C++ array::get_type方法代码示例

void pydynd::array_setitem(const dynd::nd::array& n, PyObject *subscript, PyObject *value)
{
    if (subscript == Py_Ellipsis) {
        array_broadcast_assign_from_py(n, value);
#if PY_VERSION_HEX < 0x03000000
    } else if (PyInt_Check(subscript)) {
        long i = PyInt_AS_LONG(subscript);
        const char *metadata = n.get_ndo_meta();
        char *data = n.get_readwrite_originptr();
        ndt::type d = n.get_type().at_single(i, &metadata, const_cast<const char **>(&data));
        array_broadcast_assign_from_py(d, metadata, data, value);
#endif // PY_VERSION_HEX < 0x03000000
    } else if (PyLong_Check(subscript)) {
        intptr_t i = PyLong_AsSsize_t(subscript);
        if (i == -1 && PyErr_Occurred()) {
            throw runtime_error("error converting int value");
        }
        const char *metadata = n.get_ndo_meta();
        char *data = n.get_readwrite_originptr();
        ndt::type d = n.get_type().at_single(i, &metadata, const_cast<const char **>(&data));
        array_broadcast_assign_from_py(d, metadata, data, value);
    } else {
        intptr_t size;
        shortvector<irange> indices;
        pyobject_as_irange_array(size, indices, subscript);
        array_broadcast_assign_from_py(n.at_array(size, indices.get(), false), value);
    }
}

bool pydynd::array_contains(const dynd::nd::array& n, PyObject *x)
{
    if (n.get_ndo() == NULL) {
        return false;
    }
    if (n.get_ndim() == 0) {
        // TODO: Allow for struct types, etc?
        throw runtime_error("cannot call __contains__ on a scalar dynd array");
    }

    // Turn 'n' into type/metadata/data with a uniform_dim leading dimension
    nd::array tmp;
    ndt::type dt;
    const base_uniform_dim_type *budd;
    const char *metadata, *data;
    if (n.get_type().get_kind() == uniform_dim_kind) {
        dt = n.get_type();
        budd = static_cast<const base_uniform_dim_type *>(dt.extended());
        metadata = n.get_ndo_meta();
        data = n.get_readonly_originptr();
    } else {
        tmp = n.eval();
        if (tmp.get_type().get_kind() != uniform_dim_kind) {
            throw runtime_error("internal error in array_contains: expected uniform_dim kind after eval() call");
        }
        dt = tmp.get_type();
        budd = static_cast<const base_uniform_dim_type *>(dt.extended());
        metadata = tmp.get_ndo_meta();
        data = tmp.get_readonly_originptr();
    }

    // Turn 'x' into a dynd array, and make a comparison kernel
    nd::array x_ndo = array_from_py(x, 0, false);
    const ndt::type& x_dt = x_ndo.get_type();
    const char *x_metadata = x_ndo.get_ndo_meta();
    const char *x_data = x_ndo.get_readonly_originptr();
    const ndt::type& child_dt = budd->get_element_type();
    const char *child_metadata = metadata + budd->get_element_metadata_offset();
    comparison_ckernel_builder k;
    try {
        make_comparison_kernel(&k, 0,
                    x_dt, x_metadata, child_dt, child_metadata,
                    comparison_type_equal, &eval::default_eval_context);
    } catch(const not_comparable_error&) {
        return false;
    }

    contains_data aux;
    aux.x_data = x_data;
    aux.k = &k;
    aux.found = false;
    budd->foreach_leading(const_cast<char *>(data), metadata, &contains_callback, &aux);
    return aux.found;
}

inline ::testing::AssertionResult CompareDyNDArrayToJSON(const char *expr1, const char *expr2, const char *json,
                                                         const dynd::nd::array &b)
{
  using namespace dynd;
  nd::array a(nd::empty(b.get_type()));
  parse_json(a, json);
  return CompareDyNDArrays(expr1, expr2, a, b);
}

void
pydynd::array_broadcast_assign_from_py(const dynd::nd::array &a,
                                       PyObject *value,
                                       const dynd::eval::eval_context *ectx)
{
  array_broadcast_assign_from_py(a.get_type(), a.get()->metadata(), a.data(),
                                 value, ectx);
}

void
pydynd::array_broadcast_assign_from_py(const dynd::nd::array &a,
                                       PyObject *value,
                                       const dynd::eval::eval_context *ectx)
{
  array_broadcast_assign_from_py(a.get_type(), a.get_arrmeta(),
                                 a.get_readwrite_originptr(), value, ectx);
}

inline ::testing::AssertionResult CompareDyNDArrayValues(const char *expr1, const char *expr2,
                                                         const dynd::nd::array &val1, const dynd::nd::array &val2)
{
  using namespace dynd;
  ndt::type common_tp;
  try {
    common_tp = promote_types_arithmetic(val1.get_type(), val2.get_type());
  }
  catch (const type_error &) {
    return ::testing::AssertionFailure() << "The types of " << expr1 << " and " << expr2
                                         << " do not have mutually promotable types\n" << expr1 << " has type "
                                         << val1.get_type() << ",\n" << expr2 << " has type " << val2.get_type() << ".";
  }
  nd::array v1 = nd::empty(common_tp), v2 = nd::empty(common_tp);
  v1.vals() = val1;
  v2.vals() = val2;
  return CompareDyNDArrays(expr1, expr2, v1, v2);
}

nd::string::string(const nd::array& rhs)
{
    if (!rhs.is_null()) {
        if (rhs.is_immutable() &&
                rhs.get_type().get_type_id() == string_type_id &&
                rhs.get_type().extended<ndt::string_type>()->get_encoding() ==
                    string_encoding_utf_8) {
            // It's already immutable and the right type
            m_value = rhs;
        } else if (rhs.get_type().value_type().get_kind() == string_kind) {
            m_value = rhs.ucast(ndt::make_string()).eval_immutable();
        } else {
            stringstream ss;
            ss << "Cannot implicitly convert nd::array of type "
               << rhs.get_type().value_type() << " to  string";
            throw type_error(ss.str());
        }
    }
}

inline ::testing::AssertionResult AssertArrayNear(const char *expected_expr, const char *actual_expr,
                                                  const char *rel_error_max_expr, const dynd::nd::array &expected,
                                                  const dynd::nd::array &actual, double rel_error_max)
{
  const dynd::ndt::type &expected_tp = expected.get_type();
  const dynd::ndt::type &actual_tp = actual.get_type();
  if (expected_tp.get_type_id() == dynd::cuda_device_type_id && actual_tp.get_type_id() == dynd::cuda_device_type_id) {
    return AssertArrayNear(expected_expr, actual_expr, rel_error_max_expr, expected.to_host(), actual.to_host(),
                           rel_error_max);
  }

  std::unique_ptr<test_class<dynd::complex<double>>> c(new test_class<dynd::complex<double>>(rel_error_max));

  dynd::nd::callable af = dynd::nd::functional::elwise(dynd::nd::functional::apply(c.get()));
  af(expected, actual);

  bool res = c->flag;

  if (res) {
    return ::testing::AssertionSuccess();
  }

  return ::testing::AssertionFailure() << "the values do not match";
}