clean code

include/LightGBM/boosting.h

@@ -48,7 +48,7 @@ public:
 
   virtual std::vector<double> GetEvalAt(int data_idx) const = 0;
 
-  virtual const score_t* GetScoreAt(int data_idx, data_size_t* out_len) const = 0;
+  virtual const score_t* GetTrainingScore(data_size_t* out_len) const = 0;
 
   /*!
   * \brief Prediction for one record, not sigmoid transform

include/LightGBM/c_api.h

@@ -39,8 +39,8 @@ DllExport const char* LGBM_GetLastError();
 
 /*!
 * \brief load data set from file like the command_line LightGBM do
-* \param parameters additional parameters
 * \param filename the name of the file
+* \param parameters additional parameters
 * \param reference used to align bin mapper with other dataset, nullptr means don't used
 * \param out a loaded dataset
 * \return 0 when success, -1 when failure happens
@@ -90,7 +90,7 @@ DllExport int LGBM_CreateDatasetFromCSR(const int32_t* indptr,
 * \param indices findex
 * \param data fvalue
 * \param float_type 0 for float_32 1 for float_64
-* \param nindptr number of rows in the matix + 1
+* \param ncol_ptr number of rows in the matix + 1
 * \param nelem number of nonzero elements in the matrix
 * \param num_row number of rows; when it's set to 0, then guess from data
 * \param parameters additional parameters
@@ -116,7 +116,6 @@ DllExport int LGBM_CreateDatasetFromCSC(const int32_t* col_ptr,
 * \param nrow number of rows
 * \param ncol number columns
 * \param is_row_major 1 for row major, 0 for column major
-* \param missing which value to represent missing value
 * \param parameters additional parameters
 * \param reference used to align bin mapper with other dataset, nullptr means don't used
 * \param out created dataset
@@ -151,7 +150,7 @@ DllExport int LGBM_DatasetSaveBinary(DatesetHandle handle,
 * \param handle a instance of dataset
 * \param field_name field name, can be label, weight, group
 * \param field_data pointer to vector
-* \param field_len number of element in field_data
+* \param num_element number of element in field_data
 * \param type float_32:0, uint32_t:1
 * \return 0 when success, -1 when failure happens
 */
@@ -216,6 +215,7 @@ DllExport int LGBM_BoosterCreate(const DatesetHandle train_data,
 /*!
 * \brief load an exsiting boosting from model file
 * \param filename filename of model
+* \param out handle of created Booster
 * \return 0 when success, -1 when failure happens
 */
 DllExport int LGBM_BoosterLoadFromModelfile(
@@ -232,7 +232,7 @@ DllExport int LGBM_BoosterFree(BoosterHandle handle);
 /*!
 * \brief update the model in one round
 * \param handle handle
-* \param is_finished 1 means finised
+* \param is_finished 1 means finised(cannot split any more)
 * \return 0 when success, -1 when failure happens
 */
 DllExport int LGBM_BoosterUpdateOneIter(BoosterHandle handle, int* is_finished);
@@ -243,8 +243,7 @@ DllExport int LGBM_BoosterUpdateOneIter(BoosterHandle handle, int* is_finished);
 * \param handle handle
 * \param grad gradient statistics
 * \param hess second order gradient statistics
-* \param float_type 0 for float_32, 1 for float_64
-* \param is_finished 1 means finised
+* \param is_finished 1 means finised(cannot split any more)
 * \return 0 when success, -1 when failure happens
 */
 DllExport int LGBM_BoosterUpdateOneIterCustom(BoosterHandle handle,
@@ -256,6 +255,7 @@ DllExport int LGBM_BoosterUpdateOneIterCustom(BoosterHandle handle,
 * \brief get evaluation for training data and validation datas
 * \param handle handle
 * \param data 0:training data, 1: 1st valid data, 2:2nd valid data ...
+* \param out_len len of output result
 * \param out_result the string containing evaluation statistics
 * \return 0 when success, -1 when failure happens
 */
@@ -264,15 +264,27 @@ DllExport int LGBM_BoosterEval(BoosterHandle handle,
   uint64_t* out_len,
   double* out_results);
 
+/*!
+* \brief get raw score for training data, used to calculate gradients outside
+* \param handle handle
+* \param out_len len of output result
+* \param out_result used to set a pointer to array
+* \return 0 when success, -1 when failure happens
+*/
+DllExport int LGBM_BoosterGetScore(BoosterHandle handle,
+  uint64_t* out_len,
+  const float** out_result);
+
 /*!
 * \brief make prediction for training data and validation datas
-this can be used to support customized eval function / and gradients calculation
+this can be used to support customized eval function
 * \param handle handle
 * \param data 0:training data, 1: 1st valid data, 2:2nd valid data ...
+* \param out_len len of output result
 * \param out_result used to set a pointer to array
 * \return 0 when success, -1 when failure happens
 */
-DllExport int LGBM_BoosterGetScore(BoosterHandle handle,
+DllExport int LGBM_BoosterGetPredict(BoosterHandle handle,
   int data,
   uint64_t* out_len,
   const float** out_result);
@@ -283,12 +295,13 @@ DllExport int LGBM_BoosterGetScore(BoosterHandle handle,
 * \param indptr pointer to row headers
 * \param indices findex
 * \param data fvalue
+* \param float_type 0:float_32 1:float64
 * \param nindptr number of rows in the matix + 1
 * \param nelem number of nonzero elements in the matrix
 * \param num_col number of columns; when it's set to 0, then guess from data
 * \param predict_type
 *          0:raw score
-*          1:with sigmoid transform(if needed)
+*          1:with transform(if needed)
 *          2:leaf index
 * \param n_used_trees number of used tree
 * \param out_result used to set a pointer to array
@@ -312,12 +325,13 @@ DllExport int LGBM_BoosterPredictForCSR(BoosterHandle handle,
 * \param col_ptr pointer to col headers
 * \param indices findex
 * \param data fvalue
-* \param nindptr number of rows in the matix + 1
+* \param float_type 0:float_32 1:float64
+* \param ncol_ptr number of rows in the matix + 1
 * \param nelem number of nonzero elements in the matrix
 * \param num_row number of rows; when it's set to 0, then guess from data
 * \param predict_type
 *          0:raw score
-*          1:with sigmoid transform(if needed)
+*          1:with transform(if needed)
 *          2:leaf index
 * \param n_used_trees number of used tree
 * \param out_result used to set a pointer to array
@@ -328,7 +342,7 @@ DllExport int LGBM_BoosterPredictForCSC(BoosterHandle handle,
   const int32_t* indices,
   const void* data,
   int float_type,
-  uint64_t nindptr,
+  uint64_t ncol_ptr,
   uint64_t nelem,
   uint64_t num_row,
   int predict_type,
@@ -339,12 +353,12 @@ DllExport int LGBM_BoosterPredictForCSC(BoosterHandle handle,
 * \brief make prediction for an new data set
 * \param handle handle
 * \param data pointer to the data space
+* \param float_type 0:float_32 1:float64
 * \param nrow number of rows
 * \param ncol number columns
-* \param missing which value to represent missing value
 * \param predict_type
 *          0:raw score
-*          1:with sigmoid transform(if needed)
+*          1:with transform(if needed)
 *          2:leaf index
 * \param n_used_trees number of used tree
 * \param out_result used to set a pointer to array

src/boosting/gbdt.cpp

@@ -294,16 +294,9 @@ std::vector<double> GBDT::GetEvalAt(int data_idx) const {
 }
 
 /*! \brief Get prediction result */
-const score_t* GBDT::GetScoreAt(int data_idx, data_size_t* out_len) const {
-  CHECK(data_idx >= 0 && data_idx <= static_cast<int>(valid_score_updater_.size()));
-  if (data_idx == 0) {
+const score_t* GBDT::GetTrainingScore(data_size_t* out_len) const {
   *out_len = train_score_updater_->num_data() * num_class_;
   return train_score_updater_->score();
-  } else {
-    auto used_idx = data_idx - 1;
-    *out_len = valid_score_updater_[used_idx]->num_data() * num_class_;
-    return valid_score_updater_[used_idx]->score();
-  }
 }
 
 void GBDT::Boosting() {

src/boosting/gbdt.h

@@ -50,7 +50,7 @@ public:
   std::vector<double> GetEvalAt(int data_idx) const override;
 
   /*! \brief Get prediction result */
-  const score_t* GetScoreAt(int data_idx, data_size_t* out_len) const override;
+  const score_t* GetTrainingScore(data_size_t* out_len) const override;
 
   /*!
   * \brief Predtion for one record without sigmoid transformation

src/c_api.cpp

@@ -434,14 +434,13 @@ DllExport int LGBM_BoosterEval(BoosterHandle handle,
 }
 
 DllExport int LGBM_BoosterGetScore(BoosterHandle handle,
-  int data,
   uint64_t* out_len,
   const float** out_result) {
 
   Booster* ref_booster = reinterpret_cast<Booster*>(handle);
   auto boosting = ref_booster->GetBoosting();
   int len = 0;
-  *out_result = boosting->GetScoreAt(data, &len);
+  *out_result = boosting->GetTrainingScore(&len);
   *out_len = static_cast<uint64_t>(len);
 
   return 0;