Dictioynary output support

Author: IvanARashid

tests/IVIMmodels/unit_tests/test_ivim_fit.py

@@ -167,10 +167,10 @@ def test_ivim_fit_saved(name, bvals, data, algorithm, xfail, kwargs, tolerances,
     fit = OsipiBase(algorithm=algorithm, **kwargs)
     signal, ratio = signal_helper(data["data"])
     tolerances = tolerances_helper(tolerances, ratio, data["noise"])
-    [f_fit, Dp_fit, D_fit] = fit.osipi_fit(signal, bvals)
-    npt.assert_allclose(data['f'], fit['f'], rtol=tolerances["rtol"]["f"], atol=tolerances["atol"]["f"])
+    fit_result = fit.osipi_fit(signal, bvals)
+    npt.assert_allclose(data['f'], fit_result['f'], rtol=tolerances["rtol"]["f"], atol=tolerances["atol"]["f"])
     if data['f']<0.80: # we need some signal for D to be detected
-        npt.assert_allclose(data['D'], fit['D'], rtol=tolerances["rtol"]["D"], atol=tolerances["atol"]["D"])
+        npt.assert_allclose(data['D'], fit_result['D'], rtol=tolerances["rtol"]["D"], atol=tolerances["atol"]["D"])
     if data['f']>0.03: #we need some f for D* to be interpretable
-        npt.assert_allclose(data['Dp'], fit['D*'], rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])
+        npt.assert_allclose(data['Dp'], fit_result['D*'], rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])