Add method for creating lightcurve for object

pyproject.toml

@@ -23,6 +23,7 @@ dependencies = [
     "ipyfilechooser",
     "ipywidgets",
     "jupyter-app-launcher >=0.3.0",
+    "lightkurve",
     "matplotlib",
     "papermill",
     "pandas",
@@ -193,5 +194,7 @@ filterwarnings = [
     # papermill is using deprecated jupyter paths
     'ignore:Jupyter is migrating its paths to use standard platformdirs:DeprecationWarning',
     # papermill is also using a deprecated method of getting current time
-    'ignore:.*is deprecated and scheduled for removal.*:DeprecationWarning'
+    'ignore:.*is deprecated and scheduled for removal.*:DeprecationWarning',
+    # lightkurve is using a deprecated numpy interface
+    'ignore:.*numpy.core.einsumfunc is deprecated and has been renamed.*:DeprecationWarning'
 ]

stellarphot/conftest.py

@@ -5,8 +5,11 @@
 import pytest
 from astropy.coordinates import SkyCoord
 from astropy.table import Table
+from astropy.utils.data import get_pkg_data_filename
 from pytest_astropy_header.display import PYTEST_HEADER_MODULES, TESTED_VERSIONS
 
+from stellarphot import PhotometryData
+
 # astropy-specific-stuff
 
 
@@ -57,3 +60,22 @@ def tess_tic_expected_values():
         tic_id=236158940,
         expected_coords=SkyCoord(ra=313.41953739, dec=34.35164717, unit="degree"),
     )
+
+
+@pytest.fixture
+def simple_photometry_data():
+    # Grab the test photometry file and simplify it a bit.
+    data_file = get_pkg_data_filename("tests/data/test_photometry_data.ecsv")
+    pd_input = PhotometryData.read(data_file)
+
+    # Keep stars 1, 6, 9, 12, first time slice only
+    # These stars have no NaNs in them and we only need one image to generate
+    # more test data from that.
+    first_slice = pd_input["file"] == "wasp-10-b-S001-R001-C099-r.fit"
+    ids = [1, 6, 9, 12]
+    good_star = pd_input["star_id"] == ids[0]
+
+    for an_id in ids[1:]:
+        good_star = good_star | (pd_input["star_id"] == an_id)
+
+    return pd_input[good_star & first_slice]

stellarphot/core.py

@@ -1,5 +1,6 @@
 import re
 
+import lightkurve as lk
 import numpy as np
 import pandas as pd
 from astropy import units as u
@@ -576,6 +577,82 @@
             # Return BJD at midpoint of exposure at each location
             return Time(time_barycenter + self["exposure"] / 2, scale="tdb")
 
+    def lightcurve_for(
+        self, star_id=None, coordinates=None, name=None, flux_column="mag_inst"
+    ):
+        """
+        Return the light curve for a single star as a `lightkurve.LightCurve` object.
+        One of the parameters `star_id`, `coordinates` or `name` must be specified.
+
+        Parameters
+        ----------
+        star_id : str, optional
+            The star_id of the star in the photometry data. If not provided, coordinates
+            or name must be provided.
+
+        coordinates : `astropy.coordinates.SkyCoord`, optional
+            The coordinates of the star in the photometry data. If not provided, star_id
+            or name must be provided.
+
+        name : str, optional
+            The name of the star in Simbad. If not provided, star_id or coordinates must
+            be provided.
+
+        flux_column : str, optional
+            The name of the column to use as the flux. Default is 'mag_inst'. This need
+            not actually be a flux.
+
+        Returns
+        -------
+        `lightkurve.LightCurve`
+            The light curve for the star. This includes all of the columns in the
+            `stellarphot.`PhotometryData` object and columns ``time``, ``flux``, and
+            ``flux_err``.
+        """
+        num_args = sum([star_id is not None, coordinates is not None, name is not None])
+
+        if num_args == 0:
+            raise ValueError("Either star_id, coordinates or name must be provided.")
+
+        if num_args > 1:
+            raise ValueError(
+                "Only one of star_id, coordinates, or name can be provided."
+            )
+
+        if name is not None:
+            coordinates = SkyCoord.from_name(name)
+
+        if coordinates is not None:
+            # Find the star_id for the closest coordinate match
+            my_coordinates = SkyCoord(self["ra"], self["dec"])
+            idx, d2d, _ = coordinates.match_to_catalog_sky(my_coordinates)
+            star_id = self["star_id"][idx]
+            if d2d > 1 * u.arcsec:
+                raise ValueError(
+                    "No star in the photometry data is close enough to the "
+                    "provided coordinates."
+                )
+
+        star_data = self[self["star_id"] == star_id]
+
+        # Create the columns that light curve needs, adding metadata about where each
+        # column came from.
+        star_data["time"] = star_data["bjd"]
+        star_data.meta["time"] = "BJD at midpoint of exposure, column bjd"
+
+        star_data["flux"] = star_data[flux_column]
+        star_data.meta["flux"] = "Instrumental magnitude, column mag_inst"
+
+        # Why value? Because the instrumental magnitude error is fubar,
+        # see #463
+        flux_error_col = (
+            "mag_error" if flux_column == "mag_inst" else flux_column + "_error"
+        )
+        star_data["flux_err"] = star_data[flux_error_col].value
+        star_data.meta["flux_err"] = "Error in instrumental magnitude, column mag_error"
+
+        return lk.LightCurve(star_data)
+
 
 class CatalogData(BaseEnhancedTable):
     """

stellarphot/tests/test_core.py

@@ -6,7 +6,7 @@
 from astropy.coordinates import SkyCoord
 from astropy.io import ascii, fits
 from astropy.nddata import CCDData
-from astropy.table import Table
+from astropy.table import Table, vstack
 from astropy.time import Time
 from astropy.utils.data import get_pkg_data_filename
 from astropy.wcs import WCS
@@ -1163,3 +1163,82 @@ def test_sourcelist_slicing():
     # Checking attributes survive slicing
     assert slicing_test.has_ra_dec
     assert slicing_test.has_x_y
+
+
+@pytest.mark.parametrize("target_by", ["star_id", "coordinates"])
+@pytest.mark.parametrize("target_star_id", [1, 6])
+def test_to_lightcurve(simple_photometry_data, target_by, target_star_id):
+    # Make a few more rows of data, changing only date_obs, then update the BJD
+    delta_t = 3 * u.minute
+    new_data = [simple_photometry_data.copy()]
+    t_init = simple_photometry_data["date-obs"][0]
+
+    for i in range(1, 5):
+        data = simple_photometry_data.copy()
+        data["date-obs"] = t_init + i * delta_t
+        new_data.append(data)
+
+    # Make a new table with the new data
+    new_table = vstack(new_data)
+
+    select_star_id = simple_photometry_data["star_id"] == target_star_id
+    star_id_coords = SkyCoord(
+        simple_photometry_data["ra"][select_star_id],
+        simple_photometry_data["dec"][select_star_id],
+    )
+
+    selectors = dict(
+        star_id=target_star_id,
+        coordinates=star_id_coords,
+    )
+
+    assert isinstance(new_table, PhotometryData)
+
+    # Grab just the keywords we need for this test
+    selector = {target_by: selectors[target_by]}
+    lc = new_table.lightcurve_for(**selector)
+
+    # We made 5 times, so there should be 5 rows in the lightcurve
+    assert len(lc) == 5
+    assert (lc["star_id"] == target_star_id).all()
+
+
+@pytest.mark.remote_data
+def test_to_lightcurve_from_name(simple_photometry_data):
+    # Make a few more rows of data, changing only date_obs, then update the BJD
+    delta_t = 3 * u.minute
+    new_data = [simple_photometry_data.copy()]
+    t_init = simple_photometry_data["date-obs"][0]
+
+    for i in range(1, 5):
+        data = simple_photometry_data.copy()
+        data["date-obs"] = t_init + i * delta_t
+        new_data.append(data)
+
+    # Make a new table with the new data
+    new_table = vstack(new_data)
+
+    assert isinstance(new_table, PhotometryData)
+
+    lc = new_table.lightcurve_for(name="wasp 10")
+
+    # We made 5 times, so there should be 5 rows in the lightcurve
+    assert len(lc) == 5
+    # wasp 10 is star_id 1
+    assert (lc["star_id"] == 1).all()
+
+
+def test_to_lightcurve_argument_logic(simple_photometry_data):
+    # providing no argument should raise an error
+    with pytest.raises(
+        ValueError, match="Either star_id, coordinates or name must be provided"
+    ):
+        simple_photometry_data.lightcurve_for()
+
+    # providing two arguments should raise an error
+    with pytest.raises(
+        ValueError, match="Only one of star_id, coordinates, or name can be provided"
+    ):
+        simple_photometry_data.lightcurve_for(
+            star_id=1, coordinates=SkyCoord(0, 0, unit="deg")
+        )