Schema Update + Script Addition

sanghi23_ingest.py

@@ -0,0 +1,60 @@
+#SIMPLE & Astrodb Packages
+from astrodb_utils import ingest_publication, ingest_source, load_astrodb, find_source_in_db
+from simple.utils.spectra import * 
+from simple.schema import *
+from simple.schema import REFERENCE_TABLES
+
+#Additional Packages
+import pandas as pd
+
+
+db = load_astrodb("SIMPLE.sqlite", recreatedb=False, reference_tables=REFERENCE_TABLES)
+
+# Ingest New Sources 
+ingest_publication(
+    db,
+    doi = "10.3847/1538-4357/ad0b12")
+
+newsources = pd.read_csv('unavailable_sources.csv') # Read in new sources
+for _, source in newsources.iterrows():
+    ingest_source(
+        db,
+        source = source['name'],
+        ra = source['ra_j2000_formula'],
+        dec = source['dec_j2000_formula'],
+        reference = source['reference'],
+    )
+    print(f"Source {source['name']} ingested")
+
+## Ingest New Fundamental Parameters
+evo_cols = ["name_simbadable", "ra_j2000_formula", "dec_j2000_formula", "teff_evo", "teff_evo_err", "radius_evo", "radius_evo_err", "mass_evo", "mass_evo_err", "logg_evo", "logg_evo_err"]
+evo_table = pd.read_csv('FundamentalPropertiesbyEvoModel.csv')
+
+modeled_parameters_evo_ingest_dict = [
+    {'source': row['name_simbadable'],
+     'ra': row['ra_j2000_formula'], 
+     'dec': row['dec_j2000_formula'],
+     'Radius': {'value': row['radius_evo'], 'value_error': row['radius_evo_err'], 'parameter': "radius", 'unit': 'R_jup', "model": "evolutionary"},
+     'log_g': {'value': row['logg_evo'], 'value_error': row['logg_evo_err'], 'parameter': "log g", 'unit': 'dex', "model": "evolutionary"},
+     'T_eff': {'value': row['teff_evo'], 'value_error': row['teff_evo_err'], 'parameter': "T eff", 'unit': 'K', "model": "evolutionary"},
+     'Mass': {'value': row['mass_evo'], 'value_error': row['mass_evo_err'], 'parameter': "mass", 'unit': 'M_jup', "model": "evolutionary"},
+     'reference': "Sang23"
+     } for _, row in evo_table.iterrows()
+]
+
+
+for i, source_dict in enumerate(modeled_parameters_evo_ingest_dict):  
+    found_source = find_source_in_db(db, source_dict['source'], ra=source_dict['ra'], dec=source_dict['dec'])
+    source_dict['source'] = found_source[0]
+
+value_types = ['Radius', 'log_g', 'T_eff', 'Mass']
+with db.engine.connect() as conn:
+    for row in modeled_parameters_evo_ingest_dict:
+        for value_type in value_types:
+            if row[value_type]['value'] is not None:  
+                conn.execute(db.ModeledParameters.insert().values({'source': row['source'], **row[value_type]}))
+
+    conn.commit()  
+
+# Save to Database
+db.save_database(directory="data/")

simple/schema.py

@@ -432,12 +432,14 @@ class ModeledParameters(Base):
     value = Column(Float, nullable=False)
     value_error = Column(Float)
     unit = Column(String(20))
+    model = Column(String(20))
     comments = Column(String(1000))
     reference = Column(
         String(30),
         ForeignKey("Publications.reference", onupdate="cascade"),
         primary_key=True,
     )
+
 
 
 class CompanionRelationships(Base):