146 lines
4.3 KiB
C++
146 lines
4.3 KiB
C++
// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#include <random>
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#include <catch2/catch_all.hpp>
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#include "../jungfrau/JFPedestalCalc.h"
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TEST_CASE("JFPedestalCalc", "[JFPedestalCalc]") {
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for (int gain_level = 0; gain_level < 3; gain_level++) {
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uint16_t base_value;
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uint16_t wrong_value;
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uint16_t mask_value;
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DiffractionExperiment x(DetJF(1));
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switch (gain_level) {
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case 1:
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base_value = 0x4000;
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wrong_value = 0xc000;
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mask_value = 4;
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x.Mode(DetectorMode::PedestalG1);
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break;
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case 2:
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base_value = 0xc000;
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wrong_value = 0;
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mask_value = 8;
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x.Mode(DetectorMode::PedestalG2);
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break;
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default:
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base_value = 0;
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wrong_value = 0x4000;
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mask_value = 2;
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x.Mode(DetectorMode::Conversion);
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break;
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}
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std::vector<uint16_t> image(RAW_MODULE_SIZE, base_value);
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for (int i = 0; i < RAW_MODULE_SIZE; i++)
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image[i] += i;
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image[2] = wrong_value;
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JFPedestalCalc calc(x);
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// Predictable random number generator
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std::mt19937 g1(0);
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std::normal_distribution<double> distribution(12000.0, 12.5);
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for (int i = 0; i < 299; i++) {
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image[3] = base_value + distribution(g1);
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calc.AnalyzeImage(image.data());
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}
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image[3] = base_value + distribution(g1);
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image[0] = wrong_value;
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image[1] = wrong_value;
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image[2] = base_value;
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calc.AnalyzeImage(image.data());
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JFModulePedestal calib;
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calc.Export(calib, 1);
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for (int i = 4; i < RAW_MODULE_COLS; i++)
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REQUIRE(calib.GetPedestal()[i] == i);
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REQUIRE(calib.GetPedestal()[3] > 11900.0);
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REQUIRE(calib.GetPedestal()[3] < 12100.0);
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REQUIRE(calib.GetPedestal()[0] == 0);
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calc.Export(calib, 0);
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auto pedestal = calib.GetPedestal();
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for (int i = 4; i < RAW_MODULE_COLS; i++) {
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REQUIRE(pedestal[i] == i);
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}
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}
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}
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int16_t r(std::mt19937 &g, std::normal_distribution<double> &dist) {
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double tmp = -5;
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while ((tmp < 0) || (tmp > INT16_MAX))
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tmp = dist(g);
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return tmp;
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}
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TEST_CASE("JFPedestalCalc_MaskRMS", "[JFPedestalCalc]") {
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DiffractionExperiment x(DetJF(1));
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x.Mode(DetectorMode::Conversion);
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std::vector<uint16_t> image(RAW_MODULE_SIZE, 0);
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JFPedestalCalc calc(x);
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// Predictable random number generator
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std::mt19937 g1(0);
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std::normal_distribution<double> distribution0(12000.0, 30);
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std::normal_distribution<double> distribution1(5000.0, 50);
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std::normal_distribution<double> distribution2(1000.0, 65);
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std::normal_distribution<double> distribution3(1000.0, 70);
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for (int i = 0; i < 1024; i++) {
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image[0] = r(g1, distribution0);
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image[1] = r(g1, distribution1);
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image[2] = r(g1, distribution2);
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image[511 * 1024 + 34] = r(g1, distribution3);
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calc.AnalyzeImage(image.data());
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}
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JFModulePedestal calib;
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calc.Export(calib, 1);
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REQUIRE(fabs(calib.GetPedestalRMS()[0]-30) < 3.0);
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REQUIRE(fabs(calib.GetPedestalRMS()[1]-50) < 3.0);
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REQUIRE(fabs(calib.GetPedestalRMS()[2]-65) < 3.0);
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REQUIRE(fabs(calib.GetPedestalRMS()[511 * 1024 + 34]-70) < 3.0);
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}
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TEST_CASE("PedestalCalc_ImagesLessThanWindow", "[JFPedestalCalc]") {
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DiffractionExperiment x(DetJF(1));
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x.Mode(DetectorMode::PedestalG2);
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JFModulePedestal calib;
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JFPedestalCalc calc(x);
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// No images at all
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calc.Export(calib);
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REQUIRE(calib.GetPedestal()[0] == PEDESTAL_WRONG);
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std::vector<uint16_t> image(RAW_MODULE_SIZE, 0xc000 + 12000);
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for (int i = 0; i < PEDESTAL_MIN_IMAGE_COUNT- 1; i++)
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calc.AnalyzeImage(image.data());
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// 127 images
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calc.Export(calib);
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REQUIRE(calib.GetPedestal()[0] == PEDESTAL_WRONG);
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REQUIRE(calib.CountMaskedPixels() == RAW_MODULE_SIZE);
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// 128 images
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calc.AnalyzeImage(image.data());
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calc.Export(calib);
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REQUIRE(calib.GetPedestal()[0] == 12000);
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REQUIRE(calib.GetPedestal()[511*1024+33] == 12000);
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}
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