From 0628e0e2a821ab9347ee91520264bafaf8c39a0a Mon Sep 17 00:00:00 2001
From: Matthew Honnibal <honnibal@gmail.com>
Date: Mon, 13 Jul 2015 12:58:07 +0200
Subject: [PATCH] * Add tests for huffman encoding

---
 tests/vocab/test_huffman.py | 147 ++++++++++++++++++++++++++++++++++++
 1 file changed, 147 insertions(+)
 create mode 100644 tests/vocab/test_huffman.py

diff --git a/tests/vocab/test_huffman.py b/tests/vocab/test_huffman.py
new file mode 100644
index 000000000..4c386af71
--- /dev/null
+++ b/tests/vocab/test_huffman.py
@@ -0,0 +1,147 @@
+from __future__ import unicode_literals
+from __future__ import division
+
+import pytest
+
+from spacy.serialize import HuffmanCodec
+import numpy
+
+from heapq import heappush, heappop, heapify
+from collections import defaultdict
+
+
+class Vocab(object):
+    def __init__(self, freqs):
+        freqs['-eol-'] = 5
+        total = sum(freqs.values())
+        by_freq = freqs.items()
+        by_freq.sort(key=lambda item: item[1], reverse=True)
+        self.symbols = [sym for sym, freq in by_freq]
+        self.probs = numpy.array([item[1] / total for item in by_freq], dtype=numpy.float32)
+        self.table = {sym: i for i, sym in enumerate(self.symbols)}
+        self.codec = HuffmanCodec(self.probs, self.table['-eol-'])
+
+    def pack(self, message):
+        seq = [self.table[sym] for sym in message]
+        return self.codec.encode(numpy.array(seq, dtype=numpy.uint32))
+
+    def unpack(self, packed):
+        return [self.symbols[i] for i in self.codec.decode(packed)]
+
+ 
+def py_encode(symb2freq):
+    """Huffman encode the given dict mapping symbols to weights
+    From Rosetta Code
+    """
+    heap = [[wt, [sym, ""]] for sym, wt in symb2freq.items()]
+    heapify(heap)
+    while len(heap) > 1:
+        lo = heappop(heap)
+        hi = heappop(heap)
+        for pair in lo[1:]:
+            pair[1] = '0' + pair[1]
+        for pair in hi[1:]:
+            pair[1] = '1' + pair[1]
+        heappush(heap, [lo[0] + hi[0]] + lo[1:] + hi[1:])
+    return dict(heappop(heap)[1:])
+
+
+def test1():
+    probs = numpy.zeros(shape=(10,), dtype=numpy.float32)
+    probs[0] = 0.3
+    probs[1] = 0.2
+    probs[2] = 0.15
+    probs[3] = 0.1
+    probs[4] = 0.06
+    probs[5] = 0.02
+    probs[6] = 0.01
+    probs[7] = 0.005
+    probs[8] = 0.0001
+    probs[9] = 0.000001
+    
+    codec = HuffmanCodec(probs, 9)
+    
+    py_codes = py_encode(dict(enumerate(probs)))
+    py_codes = py_codes.items()
+    py_codes.sort()
+    assert codec.strings == [c for i, c in py_codes]
+    
+
+def test_round_trip():
+    freqs = {'the': 10, 'quick': 3, 'brown': 4, 'fox': 1, 'jumped': 5, 'over': 8,
+            'lazy': 1, 'dog': 2, '.': 9}
+    vocab = Vocab(freqs)
+
+    message = ['the', 'quick', 'brown', 'fox', 'jumped', 'over', 'the',
+                'the', 'lazy', 'dog', '.']
+    strings = list(vocab.codec.strings)
+    for i in range(len(vocab.symbols)):
+        print vocab.symbols[i], strings[i]
+    codes = {vocab.symbols[i]: strings[i] for i in range(len(vocab.symbols))}
+    packed = vocab.pack(message)
+    string = b''.join(b'{0:b}'.format(ord(c)).rjust(8, b'0')[::-1] for c in packed)
+    print string
+    for word in message:
+        code = codes[word]
+        assert string[:len(code)] == code
+        string = string[len(code):]
+    unpacked = vocab.unpack(packed)
+    assert message == unpacked
+
+
+def test_rosetta():
+    txt = u"this is an example for huffman encoding"
+    symb2freq = defaultdict(int)
+    for ch in txt:
+        symb2freq[ch] += 1
+    symb2freq['-eol-'] = 1
+    by_freq = symb2freq.items()
+    by_freq.sort(reverse=True, key=lambda item: item[1])
+    symbols = [sym for sym, prob in by_freq]
+    probs = numpy.array([prob for sym, prob in by_freq], dtype=numpy.float32)
+
+    codec = HuffmanCodec(probs, symbols.index('-eol-'))
+    py_codec = py_encode(symb2freq)
+
+    my_lengths = defaultdict(int)
+    py_lengths = defaultdict(int)
+    for i, my in enumerate(codec.strings):
+        symb = by_freq[i][0]
+        my_lengths[len(my)] += by_freq[i][1]
+        py_lengths[len(py_codec[symb])] += by_freq[i][1]
+    my_exp_len = sum(length * weight for length, weight in my_lengths.items())
+    py_exp_len = sum(length * weight for length, weight in py_lengths.items())
+    assert my_exp_len == py_exp_len
+
+
+def test_vocab(EN):
+    probs = numpy.ndarray(shape=(len(EN.vocab), 2), dtype=numpy.float32)
+    for word in EN.vocab:
+        probs[word.id, 0] = numpy.exp(word.prob)
+        probs[word.id, 1] = word.id
+    probs.sort()
+    probs[:,::-1]
+    codec = HuffmanCodec(probs[:, 0], 0)
+    expected_length = 0
+    for i, code in enumerate(codec.strings):
+        expected_length += len(code) * probs[i, 0]
+    assert 8 < expected_length < 15
+
+
+def test_freqs():
+    freqs = []
+    words = []
+    for i, line in enumerate(open('freqs.txt')):
+        pieces = line.strip().split()
+        if len(pieces) != 2:
+           continue
+        freq, word = pieces
+        freqs.append(int(freq))
+    freqs.append(1)
+    total = sum(freqs)
+    freqs = [(float(f) / total) for f in freqs]
+    codec = HuffmanCodec(numpy.array(freqs, dtype=numpy.float32), len(freqs)-1)
+    expected_length = 0
+    for i, code in enumerate(codec.strings):
+        expected_length += len(code) * freqs[i]
+    assert 8 < expected_length < 14