Api extra (#166)

Changes to be able to run the example notebooks: 

- Invert gain map on setting (multiplication is faster but user supplies
ADU/energy)
- Cast after applying gain map not to loose precision (Important for
int32 clusters)
- "factor" for ClusterFileSink 
- Cluster size available to be able to create the right file sink

include/aare/GainMap.hpp

@@ -16,10 +16,18 @@ class GainMap {
 
   public:
     explicit GainMap(const NDArray<double, 2> &gain_map)
-        : m_gain_map(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) {
         m_gain_map = NDArray<double, 2>(gain_map);
+        for (auto &item : m_gain_map) {
+            item = 1.0 / item;
+        }
     }
 
     template <typename ClusterType,
@@ -41,7 +49,7 @@ class GainMap {
                 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>(cl.data[j] * m_gain_map(y, x)); //cast after conversion to keep precision
                 }
             } else {
                 // clear edge clusters

python/aare/ClusterFinder.py

@@ -1,5 +1,8 @@
 
 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):
@@ -48,3 +51,17 @@ def ClusterCollector(clusterfindermt, cluster_size = (3,3), dtype=np.int32):
         #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/__init__.py

@@ -11,7 +11,7 @@ from ._aare import ROI
 
 # from ._aare import ClusterFinderMT, ClusterCollector, ClusterFileSink, ClusterVector_i
 
-from .ClusterFinder import ClusterFinder, ClusterCollector, ClusterFinderMT
+from .ClusterFinder import ClusterFinder, ClusterCollector, ClusterFinderMT, ClusterFileSink
 from .ClusterVector import ClusterVector
 
 

python/src/bind_ClusterVector.hpp

@@ -44,11 +44,10 @@ void define_ClusterVector(py::module &m, const std::string &typestr) {
                  auto *vec = new std::vector<Type>(self.sum());
                  return return_vector(vec);
              })
-        .def("sum_2x2",
+        .def("sum_2x2", [](ClusterVector<ClusterType> &self){
-             [](ClusterVector<ClusterType> &self) {
+            auto *vec = new std::vector<Type>(self.sum_2x2());
-                 auto *vec = new std::vector<Type>(self.sum_2x2());
+            return return_vector(vec);
-                 return return_vector(vec);
+        })
-             })
         .def_property_readonly("size", &ClusterVector<ClusterType>::size)
         .def("item_size", &ClusterVector<ClusterType>::item_size)
         .def_property_readonly("fmt",

python/src/cluster.hpp

@@ -93,6 +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)

python/src/module.cpp

@@ -10,13 +10,12 @@
 #include "file.hpp"
 #include "fit.hpp"
 #include "interpolation.hpp"
-#include "pedestal.hpp"
-#include "pixel_map.hpp"
-#include "raw_file.hpp"
-#include "raw_master_file.hpp"
-#include "var_cluster.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

src/ClusterFile.test.cpp

@@ -10,8 +10,9 @@ using aare::Cluster;
 using aare::ClusterFile;
 using aare::ClusterVector;
 
+
 TEST_CASE("Read one frame from a cluster file", "[.files]") {
-    // We know that the frame has 97 clusters
+    //We know that the frame has 97 clusters
     auto fpath = test_data_path() / "clust" / "single_frame_97_clustrers.clust";
     REQUIRE(std::filesystem::exists(fpath));