diff --git a/ptypy/engines/ML.py b/ptypy/engines/ML.py
index d9d99b9b7..9d5bb7d1a 100644
--- a/ptypy/engines/ML.py
+++ b/ptypy/engines/ML.py
@@ -100,10 +100,11 @@ class ML(PositionCorrectionEngine):
     lowlim = 0
     help = Number of iterations before probe update starts
 
-    [all_line_coeffs]
-    default = False
-    type = bool
-    help = Whether to use all nine coefficients in the linesearch instead of three
+    [poly_line_coeffs]
+    default = quadratic
+    type = str
+    help = How many coefficients to be used in the the linesearch
+    doc = choose between the 'quadratic' approximation (default) or 'all'
 
     """
 
@@ -292,7 +293,7 @@ def engine_iterate(self, num=1):
             # In principle, the way things are now programmed this part
             # could be iterated over in a real Newton-Raphson style.
             t2 = time.time()
-            if self.p.all_line_coeffs:
+            if self.p.poly_line_coeffs == "all":
                 B = self.ML_model.poly_line_all_coeffs(self.ob_h, self.pr_h)
                 diffB = np.arange(1,len(B))*B[1:] # coefficients of poly derivative
                 roots = np.roots(np.flip(diffB.astype(np.double))) # roots only supports double
@@ -302,10 +303,12 @@ def engine_iterate(self, num=1):
                 else: # find real root with smallest poly objective
                     evalp = lambda root: np.polyval(np.flip(B),root)
                     self.tmin = dt(min(real_roots, key=evalp)) # root with smallest poly objective
-            else:
+            elif self.p.poly_line_coeffs == "quadratic":
                 B = self.ML_model.poly_line_coeffs(self.ob_h, self.pr_h)
                 # same as above but quicker when poly quadratic
                 self.tmin = dt(-0.5 * B[1] / B[2])
+            else:
+                raise NotImplementedError("poly_line_coeffs should be 'quadratic' or 'all'")
                 
             tc += time.time() - t2