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Python code for calculating non-parametric morphological diagnostics of galaxy images.

License: BSD 3-Clause "New" or "Revised" License

Python 100.00%
astronomy galaxies galaxy-morphology non-parametric

statmorph's People

Contributors

gbrammer avatar larrybradley avatar vrodgom avatar

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Forkers

baraln2014 alizabeverage oxno2 gbrammer larrybradley npirzkal vimarian astro-nova jyshangguan astrojacobli astroyzgu neutrinoceros alexgo42 yue952

statmorph's Issues

source_morphology fails with TypeError 

>>> source_morphs = statmorph.source_morphology(data, segmap, weightmap=np.ones_like(data))

TypeError                                 Traceback (most recent call last)
<ipython-input-10-6e5293b8e978> in <module>
----> 1 source_morphs = statmorph.source_morphology(data, segmap, weightmap=np.ones_like(data))

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in source_morphology(image, segmap, **kwargs)
   2472     sources_morph = []
   2473     for label in segmap.labels:
-> 2474         sources_morph.append(SourceMorphology(image, segmap, label, **kwargs))
   2475         print('Finished processing source %d.\n' % (label))
   2476

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in __init__(self, image, segmap, label, mask, weightmap, gain, psf, cutout_extent, min_cutout_size, n_sigma_outlier, annulus_width, eta, petro_fraction_gini, skybox_size, petro_extent_cas, petro_fraction_cas, boxcar_size_mid, niter_bh_mid, sigma_mid, petro_extent_flux, boxcar_size_shape_asym, sersic_maxiter, segmap_overlap_ratio)
    443
    444         # For simplicity, evaluate all "lazy" properties at once:
--> 445         self._calculate_morphology()
    446
    447         # Check if image is background-subtracted; set flag=1 if not.

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _calculate_morphology(self)
    544         ]
    545         for q in quantities:
--> 546             tmp = self[q]
    547
    548     def _check_segmaps(self):

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in __getitem__(self, key)
    457
    458     def __getitem__(self, key):
--> 459         return getattr(self, key)
    460
    461     def _get_badpixels(self, image):

~/anaconda3/lib/python3.7/site-packages/astropy/utils/decorators.py in __get__(self, obj, owner)
    756                 return val
    757             else:
--> 758                 val = self.fget(obj)
    759                 obj.__dict__[self._key] = val
    760                 return val

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in xc_asymmetry(self)
   1563         relative to the original image.
   1564         """
-> 1565         return self.xmin_stamp + self._asymmetry_center[0]
   1566
   1567     @lazyproperty

~/anaconda3/lib/python3.7/site-packages/astropy/utils/decorators.py in __get__(self, obj, owner)
    756                 return val
    757             else:
--> 758                 val = self.fget(obj)
    759                 obj.__dict__[self._key] = val
    760                 return val

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _asymmetry_center(self)
   1540         center_asym = opt.fmin(self._asymmetry_function, center_0,
   1541                                args=(self._cutout_stamp_maskzeroed, 'cas'),
-> 1542                                xtol=1e-6, disp=0)
   1543
   1544         # Check if flag was activated by _asymmetry_function:

~/anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py in fmin(func, x0, args, xtol, ftol, maxiter, maxfun, full_output, disp, retall, callback, initial_simplex)
    441             'initial_simplex': initial_simplex}
    442
--> 443     res = _minimize_neldermead(func, x0, args, callback=callback, **opts)
    444     if full_output:
    445         retlist = res['x'], res['fun'], res['nit'], res['nfev'], res['status']

~/anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py in _minimize_neldermead(func, x0, args, callback, maxiter, maxfev, disp, return_all, initial_simplex, xatol, fatol, adaptive, **unknown_options)
    584
    585     for k in range(N + 1):
--> 586         fsim[k] = func(sim[k])
    587
    588     ind = numpy.argsort(fsim)

~/anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py in function_wrapper(*wrapper_args)
    325     def function_wrapper(*wrapper_args):
    326         ncalls[0] += 1
--> 327         return function(*(wrapper_args + args))
    328
    329     return ncalls, function_wrapper

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _asymmetry_function(self, center, image, kind)
   1486         # Create aperture for the chosen kind of asymmetry
   1487         if kind == 'cas':
-> 1488             r = self._petro_extent_cas * self._rpetro_circ_centroid
   1489             ap = photutils.CircularAperture(center, r)
   1490         elif kind == 'outer':

~/anaconda3/lib/python3.7/site-packages/astropy/utils/decorators.py in __get__(self, obj, owner)
    756                 return val
    757             else:
--> 758                 val = self.fget(obj)
    759                 obj.__dict__[self._key] = val
    760                 return val

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _rpetro_circ_centroid(self)
   1008         """
   1009         center = np.array([self._xc_stamp, self._yc_stamp])
-> 1010         return self._rpetro_circ_generic(center)
   1011
   1012     @lazyproperty

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _rpetro_circ_generic(self, center)
    978                               AstropyUserWarning)
    979                 self.flag = 1
--> 980             curval = self._petrosian_function_circ(r, center)
    981             if curval == 0:
    982                 warnings.warn('[rpetro_circ] We found rpetro by pure chance!',

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _petrosian_function_circ(self, r, center)
    937         # Force mean fluxes to be positive:
    938         circ_annulus_mean_flux = np.abs(_aperture_mean_nomask(
--> 939             circ_annulus, image, method='exact'))
    940         circ_aperture_mean_flux = np.abs(_aperture_mean_nomask(
    941             circ_aperture, image, method='exact'))

~/anaconda3/lib/python3.7/site-packages/statmorph/statmorph.py in _aperture_mean_nomask(ap, image, **kwargs)
     90         return ap.do_photometry(image, **kwargs)[0][0] / ap.area()
     91     else:
---> 92         return ap.do_photometry(image, **kwargs)[0][0] / ap.area
     93
     94 def _fraction_of_total_function_circ(r, image, center, fraction, total_sum):

TypeError: unsupported operand type(s) for /: 'float' and 'method'

M statistic of 0 triggers a flag

Hello,
I'm using the package to determine morphological parameters of sometimes "single clump" sources. For these sources, the code sets the M statistic to 0 and triggers a flag. This behavior is problematic for inspecting the quality of the other statistics.

How can I use my own Sky_mean value for the image?

Hello, I just want to use this code to calculate the Gini index and M20 for my image. I had got my own PSF, image, sigma maps and others. I obtained the sky mean from my own method, which is obtained via the 3-sigma clip from the cleaned sky image. However, this code use its own method to get the sky_mean. Thus, my results for the sersic index is much off from the Galfit. Is there any place for me to input my own sky mean and sky median?

Cannot import module under Python 3

Under python 3.5.4 I cannot import the statmorph module. I get the following error:

Traceback (most recent call last):
  File "tryCAS.py", line 8, in <module>
    import statmorph
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/statmorph/__init__.py", line 1, in <module>
    from .statmorph import SourceMorphology, source_morphology
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/statmorph/statmorph.py", line 15, in <module>
    import skimage.measure
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/skimage/__init__.py", line 158, in <module>
    from .util.dtype import *
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/skimage/util/__init__.py", line 5, in <module>
    from .apply_parallel import apply_parallel
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/skimage/util/apply_parallel.py", line 8, in <module>
    import dask.array as da
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/dask/array/__init__.py", line 46, in <module>
    from . import random, linalg, ghost, learn, fft
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/dask/array/ghost.py", line 8, in <module>
    from toolz.curried import map
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/toolz/curried/__init__.py", line 53, in <module>
    _curry_namespace(vars(toolz)),
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/toolz/curried/__init__.py", line 48, in _curry_namespace
    for name, f in ns.items() if '__' not in name
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/toolz/curried/__init__.py", line 48, in <genexpr>
    for name, f in ns.items() if '__' not in name
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/toolz/curried/__init__.py", line 42, in _should_curry
    return (callable(f) and _nargs(f) > 1 or f in do_curry)
  File "/Users/tdavis/anaconda/lib/python3.5/site-packages/toolz/curried/__init__.py", line 35, in _nargs
    return len(inspect.getargspec(f).args)
  File "/Users/tdavis/anaconda/lib/python3.5/inspect.py", line 1050, in getargspec
    raise ValueError("Function has keyword-only arguments or annotations"
ValueError: Function has keyword-only arguments or annotations, use getfullargspec() API which can support them

It seems to work ok on old Python 2.7 (assuming I remove the print brackets from the example, which seems to be in Python 3...)

Many thanks!

Offset of center for the fitted Sersic profile

Hello, I tired to run your turtorial code and reproduce the results. I found that there is an offset between the original image and fitted image, as the image shows below.
download
If I applied the code below, just moved the center. Then it would looks better.

morph.sersic_xc = morph.sersic_xc - 0.5
morph.sersic_yc = morph.sersic_yc - 0.5

d2

My system environment is Anaconda 3.7.1

centroid coordinates do not take segmask, or noise, into account

Values computed for the first moments/centroids seem wrong in some circumstances and the centroid can some times be well outside of the segmap. It might be a bug in skimage as the following _cutout_stamp_maskzeroed_no_bg leads to a centroid of 0.2, 3.07.

[[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
-0.07184662 0.01405155 0. 0.0648425 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0.07072073 0.18174913 0.08616358 -0.14542499 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0.31161529 0.0283908 -0.03631837 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0.09580147 -0.14492505 -0.01777303 -0.12393956 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. -0.16527912 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]
[ 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0. ]]

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