def test_CategoricalSummary__make_input_file_IO(cat_sum, expected_latext_content): with StringIO() as inputIO: cat_sum._make_input_file_IO(inputIO) input_string = inputIO.getvalue() helpers.assert_bigstring_equal(input_string, expected_latext_content)
def test_CategoricalSummary__make_report_IO(cat_sum, expected_latex_report, temp_template): with StringIO() as report, open(temp_template, 'r') as template: cat_sum._make_report_IO(template, 'testpath.tex', report, 'test report title') helpers.assert_bigstring_equal(report.getvalue(), expected_latex_report)
def test_DatasetSummary__make_tex_table(dset_sum): if dset_sum.ds.scenario == (True, True): expected = r""" \begin{table}[h!] \caption{test title} \centering \begin{tabular}{l l l l l} \toprule \textbf{Statistic} & \textbf{Inlet} & \textbf{Outlet} \\ \toprule Count & 25 & 25 \\ \midrule Number of NDs & 5 & 5 \\ \midrule Min; Max & 0.123; 123 & 0.123; 123 \\ \midrule Mean & 12.3 & 12.3 \\ %% (95\% confidence interval) & (11.3; 13.3) & (11.3; 13.3) \\ \midrule Standard Deviation & 4.56 & 4.56 \\ \midrule Log. Mean & 12.3 & 12.3 \\ %% (95\% confidence interval) & (11.3; 13.3) & (11.3; 13.3) \\ \midrule Log. Standard Deviation & 4.56 & 4.56 \\ \midrule Geo. Mean & 12.3 & 12.3 \\ %% (95\% confidence interval) & (11.3; 13.3) & (11.3; 13.3) \\ \midrule Coeff. of Variation & 5.61 & 5.61 \\ \midrule Skewness & 6.12 & 6.12 \\ \midrule Median & 1.23 & 1.23 \\ %% (95\% confidence interval) & (0.235; 2.23) & (0.235; 2.23) \\ \midrule Quartiles & 0.612; 2.35 & 0.612; 2.35 \\ \toprule Number of Pairs & \multicolumn{2}{c} {22} \\ \midrule Wilcoxon p-value & \multicolumn{2}{c} {$<0.001$} \\ \midrule Mann-Whitney p-value & \multicolumn{2}{c} {0.456} \\ \bottomrule \end{tabular} \end{table}""" + '\n' result = dset_sum._make_tex_table('test title') helpers.assert_bigstring_equal(result, expected) else: pass
def test_makeLongLandscapeTexTable(footnote, long_landscape_tables): dfdict = { "W": {"a": 0.84386963791251501, "b": -0.22109837444207142}, "X": {"a": 0.70049867715201963, "b": 1.4764939161054218}, "Y": {"a": -1.3477794473987552, "b": -1.1939220296611821}, } df = pandas.DataFrame.from_dict(dfdict) result = utils.makeLongLandscapeTexTable( df, "test caption", "label", footnotetext=footnote ) expected = long_landscape_tables[footnote] helpers.assert_bigstring_equal(result, expected)
def test_CategoricalSummary_makeReport(cat_sum, expected_latex_report, temp_template): templatepath = get_tex_file('draft_template.tex') inputpath = get_tex_file('inputs_{}.tex'.format(cat_sum.paramgroup.lower())) with TemporaryDirectory() as tmpdir: reportpath = os.path.join(tmpdir, 'report_{}.tex'.format(cat_sum.paramgroup.lower())) testpath = os.path.join(tmpdir, 'testpath.tex'.format(cat_sum.paramgroup.lower())) cat_sum.makeReport( temp_template, testpath, reportpath, 'test report title', regenfigs=False ) with open(reportpath, 'r') as rp: helpers.assert_bigstring_equal(rp.read(), expected_latex_report)
def test_CategoricalSummary_makeReport(cat_sum, expected_latex_report, temp_template): templatepath = get_tex_file('draft_template.tex') inputpath = get_tex_file('inputs_{}.tex'.format( cat_sum.paramgroup.lower())) with TemporaryDirectory() as tmpdir: reportpath = os.path.join( tmpdir, 'report_{}.tex'.format(cat_sum.paramgroup.lower())) testpath = os.path.join( tmpdir, 'testpath.tex'.format(cat_sum.paramgroup.lower())) cat_sum.makeReport(temp_template, testpath, reportpath, 'test report title', regenfigs=False) with open(reportpath, 'r') as rp: helpers.assert_bigstring_equal(rp.read(), expected_latex_report)
def test_makeLongLandscapeTexTable(footnote, long_landscape_tables): dfdict = { 'W': { 'a': 0.84386963791251501, 'b': -0.22109837444207142, }, 'X': { 'a': 0.70049867715201963, 'b': 1.4764939161054218, }, 'Y': { 'a': -1.3477794473987552, 'b': -1.1939220296611821, }, } df = pandas.DataFrame.from_dict(dfdict) result = utils.makeLongLandscapeTexTable(df, 'test caption', 'label', footnotetext=footnote) expected = long_landscape_tables[footnote] helpers.assert_bigstring_equal(result, expected)
def test_DatasetSummary_makeTexInput(dset_sum, expected_latext_input): result = dset_sum.makeTexInput('test table title') helpers.assert_bigstring_equal(result, expected_latext_input[dset_sum.ds.scenario])