Developing unittests. x fit super unstable. y fit ok, but some very off fits now and then.

analysis.py

@@ -87,7 +87,7 @@ class Analysis:
                                self.zPoints['Mean'],
                                sx = self.xPoints['Error'],
                                sy = self.zPoints['Error'])
-        xODR = odr.ODR(xData, xModel, beta0=[1, 1, 1, 1])
+        xODR = odr.ODR(xData, xModel, beta0=[1, 100, 100, 100])
         xOUT = xODR.run()
         xOUT.pprint()
         """
@@ -124,7 +124,7 @@ class Analysis:
                                self.yPoints['Mean'],
                                sx = self.zPoints['Error'],
                                sy = self.yPoints['Error'])
-        yODR = odr.ODR(yData, yModel, beta0=[1e3, 1, 1])
+        yODR = odr.ODR(yData, yModel, beta0=[1e3, 100, 100])
         yOUT = yODR.run()
         yOUT.pprint()
         """

test.py

@@ -13,5 +13,7 @@ class Particle:
 DET = Detector()
 DETRes = DET.detect(Particle())
 
-ANA = Analysis(DETRes)
+ANA = Analysis()
+ANA.fill(DETRes)
+ANA.yFit()
 

testAnalysis.py

@@ -7,7 +7,7 @@ class testAnalysis(unittest.TestCase):
     """
     A simple test to check the angle means ans error computation.
     """
-    def test(self):
+    def testxFit(self):
         #ang = np.array([6,5,6,5,8,4,8,4,7,1,7,1,10,3,10,3,None,None,None,None])
         #ang = np.reshape(ang, (5,2,2))
         A = Analysis()
@@ -15,15 +15,15 @@ class testAnalysis(unittest.TestCase):
         #self.assertEqual(A.results['Error'][0], 0.5)
         
 
-        z = np.arange(30)
-        y = A.yEOM([100,1,1], z)
+        z = np.arange(0, 30)
+        y = A.yEOM([1000,1,1], z)
         #plt.plot(z,y)
         #plt.show()
         
         Data = []
         for i in range(0,len(z)):
-            err = np.random.random(size=(4))
-            print(err)
+            err =0.01* np.random.random(size=(4))
+            #print(err)
             Data.append([[0,0], [y[i]+err[0],y[i]-err[1]], [z[i]+err[2], z[i]-err[3]]])
             #np.concatenate((Data,
             #        [[0,0], [y[i]+0.1,y[i]-0.1], [z[i]+0.1, z[i]-0.1]]), axis=0)
@@ -34,3 +34,31 @@ class testAnalysis(unittest.TestCase):
         #print(y)
         #print(z)
         #print(Data)
+
+    def testyFit(self):
+        #ang = np.array([6,5,6,5,8,4,8,4,7,1,7,1,10,3,10,3,None,None,None,None])
+        #ang = np.reshape(ang, (5,2,2))
+        A = Analysis()
+        #self.assertEqual(A.results['Mean'][0], 5.5)
+        #self.assertEqual(A.results['Error'][0], 0.5)
+        
+
+        x = np.arange(0, 10, 0.1)
+        z = A.xEOM([1,10,10,100], x)
+        #plt.plot(z,x)
+        #plt.show()
+        
+        Data = []
+        for i in range(0,len(z)):
+            err =0.01* np.random.random(size=(4))
+            #print(err)
+            Data.append([[x[i]+err[0],x[i]-err[1]], [0,0], [z[i]+err[2], z[i]-err[3]]])
+            #np.concatenate((Data,
+            #        [[0,0], [y[i]+0.1,y[i]-0.1], [z[i]+0.1, z[i]-0.1]]), axis=0)
+        Data = np.array(Data)
+
+        A.fill(Data)
+        A.xFit()
+        #print(y)
+        #print(z)
+        #print(Data)