diff --git a/generate_latex_table.py b/generate_latex_table.py
index 919caed..8e035d3 100644
--- a/generate_latex_table.py
+++ b/generate_latex_table.py
@@ -1,9 +1,19 @@
 import pandas as pd
+import numpy as np
 from main.astrodatagui.db.StarsDB import StarDB
 
 db: StarDB = StarDB.getInstance("stars.db")
 starMainIDs = db.getAllStars()
-res = []
+resFull = []
+resUsed = []
+resUnused = []
+fullData = pd.read_pickle("datav5.1.cff")
+
+usedMstars = pd.read_csv("../large sized plots/2025-5-31-sine/M/M_starlist.csv", header=0, names=["StarName"])
+usedKstars = pd.read_csv("../large sized plots/2025-5-31-sine/K/K_starlist.csv", header=0, names=["StarName"])
+usedGstars = pd.read_csv("../large sized plots/2025-5-31-sine/G/G_starlist.csv", header=0, names=["StarName"])
+usedFstars = pd.read_csv("../large sized plots/2025-5-31-sine/F/F_starlist.csv", header=0, names=["StarName"])
+
 for mainID in starMainIDs:
     altNames = db.getStarAltNames(mainID)
     infos = db.getStarInfos(mainID)
@@ -16,16 +26,59 @@ for mainID in starMainIDs:
         if name[0].startswith("KIC"):
             kicName = name[0]
     spType = infos["SpType"]
-    res.append({"MainID": mainID,
-    "Spectral Type": spType,
-    "TIC": ticName,
-    "KIC": kicName})
+    
+    hasValidSineFit = fullData[(fullData["StarName"] == mainID) & (fullData["FitType"] == "sine")]["isValidFold"].any()
+    hasValidPolyFit = fullData[(fullData["StarName"] == mainID) & (fullData["FitType"] == "poly")]["isValidFold"].any()
+    hasValidLinearFit = fullData[(fullData["StarName"] == mainID) & (fullData["FitType"] == "linear")]["isValidFold"].any()
+    
+    fitTypeString = []
+    if(hasValidSineFit): fitTypeString.append("sine")
+    if(hasValidPolyFit): fitTypeString.append("poly")
+    if(hasValidLinearFit): fitTypeString.append("linear")
+    fitTypeString = ', '.join(fitTypeString)
 
-resDF = pd.DataFrame(res)
-resDF.sort_values(by=["Spectral Type", "MainID"]) #.to_latex(index=False)
+    resFull.append({"MainID": mainID,
+                    "Spectral Type": spType,
+                    "TIC": ticName,
+                    "KIC": kicName,
+                    "Fit Types": fitTypeString})
+
+    if((usedMstars["StarName"] == mainID).any() or (usedKstars["StarName"] == mainID).any() or 
+       (usedGstars["StarName"] == mainID).any() or (usedFstars["StarName"] == mainID).any()):
+        resUsed.append({"MainID": mainID,
+                        "Spectral Type": spType,
+                        "TIC": ticName,
+                        "KIC": kicName,
+                        "Fit Types": fitTypeString})
+    else:
+        resUnused.append({"MainID": mainID,
+                          "Spectral Type": spType,
+                          "TIC": ticName,
+                          "KIC": kicName,
+                          "Fit Types": fitTypeString})
+
+
+
+resFull = pd.DataFrame(resFull)
+resFull.sort_values(by=["Spectral Type", "MainID"])
+
+resUsed = pd.DataFrame(resUsed)
+resUsed.sort_values(by=["Spectral Type", "MainID"])
+resUnused = pd.DataFrame(resUnused)
+resUnused.sort_values(by=["Spectral Type", "MainID"])
 
 for sptype in ["M", "K", "G", "F"]:
-    texFile = open(f"table_{sptype}.tex", "w")
-    tex = resDF[resDF["Spectral Type"].str.startswith(sptype)].sort_values(by=["Spectral Type", "MainID"]).to_latex(index=False)
+    texFile = open(f"table_{sptype}_used.tex", "w")
+    tex = resUsed[resUsed["Spectral Type"].str.startswith(sptype)].sort_values(by=["Spectral Type", "MainID"]).to_latex(index=False)
     texFile.write(tex)
-    texFile.close()
\ No newline at end of file
+    texFile.close()
+
+texFile = open(f"table_full.tex", "w")
+tex = resFull.sort_values(by=["Spectral Type", "MainID"]).to_latex(index=False)
+texFile.write(tex)
+texFile.close()
+
+texFile = open(f"table_unused.tex", "w")
+tex = resUnused.sort_values(by=["Spectral Type", "MainID"]).to_latex(index=False)
+texFile.write(tex)
+texFile.close()
\ No newline at end of file