mirror of
https://github.com/slsdetectorgroup/aare.git
synced 2025-06-06 21:00:41 +02:00
68dcfca74e
major changes: - add python bindings for all c++ features except network_io - changes to cross compile on windows,linux and macos - fix bugs with cluster_finder - use Dtype in Frame instead of bitdepth - remove boost::program_options and replace with our implementation - add Transforms class that applies a sequence of functions (c++ or python functions) on a Frame. - remove frame reorder and flip from SubFile.cpp. use Transforms instead - Test clusterFinder and Pedestal results in comparison with slsDetectorCalibration --------- Co-authored-by: Bechir <bechir.brahem420@gmail.com> Co-authored-by: Erik Fröjdh <erik.frojdh@gmail.com>
102 lines
3.7 KiB
C++
102 lines
3.7 KiB
C++
#include "aare/processing/Pedestal.hpp"
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#include "aare/utils/floats.hpp"
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#include <catch2/catch_test_macros.hpp>
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#include <chrono>
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#include <random>
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using namespace aare;
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TEST_CASE("test pedestal constructor") {
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aare::Pedestal pedestal(10, 10, 5);
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REQUIRE(pedestal.rows() == 10);
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REQUIRE(pedestal.cols() == 10);
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REQUIRE(pedestal.n_samples() == 5);
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REQUIRE(pedestal.cur_samples() != nullptr);
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for (int i = 0; i < 10; i++) {
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for (int j = 0; j < 10; j++) {
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REQUIRE(pedestal.get_sum()(i, j) == 0);
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REQUIRE(pedestal.get_sum2()(i, j) == 0);
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REQUIRE(pedestal.cur_samples()[pedestal.index(i, j)] == 0);
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}
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}
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}
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TEST_CASE("test pedestal push") {
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aare::Pedestal pedestal(10, 10, 5);
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aare::Frame frame(10, 10, Dtype::UINT16);
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for (int i = 0; i < 10; i++) {
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for (int j = 0; j < 10; j++) {
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frame.set<uint16_t>(i, j, i + j);
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}
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}
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// test single push
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pedestal.push<uint16_t>(frame);
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for (int i = 0; i < 10; i++) {
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for (int j = 0; j < 10; j++) {
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REQUIRE(pedestal.get_sum()(i, j) == i + j);
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REQUIRE(pedestal.get_sum2()(i, j) == (i + j) * (i + j));
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REQUIRE(pedestal.cur_samples()[pedestal.index(i, j)] == 1);
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}
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}
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// test clear
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pedestal.clear();
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for (int i = 0; i < 10; i++) {
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for (int j = 0; j < 10; j++) {
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REQUIRE(pedestal.get_sum()(i, j) == 0);
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REQUIRE(pedestal.get_sum2()(i, j) == 0);
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REQUIRE(pedestal.cur_samples()[pedestal.index(i, j)] == 0);
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}
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}
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// test number of samples after multiple push
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for (uint32_t k = 0; k < 50; k++) {
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pedestal.push<uint16_t>(frame);
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for (uint32_t i = 0; i < 10; i++) {
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for (uint32_t j = 0; j < 10; j++) {
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if (k < 5) {
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REQUIRE(pedestal.cur_samples()[pedestal.index(i, j)] == k + 1);
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REQUIRE(pedestal.get_sum()(i, j) == (k + 1) * (i + j));
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REQUIRE(pedestal.get_sum2()(i, j) == (k + 1) * (i + j) * (i + j));
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} else {
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REQUIRE(pedestal.cur_samples()[pedestal.index(i, j)] == 5);
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REQUIRE(pedestal.get_sum()(i, j) == 5 * (i + j));
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REQUIRE(pedestal.get_sum2()(i, j) == 5 * (i + j) * (i + j));
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}
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REQUIRE(pedestal.mean(i, j) == (i + j));
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REQUIRE(pedestal.variance(i, j) == 0);
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REQUIRE(pedestal.standard_deviation(i, j) == 0);
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}
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}
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}
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}
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TEST_CASE("test pedestal with normal distribution") {
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const double MEAN = 5.0, STD = 2.0, VAR = STD * STD, TOLERANCE = 0.1;
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unsigned seed = std::chrono::system_clock::now().time_since_epoch().count();
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std::default_random_engine generator(seed);
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std::normal_distribution<double> distribution(MEAN, STD);
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aare::Pedestal pedestal(3, 5, 10000);
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for (int i = 0; i < 10000; i++) {
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aare::Frame frame(3, 5, Dtype::DOUBLE);
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for (int j = 0; j < 3; j++) {
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for (int k = 0; k < 5; k++) {
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frame.set<double>(j, k, distribution(generator));
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}
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}
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pedestal.push<double>(frame);
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}
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auto mean = pedestal.mean();
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auto variance = pedestal.variance();
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auto standard_deviation = pedestal.standard_deviation();
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for (int i = 0; i < 3; i++) {
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for (int j = 0; j < 5; j++) {
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REQUIRE(compare_floats<double>(mean(i, j), MEAN, MEAN * TOLERANCE));
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REQUIRE(compare_floats<double>(variance(i, j), VAR, VAR * TOLERANCE));
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REQUIRE(compare_floats<double>(standard_deviation(i, j), STD, STD * TOLERANCE)); // maybe sqrt of tolerance?
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}
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}
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} |