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