diff --git a/script/local.py b/script/local.py
index 56fd228..66ba330 100644
--- a/script/local.py
+++ b/script/local.py
@@ -17,50 +17,8 @@ def get_energy():
     return e
 
 
-#Fitting
-
-from mathutils import estimate_peak_indexes, fit_gaussians, create_fit_point_list, Gaussian
-import java.awt.Color as Color
-
-def fit(ydata, xdata = None):
-    if xdata is None:
-        xdata = frange(0, len(ydata), 1)
-    max_y= max(ydata)    
-    index_max = ydata.index(max_y)    
-    max_x= xdata[index_max]
-    print "Max index:" + str(index_max),
-    print " x:" + str(max_x),
-    print " y:" + str(max_y)
-    
-    gaussians = fit_gaussians(ydata, xdata, [index_max,])
-    (norm, mean, sigma) = gaussians[0]
-
-    p = plot([ydata],["data"],[xdata], context="Fit" )[0] 
-    fitted_gaussian_function = Gaussian(norm, mean, sigma)    
-    scale_x = [float(min(xdata)), float(max(xdata)) ]
-    points = max((len(xdata)+1), 100)
-    resolution = (scale_x[1]-scale_x[0]) / points    
-    fit_y = []
-    fit_x = frange(scale_x[0],scale_x[1],resolution, True)
-    for x in fit_x:
-        fit_y.append(fitted_gaussian_function.value(x))    
-    p.addSeries(LinePlotSeries("fit"))
-    p.getSeries(1).setData(fit_x, fit_y)    
-
-    print "---"
-    print mean, xdata[index_max], abs(mean - xdata[index_max])
-    print scale_x, (scale_x[0] + scale_x[1])/2, abs((scale_x[0] + scale_x[1])/2)
-    print abs(mean - xdata[index_max]) < abs((scale_x[0] + scale_x[1])/2)
-    if abs(mean - xdata[index_max]) < abs((scale_x[0] + scale_x[1])/2):
-        print "Mean -> " +  str(mean)
-        p.addMarker(mean, None, "Mean="+str(round(mean,2)), Color.MAGENTA.darker())
-        return (norm, mean, sigma)
-    else:
-        p.addMarker(max_x, None, "Max="+str(round(max_x,2)), Color.GRAY)
-        print "Invalid gaussian fit: " +  str(mean)
-        return (None, None, None)
        
-
+run("fit")
 run("rock")