tests: avoid scipy dependency

The χ² in test_error_biased can be easily minimised analytically

tests/__init__.py

@@ -204,19 +204,14 @@ class GrayTest:
         err = data['Λ_r'].var() / 10
         self.assertGreater(err, 0, msg="Λ is exactly constant")
 
-        def χ2(k, var):
-            '''
-            Reduced χ² for the curve fit: Λ(s) = k⋅var(s)
-            '''
-            res = (data['Λ_r'] - k*data[var]) / err
-            return np.sum(res**2) / (data.size - 1)
-
-        import scipy.optimize
-
         for var in ['X', 'Y', 'N_⊥']:
-            k_best = scipy.optimize.minimize(χ2, x0=1, args=var).x[0]
+            # Minimise the χ²(k) = |(Λ_r - k⋅var) / err|² / (n - 1)
+            # The solution is simply: k = (Λ⋅var)/var⋅var
+            k = np.dot(data['Λ_r'], data[var]) / np.linalg.norm(data[var])**2
             with self.subTest(var=var):
-                self.assertGreater(χ2(k_best, var), 1)
+                res = (data['Λ_r'] - k*data[var]) / err
+                χ2 = np.linalg.norm(res)**2 / (data.size - 1)
+                self.assertGreater(χ2, 1)
 
 
 # Command line options