text: /* file: logistic_regression_predict_types.cpp */
  /*******************************************************************************
  * Copyright 2014-2020 Intel Corporation
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
  *
  *     http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
  *******************************************************************************/
  
  /*
  //++
  //  Implementation of logistic regression algorithm classes.
  //--
  */
  
  #include "algorithms/logistic_regression/logistic_regression_predict_types.h"
  #include "serialization_utils.h"
  #include "daal_strings.h"
  #include "logistic_regression_model_impl.h"
  
  using namespace daal::data_management;
  using namespace daal::services;
  
  namespace daal
  {
  namespace algorithms
  {
  namespace logistic_regression
  {
  namespace prediction
  {
  namespace interface1
  {
  /**
   * Returns an input object for making logistic regression model-based prediction
   * \param[in] id    Identifier of the input object
   * \return          %Input object that corresponds to the given identifier
   */
  NumericTablePtr Input::get(classifier::prediction::NumericTableInputId id) const
  {
      return algorithms::classifier::prediction::Input::get(id);
  }
  
  /**
   * Returns an input object for making logistic regression model-based prediction
   * \param[in] id    Identifier of the input object
   * \return          %Input object that corresponds to the given identifier
   */
  logistic_regression::ModelPtr Input::get(classifier::prediction::ModelInputId id) const
  {
      return staticPointerCast<logistic_regression::Model, SerializationIface>(Argument::get(id));
  }
  
  /**
   * Sets an input object for making logistic regression model-based prediction
   * \param[in] id      Identifier of the input object
   * \param[in] value   %Input object
   */
  void Input::set(classifier::prediction::NumericTableInputId id, const NumericTablePtr & value)
  {
      algorithms::classifier::prediction::Input::set(id, value);
  }
  
  /**
   * Sets an input object for making logistic regression model-based prediction
   * \param[in] id      Identifier of the input object
   * \param[in] value   %Input object
   */
  void Input::set(classifier::prediction::ModelInputId id, const logistic_regression::ModelPtr & value)
  {
      algorithms::classifier::prediction::Input::set(id, value);
  }
  
  /**
   * Checks an input object for making logistic regression model-based prediction
   */
  services::Status Input::check(const daal::algorithms::Parameter * parameter, int method) const
  {
      Status s;
      DAAL_CHECK_STATUS(s, algorithms::classifier::prediction::Input::check(parameter, method));
      ModelPtr m = get(classifier::prediction::model);
      const daal::algorithms::logistic_regression::internal::ModelImpl * pModel =
          static_cast<const daal::algorithms::logistic_regression::internal::ModelImpl *>(m.get());
      DAAL_ASSERT(pModel);
      size_t nClasses;
      {
          auto par1 = dynamic_cast<const logistic_regression::prediction::interface1::Parameter *>(parameter);
          if (par1) nClasses = par1->nClasses;
  
          auto par2 = dynamic_cast<const classifier::Parameter *>(parameter);
          if (par2) nClasses = par2->nClasses;
  
          if (par1 == nullptr && par2 == nullptr) return services::Status(ErrorNullParameterNotSupported);
      }
      const size_t nBetaPerClass = get(classifier::prediction::data)->getNumberOfColumns() + 1;
      return checkNumericTable(pModel->getBeta().get(), betaStr(), 0, 0, nBetaPerClass, nClasses == 2 ? 1 : nClasses);
  }
  
  } // namespace interface1
  } // namespace prediction
  } // namespace logistic_regression
  } // namespace algorithms
  } // namespace daal
  