def test_fsf_model(tmpdir):
cubename = get_data_file('sdetect', 'subcub_mosaic.fits')
cube = Cube(cubename)
# Read FSF model with the old method
with pytest.warns(MpdafWarning):
PSF, fwhm_pix, fwhm_arcsec = get_FSF_from_cube_keywords(cube, 13)
# Read FSF model from file
fsf = FSFModel.read(cubename)
assert len(fsf) == 9
assert fsf[0].model == 2
assert_allclose(fsf[0].get_fwhm(cube.wave.coord()), fwhm_arcsec[0])
# Read FSF model from cube
fsf = FSFModel.read(cube)
assert len(fsf) == 9
assert fsf[0].model == 2
assert_allclose(fsf[0].get_fwhm(cube.wave.coord()), fwhm_arcsec[0])
# Read FSF model from header and for a specific field
hdr = cube.primary_header.copy()
hdr.update(cube.data_header)
fsf = FSFModel.read(hdr, field=2)
assert fsf.model == 2
assert_allclose(fsf.get_fwhm(cube.wave.coord()), fwhm_arcsec[1])
# test to_header
assert [str(x).strip() for x in fsf.to_header().cards] == [
'FSFMODE = 2 / Circular MOFFAT beta=poly(lbda) fwhm=poly(lbda)',
'FSFLB1 = 5000 / FSF Blue Ref Wave (A)',
'FSFLB2 = 9000 / FSF Red Ref Wave (A)',
'FSF00FNC= 2 / FSF00 FWHM Poly Ncoef',
'FSF00F00= -0.1204 / FSF00 FWHM Poly C00',
'FSF00F01= 0.6143 / FSF00 FWHM Poly C01',
'FSF00BNC= 1 / FSF00 BETA Poly Ncoef',
'FSF00B00= 2.8 / FSF00 BETA Poly C00'
]
testfile = str(tmpdir.join('test.fits'))
outcube = cube.copy()
fsf.to_header(hdr=outcube.primary_header)
outcube.write(testfile)
fsf3 = FSFModel.read(testfile, field=0)
assert fsf3.model == 2
assert fsf3.get_beta(7000) == fsf.get_beta(7000)
assert fsf3.get_fwhm(7000) == fsf.get_fwhm(7000)
assert fsf3.get_fwhm(7000, unit='pix') == fsf.get_fwhm(7000, unit='pix')
def remove_bg(cube_in,mask,cube_out,invert=False):
""" Corrects background of a cube to zero (per wavelengh plane)
Strong emission (e.g. cluster members) should be masked.
Parameters:
----------
cube_in: string
path to input cube to be corrected
mask: string
path to mask to be used. Image with 1 for masked regions (objects)
and 0 for regions to be used to calculate the meadian background (sky)'
cube_out: string
path to the output (corrected) cube
invert: boolean
if True, 0 for masked regions (objects) and 1 for sky (old ZAP version)
Returns:
----------
mpdaf.obj.Cube
corrected cube
"""
c=Cube(cube_in)
immask = Image(mask)
c2=c.copy()
mask = immask.data.astype(bool)
if invert:
mask = np.invert(mask)
c.data.mask[:, mask] = True
tstart = time.time()
for k in range(c.shape[0]):
posmin=max(k-25,0)
posmax=min(c.shape[0],k+25)
for p in range(c.shape[1]):
med=np.ma.median(c.data[posmin:posmax,p,:])
c2.data.data[k,p,:]-=med
for q in range(c.shape[2]):
med=np.ma.median(c.data[posmin:posmax,:,q])
c2.data.data[k,:,q]-=med
tend = time.time()
print('ellapsed time %s'%(tend-tstart))
## Update Header
c2.primary_header.add_comment('This cube has been median subtracted')
c2.write(cube_out)
return c2
def masked_cube(inp, mask, value=0., method='value'):
"""Returns a masked version of the input cube
inp : str or Cube
Input filename or Cube object
mask : boolean np.array 2D of same shape (ny, nx) than cube spatial
Pixels to mask
value : float
Values to replaces masked spaxels
if method = 'value'
method : str
Method to perform the masking
value : replaces by the given value
madian : replaces by the median of all contiguous pixels including the value of the pixel itself
"""
if not isinstance(inp, Cube): # assume str
cube = Cube(inp)
else:
cube = inp
newcube = cube.copy()
nw, ny, nx = cube.shape
for ii in range(nw):
image = cube.data[ii, :, :]
if method == 'value':
aux = np.where(mask, value, image)
elif method == 'median':
inds_y, inds_x = np.where(mask)
aux = image.data
for yx in zip(inds_y, inds_x):
# import pdb;pdb.set_trace()
median = np.median(image[yx[0] - 1:yx[0] + 1,
yx[1] - 1:yx[1] + 1])
aux[yx[0], yx[1]] = median
newcube[ii, :, :] = aux
# import pdb;pdb.set_trace()
return newcube
def masked_cube(inp, mask, value=0., method='value'):
"""Returns a masked version of the input cube
inp : str or Cube
Input filename or Cube object
mask : boolean np.array 2D of same shape (ny, nx) than cube spatial
Pixels to mask
value : float
Values to replaces masked spaxels
if method = 'value'
method : str
Method to perform the masking
value : replaces by the given value
madian : replaces by the median of all contiguous pixels including the value of the pixel itself
"""
if not isinstance(inp, Cube): # assume str
cube = Cube(inp)
else:
cube = inp
newcube = cube.copy()
nw, ny, nx = cube.shape
for ii in range(nw):
image = cube.data[ii,:,:]
if method == 'value':
aux = np.where(mask, value, image)
elif method == 'median':
inds_y, inds_x = np.where(mask)
aux = image.data
for yx in zip(inds_y,inds_x):
# import pdb;pdb.set_trace()
median = np.median(image[yx[0]-1:yx[0]+1, yx[1]-1:yx[1]+1])
aux[yx[0],yx[1]] = median
newcube[ii,:,:] = aux
# import pdb;pdb.set_trace()
return newcube
