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generate_plots: use multiprocessing

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SGCMarkus
2025-05-06 11:48:01 +02:00
parent 43eb79bcc6
commit 7d574febcf
1 changed files with 515 additions and 489 deletions
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generate_plots.py
+109 -83
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@@ -1,3 +1,4 @@
from math import comb
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import itertools import itertools
@@ -9,6 +10,10 @@ from datetime import datetime
from errno import EEXIST from errno import EEXIST
from os import makedirs, path from os import makedirs, path
import shutil import shutil
import multiprocessing
import concurrent.futures
from concurrent.futures import wait, ALL_COMPLETED
from functools import partial
def normalizePhase(phase, phaseMin = None, phaseMax = None): def normalizePhase(phase, phaseMin = None, phaseMax = None):
if(phaseMin is None): if(phaseMin is None):
@@ -27,41 +32,6 @@ def mkdir_p(mypath):
pass pass
else: raise 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}-poly-only/"
#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"] == "poly")) & (data["isValidFold"])]
validStarPeriodMap = []
starList = set(list(data["StarName"]))
def allValuesWithin3Std(values: list): def allValuesWithin3Std(values: list):
if(not values or len(values) == 1): if(not values or len(values) == 1):
return True return True
@@ -71,19 +41,6 @@ def allValuesWithin3Std(values: list):
def getMeanPeriod(values: list): def getMeanPeriod(values: list):
return np.mean(values) 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): def plotBinsHistogram(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, bins, title, filename, foldedFits):
figHisto, ((axHisto)) = plt.subplots(nrows=1, ncols=1) figHisto, ((axHisto)) = plt.subplots(nrows=1, ncols=1)
y, binEdges, _ = axHisto.hist(PDCSAPdataList, bins, y, binEdges, _ = axHisto.hist(PDCSAPdataList, bins,
@@ -182,9 +139,8 @@ def plotFlarePeaks(plotdata, filters, labels, colors, maxY, title, filename):
plt.savefig(filename) plt.savefig(filename)
plt.close() plt.close()
def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, pdcsapbinningData,
PDCSAPdataList=None, dataFilter=None, pdcsapbinningDataColumn, PDCSAPdataList=None, dataFilter=None):
PeriodModulation=False):
xData = pd.DataFrame() xData = pd.DataFrame()
yData = pd.DataFrame() yData = pd.DataFrame()
for aX, aY in zip(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak): for aX, aY in zip(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak):
@@ -195,15 +151,9 @@ def setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
yData = np.asarray(yData.values)[:,0] yData = np.asarray(yData.values)[:,0]
if(PDCSAPdataList is not None): if(PDCSAPdataList is not None):
if(dataFilter is not None): if(dataFilter is not None):
if(PeriodModulation): PDCSAPdataList.append(pdcsapbinningData[dataFilter][pdcsapbinningDataColumn])
PDCSAPdataList.append(pdcsapbinningDataSpotModDiffPeriod[dataFilter]["PDCSAPNormPhasePeriod"])
else: else:
PDCSAPdataList.append(pdcsapbinningData[dataFilter]["PDCSAPNormPhase"]) PDCSAPdataList.append(pdcsapbinningData[:][pdcsapbinningDataColumn])
else:
if(PeriodModulation):
PDCSAPdataList.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhasePeriod"])
else:
PDCSAPdataList.append(pdcsapbinningData[:]["PDCSAPNormPhase"])
return xData, yData, PDCSAPdataList return xData, yData, PDCSAPdataList
@@ -226,8 +176,7 @@ def generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, histogramTit
flarePlotFilename = flarePlotFilenameArg.replace("@maxY", str(maxY)) flarePlotFilename = flarePlotFilenameArg.replace("@maxY", str(maxY))
plotFlarePeaks(plotdata, filters, flarePlotLabels, flarePlotColors, maxY, flarePlotTitle, flarePlotFilename) plotFlarePeaks(plotdata, filters, flarePlotLabels, flarePlotColors, maxY, flarePlotTitle, flarePlotFilename)
# All stars def plotStar(data, showSourceFilter, folderPath, starName):
for starName in starDB.getAllStars():
finalData = pd.DataFrame() finalData = pd.DataFrame()
starNameR = starName.replace('*', '_star_') starNameR = starName.replace('*', '_star_')
nameFilter = data["StarName"] == starName nameFilter = data["StarName"] == starName
@@ -292,11 +241,11 @@ for starName in starDB.getAllStars():
PDCSAPdataList2dhistPhase.append(pdcsapbinningData[:]["PDCSAPNormPhase"]) PDCSAPdataList2dhistPhase.append(pdcsapbinningData[:]["PDCSAPNormPhase"])
PDCSAPdataList2dhistPeak.append(pdcsapbinningData[:]["Peak"]) 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) PDCSAPcolorList.append(color)
generatePlots(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, f"Flare count in phase of {starName} with @bins bins", f"{locFolder}/{starNameR}-Flarecount-@bins_Bins.png", 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", 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", pdcsapbinningData, None, f"{starName}", color, f"Flare peaks per phase of {starName}", f"{locFolder}/{starNameR}-Flarepeaks_maxY-@maxY.png",
@@ -323,7 +272,9 @@ for starName in starDB.getAllStars():
PDCSAPdataList2dhistPhase.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhasePeriod"]) PDCSAPdataList2dhistPhase.append(pdcsapbinningDataSpotModDiffPeriod[:]["PDCSAPNormPhasePeriod"])
PDCSAPdataList2dhistPeak.append(pdcsapbinningDataSpotModDiffPeriod[:]["PeakPeriod"]) PDCSAPdataList2dhistPeak.append(pdcsapbinningDataSpotModDiffPeriod[:]["PeakPeriod"])
xData, yData, PDCSAPdataListPeriod = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataListPeriod, PeriodModulation=True) xData, yData, PDCSAPdataListPeriod = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
pdcsapbinningDataSpotModDiffPeriod, "PDCSAPNormPhasePeriod",
PDCSAPdataListPeriod)
PDCSAPlabelList.append(f"{starName}") PDCSAPlabelList.append(f"{starName}")
PDCSAPcolorList.append(color) PDCSAPcolorList.append(color)
@@ -333,9 +284,7 @@ for starName in starDB.getAllStars():
pdcsapbinningDataSpotModDiffPeriod, None, f"{starName}", color, f"Flare peaks per phase of {starName}", f"{locFolder}/{starNameR}-Flarepeaks_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) foldedPeriodFits)
def plotCombo(data, showSourceFilter, folderPath, combo):
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]: for maxFlarePeak in [1.01, 1.05, 1.1, 1.25, 1.5]:
# max Flare Peak cut # max Flare Peak cut
finalDataMaxFlarePeak = pd.DataFrame() finalDataMaxFlarePeak = pd.DataFrame()
@@ -438,10 +387,11 @@ for comboLength in range(1, len(spType) + 1):
PDCSAPcolorListU.append("greenyellow") PDCSAPcolorListU.append("greenyellow")
plotFiltersU.append(Ffilter) 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 ({numStars} 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 ({numStars} 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 ({numStars} stars)", f"{locFolderU}/{''.join(combo)}_maxFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
if(len(pdcsapbinningDataO) > 0): if(len(pdcsapbinningDataO) > 0):
@@ -485,10 +435,11 @@ for comboLength in range(1, len(spType) + 1):
PDCSAPcolorListO.append("greenyellow") PDCSAPcolorListO.append("greenyellow")
plotFiltersO.append(Ffilter) 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 ({numStars} 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 ({numStars} stars)", f"{locFolderO}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks-@bins_Bins_maxY-@maxY.png",
pdcsapbinningDataO, plotFiltersO, PDCSAPlabelListO, PDCSAPcolorListO, f"Flare peaks per phase of {', '.join(combo)} type stars ({numStars} stars)", f"{locFolderO}/{''.join(combo)}_minFlarePeak_{maxFlarePeak}-Flarepeaks_maxY-@maxY.png")
# all flare peaks # all flare peaks
finalDataAllFlarePeaks = pd.DataFrame() finalDataAllFlarePeaks = pd.DataFrame()
if("M" in combo): if("M" in combo):
@@ -575,14 +526,15 @@ for comboLength in range(1, len(spType) + 1):
PDCSAPcolorList.append("greenyellow") PDCSAPcolorList.append("greenyellow")
plotFilters.append(Ffilter) plotFilters.append(Ffilter)
xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak) xData, yData, _ = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
pdcsapbinningData, "PDCSAPNormPhase",)
plotdata = pdcsapbinningData plotdata = pdcsapbinningData
filters = plotFilters 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", 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", 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") 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): if(len(combo) == 1):
mainSpType = combo[0] 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: match mainSpType:
@@ -642,7 +594,9 @@ for comboLength in range(1, len(spType) + 1):
PDCSAPdataList2dhistPeak.append(pdcsapbinningData[SpTypefilter]["Peak"]) PDCSAPdataList2dhistPeak.append(pdcsapbinningData[SpTypefilter]["Peak"])
PDCSAPlabelList.append(f"{spTyp} Stars") PDCSAPlabelList.append(f"{spTyp} Stars")
PDCSAPcolorList.append(color) PDCSAPcolorList.append(color)
xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak, PDCSAPdataList, SpTypefilter) xData, yData, PDCSAPdataList = setupxyDataAndDataList(PDCSAPdataList2dhistPhase, PDCSAPdataList2dhistPeak,
pdcsapbinningData, "PDCSAPNormPhase",
PDCSAPdataList, SpTypefilter)
plotdata = pdcsapbinningData plotdata = pdcsapbinningData
filters = SpTypefilter filters = SpTypefilter
@@ -692,13 +646,13 @@ for comboLength in range(1, len(spType) + 1):
for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]): for td, peak, pv in zip(pdcsapVals["Phase"], pdcsapVals["Peak"], row["pdcsapPeaks"]):
normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase)) normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
if(row["MeanPeriod"] <= periodCut): 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") csvFileU.write("\n")
pdcsapbinningDataU.append({"SpType": f'{row["SpType"][0]}', pdcsapbinningDataU.append({"SpType": f'{row["SpType"][0]}',
"PDCSAPNormPhase": normPhase, "PDCSAPNormPhase": normPhase,
"Peak": peak["FlarePeak"]}) "Peak": peak["FlarePeak"]})
else: 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") csvFileO.write("\n")
pdcsapbinningDataO.append({"SpType": f'{row["SpType"][0]}', pdcsapbinningDataO.append({"SpType": f'{row["SpType"][0]}',
"PDCSAPNormPhase": normPhase, "PDCSAPNormPhase": normPhase,
@@ -782,16 +736,88 @@ for comboLength in range(1, len(spType) + 1):
plotFiltersO.append(FfilterO) plotFiltersO.append(FfilterO)
if(len(PDCSAPdataList2dhistPhaseU) > 0 and len(PDCSAPdataList2dhistPeakU) > 0): 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): 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)", 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)", 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)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_u_{periodCut}-maxY_@maxY.png")
if(len(PDCSAPdataList2dhistPhaseO) > 0 and len(PDCSAPdataList2dhistPeakO) > 0): 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): 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)", 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)", 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)", f"{locFolder}/{''.join(combo)}-Flarepeaks-Period_o_{periodCut}-maxY_@maxY.png")
binList = [10, 20, 30]
spType = ["M", "K", "G", "F"]
if __name__ == "__main__":
fileName = "datav5.1.cff"
fullData = pd.read_pickle(fileName)
starDB: StarDB = StarDB.getInstance("stars.db")
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()
executor = concurrent.futures.ProcessPoolExecutor(cpuCount)
#executor = concurrent.futures.ThreadPoolExecutor(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)
if("sine" in foldedFitTypeCombo):
foldedFitTypeComboFilter |= fullData["FitType"] == "sine"
if("poly" in foldedFitTypeCombo):
foldedFitTypeComboFilter |= fullData["FitType"] == "poly"
data = fullData[(foldedFitTypeComboFilter) & (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)
periodsCutList = [0.5, 1, 1.5, 2, 5, 10, 15, 20]
data = pd.merge(data, validStarPeriodMap, on="StarName")
starPlotFunc = partial(plotStar, data, showSourceFilter, folderPath)
list(executor.map(starPlotFunc, starDB.getAllStars())) # 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(executor.map(plotComboFunc, combos))