added working 'get_foraging_bouts' function

.github/workflows/build_env_run_tests.yml

@@ -4,14 +4,14 @@
 name: build_env_run_tests
 on:
   pull_request:
-    branches: [ main ]
+    branches: [main]
     types: [opened, reopened, synchronize]
-  workflow_dispatch:  # allows running manually from Github's 'Actions' tab
+  workflow_dispatch: # allows running manually from Github's 'Actions' tab
 
 jobs:
-  build_env_pip_pyproject:  # checks only for building env using pip and pyproject.toml
-    name: Build env using pip and pyproject.toml
-    runs-on: ubuntu-latest
+  build_env_run_tests: # checks for building env using pyproject.toml and runs codebase checks and tests
+    name: Build env using pip and pyproject.toml on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
     if: github.event.pull_request.draft == false
     strategy:
       matrix:
@@ -20,70 +20,43 @@ jobs:
       fail-fast: false
     defaults:
       run:
-        shell: bash -l {0}  # reset shell for each step
+        shell: ${{ matrix.os == 'windows-latest' && 'cmd' || 'bash' }} -l {0} # Adjust shell based on OS
     steps:
       - name: Checkout code
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
       - name: Create venv and install dependencies
         run: |
           python -m venv .venv
-          source .venv/bin/activate
+          .venv/Scripts/activate || source .venv/bin/activate
           pip install -e .[dev]
           pip list
-          .venv/bin/python -c "import aeon"
-
-  build_env_run_tests:  # checks for building env using mamba and runs codebase checks and tests
-    name: Build env and run tests on ${{ matrix.os }}
-    runs-on: ${{ matrix.os }}
-    if: github.event.pull_request.draft == false
-    strategy:
-      matrix:
-        os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: [3.11]
-      fail-fast: false
-    defaults:
-      run:
-        shell: bash -l {0}  # reset shell for each step
-    steps:
-      - name: checkout repo
-        uses: actions/checkout@v2
-      - name: set up conda env
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          use-mamba: true
-          miniforge-variant: Mambaforge
-          python-version: ${{ matrix.python-version }}
-          environment-file: ./env_config/env.yml
-          activate-environment: aeon
-      - name: Update conda env with dev reqs
-        run: mamba env update -f ./env_config/env_dev.yml
-
-      # Only run codebase checks and tests for ubuntu.
+          python -c "import aeon"
+      - name: Activate venv for later steps
+        run: |
+          echo "VIRTUAL_ENV=$(pwd)/.venv" >> $GITHUB_ENV
+          echo "$(pwd)/.venv/bin" >> $GITHUB_PATH      # For Unix-like systems
+          echo "$(pwd)/.venv/Scripts" >> $GITHUB_PATH  # For Windows
+      # Only run codebase checks and tests for Linux (ubuntu).
       - name: ruff
-        if: matrix.os == 'ubuntu-latest'
-        run: python -m ruff check --config ./pyproject.toml .
+        run: ruff check .
       - name: pyright
-        if: matrix.os == 'ubuntu-latest'
-        run: python -m pyright --level error --project ./pyproject.toml . 
+        run: pyright --level error --project ./pyproject.toml . 
       - name: pytest
-        if: matrix.os == 'ubuntu-latest'
-        run: python -m pytest tests/
-
+        run: pytest tests/ --ignore=tests/dj_pipeline
       - name: generate test coverage report
-        if: matrix.os == 'ubuntu-latest'
+        if: ${{ matrix.os == 'ubuntu-latest' }}
         run: |
-          python -m pytest --cov=aeon ./tests/ --cov-report=xml:./tests/test_coverage/test_coverage_report.xml
-          #python -m pytest --cov=aeon ./tests/ --cov-report=html:./tests/test_coverage/test_coverage_report_html
+          python -m pytest --cov=aeon tests/ --ignore=tests/dj_pipeline --cov-report=xml:tests/test_coverage/test_coverage_report.xml
       - name: upload test coverage report to codecov
-        if: matrix.os == 'ubuntu-latest'
-        uses: codecov/codecov-action@v2
+        if: ${{ matrix.os == 'ubuntu-latest' }}
+        uses: codecov/codecov-action@v4
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          directory: ./tests/test_coverage/
+          directory: tests/test_coverage/
           files: test_coverage_report.xml
           fail_ci_if_error: true
           verbose: true

.pre-commit-config.yaml

@@ -1,16 +1,12 @@
 # For info on running pre-commit manually, see `pre-commit run --help`
-
-default_language_version:
-  python: python3.11
-
 files: "^(test|aeon)\/.*$"
 repos:
   - repo: meta
     hooks:
       - id: identity
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.6.0
     hooks:
       - id: check-json
       - id: check-yaml
@@ -25,20 +21,17 @@ repos:
       - id: trailing-whitespace
         args: [--markdown-linebreak-ext=md]
 
-  - repo: https://github.com/psf/black
-    rev: 23.7.0
-    hooks:
-      - id: black
-        args: [--check, --config, ./pyproject.toml]
-
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.286
+    rev: v0.6.4
     hooks:
+      # Run the linter with the `--fix` flag.
       - id: ruff
-        args: [--config, ./pyproject.toml]
+        args: [ --fix ]
+      # Run the formatter.
+      - id: ruff-format
 
   - repo: https://github.com/RobertCraigie/pyright-python
-    rev: v1.1.324
+    rev: v1.1.380
     hooks:
       - id: pyright
         args: [--level, error, --project, ./pyproject.toml]

aeon/README.md

@@ -1 +1 @@
-#
+#

aeon/__init__.py

@@ -9,5 +9,5 @@
 finally:
     del version, PackageNotFoundError
 
-# Set functions avaialable directly under the 'aeon' top-level namespace
-from aeon.io.api import load
+# Set functions available directly under the 'aeon' top-level namespace
+from aeon.io.api import load as load  # noqa: PLC0414

aeon/analysis/__init__.py

@@ -1 +0,0 @@
-#

aeon/analysis/block_plotting.py

@@ -1,17 +1,7 @@
-import os
-import pathlib
 from colorsys import hls_to_rgb, rgb_to_hls
-from contextlib import contextmanager
-from pathlib import Path
 
-import matplotlib.pyplot as plt
 import numpy as np
-import pandas as pd
 import plotly
-import plotly.express as px
-import plotly.graph_objs as go
-import seaborn as sns
-from numpy.lib.stride_tricks import as_strided
 
 """Standardize subject colors, patch colors, and markers."""
 
@@ -35,27 +25,21 @@
     "star",
 ]
 patch_markers_symbols = ["●", "⧓", "■", "⧗", "♦", "✖", "×", "▲", "★"]
-patch_markers_dict = {
-    marker: symbol for marker, symbol in zip(patch_markers, patch_markers_symbols)
-}
+patch_markers_dict = dict(zip(patch_markers, patch_markers_symbols, strict=False))
 patch_markers_linestyles = ["solid", "dash", "dot", "dashdot", "longdashdot"]
 
 
 def gen_hex_grad(hex_col, vals, min_l=0.3):
     """Generates an array of hex color values based on a gradient defined by unit-normalized values."""
     # Convert hex to rgb to hls
-    h, l, s = rgb_to_hls(
-        *[int(hex_col.lstrip("#")[i: i + 2], 16) / 255 for i in (0, 2, 4)]
-    )
+    h, l, s = rgb_to_hls(*[int(hex_col.lstrip("#")[i : i + 2], 16) / 255 for i in (0, 2, 4)])  # noqa: E741
     grad = np.empty(shape=(len(vals),), dtype="<U10")  # init grad
     for i, val in enumerate(vals):
-        cur_l = (l * val) + (
-            min_l * (1 - val)
-        )  # get cur lightness relative to `hex_col`
+        cur_l = (l * val) + (min_l * (1 - val))  # get cur lightness relative to `hex_col`
         cur_l = max(min(cur_l, l), min_l)  # set min, max bounds
         cur_rgb_col = hls_to_rgb(h, cur_l, s)  # convert to rgb
-        cur_hex_col = "#%02x%02x%02x" % tuple(
-            int(c * 255) for c in cur_rgb_col
+        cur_hex_col = "#{:02x}{:02x}{:02x}".format(
+            *tuple(int(c * 255) for c in cur_rgb_col)
         )  # convert to hex
         grad[i] = cur_hex_col
 

aeon/analysis/movies.py

@@ -7,9 +7,8 @@
 from aeon.io import video
 
 
-def gridframes(frames, width, height, shape=None):
-    """Arranges a set of frames into a grid layout with the specified
-    pixel dimensions and shape.
+def gridframes(frames, width, height, shape: None | int | tuple[int, int] = None):
+    """Arranges a set of frames into a grid layout with the specified pixel dimensions and shape.
 
     :param list frames: A list of frames to include in the grid layout.
     :param int width: The width of the output grid image, in pixels.
@@ -21,7 +20,7 @@ def gridframes(frames, width, height, shape=None):
     """
     if shape is None:
         shape = len(frames)
-    if type(shape) not in [list, tuple]:
+    if isinstance(shape, int):
         shape = math.ceil(math.sqrt(shape))
         shape = (shape, shape)
 
@@ -44,7 +43,7 @@ def gridframes(frames, width, height, shape=None):
 
 def averageframes(frames):
     """Returns the average of the specified collection of frames."""
-    return cv2.convertScaleAbs(sum(np.multiply(1 / len(frames), frames)))
+    return cv2.convertScaleAbs(np.sum(np.multiply(1 / len(frames), frames)))
 
 
 def groupframes(frames, n, fun):
@@ -65,7 +64,7 @@ def groupframes(frames, n, fun):
             i = i + 1
 
 
-def triggerclip(data, events, before=pd.Timedelta(0), after=pd.Timedelta(0)):
+def triggerclip(data, events, before=None, after=None):
     """Split video data around the specified sequence of event timestamps.
 
     :param DataFrame data:
@@ -76,10 +75,16 @@ def triggerclip(data, events, before=pd.Timedelta(0), after=pd.Timedelta(0)):
     :return:
     A pandas DataFrame containing the frames, clip and sequence numbers for each event timestamp.
     """
-    if before is not pd.Timedelta:
+    if before is None:
+        before = pd.Timedelta(0)
+    elif before is not pd.Timedelta:
         before = pd.Timedelta(before)
-    if after is not pd.Timedelta:
+
+    if after is None:
+        after = pd.Timedelta(0)
+    elif after is not pd.Timedelta:
         after = pd.Timedelta(after)
+
     if events is not pd.Index:
         events = events.index
 
@@ -107,8 +112,7 @@ def collatemovie(clipdata, fun):
 
 
 def gridmovie(clipdata, width, height, shape=None):
-    """Collates a set of video clips into a grid movie with the specified pixel dimensions
-    and grid layout.
+    """Collates a set of video clips into a grid movie with the specified pixel dimensions and grid layout.
 
     :param DataFrame clipdata:
     A pandas DataFrame where each row specifies video path, frame number, clip and sequence number.

aeon/analysis/plotting.py

@@ -6,7 +6,7 @@
 from matplotlib import colors
 from matplotlib.collections import LineCollection
 
-from aeon.analysis.utils import *
+from aeon.analysis.utils import rate, sessiontime
 
 
 def heatmap(position, frequency, ax=None, **kwargs):
@@ -31,21 +31,20 @@ def heatmap(position, frequency, ax=None, **kwargs):
     return mesh, cbar
 
 
-def circle(x, y, radius, fmt=None, ax=None, **kwargs):
+def circle(x, y, radius, *args, ax=None, **kwargs):
     """Plot a circle centered at the given x, y position with the specified radius.
 
     :param number x: The x-component of the circle center.
     :param number y: The y-component of the circle center.
     :param number radius: The radius of the circle.
-    :param str, optional fmt: The format used to plot the circle line.
     :param Axes, optional ax: The Axes on which to draw the circle.
     """
     if ax is None:
         ax = plt.gca()
-    points = pd.DataFrame(np.linspace(0, 2 * math.pi, 360), columns=["angle"])
+    points = pd.DataFrame({"angle": np.linspace(0, 2 * math.pi, 360)})
     points["x"] = radius * np.cos(points.angle) + x
     points["y"] = radius * np.sin(points.angle) + y
-    ax.plot(points.x, points.y, fmt, **kwargs)
+    ax.plot(points.x, points.y, *args, **kwargs)
 
 
 def rateplot(
@@ -60,16 +59,17 @@ def rateplot(
     ax=None,
     **kwargs,
 ):
-    """Plot the continuous event rate and raster of a discrete event sequence, given the specified
-    window size and sampling frequency.
+    """Plot the continuous event rate and raster of a discrete event sequence.
+
+    The window size and sampling frequency can be specified.
 
     :param Series events: The discrete sequence of events.
     :param offset window: The time period of each window used to compute the rate.
     :param DateOffset, Timedelta or str frequency: The sampling frequency for the continuous rate.
     :param number, optional weight: A weight used to scale the continuous rate of each window.
     :param datetime, optional start: The left bound of the time range for the continuous rate.
     :param datetime, optional end: The right bound of the time range for the continuous rate.
-    :param datetime, optional smooth: The size of the smoothing kernel applied to the continuous rate output.
+    :param datetime, optional smooth: The size of the smoothing kernel applied to the rate output.
     :param DateOffset, Timedelta or str, optional smooth:
     The size of the smoothing kernel applied to the continuous rate output.
     :param bool, optional center: Specifies whether to center the convolution kernels.
@@ -108,8 +108,8 @@ def colorline(
     x,
     y,
     z=None,
-    cmap=plt.get_cmap("copper"),
-    norm=plt.Normalize(0.0, 1.0),
+    cmap=None,
+    norm=None,
     ax=None,
     **kwargs,
 ):
@@ -128,9 +128,13 @@ def colorline(
         ax = plt.gca()
     if z is None:
         z = np.linspace(0.0, 1.0, len(x))
+    if cmap is None:
+        cmap = plt.get_cmap("copper")
+    if norm is None:
+        norm = colors.Normalize(0.0, 1.0)
     z = np.asarray(z)
     points = np.array([x, y]).T.reshape(-1, 1, 2)
     segments = np.concatenate([points[:-1], points[1:]], axis=1)
-    lines = LineCollection(segments, array=z, cmap=cmap, norm=norm, **kwargs)
+    lines = LineCollection(segments, array=z, cmap=cmap, norm=norm, **kwargs)  # type: ignore
     ax.add_collection(lines)
     return lines

aeon/analysis/readme.md

@@ -1 +1 @@
-#
+#