def test_calculate_global_stats_adjust_grams_per_page(mock_get_grammars):
dset = mod['dset']
assert not dset.global_stats
grams_per_page = worker_jobs.GRAMS_PER_PAGE
worker_jobs.GRAMS_PER_PAGE = 5
_calculate_grammars_and_statistics('cv_dset', 1, True, 0, 'guest',
'rank_volume')
assert mock_get_grammars.called_with(True)
worker_jobs.GRAMS_PER_PAGE = grams_per_page
dset = Dataset.objects.get(name='cv_dset')
assert len(eval(dset.global_stats['grams'])) == 5
def test_calculate_global_stats(mock_get_grammars):
dset = mod['dset']
assert not dset.global_stats
global_stats = {
u'num_total_poots': 219,
u'num_total_cots': 24,
u'grams': u'[(10, frozenset([(3, 1), (2, 1)]))]',
u'percent_cots': 0.0,
u'num_poots': 11,
u'num_cots': 0,
u'percent_poots': 5.0228310502283104
}
_calculate_grammars_and_statistics('voweldset', 8, False,
0, 'guest', 'rank_volume')
assert mock_get_grammars.called_with(False)
dset = Dataset.objects.get(name='voweldset')
assert dset.global_stats == global_stats
def test_calculate_global_stats_classical_sort_by_size(mock_get_grammars):
dset = mod['dset']
assert not dset.global_stats
global_stats = {
u'num_total_cots': 24,
u'num_cots': 6,
u'grams':
(u'['
'(0, frozenset([(3, 2), (3, 4), (3, 1), (2, 1), (4, 1), (2, 4)])), '
'(1, frozenset([(3, 2), (3, 1), (2, 1), (4, 3), (4, 2), (4, 1)])), '
'(2, frozenset([(1, 2), (3, 2), (3, 1), (4, 3), (4, 2), (4, 1)])), '
'(3, frozenset([(1, 2), (3, 2), (1, 3), (4, 3), (4, 2), (4, 1)])), '
'(4, frozenset([(3, 2), (3, 4), (3, 1), (2, 1), (4, 2), (4, 1)])), '
'(5, frozenset([(1, 2), (3, 2), (3, 4), (3, 1), (4, 2), (4, 1)]))]'),
u'percent_cots': 25.0
}
_calculate_grammars_and_statistics('cv_dset', 6, True, 0, 'guest', 'size')
assert mock_get_grammars.called_with(True)
dset = Dataset.objects.get(name='cv_dset')
assert dset.global_stats == global_stats
def test_make_grammar_info(mock_get_grammars):
grammar_info = [
{
u'cots_by_cand': {
u'lasi-a': [
{u'output': u'la-si-a', u'num_cot': 5, u'per_cot': 62.5},
{u'output': u'la-sii', u'num_cot': 3, u'per_cot': 37.5}
],
u'ovea': [
{u'output': u'o-ve-a', u'num_cot': 4, u'per_cot': 50.0},
{u'output': u'o-vee', u'num_cot': 4, u'per_cot': 50.0}
],
u'rasia': [
{u'output': u'ra-si-a', u'num_cot': 8, u'per_cot': 100.0},
{u'output': u'ra-sii', u'num_cot': 0, u'per_cot': 0.0}
],
u'idea': [
{u'output': u'i-de-a', u'num_cot': 8, u'per_cot': 100.0},
{u'output': u'i-dee', u'num_cot': 0, u'per_cot': 0.0}
]
},
u'grammar': u'{(c1, c3), (c1, c2)}',
u'apriori': u'[["c1", "c3"], ["c1", "c2"]]',
u'input_totals': {
u'idea': {u'raw_sum': 8, u'per_sum': 100.0},
u'lasi-a': {u'raw_sum': 8, u'per_sum': 100.0},
u'rasia': {u'raw_sum': 8, u'per_sum': 100.0},
u'ovea': {u'raw_sum': 8, u'per_sum': 100.0}
},
u'filename': u'grammar10.png'}]
_calculate_grammars_and_statistics('voweldset', 8, False, 0, 'guest',
'rank_volume')
info_maker = GrammarInfoMaker('voweldset', 'guest')
info_maker.make_grammar_info()
dset = Dataset.objects.get(name='voweldset')
assert dset.grammar_info == grammar_info
