generate_plots_MKGF: generate histograms with lower peaks only too

generate_plots_MKGF.py

@@ -55,6 +55,148 @@ folderPath = f"../{date}/"
 #folderPath = f"G:/Meine Ablage/Masterthesis/{date}/"
 mkdir_p(folderPath)
 
+for comboLength in range(1, len(spType) + 1):
+    for combo in itertools.combinations(spType, comboLength):
+        for maxFlarePeak in [1.01, 1.05, 1.1, 1.25, 1.5]:
+            finalData = pd.DataFrame()
+            if("M" in combo):
+                Mfilter = data["SpType"].str.startswith("M")
+                Mfilter &= showSourceFilter
+                finalData = pd.concat([finalData, data[Mfilter]], ignore_index=True)
+            if("K" in combo):
+                Kfilter = data["SpType"].str.startswith("K")
+                Kfilter &= showSourceFilter
+                finalData = pd.concat([finalData, data[Kfilter]], ignore_index=True)
+            if("G" in combo):
+                Gfilter = data["SpType"].str.startswith("G")
+                Gfilter &= showSourceFilter
+                finalData = pd.concat([finalData, data[Gfilter]], ignore_index=True)
+            if("F" in combo):
+                Ffilter = data["SpType"].str.startswith("F")
+                Ffilter &= showSourceFilter
+                finalData = pd.concat([finalData, data[Ffilter]], ignore_index=True)
+
+            numStars = len(set(finalData["StarName"]))
+
+            pdcsapbinningData = []
+            locFolder = f"{folderPath}/{''.join(combo)}/"
+            mkdir_p(f"{locFolder}/")
+            csvFile = open(f"{locFolder}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}.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 finalData.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"]):
+                            if(peak["FlarePeak"] <= maxFlarePeak):
+                                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) < 1):
+                continue
+            pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
+            PDCSAPdataList = []
+            PDCSAPlabelList = []
+            PDCSAPcolorList = []
+            PDCSAPdataList2dhistPhase = []
+            PDCSAPdataList2dhistPeak = []
+            PDCSAPlabelList2dhist = []
+            PDCSAPcolorList2dhist = []
+            if("M" in combo):
+                Mfilter = pdcsapbinningData["SpType"] == "M"
+                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Mfilter]["PDCSAPNormPhase"])
+                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Mfilter]["Peak"])
+                PDCSAPlabelList2dhist.append("M Stars")
+                PDCSAPcolorList2dhist.append("red")
+
+                PDCSAPdataList.append(pdcsapbinningData[Mfilter]["PDCSAPNormPhase"])
+                PDCSAPlabelList.append("M Stars")
+                PDCSAPcolorList.append("red")
+            if("K" in combo):
+                Kfilter = pdcsapbinningData["SpType"] == "K"
+                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Kfilter]["PDCSAPNormPhase"])
+                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Kfilter]["Peak"])
+                PDCSAPlabelList2dhist.append("K Stars")
+                PDCSAPcolorList2dhist.append("orange")
+
+                PDCSAPdataList.append(pdcsapbinningData[Kfilter]["PDCSAPNormPhase"])
+                PDCSAPlabelList.append("K Stars")
+                PDCSAPcolorList.append("orange")
+            if("G" in combo):
+                Gfilter = pdcsapbinningData["SpType"] == "G"
+                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Gfilter]["PDCSAPNormPhase"])
+                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Gfilter]["Peak"])
+                PDCSAPlabelList2dhist.append("G Stars")
+                PDCSAPcolorList2dhist.append("yellow")
+
+                PDCSAPdataList.append(pdcsapbinningData[Gfilter]["PDCSAPNormPhase"])
+                PDCSAPlabelList.append("G Stars")
+                PDCSAPcolorList.append("yellow")
+            if("F" in combo):
+                Ffilter = pdcsapbinningData["SpType"] == "F"
+                PDCSAPdataList2dhistPhase.append(pdcsapbinningData[Ffilter]["PDCSAPNormPhase"])
+                PDCSAPdataList2dhistPeak.append(pdcsapbinningData[Ffilter]["Peak"])
+                PDCSAPlabelList2dhist.append("F Stars")
+                PDCSAPcolorList2dhist.append("greenyellow")
+
+                PDCSAPdataList.append(pdcsapbinningData[Ffilter]["PDCSAPNormPhase"])
+                PDCSAPlabelList.append("F Stars")
+                PDCSAPcolorList.append("greenyellow")
+
+            xData = pd.DataFrame()
+            yData = pd.DataFrame()
+            for aX, aY in zip(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak):
+                xData = pd.concat([xData, aX], ignore_index=True)
+                yData = pd.concat([yData, aY], ignore_index=True)
+
+            xData = np.asarray(xData.values)[:,0]
+            yData = np.asarray(yData.values)[:,0]
+
+            for bins in binList:
+                figHisto, ((axHisto)) = plt.subplots(nrows=1, ncols=1)
+                y, binEdges, _ = axHisto.hist(PDCSAPdataList, bins,
+                                              label=PDCSAPlabelList,
+                                              color=PDCSAPcolorList,
+                                              stacked=True,
+                                              range=[0, 2])
+                bincenters = 0.5*(binEdges[1:]+binEdges[:-1])
+                if(isinstance(y[0], np.ndarray)):
+                    y = y[-1]
+                n_i = y
+                m_i = bincenters * np.pi
+                N = np.sum(n_i)
+                mean = np.sum(n_i * m_i)/N
+                stdDev = np.sqrt(np.sum(((n_i - mean)**2)) / (N-1))
+                menStd = np.sqrt(y)
+                if(np.isinf(stdDev)):
+                    stdDev = np.mean(menStd)
+                axHisto.bar(bincenters[y > 0], y[y > 0], width=0, color='r', yerr=stdDev)
+                axHisto.set_ylim(0, max(y) + stdDev)
+                axHisto.set_ylabel("Num. flares")
+                axHisto.set_xlabel("Phase")
+                axHisto.set_title(f"Flare count per phase of {', '.join(combo)} type stars with {bins} bins ({numStars} stars)")
+                axHisto.xaxis.set_major_formatter(tck.FormatStrFormatter('%g $\pi$'))
+                axHisto.xaxis.set_major_locator(MaxNLocator(5))
+                axHisto.legend()
+
+                axHistoPhase = axHisto.twinx()
+                secAxisXdata = np.linspace(0, 2, num=10000)
+                secAxisYdata = np.cos(secAxisXdata*np.pi) + 1
+                axHistoPhase.plot(secAxisXdata, secAxisYdata)
+                axHistoPhase.set_ylim(0, 7)
+
+                plt.savefig(f"{locFolder}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarecount-{bins}_Bins.png")
+                plt.close()
+
 for comboLength in range(1, len(spType) + 1):
     for combo in itertools.combinations(spType, comboLength):
         finalData = pd.DataFrame()