add zero_point as float input

:q
q

src/tape/ensemble.py

@@ -1247,9 +1247,10 @@ def convert_flux_to_mag(self, flux_col, zero_point, err_col=None, zp_form="mag",
         ----------
         flux_col: 'str'
             The name of the ensemble flux column to convert into magnitudes.
-        zero_point: 'str'
+        zero_point: 'str' or 'float'
             The name of the ensemble column containing the zero point
-            information for column transformation.
+            information for column transformation. Alternatively, a float zero
+            point value to apply to all fluxes.
         err_col: 'str', optional
             The name of the ensemble column containing the errors to propagate.
             Errors are propagated using the following approximation:
@@ -1276,15 +1277,24 @@ def convert_flux_to_mag(self, flux_col, zero_point, err_col=None, zp_form="mag",
             out_col_name = flux_col + "_mag"
 
         if zp_form == "flux":  # mag = -2.5*np.log10(flux/zp)
-            self._source = self._source.assign(
-                **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col] / x[zero_point])}
-            )
+            if isinstance(zero_point, str):
+                self._source = self._source.assign(
+                    **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col] / x[zero_point])}
+                )
+            else:
+                self._source = self._source.assign(
+                    **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col] / zero_point)}
+                )
 
         elif zp_form == "magnitude" or zp_form == "mag":  # mag = -2.5*np.log10(flux) + zp
-            self._source = self._source.assign(
-                **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col]) + x[zero_point]}
-            )
-
+            if isinstance(zero_point, str):
+                self._source = self._source.assign(
+                    **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col]) + x[zero_point]}
+                )
+            else:
+                self._source = self._source.assign(
+                    **{out_col_name: lambda x: -2.5 * np.log10(x[flux_col]) + zero_point}
+                )
         else:
             raise ValueError(f"{zp_form} is not a valid zero_point format.")
 

tests/tape_tests/test_ensemble.py

@@ -67,6 +67,7 @@ def test_from_parquet(data_fixture, request):
         # Check to make sure the critical quantity labels are bound to real columns
         assert parquet_ensemble._source[col] is not None
 
+
 @pytest.mark.parametrize(
     "data_fixture",
     [
@@ -103,7 +104,6 @@ def test_from_dataframe(data_fixture, request):
         assert ens._source[col] is not None
 
 
-
 def test_available_datasets(dask_client):
     """
     Test that the ensemble is able to successfully read in the list of available TAPE datasets
@@ -744,10 +744,11 @@ def test_coalesce(dask_client, drop_inputs):
             assert col in ens._source.columns
 
 
+@pytest.mark.parametrize("zero_point", [("zp_mag", "zp_flux"), (25.0, 10**10)])
 @pytest.mark.parametrize("zp_form", ["flux", "mag", "magnitude", "lincc"])
 @pytest.mark.parametrize("err_col", [None, "error"])
 @pytest.mark.parametrize("out_col_name", [None, "mag"])
-def test_convert_flux_to_mag(dask_client, zp_form, err_col, out_col_name):
+def test_convert_flux_to_mag(dask_client, zero_point, zp_form, err_col, out_col_name):
     ens = Ensemble(client=dask_client)
 
     source_dict = {
@@ -770,7 +771,7 @@ def test_convert_flux_to_mag(dask_client, zp_form, err_col, out_col_name):
     ens.from_source_dict(source_dict, column_mapper=col_map)
 
     if zp_form == "flux":
-        ens.convert_flux_to_mag("flux", "zp_flux", err_col, zp_form, out_col_name)
+        ens.convert_flux_to_mag("flux", zero_point[1], err_col, zp_form, out_col_name)
 
         res_mag = ens._source.compute()[output_column].to_list()[0]
         assert pytest.approx(res_mag, 0.001) == 21.28925
@@ -782,7 +783,7 @@ def test_convert_flux_to_mag(dask_client, zp_form, err_col, out_col_name):
             assert output_column + "_err" not in ens._source.columns
 
     elif zp_form == "mag" or zp_form == "magnitude":
-        ens.convert_flux_to_mag("flux", "zp_mag", err_col, zp_form, out_col_name)
+        ens.convert_flux_to_mag("flux", zero_point[0], err_col, zp_form, out_col_name)
 
         res_mag = ens._source.compute()[output_column].to_list()[0]
         assert pytest.approx(res_mag, 0.001) == 21.28925
@@ -795,7 +796,7 @@ def test_convert_flux_to_mag(dask_client, zp_form, err_col, out_col_name):
 
     else:
         with pytest.raises(ValueError):
-            ens.convert_flux_to_mag("flux", "zp_mag", err_col, zp_form, "mag")
+            ens.convert_flux_to_mag("flux", zero_point[0], err_col, zp_form, "mag")
 
 
 def test_find_day_gap_offset(dask_client):