linear slope estimation

knife_edge.py

@@ -46,7 +46,10 @@ def knife_edge(nrun, axisKey='scannerX', signalKey='FastADC4peaks', p0=None, ful
     sortIdx = np.argsort(positions)
     positions = positions[sortIdx]
     intensities = nrun[signalKey].values.flatten()[sortIdx]
-    if intensities[0] > intensities[-1]:
+
+    # estimate a linear slope fitting the data to determine which function to fit
+    slope = np.cov(positions, intensities)[0][1]/np.var(positions) 
+    if slope < 0:
         func = integPowerDown
         funcStr = 'a*erfc(np.sqrt(2)*(x-x0)/w0)'
     else:
@@ -76,4 +79,4 @@ def knife_edge(nrun, axisKey='scannerX', signalKey='FastADC4peaks', p0=None, ful
     if full:
         return popt, pcov
     else:
-        return np.array([popt[1], pcov[1,1]**0.5])
+        return np.array([popt[1], pcov[1,1]**0.5])
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