示例#1
0
def test_parameter_summary():

    m = larch.example(1, legacy=True)
    m.load_data()
    m.loglike_null()
    m.set_values(
        **{
            'ASC_BIKE': -2.3763275319243244,
            'ASC_SR2': -2.1780143286612037,
            'ASC_SR3P': -3.725078388760564,
            'ASC_TRAN': -0.6708609582690096,
            'ASC_WALK': -0.20677521181801753,
            'hhinc#2': -0.0021699381002406883,
            'hhinc#3': 0.0003577067151217295,
            'hhinc#4': -0.00528632366072714,
            'hhinc#5': -0.012807975284603574,
            'hhinc#6': -0.009686302933787567,
            'totcost': -0.00492023540098787,
            'tottime': -0.05134209452571549,
        })
    m.loglike()
    assert m.parameter_summary('xml').tostring() == (
        '<div><table><thead><tr><th style="text-align: left;">Category</th><th style="text-align: left;">Parameter</th>'
        '<th>Value</th><th>Null Value</th></tr></thead><tbody><tr><th rowspan="2" style="vertical-align: top; text-alig'
        'n: left;">LOS</th><th style="vertical-align: top; text-align: left;">totcost</th><td>-0.00492</td><td>0.0</td>'
        '</tr><tr><th style="vertical-align: top; text-align: left;">tottime</th><td>-0.05134</td><td>0.0</td></tr><tr>'
        '<th rowspan="5" style="vertical-align: top; text-align: left;">ASCs</th><th style="vertical-align: top; text-a'
        'lign: left;">ASC_BIKE</th><td>-2.376</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left'
        ';">ASC_SR2</th><td>-2.178</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">ASC_SR3P'
        '</th><td>-3.725</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">ASC_TRAN</th><td>-'
        '0.6709</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">ASC_WALK</th><td>-0.2068</t'
        'd><td>0.0</td></tr><tr><th rowspan="5" style="vertical-align: top; text-align: left;">Income</th><th style="ve'
        'rtical-align: top; text-align: left;">hhinc#2</th><td>-0.00217</td><td>0.0</td></tr><tr><th style="vertical-al'
        'ign: top; text-align: left;">hhinc#3</th><td>0.0003577</td><td>0.0</td></tr><tr><th style="vertical-align: top'
        '; text-align: left;">hhinc#4</th><td>-0.005286</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-a'
        'lign: left;">hhinc#5</th><td>-0.01281</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: lef'
        't;">hhinc#6</th><td>-0.009686</td><td>0.0</td></tr></tbody></table></div>'
    )
    m.ordering = ()
    assert m.parameter_summary('xml').tostring() == (
        '<div><table><thead><tr><th style="text-align: left;">Parameter</th><th>Value</th><th>Null Value</th></tr></the'
        'ad><tbody><tr><th style="vertical-align: top; text-align: left;">ASC_BIKE</th><td>-2.376</td><td>0.0</td></tr>'
        '<tr><th style="vertical-align: top; text-align: left;">ASC_SR2</th><td>-2.178</td><td>0.0</td></tr><tr><th sty'
        'le="vertical-align: top; text-align: left;">ASC_SR3P</th><td>-3.725</td><td>0.0</td></tr><tr><th style="vertic'
        'al-align: top; text-align: left;">ASC_TRAN</th><td>-0.6709</td><td>0.0</td></tr><tr><th style="vertical-align:'
        ' top; text-align: left;">ASC_WALK</th><td>-0.2068</td><td>0.0</td></tr><tr><th style="vertical-align: top; tex'
        't-align: left;">hhinc#2</th><td>-0.00217</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: '
        'left;">hhinc#3</th><td>0.0003577</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">h'
        'hinc#4</th><td>-0.005286</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">hhinc#5</'
        'th><td>-0.01281</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">hhinc#6</th><td>-0'
        '.009686</td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">totcost</th><td>-0.00492</'
        'td><td>0.0</td></tr><tr><th style="vertical-align: top; text-align: left;">tottime</th><td>-0.05134</td><td>0.'
        '0</td></tr></tbody></table></div>')
示例#2
0
def test_excel_metadata():

    import larch.util.excel
    if larch.util.excel.xlsxwriter is not None:
        from larch.util.excel import _make_excel_writer

        from larch.util.temporaryfile import TemporaryDirectory

        tempdir = TemporaryDirectory()
        os.path.join(tempdir, 'larchtest.xlsx')

        m = larch.example(1, legacy=True)
        m.load_data()
        m.loglike_null()
        m.maximize_loglike()

        xl = _make_excel_writer(m,
                                os.path.join(tempdir, 'larchtest.xlsx'),
                                save_now=False)
        # xl.add_metadata('self', m) # now automatic
        xl.add_metadata('short', 123)
        xl.add_metadata('plain', 'text')
        xl.save()

        md = larch.util.excel.load_metadata(
            os.path.join(tempdir, 'larchtest.xlsx'))
        assert len(md) == 3
        assert isinstance(md['_self_'], larch.Model)
        assert md['short'] == 123
        assert md['plain'] == 'text'

        md_m = larch.util.excel.load_metadata(
            os.path.join(tempdir, 'larchtest.xlsx'), '_self_')
        assert isinstance(md_m, larch.Model)

        assert larch.util.excel.load_metadata(
            os.path.join(tempdir, 'larchtest.xlsx'), 'short') == 123

        from numpy import inf
        assert md_m._get_cached_loglike_values() == approx({
            'nil': 0.0,
            'null': -7309.600971749679,
            'constants_only': 0.0,
            'best': -inf
        })

        md_m.estimation_statistics()
示例#3
0
文件: test_nl_1.py 项目: jpn--/larch
def simple_nl():
    m = larch.example(1, legacy=True)
    mot = m.graph.new_node(parameter="MuSR", children=[2, 3])
    m.set_values(
        **{
            'ASC_BIKE': -2.369583417234141,
            'ASC_SR2': -2.1003772176440494,
            'ASC_SR3P': -3.1652310001168176,
            'ASC_TRAN': -0.6716514097035154,
            'ASC_WALK': -0.20573835594484602,
            'MuSR': 0.656152401524297,
            'hhinc#2': -0.0018493368570253318,
            'hhinc#3': -0.0005878635612891558,
            'hhinc#4': -0.0051673845801924615,
            'hhinc#5': -0.012777495307881156,
            'hhinc#6': -0.00967649032713631,
            'totcost': -0.004808452908429623,
            'tottime': -0.05107162036470516,
        })
    m.load_data()
    return m
示例#4
0
def test_joint_parameter_summary():
    m = larch.example(1, legacy=True)
    m.load_data()
    m.loglike_null()
    m.set_values(
        **{
            'ASC_BIKE': -2.3763275319243244,
            'ASC_SR2': -2.1780143286612037,
            'ASC_SR3P': -3.725078388760564,
            'ASC_TRAN': -0.6708609582690096,
            'ASC_WALK': -0.20677521181801753,
            'hhinc#2': -0.0021699381002406883,
            'hhinc#3': 0.0003577067151217295,
            'hhinc#4': -0.00528632366072714,
            'hhinc#5': -0.012807975284603574,
            'hhinc#6': -0.009686302933787567,
            'totcost': -0.00492023540098787,
            'tottime': -0.05134209452571549,
        })
    m.loglike()
    m.maximize_loglike()

    m_c = larch.Model(dataservice=m.dataservice)
    m_c.choice_ca_var = '_choice_'
    m_c.availability_var = '_avail_'
    m_c.utility_co[2] = P("ASC_SR2")
    m_c.utility_co[3] = P("ASC_SR3P")
    m_c.utility_co[4] = P("ASC_TRAN")
    m_c.utility_co[5] = P("ASC_BIKE")
    m_c.utility_co[6] = P("ASC_WALK")
    m_c.title = "Constants Only"
    m_c.load_data()
    m_c.loglike_null()
    m_c.maximize_loglike()

    from larch.util.summary import joint_parameter_summary
    stable_df(joint_parameter_summary([m, m_c], bases=[m_c]),
              'joint_parameter_summary')
示例#5
0
def test_dfs_feathers():
    import tempfile
    m = example(1, legacy=True)
    with tempfile.TemporaryDirectory() as td:
        m.load_data()
        filename = os.path.join(td, 'dfs')
        m.dataframes.to_feathers(filename)
        d_co = m.dataframes.data_co.copy()
        d_ca = m.dataframes.data_ca.copy()
        d_ch = m.dataframes.data_ch.copy()
        d_av = m.dataframes.data_av.copy()
        m.dataframes.data_co.iloc[:] = 0.0
        m.dataframes.data_ca.iloc[:] = 0.0
        m.dataframes.data_ch.iloc[:] = 0.0
        m.dataframes.data_av.iloc[:] = 0.0
        assert all(m.dataframes.array_co().reshape(-1) == 0)
        assert all(m.dataframes.array_ca().reshape(-1) == 0)
        assert all(m.dataframes.array_ch().reshape(-1) == 0)
        assert all(m.dataframes.array_av().reshape(-1) == 0)
        m.dataframes.inject_feathers(filename)
        pandas.testing.assert_frame_equal(m.dataframes.data_co, d_co)
        pandas.testing.assert_frame_equal(m.dataframes.data_ca, d_ca)
        pandas.testing.assert_frame_equal(m.dataframes.data_ch, d_ch)
        pandas.testing.assert_frame_equal(m.dataframes.data_av, d_av)

        df = pandas.read_csv(example_file("MTCwork.csv.gz"))
        df.set_index(['casenum', 'altnum'], inplace=True)
        ds = DataFrames(df)
        filename2 = os.path.join(td, 'dfs1')
        ds.to_feathers(filename2)
        d_ce = ds.data_ce.copy()
        ds.data_ce.iloc[:] = 0.0
        assert all(ds.array_ce().reshape(-1) == 0)
        ds.inject_feathers(filename2)
        pandas.testing.assert_frame_equal(ds.data_ce, d_ce)

        filename3 = os.path.join(td, 'dfs2')
        ds.to_feathers(filename3)
        ds2 = DataFrames.from_feathers(filename3)
        pandas.testing.assert_index_equal(
            ds.alternative_codes(),
            ds2.alternative_codes(),
            check_names=False,
        )
        pandas.testing.assert_frame_equal(
            ds.data_ce,
            ds2.data_ce,
        )
        pandas.testing.assert_frame_equal(
            ds.data_av,
            ds2.data_av,
        )
        pandas.testing.assert_index_equal(
            ds.caseindex,
            ds2.caseindex,
        )

        dfs2 = DataFrames.from_feathers(filename)
        pandas.testing.assert_index_equal(
            m.dataframes.alternative_codes(),
            dfs2.alternative_codes(),
            check_names=False,
        )
        pandas.testing.assert_frame_equal(
            m.dataframes.data_co,
            dfs2.data_co,
        )
        pandas.testing.assert_frame_equal(
            m.dataframes.data_ca,
            dfs2.data_ca,
        )
        pandas.testing.assert_frame_equal(
            m.dataframes.data_av,
            dfs2.data_av,
        )
        pandas.testing.assert_index_equal(
            m.dataframes.caseindex,
            dfs2.caseindex,
        )