[Scipy-svn] r3405 - trunk/scipy/io/nifti

[scipy-svn at scipy.org]

Author: jarrod.millman
Date: 2007-10-04 02:19:55 -0500 (Thu, 04 Oct 2007)
New Revision: 3405

Removed:
   trunk/scipy/io/nifti/bin/
   trunk/scipy/io/nifti/man/
   trunk/scipy/io/nifti/utils.py
Log:
remove script


Deleted: trunk/scipy/io/nifti/utils.py
===================================================================
--- trunk/scipy/io/nifti/utils.py	2007-10-04 07:05:17 UTC (rev 3404)
+++ trunk/scipy/io/nifti/utils.py	2007-10-04 07:19:55 UTC (rev 3405)
@@ -1,129 +0,0 @@
-### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-#
-#    Utility function for PyNifti
-#
-#    Copyright (C) 2007 by
-#    Michael Hanke <michael.hanke at gmail.com>
-#
-#    This is free software; you can redistribute it and/or
-#    modify it under the terms of the MIT License.
-#
-#    This package is distributed in the hope that it will be useful,
-#    but WITHOUT ANY WARRANTY; without even the implied warranty of
-#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the COPYING
-#    file that comes with this package for more details.
-#
-### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
-
-import numpy
-import scipy.io.nifti
-
-def time2vol( t, tr, lag=0.0, decimals=0 ):
-    """ Translates a time 't' into a volume number. By default function returns
-    the volume number that is closest in time. Volumes are assumed to be
-    recorded exactly (and completely) after tr/2, e.g. if 'tr' is 2 secs the
-    first volume is recorded at exactly one second.
-
-    't' might be a single value, a sequence or an array.
-
-    The repetition 'tr' might be specified directly, but can also be a 
-    NiftiImage object. In the latter case the value of 'tr' is determined from
-    the 'rtime' property of the NiftiImage object.
-
-    't' and 'tr' can be given in an arbitrary unit (but both have to be in the
-    same unit).
-
-    The 'lag' argument can be used to shift the times by constant offset.
-
-    Please note that numpy.round() is used to round to interger value (rounds
-    to even numbers). The 'decimals' argument will be passed to numpy.round().
-    """
-    # transform to numpy array for easy handling
-    tmp = numpy.array(t)
-    
-    # determine tr if NiftiImage object
-    if isinstance( tr, nifti.NiftiImage ):
-        tr = tr.rtime
-
-    vol = numpy.round( ( tmp + lag + tr/2 ) / tr, decimals )
-
-    return vol
-
-
-def applyFxToVolumes( ts, vols, fx, **kwargs ):
-    """ Apply a function on selected volumes of a timeseries.
-
-    'ts' is a 4d timeseries. It can be a NiftiImage or a numpy array.
-    In case of a numpy array one has to make sure that the time is on the
-    first axis. 'ts' can actually be of any dimensionality, but datasets aka
-    volumes are assumed to be along the first axis.
-
-    'vols' is either a sequence of sequences or a 2d array indicating which 
-    volumes fx should be applied to. Each row defines a set of volumes.
-
-    'fx' is a callable function to get an array of the selected volumes as
-    argument. Additonal arguments may be specified as keyword arguments and
-    are passed to 'fx'.
-
-    The output will be a 4d array with one computed volume per row in the 'vols'
-    array.
-    """
-    # get data array from nifti image or assume data array is
-    # already present
-    if isinstance( ts, nifti.NiftiImage ):
-        data = ts.data
-    else:
-        data = ts
-
-    out = []
-
-    for vol in vols:
-        out.append( fx( data[ numpy.array( vol ) ], **kwargs ) )
-
-    return numpy.array( out )
-
-
-def cropImage( nimg, bbox ):
-    """ Crop an image.
-
-    'bbox' has to be a sequency of (min,max) tuples (one for each image
-    dimension).
-
-    The function returns the cropped image. The data is not shared with the
-    original image, but is copied.
-    """
-
-    # build crop command
-    cmd = 'nimg.data.squeeze()['
-    cmd += ','.join( [ ':'.join( [ str(i) for i in dim ] ) for dim in bbox ] )
-    cmd += ']'
-
-    # crop the image data array
-    cropped = eval(cmd).copy()
-
-    # return the cropped image with preserved header data
-    return nifti.NiftiImage(cropped, nimg.header)
-
-
-def getPeristimulusTimeseries( ts, onsetvols, nvols = 10, fx = numpy.mean ):
-    """ Returns 4d array with peristimulus timeseries.
-
-    Parameters:
-        ts        - source 4d timeseries
-        onsetvols - sequence of onsetvolumes to be averaged over
-        nvols     - length of the peristimulus timeseries in volumes
-                    (starting from onsetvol)
-        fx        - function to be applied to the list of corresponding
-                    volumes. Typically this will be mean(), so it is default,
-                    but it could also be var() or something different. The
-                    supplied function is to be able to handle an 'axis=0'
-                    argument similiar to NumPy's mean(), var(), ...
-    """
-    selected = [ [ o + offset for o in onsetvols ] \
-                    for offset in range( nvols ) ]
-
-    if fx == tuple:
-        return applyFxToVolumes( ts, selected, fx )
-    else:
-        return applyFxToVolumes( ts, selected, fx, axis=0 )
-