generate_plots: fix formatting and star count

generate_latex_table.py

@@ -0,0 +1,84 @@
+import pandas as pd
+import numpy as np
+from main.astrodatagui.db.StarsDB import StarDB
+
+db: StarDB = StarDB.getInstance("stars.db")
+starMainIDs = db.getAllStars()
+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)
+    kicName = "-"
+    ticName = "-"
+    spType = "-"
+    for name in altNames:
+        if name[0].startswith("TIC"):
+            ticName = name[0]
+        if name[0].startswith("KIC"):
+            kicName = name[0]
+    spType = infos["SpType"]
+    
+    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)
+
+    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}_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 = 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()

generate_plots.py

@@ -1,3 +1,4 @@
+from math import comb
 import numpy as np
 import pandas as pd
 import itertools
@@ -9,6 +10,22 @@ from datetime import datetime
 from errno import EEXIST
 from os import makedirs, path
 import shutil
+import multiprocessing
+import concurrent.futures
+from concurrent.futures import wait, ALL_COMPLETED
+from functools import partial
+
+SMALL_SIZE = 16
+MEDIUM_SIZE = 18
+BIGGER_SIZE = 20
+
+plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
+plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title
+plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
+plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
+plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
+plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
+plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title
 
 def normalizePhase(phase, phaseMin = None, phaseMax = None):
     if(phaseMin is None):
@@ -27,41 +44,6 @@ def mkdir_p(mypath):
             pass
         else: raise
 
-fileName = "datav5.1.cff"
-data = pd.read_pickle(fileName)
-
-binList = [10, 20, 30]
-spType = ["M", "K", "G", "F"]
-
-useKepler = True
-useK2 = True
-useTESS = True
-
-showSourceFilter = np.full(len(data), False)
-if(useKepler):
-    showKepler = data["Source"] == "Kepler"
-    showSourceFilter |= showKepler
-if(useK2):
-    showK2 = data["Source"] == "K2"
-    showSourceFilter |= showK2
-if(useTESS):
-    showTESS = data["Source"] == "TESS"
-    showSourceFilter |= showTESS
-
-current = datetime.now()
-date = f"{current.year}-{current.month}-{current.day}"
-time = f"{current.hour}-{current.minute}-{current.second}"
-folderPath = f"../{date}-sine-poly/"
-#folderPath = f"G:/Meine Ablage/Masterthesis/{date}/"
-mkdir_p(folderPath)
-
-# remove any data that has no period
-#data = data[(data["FitType"] == "sine") | (data["FitType"] == "poly")]
-data = data[((data["FitType"] == "sine") | (data["FitType"] == "poly")) & (data["isValidFold"])]
-
-validStarPeriodMap = []
-starList = set(list(data["StarName"]))
-
 def allValuesWithin3Std(values: list):
     if(not values or len(values) == 1):
         return True
@@ -71,19 +53,6 @@ def allValuesWithin3Std(values: list):
 def getMeanPeriod(values: list):
     return np.mean(values)
 
-for starName in starList:
-    periods = list(data[data["StarName"] == starName]["pdcsapPeriod"])
-
-    validStarPeriodMap.append({"StarName": starName,
-                               "MeanPeriod": getMeanPeriod(periods),
-                               "PeriodWithinStd": allValuesWithin3Std(periods)})
-
-validStarPeriodMap = pd.DataFrame(validStarPeriodMap)
-periodsCutList = [0.5, 1, 1.5, 2, 5, 10, 15, 20]
-
-data = pd.merge(data, validStarPeriodMap, on="StarName")
-starDB: StarDB = StarDB.getInstance("stars.db")
-
 def plotBinsHistogram(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, bins, title, filename, foldedFits):
     figHisto, ((axHisto)) = plt.subplots(nrows=1, ncols=1)
     y, binEdges, _ = axHisto.hist(PDCSAPdataList, bins,
@@ -113,10 +82,10 @@ def plotBinsHistogram(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, bins, ti
         quit()
     axHisto.set_ylabel("Num. flares")
     axHisto.set_xlabel("Phase")
-    axHisto.set_title(title)
+    axHisto.set_title(title, wrap=True)
     axHisto.xaxis.set_major_formatter(tck.FormatStrFormatter('%g $\pi$'))
     axHisto.xaxis.set_major_locator(MaxNLocator(5))
-    axHisto.legend()
+    axHisto.legend(loc="lower right")
 
     axHistoPhase = axHisto.twinx()
     if(foldedFits is None):
@@ -129,9 +98,11 @@ def plotBinsHistogram(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, bins, ti
             axHistoPhase.plot(fit[0], fit[1], color="blue")
         fitCol = [fit[1] for fit in foldedFits]
         fitCol = np.array(list(itertools.chain.from_iterable(fitCol)))
+        if(len(fitCol) == 0):
+            fitCol = np.array([0, 1])
         axHistoPhase.set_ylim(np.min(fitCol), np.max(fitCol)*1.2)
 
-    plt.savefig(filename)
+    plt.savefig(filename, bbox_inches="tight")
     plt.close()
 
 def plotFlarePhasePeakHistogram(xData, yData, bins, maxY, title, filename):
@@ -147,8 +118,8 @@ def plotFlarePhasePeakHistogram(xData, yData, bins, maxY, title, filename):
     figFlarepeakHist.colorbar(im, label='Counts', ax=axFlarepeakHist)
     axFlarepeakHist.xaxis.set_major_formatter(tck.FormatStrFormatter('%g $\pi$'))
     axFlarepeakHist.xaxis.set_major_locator(MaxNLocator(5))
-    axFlarepeakHist.set_title(title)
+    axFlarepeakHist.set_title(title, wrap=True)
-    plt.savefig(filename)
+    plt.savefig(filename, bbox_inches="tight")
     plt.close()
 
 def plotFlarePeaks(plotdata, filters, labels, colors, maxY, title, filename):
@@ -175,15 +146,15 @@ def plotFlarePeaks(plotdata, filters, labels, colors, maxY, title, filename):
     axFlarePeaks.set_ylim(0.99, maxY)
     axFlarePeaks.set_ylabel("Flare peak")
     axFlarePeaks.set_xlabel("Phase")
-    axFlarePeaks.set_title(title)
+    axFlarePeaks.set_title(title, wrap=True)
     axFlarePeaks.xaxis.set_major_formatter(tck.FormatStrFormatter('%g $\pi$'))
     axFlarePeaks.xaxis.set_major_locator(MaxNLocator(5))
-    axFlarePeaks.legend()
+    axFlarePeaks.legend(loc="lower right")
-    plt.savefig(filename)
+    plt.savefig(filename, bbox_inches="tight")
     plt.close()
 
-def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
+def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, pdcsapbinningData,
-                                  PDCSAPdataList=None, dataFilter=None):
+                           pdcsapbinningDataColumn, PDCSAPdataList=None, dataFilter=None):
     xData = pd.DataFrame()
     yData = pd.DataFrame()
     for aX, aY in zip(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak):
@@ -194,9 +165,9 @@ def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
     yData = np.asarray(yData.values)[:,0]
     if(PDCSAPdataList is not None):
         if(dataFilter is not None):
-            PDCSAPdataList.append(pdcsapbinningData[dataFilter]["PDCSAPNormPhase"])
+            PDCSAPdataList.append(pdcsapbinningData[dataFilter][pdcsapbinningDataColumn])
         else:
-            PDCSAPdataList.append(pdcsapbinningData[:]["PDCSAPNormPhase"])
+            PDCSAPdataList.append(pdcsapbinningData[:][pdcsapbinningDataColumn])
 
     return xData, yData, PDCSAPdataList
 
@@ -219,8 +190,7 @@ def generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, histogramTit
         flarePlotFilename = flarePlotFilenameArg.replace("@maxY", str(maxY))
         plotFlarePeaks(plotdata, filters, flarePlotLabels, flarePlotColors, maxY, flarePlotTitle, flarePlotFilename)
 
-# All stars
+def plotStar(data, showSourceFilter, folderPath, starName):
-for starName in starDB.getAllStars():
     finalData = pd.DataFrame()
     starNameR = starName.replace('*', '_star_')
     nameFilter = data["StarName"] == starName
@@ -228,9 +198,7 @@ for starName in starDB.getAllStars():
     finalData = pd.concat([finalData, data[nameFilter]], ignore_index=True)
 
     pdcsapbinningData = []
-    pdcsapbinningDataSpotModDiffPeriod = []
     foldedFits = []
-    foldedPeriodFits = []
     locFolder = f"{folderPath}/stars/{starNameR}/"
     mkdir_p(f"{locFolder}/")
     csvFile = open(f"{locFolder}/{starNameR}.csv", "a")
@@ -252,25 +220,14 @@ for starName in starDB.getAllStars():
                     if(peak["FlarePeak"] > 100):
                         print(row["StarName"], "has over 100 peak")
                 foldedFits.append([normalizePhase(row["pdcsapFoldedFitPhase"]), row["pdcsapFoldedFit"]])
-                if(row["pdcsapPeriodFoldedPhase"] is not None):
+              
-                    periodPdcsapVals = pd.DataFrame(row["pdcsapPeriodFoldedPeaksPhasePair"])
-                    for td, peak in zip(periodPdcsapVals["Phase"], periodPdcsapVals["Peak"]):
-                        normPhasePeriod = normalizePhase(td.value, np.abs(row["pdcsapPeriodFoldedFitPhaseStarEnd"][0]), np.abs(row["pdcsapPeriodFoldedFitPhaseStarEnd"][1]))
-                        pdcsapbinningDataSpotModDiffPeriod.append({"SpType": f'{row["SpType"][0:2] if len(row["SpType"]) > 1 else row["SpType"][0]}',
-                                                                  "PDCSAPNormPhasePeriod": normPhasePeriod,
-                                                                  "PeakPeriod": peak["FlarePeak"]})
-                        if(peak["FlarePeak"] > 100):
-                            print(row["StarName"], "has over 100 peak")
-                    foldedPeriodFits.append([normalizePhase(row["pdcsapPeriodFoldedFitPhase"]), row["pdcsapPeriodFoldedFit"]])
     csvFile.close()
     pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
-    pdcsapbinningDataSpotModDiffPeriod = pd.DataFrame(pdcsapbinningDataSpotModDiffPeriod) if len(pdcsapbinningDataSpotModDiffPeriod) > 0 else None
     PDCSAPdataList = []
     PDCSAPlabelList = []
     PDCSAPcolorList = []
     PDCSAPdataList2dhistPhase = []
     PDCSAPdataList2dhistPeak = []
-
     if(len(pdcsapbinningData) > 0):
         if(pdcsapbinningData["SpType"][0][0] == "M"):
             color = "red"
@@ -286,30 +243,64 @@ for starName in starDB.getAllStars():
         PDCSAPdataList2dhistPhase.append(pdcsapbinningData[:]["PDCSAPNormPhase"])
         PDCSAPdataList2dhistPeak.append(pdcsapbinningData[:]["Peak"])
 
-        xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataList)
+        xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
+                                                              pdcsapbinningData, "PDCSAPNormPhase",
+                                                              PDCSAPdataList)
 
-        PDCSAPlabelList.append(f"{starName}")
         PDCSAPcolorList.append(color)
-
         generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarecount-@bins_Bins.png",
                         xData, yData, f"Flare peak per phase histogram of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
                         pdcsapbinningData, None, f"{starName}", color, f"Flare peaks per phase of {starName}", f"{locFolder}/{starNameR}-Flarepeaks_maxY-@maxY.png",
                         foldedFits)
 
+def plotStarPeriod(data, showSourceFilter, folderPath, starName):
+    finalData = pd.DataFrame()
+    starNameR = starName.replace('*', '_star_')
+    nameFilter = data["StarName"] == starName
+    nameFilter &= showSourceFilter
+    finalData = pd.concat([finalData, data[nameFilter]], ignore_index=True)
+
+    pdcsapbinningDataSpotModDiffPeriod = []
+    foldedPeriodFits = []
+    locFolder = f"{folderPath}/stars/{starNameR}/"
+    mkdir_p(f"{locFolder}/")
+    csvFile = open(f"{locFolder}/{starNameR}_Period.csv", "a")
+    csvFile.write("Star Name,Spectral Type,Source,File,Flare Time,Flare Peak,Period,Spot Modulation,Normalized Phase of Peak,Peak in Period")
+    csvFile.write("\n")
+    for ind, row in finalData.reset_index().iterrows():
+        PDCSAPminOrigPhase = row["pdcsapPeriodFoldedFitPhaseStarEnd"][0]
+        PDCSAPmaxOrigPhase = row["pdcsapPeriodFoldedFitPhaseStarEnd"][1]
+
+        if(len(row["pdcsapPeriodFoldedPeaksPhasePair"]) > 0):
+                pdcsapVals = pd.DataFrame(row["pdcsapPeriodFoldedPeaksPhasePair"])
+                for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]):
+                    normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
+                    csvFile.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row['pdcsapSpotModulation']},{normPhase},{peak['FlarePeak']}")
+                    csvFile.write("\n")
+                    pdcsapbinningDataSpotModDiffPeriod.append({"SpType": f'{row["SpType"][0:2] if len(row["SpType"]) > 1 else row["SpType"][0]}',
+                                            "PDCSAPNormPhasePeriod": normPhase,
+                                            "PeakPeriod": peak["FlarePeak"]})
+                    if(peak["FlarePeak"] > 100):
+                        print(row["StarName"], "has over 100 peak")
+                foldedPeriodFits.append([normalizePhase(row["pdcsapPeriodFoldedFitPhase"]), row["pdcsapPeriodFoldedFit"]])
+
+    csvFile.close()
+    pdcsapbinningDataSpotModDiffPeriod = pd.DataFrame(pdcsapbinningDataSpotModDiffPeriod) if len(pdcsapbinningDataSpotModDiffPeriod) > 0 else None
+
     if(pdcsapbinningDataSpotModDiffPeriod is not None):
-        PDCSAPdataList = []
+        PDCSAPdataListPeriod = []
         PDCSAPlabelList = []
         PDCSAPcolorList = []
         PDCSAPdataList2dhistPhase = []
         PDCSAPdataList2dhistPeak = []
 
-        if(pdcsapbinningData["SpType"][0][0] == "M"):
+        if(pdcsapbinningDataSpotModDiffPeriod["SpType"][0][0] == "M"):
             color = "red"
-        elif(pdcsapbinningData["SpType"][0][0] == "K"):
+        elif(pdcsapbinningDataSpotModDiffPeriod["SpType"][0][0] == "K"):
             color = "orange"
-        elif(pdcsapbinningData["SpType"][0][0] == "G"):
+        elif(pdcsapbinningDataSpotModDiffPeriod["SpType"][0][0] == "G"):
             color = "yellow"
-        elif(pdcsapbinningData["SpType"][0][0] == "F"):
+        elif(pdcsapbinningDataSpotModDiffPeriod["SpType"][0][0] == "F"):
             color = "greenyellow"
         else:
             color = "gray"
@@ -317,19 +308,115 @@ for starName in starDB.getAllStars():
         PDCSAPdataList2dhistPhase.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhasePeriod"])
         PDCSAPdataList2dhistPeak.append(pdcsapbinningDataSpotModDiffPeriod[:]["PeakPeriod"])
 
-        xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataList)
+        xData, yData, PDCSAPdataListPeriod = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
+                                                                    pdcsapbinningDataSpotModDiffPeriod, "PDCSAPNormPhasePeriod",
+                                                                    PDCSAPdataListPeriod)
 
         PDCSAPlabelList.append(f"{starName}")
         PDCSAPcolorList.append(color)
 
-        generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarecount-@bins_Bins_Period.png",
+        generatePlots(PDCSAPdataListPeriod, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarecount-@bins_Bins_Period.png",
                         xData, yData, f"Flare peak per phase histogram of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarepeaks-@bins_Bins_maxY-@maxY_Period.png",
                         pdcsapbinningDataSpotModDiffPeriod, None, f"{starName}", color, f"Flare peaks per phase of {starName}", f"{locFolder}/{starNameR}-Flarepeaks_maxY-@maxY_Period.png",
                         foldedPeriodFits)
 
 
-for comboLength in range(1, len(spType) + 1):
+def plotCombo(data, showSourceFilter, folderPath, combo):
-    for combo in itertools.combinations(spType, comboLength):
+    # all flare peaks
+    finalDataAllFlarePeaks = pd.DataFrame()
+    if("M" in combo):
+        Mfilter = data["SpType"].str.startswith("M")
+        Mfilter &= showSourceFilter
+        finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Mfilter]], ignore_index=True)
+    if("K" in combo):
+        Kfilter = data["SpType"].str.startswith("K")
+        Kfilter &= showSourceFilter
+        finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Kfilter]], ignore_index=True)
+    if("G" in combo):
+        Gfilter = data["SpType"].str.startswith("G")
+        Gfilter &= showSourceFilter
+        finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Gfilter]], ignore_index=True)
+    if("F" in combo):
+        Ffilter = data["SpType"].str.startswith("F")
+        Ffilter &= showSourceFilter
+        finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Ffilter]], ignore_index=True)
+
+    pdcsapbinningDataAllFlarePeaks = []
+    locFolder = f"{folderPath}/{''.join(combo)}/"
+    mkdir_p(f"{locFolder}/")
+    csvFile = open(f"{locFolder}/{''.join(combo)}.csv", "a")
+    csvFile.write("Star Name,Spectral Type,Source,File,Flare Time,Flare Peak,Period,Normalized Phase of Peak,Peak in Period")
+    csvFile.write("\n")
+    for ind, row in finalDataAllFlarePeaks.reset_index().iterrows():
+        PDCSAPminOrigPhase = row["pdcsapFoldedFitPhaseStarEnd"][0]
+        PDCSAPmaxOrigPhase = row["pdcsapFoldedFitPhaseStarEnd"][1]
+        if(len(row["pdcsapFoldedPeaksPhasePair"]) > 0):
+                pdcsapVals = pd.DataFrame(row["pdcsapFoldedPeaksPhasePair"])
+                for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]):
+                    normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
+                    csvFile.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{normPhase},{peak['FlarePeak']}")
+                    csvFile.write("\n")
+                    pdcsapbinningDataAllFlarePeaks.append({"SpType": row["SpType"][0],
+                                            "PDCSAPNormPhase": normPhase,
+                                            "Peak": peak["FlarePeak"],
+                                            "StarName": row['StarName']})
+                    if(peak["FlarePeak"] > 100):
+                        print(row["StarName"], "has over 100 peak")
+
+    csvFile.close()
+    if(len(pdcsapbinningDataAllFlarePeaks) > 0):
+        pdcsapbinningDataAllFlarePeaks = pd.DataFrame(pdcsapbinningDataAllFlarePeaks)
+        numStarsAllFLarePeaks = len(set(pdcsapbinningDataAllFlarePeaks["StarName"]))
+        pd.DataFrame(set(pdcsapbinningDataAllFlarePeaks["StarName"])).to_csv(f"{locFolder}/{''.join(combo)}_starlist.csv")
+        PDCSAPdataListDataAllFlarePeaks = []
+        PDCSAPlabelListDataAllFlarePeaks = []
+        PDCSAPcolorListDataAllFlarePeaks = []
+        PDCSAPdataList2dhistPhaseDataAllFlarePeaks = []
+        PDCSAPdataList2dhistPeakDataAllFlarePeaks = []
+        PDCSAPlabelList2dhistDataAllFlarePeaks = []
+        PDCSAPcolorList2dhistDataAllFlarePeaks = []
+        plotFiltersDataAllFlarePeaks = []
+        if("M" in combo):
+            MfilterDataAllFlarePeaks = pdcsapbinningDataAllFlarePeaks["SpType"] == "M"
+            PDCSAPdataList2dhistPhaseDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[MfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPdataList2dhistPeakDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[MfilterDataAllFlarePeaks]["Peak"])
+            PDCSAPdataListDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[MfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPlabelListDataAllFlarePeaks.append("M Stars")
+            PDCSAPcolorListDataAllFlarePeaks.append("red")
+            plotFiltersDataAllFlarePeaks.append(MfilterDataAllFlarePeaks)
+        if("K" in combo):
+            KfilterDataAllFlarePeaks = pdcsapbinningDataAllFlarePeaks["SpType"] == "K"
+            PDCSAPdataList2dhistPhaseDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[KfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPdataList2dhistPeakDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[KfilterDataAllFlarePeaks]["Peak"])
+            PDCSAPdataListDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[KfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPlabelListDataAllFlarePeaks.append("K Stars")
+            PDCSAPcolorListDataAllFlarePeaks.append("orange")
+            plotFiltersDataAllFlarePeaks.append(KfilterDataAllFlarePeaks)
+        if("G" in combo):
+            GfilterDataAllFlarePeaks = pdcsapbinningDataAllFlarePeaks["SpType"] == "G"
+            PDCSAPdataList2dhistPhaseDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[GfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPdataList2dhistPeakDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[GfilterDataAllFlarePeaks]["Peak"])
+            PDCSAPdataListDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[GfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPlabelListDataAllFlarePeaks.append("G Stars")
+            PDCSAPcolorListDataAllFlarePeaks.append("yellow")
+            plotFiltersDataAllFlarePeaks.append(GfilterDataAllFlarePeaks)
+        if("F" in combo):
+            FfilterDataAllFlarePeaks = pdcsapbinningDataAllFlarePeaks["SpType"] == "F"
+            PDCSAPdataList2dhistPhaseDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[FfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPdataList2dhistPeakDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[FfilterDataAllFlarePeaks]["Peak"])
+            PDCSAPdataListDataAllFlarePeaks.append(pdcsapbinningDataAllFlarePeaks[FfilterDataAllFlarePeaks]["PDCSAPNormPhase"])
+            PDCSAPlabelListDataAllFlarePeaks.append("F Stars")
+            PDCSAPcolorListDataAllFlarePeaks.append("greenyellow")
+            plotFiltersDataAllFlarePeaks.append(FfilterDataAllFlarePeaks)
+
+        xDataDataAllFlarePeaks, yDataDataAllFlarePeaks, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseDataAllFlarePeaks, PDCSAPdataList2dhistPeakDataAllFlarePeaks,
+                                                    pdcsapbinningDataAllFlarePeaks, "PDCSAPNormPhase")
+
+        generatePlots(PDCSAPdataListDataAllFlarePeaks, PDCSAPlabelListDataAllFlarePeaks, PDCSAPcolorListDataAllFlarePeaks, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStarsAllFLarePeaks} stars)", f"{locFolder}/{''.join(combo)}-Flarecount-@bins_Bins.png",
+                        xDataDataAllFlarePeaks, yDataDataAllFlarePeaks, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStarsAllFLarePeaks} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
+                        pdcsapbinningDataAllFlarePeaks, plotFiltersDataAllFlarePeaks, PDCSAPlabelListDataAllFlarePeaks, PDCSAPcolorListDataAllFlarePeaks, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStarsAllFLarePeaks} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks_maxY-@maxY.png")
+        
+
     for maxFlarePeak in [1.01, 1.05, 1.1, 1.25, 1.5]:
         # max Flare Peak cut
         finalDataMaxFlarePeak = pd.DataFrame()
@@ -350,8 +437,6 @@ for comboLength in range(1, len(spType) + 1):
             Ffilter &= showSourceFilter
             finalDataMaxFlarePeak = pd.concat([finalDataMaxFlarePeak, data[Ffilter]], ignore_index=True)
 
-            numStars = len(set(finalDataMaxFlarePeak["StarName"]))
-
         pdcsapbinningDataU = []
         pdcsapbinningDataO = []
         locFolderU = f"{folderPath}/{''.join(combo)}/maxFlarePeaks/{maxFlarePeak}/"
@@ -376,7 +461,8 @@ for comboLength in range(1, len(spType) + 1):
                             csvFileU.write("\n")
                             pdcsapbinningDataU.append({"SpType": row["SpType"][0],
                                                     "PDCSAPNormPhase": normPhase,
-                                                      "Peak": peak["FlarePeak"]})
+                                                    "Peak": peak["FlarePeak"],
+                                                    "StarName": row['StarName']})
                             if(peak["FlarePeak"] > 100):
                                 print(row["StarName"], "has over 100 peak")
                         else:
@@ -385,7 +471,8 @@ for comboLength in range(1, len(spType) + 1):
                             csvFileO.write("\n")
                             pdcsapbinningDataO.append({"SpType": row["SpType"][0],
                                                     "PDCSAPNormPhase": normPhase,
-                                                      "Peak": peak["FlarePeak"]})
+                                                    "Peak": peak["FlarePeak"],
+                                                    "StarName": row['StarName']})
                             if(peak["FlarePeak"] > 100):
                                 print(row["StarName"], "has over 100 peak")
 
@@ -393,6 +480,8 @@ for comboLength in range(1, len(spType) + 1):
         csvFileO.close()
         if(len(pdcsapbinningDataU) > 0):
             pdcsapbinningDataU = pd.DataFrame(pdcsapbinningDataU)
+            numStarsFlarePeakU = len(set(pdcsapbinningDataU["StarName"]))
+            pd.DataFrame(set(pdcsapbinningDataU["StarName"])).to_csv(f"{locFolderU}/{''.join(combo)}_starlist.csv")
             PDCSAPdataListU = []
             PDCSAPlabelListU = []
             PDCSAPcolorListU = []
@@ -432,14 +521,16 @@ for comboLength in range(1, len(spType) + 1):
                 PDCSAPcolorListU.append("greenyellow")
                 plotFiltersU.append(Ffilter)
 
-                xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseU, PDCSAPdataList2dhistPeakU)
+            xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseU, PDCSAPdataList2dhistPeakU,
-                generatePlots(PDCSAPdataListU, PDCSAPlabelListU, PDCSAPcolorListU, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarecount-@bins_Bins.png",
+                                                        pdcsapbinningDataU, "PDCSAPNormPhase")
-                              xData, yData, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
+            generatePlots(PDCSAPdataListU, PDCSAPlabelListU, PDCSAPcolorListU, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStarsFlarePeakU} stars)", f"{locFolderU}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarecount-@bins_Bins.png",
-                              pdcsapbinningDataU, plotFiltersU, PDCSAPlabelListU, PDCSAPcolorListU, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStars} stars)", f"{locFolder}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
+                            xData, yData, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStarsFlarePeakU} stars)", f"{locFolderU}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
-
+                            pdcsapbinningDataU, plotFiltersU, PDCSAPlabelListU, PDCSAPcolorListU, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStarsFlarePeakU} stars)", f"{locFolderU}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
 
         if(len(pdcsapbinningDataO) > 0):
             pdcsapbinningDataO = pd.DataFrame(pdcsapbinningDataO)
+            numStarsFlarePeakO = len(set(pdcsapbinningDataO["StarName"]))
+            pd.DataFrame(set(pdcsapbinningDataO["StarName"])).to_csv(f"{locFolderO}/{''.join(combo)}_starlist.csv")
             PDCSAPdataListO = []
             PDCSAPlabelListO = []
             PDCSAPcolorListO = []
@@ -479,104 +570,13 @@ for comboLength in range(1, len(spType) + 1):
                 PDCSAPcolorListO.append("greenyellow")
                 plotFiltersO.append(Ffilter)
 
-                xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseO, PDCSAPdataList2dhistPeakO)
+            xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseO, PDCSAPdataList2dhistPeakO,
-                generatePlots(PDCSAPdataListO, PDCSAPlabelListO, PDCSAPcolorListO, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarecount-@bins_Bins.png",
+                                                        pdcsapbinningDataO, "PDCSAPNormPhase")
-                              xData, yData, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
+            generatePlots(PDCSAPdataListO, PDCSAPlabelListO, PDCSAPcolorListO, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStarsFlarePeakO} stars)", f"{locFolderO}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarecount-@bins_Bins.png",
-                              pdcsapbinningDataO, plotFiltersO, PDCSAPlabelListO, PDCSAPcolorListO, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStars} stars)", f"{locFolder}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
+                            xData, yData, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStarsFlarePeakO} stars)", f"{locFolderO}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
-        # all flare peaks
+                            pdcsapbinningDataO, plotFiltersO, PDCSAPlabelListO, PDCSAPcolorListO, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStarsFlarePeakO} stars)", f"{locFolderO}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
-        finalDataAllFlarePeaks = pd.DataFrame()
-        if("M" in combo):
-            Mfilter = data["SpType"].str.startswith("M")
-            Mfilter &= showSourceFilter
-            finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Mfilter]], ignore_index=True)
-        if("K" in combo):
-            Kfilter = data["SpType"].str.startswith("K")
-            Kfilter &= showSourceFilter
-            finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Kfilter]], ignore_index=True)
-        if("G" in combo):
-            Gfilter = data["SpType"].str.startswith("G")
-            Gfilter &= showSourceFilter
-            finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Gfilter]], ignore_index=True)
-        if("F" in combo):
-            Ffilter = data["SpType"].str.startswith("F")
-            Ffilter &= showSourceFilter
-            finalDataAllFlarePeaks = pd.concat([finalDataAllFlarePeaks, data[Ffilter]], ignore_index=True)
     
-        numStars = len(set(finalDataAllFlarePeaks["StarName"]))
+    if(len(combo) == 1):
-
-        pdcsapbinningData = []
-        locFolder = f"{folderPath}/{''.join(combo)}/"
-        mkdir_p(f"{locFolder}/")
-        csvFile = open(f"{locFolder}/{''.join(combo)}.csv", "a")
-        csvFile.write("Star Name,Spectral Type,Source,File,Flare Time,Flare Peak,Period,Normalized Phase of Peak,Peak in Period")
-        csvFile.write("\n")
-        for ind, row in finalDataAllFlarePeaks.reset_index().iterrows():
-            PDCSAPminOrigPhase = row["pdcsapFoldedFitPhaseStarEnd"][0]
-            PDCSAPmaxOrigPhase = row["pdcsapFoldedFitPhaseStarEnd"][1]
-            if(len(row["pdcsapFoldedPeaksPhasePair"]) > 0):
-                    pdcsapVals = pd.DataFrame(row["pdcsapFoldedPeaksPhasePair"])
-                    for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]):
-                        normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
-                        csvFile.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{normPhase},{peak['FlarePeak']}")
-                        csvFile.write("\n")
-                        pdcsapbinningData.append({"SpType": row["SpType"][0],
-                                              "PDCSAPNormPhase": normPhase,
-                                              "Peak": peak["FlarePeak"]})
-                        if(peak["FlarePeak"] > 100):
-                            print(row["StarName"], "has over 100 peak")
-
-        csvFile.close()
-        if(len(pdcsapbinningData) > 0):
-            pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
-            PDCSAPdataList = []
-            PDCSAPlabelList = []
-            PDCSAPcolorList = []
-            PDCSAPdataList2dhistPhase = []
-            PDCSAPdataList2dhistPeak = []
-            PDCSAPlabelList2dhist = []
-            PDCSAPcolorList2dhist = []
-            plotFilters = []
-            if("M" in combo):
-                Mfilter = pdcsapbinningData["SpType"] == "M"
-                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Mfilter]["PDCSAPNormPhase"])
-                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Mfilter]["Peak"])
-                PDCSAPdataList.append(pdcsapbinningData[Mfilter]["PDCSAPNormPhase"])
-                PDCSAPlabelList.append("M Stars")
-                PDCSAPcolorList.append("red")
-                plotFilters.append(Mfilter)
-            if("K" in combo):
-                Kfilter = pdcsapbinningData["SpType"] == "K"
-                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Kfilter]["PDCSAPNormPhase"])
-                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Kfilter]["Peak"])
-                PDCSAPdataList.append(pdcsapbinningData[Kfilter]["PDCSAPNormPhase"])
-                PDCSAPlabelList.append("K Stars")
-                PDCSAPcolorList.append("orange")
-                plotFilters.append(Kfilter)
-            if("G" in combo):
-                Gfilter = pdcsapbinningData["SpType"] == "G"
-                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Gfilter]["PDCSAPNormPhase"])
-                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Gfilter]["Peak"])
-                PDCSAPdataList.append(pdcsapbinningData[Gfilter]["PDCSAPNormPhase"])
-                PDCSAPlabelList.append("G Stars")
-                PDCSAPcolorList.append("yellow")
-                plotFilters.append(Gfilter)
-            if("F" in combo):
-                Ffilter = pdcsapbinningData["SpType"] == "F"
-                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Ffilter]["PDCSAPNormPhase"])
-                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Ffilter]["Peak"])
-                PDCSAPdataList.append(pdcsapbinningData[Ffilter]["PDCSAPNormPhase"])
-                PDCSAPlabelList.append("F Stars")
-                PDCSAPcolorList.append("greenyellow")
-                plotFilters.append(Ffilter)
-
-            xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak)
-            plotdata = pdcsapbinningData
-            filters = plotFilters
-            generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}-Flarecount-@bins_Bins.png",
-                          xData, yData, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
-                          plotdata, filters, PDCSAPlabelList, PDCSAPcolorList, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStars} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks_maxY-@maxY.png")
-        
-        if(comboLength == 1):
         mainSpType = combo[0]
         spTypes = [f"{mainSpType}0", f"{mainSpType}1", f"{mainSpType}2", f"{mainSpType}3", f"{mainSpType}4", f"{mainSpType}5", f"{mainSpType}6", f"{mainSpType}7", f"{mainSpType}8", f"{mainSpType}9"]
         match mainSpType:
@@ -593,7 +593,6 @@ for comboLength in range(1, len(spType) + 1):
             finalDataAccSpTypes = pd.DataFrame()
         
             typeFilter = data["SpType"].str.startswith(spTyp)
-                numStars = len(set(data[typeFilter]["StarName"]))
             typeFilter &= showSourceFilter
             finalDataAccSpTypes = pd.concat([finalDataAccSpTypes, data[typeFilter]], ignore_index=True)
 
@@ -614,12 +613,15 @@ for comboLength in range(1, len(spType) + 1):
                             csvFile.write("\n")
                             pdcsapbinningData.append({"SpType": f'{row["SpType"][0]}{row["SpType"][1]}',
                                                     "PDCSAPNormPhase": normPhase,
-                                                      "Peak": peak["FlarePeak"]})
+                                                    "Peak": peak["FlarePeak"],
+                                                    "StarName": row['StarName']})
                             if(peak["FlarePeak"] > 100):
                                 print(row["StarName"], "has over 100 peak")
             csvFile.close()
             if(len(pdcsapbinningData) > 0):
                 pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
+                numStarsAccSpType = len(set(pdcsapbinningData["StarName"]))
+                pd.DataFrame(set(pdcsapbinningData["StarName"])).to_csv(f"{locFolder}/{spTyp}_starlist.csv")
                 PDCSAPdataList = []
                 PDCSAPlabelList = []
                 PDCSAPcolorList = []
@@ -636,13 +638,15 @@ for comboLength in range(1, len(spType) + 1):
                 PDCSAPdataList2dhistPeak.append(pdcsapbinningData[SpTypefilter]["Peak"])
                 PDCSAPlabelList.append(f"{spTyp} Stars")
                 PDCSAPcolorList.append(color)
-                    xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataList, SpTypefilter)
+                xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
+                                                                        pdcsapbinningData, "PDCSAPNormPhase",
+                                                                        PDCSAPdataList, SpTypefilter)
 
                 plotdata = pdcsapbinningData
                 filters = SpTypefilter
-                    generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {spTyp} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(spTyp)}-Flarecount-@bins_Bins.png",
+                generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {spTyp} type stars with @bins bins ({numStarsAccSpType} stars)", f"{locFolder}/{''.join(spTyp)}-Flarecount-@bins_Bins.png",
-                                  xData, yData, f"Flare peak per phase histogram of {spTyp} type stars with @bins bins ({numStars} stars)", f"{locFolder}/{''.join(spTyp)}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
+                                xData, yData, f"Flare peak per phase histogram of {spTyp} type stars with @bins bins ({numStarsAccSpType} stars)", f"{locFolder}/{''.join(spTyp)}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
-                                  plotdata, filters, PDCSAPlabelList[0], PDCSAPcolorList[0], f"Flare peaks per phase of {spTyp} type stars ({numStars} stars)", f"{locFolder}/{''.join(spTyp)}-Flarepeaks_maxY-@maxY.png")
+                                plotdata, filters, PDCSAPlabelList[0], PDCSAPcolorList[0], f"Flare peaks per phase of {spTyp} type stars ({numStarsAccSpType} stars)", f"{locFolder}/{''.join(spTyp)}-Flarepeaks_maxY-@maxY.png")
         
     # per Period
     for periodCut in periodsCutList:
@@ -686,17 +690,19 @@ for comboLength in range(1, len(spType) + 1):
                     for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]):
                         normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
                         if(row["MeanPeriod"] <= periodCut):
-                                csvFileU.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row["MeanPeriod"]},{normPhase},{peak['FlarePeak']}")
+                            csvFileU.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row['MeanPeriod']},{normPhase},{peak['FlarePeak']}")
                             csvFileU.write("\n")
                             pdcsapbinningDataU.append({"SpType": f'{row["SpType"][0]}',
                                                         "PDCSAPNormPhase": normPhase,
-                                                           "Peak": peak["FlarePeak"]})
+                                                        "Peak": peak["FlarePeak"],
+                                                        "StarName": row['StarName']})
                         else:
-                                csvFileO.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row["MeanPeriod"]},{normPhase},{peak['FlarePeak']}")
+                            csvFileO.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row['MeanPeriod']},{normPhase},{peak['FlarePeak']}")
                             csvFileO.write("\n")
                             pdcsapbinningDataO.append({"SpType": f'{row["SpType"][0]}',
                                                         "PDCSAPNormPhase": normPhase,
-                                                           "Peak": peak["FlarePeak"]})
+                                                        "Peak": peak["FlarePeak"],
+                                                        "StarName": row['StarName']})
                         if(peak["FlarePeak"] > 100):
                             print(row["StarName"], "has over 100 peak")
         csvFileU.close()
@@ -724,6 +730,8 @@ for comboLength in range(1, len(spType) + 1):
             PDCSAPcolorList.append("greenyellow")
 
         if(len(pdcsapbinningDataU) > 0):
+            numStarsPeriodU = len(set(pdcsapbinningDataU["StarName"]))
+            pd.DataFrame(set(pdcsapbinningDataU["StarName"])).to_csv(f"{locFolder}/under_{periodCut}_starlist.csv")
             if("M" in combo):
                 MfilterU = pdcsapbinningDataU["SpType"] == "M"
                 PDCSAPdataList2dhistPhaseU.append(pdcsapbinningDataU[MfilterU]["PDCSAPNormPhase"])
@@ -750,6 +758,8 @@ for comboLength in range(1, len(spType) + 1):
                 plotFiltersU.append(FfilterU)
 
         if(len(pdcsapbinningDataO) > 0):
+            numStarsPeriodO = len(set(pdcsapbinningDataO["StarName"]))
+            pd.DataFrame(set(pdcsapbinningDataO["StarName"])).to_csv(f"{locFolder}/over_{periodCut}_starlist.csv")
             if("M" in combo):
                 MfilterO = pdcsapbinningDataO["SpType"] == "M"
                 PDCSAPdataList2dhistPhaseO.append(pdcsapbinningDataO[MfilterO]["PDCSAPNormPhase"])
@@ -776,16 +786,94 @@ for comboLength in range(1, len(spType) + 1):
                 plotFiltersO.append(FfilterO)
 
         if(len(PDCSAPdataList2dhistPhaseU) > 0 and len(PDCSAPdataList2dhistPeakU) > 0):
-                xDataU, yDataU, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseU, PDCSAPdataList2dhistPeakU)
+            xDataU, yDataU, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseU, PDCSAPdataList2dhistPeakU,
+                                                        pdcsapbinningDataU, "PDCSAPNormPhase",)
             if(len(PDCSAPdataListU) > 0 and len(xDataU) > 0 and len(yDataU) > 0):
-                    generatePlots(PDCSAPdataListU, PDCSAPlabelList, PDCSAPcolorList, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins (Rot. Period under {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarecount-Period_u_{periodCut}-@bins_Bins.png",
+                generatePlots(PDCSAPdataListU, PDCSAPlabelList, PDCSAPcolorList, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins (Rot. Period under {periodCut} days, {numStarsPeriodU} stars)", f"{locFolder}/{''.join(combo)}-Flarecount-Period_u_{periodCut}-@bins_Bins.png",
-                                  xDataU, yDataU, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins (Rot. Period under {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_u_{periodCut}-@bins_Bins_maxY-@maxY.png",
+                                xDataU, yDataU, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins (Rot. Period under {periodCut} days, {numStarsPeriodU} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_u_{periodCut}-@bins_Bins_maxY-@maxY.png",
-                                  pdcsapbinningDataU, plotFiltersU, PDCSAPlabelList, PDCSAPcolorList, f"Flare peaks per phase of {', '.join(combo)} type stars (Rot. Period under {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_u_{periodCut}-maxY_@maxY.png")
+                                pdcsapbinningDataU, plotFiltersU, PDCSAPlabelList, PDCSAPcolorList, f"Flare peaks per phase of {', '.join(combo)} type stars (Rot. Period under {periodCut} days, {numStarsPeriodU} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_u_{periodCut}-maxY_@maxY.png")
 
         if(len(PDCSAPdataList2dhistPhaseO) > 0 and len(PDCSAPdataList2dhistPeakO) > 0):
-                xDataO, yDataO, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseO, PDCSAPdataList2dhistPeakO)
+            xDataO, yDataO, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhaseO, PDCSAPdataList2dhistPeakO,
+                                                        pdcsapbinningDataO, "PDCSAPNormPhase",)
             if(len(PDCSAPdataListO) > 0 and len(xDataO) > 0 and len(yDataO) > 0):
-                    generatePlots(PDCSAPdataListO, PDCSAPlabelList, PDCSAPcolorList, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins (Rot. Period over {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarecount-Period_o_{periodCut}-@bins_Bins.png",
+                generatePlots(PDCSAPdataListO, PDCSAPlabelList, PDCSAPcolorList, f"Flare count per phase of {', '.join(combo)} type stars with @bins bins (Rot. Period over {periodCut} days, {numStarsPeriodO} stars)", f"{locFolder}/{''.join(combo)}-Flarecount-Period_o_{periodCut}-@bins_Bins.png",
-                                  xDataO, yDataO, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins (Rot. Period over {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_o_{periodCut}-@bins_Bins_maxY-@maxY.png",
+                                xDataO, yDataO, f"Flare peak per phase histogram of {', '.join(combo)} type stars with @bins bins (Rot. Period over {periodCut} days, {numStarsPeriodO} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_o_{periodCut}-@bins_Bins_maxY-@maxY.png",
-                                  pdcsapbinningDataO, plotFiltersO, PDCSAPlabelList, PDCSAPcolorList, f"Flare peaks per phase of {', '.join(combo)} type stars (Rot. Period over {periodCut} days)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_o_{periodCut}-maxY_@maxY.png")
+                                pdcsapbinningDataO, plotFiltersO, PDCSAPlabelList, PDCSAPcolorList, f"Flare peaks per phase of {', '.join(combo)} type stars (Rot. Period over {periodCut} days, {numStarsPeriodO} stars)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_o_{periodCut}-maxY_@maxY.png")
 
+binList = [10, 20, 30]
+spType = ["M", "K", "G", "F"]
+periodsCutList = [0.5, 1, 1.5, 2, 5, 10, 15, 20]
+
+if __name__ == "__main__":
+    fileName = "datav5.1.cff"
+    fullData = pd.read_pickle(fileName)
+    starDB: StarDB = StarDB.getInstance("stars.db")
+    allStars = starDB.getAllStars()
+
+    useKepler = True
+    useK2 = True
+    useTESS = True
+
+    current = datetime.now()
+    date = f"{current.year}-{current.month}-{current.day}"
+    time = f"{current.hour}-{current.minute}-{current.second}"
+
+    cpuCount = multiprocessing.cpu_count()
+    pool = multiprocessing.Pool(processes=cpuCount)
+
+    foldedFitTypes = ["sine", "poly"]
+    for foldedFitTypesLength in range(1, len(foldedFitTypes)+1):
+        for foldedFitTypeCombo in itertools.combinations(foldedFitTypes, foldedFitTypesLength):
+            folderPath = f"../{date}-{'-'.join(foldedFitTypeCombo)}/"
+            mkdir_p(folderPath)
+            foldedFitTypeComboFilter = np.full(len(fullData), False)
+            foldedFitTypeComboFilterPeriod = np.full(len(fullData), False)
+            if("sine" in foldedFitTypeCombo):
+                foldedFitTypeComboFilter |= fullData["FitType"] == "sine"
+                foldedFitTypeComboFilterPeriod |= fullData["periodFitType"] == "sine"
+            if("poly" in foldedFitTypeCombo):
+                foldedFitTypeComboFilter |= fullData["FitType"] == "poly"
+                foldedFitTypeComboFilterPeriod |= fullData["periodFitType"] == "poly"
+
+            data = fullData[(foldedFitTypeComboFilter) & (fullData["isValidFold"])]
+            dataPeriod = fullData[(foldedFitTypeComboFilterPeriod) & (fullData["isValidFold"])]
+
+            showSourceFilter = np.full(len(data), False)
+            if(useKepler):
+                showKepler = data["Source"] == "Kepler"
+                showSourceFilter |= showKepler
+            if(useK2):
+                showK2 = data["Source"] == "K2"
+                showSourceFilter |= showK2
+            if(useTESS):
+                showTESS = data["Source"] == "TESS"
+                showSourceFilter |= showTESS
+
+            validStarPeriodMap = []
+            starList = set(list(data["StarName"]))
+
+            for starName in starList:
+                periods = list(data[data["StarName"] == starName]["pdcsapPeriod"])
+
+                validStarPeriodMap.append({"StarName": starName,
+                                           "MeanPeriod": getMeanPeriod(periods),
+                                           "PeriodWithinStd": allValuesWithin3Std(periods)})
+
+            validStarPeriodMap = pd.DataFrame(validStarPeriodMap)
+
+            data = pd.merge(data, validStarPeriodMap, on="StarName")
+            
+            #starPlotFunc = partial(plotStar, data, showSourceFilter, folderPath)
+            #list(pool.map(starPlotFunc, allStars)) # wrap in list, to force evaluation
+            
+            #starPlotPeriodFunc = partial(plotStarPeriod, dataPeriod, showSourceFilter, folderPath)
+            #list(pool.map(starPlotPeriodFunc, allStars)) # wrap in list, to force evaluation
+
+            combos = []
+            for comboLength in range(1, len(spType) + 1):
+                for combo in itertools.combinations(spType, comboLength):
+                    combos.append(combo)
+
+            plotComboFunc = partial(plotCombo, data, showSourceFilter, folderPath)
+            list(pool.map(plotComboFunc, combos)) # wrap in list, to force evaluation

main/astrodatagui/CalcAllFlaresThread.py

@@ -15,6 +15,18 @@ from errno import EEXIST
 from os import makedirs, path
 from datetime import datetime
 
+SMALL_SIZE = 16
+MEDIUM_SIZE = 18
+BIGGER_SIZE = 20
+
+plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
+plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title
+plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
+plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
+plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
+plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
+plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title
+
 def mkdir_p(mypath):
     '''Creates a directory. equivalent to using mkdir -p on the command line'''
 
@@ -48,13 +60,13 @@ def getFlareCount(filesDict):
 
         lc.plot()
         plt.title(f"{starName} - normalized lightcurve")
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-lc.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-lc.png", bbox_inches="tight")
         plt.close()
 
         flattenedLc = lc.flatten()
         flattenedLc.plot()
         plt.title(f"{starName} - flattened lightcurve")
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-flattened_lc.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-flattened_lc.png", bbox_inches="tight")
         plt.close()
 
         pdcsapPeaks, pdcsapFits = calculateFlareFitsForLightcurve(flattenedLc, normalizedLC=lc)
@@ -64,7 +76,7 @@ def getFlareCount(filesDict):
             plt.plot(p["FlarePeakTime"].value, lc.flux[p["StandardIndex"]], "x", color="red")
         plt.plot([], [], "x", color="red", label="Flare peaks")
         plt.legend()
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-lc-marked_flares.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-lc-marked_flares.png", bbox_inches="tight")
         plt.close()
 
         flattenedLc.plot()
@@ -76,7 +88,7 @@ def getFlareCount(filesDict):
             plt.plot(p["FlarePeakTime"].value, p["FlarePeak"], "x", color="red")
         plt.plot([], [], "x", color="red", label="Flare peaks")
         plt.legend()
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-flattened_lc-marked_flares.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-flattened_lc-marked_flares.png", bbox_inches="tight")
         plt.close()
 
         pdcsapValSec, pdcsapTds = getTotalValidDataInSeconds(lc, "pdcsap_flux")
@@ -86,7 +98,7 @@ def getFlareCount(filesDict):
 
         pdcsapPeriodogram.plot(view="period")
         plt.plot(pdcsapPeakPeriod, pdcsapPeriodogram.power[maxPeriodIndex], "x", color="red")
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-periodogram-marked_max.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-periodogram-marked_max.png", bbox_inches="tight")
         plt.close()
 
         #pdcsapEpochTime = getEpochTime(lc)
@@ -108,7 +120,7 @@ def getFlareCount(filesDict):
                      optimizedFit["foldedLC"].flux[optimizedFit["foldedLC"].cycle == cycle][foldedIndex], "x", color="red")
         plt.plot([], [], "x", color="red", label="Flare peaks")
         plt.legend()
-        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-foldedLC-marked_fit_flares.png")
+        plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-foldedLC-marked_fit_flares.png", bbox_inches="tight")
         plt.close()
 
         if(optimizedFit["periodFoldedLC"] is not None):
@@ -123,7 +135,7 @@ def getFlareCount(filesDict):
                          optimizedFit["periodFoldedLC"].flux[optimizedFit["periodFoldedLC"].cycle == cycle][foldedIndex], "x", color="red")
             plt.plot([], [], "x", color="red", label="Flare peaks")
             plt.legend()
-            plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-periodFoldedLC-marked_fit_flares.png")
+            plt.savefig(f"{starFolder}/{starNameR}_{source}-{sequence}-periodFoldedLC-marked_fit_flares.png", bbox_inches="tight")
             plt.close()
         
         filesDict["pdcsapPeaks"] = pdcsapPeaks

main/astrodatagui/FlareSummaryPlotGUI.py

@@ -120,7 +120,7 @@ class FlareSummaryPlotGUI(QWidget):
         self.cbSpTypeUnknown.setChecked(False)
 
         self.cbShowSAP = QCheckBox("SAP")
-        self.cbShowSAP.setChecked(True)
+        self.cbShowSAP.setChecked(False)
         self.cbShowPDCSAP = QCheckBox("PDCSAP")
         self.cbShowPDCSAP.setChecked(True)
 
@@ -129,12 +129,12 @@ class FlareSummaryPlotGUI(QWidget):
         self.buttonGridLayout.addWidget(self.btShowFlaresPerStar, 0, 2)
         self.buttonGridLayout.addWidget(self.btShowFlaresPerStarNormalized, 0, 3)
         self.buttonGridLayout.addWidget(self.btShowPeriods, 0, 4)
-        self.buttonGridLayout.addWidget(self.btNumMinimaMaxima, 0, 5)
+        #self.buttonGridLayout.addWidget(self.btNumMinimaMaxima, 0, 5)
-        self.buttonGridLayout.addWidget(self.btNumMinimaMaximaNorm, 0, 6)
+        #self.buttonGridLayout.addWidget(self.btNumMinimaMaximaNorm, 0, 6)
-        self.buttonGridLayout.addWidget(self.btShowFlaresInMinimaMaxima, 0, 7)
+        #self.buttonGridLayout.addWidget(self.btShowFlaresInMinimaMaxima, 0, 7)
-        self.buttonGridLayout.addWidget(self.btShowFlaresInMinimaMaximaPerMinimaMaxima, 0, 8)
+        #self.buttonGridLayout.addWidget(self.btShowFlaresInMinimaMaximaPerMinimaMaxima, 0, 8)
-        self.buttonGridLayout.addWidget(self.btShowFlaresBinnedOnPhase, 0, 9)
+        #self.buttonGridLayout.addWidget(self.btShowFlaresBinnedOnPhase, 0, 9)
-        self.buttonGridLayout.addWidget(self.textNumBins, 0, 10)
+        #self.buttonGridLayout.addWidget(self.textNumBins, 0, 10)
 
         self.buttonGridLayout.addWidget(QLabel("Sources: "), 1, 0)
         self.buttonGridLayout.addWidget(self.cbKepler, 1, 1)
@@ -149,7 +149,7 @@ class FlareSummaryPlotGUI(QWidget):
         self.buttonGridLayout.addWidget(self.cbSpTypeF, 2, 4)
         #self.buttonGridLayout.addWidget(self.cbSpTypeUnknown, 2, 6)
         
-        self.buttonGridLayout.addWidget(self.cbShowSAP, 3, 0)
+        #self.buttonGridLayout.addWidget(self.cbShowSAP, 3, 0)
         self.buttonGridLayout.addWidget(self.cbShowPDCSAP, 3, 1)
 
         self.mainLayout.addLayout(self.buttonGridLayout)
@@ -243,27 +243,7 @@ class FlareSummaryPlotGUI(QWidget):
         self.figure.canvas.draw_idle()
 
     def btShowFlaresPerStarClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'pdcsapPeaks',
-                                                    'sapFits',
-                                                    'sapPeaks',
-                                                    'sapPeriod',
-                                                    'sapPeriodMinima',
-                                                    'sapPeriodMinimaBoundaries',
-                                                    'sapPeriodMaxima',
-                                                    'sapPeriodMaximaBoundaries',
-                                                    'pdcsapValidTimespans',
-                                                    'pdcsapPeriod',
-                                                    'pdcsapPeriodMinima',
-                                                    'pdcsapPeriodMinimaBoundaries',
-                                                    'pdcsapPeriodMaxima',
-                                                    'pdcsapPeriodMaximaBoundaries'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -277,9 +257,14 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
+        aggDic = {}
+        if(self.cbShowSAP.isChecked()):
+            aggDic["sapPeaksCount"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["pdcsapPeaksCount"] = "sum"
+
         data = data[showSourceFilter].groupby(["StarName", "SpType"],
-                            as_index=False).agg({"sapPeaksCount": "sum",
+                            as_index=False).agg(aggDic)
-                                                 "pdcsapPeaksCount": "sum"})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):
@@ -345,28 +330,7 @@ class FlareSummaryPlotGUI(QWidget):
         self.figure.canvas.draw_idle()
 
     def btShowFlaresPerStarNormalizedClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'pdcsapPeaks',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'sapPeaks',
-                                                    'sapPeriod',
-                                                    'sapPeriodMinima',
-                                                    'sapPeriodMinimaBoundaries',
-                                                    'sapPeriodMaxima',
-                                                    'sapPeriodMaximaBoundaries',
-                                                    'pdcsapValidTimespans',
-                                                    'pdcsapPeriod',
-                                                    'pdcsapPeriodMinima',
-                                                    'pdcsapPeriodMinimaBoundaries',
-                                                    'pdcsapPeriodMaxima',
-                                                    'pdcsapPeriodMaximaBoundaries'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -380,11 +344,16 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
+        aggDic = {}
+        if(self.cbShowSAP.isChecked()):
+            aggDic["sapPeaksCount"] = "sum"
+            aggDic["sapValidSeconds"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["pdcsapPeaksCount"] = "sum"
+            aggDic["pdcsapValidSeconds"] = "sum"
+
         data = data[showSourceFilter].groupby(["StarName", "SpType"],
-                            as_index=False).agg({"sapPeaksCount": "sum",
+                            as_index=False).agg(aggDic)
-                                                 "pdcsapPeaksCount": "sum",
-                                                 "sapValidSeconds": "sum",
-                                                 "pdcsapValidSeconds": "sum"})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):
@@ -462,30 +431,7 @@ class FlareSummaryPlotGUI(QWidget):
         self.figure.canvas.draw_idle()
 
     def btShowPeriodsClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'pdcsapPeaks',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'sapPeaks',
-                                                    'sapPeriodMinima',
-                                                    'sapPeriodMinimaBoundaries',
-                                                    'sapPeriodMaxima',
-                                                    'sapPeriodMaximaBoundaries',
-                                                    'pdcsapValidTimespans',
-                                                    'pdcsapPeriodMinima',
-                                                    'pdcsapPeriodMinimaBoundaries',
-                                                    'pdcsapPeriodMaxima',
-                                                    'pdcsapPeriodMaximaBoundaries',
-                                                    'sapPeaksCount',
-                                                    'pdcsapPeaksCount',
-                                                    'sapValidSeconds',
-                                                    'pdcsapValidSeconds'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -499,11 +445,14 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
-        print(data["sapPeriod"])
+        aggDic = {}
+        if(self.cbShowSAP.isChecked()):
+            aggDic["sapPeriod"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["pdcsapPeriod"] = "sum"
 
         data = data[showSourceFilter].groupby(["StarName", "SpType"],
-                            as_index=False).agg({"sapPeriod": "mean",
+                            as_index=False).agg(aggDic)
-                                                 "pdcsapPeriod": "mean"})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):
@@ -582,20 +531,7 @@ class FlareSummaryPlotGUI(QWidget):
         pass
 
     def btShowNumMinimaMaximaClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'pdcsapValidTimespans',
-                                                    'sapPeaksCount',
-                                                    'pdcsapPeaksCount',
-                                                    'sapValidSeconds',
-                                                    'pdcsapValidSeconds'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -609,13 +545,15 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
-        print(data["sapPeriod"])
+        aggDic = {}
-
+        if(self.cbShowSAP.isChecked()):
+            aggDic["sapPeriodMinima"] = "sum"
+            aggDic["sapPeriodMaxima"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["pdcsapPeriodMinima"] = "sum"
+            aggDic["pdcsapPeriodMaxima"] = "sum"
         data = data[showSourceFilter].groupby(["StarName", "SpType"],
-                            as_index=False).agg({"sapPeriodMinima": sumArrayLengths,
+                            as_index=False).agg(aggDic)
-                                                 "sapPeriodMaxima": sumArrayLengths,
-                                                 "pdcsapPeriodMinima": sumArrayLengths,
-                                                 "pdcsapPeriodMaxima": sumArrayLengths})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):
@@ -718,20 +656,7 @@ class FlareSummaryPlotGUI(QWidget):
         pass
 
     def btShowNumMinimaMaximaNormalizedClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'pdcsapValidTimespans',
-                                                    'sapPeaksCount',
-                                                    'pdcsapPeaksCount',
-                                                    'sapValidSeconds',
-                                                    'pdcsapValidSeconds'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -745,13 +670,15 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
-        print(data["sapPeriod"])
+        aggDic = {}
-
+        if(self.cbShowSAP.isChecked()):
+            aggDic["sapPeriodMinima"] = "sum"
+            aggDic["sapPeriodMaxima"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["pdcsapPeriodMinima"] = "sum"
+            aggDic["pdcsapPeriodMaxima"] = "sum"
         data = data[showSourceFilter].groupby(["StarName", "SpType"],
-                            as_index=False).agg({"sapPeriodMinima": sumArrayLengthsNorm,
+                            as_index=False).agg(aggDic)
-                                                 "sapPeriodMaxima": sumArrayLengthsNorm,
-                                                 "pdcsapPeriodMinima": sumArrayLengthsNorm,
-                                                 "pdcsapPeriodMaxima": sumArrayLengthsNorm})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):
@@ -854,20 +781,7 @@ class FlareSummaryPlotGUI(QWidget):
         pass
 
     def btShowFlaresInMinimaMaximaClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'pdcsapValidTimespans',
-                                                    'sapPeaksCount',
-                                                    'pdcsapPeaksCount',
-                                                    'sapValidSeconds',
-                                                    'pdcsapValidSeconds'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -881,8 +795,6 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
-        print(data["sapPeriod"])
-
         finalData = []
         #data = data[showSourceFilter].groupby(["StarName", "SpType"],
         #                    as_index=False).agg({"sapPeriod": "mean",
@@ -1011,20 +923,7 @@ class FlareSummaryPlotGUI(QWidget):
         pass
 
     def btShowFlaresInMinimaMaximaPerMinimaMaximaClicked(self):
-        data = self.starFLareDictList.drop(columns=['Distance',
+        data = self.starFLareDictList
-                                                    'DistanceUnit',
-                                                    'FilePath',
-                                                    'RotVel',
-                                                    'RotVelUnit',
-                                                    'Sequence',
-                                                    'pdcsapFits',
-                                                    'sapFits',
-                                                    'sapValidTimespans',
-                                                    'pdcsapValidTimespans',
-                                                    'sapPeaksCount',
-                                                    'pdcsapPeaksCount',
-                                                    'sapValidSeconds',
-                                                    'pdcsapValidSeconds'])
 
         showSourceFilter = np.full(len(data), False)
 
@@ -1038,8 +937,6 @@ class FlareSummaryPlotGUI(QWidget):
             showTESS = data["Source"] == "TESS"
             showSourceFilter |= showTESS
 
-        print(data["sapPeriod"])
-
         finalData = []
         for ind, row in data[showSourceFilter].reset_index().iterrows():
             minimaCountSAP = getNumFlaresInBounds(row["sapFoldedPeaksPhasePair"], 
@@ -1056,15 +953,20 @@ class FlareSummaryPlotGUI(QWidget):
                               "minimaCountPDCSAP": minimaCountPDCSAP, "maximaCountPDCSAP": maximaCountPDCSAP,
                               "minimasPDCSAP": len(row["pdcsapPeriodMinima"]), "maximasPDCSAP": len(row["pdcsapPeriodMaxima"])})
             
+        aggDic = {}
+        if(self.cbShowSAP.isChecked()):
+            aggDic["minimaCountSAP"] = "sum"
+            aggDic["maximaCountSAP"] = "sum"
+            aggDic["minimasSAP"] = "sum"
+            aggDic["maximasSAP"] = "sum"
+        if(self.cbShowPDCSAP.isChecked()):
+            aggDic["minimaCountPDCSAP"] = "sum"
+            aggDic["maximaCountPDCSAP"] = "sum"
+            aggDic["minimasPDCSAP"] = "sum"
+            aggDic["maximasPDCSAP"] = "sum"
+
         data = pd.DataFrame(finalData).groupby(["StarName", "SpType"],
-                            as_index=False).agg({"minimaCountSAP": "sum",
+                            as_index=False).agg(aggDic)
-                                                 "maximaCountSAP": "sum",
-                                                 "minimasSAP": "sum",
-                                                 "maximasSAP": "sum",
-                                                 "minimaCountPDCSAP": "sum",
-                                                 "maximaCountPDCSAP": "sum",
-                                                 "minimasPDCSAP": "sum",
-                                                 "maximasPDCSAP": "sum"})
         x = np.arange(start=1, stop=len(data)+1, step=1, dtype=int)
 
         if(self.cbSpTypeL.isChecked()):

main/astrodatagui/ui/FlaredetectorWidget.py

@@ -265,7 +265,7 @@ class FlaredetectorWidget(QtWidgets.QWidget):
                     self.periodsCalculated.emit([optimizedFold["SpotModulation"]])
                     foldOptimizePhase = optimizedFold["phase"]
                     foldOptimizeFit = optimizedFold["fit"]
-                print(self.FoldState["SpotModulation"])
+                print("SpotModulation", self.FoldState["SpotModulation"])
                 self.epochCalculated.emit(optimizedFold["epoch"])
             else:
                 lc = lc.fold(period=self.FoldState["Period"],
@@ -301,8 +301,8 @@ class FlaredetectorWidget(QtWidgets.QWidget):
                     phase, sineFit, _ = getFoldedBestFit(lc, fitType=self.foldedFitType)
                     self.figureAxis.plot(phase, sineFit, color="red")
                     print(phase, sineFit)
-                    minPhasesBoundsIndices, maxPhasesBoundsIndices = getPhaseRangesNearPeak(getFoldedFitPeakValley(sineFit), phase)
+                    #minPhasesBoundsIndices, maxPhasesBoundsIndices = getPhaseRangesNearPeak(getFoldedFitPeakValley(sineFit), phase)
-                    plotPhaseRangesNearPeak((minPhasesBoundsIndices, maxPhasesBoundsIndices), phase, ax=self.figureAxis)
+                    #plotPhaseRangesNearPeak((minPhasesBoundsIndices, maxPhasesBoundsIndices), phase, ax=self.figureAxis)
                 except Exception as e:
                     print("Failed to get fit")
                     print(e)