C++ array::is_null方法代码示例

ndt::busdate_type::busdate_type(busdate_roll_t roll, const bool *weekmask,
                                const nd::array &holidays)
    : base_type(busdate_type_id, datetime_kind, 4, 4, type_flag_scalar, 0, 0,
                0),
      m_roll(roll)
{
  memcpy(m_workweek, weekmask, sizeof(m_workweek));
  m_busdays_in_weekmask = 0;
  for (int i = 0; i < 7; ++i) {
    m_busdays_in_weekmask += weekmask[i] ? 1 : 0;
  }
  if (!holidays.is_null()) {
    nd::array hol = holidays.ucast(make_date()).eval_immutable();
    // TODO: Make sure hol is contiguous and one-dimensional
    m_holidays = hol;
  }
}

nd::callable::callable(const nd::array &rhs)
{
  if (!rhs.is_null()) {
    if (rhs.get_type().get_type_id() == callable_type_id) {
      const callable_type_data *af =
          reinterpret_cast<const callable_type_data *>(
              rhs.cdata());
      if (af->instantiate != NULL) {
        // It's valid: callable type, contains instantiate function.
        m_value = rhs;
      } else {
        throw invalid_argument("Require a non-empty callable, "
                               "provided callable has NULL "
                               "instantiate function");
      }
    } else {
      stringstream ss;
      ss << "Cannot implicitly convert nd::array of type "
         << rhs.get_type().value_type() << " to  callable";
      throw type_error(ss.str());
    }
  }
}

/**
 * Adds a ckernel layer for processing one dimension of the reduction.
 * This is for a strided dimension which is being broadcast, and is
 * the final dimension before the accumulation operation.
 */
static size_t make_strided_inner_broadcast_dimension_kernel(
    const callable_type_data *elwise_reduction_const,
    const ndt::callable_type *elwise_reduction_tp,
    const callable_type_data *dst_initialization_const,
    const ndt::callable_type *dst_initialization_tp, void *ckb,
    intptr_t ckb_offset, intptr_t dst_stride, intptr_t src_stride,
    intptr_t src_size, const ndt::type &dst_tp, const char *dst_arrmeta,
    const ndt::type &src_tp, const char *src_arrmeta, bool right_associative,
    const nd::array &reduction_identity, kernel_request_t kernreq,
    const eval::eval_context *ectx)
{
  callable_type_data *elwise_reduction =
      const_cast<callable_type_data *>(elwise_reduction_const);
  callable_type_data *dst_initialization =
      const_cast<callable_type_data *>(dst_initialization_const);

  intptr_t root_ckb_offset = ckb_offset;
  strided_inner_broadcast_kernel_extra *e =
      reinterpret_cast<ckernel_builder<kernel_request_host> *>(ckb)
          ->alloc_ck<strided_inner_broadcast_kernel_extra>(ckb_offset);
  e->destructor = &strided_inner_broadcast_kernel_extra::destruct;
  // Cannot have both a dst_initialization kernel and a reduction identity
  if (dst_initialization != NULL && !reduction_identity.is_null()) {
    throw invalid_argument(
        "make_lifted_reduction_ckernel: cannot specify"
        " both a dst_initialization kernel and a reduction_identity");
  }
  if (reduction_identity.is_null()) {
    // Get the function pointer for the first_call, for the case with
    // no reduction identity
    if (kernreq == kernel_request_single) {
      e->set_first_call_function(
          &strided_inner_broadcast_kernel_extra::single_first);
    } else if (kernreq == kernel_request_strided) {
      e->set_first_call_function(
          &strided_inner_broadcast_kernel_extra::strided_first);
    } else {
      stringstream ss;
      ss << "make_lifted_reduction_ckernel: unrecognized request "
         << (int)kernreq;
      throw runtime_error(ss.str());
    }
  } else {
    // Get the function pointer for the first_call, for the case with
    // a reduction identity
    if (kernreq == kernel_request_single) {
      e->set_first_call_function(
          &strided_inner_broadcast_kernel_extra::single_first_with_ident);
    } else if (kernreq == kernel_request_strided) {
      e->set_first_call_function(
          &strided_inner_broadcast_kernel_extra::strided_first_with_ident);
    } else {
      stringstream ss;
      ss << "make_lifted_reduction_ckernel: unrecognized request "
         << (int)kernreq;
      throw runtime_error(ss.str());
    }
    if (reduction_identity.get_type() != dst_tp) {
      stringstream ss;
      ss << "make_lifted_reduction_ckernel: reduction identity type ";
      ss << reduction_identity.get_type() << " does not match dst type ";
      ss << dst_tp;
      throw runtime_error(ss.str());
    }
    e->ident_data = reduction_identity.get_readonly_originptr();
    e->ident_ref = reduction_identity.get_memblock().release();
  }
  // The function pointer for followup accumulation calls
  e->set_followup_call_function(
      &strided_inner_broadcast_kernel_extra::strided_followup);
  // The striding parameters
  e->dst_stride = dst_stride;
  e->src_stride = src_stride;
  e->size = src_size;
  // Validate that the provided callables are unary operations,
  // and have the correct types
  if (elwise_reduction_tp->get_npos() != 1 &&
      elwise_reduction_tp->get_npos() != 2) {
    stringstream ss;
    ss << "make_lifted_reduction_ckernel: elwise reduction ckernel ";
    ss << "funcproto must be unary or a binary expr with all equal types";
    throw runtime_error(ss.str());
  }
  if (elwise_reduction_tp->get_return_type() != dst_tp) {
    stringstream ss;
    ss << "make_lifted_reduction_ckernel: elwise reduction ckernel ";
    ss << "dst type is " << elwise_reduction_tp->get_return_type();
    ss << ", expected " << dst_tp;
    throw type_error(ss.str());
  }
  if (elwise_reduction_tp->get_pos_type(0) != src_tp) {
    stringstream ss;
    ss << "make_lifted_reduction_ckernel: elwise reduction ckernel ";
    ss << "src type is " << elwise_reduction_tp->get_return_type();
    ss << ", expected " << src_tp;
//.........这里部分代码省略.........

size_t dynd::make_lifted_reduction_ckernel(
    const callable_type_data *elwise_reduction_const,
    const ndt::callable_type *elwise_reduction_tp,
    const callable_type_data *dst_initialization_const,
    const ndt::callable_type *dst_initialization_tp, void *ckb,
    intptr_t ckb_offset, const ndt::type &dst_tp, const char *dst_arrmeta,
    const ndt::type &src_tp, const char *src_arrmeta, intptr_t reduction_ndim,
    const bool *reduction_dimflags, bool associative, bool commutative,
    bool right_associative, const nd::array &reduction_identity,
    dynd::kernel_request_t kernreq, const eval::eval_context *ectx)
{
  callable_type_data *elwise_reduction =
      const_cast<callable_type_data *>(elwise_reduction_const);
  callable_type_data *dst_initialization =
      const_cast<callable_type_data *>(dst_initialization_const);

  // Count the number of dimensions being reduced
  intptr_t reducedim_count = 0;
  for (intptr_t i = 0; i < reduction_ndim; ++i) {
    reducedim_count += reduction_dimflags[i];
  }
  if (reducedim_count == 0) {
    if (reduction_ndim == 0) {
      // If there are no dimensions to reduce, it's
      // just a dst_initialization operation, so create
      // that ckernel directly
      if (dst_initialization != NULL) {
        return dst_initialization->instantiate(
            dst_initialization->static_data, 0, NULL, ckb, ckb_offset, dst_tp,
            dst_arrmeta, elwise_reduction_tp->get_npos(), &src_tp, &src_arrmeta,
            kernreq, ectx, nd::array(), std::map<nd::string, ndt::type>());
      } else if (reduction_identity.is_null()) {
        return make_assignment_kernel(ckb, ckb_offset, dst_tp, dst_arrmeta,
                                      src_tp, src_arrmeta, kernreq, ectx);
      } else {
        // Create the kernel which copies the identity and then
        // does one reduction
        return make_strided_inner_reduction_dimension_kernel(
            elwise_reduction, elwise_reduction_tp, dst_initialization,
            dst_initialization_tp, ckb, ckb_offset, 0, 1, dst_tp, dst_arrmeta,
            src_tp, src_arrmeta, right_associative, reduction_identity, kernreq,
            ectx);
      }
    }
    throw runtime_error("make_lifted_reduction_ckernel: no dimensions were "
                        "flagged for reduction");
  }

  if (!(reducedim_count == 1 || (associative && commutative))) {
    throw runtime_error(
        "make_lifted_reduction_ckernel: for reducing along multiple dimensions,"
        " the reduction function must be both associative and commutative");
  }
  if (right_associative) {
    throw runtime_error("make_lifted_reduction_ckernel: right_associative is "
                        "not yet supported");
  }

  ndt::type dst_el_tp = elwise_reduction_tp->get_return_type();
  ndt::type src_el_tp = elwise_reduction_tp->get_pos_type(0);

  // This is the number of dimensions being processed by the reduction
  if (reduction_ndim != src_tp.get_ndim() - src_el_tp.get_ndim()) {
    stringstream ss;
    ss << "make_lifted_reduction_ckernel: wrong number of reduction "
          "dimensions, ";
    ss << "requested " << reduction_ndim << ", but types have ";
    ss << (src_tp.get_ndim() - src_el_tp.get_ndim());
    ss << " lifting from " << src_el_tp << " to " << src_tp;
    throw runtime_error(ss.str());
  }
  // Determine whether reduced dimensions are being kept or not
  bool keep_dims;
  if (reduction_ndim == dst_tp.get_ndim() - dst_el_tp.get_ndim()) {
    keep_dims = true;
  } else if (reduction_ndim - reducedim_count ==
             dst_tp.get_ndim() - dst_el_tp.get_ndim()) {
    keep_dims = false;
  } else {
    stringstream ss;
    ss << "make_lifted_reduction_ckernel: The number of dimensions flagged for "
          "reduction, ";
    ss << reducedim_count << ", is not consistent with the destination type ";
    ss << "reducing " << dst_tp << " with element " << dst_el_tp;
    throw runtime_error(ss.str());
  }

  ndt::type dst_i_tp = dst_tp, src_i_tp = src_tp;

  for (intptr_t i = 0; i < reduction_ndim; ++i) {
    intptr_t dst_stride, dst_size, src_stride, src_size;
    // Get the striding parameters for the source dimension
    if (!src_i_tp.get_as_strided(src_arrmeta, &src_size, &src_stride, &src_i_tp,
                                 &src_arrmeta)) {
      stringstream ss;
      ss << "make_lifted_reduction_ckernel: type " << src_i_tp
         << " not supported as source";
      throw type_error(ss.str());
    }
    if (reduction_dimflags[i]) {
//.........这里部分代码省略.........

void dynd::lift_reduction_arrfunc(arrfunc_type_data *out_ar,
                const nd::arrfunc& elwise_reduction_arr,
                const ndt::type& lifted_arr_type,
                const nd::arrfunc& dst_initialization_arr,
                bool keepdims,
                intptr_t reduction_ndim,
                const bool *reduction_dimflags,
                bool associative,
                bool commutative,
                bool right_associative,
                const nd::array& reduction_identity)
{
    // Validate the input elwise_reduction arrfunc
    if (elwise_reduction_arr.is_null()) {
        throw runtime_error("lift_reduction_arrfunc: 'elwise_reduction' may not be empty");
    }
    const arrfunc_type_data *elwise_reduction = elwise_reduction_arr.get();
    if (elwise_reduction->get_param_count() != 1 &&
            !(elwise_reduction->get_param_count() == 2 &&
              elwise_reduction->get_param_type(0) ==
                  elwise_reduction->get_param_type(1) &&
              elwise_reduction->get_param_type(0) ==
                  elwise_reduction->get_return_type())) {
        stringstream ss;
        ss << "lift_reduction_arrfunc: 'elwise_reduction' must contain a"
              " unary operation ckernel or a binary expr ckernel with all "
              "equal types, its prototype is " << elwise_reduction->func_proto;
        throw invalid_argument(ss.str());
    }

    lifted_reduction_arrfunc_data *self = new lifted_reduction_arrfunc_data;
    *out_ar->get_data_as<lifted_reduction_arrfunc_data *>() = self;
    out_ar->free_func = &delete_lifted_reduction_arrfunc_data;
    self->child_elwise_reduction = elwise_reduction_arr;
    self->child_dst_initialization = dst_initialization_arr;
    if (!reduction_identity.is_null()) {
        if (reduction_identity.is_immutable() &&
                reduction_identity.get_type() == elwise_reduction->get_return_type()) {
            self->reduction_identity = reduction_identity;
        } else {
            self->reduction_identity = nd::empty(elwise_reduction->get_return_type());
            self->reduction_identity.vals() = reduction_identity;
            self->reduction_identity.flag_as_immutable();
        }
    }

    // Figure out the result type
    ndt::type lifted_dst_type = elwise_reduction->get_return_type();
    for (intptr_t i = reduction_ndim - 1; i >= 0; --i) {
        if (reduction_dimflags[i]) {
            if (keepdims) {
                lifted_dst_type = ndt::make_strided_dim(lifted_dst_type);
            }
        } else {
            ndt::type subtype = lifted_arr_type.get_type_at_dimension(NULL, i);
            switch (subtype.get_type_id()) {
                case strided_dim_type_id:
                case cfixed_dim_type_id:
                    lifted_dst_type = ndt::make_strided_dim(lifted_dst_type);
                    break;
                case var_dim_type_id:
                    lifted_dst_type = ndt::make_var_dim(lifted_dst_type);
                    break;
                default: {
                    stringstream ss;
                    ss << "lift_reduction_arrfunc: don't know how to process ";
                    ss << "dimension of type " << subtype;
                    throw type_error(ss.str());
                }
            }
        }
    }
    self->data_types[0] = lifted_dst_type;
    self->data_types[1] = lifted_arr_type;
    self->reduction_ndim = reduction_ndim;
    self->associative = associative;
    self->commutative = commutative;
    self->right_associative = right_associative;
    self->reduction_dimflags.init(reduction_ndim);
    memcpy(self->reduction_dimflags.get(), reduction_dimflags, sizeof(bool) * reduction_ndim);

    out_ar->instantiate = &instantiate_lifted_reduction_arrfunc_data;
    out_ar->func_proto = ndt::make_funcproto(lifted_arr_type, lifted_dst_type);
}

 inline const arrfunc_type_data *get() const
 {
   return !m_value.is_null() ? reinterpret_cast<const arrfunc_type_data *>(
                                   m_value.get_readonly_originptr())
                             : NULL;
 }

 inline bool is_null() const { return m_value.is_null(); }

nd::array dynd::struct_concat(nd::array lhs, nd::array rhs)
{
  nd::array res;
  if (lhs.is_null()) {
    res = rhs;
    return res;
  }
  if (rhs.is_null()) {
    res = lhs;
    return res;
  }
  const ndt::type &lhs_tp = lhs.get_type(), &rhs_tp = rhs.get_type();
  if (lhs_tp.get_kind() != struct_kind) {
    stringstream ss;
    ss << "Cannot concatenate array with type " << lhs_tp << " as a struct";
    throw invalid_argument(ss.str());
  }
  if (rhs_tp.get_kind() != struct_kind) {
    stringstream ss;
    ss << "Cannot concatenate array with type " << rhs_tp << " as a struct";
    throw invalid_argument(ss.str());
  }

  // Make an empty shell struct by concatenating the fields together
  intptr_t lhs_n = lhs_tp.extended<ndt::base_struct_type>()->get_field_count();
  intptr_t rhs_n = rhs_tp.extended<ndt::base_struct_type>()->get_field_count();
  intptr_t res_n = lhs_n + rhs_n;
  nd::array res_field_names = nd::empty(res_n, ndt::string_type::make());
  nd::array res_field_types = nd::empty(res_n, ndt::make_type());
  res_field_names(irange(0, lhs_n)).vals() = lhs_tp.extended<ndt::base_struct_type>()->get_field_names();
  res_field_names(irange(lhs_n, res_n)).vals() = rhs_tp.extended<ndt::base_struct_type>()->get_field_names();
  res_field_types(irange(0, lhs_n)).vals() = lhs_tp.extended<ndt::base_struct_type>()->get_field_types();
  res_field_types(irange(lhs_n, res_n)).vals() = rhs_tp.extended<ndt::base_struct_type>()->get_field_types();
  ndt::type res_tp = ndt::struct_type::make(res_field_names, res_field_types);
  const ndt::type *res_field_tps = res_tp.extended<ndt::base_struct_type>()->get_field_types_raw();
  res = nd::empty_shell(res_tp);

  // Initialize the default data offsets for the struct arrmeta
  ndt::struct_type::fill_default_data_offsets(res_n, res_tp.extended<ndt::base_struct_type>()->get_field_types_raw(),
                                              reinterpret_cast<uintptr_t *>(res.get_arrmeta()));
  // Get information about the arrmeta layout of the input and res
  const uintptr_t *lhs_arrmeta_offsets = lhs_tp.extended<ndt::base_struct_type>()->get_arrmeta_offsets_raw();
  const uintptr_t *rhs_arrmeta_offsets = rhs_tp.extended<ndt::base_struct_type>()->get_arrmeta_offsets_raw();
  const uintptr_t *res_arrmeta_offsets = res_tp.extended<ndt::base_struct_type>()->get_arrmeta_offsets_raw();
  const char *lhs_arrmeta = lhs.get_arrmeta();
  const char *rhs_arrmeta = rhs.get_arrmeta();
  char *res_arrmeta = res.get_arrmeta();
  // Copy the arrmeta from the input arrays
  for (intptr_t i = 0; i < lhs_n; ++i) {
    const ndt::type &tp = res_field_tps[i];
    if (!tp.is_builtin()) {
      tp.extended()->arrmeta_copy_construct(res_arrmeta + res_arrmeta_offsets[i], lhs_arrmeta + lhs_arrmeta_offsets[i],
                                            lhs.get_data_memblock().get());
    }
  }
  for (intptr_t i = 0; i < rhs_n; ++i) {
    const ndt::type &tp = res_field_tps[i + lhs_n];
    if (!tp.is_builtin()) {
      tp.extended()->arrmeta_copy_construct(res_arrmeta + res_arrmeta_offsets[i + lhs_n],
                                            rhs_arrmeta + rhs_arrmeta_offsets[i], rhs.get_data_memblock().get());
    }
  }

  // Get information about the data layout of the input and res
  const uintptr_t *lhs_data_offsets = lhs_tp.extended<ndt::base_struct_type>()->get_data_offsets(lhs.get_arrmeta());
  const uintptr_t *rhs_data_offsets = rhs_tp.extended<ndt::base_struct_type>()->get_data_offsets(rhs.get_arrmeta());
  const uintptr_t *res_data_offsets = res_tp.extended<ndt::base_struct_type>()->get_data_offsets(res.get_arrmeta());
  const char *lhs_data = lhs.get_readonly_originptr();
  const char *rhs_data = rhs.get_readonly_originptr();
  char *res_data = res.get_readwrite_originptr();
  // Copy the data from the input arrays
  for (intptr_t i = 0; i < lhs_n; ++i) {
    const ndt::type &tp = res_field_tps[i];
    typed_data_copy(tp, res_arrmeta + res_arrmeta_offsets[i], res_data + res_data_offsets[i],
                    lhs_arrmeta + lhs_arrmeta_offsets[i], lhs_data + lhs_data_offsets[i]);
  }

  for (intptr_t i = 0; i < rhs_n; ++i) {
    const ndt::type &tp = res_field_tps[i + lhs_n];
    typed_data_copy(tp, res_arrmeta + res_arrmeta_offsets[i + lhs_n], res_data + res_data_offsets[i + lhs_n],
                    rhs_arrmeta + rhs_arrmeta_offsets[i], rhs_data + rhs_data_offsets[i]);
  }

  return res;
}