问题
I am attempting to produce a beam on a healpix map, using healpy. For starters, I would like to be able to produce a 2D gaussian in a mollweide projection, but I really don't know where to begin.
I can define a 2D gaussian:
import numpy as np
def gaussian_2D(x,y,mu_x=0.,mu_y=0.,sig_x=1.,sig_y=1.):
return np.exp(-0.5*(((x-mu_x) / sig_x)**2 + ((y-mu_y) / sig_y)**2))
such that I can build up a 3D X, Y, Z space like:
delta = 0.025
x = np.arange(-4, 4, delta)
y = np.arange(-4, 4, delta)
X, Y = np.meshgrid(x,y)
Z = gaussian_2D(X,Y)
but from here I'm pretty lost, and can't track down much useful documentation concerning how and/or what to project. Any suggestions for a direction of attack would be much appreciated!
回答1:
here is how I do this:
using a small trick. I insert a point at the desired Gaussian centrer and then I use "smearing" to create a Gaussian with some sigma.
Here is some example:
#!/usr/bin/env python
import numpy as np
import healpy as hp
import pylab as pl
NSIDE=512 #the map garannularity
m_sm=np.arange(hp.nside2npix(NSIDE)) # creates the map
m_sm=m_sm*0. # sets all values to zero
theta=np.radians(80.) # coordinates for the gaussian
phi=np.radians(20.)
indx=hp.pixelfunc.ang2pix(NSIDE,theta,phi) # getting the index of the point corresponding to the coordinates
m_sm[indx]=1. # setting that point value to 1.
gmap=hp.smoothing(m_sm, sigma=np.radians(20.),verbose=False,lmax=1024) # creating a new map, smmeared version of m_sm
hp.mollview(gmap, title="Gaussian Map") #draw it
pl.show()
now if you want to do that by hand, you would use a function for a gaussian
1) you feed it some coordinates
2) you retrieve the index corresponding to that coordinate using:
indx=hp.pixelfunc.ang2pix(NSIDE,theta,phi)
3) you set the value for that point to the value from your gaussian function. i.e.:
my_healpy_map[indx]=my_gauss(theta, phy, mean_theta, mean_phy, sigma_theta, sigma_phy)
来源：https://stackoverflow.com/questions/25539428/plotting-a-numpy-array-in-healpy