def test_distribplot_lines_normalized_data1(self): '''Check plot data agrees with LaminateModel data; normalized=True. Compares lists of zipped (x,y) datapoints. Notes ----- - Supports normalize triggering; normalized=True|False - Supports non-fixed extrema, i.e p>=2; extrema=False. - Supports multiple ps, cases, geo_strings ''' # DEV: change parameters #cases_ = self.case1 #cases_ = self.cases2 cases_ = self.cases3 # Compare plot data with LaminateModel data line_df_case = upt.extract_plot_LM_xy(cases_, normalized=True, extrema=False) line_data, df_data = line_df_case actual = line_data expected = df_data nt.assert_equal(actual, expected) plt.close() # in jupyter, cuts out last plot
def test_extract_equivalence4(): '''Given a case, line plot data agrees with the DataFrame data; {extrema,normalized}=False.''' case = ut.laminator(['400-[200]-800']) # unnormalized multiplot requires only one geoemetry line_df_case = upt.extract_plot_LM_xy(case, extrema=False, normalized=False) line_data, df_data = line_df_case actual = line_data expected = df_data nt.assert_equal(actual, expected)
def test_extract_equivalence2(): '''Given a case, line plot data agrees with the DataFrame data; extrema=True.''' case = ut.laminator(['400-[200]-800', '400-[400]-400']) line_df_case = upt.extract_plot_LM_xy(case, extrema=True) line_data, df_data = line_df_case actual = line_data expected = df_data nt.assert_equal(actual, expected)