import pandas
import numpy as np

from statsmodels.tools import data

def test_missing_data_pandas():
    """
    Fixes GH: #144
    """
    X = np.random.random((10,5))
    X[1,2] = np.nan
    df = pandas.DataFrame(X)
    vals, cnames, rnames = data.interpret_data(df)
    np.testing.assert_equal(rnames.tolist(), [0,2,3,4,5,6,7,8,9])

def test_structarray():
    X = np.random.random((9,)).view([('var1', 'f8'),
                                        ('var2', 'f8'),
                                        ('var3', 'f8')])
    vals, cnames, rnames = data.interpret_data(X)
    np.testing.assert_equal(cnames, X.dtype.names)
    np.testing.assert_equal(vals, X.view((float,3)))
    np.testing.assert_equal(rnames, None)

def test_recarray():
    X = np.random.random((9,)).view([('var1', 'f8'),
                                        ('var2', 'f8'),
                                        ('var3', 'f8')])
    vals, cnames, rnames = data.interpret_data(X.view(np.recarray))
    np.testing.assert_equal(cnames, X.dtype.names)
    np.testing.assert_equal(vals, X.view((float,3)))
    np.testing.assert_equal(rnames, None)


def test_dataframe():
    X = np.random.random((10,5))
    df = pandas.DataFrame(X)
    vals, cnames, rnames = data.interpret_data(df)
    np.testing.assert_equal(vals, df.values)
    np.testing.assert_equal(rnames.tolist(), df.index.tolist())
    np.testing.assert_equal(cnames, df.columns.tolist())

import pandas
import numpy as np

from statsmodels.tools import data

def test_missing_data_pandas():
    """
    Fixes GH: #144
    """
    X = np.random.random((10,5))
    X[1,2] = np.nan
    df = pandas.DataFrame(X)
    vals, cnames, rnames = data.interpret_data(df)
    np.testing.assert_equal(rnames.tolist(), [0,2,3,4,5,6,7,8,9])

def test_structarray():
    X = np.random.random((9,)).view([('var1', 'f8'),
                                        ('var2', 'f8'),
                                        ('var3', 'f8')])
    vals, cnames, rnames = data.interpret_data(X)
    np.testing.assert_equal(cnames, X.dtype.names)
    np.testing.assert_equal(vals, X.view((float,3)))
    np.testing.assert_equal(rnames, None)

def test_recarray():
    X = np.random.random((9,)).view([('var1', 'f8'),
                                        ('var2', 'f8'),
                                        ('var3', 'f8')])
    vals, cnames, rnames = data.interpret_data(X.view(np.recarray))
    np.testing.assert_equal(cnames, X.dtype.names)
    np.testing.assert_equal(vals, X.view((float,3)))
    np.testing.assert_equal(rnames, None)


def test_dataframe():
    X = np.random.random((10,5))
    df = pandas.DataFrame(X)
    vals, cnames, rnames = data.interpret_data(df)
    np.testing.assert_equal(vals, df.values)
    np.testing.assert_equal(rnames.tolist(), df.index.tolist())
    np.testing.assert_equal(cnames, df.columns.tolist())

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))


Test patsy DesignMatrix with exog == None