def checkDistances(inFileName, angDiamFileName, outFileName):
hashSearch = csvFree.readCSVFile(
hashSearchFileName[:hashSearchFileName.rfind('.')] +
'_with_header.csv')
hashFound = csvFree.readCSVFile(inFileName)
angDiams = csvFree.readCSVFile(angDiamFileName)
csvOut = csvData.CSVData()
csvOut.header = hashFound.header
nNotFound = 0
ra_3238 = hmsToDeg('17:59:45.20')
dec_3238 = dmsToDeg('-33:21:13.00')
toDelete = []
for i in range(hashFound.size()):
name = hashFound.getData('id', i)
idPNMain = hashFound.getData('pndb', i)
if idPNMain == '':
csvOut.append(hashFound.getData(i))
else:
dist = float(hashFound.getData('dist[arcsec]', i))
found = False
for j in range(angDiams.size()):
if angDiams.getData('idPNMain', j) == idPNMain:
if angDiams.getData('InUse', j) == '1':
found = True
if dist > float(angDiams.getData('MajDiam', j)):
csvOut.append([name, '', ''])
else:
csvOut.append(hashFound.getData(i))
if not found:
nNotFound += 1
print(
'Problem: did not find an angular diameter for <' + name +
'>: idPNMain = ', idPNMain, ', dist = ', dist)
if dist > 50.:
csvOut.append([name, '', ''])
else:
csvOut.append(hashFound.getData(i))
for j in range(hashSearch.size()):
if hashSearch.getData('id',
j) == csvOut.getData('id',
csvOut.size() - 1):
ra = hmsToDeg(hashSearch.getData('ra', j))
dec = dmsToDeg(hashSearch.getData('dec', j))
angDist = angularDistance(ra, dec, ra_3238, dec_3238)
print('ra = ', ra, ', dec = ', dec, ': angDist = ', angDist)
angDistPyAsl = pyasl.getAngDist(ra, dec, ra_3238,
dec_3238) * 3600.
if angDist < 800:
if csvOut.getData('pndb', csvOut.size() - 1) != '3238':
toDelete.append([
csvOut.getData('pndb',
csvOut.size() - 1), ra, dec,
angDist, angDistPyAsl
])
csvOut.setData('pndb', csvOut.size() - 1, '3238')
csvFree.writeCSVFile(csvOut, outFileName)
for i in toDelete:
print('toDelete : ', i)
def readFiles():
csv = csvData.CSVData()
for iFile in np.arange(0, len(files), 1):
dataTemp = readFile(files[iFile])
if iFile == 0:
csv.header = dataTemp[0]
csv.data = dataTemp[1:]
else:
csv.append(dataTemp[1:])
return csv
def findClosestMatch(hashFoundFile, outFileName):
hashFound = csvFree.readCSVFile(hashFoundFile)
closestMatch = csvData.CSVData()
closestMatch.header = hashFound.header
hashFoundNames = np.array([str(n) for n in hashFound.getData('id')])
print('hashFoundNames = ', hashFoundNames)
nDoubles = 0
for name in hashFoundNames:
name = str(name)
idx = np.where(hashFoundNames == name)[0]
if len(idx) == 0:
arr = bytes(name, 'utf-8')
arr2 = bytes(hashFoundNames[0], 'utf-8')
for byte in arr:
print(byte, end=' ')
print("\n")
for byte in arr2:
print(byte, end=' ')
print("\n")
if name == hashFoundNames[0]:
print('both are the same')
else:
print('both are still not the same')
if str(name) == str(hashFoundNames[0]):
print('both are the same if using unicode')
else:
print('both are still not the same if using unicode')
print('found name <' + name + '> ', len(idx), ' times in indices ',
idx)
lineToAdd = ''
if len(idx) == 1:
lineToAdd = hashFound.getData(idx[0])
else:
dists = []
for i in range(len(idx)):
dist = hashFound.getData('dist[arcsec]', idx[i])
if dist != '':
dists.append(float(dist))
if len(dists) > 0:
minId = np.where(dists == np.min(dists))[0][0]
else:
minId = 0
print('idx[', minId, '] = ', idx[minId])
lineToAdd = hashFound.getData(idx[minId])
closestMatchNames = closestMatch.getData('id')
if name not in closestMatchNames:
print('lineToAdd = ', lineToAdd)
closestMatch.append(lineToAdd)
else:
print('name <' + name + '> already in closestMatch')
nDoubles += 1
print('nDoubles = ', nDoubles)
csvFree.writeCSVFile(closestMatch, outFileName)
def combineDiscrepancies():
discrepanciesA = readCSVFile(discrepanciesAFile)
discrepanciesB = readCSVFile(discrepanciesBFile)
csvOut = csvData.CSVData()
csvOut.header = ['Name','RA','DEC']
for c in [discrepanciesA,discrepanciesB]:
for i in range(c.size()):
lineOut = [c.getData('NOM',i),c.getData('AD:(J2000)',i),c.getData('DEC (J2000)',i)]
csvOut.append(lineOut)
print('csvOut.size() = ',csvOut.size())
return csvOut
def checkCombinedDiscrepancies(combinedDiscrepancies, allHASHobjects, hashCommonNames):
csvOut = csvData.CSVData()
csvOut.header = ['Name','idPNMain','HASH common names', 'RA FRA', 'RA HASH', 'DEC FRA', 'DEC HASH', 'angular distance [arcsec]']
csvOut.data = []
emptyData = ['','','', '', '', '', '', '']
for i in range(combinedDiscrepancies.size()):
ra = combinedDiscrepancies.getData('RA',i)
dec = combinedDiscrepancies.getData('DEC',i)
raDeg = hmsToDeg(ra)
decDeg = dmsToDeg(dec)
name = getName(combinedDiscrepancies,'Name',i)
print('name = <'+name+'>')
found = False
for j in range(allHASHobjects.size()):
if name == allHASHobjects.getData('Name',j).replace(' ',''):
hashID = allHASHobjects.getData('idPNMain',j)
angDist = degToArcsec(angularDistancePyAsl(raDeg,decDeg,hmsToDeg(allHASHobjects.getData('RAJ2000',j)),dmsToDeg(allHASHobjects.getData('DECJ2000',j))))
commonNames = getCommonNames(hashCommonNames,'idPNMain',hashID)
print('Name = '+name+': HASH ID = ',hashID,': commonNames = ',commonNames,': ra = ',ra,', RA = ',allHASHobjects.getData('RAJ2000',j),', dec = ',dec,', DEC = ',allHASHobjects.getData('DECJ2000',j),', angDist = ',angDist)
found = True
if not found:
print('ERROR: object with name <'+name+'> not found in HASH')
for j in range(allHASHobjects.size()):
angDist = degToArcsec(angularDistancePyAsl(raDeg,decDeg,hmsToDeg(allHASHobjects.getData('RAJ2000',j)),dmsToDeg(allHASHobjects.getData('DECJ2000',j))))
if angDist < maxAngularDistance:
hashID = allHASHobjects.getData('idPNMain',j)
commonNames = getCommonNames(hashCommonNames,'idPNMain',hashID)
if name in commonNames:
print('Name = '+name+': HASH ID = ',hashID,': commonNames = ',commonNames,': ra = ',ra,', RA = ',allHASHobjects.getData('RAJ2000',j),', dec = ',dec,', DEC = ',allHASHobjects.getData('DECJ2000',j),', angDist = ',angDist)
found = True
else:
print('Name = <'+name+'>: object found within ',maxAngularDistance,' arcsec: angDist = ',angDist,': ra = ',ra,', RA = ',allHASHobjects.getData('RAJ2000',j),', dec = ',dec,', DEC = ',allHASHobjects.getData('DECJ2000',j),', HASH name = <'+allHASHobjects.getData('Name',j))
csvOut.append(emptyData)
csvOut.setData('Name',csvOut.size()-1,name)
csvOut.setData('idPNMain',csvOut.size()-1,hashID)
cNames = commonNames[0]
for k in np.arange(1,len(commonNames),1):
cNames += ';'+commonNames[k]
csvOut.setData('HASH common names',csvOut.size()-1,cNames)
csvOut.setData('RA FRA',csvOut.size()-1,ra)
csvOut.setData('RA HASH',csvOut.size()-1,allHASHobjects.getData('RAJ2000',j))
csvOut.setData('DEC FRA',csvOut.size()-1,dec)
csvOut.setData('DEC HASH',csvOut.size()-1,allHASHobjects.getData('DECJ2000',j))
csvOut.setData('angular distance [arcsec]',csvOut.size()-1,str(angDist))
writeCSVFile(csvOut,disrepanciesOutFileName)
def fixHashFile():
with open(outputSQLFile, 'w') as w:
csvHash = csvData.CSVData()
with open(inputHashFile, 'r') as f:
hashData = csv.DictReader(f)
print('hashData.fieldnames = ', hashData.fieldnames)
csvHash.header = hashData.fieldnames
with open(inputHashFile, 'r') as f:
hashData = csv.DictReader(f)
print('hashData.fieldnames = ', hashData.fieldnames)
nRows = 0
for row in hashData:
nRows += 1
csvHash.append([row[x] for x in hashData.fieldnames])
# if row['CS_DRAJ2000'] == 'NULL':
print("row['CS_DECJ2000'].split(':')[0][:2] = <" +
row['CS_DECJ2000'].split(':')[0][:2] + ">")
if row['CS_DECJ2000'].split(':')[0][:2] == '-0':
print('row = ', row)
dra = hmsToDeg(
csvHash.getData('CS_RAJ2000',
csvHash.size() - 1))
ddec = dmsToDeg(
csvHash.getData('CS_DECJ2000',
csvHash.size() - 1))
lon, lat = raDecToLonLat(dra, ddec)
csvHash.setData('CS_DRAJ2000',
csvHash.size() - 1, str(dra))
csvHash.setData('CS_DDECJ2000',
csvHash.size() - 1, str(ddec))
csvHash.setData('CS_Glon', csvHash.size() - 1, str(lon))
csvHash.setData('CS_Glat', csvHash.size() - 1, str(lat))
w.write("UPDATE MainGPN.tbCSCoords SET CS_DRAJ2000 = " +
str(dra) + ", CS_DDECJ2000 = " + str(ddec) +
", CS_Glon = " + str(lon) + ", CS_Glat = " +
str(lat) + ", CSstat = 'p' WHERE idtbCSCoords = " +
csvHash.getData('idtbCSCoords',
csvHash.size() - 1) + ";\n")
return csvHash
import csvData,csvFree
inFileName = '/Users/azuri/daten/uni/HKU/HASH/hash-no-show.csv'
inData = csvFree.readCSVFile(inFileName)
print('inData.size() = ',inData.size())
pnStat = inData.getData('PNstat')
print('pnStat = ',pnStat)
tlps = csvData.CSVData()
tlps.header = inData.header
newCandidates = csvData.CSVData()
newCandidates.header = inData.header
others = csvData.CSVData()
others.header = inData.header
for i in range(inData.size()):
pnStat = inData.getData('PNstat',i)
if pnStat in ['T','L','P']:
tlps.append(inData.getData(i))
elif pnStat == 'c':
newCandidates.append(inData.getData(i))
else:
others.append(inData.getData(i))
csvFree.writeCSVFile(tlps,inFileName[:-4]+'_TLPs.csv')
csvFree.writeCSVFile(newCandidates,inFileName[:-4]+'_newCandidates.csv')
csvFree.writeCSVFile(others,inFileName[:-4]+'_others.csv')
import numpy as np
import csvFree, csvData
eventRegistrationFile = '/Users/azuri/daten/parties/Wild Wood/contacts/Completed orders export.csv'
oldContactsFile = '/Users/azuri/daten/parties/Wild Wood/contacts/contacts.csv'
contactsToImport = '/Users/azuri/daten/parties/Wild Wood/contacts/contacts_to_import.csv'
existingContactsFile = '/Users/azuri/daten/parties/Wild Wood/existing_contacts.csv'
volunteersFile = '/Users/azuri/daten/parties/Wild Wood/Wild Woods Volunteers Questionnaire.csv'
csvEventRegistration = csvFree.readCSVFile(eventRegistrationFile)
csvOldContacts = csvFree.readCSVFile(oldContactsFile)
existingContacts = csvFree.readCSVFile(existingContactsFile)
volunteers = csvFree.readCSVFile(volunteersFile)
csvContactsToImport = csvData.CSVData()
csvContactsToImport.header = csvOldContacts.header
newLine = ['' for i in csvOldContacts.header]
print('csvEventRegistration.header = ', csvEventRegistration.header)
iContact = 0
names = []
for i in range(csvEventRegistration.size()):
name = csvEventRegistration.getData(
'First Name (Billing)', i) + ' ' + csvEventRegistration.getData(
'Last Name (Billing)', i) + ' Wild Wood Guest'
print('name = ', name)
if name not in names:
print(name + ' not found')
names.append(name)
import csvFree, csvData
from myUtils import angularDistance, hmsToDeg, dmsToDeg
f1name = '/Users/azuri/daten/uni/HKU/interns_projects/simba/Weidman-table1.csv'
f2name = '/Users/azuri/daten/uni/HKU/interns_projects/simba/Weidmann2020-cs-parameters.txt'
sqlFileOut = '/Users/azuri/daten/uni/HKU/interns_projects/simba/Weidman-table1.sql'
hashFile = '/Users/azuri/daten/uni/HKU/HASH/PNMain_full_June-30-2020.csv'
csvHash = csvFree.readCSVFile(hashFile)
simbaFile = '/Users/azuri/daten/uni/HKU/interns_projects/simba/All list v1.csv'
#simbaFile = '/Users/azuri/daten/uni/HKU/interns_projects/simba/simba_table.csv'
csvSimba = csvFree.readCSVFile(simbaFile)
with open(f2name, encoding="utf8", errors='ignore') as f:
lines = f.readlines()
csv2 = csvData.CSVData()
csv2.header = [
'PNG', 'log g', 'ref log g', 'met', 'log T', 'ref log T',
'log (L_star/L_sun)', 'ref log(L_star/L_sun', 'mag', 'ref mag'
]
for iLine in np.arange(1, len(lines), 1):
data = []
lines[iLine] = lines[iLine].replace('\r', '')
lines[iLine] = lines[iLine].replace('\n', '')
lines[iLine] = lines[iLine].replace('}', '+-')
lines[iLine] = lines[iLine].replace(' v ', ' v')
lines[iLine] = lines[iLine].replace(' r ', ' r')
lines[iLine] = lines[iLine].replace(' b ', ' b')
lines[iLine] = lines[iLine].replace(' i ', ' i')
data = lines[iLine].split(' ')
if len(data) < len(csv2.header):
csvA = csvFree.readCSVFile(
'/Users/azuri/daten/uni/HKU/HASH/ziggy_Calern_PN_candidates_May2019.csv')
csvA.append(
csvFree.readCSVFile(
'/Users/azuri/daten/uni/HKU/HASH/ziggy_Calern_PN_candidates_May2019_II.csv'
))
csvA.append(
csvFree.readCSVFile(
'/Users/azuri/daten/uni/HKU/HASH/ziggy_Calern_PN_candidates_May2019_III.csv'
))
sorted = np.sort(
csvFree.convertStringVectorToUnsignedVector(csvA.getData('idPNMain')))
print('sorted = ', sorted)
fNameOut = '/Users/azuri/daten/uni/HKU/HASH/ziggy_Calern_PN_candidates_May2019_out.csv'
csvOut = csvData.CSVData()
csvOut.header = csvA.header
for i in np.arange(0, len(sorted), 1):
found = csvA.find('idPNMain', str(sorted[i]))
print('i = ', i, ': found = ', found)
csvOut.append(csvA.getData(found))
print('csvOut.size() = ', csvOut.size())
csvFree.writeCSVFile(csvOut, fNameOut)
import csvFree,csvData
csv = csvData.CSVData()
csv.header = ['fiber', 'centerDistanceX', 'centerDistanceY', 'Halpha6563a', 'Halpha6563b', 'OIII5007a', 'OIII5007b', 'SII6716a', 'SII6731a', 'SII6716b', 'SII6731b', 'ArIII7136']
tab = [
#{'fiber': 1135, 'centerDistanceX' : -85.12, 'centerDistanceY' : -85.12, 'SII6716a': 0.0, 'SII6731a' : 0.0, 'SII6716b' : 6724.81, 'SII6731b' : 6737.28, 'unidentified1' : 0.0, 'ArIII7136' : 0.0, 'unidentified2' : 0.0},
{'fiber': 1, 'centerDistanceX' : 9.85, 'centerDistanceY' : 0.0, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6696.62, 18289.,20.9], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6754.51, 10737., 23.6], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 2, 'centerDistanceX' : -29.56, 'centerDistanceY' : 61.92, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6713.3,7149.0,5.672], 'SII6731a' : [6726.07,7619.0,7.832], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 3, 'centerDistanceX' : 34.49, 'centerDistanceY' : 25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [6730.48,3930.0,5.12], 'SII6731b' : [6745.08,6399.0,6.95], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 4, 'centerDistanceX' : 24.64, 'centerDistanceY' : 8.44, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6703.77,4931.0,8.954], 'SII6731a' : [6721.79,9516.0,13.13], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 5, 'centerDistanceX' : 29.56, 'centerDistanceY' : 16.89, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6716.82,2505.0,4.993], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6746.48,12718.0,21.9], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 6, 'centerDistanceX' : 29.56, 'centerDistanceY' : 33.77, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6702.26,76862.0,9.071], 'SII6731a' : [6717.98,7442.0,9.852], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 7, 'centerDistanceX' : 24.64, 'centerDistanceY' : 25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6693.59,5645.0,13.32], 'SII6731a' : [6711.32,8018.0,15.05], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 8, 'centerDistanceX' : 29.56, 'centerDistanceY' : 0.0, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6700.25,4676.0,11.78], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 9, 'centerDistanceX' : 34.49, 'centerDistanceY' : 8.44, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 10, 'centerDistanceX' : 34.49, 'centerDistanceY' : -25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [6726.09,6722.0,11.31], 'SII6731b' : [6743.01,10599.0,14.66], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 11, 'centerDistanceX' : 24.64, 'centerDistanceY' : -25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6698.94,6805.0,8.99], 'SII6731a' : [6714.9,3550.0,4.009], 'SII6716b' : [6730.94,4552.0,7.866], 'SII6731b' : [6743.89,8403.0,13.03], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 12, 'centerDistanceX' : 29.56, 'centerDistanceY' : -33.77, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6704.1,4780.0,7.665], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6745.27,7437.0,10.23], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 13, 'centerDistanceX' : 34.49, 'centerDistanceY' : -8.44, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [6727.22,4436.0,10.62], 'SII6731b' : [6747.52,4568.0,6.754], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 14, 'centerDistanceX' : 29.56, 'centerDistanceY' : -16.89, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [6739.42,6693.0,6.918], 'SII6731b' : [6753.71,4630.0,5.577], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 15, 'centerDistanceX' : 24.64, 'centerDistanceY' : -8.44, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6696.13,3748.0,5.126], 'SII6731a' : [6708.96,4156.0,10.11], 'SII6716b' : [6730.28,4694.0,6.399], 'SII6731b' : [6744.81,7185.0,8.379], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 16, 'centerDistanceX' : 0.0, 'centerDistanceY' : 61.92, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [0.0,0.0,0.0], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6746.04,5866.0,8.922], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 17, 'centerDistanceX' : 19.71, 'centerDistanceY' : 33.77, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6702.74,4785.0,7.129], 'SII6731a' : [6722.02,10062.0,14.37], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6744.92,3591.0,5.948], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 18, 'centerDistanceX' : 4.93, 'centerDistanceY' : 25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [4988.85,20479.0,2.921], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6695.67,9157.0,7.79], 'SII6731a' : [6708.06,8492.0,8.629], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 19, 'centerDistanceX' : 9.85, 'centerDistanceY' : 33.77, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6701.8,3261.0,3.222], 'SII6731a' : [6714.96,6414.0,10.71], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 20, 'centerDistanceX' : 14.78, 'centerDistanceY' : 25.33, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6703.34,4708.0,6.392], 'SII6731a' : [6717.12,6281.0,7.234], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 21, 'centerDistanceX' : 9.85, 'centerDistanceY' : 16.89, 'Halpha6563a': [6538.0,5087.0,2.931], 'Halpha6563b': [6581.12,4449.0,3.129], 'OIII5007a': [4990.98,27483.0,3.864], 'OIII5007b': [5020.9,15711.0,2.96], 'SII6716a': [6696.75,17792.0,6.442], 'SII6731a' : [6711.58,14306.0,7.242], 'SII6716b' : [6734.78,5993.0,7.468], 'SII6731b' : [6751.43,4412.0,8.583], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 22, 'centerDistanceX' : 29.56, 'centerDistanceY' : 61.92, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6713.41,2359.0,3.665], 'SII6731a' : [6725.49,7284.0,7.063], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [6744.61,3890.0,6.373], 'ArIII7136' : [0.0,0.0,0.0]},
{'fiber': 23, 'centerDistanceX' : 14.78, 'centerDistanceY' : 8.44, 'Halpha6563a': [0.0,0.0,0.0], 'Halpha6563b': [0.0,0.0,0.0], 'OIII5007a': [0.0,0.0,0.0], 'OIII5007b': [0.0,0.0,0.0], 'SII6716a': [6706.16,4161.0,7.101], 'SII6731a' : [0.0,0.0,0.0], 'SII6716b' : [0.0,0.0,0.0], 'SII6731b' : [0.0,0.0,0.0], 'ArIII7136' : [0.0,0.0,0.0]},
import numpy as np
import os
import csvFree, csvData
imageDirList = '/Users/azuri/daten/uni/HKU/HASH/%s_images.txt'
hashPNMain = '/Users/azuri/daten/uni/HKU/HASH/PNMain_full.csv'
commandFileOut = '/Users/azuri/daten/uni/HKU/HASH/addSurveyImages'
if os.path.exists(commandFileOut):
os.remove(commandFileOut)
surveyCSV = csvData.CSVData()
surveyCSV.header = ['Name', 'lMin', 'lMax', 'bMin', 'bMax']
surveyCSV.append(['IPHAS', '29.', '215.', '-5.', '5.'])
surveyCSV.append(['VVV', '350.', '360.', '-14.5', '9.5'])
surveyCSV.append(['VVV', '0.', '10.', '-14.5', '9.5'])
surveyCSV.append(['VVV', '230.', '350.', '-4.5', '4.5'])
surveyCSV.append(['VVV', '10.', '20.', '-4.5', '4.5'])
if __name__ == '__main__':
for iSurvey in range(surveyCSV.size()):
with open(imageDirList % surveyCSV.getData('Name', iSurvey).lower(),
'r') as f:
imDirLines = f.readlines()
idsWithoutSurveyImages = []
freshIDFound = False
idPNMain = 0
idsStr = ''
for line in imDirLines:
def plotHistogram():
csvSG = csvData.CSVData()
csvSG.header = ['PNG', 'Name', 'DRA', 'DDec', 'flag']
with open(inputSGFile, 'r') as f:
linesSG = f.readlines()
for iLine in range(len(linesSG)):
linesSG[iLine] = linesSG[iLine].strip().split()
print('linesSG[', iLine, '] = ', linesSG[iLine])
csvSG.append([
linesSG[iLine][1][1:], linesSG[iLine][2], linesSG[iLine][5],
linesSG[iLine][6], linesSG[iLine][4]
])
csvPNMain = csvFree.readCSVFile(inputHashPNMainFile)
csvHash = fixHashFile()
csvHash.addColumn('PNG')
for iRow in range(csvHash.size()):
csvHash.setData(
'PNG', iRow,
csvPNMain.getData(
'PNG',
csvPNMain.find('idPNMain', csvHash.getData('idPNMain',
iRow))[0]))
print('csvSG.size() = ', csvSG.size(), ', csvHash.size() = ',
csvHash.size(), ', csvPNMain.size() = ', csvPNMain.size())
print('csvPNMain.header = ', csvPNMain.header)
distances = []
print('csvSG.header = ', csvSG.header)
for i in range(csvHash.size()):
if csvHash.getData('InUse', i) == '1':
posSG = csvSG.find('PNG', csvHash.getData('PNG', i))
print('i = ', i, ': posSG = ', posSG)
if len(posSG) > 1:
print('Problem: len(posSG) = ', len(posSG), ' > 1')
STOP
if posSG[0] >= 0:
print("csvHash.getData('CS_DRAJ2000',", i, ") = ",
csvHash.getData('CS_DRAJ2000', i))
print("csvHash.getData('CS_DDECJ2000',", i, ") = ",
csvHash.getData('CS_DDECJ2000', i))
print("csvSG.getData('DRA',", posSG[0], ") = ",
csvSG.getData('DRA', posSG[0]))
print("csvSG.getData('DDec',", posSG[0], ") = ",
csvSG.getData('DDec', posSG[0]))
distances.append([
angularDistancePyAsl(
float(csvHash.getData('CS_DRAJ2000', i)),
float(csvHash.getData('CS_DDECJ2000', i)),
float(csvSG.getData('DRA', posSG[0])),
float(csvSG.getData('DDec', posSG[0]))) * 3600.,
csvHash.getData('idPNMain', i),
csvDiam.getData(
'MajDiam',
csvDiam.find('idPNMain',
csvHash.getData('idPNMain', i))[0]),
csvHash.getData('refCSstat', i),
float(csvSG.getData('DRA', posSG[0])),
float(csvSG.getData('DDec', posSG[0])),
float(csvHash.getData('CS_DRAJ2000', i)),
float(csvHash.getData('CS_DDECJ2000', i)),
])
if distances[len(distances) - 1][0] > 5:
print('distances[',
len(distances) - 1, '] = ',
distances[len(distances) - 1])
distances = np.array(distances)
print('distances = ', len(distances), ': ', distances)
# print('[d[0] for d in distances] = ',[d[0] for d in distances])
# print('np.array( [float(d[0]) for d in distances])>5. = ',np.array( [float(d[0]) for d in distances])>5.)
largeDistances = distances[np.array([float(d[0]) for d in distances]) > 5.]
print('largeDistances = ', len(largeDistances), ': ', largeDistances)
histVals = plt.hist(np.sort(
np.array([float(distance[0]) for distance in distances])),
bins=40,
range=[0., 40.])
print('histVals = ', histVals)
plt.xlabel('distance in "')
plt.ylabel('number of CSPN')
plt.show()
return csvHash, csvSG