Merge branch 'neuroinformatics-unit:main' into dhruv

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
           - id: requirements-txt-fixer
           - id: trailing-whitespace
     - repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.0.287
+      rev: v0.0.291
       hooks:
         - id: ruff
     - repo: https://github.com/psf/black

CONTRIBUTING.md

@@ -144,7 +144,7 @@ The version number is automatically determined from the latest tag on the _main_
 ## Contributing documentation
 
 The documentation is hosted via [GitHub pages](https://pages.github.com/) at
-[neuroinformatics-unit.github.io/movement](https://neuroinformatics-unit.github.io/movement/).
+[movement.neuroinformatics.dev](https://movement.neuroinformatics.dev).
 Its source files are located in the `docs` folder of this repository.
 They are written in either [reStructuredText](https://docutils.sourceforge.io/rst.html) or
 [markdown](https://myst-parser.readthedocs.io/en/stable/syntax/typography.html).
@@ -185,7 +185,7 @@ my_new_file
 ### Updating the API reference
 If your PR introduces new public-facing functions, classes, or methods,
 make sure to add them to the `docs/source/api_index.rst` page, so that they are
-included in the [API reference](https://neuroinformatics-unit.github.io/movement/api_index.html),
+included in the [API reference](https://movement.neuroinformatics.dev/api_index.html),
 e.g.:
 
 ```rst
@@ -204,7 +204,7 @@ that follow the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html
 
 ### Updating the examples
 We use [sphinx-gallery](https://sphinx-gallery.github.io/stable/index.html)
-to create the [examples](https://neuroinformatics-unit.github.io/movement/auto_examples/index.html).
+to create the [examples](https://movement.neuroinformatics.dev/auto_examples/index.html).
 To add new examples, you will need to create a new `.py` file in `examples/`.
 The file should be structured as specified in the relevant
 [sphinx-gallery documentation](https://sphinx-gallery.github.io/stable/syntax.html).

README.md

@@ -4,19 +4,21 @@
 [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v0.json)](https://github.com/charliermarsh/ruff)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)
 [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
+[![project chat](https://img.shields.io/badge/zulip-join_chat-brightgreen.svg)](https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement/topic/Welcome!)
 
 # movement
 
 Kinematic analysis of animal 🐝 🦀 🐀 🐒 body movements for neuroscience and ethology research 🔬.
 
-- Read the [documentation](https://neuroinformatics-unit.github.io/movement/) for more information.
+- Read the [documentation](https://movement.neuroinformatics.dev) for more information.
 - If you wish to contribute, please read the [contributing guide](./CONTRIBUTING.md).
+- Join us on [zulip](https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement/topic/Welcome!) to chat with the team. We welcome your questions and suggestions.
 
 ## Status
 > **Warning**
 > - 🏗️ The package is currently in early development. Stay tuned ⌛
 > - It is not sufficiently tested to be used for scientific analysis
-> - The interface is subject to changes. [Open an issue](https://github.com/neuroinformatics-unit/movement/issues) if you have suggestions.
+> - The interface is subject to changes.
 
 ## Aims
 * Load pose tracks from pose estimation software packages (e.g. [DeepLabCut](http://www.mackenziemathislab.org/deeplabcut) or [SLEAP](https://sleap.ai/))

docs/source/conf.py

@@ -125,7 +125,7 @@
 # The default is the URL of the GitHub pages
 # https://www.sphinx-doc.org/en/master/usage/extensions/githubpages.html
 github_user = "neuroinformatics-unit"
-html_baseurl = "https://neuroinformatics-unit.github.io/movement/"
+html_baseurl = "https://movement.neuroinformatics.dev"
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,

docs/source/getting_started.md

@@ -36,7 +36,7 @@ pip install --upgrade movement
 
 :::{tab-item} Developers
 To get the latest development version, clone the
-[GitHub repository](https://neuroinformatics-unit.github.io/movement/)
+[GitHub repository](https://github.com/neuroinformatics-unit/movement/)
 and then run from inside the repository:
 
 ```sh

docs/source/index.md

@@ -27,11 +27,15 @@ Index of all functions, classes, and methods.
 :::
 ::::
 
+:::{admonition} Chat with us!
+We welcome your questions and suggestions. Join us on [zulip](https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement/topic/Welcome!) to chat with the team.
+:::
+
 ## Status
 :::{warning}
 - 🏗️ The package is currently in early development. Stay tuned ⌛
 - It is not sufficiently tested to be used for scientific analysis
-- The interface is subject to changes. [Open an issue](https://github.com/neuroinformatics-unit/movement/issues) if you have suggestions.
+- The interface is subject to changes
 :::
 
 

movement/logging.py

@@ -31,34 +31,37 @@ def configure_logging(
 
     # Set the log directory and file path
     log_directory.mkdir(parents=True, exist_ok=True)
-    log_file = log_directory / f"{logger_name}.log"
-
-    # If a logger with the given name is already configured
-    if logger_name in logging.root.manager.loggerDict:
-        logger = logging.getLogger(logger_name)
-        handlers = logger.handlers[:]
-        # If the log file path has changed
-        if log_file.as_posix() != handlers[0].baseFilename:  # type: ignore
-            # remove the handlers to allow for reconfiguration
-            for handler in handlers:
-                logger.removeHandler(handler)
-        else:
-            # otherwise, do nothing
-            return
+    log_file = (log_directory / f"{logger_name}.log").as_posix()
+
+    # Check if logger with the given name is already configured
+    logger_configured = logger_name in logging.root.manager.loggerDict
 
     logger = logging.getLogger(logger_name)
-    logger.setLevel(log_level)
 
-    # Create a rotating file handler
-    max_log_size = 5 * 1024 * 1024  # 5 MB
-    handler = RotatingFileHandler(log_file, maxBytes=max_log_size)
+    # Logger needs to be (re)configured if unconfigured or
+    # if configured but the log file path has changed
+    configure_logger = (
+        not logger_configured
+        or log_file != logger.handlers[0].baseFilename  # type: ignore
+    )
+
+    if configure_logger:
+        if logger_configured:
+            # remove the handlers to allow for reconfiguration
+            logger.handlers.clear()
+
+        logger.setLevel(log_level)
+
+        # Create a rotating file handler
+        max_log_size = 5 * 1024 * 1024  # 5 MB
+        handler = RotatingFileHandler(log_file, maxBytes=max_log_size)
 
-    # Create a formatter and set it to the handler
-    formatter = logging.Formatter(FORMAT)
-    handler.setFormatter(formatter)
+        # Create a formatter and set it to the handler
+        formatter = logging.Formatter(FORMAT)
+        handler.setFormatter(formatter)
 
-    # Add the handler to the logger
-    logger.addHandler(handler)
+        # Add the handler to the logger
+        logger.addHandler(handler)
 
 
 def log_error(error, message: str, logger_name: str = "movement"):

pyproject.toml

@@ -34,11 +34,11 @@ classifiers = [
 ]
 
 [project.urls]
-homepage = "https://github.com/neuroinformatics-unit/movement"
-bug_tracker = "https://github.com/neuroinformatics-unit/movement/issues"
-documentation = "https://github.com/neuroinformatics-unit/movement"
-source_code = "https://github.com/neuroinformatics-unit/movement"
-user_support = "https://github.com/neuroinformatics-unit/movement/issues"
+"Homepage" = "https://github.com/neuroinformatics-unit/movement"
+"Bug Tracker" = "https://github.com/neuroinformatics-unit/movement/issues"
+"Documentation" = "https://movement.neuroinformatics.dev/"
+"Source Code" = "https://github.com/neuroinformatics-unit/movement"
+"User Support" = "https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement"
 
 [project.optional-dependencies]
 dev = [

tests/conftest.py

@@ -1,10 +1,35 @@
 import logging
+import os
+import stat
 
+import h5py
+import numpy as np
+import pandas as pd
 import pytest
+import xarray as xr
 
+from movement.datasets import fetch_pose_data_path
+from movement.io import PosesAccessor
 from movement.logging import configure_logging
 
 
+def pytest_configure():
+    """Perform initial configuration for pytest.
+    Fetches pose data file paths as a dictionary for tests."""
+    pytest.POSE_DATA = {
+        file_name: fetch_pose_data_path(file_name)
+        for file_name in [
+            "DLC_single-wasp.predictions.h5",
+            "DLC_single-wasp.predictions.csv",
+            "DLC_two-mice.predictions.csv",
+            "SLEAP_single-mouse_EPM.analysis.h5",
+            "SLEAP_single-mouse_EPM.predictions.slp",
+            "SLEAP_three-mice_Aeon_proofread.analysis.h5",
+            "SLEAP_three-mice_Aeon_proofread.predictions.slp",
+        ]
+    }
+
+
 @pytest.fixture(autouse=True)
 def setup_logging(tmp_path):
     """Set up logging for the test module.
@@ -14,3 +39,174 @@ def setup_logging(tmp_path):
         logger_name="movement",
         log_directory=(tmp_path / ".movement"),
     )
+
+
+@pytest.fixture
+def unreadable_file(tmp_path):
+    """Return a dictionary containing the file path and
+    expected permission for an unreadable h5 file."""
+    file_path = tmp_path / "unreadable.h5"
+    with open(file_path, "w") as f:
+        f.write("unreadable data")
+    os.chmod(f.name, not stat.S_IRUSR)
+    yield {
+        "file_path": file_path,
+        "expected_permission": "r",
+    }
+    os.chmod(f.name, stat.S_IRUSR)
+
+
+@pytest.fixture
+def unwriteable_file(tmp_path):
+    """Return a dictionary containing the file path and
+    expected permission for an unwriteable h5 file."""
+    unwriteable_dir = tmp_path / "no_write"
+    unwriteable_dir.mkdir()
+    os.chmod(unwriteable_dir, not stat.S_IWUSR)
+    file_path = unwriteable_dir / "unwriteable.h5"
+    yield {
+        "file_path": file_path,
+        "expected_permission": "w",
+    }
+    os.chmod(unwriteable_dir, stat.S_IWUSR)
+
+
+@pytest.fixture
+def wrong_ext_file(tmp_path):
+    """Return a dictionary containing the file path,
+    expected permission, and expected suffix for a file
+    with an incorrect extension.
+    """
+    file_path = tmp_path / "wrong_extension.txt"
+    with open(file_path, "w") as f:
+        f.write("")
+    return {
+        "file_path": file_path,
+        "expected_permission": "r",
+        "expected_suffix": ["h5", "csv"],
+    }
+
+
+@pytest.fixture
+def nonexistent_file(tmp_path):
+    """Return a dictionary containing the file path and
+    expected permission for a nonexistent file."""
+    file_path = tmp_path / "nonexistent.h5"
+    return {
+        "file_path": file_path,
+        "expected_permission": "r",
+    }
+
+
+@pytest.fixture
+def directory(tmp_path):  # used in save_poses, validators
+    """Return a dictionary containing the file path and
+    expected permission for a directory."""
+    file_path = tmp_path / "directory"
+    file_path.mkdir()
+    return {
+        "file_path": file_path,
+        "expected_permission": "r",
+    }
+
+
+@pytest.fixture
+def h5_file_no_dataframe(tmp_path):
+    """Return a dictionary containing the file path and
+    expected datasets for an h5 file with no dataframe."""
+    file_path = tmp_path / "no_dataframe.h5"
+    with h5py.File(file_path, "w") as f:
+        f.create_dataset("data_in_list", data=[1, 2, 3])
+    return {
+        "file_path": file_path,
+        "expected_datasets": ["dataframe"],
+    }
+
+
+@pytest.fixture
+def fake_h5_file(tmp_path):  # used in save_poses, validators
+    """Return a dictionary containing the file path,
+    expected exception, and expected datasets for
+    a file with .h5 extension that is not in HDF5 format.
+    """
+    file_path = tmp_path / "fake.h5"
+    with open(file_path, "w") as f:
+        f.write("")
+    return {
+        "file_path": file_path,
+        "expected_datasets": ["dataframe"],
+        "expected_permission": "w",
+    }
+
+
+@pytest.fixture
+def invalid_single_animal_csv_file(tmp_path):
+    """Return the file path for a fake single-animal csv file."""
+    file_path = tmp_path / "fake_single_animal.csv"
+    with open(file_path, "w") as f:
+        f.write("scorer,columns\nsome,columns\ncoords,columns\n")
+        f.write("1,2")
+    return file_path
+
+
+@pytest.fixture
+def invalid_multi_animal_csv_file(tmp_path):
+    """Return the file path for a fake multi-animal csv file."""
+    file_path = tmp_path / "fake_multi_animal.csv"
+    with open(file_path, "w") as f:
+        f.write(
+            "scorer,columns\nindividuals,columns\nbodyparts,columns\nsome,columns\n"
+        )
+        f.write("1,2")
+    return file_path
+
+
+@pytest.fixture
+def dlc_style_df():
+    """Return a valid DLC-style DataFrame."""
+    return pd.read_hdf(pytest.POSE_DATA.get("DLC_single-wasp.predictions.h5"))
+
+
+@pytest.fixture
+def valid_tracks_array():
+    """Return a function that generate different kinds
+    of valid tracks array."""
+
+    def _valid_tracks_array(array_type):
+        """Return a valid tracks array."""
+        if array_type == "single_keypoint_array":
+            return np.zeros((10, 2, 1, 2))
+        elif array_type == "single_track_array":
+            return np.zeros((10, 1, 2, 2))
+        else:  # "multi_track_array":
+            return np.zeros((10, 2, 2, 2))
+
+    return _valid_tracks_array
+
+
+@pytest.fixture
+def valid_pose_dataset(valid_tracks_array):
+    """Return a valid pose tracks dataset."""
+    dim_names = PosesAccessor.dim_names
+    tracks_array = valid_tracks_array("multi_track_array")
+    return xr.Dataset(
+        data_vars={
+            "pose_tracks": xr.DataArray(tracks_array, dims=dim_names),
+            "confidence": xr.DataArray(
+                tracks_array[..., 0],
+                dims=dim_names[:-1],
+            ),
+        },
+        coords={
+            "time": np.arange(tracks_array.shape[0]),
+            "individuals": ["ind1", "ind2"],
+            "keypoints": ["key1", "key2"],
+            "space": ["x", "y"],
+        },
+        attrs={
+            "fps": None,
+            "time_unit": "frames",
+            "source_software": "SLEAP",
+            "source_file": "test.h5",
+        },
+    )