For my comprehensive exam, I needed to quickly convert some NumPy arrays into nice-looking LaTeX array elements. The TeX Stack Exchange site has a good answer for tabular environments, but wasn’t quite suited to the array environment. The usual answer here would be Pweave but, being short on time, I ended up rolling my own function instead:

def to_latex(a,label='A'):
    sys.stdout.write('\[ '
                     + label
                     + ' = \\left| \\begin{array}{'
                     + ('c'*a.shape[1])
                     + '}\n' )
    for r in a:
        sys.stdout.write(str(r[0]))
        for c in r[1:]:
            sys.stdout.write(' & '+str(c))
        sys.stdout.write('\\\\\n')
    sys.stdout.write('\\end{array} \\right| \]\n')

Here’s an incomplete snippet of it in action, where I convolve an array t with four different filters, producing a latex formula for each result:

filters = (('A \\oplus H_1',h1)
           , ('A \\oplus H_2',h2)
           , ('A \\oplus H_3',h3)
           , ('A \\oplus H_4',h4))

for label,f in filters:
    t2 = scipy.signal.convolve(t,f,'same')
    to_latex(t2.astype('uint8'),label=label)

I’ll likely get around to expanding this into a full package sometime in the future, since there’s a lot that is hard coded (the \[ \] environment, stringification of the array, the fact that all columns are centered, etc.). A gist of the function is available here.