def getMeanDarkFrame(self):
if type(self.darksPath) == str and self.darksPath == "":
return np.zeros_like(pyfits.getdata(self.imagesPaths[0]))
else:
# Else it will be a list of strings
return systematics.meanDarkFrame(self.darksPath)
import dataBank
import systematics
import IO
import pyfits
from matplotlib import pyplot as plt
plt.ion() ## Turn on interactive plots
data = dataBank.dataBank(
) #imagesPath,darksPath,flatPath,regsPath,ingress,egress) ## initalize databank for data storage
allStars = data.getDict() ## Store initialized dictionary
outputPath = data.outputPath
N_exposures = len(data.getPaths())
## Prepare systematic corrections: dark frame, flat field
meanDarkFrame = systematics.meanDarkFrame(data.darksPath)
masterFlat = data.masterFlat
## Tell oscaar what figure settings to use
plottingThings, statusBarFig, statusBarAx = IO.plottingSettings(
data.trackPlots, data.photPlots)
## Main loop: iterate through each exposures
for expNumber in range(0, N_exposures):
if statusBarAx != None and expNumber % 15 == 0:
'''Prepare some plotting settings here'''
plt.cla()
statusBarAx.set_title('oscaar2.0 is running...')
statusBarAx.set_xlim([0, 100])
statusBarAx.set_xlabel('Percent Complete (%)')
def getMeanDarkFrame(self):
if type(self.darksPath) == str and self.darksPath == "":
return np.zeros_like(pyfits.getdata(self.imagesPaths[0]))
else:
# Else it will be a list of strings
return systematics.meanDarkFrame(self.darksPath)
import systematics
import IO
import pyfits
# Turn on interactive plots
plt.ion()
# initalize databank for data storage
data = dataBank.dataBank()
# Store initialized dictionary
allStars = data.getDict()
outputPath = data.outputPath
N_exposures = len(data.getPaths())
# Prepare systematic corrections: dark frame, flat field
meanDarkFrame = systematics.meanDarkFrame(data.darksPath)
masterFlat = data.masterFlat
# Tell oscaar what figure settings to use
plottingThings, statusBarFig, statusBarAx = IO.plottingSettings(data.trackPlots, data.photPlots)
# Main loop: iterate through each exposures
for expNumber in xrange(N_exposures):
if statusBarAx is not None and expNumber % 15 == 0:
# Prepare some plotting settings here
plt.cla()
statusBarAx.set_title("oscaar2.0 is running...")
statusBarAx.set_xlim([0, 100])
statusBarAx.set_xlabel("Percent Complete (%)")
statusBarAx.get_yaxis().set_ticks([])
statusBarAx.barh([0], [100.0 * expNumber / len(data.getPaths())], [1], color="k")
