Compare commits

1 Commits

Author SHA1 Message Date
SGCMarkus 748589da17 fix period plot generation after rework 2025-05-21 19:44:23 +02:00
+4 -4
View File
@@ -86,6 +86,8 @@ 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)
@@ -246,9 +248,7 @@ def plotStarPeriod(data, showSourceFilter, folderPath, starName):
nameFilter &= showSourceFilter
finalData = pd.concat([finalData, data[nameFilter]], ignore_index=True)
pdcsapbinningData = []
pdcsapbinningDataSpotModDiffPeriod = []
foldedFits = []
foldedPeriodFits = []
locFolder = f"{folderPath}/stars/{starNameR}/"
mkdir_p(f"{locFolder}/")
@@ -265,12 +265,12 @@ def plotStarPeriod(data, showSourceFilter, folderPath, starName):
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")
pdcsapbinningData.append({"SpType": f'{row["SpType"][0:2] if len(row["SpType"]) > 1 else row["SpType"][0]}',
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")
foldedFits.append([normalizePhase(row["pdcsapFoldedFitPhase"]), row["pdcsapFoldedFit"]])
foldedPeriodFits.append([normalizePhase(row["pdcsapFoldedFitPhase"]), row["pdcsapFoldedFit"]])
csvFile.close()
pdcsapbinningDataSpotModDiffPeriod = pd.DataFrame(pdcsapbinningDataSpotModDiffPeriod) if len(pdcsapbinningDataSpotModDiffPeriod) > 0 else None