Merge 'origin/main' into feature/cuda_clusterfinder

python/tests/test_InterpolationAPI.py

@@ -0,0 +1,31 @@
+import pytest 
+
+from aare import Interpolator, ClusterVector, Etai, Cluster
+
+import numpy as np 
+
+
+def test_interpolation_api():
+    eta_distribution = np.zeros((10, 10, 1)) # dummy eta distribution 
+    etax_bins = np.linspace(0, 1.0, 11) 
+    etay_bins = np.linspace(0, 1.0, 11)
+    e_bins = np.array([0., 10.]) # dummy energy bins
+    interpolator = Interpolator(eta_distribution, etax_bins, etay_bins, e_bins)
+
+    cluster_vector = ClusterVector()
+    cluster_vector.push_back(Cluster(10, 5, np.ones(shape=9, dtype=np.int32)))
+    cluster_vector.push_back(Cluster(20, 10, np.ones(shape=9, dtype=np.int32)))
+
+    eta1 = Etai()
+    eta1.x = 0.1
+    eta1.y = 0.1
+    eta1.sum = 5
+    eta2 = Etai()
+    eta2.x = 0.1
+    eta2.y = 0.9
+    eta2.sum = 6
+    etas = np.array([eta1, eta2]) # dummy etas for the clusters
+
+    photons = interpolator.interpolate(cluster_vector, etas)
+
+    assert photons.size == cluster_vector.size # should return one photon per cluster

python/tests/test_Pedestal.py

@@ -0,0 +1,40 @@
+import numpy as np
+import pytest
+
+from aare import Pedestal_d, Pedestal_f
+
+
+@pytest.mark.parametrize(
+    ("pedestal_type", "expected_dtype"),
+    [(Pedestal_d, np.float64), (Pedestal_f, np.float32)],
+)
+def test_numpy_array_minus_pedestal(pedestal_type, expected_dtype):
+    pedestal = pedestal_type(2, 3)
+    pedestal.push(np.array([[2, 4, 6], [8, 10, 12]], dtype=np.uint16))
+    array = np.array([[12, 14, 16], [18, 20, 22]], dtype=np.uint16)
+
+    result = array - pedestal
+
+    np.testing.assert_array_equal(
+        result, np.array([[10, 10, 10], [10, 10, 10]], dtype=expected_dtype)
+    )
+    assert result.dtype == expected_dtype
+
+
+def test_numpy_array_minus_pedestal_rejects_incompatible_shape():
+    pedestal = Pedestal_d(2, 3)
+    array = np.zeros((2, 2), dtype=np.float64)
+
+    with pytest.raises(ValueError):
+        array - pedestal
+
+
+def test_pedestal_exposes_mean_as_read_only_buffer():
+    pedestal = Pedestal_d(2, 3)
+    pedestal.push(np.array([[2, 4, 6], [8, 10, 12]], dtype=np.uint16))
+
+    mean = np.asarray(pedestal)
+
+    np.testing.assert_array_equal(mean, pedestal.view())
+    assert np.shares_memory(mean, pedestal.view())
+    assert not mean.flags.writeable

python/tests/test_Transformation.py

@@ -8,10 +8,10 @@ def test_matterhorn10_16bit(test_data_path):
     with CtbRawFile(test_data_path / "raw/Matterhorn10/16bit_master_0.json", transform = transform.Matterhorn10Transform(dynamic_range=16, num_counters=1)) as f:
         headers, frames = f.read_frame()
 
-        assert frames.shape == (256, 256)
+        assert frames.shape == (1, 256, 256)
         assert frames.dtype == np.uint16
 
-        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint16), (256, 1)) # TODO: endianess issue ? 
+        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint16), (1, 256, 1)) # TODO: endianess issue ? 
 
         assert np.all(frames == expected_data)
 
@@ -22,24 +22,23 @@ def test_matterhorn10_8bit(test_data_path):
     with CtbRawFile(test_data_path / "raw/Matterhorn10/8bit_master_1.json", transform = transform.Matterhorn10Transform(dynamic_range=8, num_counters=1)) as f:
         headers, frames = f.read_frame()
 
-        assert frames.shape == (256, 256)
+        assert frames.shape == (1, 256, 256)
         assert frames.dtype == np.uint8
 
-        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint8), (256, 1)) # TODO: endianess issue ? 
+        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint8), (1, 256, 1)) # TODO: endianess issue ? 
 
         assert np.all(frames == expected_data)
 
-
 @pytest.mark.withdata
 def test_matterhorn10_4bit(test_data_path): 
     """ Matterhorn10Transform 1 counter 4 bit dynamic range """
     with CtbRawFile(test_data_path / "raw/Matterhorn10/newnewrun_4bit_1counter_master_0.json", transform = transform.Matterhorn10Transform(dynamic_range=4, num_counters=1)) as f:
         headers, frames = f.read_frame()
 
-        assert frames.shape == (256, 256)
+        assert frames.shape == (1, 256, 256)
         assert frames.dtype == np.uint8
 
-        expected_data = np.tile(np.tile(np.arange(15, -1, -1, dtype=np.uint8), 16), (256, 1)) # TODO: endianess issue ? 
+        expected_data = np.tile(np.tile(np.arange(15, -1, -1, dtype=np.uint8), 16), (1, 256, 1)) # TODO: endianess issue ? 
 
         assert np.all(frames == expected_data)
 
@@ -50,9 +49,9 @@ def test_matterhorn10_16bit_4counters(test_data_path):
     with CtbRawFile(test_data_path / "raw/Matterhorn10/4counter_16bit_master_4.json", transform = transform.Matterhorn10Transform(dynamic_range=16, num_counters=4)) as f:
         headers, frames = f.read_frame()
 
-        assert frames.shape == (4*256, 256)
+        assert frames.shape == (4, 256, 256)
         assert frames.dtype == np.uint16
 
-        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint16), (4*256, 1)) # TODO: endianess issue ? 
+        expected_data = np.tile(np.arange(255, -1, -1,dtype=np.uint16), (4, 256, 1)) # TODO: endianess issue ? 
 
         assert np.all(frames == expected_data)