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)