|
| 1 | +string = 'BCAADDDCCACACAC' |
| 2 | + |
| 3 | + |
| 4 | +# Creating tree nodes |
| 5 | +class NodeTree(object): |
| 6 | + |
| 7 | + def __init__(self, left=None, right=None): |
| 8 | + self.left = left |
| 9 | + self.right = right |
| 10 | + |
| 11 | + def children(self): |
| 12 | + return (self.left, self.right) |
| 13 | + |
| 14 | + def nodes(self): |
| 15 | + return (self.left, self.right) |
| 16 | + |
| 17 | + def __str__(self): |
| 18 | + return '%s_%s' % (self.left, self.right) |
| 19 | + |
| 20 | + |
| 21 | +# Main function implementing huffman coding |
| 22 | +def huffman_code_tree(node, left=True, binString=''): |
| 23 | + if type(node) is str: |
| 24 | + return {node: binString} |
| 25 | + (l, r) = node.children() |
| 26 | + d = dict() |
| 27 | + d.update(huffman_code_tree(l, True, binString + '0')) |
| 28 | + d.update(huffman_code_tree(r, False, binString + '1')) |
| 29 | + return d |
| 30 | + |
| 31 | + |
| 32 | +# Calculating frequency |
| 33 | +freq = {} |
| 34 | +for c in string: |
| 35 | + if c in freq: |
| 36 | + freq[c] += 1 |
| 37 | + else: |
| 38 | + freq[c] = 1 |
| 39 | + |
| 40 | +freq = sorted(freq.items(), key=lambda x: x[1], reverse=True) |
| 41 | + |
| 42 | +nodes = freq |
| 43 | + |
| 44 | +while len(nodes) > 1: |
| 45 | + (key1, c1) = nodes[-1] |
| 46 | + (key2, c2) = nodes[-2] |
| 47 | + nodes = nodes[:-2] |
| 48 | + node = NodeTree(key1, key2) |
| 49 | + nodes.append((node, c1 + c2)) |
| 50 | + |
| 51 | + nodes = sorted(nodes, key=lambda x: x[1], reverse=True) |
| 52 | + |
| 53 | +huffmanCode = huffman_code_tree(nodes[0][0]) |
| 54 | + |
| 55 | +print(' Char | Huffman code ') |
| 56 | +print('----------------------') |
| 57 | +for (char, frequency) in freq: |
| 58 | + print(' %-4r |%12s' % (char, huffmanCode[char])) |
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