• NumarrayTutorialSolutionSet3

Exercise 1:

 >>> import pyfits
 >>> from pylab import *
 >>> fo = pyfits.open('tut3f1.fits')
 >>> fo.info()
 [shows 10 Int32 extensions with 400x400 images]
 >>> cube = zeros((10,400,400))
 >>> for i in range(len(fo)-1): cube[i] = fo[i+1].data
 >>> s = sum(cube)
 >>> imshow(s)

Exercise 2 (using PyRAF so that iraf tools can be used):

 --> import pyfits
 --> imhead tut3f1.fits[1] l+
 tut3f1.fits[1][400,400][int]:
 No bad pixels, min=0., max=0. (old)
 Line storage mode, physdim [400,400], length of user area 162 s.u.
 Created Fri 12:19:29 22-Jul-2005, Last modified Fri 12:19:29 22-Jul-2005
 Pixel file "fff.fits" [ok]
 PCOUNT  =                    0 / number of parameters
 GCOUNT  =                    1 / number of groups
 TARGET  = 'cosmic background'
 PURPOSE = 'none that I can think of'
 --> fo = pyfits.open('tut3f1.fits', mode='update')
 --> for i in range(10):
 ...     fo[i+1].header.update('imnum', i+1, after='target')
 ...     fo[i+1].header.add_history('added imnum value')
 ...
 --> fo.flush()
 --> imhead tut3f1.fits[3] l+
 tut3f1.fits[3][400,400][int]:
 No bad pixels, min=0., max=0. (old)
 Line storage mode, physdim [400,400], length of user area 243 s.u.
 Created Fri 14:05:36 22-Jul-2005, Last modified Fri 14:05:36 22-Jul-2005
 Pixel file "xxx.fits" [ok]
 PCOUNT  =                    0 / number of parameters
 GCOUNT  =                    1 / number of groups
 TARGET  = 'cosmic background'
 IMNUM   =                    3
 PURPOSE = 'none that I can think of'
 HISTORY added imnum value

Exercise 3:

 >>> import numarray.random_array as nr
 >>> rx = nr.random(1000000)
 >>> ry = nr.random(1000000)
 >>> r = sqrt(rx**2 + ry**2)
 >>> float(len(where(r<1)[0]))/len(r)
 0.785991
 >>> pi/4
 0.78539816339744828

Exercise 4:

• First generate some data, N time values, and M frequency values to be sampled (between 0 and 2pi), pick 100 for N and 147 for M, and generate random numbers. Note that these frequency sampling points are neither uniform, nor in any order.

 >>> import numarray.random_array as nr
 >>> ts = nr.random(100)
 >>> freqsamp = nr.random(147)*2*pi
 >>> n = arange(100)
 >>> earg = multiply.outer(n, freqsamp) # generate array for exponential  argument
 >>> eval = exp(-1.j*earg) # evaluated exponential
 >>> ts.shape = (100, 1) # to make broadcasting work properly; can use NewAxis too (see docs).
 >>> sprod = ts*expval
 >>> freqvals = sum(sprod) # perform summation