Add documentation and __init__ files to make auto importing easier.

docs/index.rst

@@ -1,17 +1,15 @@
-.. sinusoidal documentation main file.
-   You can adapt this file completely to your liking, but it should at least
-   contain the root `toctree` directive.
-
 Welcome to Sorcha's community utilities documentation!
-========================================================================================
-
+======================================================
 
+Sorcha Community Utils is a collection of plugins for Sorcha that can be used to
+model changes to the magnitude of objects in the solar system simulation.
 
 .. toctree::
    :hidden:
 
    Home page <self>
-   Contributing <contributing>
+   Usage <usage>
    Community Modules <community_modules>
    Notebooks <notebooks>
+   Contributing <contributing>
    API Reference <autoapi/index>

docs/notebooks/lightcurve/sinusoidal/sinusoidal_example.ipynb

@@ -41,7 +41,7 @@
     "import pandas as pd\n",
     "\n",
     "data_dict = {\n",
-    "    'FieldMJD': [60277.351867, 60289.319749, 60289.330920, 60292.334497, 60292.346208],\n",
+    "    'FieldMJD_TAI': [60277.351867, 60289.319749, 60289.330920, 60292.334497, 60292.346208],\n",
     "    'LCA': [1, 1, 1, 1, 1],\n",
     "    'Period': [0.001, 0.001, 0.001, 0.001, 0.001],\n",
     "    'Time0': [60277.351867, 60277.351867, 60277.351867, 60277.351867, 60277.351867],\n",

docs/usage.rst

@@ -0,0 +1,20 @@
+Using Sorcha Community Utils
+============================
+
+In order to use the community utilities, first install this package in your
+virtual environment.
+
+.. code:: bash
+
+    >> pip install sorcha-community-utils
+
+Once the ``sorcha-community-utils`` is installed, Sorcha will automatically detect 
+the available plugins and make them available during processing.
+
+To use one of the plugins from the community utilities, simply add the unique
+name of the plugin to the configuration file provided to Sorcha, and provide the
+complex parameters file on the command line.
+
+For more information about running Sorcha, the configuration file, and providing 
+arguments on the command line, see the documentation available 
+`here <https://sorcha.readthedocs.io/en/latest/gettingstarted.html#setting-up-sorcha-s-configuration-file>`_.

src/sorcha_community_utils/__init__.py

@@ -0,0 +1,4 @@
+__all__ = [
+    "activity",
+    "lightcurve",
+]

src/sorcha_community_utils/activity/__init__.py

@@ -0,0 +1 @@
+from .lsst_comet import lsst_comet_activity

src/sorcha_community_utils/lightcurve/__init__.py

@@ -0,0 +1 @@
+from .sinusoidal import sinusoidal_lightcurve

src/sorcha_community_utils/lightcurve/sinusoidal/sinusoidal_lightcurve.py

@@ -11,13 +11,13 @@ class SinusoidalLightCurve(AbstractLightCurve):
     The observation dataframe provided to the ``compute``
     method should have the following columns:
 
-    * ``FieldMJD`` - time of observation.
+    * ``FieldMJD_TAI`` - time of observation.
     * ``LCA`` - lightcurve amplitude [magnitudes].
     * ``Period`` - period of the sinusoidal oscillation [days]. Should be a positive value.
     * ``Time0`` - phase for the light curve [days].
     """
 
-    def __init__(self, required_column_names: List[str] = ["FieldMJD", "LCA", "Period", "Time0"]) -> None:
+    def __init__(self, required_column_names: List[str] = ["FieldMJD_TAI", "LCA", "Period", "Time0"]) -> None:
         super().__init__(required_column_names)
 
     def compute(self, df: pd.DataFrame) -> np.array:
@@ -39,7 +39,7 @@ def compute(self, df: pd.DataFrame) -> np.array:
         # Verify that the input data frame contains each of the required columns.
         self._validate_column_names(df)
 
-        time = 2 * np.pi * (df["FieldMJD"] - df["Time0"]) / df["Period"]
+        time = 2 * np.pi * (df["FieldMJD_TAI"] - df["Time0"]) / df["Period"]
         return df["LCA"] * np.sin(time)
 
     @staticmethod

tests/lightcurve/sinusoidal/test_sinusoidal.py

@@ -9,7 +9,7 @@ def test_sinusoidal_lightcurve_name():
 
 def test_compute_simple():
     data_dict = {
-        "FieldMJD": [1./4],
+        "FieldMJD_TAI": [1.0 / 4],
         "LCA": [1],
         "Period": [1],
         "Time0": [0],