if count == len(encoding_dict) :
index = index + 1
return rlt
def compare(a, b) :
if len(a) != len(b) :
return False
for i in range(len(a)) :
if a[i] != b[i] :
return False
return True
if __name__ == '__main__':
# start by building Huffman tree from probabilities
plist = ((0.34,'A'),(0.5,'B'),(0.08,'C'),(0.08,'D'))
cdict = huffman(plist)
# test case 1: decode a simple message
message = ['A', 'B', 'C', 'D']
encoded_message = PS1_tests.encode(cdict,message)
decoded_message = decode(cdict,encoded_message)
assert message == decoded_message, \
"Decoding failed: expected %s, got %s" % \
(message,decoded_message)
# test case 2: construct a random message and encode it
message = [random.choice('ABCD') for i in xrange(100)]
encoded_message = PS1_tests.encode(cdict,message)
decoded_message = decode(cdict,encoded_message)
assert message == decoded_message, \
"Decoding failed: expected %s, got %s" % \
print "\nBaseline 1:"
print " total number of runs:",runs.size
print " bits to encode runs with fixed-length code:",\
8*runs.size
print "\nBaseline 2:"
print " bits in Lempel-Ziv compressed PNG file:",\
os.stat('PS1_fax_image.png').st_size*8
# Start by computing the probability of each run length
# by simply counting how many of each run length we have
plist = PS1_tests.histogram(runs)
# Experiment 1: Huffman-encoding run lengths
cdict = huffman(plist)
encoded_runs = numpy.concatenate([cdict[r] for r in runs])
print "\nExperiment 1:"
print " bits when Huffman-encoding runs:",\
len(encoded_runs)
print " Top 10 run lengths [probability]:"
for i in xrange(10):
print " %d [%3.2f]" % (plist[i][1],plist[i][0])
# Experiment 2: Huffman-encoding white runs, black runs
plist_white = PS1_tests.histogram(runs[0::2])
cwhite = huffman(plist_white)
plist_black = PS1_tests.histogram(runs[1::2])
cblack = huffman(plist_black)
encoded_runs = numpy.concatenate(
[cwhite[runs[i]] if (i & 1) == 0 else cblack[runs[i]]
return rlt
def compare(a, b):
if len(a) != len(b):
return False
for i in range(len(a)):
if a[i] != b[i]:
return False
return True
if __name__ == '__main__':
# start by building Huffman tree from probabilities
plist = ((0.34, 'A'), (0.5, 'B'), (0.08, 'C'), (0.08, 'D'))
cdict = huffman(plist)
# test case 1: decode a simple message
message = ['A', 'B', 'C', 'D']
encoded_message = PS1_tests.encode(cdict, message)
decoded_message = decode(cdict, encoded_message)
assert message == decoded_message, \
"Decoding failed: expected %s, got %s" % \
(message,decoded_message)
# test case 2: construct a random message and encode it
message = [random.choice('ABCD') for i in xrange(100)]
encoded_message = PS1_tests.encode(cdict, message)
decoded_message = decode(cdict, encoded_message)
assert message == decoded_message, \
"Decoding failed: expected %s, got %s" % \
