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(ipythonenv)unwarped:temp satra$ which ipython
/software/pysoft/ipythonenv/bin/ipython
(ipythonenv)unwarped:temp satra$ ipython
Python 2.6.1 (r261:67515, Jul 7 2009, 23:51:51)
Type "copyright", "credits" or "license" for more information.
IPython 0.10 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
class TraitedSpec2(traits.HasTraits):
trigger = traits.Event
hashval = traits.Property(depends_on='trigger')
@traits.cached_property
def _get_hashval(self):
print "calc hash"
import numpy as np
return np.random.random()
#!/bin/bash
basedir=$1
mkdir -p $basedir
mkdir -p installdir
cd installdir
# install python if it doesn't exist
if [ ! -e $basedir/bin/python ]; then
<?xml version="1.0"?>
<XCEDE xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.xcede.org/xcede-2" version="2.0">
<subject ID="ID_SUBJECT">
<subjectInfo>
<sex>male</sex>
</subjectInfo>
</subject>
<visit ID="ID_VISIT" subjectID="ID_SUBJECT"/>
<data xsi:type="assessment_t" ID="ID_AGE" subjectID="ID_SUBJECT" visitID="ID_VISIT">
<name>age</name>
In [127]: zm_samples.shape
Out[127]: (22, 50)
In [128]: grpinfo.shape
Out[128]: (22,)
In [129]: grpinfo[0]
Out[129]: 'a'
In [130]: ds = dataset_wizard(zm_samples, targets=grpinfo, chunks=1)
import numpy as np
import matplotlib.pyplot as plt
import mvpa.suite as ms
# create xor dataset
samples = np.random.rand(100,2)-0.5
targets = np.sign(samples)
targets = targets[:,0] == targets[:,1]
# display samples
In [21]: class A(HasTraits):
foo = Either(File(exists=True), List(File(exists=True)))
In [23]: a.foo = '/software/temp/volumecompare.png'
In [25]: a.foo = glob('/software/temp/*.png')
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (3, 0))
In [13]: from enthought.traits.api import *
In [14]: class A(HasTraits):
....: pass
....:
In [16]: a = A()
In [17]: a.add_trait('foo',MultiPath(File(exists=True)))
grp1_subjects = ['s1','s2']
grp2_subjects = ['s3','s4']
def pickfiles(files, subjects):
outfiles = []
for s in subjects:
outfiles.extend([f for f in files if s in f])
return outfiles
"""
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
volsource = pe.Node(interface = nio.DataGrabber(outfields=["dw_imgs"]), name="volsource")
project_dir = "/mindhive/gablab/sad/PY_STUDY_DIR/Block"
volsource.inputs.base_directory = project_dir
volsource.inputs.template = "diffusion/preproc/SAD_*/%s_warp.nii.gz"
volsource.base_dir = '.'
volsource.inputs.template_args = dict(dw_imgs=[[["fa", "ra", "adc"]]])
res = volsource.run()