WiP test fix

napytau/core/chi.py

@@ -1,7 +1,6 @@
 from napytau.core.polynomials import polynomial_sum_at_measuring_times
 from napytau.core.polynomials import differentiated_polynomial_sum_at_measuring_times
 from numpy import sum
-from numpy import array
 from numpy import ndarray
 from numpy import mean
 from numpy import power
@@ -141,9 +140,9 @@ def chi_squared_t_hyp(t_hyp: float) -> float:
             delta_doppler_shifted_intensities,
             delta_unshifted_intensities,
             time,
+            initial_coefficients,
             t_hyp,
             weight_factor,
-            initial_coefficients,
         )[1]
 
     # minimize chi-squared function over the range of t_hyp

tests/core/chi_test.py

@@ -4,10 +4,7 @@
 from numpy import testing
 from scipy.optimize import OptimizeResult
 
-from napytau.core.chi import chi_squared_fixed_t
-
-
-def set_up_mocks() -> (MagicMock, MagicMock, MagicMock):
+def set_up_mocks() -> (MagicMock, MagicMock):
     polynomials_mock = MagicMock()
     polynomials_mock.polynomial_sum_at_measuring_times = MagicMock()
     polynomials_mock.differentiated_polynomial_sum_at_measuring_times = MagicMock()
@@ -33,7 +30,7 @@ def test_ChiCalculationForValidData(self):
                 {
                     "napytau.core.polynomials": polynomials_mock,
                 },
-        ):
+            ):
 
             from napytau.core.chi import chi_squared_fixed_t
 
@@ -543,6 +540,7 @@ def test_coefficientOptimization(self):
         ):
 
             from napytau.core.chi import optimize_coefficients
+            from napytau.core.chi import chi_squared_fixed_t
 
             # Mocked input data
             doppler_shifted_intensities: array = array([2, 6])