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111 lines
3.3 KiB
Python
111 lines
3.3 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from __future__ import division
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from ...serialize.huffman import HuffmanCodec
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from ...serialize.bits import BitArray
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from heapq import heappush, heappop, heapify
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from collections import defaultdict
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import numpy
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import pytest
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def py_encode(symb2freq):
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"""Huffman encode the given dict mapping symbols to weights
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From Rosetta Code
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"""
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heap = [[wt, [sym, ""]] for sym, wt in symb2freq.items()]
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heapify(heap)
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while len(heap) > 1:
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lo = heappop(heap)
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hi = heappop(heap)
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for pair in lo[1:]:
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pair[1] = '0' + pair[1]
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for pair in hi[1:]:
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pair[1] = '1' + pair[1]
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heappush(heap, [lo[0] + hi[0]] + lo[1:] + hi[1:])
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return dict(heappop(heap)[1:])
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def test_serialize_huffman_1():
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probs = numpy.zeros(shape=(10,), dtype=numpy.float32)
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probs[0] = 0.3
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probs[1] = 0.2
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probs[2] = 0.15
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probs[3] = 0.1
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probs[4] = 0.06
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probs[5] = 0.02
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probs[6] = 0.01
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probs[7] = 0.005
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probs[8] = 0.0001
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probs[9] = 0.000001
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codec = HuffmanCodec(list(enumerate(probs)))
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py_codes = py_encode(dict(enumerate(probs)))
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py_codes = list(py_codes.items())
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py_codes.sort()
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assert codec.strings == [c for i, c in py_codes]
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def test_serialize_huffman_empty():
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codec = HuffmanCodec({})
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assert codec.strings == []
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def test_serialize_huffman_round_trip():
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words = ['the', 'quick', 'brown', 'fox', 'jumped', 'over', 'the', 'the',
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'lazy', 'dog', '.']
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freqs = {'the': 10, 'quick': 3, 'brown': 4, 'fox': 1, 'jumped': 5,
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'over': 8, 'lazy': 1, 'dog': 2, '.': 9}
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codec = HuffmanCodec(freqs.items())
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strings = list(codec.strings)
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codes = dict([(codec.leaves[i], strings[i]) for i in range(len(codec.leaves))])
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bits = codec.encode(words)
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string = ''.join('{0:b}'.format(c).rjust(8, '0')[::-1] for c in bits.as_bytes())
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for word in words:
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code = codes[word]
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assert string[:len(code)] == code
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string = string[len(code):]
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unpacked = [0] * len(words)
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bits.seek(0)
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codec.decode(bits, unpacked)
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assert words == unpacked
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def test_serialize_huffman_rosetta():
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text = "this is an example for huffman encoding"
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symb2freq = defaultdict(int)
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for ch in text:
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symb2freq[ch] += 1
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by_freq = list(symb2freq.items())
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by_freq.sort(reverse=True, key=lambda item: item[1])
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symbols = [sym for sym, prob in by_freq]
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codec = HuffmanCodec(symb2freq.items())
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py_codec = py_encode(symb2freq)
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codes = dict([(codec.leaves[i], codec.strings[i]) for i in range(len(codec.leaves))])
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my_lengths = defaultdict(int)
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py_lengths = defaultdict(int)
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for symb, freq in symb2freq.items():
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my = codes[symb]
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my_lengths[len(my)] += freq
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py_lengths[len(py_codec[symb])] += freq
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my_exp_len = sum(length * weight for length, weight in my_lengths.items())
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py_exp_len = sum(length * weight for length, weight in py_lengths.items())
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assert my_exp_len == py_exp_len
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@pytest.mark.models
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def test_vocab(EN):
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codec = HuffmanCodec([(w.orth, numpy.exp(w.prob)) for w in EN.vocab])
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expected_length = 0
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for i, code in enumerate(codec.strings):
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leaf = codec.leaves[i]
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expected_length += len(code) * numpy.exp(EN.vocab[leaf].prob)
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assert 8 < expected_length < 15
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