Source code for ClearMap.ImageProcessing.Clipping.Clipping

"""
Clipping
========

Module to compute clipped images

Usefull to sace memory in large data sets
"""
__author__    = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__   = 'GPLv3 - GNU General Pulic License v3 (see LICENSE.txt)'
__copyright__ = 'Copyright © 2020 by Christoph Kirst'
__webpage__   = 'http://idisco.info'
__download__  = 'http://www.github.com/ChristophKirst/ClearMap2'

import numpy as np

import pyximport;
pyximport.install(setup_args={"include_dirs":np.get_include()}, 
                  reload_support=True)

import ClearMap.ParallelProcessing.DataProcessing.ArrayProcessing as ap

from . import ClippingCode as code

###############################################################################
### Clipping
###############################################################################

[docs] def clip(source, sink = None, clip_min = None, clip_max = None, clip_norm = None, processes = None, verbose = False): """Clip and normalize data. Arguments --------- source : array Input source. sink : array, dtype or None output sink or output data type, if None, a new array is allocated. clip_min : number Minimal number to clip source data to. clip_max : number Maximal number to clip source data to. clip_norm : number Normalization constant. Returns ------- sink : array Clipped output. """ processes, timer = ap.initialize_processing(verbose=verbose, processes=processes, function='clip'); source, source_buffer = ap.initialize_source(source); if source.ndim != 3: raise ValueError('Source assumed to be 3d found %dd!' % source.ndim); if clip_min is None: clip_min = ap.io.min_value(source); if clip_max is None: clip_max = ap.io.max_value(source); if clip_norm is None: clip_norm = clip_max - clip_min; sink, sink_buffer = ap.initialize_sink(sink = sink, source = source); code.clip(source_buffer, sink_buffer, clip_min, clip_max, clip_norm, processes); return sink;
############################################################################### ### Tests ############################################################################### def _test(): import numpy as np import ClearMap.Utils.Timer as tmr import ClearMap.ImageProcessing.Clipping.Clipping as clp data = np.random.rand(1000,1000,2000); for p in [1, 10, None]: print('Clipping: processes = %r' % p); timer = tmr.Timer(); clipped = clp.clip(data, clip_max = 0.5, processes = p); timer.print_elapsed_time('Clipping');