def genSpecDistribute():
allModelList = util.listDirFiles(sourceDir)
dic = {}
for modelPath in allModelList:
specType = getSpecType(modelPath)
util.addItemToDic(dic, specType[0], modelPath)
avgCount = int(modelCount / 7)
for key in dic.keys():
modelMatchFileCopy(dic, key, avgCount, modelDir_avg)
disCount = 0
for key in dic_dis.keys():
disCount += dic_dis[key]
for key in dic.keys():
typeCount = int(float(dic_dis[key]) / disCount * modelCount)
if typeCount == 0:
typeCount = 1
modelMatchFileCopy(dic, key, typeCount, modelDir_dis)
for key in dic.keys():
modelMatchFileCopy(dic, key, 10, targetFitsDir)
def fitsToDatabase(self, strategy):
strategy.preHandle()
filePaths = util.listDirFiles(strategy.dirPath, ".fits")
for filePath in filePaths:
try:
fitsInfo = astroUtil.getFitsInfo(filePath)
strategy.handle(fitsInfo)
except Exception, ex:
exUtil.printTagMessage(ex, "Fits handle error", filePath)
def calcMinChi22(flux_target, templateDir, waveRange):
minChi2 = 0
templatePath = ""
templatePaths = util.listDirFiles(templateDir)
for path in templatePaths:
data = np.loadtxt(path)
wave, flux = formatWaveAndFlux(data[:, 0], data[:, 1], waveRange)
chi2_value = mathUtil.chi2(flux_target, flux)
if minChi2 == 0 or chi2_value < minChi2:
minChi2 = chi2_value
templatePath = path
return templatePath, minChi2
def calcMinChi2(flux_target, templateDir, waveRange):
minChi2 = 0
templatePath = ""
minCoeff = None
templatePaths = util.listDirFiles(templateDir)
for path in templatePaths:
data = np.loadtxt(path)
wave, flux = formatWaveAndFlux(data[:, 0], data[:, 1], waveRange)
try:
coeff = mathUtil.calcChi2Coeff(flux_target, flux, wave)
except Exception, ex:
exUtil.printTagMessage(ex, "error", path)
continue
chi2_value = mathUtil.chi2_ploy(wave, flux_target, flux, coeff[0], coeff[1], coeff[2])
if minChi2 == 0 or chi2_value < minChi2:
minChi2 = chi2_value
templatePath = path
minCoeff = coeff
for key in dic_dis.keys():
disCount += dic_dis[key]
for key in dic.keys():
typeCount = int(float(dic_dis[key]) / disCount * modelCount)
if typeCount == 0:
typeCount = 1
modelMatchFileCopy(dic, key, typeCount, modelDir_dis)
for key in dic.keys():
modelMatchFileCopy(dic, key, 10, targetFitsDir)
# genSpecDistribute()
targetFitsList = util.listDirFiles(targetFitsDir, ".sm")
c_1 = 0
c_2 = 0
c_m_1 = 0
c_m_2 = 0
for target in targetFitsList:
st = getSpecType(target)
print "%s , %s" % (target, st)
templatePath, minChi2 = specUtil.modelMatch2(target, modelDir_avg)
st1 = getSpecType(templatePath)
print "AVG : %s , %s, %s" % (templatePath, minChi2, st1)
templatePath_dis, minChi2_dis = specUtil.modelMatch2(target, modelDir_dis)
st2 = getSpecType(templatePath_dis)
