Very basic testing of signal normalization

Author: IvanARashid

tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py

@@ -22,22 +22,22 @@ def ivim_model(b, S0=1, f=0.1, Dstar=0.01, D=0.001):
         return S0*(f*np.exp(-b*Dstar) + (1-f)*np.exp(-b*D))
 
     signals = ivim_model(bvalues)
-    data = np.array([signals, signals, signals])
+    data = np.array([[signals, signals, signals], [signals, signals, signals]])
     #print(data)
     signals = data
 
     #model = ETP_SRI_LinearFitting(thresholds=[200])
     if kwargs:
-        results = model.osipi_fit(signals, bvalues, **kwargs)
+        results = model.osipi_fit_full_volume(signals, bvalues, **kwargs)
     else:
-        results = model.osipi_fit(signals, bvalues)
+        results = model.osipi_fit_full_volume(signals, bvalues)
     print(results)
     #test = model.osipi_simple_bias_and_RMSE_test(SNR=20, bvalues=bvalues, f=0.1, Dstar=0.03, D=0.001, noise_realizations=10)
 
 #model1 = ETP_SRI_LinearFitting(thresholds=[200])
-#model2 = IAR_LU_biexp(bounds=([0,0,0,0], [1,1,1,1]))
+model2 = IAR_LU_biexp(bounds=([0,0,0,0], [1,1,1,1]))
 #model2 = IAR_LU_modified_mix()
-model2 = OGC_AmsterdamUMC_biexp()
+#model2 = OGC_AmsterdamUMC_biexp()
 
 #dev_test_run(model1)
 dev_test_run(model2)