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https://github.com/UpsilonNumworks/Upsilon.git
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95 lines
3.2 KiB
C++
95 lines
3.2 KiB
C++
#include "go_to_parameter_controller.h"
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#include "graph_controller.h"
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#include "../apps_container.h"
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#include <assert.h>
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#include <float.h>
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#include <cmath>
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using namespace Shared;
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using namespace Poincare;
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namespace Regression {
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GoToParameterController::GoToParameterController(Responder * parentResponder, InputEventHandlerDelegate * inputEventHandlerDelegate, Store * store, CurveViewCursor * cursor, GraphController * graphController) :
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Shared::GoToParameterController(parentResponder, inputEventHandlerDelegate, store, cursor, I18n::Message::X),
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m_store(store),
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m_xPrediction(true),
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m_graphController(graphController)
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{
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}
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void GoToParameterController::setXPrediction(bool xPrediction) {
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m_xPrediction = xPrediction;
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}
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const char * GoToParameterController::title() {
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if (m_xPrediction) {
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return I18n::translate(I18n::Message::XPrediction);
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}
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return I18n::translate(I18n::Message::YPrediction);
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}
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double GoToParameterController::parameterAtIndex(int index) {
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assert(index == 0);
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if (m_xPrediction) {
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return m_cursor->x();
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}
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return m_cursor->y();
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}
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bool GoToParameterController::setParameterAtIndex(int parameterIndex, double f) {
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assert(parameterIndex == 0);
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int series = m_graphController->selectedSeriesIndex();
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Poincare::Context * globContext = AppsContainer::sharedAppsContainer()->globalContext();
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double unknown = m_xPrediction ?
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m_store->yValueForXValue(series, f, globContext) :
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m_store->xValueForYValue(series, f, globContext);
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if (std::isnan(unknown) || std::isinf(unknown)) {
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if (!m_xPrediction) {
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double x = m_cursor->x();
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unknown = m_store->modelForSeries(series)->evaluate(m_store->coefficientsForSeries(series, globContext), x);
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if (std::fabs(unknown - f) < DBL_EPSILON) {
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// If the computed value is NaN and the current abscissa is solution
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m_graphController->selectRegressionCurve();
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m_cursor->moveTo(x, x, unknown);
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return true;
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}
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}
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// Value not reached
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Container::activeApp()->displayWarning(I18n::Message::ValueNotReachedByRegression);
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return false;
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}
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m_graphController->selectRegressionCurve();
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if (m_xPrediction) {
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m_cursor->moveTo(f, f, unknown);
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} else {
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double yFromX = m_store->modelForSeries(series)->evaluate(m_store->coefficientsForSeries(series, globContext), unknown);
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/* We here compute y2 = a*((y1-b)/a)+b, which does not always give y1,
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* because of computation precision. y2 migth thus be invalid. */
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if (std::isnan(yFromX) || std::isinf(yFromX)) {
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Container::activeApp()->displayWarning(I18n::Message::ForbiddenValue);
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return false;
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}
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m_cursor->moveTo(unknown, unknown, yFromX);
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}
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m_graphRange->centerAxisAround(CurveViewRange::Axis::X, m_cursor->x());
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m_graphRange->centerAxisAround(CurveViewRange::Axis::Y, m_cursor->y());
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return true;
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}
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void GoToParameterController::willDisplayCellForIndex(HighlightCell * cell, int index) {
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if (index == numberOfRows()-1) {
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return;
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}
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MessageTableCellWithEditableText * myCell = (MessageTableCellWithEditableText *) cell;
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if (m_xPrediction) {
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myCell->setMessage(I18n::Message::X);
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} else {
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myCell->setMessage(I18n::Message::Y);
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}
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FloatParameterController::willDisplayCellForIndex(cell, index);
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}
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}
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