First pass at adding napari reader

.github/workflows/build.yml

@@ -24,21 +24,13 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
-      # note: if you need dependencies from conda, considering using
-      # setup-miniconda: https://github.com/conda-incubator/setup-miniconda
-      # and
-      # tox-conda: https://github.com/tox-dev/tox-conda
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install setuptools tox tox-gh-actions
+          python -m pip install setuptools tox tox-gh-actions
 
-      # this runs the platform-specific tests declared in tox.ini
       - name: Test with tox
         run: tox
-        env:
-          PLATFORM: ${{ matrix.platform }}
 
       - name: Coverage
-        if: runner.os == 'Linux' && matrix.python-version == 3.9
         uses: codecov/codecov-action@v2

btrack/napari/reader.py

@@ -0,0 +1,96 @@
+"""
+This module is a reader plugin btrack files for napari.
+"""
+from pathlib import Path
+from typing import Callable, List, Optional, Sequence, Union
+
+from napari.types import LayerDataTuple
+from napari_plugin_engine import napari_hook_implementation
+
+from btrack.dataio import HDF5FileHandler
+from btrack.utils import tracks_to_napari
+
+# Type definitions
+PathLike = Union[str, Path]
+PathOrPaths = Union[PathLike, Sequence[PathLike]]
+ReaderFunction = Callable[[PathOrPaths], List[LayerDataTuple]]
+
+
+@napari_hook_implementation
+def get_reader(path: PathOrPaths) -> Optional[ReaderFunction]:
+    """A basic implementation of the napari_get_reader hook specification.
+
+    Parameters
+    ----------
+    path : str or list of str
+        Path to file, or list of paths.
+
+    Returns
+    -------
+    function or None
+        If the path is a recognized format, return a function that accepts the
+        same path or list of paths, and returns a list of layer data tuples.
+    """
+    return reader_function
+
+
+def reader_function(path: PathLike) -> List[LayerDataTuple]:
+    """Take a path or list of paths and return a list of LayerData tuples.
+
+    Readers are expected to return data as a list of tuples, where each tuple
+    is (data, [add_kwargs, [layer_type]]), "add_kwargs" and "layer_type" are
+    both optional.
+
+    Parameters
+    ----------
+    path : str or list of str
+        Path to file, or list of paths.
+
+    Returns
+    -------
+    layer_data : list of tuples
+        A list of LayerData tuples where each tuple in the list contains
+        (data, metadata, layer_type), where data is a numpy array, metadata is
+        a dict of keyword arguments for the corresponding viewer.add_* method
+        in napari, and layer_type is a lower-case string naming the type of
+        layer. Both "meta", and "layer_type" are optional. napari will default
+        to layer_type=="image" if not provided
+    """
+    # handle both a string and a list of strings
+    paths = [path] if isinstance(path, str) else path
+
+    # store the layers to be generated
+    layers = []
+
+    for _path in paths:
+        with HDF5FileHandler(_path, "r") as hdf:
+
+            # get the segmentation if there is one
+            if "segmentation" in hdf._hdf:
+                segmentation = hdf.segmentation
+                layers.append((segmentation, {}, "labels"))
+
+            # iterate over object types and create a layer for each
+            for obj_type in hdf.object_types:
+
+                # set the object type, and retrieve the tracks
+                hdf.object_type = obj_type
+
+                if f"tracks/{obj_type}" not in hdf._hdf:
+                    continue
+
+                tracklets = hdf.tracks
+                tracks, properties, graph = tracks_to_napari(tracklets, ndim=2)
+
+                # optional kwargs for the corresponding viewer.add_* method
+                # https://napari.org/docs/api/napari.components.html#module-napari.components.add_layers_mixin
+                add_kwargs = {
+                    "properties": properties,
+                    "graph": graph,
+                    "name": obj_type,
+                    "blending": "translucent",
+                }
+
+                layer = (tracks, add_kwargs, "tracks")
+                layers.append(layer)
+    return layers

btrack/napari/tests/test_btrack_reader.py

@@ -0,0 +1,33 @@
+import pytest
+# Only run tests is napari is installed
+pytest.importorskip("napari")
+
+from btrack.napari.reader import get_reader
+
+
+# # tmp_path is a pytest fixture
+# def test_reader(tmp_path):
+#     """An example of how you might test your plugin."""
+#
+#     # write some fake data using your supported file format
+#     my_test_file = str(tmp_path / "myfile.npy")
+#     original_data = np.random.rand(20, 20)
+#     np.save(my_test_file, original_data)
+#
+#     # try to read it back in
+#     reader = napari_get_reader(my_test_file)
+#     assert callable(reader)
+#
+#     # make sure we're delivering the right format
+#     layer_data_list = reader(my_test_file)
+#     assert isinstance(layer_data_list, list) and len(layer_data_list) > 0
+#     layer_data_tuple = layer_data_list[0]
+#     assert isinstance(layer_data_tuple, tuple) and len(layer_data_tuple) > 0
+#
+#     # make sure it's the same as it started
+#     np.testing.assert_allclose(original_data, layer_data_tuple[0])
+
+
+def test_get_reader_pass():
+    reader = get_reader("fake.file")
+    assert reader is not None

napari.yaml

@@ -0,0 +1,11 @@
+contributions:
+  commands:
+  - id: btrack.read_btrack
+    title: Read BayesianTracker files
+    python_name: btrack.napari.reader:get_reader
+
+  readers:
+  - command: btrack.read_btrack
+    filename_patterns:
+    - ['*.h5', '*.hdf', '*.hdf5']
+    accepts_directories: false

requirements-napari.txt

@@ -0,0 +1 @@
+napari

setup.cfg

@@ -1,6 +1,14 @@
 [metadata]
 description-file = README.md
 
+[options.entry_points]
+napari.manifest =
+    example-plugin = example_plugin:napari.yaml
+
+# make sure it gets included in your package
+[options.package_data]
+example-plugin = napari.yaml
+
 [flake8]
 # Ignores - https://lintlyci.github.io/Flake8Rules
 # E203  Whitespace before ':'  (sometimes conflicts with black)

setup.py

@@ -23,6 +23,8 @@ def get_version():
 DESCRIPTION = "A framework for Bayesian multi-object tracking"
 LONG_DESCRIPTION = __doc__
 
+extras = ['docs', 'napari']
+extras_require = {extra: get_install_required(extra) for extra in extras}
 
 setup(
     name="btrack",
@@ -36,7 +38,7 @@ def get_version():
     packages=find_packages(),
     package_data={"btrack": ["libs/libtracker*", "VERSION.txt"]},
     install_requires=get_install_required(),
-    extras_require={"docs": get_install_required("docs")},
+    extras_require=extras_require,
     python_requires=">=3.6",
     license="LICENSE.md",
     classifiers=[

tox.ini

@@ -1,29 +1,21 @@
 # For more information about tox, see https://tox.readthedocs.io/en/latest/
 [tox]
-envlist = py{37,38,39}-{linux,macos,windows}
+envlist = py{37,38,39}{,-napari}
 
 [gh-actions]
 python =
     3.7: py37
     3.8: py38
-    3.9: py39
-
-[gh-actions:env]
-PLATFORM =
-    ubuntu-latest: linux
-    macos-latest: macos
-    windows-latest: windows
+    3.9: py39, py39-napari
 
 [testenv]
 platform =
     macos: darwin
     linux: linux
     windows: windows
-passenv =
-    CI
-    GITHUB_ACTIONS
-    NUMPY_EXPERIMENTAL_ARRAY_FUNCTION
 deps =
     pytest  # https://docs.pytest.org/en/latest/contents.html
     pytest-cov  # https://pytest-cov.readthedocs.io/en/latest/
+extras =
+    napari: napari
 commands = pytest -v --color=yes --cov=btrack --cov-report=xml