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1##################### generated by xml-casa (v2) from imdev.xml ##################### 

2##################### 5c1128ffa9091f060432190f8202f67f ############################## 

3from __future__ import absolute_import 

4import numpy 

5from casatools.typecheck import CasaValidator as _val_ctor 

6_pc = _val_ctor( ) 

7from casatools.coercetype import coerce as _coerce 

8from casatools.errors import create_error_string 

9from .private.task_imdev import imdev as _imdev_t 

10from casatasks.private.task_logging import start_log as _start_log 

11from casatasks.private.task_logging import end_log as _end_log 

12from casatasks.private.task_logging import except_log as _except_log 

13 

14class _imdev: 

15 """ 

16 imdev ---- Create an image that can represent the statistical deviations of the input image. 

17 

18 --------- parameter descriptions --------------------------------------------- 

19 

20 imagename Input image name 

21 outfile Output image file name. If left blank (the default), no image is written but a new image tool referencing the collapsed image is returned. 

22 region Region selection. Default is to use the full image. 

23 box Rectangular region(s) to select in direction plane. Default is to use the entire direction plane. 

24 chans Channels to use. Default is to use all channels. 

25 stokes Stokes planes to use. Default is to use all Stokes planes. 

26 mask Mask to use. Default setting is none. 

27 overwrite Overwrite (unprompted) pre-existing output file? Ignored if "outfile" is left blank. 

28 stretch Stretch the mask if necessary and possible? Default value is False. 

29 grid x,y grid spacing. Array of exactly two positive integers. 

30 anchor x,y anchor pixel location. Either "ref" to use the image reference pixel, or an array of exactly two integers. 

31 xlength Either x coordinate length of box, or diameter of circle. Circle is used if ylength is empty string. 

32 ylength y coordinate length of box. Use a circle if ylength is empty string. 

33 interp Interpolation algorithm to use. One of "nearest", "linear", or "cubic". Minimum match supported. 

34 stattype Statistic to compute. See full description for supported statistics. 

35 statalg Statistics computation algorithm to use. Supported values are "chauvenet" and "classic", Minimum match is supported. 

36 zscore For chauvenet, this is the target maximum number of standard deviations data may have to be included. If negative, use Chauvenet"s criterion. Ignored if algorithm is not "chauvenet". 

37 maxiter For chauvenet, this is the maximum number of iterations to attempt. Iterating will stop when either this limit is reached, or the zscore criterion is met. If negative, iterate until the zscore criterion is met. Ignored if algortihm is not "chauvenet". 

38 RETURNS bool 

39 

40 --------- examples ----------------------------------------------------------- 

41 

42  

43 This application creates an image that reflects the statistics of the input image. The output image has 

44 the same dimensions and coordinate system as the (selected region in) input image. The grid parameter 

45 describes how many pixels apart "grid" pixels are. Statistics are computed around each grid pixel. Grid 

46 pixels are limited to the direction plane only; independent statistics are computed for each direction plane 

47 (ie at each frequency/stokes pixel should the input image happen to have such additional axes). Using the 

48 xlength and ylength parameters, one may specify either a rectangular or circular region around each grid 

49 point that defines which surrounding pixels are used in the statistic computation for individual grid points. 

50 If the ylength parameter is the empty string, then a circle of diameter provided by xlength centered on 

51 the grid point is used. If ylength is not empty, then a rectangular box of dimensions xlength x ylength centered 

52 on the grid pixel is used. These two parameters may be specified in pixels, using either numerical values or 

53 valid quantities with "pix" as the unit (eg "4pix"). Otherwise, they must be specified as valid angular 

54 quantities, with recognized units (eg "4arcsec"). As with other region selections in CASA, full pixels are 

55 included in the computation even if the specified region includes only a fraction of that pixel. BEWARE OF 

56 MACHINE PRECISION ISSUES, because you may get a smaller number of pixels included in a region than you 

57 expect if you specify, eg, an integer number of pixels. In such cases, you probably want to specify that 

58 number plus a small epsilon value (eg "2.0001pix" rather than "2pix") to mitigate machine precision issues 

59 when computing region extents. 

60  

61 The output image is formed by putting the statistics calculated at each grid point at the corresponding 

62 grid point in the output image. Interpolation of these output values is then used to compute values at 

63 non-grid-point pixels. The user may specify which interpolation algorithm to use for this computation 

64 using the interp parameter. 

65  

66 The input image pixel mask is copied to the output image. If interpolation is performed, output pixels are 

67 masked where the interpolation fails. 

68  

69 ANCHORING THE GRID 

70  

71 The user may choose at which pixel to "anchor" the grid. For example, if one specifies grid=[4,4] and 

72 anchor=[0,0], grid points will be located at pixels [0,0], [0,4], [0,8] ... [4,0], [4,4], etc. This 

73 is exactly the same grid that would be produced if the user specified anchor=[4,4] or anchor=[20,44]. 

74 If the user specifies anchor=[1, 2] and grid=[4,4], then the grid points will be at pixels [1,2], [5,2], 

75 [9,2]... [5,2], [5,6], etc. and the resulting grid is the same as it would be if the user specified eg 

76 anchor=[9,10] or anchor=[21, 18]. The value "ref", which is the default, indicates that the reference 

77 pixel of the input image should be used to anchor the grid. The x and y values of this pixel will be 

78 rounded to the nearest integer if necessary. 

79  

80 SUPPORTED STATISTICS AND STATISTICS ALGORITHMS 

81  

82 One may specify which statistic should be represented using the stattype parameter. The following values 

83 are recognized (minimum match supported): 

84  

85 iqr inner quartile range (q3 - q1) 

86 max maximum 

87 mean mean 

88 medabsdevmed, madm median absolute deviation from the median 

89 median median 

90 min minimum 

91 npts number of points 

92 q1 first quartile 

93 q3 third quartile 

94 rms rms 

95 sigma, std standard deviation 

96 sumsq sum of squares 

97 sum sum 

98 var variance 

99 xmadm median absolute deviation from the median multipied by x, where x is the reciprocal of Phi^-1(3/4), 

100 where Phi^-1 is the reciprocal of the quantile function. Numerically, x = 1.482602218505602. See, eg, 

101 https://en.wikipedia.org/wiki/Median_absolute_deviation#Relation_to_standard_deviation 

102  

103 Using the statalg parameter, one may also select whether to use the Classical or Chauvenet/ZScore statistics algorithm to 

104 compute the desired statistic (see the help for ia.statistics() or imstat for a full description of these algorithms). 

105  

106 # compute standard deviations in circles of diameter 10arcsec around 

107 # grid pixels spaced every 4 x 5 pixels and anchored at pixel [30, 40], 

108 # and use linear interpolation to compute values at non-grid-pixels 

109 imdev("my.im", "sigma.im", grid=[4, 5], anchor=[30, 40], xlength="10arcsec", stattype="sigma", interp="lin", statalg="cl") 

110  

111 # compute median of the absolute deviations from the median values using 

112 # the z-score/Chauvenet algorithm, by fixing the maximum z-score to determine outliers to 5. 

113 # Use cubic interpolation to compute values for non-grid-point pixels. Use a rectangular region 

114 # of dimensions 5arcsec x 20arcsec centered on each grid point as the region in which to include 

115 # pixels for the computation of stats for that grid point. 

116 imdev("my.im", "madm.im", grid=[4, 5], anchor=[30, 40], xlength="5arcsec", ylength="20arcsec, stattype="madm", interp="cub", statalg="ch", zscore=5) 

117 

118 

119 """ 

120 

121 _info_group_ = """analysis""" 

122 _info_desc_ = """Create an image that can represent the statistical deviations of the input image.""" 

123 

124 def __call__( self, imagename='', outfile='', region='', box='', chans='', stokes='', mask='', overwrite=False, stretch=False, grid=[ int(1),int(1) ], anchor='ref', xlength='1pix', ylength='1pix', interp='cubic', stattype='sigma', statalg='classic', zscore=float(-1), maxiter=int(-1) ): 

125 schema = {'imagename': {'type': 'cReqPath', 'coerce': _coerce.expand_path}, 'outfile': {'type': 'cStr', 'coerce': _coerce.to_str}, 'region': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cDict'}]}, 'box': {'type': 'cStr', 'coerce': _coerce.to_str}, 'chans': {'type': 'cStr', 'coerce': _coerce.to_str}, 'stokes': {'type': 'cStr', 'coerce': _coerce.to_str}, 'mask': {'type': 'cStr', 'coerce': _coerce.to_str}, 'overwrite': {'type': 'cBool'}, 'stretch': {'type': 'cBool'}, 'grid': {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}, 'anchor': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}]}, 'xlength': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cInt'}]}, 'ylength': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cInt'}]}, 'interp': {'type': 'cStr', 'coerce': _coerce.to_str}, 'stattype': {'type': 'cStr', 'coerce': _coerce.to_str}, 'statalg': {'type': 'cStr', 'coerce': _coerce.to_str}, 'zscore': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'maxiter': {'type': 'cInt'}} 

126 doc = {'imagename': imagename, 'outfile': outfile, 'region': region, 'box': box, 'chans': chans, 'stokes': stokes, 'mask': mask, 'overwrite': overwrite, 'stretch': stretch, 'grid': grid, 'anchor': anchor, 'xlength': xlength, 'ylength': ylength, 'interp': interp, 'stattype': stattype, 'statalg': statalg, 'zscore': zscore, 'maxiter': maxiter} 

127 assert _pc.validate(doc,schema), create_error_string(_pc.errors) 

128 _logging_state_ = _start_log( 'imdev', [ 'imagename=' + repr(_pc.document['imagename']), 'outfile=' + repr(_pc.document['outfile']), 'region=' + repr(_pc.document['region']), 'box=' + repr(_pc.document['box']), 'chans=' + repr(_pc.document['chans']), 'stokes=' + repr(_pc.document['stokes']), 'mask=' + repr(_pc.document['mask']), 'overwrite=' + repr(_pc.document['overwrite']), 'stretch=' + repr(_pc.document['stretch']), 'grid=' + repr(_pc.document['grid']), 'anchor=' + repr(_pc.document['anchor']), 'xlength=' + repr(_pc.document['xlength']), 'ylength=' + repr(_pc.document['ylength']), 'interp=' + repr(_pc.document['interp']), 'stattype=' + repr(_pc.document['stattype']), 'statalg=' + repr(_pc.document['statalg']), 'zscore=' + repr(_pc.document['zscore']), 'maxiter=' + repr(_pc.document['maxiter']) ] ) 

129 task_result = None 

130 try: 

131 task_result = _imdev_t( _pc.document['imagename'], _pc.document['outfile'], _pc.document['region'], _pc.document['box'], _pc.document['chans'], _pc.document['stokes'], _pc.document['mask'], _pc.document['overwrite'], _pc.document['stretch'], _pc.document['grid'], _pc.document['anchor'], _pc.document['xlength'], _pc.document['ylength'], _pc.document['interp'], _pc.document['stattype'], _pc.document['statalg'], _pc.document['zscore'], _pc.document['maxiter'] ) 

132 except Exception as exc: 

133 _except_log('imdev', exc) 

134 raise 

135 finally: 

136 task_result = _end_log( _logging_state_, 'imdev', task_result ) 

137 return task_result 

138 

139imdev = _imdev( ) 

140