Exemple #1
0
def test_patsy_577():
    X = np.random.random((10, 2))
    df = pandas.DataFrame(X, columns=["var1", "var2"])
    from patsy import dmatrix
    endog = dmatrix("var1 - 1", df)
    np.testing.assert_(data._is_using_patsy(endog, None))
    exog = dmatrix("var2 - 1", df)
    np.testing.assert_(data._is_using_patsy(endog, exog))
Exemple #2
0
def test_patsy_577():
    X = np.random.random((10, 2))
    df = pandas.DataFrame(X, columns=["var1", "var2"])
    from patsy import dmatrix
    endog = dmatrix("var1 - 1", df)
    np.testing.assert_(data._is_using_patsy(endog, None))
    exog = dmatrix("var2 - 1", df)
    np.testing.assert_(data._is_using_patsy(endog, exog))
Exemple #3
0
def handle_data(endog, exog, missing='none', hasconst=None, **kwargs):
    """
    Given inputs
    """
    # deal with lists and tuples up-front
    if isinstance(endog, (list, tuple)):
        endog = np.asarray(endog)
    if isinstance(exog, (list, tuple)):
        exog = np.asarray(exog)

    if data_util._is_using_ndarray_type(endog, exog):
        klass = ModelData
    elif data_util._is_using_pandas(endog, exog):
        klass = PandasData
    elif data_util._is_using_patsy(endog, exog):
        klass = PatsyData
    # keep this check last
    elif data_util._is_using_ndarray(endog, exog):
        klass = ModelData
    else:
        raise ValueError('unrecognized data structures: %s / %s' %
                         (type(endog), type(exog)))

    return klass(endog,
                 exog=exog,
                 missing=missing,
                 hasconst=hasconst,
                 **kwargs)
Exemple #4
0
def handle_data(endog, exog):
    """
    Given inputs
    """
    # deal with lists and tuples up-front
    if isinstance(endog, (list, tuple)):
        endog = np.asarray(endog)
    if isinstance(exog, (list, tuple)):
        exog = np.asarray(exog)

    if data_util._is_using_pandas(endog, exog):
        klass = PandasData
    elif data_util._is_using_larry(endog, exog):
        klass = LarryData
    elif data_util._is_using_timeseries(endog, exog):
        klass = TimeSeriesData
    elif data_util._is_using_patsy(endog, exog):
        klass = PatsyData
    # keep this check last
    elif data_util._is_using_ndarray(endog, exog):
        klass = ModelData
    else:
        raise ValueError("unrecognized data structures: %s / %s" % (type(endog), type(exog)))

    return klass(endog, exog=exog)
Exemple #5
0
def handle_data_class_factory(endog, exog):
    """
    Given inputs
    """
    if data_util._is_using_ndarray_type(endog, exog):
        klass = ModelData
    elif data_util._is_using_pandas(endog, exog):
        klass = PandasData
    elif data_util._is_using_patsy(endog, exog):
        klass = PatsyData
    # keep this check last
    elif data_util._is_using_ndarray(endog, exog):
        klass = ModelData
    else:
        raise ValueError("unrecognized data structures: %s / %s" % (type(endog), type(exog)))
    return klass
Exemple #6
0
def handle_data_class_factory(endog, exog):
    """
    Given inputs
    """
    if data_util._is_using_ndarray_type(endog, exog):
        klass = ModelData
    elif data_util._is_using_pandas(endog, exog):
        klass = PandasData
    elif data_util._is_using_patsy(endog, exog):
        klass = PatsyData
    # keep this check last
    elif data_util._is_using_ndarray(endog, exog):
        klass = ModelData
    else:
        raise ValueError('unrecognized data structures: %s / %s' %
                         (type(endog), type(exog)))
    return klass
Exemple #7
0
def handle_data(endog, exog, missing="none", hasconst=None, **kwargs):
    """
    Given inputs
    """
    # deal with lists and tuples up-front
    if isinstance(endog, (list, tuple)):
        endog = np.asarray(endog)
    if isinstance(exog, (list, tuple)):
        exog = np.asarray(exog)

    if data_util._is_using_ndarray_type(endog, exog):
        klass = ModelData
    elif data_util._is_using_pandas(endog, exog):
        klass = PandasData
    elif data_util._is_using_patsy(endog, exog):
        klass = PatsyData
    # keep this check last
    elif data_util._is_using_ndarray(endog, exog):
        klass = ModelData
    else:
        raise ValueError("unrecognized data structures: %s / %s" % (type(endog), type(exog)))

    return klass(endog, exog=exog, missing=missing, hasconst=hasconst, **kwargs)