Coverage for /wheeldirectory/casa-6.7.0-12-py3.10.el8/lib/py/lib/python3.10/site-packages/casatasks/imstat.py: 56%

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

2##################### 76730722711b052751c7e443e885cbf7 ############################## 

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_imstat import imstat as _imstat_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 _imstat: 

15 """ 

16 imstat ---- Calculates statistical information from an image or image region 

17 

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

19 

20 imagename Name of the input image 

21 axes List of axes to evaluate statistics over. Default is all axes. 

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 listit Print stats and bounding box to logger? 

27 verbose Print additional messages to logger? 

28 mask Mask to use. Default is none. 

29 stretch Stretch the mask if necessary and possible? 

30 logfile Name of file to write fit results. 

31 append If logfile exists, append to it if True or overwrite it if False 

32 algorithm Algorithm to use. Supported values are "biweight", "chauvenet", "classic", "fit-half", and "hinges-fences". Minimum match is supported. 

33 fence Fence value for hinges-fences. A negative value means use the entire data set (ie default to the "classic" algorithm). Ignored if algorithm is not "hinges-fences". 

34 center Center to use for fit-half. Valid choices are "mean", "median", and "zero". Ignored if algorithm is not "fit-half". 

35 lside For fit-half, use values <= center for real data if True? If False, use values >= center as real data. Ignored if algorithm is not "fit-half". 

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 algorithm is not "chauvenet". 

38 clmethod Method to use for calculating classical statistics. Supported methods are "auto", "tiled", and "framework". Ignored if algorithm is not "classic". 

39 niter For biweight, 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, do a fast, simple computation (see description). Ignored if the algorithm is not "biweight". 

40 RETURNS void 

41 

42 --------- examples ----------------------------------------------------------- 

43 

44  

45 

46 

47 """ 

48 

49 _info_group_ = """information, analysis""" 

50 _info_desc_ = """Calculates statistical information from an image or image region""" 

51 

52 def __call__( self, imagename='', axes=[ ], region='', box='', chans='', stokes='', listit=True, verbose=True, mask='', stretch=False, logfile='', append=True, algorithm='classic', fence=float(-1), center='mean', lside=True, zscore=float(-1), maxiter=int(-1), clmethod='auto', niter=int(3) ): 

53 schema = {'imagename': {'type': 'cReqPath', 'coerce': _coerce.expand_path}, 'axes': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'region': {'anyof': [{'type': 'cPath', 'coerce': _coerce.expand_path}, {'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}, 'listit': {'type': 'cBool'}, 'verbose': {'type': 'cBool'}, 'mask': {'type': 'cStr', 'coerce': _coerce.to_str}, 'stretch': {'type': 'cBool'}, 'logfile': {'type': 'cStr', 'coerce': _coerce.to_str}, 'append': {'type': 'cBool'}, 'algorithm': {'type': 'cStr', 'coerce': _coerce.to_str}, 'fence': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'center': {'type': 'cStr', 'coerce': _coerce.to_str}, 'lside': {'type': 'cBool'}, 'zscore': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'maxiter': {'type': 'cInt'}, 'clmethod': {'type': 'cStr', 'coerce': _coerce.to_str}, 'niter': {'type': 'cInt'}} 

54 doc = {'imagename': imagename, 'axes': axes, 'region': region, 'box': box, 'chans': chans, 'stokes': stokes, 'listit': listit, 'verbose': verbose, 'mask': mask, 'stretch': stretch, 'logfile': logfile, 'append': append, 'algorithm': algorithm, 'fence': fence, 'center': center, 'lside': lside, 'zscore': zscore, 'maxiter': maxiter, 'clmethod': clmethod, 'niter': niter} 

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

56 _logging_state_ = _start_log( 'imstat', [ 'imagename=' + repr(_pc.document['imagename']), 'axes=' + repr(_pc.document['axes']), 'region=' + repr(_pc.document['region']), 'box=' + repr(_pc.document['box']), 'chans=' + repr(_pc.document['chans']), 'stokes=' + repr(_pc.document['stokes']), 'listit=' + repr(_pc.document['listit']), 'verbose=' + repr(_pc.document['verbose']), 'mask=' + repr(_pc.document['mask']), 'stretch=' + repr(_pc.document['stretch']), 'logfile=' + repr(_pc.document['logfile']), 'append=' + repr(_pc.document['append']), 'algorithm=' + repr(_pc.document['algorithm']), 'fence=' + repr(_pc.document['fence']), 'center=' + repr(_pc.document['center']), 'lside=' + repr(_pc.document['lside']), 'zscore=' + repr(_pc.document['zscore']), 'maxiter=' + repr(_pc.document['maxiter']), 'clmethod=' + repr(_pc.document['clmethod']), 'niter=' + repr(_pc.document['niter']) ] ) 

57 task_result = None 

58 try: 

59 task_result = _imstat_t( _pc.document['imagename'], _pc.document['axes'], _pc.document['region'], _pc.document['box'], _pc.document['chans'], _pc.document['stokes'], _pc.document['listit'], _pc.document['verbose'], _pc.document['mask'], _pc.document['stretch'], _pc.document['logfile'], _pc.document['append'], _pc.document['algorithm'], _pc.document['fence'], _pc.document['center'], _pc.document['lside'], _pc.document['zscore'], _pc.document['maxiter'], _pc.document['clmethod'], _pc.document['niter'] ) 

60 except Exception as exc: 

61 _except_log('imstat', exc) 

62 raise 

63 finally: 

64 task_result = _end_log( _logging_state_, 'imstat', task_result ) 

65 return task_result 

66 

67imstat = _imstat( ) 

68