def fget(self):
filename = '%s.pickle' % self.anlFilename
try:
self._data = pickle.load(open(filename))
print 'found pickled data in: %s' % filename
return self._data
except IOError:
print 'processing data in: %s' % self.anlFilename
self._data = load_correlOutput('%s' % self.anlFilename)
pickle.dump(self._data ,open(filename, 'w'))
return self._data
def build_nativeContactMatrix(self):
"""
Builds a 2D numpy array from available correl output files. The first
index references the contact number, the second index references the
correl time array value (which in turn corresponds to nstep of the
original dynamics in quanta of ``correlSkip``. This method can take
awhile because of disk IO.
"""
print "Building native contact matrix."
rowLength = (self.correlStop - self.correlStart) / self.correlSkip + 1
tmp = []
for i in xrange(len(self.nativeContacts)):
try:
tmp.append(load_correlOutput('%s/natq%04d.anl' % (self.anlPathname, i)))
except IOError:
tmp.append(np.zeros(rowLength))
print "Can't find correl output for natq number: %04d." % i
return np.array(tmp, dtype=np.float64)
