Below is the syntax highlighted version of comparedocuments.py
from §3.3 Designing Data Types.
#----------------------------------------------------------------------- # compareadocuments.py #----------------------------------------------------------------------- import sys import stdarray import stdio from instream import InStream from sketch import Sketch #----------------------------------------------------------------------- # Accept integers k and d as command-line arguments. Read a document # list from standard input, compute profiles based on k-gram # frequencies for all the documents, and write a matrix of similarity # measures between all pairs of documents. d is the dimension of the # profiles. k = int(sys.argv[1]) d = int(sys.argv[2]) filenames = stdio.readAllStrings() sketches = stdarray.create1D(len(filenames)) for i in range(len(filenames)): text = InStream(filenames[i]).readAll() sketches[i] = Sketch(text, k, d) stdio.write(' ') for i in range(len(filenames)): stdio.writef('%8.4s', filenames[i]) stdio.writeln() for i in range(len(filenames)): stdio.writef('%.4s', filenames[i]) for j in range(len(filenames)): stdio.writef('%8.2f', sketches[i].similarTo(sketches[j])) stdio.writeln() #----------------------------------------------------------------------- # more documents.txt # constitution.txt # tomsawyer.txt # huckfinn.txt # prejudice.txt # vector.py # djia.csv # amazon.html # actg.txt # $ python comparedocuments.py 5 10000 < documents.txt # cons toms huck prej vect djia amaz actg # cons 1.00 0.69 0.63 0.67 0.09 0.15 0.19 0.12 # toms 0.69 1.00 0.93 0.89 0.07 0.18 0.19 0.14 # huck 0.63 0.93 1.00 0.83 0.05 0.16 0.16 0.13 # prej 0.67 0.89 0.83 1.00 0.06 0.20 0.20 0.14 # vect 0.09 0.07 0.05 0.06 1.00 0.02 0.19 0.02 # djia 0.15 0.18 0.16 0.20 0.02 1.00 0.11 0.07 # amaz 0.19 0.19 0.16 0.20 0.19 0.11 1.00 0.06 # actg 0.12 0.14 0.13 0.14 0.02 0.07 0.06 1.00