environment and requirements micro-update

environment.yml

@@ -1,10 +1,10 @@
 name: simple
 channels:
-  - http://ssb.stsci.edu/astroconda
   - defaults
   - conda-forge
+  - http://ssb.stsci.edu/astroconda
 dependencies:
-  - python=3.8
+  - python=3.9.16
   - pip
   - pip:
     - -r requirements.txt

requirements.txt

@@ -1,18 +1,18 @@
-astrodbkit2
-astropy
-bokeh
-flask
-flask-cors
-flask-wtf
-markdown2
-multiprocess
-numpy
-pandas
-pysqlite3
-pytest
-requests
-specutils
-sqlalchemy
-tqdm
-werkzeug
-wtforms
+astrodbkit2>=0.5.1
+astropy>=5.2.0
+bokeh==3.0.2
+flask>=3.0.1
+flask-cors>=4.0.0
+flask-wtf>=1.2.1
+markdown2>=2.4.12
+multiprocess>=0.70.16
+numpy>=1.24.0
+pandas>=2.0.0
+pysqlite3>=0.5.2
+pytest>=8.0.0
+requests>=2.31.0
+specutils>=1.12.0
+sqlalchemy>=2.0.25
+tqdm>=4.66.1
+werkzeug>=3.0.1
+wtforms>=3.1.2

simple_app/utils.py

@@ -721,7 +721,7 @@ def absolute_magnitudes(df: pd.DataFrame, all_bands: np.ndarray) -> pd.DataFrame
         The output dataframe with absolute mags calculated
     """
 
-    def pogson_law(m: Union[float, np.ndarray]) -> Union[float, np.ndarray]:
+    def pogson_law(m: Union[float, pd.Series]) -> Union[float, np.ndarray]:
         """
         Distance modulus equation. Calculates the absolute magnitude only for sources with a positive parallax,
         otherwise returns a NaN
@@ -735,7 +735,10 @@ def pogson_law(m: Union[float, np.ndarray]) -> Union[float, np.ndarray]:
         _
             Absolute magnitude
         """
-        return np.where(df.parallax > 0, m + 5 * np.log10(df.parallax, where=df.parallax > 0) - 10, np.nan)
+        mask = df.parallax > 0
+        _abs_mag = np.full_like(m, fill_value=np.nan)
+        _abs_mag[mask] = m[mask] + 5 * np.log10(df.parallax[mask]) - 10
+        return _abs_mag
 
     # create absolute magnitude for each apparent magnitude
     d_magnitudes: Dict[str, np.ndarray] = {}