For 2025.5.22 release (#181)

Co-authored-by: Patrick <patrick.sieberer@psi.ch>
Co-authored-by: JulianHeymes <julian.heymes@psi.ch>
Co-authored-by: Dhanya Thattil <dhanya.thattil@psi.ch>
Co-authored-by: Xiangyu Xie <45243914+xiangyuxie@users.noreply.github.com>
Co-authored-by: xiangyu.xie <xiangyu.xie@psi.ch>
Co-authored-by: AliceMazzoleni99 <alice.mazzoleni@psi.ch>
Co-authored-by: Mazzoleni Alice Francesca <mazzol_a@pc17378.psi.ch>
Co-authored-by: siebsi <sieb.patr@gmail.com>

.gitea/workflows/rh8-native.yml

@@ -1,18 +1,24 @@
 name: Build on RHEL8
 
 on:
+  push:
   workflow_dispatch:
 
 permissions:
   contents: read
 
 jobs:
-  buildh:
+  build:
     runs-on: "ubuntu-latest"
     container:
       image: gitea.psi.ch/images/rhel8-developer-gitea-actions
     steps:
-      - uses: actions/checkout@v4
+      # workaround until actions/checkout@v4 is available for RH8
+      # - uses: actions/checkout@v4
+      - name: Clone repository
+        run: |
+          echo Cloning ${{ github.ref_name }}
+          git clone https://${{secrets.GITHUB_TOKEN}}@gitea.psi.ch/${{ github.repository }}.git --branch=${{ github.ref_name }} .
 
 
       - name: Install dependencies
@@ -22,7 +28,7 @@ jobs:
       - name: Build library 
         run: |
             mkdir build && cd build
-            cmake .. -DAARE_PYTHON_BINDINGS=ON -DAARE_TESTS=ON
+            cmake .. -DAARE_PYTHON_BINDINGS=ON -DAARE_TESTS=ON -DPython_FIND_VIRTUALENV=FIRST
             make -j 2 
 
       - name: C++ unit tests

.gitea/workflows/rh9-native.yml

@@ -8,7 +8,7 @@ permissions:
   contents: read
 
 jobs:
-  buildh:
+  build:
     runs-on: "ubuntu-latest"
     container:
       image: gitea.psi.ch/images/rhel9-developer-gitea-actions

.github/workflows/build_and_deploy_conda.yml

@@ -1,9 +1,9 @@
 name: Build pkgs and deploy if on main
 
 on:
-  push:
-    branches:
-     - main
+  release:
+      types:
+        - published
 
 jobs:
   build:
@@ -24,13 +24,13 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Get conda
-        uses: conda-incubator/setup-miniconda@v3.0.4
+        uses: conda-incubator/setup-miniconda@v3
         with:
           python-version: ${{ matrix.python-version }}
+          environment-file: etc/dev-env.yml
+          miniforge-version: latest
           channels: conda-forge
-
-      - name: Prepare
-        run: conda install conda-build=24.9 conda-verify pytest anaconda-client
+          conda-remove-defaults: "true"
 
       - name: Enable upload
         run: conda config --set anaconda_upload yes

.github/workflows/build_conda.yml

@@ -24,14 +24,15 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Get conda
-        uses: conda-incubator/setup-miniconda@v3.0.4
+        uses: conda-incubator/setup-miniconda@v3
         with:
           python-version: ${{ matrix.python-version }}
+          environment-file: etc/dev-env.yml
+          miniforge-version: latest
           channels: conda-forge
+          conda-remove-defaults: "true"
 
-      - name: Prepare
-        run: conda install conda-build=24.9 conda-verify pytest anaconda-client
-
+  
       - name: Disable upload
         run: conda config --set anaconda_upload no
 

.github/workflows/build_wheel.yml

@@ -0,0 +1,64 @@
+name: Build wheel
+
+on:
+    workflow_dispatch:
+    pull_request:
+    push:
+      branches:
+        - main
+    release:
+      types:
+        - published
+  
+
+jobs:
+  build_wheels:
+    name: Build wheels on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest,]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Build wheels
+        run: pipx run cibuildwheel==2.23.0
+
+      - uses: actions/upload-artifact@v4
+        with:
+          name: cibw-wheels-${{ matrix.os }}-${{ strategy.job-index }}
+          path: ./wheelhouse/*.whl
+    
+  build_sdist:
+    name: Build source distribution
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Build sdist
+      run: pipx run build --sdist
+
+    - uses: actions/upload-artifact@v4
+      with:
+        name: cibw-sdist
+        path: dist/*.tar.gz
+
+  upload_pypi:
+    needs: [build_wheels, build_sdist]
+    runs-on: ubuntu-latest
+    environment: pypi
+    permissions:
+        id-token: write
+    if: github.event_name == 'release' && github.event.action == 'published'
+    # or, alternatively, upload to PyPI on every tag starting with 'v' (remove on: release above to use this)
+    # if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v')
+    steps:
+        - uses: actions/download-artifact@v4
+          with:
+            # unpacks all CIBW artifacts into dist/
+            pattern: cibw-*
+            path: dist
+            merge-multiple: true
+
+        - uses: pypa/gh-action-pypi-publish@release/v1

.gitignore

@@ -17,7 +17,8 @@ Testing/
 ctbDict.cpp
 ctbDict.h
 
-
+wheelhouse/
+dist/
 
 *.pyc
 */__pycache__/*

CMakeLists.txt

@@ -1,16 +1,29 @@
-cmake_minimum_required(VERSION 3.14)
+cmake_minimum_required(VERSION 3.15)
 
 project(aare 
-    VERSION 1.0.0
     DESCRIPTION "Data processing library for PSI detectors"
     HOMEPAGE_URL "https://github.com/slsdetectorgroup/aare"
     LANGUAGES C CXX 
 )
 
+# Read VERSION file into project version
+set(VERSION_FILE "${CMAKE_CURRENT_SOURCE_DIR}/VERSION")
+file(READ "${VERSION_FILE}" VERSION_CONTENT)
+string(STRIP "${VERSION_CONTENT}" PROJECT_VERSION_STRING)
+set(PROJECT_VERSION ${PROJECT_VERSION_STRING})
+
 set(CMAKE_CXX_STANDARD 17) 
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 set(CMAKE_CXX_EXTENSIONS OFF)
 
+execute_process(
+        COMMAND git log -1 --format=%h
+        WORKING_DIRECTORY ${CMAKE_CURRENT_LIST_DIR}
+        OUTPUT_VARIABLE GIT_HASH
+        OUTPUT_STRIP_TRAILING_WHITESPACE
+        )
+message(STATUS "Building from git hash: ${GIT_HASH}")
+
 if (${CMAKE_VERSION} VERSION_GREATER "3.24")
     cmake_policy(SET CMP0135 NEW) #Fetch content download timestamp
 endif()
@@ -66,6 +79,9 @@ endif()
 
 if(AARE_VERBOSE)
     add_compile_definitions(AARE_VERBOSE)
+    add_compile_definitions(AARE_LOG_LEVEL=aare::logDEBUG5)
+else()
+    add_compile_definitions(AARE_LOG_LEVEL=aare::logERROR)
 endif()
 
 if(AARE_CUSTOM_ASSERT)
@@ -77,6 +93,7 @@ if(AARE_BENCHMARKS)
 endif()
 
 
+
 set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
 
 if(AARE_FETCH_LMFIT)
@@ -382,15 +399,18 @@ set(SourceFiles
     ${CMAKE_CURRENT_SOURCE_DIR}/src/RawSubFile.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/src/RawMasterFile.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/src/utils/task.cpp
+    ${CMAKE_CURRENT_SOURCE_DIR}/src/utils/ifstream_helpers.cpp
 )
 
-
 add_library(aare_core STATIC ${SourceFiles})
 target_include_directories(aare_core PUBLIC 
     "$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>" 
     "$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}>" 
 )
 
+set(THREADS_PREFER_PTHREAD_FLAG ON)
+find_package(Threads REQUIRED)
+
 target_link_libraries(
     aare_core 
     PUBLIC 
@@ -399,6 +419,7 @@ target_link_libraries(
     ${STD_FS_LIB} # from helpers.cmake
     PRIVATE 
     aare_compiler_flags 
+    Threads::Threads
     $<BUILD_INTERFACE:lmfit>
 
 )
@@ -416,6 +437,7 @@ if(AARE_TESTS)
     set(TestSources
             ${CMAKE_CURRENT_SOURCE_DIR}/src/algorithm.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/defs.test.cpp
+            ${CMAKE_CURRENT_SOURCE_DIR}/src/decode.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/Dtype.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/Frame.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/geo_helpers.test.cpp
@@ -427,11 +449,13 @@ if(AARE_TESTS)
             ${CMAKE_CURRENT_SOURCE_DIR}/src/Cluster.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/CalculateEta.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/ClusterFile.test.cpp
+            ${CMAKE_CURRENT_SOURCE_DIR}/src/ClusterFinderMT.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/Pedestal.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/JungfrauDataFile.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/NumpyFile.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/NumpyHelpers.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/RawFile.test.cpp
+            ${CMAKE_CURRENT_SOURCE_DIR}/src/RawSubFile.test.cpp
             ${CMAKE_CURRENT_SOURCE_DIR}/src/utils/task.test.cpp
 
         )

VERSION

@@ -0,0 +1 @@
+2025.5.22

conda-recipe/conda_build_config.yaml

@@ -1,28 +1,5 @@
 python:
     - 3.11
-    - 3.11
-    - 3.11
-    - 3.12
-    - 3.12
     - 3.12
     - 3.13
 
-
-    
-numpy: 
-    - 1.26
-    - 2.0
-    - 2.1
-    - 1.26
-    - 2.0
-    - 2.1
-    - 2.1
-
-
-zip_keys:
-    - python
-    - numpy
-
-pin_run_as_build:
-  numpy: x.x
-  python: x.x

conda-recipe/meta.yaml

@@ -1,10 +1,10 @@
+source:
+  path: ../
+
+{% set version = load_file_regex(load_file = 'VERSION', regex_pattern = '(\d+(?:\.\d+)*(?:[\+\w\.]+))').group(1) %}
 package:
   name: aare
-  version: 2025.4.1 #TODO! how to not duplicate this?
-
-
-
-
+  version: {{version}}
 
 source:
   path: ..
@@ -12,44 +12,39 @@ source:
 build:
   number: 0
   script:
-    - unset CMAKE_GENERATOR && {{ PYTHON }} -m pip install . -vv  # [not win]
-    - {{ PYTHON }} -m pip install . -vv  # [win]
+    - unset CMAKE_GENERATOR && {{ PYTHON }} -m pip install . -vv 
 
 requirements:
   build:
-    - python {{python}}
-    - numpy {{ numpy }}
     - {{ compiler('cxx') }}
-
-
-  host:
     - cmake
     - ninja
-    - python {{python}}
-    - numpy {{ numpy }}
+
+  host:
+    - python
     - pip
+    - numpy=2.1
     - scikit-build-core
     - pybind11 >=2.13.0
-    - fmt
-    - zeromq
-    - nlohmann_json
-    - catch2
+    - matplotlib # needed in host to solve the environment for run
 
   run:
-    - python {{python}}
-    - numpy {{ numpy }}
+    - python
+    - {{ pin_compatible('numpy') }}
+    - matplotlib
+    
 
 
 test:
   imports:
     - aare
-  # requires:
-  #   - pytest
-  # source_files:
-  #   - tests
-  # commands:
-  #   - pytest tests
+  requires:
+    - pytest
+    - boost-histogram 
+  source_files:
+    - python/tests
+  commands:
+    - python -m pytest python/tests
 
 about:
-  summary: An example project built with pybind11 and scikit-build.
-  # license_file: LICENSE
+  summary: Data analysis library for hybrid pixel detectors from PSI 

etc/dev-env.yml

@@ -3,13 +3,11 @@ channels:
   - conda-forge
 dependencies:
   - anaconda-client
+  - conda-build
   - doxygen 
   - sphinx=7.1.2 
   - breathe 
-  - pybind11 
   - sphinx_rtd_theme 
   - furo 
-  - nlohmann_json 
   - zeromq 
-  - fmt 
-  - numpy
+

include/aare/ArrayExpr.hpp

@@ -1,22 +1,24 @@
 #pragma once
-#include <cstdint> //int64_t
-#include <cstddef> //size_t
+#include <cstdint> 
+#include <cstddef> 
 #include <array> 
-
 #include <cassert>
+#include "aare/defs.hpp"
+
+
 namespace aare {
 
-template <typename E, int64_t Ndim> class ArrayExpr {
+template <typename E, ssize_t Ndim> class ArrayExpr {
   public:
     static constexpr bool is_leaf = false;
 
     auto operator[](size_t i) const { return static_cast<E const &>(*this)[i]; }
     auto operator()(size_t i) const { return static_cast<E const &>(*this)[i]; }
     auto size() const { return static_cast<E const &>(*this).size(); }
-    std::array<int64_t, Ndim> shape() const { return static_cast<E const &>(*this).shape(); }
+    std::array<ssize_t, Ndim> shape() const { return static_cast<E const &>(*this).shape(); }
 };
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 class ArrayAdd : public ArrayExpr<ArrayAdd<A, B, Ndim>, Ndim> {
     const A &arr1_;
     const B &arr2_;
@@ -27,10 +29,10 @@ class ArrayAdd : public ArrayExpr<ArrayAdd<A, B, Ndim>, Ndim> {
     }
     auto operator[](int i) const { return arr1_[i] + arr2_[i]; }
     size_t size() const { return arr1_.size(); }
-    std::array<int64_t, Ndim> shape() const { return arr1_.shape(); }
+    std::array<ssize_t, Ndim> shape() const { return arr1_.shape(); }
 };
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 class ArraySub : public ArrayExpr<ArraySub<A, B, Ndim>, Ndim> {
     const A &arr1_;
     const B &arr2_;
@@ -41,10 +43,10 @@ class ArraySub : public ArrayExpr<ArraySub<A, B, Ndim>, Ndim> {
     }
     auto operator[](int i) const { return arr1_[i] - arr2_[i]; }
     size_t size() const { return arr1_.size(); }
-    std::array<int64_t, Ndim> shape() const { return arr1_.shape(); }
+    std::array<ssize_t, Ndim> shape() const { return arr1_.shape(); }
 };
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 class ArrayMul : public ArrayExpr<ArrayMul<A, B, Ndim>,Ndim> {
     const A &arr1_;
     const B &arr2_;
@@ -55,10 +57,10 @@ class ArrayMul : public ArrayExpr<ArrayMul<A, B, Ndim>,Ndim> {
     }
     auto operator[](int i) const { return arr1_[i] * arr2_[i]; }
     size_t size() const { return arr1_.size(); }
-    std::array<int64_t, Ndim> shape() const { return arr1_.shape(); }
+    std::array<ssize_t, Ndim> shape() const { return arr1_.shape(); }
 };
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 class ArrayDiv : public ArrayExpr<ArrayDiv<A, B, Ndim>, Ndim> {
     const A &arr1_;
     const B &arr2_;
@@ -69,27 +71,27 @@ class ArrayDiv : public ArrayExpr<ArrayDiv<A, B, Ndim>, Ndim> {
     }
     auto operator[](int i) const { return arr1_[i] / arr2_[i]; }
     size_t size() const { return arr1_.size(); }
-    std::array<int64_t, Ndim> shape() const { return arr1_.shape(); }
+    std::array<ssize_t, Ndim> shape() const { return arr1_.shape(); }
 };
 
 
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 auto operator+(const ArrayExpr<A, Ndim> &arr1, const ArrayExpr<B, Ndim> &arr2) {
     return ArrayAdd<ArrayExpr<A, Ndim>, ArrayExpr<B, Ndim>, Ndim>(arr1, arr2);
 }
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 auto operator-(const ArrayExpr<A,Ndim> &arr1, const ArrayExpr<B, Ndim> &arr2) {
     return ArraySub<ArrayExpr<A, Ndim>, ArrayExpr<B, Ndim>, Ndim>(arr1, arr2);
 }
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 auto operator*(const ArrayExpr<A, Ndim> &arr1, const ArrayExpr<B, Ndim> &arr2) {
     return ArrayMul<ArrayExpr<A, Ndim>, ArrayExpr<B, Ndim>, Ndim>(arr1, arr2);
 }
 
-template <typename A, typename B, int64_t Ndim>
+template <typename A, typename B, ssize_t Ndim>
 auto operator/(const ArrayExpr<A, Ndim> &arr1, const ArrayExpr<B, Ndim> &arr2) {
     return ArrayDiv<ArrayExpr<A, Ndim>, ArrayExpr<B, Ndim>, Ndim>(arr1, arr2);
 }

include/aare/CalculateEta.hpp

@@ -6,14 +6,14 @@
 
 namespace aare {
 
-typedef enum {
+enum class corner : int {
     cBottomLeft = 0,
     cBottomRight = 1,
     cTopLeft = 2,
     cTopRight = 3
-} corner;
+};
 
-typedef enum {
+enum class pixel : int {
     pBottomLeft = 0,
     pBottom = 1,
     pBottomRight = 2,
@@ -23,7 +23,7 @@ typedef enum {
     pTopLeft = 6,
     pTop = 7,
     pTopRight = 8
-} pixel;
+};
 
 template <typename T> struct Eta2 {
     double x;
@@ -33,7 +33,7 @@ template <typename T> struct Eta2 {
 };
 
 /**
- * @brief Calculate the eta2 values for all clusters in a Clsutervector
+ * @brief Calculate the eta2 values for all clusters in a Clustervector
  */
 template <typename ClusterType,
           typename = std::enable_if_t<is_cluster_v<ClusterType>>>
@@ -41,7 +41,7 @@ NDArray<double, 2> calculate_eta2(const ClusterVector<ClusterType> &clusters) {
     NDArray<double, 2> eta2({static_cast<int64_t>(clusters.size()), 2});
 
     for (size_t i = 0; i < clusters.size(); i++) {
-        auto e = calculate_eta2(clusters.at(i));
+        auto e = calculate_eta2(clusters[i]);
         eta2(i, 0) = e.x;
         eta2(i, 1) = e.y;
     }
@@ -64,31 +64,79 @@ calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
     eta.sum = max_sum.first;
     auto c = max_sum.second;
 
+    size_t cluster_center_index =
+        (ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
+
     size_t index_bottom_left_max_2x2_subcluster =
         (int(c / (ClusterSizeX - 1))) * ClusterSizeX + c % (ClusterSizeX - 1);
 
-    if ((cl.data[index_bottom_left_max_2x2_subcluster] +
-         cl.data[index_bottom_left_max_2x2_subcluster + 1]) != 0)
-        eta.x = static_cast<double>(
-                    cl.data[index_bottom_left_max_2x2_subcluster + 1]) /
-                static_cast<double>(
-                    (cl.data[index_bottom_left_max_2x2_subcluster] +
-                     cl.data[index_bottom_left_max_2x2_subcluster + 1]));
+    // check that cluster center is in max subcluster
+    if (cluster_center_index != index_bottom_left_max_2x2_subcluster &&
+        cluster_center_index != index_bottom_left_max_2x2_subcluster + 1 &&
+        cluster_center_index !=
+            index_bottom_left_max_2x2_subcluster + ClusterSizeX &&
+        cluster_center_index !=
+            index_bottom_left_max_2x2_subcluster + ClusterSizeX + 1)
+        throw std::runtime_error("Photon center is not in max 2x2_subcluster");
 
-    if ((cl.data[index_bottom_left_max_2x2_subcluster] +
-         cl.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX]) != 0)
-        eta.y =
-            static_cast<double>(
-                cl.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX]) /
-            static_cast<double>(
-                (cl.data[index_bottom_left_max_2x2_subcluster] +
-                 cl.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX]));
+    if ((cluster_center_index - index_bottom_left_max_2x2_subcluster) %
+            ClusterSizeX ==
+        0) {
+        if ((cl.data[cluster_center_index + 1] +
+             cl.data[cluster_center_index]) != 0)
+
+            eta.x = static_cast<double>(cl.data[cluster_center_index + 1]) /
+                    static_cast<double>((cl.data[cluster_center_index + 1] +
+                                         cl.data[cluster_center_index]));
+    } else {
+        if ((cl.data[cluster_center_index] +
+             cl.data[cluster_center_index - 1]) != 0)
+
+            eta.x = static_cast<double>(cl.data[cluster_center_index]) /
+                    static_cast<double>((cl.data[cluster_center_index - 1] +
+                                         cl.data[cluster_center_index]));
+    }
+    if ((cluster_center_index - index_bottom_left_max_2x2_subcluster) /
+            ClusterSizeX <
+        1) {
+        assert(cluster_center_index + ClusterSizeX <
+               ClusterSizeX * ClusterSizeY); // suppress warning
+        if ((cl.data[cluster_center_index] +
+             cl.data[cluster_center_index + ClusterSizeX]) != 0)
+            eta.y = static_cast<double>(
+                        cl.data[cluster_center_index + ClusterSizeX]) /
+                    static_cast<double>(
+                        (cl.data[cluster_center_index] +
+                         cl.data[cluster_center_index + ClusterSizeX]));
+    } else {
+        if ((cl.data[cluster_center_index] +
+             cl.data[cluster_center_index - ClusterSizeX]) != 0)
+            eta.y = static_cast<double>(cl.data[cluster_center_index]) /
+                    static_cast<double>(
+                        (cl.data[cluster_center_index] +
+                         cl.data[cluster_center_index - ClusterSizeX]));
+    }
 
     eta.c = c; // TODO only supported for 2x2 and 3x3 clusters -> at least no
                // underyling enum class
     return eta;
 }
 
+// TODO! Look up eta2 calculation - photon center should be top right corner
+template <typename T>
+Eta2<T> calculate_eta2(const Cluster<T, 2, 2, int16_t> &cl) {
+    Eta2<T> eta{};
+
+    if ((cl.data[0] + cl.data[1]) != 0)
+        eta.x = static_cast<double>(cl.data[1]) / (cl.data[0] + cl.data[1]);
+    if ((cl.data[0] + cl.data[2]) != 0)
+        eta.y = static_cast<double>(cl.data[2]) / (cl.data[0] + cl.data[2]);
+    eta.sum = cl.sum();
+    eta.c = static_cast<int>(corner::cBottomLeft); // TODO! This is not correct,
+                                                   // but need to put something
+    return eta;
+}
+
 // calculates Eta3 for 3x3 cluster based on code from analyze_cluster
 // TODO only supported for 3x3 Clusters
 template <typename T> Eta2<T> calculate_eta3(const Cluster<T, 3, 3> &cl) {

include/aare/Cluster.hpp

@@ -16,80 +16,61 @@
 
 namespace aare {
 
-template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-          typename CoordType = int16_t>
-constexpr bool is_valid_cluster =
-    std::is_arithmetic_v<T> && std::is_integral_v<CoordType> &&
-    (ClusterSizeX > 0) && (ClusterSizeY > 0);
-
 // requires clause c++20 maybe update
 template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-          typename CoordType = int16_t,
-          typename Enable = std::enable_if_t<
-              is_valid_cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>>
+          typename CoordType = int16_t>
 struct Cluster {
+
+    static_assert(std::is_arithmetic_v<T>, "T needs to be an arithmetic type");
+    static_assert(std::is_integral_v<CoordType>,
+                  "CoordType needs to be an integral type");
+    static_assert(ClusterSizeX > 0 && ClusterSizeY > 0,
+                  "Cluster sizes must be bigger than zero");
+
     CoordType x;
     CoordType y;
-    T data[ClusterSizeX * ClusterSizeY];
+    std::array<T, ClusterSizeX * ClusterSizeY> data;
 
-    T sum() const {
-        return std::accumulate(data, data + ClusterSizeX * ClusterSizeY, 0);
-    }
+    static constexpr uint8_t cluster_size_x = ClusterSizeX;
+    static constexpr uint8_t cluster_size_y = ClusterSizeY;
+    using value_type = T;
+    using coord_type = CoordType;
+
+    T sum() const { return std::accumulate(data.begin(), data.end(), T{}); }
 
     std::pair<T, int> max_sum_2x2() const {
 
-        constexpr size_t num_2x2_subclusters =
-            (ClusterSizeX - 1) * (ClusterSizeY - 1);
+        if constexpr (cluster_size_x == 3 && cluster_size_y == 3) {
+            std::array<T, 4> sum_2x2_subclusters;
+            sum_2x2_subclusters[0] = data[0] + data[1] + data[3] + data[4];
+            sum_2x2_subclusters[1] = data[1] + data[2] + data[4] + data[5];
+            sum_2x2_subclusters[2] = data[3] + data[4] + data[6] + data[7];
+            sum_2x2_subclusters[3] = data[4] + data[5] + data[7] + data[8];
+            int index = std::max_element(sum_2x2_subclusters.begin(),
+                                         sum_2x2_subclusters.end()) -
+                        sum_2x2_subclusters.begin();
+            return std::make_pair(sum_2x2_subclusters[index], index);
+        } else if constexpr (cluster_size_x == 2 && cluster_size_y == 2) {
+            return std::make_pair(data[0] + data[1] + data[2] + data[3], 0);
+        } else {
+            constexpr size_t num_2x2_subclusters =
+                (ClusterSizeX - 1) * (ClusterSizeY - 1);
 
-        std::array<T, num_2x2_subclusters> sum_2x2_subcluster;
-        for (size_t i = 0; i < ClusterSizeY - 1; ++i) {
-            for (size_t j = 0; j < ClusterSizeX - 1; ++j)
-                sum_2x2_subcluster[i * (ClusterSizeX - 1) + j] =
-                    data[i * ClusterSizeX + j] +
-                    data[i * ClusterSizeX + j + 1] +
-                    data[(i + 1) * ClusterSizeX + j] +
-                    data[(i + 1) * ClusterSizeX + j + 1];
+            std::array<T, num_2x2_subclusters> sum_2x2_subcluster;
+            for (size_t i = 0; i < ClusterSizeY - 1; ++i) {
+                for (size_t j = 0; j < ClusterSizeX - 1; ++j)
+                    sum_2x2_subcluster[i * (ClusterSizeX - 1) + j] =
+                        data[i * ClusterSizeX + j] +
+                        data[i * ClusterSizeX + j + 1] +
+                        data[(i + 1) * ClusterSizeX + j] +
+                        data[(i + 1) * ClusterSizeX + j + 1];
+            }
+
+            int index = std::max_element(sum_2x2_subcluster.begin(),
+                                         sum_2x2_subcluster.end()) -
+                        sum_2x2_subcluster.begin();
+            return std::make_pair(sum_2x2_subcluster[index], index);
         }
-
-        int index = std::max_element(sum_2x2_subcluster.begin(),
-                                     sum_2x2_subcluster.end()) -
-                    sum_2x2_subcluster.begin();
-        return std::make_pair(sum_2x2_subcluster[index], index);
-    }
-};
-
-// Specialization for 2x2 clusters (only one sum exists)
-template <typename T> struct Cluster<T, 2, 2, int16_t> {
-    int16_t x;
-    int16_t y;
-    T data[4];
-
-    T sum() const { return std::accumulate(data, data + 4, 0); }
-
-    std::pair<T, int> max_sum_2x2() const {
-        return std::make_pair(data[0] + data[1] + data[2] + data[3],
-                              0); // Only one possible 2x2 sum
-    }
-};
-
-// Specialization for 3x3 clusters
-template <typename T> struct Cluster<T, 3, 3, int16_t> {
-    int16_t x;
-    int16_t y;
-    T data[9];
-
-    T sum() const { return std::accumulate(data, data + 9, 0); }
-
-    std::pair<T, int> max_sum_2x2() const {
-        std::array<T, 4> sum_2x2_subclusters;
-        sum_2x2_subclusters[0] = data[0] + data[1] + data[3] + data[4];
-        sum_2x2_subclusters[1] = data[1] + data[2] + data[4] + data[5];
-        sum_2x2_subclusters[2] = data[3] + data[4] + data[6] + data[7];
-        sum_2x2_subclusters[3] = data[4] + data[5] + data[7] + data[8];
-        int index = std::max_element(sum_2x2_subclusters.begin(),
-                                     sum_2x2_subclusters.end()) -
-                    sum_2x2_subclusters.begin();
-        return std::make_pair(sum_2x2_subclusters[index], index);
     }
 };
 
@@ -102,20 +83,4 @@ struct is_cluster<Cluster<T, X, Y, CoordType>> : std::true_type {}; // Cluster
 
 template <typename T> constexpr bool is_cluster_v = is_cluster<T>::value;
 
-template <typename ClusterType,
-          typename = std::enable_if_t<is_cluster_v<ClusterType>>>
-struct extract_template_arguments; // Forward declaration
-
-// helper struct to extract template argument
-template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-          typename CoordType>
-struct extract_template_arguments<
-    Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
-
-    using value_type = T;
-    static constexpr int cluster_size_x = ClusterSizeX;
-    static constexpr int cluster_size_y = ClusterSizeY;
-    using coordtype = CoordType;
-};
-
 } // namespace aare

include/aare/ClusterCollector.hpp

@@ -37,7 +37,11 @@ class ClusterCollector {
   public:
     ClusterCollector(ClusterFinderMT<ClusterType, uint16_t, double> *source) {
         m_source = source->sink();
-        m_thread = std::thread(&ClusterCollector::process, this);
+        m_thread =
+            std::thread(&ClusterCollector::process,
+                        this); // only one process does that so why isnt it
+                               // automatically written to m_cluster in collect
+                               // - instead of writing first to m_sink?
     }
     void stop() {
         m_stop_requested = true;

include/aare/ClusterFile.hpp

@@ -39,14 +39,15 @@ template <typename ClusterType,
           typename Enable = std::enable_if_t<is_cluster_v<ClusterType>>>
 class ClusterFile {
     FILE *fp{};
+    const std::string m_filename{};
     uint32_t m_num_left{};    /*Number of photons left in frame*/
     size_t m_chunk_size{};    /*Number of clusters to read at a time*/
-    const std::string m_mode; /*Mode to open the file in*/
+    std::string m_mode;       /*Mode to open the file in*/
     std::optional<ROI> m_roi; /*Region of interest, will be applied if set*/
     std::optional<NDArray<int32_t, 2>>
         m_noise_map; /*Noise map to cut photons, will be applied if set*/
-    std::optional<GainMap> m_gain_map; /*Gain map to apply to the clusters, will
-                                          be applied if set*/
+    std::optional<InvertedGainMap> m_gain_map; /*Gain map to apply to the
+                                          clusters, will be applied if set*/
 
   public:
     /**
@@ -59,26 +60,81 @@ class ClusterFile {
      * @throws std::runtime_error if the file could not be opened
      */
     ClusterFile(const std::filesystem::path &fname, size_t chunk_size = 1000,
-                const std::string &mode = "r");
+                const std::string &mode = "r")
 
-    ~ClusterFile();
+        : m_filename(fname.string()), m_chunk_size(chunk_size), m_mode(mode) {
+
+        if (mode == "r") {
+            fp = fopen(m_filename.c_str(), "rb");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for reading: " +
+                                         m_filename);
+            }
+        } else if (mode == "w") {
+            fp = fopen(m_filename.c_str(), "wb");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for writing: " +
+                                         m_filename);
+            }
+        } else if (mode == "a") {
+            fp = fopen(m_filename.c_str(), "ab");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for appending: " +
+                                         m_filename);
+            }
+        } else {
+            throw std::runtime_error("Unsupported mode: " + mode);
+        }
+    }
+
+    ~ClusterFile() { close(); }
 
     /**
-     * @brief Read n_clusters clusters from the file discarding frame numbers.
-     * If EOF is reached the returned vector will have less than n_clusters
-     * clusters
+     * @brief Read n_clusters clusters from the file discarding
+     * frame numbers. If EOF is reached the returned vector will
+     * have less than n_clusters clusters
      */
-    ClusterVector<ClusterType> read_clusters(size_t n_clusters);
+    ClusterVector<ClusterType> read_clusters(size_t n_clusters) {
+        if (m_mode != "r") {
+            throw std::runtime_error("File not opened for reading");
+        }
+        if (m_noise_map || m_roi) {
+            return read_clusters_with_cut(n_clusters);
+        } else {
+            return read_clusters_without_cut(n_clusters);
+        }
+    }
 
     /**
-     * @brief Read a single frame from the file and return the clusters. The
-     * cluster vector will have the frame number set.
-     * @throws std::runtime_error if the file is not opened for reading or the
-     * file pointer not at the beginning of a frame
+     * @brief Read a single frame from the file and return the
+     * clusters. The cluster vector will have the frame number
+     * set.
+     * @throws std::runtime_error if the file is not opened for
+     * reading or the file pointer not at the beginning of a
+     * frame
      */
-    ClusterVector<ClusterType> read_frame();
+    ClusterVector<ClusterType> read_frame() {
+        if (m_mode != "r") {
+            throw std::runtime_error(LOCATION + "File not opened for reading");
+        }
+        if (m_noise_map || m_roi) {
+            return read_frame_with_cut();
+        } else {
+            return read_frame_without_cut();
+        }
+    }
 
-    void write_frame(const ClusterVector<ClusterType> &clusters);
+    void write_frame(const ClusterVector<ClusterType> &clusters) {
+        if (m_mode != "w" && m_mode != "a") {
+            throw std::runtime_error("File not opened for writing");
+        }
+
+        int32_t frame_number = clusters.frame_number();
+        fwrite(&frame_number, sizeof(frame_number), 1, fp);
+        uint32_t n_clusters = clusters.size();
+        fwrite(&n_clusters, sizeof(n_clusters), 1, fp);
+        fwrite(clusters.data(), clusters.item_size(), clusters.size(), fp);
+    }
 
     /**
      * @brief Return the chunk size
@@ -86,34 +142,84 @@ class ClusterFile {
     size_t chunk_size() const { return m_chunk_size; }
 
     /**
-     * @brief Set the region of interest to use when reading clusters. If set
-     * only clusters within the ROI will be read.
+     * @brief Set the region of interest to use when reading
+     * clusters. If set only clusters within the ROI will be
+     * read.
      */
-    void set_roi(ROI roi);
+    void set_roi(ROI roi) { m_roi = roi; }
 
     /**
-     * @brief Set the noise map to use when reading clusters. If set clusters
-     * below the noise level will be discarded. Selection criteria one of:
-     * Central pixel above noise, highest 2x2 sum above 2 * noise, total sum
-     * above 3 * noise.
+     * @brief Set the noise map to use when reading clusters. If
+     * set clusters below the noise level will be discarded.
+     * Selection criteria one of: Central pixel above noise,
+     * highest 2x2 sum above 2 * noise, total sum above 3 *
+     * noise.
      */
-    void set_noise_map(const NDView<int32_t, 2> noise_map);
+    void set_noise_map(const NDView<int32_t, 2> noise_map) {
+        m_noise_map = NDArray<int32_t, 2>(noise_map);
+    }
 
     /**
      * @brief Set the gain map to use when reading clusters. If set the gain map
      * will be applied to the clusters that pass ROI and noise_map selection.
+     * The gain map is expected to be in ADU/energy.
      */
-    void set_gain_map(const NDView<double, 2> gain_map);
+    void set_gain_map(const NDView<double, 2> gain_map) {
+        m_gain_map = InvertedGainMap(gain_map);
+    }
 
-    void set_gain_map(const GainMap &gain_map);
+    void set_gain_map(const InvertedGainMap &gain_map) {
+        m_gain_map = gain_map;
+    }
 
-    void set_gain_map(const GainMap &&gain_map);
+    void set_gain_map(const InvertedGainMap &&gain_map) {
+        m_gain_map = gain_map;
+    }
 
     /**
-     * @brief Close the file. If not closed the file will be closed in the
-     * destructor
+     * @brief Close the file. If not closed the file will be
+     * closed in the destructor
      */
-    void close();
+    void close() {
+        if (fp) {
+            fclose(fp);
+            fp = nullptr;
+        }
+    }
+
+    /** @brief Open the file in specific mode
+     *
+     */
+    void open(const std::string &mode) {
+        if (fp) {
+            close();
+        }
+
+        if (mode == "r") {
+            fp = fopen(m_filename.c_str(), "rb");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for reading: " +
+                                         m_filename);
+            }
+            m_mode = "r";
+        } else if (mode == "w") {
+            fp = fopen(m_filename.c_str(), "wb");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for writing: " +
+                                         m_filename);
+            }
+            m_mode = "w";
+        } else if (mode == "a") {
+            fp = fopen(m_filename.c_str(), "ab");
+            if (!fp) {
+                throw std::runtime_error("Could not open file for appending: " +
+                                         m_filename);
+            }
+            m_mode = "a";
+        } else {
+            throw std::runtime_error("Unsupported mode: " + mode);
+        }
+    }
 
   private:
     ClusterVector<ClusterType> read_clusters_with_cut(size_t n_clusters);
@@ -124,103 +230,6 @@ class ClusterFile {
     ClusterType read_one_cluster();
 };
 
-template <typename ClusterType, typename Enable>
-ClusterFile<ClusterType, Enable>::ClusterFile(
-    const std::filesystem::path &fname, size_t chunk_size,
-    const std::string &mode)
-    : m_chunk_size(chunk_size), m_mode(mode) {
-
-    if (mode == "r") {
-        fp = fopen(fname.c_str(), "rb");
-        if (!fp) {
-            throw std::runtime_error("Could not open file for reading: " +
-                                     fname.string());
-        }
-    } else if (mode == "w") {
-        fp = fopen(fname.c_str(), "wb");
-        if (!fp) {
-            throw std::runtime_error("Could not open file for writing: " +
-                                     fname.string());
-        }
-    } else if (mode == "a") {
-        fp = fopen(fname.c_str(), "ab");
-        if (!fp) {
-            throw std::runtime_error("Could not open file for appending: " +
-                                     fname.string());
-        }
-    } else {
-        throw std::runtime_error("Unsupported mode: " + mode);
-    }
-}
-
-template <typename ClusterType, typename Enable>
-ClusterFile<ClusterType, Enable>::~ClusterFile() {
-    close();
-}
-
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::close() {
-    if (fp) {
-        fclose(fp);
-        fp = nullptr;
-    }
-}
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::set_roi(ROI roi) {
-    m_roi = roi;
-}
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::set_noise_map(
-    const NDView<int32_t, 2> noise_map) {
-    m_noise_map = NDArray<int32_t, 2>(noise_map);
-}
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::set_gain_map(
-    const NDView<double, 2> gain_map) {
-    m_gain_map = GainMap(gain_map);
-}
-
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::set_gain_map(const GainMap &gain_map) {
-    m_gain_map = gain_map;
-}
-
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::set_gain_map(const GainMap &&gain_map) {
-    m_gain_map = gain_map;
-}
-
-// TODO generally supported for all clsuter types
-template <typename ClusterType, typename Enable>
-void ClusterFile<ClusterType, Enable>::write_frame(
-    const ClusterVector<ClusterType> &clusters) {
-    if (m_mode != "w" && m_mode != "a") {
-        throw std::runtime_error("File not opened for writing");
-    }
-    if (!(clusters.cluster_size_x() == 3) &&
-        !(clusters.cluster_size_y() == 3)) {
-        throw std::runtime_error("Only 3x3 clusters are supported");
-    }
-    int32_t frame_number = clusters.frame_number();
-    fwrite(&frame_number, sizeof(frame_number), 1, fp);
-    uint32_t n_clusters = clusters.size();
-    fwrite(&n_clusters, sizeof(n_clusters), 1, fp);
-    fwrite(clusters.data(), clusters.item_size(), clusters.size(), fp);
-}
-
-template <typename ClusterType, typename Enable>
-ClusterVector<ClusterType>
-ClusterFile<ClusterType, Enable>::read_clusters(size_t n_clusters) {
-    if (m_mode != "r") {
-        throw std::runtime_error("File not opened for reading");
-    }
-    if (m_noise_map || m_roi) {
-        return read_clusters_with_cut(n_clusters);
-    } else {
-        return read_clusters_without_cut(n_clusters);
-    }
-}
-
 template <typename ClusterType, typename Enable>
 ClusterVector<ClusterType>
 ClusterFile<ClusterType, Enable>::read_clusters_without_cut(size_t n_clusters) {
@@ -240,8 +249,8 @@ ClusterFile<ClusterType, Enable>::read_clusters_without_cut(size_t n_clusters) {
     // if there are photons left from previous frame read them first
     if (nph) {
         if (nph > n_clusters) {
-            // if we have more photons left in the frame then photons to read we
-            // read directly the requested number
+            // if we have more photons left in the frame then photons to
+            // read we read directly the requested number
             nn = n_clusters;
         } else {
             nn = nph;
@@ -270,7 +279,7 @@ ClusterFile<ClusterType, Enable>::read_clusters_without_cut(size_t n_clusters) {
         }
     }
 
-    // Resize the vector to the number of clusters.
+    // Resize the vector to the number o f clusters.
     // No new allocation, only change bounds.
     clusters.resize(nph_read);
     if (m_gain_map)
@@ -282,7 +291,7 @@ template <typename ClusterType, typename Enable>
 ClusterVector<ClusterType>
 ClusterFile<ClusterType, Enable>::read_clusters_with_cut(size_t n_clusters) {
     ClusterVector<ClusterType> clusters;
-    clusters.resize(n_clusters);
+    clusters.reserve(n_clusters);
 
     // if there are photons left from previous frame read them first
     if (m_num_left) {
@@ -307,8 +316,8 @@ ClusterFile<ClusterType, Enable>::read_clusters_with_cut(size_t n_clusters) {
         while (fread(&frame_number, sizeof(frame_number), 1, fp)) {
             if (fread(&m_num_left, sizeof(m_num_left), 1, fp)) {
                 clusters.set_frame_number(
-                    frame_number); // cluster vector will hold the last frame
-                                   // number
+                    frame_number); // cluster vector will hold the last
+                                   // frame number
                 while (m_num_left && clusters.size() < n_clusters) {
                     ClusterType c = read_one_cluster();
                     if (is_selected(c)) {
@@ -339,18 +348,6 @@ ClusterType ClusterFile<ClusterType, Enable>::read_one_cluster() {
     return c;
 }
 
-template <typename ClusterType, typename Enable>
-ClusterVector<ClusterType> ClusterFile<ClusterType, Enable>::read_frame() {
-    if (m_mode != "r") {
-        throw std::runtime_error(LOCATION + "File not opened for reading");
-    }
-    if (m_noise_map || m_roi) {
-        return read_frame_with_cut();
-    } else {
-        return read_frame_without_cut();
-    }
-}
-
 template <typename ClusterType, typename Enable>
 ClusterVector<ClusterType>
 ClusterFile<ClusterType, Enable>::read_frame_without_cut() {
@@ -375,11 +372,13 @@ ClusterFile<ClusterType, Enable>::read_frame_without_cut() {
     ClusterVector<ClusterType> clusters(n_clusters);
     clusters.set_frame_number(frame_number);
 
+    clusters.resize(n_clusters);
+
     if (fread(clusters.data(), clusters.item_size(), n_clusters, fp) !=
         static_cast<size_t>(n_clusters)) {
         throw std::runtime_error(LOCATION + "Could not read clusters");
     }
-    clusters.resize(n_clusters);
+
     if (m_gain_map)
         m_gain_map->apply_gain_map(clusters);
     return clusters;
@@ -427,13 +426,9 @@ bool ClusterFile<ClusterType, Enable>::is_selected(ClusterType &cl) {
         }
     }
 
-    auto cluster_size_x = extract_template_arguments<
-        std::remove_reference_t<decltype(cl)>>::cluster_size_x;
-    auto cluster_size_y = extract_template_arguments<
-        std::remove_reference_t<decltype(cl)>>::cluster_size_y;
-
     size_t cluster_center_index =
-        (cluster_size_x / 2) + (cluster_size_y / 2) * cluster_size_x;
+        (ClusterType::cluster_size_x / 2) +
+        (ClusterType::cluster_size_y / 2) * ClusterType::cluster_size_x;
 
     if (m_noise_map) {
         auto sum_1x1 = cl.data[cluster_center_index]; // central pixel

include/aare/ClusterFileV2.hpp

@@ -1,154 +0,0 @@
-#pragma once
-#include "aare/core/defs.hpp"
-#include <filesystem>
-#include <fmt/format.h>
-#include <string>
-
-namespace aare {
-struct ClusterHeader {
-    int32_t frame_number;
-    int32_t n_clusters;
-    std::string to_string() const {
-        return "frame_number: " + std::to_string(frame_number) +
-               ", n_clusters: " + std::to_string(n_clusters);
-    }
-};
-
-struct ClusterV2_ {
-    int16_t x;
-    int16_t y;
-    std::array<int32_t, 9> data;
-    std::string to_string(bool detailed = false) const {
-        if (detailed) {
-            std::string data_str = "[";
-            for (auto &d : data) {
-                data_str += std::to_string(d) + ", ";
-            }
-            data_str += "]";
-            return "x: " + std::to_string(x) + ", y: " + std::to_string(y) +
-                   ", data: " + data_str;
-        }
-        return "x: " + std::to_string(x) + ", y: " + std::to_string(y);
-    }
-};
-
-struct ClusterV2 {
-    ClusterV2_ cluster;
-    int32_t frame_number;
-    std::string to_string() const {
-        return "frame_number: " + std::to_string(frame_number) + ", " +
-               cluster.to_string();
-    }
-};
-
-/**
- * @brief
- * important not: fp always points to the clusters header and does not point to
- * individual clusters
- *
- */
-class ClusterFileV2 {
-    std::filesystem::path m_fpath;
-    std::string m_mode;
-    FILE *fp{nullptr};
-
-    void check_open() {
-        if (!fp)
-            throw std::runtime_error(
-                fmt::format("File: {} not open", m_fpath.string()));
-    }
-
-  public:
-    ClusterFileV2(std::filesystem::path const &fpath, std::string const &mode)
-        : m_fpath(fpath), m_mode(mode) {
-        if (m_mode != "r" && m_mode != "w")
-            throw std::invalid_argument("mode must be 'r' or 'w'");
-        if (m_mode == "r" && !std::filesystem::exists(m_fpath))
-            throw std::invalid_argument("File does not exist");
-        if (mode == "r") {
-            fp = fopen(fpath.string().c_str(), "rb");
-        } else if (mode == "w") {
-            if (std::filesystem::exists(fpath)) {
-                fp = fopen(fpath.string().c_str(), "r+b");
-            } else {
-                fp = fopen(fpath.string().c_str(), "wb");
-            }
-        }
-        if (fp == nullptr) {
-            throw std::runtime_error("Failed to open file");
-        }
-    }
-    ~ClusterFileV2() { close(); }
-    std::vector<ClusterV2> read() {
-        check_open();
-
-        ClusterHeader header;
-        fread(&header, sizeof(ClusterHeader), 1, fp);
-        std::vector<ClusterV2_> clusters_(header.n_clusters);
-        fread(clusters_.data(), sizeof(ClusterV2_), header.n_clusters, fp);
-        std::vector<ClusterV2> clusters;
-        for (auto &c : clusters_) {
-            ClusterV2 cluster;
-            cluster.cluster = std::move(c);
-            cluster.frame_number = header.frame_number;
-            clusters.push_back(cluster);
-        }
-
-        return clusters;
-    }
-    std::vector<std::vector<ClusterV2>> read(int n_frames) {
-        std::vector<std::vector<ClusterV2>> clusters;
-        for (int i = 0; i < n_frames; i++) {
-            clusters.push_back(read());
-        }
-        return clusters;
-    }
-
-    size_t write(std::vector<ClusterV2> const &clusters) {
-        check_open();
-        if (m_mode != "w")
-            throw std::runtime_error("File not opened in write mode");
-        if (clusters.empty())
-            return 0;
-
-        ClusterHeader header;
-        header.frame_number = clusters[0].frame_number;
-        header.n_clusters = clusters.size();
-        fwrite(&header, sizeof(ClusterHeader), 1, fp);
-        for (auto &c : clusters) {
-            fwrite(&c.cluster, sizeof(ClusterV2_), 1, fp);
-        }
-        return clusters.size();
-    }
-
-    size_t write(std::vector<std::vector<ClusterV2>> const &clusters) {
-        check_open();
-        if (m_mode != "w")
-            throw std::runtime_error("File not opened in write mode");
-
-        size_t n_clusters = 0;
-        for (auto &c : clusters) {
-            n_clusters += write(c);
-        }
-        return n_clusters;
-    }
-
-    int seek_to_begin() { return fseek(fp, 0, SEEK_SET); }
-    int seek_to_end() { return fseek(fp, 0, SEEK_END); }
-
-    int32_t frame_number() {
-        auto pos = ftell(fp);
-        ClusterHeader header;
-        fread(&header, sizeof(ClusterHeader), 1, fp);
-        fseek(fp, pos, SEEK_SET);
-        return header.frame_number;
-    }
-
-    void close() {
-        if (fp) {
-            fclose(fp);
-            fp = nullptr;
-        }
-    }
-};
-} // namespace aare

include/aare/ClusterFinder.hpp

@@ -20,11 +20,9 @@ class ClusterFinder {
     Pedestal<PEDESTAL_TYPE> m_pedestal;
     ClusterVector<ClusterType> m_clusters;
 
-    static const uint8_t ClusterSizeX =
-        extract_template_arguments<ClusterType>::cluster_size_x;
-    static const uint8_t ClusterSizeY =
-        extract_template_arguments<ClusterType>::cluster_size_x;
-    using CT = typename extract_template_arguments<ClusterType>::value_type;
+    static const uint8_t ClusterSizeX = ClusterType::cluster_size_x;
+    static const uint8_t ClusterSizeY = ClusterType::cluster_size_y;
+    using CT = typename ClusterType::value_type;
 
   public:
     /**
@@ -79,7 +77,6 @@ class ClusterFinder {
         int has_center_pixel_y = ClusterSizeY % 2;
 
         m_clusters.set_frame_number(frame_number);
-        std::vector<CT> cluster_data(ClusterSizeX * ClusterSizeY);
         for (int iy = 0; iy < frame.shape(0); iy++) {
             for (int ix = 0; ix < frame.shape(1); ix++) {
 
@@ -126,8 +123,9 @@ class ClusterFinder {
 
                 // Store cluster
                 if (value == max) {
-                    // Zero out the cluster data
-                    std::fill(cluster_data.begin(), cluster_data.end(), 0);
+                    ClusterType cluster{};
+                    cluster.x = ix;
+                    cluster.y = iy;
 
                     // Fill the cluster data since we have a photon to store
                     // It's worth redoing the look since most of the time we
@@ -141,20 +139,15 @@ class ClusterFinder {
                                     static_cast<CT>(frame(iy + ir, ix + ic)) -
                                     static_cast<CT>(
                                         m_pedestal.mean(iy + ir, ix + ic));
-                                cluster_data[i] =
+                                cluster.data[i] =
                                     tmp; // Watch for out of bounds access
                                 i++;
                             }
                         }
                     }
 
-                    ClusterType new_cluster{};
-                    new_cluster.x = ix;
-                    new_cluster.y = iy;
-                    std::copy(cluster_data.begin(), cluster_data.end(),
-                              new_cluster.data);
                     // Add the cluster to the output ClusterVector
-                    m_clusters.push_back(new_cluster);
+                    m_clusters.push_back(cluster);
                 }
             }
         }

include/aare/ClusterFinderMT.hpp

@@ -34,7 +34,8 @@ template <typename ClusterType = Cluster<int32_t, 3, 3>,
           typename FRAME_TYPE = uint16_t, typename PEDESTAL_TYPE = double>
 class ClusterFinderMT {
 
-    using CT = typename extract_template_arguments<ClusterType>::value_type;
+  protected:
+    using CT = typename ClusterType::value_type;
     size_t m_current_thread{0};
     size_t m_n_threads{0};
     using Finder = ClusterFinder<ClusterType, FRAME_TYPE, PEDESTAL_TYPE>;
@@ -50,6 +51,7 @@ class ClusterFinderMT {
     std::thread m_collect_thread;
     std::chrono::milliseconds m_default_wait{1};
 
+  private:
     std::atomic<bool> m_stop_requested{false};
     std::atomic<bool> m_processing_threads_stopped{true};
 
@@ -120,6 +122,7 @@ class ClusterFinderMT {
     ClusterFinderMT(Shape<2> image_size, PEDESTAL_TYPE nSigma = 5.0,
                     size_t capacity = 2000, size_t n_threads = 3)
         : m_n_threads(n_threads) {
+
         for (size_t i = 0; i < n_threads; i++) {
             m_cluster_finders.push_back(
                 std::make_unique<

include/aare/ClusterVector.hpp

@@ -18,256 +18,6 @@ template <typename ClusterType,
           typename = std::enable_if_t<is_cluster_v<ClusterType>>>
 class ClusterVector; // Forward declaration
 
-/**
- * @brief ClusterVector is a container for clusters of various sizes. It uses a
- * contiguous memory buffer to store the clusters. It is templated on the data
- * type and the coordinate type of the clusters.
- * @note push_back can invalidate pointers to elements in the container
- * @warning ClusterVector is currently move only to catch unintended copies, but
- * this might change since there are probably use cases where copying is needed.
- * @tparam T data type of the pixels in the cluster
- * @tparam CoordType data type of the x and y coordinates of the cluster
- * (normally int16_t)
- */
-#if 0
-template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-          typename CoordType>
-class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
-
-    std::byte *m_data{};
-    size_t m_size{0};
-    size_t m_capacity;
-    uint64_t m_frame_number{0}; // TODO! Check frame number size and type
-    /** 
-    Format string used in the python bindings to create a numpy
-    array from the buffer
-    = - native byte order
-    h - short
-    d - double
-    i - int
-    */
-    constexpr static char m_fmt_base[] = "=h:x:\nh:y:\n({},{}){}:data:";
-
-  public:
-    using value_type = T;
-    using ClusterType = Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>;
-
-    /**
-     * @brief Construct a new ClusterVector object
-     * @param capacity initial capacity of the buffer in number of clusters
-     * @param frame_number frame number of the clusters. Default is 0, which is
-     * also used to indicate that the clusters come from many frames
-     */
-    ClusterVector(size_t capacity = 1024, uint64_t frame_number = 0)
-        : m_capacity(capacity), m_frame_number(frame_number) {
-        allocate_buffer(m_capacity);
-    }
-
-    ~ClusterVector() { delete[] m_data; }
-
-    // Move constructor
-    ClusterVector(ClusterVector &&other) noexcept
-        : m_data(other.m_data), m_size(other.m_size),
-          m_capacity(other.m_capacity), m_frame_number(other.m_frame_number) {
-        other.m_data = nullptr;
-        other.m_size = 0;
-        other.m_capacity = 0;
-    }
-
-    // Move assignment operator
-    ClusterVector &operator=(ClusterVector &&other) noexcept {
-        if (this != &other) {
-            delete[] m_data;
-            m_data = other.m_data;
-            m_size = other.m_size;
-            m_capacity = other.m_capacity;
-            m_frame_number = other.m_frame_number;
-            other.m_data = nullptr;
-            other.m_size = 0;
-            other.m_capacity = 0;
-            other.m_frame_number = 0;
-        }
-        return *this;
-    }
-
-    /**
-     * @brief Reserve space for at least capacity clusters
-     * @param capacity number of clusters to reserve space for
-     * @note If capacity is less than the current capacity, the function does
-     * nothing.
-     */
-    void reserve(size_t capacity) {
-        if (capacity > m_capacity) {
-            allocate_buffer(capacity);
-        }
-    }
-
-    /**
-     * @brief Add a cluster to the vector
-     */
-    void push_back(const ClusterType &cluster) {
-        if (m_size == m_capacity) {
-            allocate_buffer(m_capacity * 2);
-        }
-        std::byte *ptr = element_ptr(m_size);
-        *reinterpret_cast<CoordType *>(ptr) = cluster.x;
-        ptr += sizeof(CoordType);
-        *reinterpret_cast<CoordType *>(ptr) = cluster.y;
-        ptr += sizeof(CoordType);
-
-        std::memcpy(ptr, cluster.data, ClusterSizeX * ClusterSizeY * sizeof(T));
-
-        m_size++;
-    }
-
-    ClusterVector &operator+=(const ClusterVector &other) {
-        if (m_size + other.m_size > m_capacity) {
-            allocate_buffer(m_capacity + other.m_size);
-        }
-        std::copy(other.m_data, other.m_data + other.m_size * item_size(),
-                  m_data + m_size * item_size());
-        m_size += other.m_size;
-        return *this;
-    }
-
-    /**
-     * @brief Sum the pixels in each cluster
-     * @return std::vector<T> vector of sums for each cluster
-     */
-    /*
-    std::vector<T> sum() {
-        std::vector<T> sums(m_size);
-        const size_t stride = item_size();
-        const size_t n_pixels = ClusterSizeX * ClusterSizeY;
-        std::byte *ptr = m_data + 2 * sizeof(CoordType); // skip x and y
-
-        for (size_t i = 0; i < m_size; i++) {
-            sums[i] =
-                std::accumulate(reinterpret_cast<T *>(ptr),
-                                reinterpret_cast<T *>(ptr) + n_pixels, T{});
-            ptr += stride;
-        }
-        return sums;
-    }
-    */
-
-    /**
-     * @brief Sum the pixels in the 2x2 subcluster with the biggest pixel sum in
-     * each cluster
-     * @return std::vector<T> vector of sums for each cluster
-     */ //TODO if underlying container is a vector use std::for_each
-    /*
-    std::vector<T> sum_2x2() {
-        std::vector<T> sums_2x2(m_size);
-
-        for (size_t i = 0; i < m_size; i++) {
-            sums_2x2[i] = at(i).max_sum_2x2;
-        }
-        return sums_2x2;
-    }
-    */
-
-    /**
-     * @brief Return the number of clusters in the vector
-     */
-    size_t size() const { return m_size; }
-
-    uint8_t cluster_size_x() const { return ClusterSizeX; }
-
-    uint8_t cluster_size_y() const { return ClusterSizeY; }
-
-    /**
-     * @brief Return the capacity of the buffer in number of clusters. This is
-     * the number of clusters that can be stored in the current buffer without
-     * reallocation.
-     */
-    size_t capacity() const { return m_capacity; }
-
-    /**
-     * @brief Return the size in bytes of a single cluster
-     */
-    size_t item_size() const {
-        return 2 * sizeof(CoordType) + ClusterSizeX * ClusterSizeY * sizeof(T);
-    }
-
-    /**
-     * @brief Return the offset in bytes for the i-th cluster
-     */
-    size_t element_offset(size_t i) const { return item_size() * i; }
-
-    /**
-     * @brief Return a pointer to the i-th cluster
-     */
-    std::byte *element_ptr(size_t i) { return m_data + element_offset(i); }
-
-    /**
-     * @brief Return a pointer to the i-th cluster
-     */
-    const std::byte *element_ptr(size_t i) const {
-        return m_data + element_offset(i);
-    }
-
-    std::byte *data() { return m_data; }
-    std::byte const *data() const { return m_data; }
-
-    /**
-     * @brief Return a reference to the i-th cluster casted to type V
-     * @tparam V type of the cluster
-     */
-    ClusterType &at(size_t i) {
-        return *reinterpret_cast<ClusterType *>(element_ptr(i));
-    }
-
-    const ClusterType &at(size_t i) const {
-        return *reinterpret_cast<const ClusterType *>(element_ptr(i));
-    }
-
-    template <typename V> const V &at(size_t i) const {
-        return *reinterpret_cast<const V *>(element_ptr(i));
-    }
-
-    const std::string_view fmt_base() const {
-        // TODO! how do we match on coord_t?
-        return m_fmt_base;
-    }
-
-    /** 
-     * @brief Return the frame number of the clusters. 0 is used to indicate
-     * that the clusters come from many frames
-     */
-    uint64_t frame_number() const { return m_frame_number; }
-
-    void set_frame_number(uint64_t frame_number) {
-        m_frame_number = frame_number;
-    }
-
-    /** 
-     * @brief Resize the vector to contain new_size clusters. If new_size is
-     * greater than the current capacity, a new buffer is allocated. If the size
-     * is smaller no memory is freed, size is just updated.
-     * @param new_size new size of the vector
-     * @warning The additional clusters are not initialized
-     */
-    void resize(size_t new_size) {
-        // TODO! Should we initialize the new clusters?
-        if (new_size > m_capacity) {
-            allocate_buffer(new_size);
-        }
-        m_size = new_size;
-    }
-
-  private:
-    void allocate_buffer(size_t new_capacity) {
-        size_t num_bytes = item_size() * new_capacity;
-        std::byte *new_data = new std::byte[num_bytes]{};
-        std::copy(m_data, m_data + item_size() * m_size, new_data);
-        delete[] m_data;
-        m_data = new_data;
-        m_capacity = new_capacity;
-    }
-};
-#endif
-
 /**
  * @brief ClusterVector is a container for clusters of various sizes. It
  * uses a contiguous memory buffer to store the clusters. It is templated on
@@ -285,7 +35,7 @@ template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
 class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
 
     std::vector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> m_data{};
-    uint64_t m_frame_number{0}; // TODO! Check frame number size and type
+    int32_t m_frame_number{0}; // TODO! Check frame number size and type
 
   public:
     using value_type = T;
@@ -297,7 +47,7 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
      * @param frame_number frame number of the clusters. Default is 0, which is
      * also used to indicate that the clusters come from many frames
      */
-    ClusterVector(size_t capacity = 300, int32_t frame_number = 0)
+    ClusterVector(size_t capacity = 1024, uint64_t frame_number = 0)
         : m_frame_number(frame_number) {
         m_data.reserve(capacity);
     }
@@ -319,6 +69,36 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
         return *this;
     }
 
+    /**
+     * @brief Sum the pixels in each cluster
+     * @return std::vector<T> vector of sums for each cluster
+     */
+    std::vector<T> sum() {
+        std::vector<T> sums(m_data.size());
+
+        std::transform(
+            m_data.begin(), m_data.end(), sums.begin(),
+            [](const ClusterType &cluster) { return cluster.sum(); });
+
+        return sums;
+    }
+
+    /**
+     * @brief Sum the pixels in the 2x2 subcluster with the biggest pixel sum in
+     * each cluster
+     * @return std::vector<T> vector of sums for each cluster
+     */
+    std::vector<T> sum_2x2() {
+        std::vector<T> sums_2x2(m_data.size());
+
+        std::transform(m_data.begin(), m_data.end(), sums_2x2.begin(),
+                       [](const ClusterType &cluster) {
+                           return cluster.max_sum_2x2().first;
+                       });
+
+        return sums_2x2;
+    }
+
     /**
      * @brief Reserve space for at least capacity clusters
      * @param capacity number of clusters to reserve space for
@@ -353,15 +133,16 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
      */
     size_t capacity() const { return m_data.capacity(); }
 
-    const auto begin() const { return m_data.begin(); }
+    auto begin() const { return m_data.begin(); }
 
-    const auto end() const { return m_data.end(); }
+    auto end() const { return m_data.end(); }
 
     /**
      * @brief Return the size in bytes of a single cluster
      */
     size_t item_size() const {
-        return 2 * sizeof(CoordType) + ClusterSizeX * ClusterSizeY * sizeof(T);
+        return sizeof(ClusterType); // 2 * sizeof(CoordType) + ClusterSizeX *
+                                    // ClusterSizeY * sizeof(T);
     }
 
     ClusterType *data() { return m_data.data(); }
@@ -371,17 +152,17 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
      * @brief Return a reference to the i-th cluster casted to type V
      * @tparam V type of the cluster
      */
-    ClusterType &at(size_t i) { return m_data[i]; }
+    ClusterType &operator[](size_t i) { return m_data[i]; }
 
-    const ClusterType &at(size_t i) const { return m_data[i]; }
+    const ClusterType &operator[](size_t i) const { return m_data[i]; }
 
     /**
      * @brief Return the frame number of the clusters. 0 is used to indicate
      * that the clusters come from many frames
      */
-    uint64_t frame_number() const { return m_frame_number; }
+    int32_t frame_number() const { return m_frame_number; }
 
-    void set_frame_number(uint64_t frame_number) {
+    void set_frame_number(int32_t frame_number) {
         m_frame_number = frame_number;
     }
 };

include/aare/FilePtr.hpp

@@ -18,8 +18,8 @@ class FilePtr {
     FilePtr(FilePtr &&other);
     FilePtr &operator=(FilePtr &&other);
     FILE *get();
-    int64_t tell();
-    void seek(int64_t offset, int whence = SEEK_SET) {
+    ssize_t tell();
+    void seek(ssize_t offset, int whence = SEEK_SET) {
         if (fseek(fp_, offset, whence) != 0)
             throw std::runtime_error("Error seeking in file");
     }

include/aare/Fit.hpp

@@ -15,6 +15,12 @@ NDArray<double, 1> gaus(NDView<double, 1> x, NDView<double, 1> par);
 double pol1(const double x, const double *par);
 NDArray<double, 1> pol1(NDView<double, 1> x, NDView<double, 1> par);
 
+double scurve(const double x, const double *par);
+NDArray<double, 1> scurve(NDView<double, 1> x, NDView<double, 1> par);
+
+double scurve2(const double x, const double *par);
+NDArray<double, 1> scurve2(NDView<double, 1> x, NDView<double, 1> par);
+
 } // namespace func
 
 
@@ -25,6 +31,9 @@ std::array<double, 3> gaus_init_par(const NDView<double, 1> x, const NDView<doub
 
 std::array<double, 2> pol1_init_par(const NDView<double, 1> x, const NDView<double, 1> y);
 
+std::array<double, 6> scurve_init_par(const NDView<double, 1> x, const NDView<double, 1> y); 
+std::array<double, 6> scurve2_init_par(const NDView<double, 1> x, const NDView<double, 1> y);
+
 static constexpr int DEFAULT_NUM_THREADS = 4;
 
 /**
@@ -38,7 +47,7 @@ NDArray<double, 1> fit_gaus(NDView<double, 1> x, NDView<double, 1> y);
 /**
  * @brief Fit a 1D Gaussian to each pixel. Data layout [row, col, values]
  * @param x x values
- * @param y y vales, layout [row, col, values]
+ * @param y y values, layout [row, col, values]
  * @param n_threads number of threads to use
  */
 
@@ -51,7 +60,7 @@ NDArray<double, 3> fit_gaus(NDView<double, 1> x, NDView<double, 3> y,
 /**
  * @brief Fit a 1D Gaussian with error estimates
  * @param x x values
- * @param y y vales, layout [row, col, values]
+ * @param y y values, layout [row, col, values]
  * @param y_err error in y, layout [row, col, values]
  * @param par_out output parameters
  * @param par_err_out output error parameters
@@ -64,7 +73,7 @@ void fit_gaus(NDView<double, 1> x, NDView<double, 1> y, NDView<double, 1> y_err,
  * @brief Fit a 1D Gaussian to each pixel with error estimates. Data layout
  * [row, col, values]
  * @param x x values
- * @param y y vales, layout [row, col, values]
+ * @param y y values, layout [row, col, values]
  * @param y_err error in y, layout [row, col, values]
  * @param par_out output parameters, layout [row, col, values]
  * @param par_err_out output parameter errors, layout [row, col, values]
@@ -88,5 +97,19 @@ void fit_pol1(NDView<double, 1> x, NDView<double, 3> y, NDView<double, 3> y_err,
               NDView<double, 3> par_out, NDView<double, 3> par_err_out,NDView<double, 2> chi2_out,
               int n_threads = DEFAULT_NUM_THREADS);
 
+NDArray<double, 1> fit_scurve(NDView<double, 1> x, NDView<double, 1> y); 
+NDArray<double, 3> fit_scurve(NDView<double, 1> x, NDView<double, 3> y, int n_threads); 
+void fit_scurve(NDView<double, 1> x, NDView<double, 1> y, NDView<double, 1> y_err,
+              NDView<double, 1> par_out, NDView<double, 1> par_err_out, double& chi2); 
+void fit_scurve(NDView<double, 1> x, NDView<double, 3> y, NDView<double, 3> y_err,
+              NDView<double, 3> par_out, NDView<double, 3> par_err_out, NDView<double, 2> chi2_out,
+              int n_threads); 
 
+NDArray<double, 1> fit_scurve2(NDView<double, 1> x, NDView<double, 1> y); 
+NDArray<double, 3> fit_scurve2(NDView<double, 1> x, NDView<double, 3> y, int n_threads); 
+void fit_scurve2(NDView<double, 1> x, NDView<double, 1> y, NDView<double, 1> y_err,
+              NDView<double, 1> par_out, NDView<double, 1> par_err_out, double& chi2); 
+void fit_scurve2(NDView<double, 1> x, NDView<double, 3> y, NDView<double, 3> y_err,
+              NDView<double, 3> par_out, NDView<double, 3> par_err_out, NDView<double, 2> chi2_out,
+              int n_threads); 
 } // namespace aare

include/aare/Frame.hpp

@@ -107,8 +107,8 @@ class Frame {
      * @return NDView<T, 2> 
      */
     template <typename T> NDView<T, 2> view() {
-        std::array<int64_t, 2> shape = {static_cast<int64_t>(m_rows),
-                                        static_cast<int64_t>(m_cols)};
+        std::array<ssize_t, 2> shape = {static_cast<ssize_t>(m_rows),
+                                        static_cast<ssize_t>(m_cols)};
         T *data = reinterpret_cast<T *>(m_data);
         return NDView<T, 2>(data, shape);
     }

include/aare/GainMap.hpp

@@ -1,6 +1,7 @@
 /************************************************
- * @file ApplyGainMap.hpp
- * @short function to apply gain map of image size to a vector of clusters
+ * @file GainMap.hpp
+ * @short function to apply gain map of image size to a vector of clusters -
+ *note stored gainmap is inverted for efficient aaplication to images
  ***********************************************/
 
 #pragma once
@@ -12,14 +13,21 @@
 
 namespace aare {
 
-class GainMap {
+class InvertedGainMap {
 
   public:
-    explicit GainMap(const NDArray<double, 2> &gain_map)
-        : m_gain_map(gain_map) {};
+    explicit InvertedGainMap(const NDArray<double, 2> &gain_map)
+        : m_gain_map(gain_map) {
+        for (auto &item : m_gain_map) {
+            item = 1.0 / item;
+        }
+    };
 
-    explicit GainMap(const NDView<double, 2> gain_map) {
+    explicit InvertedGainMap(const NDView<double, 2> gain_map) {
         m_gain_map = NDArray<double, 2>(gain_map);
+        for (auto &item : m_gain_map) {
+            item = 1.0 / item;
+        }
     }
 
     template <typename ClusterType,
@@ -34,19 +42,21 @@ class GainMap {
         int64_t index_cluster_center_x = ClusterSizeX / 2;
         int64_t index_cluster_center_y = ClusterSizeY / 2;
         for (size_t i = 0; i < clustervec.size(); i++) {
-            auto &cl = clustervec.at(i);
+            auto &cl = clustervec[i];
 
             if (cl.x > 0 && cl.y > 0 && cl.x < m_gain_map.shape(1) - 1 &&
                 cl.y < m_gain_map.shape(0) - 1) {
                 for (size_t j = 0; j < ClusterSizeX * ClusterSizeY; j++) {
                     size_t x = cl.x + j % ClusterSizeX - index_cluster_center_x;
                     size_t y = cl.y + j / ClusterSizeX - index_cluster_center_y;
-                    cl.data[j] = cl.data[j] * static_cast<T>(m_gain_map(y, x));
+                    cl.data[j] = static_cast<T>(
+                        static_cast<double>(cl.data[j]) *
+                        m_gain_map(
+                            y, x)); // cast after conversion to keep precision
                 }
             } else {
-                memset(cl.data, 0,
-                       ClusterSizeX * ClusterSizeY *
-                           sizeof(T)); // clear edge clusters
+                // clear edge clusters
+                cl.data.fill(0);
             }
         }
     }

include/aare/Interpolator.hpp

@@ -44,15 +44,14 @@ Interpolator::interpolate(const ClusterVector<ClusterType> &clusters) {
     photons.reserve(clusters.size());
 
     if (clusters.cluster_size_x() == 3 || clusters.cluster_size_y() == 3) {
-        for (size_t i = 0; i < clusters.size(); i++) {
+        for (const ClusterType &cluster : clusters) {
 
-            auto cluster = clusters.at(i);
             auto eta = calculate_eta2(cluster);
 
             Photon photon;
             photon.x = cluster.x;
             photon.y = cluster.y;
-            photon.energy = eta.sum;
+            photon.energy = static_cast<decltype(photon.energy)>(eta.sum);
 
             // auto ie = nearest_index(m_energy_bins, photon.energy)-1;
             // auto ix = nearest_index(m_etabinsx, eta.x)-1;
@@ -70,20 +69,20 @@ Interpolator::interpolate(const ClusterVector<ClusterType> &clusters) {
             // cBottomRight = 1,
             // cTopLeft = 2,
             // cTopRight = 3
-            switch (eta.c) {
-            case cTopLeft:
+            switch (static_cast<corner>(eta.c)) {
+            case corner::cTopLeft:
                 dX = -1.;
                 dY = 0;
                 break;
-            case cTopRight:;
+            case corner::cTopRight:;
                 dX = 0;
                 dY = 0;
                 break;
-            case cBottomLeft:
+            case corner::cBottomLeft:
                 dX = -1.;
                 dY = -1.;
                 break;
-            case cBottomRight:
+            case corner::cBottomRight:
                 dX = 0.;
                 dY = -1.;
                 break;
@@ -94,14 +93,13 @@ Interpolator::interpolate(const ClusterVector<ClusterType> &clusters) {
         }
     } else if (clusters.cluster_size_x() == 2 ||
                clusters.cluster_size_y() == 2) {
-        for (size_t i = 0; i < clusters.size(); i++) {
-            auto cluster = clusters.at(i);
+        for (const ClusterType &cluster : clusters) {
             auto eta = calculate_eta2(cluster);
 
             Photon photon;
             photon.x = cluster.x;
             photon.y = cluster.y;
-            photon.energy = eta.sum;
+            photon.energy = static_cast<decltype(photon.energy)>(eta.sum);
 
             // Now do some actual interpolation.
             // Find which energy bin the cluster is in

include/aare/NDArray.hpp

@@ -22,10 +22,10 @@ TODO! Add expression templates for operators
 namespace aare {
 
 
-template <typename T, int64_t Ndim = 2>
+template <typename T, ssize_t Ndim = 2>
 class NDArray : public ArrayExpr<NDArray<T, Ndim>, Ndim> {
-    std::array<int64_t, Ndim> shape_;
-    std::array<int64_t, Ndim> strides_;
+    std::array<ssize_t, Ndim> shape_;
+    std::array<ssize_t, Ndim> strides_;
     size_t size_{};
     T *data_;
 
@@ -42,7 +42,7 @@ class NDArray : public ArrayExpr<NDArray<T, Ndim>, Ndim> {
      *
      * @param shape shape of the new NDArray
      */
-    explicit NDArray(std::array<int64_t, Ndim> shape)
+    explicit NDArray(std::array<ssize_t, Ndim> shape)
         : shape_(shape), strides_(c_strides<Ndim>(shape_)),
           size_(std::accumulate(shape_.begin(), shape_.end(), 1,
                                 std::multiplies<>())),
@@ -55,7 +55,7 @@ class NDArray : public ArrayExpr<NDArray<T, Ndim>, Ndim> {
      * @param shape shape of the new array
      * @param value value to initialize the array with
      */
-    NDArray(std::array<int64_t, Ndim> shape, T value) : NDArray(shape) {
+    NDArray(std::array<ssize_t, Ndim> shape, T value) : NDArray(shape) {
         this->operator=(value);
     }
 
@@ -186,22 +186,22 @@ class NDArray : public ArrayExpr<NDArray<T, Ndim>, Ndim> {
     }
 
     // TODO! is int the right type for index?
-    T &operator()(int64_t i) { return data_[i]; }
-    const T &operator()(int64_t i) const { return data_[i]; }
+    T &operator()(ssize_t i) { return data_[i]; }
+    const T &operator()(ssize_t i) const { return data_[i]; }
 
-    T &operator[](int64_t i) { return data_[i]; }
-    const T &operator[](int64_t i) const { return data_[i]; }
+    T &operator[](ssize_t i) { return data_[i]; }
+    const T &operator[](ssize_t i) const { return data_[i]; }
 
     T *data() { return data_; }
     std::byte *buffer() { return reinterpret_cast<std::byte *>(data_); }
     ssize_t size() const { return static_cast<ssize_t>(size_); }
     size_t total_bytes() const { return size_ * sizeof(T); }
-    std::array<int64_t, Ndim> shape() const noexcept { return shape_; }
-    int64_t shape(int64_t i) const noexcept { return shape_[i]; }
-    std::array<int64_t, Ndim> strides() const noexcept { return strides_; }
+    std::array<ssize_t, Ndim> shape() const noexcept { return shape_; }
+    ssize_t shape(ssize_t i) const noexcept { return shape_[i]; }
+    std::array<ssize_t, Ndim> strides() const noexcept { return strides_; }
     size_t bitdepth() const noexcept { return sizeof(T) * 8; }
 
-    std::array<int64_t, Ndim> byte_strides() const noexcept {
+    std::array<ssize_t, Ndim> byte_strides() const noexcept {
         auto byte_strides = strides_;
         for (auto &val : byte_strides)
             val *= sizeof(T);
@@ -228,7 +228,7 @@ class NDArray : public ArrayExpr<NDArray<T, Ndim>, Ndim> {
 };
 
 // Move assign
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &
 NDArray<T, Ndim>::operator=(NDArray<T, Ndim> &&other) noexcept {
     if (this != &other) {
@@ -242,7 +242,7 @@ NDArray<T, Ndim>::operator=(NDArray<T, Ndim> &&other) noexcept {
     return *this;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator+=(const NDArray<T, Ndim> &other) {
     // check shape
     if (shape_ == other.shape_) {
@@ -254,7 +254,7 @@ NDArray<T, Ndim> &NDArray<T, Ndim>::operator+=(const NDArray<T, Ndim> &other) {
     throw(std::runtime_error("Shape of ImageDatas must match"));
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator-=(const NDArray<T, Ndim> &other) {
     // check shape
     if (shape_ == other.shape_) {
@@ -266,7 +266,7 @@ NDArray<T, Ndim> &NDArray<T, Ndim>::operator-=(const NDArray<T, Ndim> &other) {
     throw(std::runtime_error("Shape of ImageDatas must match"));
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator*=(const NDArray<T, Ndim> &other) {
     // check shape
     if (shape_ == other.shape_) {
@@ -278,14 +278,14 @@ NDArray<T, Ndim> &NDArray<T, Ndim>::operator*=(const NDArray<T, Ndim> &other) {
     throw(std::runtime_error("Shape of ImageDatas must match"));
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator&=(const T &mask) {
     for (auto it = begin(); it != end(); ++it)
         *it &= mask;
     return *this;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<bool, Ndim> NDArray<T, Ndim>::operator>(const NDArray &other) {
     if (shape_ == other.shape_) {
         NDArray<bool, Ndim> result{shape_};
@@ -297,7 +297,7 @@ NDArray<bool, Ndim> NDArray<T, Ndim>::operator>(const NDArray &other) {
     throw(std::runtime_error("Shape of ImageDatas must match"));
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator=(const NDArray<T, Ndim> &other) {
     if (this != &other) {
         delete[] data_;
@@ -310,7 +310,7 @@ NDArray<T, Ndim> &NDArray<T, Ndim>::operator=(const NDArray<T, Ndim> &other) {
     return *this;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 bool NDArray<T, Ndim>::operator==(const NDArray<T, Ndim> &other) const {
     if (shape_ != other.shape_)
         return false;
@@ -322,23 +322,23 @@ bool NDArray<T, Ndim>::operator==(const NDArray<T, Ndim> &other) const {
     return true;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 bool NDArray<T, Ndim>::operator!=(const NDArray<T, Ndim> &other) const {
     return !((*this) == other);
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator++() {
     for (uint32_t i = 0; i < size_; ++i)
         data_[i] += 1;
     return *this;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator=(const T &value) {
     std::fill_n(data_, size_, value);
     return *this;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator+=(const T &value) {
     for (uint32_t i = 0; i < size_; ++i)
         data_[i] += value;
@@ -348,57 +348,57 @@ NDArray<T, Ndim> &NDArray<T, Ndim>::operator+=(const T &value) {
 
 
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> NDArray<T, Ndim>::operator+(const T &value) {
     NDArray result = *this;
     result += value;
     return result;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator-=(const T &value) {
     for (uint32_t i = 0; i < size_; ++i)
         data_[i] -= value;
     return *this;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> NDArray<T, Ndim>::operator-(const T &value) {
     NDArray result = *this;
     result -= value;
     return result;
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator/=(const T &value) {
     for (uint32_t i = 0; i < size_; ++i)
         data_[i] /= value;
     return *this;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> NDArray<T, Ndim>::operator/(const T &value) {
     NDArray result = *this;
     result /= value;
     return result;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> &NDArray<T, Ndim>::operator*=(const T &value) {
     for (uint32_t i = 0; i < size_; ++i)
         data_[i] *= value;
     return *this;
 }
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> NDArray<T, Ndim>::operator*(const T &value) {
     NDArray result = *this;
     result *= value;
     return result;
 }
-// template <typename T, int64_t Ndim> void NDArray<T, Ndim>::Print() {
+// template <typename T, ssize_t Ndim> void NDArray<T, Ndim>::Print() {
 //     if (shape_[0] < 20 && shape_[1] < 20)
 //         Print_all();
 //     else
 //         Print_some();
 // }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 std::ostream &operator<<(std::ostream &os, const NDArray<T, Ndim> &arr) {
     for (auto row = 0; row < arr.shape(0); ++row) {
         for (auto col = 0; col < arr.shape(1); ++col) {
@@ -410,7 +410,7 @@ std::ostream &operator<<(std::ostream &os, const NDArray<T, Ndim> &arr) {
     return os;
 }
 
-template <typename T, int64_t Ndim> void NDArray<T, Ndim>::Print_all() {
+template <typename T, ssize_t Ndim> void NDArray<T, Ndim>::Print_all() {
     for (auto row = 0; row < shape_[0]; ++row) {
         for (auto col = 0; col < shape_[1]; ++col) {
             std::cout << std::setw(3);
@@ -419,7 +419,7 @@ template <typename T, int64_t Ndim> void NDArray<T, Ndim>::Print_all() {
         std::cout << "\n";
     }
 }
-template <typename T, int64_t Ndim> void NDArray<T, Ndim>::Print_some() {
+template <typename T, ssize_t Ndim> void NDArray<T, Ndim>::Print_some() {
     for (auto row = 0; row < 5; ++row) {
         for (auto col = 0; col < 5; ++col) {
             std::cout << std::setw(7);
@@ -429,7 +429,7 @@ template <typename T, int64_t Ndim> void NDArray<T, Ndim>::Print_some() {
     }
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 void save(NDArray<T, Ndim> &img, std::string &pathname) {
     std::ofstream f;
     f.open(pathname, std::ios::binary);
@@ -437,9 +437,9 @@ void save(NDArray<T, Ndim> &img, std::string &pathname) {
     f.close();
 }
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 NDArray<T, Ndim> load(const std::string &pathname,
-                      std::array<int64_t, Ndim> shape) {
+                      std::array<ssize_t, Ndim> shape) {
     NDArray<T, Ndim> img{shape};
     std::ifstream f;
     f.open(pathname, std::ios::binary);

include/aare/NDView.hpp

@@ -14,10 +14,10 @@
 #include <vector>
 namespace aare {
 
-template <int64_t Ndim> using Shape = std::array<int64_t, Ndim>;
+template <ssize_t Ndim> using Shape = std::array<ssize_t, Ndim>;
 
 // TODO! fix mismatch between signed and unsigned
-template <int64_t Ndim> Shape<Ndim> make_shape(const std::vector<size_t> &shape) {
+template <ssize_t Ndim> Shape<Ndim> make_shape(const std::vector<size_t> &shape) {
     if (shape.size() != Ndim)
         throw std::runtime_error("Shape size mismatch");
     Shape<Ndim> arr;
@@ -25,41 +25,41 @@ template <int64_t Ndim> Shape<Ndim> make_shape(const std::vector<size_t> &shape)
     return arr;
 }
 
-template <int64_t Dim = 0, typename Strides> int64_t element_offset(const Strides & /*unused*/) { return 0; }
+template <ssize_t Dim = 0, typename Strides> ssize_t element_offset(const Strides & /*unused*/) { return 0; }
 
-template <int64_t Dim = 0, typename Strides, typename... Ix>
-int64_t element_offset(const Strides &strides, int64_t i, Ix... index) {
+template <ssize_t Dim = 0, typename Strides, typename... Ix>
+ssize_t element_offset(const Strides &strides, ssize_t i, Ix... index) {
     return i * strides[Dim] + element_offset<Dim + 1>(strides, index...);
 }
 
-template <int64_t Ndim> std::array<int64_t, Ndim> c_strides(const std::array<int64_t, Ndim> &shape) {
-    std::array<int64_t, Ndim> strides{};
+template <ssize_t Ndim> std::array<ssize_t, Ndim> c_strides(const std::array<ssize_t, Ndim> &shape) {
+    std::array<ssize_t, Ndim> strides{};
     std::fill(strides.begin(), strides.end(), 1);
-    for (int64_t i = Ndim - 1; i > 0; --i) {
+    for (ssize_t i = Ndim - 1; i > 0; --i) {
         strides[i - 1] = strides[i] * shape[i];
     }
     return strides;
 }
 
-template <int64_t Ndim> std::array<int64_t, Ndim> make_array(const std::vector<int64_t> &vec) {
+template <ssize_t Ndim> std::array<ssize_t, Ndim> make_array(const std::vector<ssize_t> &vec) {
     assert(vec.size() == Ndim);
-    std::array<int64_t, Ndim> arr{};
+    std::array<ssize_t, Ndim> arr{};
     std::copy_n(vec.begin(), Ndim, arr.begin());
     return arr;
 }
 
-template <typename T, int64_t Ndim = 2> class NDView : public ArrayExpr<NDView<T, Ndim>, Ndim> {
+template <typename T, ssize_t Ndim = 2> class NDView : public ArrayExpr<NDView<T, Ndim>, Ndim> {
   public:
     NDView() = default;
     ~NDView() = default;
     NDView(const NDView &) = default;
     NDView(NDView &&) = default;
 
-    NDView(T *buffer, std::array<int64_t, Ndim> shape)
+    NDView(T *buffer, std::array<ssize_t, Ndim> shape)
         : buffer_(buffer), strides_(c_strides<Ndim>(shape)), shape_(shape),
           size_(std::accumulate(std::begin(shape), std::end(shape), 1, std::multiplies<>())) {}
 
-    // NDView(T *buffer, const std::vector<int64_t> &shape)
+    // NDView(T *buffer, const std::vector<ssize_t> &shape)
     //     : buffer_(buffer), strides_(c_strides<Ndim>(make_array<Ndim>(shape))), shape_(make_array<Ndim>(shape)),
     //       size_(std::accumulate(std::begin(shape), std::end(shape), 1, std::multiplies<>())) {}
 
@@ -73,14 +73,14 @@ template <typename T, int64_t Ndim = 2> class NDView : public ArrayExpr<NDView<T
 
     ssize_t size() const { return static_cast<ssize_t>(size_); }
     size_t total_bytes() const { return size_ * sizeof(T); }
-    std::array<int64_t, Ndim> strides() const noexcept { return strides_; }
+    std::array<ssize_t, Ndim> strides() const noexcept { return strides_; }
 
     T *begin() { return buffer_; }
     T *end() { return buffer_ + size_; }
     T const *begin() const { return buffer_; }
     T const *end() const { return buffer_ + size_; }
-    T &operator()(int64_t i) const { return buffer_[i]; }
-    T &operator[](int64_t i) const { return buffer_[i]; }
+    T &operator()(ssize_t i) const { return buffer_[i]; }
+    T &operator[](ssize_t i) const { return buffer_[i]; }
 
     bool operator==(const NDView &other) const {
         if (size_ != other.size_)
@@ -136,15 +136,15 @@ template <typename T, int64_t Ndim = 2> class NDView : public ArrayExpr<NDView<T
     }
 
     auto &shape() const { return shape_; }
-    auto shape(int64_t i) const { return shape_[i]; }
+    auto shape(ssize_t i) const { return shape_[i]; }
 
     T *data() { return buffer_; }
     void print_all() const;
 
   private:
     T *buffer_{nullptr};
-    std::array<int64_t, Ndim> strides_{};
-    std::array<int64_t, Ndim> shape_{};
+    std::array<ssize_t, Ndim> strides_{};
+    std::array<ssize_t, Ndim> shape_{};
     uint64_t size_{};
 
     template <class BinaryOperation> NDView &elemenwise(T val, BinaryOperation op) {
@@ -160,7 +160,7 @@ template <typename T, int64_t Ndim = 2> class NDView : public ArrayExpr<NDView<T
         return *this;
     }
 };
-template <typename T, int64_t Ndim> void NDView<T, Ndim>::print_all() const {
+template <typename T, ssize_t Ndim> void NDView<T, Ndim>::print_all() const {
     for (auto row = 0; row < shape_[0]; ++row) {
         for (auto col = 0; col < shape_[1]; ++col) {
             std::cout << std::setw(3);
@@ -171,7 +171,7 @@ template <typename T, int64_t Ndim> void NDView<T, Ndim>::print_all() const {
 }
 
 
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 std::ostream& operator <<(std::ostream& os, const NDView<T, Ndim>& arr){
     for (auto row = 0; row < arr.shape(0); ++row) {
         for (auto col = 0; col < arr.shape(1); ++col) {
@@ -184,4 +184,9 @@ std::ostream& operator <<(std::ostream& os, const NDView<T, Ndim>& arr){
 }
 
 
+template <typename T>
+NDView<T,1> make_view(std::vector<T>& vec){
+    return NDView<T,1>(vec.data(), {static_cast<ssize_t>(vec.size())});
+}
+
 } // namespace aare

include/aare/NumpyFile.hpp

@@ -69,7 +69,7 @@ class NumpyFile : public FileInterface {
      */
     template <typename T, size_t NDim> NDArray<T, NDim> load() {
         NDArray<T, NDim> arr(make_shape<NDim>(m_header.shape));
-        if (fseek(fp, static_cast<int64_t>(header_size), SEEK_SET)) {
+        if (fseek(fp, static_cast<long>(header_size), SEEK_SET)) {
             throw std::runtime_error(LOCATION + "Error seeking to the start of the data");
         }
         size_t rc = fread(arr.data(), sizeof(T), arr.size(), fp);

include/aare/Pedestal.hpp

@@ -107,7 +107,7 @@ template <typename SUM_TYPE = double> class Pedestal {
         assert(frame.size() == m_rows * m_cols);
 
         // TODO! move away from m_rows, m_cols
-        if (frame.shape() != std::array<int64_t, 2>{m_rows, m_cols}) {
+        if (frame.shape() != std::array<ssize_t, 2>{m_rows, m_cols}) {
             throw std::runtime_error(
                 "Frame shape does not match pedestal shape");
         }
@@ -128,7 +128,7 @@ template <typename SUM_TYPE = double> class Pedestal {
         assert(frame.size() == m_rows * m_cols);
 
         // TODO! move away from m_rows, m_cols
-        if (frame.shape() != std::array<int64_t, 2>{m_rows, m_cols}) {
+        if (frame.shape() != std::array<ssize_t, 2>{m_rows, m_cols}) {
             throw std::runtime_error(
                 "Frame shape does not match pedestal shape");
         }

include/aare/RawFile.hpp

@@ -30,22 +30,11 @@ struct ModuleConfig {
  * Consider using that unless you need raw file specific functionality.
  */
 class RawFile : public FileInterface {
-    size_t n_subfiles{}; //f0,f1...fn
-    size_t n_subfile_parts{}; // d0,d1...dn
-    //TODO! move to vector of SubFile instead of pointers
-    std::vector<std::vector<RawSubFile *>> subfiles; //subfiles[f0,f1...fn][d0,d1...dn]
-    // std::vector<xy> positions;
-    
+    std::vector<std::unique_ptr<RawSubFile>> m_subfiles;
     ModuleConfig cfg{0, 0};
-
     RawMasterFile m_master;
-
     size_t m_current_frame{};
-
-    // std::vector<ModuleGeometry> m_module_pixel_0;
-    // size_t m_rows{};
-    // size_t m_cols{};
-
+    size_t m_current_subfile{};
     DetectorGeometry m_geometry;
 
   public:
@@ -56,7 +45,7 @@ class RawFile : public FileInterface {
 
      */
     RawFile(const std::filesystem::path &fname, const std::string &mode = "r");
-    virtual ~RawFile() override;
+    virtual ~RawFile() override = default;
 
     Frame read_frame() override;
     Frame read_frame(size_t frame_number) override;
@@ -80,7 +69,7 @@ class RawFile : public FileInterface {
     size_t cols() const override;
     size_t bitdepth() const override;
     xy geometry();
-    size_t n_mod() const;
+    size_t n_modules() const;
     
     RawMasterFile master() const;
 
@@ -115,9 +104,6 @@ class RawFile : public FileInterface {
      */
     static DetectorHeader read_header(const std::filesystem::path &fname);
 
-    // void update_geometry_with_roi();
-    int find_number_of_subfiles();
-
     void open_subfiles();
     void find_geometry();
 };

include/aare/RawMasterFile.hpp

@@ -121,6 +121,7 @@ class RawMasterFile {
 
     size_t total_frames_expected() const;
     xy geometry() const;
+    size_t n_modules() const;
 
     std::optional<size_t> analog_samples() const;
     std::optional<size_t> digital_samples() const;

include/aare/RawSubFile.hpp

@@ -18,11 +18,20 @@ class RawSubFile {
     std::ifstream m_file;
     DetectorType m_detector_type;
     size_t m_bitdepth;
-    std::filesystem::path m_fname;
+    std::filesystem::path m_path;     //!< path to the subfile
+    std::string m_base_name;          //!< base name used for formatting file names
+    size_t m_offset{}; //!< file index of the first file, allow starting at non zero file
+    size_t m_total_frames{};    //!< total number of frames in the series of files
     size_t m_rows{};
     size_t m_cols{};
     size_t m_bytes_per_frame{};
-    size_t n_frames{};
+
+
+    int m_module_index{};
+    size_t m_current_file_index{};   //!< The index of the open file
+    size_t m_current_frame_index{};  //!< The index of the current frame (with reference to all files)
+    std::vector<size_t> m_last_frame_in_file{}; //!< Used for seeking to the correct file
+
     uint32_t m_pos_row{};
     uint32_t m_pos_col{};
  
@@ -53,6 +62,7 @@ class RawSubFile {
     size_t tell();
 
     void read_into(std::byte *image_buf, DetectorHeader *header = nullptr);
+    void read_into(std::byte *image_buf, size_t n_frames, DetectorHeader *header= nullptr);
     void get_part(std::byte *buffer, size_t frame_index);
     
     void read_header(DetectorHeader *header);
@@ -66,10 +76,17 @@ class RawSubFile {
     size_t pixels_per_frame() const { return m_rows * m_cols; }
     size_t bytes_per_pixel() const { return m_bitdepth / bits_per_byte; }
 
+    size_t frames_in_file() const { return m_total_frames; }
+
 private:
   template <typename T>
   void read_with_map(std::byte *image_buf);
 
+  void parse_fname(const std::filesystem::path &fname);
+  void scan_files();
+  void open_file(size_t file_index);
+  std::filesystem::path fpath(size_t file_index) const;
+
 };
 
 } // namespace aare

include/aare/VarClusterFinder.hpp

@@ -28,7 +28,7 @@ template <typename T> class VarClusterFinder {
     };
 
   private:
-    const std::array<int64_t, 2> shape_;
+    const std::array<ssize_t, 2> shape_;
     NDView<T, 2> original_;
     NDArray<int, 2> labeled_;
     NDArray<int, 2> peripheral_labeled_;

include/aare/algorithm.hpp

@@ -107,5 +107,16 @@ std::vector<T> cumsum(const std::vector<T>& vec) {
 }
 
 
+template <typename Container> bool all_equal(const Container &c) {
+    if (!c.empty() &&
+        std::all_of(begin(c), end(c),
+                    [c](const typename Container::value_type &element) {
+                        return element == c.front();
+                    }))
+        return true;
+    return false;
+}
+
+
 
 } // namespace aare

include/aare/decode.hpp

@@ -1,6 +1,7 @@
 #pragma once
 
 #include <cstdint>
+#include <vector>
 #include <aare/NDView.hpp>
 namespace aare {
 
@@ -10,4 +11,16 @@ uint16_t adc_sar_04_decode64to16(uint64_t input);
 void adc_sar_05_decode64to16(NDView<uint64_t, 2> input, NDView<uint16_t,2> output);
 void adc_sar_04_decode64to16(NDView<uint64_t, 2> input, NDView<uint16_t,2> output);
 
-} // namespace aare
+
+/**
+ * @brief Apply custom weights to a 16-bit input value. Will sum up weights[i]**i
+ * for each bit i that is set in the input value.
+ * @throws std::out_of_range if weights.size() < 16
+ * @param input 16-bit input value
+ * @param weights vector of weights, size must be less than or equal to 16
+ */
+double apply_custom_weights(uint16_t input, const NDView<double, 1> weights);
+
+void apply_custom_weights(NDView<uint16_t, 1> input, NDView<double, 1> output, const NDView<double, 1> weights);
+
+} // namespace aare

include/aare/defs.hpp

@@ -204,23 +204,25 @@ struct DetectorGeometry{
     int module_gap_row{};
     int module_gap_col{};
     std::vector<ModuleGeometry> module_pixel_0;
+    
+    auto size() const { return module_pixel_0.size(); }
 };
 
 struct ROI{
-    int64_t xmin{};
-    int64_t xmax{};
-    int64_t ymin{};
-    int64_t ymax{};
+    ssize_t xmin{};
+    ssize_t xmax{};
+    ssize_t ymin{};
+    ssize_t ymax{};
   
-    int64_t height() const { return ymax - ymin; }
-    int64_t width() const { return xmax - xmin; }
-    bool contains(int64_t x, int64_t y) const {
+    ssize_t height() const { return ymax - ymin; }
+    ssize_t width() const { return xmax - xmin; }
+    bool contains(ssize_t x, ssize_t y) const {
         return x >= xmin && x < xmax && y >= ymin && y < ymax;
     }
   };
 
 
-using dynamic_shape = std::vector<int64_t>;
+using dynamic_shape = std::vector<ssize_t>;
 
 //TODO! Can we uniform enums between the libraries?
 

include/aare/logger.hpp

@@ -0,0 +1,139 @@
+#pragma once
+/*Utility to log to console*/
+
+
+#include <iostream>
+#include <sstream>
+#include <sys/time.h>
+
+namespace aare {
+
+#define RED      "\x1b[31m"
+#define GREEN    "\x1b[32m"
+#define YELLOW   "\x1b[33m"
+#define BLUE     "\x1b[34m"
+#define MAGENTA  "\x1b[35m"
+#define CYAN     "\x1b[36m"
+#define GRAY     "\x1b[37m"
+#define DARKGRAY "\x1b[30m"
+
+#define BG_BLACK   "\x1b[48;5;232m"
+#define BG_RED     "\x1b[41m"
+#define BG_GREEN   "\x1b[42m"
+#define BG_YELLOW  "\x1b[43m"
+#define BG_BLUE    "\x1b[44m"
+#define BG_MAGENTA "\x1b[45m"
+#define BG_CYAN    "\x1b[46m"
+#define RESET      "\x1b[0m"
+#define BOLD       "\x1b[1m"
+
+
+enum TLogLevel {
+    logERROR,
+    logWARNING,
+    logINFOBLUE,
+    logINFOGREEN,
+    logINFORED,
+    logINFOCYAN,
+    logINFOMAGENTA,
+    logINFO,
+    logDEBUG,
+    logDEBUG1,
+    logDEBUG2,
+    logDEBUG3,
+    logDEBUG4,
+    logDEBUG5
+};
+
+// Compiler should optimize away anything below this value
+#ifndef AARE_LOG_LEVEL
+#define AARE_LOG_LEVEL "LOG LEVEL NOT SET IN CMAKE" //This is configured in the main CMakeLists.txt
+#endif
+
+#define __AT__                                                                 \
+    std::string(__FILE__) + std::string("::") + std::string(__func__) +        \
+        std::string("(): ")
+#define __SHORT_FORM_OF_FILE__                                                 \
+    (strrchr(__FILE__, '/') ? strrchr(__FILE__, '/') + 1 : __FILE__)
+#define __SHORT_AT__                                                           \
+    std::string(__SHORT_FORM_OF_FILE__) + std::string("::") +                  \
+        std::string(__func__) + std::string("(): ")
+
+class Logger {
+    std::ostringstream os;
+    TLogLevel m_level = AARE_LOG_LEVEL;
+
+  public:
+    Logger() = default;
+    explicit Logger(TLogLevel level) : m_level(level){};
+    ~Logger() {
+        // output in the destructor to allow for << syntax
+        os << RESET << '\n';
+        std::clog << os.str() << std::flush; // Single write
+    }
+
+    static TLogLevel &ReportingLevel() { // singelton eeh TODO! Do we need a runtime option?
+        static TLogLevel reportingLevel = logDEBUG5;
+        return reportingLevel;
+    }
+
+    // Danger this buffer need as many elements as TLogLevel
+    static const char *Color(TLogLevel level) noexcept {
+        static const char *const colors[] = {
+            RED BOLD, YELLOW BOLD, BLUE,  GREEN, RED,   CYAN,  MAGENTA,
+            RESET,    RESET,       RESET, RESET, RESET, RESET, RESET};
+        // out of bounds
+        if (level < 0 || level >= sizeof(colors) / sizeof(colors[0])) {
+            return RESET;
+        }
+        return colors[level];
+    }
+
+    // Danger this buffer need as many elements as TLogLevel
+    static std::string ToString(TLogLevel level) {
+        static const char *const buffer[] = {
+            "ERROR",  "WARNING", "INFO",   "INFO",  "INFO",
+            "INFO",   "INFO",    "INFO",   "DEBUG", "DEBUG1",
+            "DEBUG2", "DEBUG3",  "DEBUG4", "DEBUG5"};
+        // out of bounds
+        if (level < 0 || level >= sizeof(buffer) / sizeof(buffer[0])) {
+            return "UNKNOWN";
+        }
+        return buffer[level];
+    }
+
+    std::ostringstream &Get() {
+        os << Color(m_level) << "- " << Timestamp() << " " << ToString(m_level)
+           << ": ";
+        return os;
+    }
+
+    static std::string Timestamp() {
+        constexpr size_t buffer_len = 12;
+        char buffer[buffer_len];
+        time_t t;
+        ::time(&t);
+        tm r;
+        strftime(buffer, buffer_len, "%X", localtime_r(&t, &r));
+        buffer[buffer_len - 1] = '\0';
+        struct timeval tv;
+        gettimeofday(&tv, nullptr);
+        constexpr size_t result_len = 100;
+        char result[result_len];
+        snprintf(result, result_len, "%s.%03ld", buffer,
+                 static_cast<long>(tv.tv_usec) / 1000);
+        result[result_len - 1] = '\0';
+        return result;
+    }
+};
+
+// TODO! Do we need to keep the runtime option?
+#define LOG(level)                                                             \
+    if (level > AARE_LOG_LEVEL)                                                \
+        ;                                                                      \
+    else if (level > aare::Logger::ReportingLevel())                           \
+        ;                                                                      \
+    else                                                                       \
+        aare::Logger(level).Get()
+
+} // namespace aare

include/aare/utils/ifstream_helpers.hpp

@@ -0,0 +1,12 @@
+#pragma once
+
+#include <fstream>
+#include <string>
+namespace aare {
+
+/** 
+ * @brief Get the error message from an ifstream object
+*/
+std::string ifstream_error_msg(std::ifstream &ifs);
+
+} // namespace aare

pyproject.toml

@@ -1,22 +1,40 @@
+[tool.scikit-build.metadata.version]
+provider = "scikit_build_core.metadata.regex"
+input = "VERSION"
+regex = '^(?P<version>\d+(?:\.\d+)*(?:[\.\+\w]+)?)$'
+result = "{version}" 
+
 [build-system]
 requires = ["scikit-build-core>=0.10", "pybind11", "numpy"]
 build-backend = "scikit_build_core.build"
 
 [project]
 name = "aare"
-version = "2025.4.1"
+dynamic = ["version"]
+requires-python = ">=3.11"
+dependencies = [
+    "numpy",
+    "matplotlib",
+]
+
+
+[tool.cibuildwheel]
+
+build = "cp{311,312,313}-manylinux_x86_64"
 
 
 
 
 [tool.scikit-build]
-cmake.verbose = true
+build.verbose = true
+cmake.build-type = "Release"
+install.components = ["python"]
 
 [tool.scikit-build.cmake.define]
 AARE_PYTHON_BINDINGS = "ON"
-AARE_SYSTEM_LIBRARIES = "ON"
 AARE_INSTALL_PYTHONEXT = "ON"
 
+
 [tool.pytest.ini_options]
 markers = [
     "files: marks tests that need additional data (deselect with '-m \"not files\"')",

python/CMakeLists.txt

@@ -1,12 +1,13 @@
 
-find_package (Python 3.10 COMPONENTS Interpreter Development REQUIRED)
+find_package (Python 3.10 COMPONENTS Interpreter Development.Module REQUIRED)
+set(PYBIND11_FINDPYTHON ON) # Needed for RH8
 
 # Download or find pybind11 depending on configuration
 if(AARE_FETCH_PYBIND11)
     FetchContent_Declare(
         pybind11
         GIT_REPOSITORY https://github.com/pybind/pybind11
-        GIT_TAG        v2.13.0
+        GIT_TAG        v2.13.6
     )
     FetchContent_MakeAvailable(pybind11)
 else()
@@ -28,6 +29,9 @@ target_link_libraries(_aare PRIVATE aare_core aare_compiler_flags)
 set( PYTHON_FILES
     aare/__init__.py
     aare/CtbRawFile.py
+    aare/ClusterFinder.py
+    aare/ClusterVector.py
+
     aare/func.py
     aare/RawFile.py
     aare/transform.py
@@ -35,6 +39,7 @@ set( PYTHON_FILES
     aare/utils.py
 )
 
+
 # Copy the python files to the build directory
 foreach(FILE ${PYTHON_FILES})
     configure_file(${FILE} ${CMAKE_BINARY_DIR}/${FILE}  )
@@ -58,10 +63,16 @@ endforeach(FILE ${PYTHON_EXAMPLES})
 
 
 if(AARE_INSTALL_PYTHONEXT)
-    install(TARGETS _aare
+    install(
+        TARGETS _aare
         EXPORT "${TARGETS_EXPORT_NAME}"
         LIBRARY DESTINATION aare
+        COMPONENT python
     )
 
-    install(FILES ${PYTHON_FILES} DESTINATION aare)
+    install(
+        FILES ${PYTHON_FILES} 
+        DESTINATION aare
+        COMPONENT python
+        )
 endif()

python/aare/ClusterFinder.py

@@ -0,0 +1,67 @@
+
+from ._aare import ClusterFinder_Cluster3x3i, ClusterFinder_Cluster2x2i, ClusterFinderMT_Cluster3x3i, ClusterFinderMT_Cluster2x2i, ClusterCollector_Cluster3x3i, ClusterCollector_Cluster2x2i
+
+
+from ._aare import ClusterFileSink_Cluster3x3i, ClusterFileSink_Cluster2x2i
+import numpy as np
+
+def ClusterFinder(image_size, cluster_size, n_sigma=5, dtype = np.int32, capacity = 1024):
+    """
+    Factory function to create a ClusterFinder object. Provides a cleaner syntax for 
+    the templated ClusterFinder in C++.
+    """
+    if dtype == np.int32 and cluster_size == (3,3):
+        return ClusterFinder_Cluster3x3i(image_size, n_sigma = n_sigma, capacity=capacity)
+    elif dtype == np.int32 and cluster_size == (2,2): 
+        return ClusterFinder_Cluster2x2i(image_size, n_sigma = n_sigma, capacity=capacity)
+    else:
+        #TODO! add the other formats
+        raise ValueError(f"Unsupported dtype: {dtype}. Only np.int32 is supported.")
+
+
+def ClusterFinderMT(image_size, cluster_size = (3,3), dtype=np.int32, n_sigma=5, capacity = 1024, n_threads = 3): 
+    """ 
+    Factory function to create a ClusterFinderMT object. Provides a cleaner syntax for 
+    the templated ClusterFinderMT in C++.
+    """
+
+    if dtype == np.int32 and cluster_size == (3,3):
+        return ClusterFinderMT_Cluster3x3i(image_size, n_sigma = n_sigma,
+                    capacity = capacity, n_threads = n_threads)
+    elif dtype == np.int32 and cluster_size == (2,2):
+        return ClusterFinderMT_Cluster2x2i(image_size, n_sigma = n_sigma,
+                    capacity = capacity, n_threads = n_threads)
+    else:
+        #TODO! add the other formats
+        raise ValueError(f"Unsupported dtype: {dtype}. Only np.int32 is supported.")
+
+
+def ClusterCollector(clusterfindermt, cluster_size = (3,3), dtype=np.int32): 
+    """ 
+    Factory function to create a ClusterCollector object. Provides a cleaner syntax for 
+    the templated ClusterCollector in C++.
+    """
+
+    if dtype == np.int32 and cluster_size == (3,3): 
+        return ClusterCollector_Cluster3x3i(clusterfindermt)
+    elif dtype == np.int32 and cluster_size == (2,2):
+        return ClusterCollector_Cluster2x2i(clusterfindermt)
+     
+    else: 
+        #TODO! add the other formats
+        raise ValueError(f"Unsupported dtype: {dtype}. Only np.int32 is supported.")
+
+def ClusterFileSink(clusterfindermt, cluster_file, dtype=np.int32): 
+    """ 
+    Factory function to create a ClusterCollector object. Provides a cleaner syntax for 
+    the templated ClusterCollector in C++.
+    """
+
+    if dtype == np.int32 and clusterfindermt.cluster_size == (3,3): 
+        return ClusterFileSink_Cluster3x3i(clusterfindermt, cluster_file)
+    elif dtype == np.int32 and clusterfindermt.cluster_size == (2,2):
+        return ClusterFileSink_Cluster2x2i(clusterfindermt, cluster_file)
+     
+    else: 
+        #TODO! add the other formats
+        raise ValueError(f"Unsupported dtype: {dtype}. Only np.int32 is supported.")

python/aare/ClusterVector.py

@@ -0,0 +1,11 @@
+
+
+from ._aare import ClusterVector_Cluster3x3i
+import numpy as np
+
+def ClusterVector(cluster_size, dtype = np.int32):
+
+    if dtype == np.int32 and cluster_size == (3,3):
+        return ClusterVector_Cluster3x3i()
+    else:
+        raise ValueError(f"Unsupported dtype: {dtype}. Only np.int32 is supported.")

python/aare/__init__.py

@@ -11,8 +11,17 @@ from ._aare import ROI
 
 # from ._aare import ClusterFinderMT, ClusterCollector, ClusterFileSink, ClusterVector_i
 
-from ._aare import fit_gaus, fit_pol1
+from .ClusterFinder import ClusterFinder, ClusterCollector, ClusterFinderMT, ClusterFileSink
+from .ClusterVector import ClusterVector
+
+
+from ._aare import fit_gaus, fit_pol1, fit_scurve, fit_scurve2
 from ._aare import Interpolator
+from ._aare import calculate_eta2
+
+
+from ._aare import apply_custom_weights
+
 from .CtbRawFile import CtbRawFile
 from .RawFile import RawFile
 from .ScanParameters import ScanParameters

python/aare/func.py

@@ -1 +1 @@
-from ._aare import gaus, pol1
+from ._aare import gaus, pol1, scurve, scurve2

python/examples/play.py

@@ -1,79 +1,89 @@
 import sys
 sys.path.append('/home/l_msdetect/erik/aare/build')
 
-from aare._aare import ClusterVector_i, Interpolator
 
-import pickle 
-import numpy as np
-import matplotlib.pyplot as plt
-import boost_histogram as bh
-import torch
-import math
-import time
+from aare import RawSubFile, DetectorType, RawFile
+
+from pathlib import Path
+path = Path("/home/l_msdetect/erik/data/aare-test-data/raw/jungfrau/")
+f = RawSubFile(path/"jungfrau_single_d0_f0_0.raw", DetectorType.Jungfrau, 512, 1024, 16)
+
+# f = RawFile(path/"jungfrau_single_master_0.json")
+
+
+# from aare._aare import ClusterVector_i, Interpolator
+
+# import pickle 
+# import numpy as np
+# import matplotlib.pyplot as plt
+# import boost_histogram as bh
+# import torch
+# import math
+# import time
 
 
 
-def gaussian_2d(mx, my, sigma = 1, res=100, grid_size = 2):
-    """
-    Generate a 2D gaussian as position mx, my, with sigma=sigma. 
-    The gaussian is placed on a 2x2 pixel matrix with resolution 
-    res in one dimesion.
-    """
-    x = torch.linspace(0, pixel_size*grid_size, res)
-    x,y = torch.meshgrid(x,x, indexing="ij")
-    return 1 / (2*math.pi*sigma**2) * \
-      torch.exp(-((x - my)**2 / (2*sigma**2) + (y - mx)**2 / (2*sigma**2)))
+# def gaussian_2d(mx, my, sigma = 1, res=100, grid_size = 2):
+#     """
+#     Generate a 2D gaussian as position mx, my, with sigma=sigma. 
+#     The gaussian is placed on a 2x2 pixel matrix with resolution 
+#     res in one dimesion.
+#     """
+#     x = torch.linspace(0, pixel_size*grid_size, res)
+#     x,y = torch.meshgrid(x,x, indexing="ij")
+#     return 1 / (2*math.pi*sigma**2) * \
+#       torch.exp(-((x - my)**2 / (2*sigma**2) + (y - mx)**2 / (2*sigma**2)))
 
-scale = 1000 #Scale factor when converting to integer
-pixel_size = 25 #um
-grid = 2
-resolution = 100
-sigma_um = 10
-xa = np.linspace(0,grid*pixel_size,resolution)
-ticks = [0, 25, 50]
+# scale = 1000 #Scale factor when converting to integer
+# pixel_size = 25 #um
+# grid = 2
+# resolution = 100
+# sigma_um = 10
+# xa = np.linspace(0,grid*pixel_size,resolution)
+# ticks = [0, 25, 50]
 
-hit = np.array((20,20))
-etahist_fname = "/home/l_msdetect/erik/tmp/test_hist.pkl"
+# hit = np.array((20,20))
+# etahist_fname = "/home/l_msdetect/erik/tmp/test_hist.pkl"
 
-local_resolution = 99
-grid_size = 3
-xaxis = np.linspace(0,grid_size*pixel_size, local_resolution)
-t = gaussian_2d(hit[0],hit[1], grid_size = grid_size, sigma = 10, res = local_resolution)
-pixels = t.reshape(grid_size, t.shape[0] // grid_size, grid_size, t.shape[1] // grid_size).sum(axis = 3).sum(axis = 1)
-pixels = pixels.numpy()
-pixels = (pixels*scale).astype(np.int32)
-v = ClusterVector_i(3,3)
-v.push_back(1,1, pixels)
+# local_resolution = 99
+# grid_size = 3
+# xaxis = np.linspace(0,grid_size*pixel_size, local_resolution)
+# t = gaussian_2d(hit[0],hit[1], grid_size = grid_size, sigma = 10, res = local_resolution)
+# pixels = t.reshape(grid_size, t.shape[0] // grid_size, grid_size, t.shape[1] // grid_size).sum(axis = 3).sum(axis = 1)
+# pixels = pixels.numpy()
+# pixels = (pixels*scale).astype(np.int32)
+# v = ClusterVector_i(3,3)
+# v.push_back(1,1, pixels)
 
-with open(etahist_fname, "rb") as f:
-        hist = pickle.load(f)
-eta = hist.view().copy()
-etabinsx = np.array(hist.axes.edges.T[0].flat)
-etabinsy = np.array(hist.axes.edges.T[1].flat)
-ebins = np.array(hist.axes.edges.T[2].flat)
-p = Interpolator(eta, etabinsx[0:-1], etabinsy[0:-1], ebins[0:-1])
+# with open(etahist_fname, "rb") as f:
+#         hist = pickle.load(f)
+# eta = hist.view().copy()
+# etabinsx = np.array(hist.axes.edges.T[0].flat)
+# etabinsy = np.array(hist.axes.edges.T[1].flat)
+# ebins = np.array(hist.axes.edges.T[2].flat)
+# p = Interpolator(eta, etabinsx[0:-1], etabinsy[0:-1], ebins[0:-1])
 
 
 
 
-#Generate the hit
+# #Generate the hit
 
 
 
 
-tmp = p.interpolate(v)
-print(f'tmp:{tmp}')
-pos = np.array((tmp['x'], tmp['y']))*25
+# tmp = p.interpolate(v)
+# print(f'tmp:{tmp}')
+# pos = np.array((tmp['x'], tmp['y']))*25
 
 
-print(pixels)
-fig, ax = plt.subplots(figsize = (7,7))
-ax.pcolormesh(xaxis, xaxis, t)
-ax.plot(*pos, 'o')
-ax.set_xticks([0,25,50,75])
-ax.set_yticks([0,25,50,75])
-ax.set_xlim(0,75)
-ax.set_ylim(0,75)
-ax.grid()
-print(f'{hit=}')
-print(f'{pos=}')
+# print(pixels)
+# fig, ax = plt.subplots(figsize = (7,7))
+# ax.pcolormesh(xaxis, xaxis, t)
+# ax.plot(*pos, 'o')
+# ax.set_xticks([0,25,50,75])
+# ax.set_yticks([0,25,50,75])
+# ax.set_xlim(0,75)
+# ax.set_ylim(0,75)
+# ax.grid()
+# print(f'{hit=}')
+# print(f'{pos=}')

python/src/bind_ClusterVector.hpp

@@ -0,0 +1,104 @@
+#include "aare/ClusterCollector.hpp"
+#include "aare/ClusterFileSink.hpp"
+#include "aare/ClusterFinder.hpp"
+#include "aare/ClusterFinderMT.hpp"
+#include "aare/ClusterVector.hpp"
+#include "aare/NDView.hpp"
+#include "aare/Pedestal.hpp"
+#include "np_helper.hpp"
+
+#include <cstdint>
+#include <filesystem>
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <pybind11/stl_bind.h>
+
+namespace py = pybind11;
+using pd_type = double;
+
+using namespace aare;
+
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
+
+template <typename Type, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
+          typename CoordType = uint16_t>
+void define_ClusterVector(py::module &m, const std::string &typestr) {
+    using ClusterType = Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>;
+    auto class_name = fmt::format("ClusterVector_{}", typestr);
+
+    py::class_<ClusterVector<
+        Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>, void>>(
+        m, class_name.c_str(),
+        py::buffer_protocol())
+
+        .def(py::init()) // TODO change!!!
+
+        .def("push_back",
+             [](ClusterVector<ClusterType> &self, const ClusterType &cluster) {
+                 self.push_back(cluster);
+             })
+
+        .def("sum",
+             [](ClusterVector<ClusterType> &self) {
+                 auto *vec = new std::vector<Type>(self.sum());
+                 return return_vector(vec);
+             })
+        .def("sum_2x2", [](ClusterVector<ClusterType> &self){
+            auto *vec = new std::vector<Type>(self.sum_2x2());
+            return return_vector(vec);
+        })
+        .def_property_readonly("size", &ClusterVector<ClusterType>::size)
+        .def("item_size", &ClusterVector<ClusterType>::item_size)
+        .def_property_readonly("fmt",
+                               [typestr](ClusterVector<ClusterType> &self) {
+                                   return fmt_format<ClusterType>;
+                               })
+
+        .def_property_readonly("cluster_size_x",
+                               &ClusterVector<ClusterType>::cluster_size_x)
+        .def_property_readonly("cluster_size_y",
+                               &ClusterVector<ClusterType>::cluster_size_y)
+        .def_property_readonly("capacity",
+                               &ClusterVector<ClusterType>::capacity)
+        .def_property("frame_number", &ClusterVector<ClusterType>::frame_number,
+                      &ClusterVector<ClusterType>::set_frame_number)
+        .def_buffer(
+            [typestr](ClusterVector<ClusterType> &self) -> py::buffer_info {
+                return py::buffer_info(
+                    self.data(),             /* Pointer to buffer */
+                    self.item_size(),        /* Size of one scalar */
+                    fmt_format<ClusterType>, /* Format descriptor */
+                    1,                       /* Number of dimensions */
+                    {self.size()},           /* Buffer dimensions */
+                    {self.item_size()} /* Strides (in bytes) for each index */
+                );
+            });
+
+    // Free functions using ClusterVector
+    m.def("hitmap",
+          [](std::array<size_t, 2> image_size, ClusterVector<ClusterType> &cv) {
+              // Create a numpy array to hold the hitmap
+              // The shape of the array is (image_size[0], image_size[1])
+              // note that the python array is passed as [row, col] which
+              // is the opposite of the clusters [x,y]
+              py::array_t<int32_t> hitmap(image_size);
+              auto r = hitmap.mutable_unchecked<2>();
+
+              // Initialize hitmap to 0
+              for (py::ssize_t i = 0; i < r.shape(0); i++)
+                  for (py::ssize_t j = 0; j < r.shape(1); j++)
+                      r(i, j) = 0;
+
+              // Loop over the clusters and increment the hitmap
+              // Skip out of bound clusters
+              for (const auto &cluster : cv) {
+                  auto x = cluster.x;
+                  auto y = cluster.y;
+                  if (x < image_size[1] && y < image_size[0])
+                      r(cluster.y, cluster.x) += 1;
+              }
+
+              return hitmap;
+          });
+}

python/src/cluster.hpp

@@ -26,17 +26,18 @@ template <typename Type, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
 void define_cluster(py::module &m, const std::string &typestr) {
     auto class_name = fmt::format("Cluster{}", typestr);
 
-    py::class_<Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType, void>>(
+    py::class_<Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>>(
         m, class_name.c_str(), py::buffer_protocol())
 
         .def(py::init([](uint8_t x, uint8_t y, py::array_t<Type> data) {
             py::buffer_info buf_info = data.request();
-            Type *ptr = static_cast<Type *>(buf_info.ptr);
-            Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType, void> cluster;
+            Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType> cluster;
             cluster.x = x;
             cluster.y = y;
-            std::copy(ptr, ptr + ClusterSizeX * ClusterSizeY,
-                      cluster.data); // Copy array contents
+            auto r = data.template unchecked<1>(); // no bounds checks
+            for (py::ssize_t i = 0; i < data.size(); ++i) {
+                cluster.data[i] = r(i);
+            }
             return cluster;
         }));
 
@@ -64,54 +65,6 @@ void define_cluster(py::module &m, const std::string &typestr) {
     */
 }
 
-template <typename Type, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-          typename CoordType = uint16_t>
-void define_cluster_vector(py::module &m, const std::string &typestr) {
-    using ClusterType =
-        Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType, void>;
-    auto class_name = fmt::format("ClusterVector_{}", typestr);
-
-    py::class_<ClusterVector<
-        Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType, void>, void>>(
-        m, class_name.c_str(),
-        py::buffer_protocol())
-
-        .def(py::init()) // TODO change!!!
-
-        .def("push_back",
-             [](ClusterVector<ClusterType> &self, const ClusterType &cluster) {
-                 self.push_back(cluster);
-             })
-
-        // implement push_back
-        .def_property_readonly("size", &ClusterVector<ClusterType>::size)
-        .def("item_size", &ClusterVector<ClusterType>::item_size)
-        .def_property_readonly("fmt",
-                               [typestr](ClusterVector<ClusterType> &self) {
-                                   return fmt_format<ClusterType>;
-                               })
-
-        .def_property_readonly("cluster_size_x",
-                               &ClusterVector<ClusterType>::cluster_size_x)
-        .def_property_readonly("cluster_size_y",
-                               &ClusterVector<ClusterType>::cluster_size_y)
-        .def_property_readonly("capacity",
-                               &ClusterVector<ClusterType>::capacity)
-        .def_property("frame_number", &ClusterVector<ClusterType>::frame_number,
-                      &ClusterVector<ClusterType>::set_frame_number)
-        .def_buffer(
-            [typestr](ClusterVector<ClusterType> &self) -> py::buffer_info {
-                return py::buffer_info(
-                    self.data(),             /* Pointer to buffer */
-                    self.item_size(),        /* Size of one scalar */
-                    fmt_format<ClusterType>, /* Format descriptor */
-                    1,                       /* Number of dimensions */
-                    {self.size()},           /* Buffer dimensions */
-                    {self.item_size()} /* Strides (in bytes) for each index */
-                );
-            });
-}
-
 template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
           typename CoordType = uint16_t>
 void define_cluster_finder_mt_bindings(py::module &m,
@@ -140,6 +93,9 @@ void define_cluster_finder_mt_bindings(py::module &m,
                 return;
             },
             py::arg(), py::arg("frame_number") = 0)
+        .def_property_readonly("cluster_size", [](ClusterFinderMT<ClusterType, uint16_t, pd_type> &self){
+            return py::make_tuple(ClusterSizeX, ClusterSizeY);
+        })
         .def("clear_pedestal",
              &ClusterFinderMT<ClusterType, uint16_t, pd_type>::clear_pedestal)
         .def("sync", &ClusterFinderMT<ClusterType, uint16_t, pd_type>::sync)
@@ -251,26 +207,5 @@ void define_cluster_finder_bindings(py::module &m, const std::string &typestr) {
                 return;
             },
             py::arg(), py::arg("frame_number") = 0);
-
-    m.def("hitmap",
-          [](std::array<size_t, 2> image_size, ClusterVector<ClusterType> &cv) {
-              py::array_t<int32_t> hitmap(image_size);
-              auto r = hitmap.mutable_unchecked<2>();
-
-              // Initialize hitmap to 0
-              for (py::ssize_t i = 0; i < r.shape(0); i++)
-                  for (py::ssize_t j = 0; j < r.shape(1); j++)
-                      r(i, j) = 0;
-
-              size_t stride = cv.item_size();
-              auto ptr = cv.data();
-              for (size_t i = 0; i < cv.size(); i++) {
-                  auto x = *reinterpret_cast<int16_t *>(ptr);
-                  auto y = *reinterpret_cast<int16_t *>(ptr + sizeof(int16_t));
-                  r(y, x) += 1;
-                  ptr += stride;
-              }
-              return hitmap;
-          });
 }
 #pragma GCC diagnostic pop

python/src/cluster_file.hpp

@@ -59,9 +59,6 @@ void define_cluster_file_io_bindings(py::module &m,
                  self.set_gain_map(view);
              })
 
-        // void set_gain_map(const GainMap &gain_map); //TODO do i need a
-        // gainmap constructor?
-
         .def("close", &ClusterFile<ClusterType>::close)
         .def("write_frame", &ClusterFile<ClusterType>::write_frame)
         .def("__enter__", [](ClusterFile<ClusterType> &self) { return &self; })

python/src/ctb_raw_file.hpp

@@ -10,6 +10,8 @@
 #include "aare/decode.hpp"
 // #include "aare/fClusterFileV2.hpp"
 
+#include "np_helper.hpp"
+
 #include <cstdint>
 #include <filesystem>
 #include <pybind11/iostream.h>
@@ -32,7 +34,7 @@ m.def("adc_sar_05_decode64to16", [](py::array_t<uint8_t> input) {
     }
 
     //Create a 2D output array with the same shape as the input
-    std::vector<ssize_t> shape{input.shape(0), input.shape(1)/static_cast<int64_t>(bits_per_byte)};
+    std::vector<ssize_t> shape{input.shape(0), input.shape(1)/static_cast<ssize_t>(bits_per_byte)};
     py::array_t<uint16_t> output(shape);
 
     //Create a view of the input and output arrays
@@ -53,7 +55,7 @@ m.def("adc_sar_04_decode64to16", [](py::array_t<uint8_t> input) {
     }
 
     //Create a 2D output array with the same shape as the input
-    std::vector<ssize_t> shape{input.shape(0), input.shape(1)/static_cast<int64_t>(bits_per_byte)};
+    std::vector<ssize_t> shape{input.shape(0), input.shape(1)/static_cast<ssize_t>(bits_per_byte)};
     py::array_t<uint16_t> output(shape);
 
     //Create a view of the input and output arrays
@@ -65,35 +67,54 @@ m.def("adc_sar_04_decode64to16", [](py::array_t<uint8_t> input) {
     return output;
 });
 
- py::class_<CtbRawFile>(m, "CtbRawFile")
-        .def(py::init<const std::filesystem::path &>())
-        .def("read_frame",
-             [](CtbRawFile &self) {
-                 size_t image_size = self.image_size_in_bytes();
-                 py::array image;
-                 std::vector<ssize_t> shape;
-                 shape.reserve(2);
-                 shape.push_back(1);
-                 shape.push_back(image_size);
+m.def(
+    "apply_custom_weights",
+    [](py::array_t<uint16_t, py::array::c_style | py::array::forcecast> &input,
+       py::array_t<double, py::array::c_style | py::array::forcecast>
+           &weights) {
+        
 
-                 py::array_t<DetectorHeader> header(1);
+        // Create new array with same shape as the input array (uninitialized values)
+        py::buffer_info buf = input.request();
+        py::array_t<double> output(buf.shape);
 
-                 // always read bytes
-                 image = py::array_t<uint8_t>(shape);
+        // Use NDViews to call into the C++ library
+        auto weights_view = make_view_1d(weights);
+        NDView<uint16_t, 1> input_view(input.mutable_data(), {input.size()});
+        NDView<double, 1> output_view(output.mutable_data(), {output.size()});
 
-                 self.read_into(
-                     reinterpret_cast<std::byte *>(image.mutable_data()),
-                     header.mutable_data());
+        apply_custom_weights(input_view, output_view, weights_view);
+        return output;
+    });
 
-                 return py::make_tuple(header, image);
-             })
-        .def("seek", &CtbRawFile::seek)
-        .def("tell", &CtbRawFile::tell)
-        .def("master", &CtbRawFile::master)
+py::class_<CtbRawFile>(m, "CtbRawFile")
+    .def(py::init<const std::filesystem::path &>())
+    .def("read_frame",
+         [](CtbRawFile &self) {
+             size_t image_size = self.image_size_in_bytes();
+             py::array image;
+             std::vector<ssize_t> shape;
+             shape.reserve(2);
+             shape.push_back(1);
+             shape.push_back(image_size);
 
-        .def_property_readonly("image_size_in_bytes",
-                               &CtbRawFile::image_size_in_bytes)
+             py::array_t<DetectorHeader> header(1);
 
-        .def_property_readonly("frames_in_file", &CtbRawFile::frames_in_file);
+             // always read bytes
+             image = py::array_t<uint8_t>(shape);
 
-}
+             self.read_into(reinterpret_cast<std::byte *>(image.mutable_data()),
+                            header.mutable_data());
+
+             return py::make_tuple(header, image);
+         })
+    .def("seek", &CtbRawFile::seek)
+    .def("tell", &CtbRawFile::tell)
+    .def("master", &CtbRawFile::master)
+
+    .def_property_readonly("image_size_in_bytes",
+                           &CtbRawFile::image_size_in_bytes)
+
+    .def_property_readonly("frames_in_file", &CtbRawFile::frames_in_file);
+
+}

python/src/file.hpp

@@ -20,6 +20,9 @@
 namespace py = pybind11;
 using namespace ::aare;
 
+
+
+
 //Disable warnings for unused parameters, as we ignore some
 //in the __exit__ method
 #pragma GCC diagnostic push
@@ -195,7 +198,7 @@ void define_file_io_bindings(py::module &m) {
 
     py::class_<ROI>(m, "ROI")
         .def(py::init<>())
-        .def(py::init<int64_t, int64_t, int64_t, int64_t>(), py::arg("xmin"),
+        .def(py::init<ssize_t, ssize_t, ssize_t, ssize_t>(), py::arg("xmin"),
              py::arg("xmax"), py::arg("ymin"), py::arg("ymax"))
         .def_readwrite("xmin", &ROI::xmin)
         .def_readwrite("xmax", &ROI::xmax)
@@ -214,36 +217,9 @@ void define_file_io_bindings(py::module &m) {
     
 
 
-    py::class_<RawSubFile>(m, "RawSubFile")
-        .def(py::init<const std::filesystem::path &, DetectorType, size_t,
-                      size_t, size_t>())
-        .def_property_readonly("bytes_per_frame", &RawSubFile::bytes_per_frame)
-        .def_property_readonly("pixels_per_frame",
-                               &RawSubFile::pixels_per_frame)
-        .def("seek", &RawSubFile::seek)
-        .def("tell", &RawSubFile::tell)
-        .def_property_readonly("rows", &RawSubFile::rows)
-        .def_property_readonly("cols", &RawSubFile::cols)
-        .def("read_frame",
-             [](RawSubFile &self) {
-                 const uint8_t item_size = self.bytes_per_pixel();
-                 py::array image;
-                 std::vector<ssize_t> shape;
-                 shape.reserve(2);
-                 shape.push_back(self.rows());
-                 shape.push_back(self.cols());
-                 if (item_size == 1) {
-                     image = py::array_t<uint8_t>(shape);
-                 } else if (item_size == 2) {
-                     image = py::array_t<uint16_t>(shape);
-                 } else if (item_size == 4) {
-                     image = py::array_t<uint32_t>(shape);
-                 }
-                 fmt::print("item_size: {} rows: {} cols: {}\n", item_size, self.rows(), self.cols());
-                 self.read_into(
-                     reinterpret_cast<std::byte *>(image.mutable_data()));
-                 return image;
-             });
+
+
+
 
 #pragma GCC diagnostic pop
     // py::class_<ClusterHeader>(m, "ClusterHeader")

python/src/fit.hpp

@@ -55,6 +55,47 @@ void define_fit_bindings(py::module &m) {
         )",
         py::arg("x"), py::arg("par"));
 
+    m.def(
+        "scurve",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> par) {
+            auto x_view = make_view_1d(x);
+            auto par_view = make_view_1d(par);
+            auto y = new NDArray<double, 1>{aare::func::scurve(x_view, par_view)};
+            return return_image_data(y);
+        },
+        R"(
+        Evaluate a 1D scurve function for all points in x using parameters par. 
+        
+        Parameters
+        ----------
+        x : array_like
+            The points at which to evaluate the scurve function.
+        par : array_like
+            The parameters of the scurve function. The first element is the background slope, the second element is the background intercept, the third element is the mean, the fourth element is the standard deviation, the fifth element is inflexion point count number, and the sixth element is C.     
+        )",
+        py::arg("x"), py::arg("par"));
+
+    m.def(
+        "scurve2",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> par) {
+            auto x_view = make_view_1d(x);
+            auto par_view = make_view_1d(par);
+            auto y = new NDArray<double, 1>{aare::func::scurve2(x_view, par_view)};
+            return return_image_data(y);
+        },
+        R"(
+        Evaluate a 1D scurve2 function for all points in x using parameters par. 
+        
+        Parameters
+        ----------
+        x : array_like
+            The points at which to evaluate the scurve function.
+        par : array_like
+            The parameters of the scurve2 function. The first element is the background slope, the second element is the background intercept, the third element is the mean, the fourth element is the standard deviation, the fifth element is inflexion point count number, and the sixth element is C.     
+        )",
+        py::arg("x"), py::arg("par"));
 
     m.def(
         "fit_gaus",
@@ -235,6 +276,180 @@ n_threads : int, optional
         R"(
 Fit a 1D polynomial to data with error estimates.
 
+Parameters
+----------
+x : array_like
+    The x values.
+y : array_like
+    The y values.
+y_err : array_like
+    The error in the y values.
+n_threads : int, optional
+    The number of threads to use. Default is 4.
+)",
+        py::arg("x"), py::arg("y"), py::arg("y_err"), py::arg("n_threads") = 4);
+
+//=========
+    m.def(
+        "fit_scurve",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y,
+           int n_threads) {
+            if (y.ndim() == 3) {
+                auto par = new NDArray<double, 3>{};
+
+                auto x_view = make_view_1d(x);
+                auto y_view = make_view_3d(y);
+                *par = aare::fit_scurve(x_view, y_view, n_threads);
+                return return_image_data(par);
+            } else if (y.ndim() == 1) {
+                auto par = new NDArray<double, 1>{};
+                auto x_view = make_view_1d(x);
+                auto y_view = make_view_1d(y);
+                *par = aare::fit_scurve(x_view, y_view);
+                return return_image_data(par);
+            } else {
+                throw std::runtime_error("Data must be 1D or 3D");
+            }
+        },
+        py::arg("x"), py::arg("y"), py::arg("n_threads") = 4);
+
+    m.def(
+        "fit_scurve",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y_err,
+           int n_threads) {
+            if (y.ndim() == 3) {
+                auto par = new NDArray<double, 3>({y.shape(0), y.shape(1), 6});
+
+                auto par_err =
+                    new NDArray<double, 3>({y.shape(0), y.shape(1), 6});
+
+                auto y_view = make_view_3d(y);
+                auto y_view_err = make_view_3d(y_err);
+                auto x_view = make_view_1d(x);
+
+                auto chi2 = new NDArray<double, 2>({y.shape(0), y.shape(1)});
+
+                aare::fit_scurve(x_view, y_view, y_view_err, par->view(),
+                               par_err->view(), chi2->view(), n_threads);
+                return py::dict("par"_a = return_image_data(par),
+                                "par_err"_a = return_image_data(par_err), 
+                                "chi2"_a = return_image_data(chi2),
+                                "Ndf"_a = y.shape(2) - 2);
+
+
+            } else if (y.ndim() == 1) {
+                auto par = new NDArray<double, 1>({2});
+                auto par_err = new NDArray<double, 1>({2});
+
+                auto y_view = make_view_1d(y);
+                auto y_view_err = make_view_1d(y_err);
+                auto x_view = make_view_1d(x);
+
+                double chi2 = 0;
+
+                aare::fit_scurve(x_view, y_view, y_view_err, par->view(),
+                               par_err->view(), chi2);
+                return py::dict("par"_a = return_image_data(par),
+                                "par_err"_a = return_image_data(par_err),
+                                "chi2"_a = chi2, "Ndf"_a = y.size() - 2);
+
+            } else {
+                throw std::runtime_error("Data must be 1D or 3D");
+            }
+        },
+        R"(
+Fit a 1D polynomial to data with error estimates.
+
+Parameters
+----------
+x : array_like
+    The x values.
+y : array_like
+    The y values.
+y_err : array_like
+    The error in the y values.
+n_threads : int, optional
+    The number of threads to use. Default is 4.
+)",
+        py::arg("x"), py::arg("y"), py::arg("y_err"), py::arg("n_threads") = 4);
+    
+
+    m.def(
+        "fit_scurve2",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y,
+           int n_threads) {
+            if (y.ndim() == 3) {
+                auto par = new NDArray<double, 3>{};
+
+                auto x_view = make_view_1d(x);
+                auto y_view = make_view_3d(y);
+                *par = aare::fit_scurve2(x_view, y_view, n_threads);
+                return return_image_data(par);
+            } else if (y.ndim() == 1) {
+                auto par = new NDArray<double, 1>{};
+                auto x_view = make_view_1d(x);
+                auto y_view = make_view_1d(y);
+                *par = aare::fit_scurve2(x_view, y_view);
+                return return_image_data(par);
+            } else {
+                throw std::runtime_error("Data must be 1D or 3D");
+            }
+        },
+        py::arg("x"), py::arg("y"), py::arg("n_threads") = 4);
+
+    m.def(
+        "fit_scurve2",
+        [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y,
+           py::array_t<double, py::array::c_style | py::array::forcecast> y_err,
+           int n_threads) {
+            if (y.ndim() == 3) {
+                auto par = new NDArray<double, 3>({y.shape(0), y.shape(1), 6});
+
+                auto par_err =
+                    new NDArray<double, 3>({y.shape(0), y.shape(1), 6});
+
+                auto y_view = make_view_3d(y);
+                auto y_view_err = make_view_3d(y_err);
+                auto x_view = make_view_1d(x);
+
+                auto chi2 = new NDArray<double, 2>({y.shape(0), y.shape(1)});
+
+                aare::fit_scurve2(x_view, y_view, y_view_err, par->view(),
+                               par_err->view(), chi2->view(), n_threads);
+                return py::dict("par"_a = return_image_data(par),
+                                "par_err"_a = return_image_data(par_err), 
+                                "chi2"_a = return_image_data(chi2),
+                                "Ndf"_a = y.shape(2) - 2);
+
+
+            } else if (y.ndim() == 1) {
+                auto par = new NDArray<double, 1>({6});
+                auto par_err = new NDArray<double, 1>({6});
+
+                auto y_view = make_view_1d(y);
+                auto y_view_err = make_view_1d(y_err);
+                auto x_view = make_view_1d(x);
+
+                double chi2 = 0;
+
+                aare::fit_scurve2(x_view, y_view, y_view_err, par->view(),
+                               par_err->view(), chi2);
+                return py::dict("par"_a = return_image_data(par),
+                                "par_err"_a = return_image_data(par_err),
+                                "chi2"_a = chi2, "Ndf"_a = y.size() - 2);
+
+            } else {
+                throw std::runtime_error("Data must be 1D or 3D");
+            }
+        },
+        R"(
+Fit a 1D polynomial to data with error estimates.
+
 Parameters
 ----------
 x : array_like

python/src/module.cpp

@@ -1,16 +1,21 @@
 // Files with bindings to the different classes
+
+//New style file naming
+#include "bind_ClusterVector.hpp"
+
+//TODO! migrate the other names
 #include "cluster.hpp"
 #include "cluster_file.hpp"
 #include "ctb_raw_file.hpp"
 #include "file.hpp"
 #include "fit.hpp"
 #include "interpolation.hpp"
-#include "pedestal.hpp"
-#include "pixel_map.hpp"
-#include "raw_file.hpp"
+#include "raw_sub_file.hpp"
 #include "raw_master_file.hpp"
+#include "raw_file.hpp"
+#include "pixel_map.hpp"
 #include "var_cluster.hpp"
-
+#include "pedestal.hpp"
 #include "jungfrau_data_file.hpp"
 
 // Pybind stuff
@@ -22,6 +27,7 @@ namespace py = pybind11;
 PYBIND11_MODULE(_aare, m) {
     define_file_io_bindings(m);
     define_raw_file_io_bindings(m);
+    define_raw_sub_file_io_bindings(m);
     define_ctb_raw_file_io_bindings(m);
     define_raw_master_file_bindings(m);
     define_var_cluster_finder_bindings(m);
@@ -39,12 +45,12 @@ PYBIND11_MODULE(_aare, m) {
     define_cluster_file_io_bindings<float, 2, 2, uint16_t>(m, "Cluster2x2f");
     define_cluster_file_io_bindings<double, 2, 2, uint16_t>(m, "Cluster2x2d");
 
-    define_cluster_vector<int, 3, 3, uint16_t>(m, "Cluster3x3i");
-    define_cluster_vector<double, 3, 3, uint16_t>(m, "Cluster3x3d");
-    define_cluster_vector<float, 3, 3, uint16_t>(m, "Cluster3x3f");
-    define_cluster_vector<int, 2, 2, uint16_t>(m, "Cluster2x2i");
-    define_cluster_vector<double, 2, 2, uint16_t>(m, "Cluster2x2d");
-    define_cluster_vector<float, 2, 2, uint16_t>(m, "Cluster2x2f");
+    define_ClusterVector<int, 3, 3, uint16_t>(m, "Cluster3x3i");
+    define_ClusterVector<double, 3, 3, uint16_t>(m, "Cluster3x3d");
+    define_ClusterVector<float, 3, 3, uint16_t>(m, "Cluster3x3f");
+    define_ClusterVector<int, 2, 2, uint16_t>(m, "Cluster2x2i");
+    define_ClusterVector<double, 2, 2, uint16_t>(m, "Cluster2x2d");
+    define_ClusterVector<float, 2, 2, uint16_t>(m, "Cluster2x2f");
 
     define_cluster_finder_bindings<int, 3, 3, uint16_t>(m, "Cluster3x3i");
     define_cluster_finder_bindings<double, 3, 3, uint16_t>(m, "Cluster3x3d");

python/src/np_helper.hpp

@@ -13,7 +13,7 @@ namespace py = pybind11;
 using namespace aare;
 
 // Pass image data back to python as a numpy array
-template <typename T, int64_t Ndim>
+template <typename T, ssize_t Ndim>
 py::array return_image_data(aare::NDArray<T, Ndim> *image) {
 
     py::capsule free_when_done(image, [](void *f) {

python/src/raw_file.hpp

@@ -32,7 +32,7 @@ void define_raw_file_io_bindings(py::module &m) {
                  shape.push_back(self.cols());
 
                  // return headers from all subfiles
-                 py::array_t<DetectorHeader> header(self.n_mod());
+                 py::array_t<DetectorHeader> header(self.n_modules());
 
                  const uint8_t item_size = self.bytes_per_pixel();
                  if (item_size == 1) {
@@ -61,10 +61,10 @@ void define_raw_file_io_bindings(py::module &m) {
             
                 // return headers from all subfiles
                 py::array_t<DetectorHeader> header;
-                if (self.n_mod() == 1) {
+                if (self.n_modules() == 1) {
                     header = py::array_t<DetectorHeader>(n_frames);
                 } else {
-                    header = py::array_t<DetectorHeader>({self.n_mod(), n_frames});
+                    header = py::array_t<DetectorHeader>({self.n_modules(), n_frames});
                 }
                 // py::array_t<DetectorHeader> header({self.n_mod(), n_frames});
 
@@ -100,7 +100,7 @@ void define_raw_file_io_bindings(py::module &m) {
         .def_property_readonly("cols", &RawFile::cols)
         .def_property_readonly("bitdepth", &RawFile::bitdepth)
         .def_property_readonly("geometry", &RawFile::geometry)
-        .def_property_readonly("n_mod", &RawFile::n_mod)
+        .def_property_readonly("n_modules", &RawFile::n_modules)
         .def_property_readonly("detector_type", &RawFile::detector_type)
         .def_property_readonly("master", &RawFile::master);
 }

python/src/raw_sub_file.hpp

@@ -0,0 +1,110 @@
+#include "aare/CtbRawFile.hpp"
+#include "aare/File.hpp"
+#include "aare/Frame.hpp"
+#include "aare/RawFile.hpp"
+#include "aare/RawMasterFile.hpp"
+#include "aare/RawSubFile.hpp"
+
+#include "aare/defs.hpp"
+// #include "aare/fClusterFileV2.hpp"
+
+#include <cstdint>
+#include <filesystem>
+#include <pybind11/iostream.h>
+#include <pybind11/numpy.h>
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <pybind11/stl/filesystem.h>
+#include <string>
+
+namespace py = pybind11;
+using namespace ::aare;
+
+auto read_frame_from_RawSubFile(RawSubFile &self) {
+    py::array_t<DetectorHeader> header(1);
+    const uint8_t item_size = self.bytes_per_pixel();
+    std::vector<ssize_t> shape{static_cast<ssize_t>(self.rows()),
+        static_cast<ssize_t>(self.cols())};
+    
+    py::array image;
+    if (item_size == 1) {
+        image = py::array_t<uint8_t>(shape);
+    } else if (item_size == 2) {
+        image = py::array_t<uint16_t>(shape);
+    } else if (item_size == 4) {
+        image = py::array_t<uint32_t>(shape);
+    }
+    self.read_into(reinterpret_cast<std::byte *>(image.mutable_data()),
+                   header.mutable_data());
+
+    return py::make_tuple(header, image);
+}
+
+auto read_n_frames_from_RawSubFile(RawSubFile &self, size_t n_frames) {
+    py::array_t<DetectorHeader> header(n_frames);
+    const uint8_t item_size = self.bytes_per_pixel();
+    std::vector<ssize_t> shape{
+        static_cast<ssize_t>(n_frames), 
+        static_cast<ssize_t>(self.rows()),
+        static_cast<ssize_t>(self.cols())
+    };
+    
+    py::array image;
+    if (item_size == 1) {
+        image = py::array_t<uint8_t>(shape);
+    } else if (item_size == 2) {
+        image = py::array_t<uint16_t>(shape);
+    } else if (item_size == 4) {
+        image = py::array_t<uint32_t>(shape);
+    }
+    self.read_into(reinterpret_cast<std::byte *>(image.mutable_data()), n_frames,
+                   header.mutable_data());
+
+    return py::make_tuple(header, image);
+}
+
+
+//Disable warnings for unused parameters, as we ignore some
+//in the __exit__ method
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
+
+void define_raw_sub_file_io_bindings(py::module &m) {
+    py::class_<RawSubFile>(m, "RawSubFile")
+        .def(py::init<const std::filesystem::path &, DetectorType, size_t,
+                      size_t, size_t>())
+        .def_property_readonly("bytes_per_frame", &RawSubFile::bytes_per_frame)
+        .def_property_readonly("pixels_per_frame",
+                               &RawSubFile::pixels_per_frame)
+        .def_property_readonly("bytes_per_pixel", &RawSubFile::bytes_per_pixel)                    
+        .def("seek", &RawSubFile::seek)
+        .def("tell", &RawSubFile::tell)
+        .def_property_readonly("rows", &RawSubFile::rows)
+        .def_property_readonly("cols", &RawSubFile::cols)
+        .def_property_readonly("frames_in_file", &RawSubFile::frames_in_file)
+        .def("read_frame", &read_frame_from_RawSubFile)
+        .def("read_n", &read_n_frames_from_RawSubFile)
+        .def("read", [](RawSubFile &self){
+            self.seek(0);
+            auto n_frames = self.frames_in_file();
+            return read_n_frames_from_RawSubFile(self, n_frames);
+        })
+        .def("__enter__", [](RawSubFile &self) { return &self; })
+        .def("__exit__",
+             [](RawSubFile &self,
+                const std::optional<pybind11::type> &exc_type,
+                const std::optional<pybind11::object> &exc_value,
+                const std::optional<pybind11::object> &traceback) {
+             })
+        .def("__iter__", [](RawSubFile &self) { return &self; })
+        .def("__next__", [](RawSubFile &self) {
+            try {
+                return read_frame_from_RawSubFile(self);
+            } catch (std::runtime_error &e) {
+                throw py::stop_iteration();
+            }
+        });
+
+}
+
+#pragma GCC diagnostic pop

python/tests/test_Cluster.py

@@ -1,12 +1,12 @@
 import pytest 
 import numpy as np
 
-import aare._aare as aare
+from aare import _aare #import the C++ module
 from conftest import test_data_path
 
 
 def test_cluster_vector_can_be_converted_to_numpy():
-    cv = aare.ClusterVector_Cluster3x3i()
+    cv = _aare.ClusterVector_Cluster3x3i()
     arr = np.array(cv, copy=False)
     assert arr.shape == (0,)  # 4 for x, y, size, energy and 9 for the cluster data
 
@@ -14,24 +14,23 @@ def test_cluster_vector_can_be_converted_to_numpy():
 def test_ClusterVector(): 
     """Test ClusterVector""" 
 
-    clustervector = aare.ClusterVector_Cluster3x3i()
+    clustervector = _aare.ClusterVector_Cluster3x3i()
     assert clustervector.cluster_size_x == 3
     assert clustervector.cluster_size_y == 3
     assert clustervector.item_size() == 4+9*4
     assert clustervector.frame_number == 0
-    assert clustervector.capacity == 1024
     assert clustervector.size == 0
 
-    cluster = aare.Cluster3x3i(0,0,np.ones(9, dtype=np.int32))
+    cluster = _aare.Cluster3x3i(0,0,np.ones(9, dtype=np.int32))
     
     clustervector.push_back(cluster) 
     assert clustervector.size == 1
 
     with pytest.raises(TypeError):  # Or use the appropriate exception type
-        clustervector.push_back(aare.Cluster2x2i(0,0,np.ones(4, dtype=np.int32)))
+        clustervector.push_back(_aare.Cluster2x2i(0,0,np.ones(4, dtype=np.int32)))
 
     with pytest.raises(TypeError): 
-        clustervector.push_back(aare.Cluster3x3f(0,0,np.ones(9, dtype=np.float32))) 
+        clustervector.push_back(_aare.Cluster3x3f(0,0,np.ones(9, dtype=np.float32))) 
 
 def test_Interpolator(): 
     """Test Interpolator"""
@@ -41,13 +40,13 @@ def test_Interpolator():
     ybins = np.linspace(0, 5, 30, dtype=np.float64)
 
     etacube = np.zeros(shape=[30, 30, 20], dtype=np.float64)
-    interpolator = aare.Interpolator(etacube, xbins, ybins, ebins)
+    interpolator = _aare.Interpolator(etacube, xbins, ybins, ebins)
 
     assert interpolator.get_ietax().shape == (30,30,20)
     assert interpolator.get_ietay().shape == (30,30,20)
-    clustervector = aare.ClusterVector_Cluster3x3i()
+    clustervector = _aare.ClusterVector_Cluster3x3i()
     
-    cluster = aare.Cluster3x3i(0,0, np.ones(9, dtype=np.int32))
+    cluster = _aare.Cluster3x3i(0,0, np.ones(9, dtype=np.int32))
     clustervector.push_back(cluster) 
 
     interpolated_photons = interpolator.interpolate(clustervector)
@@ -58,9 +57,9 @@ def test_Interpolator():
     assert interpolated_photons[0]["y"] == -1
     assert interpolated_photons[0]["energy"] == 4 #eta_sum = 4, dx, dy = -1,-1 m_ietax = 0, m_ietay = 0
 
-    clustervector = aare.ClusterVector_Cluster2x2i()
+    clustervector = _aare.ClusterVector_Cluster2x2i()
 
-    cluster = aare.Cluster2x2i(0,0, np.ones(4, dtype=np.int32))
+    cluster = _aare.Cluster2x2i(0,0, np.ones(4, dtype=np.int32))
     clustervector.push_back(cluster) 
 
     interpolated_photons = interpolator.interpolate(clustervector)
@@ -71,28 +70,15 @@ def test_Interpolator():
     assert interpolated_photons[0]["y"] == 0
     assert interpolated_photons[0]["energy"] == 4
 
-@pytest.mark.files
-def test_cluster_file(test_data_path): 
-    """Test ClusterFile""" 
-    cluster_file = aare.ClusterFile_Cluster3x3i(test_data_path / "clust/single_frame_97_clustrers.clust") 
-    clustervector = cluster_file.read_clusters(10) #conversion does not work
 
-    cluster_file.close()
-
-    assert clustervector.size == 10
-
-    ###reading with wrong file
-    with pytest.raises(TypeError): 
-        cluster_file = aare.ClusterFile_Cluster2x2i(test_data_path / "clust/single_frame_97_clustrers.clust") 
-        cluster_file.close()
 
 def test_calculate_eta(): 
     """Calculate Eta""" 
-    clusters = aare.ClusterVector_Cluster3x3i() 
-    clusters.push_back(aare.Cluster3x3i(0,0, np.ones(9, dtype=np.int32)))
-    clusters.push_back(aare.Cluster3x3i(0,0, np.array([1,1,1,2,2,2,3,3,3])))
+    clusters = _aare.ClusterVector_Cluster3x3i() 
+    clusters.push_back(_aare.Cluster3x3i(0,0, np.ones(9, dtype=np.int32)))
+    clusters.push_back(_aare.Cluster3x3i(0,0, np.array([1,1,1,2,2,2,3,3,3])))
 
-    eta2 = aare.calculate_eta2(clusters)
+    eta2 = _aare.calculate_eta2(clusters)
 
     assert eta2.shape == (2,2)
     assert eta2[0,0] == 0.5
@@ -103,7 +89,7 @@ def test_calculate_eta():
 def test_cluster_finder(): 
     """Test ClusterFinder""" 
 
-    clusterfinder = aare.ClusterFinder_Cluster3x3i([100,100])
+    clusterfinder = _aare.ClusterFinder_Cluster3x3i([100,100])
 
     #frame = np.random.rand(100,100)
     frame = np.zeros(shape=[100,100])
@@ -115,18 +101,7 @@ def test_cluster_finder():
     assert clusters.size == 0
 
 
-#TODO dont understand behavior
-def test_cluster_collector(): 
-    """Test ClusterCollector"""
-
-    clusterfinder = aare.ClusterFinderMT_Cluster3x3i([100,100]) #TODO: no idea what the data is in InputQueue not zero 
-
-    clustercollector = aare.ClusterCollector_Cluster3x3i(clusterfinder)
-
-    cluster_vectors = clustercollector.steal_clusters()
-
-    assert len(cluster_vectors) == 1 #single thread execution
-    assert cluster_vectors[0].size == 0 #
+
 
 
 

python/tests/test_ClusterFile.py

@@ -0,0 +1,64 @@
+
+import pytest 
+import numpy as np
+import boost_histogram as bh
+import time
+from pathlib import Path
+import pickle
+
+from aare import ClusterFile
+from conftest import test_data_path
+
+@pytest.mark.files
+def test_cluster_file(test_data_path): 
+    """Test ClusterFile""" 
+    f =  ClusterFile(test_data_path / "clust/single_frame_97_clustrers.clust") 
+    cv = f.read_clusters(10) #conversion does not work
+
+
+    assert cv.frame_number == 135
+    assert cv.size == 10
+
+    #Known data 
+    #frame_number, num_clusters   [135] 97
+    #[  1 200] [0 1 2 3 4 5 6 7 8]
+    #[  2 201] [ 9 10 11 12 13 14 15 16 17]
+    #[  3 202] [18 19 20 21 22 23 24 25 26]
+    #[  4 203] [27 28 29 30 31 32 33 34 35]
+    #[  5 204] [36 37 38 39 40 41 42 43 44]
+    #[  6 205] [45 46 47 48 49 50 51 52 53]
+    #[  7 206] [54 55 56 57 58 59 60 61 62]
+    #[  8 207] [63 64 65 66 67 68 69 70 71]
+    #[  9 208] [72 73 74 75 76 77 78 79 80]
+    #[ 10 209] [81 82 83 84 85 86 87 88 89]
+
+    #conversion to numpy array
+    arr = np.array(cv, copy = False)
+    
+    assert arr.size == 10
+    for i in range(10):
+        assert arr[i]['x'] == i+1
+
+@pytest.mark.files
+def test_read_clusters_and_fill_histogram(test_data_path): 
+    # Create the histogram
+    n_bins = 100
+    xmin = -100
+    xmax = 1e4
+    hist_aare = bh.Histogram(bh.axis.Regular(n_bins, xmin, xmax))
+
+    fname = test_data_path / "clust/beam_En700eV_-40deg_300V_10us_d0_f0_100.clust"
+
+    #Read clusters and fill the histogram with pixel values
+    with ClusterFile(fname, chunk_size = 10000) as f:
+        for clusters in f:
+            arr = np.array(clusters, copy = False)
+            hist_aare.fill(arr['data'].flat)
+
+
+    #Load the histogram from the pickle file
+    with open(fname.with_suffix('.pkl'), 'rb') as f:
+        hist_py = pickle.load(f)
+        
+    #Compare the two histograms
+    assert hist_aare == hist_py

python/tests/test_ClusterVector.py

@@ -0,0 +1,54 @@
+import pytest 
+import numpy as np
+import boost_histogram as bh
+import time
+from pathlib import Path
+import pickle
+
+from aare import ClusterFile
+from aare import _aare
+from conftest import test_data_path
+
+
+def test_create_cluster_vector():
+    cv = _aare.ClusterVector_Cluster3x3i()
+    assert cv.cluster_size_x == 3
+    assert cv.cluster_size_y == 3
+    assert cv.size == 0
+
+
+def test_push_back_on_cluster_vector():
+    cv = _aare.ClusterVector_Cluster2x2i()
+    assert cv.cluster_size_x == 2
+    assert cv.cluster_size_y == 2
+    assert cv.size == 0
+
+    cluster = _aare.Cluster2x2i(19, 22, np.ones(4, dtype=np.int32))
+    cv.push_back(cluster)
+    assert cv.size == 1
+
+    arr = np.array(cv, copy=False)
+    assert arr[0]['x'] == 19
+    assert arr[0]['y'] == 22
+
+
+def test_make_a_hitmap_from_cluster_vector():
+    cv = _aare.ClusterVector_Cluster3x3i()
+
+    # Push back 4 clusters with different positions
+    cv.push_back(_aare.Cluster3x3i(0, 0, np.ones(9, dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(1, 1, np.ones(9, dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(1, 1, np.ones(9, dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(2, 2, np.ones(9, dtype=np.int32)))
+
+    ref = np.zeros((5, 5), dtype=np.int32)
+    ref[0,0] = 1
+    ref[1,1] = 2
+    ref[2,2] = 1
+
+
+    img = _aare.hitmap((5,5), cv)
+    # print(img)
+    # print(ref)
+    assert (img == ref).all()
+    

python/tests/test_RawSubFile.py

@@ -0,0 +1,39 @@
+import pytest
+import numpy as np
+from aare import RawSubFile, DetectorType
+
+
+@pytest.mark.files
+def test_read_a_jungfrau_RawSubFile(test_data_path):
+
+    # Starting with f1 there is now 7 frames left in the series of files
+    with RawSubFile(test_data_path / "raw/jungfrau/jungfrau_single_d0_f1_0.raw", DetectorType.Jungfrau, 512, 1024, 16) as f:
+        assert f.frames_in_file == 7
+
+        headers, frames = f.read()
+
+    assert headers.size == 7
+    assert frames.shape == (7, 512, 1024)
+    
+
+    for i,h in zip(range(4,11,1), headers):
+        assert h["frameNumber"] == i
+
+    # Compare to canned data using numpy
+    data = np.load(test_data_path / "raw/jungfrau/jungfrau_single_0.npy")
+    assert np.all(data[3:] == frames)
+
+@pytest.mark.files
+def test_iterate_over_a_jungfrau_RawSubFile(test_data_path):
+
+    data = np.load(test_data_path / "raw/jungfrau/jungfrau_single_0.npy")
+
+    # Given the first subfile in a series we can read all frames from f0, f1, f2...fN
+    with RawSubFile(test_data_path / "raw/jungfrau/jungfrau_single_d0_f0_0.raw", DetectorType.Jungfrau, 512, 1024, 16) as f:
+        i = 0
+        for header, frame in f:
+            assert header["frameNumber"] == i+1
+            assert np.all(frame == data[i])
+            i += 1
+        assert i == 10
+        assert header["frameNumber"] == 10

src/CalculateEta.test.cpp

@@ -21,23 +21,35 @@ using ClusterTypes =
 auto get_test_parameters() {
     return GENERATE(
         std::make_tuple(ClusterTypes{Cluster<int, 2, 2>{0, 0, {1, 2, 3, 1}}},
-                        Eta2<int>{2. / 3, 3. / 4, corner::cBottomLeft, 7}),
+                        Eta2<int>{2. / 3, 3. / 4,
+                                  static_cast<int>(corner::cBottomLeft), 7}),
         std::make_tuple(
             ClusterTypes{Cluster<int, 3, 3>{0, 0, {1, 2, 3, 4, 5, 6, 1, 2, 7}}},
-            Eta2<int>{6. / 11, 2. / 7, corner::cTopRight, 20}),
+            Eta2<int>{6. / 11, 2. / 7, static_cast<int>(corner::cTopRight),
+                      20}),
         std::make_tuple(ClusterTypes{Cluster<int, 5, 5>{
-                            0, 0, {1, 6, 7, 6, 5, 4, 3, 2, 1, 8, 8, 9, 2,
+                            0, 0, {1, 6, 7, 6, 5, 4, 3, 2, 1, 2, 8, 9, 8,
                                    1, 4, 5, 6, 7, 8, 4, 1, 1, 1, 1, 1}}},
-                        Eta2<int>{9. / 17, 5. / 13, 8, 28}),
+                        Eta2<int>{8. / 17, 7. / 15, 9, 30}),
         std::make_tuple(
             ClusterTypes{Cluster<int, 4, 2>{0, 0, {1, 4, 7, 2, 5, 6, 4, 3}}},
-            Eta2<int>{7. / 11, 6. / 10, 1, 21}),
+            Eta2<int>{4. / 10, 4. / 11, 1, 21}),
         std::make_tuple(
             ClusterTypes{Cluster<int, 2, 3>{0, 0, {1, 3, 2, 3, 4, 2}}},
-            Eta2<int>{3. / 5, 4. / 6, 1, 11}));
+            Eta2<int>{3. / 5, 2. / 5, 1, 11}));
 }
 
-TEST_CASE("calculate_eta2", "[.eta_calculation]") {
+TEST_CASE("compute_largest_2x2_subcluster", "[eta_calculation]") {
+    auto [cluster, expected_eta] = get_test_parameters();
+
+    auto [sum, index] = std::visit(
+        [](const auto &clustertype) { return clustertype.max_sum_2x2(); },
+        cluster);
+    CHECK(expected_eta.c == index);
+    CHECK(expected_eta.sum == sum);
+}
+
+TEST_CASE("calculate_eta2", "[eta_calculation]") {
 
     auto [cluster, expected_eta] = get_test_parameters();
 
@@ -50,3 +62,66 @@ TEST_CASE("calculate_eta2", "[.eta_calculation]") {
     CHECK(eta.c == expected_eta.c);
     CHECK(eta.sum == expected_eta.sum);
 }
+
+// 3x3 cluster layout (rotated to match the cBottomLeft enum):
+//  6, 7, 8
+//  3, 4, 5
+//  0, 1, 2
+
+TEST_CASE("Calculate eta2 for a 3x3 int32 cluster with the largest 2x2 sum in "
+          "the bottom left",
+          "[eta_calculation]") {
+
+    // Create a 3x3 cluster
+    Cluster<int32_t, 3, 3> cl;
+    cl.x = 0;
+    cl.y = 0;
+    cl.data[0] = 30;
+    cl.data[1] = 23;
+    cl.data[2] = 5;
+    cl.data[3] = 20;
+    cl.data[4] = 50;
+    cl.data[5] = 3;
+    cl.data[6] = 8;
+    cl.data[7] = 2;
+    cl.data[8] = 3;
+
+    // 8, 2, 3
+    // 20, 50, 3
+    // 30, 23, 5
+
+    auto eta = calculate_eta2(cl);
+    CHECK(eta.c == static_cast<int>(corner::cBottomLeft));
+    CHECK(eta.x == 50.0 / (20 + 50)); // 4/(3+4)
+    CHECK(eta.y == 50.0 / (23 + 50)); // 4/(1+4)
+    CHECK(eta.sum == 30 + 23 + 20 + 50);
+}
+
+TEST_CASE("Calculate eta2 for a 3x3 int32 cluster with the largest 2x2 sum in "
+          "the top left",
+          "[eta_calculation]") {
+
+    // Create a 3x3 cluster
+    Cluster<int32_t, 3, 3> cl;
+    cl.x = 0;
+    cl.y = 0;
+    cl.data[0] = 8;
+    cl.data[1] = 12;
+    cl.data[2] = 5;
+    cl.data[3] = 77;
+    cl.data[4] = 80;
+    cl.data[5] = 3;
+    cl.data[6] = 82;
+    cl.data[7] = 91;
+    cl.data[8] = 3;
+
+    // 82, 91, 3
+    // 77, 80, 3
+    // 8, 12, 5
+
+    auto eta = calculate_eta2(cl);
+    CHECK(eta.c == static_cast<int>(corner::cTopLeft));
+    CHECK(eta.x == 80. / (77 + 80));  // 4/(3+4)
+    CHECK(eta.y == 91.0 / (91 + 80)); // 7/(7+4)
+    CHECK(eta.sum == 77 + 80 + 82 + 91);
+}

src/Cluster.test.cpp

@@ -14,61 +14,8 @@
 
 using namespace aare;
 
-TEST_CASE("Correct Instantiation of Cluster and ClusterVector",
-          "[.cluster][.instantiation]") {
-
-    CHECK(is_valid_cluster<double, 3, 3>);
-    CHECK(is_valid_cluster<double, 3, 2>);
-    CHECK(not is_valid_cluster<int, 0, 0>);
-    CHECK(not is_valid_cluster<std::string, 2, 2>);
-    CHECK(not is_valid_cluster<int, 2, 2, double>);
-
-    CHECK(not is_cluster_v<int>);
-    CHECK(is_cluster_v<Cluster<int, 3, 3>>);
-}
-<<<<<<< Updated upstream
-=======
-
-using ClusterTypes =
-    std::variant<Cluster<int, 2, 2>, Cluster<int, 3, 3>, Cluster<int, 5, 5>,
-                 Cluster<int, 4, 2>, Cluster<int, 2, 3>>;
-
-auto get_test_sum_parameters() {
-    return GENERATE(
-        std::make_tuple(ClusterTypes{Cluster<int, 2, 2>{0, 0, {1, 2, 3, 1}}},
-                        std::make_pair(7, 0)),
-        std::make_tuple(
-            ClusterTypes{Cluster<int, 3, 3>{0, 0, {1, 2, 3, 4, 5, 6, 1, 2, 7}}},
-            std::make_pair(20, 3)),
-        std::make_tuple(ClusterTypes{Cluster<int, 5, 5>{
-                            0, 0, {1, 6, 7, 6, 5, 4, 3, 2, 1, 8, 8, 9, 2,
-                                   1, 4, 5, 6, 7, 8, 4, 1, 1, 1, 1, 1}}},
-                        std::make_pair(28, 8)),
-        std::make_tuple(
-            ClusterTypes{Cluster<int, 4, 2>{0, 0, {1, 4, 7, 2, 5, 6, 4, 3}}},
-            std::make_pair(21, 1)),
-        std::make_tuple(
-            ClusterTypes{Cluster<int, 2, 3>{0, 0, {1, 3, 2, 3, 4, 2}}},
-            std::make_pair(11, 1)));
-}
-
-TEST_CASE("compute_largest_2x2_subcluster", "[.cluster]") {
-    auto [cluster, sum_pair] = get_test_sum_parameters();
-
-    auto sum = std::visit(
-        [](const auto &clustertype) { return clustertype.max_sum_2x2(); },
-        cluster);
-    CHECK(sum_pair.first == sum.first);
-    CHECK(sum_pair.second == sum.second);
-}
-
 TEST_CASE("Test sum of Cluster", "[.cluster]") {
     Cluster<int, 2, 2> cluster{0, 0, {1, 2, 3, 4}};
 
     CHECK(cluster.sum() == 10);
-
-    Cluster<int, 2, 3> cluster2x3{0, 0, {1, 3, 2, 3, 4, 2}};
-
-    CHECK(cluster2x3.sum() == 15);
-}
->>>>>>> Stashed changes
+}

src/ClusterFile.cpp

@@ -0,0 +1,402 @@
+#include "aare/ClusterFile.hpp"
+
+#include <algorithm>
+
+namespace aare {
+
+ClusterFile::ClusterFile(const std::filesystem::path &fname, size_t chunk_size,
+                         const std::string &mode)
+    : m_chunk_size(chunk_size), m_mode(mode) {
+
+    if (mode == "r") {
+        fp = fopen(fname.c_str(), "rb");
+        if (!fp) {
+            throw std::runtime_error("Could not open file for reading: " +
+                                     fname.string());
+        }
+    } else if (mode == "w") {
+        fp = fopen(fname.c_str(), "wb");
+        if (!fp) {
+            throw std::runtime_error("Could not open file for writing: " +
+                                     fname.string());
+        }
+    } else if (mode == "a") {
+        fp = fopen(fname.c_str(), "ab");
+        if (!fp) {
+            throw std::runtime_error("Could not open file for appending: " +
+                                     fname.string());
+        }
+    } else {
+        throw std::runtime_error("Unsupported mode: " + mode);
+    }
+}
+
+void ClusterFile::set_roi(ROI roi){
+    m_roi = roi;
+}
+
+void ClusterFile::set_noise_map(const NDView<int32_t, 2> noise_map){
+    m_noise_map = NDArray<int32_t, 2>(noise_map);
+}
+
+void ClusterFile::set_gain_map(const NDView<double, 2> gain_map){
+    m_gain_map = NDArray<double, 2>(gain_map);
+    
+    // Gain map is passed as ADU/keV to avoid dividing in when applying the gain
+    // map we invert it here
+    for (auto &item : m_gain_map->view()) {
+        item = 1.0 / item;
+    }
+}
+
+ClusterFile::~ClusterFile() { close(); }
+
+void ClusterFile::close() {
+    if (fp) {
+        fclose(fp);
+        fp = nullptr;
+    }
+}
+
+void ClusterFile::write_frame(const ClusterVector<int32_t> &clusters) {
+    if (m_mode != "w" && m_mode != "a") {
+        throw std::runtime_error("File not opened for writing");
+    }
+    if (!(clusters.cluster_size_x() == 3) &&
+        !(clusters.cluster_size_y() == 3)) {
+        throw std::runtime_error("Only 3x3 clusters are supported");
+    }
+    //First write the frame number - 4 bytes
+    int32_t frame_number = clusters.frame_number();
+    if(fwrite(&frame_number, sizeof(frame_number), 1, fp)!=1){
+        throw std::runtime_error(LOCATION + "Could not write frame number");
+    }
+
+    //Then write the number of clusters - 4 bytes
+    uint32_t n_clusters = clusters.size();
+    if(fwrite(&n_clusters, sizeof(n_clusters), 1, fp)!=1){
+        throw std::runtime_error(LOCATION + "Could not write number of clusters");
+    }
+
+    //Now write the clusters in the frame
+    if(fwrite(clusters.data(), clusters.item_size(), clusters.size(), fp)!=clusters.size()){
+        throw std::runtime_error(LOCATION + "Could not write clusters");
+    }
+}
+
+
+ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters){
+    if (m_mode != "r") {
+        throw std::runtime_error("File not opened for reading");
+    }
+    if (m_noise_map || m_roi){
+        return read_clusters_with_cut(n_clusters);
+    }else{
+        return read_clusters_without_cut(n_clusters);
+    }
+}
+
+ClusterVector<int32_t> ClusterFile::read_clusters_without_cut(size_t n_clusters) {
+    if (m_mode != "r") {
+        throw std::runtime_error("File not opened for reading");
+    }
+    
+    ClusterVector<int32_t> clusters(3,3, n_clusters);
+
+    int32_t iframe = 0; // frame number needs to be 4 bytes!
+    size_t nph_read = 0;
+    uint32_t nn = m_num_left;
+    uint32_t nph = m_num_left; // number of clusters in frame needs to be 4
+
+    // auto buf = reinterpret_cast<Cluster3x3 *>(clusters.data());
+    auto buf = clusters.data();
+    // if there are photons left from previous frame read them first
+    if (nph) {
+        if (nph > n_clusters) {
+            // if we have more photons left in the frame then photons to read we
+            // read directly the requested number
+            nn = n_clusters;
+        } else {
+            nn = nph;
+        }
+        nph_read += fread((buf + nph_read*clusters.item_size()),
+                          clusters.item_size(), nn, fp);
+        m_num_left = nph - nn; // write back the number of photons left
+    }
+
+    if (nph_read < n_clusters) {
+        // keep on reading frames and photons until reaching n_clusters
+        while (fread(&iframe, sizeof(iframe), 1, fp)) {
+            clusters.set_frame_number(iframe);
+            // read number of clusters in frame
+            if (fread(&nph, sizeof(nph), 1, fp)) {
+                if (nph > (n_clusters - nph_read))
+                    nn = n_clusters - nph_read;
+                else
+                    nn = nph;
+
+                nph_read += fread((buf + nph_read*clusters.item_size()),
+                                  clusters.item_size(), nn, fp);
+                m_num_left = nph - nn;
+            }
+            if (nph_read >= n_clusters)
+                break;
+        }
+    }
+
+    // Resize the vector to the number of clusters.
+    // No new allocation, only change bounds.
+    clusters.resize(nph_read);
+    if(m_gain_map)
+        clusters.apply_gain_map(m_gain_map->view());
+    return clusters;
+}
+
+
+ClusterVector<int32_t> ClusterFile::read_clusters_with_cut(size_t n_clusters) {
+    ClusterVector<int32_t> clusters(3,3);
+    clusters.reserve(n_clusters);
+
+    // if there are photons left from previous frame read them first
+    if (m_num_left) {
+        while(m_num_left && clusters.size() < n_clusters){
+            Cluster3x3 c = read_one_cluster();
+            if(is_selected(c)){
+                clusters.push_back(c.x, c.y, reinterpret_cast<std::byte*>(c.data));
+            }
+        }
+    }
+
+    // we did not have enough clusters left in the previous frame
+    // keep on reading frames until reaching n_clusters
+    if (clusters.size() < n_clusters) {
+        // sanity check
+        if (m_num_left) {
+            throw std::runtime_error(LOCATION + "Entered second loop with clusters left\n");
+        }
+        
+        int32_t frame_number = 0; // frame number needs to be 4 bytes!
+        while (fread(&frame_number, sizeof(frame_number), 1, fp)) {
+            if (fread(&m_num_left, sizeof(m_num_left), 1, fp)) {
+                clusters.set_frame_number(frame_number); //cluster vector will hold the last frame number
+                while(m_num_left && clusters.size() < n_clusters){
+                    Cluster3x3 c = read_one_cluster();
+                    if(is_selected(c)){
+                        clusters.push_back(c.x, c.y, reinterpret_cast<std::byte*>(c.data));
+                    }
+                }
+            }
+
+            // we have enough clusters, break out of the outer while loop
+            if (clusters.size() >= n_clusters)
+                break;
+        }
+
+    }
+    if(m_gain_map)
+        clusters.apply_gain_map(m_gain_map->view());
+
+    return clusters;
+}
+
+Cluster3x3 ClusterFile::read_one_cluster(){
+    Cluster3x3 c;
+    auto rc = fread(&c, sizeof(c), 1, fp);
+    if (rc != 1) {
+        throw std::runtime_error(LOCATION + "Could not read cluster");
+    }
+    --m_num_left;
+    return c;
+}
+
+ClusterVector<int32_t> ClusterFile::read_frame(){
+    if (m_mode != "r") {
+        throw std::runtime_error(LOCATION + "File not opened for reading");
+    }
+    if (m_noise_map || m_roi){
+        return read_frame_with_cut();
+    }else{
+        return read_frame_without_cut();
+    }
+}
+
+ClusterVector<int32_t> ClusterFile::read_frame_without_cut() {
+    if (m_mode != "r") {
+        throw std::runtime_error("File not opened for reading");
+    }
+    if (m_num_left) {
+        throw std::runtime_error(
+            "There are still photons left in the last frame");
+    }
+    int32_t frame_number;
+    if (fread(&frame_number, sizeof(frame_number), 1, fp) != 1) {
+        throw std::runtime_error(LOCATION + "Could not read frame number");
+    }
+
+    int32_t n_clusters; // Saved as 32bit integer in the cluster file
+    if (fread(&n_clusters, sizeof(n_clusters), 1, fp) != 1) {
+        throw std::runtime_error(LOCATION + "Could not read number of clusters");
+    }
+
+    ClusterVector<int32_t> clusters(3, 3, n_clusters);
+    clusters.set_frame_number(frame_number);
+
+    if (fread(clusters.data(), clusters.item_size(), n_clusters, fp) !=
+        static_cast<size_t>(n_clusters)) {
+        throw std::runtime_error(LOCATION + "Could not read clusters");
+    }
+    clusters.resize(n_clusters);
+    if (m_gain_map)
+        clusters.apply_gain_map(m_gain_map->view());
+    return clusters;
+}
+
+ClusterVector<int32_t> ClusterFile::read_frame_with_cut() {
+    if (m_mode != "r") {
+        throw std::runtime_error("File not opened for reading");
+    }
+    if (m_num_left) {
+        throw std::runtime_error(
+            "There are still photons left in the last frame");
+    }
+    int32_t frame_number;
+    if (fread(&frame_number, sizeof(frame_number), 1, fp) != 1) {
+        throw std::runtime_error("Could not read frame number");
+    }
+
+
+    if (fread(&m_num_left, sizeof(m_num_left), 1, fp) != 1) {
+        throw std::runtime_error("Could not read number of clusters");
+    }
+    
+    ClusterVector<int32_t> clusters(3, 3);
+    clusters.reserve(m_num_left);
+    clusters.set_frame_number(frame_number);
+    while(m_num_left){
+        Cluster3x3 c = read_one_cluster();
+        if(is_selected(c)){
+            clusters.push_back(c.x, c.y, reinterpret_cast<std::byte*>(c.data));
+        }
+    }
+    if (m_gain_map)
+        clusters.apply_gain_map(m_gain_map->view());
+    return clusters;
+}
+
+
+
+bool ClusterFile::is_selected(Cluster3x3 &cl) {
+    //Should fail fast
+    if (m_roi) {
+        if (!(m_roi->contains(cl.x, cl.y))) {
+            return false;
+        }
+    }
+    if (m_noise_map){
+        int32_t sum_1x1 = cl.data[4]; // central pixel
+        int32_t sum_2x2 = cl.sum_2x2(); // highest sum of 2x2 subclusters
+        int32_t sum_3x3 = cl.sum(); // sum of all pixels
+
+        auto noise = (*m_noise_map)(cl.y, cl.x); //TODO! check if this is correct
+        if (sum_1x1 <= noise || sum_2x2 <= 2 * noise || sum_3x3 <= 3 * noise) {
+            return false;
+        }
+    }
+    //we passed all checks
+    return true;
+}
+
+NDArray<double, 2> calculate_eta2(ClusterVector<int> &clusters) {
+    //TOTO! make work with 2x2 clusters
+    NDArray<double, 2> eta2({static_cast<int64_t>(clusters.size()), 2});
+    
+    if (clusters.cluster_size_x() == 3 || clusters.cluster_size_y() == 3) {
+        for (size_t i = 0; i < clusters.size(); i++) {
+            auto e = calculate_eta2(clusters.at<Cluster3x3>(i));
+            eta2(i, 0) = e.x;
+            eta2(i, 1) = e.y;
+        }
+    }else if(clusters.cluster_size_x() == 2 || clusters.cluster_size_y() == 2){
+        for (size_t i = 0; i < clusters.size(); i++) {
+            auto e = calculate_eta2(clusters.at<Cluster2x2>(i));
+            eta2(i, 0) = e.x;
+            eta2(i, 1) = e.y;
+        }
+    }else{
+        throw std::runtime_error("Only 3x3 and 2x2 clusters are supported");
+    }
+    
+    return eta2;
+}
+
+/** 
+ * @brief Calculate the eta2 values for a 3x3 cluster and return them in a Eta2 struct
+ * containing etay, etax and the corner of the cluster. 
+*/
+Eta2 calculate_eta2(Cluster3x3 &cl) {
+    Eta2 eta{};
+
+    std::array<int32_t, 4> tot2;
+    tot2[0] = cl.data[0] + cl.data[1] + cl.data[3] + cl.data[4];
+    tot2[1] = cl.data[1] + cl.data[2] + cl.data[4] + cl.data[5];
+    tot2[2] = cl.data[3] + cl.data[4] + cl.data[6] + cl.data[7];
+    tot2[3] = cl.data[4] + cl.data[5] + cl.data[7] + cl.data[8];
+
+    auto c = std::max_element(tot2.begin(), tot2.end()) - tot2.begin();
+    eta.sum = tot2[c];
+    switch (c) {
+    case cBottomLeft:
+        if ((cl.data[3] + cl.data[4]) != 0)
+            eta.x =
+                static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
+        if ((cl.data[1] + cl.data[4]) != 0)
+            eta.y =
+                static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
+        eta.c = cBottomLeft;
+        break;
+    case cBottomRight:
+        if ((cl.data[2] + cl.data[5]) != 0)
+            eta.x =
+                static_cast<double>(cl.data[5]) / (cl.data[4] + cl.data[5]);
+        if ((cl.data[1] + cl.data[4]) != 0)
+            eta.y =
+                static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
+        eta.c = cBottomRight;
+        break;
+    case cTopLeft:
+        if ((cl.data[7] + cl.data[4]) != 0)
+            eta.x =
+                static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
+        if ((cl.data[7] + cl.data[4]) != 0)
+            eta.y =
+                static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
+        eta.c = cTopLeft;
+        break;
+    case cTopRight:
+        if ((cl.data[5] + cl.data[4]) != 0)
+            eta.x =
+                static_cast<double>(cl.data[5]) / (cl.data[5] + cl.data[4]);
+        if ((cl.data[7] + cl.data[4]) != 0)
+            eta.y =
+                static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
+        eta.c = cTopRight;
+        break;
+    // no default to allow compiler to warn about missing cases
+    }
+    return eta;
+}
+
+
+Eta2 calculate_eta2(Cluster2x2 &cl) {
+    Eta2 eta{};
+    if ((cl.data[0] + cl.data[1]) != 0)
+        eta.x = static_cast<double>(cl.data[1]) / (cl.data[0] + cl.data[1]);
+    if ((cl.data[0] + cl.data[2]) != 0)
+        eta.y = static_cast<double>(cl.data[2]) / (cl.data[0] + cl.data[2]);
+    eta.sum = cl.data[0] + cl.data[1] + cl.data[2]+ cl.data[3];
+    eta.c = cBottomLeft; //TODO! This is not correct, but need to put something
+    return eta;
+}
+
+
+} // namespace aare

src/ClusterFile.test.cpp

@@ -2,23 +2,32 @@
 #include "test_config.hpp"
 
 #include "aare/defs.hpp"
+#include <algorithm>
 #include <catch2/catch_test_macros.hpp>
 #include <filesystem>
 
 using aare::Cluster;
 using aare::ClusterFile;
+using aare::ClusterVector;
 
-TEST_CASE("Read one frame from a a cluster file", "[.files]") {
-    // We know that the frame has 97 clusters
+
+TEST_CASE("Read one frame from a cluster file", "[.files]") {
+    //We know that the frame has 97 clusters
     auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
     REQUIRE(std::filesystem::exists(fpath));
 
     ClusterFile<Cluster<int32_t, 3, 3>> f(fpath);
     auto clusters = f.read_frame();
-    REQUIRE(clusters.size() == 97);
-    REQUIRE(clusters.frame_number() == 135);
+    CHECK(clusters.size() == 97);
+    CHECK(clusters.frame_number() == 135);
+    CHECK(clusters[0].x == 1);
+    CHECK(clusters[0].y == 200);
+    int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+    CHECK(std::equal(std::begin(clusters[0].data), std::end(clusters[0].data),
+                     std::begin(expected_cluster_data)));
 }
 
+
 TEST_CASE("Read one frame using ROI", "[.files]") {
     // We know that the frame has 97 clusters
     auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
@@ -37,14 +46,22 @@ TEST_CASE("Read one frame using ROI", "[.files]") {
 
     // Check that all clusters are within the ROI
     for (size_t i = 0; i < clusters.size(); i++) {
-        auto c = clusters.at(i);
+        auto c = clusters[i];
         REQUIRE(c.x >= roi.xmin);
         REQUIRE(c.x <= roi.xmax);
         REQUIRE(c.y >= roi.ymin);
         REQUIRE(c.y <= roi.ymax);
     }
+
+    CHECK(clusters[0].x == 1);
+    CHECK(clusters[0].y == 200);
+    int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+    CHECK(std::equal(std::begin(clusters[0].data), std::end(clusters[0].data),
+                     std::begin(expected_cluster_data)));
 }
 
+
+
 TEST_CASE("Read clusters from single frame file", "[.files]") {
 
     //  frame_number, num_clusters   [135] 97
@@ -147,6 +164,7 @@ TEST_CASE("Read clusters from single frame file", "[.files]") {
     // [ 97 296] [864 865 866 867 868 869 870 871 872]
 
     auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
+
     REQUIRE(std::filesystem::exists(fpath));
 
     SECTION("Read fewer clusters than available") {
@@ -154,6 +172,12 @@ TEST_CASE("Read clusters from single frame file", "[.files]") {
         auto clusters = f.read_clusters(50);
         REQUIRE(clusters.size() == 50);
         REQUIRE(clusters.frame_number() == 135);
+        int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+        REQUIRE(clusters[0].x == 1);
+        REQUIRE(clusters[0].y == 200);
+        CHECK(std::equal(std::begin(clusters[0].data),
+                         std::end(clusters[0].data),
+                         std::begin(expected_cluster_data)));
     }
     SECTION("Read more clusters than available") {
         ClusterFile<Cluster<int32_t, 3, 3>> f(fpath);
@@ -161,24 +185,167 @@ TEST_CASE("Read clusters from single frame file", "[.files]") {
         auto clusters = f.read_clusters(100);
         REQUIRE(clusters.size() == 97);
         REQUIRE(clusters.frame_number() == 135);
+        int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+        REQUIRE(clusters[0].x == 1);
+        REQUIRE(clusters[0].y == 200);
+        CHECK(std::equal(std::begin(clusters[0].data),
+                         std::end(clusters[0].data),
+                         std::begin(expected_cluster_data)));
     }
     SECTION("Read all clusters") {
         ClusterFile<Cluster<int32_t, 3, 3>> f(fpath);
         auto clusters = f.read_clusters(97);
         REQUIRE(clusters.size() == 97);
         REQUIRE(clusters.frame_number() == 135);
-
-        REQUIRE(clusters.at(0).x == 1);
-        REQUIRE(clusters.at(0).y == 200);
+        REQUIRE(clusters[0].x == 1);
+        REQUIRE(clusters[0].y == 200);
+        int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+        CHECK(std::equal(std::begin(clusters[0].data),
+                         std::end(clusters[0].data),
+                         std::begin(expected_cluster_data)));
     }
 }
 
-TEST_CASE("Read clusters", "[.files]") {
-    // beam_En700eV_-40deg_300V_10us_d0_f0_100.clust
-    auto fpath = test_data_path() / "clust" /
-                 "beam_En700eV_-40deg_300V_10us_d0_f0_100.clust";
+TEST_CASE("Read clusters from single frame file with ROI", "[.files]") {
+    auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
     REQUIRE(std::filesystem::exists(fpath));
 
     ClusterFile<Cluster<int32_t, 3, 3>> f(fpath);
-    auto clusters = f.read_clusters(500);
+
+    aare::ROI roi;
+    roi.xmin = 0;
+    roi.xmax = 50;
+    roi.ymin = 200;
+    roi.ymax = 249;
+    f.set_roi(roi);
+
+    auto clusters = f.read_clusters(10);
+
+    CHECK(clusters.size() == 10);
+    CHECK(clusters.frame_number() == 135);
+    CHECK(clusters[0].x == 1);
+    CHECK(clusters[0].y == 200);
+    int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+    CHECK(std::equal(std::begin(clusters[0].data), std::end(clusters[0].data),
+                     std::begin(expected_cluster_data)));
+}
+
+TEST_CASE("Read cluster from multiple frame file", "[.files]") {
+
+    using ClusterType = Cluster<double, 2, 2>;
+
+    auto fpath =
+        test_data_path() / "clust" / "Two_frames_2x2double_test_clusters.clust";
+
+    REQUIRE(std::filesystem::exists(fpath));
+
+    // Two_frames_2x2double_test_clusters.clust
+    //  frame number, num_clusters 0, 4
+    //[10, 20], {0. ,0., 0., 0.}
+    //[11, 30], {1., 1., 1., 1.}
+    //[12, 40], {2., 2., 2., 2.}
+    //[13, 50], {3., 3., 3., 3.}
+    //  1,4
+    //[10, 20], {4., 4., 4., 4.}
+    //[11, 30], {5., 5., 5., 5.}
+    //[12, 40], {6., 6., 6., 6.}
+    //[13, 50], {7., 7., 7., 7.}
+
+    SECTION("Read clusters from both frames") {
+        ClusterFile<ClusterType> f(fpath);
+        auto clusters = f.read_clusters(2);
+        REQUIRE(clusters.size() == 2);
+        REQUIRE(clusters.frame_number() == 0);
+
+        auto clusters1 = f.read_clusters(3);
+
+        REQUIRE(clusters1.size() == 3);
+        REQUIRE(clusters1.frame_number() == 1);
+    }
+
+    SECTION("Read all clusters") {
+        ClusterFile<ClusterType> f(fpath);
+        auto clusters = f.read_clusters(8);
+        REQUIRE(clusters.size() == 8);
+        REQUIRE(clusters.frame_number() == 1);
+    }
+
+    SECTION("Read clusters from one frame") {
+        ClusterFile<ClusterType> f(fpath);
+        auto clusters = f.read_clusters(2);
+        REQUIRE(clusters.size() == 2);
+        REQUIRE(clusters.frame_number() == 0);
+
+        auto clusters1 = f.read_clusters(1);
+
+        REQUIRE(clusters1.size() == 1);
+        REQUIRE(clusters1.frame_number() == 0);
+    }
+}
+
+TEST_CASE("Write cluster with potential padding", "[.files][.ClusterFile]") {
+
+    using ClusterType = Cluster<double, 3, 3>;
+
+    REQUIRE(std::filesystem::exists(test_data_path() / "clust"));
+
+    auto fpath = test_data_path() / "clust" / "single_frame_2_clusters.clust";
+
+    ClusterFile<ClusterType> file(fpath, 1000, "w");
+
+    ClusterVector<ClusterType> clustervec(2);
+    int16_t coordinate = 5;
+    clustervec.push_back(ClusterType{
+        coordinate, coordinate, {0., 0., 0., 0., 0., 0., 0., 0., 0.}});
+    clustervec.push_back(ClusterType{
+        coordinate, coordinate, {0., 0., 0., 0., 0., 0., 0., 0., 0.}});
+
+    file.write_frame(clustervec);
+
+    file.close();
+
+    file.open("r");
+
+    auto read_cluster_vector = file.read_frame();
+
+    CHECK(read_cluster_vector.size() == 2);
+    CHECK(read_cluster_vector.frame_number() == 0);
+
+    CHECK(read_cluster_vector[0].x == clustervec[0].x);
+    CHECK(read_cluster_vector[0].y == clustervec[0].y);
+    CHECK(std::equal(
+        clustervec[0].data.begin(), clustervec[0].data.end(),
+        read_cluster_vector[0].data.begin(), [](double a, double b) {
+            return std::abs(a - b) < std::numeric_limits<double>::epsilon();
+        }));
+
+    CHECK(read_cluster_vector[1].x == clustervec[1].x);
+    CHECK(read_cluster_vector[1].y == clustervec[1].y);
+    CHECK(std::equal(
+        clustervec[1].data.begin(), clustervec[1].data.end(),
+        read_cluster_vector[1].data.begin(), [](double a, double b) {
+            return std::abs(a - b) < std::numeric_limits<double>::epsilon();
+        }));
+}
+
+TEST_CASE("Read frame and modify cluster data", "[.files][.ClusterFile]") {
+    auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
+    REQUIRE(std::filesystem::exists(fpath));
+
+    ClusterFile<Cluster<int32_t, 3, 3>> f(fpath);
+
+    auto clusters = f.read_frame();
+    CHECK(clusters.size() == 97);
+    CHECK(clusters.frame_number() == 135);
+
+    int32_t expected_cluster_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
+    clusters.push_back(
+        Cluster<int32_t, 3, 3>{0, 0, {0, 1, 2, 3, 4, 5, 6, 7, 8}});
+
+    CHECK(clusters.size() == 98);
+    CHECK(clusters[0].x == 1);
+    CHECK(clusters[0].y == 200);
+
+    CHECK(std::equal(std::begin(clusters[0].data), std::end(clusters[0].data),
+                     std::begin(expected_cluster_data)));
 }

src/ClusterFinderMT.test.cpp

@@ -0,0 +1,99 @@
+
+#include "aare/ClusterFinderMT.hpp"
+#include "aare/Cluster.hpp"
+#include "aare/ClusterCollector.hpp"
+#include "aare/File.hpp"
+
+#include "test_config.hpp"
+
+#include <catch2/catch_test_macros.hpp>
+#include <filesystem>
+#include <memory>
+
+using namespace aare;
+
+// wrapper function to access private member variables for testing
+template <typename ClusterType, typename FRAME_TYPE = uint16_t,
+          typename PEDESTAL_TYPE = double>
+class ClusterFinderMTWrapper
+    : public ClusterFinderMT<ClusterType, FRAME_TYPE, PEDESTAL_TYPE> {
+
+  public:
+    ClusterFinderMTWrapper(Shape<2> image_size, PEDESTAL_TYPE nSigma = 5.0,
+                           size_t capacity = 2000, size_t n_threads = 3)
+        : ClusterFinderMT<ClusterType, FRAME_TYPE, PEDESTAL_TYPE>(
+              image_size, nSigma, capacity, n_threads) {}
+
+    size_t get_m_input_queues_size() const {
+        return this->m_input_queues.size();
+    }
+
+    size_t get_m_output_queues_size() const {
+        return this->m_output_queues.size();
+    }
+
+    size_t get_m_cluster_finders_size() const {
+        return this->m_cluster_finders.size();
+    }
+
+    bool m_output_queues_are_empty() const {
+        for (auto &queue : this->m_output_queues) {
+            if (!queue->isEmpty())
+                return false;
+        }
+        return true;
+    }
+
+    bool m_input_queues_are_empty() const {
+        for (auto &queue : this->m_input_queues) {
+            if (!queue->isEmpty())
+                return false;
+        }
+        return true;
+    }
+
+    bool m_sink_is_empty() const { return this->m_sink.isEmpty(); }
+
+    size_t m_sink_size() const { return this->m_sink.sizeGuess(); }
+};
+
+TEST_CASE("multithreaded cluster finder", "[.files][.ClusterFinder]") {
+    auto fpath = "/mnt/sls_det_storage/matterhorn_data/aare_test_data/"
+                 "Moench03new/cu_half_speed_master_4.json";
+
+    File file(fpath);
+
+    size_t n_threads = 2;
+    size_t n_frames_pd = 10;
+
+    using ClusterType = Cluster<int32_t, 3, 3>;
+
+    ClusterFinderMTWrapper<ClusterType> cf(
+        {static_cast<int64_t>(file.rows()), static_cast<int64_t>(file.cols())},
+        5, 2000, n_threads); // no idea what frame type is!!! default uint16_t
+
+    CHECK(cf.get_m_input_queues_size() == n_threads);
+    CHECK(cf.get_m_output_queues_size() == n_threads);
+    CHECK(cf.get_m_cluster_finders_size() == n_threads);
+    CHECK(cf.m_output_queues_are_empty() == true);
+    CHECK(cf.m_input_queues_are_empty() == true);
+
+    for (size_t i = 0; i < n_frames_pd; ++i) {
+        cf.find_clusters(file.read_frame().view<uint16_t>());
+    }
+
+    cf.stop();
+
+    CHECK(cf.m_output_queues_are_empty() == true);
+    CHECK(cf.m_input_queues_are_empty() == true);
+
+    CHECK(cf.m_sink_size() == n_frames_pd);
+    ClusterCollector<ClusterType> clustercollector(&cf);
+
+    clustercollector.stop();
+
+    CHECK(cf.m_sink_size() == 0);
+
+    auto clustervec = clustercollector.steal_clusters();
+    // CHECK(clustervec.size() == ) //dont know how many clusters to expect
+}

src/ClusterVector.test.cpp

@@ -8,15 +8,14 @@
 using aare::Cluster;
 using aare::ClusterVector;
 
-
-TEST_CASE("item_size return the size of the cluster stored"){
+TEST_CASE("item_size return the size of the cluster stored") {
     using C1 = Cluster<int32_t, 2, 2>;
     ClusterVector<C1> cv(4);
     CHECK(cv.item_size() == sizeof(C1));
 
-    //Sanity check 
-    //2*2*4 = 16 bytes of data for the cluster
-    // 2*2 = 4 bytes for the x and y coordinates
+    // Sanity check
+    // 2*2*4 = 16 bytes of data for the cluster
+    //  2*2 = 4 bytes for the x and y coordinates
     REQUIRE(cv.item_size() == 20);
 
     using C2 = Cluster<int32_t, 3, 3>;
@@ -30,8 +29,6 @@ TEST_CASE("item_size return the size of the cluster stored"){
     using C4 = Cluster<char, 10, 5>;
     ClusterVector<C4> cv4(4);
     CHECK(cv4.item_size() == sizeof(C4));
-<<<<<<< Updated upstream
-=======
 
     using C5 = Cluster<int32_t, 2, 3>;
     ClusterVector<C5> cv5(4);
@@ -39,12 +36,11 @@ TEST_CASE("item_size return the size of the cluster stored"){
 
     using C6 = Cluster<double, 5, 5>;
     ClusterVector<C6> cv6(4);
-    CHECK(cv6.item_size() == sizeof(C6)); // double uses padding!!!
+    CHECK(cv6.item_size() == sizeof(C6));
 
     using C7 = Cluster<double, 3, 3>;
     ClusterVector<C7> cv7(4);
     CHECK(cv7.item_size() == sizeof(C7));
->>>>>>> Stashed changes
 }
 
 TEST_CASE("ClusterVector 2x2 int32_t capacity 4, push back then read",
@@ -64,7 +60,7 @@ TEST_CASE("ClusterVector 2x2 int32_t capacity 4, push back then read",
     REQUIRE(cv.size() == 1);
     REQUIRE(cv.capacity() == 4);
 
-    auto c2 = cv.at(0);
+    auto c2 = cv[0];
 
     // Check that the data is the same
     REQUIRE(c1.x == c2.x);
@@ -226,32 +222,6 @@ TEST_CASE("Concatenate two cluster vectors where we need to allocate",
     REQUIRE(ptr[3].y == 17);
 }
 
-TEST_CASE("calculate cluster sum", "[.ClusterVector]") {
-    ClusterVector<Cluster<int32_t, 2, 2>> cv1(2);
-    Cluster<int32_t, 2, 2> c1 = {1, 2, {3, 4, 5, 6}};
-    cv1.push_back(c1);
-    Cluster<int32_t, 2, 2> c2 = {6, 7, {8, 9, 10, 11}};
-    cv1.push_back(c2);
-
-    auto sum1 = cv1.sum();
-
-    std::vector<int32_t> expected_sum1{18, 38};
-
-    CHECK(sum1 == expected_sum1);
-
-    ClusterVector<Cluster<int32_t, 3, 3>> cv2(2);
-    Cluster<int32_t, 3, 3> c3 = {1, 2, {3, 4, 5, 6, 1, 7, 8, 1, 1}};
-    cv2.push_back(c3);
-    Cluster<int32_t, 3, 3> c4 = {6, 7, {8, 9, 10, 11, 13, 5, 12, 2, 4}};
-    cv2.push_back(c4);
-
-    auto sum2 = cv2.sum();
-
-    std::vector<int32_t> expected_sum2{36, 74};
-
-    CHECK(sum2 == expected_sum2);
-}
-
 struct ClusterTestData {
     uint8_t ClusterSizeX;
     uint8_t ClusterSizeY;

src/FilePtr.cpp

@@ -21,7 +21,7 @@ FilePtr &FilePtr::operator=(FilePtr &&other) {
 
 FILE *FilePtr::get() { return fp_; }
 
-int64_t FilePtr::tell() {
+ssize_t FilePtr::tell() {
     auto pos = ftell(fp_);
     if (pos == -1)
         throw std::runtime_error(fmt::format("Error getting file position: {}", error_msg()));

src/Fit.cpp

@@ -34,6 +34,30 @@ NDArray<double, 1> pol1(NDView<double, 1> x, NDView<double, 1> par) {
     return y;
 }
 
+double scurve(const double x, const double * par) {
+    return (par[0] + par[1] * x) + 0.5 * (1 + erf((x - par[2]) / (sqrt(2) * par[3]))) * (par[4] + par[5] * (x - par[2]));
+}
+
+NDArray<double, 1> scurve(NDView<double, 1> x, NDView<double, 1> par) {
+    NDArray<double, 1> y({x.shape()}, 0);
+    for (ssize_t i = 0; i < x.size(); i++) {
+        y(i) = scurve(x(i), par.data());
+    }
+    return y;
+}
+
+double scurve2(const double x, const double * par) {
+    return (par[0] + par[1] * x) + 0.5 * (1 - erf((x - par[2]) / (sqrt(2) * par[3]))) * (par[4] + par[5] * (x - par[2]));
+}
+
+NDArray<double, 1> scurve2(NDView<double, 1> x, NDView<double, 1> par) {
+    NDArray<double, 1> y({x.shape()}, 0);
+    for (ssize_t i = 0; i < x.size(); i++) {
+        y(i) = scurve2(x(i), par.data());
+    }
+    return y;
+}
+
 } // namespace func
 
 NDArray<double, 1> fit_gaus(NDView<double, 1> x, NDView<double, 1> y) {
@@ -81,7 +105,7 @@ std::array<double, 3> gaus_init_par(const NDView<double, 1> x, const NDView<doub
     auto delta = x[1] - x[0];
     start_par[2] =
         std::count_if(y.begin(), y.end(),
-                      [e, delta](double val) { return val > *e / 2; }) *
+                      [e](double val) { return val > *e / 2; }) *
         delta / 2.35;
 
     return start_par;
@@ -273,4 +297,229 @@ NDArray<double, 3> fit_pol1(NDView<double, 1> x, NDView<double, 3> y,
     return result;
 }
 
+// ~~ S-CURVES ~~
+
+// SCURVE --
+std::array<double, 6> scurve_init_par(const NDView<double, 1> x, const NDView<double, 1> y){
+        // Estimate the initial parameters for the fit
+        std::array<double, 6> start_par{0, 0, 0, 0, 0, 0};
+
+        auto ymax = std::max_element(y.begin(), y.end());
+        auto ymin = std::min_element(y.begin(), y.end());
+        start_par[4] = *ymin + (*ymax - *ymin) / 2;
+        
+        // Find the first x where the corresponding y value is above the threshold (start_par[4])
+        for (ssize_t i = 0; i < y.size(); ++i) {
+            if (y[i] >= start_par[4]) {
+                start_par[2] = x[i];
+                break; // Exit the loop after finding the first valid x
+            }
+        }
+
+        start_par[3] = 2 * sqrt(start_par[2]); 
+        start_par[0] = 100; 
+        start_par[1] = 0.25;
+        start_par[5] = 1;
+        return start_par;
+}
+
+// - No error
+NDArray<double, 1> fit_scurve(NDView<double, 1> x, NDView<double, 1> y) {
+    NDArray<double, 1> result = scurve_init_par(x, y);
+    lm_status_struct status;
+
+    lmcurve(result.size(), result.data(), x.size(), x.data(), y.data(),
+            aare::func::scurve, &lm_control_double, &status);
+
+    return result;
+}
+
+NDArray<double, 3> fit_scurve(NDView<double, 1> x, NDView<double, 3> y, int n_threads) {
+    NDArray<double, 3> result({y.shape(0), y.shape(1), 6}, 0);
+
+    auto process = [&x, &y, &result](ssize_t first_row, ssize_t last_row) {
+        for (ssize_t row = first_row; row < last_row; row++) {
+            for (ssize_t col = 0; col < y.shape(1); col++) {
+                NDView<double, 1> values(&y(row, col, 0), {y.shape(2)});
+                auto res = fit_scurve(x, values);
+                result(row, col, 0) = res(0);
+                result(row, col, 1) = res(1);
+                result(row, col, 2) = res(2);
+                result(row, col, 3) = res(3);
+                result(row, col, 4) = res(4);
+                result(row, col, 5) = res(5);
+            }
+        }
+    };
+
+    auto tasks = split_task(0, y.shape(0), n_threads);
+    RunInParallel(process, tasks);
+    return result;
+}
+
+// - Error
+void fit_scurve(NDView<double, 1> x, NDView<double, 1> y, NDView<double, 1> y_err,
+              NDView<double, 1> par_out, NDView<double, 1> par_err_out, double& chi2) {
+
+    // Check that we have the correct sizes
+    if (y.size() != x.size() || y.size() != y_err.size() ||
+        par_out.size() != 6 || par_err_out.size() != 6) {
+        throw std::runtime_error("Data, x, data_err must have the same size "
+                                 "and par_out, par_err_out must have size 6");
+    }
+
+    lm_status_struct status;
+    par_out = scurve_init_par(x, y);
+    std::array<double, 36> cov = {0}; // size 6x6
+    // std::array<double, 4> cov{0, 0, 0, 0};
+
+    lmcurve2(par_out.size(), par_out.data(), par_err_out.data(), cov.data(),
+             x.size(), x.data(), y.data(), y_err.data(), aare::func::scurve,
+             &lm_control_double, &status);
+
+    // Calculate chi2
+    chi2 = 0;
+    for (ssize_t i = 0; i < y.size(); i++) {
+        chi2 += std::pow((y(i) - func::pol1(x(i), par_out.data())) / y_err(i), 2);
+    }
+}
+
+void fit_scurve(NDView<double, 1> x, NDView<double, 3> y, NDView<double, 3> y_err,
+              NDView<double, 3> par_out, NDView<double, 3> par_err_out, NDView<double, 2> chi2_out,
+              int n_threads) {
+
+    auto process = [&](ssize_t first_row, ssize_t last_row) {
+        for (ssize_t row = first_row; row < last_row; row++) {
+            for (ssize_t col = 0; col < y.shape(1); col++) {
+                NDView<double, 1> y_view(&y(row, col, 0), {y.shape(2)});
+                NDView<double, 1> y_err_view(&y_err(row, col, 0),
+                                             {y_err.shape(2)});
+                NDView<double, 1> par_out_view(&par_out(row, col, 0),
+                                               {par_out.shape(2)});
+                NDView<double, 1> par_err_out_view(&par_err_out(row, col, 0),
+                                                   {par_err_out.shape(2)});
+
+                fit_scurve(x, y_view, y_err_view, par_out_view, par_err_out_view, chi2_out(row, col));
+
+            }
+        }
+    };
+
+    auto tasks = split_task(0, y.shape(0), n_threads);
+    RunInParallel(process, tasks);
+
+}
+
+// SCURVE2 ---
+
+std::array<double, 6> scurve2_init_par(const NDView<double, 1> x, const NDView<double, 1> y){
+        // Estimate the initial parameters for the fit
+        std::array<double, 6> start_par{0, 0, 0, 0, 0, 0};
+
+        auto ymax = std::max_element(y.begin(), y.end());
+        auto ymin = std::min_element(y.begin(), y.end());
+        start_par[4] = *ymin + (*ymax - *ymin) / 2;
+        
+        // Find the first x where the corresponding y value is above the threshold (start_par[4])
+        for (ssize_t i = 0; i < y.size(); ++i) {
+            if (y[i] <= start_par[4]) {
+                start_par[2] = x[i];
+                break; // Exit the loop after finding the first valid x
+            }
+        }
+
+        start_par[3] = 2 * sqrt(start_par[2]); 
+        start_par[0] = 100; 
+        start_par[1] = 0.25;
+        start_par[5] = -1;
+        return start_par;
+}
+
+// - No error
+NDArray<double, 1> fit_scurve2(NDView<double, 1> x, NDView<double, 1> y) {
+    NDArray<double, 1> result = scurve2_init_par(x, y);
+    lm_status_struct status;
+
+    lmcurve(result.size(), result.data(), x.size(), x.data(), y.data(),
+            aare::func::scurve2, &lm_control_double, &status);
+
+    return result;
+}
+
+NDArray<double, 3> fit_scurve2(NDView<double, 1> x, NDView<double, 3> y, int n_threads) {
+    NDArray<double, 3> result({y.shape(0), y.shape(1), 6}, 0);
+
+    auto process = [&x, &y, &result](ssize_t first_row, ssize_t last_row) {
+        for (ssize_t row = first_row; row < last_row; row++) {
+            for (ssize_t col = 0; col < y.shape(1); col++) {
+                NDView<double, 1> values(&y(row, col, 0), {y.shape(2)});
+                auto res = fit_scurve2(x, values);
+                result(row, col, 0) = res(0);
+                result(row, col, 1) = res(1);
+                result(row, col, 2) = res(2);
+                result(row, col, 3) = res(3);
+                result(row, col, 4) = res(4);
+                result(row, col, 5) = res(5);
+            }
+        }
+    };
+
+    auto tasks = split_task(0, y.shape(0), n_threads);
+    RunInParallel(process, tasks);
+    return result;
+}
+
+// - Error
+void fit_scurve2(NDView<double, 1> x, NDView<double, 1> y, NDView<double, 1> y_err,
+              NDView<double, 1> par_out, NDView<double, 1> par_err_out, double& chi2) {
+
+    // Check that we have the correct sizes
+    if (y.size() != x.size() || y.size() != y_err.size() ||
+        par_out.size() != 6 || par_err_out.size() != 6) {
+        throw std::runtime_error("Data, x, data_err must have the same size "
+                                 "and par_out, par_err_out must have size 6");
+    }
+
+    lm_status_struct status;
+    par_out = scurve2_init_par(x, y);
+    std::array<double, 36> cov = {0}; // size 6x6
+    // std::array<double, 4> cov{0, 0, 0, 0};
+
+    lmcurve2(par_out.size(), par_out.data(), par_err_out.data(), cov.data(),
+             x.size(), x.data(), y.data(), y_err.data(), aare::func::scurve2,
+             &lm_control_double, &status);
+
+    // Calculate chi2
+    chi2 = 0;
+    for (ssize_t i = 0; i < y.size(); i++) {
+        chi2 += std::pow((y(i) - func::pol1(x(i), par_out.data())) / y_err(i), 2);
+    }
+}
+
+void fit_scurve2(NDView<double, 1> x, NDView<double, 3> y, NDView<double, 3> y_err,
+              NDView<double, 3> par_out, NDView<double, 3> par_err_out, NDView<double, 2> chi2_out,
+              int n_threads) {
+
+    auto process = [&](ssize_t first_row, ssize_t last_row) {
+        for (ssize_t row = first_row; row < last_row; row++) {
+            for (ssize_t col = 0; col < y.shape(1); col++) {
+                NDView<double, 1> y_view(&y(row, col, 0), {y.shape(2)});
+                NDView<double, 1> y_err_view(&y_err(row, col, 0),
+                                             {y_err.shape(2)});
+                NDView<double, 1> par_out_view(&par_out(row, col, 0),
+                                               {par_out.shape(2)});
+                NDView<double, 1> par_err_out_view(&par_err_out(row, col, 0),
+                                                   {par_err_out.shape(2)});
+
+                fit_scurve2(x, y_view, y_err_view, par_out_view, par_err_out_view, chi2_out(row, col));
+
+            }
+        }
+    };
+
+    auto tasks = split_task(0, y.shape(0), n_threads);
+    RunInParallel(process, tasks);
+
+}
+
 } // namespace aare

src/JungfrauDataFile.cpp

@@ -89,7 +89,7 @@ void JungfrauDataFile::seek(size_t frame_index) {
                             : frame_index;
     auto byte_offset = frame_offset * (m_bytes_per_frame + header_size);
     m_fp.seek(byte_offset);
-};
+}
 
 size_t JungfrauDataFile::tell() { return m_current_frame_index; }
 size_t JungfrauDataFile::total_frames() const { return m_total_frames; }
@@ -235,4 +235,4 @@ std::filesystem::path JungfrauDataFile::fpath(size_t file_index) const {
     return m_path / fname;
 }
 
-} // namespace aare
+} // namespace aare

src/NDArray.test.cpp

@@ -44,9 +44,9 @@ TEST_CASE("3D NDArray from NDView"){
     REQUIRE(image.size() == view.size());
     REQUIRE(image.data() != view.data());
 
-    for(int64_t i=0; i<image.shape(0); i++){
-        for(int64_t j=0; j<image.shape(1); j++){
-            for(int64_t k=0; k<image.shape(2); k++){
+    for(ssize_t i=0; i<image.shape(0); i++){
+        for(ssize_t j=0; j<image.shape(1); j++){
+            for(ssize_t k=0; k<image.shape(2); k++){
                 REQUIRE(image(i, j, k) == view(i, j, k));
             }
         }
@@ -54,7 +54,7 @@ TEST_CASE("3D NDArray from NDView"){
 }
 
 TEST_CASE("1D image") {
-    std::array<int64_t, 1> shape{{20}};
+    std::array<ssize_t, 1> shape{{20}};
     NDArray<short, 1> img(shape, 3);
     REQUIRE(img.size() == 20);
     REQUIRE(img(5) == 3);
@@ -71,7 +71,7 @@ TEST_CASE("Accessing a const object") {
 }
 
 TEST_CASE("Indexing of a 2D image") {
-    std::array<int64_t, 2> shape{{3, 7}};
+    std::array<ssize_t, 2> shape{{3, 7}};
     NDArray<long> img(shape, 5);
     for (uint32_t i = 0; i != img.size(); ++i) {
         REQUIRE(img(i) == 5);
@@ -114,7 +114,7 @@ TEST_CASE("Divide double by int") {
 }
 
 TEST_CASE("Elementwise multiplication of 3D image") {
-    std::array<int64_t, 3> shape{3, 4, 2};
+    std::array<ssize_t, 3> shape{3, 4, 2};
     NDArray<double, 3> a{shape};
     NDArray<double, 3> b{shape};
     for (uint32_t i = 0; i != a.size(); ++i) {
@@ -179,9 +179,9 @@ TEST_CASE("Compare two images") {
 }
 
 TEST_CASE("Size and shape matches") {
-    int64_t w = 15;
-    int64_t h = 75;
-    std::array<int64_t, 2> shape{w, h};
+    ssize_t w = 15;
+    ssize_t h = 75;
+    std::array<ssize_t, 2> shape{w, h};
     NDArray<double> a{shape};
     REQUIRE(a.size() == w * h);
     REQUIRE(a.shape() == shape);
@@ -224,7 +224,7 @@ TEST_CASE("Bitwise and on data") {
 
 
 TEST_CASE("Elementwise operations on images") {
-    std::array<int64_t, 2> shape{5, 5};
+    std::array<ssize_t, 2> shape{5, 5};
     double a_val = 3.0;
     double b_val = 8.0;
 

src/NDView.test.cpp

@@ -3,6 +3,7 @@
 
 #include <iostream>
 #include <vector>
+#include <numeric>
 
 using aare::NDView;
 using aare::Shape;
@@ -21,10 +22,8 @@ TEST_CASE("Element reference 1D") {
 }
 
 TEST_CASE("Element reference 2D") {
-    std::vector<int> vec;
-    for (int i = 0; i != 12; ++i) {
-        vec.push_back(i);
-    }
+    std::vector<int> vec(12);
+    std::iota(vec.begin(), vec.end(), 0);
 
     NDView<int, 2> data(vec.data(), Shape<2>{3, 4});
     REQUIRE(vec.size() == static_cast<size_t>(data.size()));
@@ -58,10 +57,8 @@ TEST_CASE("Element reference 3D") {
 }
 
 TEST_CASE("Plus and miuns with single value") {
-    std::vector<int> vec;
-    for (int i = 0; i != 12; ++i) {
-        vec.push_back(i);
-    }
+    std::vector<int> vec(12);
+    std::iota(vec.begin(), vec.end(), 0);
     NDView<int, 2> data(vec.data(), Shape<2>{3, 4});
     data += 5;
     int i = 0;
@@ -116,10 +113,8 @@ TEST_CASE("elementwise assign") {
 }
 
 TEST_CASE("iterators") {
-    std::vector<int> vec;
-    for (int i = 0; i != 12; ++i) {
-        vec.push_back(i);
-    }
+    std::vector<int> vec(12);
+    std::iota(vec.begin(), vec.end(), 0);
     NDView<int, 1> data(vec.data(), Shape<1>{12});
     int i = 0;
     for (const auto item : data) {
@@ -147,7 +142,7 @@ TEST_CASE("iterators") {
 //     for (int i = 0; i != 12; ++i) {
 //         vec.push_back(i);
 //     }
-//     std::vector<int64_t> shape{3, 4};
+//     std::vector<ssize_t> shape{3, 4};
 //     NDView<int, 2> data(vec.data(), shape);
 // }
 
@@ -156,8 +151,8 @@ TEST_CASE("divide with another span") {
     std::vector<int> vec1{3, 2, 1};
     std::vector<int> result{3, 6, 3};
 
-    NDView<int, 1> data0(vec0.data(), Shape<1>{static_cast<int64_t>(vec0.size())});
-    NDView<int, 1> data1(vec1.data(), Shape<1>{static_cast<int64_t>(vec1.size())});
+    NDView<int, 1> data0(vec0.data(), Shape<1>{static_cast<ssize_t>(vec0.size())});
+    NDView<int, 1> data1(vec1.data(), Shape<1>{static_cast<ssize_t>(vec1.size())});
 
     data0 /= data1;
 
@@ -167,27 +162,31 @@ TEST_CASE("divide with another span") {
 }
 
 TEST_CASE("Retrieve shape") {
-    std::vector<int> vec;
-    for (int i = 0; i != 12; ++i) {
-        vec.push_back(i);
-    }
+    std::vector<int> vec(12);
+    std::iota(vec.begin(), vec.end(), 0);
     NDView<int, 2> data(vec.data(), Shape<2>{3, 4});
     REQUIRE(data.shape()[0] == 3);
     REQUIRE(data.shape()[1] == 4);
 }
 
 TEST_CASE("compare two views") {
-    std::vector<int> vec1;
-    for (int i = 0; i != 12; ++i) {
-        vec1.push_back(i);
-    }
+    std::vector<int> vec1(12);
+    std::iota(vec1.begin(), vec1.end(), 0);
     NDView<int, 2> view1(vec1.data(), Shape<2>{3, 4});
 
-    std::vector<int> vec2;
-    for (int i = 0; i != 12; ++i) {
-        vec2.push_back(i);
-    }
+    std::vector<int> vec2(12);
+    std::iota(vec2.begin(), vec2.end(), 0);
     NDView<int, 2> view2(vec2.data(), Shape<2>{3, 4});
 
     REQUIRE((view1 == view2));
+}
+
+
+TEST_CASE("Create a view over a vector"){
+    std::vector<int> vec(12);
+    std::iota(vec.begin(), vec.end(), 0);
+    auto v = aare::make_view(vec);
+    REQUIRE(v.shape()[0] == 12);
+    REQUIRE(v[0] == 0);
+    REQUIRE(v[11] == 11);
 }

src/NumpyFile.cpp

@@ -72,8 +72,8 @@ void NumpyFile::get_frame_into(size_t frame_number, std::byte *image_buf) {
     }
 }
 
-size_t NumpyFile::pixels_per_frame() { return m_pixels_per_frame; };
-size_t NumpyFile::bytes_per_frame() { return m_bytes_per_frame; };
+size_t NumpyFile::pixels_per_frame() { return m_pixels_per_frame; }
+size_t NumpyFile::bytes_per_frame() { return m_bytes_per_frame; }
 
 std::vector<Frame> NumpyFile::read_n(size_t n_frames) {
     // TODO: implement this in a more efficient way
@@ -197,4 +197,4 @@ void NumpyFile::load_metadata() {
     m_header = {dtype, fortran_order, shape};
 }
 
-} // namespace aare
+} // namespace aare

src/RawFile.cpp

@@ -1,6 +1,8 @@
 #include "aare/RawFile.hpp"
+#include "aare/algorithm.hpp"
 #include "aare/PixelMap.hpp"
 #include "aare/defs.hpp"
+#include "aare/logger.hpp"
 #include "aare/geo_helpers.hpp"
 
 #include <fmt/format.h>
@@ -14,27 +16,18 @@ RawFile::RawFile(const std::filesystem::path &fname, const std::string &mode)
     : m_master(fname) {
     m_mode = mode;
     if (mode == "r") {
-
-        n_subfiles = find_number_of_subfiles(); // f0,f1...fn
-        n_subfile_parts =
-            m_master.geometry().col * m_master.geometry().row; // d0,d1...dn
-
-        
-
         find_geometry();
-
         if (m_master.roi()){
             m_geometry = update_geometry_with_roi(m_geometry, m_master.roi().value());
         }
-        
         open_subfiles();
     } else {
         throw std::runtime_error(LOCATION +
-                                 "Unsupported mode. Can only read RawFiles.");
+                                 " Unsupported mode. Can only read RawFiles.");
     }
 }
 
-Frame RawFile::read_frame() { return get_frame(m_current_frame++); };
+Frame RawFile::read_frame() { return get_frame(m_current_frame++); }
 
 Frame RawFile::read_frame(size_t frame_number) {
     seek(frame_number);
@@ -52,13 +45,13 @@ void RawFile::read_into(std::byte *image_buf, size_t n_frames) {
 
 void RawFile::read_into(std::byte *image_buf) {
     return get_frame_into(m_current_frame++, image_buf);
-};
+}
 
 
 void RawFile::read_into(std::byte *image_buf, DetectorHeader *header) {
 
     return get_frame_into(m_current_frame++, image_buf, header);
-};
+}
 
 void RawFile::read_into(std::byte *image_buf, size_t n_frames, DetectorHeader *header) {
     // return get_frame_into(m_current_frame++, image_buf, header);
@@ -67,12 +60,12 @@ void RawFile::read_into(std::byte *image_buf, size_t n_frames, DetectorHeader *h
         this->get_frame_into(m_current_frame++, image_buf, header);
         image_buf += bytes_per_frame();
         if(header) 
-            header+=n_mod();
+            header+=n_modules();
     }
 
-};
+}
 
-size_t RawFile::n_mod() const { return n_subfile_parts; }
+size_t RawFile::n_modules() const { return m_master.n_modules(); }
 
 
 size_t RawFile::bytes_per_frame() {
@@ -94,9 +87,9 @@ void RawFile::seek(size_t frame_index) {
                         frame_index, total_frames()));
     }
     m_current_frame = frame_index;
-};
+}
 
-size_t RawFile::tell() { return m_current_frame; };
+size_t RawFile::tell() { return m_current_frame; }
 
 size_t RawFile::total_frames() const { return m_master.frames_in_file(); }
 size_t RawFile::rows() const { return m_geometry.pixels_y; }
@@ -106,17 +99,11 @@ xy RawFile::geometry() { return m_master.geometry(); }
 
 void RawFile::open_subfiles() {
     if (m_mode == "r")
-        for (size_t i = 0; i != n_subfiles; ++i) {
-            auto v = std::vector<RawSubFile *>(n_subfile_parts);
-            for (size_t j = 0; j != n_subfile_parts; ++j) {
-                auto pos = m_geometry.module_pixel_0[j];
-                v[j] = new RawSubFile(m_master.data_fname(j, i),
-                                      m_master.detector_type(), pos.height,
-                                      pos.width, m_master.bitdepth(),
-                                      pos.row_index, pos.col_index);
-
-            }
-            subfiles.push_back(v);
+        for (size_t i = 0; i != n_modules(); ++i) {
+            auto pos = m_geometry.module_pixel_0[i];
+            m_subfiles.emplace_back(std::make_unique<RawSubFile>(
+                m_master.data_fname(i, 0), m_master.detector_type(), pos.height,
+                pos.width, m_master.bitdepth(), pos.row_index, pos.col_index));
         }
     else {
         throw std::runtime_error(LOCATION +
@@ -141,18 +128,6 @@ DetectorHeader RawFile::read_header(const std::filesystem::path &fname) {
     return h;
 }
 
-int RawFile::find_number_of_subfiles() {
-    int n_files = 0;
-    // f0,f1...fn How many files is the data split into?
-    while (std::filesystem::exists(m_master.data_fname(0, n_files)))
-        n_files++; // increment after test
-
-#ifdef AARE_VERBOSE
-    fmt::print("Found: {} subfiles\n", n_files);
-#endif
-    return n_files;
-
-}
 
 RawMasterFile RawFile::master() const { return m_master; }
 
@@ -168,7 +143,7 @@ void RawFile::find_geometry() {
     uint16_t c{};
 
 
-    for (size_t i = 0; i < n_subfile_parts; i++) {
+    for (size_t i = 0; i < n_modules(); i++) {
         auto h = read_header(m_master.data_fname(i, 0));
         r = std::max(r, h.row);
         c = std::max(c, h.column);
@@ -210,70 +185,58 @@ size_t RawFile::bytes_per_pixel() const {
 }
 
 void RawFile::get_frame_into(size_t frame_index, std::byte *frame_buffer, DetectorHeader *header) {
+    LOG(logDEBUG) << "RawFile::get_frame_into(" << frame_index << ")";
     if (frame_index >= total_frames()) {
         throw std::runtime_error(LOCATION + "Frame number out of range");
     }
-    std::vector<size_t> frame_numbers(n_subfile_parts);
-    std::vector<size_t> frame_indices(n_subfile_parts, frame_index);
+    std::vector<size_t> frame_numbers(n_modules());
+    std::vector<size_t> frame_indices(n_modules(), frame_index);
 
 
     // sync the frame numbers
 
-    if (n_subfile_parts != 1) {
-        for (size_t part_idx = 0; part_idx != n_subfile_parts; ++part_idx) {
-            auto subfile_id = frame_index / m_master.max_frames_per_file();
-            if (subfile_id >= subfiles.size()) {
-                throw std::runtime_error(LOCATION +
-                                         " Subfile out of range. Possible missing data.");
-            }
-            frame_numbers[part_idx] =
-                subfiles[subfile_id][part_idx]->frame_number(
-                    frame_index % m_master.max_frames_per_file());
+    if (n_modules() != 1) { //if we have more than one module
+        for (size_t part_idx = 0; part_idx != n_modules(); ++part_idx) {
+            frame_numbers[part_idx] = m_subfiles[part_idx]->frame_number(frame_index); 
         }
+
         // 1. if frame number vector is the same break
-        while (std::adjacent_find(frame_numbers.begin(), frame_numbers.end(),
-                                  std::not_equal_to<>()) !=
-               frame_numbers.end()) {
+        while (!all_equal(frame_numbers)) {
+
             // 2. find the index of the minimum frame number,
             auto min_frame_idx = std::distance(
                 frame_numbers.begin(),
                 std::min_element(frame_numbers.begin(), frame_numbers.end()));
+
             // 3. increase its index and update its respective frame number
             frame_indices[min_frame_idx]++;
+
             // 4. if we can't increase its index => throw error
             if (frame_indices[min_frame_idx] >= total_frames()) {
                 throw std::runtime_error(LOCATION +
                                          "Frame number out of range");
             }
-            auto subfile_id =
-                frame_indices[min_frame_idx] / m_master.max_frames_per_file();
+
             frame_numbers[min_frame_idx] =
-                subfiles[subfile_id][min_frame_idx]->frame_number(
-                    frame_indices[min_frame_idx] %
-                    m_master.max_frames_per_file());
+                m_subfiles[min_frame_idx]->frame_number(frame_indices[min_frame_idx]);
         }
     }
 
     if (m_master.geometry().col == 1) {
         // get the part from each subfile and copy it to the frame
-        for (size_t part_idx = 0; part_idx != n_subfile_parts; ++part_idx) {
+        for (size_t part_idx = 0; part_idx != n_modules(); ++part_idx) {
             auto corrected_idx = frame_indices[part_idx];
-            auto subfile_id = corrected_idx / m_master.max_frames_per_file();
-            if (subfile_id >= subfiles.size()) {
-                throw std::runtime_error(LOCATION +
-                                         " Subfile out of range. Possible missing data.");
-            }
-
+      
             // This is where we start writing
             auto offset = (m_geometry.module_pixel_0[part_idx].origin_y * m_geometry.pixels_x +
                 m_geometry.module_pixel_0[part_idx].origin_x)*m_master.bitdepth()/8;
 
             if (m_geometry.module_pixel_0[part_idx].origin_x!=0)
-                throw std::runtime_error(LOCATION + "Implementation error. x pos not 0.");
+                throw std::runtime_error(LOCATION + " Implementation error. x pos not 0.");
             
-            //TODO! Risk for out of range access
-            subfiles[subfile_id][part_idx]->seek(corrected_idx % m_master.max_frames_per_file());
-            subfiles[subfile_id][part_idx]->read_into(frame_buffer + offset, header);
+            //TODO! What if the files don't match?
+            m_subfiles[part_idx]->seek(corrected_idx);
+            m_subfiles[part_idx]->read_into(frame_buffer + offset, header);
             if (header)
                 ++header;
         }
@@ -282,26 +245,21 @@ void RawFile::get_frame_into(size_t frame_index, std::byte *frame_buffer, Detect
         //TODO! should we read row by row?
 
         // create a buffer large enough to hold a full module
-
         auto bytes_per_part = m_master.pixels_y() * m_master.pixels_x() *
                               m_master.bitdepth() /
                               8; // TODO! replace with image_size_in_bytes
+
         auto *part_buffer = new std::byte[bytes_per_part];
 
         // TODO! if we have many submodules we should reorder them on the module
         // level
 
-        for (size_t part_idx = 0; part_idx != n_subfile_parts; ++part_idx) {
+        for (size_t part_idx = 0; part_idx != n_modules(); ++part_idx) {
             auto pos = m_geometry.module_pixel_0[part_idx];
             auto corrected_idx = frame_indices[part_idx];
-            auto subfile_id = corrected_idx / m_master.max_frames_per_file();
-            if (subfile_id >= subfiles.size()) {
-                throw std::runtime_error(LOCATION +
-                                         " Subfile out of range. Possible missing data.");
-            }
 
-            subfiles[subfile_id][part_idx]->seek(corrected_idx % m_master.max_frames_per_file());
-            subfiles[subfile_id][part_idx]->read_into(part_buffer, header);
+            m_subfiles[part_idx]->seek(corrected_idx);
+            m_subfiles[part_idx]->read_into(part_buffer, header);
             if(header)
                 ++header;
 
@@ -321,6 +279,7 @@ void RawFile::get_frame_into(size_t frame_index, std::byte *frame_buffer, Detect
         }
         delete[] part_buffer;
     }
+        
 }
 
 std::vector<Frame> RawFile::read_n(size_t n_frames) {
@@ -337,27 +296,8 @@ size_t RawFile::frame_number(size_t frame_index) {
     if (frame_index >= m_master.frames_in_file()) {
         throw std::runtime_error(LOCATION + " Frame number out of range");
     }
-    size_t subfile_id = frame_index / m_master.max_frames_per_file();
-    if (subfile_id >= subfiles.size()) {
-        throw std::runtime_error(
-            LOCATION + " Subfile out of range. Possible missing data.");
-    }
-    return subfiles[subfile_id][0]->frame_number(
-        frame_index % m_master.max_frames_per_file());
-}
-
-RawFile::~RawFile() {
-
-    // TODO! Fix this, for file closing
-    for (auto &vec : subfiles) {
-        for (auto *subfile : vec) {
-            delete subfile;
-        }
-    }
+    return m_subfiles[0]->frame_number(frame_index);
 }
 
 
-
-
-
-} // namespace aare
+} // namespace aare

src/RawFile.test.cpp

@@ -99,11 +99,11 @@ TEST_CASE("Read frame numbers from a raw file", "[.integration]") {
     }
 }
 
-TEST_CASE("Compare reading from a numpy file with a raw file", "[.integration]") {
-    auto fpath_raw = test_data_path() / "jungfrau" / "jungfrau_single_master_0.json";
+TEST_CASE("Compare reading from a numpy file with a raw file", "[.files]") {
+    auto fpath_raw = test_data_path() / "raw/jungfrau" / "jungfrau_single_master_0.json";
     REQUIRE(std::filesystem::exists(fpath_raw));
 
-    auto fpath_npy = test_data_path() / "jungfrau" / "jungfrau_single_0.npy";
+    auto fpath_npy = test_data_path() / "raw/jungfrau" / "jungfrau_single_0.npy";
     REQUIRE(std::filesystem::exists(fpath_npy));
 
     File raw(fpath_raw, "r");
@@ -113,6 +113,7 @@ TEST_CASE("Compare reading from a numpy file with a raw file", "[.integration]")
     CHECK(npy.total_frames() == 10);
 
     for (size_t i = 0; i < 10; ++i) {
+        CHECK(raw.tell() == i);
         auto raw_frame = raw.read_frame();
         auto npy_frame = npy.read_frame();
         CHECK((raw_frame.view<uint16_t>() == npy_frame.view<uint16_t>()));

src/RawMasterFile.cpp

@@ -87,7 +87,7 @@ int ScanParameters::start() const { return m_start; }
 int ScanParameters::stop() const { return m_stop; }
 void ScanParameters::increment_stop(){
     m_stop += 1;
-};
+}
 int ScanParameters::step() const { return m_step; }
 const std::string &ScanParameters::dac() const { return m_dac; }
 bool ScanParameters::enabled() const { return m_enabled; }
@@ -140,6 +140,10 @@ std::optional<size_t> RawMasterFile::number_of_rows() const {
 
 xy RawMasterFile::geometry() const { return m_geometry; }
 
+size_t RawMasterFile::n_modules() const {
+    return m_geometry.row * m_geometry.col;
+}
+
 std::optional<uint8_t> RawMasterFile::quad() const { return m_quad; }
 
 // optional values, these may or may not be present in the master file
@@ -417,4 +421,4 @@ void RawMasterFile::parse_raw(const std::filesystem::path &fpath) {
     if(m_frames_in_file==0)
         m_frames_in_file = m_total_frames_expected;
 }
-} // namespace aare
+} // namespace aare

src/RawSubFile.cpp

@@ -1,65 +1,78 @@
 #include "aare/RawSubFile.hpp"
 #include "aare/PixelMap.hpp"
+#include "aare/algorithm.hpp"
+#include "aare/utils/ifstream_helpers.hpp"
+#include "aare/logger.hpp"
+
+
 #include <cstring> // memcpy
 #include <fmt/core.h>
 #include <iostream>
+#include <regex>
+
+
+
 
 namespace aare {
 
 RawSubFile::RawSubFile(const std::filesystem::path &fname,
                        DetectorType detector, size_t rows, size_t cols,
                        size_t bitdepth, uint32_t pos_row, uint32_t pos_col)
-    : m_detector_type(detector), m_bitdepth(bitdepth), m_fname(fname),
+    : m_detector_type(detector), m_bitdepth(bitdepth),
       m_rows(rows), m_cols(cols),
       m_bytes_per_frame((m_bitdepth / 8) * m_rows * m_cols), m_pos_row(pos_row),
       m_pos_col(pos_col) {
+
+    LOG(logDEBUG) << "RawSubFile::RawSubFile()";  
     if (m_detector_type == DetectorType::Moench03_old) {
         m_pixel_map = GenerateMoench03PixelMap();
     } else if (m_detector_type == DetectorType::Eiger && m_pos_row % 2 == 0) {
         m_pixel_map = GenerateEigerFlipRowsPixelMap();
     }
 
-    if (std::filesystem::exists(fname)) {
-        n_frames = std::filesystem::file_size(fname) /
-                   (sizeof(DetectorHeader) + rows * cols * bitdepth / 8);
-    } else {
-        throw std::runtime_error(
-            LOCATION + fmt::format("File {} does not exist", m_fname.string()));
-    }
 
-    // fp = fopen(m_fname.string().c_str(), "rb");
-    m_file.open(m_fname, std::ios::binary);
-    if (!m_file.is_open()) {
-        throw std::runtime_error(
-            LOCATION + fmt::format("Could not open file {}", m_fname.string()));
-    }
-
-#ifdef AARE_VERBOSE
-    fmt::print("Opened file: {} with {} frames\n", m_fname.string(), n_frames);
-    fmt::print("m_rows: {}, m_cols: {}, m_bitdepth: {}\n", m_rows, m_cols,
-               m_bitdepth);
-    fmt::print("file size: {}\n", std::filesystem::file_size(fname));
-#endif
+    parse_fname(fname);
+    scan_files();
+    open_file(m_current_file_index); // open the first file
 }
 
 void RawSubFile::seek(size_t frame_index) {
-    if (frame_index >= n_frames) {
-        throw std::runtime_error(LOCATION + fmt::format("Frame index {} out of range in a file with {} frames", frame_index, n_frames));
+    LOG(logDEBUG) << "RawSubFile::seek(" << frame_index << ")";
+    if (frame_index >= m_total_frames) {
+        throw std::runtime_error(LOCATION + " Frame index out of range: " +
+                                 std::to_string(frame_index));
     }
-    m_file.seekg((sizeof(DetectorHeader) + bytes_per_frame()) * frame_index);
+    m_current_frame_index = frame_index;
+    auto file_index = first_larger(m_last_frame_in_file, frame_index);
+
+    if (file_index != m_current_file_index)
+        open_file(file_index);
+
+    auto frame_offset = (file_index)
+                            ? frame_index - m_last_frame_in_file[file_index - 1]
+                            : frame_index;
+    auto byte_offset = frame_offset * (m_bytes_per_frame + sizeof(DetectorHeader));
+    m_file.seekg(byte_offset);
 }
 
 size_t RawSubFile::tell() {
-    return m_file.tellg() / (sizeof(DetectorHeader) + bytes_per_frame());
+    LOG(logDEBUG) << "RawSubFile::tell():" << m_current_frame_index;
+    return m_current_frame_index;
 }
 
 void RawSubFile::read_into(std::byte *image_buf, DetectorHeader *header) {
+    LOG(logDEBUG) << "RawSubFile::read_into()";
+
     if (header) {
         m_file.read(reinterpret_cast<char *>(header), sizeof(DetectorHeader));
     } else {
         m_file.seekg(sizeof(DetectorHeader), std::ios::cur);
     }
 
+    if (m_file.fail()){
+        throw std::runtime_error(LOCATION + ifstream_error_msg(m_file));
+    }
+
     // TODO! expand support for different bitdepths
     if (m_pixel_map) {
         // read into a temporary buffer and then copy the data to the buffer
@@ -79,8 +92,31 @@ void RawSubFile::read_into(std::byte *image_buf, DetectorHeader *header) {
         // read directly into the buffer
         m_file.read(reinterpret_cast<char *>(image_buf), bytes_per_frame());
     }
+
+    if (m_file.fail()){
+        throw std::runtime_error(LOCATION + ifstream_error_msg(m_file));
+    }
+
+    ++ m_current_frame_index;
+    if (m_current_frame_index >= m_last_frame_in_file[m_current_file_index] &&
+        (m_current_frame_index < m_total_frames)) {
+        ++m_current_file_index;
+        open_file(m_current_file_index);
+    }
 }
 
+void RawSubFile::read_into(std::byte *image_buf, size_t n_frames, DetectorHeader *header) {
+    for (size_t i = 0; i < n_frames; i++) {
+        read_into(image_buf, header);
+        image_buf += bytes_per_frame();
+        if (header) {
+            ++header;
+        }
+    }
+}
+
+
+
 template <typename T>
 void RawSubFile::read_with_map(std::byte *image_buf) {
     auto part_buffer = new std::byte[bytes_per_frame()];
@@ -107,4 +143,69 @@ size_t RawSubFile::frame_number(size_t frame_index) {
     return h.frameNumber;
 }
 
+void RawSubFile::parse_fname(const std::filesystem::path &fname) {
+    LOG(logDEBUG) << "RawSubFile::parse_fname()";
+    // data has the format: /path/too/data/jungfrau_single_d0_f1_0.raw
+    // d0 is the module index, will not change for this file
+    // f1 is the file index - thi is the one we need
+    // 0 is the measurement index, will not change
+    m_path = fname.parent_path();
+    m_base_name = fname.filename();
+
+    // Regex to extract numbers after 'd' and 'f'
+    std::regex pattern(R"(^(.*_d)(\d+)(_f)(\d+)(_\d+\.raw)$)");
+    std::smatch match;
+
+    if (std::regex_match(m_base_name, match, pattern)) {
+        m_offset = std::stoi(match[4].str()); // find the first file index in case of a truncated series
+        m_base_name = match[1].str() + match[2].str() + match[3].str() + "{}" + match[5].str();
+        LOG(logDEBUG) << "Base name: " << m_base_name;
+        LOG(logDEBUG) << "Offset: " << m_offset;
+        LOG(logDEBUG) << "Path: " << m_path.string();
+    } else {
+        throw std::runtime_error(
+            LOCATION + fmt::format("Could not parse file name {}", fname.string()));
+    }
+}
+
+std::filesystem::path RawSubFile::fpath(size_t file_index) const {
+    auto fname = fmt::format(m_base_name, file_index);
+    return m_path / fname;
+}
+
+void RawSubFile::open_file(size_t file_index) {
+    m_file.close();
+    auto fname = fpath(file_index+m_offset);
+    LOG(logDEBUG) << "RawSubFile::open_file():  " << fname.string();
+    m_file.open(fname, std::ios::binary);
+    if (!m_file.is_open()) {
+        throw std::runtime_error(
+            LOCATION + fmt::format("Could not open file {}", fpath(file_index).string()));
+    }
+    m_current_file_index = file_index;
+}
+
+void RawSubFile::scan_files() {
+    LOG(logDEBUG) << "RawSubFile::scan_files()";
+    // find how many files we have and the number of frames in each file
+    m_last_frame_in_file.clear();
+    size_t file_index = m_offset;
+    
+    while (std::filesystem::exists(fpath(file_index))) {
+        auto n_frames = std::filesystem::file_size(fpath(file_index)) /
+                        (m_bytes_per_frame + sizeof(DetectorHeader));
+        m_last_frame_in_file.push_back(n_frames);
+        LOG(logDEBUG) << "Found: " << n_frames << " frames in file: " << fpath(file_index).string();
+        ++file_index;
+    }
+
+    // find where we need to open the next file and total number of frames
+    m_last_frame_in_file = cumsum(m_last_frame_in_file);
+    if(m_last_frame_in_file.empty()){
+        m_total_frames = 0;
+    }else{
+        m_total_frames = m_last_frame_in_file.back();
+    }
+}
+
 } // namespace aare

src/RawSubFile.test.cpp

@@ -0,0 +1,76 @@
+#include "aare/RawSubFile.hpp"
+#include "aare/File.hpp"
+#include "aare/NDArray.hpp"
+#include <catch2/catch_test_macros.hpp>
+#include "test_config.hpp"
+
+using namespace aare;
+
+TEST_CASE("Read frames directly from a RawSubFile", "[.files]"){
+    auto fpath_raw = test_data_path() / "raw/jungfrau" / "jungfrau_single_d0_f0_0.raw";
+    REQUIRE(std::filesystem::exists(fpath_raw));
+
+    RawSubFile f(fpath_raw, DetectorType::Jungfrau, 512, 1024, 16);
+    REQUIRE(f.rows() == 512);
+    REQUIRE(f.cols() == 1024);
+    REQUIRE(f.pixels_per_frame() == 512 * 1024);
+    REQUIRE(f.bytes_per_frame() == 512 * 1024 * 2);
+    REQUIRE(f.bytes_per_pixel() == 2);
+
+
+    auto fpath_npy = test_data_path() / "raw/jungfrau" / "jungfrau_single_0.npy";
+    REQUIRE(std::filesystem::exists(fpath_npy));
+
+    //Numpy file with the same data to use as reference
+    File npy(fpath_npy, "r");
+
+    CHECK(f.frames_in_file() == 10);
+    CHECK(npy.total_frames() == 10);
+
+
+    DetectorHeader header{};
+    NDArray<uint16_t, 2> image({static_cast<ssize_t>(f.rows()), static_cast<ssize_t>(f.cols())});
+    for (size_t i = 0; i < 10; ++i) {
+        CHECK(f.tell() == i);
+        f.read_into(image.buffer(), &header);
+        auto npy_frame = npy.read_frame();
+        CHECK((image.view() == npy_frame.view<uint16_t>()));
+    }
+}
+
+TEST_CASE("Read frames directly from a RawSubFile starting at the second file", "[.files]"){
+    // we know this file has 10 frames with frame numbers 1 to 10
+    // f0 1,2,3
+    // f1 4,5,6 <-- starting here
+    // f2 7,8,9
+    // f3 10
+    
+    auto fpath_raw = test_data_path() / "raw/jungfrau" / "jungfrau_single_d0_f1_0.raw";
+    REQUIRE(std::filesystem::exists(fpath_raw));
+
+    RawSubFile f(fpath_raw, DetectorType::Jungfrau, 512, 1024, 16);
+
+
+    auto fpath_npy = test_data_path() / "raw/jungfrau" / "jungfrau_single_0.npy";
+    REQUIRE(std::filesystem::exists(fpath_npy));
+
+    //Numpy file with the same data to use as reference
+    File npy(fpath_npy, "r");
+    npy.seek(3);
+
+    CHECK(f.frames_in_file() == 7);
+    CHECK(npy.total_frames() == 10);
+
+
+    DetectorHeader header{};
+    NDArray<uint16_t, 2> image({static_cast<ssize_t>(f.rows()), static_cast<ssize_t>(f.cols())});
+    for (size_t i = 0; i < 7; ++i) {
+        CHECK(f.tell() == i);
+        f.read_into(image.buffer(), &header);
+        // frame numbers start at 1 frame index at 0 
+        // adding 3 + 1 to verify the frame number
+        CHECK(header.frameNumber == i + 4); 
+        auto npy_frame = npy.read_frame();
+        CHECK((image.view() == npy_frame.view<uint16_t>()));
+    }
+}

src/algorithm.test.cpp

@@ -160,3 +160,36 @@ TEST_CASE("cumsum works with negative numbers", "[algorithm]") {
     REQUIRE(result[3] == -6);
     REQUIRE(result[4] == -10);
 }
+
+
+TEST_CASE("cumsum on an empty vector", "[algorithm]") {
+    std::vector<double> vec = {};
+    auto result = aare::cumsum(vec);
+    REQUIRE(result.size() == 0);
+
+}
+
+TEST_CASE("All equal on an empty vector is false", "[algorithm]") {
+    std::vector<int> vec = {};
+    REQUIRE(aare::all_equal(vec) == false);
+}
+
+TEST_CASE("All equal on a vector with 1 element is true", "[algorithm]") {
+    std::vector<int> vec = {1};
+    REQUIRE(aare::all_equal(vec) == true);
+}
+
+TEST_CASE("All equal on a vector with 2 elements is true", "[algorithm]") {
+    std::vector<int> vec = {1, 1};
+    REQUIRE(aare::all_equal(vec) == true);
+}
+
+TEST_CASE("All equal on a vector with two different  elements is false", "[algorithm]") {
+    std::vector<int> vec = {1, 2};
+    REQUIRE(aare::all_equal(vec) == false);
+}
+
+TEST_CASE("Last element is different", "[algorithm]") {
+    std::vector<int> vec = {1, 1, 1, 1, 2};
+    REQUIRE(aare::all_equal(vec) == false);
+}

src/decode.cpp

@@ -1,5 +1,5 @@
 #include "aare/decode.hpp"
-
+#include <cmath>
 namespace aare {
 
 uint16_t adc_sar_05_decode64to16(uint64_t input){
@@ -22,8 +22,12 @@ uint16_t adc_sar_05_decode64to16(uint64_t input){
 }
 
 void adc_sar_05_decode64to16(NDView<uint64_t, 2> input, NDView<uint16_t,2> output){
-    for(int64_t i = 0; i < input.shape(0); i++){
-        for(int64_t j = 0; j < input.shape(1); j++){
+    if(input.shape() != output.shape()){
+        throw std::invalid_argument(LOCATION + " input and output shapes must match");
+    }
+
+    for(ssize_t i = 0; i < input.shape(0); i++){
+        for(ssize_t j = 0; j < input.shape(1); j++){
             output(i,j) = adc_sar_05_decode64to16(input(i,j));
         }
     }
@@ -49,13 +53,50 @@ uint16_t adc_sar_04_decode64to16(uint64_t input){
 }
 
 void adc_sar_04_decode64to16(NDView<uint64_t, 2> input, NDView<uint16_t,2> output){
-    for(int64_t i = 0; i < input.shape(0); i++){
-        for(int64_t j = 0; j < input.shape(1); j++){
+    if(input.shape() != output.shape()){
+        throw std::invalid_argument(LOCATION + " input and output shapes must match");
+    }
+    for(ssize_t i = 0; i < input.shape(0); i++){
+        for(ssize_t j = 0; j < input.shape(1); j++){
             output(i,j) = adc_sar_04_decode64to16(input(i,j));
         }
     }
 }
 
+double apply_custom_weights(uint16_t input, const NDView<double, 1> weights) {
+    if(weights.size() > 16){
+        throw std::invalid_argument("weights size must be less than or equal to 16");
+    }
+
+    double result = 0.0;
+    for (ssize_t i = 0; i < weights.size(); ++i) {
+        result += ((input >> i) & 1) * std::pow(weights[i], i);
+    }
+    return result;
+
+}
+
+void apply_custom_weights(NDView<uint16_t, 1> input, NDView<double, 1> output, const NDView<double,1> weights) {
+    if(input.shape() != output.shape()){
+        throw std::invalid_argument(LOCATION + " input and output shapes must match");
+    }
+
+    //Calculate weights to avoid repeatedly calling std::pow
+    std::vector<double> weights_powers(weights.size());
+    for (ssize_t i = 0; i < weights.size(); ++i) {
+        weights_powers[i] = std::pow(weights[i], i);
+    }
+
+    // Apply custom weights to each element in the input array
+    for (ssize_t i = 0; i < input.shape(0); i++) {            
+        double result = 0.0;
+        for (size_t bit_index = 0; bit_index < weights_powers.size(); ++bit_index) {
+            result += ((input(i) >> bit_index) & 1) * weights_powers[bit_index];
+        }
+        output(i) = result;
+    }
+}
+
 
 
 } // namespace aare

src/decode.test.cpp

@@ -0,0 +1,80 @@
+#include "aare/decode.hpp"
+
+#include <catch2/matchers/catch_matchers_floating_point.hpp>
+#include <catch2/catch_test_macros.hpp>
+#include "aare/NDArray.hpp"
+using Catch::Matchers::WithinAbs;
+#include <vector>
+
+TEST_CASE("test_adc_sar_05_decode64to16"){
+    uint64_t input = 0;
+    uint16_t output = aare::adc_sar_05_decode64to16(input);
+    CHECK(output == 0);
+
+
+    // bit 29 on th input is bit 0 on the output
+    input = 1UL << 29;
+    output = aare::adc_sar_05_decode64to16(input);
+    CHECK(output == 1);
+
+    // test all bits by iteratting through the bitlist
+    std::vector<int> bitlist = {29, 19, 28, 18, 31, 21, 27, 20, 24, 23, 25, 22};
+    for (size_t i = 0; i < bitlist.size(); i++) {
+        input = 1UL << bitlist[i];
+        output = aare::adc_sar_05_decode64to16(input);
+        CHECK(output == (1 << i));
+    }
+
+    
+    // test a few "random" values
+    input = 0;
+    input |= (1UL << 29);
+    input |= (1UL << 19);
+    input |= (1UL << 28);
+    output = aare::adc_sar_05_decode64to16(input);
+    CHECK(output == 7UL);
+
+
+    input = 0;
+    input |= (1UL << 18);
+    input |= (1UL << 27);
+    input |= (1UL << 25);
+    output = aare::adc_sar_05_decode64to16(input);
+    CHECK(output == 1096UL);
+
+    input = 0;
+    input |= (1UL << 25);
+    input |= (1UL << 22);
+    output = aare::adc_sar_05_decode64to16(input);
+    CHECK(output == 3072UL);
+ }
+
+
+ TEST_CASE("test_apply_custom_weights") {
+
+    uint16_t input = 1;
+    aare::NDArray<double, 1> weights_data({3}, 0.0);
+    weights_data(0) = 1.7;
+    weights_data(1) = 2.1;
+    weights_data(2) = 1.8;
+
+    auto weights = weights_data.view();
+
+
+    double output = aare::apply_custom_weights(input, weights);
+    CHECK_THAT(output, WithinAbs(1.0, 0.001));
+
+    input = 1 << 1;
+    output = aare::apply_custom_weights(input, weights);
+    CHECK_THAT(output, WithinAbs(2.1, 0.001));
+
+
+    input = 1 << 2;
+    output = aare::apply_custom_weights(input, weights);
+    CHECK_THAT(output, WithinAbs(3.24, 0.001));
+
+    input = 0b111;
+    output = aare::apply_custom_weights(input, weights);
+    CHECK_THAT(output, WithinAbs(6.34, 0.001));
+
+ }

src/utils/ifstream_helpers.cpp

@@ -0,0 +1,18 @@
+#include "aare/utils/ifstream_helpers.hpp"
+
+namespace aare {
+
+std::string ifstream_error_msg(std::ifstream &ifs) {
+    std::ios_base::iostate state = ifs.rdstate();
+    if (state & std::ios_base::eofbit) {
+        return " End of file reached";
+    } else if (state & std::ios_base::badbit) {
+        return " Bad file stream";
+    } else if (state & std::ios_base::failbit) {
+        return " File read failed";
+    }else{
+        return " Unknown/no error";
+    }
+}
+
+} // namespace aare

update_version.py

@@ -0,0 +1,57 @@
+# SPDX-License-Identifier: LGPL-3.0-or-other
+# Copyright (C) 2021 Contributors to the Aare Package
+"""
+Script to update VERSION file with semantic versioning if provided as an argument, or with 0.0.0 if no argument is provided.
+"""
+
+import sys
+import os
+import re
+
+from packaging.version import Version, InvalidVersion
+
+
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+
+def is_integer(value): 
+    try:
+        int(value)
+    except ValueError:
+        return False
+    else:
+        return True
+
+
+def get_version():
+
+    # Check at least one argument is passed
+    if len(sys.argv) < 2:
+        return "0.0.0"
+
+    version = sys.argv[1]
+
+    try:
+        v = Version(version)  # normalize check if version follows PEP 440 specification
+        
+        version_normalized = version.replace("-", ".")
+
+        version_normalized =  re.sub(r'0*(\d+)', lambda m : str(int(m.group(0))), version_normalized) #remove leading zeros 
+
+        return version_normalized 
+
+    except InvalidVersion as e:
+        print(f"Invalid version {version}. Version format must follow semantic versioning format of python PEP 440 version identification specification.")
+        sys.exit(1)
+    
+
+def write_version_to_file(version):
+    version_file_path = os.path.join(SCRIPT_DIR, "VERSION")
+    with open(version_file_path, "w") as version_file:
+        version_file.write(version)
+    print(f"Version {version} written to VERSION file.")
+
+# Main script
+if __name__ == "__main__":
+
+    version = get_version()
+    write_version_to_file(version)