def runmc(self, length, prob, steps): # ----------------------------- cis = numpy.arange(0, length-1) trans = numpy.array([]) rpr = Representation(cis,trans) z = OneDimChain(rpr) # ----------------------------- dT = 0.0 dL = 0 old_trans = z.get_cfg().trans.size adata = [] for i in range(steps): it = z.get_lifetime(prob) dT += it # ----------------------------- disp = z.get_cfg().trans.size - old_trans if disp in [1, -(z.get_cfg().length-1)]: dL += 1 elif disp in [-1, z.get_cfg().length-1]: dL += -1 # ----------------------------- old_trans = z.get_cfg().trans.size j = dL/dT adata.append((dT, z.get_cfg().cis.size, dL, j)) #print (dT, z.get_cfg().cis.size, dL, j) c, n = z.reconfigure(prob) return adata
def run(self, length, prob, steps): # ----------------------------- cis = numpy.arange(0, length-1) trans = numpy.array([]) rpr = Representation(cis,trans) z = OneDimChain(rpr) # ----------------------------- dT = 0.0 dL = 0 old_trans = z.get_cfg().trans.size data = [] for i in range(steps): it = z.get_lifetime(prob) dT += it old_trans = z.get_cfg().cis print dT, it, '\t'.join(map(str, -z.get_cfg().cis)), '\t'.join(map(str,z.get_cfg().trans)) z.reconfigure(PROB)