SGCMarkus/flaredetector
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Merge branch 'main' of https://gitea.markus.stammgruppe.eu/SGCMarkus/flaredetector

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SGCMarkus
2025-06-08 15:38:40 +02:00
parent 6514a6d125 ecf480c2de
commit 95ce7917d9
1 changed files with 63 additions and 10 deletions
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generate_latex_table.py
+63 -10
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@@ -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()
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()