Source Code for Module stsci.ndimage._ni_support

 1  # Copyright (C) 2003-2005 Peter J. Verveer 
 2  # 
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 4  # modification, are permitted provided that the following conditions 
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 7  # 1. Redistributions of source code must retain the above copyright 
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10  # 2. Redistributions in binary form must reproduce the above 
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30   
31  from __future__ import division 
32  import types 
33  import numpy 
34   
35 -def _extend_mode_to_code(mode): 
36      """Convert an extension mode to the corresponding integer code. 
37      """ 
38      if mode == 'nearest': 
39          return 0 
40      elif mode == 'wrap': 
41          return 1 
42      elif mode == 'reflect': 
43          return 2 
44      elif mode == 'mirror': 
45          return 3 
46      elif mode == 'constant': 
47          return 4 
48      else: 
49          raise RuntimeError('boundary mode not supported') 
50   
51 -def _normalize_sequence(input, rank, array_type=None): 
52      """If input is a scalar, create a sequence of length equal to the 
53      rank by duplicating the input. If input is a sequence, 
54      check if its length is equal to the length of array. 
55      """ 
56      if (isinstance(input, (types.IntType, types.LongType, 
57                             types.FloatType))): 
58          normalized = [input] * rank 
59      else: 
60          normalized = list(input) 
61          if len(normalized) != rank: 
62              err = "sequence argument must have length equal to input rank" 
63              raise RuntimeError(err) 
64      return normalized 
65   
66 -def _get_output(output, input, shape=None): 
67      if shape is None: 
68          shape = input.shape 
69      if output is None: 
70          output = numpy.zeros(shape, dtype = input.dtype.name) 
71          return_value = output 
72      elif type(output) in [type(types.TypeType), type(numpy.zeros((4,)).dtype)]: 
73          output = numpy.zeros(shape, dtype = output) 
74          return_value = output 
75      elif type(output) is types.StringType: 
76          output = numpy.typeDict[output] 
77          output = numpy.zeros(shape, dtype = output) 
78          return_value = output 
79      else: 
80          if output.shape != shape: 
81              raise RuntimeError("output shape not correct") 
82          return_value = None 
83      return output, return_value 
84   
85 -def _check_axis(axis, rank): 
86      if axis < 0: 
87          axis += rank 
88      if axis < 0 or axis >= rank: 
89          raise ValueError('invalid axis') 
90      return axis 
91