def test_dateheader_unsupported(self):
        def read_dateheader_unsupported():
            ofile = open(test8)
            rel, attrs = read_header(ofile)
            ofile.close()

        assert_raises(ValueError, read_dateheader_unsupported)

def test_orthogonal_procrustes_shape_mismatch():
    np.random.seed(1234)
    shapes = ((3, 3), (3, 4), (4, 3), (4, 4))
    for a, b in permutations(shapes, 2):
        A = np.random.randn(*a)
        B = np.random.randn(*b)
        assert_raises(ValueError, orthogonal_procrustes, A, B)

def test_abort_co_read(conn, monkeypatch):
    # We need to delay the write to ensure that we encounter a blocking read
    path = '/foo/wurfl'
    chunks = [300, 317, 283]
    delay = 10
    while True:
        monkeypatch.setattr(MockRequestHandler, 'do_GET',
                            get_chunked_GET_handler(path, chunks, delay))
        conn.send_request('GET', path)
        resp = conn.read_response()
        assert resp.status == 200
        cofun = conn.co_read(450)
        try:
            next(cofun)
        except StopIteration:
            # Not good, need to wait longer
            pass
        else:
            break
        finally:
            conn.disconnect()

        if delay > 5000:
            pytest.fail('no blocking read even with %f sec sleep' % delay)
        delay *= 2

    assert_raises(dugong.ConnectionClosed, next, cofun)

    def test_neldermead_initial_simplex_bad(self):
        # Check it fails with a bad simplices
        bad_simplices = []

        simplex = np.zeros((3, 2))
        simplex[...] = self.startparams[:2]
        for j in range(2):
            simplex[j+1,j] += 0.1
        bad_simplices.append(simplex)

        simplex = np.zeros((3, 3))
        bad_simplices.append(simplex)

        for simplex in bad_simplices:
            if self.use_wrapper:
                opts = {'maxiter': self.maxiter, 'disp': False,
                        'return_all': False, 'initial_simplex': simplex}
                assert_raises(ValueError,
                              optimize.minimize, self.func, self.startparams, args=(),
                              method='Nelder-mead', options=opts)
            else:
                assert_raises(ValueError, optimize.fmin, self.func, self.startparams,
                              args=(), maxiter=self.maxiter,
                              full_output=True, disp=False, retall=False,
                              initial_simplex=simplex)

def test_roots_hermite():
    rootf = sc.roots_hermite
    evalf = orth.eval_hermite
    weightf = orth.hermite(5).weight_func

    verify_gauss_quad(rootf, evalf, weightf, -np.inf, np.inf, 5)
    verify_gauss_quad(rootf, evalf, weightf, -np.inf, np.inf, 25, atol=1e-13)
    verify_gauss_quad(rootf, evalf, weightf, -np.inf, np.inf, 100, atol=1e-12)

    # Golub-Welsch branch
    x, w = sc.roots_hermite(5, False)
    y, v, m = sc.roots_hermite(5, True)
    assert_allclose(x, y, 1e-14, 1e-14)
    assert_allclose(w, v, 1e-14, 1e-14)

    muI, muI_err = integrate.quad(weightf, -np.inf, np.inf)
    assert_allclose(m, muI, rtol=muI_err)

    # Asymptotic branch (switch over at n >= 150)
    x, w = sc.roots_hermite(200, False)
    y, v, m = sc.roots_hermite(200, True)
    assert_allclose(x, y, 1e-14, 1e-14)
    assert_allclose(w, v, 1e-14, 1e-14)
    assert_allclose(sum(v), m, 1e-14, 1e-14)

    assert_raises(ValueError, sc.roots_hermite, 0)
    assert_raises(ValueError, sc.roots_hermite, 3.3)

    def test_random_sampling(self):
        # Simple sanity checks for sparse random sampling.
        for f in sprand, _sprandn:
            for t in [np.float32, np.float64, np.longdouble]:
                x = f(5, 10, density=0.1, dtype=t)
                assert_equal(x.dtype, t)
                assert_equal(x.shape, (5, 10))
                assert_equal(x.nonzero()[0].size, 5)

            x1 = f(5, 10, density=0.1, random_state=4321)
            assert_equal(x1.dtype, np.double)

            x2 = f(5, 10, density=0.1, random_state=np.random.RandomState(4321))

            assert_array_equal(x1.data, x2.data)
            assert_array_equal(x1.row, x2.row)
            assert_array_equal(x1.col, x2.col)

            for density in [0.0, 0.1, 0.5, 1.0]:
                x = f(5, 10, density=density)
                assert_equal(x.nnz, int(density * np.prod(x.shape)))

            for fmt in ['coo', 'csc', 'csr', 'lil']:
                x = f(5, 10, format=fmt)
                assert_equal(x.format, fmt)

            assert_raises(ValueError, lambda: f(5, 10, 1.1))
            assert_raises(ValueError, lambda: f(5, 10, -0.1))

    def test_cardinality(self):
        test_create = self.check_cardinality_create
        test_edit = self.check_cardinality_create

        for prop,             inmin, inmax, outmin, outmax in [
            (CARD.card1_in,   1,     1,     0,      999),
            (CARD.card01_in,  0,     1,     0,      999),
            (CARD.card23_in,  2,     3,     0,      999),
            (CARD.card1n_in,  1,   999,     0,      999),
            (CARD.card0_in,   0,     0,     0,      999),
            (CARD.card1_out,  0,   999,     1,        1),
            (CARD.card01_out, 0,   999,     0,        1),
            (CARD.card23_out, 0,   999,     2,        3),
            (CARD.card1n_out, 0,   999,     1,      999),
            (CARD.card0_out,  0,   999,     0,        0),
            (EXAMPLE.label,   0,     0,     0,        1),
            ]:
            for i in range(4):
                must_pass_in = (inmin <= i <= inmax)
                must_pass_out = (outmin <= i <= outmax)

                for test_proc in [self.check_cardinality_create,
                                  self.check_cardinality_create]:

                    if must_pass_in:
                        test_proc("in", prop, i)
                    else:
                        with assert_raises(InvalidDataError):
                            test_proc("in", prop, i)

                    if must_pass_out:
                        test_proc("out", prop, i)
                    else:
                        with assert_raises(InvalidDataError):
                            test_proc("out", prop, i)

 def test_unknown_method(self):
     method = "foo"
     f0 = 10.0
     f1 = 20.0
     t1 = 1.0
     t = np.linspace(0, t1, 10)
     assert_raises(ValueError, waveforms.chirp, t, f0, t1, f1, method)

    def check(caller, func, user_data):
        caller = CALLERS[caller]
        user_data = USER_DATAS[user_data]()
        func = BAD_FUNCS[func]()

        if func is callback_python:
            func2 = lambda x: func(x, 2.0)
        else:
            func2 = LowLevelCallable(func, user_data)
            func = LowLevelCallable(func)

        # Test that basic call fails
        assert_raises(ValueError, caller, LowLevelCallable(func), 1.0)

        # Test that passing in user_data also fails
        assert_raises(ValueError, caller, func2, 1.0)

        # Test error message
        llfunc = LowLevelCallable(func)
        try:
            caller(llfunc, 1.0)
        except ValueError as err:
            msg = str(err)
            assert_(llfunc.signature in msg, msg)
            assert_('double (double, double, int *, void *)' in msg, msg)

def test_tzrzf():
    """
    This test performs an RZ decomposition in which an m x n upper trapezoidal
    array M (m <= n) is factorized as M = [R 0] * Z where R is upper triangular
    and Z is unitary.
    """
    seed(1234)
    m, n = 10, 15
    for ind, dtype in enumerate(DTYPES):
        tzrzf, tzrzf_lw = get_lapack_funcs(('tzrzf', 'tzrzf_lwork'),
                                           dtype=dtype)
        lwork = _compute_lwork(tzrzf_lw, m, n)

        if ind < 2:
            A = triu(rand(m, n).astype(dtype))
        else:
            A = triu((rand(m, n) + rand(m, n)*1j).astype(dtype))

        # assert wrong shape arg, f2py returns generic error
        assert_raises(Exception, tzrzf, A.T)
        rz, tau, info = tzrzf(A, lwork=lwork)
        # Check success
        assert_(info == 0)

        # Get Z manually for comparison
        R = np.hstack((rz[:, :m], np.zeros((m, n-m), dtype=dtype)))
        V = np.hstack((np.eye(m, dtype=dtype), rz[:, m:]))
        Id = np.eye(n, dtype=dtype)
        ref = [Id-tau[x]*V[[x], :].T.dot(V[[x], :].conj()) for x in range(m)]
        Z = reduce(np.dot, ref)
        assert_allclose(R.dot(Z) - A, zeros_like(A, dtype=dtype),
                        atol=10*np.spacing(dtype(1.0).real), rtol=0.)

 def test_hyperbolic_zero_freq(self):
     # f0=0 or f1=0 must raise a ValueError.
     method = 'hyperbolic'
     t1 = 1.0
     t = np.linspace(0, t1, 5)
     assert_raises(ValueError, waveforms.chirp, t, 0, t1, 1, method)
     assert_raises(ValueError, waveforms.chirp, t, 1, t1, 0, method)

def test_pftrs():
    """
    Test Cholesky factorization of a positive definite Rectengular Full
    Packed (RFP) format array and solve a linear system
    """
    seed(1234)
    for ind, dtype in enumerate(DTYPES):
        n = 20
        if ind > 1:
            A = (rand(n, n) + rand(n, n)*1j).astype(dtype)
            A = A + A.conj().T + n*eye(n)
        else:
            A = (rand(n, n)).astype(dtype)
            A = A + A.T + n*eye(n)

        B = ones((n, 3), dtype=dtype)
        Bf1 = ones((n+2, 3), dtype=dtype)
        Bf2 = ones((n-2, 3), dtype=dtype)
        pftrs, pftrf, trttf, tfttr = get_lapack_funcs(('pftrs',
                                                       'pftrf',
                                                       'trttf',
                                                       'tfttr'),
                                                      dtype=dtype)

        # Get the original array from TP
        Afp, info = trttf(A)
        A_chol_rfp, info = pftrf(n, Afp)
        # larger B arrays shouldn't segfault
        soln, info = pftrs(n, A_chol_rfp, Bf1)
        assert_(info == 0)
        assert_raises(Exception, pftrs, n, A_chol_rfp, Bf2)
        soln, info = pftrs(n, A_chol_rfp, B)
        assert_(info == 0)
        assert_array_almost_equal(solve(A, B), soln,
                                  decimal=4 if ind % 2 == 0 else 6)

    def test_intersect(self):
        Delta = 1.0

        x = np.zeros(3)
        s = np.array([1.0, 0.0, 0.0])
        t_neg, t_pos = intersect_trust_region(x, s, Delta)
        assert_equal(t_neg, -1)
        assert_equal(t_pos, 1)

        s = np.array([-1.0, 1.0, -1.0])
        t_neg, t_pos = intersect_trust_region(x, s, Delta)
        assert_allclose(t_neg, -3**-0.5)
        assert_allclose(t_pos, 3**-0.5)

        x = np.array([0.5, -0.5, 0])
        s = np.array([0, 0, 1.0])
        t_neg, t_pos = intersect_trust_region(x, s, Delta)
        assert_allclose(t_neg, -2**-0.5)
        assert_allclose(t_pos, 2**-0.5)

        x = np.ones(3)
        assert_raises(ValueError, intersect_trust_region, x, s, Delta)

        x = np.zeros(3)
        s = np.zeros(3)
        assert_raises(ValueError, intersect_trust_region, x, s, Delta)

 def test_type_error(self):
     c = [1]
     A_eq = [[1]]
     b_eq = "hello"
     assert_raises(TypeError, linprog,
                   c, A_eq=A_eq, b_eq=b_eq,
                   method=self.method, options=self.options)

    def test_ctypes_variants(self):
        sin_0 = get_clib_test_routine('_sin_0', ctypes.c_double,
                                      ctypes.c_double, ctypes.c_void_p)

        sin_1 = get_clib_test_routine('_sin_1', ctypes.c_double,
                                      ctypes.c_int, ctypes.POINTER(ctypes.c_double),
                                      ctypes.c_void_p)

        sin_2 = get_clib_test_routine('_sin_2', ctypes.c_double,
                                      ctypes.c_double)

        sin_3 = get_clib_test_routine('_sin_3', ctypes.c_double,
                                      ctypes.c_int, ctypes.POINTER(ctypes.c_double))

        sin_4 = get_clib_test_routine('_sin_3', ctypes.c_double,
                                      ctypes.c_int, ctypes.c_double)

        all_sigs = [sin_0, sin_1, sin_2, sin_3, sin_4]
        legacy_sigs = [sin_2, sin_4]
        legacy_only_sigs = [sin_4]

        # LowLevelCallables work for new signatures
        for j, func in enumerate(all_sigs):
            callback = LowLevelCallable(func)
            if func in legacy_only_sigs:
                assert_raises(ValueError, quad, callback, 0, pi)
            else:
                assert_allclose(quad(callback, 0, pi)[0], 2.0)

        # Plain ctypes items work only for legacy signatures
        for j, func in enumerate(legacy_sigs):
            if func in legacy_sigs:
                assert_allclose(quad(func, 0, pi)[0], 2.0)
            else:
                assert_raises(ValueError, quad, func, 0, pi)

 def test_syr2k_wrong_c(self):
     f = getattr(fblas, 'dsyr2k', None)
     if f is not None:
         assert_raises(Exception, f, **{'a': self.a,
                                        'b': self.b,
                                        'alpha': 1.,
                                        'c': np.zeros((15, 8))})

def test_t_eval():
    rtol = 1e-3
    atol = 1e-6
    y0 = [1/3, 2/9]
    for t_span in ([5, 9], [5, 1]):
        t_eval = np.linspace(t_span[0], t_span[1], 10)
        res = solve_ivp(fun_rational, t_span, y0, rtol=rtol, atol=atol,
                        t_eval=t_eval)
        assert_equal(res.t, t_eval)
        assert_(res.t_events is None)
        assert_(res.success)
        assert_equal(res.status, 0)

        y_true = sol_rational(res.t)
        e = compute_error(res.y, y_true, rtol, atol)
        assert_(np.all(e < 5))

    t_eval = [5, 5.01, 7, 8, 8.01, 9]
    res = solve_ivp(fun_rational, [5, 9], y0, rtol=rtol, atol=atol,
                    t_eval=t_eval)
    assert_equal(res.t, t_eval)
    assert_(res.t_events is None)
    assert_(res.success)
    assert_equal(res.status, 0)

    y_true = sol_rational(res.t)
    e = compute_error(res.y, y_true, rtol, atol)
    assert_(np.all(e < 5))

    t_eval = [5, 4.99, 3, 1.5, 1.1, 1.01, 1]
    res = solve_ivp(fun_rational, [5, 1], y0, rtol=rtol, atol=atol,
                    t_eval=t_eval)
    assert_equal(res.t, t_eval)
    assert_(res.t_events is None)
    assert_(res.success)
    assert_equal(res.status, 0)

    t_eval = [5.01, 7, 8, 8.01]
    res = solve_ivp(fun_rational, [5, 9], y0, rtol=rtol, atol=atol,
                    t_eval=t_eval)
    assert_equal(res.t, t_eval)
    assert_(res.t_events is None)
    assert_(res.success)
    assert_equal(res.status, 0)

    y_true = sol_rational(res.t)
    e = compute_error(res.y, y_true, rtol, atol)
    assert_(np.all(e < 5))

    t_eval = [4.99, 3, 1.5, 1.1, 1.01]
    res = solve_ivp(fun_rational, [5, 1], y0, rtol=rtol, atol=atol,
                    t_eval=t_eval)
    assert_equal(res.t, t_eval)
    assert_(res.t_events is None)
    assert_(res.success)
    assert_equal(res.status, 0)

    t_eval = [4, 6]
    assert_raises(ValueError, solve_ivp, fun_rational, [5, 9], y0,
                  rtol=rtol, atol=atol, t_eval=t_eval)

def test_read_opts():
    # tests if read is seeing option sets, at initialization and after
    # initialization
    arr = np.arange(6).reshape(1,6)
    stream = BytesIO()
    savemat(stream, {'a': arr})
    rdr = MatFile5Reader(stream)
    back_dict = rdr.get_variables()
    rarr = back_dict['a']
    assert_array_equal(rarr, arr)
    rdr = MatFile5Reader(stream, squeeze_me=True)
    assert_array_equal(rdr.get_variables()['a'], arr.reshape((6,)))
    rdr.squeeze_me = False
    assert_array_equal(rarr, arr)
    rdr = MatFile5Reader(stream, byte_order=boc.native_code)
    assert_array_equal(rdr.get_variables()['a'], arr)
    # inverted byte code leads to error on read because of swapped
    # header etc
    rdr = MatFile5Reader(stream, byte_order=boc.swapped_code)
    assert_raises(Exception, rdr.get_variables)
    rdr.byte_order = boc.native_code
    assert_array_equal(rdr.get_variables()['a'], arr)
    arr = np.array(['a string'])
    stream.truncate(0)
    stream.seek(0)
    savemat(stream, {'a': arr})
    rdr = MatFile5Reader(stream)
    assert_array_equal(rdr.get_variables()['a'], arr)
    rdr = MatFile5Reader(stream, chars_as_strings=False)
    carr = np.atleast_2d(np.array(list(arr.item()), dtype='U1'))
    assert_array_equal(rdr.get_variables()['a'], carr)
    rdr.chars_as_strings = True
    assert_array_equal(rdr.get_variables()['a'], arr)

def test_put_s3error_med(backend, monkeypatch):
    '''Fail as soon as data is received'''
    data = b'hello there, let us see whats going on'
    key = 'borg'

    # Monkeypatch request handler to produce 3 errors
    handler_class = mock_server.S3CRequestHandler
    def do_PUT(self, real_PUT=handler_class.do_PUT, count=[0]):
        count[0] += 1
        # Note: every time we return an error, the request will be retried
        # *twice*: once because of the error, and a second time because the
        # connection has been closed by the server.
        if count[0] > 2:
            return real_PUT(self)
        else:
            self.send_error(503, code='OperationAborted')

            # Since we don't read all the data, we have to close
            # the connection
            self.close_connection = True

    monkeypatch.setattr(handler_class, 'do_PUT', do_PUT)
    fh = backend.open_write(key)
    fh.write(data)
    assert_raises(OperationAbortedError, fh.close)

    enable_temp_fail(backend)
    fh.close()

def test_corrupted_data():
    import zlib
    for exc, fname in [(ValueError, 'corrupted_zlib_data.mat'),
                       (zlib.error, 'corrupted_zlib_checksum.mat')]:
        with open(pjoin(test_data_path, fname), 'rb') as fp:
            rdr = MatFile5Reader(fp)
            assert_raises(exc, rdr.get_variables)