Added tests and documentation to iris.planning.num_repeats()

.github/workflows/tests.yml

@@ -0,0 +1,45 @@
+
+name: tests
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [
+          ubuntu-latest,
+          windows-latest,
+          macOS-latest,
+        ]
+        python-version: ["3.11",]
+    name: ${{ matrix.os }}, Python ${{ matrix.python-version }} tests
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install package
+        run: |
+          python -m pip install --upgrade pip
+          pip install setuptools wheel
+          pip install -e .[test]
+      - name: Test with pytest
+        run: |
+          pip install pytest pytest-cov
+          pytest --cov=. --cov-report=html
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          file: coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella

iris/_tests/test_planning.py

@@ -0,0 +1,46 @@
+from __future__ import annotations
+import pytest
+import astropy.units as u
+import astropy.time
+import iris
+
+
+@pytest.mark.parametrize(
+    argnames="time_start",
+    argvalues=[
+        "2024-01-29T00:00:00",
+    ],
+)
+@pytest.mark.parametrize(
+    argnames="time_stop",
+    argvalues=[
+        "2024-01-29T04:00:00",
+
+    ],
+)
+@pytest.mark.parametrize(
+    argnames="timedelta_raster",
+    argvalues=[
+        1 * u.hr,
+    ],
+)
+@pytest.mark.parametrize(
+    argnames="timedelta_slew",
+    argvalues=[
+        20 * u.min,
+    ],
+)
+def test_num_repeats(
+    time_start: str | astropy.time.Time,
+    time_stop: str | astropy.time.Time,
+    timedelta_raster: u.Quantity,
+    timedelta_slew: u.Quantity,
+):
+    result = iris.planning.num_repeats(
+        time_start=time_start,
+        time_stop=time_stop,
+        timedelta_raster=timedelta_raster,
+        timedelta_slew=timedelta_slew,
+    )
+    assert isinstance(result, float)
+    assert result > 0

iris/planning.py

@@ -1,3 +1,9 @@
+"""
+Utilities for planning IRIS observations
+"""
+
+from __future__ import annotations
+import numpy as np
 import astropy.units as u
 import astropy.time
 
@@ -7,17 +13,48 @@
 
 
 def num_repeats(
-    time_start,
-    time_stop,
-    time_raster,
-    time_slew=10 * u.min,
-):
+    time_start: str | astropy.time.Time,
+    time_stop: str | astropy.time.Time,
+    timedelta_raster: u.Quantity,
+    timedelta_slew: u.Quantity = 10 * u.min,
+) -> np.ndarray:
+    """
+    Calculate the number of times we can repeat a raster given the start and stop
+    times and the length of the raster.
+
+    Parameters
+    ----------
+    time_start
+        The starting time of the observation
+    time_stop
+        The stop time of the observation
+    timedelta_raster
+        The amount of time needed to complete one raster
+    timedelta_slew
+        The amount of time needed to slew before the observation begins
+
+    Examples
+    --------
+    Determine how many times we can repeat a 1-hour raster from 00:00 to 04:00
+
+    .. jupyter-execute::
+
+        import astropy.units as u
+        import iris
+
+        iris.planning.num_repeats(
+            time_start="2024-01-01T00:00",
+            time_stop="2024-01-01T04:00",
+            timedelta_raster=1 * u.hr,
+        )
+    """
     if not isinstance(time_start, astropy.time.Time):
         time_start = astropy.time.Time(time_start)
     if not isinstance(time_stop, astropy.time.Time):
         time_stop = astropy.time.Time(time_stop)
 
-    result = (time_stop - time_start - time_slew) / time_raster
-    result = result.to(u.dimensionless_unscaled)
+    timedelta_full = time_stop - time_start
+    result = (timedelta_full - timedelta_slew) / timedelta_raster
+    result = result.to(u.dimensionless_unscaled).value
 
     return result