numpy2.0

Author: dokester

BayesicFitting/test/TestFitter.py

@@ -169,21 +169,21 @@ def testNormalize( self ):
 
         print( fmt( fitter.hessian ) )
 
-        ppp = fitter.fit( y, plot=self.doplot )
-        print( ppp )
-#        self.assertRaises( numpy.linalg.linalg.LinAlgError, fitter.fit, y )
+#        ppp = fitter.fit( y, plot=self.doplot )
+#        print( ppp )
+        self.assertRaises( numpy.linalg.linalg.LinAlgError, fitter.fit, y )
 
         fitter.normalize( [0.0, 0.0, 1.0, 0.0], 1.0 )       ## fix par[2] at 1.0
 
-        print( fmt( fitter.hessian ) )
-        print( fmt( fitter.covariance ) )
-
         par = fitter.fit( y, plot=self.doplot )
 
         print( "param = ", sm.parameters )
         assertAAE( par[2], 1.0 )
         assertAAE( par, [ -0.5, 1.0, 1.0, -0.2], 1 )
 
+        print( fmt( fitter.hessian ) )
+        print( fmt( fitter.covariance ) )
+
         chisq = fitter.chisq
         print( "chisq = %f"%( chisq) )