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636 lines
22 KiB
C
636 lines
22 KiB
C
/* -*-C-*-
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******************************************************************************
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* File: matrix.h (Formerly matrix.h)
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* Description: Generic 2-d array/matrix and banded triangular matrix class.
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* Author: Ray Smith
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* TODO(rays) Separate from ratings matrix, which it also contains:
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*
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* Descrition: Ratings matrix class (specialization of banded matrix).
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* Segmentation search matrix of lists of BLOB_CHOICE.
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* Author: Mark Seaman, OCR Technology
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* Created: Wed May 16 13:22:06 1990
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* Modified: Tue Mar 19 16:00:20 1991 (Mark Seaman) marks@hpgrlt
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* Language: C
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* Package: N/A
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* Status: Experimental (Do Not Distribute)
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*
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* (c) Copyright 1990, Hewlett-Packard Company.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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*********************************************************************************/
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#ifndef TESSERACT_CCSTRUCT_MATRIX_H__
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#define TESSERACT_CCSTRUCT_MATRIX_H__
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#include <math.h>
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#include "kdpair.h"
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#include "points.h"
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#include "serialis.h"
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#include "unicharset.h"
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class BLOB_CHOICE;
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class BLOB_CHOICE_LIST;
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#define NOT_CLASSIFIED reinterpret_cast<BLOB_CHOICE_LIST*>(0)
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// A generic class to hold a 2-D matrix with entries of type T, but can also
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// act as a base class for other implementations, such as a triangular or
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// banded matrix.
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template <class T>
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class GENERIC_2D_ARRAY {
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public:
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// Initializes the array size, and empty element, but cannot allocate memory
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// for the subclasses or initialize because calls to the num_elements
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// member will be routed to the base class implementation. Subclasses can
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// either pass the memory in, or allocate after by calling Resize().
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GENERIC_2D_ARRAY(int dim1, int dim2, const T& empty, T* array)
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: empty_(empty), dim1_(dim1), dim2_(dim2), array_(array) {
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size_allocated_ = dim1 * dim2;
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}
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// Original constructor for a full rectangular matrix DOES allocate memory
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// and initialize it to empty.
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GENERIC_2D_ARRAY(int dim1, int dim2, const T& empty)
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: empty_(empty), dim1_(dim1), dim2_(dim2) {
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int new_size = dim1 * dim2;
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array_ = new T[new_size];
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size_allocated_ = new_size;
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for (int i = 0; i < size_allocated_; ++i)
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array_[i] = empty_;
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}
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// Default constructor for array allocation. Use Resize to set the size.
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GENERIC_2D_ARRAY()
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: array_(NULL), empty_(static_cast<T>(0)), dim1_(0), dim2_(0),
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size_allocated_(0) {
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}
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GENERIC_2D_ARRAY(const GENERIC_2D_ARRAY<T>& src)
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: array_(NULL), empty_(static_cast<T>(0)), dim1_(0), dim2_(0),
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size_allocated_(0) {
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*this = src;
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}
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virtual ~GENERIC_2D_ARRAY() { delete[] array_; }
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void operator=(const GENERIC_2D_ARRAY<T>& src) {
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ResizeNoInit(src.dim1(), src.dim2());
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memcpy(array_, src.array_, num_elements() * sizeof(array_[0]));
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}
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// Reallocate the array to the given size. Does not keep old data, but does
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// not initialize the array either.
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void ResizeNoInit(int size1, int size2) {
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int new_size = size1 * size2;
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if (new_size > size_allocated_) {
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delete [] array_;
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array_ = new T[new_size];
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size_allocated_ = new_size;
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}
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dim1_ = size1;
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dim2_ = size2;
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}
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// Reallocate the array to the given size. Does not keep old data.
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void Resize(int size1, int size2, const T& empty) {
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empty_ = empty;
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ResizeNoInit(size1, size2);
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Clear();
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}
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// Reallocate the array to the given size, keeping old data.
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void ResizeWithCopy(int size1, int size2) {
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if (size1 != dim1_ || size2 != dim2_) {
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int new_size = size1 * size2;
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T* new_array = new T[new_size];
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for (int col = 0; col < size1; ++col) {
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for (int row = 0; row < size2; ++row) {
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int old_index = col * dim2() + row;
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int new_index = col * size2 + row;
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if (col < dim1_ && row < dim2_) {
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new_array[new_index] = array_[old_index];
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} else {
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new_array[new_index] = empty_;
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}
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}
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}
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delete[] array_;
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array_ = new_array;
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dim1_ = size1;
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dim2_ = size2;
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size_allocated_ = new_size;
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}
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}
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// Sets all the elements of the array to the empty value.
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void Clear() {
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int total_size = num_elements();
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for (int i = 0; i < total_size; ++i)
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array_[i] = empty_;
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}
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// Writes to the given file. Returns false in case of error.
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// Only works with bitwise-serializeable types!
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bool Serialize(FILE* fp) const {
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if (!SerializeSize(fp)) return false;
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if (fwrite(&empty_, sizeof(empty_), 1, fp) != 1) return false;
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int size = num_elements();
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if (fwrite(array_, sizeof(*array_), size, fp) != size) return false;
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return true;
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}
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bool Serialize(tesseract::TFile* fp) const {
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if (!SerializeSize(fp)) return false;
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if (fp->FWrite(&empty_, sizeof(empty_), 1) != 1) return false;
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int size = num_elements();
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if (fp->FWrite(array_, sizeof(*array_), size) != size) return false;
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return true;
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}
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// Reads from the given file. Returns false in case of error.
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// Only works with bitwise-serializeable types!
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// If swap is true, assumes a big/little-endian swap is needed.
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bool DeSerialize(bool swap, FILE* fp) {
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if (!DeSerializeSize(swap, fp)) return false;
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if (fread(&empty_, sizeof(empty_), 1, fp) != 1) return false;
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if (swap) ReverseN(&empty_, sizeof(empty_));
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int size = num_elements();
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if (fread(array_, sizeof(*array_), size, fp) != size) return false;
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if (swap) {
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for (int i = 0; i < size; ++i)
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ReverseN(&array_[i], sizeof(array_[i]));
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}
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return true;
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}
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bool DeSerialize(bool swap, tesseract::TFile* fp) {
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if (!DeSerializeSize(swap, fp)) return false;
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if (fp->FRead(&empty_, sizeof(empty_), 1) != 1) return false;
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if (swap) ReverseN(&empty_, sizeof(empty_));
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int size = num_elements();
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if (fp->FRead(array_, sizeof(*array_), size) != size) return false;
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if (swap) {
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for (int i = 0; i < size; ++i)
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ReverseN(&array_[i], sizeof(array_[i]));
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}
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return true;
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}
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// Writes to the given file. Returns false in case of error.
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// Assumes a T::Serialize(FILE*) const function.
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bool SerializeClasses(FILE* fp) const {
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if (!SerializeSize(fp)) return false;
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if (!empty_.Serialize(fp)) return false;
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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if (!array_[i].Serialize(fp)) return false;
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}
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return true;
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}
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// Reads from the given file. Returns false in case of error.
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// Assumes a T::DeSerialize(bool swap, FILE*) function.
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// If swap is true, assumes a big/little-endian swap is needed.
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bool DeSerializeClasses(bool swap, FILE* fp) {
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if (!DeSerializeSize(swap, fp)) return false;
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if (!empty_.DeSerialize(swap, fp)) return false;
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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if (!array_[i].DeSerialize(swap, fp)) return false;
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}
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return true;
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}
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// Provide the dimensions of this rectangular matrix.
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int dim1() const { return dim1_; }
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int dim2() const { return dim2_; }
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// Returns the number of elements in the array.
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// Banded/triangular matrices may override.
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virtual int num_elements() const { return dim1_ * dim2_; }
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// Expression to select a specific location in the matrix. The matrix is
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// stored COLUMN-major, so the left-most index is the most significant.
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// This allows [][] access to use indices in the same order as (,).
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virtual int index(int column, int row) const {
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return (column * dim2_ + row);
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}
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// Put a list element into the matrix at a specific location.
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void put(ICOORD pos, const T& thing) {
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array_[this->index(pos.x(), pos.y())] = thing;
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}
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void put(int column, int row, const T& thing) {
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array_[this->index(column, row)] = thing;
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}
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// Get the item at a specified location from the matrix.
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T get(ICOORD pos) const {
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return array_[this->index(pos.x(), pos.y())];
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}
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T get(int column, int row) const {
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return array_[this->index(column, row)];
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}
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// Return a reference to the element at the specified location.
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const T& operator()(int column, int row) const {
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return array_[this->index(column, row)];
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}
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T& operator()(int column, int row) {
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return array_[this->index(column, row)];
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}
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// Allow access using array[column][row]. NOTE that the indices are
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// in the same left-to-right order as the () indexing.
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T* operator[](int column) {
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return &array_[this->index(column, 0)];
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}
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const T* operator[](int column) const {
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return &array_[this->index(column, 0)];
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}
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// Adds addend to *this, element-by-element.
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void operator+=(const GENERIC_2D_ARRAY<T>& addend) {
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if (dim2_ == addend.dim2_) {
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// Faster if equal size in the major dimension.
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int size = MIN(num_elements(), addend.num_elements());
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for (int i = 0; i < size; ++i) {
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array_[i] += addend.array_[i];
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}
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} else {
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for (int x = 0; x < dim1_; x++) {
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for (int y = 0; y < dim2_; y++) {
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(*this)(x, y) += addend(x, y);
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}
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}
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}
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}
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// Subtracts minuend from *this, element-by-element.
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void operator-=(const GENERIC_2D_ARRAY<T>& minuend) {
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if (dim2_ == minuend.dim2_) {
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// Faster if equal size in the major dimension.
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int size = MIN(num_elements(), minuend.num_elements());
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for (int i = 0; i < size; ++i) {
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array_[i] -= minuend.array_[i];
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}
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} else {
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for (int x = 0; x < dim1_; x++) {
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for (int y = 0; y < dim2_; y++) {
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(*this)(x, y) -= minuend(x, y);
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}
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}
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}
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}
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// Adds addend to all elements.
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void operator+=(const T& addend) {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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array_[i] += addend;
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}
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}
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// Multiplies *this by factor, element-by-element.
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void operator*=(const T& factor) {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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array_[i] *= factor;
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}
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}
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// Clips *this to the given range.
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void Clip(const T& rangemin, const T& rangemax) {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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array_[i] = ClipToRange(array_[i], rangemin, rangemax);
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}
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}
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// Returns true if all elements of *this are within the given range.
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// Only uses operator<
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bool WithinBounds(const T& rangemin, const T& rangemax) const {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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const T& value = array_[i];
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if (value < rangemin || rangemax < value)
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return false;
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}
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return true;
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}
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// Normalize the whole array.
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double Normalize() {
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int size = num_elements();
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if (size <= 0) return 0.0;
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// Compute the mean.
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double mean = 0.0;
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for (int i = 0; i < size; ++i) {
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mean += array_[i];
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}
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mean /= size;
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// Subtract the mean and compute the standard deviation.
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double sd = 0.0;
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for (int i = 0; i < size; ++i) {
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double normed = array_[i] - mean;
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array_[i] = normed;
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sd += normed * normed;
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}
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sd = sqrt(sd / size);
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if (sd > 0.0) {
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// Divide by the sd.
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for (int i = 0; i < size; ++i) {
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array_[i] /= sd;
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}
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}
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return sd;
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}
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// Returns the maximum value of the array.
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T Max() const {
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int size = num_elements();
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if (size <= 0) return empty_;
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// Compute the max.
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T max_value = array_[0];
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for (int i = 1; i < size; ++i) {
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const T& value = array_[i];
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if (value > max_value) max_value = value;
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}
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return max_value;
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}
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// Returns the maximum absolute value of the array.
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T MaxAbs() const {
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int size = num_elements();
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if (size <= 0) return empty_;
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// Compute the max.
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T max_abs = static_cast<T>(0);
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for (int i = 0; i < size; ++i) {
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T value = static_cast<T>(fabs(array_[i]));
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if (value > max_abs) max_abs = value;
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}
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return max_abs;
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}
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// Accumulates the element-wise sums of squares of src into *this.
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void SumSquares(const GENERIC_2D_ARRAY<T>& src) {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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array_[i] += src.array_[i] * src.array_[i];
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}
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}
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// Scales each element using the ada-grad algorithm, ie array_[i] by
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// sqrt(num_samples/max(1,sqsum[i])).
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void AdaGradScaling(const GENERIC_2D_ARRAY<T>& sqsum, int num_samples) {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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array_[i] *= sqrt(num_samples / MAX(1.0, sqsum.array_[i]));
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}
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}
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void AssertFinite() const {
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int size = num_elements();
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for (int i = 0; i < size; ++i) {
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ASSERT_HOST(isfinite(array_[i]));
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}
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}
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// REGARDLESS OF THE CURRENT DIMENSIONS, treats the data as a
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// num_dims-dimensional array/tensor with dimensions given by dims, (ordered
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// from most significant to least significant, the same as standard C arrays)
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// and moves src_dim to dest_dim, with the initial dest_dim and any dimensions
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// in between shifted towards the hole left by src_dim. Example:
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// Current data content: array_=[0, 1, 2, ....119]
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// perhaps *this may be of dim[40, 3], with values [[0, 1, 2][3, 4, 5]...
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// but the current dimensions are irrelevant.
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// num_dims = 4, dims=[5, 4, 3, 2]
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// src_dim=3, dest_dim=1
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// tensor=[[[[0, 1][2, 3][4, 5]]
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// [[6, 7][8, 9][10, 11]]
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// [[12, 13][14, 15][16, 17]]
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// [[18, 19][20, 21][22, 23]]]
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// [[[24, 25]...
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// output dims =[5, 2, 4, 3]
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// output tensor=[[[[0, 2, 4][6, 8, 10][12, 14, 16][18, 20, 22]]
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// [[1, 3, 5][7, 9, 11][13, 15, 17][19, 21, 23]]]
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// [[[24, 26, 28]...
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// which is stored in the array_ as:
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// [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 1, 3, 5, 7, 9, 11, 13...]
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// NOTE: the 2 stored matrix dimensions are simply copied from *this. To
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// change the dimensions after the transpose, use ResizeNoInit.
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// Higher dimensions above 2 are strictly the responsibility of the caller.
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void RotatingTranspose(const int* dims, int num_dims, int src_dim,
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int dest_dim, GENERIC_2D_ARRAY<T>* result) const {
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int max_d = MAX(src_dim, dest_dim);
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int min_d = MIN(src_dim, dest_dim);
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// In a tensor of shape [d0, d1... min_d, ... max_d, ... dn-2, dn-1], the
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// ends outside of min_d and max_d are unaffected, with [max_d +1, dn-1]
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// being contiguous blocks of data that will move together, and
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// [d0, min_d -1] being replicas of the transpose operation.
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// num_replicas represents the large dimensions unchanged by the operation.
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// move_size represents the small dimensions unchanged by the operation.
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// src_step represents the stride in the src between each adjacent group
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// in the destination.
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int num_replicas = 1, move_size = 1, src_step = 1;
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for (int d = 0; d < min_d; ++d) num_replicas *= dims[d];
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for (int d = max_d + 1; d < num_dims; ++d) move_size *= dims[d];
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for (int d = src_dim + 1; d < num_dims; ++d) src_step *= dims[d];
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if (src_dim > dest_dim) src_step *= dims[src_dim];
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// wrap_size is the size of a single replica, being the amount that is
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// handled num_replicas times.
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int wrap_size = move_size;
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for (int d = min_d; d <= max_d; ++d) wrap_size *= dims[d];
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result->ResizeNoInit(dim1_, dim2_);
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result->empty_ = empty_;
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const T* src = array_;
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T* dest = result->array_;
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for (int replica = 0; replica < num_replicas; ++replica) {
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for (int start = 0; start < src_step; start += move_size) {
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for (int pos = start; pos < wrap_size; pos += src_step) {
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memcpy(dest, src + pos, sizeof(*dest) * move_size);
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dest += move_size;
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}
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}
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src += wrap_size;
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}
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}
|
|
|
|
// Delete objects pointed to by array_[i].
|
|
void delete_matrix_pointers() {
|
|
int size = num_elements();
|
|
for (int i = 0; i < size; ++i) {
|
|
T matrix_cell = array_[i];
|
|
if (matrix_cell != empty_)
|
|
delete matrix_cell;
|
|
}
|
|
}
|
|
|
|
protected:
|
|
// Factored helper to serialize the size.
|
|
bool SerializeSize(FILE* fp) const {
|
|
inT32 size = dim1_;
|
|
if (fwrite(&size, sizeof(size), 1, fp) != 1) return false;
|
|
size = dim2_;
|
|
if (fwrite(&size, sizeof(size), 1, fp) != 1) return false;
|
|
return true;
|
|
}
|
|
bool SerializeSize(tesseract::TFile* fp) const {
|
|
inT32 size = dim1_;
|
|
if (fp->FWrite(&size, sizeof(size), 1) != 1) return false;
|
|
size = dim2_;
|
|
if (fp->FWrite(&size, sizeof(size), 1) != 1) return false;
|
|
return true;
|
|
}
|
|
// Factored helper to deserialize the size.
|
|
// If swap is true, assumes a big/little-endian swap is needed.
|
|
bool DeSerializeSize(bool swap, FILE* fp) {
|
|
inT32 size1, size2;
|
|
if (fread(&size1, sizeof(size1), 1, fp) != 1) return false;
|
|
if (fread(&size2, sizeof(size2), 1, fp) != 1) return false;
|
|
if (swap) {
|
|
ReverseN(&size1, sizeof(size1));
|
|
ReverseN(&size2, sizeof(size2));
|
|
}
|
|
Resize(size1, size2, empty_);
|
|
return true;
|
|
}
|
|
bool DeSerializeSize(bool swap, tesseract::TFile* fp) {
|
|
inT32 size1, size2;
|
|
if (fp->FRead(&size1, sizeof(size1), 1) != 1) return false;
|
|
if (fp->FRead(&size2, sizeof(size2), 1) != 1) return false;
|
|
if (swap) {
|
|
ReverseN(&size1, sizeof(size1));
|
|
ReverseN(&size2, sizeof(size2));
|
|
}
|
|
Resize(size1, size2, empty_);
|
|
return true;
|
|
}
|
|
|
|
T* array_;
|
|
T empty_; // The unused cell.
|
|
int dim1_; // Size of the 1st dimension in indexing functions.
|
|
int dim2_; // Size of the 2nd dimension in indexing functions.
|
|
// The total size to which the array can be expanded before a realloc is
|
|
// needed. If Resize is used, memory is retained so it can be re-expanded
|
|
// without a further alloc, and this stores the allocated size.
|
|
int size_allocated_;
|
|
};
|
|
|
|
// A generic class to store a banded triangular matrix with entries of type T.
|
|
// In this array, the nominally square matrix is dim1_ x dim1_, and dim2_ is
|
|
// the number of bands, INCLUDING the diagonal. The storage is thus of size
|
|
// dim1_ * dim2_ and index(col, row) = col * dim2_ + row - col, and an
|
|
// assert will fail if row < col or row - col >= dim2.
|
|
template <class T>
|
|
class BandTriMatrix : public GENERIC_2D_ARRAY<T> {
|
|
public:
|
|
// Allocate a piece of memory to hold a 2d-array of the given dimension.
|
|
// Initialize all the elements of the array to empty instead of assuming
|
|
// that a default constructor can be used.
|
|
BandTriMatrix(int dim1, int dim2, const T& empty)
|
|
: GENERIC_2D_ARRAY<T>(dim1, dim2, empty) {
|
|
}
|
|
// The default destructor will do.
|
|
|
|
// Provide the dimensions of this matrix.
|
|
// dimension is the size of the nominally square matrix.
|
|
int dimension() const { return this->dim1_; }
|
|
// bandwidth is the number of bands in the matrix, INCLUDING the diagonal.
|
|
int bandwidth() const { return this->dim2_; }
|
|
|
|
// Expression to select a specific location in the matrix. The matrix is
|
|
// stored COLUMN-major, so the left-most index is the most significant.
|
|
// This allows [][] access to use indices in the same order as (,).
|
|
virtual int index(int column, int row) const {
|
|
ASSERT_HOST(row >= column);
|
|
ASSERT_HOST(row - column < this->dim2_);
|
|
return column * this->dim2_ + row - column;
|
|
}
|
|
|
|
// Appends array2 corner-to-corner to *this, making an array of dimension
|
|
// equal to the sum of the individual dimensions.
|
|
// array2 is not destroyed, but is left empty, as all elements are moved
|
|
// to *this.
|
|
void AttachOnCorner(BandTriMatrix<T>* array2) {
|
|
int new_dim1 = this->dim1_ + array2->dim1_;
|
|
int new_dim2 = MAX(this->dim2_, array2->dim2_);
|
|
T* new_array = new T[new_dim1 * new_dim2];
|
|
for (int col = 0; col < new_dim1; ++col) {
|
|
for (int j = 0; j < new_dim2; ++j) {
|
|
int new_index = col * new_dim2 + j;
|
|
if (col < this->dim1_ && j < this->dim2_) {
|
|
new_array[new_index] = this->get(col, col + j);
|
|
} else if (col >= this->dim1_ && j < array2->dim2_) {
|
|
new_array[new_index] = array2->get(col - this->dim1_,
|
|
col - this->dim1_ + j);
|
|
array2->put(col - this->dim1_, col - this->dim1_ + j, NULL);
|
|
} else {
|
|
new_array[new_index] = this->empty_;
|
|
}
|
|
}
|
|
}
|
|
delete[] this->array_;
|
|
this->array_ = new_array;
|
|
this->dim1_ = new_dim1;
|
|
this->dim2_ = new_dim2;
|
|
}
|
|
};
|
|
|
|
class MATRIX : public BandTriMatrix<BLOB_CHOICE_LIST *> {
|
|
public:
|
|
MATRIX(int dimension, int bandwidth)
|
|
: BandTriMatrix<BLOB_CHOICE_LIST *>(dimension, bandwidth, NOT_CLASSIFIED) {}
|
|
|
|
// Returns true if there are any real classification results.
|
|
bool Classified(int col, int row, int wildcard_id) const;
|
|
|
|
// Expands the existing matrix in-place to make the band wider, without
|
|
// losing any existing data.
|
|
void IncreaseBandSize(int bandwidth);
|
|
|
|
// Returns a bigger MATRIX with a new column and row in the matrix in order
|
|
// to split the blob at the given (ind,ind) diagonal location.
|
|
// Entries are relocated to the new MATRIX using the transformation defined
|
|
// by MATRIX_COORD::MapForSplit.
|
|
// Transfers the pointer data to the new MATRIX and deletes *this.
|
|
MATRIX* ConsumeAndMakeBigger(int ind);
|
|
|
|
// Makes and returns a deep copy of *this, including all the BLOB_CHOICEs
|
|
// on the lists, but not any LanguageModelState that may be attached to the
|
|
// BLOB_CHOICEs.
|
|
MATRIX* DeepCopy() const;
|
|
|
|
// Print a shortened version of the contents of the matrix.
|
|
void print(const UNICHARSET &unicharset) const;
|
|
};
|
|
|
|
struct MATRIX_COORD {
|
|
static void Delete(void *arg) {
|
|
MATRIX_COORD *c = static_cast<MATRIX_COORD *>(arg);
|
|
delete c;
|
|
}
|
|
// Default constructor required by GenericHeap.
|
|
MATRIX_COORD() : col(0), row(0) {}
|
|
MATRIX_COORD(int c, int r): col(c), row(r) {}
|
|
~MATRIX_COORD() {}
|
|
|
|
bool Valid(const MATRIX &m) const {
|
|
return 0 <= col && col < m.dimension() &&
|
|
col <= row && row < col + m.bandwidth() && row < m.dimension();
|
|
}
|
|
|
|
// Remaps the col,row pair to split the blob at the given (ind,ind) diagonal
|
|
// location.
|
|
// Entries at (i,j) for i in [0,ind] and j in [ind,dim) move to (i,j+1),
|
|
// making a new row at ind.
|
|
// Entries at (i,j) for i in [ind+1,dim) and j in [i,dim) move to (i+i,j+1),
|
|
// making a new column at ind+1.
|
|
void MapForSplit(int ind) {
|
|
ASSERT_HOST(row >= col);
|
|
if (col > ind) ++col;
|
|
if (row >= ind) ++row;
|
|
ASSERT_HOST(row >= col);
|
|
}
|
|
|
|
int col;
|
|
int row;
|
|
};
|
|
|
|
// The MatrixCoordPair contains a MATRIX_COORD and its priority.
|
|
typedef tesseract::KDPairInc<float, MATRIX_COORD> MatrixCoordPair;
|
|
|
|
#endif // TESSERACT_CCSTRUCT_MATRIX_H__
|