Coverage for metadetect / mfrac.py: 11%

1import ngmix 

2import numpy as np 

3 

4from .defaults import BMASK_EDGE 

5 

6 

7def measure_mfrac( 

8 *, 

9 mfrac, 

10 x, 

11 y, 

12 box_sizes, 

13 obs, 

14 fwhm, 

15): 

16 """Measure a Gaussian-weighted average of an image. 

17 

18 This function is meant to be used with images that represent the fraction 

19 of single-epoch images that are masked in each pixel of a coadd. It 

20 computes a Gaussian-weighted average of the image at a list of locations. 

21 

22 Parameters 

23 ---------- 

24 mfrac : np.ndarray 

25 The input image with which to compute the weighted averages. 

26 x : np.ndarray 

27 The input x/col values for the positions at which to compute the 

28 weighted average. 

29 y : np.ndarray 

30 The input y/row values for the positions at which to compute the 

31 weighted average. 

32 box_sizes : np.ndarray 

33 The size of the stamp to use to measure the weighted average. Should be 

34 big enough to hold 2 * `fwhm`. 

35 obs : ngmix.Observation 

36 An observation that holds the weight maps, WCS Jacobian, etc 

37 corresponding to `mfrac`. 

38 fwhm : float or None 

39 The FWHM of the Gaussian aperture in arcseconds. If None, a default 

40 of 1.2 is used. 

41 

42 Returns 

43 ------- 

44 mfracs : np.ndarray 

45 The weighted averages at each input location. 

46 """ 

47 from .detect import CatalogMEDSifier 

48 

49 if fwhm is None: 

50 fwhm = 1.2 

51 

52 obs = obs.copy() 

53 obs.set_image(mfrac) 

54 

55 gauss_wgt = ngmix.GMixModel( 

56 [0, 0, 0, 0, ngmix.moments.fwhm_to_T(fwhm), 1], 

57 'gauss', 

58 ) 

59 mbobs = ngmix.MultiBandObsList() 

60 obslist = ngmix.ObsList() 

61 mbobs.append(obslist) 

62 obslist.append(obs) 

63 m = CatalogMEDSifier(mbobs, x, y, box_sizes).get_meds(0) 

64 mfracs = [] 

65 for i in range(x.shape[0]): 

66 try: 

67 if box_sizes[i] > 0: 

68 obs = m.get_obs(i, 0) 

69 wgt = obs.weight.copy() 

70 msk = (obs.bmask & BMASK_EDGE) != 0 

71 wgt[msk] = 0 

72 wgt[~msk] = 1 

73 obs.set_weight(wgt) 

74 

75 stats = gauss_wgt.get_weighted_sums( 

76 obs, 

77 fwhm * 2, 

78 ) 

79 # this is the weighted average in the image using the 

80 # Gaussian as the weight. 

81 mfracs.append(stats["sums"][5] / stats["wsum"]) 

82 else: 

83 mfracs.append(1.0) 

84 except ngmix.GMixFatalError: 

85 mfracs.append(1.0) 

86 

87 return np.array(mfracs)