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generate_plots: bring uptodate for changes, add max flare peak plots

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SGCMarkus
2025-04-27 20:32:44 +02:00
parent 54bd2e4bff
commit 060cae2264
1 changed files with 86 additions and 83 deletions
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generate_plots.py
+15 -12
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@@ -27,7 +27,7 @@ def mkdir_p(mypath):
pass
else: raise
fileName = "datav5.cff"
fileName = "datav5.1.cff"
data = pd.read_pickle(fileName)
binList = [10, 20, 30]
@@ -51,13 +51,13 @@ if(useTESS):
current = datetime.now()
date = f"{current.year}-{current.month}-{current.day}"
time = f"{current.hour}-{current.minute}-{current.second}"
folderPath = f"../{date}/"
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 = data[((data["FitType"] == "sine") | (data["FitType"] == "poly")) & (data["isValidFold"])]
validStarPeriodMap = []
starList = set(list(data["StarName"]))
@@ -155,18 +155,19 @@ def plotFlarePeaks(plotdata, filters, labels, colors, maxY, title, filename):
if(isinstance(labels, list) and isinstance(colors, list)):
_, ((axFlarePeaks)) = plt.subplots(nrows=1, ncols=1)
for f, l, c in zip(filters, labels, colors):
axFlarePeaks.scatter(plotdata[f]["PDCSAPNormPhase"],
plotdata[f]["Peak"],
axFlarePeaks.scatter(plotdata[f]["PDCSAPNormPhase"] if "PDCSAPNormPhase" in plotdata[f].columns else plotdata[f]["PDCSAPNormPhasePeriod"],
plotdata[f]["Peak"] if "Peak" in plotdata[f].columns else plotdata[f]["PeakPeriod"],
label=l, color=c)
elif(isinstance(labels, str) and isinstance(colors, str)):
_, ((axFlarePeaks)) = plt.subplots(nrows=1, ncols=1)
if(filters is None):
axFlarePeaks.scatter(plotdata[:]["PDCSAPNormPhase"],
plotdata[:]["Peak"],
axFlarePeaks.scatter(plotdata[:]["PDCSAPNormPhase"] if "PDCSAPNormPhase" in plotdata[:].columns else plotdata[:]["PDCSAPNormPhasePeriod"],
plotdata[:]["Peak"] if "Peak" in plotdata[:].columns else plotdata[:]["PeakPeriod"],
label=labels, color=colors)
else:
axFlarePeaks.scatter(plotdata[filters]["PDCSAPNormPhase"],
plotdata[filters]["Peak"],
axFlarePeaks.scatter(plotdata[filters]["PDCSAPNormPhase"] if "PDCSAPNormPhase" in plotdata[filters].columns else plotdata[filters]["PDCSAPNormPhasePeriod"],
plotdata[filters]["Peak"] if "Peak" in plotdata[filters].columns else plotdata[filters]["PeakPeriod"],
label=labels, color=colors)
else:
return
@@ -313,8 +314,8 @@ for starName in starDB.getAllStars():
else:
color = "gray"
PDCSAPdataList2dhistPhase.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhase"])
PDCSAPdataList2dhistPeak.append(pdcsapbinningDataSpotModDiffPeriod[:]["Peak"])
PDCSAPdataList2dhistPhase.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhasePeriod"])
PDCSAPdataList2dhistPeak.append(pdcsapbinningDataSpotModDiffPeriod[:]["PeakPeriod"])
xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataList)
@@ -525,6 +526,7 @@ for comboLength in range(1, len(spType) + 1):
print(row["StarName"], "has over 100 peak")
csvFile.close()
if(len(pdcsapbinningData) > 0):
pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
PDCSAPdataList = []
PDCSAPlabelList = []
@@ -576,7 +578,7 @@ for comboLength in range(1, len(spType) + 1):
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"]
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:
case "M":
color = "red"
@@ -616,6 +618,7 @@ for comboLength in range(1, len(spType) + 1):
if(peak["FlarePeak"] > 100):
print(row["StarName"], "has over 100 peak")
csvFile.close()
if(len(pdcsapbinningData) > 0):
pdcsapbinningData = pd.DataFrame(pdcsapbinningData)
PDCSAPdataList = []
PDCSAPlabelList = []