import tensorflow as tf

    argus_t_ge_1 = m * tf.pow(u, p) * tf.exp(c * u)
    return tf.maximum(tf.zeros_like(m), argus_t_ge_1, name="argus_pdf")


# // --- Construct signal+background PDF ---
# RooRealVar nsig("nsig","#signal events",200,0.,10000) ;
# RooRealVar nbkg("nbkg","#background events",800,0.,10000) ;

nsig = tf.Variable(200, name="nsig", dtype=tf.float64)
nbkg = tf.Variable(800, name="nbkg", dtype=tf.float64)
vdict['nsig'] = nsig
vdict['nbkg'] = nbkg

# RooAddPdf sum("sum","g+a",RooArgList(gauss,argus),RooArgList(nsig,nbkg)) ;

# // --- Generate a toyMC sample from composite PDF ---
