/*******************************************************************************
 * Copyright (c) 2015-2018 Skymind, Inc.
 *
 * This program and the accompanying materials are made available under the
 * terms of the Apache License, Version 2.0 which is available at
 * https://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.
 *
 * SPDX-License-Identifier: Apache-2.0
 ******************************************************************************/

//
// @author George A. Shulinok <sgazeos@gmail.com>, created on 4/18/2019
//

#include <ops/declarable/helpers/BarnesHutTsne.h>
#include <execution/Threads.h>

namespace sd {
namespace ops {
namespace helpers {

    Nd4jLong barnes_row_count(const NDArray* rowP, const NDArray* colP, Nd4jLong N, NDArray& rowCounts) {

        int* pRowCounts = reinterpret_cast<int*>(rowCounts.buffer());
        int const* pRows = reinterpret_cast<int const*>(rowP->getBuffer());
        int const* pCols = reinterpret_cast<int const*>(colP->getBuffer());
        for (Nd4jLong n = 0; n < N; n++) {
            int begin = pRows[n];//->e<int>(n);
            int end = pRows[n + 1];//rowP->e<int>(n + 1);
            for (int i = begin; i < end; i++) {
                bool present = false;
                for (int m = pRows[pCols[i]]; m < pRows[pCols[i] + 1]; m++)
                    if (pCols[m] == n) {
                        present = true;
                        break;
                    }

                ++pRowCounts[n];

                if (!present)
                    ++pRowCounts[pCols[i]];
            }
        }
        NDArray numElementsArr = rowCounts.sumNumber(); //reduceAlongDimension(reduce::Sum, {});
        //rowCounts.printBuffer("Row counts");
        auto numElements = numElementsArr.e<Nd4jLong>(0);
        return numElements;
    }
//    static
//    void printVector(std::vector<int> const& v) {
//        for (auto x: v) {
//            printf("%d ", x);
//        }
//        printf("\n");
//        fflush(stdout);
//    }

    template <typename T>
    static void barnes_symmetrize_(const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts) {
        //auto N = rowP->lengthOf() - 1; /// 2 + rowP->lengthOf() % 2;
        //auto numElements = output->lengthOf();
        //std::vector<int> symRowP = rowCounts->asVectorT<int>();//NDArrayFactory::create<int>('c', {numElements});
        //NDArray symValP = NDArrayFactory::create<double>('c', {numElements});
        //symRowP.insert(symRowP.begin(),0);
        //symRowP(1, {0}) = *rowCounts;
        int const* pRows = reinterpret_cast<int const*>(rowP->getBuffer());
        int* symRowP = reinterpret_cast<int*>(outputRows->buffer());
        symRowP[0] = 0;
        for (Nd4jLong n = 0; n < N; n++)
            symRowP[n + 1] = symRowP[n] + rowCounts->e<int>(n);
//        outputRows->printBuffer("output rows");

        int* symColP = reinterpret_cast<int*>(outputCols->buffer());
//            symRowP.p(n + 1, symRowP.e(n) + rowCounts.e(n))
//        outputRows->printBuffer("SymRows are");
        int const* pCols = reinterpret_cast<int const*>(colP->getBuffer());
        T const* pVals = reinterpret_cast<T const*>(valP->getBuffer());
        T* pOutput = reinterpret_cast<T*>(outputVals->buffer());
        //std::vector<int> rowCountsV = rowCounts->getBufferAsVector<int>();
        std::vector<int> offset(N);// = NDArrayFactory::create<int>('c', {N});

//PRAGMA_OMP_PARALLEL_FOR_SIMD_ARGS(schedule(guided) shared(offset))
        for (Nd4jLong n = 0; n < N; n++) {
            int begin = pRows[n];
            int bound = pRows[n + 1];

            for (int i = begin; i < bound; i++) {
                bool present = false;
                int colPI = pCols[i];
                int start = pRows[colPI];
                int end = pRows[colPI + 1];

                //PRAGMA_OMP_PARALLEL_FOR_ARGS(schedule(guided) firstprivate(offset))
                for (int m = start; m < end; m++) {
                    if (pCols[m] == n) {
                        present = true;
                        if (n <= colPI) {
                            symColP[symRowP[n] + offset[n]]        = colPI;
                            symColP[symRowP[colPI] + offset[colPI]] = n;
                            pOutput[symRowP[n] + offset[n]] = pVals[i] + pVals[m];
                            pOutput[symRowP[colPI] + offset[colPI]] = pVals[i] + pVals[m];
                        }
                    }
                }

                // If (colP[i], n) is not present, there is no addition involved
                if (!present) {
                    //int colPI = pCols[i];
                    //if (n <= colPI) {
                        symColP[symRowP[n] + offset[n]] = colPI;
                        symColP[symRowP[pCols[i]] + offset[colPI]] = n;
                        pOutput[symRowP[n] + offset[n]] = pVals[i];
                        pOutput[symRowP[colPI] + offset[colPI]] = pVals[i];
                    //}

                }
                // Update offsets
                if (!present || (present && n <= colPI)) {
                    ++offset[n];

                    if (colPI != n)
                        ++offset[colPI];
                }
//                printVector(offset);
            }
        }
    }
    void barnes_symmetrize(const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts) {

        // Divide the result by two
        BUILD_SINGLE_SELECTOR(valP->dataType(), barnes_symmetrize_, (rowP, colP, valP, N, outputRows, outputCols, outputVals, rowCounts), NUMERIC_TYPES);

        *outputVals /= 2.0;
        //output->assign(symValP);
    }
    BUILD_SINGLE_TEMPLATE(template void barnes_symmetrize_, (const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts), NUMERIC_TYPES);

    template <typename T>
    static void barnes_edge_forces_(const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray const* data, NDArray* output) {
        T const* dataP = reinterpret_cast<T const*>(data->getBuffer());
        T const* vals  = reinterpret_cast<T const*>(valP->getBuffer());
        T* outputP = reinterpret_cast<T*>(output->buffer());
        int colCount = data->columns();


//        auto shift = 0;
        auto rowSize = sizeof(T) * colCount;

        auto func = PRAGMA_THREADS_FOR {
            for (auto n = start; n < stop; n++) {
                int s = rowP->e<int>(n);
                int end = rowP->e<int>(n + 1);
                int shift = n * colCount;
                for (int i = s; i < end; i++) {
                    T const *thisSlice = dataP + colP->e<int>(i) * colCount;
                    T res = 1;

                    for (int k = 0; k < colCount; k++) {
                        auto tempVal = dataP[shift + k] - thisSlice[k];//thisSlice[k];
                        res += tempVal * tempVal;
                    }

                    res = vals[i] / res;
                    for (int k = 0; k < colCount; k++)
                        outputP[shift + k] += ((dataP[shift + k] - thisSlice[k]) * res);
                }
                //shift += colCount;
            }
        };

        sd::Threads::parallel_tad(func, 0, N);
    }

    void barnes_edge_forces(const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray* output, NDArray const& data) {
        // Loop over all edges in the graph
        BUILD_SINGLE_SELECTOR(output->dataType(), barnes_edge_forces_, (rowP, colP, valP, N, &data, output), FLOAT_TYPES);
    }
    BUILD_SINGLE_TEMPLATE(template void barnes_edge_forces_, (const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray const* data, NDArray* output), FLOAT_TYPES);

    template <typename T>
    static void barnes_gains_(NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output) {
        //        gains = gains.add(.2).muli(sign(yGrads)).neq(sign(yIncs)).castTo(Nd4j.defaultFloatingPointType())
        //                .addi(gains.mul(0.8).muli(sign(yGrads)).neq(sign(yIncs)));
        auto gainsInternal = LAMBDA_TTT(x, grad, eps) {
//            return T((x + 2.) * sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps)) + T(x * 0.8 * sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps));
            //return T((x + 2.) * sd::math::nd4j_sign<T,T>(grad) == sd::math::nd4j_sign<T,T>(eps)) + T(x * 0.8 * sd::math::nd4j_sign<T,T>(grad) == sd::math::nd4j_sign<T,T>(eps));
            T res = sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps) ? x + T(.2) : x * T(.8);
            if(res < .01) res = .01;
            return res;
        };

        input->applyTriplewiseLambda<T>(*gradX, *epsilon, gainsInternal, *output);
    }

    void barnes_gains(NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output) {
        //        gains = gains.add(.2).muli(sign(yGrads)).neq(sign(yIncs)).castTo(Nd4j.defaultFloatingPointType())
        //                .addi(gains.mul(0.8).muli(sign(yGrads)).neq(sign(yIncs)));
        BUILD_SINGLE_SELECTOR(input->dataType(), barnes_gains_, (input, gradX, epsilon, output), NUMERIC_TYPES);
//        auto signGradX = *gradX;
//        auto signEpsilon = *epsilon;
//        gradX->applyTransform(transform::Sign, &signGradX, nullptr);
//        epsilon->applyTransform(transform::Sign, &signEpsilon, nullptr);
//        auto leftPart = (*input + 2.) * signGradX;
//        auto leftPartBool = NDArrayFactory::create<bool>(leftPart.ordering(), leftPart.getShapeAsVector());
//
//        leftPart.applyPairwiseTransform(pairwise::NotEqualTo, &signEpsilon, &leftPartBool, nullptr);
//        auto rightPart = *input * 0.8 * signGradX;
//        auto rightPartBool = NDArrayFactory::create<bool>(rightPart.ordering(), rightPart.getShapeAsVector());
//        rightPart.applyPairwiseTransform(pairwise::NotEqualTo, &signEpsilon, &rightPartBool, nullptr);
//        leftPart.assign(leftPartBool);
//        rightPart.assign(rightPartBool);
//        leftPart.applyPairwiseTransform(pairwise::Add, &rightPart, output, nullptr);

    }
    BUILD_SINGLE_TEMPLATE(template void barnes_gains_, (NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output), NUMERIC_TYPES);

    bool cell_contains(NDArray* corner, NDArray* width, NDArray* point, Nd4jLong dimension) {
        auto  cornerMinusWidth = *corner - *width;
        auto cornerPlusWidth = *corner + *width;

        for (Nd4jLong i = 0; i < dimension; i++) {
            if (cornerMinusWidth.e<double>(i) > point->e<double>(i))
                return false;
            if (cornerPlusWidth.e<double>(i) < point->e<double>(i))
                return false;
        }

        return true;
    }
}
}
}