identify_unknown_sptypes: add colorcoding to the output

identify_unknown_sptypes.py

@@ -1,6 +1,16 @@
 from astroquery.simbad import Simbad
 import pandas as pd
 
+class bcolors:
+    HEADER = '\033[95m'
+    OKBLUE = '\033[94m'
+    OKGREEN = '\033[92m'
+    WARNING = '\033[93m'
+    FAIL = '\033[91m'
+    ENDC = '\033[0m'
+    BOLD = '\033[1m'
+    UNDERLINE = '\033[4m'
+
 simbad = Simbad()
 
 bvStars = ["1RXS J064643.6-770027", "BD-08   995", "CPD-19   878", "PM J07058-5848", "TYC 1360-957-1", "TYC 4595-107-1"]
@@ -69,13 +79,13 @@ for star in bvStars:
     bestMatchIndexUBVonlyWeighted = distancesUBVonlyWeighted.idxmin()
     bestMatchNameUBVonlyWeighted = spTypeTable.iloc[bestMatchIndexUBVonlyWeighted, 0]
 
-    print(f"--- {star['MAIN_ID'].value[0]} ---")
-    print("Table entry: ")
+    print(f"--- {bcolors.BOLD}{bcolors.OKGREEN}{star['MAIN_ID'].value[0]}{bcolors.ENDC} ---")
+    print(f"Best no weights match: {bcolors.FAIL}{bestMatchNameUBV}{bcolors.ENDC}")
     print(spTypeTable.iloc[bestMatchIndexUBVIJHK:bestMatchIndexUBVIJHK+1])
-    print("Weighted Table entry:")
+    print(f"Best weights match: {bcolors.FAIL}{bestMatchNameUBVweighted}{bcolors.ENDC}")
     print(spTypeTable.iloc[bestMatchIndexUBVIJHKweighted:bestMatchIndexUBVIJHKweighted+1])
-    print("UBV Table entry:")
+    print(f"Best UBV match: {bcolors.FAIL}{bestMatchNameUBVonlyWeighted}{bcolors.ENDC}")
     print(spTypeTable.iloc[bestMatchIndexUBVonlyWeighted:bestMatchIndexUBVonlyWeighted+1])
-    print("Star: ")
+    print(f"Star: ")
     print(fluxDiff)
     print("-------------------------------------------------------------------------------------")