.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/sampling/flycheck_plot_b03cnl.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_sampling_flycheck_plot_b03cnl.py: Cross-nested logit ================== Estimation of a cross-nested logit model using sampling of alternatives. :author: Michel Bierlaire :date: Wed Nov 1 18:00:33 2023 .. GENERATED FROM PYTHON SOURCE LINES 11-34 .. code-block:: default import pandas as pd from biogeme.sampling_of_alternatives import ( SamplingContext, ChoiceSetsGeneration, GenerateModel, generate_segment_size, ) from biogeme.expressions import Beta import biogeme.biogeme_logging as blog import biogeme.biogeme as bio from biogeme.nests import OneNestForCrossNestedLogit, NestsForCrossNestedLogit from specification import V, combined_variables from compare import compare from alternatives import ( alternatives, ID_COLUMN, partitions, all_alternatives, asian_and_downtown, only_downtown, only_asian, ) .. GENERATED FROM PYTHON SOURCE LINES 35-37 .. code-block:: default logger = blog.get_screen_logger(level=blog.INFO) .. GENERATED FROM PYTHON SOURCE LINES 38-46 .. code-block:: default PARTITION = 'downtown' MEV_PARTITION = 'uniform_asian_or_downtown' SAMPLE_SIZE = 10 # out of 100 alternatives SAMPLE_SIZE_MEV = 63 # out of 63 alternatives CHOICE_COLUMN = 'cnl_3' MODEL_NAME = f'cnl_{SAMPLE_SIZE}_{SAMPLE_SIZE_MEV}' FILE_NAME = f'{MODEL_NAME}.dat' .. GENERATED FROM PYTHON SOURCE LINES 47-51 .. code-block:: default the_partition = partitions.get(PARTITION) if the_partition is None: raise ValueError(f'Unknown partition: {PARTITION}') .. GENERATED FROM PYTHON SOURCE LINES 52-56 .. code-block:: default segment_sizes = list( generate_segment_size(SAMPLE_SIZE, the_partition.number_of_segments()) ) .. GENERATED FROM PYTHON SOURCE LINES 57-58 We use all alternatives in the nest. .. GENERATED FROM PYTHON SOURCE LINES 58-65 .. code-block:: default mev_partition = partitions.get(MEV_PARTITION) if mev_partition is None: raise ValueError(f'Unknown partition: {MEV_PARTITION}') mev_segment_sizes = [ SAMPLE_SIZE_MEV, ] .. GENERATED FROM PYTHON SOURCE LINES 66-67 Nests .. GENERATED FROM PYTHON SOURCE LINES 69-70 Downtown .. GENERATED FROM PYTHON SOURCE LINES 70-78 .. code-block:: default mu_downtown = Beta('mu_downtown', 1, 1, None, 0) downtown_alpha_dict = {i: 0.5 for i in asian_and_downtown} | { i: 1 for i in only_downtown } downtown_nest = OneNestForCrossNestedLogit( nest_param=mu_downtown, dict_of_alpha=downtown_alpha_dict, name='downtown' ) .. GENERATED FROM PYTHON SOURCE LINES 79-80 Asian .. GENERATED FROM PYTHON SOURCE LINES 80-91 .. code-block:: default mu_asian = Beta('mu_asian', 1, 1, None, 0) asian_alpha_dict = {i: 0.5 for i in asian_and_downtown} | {i: 1.0 for i in only_asian} asian_nest = OneNestForCrossNestedLogit( nest_param=mu_asian, dict_of_alpha=asian_alpha_dict, name='asian' ) cnl_nests = NestsForCrossNestedLogit( choice_set=all_alternatives, tuple_of_nests=(downtown_nest, asian_nest), ) .. GENERATED FROM PYTHON SOURCE LINES 92-94 .. code-block:: default observations = pd.read_csv('obs_choice.dat') .. GENERATED FROM PYTHON SOURCE LINES 95-110 .. code-block:: default context = SamplingContext( the_partition=the_partition, sample_sizes=segment_sizes, individuals=observations, choice_column=CHOICE_COLUMN, alternatives=alternatives, id_column=ID_COLUMN, biogeme_file_name=FILE_NAME, utility_function=V, combined_variables=combined_variables, mev_partition=mev_partition, mev_sample_sizes=mev_segment_sizes, cnl_nests=cnl_nests, ) .. GENERATED FROM PYTHON SOURCE LINES 111-113 .. code-block:: default logger.info(context.reporting()) .. GENERATED FROM PYTHON SOURCE LINES 114-117 .. code-block:: default the_data_generation = ChoiceSetsGeneration(context=context) the_model_generation = GenerateModel(context=context) .. GENERATED FROM PYTHON SOURCE LINES 118-120 .. code-block:: default biogeme_database = the_data_generation.sample_and_merge(recycle=False) .. GENERATED FROM PYTHON SOURCE LINES 121-123 .. code-block:: default logprob = the_model_generation.get_cross_nested_logit() .. GENERATED FROM PYTHON SOURCE LINES 124-127 .. code-block:: default the_biogeme = bio.BIOGEME(biogeme_database, logprob) the_biogeme.modelName = MODEL_NAME .. GENERATED FROM PYTHON SOURCE LINES 128-129 Calculate the null log likelihood for reporting. .. GENERATED FROM PYTHON SOURCE LINES 129-131 .. code-block:: default the_biogeme.calculateNullLoglikelihood({i: 1 for i in range(context.total_sample_size)}) .. GENERATED FROM PYTHON SOURCE LINES 132-133 Estimate the parameters. .. GENERATED FROM PYTHON SOURCE LINES 133-135 .. code-block:: default results = the_biogeme.estimate(recycle=False) .. GENERATED FROM PYTHON SOURCE LINES 136-138 .. code-block:: default print(results.short_summary()) .. GENERATED FROM PYTHON SOURCE LINES 139-142 .. code-block:: default estimated_parameters = results.getEstimatedParameters() estimated_parameters .. GENERATED FROM PYTHON SOURCE LINES 143-145 .. code-block:: default df, msg = compare(estimated_parameters) .. GENERATED FROM PYTHON SOURCE LINES 146-148 .. code-block:: default print(df) .. GENERATED FROM PYTHON SOURCE LINES 149-150 .. code-block:: default print(msg) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.000 seconds) .. _sphx_glr_download_auto_examples_sampling_flycheck_plot_b03cnl.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: flycheck_plot_b03cnl.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: flycheck_plot_b03cnl.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_