fitsfile = 'leop.fluxRescale.16arcsec.vel.bin5arcsec.fits' if lappy: fitsDir = '/home/elijah/research/leop/data/vla.gmrt/fitsImages/' if cosmos: fitsDir = '/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' f = pf.open(fitsDir + fitsfile) header, cube = f[0].header, f[0].data # Create subsection of cube #subCube = cube[:,400:600,400:600] #subCube = cube[:,450:550,450:550] subCube = cube # Define characteristics of cube std = noiseCube.std() # standard deviation of cube without rescaling velocities = make_velocityAxis(header) # writes velocities in km/s velWidth = header['CDELT3'] / 1000. beamsize = 16 # arcsec cellsize = 6. # arcsec / pix raSize = len(subCube[0, :]) decSize = len(subCube[0, 0, :]) size = raSize * decSize count = 0 # Set threshold threshold = 5 # if max value of profile is above threshold*std then fit # Perform monte carlo simulationNum = 1000 simMeans = np.zeros(simulationNum) simMedians = np.zeros(simulationNum)
from mycoords import make_velocityAxis from agpy.gaussfitter import multigaussfit as gfit import gaussFitting import os # Define paths: fitsDir = '/d/bip3/ezbc/leop/data/hi/models/modelCreationFolder5/models/' writeDir = '/d/bip3/ezbc/leop/data/hi/models/data/' psDir = '/d/bip3/ezbc/leop/figures/' # Open data cube with flux scaling f = pf.open('/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' + \ 'leop.fluxRescale.16arcsec.vel.modelBin.fits') h, d = f[0].header, f[0].data[:, :, :] velArray = make_velocityAxis(h) # Compute the final noise from data cube without flux scaling def get_rms(x, axis=None): return np.sqrt(np.mean(x**2, axis=axis)) fnoise = pf.open('/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' +\ 'originalCubes/leop.16arcsec.fits') hnoise, dnoise = fnoise[0].header, fnoise[0].data[:, :, :] rms = get_rms(dnoise) std = dnoise.std() threshold = 3. * rms # Define number of models being used: models = [name for name in os.listdir(fitsDir) if name.endswith('.FITS')]
fitsfile = 'leop.fluxRescale.16arcsec.vel.bin5arcsec.fits' if lappy: fitsDir = '/home/elijah/research/leop/data/vla.gmrt/fitsImages/' if cosmos: fitsDir = '/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' f = pf.open(fitsDir + fitsfile) header, cube = f[0].header, f[0].data # Create subsection of cube #subCube = cube[:,400:600,400:600] #subCube = cube[:,450:550,450:550] subCube = cube # Define characteristics of cube std = noiseCube.std() # standard deviation of cube without rescaling velocities = make_velocityAxis(header) # writes velocities in km/s velWidth = header['CDELT3']/1000. beamsize = 16 # arcsec cellsize = 6. # arcsec / pix raSize = len(subCube[0,:]) decSize = len(subCube[0,0,:]) size = raSize * decSize count = 0 # Set threshold threshold = 5 # if max value of profile is above threshold*std then fit # Perform monte carlo simulationNum = 1000 simMeans = np.zeros(simulationNum) simMedians = np.zeros(simulationNum)
from mycoords import make_velocityAxis from agpy.gaussfitter import multigaussfit as gfit import gaussFitting import os # Define paths: fitsDir = '/d/bip3/ezbc/leop/data/hi/models/modelCreationFolder5/models/' writeDir = '/d/bip3/ezbc/leop/data/hi/models/data/' psDir = '/d/bip3/ezbc/leop/figures/' # Open data cube with flux scaling f = pf.open('/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' + \ 'leop.fluxRescale.16arcsec.vel.modelBin.fits') h, d = f[0].header, f[0].data[:,:,:] velArray = make_velocityAxis(h) # Compute the final noise from data cube without flux scaling def get_rms(x, axis=None): return np.sqrt(np.mean(x**2, axis=axis)) fnoise = pf.open('/d/bip3/ezbc/leop/data/hi/casa/fitsImages/fluxRescale/' +\ 'originalCubes/leop.16arcsec.fits') hnoise,dnoise = fnoise[0].header, fnoise[0].data[:,:,:] rms = get_rms(dnoise) std = dnoise.std() threshold = 3. * rms # Define number of models being used: models = [name for name in os.listdir(fitsDir) if name.endswith('.FITS')] modelNum = len(models)