Release v1.0.1

.bumper.toml

@@ -1,5 +1,5 @@
 [tool.bumper]
-current_version = "1.0.0"
+current_version = "1.0.1"
 
 [[tool.bumper.files]]
 file = "./pyproject.toml"

.github/workflows/lint_test.yml

@@ -58,10 +58,11 @@ jobs:
         python-version: ${{ matrix.python-version }}
 
     - name: Set up (deadsnakes) Python ${{ matrix.python-version }}
-      uses: deadsnakes/action@v3.1.0
+      uses: deadsnakes/action@v3.2.0
       if: endsWith(matrix.python-version, '-dev')
       with:
         python-version: ${{ matrix.python-version }}
+        tk: true
 
     - name: Install dependencies
       run: |

.pre-commit-config.yaml

@@ -35,6 +35,6 @@ repos:
       -  id: python-check-blanket-type-ignore
       -  id: python-use-type-annotations
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.1
+    rev: v0.8.4
     hooks:
       - id: ruff

CHANGELOG.md

@@ -1,2 +1,10 @@
 # Changelog
 Versions follow [Semantic Versioning](https://semver.org/spec/v2.0.0.html) (`<major>`.`<minor>`.`<patch>`)
+
+## [v1.0.1]
+### Fixed
+* #8 Fix snapping error when plotting timedelta-based axis data
+
+
+## [v1.0.0]
+Initial release - yay!

README.md

@@ -1,5 +1,5 @@
 # matplotlib-window
-[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/matplotlib-window/1.0.0?logo=python&logoColor=FFD43B)](https://pypi.org/project/matplotlib-window/)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/matplotlib-window/1.0.1?logo=python&logoColor=FFD43B)](https://pypi.org/project/matplotlib-window/)
 [![PyPI](https://img.shields.io/pypi/v/matplotlib-window?logo=Python&logoColor=FFD43B)](https://pypi.org/project/matplotlib-window/)
 [![PyPI - License](https://img.shields.io/pypi/l/matplotlib-window?color=magenta)](https://github.com/sco1/matplotlib-window/blob/main/LICENSE)
 [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/sco1/matplotlib-window/main.svg)](https://results.pre-commit.ci/latest/github/sco1/matplotlib-window/main)

matplotlib_window/base.py

@@ -3,6 +3,7 @@
 from enum import StrEnum
 from functools import partial
 
+import numpy as np
 from matplotlib.axes import Axes
 from matplotlib.backend_bases import Event, FigureCanvasBase, MouseEvent
 from matplotlib.lines import Line2D
@@ -192,6 +193,18 @@ def limit_drag(plotted_data: npt.ArrayLike, query: float) -> float:
     # Data series may not be sorted, so use min/max
     # I'm not sure how to properly type annotate this right now
     min_val, max_val = plotted_data.min(), plotted_data.max()  # type: ignore[union-attr]
+
+    # Per #8, numpy's timedeltas don't support gt/lt so we need to extract a different value for our
+    # comparison if we're using them
+    # If the reach ends up being wider then it might be better to perform a more generic check but
+    # for now the explicit conversion should cover the currently encountered use cases
+    if isinstance(min_val, np.timedelta64):  # min_val and max_val should be the same type
+        # I couldn't figure out how to access the timedelta unit that numpy holds internally, but
+        # casting to float seems to work well enough to keep it in the same dimension being used for
+        # the plot
+        min_val = min_val.astype(float)
+        max_val = max_val.astype(float)
+
     if query > max_val:
         return max_val  # type: ignore[no-any-return]
     elif query < min_val:

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "matplotlib-window"
-version = "1.0.0"
+version = "1.0.1"
 description = "Draggable data windowing for matplotlib plots"
 authors = [
     {name = "sco1", email = "[email protected]"}

tests/test_base_helpers.py

@@ -24,6 +24,26 @@ def test_limit_drag(query: NUMERIC_T, truth_out: NUMERIC_T) -> None:
     assert limit_drag(plotted_data=PLOTTED_DATA, query=query) == pytest.approx(truth_out)
 
 
+PLOTTED_TIMEDELTA = np.array([np.timedelta64(i) for i in range(1, 6)])
+NP_TIMEDELTA_LIMIT_DRAG_TEST_CASES = (
+    (-1, 1),
+    (-1.0, 1),
+    (1, 1),
+    (1.0, 1.0),
+    (3, 3),
+    (3.0, 3),
+    (5, 5),
+    (5.0, 5),
+    (7, 5),
+    (7.0, 5),
+)
+
+
+@pytest.mark.parametrize(("query", "truth_out"), NP_TIMEDELTA_LIMIT_DRAG_TEST_CASES)
+def test_limit_np_timedelta_drag(query: NUMERIC_T, truth_out: NUMERIC_T) -> None:
+    assert limit_drag(plotted_data=PLOTTED_TIMEDELTA, query=query) == pytest.approx(truth_out)
+
+
 def test_transform_rect() -> None:
     _, ax = plt.subplots()
     ax.set(xlim=(-10, 10), ylim=(-10, 10))