevs * math.pi / 180 ) + fcos * numarray.cos(elevs * math.pi / 180 )
def recenter(self):
"""
Reset the reference position values to correspond to the center
of the reference frame.
Algorithm used here developed by Colin Cox - 27-Jan-2004.
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'WCS.recenter() only supported for TAN projections.'
raise TypeError
# Check to see if WCS is already centered...
if self.crpix1 == self.naxis1 / 2. and self.crpix2 == self.naxis2 / 2.:
# No recentering necessary... return without changing WCS.
return
# This offset aligns the WCS to the center of the pixel, in accordance
# with the 'align=center' option used by 'drizzle'.
#_drz_off = -0.5
_drz_off = 0.
_cen = (self.naxis1 / 2. + _drz_off, self.naxis2 / 2. + _drz_off)
# Compute the RA and Dec for center pixel
_cenrd = self.xy2rd(_cen)
_cd = N.array([[self.cd11, self.cd12], [self.cd21, self.cd22]],
type=N.Float64)
_ra0 = DEGTORAD(self.crval1)
_dec0 = DEGTORAD(self.crval2)
_ra = DEGTORAD(_cenrd[0])
_dec = DEGTORAD(_cenrd[1])
# Set up some terms for use in the final result
_dx = self.naxis1 / 2. - self.crpix1
_dy = self.naxis2 / 2. - self.crpix2
_dE, _dN = DEGTORAD(N.dot(_cd, (_dx, _dy)))
_dE_dN = 1 + N.power(_dE, 2) + N.power(_dN, 2)
_cosdec = N.cos(_dec)
_sindec = N.sin(_dec)
_cosdec0 = N.cos(_dec0)
_sindec0 = N.sin(_dec0)
_n1 = N.power(_cosdec, 2) + _dE * _dE + _dN * _dN * N.power(_sindec, 2)
_dra_dE = (_cosdec0 - _dN * _sindec0) / _n1
_dra_dN = _dE * _sindec0 / _n1
_ddec_dE = -_dE * N.tan(_dec) / _dE_dN
_ddec_dN = (1 / _cosdec) * ((_cosdec0 / N.sqrt(_dE_dN)) -
(_dN * N.sin(_dec) / _dE_dN))
# Compute new CD matrix values now...
_cd11n = _cosdec * (self.cd11 * _dra_dE + self.cd21 * _dra_dN)
_cd12n = _cosdec * (self.cd12 * _dra_dE + self.cd22 * _dra_dN)
_cd21n = self.cd11 * _ddec_dE + self.cd21 * _ddec_dN
_cd22n = self.cd12 * _ddec_dE + self.cd22 * _ddec_dN
_new_orient = RADTODEG(N.arctan2(_cd12n, _cd22n))
# Update the values now...
self.crpix1 = _cen[0]
self.crpix2 = _cen[1]
self.crval1 = RADTODEG(_ra)
self.crval2 = RADTODEG(_dec)
# Keep the same plate scale, only change the orientation
self.rotateCD(_new_orient)
# These would update the CD matrix with the new rotation
# ALONG with the new plate scale which we do not want.
self.cd11 = _cd11n
self.cd12 = _cd12n
self.cd21 = _cd21n
self.cd22 = _cd22n
def recenter(self):
"""
Reset the reference position values to correspond to the center
of the reference frame.
Algorithm used here developed by Colin Cox - 27-Jan-2004.
"""
if self.ctype1.find('TAN') < 0 or self.ctype2.find('TAN') < 0:
print 'WCS.recenter() only supported for TAN projections.'
raise TypeError
# Check to see if WCS is already centered...
if self.crpix1 == self.naxis1/2. and self.crpix2 == self.naxis2/2.:
# No recentering necessary... return without changing WCS.
return
# This offset aligns the WCS to the center of the pixel, in accordance
# with the 'align=center' option used by 'drizzle'.
#_drz_off = -0.5
_drz_off = 0.
_cen = (self.naxis1/2.+ _drz_off,self.naxis2/2. + _drz_off)
# Compute the RA and Dec for center pixel
_cenrd = self.xy2rd(_cen)
_cd = N.array([[self.cd11,self.cd12],[self.cd21,self.cd22]],type=N.Float64)
_ra0 = DEGTORAD(self.crval1)
_dec0 = DEGTORAD(self.crval2)
_ra = DEGTORAD(_cenrd[0])
_dec = DEGTORAD(_cenrd[1])
# Set up some terms for use in the final result
_dx = self.naxis1/2. - self.crpix1
_dy = self.naxis2/2. - self.crpix2
_dE,_dN = DEGTORAD(N.dot(_cd,(_dx,_dy)))
_dE_dN = 1 + N.power(_dE,2) + N.power(_dN,2)
_cosdec = N.cos(_dec)
_sindec = N.sin(_dec)
_cosdec0 = N.cos(_dec0)
_sindec0 = N.sin(_dec0)
_n1 = N.power(_cosdec,2) + _dE*_dE + _dN*_dN*N.power(_sindec,2)
_dra_dE = (_cosdec0 - _dN*_sindec0)/_n1
_dra_dN = _dE*_sindec0 /_n1
_ddec_dE = -_dE*N.tan(_dec) / _dE_dN
_ddec_dN = (1/_cosdec) * ((_cosdec0 / N.sqrt(_dE_dN)) - (_dN*N.sin(_dec) / _dE_dN))
# Compute new CD matrix values now...
_cd11n = _cosdec * (self.cd11*_dra_dE + self.cd21 * _dra_dN)
_cd12n = _cosdec * (self.cd12*_dra_dE + self.cd22 * _dra_dN)
_cd21n = self.cd11 * _ddec_dE + self.cd21 * _ddec_dN
_cd22n = self.cd12 * _ddec_dE + self.cd22 * _ddec_dN
_new_orient = RADTODEG(N.arctan2(_cd12n,_cd22n))
# Update the values now...
self.crpix1 = _cen[0]
self.crpix2 = _cen[1]
self.crval1 = RADTODEG(_ra)
self.crval2 = RADTODEG(_dec)
# Keep the same plate scale, only change the orientation
self.rotateCD(_new_orient)
# These would update the CD matrix with the new rotation
# ALONG with the new plate scale which we do not want.
self.cd11 = _cd11n
self.cd12 = _cd12n
self.cd21 = _cd21n
self.cd22 = _cd22n