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The caches used for function values memoization are now stored in ContinuousFunctionStore : there are now only a fixed number, instead of one per function. This effectively enables caching only for the first few functions on screen, while reducing the memory usage. Change-Id: I2ade091717f73a14a756fe527c773db8e8627be7
155 lines
5.3 KiB
C++
155 lines
5.3 KiB
C++
#include "continuous_function_cache.h"
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#include "continuous_function.h"
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namespace Shared {
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constexpr int ContinuousFunctionCache::k_sizeOfCache;
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constexpr float ContinuousFunctionCache::k_cacheHitTolerance;
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constexpr int ContinuousFunctionCache::k_numberOfAvailableCaches;
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// public
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void ContinuousFunctionCache::PrepareCache(void * f, void * ctx, void * cch, float tMin, float tStep) {
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if (!cch) {
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return;
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}
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ContinuousFunction * function = (ContinuousFunction *)f;
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Poincare::Context * context = (Poincare::Context *)ctx;
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if (!function->cache()) {
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ContinuousFunctionCache * cache = (ContinuousFunctionCache *)cch;
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cache->clear();
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function->setCache(cache);
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}
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if (function->cache()->filled() && tStep / StepFactor(function) == function->cache()->step()) {
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if (function->plotType() == ContinuousFunction::PlotType::Cartesian) {
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function->cache()->pan(function, context, tMin);
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}
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return;
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}
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function->cache()->setRange(function, tMin, tStep);
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function->cache()->memoize(function, context);
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}
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void ContinuousFunctionCache::clear() {
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m_filled = false;
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m_startOfCache = 0;
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}
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Poincare::Coordinate2D<float> ContinuousFunctionCache::valueForParameter(const ContinuousFunction * function, float t) const {
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int iRes = indexForParameter(function, t);
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/* If t does not map to an index, iRes is -1 */
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if (iRes < 0) {
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return Poincare::Coordinate2D<float>(NAN, NAN);
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}
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if (function->plotType() == ContinuousFunction::PlotType::Cartesian) {
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return Poincare::Coordinate2D<float>(t, m_cache[iRes]);
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}
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assert(m_startOfCache == 0);
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return Poincare::Coordinate2D<float>(m_cache[2*iRes], m_cache[2*iRes+1]);
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}
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// private
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float ContinuousFunctionCache::StepFactor(ContinuousFunction * function) {
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/* When drawing a parametric or polar curve, the range is first divided by
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* ~10,9, creating 11 intervals which are filled by dichotomy.
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* We memoize 16 values for each of the 10 big intervals. */
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return (function->plotType() == ContinuousFunction::PlotType::Cartesian) ? 1.f : 16.f;
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}
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void ContinuousFunctionCache::setRange(ContinuousFunction * function, float tMin, float tStep) {
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m_tMin = tMin;
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m_tStep = tStep / StepFactor(function);
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}
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void ContinuousFunctionCache::memoize(ContinuousFunction * function, Poincare::Context * context) {
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m_filled = true;
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m_startOfCache = 0;
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if (function->plotType() == ContinuousFunction::PlotType::Cartesian) {
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memoizeYForX(function, context);
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return;
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}
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memoizeXYForT(function, context);
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}
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void ContinuousFunctionCache::memoizeYForX(ContinuousFunction * function, Poincare::Context * context) {
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memoizeYForXBetweenIndices(function, context, 0, k_sizeOfCache);
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}
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void ContinuousFunctionCache::memoizeYForXBetweenIndices(ContinuousFunction * function, Poincare::Context * context, int iInf, int iSup) {
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assert(function->plotType() == ContinuousFunction::PlotType::Cartesian);
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for (int i = iInf; i < iSup; i++) {
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m_cache[i] = function->privateEvaluateXYAtParameter(parameterForIndex(i), context).x2();
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}
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}
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void ContinuousFunctionCache::memoizeXYForT(ContinuousFunction * function, Poincare::Context * context) {
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assert(function->plotType() != ContinuousFunction::PlotType::Cartesian);
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for (int i = 1; i < k_sizeOfCache; i += 2) {
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Poincare::Coordinate2D<float> res = function->privateEvaluateXYAtParameter(parameterForIndex(i/2), context);
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m_cache[i - 1] = res.x1();
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m_cache[i] = res.x2();
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}
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}
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float ContinuousFunctionCache::parameterForIndex(int i) const {
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if (i < m_startOfCache) {
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i += k_sizeOfCache;
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}
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return m_tMin + m_tStep * (i - m_startOfCache);
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}
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int ContinuousFunctionCache::indexForParameter(const ContinuousFunction * function, float t) const {
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float delta = (t - m_tMin) / m_tStep;
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if (delta < 0 || delta > INT_MAX) {
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return -1;
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}
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int res = std::round(delta);
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assert(res >= 0);
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if (res >= k_sizeOfCache || std::abs(res - delta) > k_cacheHitTolerance) {
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return -1;
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}
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assert(function->plotType() == ContinuousFunction::PlotType::Cartesian || m_startOfCache == 0);
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return (res + m_startOfCache) % k_sizeOfCache;
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}
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void ContinuousFunctionCache::pan(ContinuousFunction * function, Poincare::Context * context, float newTMin) {
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assert(function->plotType() == ContinuousFunction::PlotType::Cartesian);
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if (newTMin == m_tMin) {
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return;
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}
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float dT = (newTMin - m_tMin) / m_tStep;
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m_tMin = newTMin;
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if (std::abs(dT) > INT_MAX) {
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memoize(function, context);
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return;
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}
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int dI = std::round(dT);
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if (dI >= k_sizeOfCache || dI <= -k_sizeOfCache || std::abs(dT - dI) > k_cacheHitTolerance) {
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memoize(function, context);
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return;
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}
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int oldStart = m_startOfCache;
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m_startOfCache = (m_startOfCache + dI) % k_sizeOfCache;
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if (m_startOfCache < 0) {
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m_startOfCache += k_sizeOfCache;
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}
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if (dI > 0) {
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if (m_startOfCache > oldStart) {
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memoizeYForXBetweenIndices(function, context, oldStart, m_startOfCache);
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} else {
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memoizeYForXBetweenIndices(function, context, oldStart, k_sizeOfCache);
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memoizeYForXBetweenIndices(function, context, 0, m_startOfCache);
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}
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} else {
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if (m_startOfCache > oldStart) {
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memoizeYForXBetweenIndices(function, context, m_startOfCache, k_sizeOfCache);
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memoizeYForXBetweenIndices(function, context, 0, oldStart);
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} else {
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memoizeYForXBetweenIndices(function, context, m_startOfCache, oldStart);
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}
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}
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}
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}
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