def fftFromLiteMap(liteMap,applySlepianTaper = False,nresForSlepian=3.0):
"""
@brief Creates an fft2D object out of a liteMap
@param liteMap The map whose fft is being taken
@param applySlepianTaper If True applies the lowest order taper (to minimize edge-leakage)
@param nresForSlepian If above is True, specifies the resolution of the taeper to use.
"""
ft = fft2D()
ft.Nx = liteMap.Nx
ft.Ny = liteMap.Ny
flTrace.issue("flipper.fftTools",1, "Taking FFT of map with (Ny,Nx)= (%f,%f)"%(ft.Ny,ft.Nx))
ft.pixScaleX = liteMap.pixScaleX
ft.pixScaleY = liteMap.pixScaleY
lx = 2*np.pi * fftfreq( ft.Nx, d = ft.pixScaleX )
ly = 2*np.pi * fftfreq( ft.Ny, d = ft.pixScaleY )
ix = np.mod(np.arange(ft.Nx*ft.Ny),ft.Nx)
iy = np.arange(ft.Nx*ft.Ny)/ft.Nx
modLMap = np.zeros([ft.Ny,ft.Nx])
modLMap[iy,ix] = np.sqrt(lx[ix]**2 + ly[iy]**2)
ft.modLMap = modLMap
ft.lx = lx
ft.ly = ly
ft.ix = ix
ft.iy = iy
ft.thetaMap = np.zeros([ft.Ny,ft.Nx])
ft.thetaMap[iy[:],ix[:]] = np.arctan2(ly[iy[:]],lx[ix[:]])
ft.thetaMap *=180./np.pi
map = liteMap.data.copy()
#map = map0.copy()
#map[:,:] =map0[::-1,:]
taper = map.copy()*0.0 + 1.0
if (applySlepianTaper) :
try:
path_to_taper = os.path.join(__FLIPPER_DIR__, "tapers", 'taper_Ny%d_Nx%d_Nres%3.1f'%(ft.Ny,ft.Nx,nresForSlepian))
f = open(path_to_taper)
taper = pickle.load(f)
f.close()
except:
taper = slepianTaper00(ft.Nx,ft.Ny,nresForSlepian)
path_to_taper = os.path.join(__FLIPPER_DIR__, "tapers", 'taper_Ny%d_Nx%d_Nres%3.1f'%(ft.Ny,ft.Nx,nresForSlepian))
f = open(path_to_taper, mode="w")
pickle.dump(taper,f)
f.close()
ft.kMap = fftfast.fft(map*taper,axes=[-2,-1])
del map, modLMap, lx, ly
return ft
def apply(self,ltMap):
discDiffMap = discDifference(self.radius,ltMap,\
discKern1=self.discKern1,\
discKern3=self.discKern3)
flTrace.issue("flipper.prewhitener",5,"Applying disc differencing with R=%f arcmin"%self.radius)
discDiffMap.data[:] += self.addBackFraction*ltMap.data[:]
if self.smoothingFWHM>0.:
flTrace.issue("flipper.prewhitener",5,"Smoothing with FWHM: %f arcmin"%self.smoothingFWHM)
discDiffMap = discDiffMap.convolveWithGaussian(self.smoothingFWHM)
return discDiffMap
def testIsotropyInAnnuli(self,binningFile,cutByMask=False):
"""
@brief tests the isotropy in each annulus specfied by the binningFIle (see _testIsotropyInAnnulus)
@param binningFile An ascii file with columns binLower, binUpper, binCenter (nBins on the first line)
@param cutByMask If set to True, multiply the annulus by the k-space mask before adding pixels (see createKspaceMask).
@return binLowerBound,binUpperBound,BinCenter,BinnedValue,BinWeight
"""
binLower,binUpper,binCenter = readBinningFile(binningFile)
nBins = binLower.size
flTrace.issue("fftTools",0, "nBins= %d"%nBins)
binMean = np.zeros(nBins)
binWeight = np.zeros(nBins)
for i in xrange(nBins):
(binMean[i],binWeight[i]) = self._testIsotropyInAnnulus(binLower[i],binUpper[i],cutByMask=cutByMask)
return binLower,binUpper,binCenter,binMean,binWeight
def liteMapFromDataAndWCS(data,wcs):
"""
@brief Given a np array: data and a astLib.astWCS instance: wcs creates a liteMap
"""
ltmap = liteMap()
ltmap.data = data.copy()
[ltmap.Ny,ltmap.Nx] = ltmap.data.shape
ltmap.wcs = wcs.copy()
ltmap.header = ltmap.wcs.header
#[ltmap.x0,ltmap.x1,ltmap.y0,ltmap.y1] = wcs.getImageMinMaxWCSCoords()
ltmap.x0,ltmap.y0 = wcs.pix2wcs(0,0)
ltmap.x1,ltmap.y1 = wcs.pix2wcs(ltmap.Nx-1,ltmap.Ny-1)
if ltmap.x0 > ltmap.x1:
ltmap.pixScaleX = np.abs(ltmap.x1-ltmap.x0)/ltmap.Nx*np.pi/180.\
*np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
else:
ltmap.pixScaleX = np.abs((360.-ltmap.x1)+ltmap.x0)/ltmap.Nx*np.pi/180.\
*np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
ltmap.pixScaleY = np.abs(ltmap.y1-ltmap.y0)/ltmap.Ny*np.pi/180.
#print 0.5*(ltmap.y0+ltmap.y1)
ltmap.area = ltmap.Nx*ltmap.Ny*ltmap.pixScaleX*ltmap.pixScaleY*(180./np.pi)**2
#print np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
flTrace.issue('flipper.liteMap',1,'Reading file %s'%file)
flTrace.issue("flipper.liteMap",1, "Map dimensions (Ny,Nx) %d %d"%\
(ltmap.Ny,ltmap.Nx))
flTrace.issue("flipper.liteMap",1, "pixel scales Y, X (degrees) %f %f"%\
(ltmap.pixScaleY*180./np.pi,ltmap.pixScaleX*180./np.pi))
return ltmap
def liteMapFromFits(file,extension=0):
"""
@brief Reads in a FITS file and creates a liteMap object out of it.
@param extension specify the FITS HDU where the map image is stored
"""
ltmap = liteMap()
hdulist = pyfits.open(file)
header = hdulist[extension].header
flTrace.issue('flipper.liteMap',3,"Map header \n %s"%header)
ltmap.data = hdulist[extension].data.copy()
[ltmap.Ny,ltmap.Nx] = ltmap.data.shape
wcs = astLib.astWCS.WCS(file,extensionName = extension)
ltmap.wcs = wcs.copy()
ltmap.header = ltmap.wcs.header
ltmap.x0,ltmap.y0 = wcs.pix2wcs(0,0)
ltmap.x1,ltmap.y1 = wcs.pix2wcs(ltmap.Nx-1,ltmap.Ny-1)
#[ltmap.x0,ltmap.x1,ltmap.y0,ltmap.y1] = wcs.getImageMinMaxWCSCoords()
if ltmap.x0 > ltmap.x1:
ltmap.pixScaleX = np.abs(ltmap.x1-ltmap.x0)/ltmap.Nx*np.pi/180.\
*np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
else:
ltmap.pixScaleX = np.abs((360.-ltmap.x1)+ltmap.x0)/ltmap.Nx*np.pi/180.\
*np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
ltmap.pixScaleY = np.abs(ltmap.y1-ltmap.y0)/ltmap.Ny*np.pi/180.
#print 0.5*(ltmap.y0+ltmap.y1)
ltmap.area = ltmap.Nx*ltmap.Ny*ltmap.pixScaleX*ltmap.pixScaleY*(180./np.pi)**2
#print np.cos(np.pi/180.*0.5*(ltmap.y0+ltmap.y1))
flTrace.issue('flipper.liteMap',1,'Reading file %s'%file)
flTrace.issue("flipper.liteMap",1, "Map dimensions (Ny,Nx) %d %d"%\
(ltmap.Ny,ltmap.Nx))
flTrace.issue("flipper.liteMap",1, "pixel scales Y, X (degrees) %f %f"%\
(ltmap.pixScaleY*180./np.pi,ltmap.pixScaleX*180./np.pi))
return ltmap
def liteMapFromDataAndWCS(data, wcs):
"""
@brief Given a numpy array: data and a astLib.astWCS instance: wcs creates a liteMap
"""
ltmap = liteMap()
ltmap.data = data.copy()
[ltmap.Ny, ltmap.Nx] = ltmap.data.shape
ltmap.wcs = wcs.copy()
ltmap.header = ltmap.wcs.header
#[ltmap.x0,ltmap.x1,ltmap.y0,ltmap.y1] = wcs.getImageMinMaxWCSCoords()
ltmap.x0, ltmap.y0 = wcs.pix2wcs(0, 0)
ltmap.x1, ltmap.y1 = wcs.pix2wcs(ltmap.Nx - 1, ltmap.Ny - 1)
if ltmap.x0 > ltmap.x1:
ltmap.pixScaleX = numpy.abs(ltmap.x1-ltmap.x0)/ltmap.Nx*numpy.pi/180.\
*numpy.cos(numpy.pi/180.*0.5*(ltmap.y0+ltmap.y1))
else:
ltmap.pixScaleX = numpy.abs((360.-ltmap.x1)+ltmap.x0)/ltmap.Nx*numpy.pi/180.\
*numpy.cos(numpy.pi/180.*0.5*(ltmap.y0+ltmap.y1))
ltmap.pixScaleY = numpy.abs(ltmap.y1 -
ltmap.y0) / ltmap.Ny * numpy.pi / 180.
#print 0.5*(ltmap.y0+ltmap.y1)
ltmap.area = ltmap.Nx * ltmap.Ny * ltmap.pixScaleX * ltmap.pixScaleY * (
180. / numpy.pi)**2
#print numpy.cos(numpy.pi/180.*0.5*(ltmap.y0+ltmap.y1))
flTrace.issue('flipper.liteMap', 1, 'Reading file %s' % file)
flTrace.issue("flipper.liteMap",1, "Map dimensions (Ny,Nx) %d %d"%\
(ltmap.Ny,ltmap.Nx))
flTrace.issue("flipper.liteMap",1, "pixel scales Y, X (degrees) %f %f"%\
(ltmap.pixScaleY*180./numpy.pi,ltmap.pixScaleX*180./numpy.pi))
return ltmap
def fftFromLiteMap(liteMap,
applySlepianTaper=False,
nresForSlepian=3.0,
fftType=None):
"""
@brief Creates an fft2D object out of a liteMap
@param liteMap The map whose fft is being taken
@param applySlepianTaper If True applies the lowest order taper (to minimize edge-leakage)
@param nresForSlepian If above is True, specifies the resolution of the taeper to use.
"""
ft = fft2D()
ft.Nx = liteMap.Nx
ft.Ny = liteMap.Ny
flTrace.issue("flipper.fftTools", 1,
"Taking FFT of map with (Ny,Nx)= (%f,%f)" % (ft.Ny, ft.Nx))
ft.pixScaleX = liteMap.pixScaleX
ft.pixScaleY = liteMap.pixScaleY
lx = 2 * numpy.pi * fftfreq(ft.Nx, d=ft.pixScaleX)
ly = 2 * numpy.pi * fftfreq(ft.Ny, d=ft.pixScaleY)
ix = numpy.mod(numpy.arange(ft.Nx * ft.Ny), ft.Nx)
iy = numpy.arange(ft.Nx * ft.Ny) / ft.Nx
modLMap = numpy.zeros([ft.Ny, ft.Nx])
modLMap[iy, ix] = numpy.sqrt(lx[ix]**2 + ly[iy]**2)
ft.modLMap = modLMap
ft.lx = lx
ft.ly = ly
ft.ix = ix
ft.iy = iy
ft.thetaMap = numpy.zeros([ft.Ny, ft.Nx])
ft.thetaMap[iy[:], ix[:]] = numpy.arctan2(ly[iy[:]], lx[ix[:]])
ft.thetaMap *= 180. / numpy.pi
map = liteMap.data.copy()
#map = map0.copy()
#map[:,:] =map0[::-1,:]
taper = map.copy() * 0.0 + 1.0
if (applySlepianTaper):
try:
f = open(taperDir + os.path.sep + 'taper_Ny%d_Nx%d_Nres%3.1f' %
(ft.Ny, ft.Nx, nresForSlepian))
taper = pickle.load(f)
f.close()
except:
taper = slepianTaper00(ft.Nx, ft.Ny, nresForSlepian)
f = open(taperDir + os.path.sep + 'taper_Ny%d_Nx%d_Nres%3.1f' %
(ft.Ny, ft.Nx, nresForSlepian),
mode="w")
pickle.dump(taper, f)
f.close()
if fftType == 'fftw3':
ft.kMap = fft.fft(map * taper, axes=[-2, -1])
else:
ft.kMap = fft2(map * taper)
del map, modLMap, lx, ly
return ft
def addLiteMapsWithSpectralWeighting( liteMap1, liteMap2, kMask1Params = None, kMask2Params = None, signalMap = None ):
"""
@brief add two maps, weighting in Fourier space
Maps must be the same size.
@param kMask1Params mask params for liteMap1 (see fftTools.power2D.createKspaceMask)
@param kMask2Params mask params for liteMap2 (see fftTools.power2D.createKspaceMask)
@param signalMap liteMap with best estimate of signal to use when estimating noise weighting
@return new map
"""
#Get fourier weights
flTrace.issue("liteMap", 0, "Computing Weights")
#np1 = fftTools.noisePowerFromLiteMaps(liteMap1, liteMap2, applySlepianTaper = False)
#np2 = fftTools.noisePowerFromLiteMaps(liteMap2, liteMap1, applySlepianTaper = False)
data1 = copy.copy(liteMap1.data)
data2 = copy.copy(liteMap2.data)
if signalMap != None:
liteMap1.data[:] = (liteMap1.data - signalMap.data)[:]
liteMap2.data[:] = (liteMap2.data - signalMap.data)[:]
np1 = fftTools.powerFromLiteMap(liteMap1)#, applySlepianTaper = True)
np2 = fftTools.powerFromLiteMap(liteMap2)#), applySlepianTaper = True)
print "testing", liteMap1.data == data1
liteMap1.data[:] = data1[:]
liteMap2.data[:] = data2[:]
n1 = np1.powerMap
n2 = np2.powerMap
# n1[np.where( n1<n1.max()*.002)] = n1.max()*.001
# n2[np.where( n2<n2.max()*.002)] = n2.max()*.001
w1 = 1/n1
w2 = 1/n2
m1 = np.median(w1)
m2 = np.median(w2)
w1[np.where(abs(w1)>4*m1)]=4*m1
w2[np.where(abs(w2)>4*m2)]=4*m2
#w1[:] = 1.
#w2[:] = 1.
#pylab.hist(w1.ravel())
#pylab.savefig("hist1.png")
#pylab.clf()
yrange = [4,5000]
np1.powerMap = w1
#np1.plot(pngFile="w1.png", log=True, zoomUptoL=8000, yrange = yrange)
np2.powerMap = w2
#np2.plot(pngFile="w2.png", log=True, zoomUptoL=8000, yrange = yrange)
if kMask1Params != None:
np1.createKspaceMask(**kMask1Params)
w1 *= np1.kMask
if kMask2Params != None:
np2.createKspaceMask(**kMask2Params)
w2 *= np2.kMask
pylab.clf()
invW = 1.0/(w1+w2)
invW[np.where(np.isnan(invW))] = 0.
invW[np.where(np.isinf(invW))] = 0.
flTrace.issue("liteMap", 3, "NaNs in inverse weight: %s" % str(np.where(np.isnan(invW))))
flTrace.issue("liteMap", 3, "Infs in inverse weight: %s" % str(np.where(np.isinf(invW))))
flTrace.issue("liteMap", 2, "Adding Maps")
f1 = fftTools.fftFromLiteMap( liteMap1, applySlepianTaper = False )
f2 = fftTools.fftFromLiteMap( liteMap2, applySlepianTaper = False )
kTot = (f1.kMap*w1 + f2.kMap*w2)*invW
flTrace.issue("liteMap", 3, "NaNs in filtered transform: %s" % str(np.where(np.isnan(kTot))))
f1.kMap = kTot
finalMap = liteMap1.copy()
finalMap.data[:] = 0.
finalMap.data = f1.mapFromFFT()
return finalMap
def loadDataFromHealpixMap(self, hpm, interpolate = False, hpCoords = "J2000"):
"""
@brief copy data from a Healpix map (from healpy), return a lite map
@param hpm healpy map
@param interpolate use interpolation when copying
@param hpCoords coordinates of hpm (e.g., "J2000"(RA, Dec) or "GALACTIC")
Assumes that liteMap is in J2000 RA Dec. The Healpix map must contain the liteMap.
"""
inds = np.indices([self.Nx, self.Ny])
x = inds[0].ravel()
y = inds[1].ravel()
skyLinear = np.array(self.pixToSky(x,y))
ph = skyLinear[:,0]
th = skyLinear[:,1]
thOut = []
phOut = []
if hpCoords != "J2000":
for i in xrange(len(th)):
crd = astCoords.convertCoords("J2000", hpCoords, ph[i], th[i], 0.)
phOut.append(crd[0])
thOut.append(crd[1])
thOut = np.array(thOut)
phOut = np.array(phOut)
else:
thOut = th
phOut = ph
flTrace.issue("flipper.liteMap", 3, "theta (min, max): %f, %f" % (th.min(), th.max()))
flTrace.issue("flipper.liteMap", 3, "phi (min, max): %f, %f" % (ph.min(), ph.max()))
flTrace.issue("flipper.liteMap", 3, "phiOut (min, max): (%f, %f) " % ( phOut.min(), phOut.max() ))
flTrace.issue("flipper.liteMap", 3, "thetaOut (min, max): (%f, %f) " % ( thOut.min(), thOut.max() ))
phOut *= np.pi/180
thOut = 90. - thOut #polar angle is 0 at north pole
thOut *= np.pi/180
flTrace.issue("flipper.liteMap", 3, "phiOut rad (min, max): (%f, %f) " % ( phOut.min(), phOut.max() ))
flTrace.issue("flipper.liteMap", 3, "thetaOut rad (min, max): (%f, %f) " % ( thOut.min(), thOut.max() ))
if interpolate:
self.data[y,x] = healpy.get_interp_val(hpm, thOut, phOut)
else:
ind = healpy.ang2pix( healpy.get_nside(hpm), thOut, phOut )
flTrace.issue("flipper.liteMap", 3, "healpix indices (min,max): %d, %d" % (ind.min(), ind.max()))
self.data[:] = 0.
self.data[[y,x]]=hpm[ind]
def addLiteMapsWithSpectralWeighting( liteMap1, liteMap2, kMask1Params = None, kMask2Params = None, signalMap = None ):
"""
@brief add two maps, weighting in Fourier space
Maps must be the same size.
@param kMask1Params mask params for liteMap1 (see fftTools.power2D.createKspaceMask)
@param kMask2Params mask params for liteMap2 (see fftTools.power2D.createKspaceMask)
@param signalMap liteMap with best estimate of signal to use when estimating noise weighting
@return new map
"""
#Get fourier weights
flTrace.issue("liteMap", 0, "Computing Weights")
#np1 = fftTools.noisePowerFromLiteMaps(liteMap1, liteMap2, applySlepianTaper = False)
#np2 = fftTools.noisePowerFromLiteMaps(liteMap2, liteMap1, applySlepianTaper = False)
data1 = copy.copy(liteMap1.data)
data2 = copy.copy(liteMap2.data)
if signalMap != None:
liteMap1.data[:] = (liteMap1.data - signalMap.data)[:]
liteMap2.data[:] = (liteMap2.data - signalMap.data)[:]
np1 = fftTools.powerFromLiteMap(liteMap1)#, applySlepianTaper = True)
np2 = fftTools.powerFromLiteMap(liteMap2)#), applySlepianTaper = True)
print "testing", liteMap1.data == data1
liteMap1.data[:] = data1[:]
liteMap2.data[:] = data2[:]
n1 = np1.powerMap
n2 = np2.powerMap
# n1[np.where( n1<n1.max()*.002)] = n1.max()*.001
# n2[np.where( n2<n2.max()*.002)] = n2.max()*.001
w1 = 1/n1
w2 = 1/n2
m1 = np.median(w1)
m2 = np.median(w2)
w1[np.where(abs(w1)>4*m1)]=4*m1
w2[np.where(abs(w2)>4*m2)]=4*m2
#w1[:] = 1.
#w2[:] = 1.
#pylab.hist(w1.ravel())
#pylab.savefig("hist1.png")
#pylab.clf()
yrange = [4,5000]
np1.powerMap = w1
#np1.plot(pngFile="w1.png", log=True, zoomUptoL=8000, yrange = yrange)
np2.powerMap = w2
#np2.plot(pngFile="w2.png", log=True, zoomUptoL=8000, yrange = yrange)
if kMask1Params != None:
np1.createKspaceMask(**kMask1Params)
w1 *= np1.kMask
if kMask2Params != None:
np2.createKspaceMask(**kMask2Params)
w2 *= np2.kMask
pylab.clf()
invW = 1.0/(w1+w2)
invW[np.where(np.isnan(invW))] = 0.
invW[np.where(np.isinf(invW))] = 0.
flTrace.issue("liteMap", 3, "NaNs in inverse weight: %s" % str(np.where(np.isnan(invW))))
flTrace.issue("liteMap", 3, "Infs in inverse weight: %s" % str(np.where(np.isinf(invW))))
flTrace.issue("liteMap", 2, "Adding Maps")
f1 = fftTools.fftFromLiteMap( liteMap1, applySlepianTaper = False )
f2 = fftTools.fftFromLiteMap( liteMap2, applySlepianTaper = False )
kTot = (f1.kMap*w1 + f2.kMap*w2)*invW
flTrace.issue("liteMap", 3, "NaNs in filtered transform: %s" % str(np.where(np.isnan(kTot))))
f1.kMap = kTot
finalMap = liteMap1.copy()
finalMap.data[:] = 0.
finalMap.data = f1.mapFromFFT()
return finalMap
def loadDataFromHealpixMap(self, hpm, interpolate = False, hpCoords = "J2000"):
"""
@brief copy data from a Healpix map (from healpy), return a lite map
@param hpm healpy map
@param interpolate use interpolation when copying
@param hpCoords coordinates of hpm (e.g., "J2000"(RA, Dec) or "GALACTIC")
Assumes that liteMap is in J2000 RA Dec. The Healpix map must contain the liteMap.
"""
inds = np.indices([self.Nx, self.Ny])
x = inds[0].ravel()
y = inds[1].ravel()
skyLinear = np.array(self.pixToSky(x,y))
ph = skyLinear[:,0]
th = skyLinear[:,1]
thOut = []
phOut = []
if hpCoords != "J2000":
for i in xrange(len(th)):
crd = astCoords.convertCoords("J2000", hpCoords, ph[i], th[i], 0.)
phOut.append(crd[0])
thOut.append(crd[1])
thOut = np.array(thOut)
phOut = np.array(phOut)
else:
thOut = th
phOut = ph
flTrace.issue("flipper.liteMap", 3, "theta (min, max): %f, %f" % (th.min(), th.max()))
flTrace.issue("flipper.liteMap", 3, "phi (min, max): %f, %f" % (ph.min(), ph.max()))
flTrace.issue("flipper.liteMap", 3, "phiOut (min, max): (%f, %f) " % ( phOut.min(), phOut.max() ))
flTrace.issue("flipper.liteMap", 3, "thetaOut (min, max): (%f, %f) " % ( thOut.min(), thOut.max() ))
phOut *= np.pi/180
thOut = 90. - thOut #polar angle is 0 at north pole
thOut *= np.pi/180
flTrace.issue("flipper.liteMap", 3, "phiOut rad (min, max): (%f, %f) " % ( phOut.min(), phOut.max() ))
flTrace.issue("flipper.liteMap", 3, "thetaOut rad (min, max): (%f, %f) " % ( thOut.min(), thOut.max() ))
if interpolate:
self.data[y,x] = healpy.get_interp_val(hpm, thOut, phOut)
else:
ind = healpy.ang2pix( healpy.get_nside(hpm), thOut, phOut )
flTrace.issue("flipper.liteMap", 3, "healpix indices (min,max): %d, %d" % (ind.min(), ind.max()))
self.data[:] = 0.
self.data[[y,x]]=hpm[ind]