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)