def crear_archivos(temporary_path, number=5):
from megaradrp.simulation.actions import simulate_flat
from megaradrp.simulation.detector import ReadParams, MegaraDetectorSat
from megaradrp.recipes.calibration.bpm import BadPixelsMaskRecipe
PSCAN = 50
DSHAPE = (2056 * 2, 2048 * 2)
OSCAN = 50
ron = 2.0
gain = 1.0
bias = 1000.0
qe = 0.8 * np.ones(DSHAPE)
qe[0:15, 0:170] = 0.0
readpars1 = ReadParams(gain=gain, ron=ron, bias=bias)
readpars2 = ReadParams(gain=gain, ron=ron, bias=bias)
detector = MegaraDetectorSat('megara_test_detector', DSHAPE, OSCAN, PSCAN,
qe=qe,
dark=(3.0 / 3600.0),
readpars1=readpars1, readpars2=readpars2,
bins='11')
source2 = 1.0
fs = [simulate_flat(detector, exposure=1.0, source=5000 * source2) for i in
range(number)]
for aux in range(len(fs)):
fits.writeto('%s/flat_%s.fits' % (temporary_path, aux), fs[aux],
clobber=True)
master_bias = generate_bias(detector, number, temporary_path)
master_bias_data = master_bias.master_bias.frame[0].data
fits.writeto('%s/master_bias_data0.fits' % temporary_path,
master_bias_data, clobber=True) # Master Bias
ob = ObservationResult()
ob.instrument = 'MEGARA'
ob.mode = 'bias_image'
ob.configuration = build_instrument_config('4fd05b24-2ed9-457b-b563-a3c618bb1d4c', loader=Loader())
names = []
for aux in range(number):
names.append('%s/flat_%s.fits' % (temporary_path, aux))
ob.frames = [DataFrame(filename=open(nombre).name) for nombre in names]
recipe = BadPixelsMaskRecipe()
ri = recipe.create_input(obresult=ob, master_bias=DataFrame(
filename=open(temporary_path + '/master_bias_data0.fits').name))
aux = recipe.run(ri)
fits.writeto('%s/master_bpm.fits' % temporary_path,
aux.master_bpm.frame[0].data, clobber=True)
return names
def generate_bias(detector, number, temporary_path):
from megaradrp.simulation.actions import simulate_bias
from megaradrp.recipes.calibration.bias import BiasRecipe
fs = [simulate_bias(detector) for i in range(number)]
for aux in range(len(fs)):
fits.writeto('%s/bias_%s.fits' % (temporary_path, aux), fs[aux],
clobber=True)
fs = ["%s/bias_%s.fits" % (temporary_path, i) for i in range(number)]
ob = ObservationResult()
ob.instrument = 'MEGARA'
ob.mode = 'bias_image'
ob.configuration = build_instrument_config('4fd05b24-2ed9-457b-b563-a3c618bb1d4c', loader=Loader())
ob.frames = [DataFrame(filename=f) for f in fs]
recipe = BiasRecipe()
ri = recipe.create_input(obresult=ob)
return recipe.run(ri)
def test_bpm_corrector():
import shutil
from tempfile import mkdtemp
directorio = mkdtemp()
names = crear_archivos(directorio, number=4)
ob = ObservationResult()
ob.instrument = 'MEGARA'
ob.mode = 'bias_image'
ob.configuration = build_instrument_config('4fd05b24-2ed9-457b-b563-a3c618bb1d4c', loader=Loader())
ob.frames = [DataFrame(filename=open(nombre).name) for nombre in names]
recipe = TestRecipe(directorio)
ri = recipe.create_input(obresult=ob, master_bias=DataFrame(
filename=open(directorio + '/master_bias_data0.fits').name),
master_bpm=DataFrame(filename=open(
directorio + '/master_bpm.fits').name))
recipe.run(ri)
shutil.rmtree(directorio)
