diff --git a/raremodel-tf.py b/raremodel-tf.py
index 2d368cb..4dc5bcf 100644
--- a/raremodel-tf.py
+++ b/raremodel-tf.py
@@ -60,7 +60,7 @@
         for i in range(N):
             _sum += b0[i]*(tf.pow(z,i))
 
-        return prefactor * _sum
+        return tf.complex(prefactor * _sum, ztf.constant(0.0))
 
     #calculate f+ or fT
 
@@ -76,7 +76,7 @@
         for i in range(N):
             _sum += b[i] * (tf.pow(z, i) - ((-1)**(i-N)) * (i/N) * tf.pow(z, N))
 
-        return prefactor * _sum
+        return tf.complex(prefactor * _sum, ztf.constant(0.0))
 
 def resonance(q, _mass, width, phase, scale):
 
@@ -109,29 +109,19 @@
     x = tf.cos(phase)*r
     y = tf.sin(phase)*r
 
-    com = tf.complex(x, y)
+    com = tf.complex(scale* x, scale * y)
 
     return com
 
 def bifur_gauss(q, mean, sigma_L, sigma_R, scale):
 
-    x_left = tf.where(q < mean, q, False)
-
-    x_right = tf.where(q >= mean, q, False)
-
-    #Calculate the exponential part of the cusp
-
-    _exp_left = ztf.exp(- tf.pow((x_left-mean),2) / (2 * sigma_L**2))
-    _exp_right = ztf.exp(- tf.pow((x_right-mean),2) / (2 * sigma_R**2))
-
+    _exp = tf.where(q < mean, ztf.exp(- tf.pow((q-mean),2) / (2 * sigma_L**2)), ztf.exp(- tf.pow((q-mean),2) / (2 * sigma_R**2)))
 
     #Scale so the total area under curve is 1 and the top of the cusp is continuous
 
-    _exp = _exp_left + _exp_right
-
     dgamma = scale*_exp/(ztf.sqrt(2*np.pi))*2*(sigma_L*sigma_R)/(sigma_L+sigma_R)
 
-    com = ztf.complex(dgamma, 0)
+    com = ztf.complex(dgamma, ztf.constant(0.0))
 
     return com
 
@@ -149,7 +139,7 @@
     mK = ztf.constant(pdg['Ks_M'])
     mB = ztf.constant(pdg['Bplus_M'])
 
-    q2 = tf.pow(x, 2)
+    q2 = tf.pow(q, 2)
 
     #Some helperfunctions
 
@@ -163,7 +153,7 @@
 
     #left term in bracket
 
-    bracket_left = 2./3. * kabs**2. * beta**2. *tf.abs(C10eff*formfactor(q2, "+"))**2.
+    bracket_left = 2./3. * kabs**2. * beta**2. *tf.abs(tf.complex(C10eff, ztf.constant(0.0))*formfactor(q2, "+"))**2.
 
     #middle term in bracket
 
@@ -171,7 +161,7 @@
 
     _under = q2 * mB**2.
 
-    bracket_middle = _top/_under *tf.pow(tf.abs(C10eff * formfactor(q2, "0")), 2)
+    bracket_middle = _top/_under *tf.pow(tf.abs(tf.complex(C10eff, ztf.constant(0.0)) * formfactor(q2, "0")), 2)
 
     #Note sqrt(q2) comes from derivation as we use q2 and plot q
 
@@ -179,9 +169,9 @@
 
 def vec(q, scale_vec, funcs):
 
-    scale = self.params['scale']
+    scale = scale_vec
 
-    q2 = tf.pow(x, 2)
+    q2 = tf.pow(q, 2)
 
     GF = ztf.constant(pdg['GF'])
     alpha_ew = ztf.constant(pdg['alpha_ew'])
@@ -209,7 +199,7 @@
 
     prefactor2 = kabs**2 * (1. - 1./3. * beta**2)
 
-    abs_bracket = tf.abs(c9eff(x, funcs) * formfactor(q2, "+") + 2 * C7eff * (mb + ms)/(mB + mK) * formfactor(q2, "T"))**2
+    abs_bracket = tf.abs(c9eff(q, funcs) * formfactor(q2, "+") + tf.complex(2.0 * C7eff * (mb + ms)/(mB + mK), ztf.constant(0.0)) * formfactor(q2, "T"))**2
 
     bracket_right = prefactor2 * abs_bracket
 
@@ -219,12 +209,11 @@
 
 def c9eff(q, funcs):
 
-    C9eff_nr = ztf.constant(pdg['C9eff'])
+    C9eff_nr = tf.complex(ztf.constant(pdg['C9eff']), ztf.constant(0.0))
 
     c9 = C9eff_nr
 
-    for func in funcs:
-        c9 += func(q)
+    c9 = c9 + funcs
 
     return c9
 
@@ -247,11 +236,11 @@
         def cusp(q):
             return bifur_gauss(q, mean = self.params['cusp_mass'], sigma_L = self.params['sigma_L'], sigma_R = self.params['sigma_R'], scale = self.params['cusp_scale'])
 
-        funcs = [jpsi_res(x), psi2s_res(x), cusp(x)]
+        funcs = jpsi_res(x) + psi2s_res(x) + cusp(x)
 
         vec_f = vec(x, self.params['scale_vec'], funcs)
 
-        axiv_nr = axiv(x, self.params['scale_axiv'])
+        axiv_nr = axiv_nonres(x, self.params['scale_axiv'])
 
         tot = vec_f + axiv_nr
 
@@ -318,6 +307,7 @@
 nll = zfit.loss.UnbinnedNLL(model=total_f, data=data, fit_range = (x_min, x_max))
 
 minimizer = zfit.minimize.MinuitMinimizer()
+minimizer._use_tfgrad = False
 result = minimizer.minimize(nll)
 
 param_errors = result.error()