def test_fast_versus_slow(): df = pd.DataFrame({"Sample": "001", "epitope": ["AAAAL"] * 1000, "iedb_epitope": ["AGGGT"] * 1000}) from timeit import Timer slow_timer = Timer(lambda: calculate_similarity_from_df(df, ignore_seqalign=True)) slow_time = slow_timer.timeit(number=3) fast_timer = Timer(lambda: calculate_similarity_from_df(df, ignore_seqalign=False)) fast_time = fast_timer.timeit(number=3) ok_( slow_time > fast_time * 5, ("The fast similarity calculation (%0.2f) should be at least " "5x faster than the slower version (%0.2f).") % (fast_time, slow_time), )
def test_fast_versus_slow(): df = pd.DataFrame({'Sample': '001', 'epitope': ['AAAAL'] * 1000, 'iedb_epitope': ['AGGGT'] * 1000}) from timeit import Timer slow_timer = Timer(lambda: calculate_similarity_from_df(df, ignore_seqalign=True)) slow_time = slow_timer.timeit(number=3) fast_timer = Timer(lambda: calculate_similarity_from_df(df, ignore_seqalign=False)) fast_time = fast_timer.timeit(number=3) ok_(slow_time > fast_time * 5, ("The fast similarity calculation (%0.2f) should be at least " "5x faster than the slower version (%0.2f).") % ( fast_time, slow_time))
def test_single_comparison_ignore_seqalign(): df = pd.DataFrame({'Sample': '001', 'epitope': ['AAALPGKCGV'], 'iedb_epitope': ['EFKEFAAGRR']}) df_scores = calculate_similarity_from_df(df, ignore_seqalign=True) # TODO: This score is currently unverified eq_(df_scores.score.max(), 2.38)
def test_single_comparison(): # TODO: Figure out why this doesn't work when trim_seq isn't used # Error: https://github.com/ekg/vcflib/blob/master/src/ssw.c#L556 df = pd.DataFrame({'Sample': '001', 'epitope': ['AAALPGKCGV'], 'iedb_epitope': ['EFKEFAAGRR']}) df_scores = calculate_similarity_from_df(df) # TODO: This score is currently unverified eq_(df_scores.score.max(), 2.38)
def test_single_comparison_ignore_seqalign(): df = pd.DataFrame({ 'Sample': '001', 'epitope': ['AAALPGKCGV'], 'iedb_epitope': ['EFKEFAAGRR'] }) df_scores = calculate_similarity_from_df(df, ignore_seqalign=True) # TODO: This score is currently unverified eq_(df_scores.score.max(), 2.38)
def test_single_comparison(): # TODO: Figure out why this doesn't work when trim_seq isn't used # Error: https://github.com/ekg/vcflib/blob/master/src/ssw.c#L556 df = pd.DataFrame({ 'Sample': '001', 'epitope': ['AAALPGKCGV'], 'iedb_epitope': ['EFKEFAAGRR'] }) df_scores = calculate_similarity_from_df(df) # TODO: This score is currently unverified eq_(df_scores.score.max(), 2.38)