# Copyright (C) 2003-2005 Peter J. Verveer # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # 1. Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following # disclaimer in the documentation and/or other materials provided # with the distribution. # # 3. The name of the author may not be used to endorse or promote # products derived from this software without specific prior # written permission. # # THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS # OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE # GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING # NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. from collections.abc import Iterable import numpy def _extend_mode_to_code(mode): """Convert an extension mode to the corresponding integer code. """ if mode == 'nearest': return 0 elif mode == 'wrap': return 1 elif mode == 'reflect': return 2 elif mode == 'mirror': return 3 elif mode == 'constant': return 4 else: raise RuntimeError('boundary mode not supported') def _normalize_sequence(input, rank): """If input is a scalar, create a sequence of length equal to the rank by duplicating the input. If input is a sequence, check if its length is equal to the length of array. """ is_str = isinstance(input, str) if not is_str and isinstance(input, Iterable): normalized = list(input) if len(normalized) != rank: err = "sequence argument must have length equal to input rank" raise RuntimeError(err) else: normalized = [input] * rank return normalized def _get_output(output, input, shape=None): if shape is None: shape = input.shape if output is None: output = numpy.zeros(shape, dtype=input.dtype.name) elif isinstance(output, (type, numpy.dtype)): # Classes (like `np.float32`) and dtypes are interpreted as dtype output = numpy.zeros(shape, dtype=output) elif isinstance(output, str): output = numpy.typeDict[output] output = numpy.zeros(shape, dtype=output) elif output.shape != shape: raise RuntimeError("output shape not correct") return output