mirror of
https://github.com/UpsilonNumworks/Upsilon.git
synced 2026-01-18 16:27:34 +01:00
* Initial test - working on Linux
* Try to make it work with liba
* Stop using liba and the filesystem
* IT WORKS
* Key input, full res, fix some of the crashes
* Fix the hang when doing calculations
* Add some more key mappings
* Fix the square root issue
* Icons
* Better key mappings, brightness control, better gamma correction, more effficient framebuffer
* Cleanup stage 1
* Cleanup stage 2
* Make the build system build a g3a
* Make it not exit when you press the menu button
* Add Casio port to README
* Use omega-master instead of omega-dev
* Fix mistake with cherry-picking in the README
* Fix internal storage crash
* Fix compile error on Numworks calculators
* Upsilon branding
* Sharper icon
* Make the CI work
* Add power off and improve menu
* Map Alpha + up/down to the brightness shortcut
* Add missing file
* Fix web CI build
* Revert "Fix web CI build"
This reverts commit f19657d9fc.
* Change "prizm" to "fxcg"
* Add FASTLOAD option for Add-in Push
* Add some charatcers to the catalog on Casio and improve key mappings
* Build with -Os -flto
* Disable LTO for now as it's causing crashes
* Put back the fonts I accidently changed
I'd like to add an option for this though as I prefer the ones from Epsilon
436 lines
19 KiB
C++
436 lines
19 KiB
C++
#include "continuous_function.h"
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#include "poincare_helpers.h"
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#include <apps/constant.h>
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#include <poincare/derivative.h>
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#include <poincare/integral.h>
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#include <poincare/matrix.h>
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#include <poincare/multiplication.h>
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#include <poincare/rational.h>
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#include <poincare/serialization_helper.h>
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#include <poincare/trigonometry.h>
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#include <escher/palette.h>
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#include <ion/unicode/utf8_helper.h>
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#include <ion/unicode/utf8_decoder.h>
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#include <apps/i18n.h>
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#include <float.h>
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#include <cmath>
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#include <algorithm>
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using namespace Poincare;
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namespace Shared {
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void ContinuousFunction::DefaultName(char buffer[], size_t bufferSize) {
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constexpr int k_maxNumberOfDefaultLetterNames = 4;
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static constexpr const char k_defaultLetterNames[k_maxNumberOfDefaultLetterNames] = {
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'f', 'g', 'h', 'p'
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};
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/* First default names are f, g, h, p and then f0, f1... ie, "f[number]",
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* for instance "f12", that does not exist yet in the storage. */
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size_t constantNameLength = 1; // 'f', no null-terminating char
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assert(bufferSize > constantNameLength+1);
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// Find the next available name
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int currentNumber = -k_maxNumberOfDefaultLetterNames;
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int currentNumberLength = 0;
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int availableBufferSize = bufferSize - constantNameLength;
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while (currentNumberLength < availableBufferSize) {
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// Choose letter
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buffer[0] = currentNumber < 0 ? k_defaultLetterNames[k_maxNumberOfDefaultLetterNames+currentNumber] : k_defaultLetterNames[0];
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// Choose number if required
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if (currentNumber >= 0) {
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currentNumberLength = Poincare::Integer(currentNumber).serialize(&buffer[1], availableBufferSize);
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} else {
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buffer[1] = 0;
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}
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if (GlobalContext::SymbolAbstractNameIsFree(buffer)) {
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// Name found
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break;
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}
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currentNumber++;
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}
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assert(currentNumberLength >= 0 && currentNumberLength < availableBufferSize);
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}
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ContinuousFunction ContinuousFunction::NewModel(Ion::Storage::Record::ErrorStatus * error, const char * baseName) {
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static int s_colorIndex = 0;
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// Create the record
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char nameBuffer[SymbolAbstract::k_maxNameSize];
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RecordDataBuffer data(Palette::nextDataColor(&s_colorIndex));
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if (baseName == nullptr) {
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DefaultName(nameBuffer, SymbolAbstract::k_maxNameSize);
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baseName = nameBuffer;
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}
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*error = Ion::Storage::sharedStorage()->createRecordWithExtension(baseName, Ion::Storage::funcExtension, &data, sizeof(data));
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// Return if error
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if (*error != Ion::Storage::Record::ErrorStatus::None) {
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return ContinuousFunction();
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}
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// Return the ContinuousFunction withthe new record
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return ContinuousFunction(Ion::Storage::sharedStorage()->recordBaseNamedWithExtension(baseName, Ion::Storage::funcExtension));
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}
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int ContinuousFunction::derivativeNameWithArgument(char * buffer, size_t bufferSize) {
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// Fill buffer with f(x). Keep size for derivative sign.
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int derivativeSize = UTF8Decoder::CharSizeOfCodePoint('\'');
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int numberOfChars = nameWithArgument(buffer, bufferSize - derivativeSize);
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assert(numberOfChars + derivativeSize < (int)bufferSize);
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char * firstParenthesis = const_cast<char *>(UTF8Helper::CodePointSearch(buffer, '('));
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if (!UTF8Helper::CodePointIs(firstParenthesis, '(')) {
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return numberOfChars;
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}
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memmove(firstParenthesis + derivativeSize, firstParenthesis, numberOfChars - (firstParenthesis - buffer) + 1);
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UTF8Decoder::CodePointToChars('\'', firstParenthesis, derivativeSize);
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return numberOfChars + derivativeSize;
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}
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Poincare::Expression ContinuousFunction::expressionReduced(Poincare::Context * context) const {
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Poincare::Expression result = ExpressionModelHandle::expressionReduced(context);
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if (plotType() == PlotType::Parametric && (
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result.type() != Poincare::ExpressionNode::Type::Matrix ||
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static_cast<Poincare::Matrix&>(result).numberOfRows() != 2 ||
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static_cast<Poincare::Matrix&>(result).numberOfColumns() != 1)
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) {
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return Poincare::Expression::Parse("[[undef][undef]]", nullptr);
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}
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return result;
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}
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I18n::Message ContinuousFunction::parameterMessageName() const {
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return ParameterMessageForPlotType(plotType());
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}
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CodePoint ContinuousFunction::symbol() const {
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switch (plotType()) {
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case PlotType::Cartesian:
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return 'x';
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case PlotType::Polar:
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return UCodePointGreekSmallLetterTheta;
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default:
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assert(plotType() == PlotType::Parametric);
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return 't';
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}
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}
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ContinuousFunction::PlotType ContinuousFunction::plotType() const {
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return recordData()->plotType();
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}
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void ContinuousFunction::setPlotType(PlotType newPlotType, Poincare::Preferences::AngleUnit angleUnit, Context * context) {
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PlotType currentPlotType = plotType();
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if (newPlotType == currentPlotType) {
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return;
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}
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recordData()->setPlotType(newPlotType);
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setCache(nullptr);
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// Recompute the layouts
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m_model.tidy();
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// Recompute the definition domain
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double tMin = newPlotType == PlotType::Cartesian ? -INFINITY : 0.0;
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double tMax = newPlotType == PlotType::Cartesian ? INFINITY : 2.0*Trigonometry::PiInAngleUnit(angleUnit);
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setTMin(tMin);
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setTMax(tMax);
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/* Recompute the unknowns. For instance, if the function was f(x) = xθ, it is
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* stored as f(?) = ?θ. When switching to polar type, it should be stored as
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* f(?) = ?? */
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constexpr int previousTextContentMaxSize = Constant::MaxSerializedExpressionSize;
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char previousTextContent[previousTextContentMaxSize];
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m_model.text(this, previousTextContent, previousTextContentMaxSize, symbol());
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setContent(previousTextContent, context);
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// Handle parametric function switch
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if (currentPlotType == PlotType::Parametric) {
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Expression e = expressionClone();
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// Change [x(t) y(t)] to y(t)
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if (!e.isUninitialized()
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&& e.type() == ExpressionNode::Type::Matrix
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&& static_cast<Poincare::Matrix&>(e).numberOfRows() == 2
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&& static_cast<Poincare::Matrix&>(e).numberOfColumns() == 1)
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{
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Expression nextContent = e.childAtIndex(1);
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/* We need to detach it, otherwise nextContent will think it has a parent
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* when we retrieve it from the storage. */
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nextContent.detachFromParent();
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setExpressionContent(nextContent);
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}
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return;
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} else if (newPlotType == PlotType::Parametric) {
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Expression e = expressionClone();
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// Change y(t) to [t y(t)]
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Matrix newExpr = Matrix::Builder();
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newExpr.addChildAtIndexInPlace(Symbol::Builder(UCodePointUnknown), 0, 0);
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// if y(t) was not uninitialized, insert [t 2t] to set an example
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e = e.isUninitialized() ? Multiplication::Builder(Rational::Builder(2), Symbol::Builder(UCodePointUnknown)) : e;
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newExpr.addChildAtIndexInPlace(e, newExpr.numberOfChildren(), newExpr.numberOfChildren());
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newExpr.setDimensions(2, 1);
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setExpressionContent(newExpr);
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}
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}
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I18n::Message ContinuousFunction::ParameterMessageForPlotType(PlotType plotType) {
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if (plotType == PlotType::Cartesian) {
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return I18n::Message::X;
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}
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if (plotType == PlotType::Polar) {
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return I18n::Message::Theta;
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}
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assert(plotType == PlotType::Parametric);
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return I18n::Message::T;
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}
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template <typename T>
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Poincare::Coordinate2D<T> ContinuousFunction::privateEvaluateXYAtParameter(T t, Poincare::Context * context) const {
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Coordinate2D<T> x1x2 = templatedApproximateAtParameter(t, context);
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PlotType type = plotType();
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if (type == PlotType::Cartesian || type == PlotType::Parametric) {
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return x1x2;
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}
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assert(type == PlotType::Polar);
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T factor = (T)1.0;
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Preferences::AngleUnit angleUnit = Preferences::sharedPreferences()->angleUnit();
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if (angleUnit == Preferences::AngleUnit::Degree) {
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factor = (T) (M_PI/180.0);
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} else if (angleUnit == Preferences::AngleUnit::Gradian) {
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factor = (T) (M_PI/200.0);
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} else {
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assert(angleUnit == Preferences::AngleUnit::Radian);
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}
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const float angle = x1x2.x1()*factor;
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return Coordinate2D<T>(x1x2.x2() * std::cos(angle), x1x2.x2() * std::sin(angle));
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}
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bool ContinuousFunction::displayDerivative() const {
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return recordData()->displayDerivative();
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}
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void ContinuousFunction::setDisplayDerivative(bool display) {
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return recordData()->setDisplayDerivative(display);
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}
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int ContinuousFunction::printValue(double cursorT, double cursorX, double cursorY, char * buffer, int bufferSize, int precision, Poincare::Context * context) {
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PlotType type = plotType();
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if (type == PlotType::Cartesian) {
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return Function::printValue(cursorT, cursorX, cursorY, buffer, bufferSize, precision, context);
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}
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if (type == PlotType::Polar) {
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return PoincareHelpers::ConvertFloatToText<double>(evaluate2DAtParameter(cursorT, context).x2(), buffer, bufferSize, precision);
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}
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assert(type == PlotType::Parametric);
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int result = 0;
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result += UTF8Decoder::CodePointToChars('(', buffer+result, bufferSize-result);
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result += PoincareHelpers::ConvertFloatToText<double>(cursorX, buffer+result, bufferSize-result, precision);
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result += UTF8Decoder::CodePointToChars(';', buffer+result, bufferSize-result);
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result += PoincareHelpers::ConvertFloatToText<double>(cursorY, buffer+result, bufferSize-result, precision);
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result += UTF8Decoder::CodePointToChars(')', buffer+result, bufferSize-result);
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return result;
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}
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double ContinuousFunction::approximateDerivative(double x, Poincare::Context * context) const {
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assert(plotType() == PlotType::Cartesian);
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if (x < tMin() || x > tMax()) {
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return NAN;
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}
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Poincare::Derivative derivative = Poincare::Derivative::Builder(expressionReduced(context).clone(), Symbol::Builder(UCodePointUnknown), Poincare::Float<double>::Builder(x)); // derivative takes ownership of Poincare::Float<double>::Builder(x) and the clone of expression
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/* TODO: when we approximate derivative, we might want to simplify the
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* derivative here. However, we might want to do it once for all x (to avoid
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* lagging in the derivative table. */
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return PoincareHelpers::ApproximateToScalar<double>(derivative, context);
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}
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float ContinuousFunction::tMin() const {
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return recordData()->tMin();
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}
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float ContinuousFunction::tMax() const {
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return recordData()->tMax();
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}
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void ContinuousFunction::setTMin(float tMin) {
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recordData()->setTMin(tMin);
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setCache(nullptr);
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}
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void ContinuousFunction::setTMax(float tMax) {
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recordData()->setTMax(tMax);
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setCache(nullptr);
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}
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void ContinuousFunction::rangeForDisplay(float * xMin, float * xMax, float * yMin, float * yMax, float targetRatio, Poincare::Context * context) const {
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if (plotType() != PlotType::Cartesian) {
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assert(std::isfinite(tMin()) && std::isfinite(tMax()) && std::isfinite(rangeStep()) && rangeStep() > 0);
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protectedFullRangeForDisplay(tMin(), tMax(), rangeStep(), xMin, xMax, context, true);
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protectedFullRangeForDisplay(tMin(), tMax(), rangeStep(), yMin, yMax, context, false);
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return;
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}
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if (!basedOnCostlyAlgorithms(context)) {
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Zoom::ValueAtAbscissa evaluation = [](float x, Context * context, const void * auxiliary) -> float {
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/* When evaluating sin(x)/x close to zero using the standard sine function,
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* one can detect small variations, while the cardinal sine is supposed to be
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* locally monotonous. To smooth our such variations, we round the result of
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* the evaluations. As we are not interested in precise results but only in
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* ordering, this approximation is sufficient. */
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constexpr float precision = 1e-5;
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return precision * std::round(static_cast<const Function *>(auxiliary)->evaluateXYAtParameter(x, context).x2() / precision);
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};
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bool fullyComputed = Zoom::InterestingRangesForDisplay(evaluation, xMin, xMax, yMin, yMax, tMin(), tMax(), context, this);
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evaluation = [](float x, Context * context, const void * auxiliary) {
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return static_cast<const Function *>(auxiliary)->evaluateXYAtParameter(x, context).x2();
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};
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if (fullyComputed) {
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/* The function has points of interest. */
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Zoom::RefinedYRangeForDisplay(evaluation, xMin, xMax, yMin, yMax, context, this);
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return;
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}
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/* Try to display an orthonormal range. */
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Zoom::RangeWithRatioForDisplay(evaluation, targetRatio, xMin, xMax, yMin, yMax, context, this);
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if (std::isfinite(*xMin) && std::isfinite(*xMax) && std::isfinite(*yMin) && std::isfinite(*yMax)) {
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return;
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}
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/* The function's profile is not great for an orthonormal range.
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* Try a basic range. */
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*xMin = - Zoom::k_defaultHalfRange;
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*xMax = Zoom::k_defaultHalfRange;
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Zoom::RefinedYRangeForDisplay(evaluation, xMin, xMax, yMin, yMax, context, this);
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if (std::isfinite(*xMin) && std::isfinite(*xMax) && std::isfinite(*yMin) && std::isfinite(*yMax)) {
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return;
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}
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/* The function's order of magnitude cannot be computed. Try to just display
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* the full function. */
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float step = (*xMax - *xMin) / k_polarParamRangeSearchNumberOfPoints;
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Zoom::FullRange(evaluation, *xMin, *xMax, step, yMin, yMax, context, this);
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if (std::isfinite(*xMin) && std::isfinite(*xMax) && std::isfinite(*yMin) && std::isfinite(*yMax)) {
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return;
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}
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}
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/* The function makes use of some costly algorithms and cannot be computed in
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* a timely manner, or it is probably undefined. */
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*xMin = NAN;
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*xMax = NAN;
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*yMin = NAN;
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*yMax = NAN;
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}
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void * ContinuousFunction::Model::expressionAddress(const Ion::Storage::Record * record) const {
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return (char *)record->value().buffer+sizeof(RecordDataBuffer);
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}
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size_t ContinuousFunction::Model::expressionSize(const Ion::Storage::Record * record) const {
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return record->value().size-sizeof(RecordDataBuffer);
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}
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ContinuousFunction::RecordDataBuffer * ContinuousFunction::recordData() const {
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assert(!isNull());
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Ion::Storage::Record::Data d = value();
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return reinterpret_cast<RecordDataBuffer *>(const_cast<void *>(d.buffer));
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}
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template<typename T>
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Coordinate2D<T> ContinuousFunction::templatedApproximateAtParameter(T t, Poincare::Context * context) const {
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if (t < tMin() || t > tMax()) {
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return Coordinate2D<T>(plotType() == PlotType::Cartesian ? t : NAN, NAN);
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}
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constexpr int bufferSize = CodePoint::MaxCodePointCharLength + 1;
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char unknown[bufferSize];
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Poincare::SerializationHelper::CodePoint(unknown, bufferSize, UCodePointUnknown);
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PlotType type = plotType();
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Expression e = expressionReduced(context);
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if (type != PlotType::Parametric) {
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assert(type == PlotType::Cartesian || type == PlotType::Polar);
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return Coordinate2D<T>(t, PoincareHelpers::ApproximateWithValueForSymbol(e, unknown, t, context));
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}
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assert(e.type() == ExpressionNode::Type::Matrix);
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assert(static_cast<Poincare::Matrix&>(e).numberOfRows() == 2);
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assert(static_cast<Poincare::Matrix&>(e).numberOfColumns() == 1);
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return Coordinate2D<T>(
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PoincareHelpers::ApproximateWithValueForSymbol(e.childAtIndex(0), unknown, t, context),
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PoincareHelpers::ApproximateWithValueForSymbol(e.childAtIndex(1), unknown, t, context));
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}
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Coordinate2D<double> ContinuousFunction::nextMinimumFrom(double start, double step, double max, Context * context) const {
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return nextPointOfInterestFrom(start, step, max, context, [](Expression e, char * symbol, double start, double step, double max, Context * context) { return PoincareHelpers::NextMinimum(e, symbol, start, step, max, context); });
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}
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Coordinate2D<double> ContinuousFunction::nextMaximumFrom(double start, double step, double max, Context * context) const {
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return nextPointOfInterestFrom(start, step, max, context, [](Expression e, char * symbol, double start, double step, double max, Context * context) { return PoincareHelpers::NextMaximum(e, symbol, start, step, max, context); });
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}
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Coordinate2D<double> ContinuousFunction::nextRootFrom(double start, double step, double max, Context * context) const {
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return nextPointOfInterestFrom(start, step, max, context, [](Expression e, char * symbol, double start, double step, double max, Context * context) { return Coordinate2D<double>(PoincareHelpers::NextRoot(e, symbol, start, step, max, context), 0.0); });
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}
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Coordinate2D<double> ContinuousFunction::nextIntersectionFrom(double start, double step, double max, Poincare::Context * context, Poincare::Expression e, double eDomainMin, double eDomainMax) const {
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assert(plotType() == PlotType::Cartesian);
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constexpr int bufferSize = CodePoint::MaxCodePointCharLength + 1;
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char unknownX[bufferSize];
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SerializationHelper::CodePoint(unknownX, bufferSize, UCodePointUnknown);
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double domainMin = std::max<double>(tMin(), eDomainMin);
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double domainMax = std::min<double>(tMax(), eDomainMax);
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if (step > 0.0f) {
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start = std::max(start, domainMin);
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max = std::min(max, domainMax);
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} else {
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start = std::min(start, domainMax);
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max = std::max(max, domainMin);
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}
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return PoincareHelpers::NextIntersection(expressionReduced(context), unknownX, start, step, max, context, e);
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}
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Coordinate2D<double> ContinuousFunction::nextPointOfInterestFrom(double start, double step, double max, Context * context, ComputePointOfInterest compute) const {
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assert(plotType() == PlotType::Cartesian);
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constexpr int bufferSize = CodePoint::MaxCodePointCharLength + 1;
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char unknownX[bufferSize];
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SerializationHelper::CodePoint(unknownX, bufferSize, UCodePointUnknown);
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if (step > 0.0f) {
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start = std::max<double>(start, tMin());
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max = std::min<double>(max, tMax());
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} else {
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start = std::min<double>(start, tMax());
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max = std::max<double>(max, tMin());
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}
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return compute(expressionReduced(context), unknownX, start, step, max, context);
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}
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Poincare::Expression ContinuousFunction::sumBetweenBounds(double start, double end, Poincare::Context * context) const {
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assert(plotType() == PlotType::Cartesian);
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start = std::max<double>(start, tMin());
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end = std::min<double>(end, tMax());
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return Poincare::Integral::Builder(expressionReduced(context).clone(), Poincare::Symbol::Builder(UCodePointUnknown), Poincare::Float<double>::Builder(start), Poincare::Float<double>::Builder(end)); // Integral takes ownership of args
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/* TODO: when we approximate integral, we might want to simplify the integral
|
|
* here. However, we might want to do it once for all x (to avoid lagging in
|
|
* the derivative table. */
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}
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Ion::Storage::Record::ErrorStatus ContinuousFunction::setContent(const char * c, Poincare::Context * context) {
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setCache(nullptr);
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return ExpressionModelHandle::setContent(c, context);
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}
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|
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bool ContinuousFunction::basedOnCostlyAlgorithms(Context * context) const {
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return expressionReduced(context).hasExpression([](const Expression e, const void * context) {
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|
return e.type() == ExpressionNode::Type::Sequence
|
|
|| e.type() == ExpressionNode::Type::Integral
|
|
|| e.type() == ExpressionNode::Type::Derivative;
|
|
}, nullptr);
|
|
}
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template Coordinate2D<float> ContinuousFunction::templatedApproximateAtParameter<float>(float, Poincare::Context *) const;
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template Coordinate2D<double> ContinuousFunction::templatedApproximateAtParameter<double>(double, Poincare::Context *) const;
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template Poincare::Coordinate2D<float> ContinuousFunction::privateEvaluateXYAtParameter<float>(float, Poincare::Context *) const;
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template Poincare::Coordinate2D<double> ContinuousFunction::privateEvaluateXYAtParameter<double>(double, Poincare::Context *) const;
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|
|
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}
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