from unittest import TestCase
from itertools import repeat, imap, izip, cycle

from spicedham.bayes import Bayes
from spicedham import Spicedham


class TestBayes(TestCase):
    
    def test_classify(self):
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        alphabet = map(chr, range(97, 123))
        for letter in alphabet:
            p = b.classify(letter)
            self.assertEqual(p, 0.5)

    def _training(self, bayes):
        alphabet = map(chr, range(97, 123))
        reversed_alphabet = reversed(alphabet)
        messagePairs = izip(alphabet, reversed_alphabet)
        for message, is_spam in izip(messagePairs, cycle((True, False))):
            bayes.train(message, is_spam)

    def test_train(self):
        alphabet = map(chr, range(97, 123))
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        for letter in alphabet:
            result = sh.backend.get_key(b.__class__.__name__, letter)
            self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
            self.assertGreaterEqual(result['numTotal'], result['numSpam'])

from unittest import TestCase
from itertools import repeat, imap, izip, cycle

from spicedham.bayes import Bayes
from spicedham import Spicedham


class TestBayes(TestCase):
    
    def test_classify(self):
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        alphabet = map(chr, range(97, 123))
        for letter in alphabet:
            p = b.classify(letter)
            self.assertEqual(p, 0.5)

    def _training(self, bayes):
        alphabet = map(chr, range(97, 123))
        reversed_alphabet = reversed(alphabet)
        messagePairs = izip(alphabet, reversed_alphabet)
        for message, is_spam in izip(messagePairs, cycle((True, False))):
            bayes.train(message, is_spam)

    def test_train(self):
        alphabet = map(chr, range(97, 123))
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        for letter in alphabet:
            result = sh.backend.get_key(b.__class__.__name__, letter)
            self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
            self.assertTrue(result['numTotal'] >= result['numSpam'])

Replace assertGreaterEqual with assertTrue(a >= b)
Replace assertGreaterEqual with assertTrue(a >= b)

  from unittest import TestCase
  from itertools import repeat, imap, izip, cycle
  
  from spicedham.bayes import Bayes
  from spicedham import Spicedham
  
  
  class TestBayes(TestCase):
      
      def test_classify(self):
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          alphabet = map(chr, range(97, 123))
          for letter in alphabet:
              p = b.classify(letter)
              self.assertEqual(p, 0.5)
  
      def _training(self, bayes):
          alphabet = map(chr, range(97, 123))
          reversed_alphabet = reversed(alphabet)
          messagePairs = izip(alphabet, reversed_alphabet)
          for message, is_spam in izip(messagePairs, cycle((True, False))):
              bayes.train(message, is_spam)
  
      def test_train(self):
          alphabet = map(chr, range(97, 123))
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          for letter in alphabet:
              result = sh.backend.get_key(b.__class__.__name__, letter)
              self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
-             self.assertGreaterEqual(result['numTotal'], result['numSpam'])
+             self.assertTrue(result['numTotal'] >= result['numSpam'])
  
Replace assertGreaterEqual with assertTrue(a >= b)
## Code Before:
from unittest import TestCase
from itertools import repeat, imap, izip, cycle

from spicedham.bayes import Bayes
from spicedham import Spicedham


class TestBayes(TestCase):
    
    def test_classify(self):
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        alphabet = map(chr, range(97, 123))
        for letter in alphabet:
            p = b.classify(letter)
            self.assertEqual(p, 0.5)

    def _training(self, bayes):
        alphabet = map(chr, range(97, 123))
        reversed_alphabet = reversed(alphabet)
        messagePairs = izip(alphabet, reversed_alphabet)
        for message, is_spam in izip(messagePairs, cycle((True, False))):
            bayes.train(message, is_spam)

    def test_train(self):
        alphabet = map(chr, range(97, 123))
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        for letter in alphabet:
            result = sh.backend.get_key(b.__class__.__name__, letter)
            self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
            self.assertGreaterEqual(result['numTotal'], result['numSpam'])

## Instruction:
Replace assertGreaterEqual with assertTrue(a >= b)
## Code After:
from unittest import TestCase
from itertools import repeat, imap, izip, cycle

from spicedham.bayes import Bayes
from spicedham import Spicedham


class TestBayes(TestCase):
    
    def test_classify(self):
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        alphabet = map(chr, range(97, 123))
        for letter in alphabet:
            p = b.classify(letter)
            self.assertEqual(p, 0.5)

    def _training(self, bayes):
        alphabet = map(chr, range(97, 123))
        reversed_alphabet = reversed(alphabet)
        messagePairs = izip(alphabet, reversed_alphabet)
        for message, is_spam in izip(messagePairs, cycle((True, False))):
            bayes.train(message, is_spam)

    def test_train(self):
        alphabet = map(chr, range(97, 123))
        sh = Spicedham()
        b = Bayes(sh.config, sh.backend)
        b.backend.reset()
        self._training(b)
        for letter in alphabet:
            result = sh.backend.get_key(b.__class__.__name__, letter)
            self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
            self.assertTrue(result['numTotal'] >= result['numSpam'])
