models_learners.py 文件源码

def savelogs(self, ts=None, saveres=True, filename=None):
        # FIXME: consider HDF5
        if ts == None:
            ts = time.strftime("%Y%m%d-%H%M%S")

        # np.save("%s/log-x-%s" % (self.cfgprefix, ts), self.iosm.x_)
        # np.save("%s/log-x_raw-%s" % (self.cfgprefix, ts), self.iosm.x_raw_)
        # np.save("%s/log-z-%s" % (self.cfgprefix, ts), self.iosm.z_)
        # np.save("%s/log-zn-%s" % (self.cfgprefix, ts), self.iosm.zn_)
        # np.save("%s/log-zn_lp-%s" % (self.cfgprefix, ts), self.iosm.zn_lp_)
        # np.save("%s/log-r-%s" % (self.cfgprefix, ts), self.iosm.r_)
        # np.save("%s/log-w-%s" % (self.cfgprefix, ts), self.iosm.w_)
        # network data, pickling reservoir, input weights, output weights
        # self.res.save("%s/log-%s-res-%s.bin" % (self.cfgprefix, self.cfgprefix, ts))

        if filename == None:
            logfile = "%s/log-learner-%s" % (self.cfgprefix, ts)
        else:
            logfile = filename
        if saveres:
            np.savez_compressed(logfile, x = self.iosm.x_,
                            x_raw = self.iosm.x_raw_, z = self.iosm.z_, zn = self.iosm.zn_,
                            zn_lp = self.iosm.zn_lp_, r = self.iosm.r_, w = self.iosm.w_, e = self.iosm.e_,
                            t = self.iosm.t_, mse = self.iosm.mse_)
        else:
            np.savez_compressed(logfile, x = self.iosm.x_,
                            x_raw = self.iosm.x_raw_, z = self.iosm.z_, zn = self.iosm.zn_,
                            zn_lp = self.iosm.zn_lp_, w = self.iosm.w_, e = self.iosm.e_,
                            t = self.iosm.t_,
                            mse = self.iosm.mse_)
        print "logs saved to %s" % logfile
        return logfile