예제 #1
0
def test_check_array():
    # accept_sparse == None
    # raise error on sparse inputs
    X = [[1, 2], [3, 4]]
    X_csr = sp.csr_matrix(X)
    assert_raises(TypeError, check_array, X_csr)
    # ensure_2d
    assert_warns(DeprecationWarning, check_array, [0, 1, 2])
    X_array = check_array([0, 1, 2])
    assert_equal(X_array.ndim, 2)
    X_array = check_array([0, 1, 2], ensure_2d=False)
    assert_equal(X_array.ndim, 1)
    # don't allow ndim > 3
    X_ndim = np.arange(8).reshape(2, 2, 2)
    assert_raises(ValueError, check_array, X_ndim)
    check_array(X_ndim, allow_nd=True)  # doesn't raise
    # force_all_finite
    X_inf = np.arange(4).reshape(2, 2).astype(np.float)
    X_inf[0, 0] = np.inf
    assert_raises(ValueError, check_array, X_inf)
    check_array(X_inf, force_all_finite=False)  # no raise
    # nan check
    X_nan = np.arange(4).reshape(2, 2).astype(np.float)
    X_nan[0, 0] = np.nan
    assert_raises(ValueError, check_array, X_nan)
    check_array(X_inf, force_all_finite=False)  # no raise

    # dtype and order enforcement.
    X_C = np.arange(4).reshape(2, 2).copy("C")
    X_F = X_C.copy("F")
    X_int = X_C.astype(np.int)
    X_float = X_C.astype(np.float)
    Xs = [X_C, X_F, X_int, X_float]
    dtypes = [np.int32, np.int, np.float, np.float32, None, np.bool, object]
    orders = ['C', 'F', None]
    copys = [True, False]

    for X, dtype, order, copy in product(Xs, dtypes, orders, copys):
        X_checked = check_array(X, dtype=dtype, order=order, copy=copy)
        if dtype is not None:
            assert_equal(X_checked.dtype, dtype)
        else:
            assert_equal(X_checked.dtype, X.dtype)
        if order == 'C':
            assert_true(X_checked.flags['C_CONTIGUOUS'])
            assert_false(X_checked.flags['F_CONTIGUOUS'])
        elif order == 'F':
            assert_true(X_checked.flags['F_CONTIGUOUS'])
            assert_false(X_checked.flags['C_CONTIGUOUS'])
        if copy:
            assert_false(X is X_checked)
        else:
            # doesn't copy if it was already good
            if (X.dtype == X_checked.dtype and
                    X_checked.flags['C_CONTIGUOUS'] == X.flags['C_CONTIGUOUS']
                    and X_checked.flags['F_CONTIGUOUS'] == X.flags['F_CONTIGUOUS']):
                assert_true(X is X_checked)

    # allowed sparse != None
    X_csc = sp.csc_matrix(X_C)
    X_coo = X_csc.tocoo()
    X_dok = X_csc.todok()
    X_int = X_csc.astype(np.int)
    X_float = X_csc.astype(np.float)

    Xs = [X_csc, X_coo, X_dok, X_int, X_float]
    accept_sparses = [['csr', 'coo'], ['coo', 'dok']]
    for X, dtype, accept_sparse, copy in product(Xs, dtypes, accept_sparses,
                                                 copys):
        with warnings.catch_warnings(record=True) as w:
            X_checked = check_array(X, dtype=dtype,
                                    accept_sparse=accept_sparse, copy=copy)
        if (dtype is object or sp.isspmatrix_dok(X)) and len(w):
            message = str(w[0].message)
            messages = ["object dtype is not supported by sparse matrices",
                        "Can't check dok sparse matrix for nan or inf."]
            assert_true(message in messages)
        else:
            assert_equal(len(w), 0)
        if dtype is not None:
            assert_equal(X_checked.dtype, dtype)
        else:
            assert_equal(X_checked.dtype, X.dtype)
        if X.format in accept_sparse:
            # no change if allowed
            assert_equal(X.format, X_checked.format)
        else:
            # got converted
            assert_equal(X_checked.format, accept_sparse[0])
        if copy:
            assert_false(X is X_checked)
        else:
            # doesn't copy if it was already good
            if (X.dtype == X_checked.dtype and X.format == X_checked.format):
                assert_true(X is X_checked)

    # other input formats
    # convert lists to arrays
    X_dense = check_array([[1, 2], [3, 4]])
    assert_true(isinstance(X_dense, np.ndarray))
    # raise on too deep lists
    assert_raises(ValueError, check_array, X_ndim.tolist())
    check_array(X_ndim.tolist(), allow_nd=True)  # doesn't raise
예제 #2
0
def test_check_array():
    # accept_sparse == None
    # raise error on sparse inputs
    X = [[1, 2], [3, 4]]
    X_csr = sp.csr_matrix(X)
    assert_raises(TypeError, check_array, X_csr)
    # ensure_2d
    assert_warns(DeprecationWarning, check_array, [0, 1, 2])
    X_array = check_array([0, 1, 2])
    assert_equal(X_array.ndim, 2)
    X_array = check_array([0, 1, 2], ensure_2d=False)
    assert_equal(X_array.ndim, 1)
    # don't allow ndim > 3
    X_ndim = np.arange(8).reshape(2, 2, 2)
    assert_raises(ValueError, check_array, X_ndim)
    check_array(X_ndim, allow_nd=True)  # doesn't raise
    # force_all_finite
    X_inf = np.arange(4).reshape(2, 2).astype(np.float)
    X_inf[0, 0] = np.inf
    assert_raises(ValueError, check_array, X_inf)
    check_array(X_inf, force_all_finite=False)  # no raise
    # nan check
    X_nan = np.arange(4).reshape(2, 2).astype(np.float)
    X_nan[0, 0] = np.nan
    assert_raises(ValueError, check_array, X_nan)
    check_array(X_inf, force_all_finite=False)  # no raise

    # dtype and order enforcement.
    X_C = np.arange(4).reshape(2, 2).copy("C")
    X_F = X_C.copy("F")
    X_int = X_C.astype(np.int)
    X_float = X_C.astype(np.float)
    Xs = [X_C, X_F, X_int, X_float]
    dtypes = [np.int32, np.int, np.float, np.float32, None, np.bool, object]
    orders = ['C', 'F', None]
    copys = [True, False]

    for X, dtype, order, copy in product(Xs, dtypes, orders, copys):
        X_checked = check_array(X, dtype=dtype, order=order, copy=copy)
        if dtype is not None:
            assert_equal(X_checked.dtype, dtype)
        else:
            assert_equal(X_checked.dtype, X.dtype)
        if order == 'C':
            assert_true(X_checked.flags['C_CONTIGUOUS'])
            assert_false(X_checked.flags['F_CONTIGUOUS'])
        elif order == 'F':
            assert_true(X_checked.flags['F_CONTIGUOUS'])
            assert_false(X_checked.flags['C_CONTIGUOUS'])
        if copy:
            assert_false(X is X_checked)
        else:
            # doesn't copy if it was already good
            if (X.dtype == X_checked.dtype and X_checked.flags['C_CONTIGUOUS']
                    == X.flags['C_CONTIGUOUS']
                    and X_checked.flags['F_CONTIGUOUS']
                    == X.flags['F_CONTIGUOUS']):
                assert_true(X is X_checked)

    # allowed sparse != None
    X_csc = sp.csc_matrix(X_C)
    X_coo = X_csc.tocoo()
    X_dok = X_csc.todok()
    X_int = X_csc.astype(np.int)
    X_float = X_csc.astype(np.float)

    Xs = [X_csc, X_coo, X_dok, X_int, X_float]
    accept_sparses = [['csr', 'coo'], ['coo', 'dok']]
    for X, dtype, accept_sparse, copy in product(Xs, dtypes, accept_sparses,
                                                 copys):
        with warnings.catch_warnings(record=True) as w:
            X_checked = check_array(X,
                                    dtype=dtype,
                                    accept_sparse=accept_sparse,
                                    copy=copy)
        if (dtype is object or sp.isspmatrix_dok(X)) and len(w):
            message = str(w[0].message)
            messages = [
                "object dtype is not supported by sparse matrices",
                "Can't check dok sparse matrix for nan or inf."
            ]
            assert_true(message in messages)
        else:
            assert_equal(len(w), 0)
        if dtype is not None:
            assert_equal(X_checked.dtype, dtype)
        else:
            assert_equal(X_checked.dtype, X.dtype)
        if X.format in accept_sparse:
            # no change if allowed
            assert_equal(X.format, X_checked.format)
        else:
            # got converted
            assert_equal(X_checked.format, accept_sparse[0])
        if copy:
            assert_false(X is X_checked)
        else:
            # doesn't copy if it was already good
            if (X.dtype == X_checked.dtype and X.format == X_checked.format):
                assert_true(X is X_checked)

    # other input formats
    # convert lists to arrays
    X_dense = check_array([[1, 2], [3, 4]])
    assert_true(isinstance(X_dense, np.ndarray))
    # raise on too deep lists
    assert_raises(ValueError, check_array, X_ndim.tolist())
    check_array(X_ndim.tolist(), allow_nd=True)  # doesn't raise
예제 #3
0
def test_check_array_dtype_stability():
    # test that lists with ints don't get converted to floats
    X = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
    assert_equal(check_array(X).dtype.kind, "i")
    assert_equal(check_array(X, ensure_2d=False).dtype.kind, "i")
예제 #4
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def test_check_array_dtype_stability():
    # test that lists with ints don't get converted to floats
    X = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
    assert_equal(check_array(X).dtype.kind, "i")
    assert_equal(check_array(X, ensure_2d=False).dtype.kind, "i")