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LineScanCameraTests.cpp

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    • LineScanCameraTests.cpp 11.12 KiB 
    #define _USE_MATH_DEFINES

#include "Fixtures.h"
#include "UsgsAstroLsSensorModel.h"
#include "UsgsAstroPlugin.h"

#include <gtest/gtest.h>
#include <nlohmann/json.hpp>

#include <math.h>
#include <iostream>

using json = nlohmann::json;

TEST_F(ConstVelocityLineScanSensorModel, State) {
  std::string modelState = sensorModel->getModelState();
  sensorModel->replaceModelState(modelState);

  // When this is different, the output is very hard to parse
  // TODO implement JSON diff for gtest

  EXPECT_EQ(sensorModel->getModelState(), modelState);
}

// Fly by tests

TEST_F(ConstVelocityLineScanSensorModel, Center) {
  csm::ImageCoord imagePt(8.0, 8.0);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  EXPECT_NEAR(groundPt.x, 9.99999500000, 1e-10);
  EXPECT_NEAR(groundPt.y, 0.0, 1e-10);
  EXPECT_NEAR(groundPt.z, 0.00999999500, 1e-10);
}

TEST_F(ConstVelocityLineScanSensorModel, Inversion) {
  double achievedPrecision;
  csm::ImageCoord imagePt(8.5, 8);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  csm::ImageCoord imageReprojPt =
      sensorModel->groundToImage(groundPt, 0.001, &achievedPrecision);

  EXPECT_LT(achievedPrecision, 0.001);
  EXPECT_NEAR(imagePt.line, imageReprojPt.line, 1e-3);
  EXPECT_NEAR(imagePt.samp, imageReprojPt.samp, 1e-3);
}

TEST_F(ConstVelocityLineScanSensorModel, OffBody) {
  csm::ImageCoord imagePt(0.0, 4.0);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  EXPECT_NEAR(groundPt.x, 0.04799688020, 1e-10);
  EXPECT_NEAR(groundPt.y, -7.99961602495, 1e-10);
  EXPECT_NEAR(groundPt.z, 16.00004799688, 1e-10);
}

TEST_F(ConstVelocityLineScanSensorModel, ProximateImageLocus) {
  csm::ImageCoord imagePt(8.0, 8.0);
  csm::EcefCoord groundPt(10, 2, 1);
  double precision;
  csm::WarningList warnings;
  csm::EcefLocus remoteLocus = sensorModel->imageToRemoteImagingLocus(imagePt);
  csm::EcefLocus locus = sensorModel->imageToProximateImagingLocus(
      imagePt, groundPt, 0.001, &precision, &warnings);
  double locusToGroundX = locus.point.x - groundPt.x;
  double locusToGroundY = locus.point.y - groundPt.y;
  double locusToGroundZ = locus.point.z - groundPt.z;
  EXPECT_NEAR(locus.direction.x, remoteLocus.direction.x, 1e-10);
  EXPECT_NEAR(locus.direction.y, remoteLocus.direction.y, 1e-10);
  EXPECT_NEAR(locus.direction.z, remoteLocus.direction.z, 1e-10);
  EXPECT_NEAR(locusToGroundX * locus.direction.x +
                  locusToGroundY * locus.direction.y +
                      locusToGroundZ * locus.direction.z,
              0.0, 1e-10);
  EXPECT_LT(precision, 0.001);
  EXPECT_TRUE(warnings.empty());
}

TEST_F(ConstVelocityLineScanSensorModel, RemoteImageLocus) {
  csm::ImageCoord imagePt(8.5, 8.0);
  double precision;
  csm::WarningList warnings;
  csm::EcefLocus locus = sensorModel->imageToRemoteImagingLocus(
      imagePt, 0.001, &precision, &warnings);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  double lookX = groundPt.x - locus.point.x;
  double lookY = groundPt.y - locus.point.y;
  double lookZ = groundPt.z - locus.point.z;
  double lookMag = sqrt(lookX * lookX + lookY * lookY + lookZ * lookZ);
  lookX /= lookMag;
  lookY /= lookMag;
  lookZ /= lookMag;
  EXPECT_NEAR(locus.direction.x, lookX, 1e-10);
  EXPECT_NEAR(locus.direction.y, lookY, 1e-10);
  EXPECT_NEAR(locus.direction.z, lookZ, 1e-10);
  EXPECT_NEAR(locus.point.x, 1000.0, 1e-10);
  EXPECT_NEAR(locus.point.y, 0.0, 1e-10);
  EXPECT_NEAR(locus.point.z, 0.0, 1e-10);
  EXPECT_LT(precision, 0.001);
  EXPECT_TRUE(warnings.empty());
}

TEST_F(ConstVelocityLineScanSensorModel, calculateAttitudeCorrection) {
  std::vector<double> adj;
  double attCorr[9];
  adj.resize(15, 0);
  // Pi/2 with simply compensating for member variable m_flyingHeight in
  // UsgsAstroLsSensorModel
  adj[7] = (M_PI / 2) * sensorModel->m_flyingHeight;
  sensorModel->calculateAttitudeCorrection(999.5, adj, attCorr);

  // EXPECT_NEARs are used here instead of EXPECT_DOUBLE_EQs because index 0 and
  // 8 of the matrix are evaluating to 6.12...e-17. This is too small to be
  // worried about here, but EXPECT_DOUBLE_EQ is too sensitive.
  EXPECT_NEAR(attCorr[0], 0, 1e-8);
  EXPECT_NEAR(attCorr[1], 0, 1e-8);
  EXPECT_NEAR(attCorr[2], 1, 1e-8);
  EXPECT_NEAR(attCorr[3], 0, 1e-8);
  EXPECT_NEAR(attCorr[4], 1, 1e-8);
  EXPECT_NEAR(attCorr[5], 0, 1e-8);
  EXPECT_NEAR(attCorr[6], -1, 1e-8);
  EXPECT_NEAR(attCorr[7], 0, 1e-8);
  EXPECT_NEAR(attCorr[8], 0, 1e-8);
}

TEST_F(OrbitalLineScanSensorModel, getIlluminationDirectionStationary) {
  // Get state information, replace sun position / velocity to hit third case:
  //  One position, no velocity.
  std::string state = sensorModel->getModelState();
  json jState = stateAsJson(state);
  jState["m_sunPosition"] = std::vector<double>{100.0, 100.0, 100.0};
  jState["m_sunVelocity"] = std::vector<double>{};
  sensorModel->replaceModelState(jState.dump());

  csm::ImageCoord imagePt(8.5, 8);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  csm::EcefVector direction = sensorModel->getIlluminationDirection(groundPt);

  // Calculate expected sun direction
  // These are the ground point coordinates minus constant sun positions.
  double expected_x = groundPt.x - sensorModel->m_sunPosition[0];
  double expected_y = groundPt.y - sensorModel->m_sunPosition[1];
      double expected_z = groundPt.z - sensorModel->m_sunPosition[2];

  // normalize
  double scale = sqrt((expected_x * expected_x) + (expected_y * expected_y) +
                      (expected_z * expected_z));
  expected_x /= scale;
  expected_y /= scale;
  expected_z /= scale;

  EXPECT_DOUBLE_EQ(direction.x, expected_x);
  EXPECT_DOUBLE_EQ(direction.y, expected_y);
  EXPECT_DOUBLE_EQ(direction.z, expected_z);
}

TEST_F(OrbitalLineScanSensorModel, getSunPositionLagrange) {
  csm::EcefVector sunPosition = sensorModel->getSunPosition(-.6);
  EXPECT_NEAR(sunPosition.x, 125, 1e-11);
  EXPECT_NEAR(sunPosition.y, 125, 1e-11);
  EXPECT_NEAR(sunPosition.z, 125, 1e-11);
}

TEST_F(OrbitalLineScanSensorModel, getSunPositionLinear) {
  // Get state information, replace sun position / velocity to hit third case:
  //  One position, no velocity.
  std::string state = sensorModel->getModelState();
  json jState = stateAsJson(state);
  jState["m_sunPosition"] = std::vector<double>{100.0, 100.0, 100.0};
  jState["m_sunVelocity"] = std::vector<double>{50.0, 50.0, 50.0};
  sensorModel->replaceModelState(jState.dump());

  csm::EcefVector sunPosition = sensorModel->getSunPosition(.5);
  EXPECT_DOUBLE_EQ(sunPosition.x, 125);
  EXPECT_DOUBLE_EQ(sunPosition.y, 125);
  EXPECT_DOUBLE_EQ(sunPosition.z, 125);
}

TEST_F(OrbitalLineScanSensorModel, getSunPositionStationary) {
  // Get state information, replace sun position / velocity to hit third case:
  //  One position, no velocity.
  std::string state = sensorModel->getModelState();
  json jState = stateAsJson(state);
  jState["m_sunPosition"] = std::vector<double>{100.0, 100.0, 100.0};
  jState["m_sunVelocity"] = std::vector<double>{};
  sensorModel->replaceModelState(jState.dump());

  csm::EcefVector sunPosition = sensorModel->getSunPosition(1);
  EXPECT_DOUBLE_EQ(sunPosition.x, 100);
  EXPECT_DOUBLE_EQ(sunPosition.y, 100);
  EXPECT_DOUBLE_EQ(sunPosition.z, 100);
}

TEST_F(OrbitalLineScanSensorModel, Center) {
  csm::ImageCoord imagePt(8.5, 8.0);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
  EXPECT_NEAR(groundPt.x, 999999.67004351015, 1e-9);
  EXPECT_NEAR(groundPt.y, 0.0, 1e-9);
  EXPECT_NEAR(groundPt.z, -812.35021438796923, 1e-9);
}

TEST_F(OrbitalLineScanSensorModel, Inversion) {
  double achievedPrecision;
  for (double line = 0.5; line < 16; line++) {
    csm::ImageCoord imagePt(line, 8);
    csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 0.0);
    csm::ImageCoord imageReprojPt =
        sensorModel->groundToImage(groundPt, 0.001, &achievedPrecision);

    // groundToImage has a default precision of 0.001m and each pixel is 100m
    // so we should be within 0.1 pixels
    EXPECT_LT(achievedPrecision, 0.001);
        EXPECT_NEAR(imagePt.line, imageReprojPt.line, 0.1);
    EXPECT_NEAR(imagePt.samp, imageReprojPt.samp, 0.1);
  }
}

TEST_F(OrbitalLineScanSensorModel, ImageToGroundHeight) {
  csm::ImageCoord imagePt(8.5, 8);
  csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 100.0);
  double height = sqrt(groundPt.x * groundPt.x + groundPt.y * groundPt.y +
                       groundPt.z * groundPt.z);

  EXPECT_DOUBLE_EQ(height, 1000100);
}

TEST_F(OrbitalLineScanSensorModel, InversionHeight) {
  for (double line = 0.5; line < 16; line++) {
    csm::ImageCoord imagePt(line, 8);
    csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 100.0);
    csm::ImageCoord imageReprojPt = sensorModel->groundToImage(groundPt);

    // groundToImage has a default precision of 0.001m and each pixel is 100m
    // so we should be within 0.1 pixels
    EXPECT_NEAR(imagePt.line, imageReprojPt.line, 0.1);
    EXPECT_NEAR(imagePt.samp, imageReprojPt.samp, 0.1);
  }
}

TEST_F(OrbitalLineScanSensorModel, InversionReallyHigh) {
  for (double line = 0.5; line < 16; line++) {
    csm::ImageCoord imagePt(line, 8);
    csm::EcefCoord groundPt = sensorModel->imageToGround(imagePt, 4900.0);
    csm::ImageCoord imageReprojPt = sensorModel->groundToImage(groundPt);

    // groundToImage has a default precision of 0.001m and each pixel is 2m
    // so we should be within 0.002 pixels
    EXPECT_NEAR(imagePt.line, imageReprojPt.line, 0.002);
    EXPECT_NEAR(imagePt.samp, imageReprojPt.samp, 0.002);
  }
}

TEST_F(OrbitalLineScanSensorModel, ReferenceDateTime) {
  std::string date = sensorModel->getReferenceDateAndTime();
  EXPECT_EQ(date, "2000-01-01T00:16:39Z");
}

TEST_F(TwoLineScanSensorModels, CrossCovariance) {
  std::vector<double> crossCovars =
      sensorModel1->getCrossCovarianceMatrix(*sensorModel2);
  ASSERT_EQ(crossCovars.size(), sensorModel1->getNumParameters() *
                                    sensorModel2->getNumParameters());
  for (int i = 0; i < sensorModel1->getNumParameters(); i++) {
    for (int j = 0; j < sensorModel2->getNumParameters(); j++) {
      EXPECT_EQ(crossCovars[i * sensorModel2->getNumParameters() + j], 0.0)
          << "Value at row " << i << " column " << j;
    }
  }

  std::vector<double> covars =
      sensorModel1->getCrossCovarianceMatrix(*sensorModel1);
  ASSERT_EQ(covars.size(), 16 * 16);
  for (int i = 0; i < 16; i++) {
    for (int j = 0; j < 16; j++) {
      if (i == j) {
        EXPECT_GT(covars[i * 16 + j], 0.0)
            << "Value at row " << i << " column " << j;
      } else {
        EXPECT_EQ(covars[i * 16 + j], 0.0)
            << "Value at row " << i << " column " << j;
      }
    }
      }

  std::vector<double> fixedCovars = sensorModel1->getCrossCovarianceMatrix(
      *sensorModel1, csm::param::NON_ADJUSTABLE);
  EXPECT_EQ(fixedCovars.size(), 0);
}

TEST_F(ConstVelocityLineScanSensorModel, FocalLengthAdjustment) {
  csm::ImageCoord imagePt(8.5, 4.0);
  sensorModel->setParameterValue(15, 0.9 * sensorModel->m_halfSwath);
  csm::EcefLocus locus = sensorModel->imageToRemoteImagingLocus(imagePt);
  double scale = sqrt(5 * 5 + 0.4 * 0.4 + 0.05 * 0.05);
  EXPECT_DOUBLE_EQ(locus.direction.x, -5.0 / scale);
  EXPECT_DOUBLE_EQ(locus.direction.y, -0.4 / scale);
  EXPECT_DOUBLE_EQ(locus.direction.z, -0.05 / scale);
}