define type alias for Array (#82)

* define type alias for Array

* remove TypeAlias (not supported in python 3.9)

* use Union

* remove Array type alias from test coverage

* test on 3.12

* update tox

* add numpy matrix

* change matrix

* change matrix

* loosen numpy dep.

* add setuptools for tests

* change GHA

* change matrix

* change matrix

* change matrix

* change matrix

* change matrix

* change matrix

* change matrix

* change GHA and narrow down python version

* change GHA

* squeeze index array

* correct )

* change event mult

* change call to size

* change numpy dep + testing

* disable xp test

* remove torch tests (not compatible with numpy 2.0)

* ignore torch enabled lines for test coverage

* configure 2 test envs

.github/workflows/c_python_build.yml

@@ -23,7 +23,8 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, windows-latest] # not building on mac-os because there is no OpenMP
-        python-version: ['3.9','3.11']
+        python-version: [3.9, 3.12]
+        test-env: [test-numpy-1, test-numpy-2]
 
     steps:
     - uses: actions/checkout@v4
@@ -47,7 +48,7 @@ jobs:
         pdm show --version
     - name: Install dependencies and package
       run: |
-        pdm install -d -G test
+        pdm install -d -G ${{ matrix.test-env }}
 
     - if: matrix.os == 'ubuntu-latest'
       name: Run Tests

examples/05_algorithms/03_run_mlem_projection_data.py

@@ -28,7 +28,7 @@
 
 # %%
 from __future__ import annotations
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 import array_api_compat.numpy as xp
 

examples/05_algorithms/04_run_osem_projection_data.py

@@ -28,7 +28,7 @@
 
 # %%
 from __future__ import annotations
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 import array_api_compat.numpy as xp
 

examples/05_algorithms/07_run_mlem_open_geometry.py

@@ -29,7 +29,7 @@
 
 # %%
 from __future__ import annotations
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 import array_api_compat.numpy as xp
 

examples/05_algorithms/utils.py

@@ -1,6 +1,6 @@
 from collections.abc import Sequence
 import abc
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 from types import ModuleType
 

examples/06_listmode_algorithms/01_listmode_mlem.py

@@ -30,7 +30,7 @@
 
 # %%
 from __future__ import annotations
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 import array_api_compat.numpy as xp
 

examples/06_listmode_algorithms/02_listmode_osem.py

@@ -30,7 +30,7 @@
 
 # %%
 from __future__ import annotations
-from array_api_strict._array_object import Array
+from parallelproj import Array
 
 import array_api_compat.numpy as xp
 

pyproject.toml

@@ -6,13 +6,12 @@ authors = [
     {name = "Georg Schramm", email = "[email protected]"},
 ]
 dependencies = [
-    "numpy~=1.23",
+    "numpy>=1.23",
     "scipy~=1.0",
     "array-api-compat~=1.7",
-    "array-api-strict~=1.0",
     "matplotlib~=3.8",
 ]
-requires-python = ">=3.9"
+requires-python = ">=3.9,<3.13"
 readme = "README.md"
 license = {text = "MIT"}
 classifiers = [
@@ -31,13 +30,20 @@ build-backend = "pdm.backend"
 distribution = true
 
 [tool.pdm.dev-dependencies]
-test = [
+test-numpy-1 = [
     "pytest>=8.1.1",
     "pytest-cov>=4.1.0",
-    "torch~=2.0",
+    "array-api-strict~=1.0",
+    "numpy<2",
+    "torch~=2.0"
 ]
-numpy122 = [
+test-numpy-2 = [
+    "pytest>=8.1.1",
+    "pytest-cov>=4.1.0",
+    "array-api-strict~=1.0",
+    "numpy>=2"
 ]
+
 [tool.coverage.report]
 exclude_lines = [
     "def __repr__",
@@ -61,6 +67,9 @@ exclude_lines = [
     "if cupy_enabled",
     "lib_parallelproj_c_fname",
     "empty_cuda_cache",
-    "__str__"
+    "__str__",
+    "Array =",
+    "elif not cupy_enabled and torch_enabled",
+    "elif cupy_enabled and not torch_enabled"
 ]
 

src/parallelproj/__init__.py

@@ -18,6 +18,7 @@
     lib_parallelproj_c_fname,
     lib_parallelproj_cuda_fname,
     cuda_kernel_file,
+    Array,
 )
 
 from .operators import (
@@ -95,9 +96,10 @@
     "SinogramSpatialAxisOrder",
     "RegularPolygonPETLORDescriptor",
     "EqualBlockPETLORDescriptor",
+    "Array",
 ]
 
-if os.getenv('PARALLELPROJ_SILENT_IMPORT') is None:
+if os.getenv("PARALLELPROJ_SILENT_IMPORT") is None:
     print(
         f"""
               -  -  -  -  -  -  -  -   -  -  -  -

src/parallelproj/backend.py

@@ -17,9 +17,10 @@
 import numpy as np
 import array_api_compat
 import numpy.ctypeslib as npct
-from array_api_strict._array_object import Array
 
 from types import ModuleType
+from typing import Union
+
 
 # check if cuda is present
 cuda_present = shutil.which("nvidia-smi") is not None
@@ -30,9 +31,26 @@
 # check if cupy is available
 torch_enabled = importlib.util.find_spec("torch") is not None
 
-# define type for cupy or numpy array
-if cupy_enabled:
+if cupy_enabled and torch_enabled:
     import array_api_compat.cupy as cp
+    import array_api_compat.torch as torch
+
+    # type alias for array
+    Array = Union[np.ndarray, cp.ndarray, torch.Tensor]
+elif cupy_enabled and not torch_enabled:
+    import array_api_compat.cupy as cp
+
+    # type alias for array
+    Array = Union[np.ndarray, cp.ndarray]
+elif not cupy_enabled and torch_enabled:
+    import array_api_compat.torch as torch
+
+    # type alias for array
+    Array = Union[np.ndarray, torch.Tensor]
+else:
+    # type alias for array
+    Array = np.ndarray
+
 
 # numpy ctypes lib array definitions
 ar_1d_single = npct.ndpointer(dtype=ctypes.c_float, ndim=1, flags="C")
@@ -1434,10 +1452,12 @@ def count_event_multiplicity(events: Array) -> Array:
         tmp = np.unique(events, axis=0, return_counts=True, return_inverse=True)
 
     mu = xp.asarray(tmp[2][tmp[1]], device=dev)
+    mu = xp.reshape(mu, (array_api_compat.size(mu),))
 
     return mu
 
 
+
 def to_numpy_array(x: Array) -> np.ndarray:
     """convert an array to a numpy array
 

src/parallelproj/operators.py

@@ -7,7 +7,7 @@
 import numpy as np
 import array_api_compat
 from array_api_compat import device
-from array_api_strict._array_object import Array
+from parallelproj import Array
 from collections.abc import Sequence
 
 import parallelproj

src/parallelproj/pet_lors.py

@@ -5,7 +5,7 @@
 import abc
 import enum
 import array_api_compat.numpy as np
-from array_api_strict._array_object import Array
+from parallelproj import Array
 import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d.art3d import Line3DCollection
 
@@ -107,7 +107,7 @@ def __init__(
         self._scanner = scanner
         self._all_block_pairs = all_block_pairs
         self._num_lorendpoints_per_block = self.scanner.modules[0].num_lor_endpoints
-        self._num_lors_per_block_pair = self._num_lorendpoints_per_block ** 2
+        self._num_lors_per_block_pair = self._num_lorendpoints_per_block**2
 
     @property
     def all_block_pairs(self) -> Array:

src/parallelproj/pet_scanners.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import abc
-from array_api_strict._array_object import Array
+from parallelproj import Array
 import matplotlib.pyplot as plt
 
 from types import ModuleType

src/parallelproj/projectors.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import array_api_compat.numpy as np
-from array_api_strict._array_object import Array
+from parallelproj import Array
 import array_api_compat
 import matplotlib.pyplot as plt
 from matplotlib.patches import Rectangle
@@ -885,21 +885,21 @@ def convert_sinogram_to_listmode(
 
                 num_events_ss = int(self.xp.sum(ss))
 
-                event_start_coords[
-                    event_offset : (event_offset + num_events_ss), :
-                ] = self.xp.take(xstart, event_sino_inds, axis=0)
-                event_end_coords[
-                    event_offset : (event_offset + num_events_ss), :
-                ] = self.xp.take(xend, event_sino_inds, axis=0)
+                event_start_coords[event_offset : (event_offset + num_events_ss), :] = (
+                    self.xp.take(xstart, event_sino_inds, axis=0)
+                )
+                event_end_coords[event_offset : (event_offset + num_events_ss), :] = (
+                    self.xp.take(xend, event_sino_inds, axis=0)
+                )
 
                 if self.tof:
-                    event_tofbins[
-                        event_offset : (event_offset + num_events_ss)
-                    ] = self.xp.full(
-                        num_events_ss,
-                        it - num_tofbins // 2,
-                        device=self._dev,
-                        dtype=self.xp.int16,
+                    event_tofbins[event_offset : (event_offset + num_events_ss)] = (
+                        self.xp.full(
+                            num_events_ss,
+                            it - num_tofbins // 2,
+                            device=self._dev,
+                            dtype=self.xp.int16,
+                        )
                     )
 
                 event_offset += num_events_ss

tests/test_projectors.py

@@ -191,8 +191,6 @@ def test_lmprojector(
         xstart, xend, img_dim, voxel_size, img_origin
     )
 
-    assert lm_proj.xp == xp
-
     assert xp.all(lm_proj.event_start_coordinates == xstart)
     assert xp.all(lm_proj.event_end_coordinates == xend)
 

tox.ini

@@ -1,12 +1,16 @@
 [tox]
 minversion = 4.0
-envlist = py{39,312}-np{122,126}
+envlist = py{39,312}-numpy{123,20}
 
 [testenv]
 groups = test
 deps =
-  np122: numpy>=1.22,<1.23, setuptools
-  np126: numpy>=1.26,<1.27
+    setuptools
+    pytest>=8.1.1
+    pytest-cov>=4.1.0
+    array-api-strict~=1.0
+    numpy123: numpy==1.23
+    numpy20: numpy>=2.0
 passenv = MPLBACKEND, PARALLELPROJ_*
 commands =
     pytest tests -v --cov-report term-missing --cov "{envsitepackagesdir}/parallelproj"  --cov-fail-under=100