From e6b11269fba718593e1f4f041c9126546725dfeb Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Mon, 8 Jan 2024 10:02:58 +0100
Subject: [PATCH 01/18] Bounds fixes

---
 src/standardized/IAR_LU_biexp.py                |  2 +-
 src/standardized/OGC_AmsterdamUMC_biexp.py      |  7 +++++--
 .../unit_tests/simple_test_run_of_algorithm.py  | 17 ++++++++++++-----
 3 files changed, 18 insertions(+), 8 deletions(-)

diff --git a/src/standardized/IAR_LU_biexp.py b/src/standardized/IAR_LU_biexp.py
index 7389f8c..9f6eb4f 100644
--- a/src/standardized/IAR_LU_biexp.py
+++ b/src/standardized/IAR_LU_biexp.py
@@ -36,7 +36,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
             Our OsipiBase object could contain functions that compare the inputs with
             the requirements.
         """
-        super(IAR_LU_biexp, self).__init__(bvalues, thresholds, bounds, initial_guess)
+        super(IAR_LU_biexp, self).__init__(bvalues, thresholds, bounds=bounds, initial_guess=initial_guess)
         
         # Check the inputs
         
diff --git a/src/standardized/OGC_AmsterdamUMC_biexp.py b/src/standardized/OGC_AmsterdamUMC_biexp.py
index 130ffc4..d61a50e 100644
--- a/src/standardized/OGC_AmsterdamUMC_biexp.py
+++ b/src/standardized/OGC_AmsterdamUMC_biexp.py
@@ -35,9 +35,11 @@ def __init__(self, bvalues=None, thresholds=None, bounds=([0, 0, 0.005, 0.7],[0.
             Our OsipiBase object could contain functions that compare the inputs with
             the requirements.
         """
-        super(OGC_AmsterdamUMC_biexp, self).__init__(bvalues, bounds, initial_guess, fitS0)
+        #super(OGC_AmsterdamUMC_biexp, self).__init__(bvalues, bounds, initial_guess, fitS0)
+        super(OGC_AmsterdamUMC_biexp, self).__init__(bvalues=bvalues, bounds=bounds, initial_guess=initial_guess)
         self.OGC_algorithm = fit_least_squares
-        self.initialize(bounds, initial_guess, fitS0)
+        #self.initialize(bounds, initial_guess, fitS0)
+        self.fitS0=fitS0
 
     def initialize(self, bounds, initial_guess, fitS0):
         if bounds is None:
@@ -60,6 +62,7 @@ def ivim_fit(self, signals, bvalues, initial_guess=None, **kwargs):
         Returns:
             _type_: _description_
         """
+
         if initial_guess is not None and len(initial_guess) == 4:
             self.initial_guess = initial_guess
         bvalues=np.array(bvalues)
diff --git a/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py b/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
index 92473bb..0f42f8e 100644
--- a/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
+++ b/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
@@ -1,11 +1,17 @@
-import numpy as np
+import sys
+sys.path.append(r"C:\Users\ivan5\Box\OSIPI\TF2.4_IVIM-MRI_CodeCollection")
+
+
 import os
+import numpy as np
 from pathlib import Path
 #from src.standardized.ETP_SRI_LinearFitting import ETP_SRI_LinearFitting
 from src.standardized.IAR_LU_biexp import IAR_LU_biexp
+from src.standardized.IAR_LU_modified_mix import IAR_LU_modified_mix
 #from src.standardized.IAR_LU_segmented_2step import IAR_LU_segmented_2step
-from src.standardized.PvH_KB_NKI_IVIMfit import PvH_KB_NKI_IVIMfit
+#from src.standardized.PvH_KB_NKI_IVIMfit import PvH_KB_NKI_IVIMfit
 #from src.standardized.PV_MUMC_biexp import PV_MUMC_biexp
+from src.standardized.OGC_AmsterdamUMC_biexp import OGC_AmsterdamUMC_biexp
 
 ## Simple test code... 
 # Used to just do a test run of an algorithm during development
@@ -26,8 +32,9 @@ def ivim_model(b, S0=1, f=0.1, Dstar=0.01, D=0.001):
     #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()
-model2 = PvH_KB_NKI_IVIMfit()
+#model2 = IAR_LU_biexp(bounds=([0,0,0,0], [1,1,1,1]))
+model2 = IAR_LU_modified_mix()
+model2 = OGC_AmsterdamUMC_biexp()
 
-#dev_test_run(model1, linear_fit_option=True)
+#dev_test_run(model1)
 dev_test_run(model2)

From 6a1cff16fb6b7dcc727a27c17fa0a8d3e6a9fcf7 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 19 Jan 2024 14:26:47 +0100
Subject: [PATCH 02/18] Minor change to super inputs

---
 src/standardized/IAR_LU_biexp.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/standardized/IAR_LU_biexp.py b/src/standardized/IAR_LU_biexp.py
index 9f6eb4f..7389f8c 100644
--- a/src/standardized/IAR_LU_biexp.py
+++ b/src/standardized/IAR_LU_biexp.py
@@ -36,7 +36,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
             Our OsipiBase object could contain functions that compare the inputs with
             the requirements.
         """
-        super(IAR_LU_biexp, self).__init__(bvalues, thresholds, bounds=bounds, initial_guess=initial_guess)
+        super(IAR_LU_biexp, self).__init__(bvalues, thresholds, bounds, initial_guess)
         
         # Check the inputs
         

From f60cd1ee3118e02cc4c8399871bbaf8378a1c7a5 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 19 Jan 2024 14:27:01 +0100
Subject: [PATCH 03/18] Testing for >1D inputs

---
 tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py b/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
index 0f42f8e..7e24062 100644
--- a/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
+++ b/tests/IVIMmodels/unit_tests/simple_test_run_of_algorithm.py
@@ -22,6 +22,9 @@ 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])
+    #print(data)
+    signals = data
 
     #model = ETP_SRI_LinearFitting(thresholds=[200])
     if kwargs:
@@ -33,7 +36,7 @@ def ivim_model(b, S0=1, f=0.1, Dstar=0.01, D=0.001):
     
 #model1 = ETP_SRI_LinearFitting(thresholds=[200])
 #model2 = IAR_LU_biexp(bounds=([0,0,0,0], [1,1,1,1]))
-model2 = IAR_LU_modified_mix()
+#model2 = IAR_LU_modified_mix()
 model2 = OGC_AmsterdamUMC_biexp()
 
 #dev_test_run(model1)

From ff486c3705d3ea9357ad5fdb6f1d877fda7be5f6 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 19 Jan 2024 14:27:38 +0100
Subject: [PATCH 04/18] Added support for >1D fits

---
 src/wrappers/OsipiBase.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index c6a2bcb..17e58ac 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -47,7 +47,7 @@ def initialize(**kwargs):
         pass
 
     #def osipi_fit(self, data=None, bvalues=None, thresholds=None, bounds=None, initial_guess=None, **kwargs):
-    def osipi_fit(self, data, bvalues, **kwargs):
+    def osipi_fit(self, data, bvalues=None, **kwargs):
         """Fits the data with the bvalues
         Returns [S0, f, Dstar, D]
         """
@@ -68,7 +68,6 @@ def osipi_fit(self, data, bvalues, **kwargs):
         #kwargs["bvalues"] = use_bvalues
         
         #args = [data, use_bvalues, use_thresholds]
-        args = [data, use_bvalues]
         #if self.required_bounds or self.required_bounds_optional:
             #args.append(use_bounds)
         #if self.required_initial_guess or self.required_initial_guess_optional:
@@ -83,7 +82,12 @@ def osipi_fit(self, data, bvalues, **kwargs):
         
         #args = [data, use_bvalues, use_initial_guess, use_bounds, use_thresholds]
         #args = [arg for arg in args if arg is not None]
-        results = self.ivim_fit(*args, **kwargs)
+
+        # Assuming the last dimension of the data is the signal values of each b-value
+        results = np.empty(data.shape[:-1], dtype=object)
+        for ijk in np.ndindex(data.shape[:-1]):
+            args = [data[ijk], use_bvalues]
+            results[ijk] = self.ivim_fit(*args, **kwargs)
         
         #self.parameter_estimates = self.ivim_fit(data, bvalues)
         return results

From 05cf7464830e69391c1a38e9d5ce63c7624490f9 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 19 Jan 2024 15:48:45 +0100
Subject: [PATCH 05/18] Fixed support for >1D inputs

---
 src/wrappers/OsipiBase.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index 17e58ac..d889b7d 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -3,6 +3,7 @@
 from scipy.stats import norm
 import pathlib
 import sys
+from tqdm import tqdm
 
 class OsipiBase:
     """The base class for OSIPI IVIM fitting"""
@@ -84,10 +85,11 @@ def osipi_fit(self, data, bvalues=None, **kwargs):
         #args = [arg for arg in args if arg is not None]
 
         # Assuming the last dimension of the data is the signal values of each b-value
-        results = np.empty(data.shape[:-1], dtype=object)
-        for ijk in np.ndindex(data.shape[:-1]):
+        results = np.empty(list(data.shape[:-1])+[3]) # Create an array with the voxel dimensions + the ones required for the fit
+        for ijk in tqdm(np.ndindex(data.shape[:-1]), total=np.prod(data.shape[:-1])):
             args = [data[ijk], use_bvalues]
-            results[ijk] = self.ivim_fit(*args, **kwargs)
+            fit = list(self.ivim_fit(*args, **kwargs))
+            results[ijk] = fit
         
         #self.parameter_estimates = self.ivim_fit(data, bvalues)
         return results

From 97990180669352b52582b5d9e1c234f439f8e96c Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Mon, 8 Jul 2024 15:06:35 +0200
Subject: [PATCH 06/18] Standardized fit results as dictionaries. Modified all
 of fitting algorithms as well. Including slight modification to testing
 script

---
 src/standardized/ETP_SRI_LinearFitting.py     | 16 ++++++++++---
 src/standardized/IAR_LU_biexp.py              |  9 +++----
 src/standardized/IAR_LU_modified_mix.py       | 12 ++++++----
 src/standardized/IAR_LU_modified_topopro.py   | 14 +++++++----
 src/standardized/IAR_LU_segmented_2step.py    | 14 +++++++----
 src/standardized/IAR_LU_segmented_3step.py    | 14 +++++++----
 src/standardized/IAR_LU_subtracted.py         | 14 +++++++----
 .../OGC_AmsterdamUMC_Bayesian_biexp.py        |  9 +++----
 src/standardized/OGC_AmsterdamUMC_biexp.py    |  9 +++----
 .../OGC_AmsterdamUMC_biexp_segmented.py       |  9 +++----
 src/standardized/OJ_GU_seg.py                 | 11 +++++----
 src/standardized/PV_MUMC_biexp.py             | 11 +++++----
 src/standardized/PvH_KB_NKI_IVIMfit.py        |  9 +++----
 src/wrappers/OsipiBase.py                     | 24 ++++++++++++++++---
 tests/IVIMmodels/unit_tests/test_ivim_fit.py  |  9 +++----
 15 files changed, 124 insertions(+), 60 deletions(-)

diff --git a/src/standardized/ETP_SRI_LinearFitting.py b/src/standardized/ETP_SRI_LinearFitting.py
index da0eb5e..a5d45c5 100644
--- a/src/standardized/ETP_SRI_LinearFitting.py
+++ b/src/standardized/ETP_SRI_LinearFitting.py
@@ -64,11 +64,21 @@ def ivim_fit(self, signals, bvalues=None, linear_fit_option=False, **kwargs):
             ETP_object = LinearFit()
         else:
             ETP_object = LinearFit(self.thresholds[0])
-            
+        
+        results = {}
         if linear_fit_option:
             f, Dstar = ETP_object.linear_fit(bvalues, signals)
-            return f, Dstar
+
+            results["f"] = f
+            results["D*"] = Dstar
+
+            return results
         else: 
             f, D, Dstar = ETP_object.ivim_fit(bvalues, signals)
-            return f, Dstar, D
+
+            results["f"] = f
+            results["D*"] = Dstar
+            results["D"] = D
+
+            return results
     
diff --git a/src/standardized/IAR_LU_biexp.py b/src/standardized/IAR_LU_biexp.py
index 7389f8c..110413a 100644
--- a/src/standardized/IAR_LU_biexp.py
+++ b/src/standardized/IAR_LU_biexp.py
@@ -76,8 +76,9 @@ def ivim_fit(self, signals, bvalues, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/IAR_LU_modified_mix.py b/src/standardized/IAR_LU_modified_mix.py
index deefde1..9571a56 100644
--- a/src/standardized/IAR_LU_modified_mix.py
+++ b/src/standardized/IAR_LU_modified_mix.py
@@ -76,8 +76,12 @@ def ivim_fit(self, signals, bvalues, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        #f = fit_results.model_params[1]
+        #Dstar = fit_results.model_params[2]
+        #D = fit_results.model_params[3]
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/IAR_LU_modified_topopro.py b/src/standardized/IAR_LU_modified_topopro.py
index 91bf9d8..9e39fc2 100644
--- a/src/standardized/IAR_LU_modified_topopro.py
+++ b/src/standardized/IAR_LU_modified_topopro.py
@@ -76,8 +76,14 @@ def ivim_fit(self, signals, bvalues, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        #f = fit_results.model_params[1]
+        #Dstar = fit_results.model_params[2]
+        #D = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        #return f, Dstar, D
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
+        
+        return results
\ No newline at end of file
diff --git a/src/standardized/IAR_LU_segmented_2step.py b/src/standardized/IAR_LU_segmented_2step.py
index 0365b5f..3fb5cdd 100644
--- a/src/standardized/IAR_LU_segmented_2step.py
+++ b/src/standardized/IAR_LU_segmented_2step.py
@@ -77,8 +77,14 @@ def ivim_fit(self, signals, bvalues, thresholds=None, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        #f = fit_results.model_params[1]
+        #Dstar = fit_results.model_params[2]
+        #D = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        #return f, Dstar, D
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
+        
+        return results
\ No newline at end of file
diff --git a/src/standardized/IAR_LU_segmented_3step.py b/src/standardized/IAR_LU_segmented_3step.py
index 6630f77..170b8ee 100644
--- a/src/standardized/IAR_LU_segmented_3step.py
+++ b/src/standardized/IAR_LU_segmented_3step.py
@@ -76,8 +76,14 @@ def ivim_fit(self, signals, bvalues, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        #f = fit_results.model_params[1]
+        #Dstar = fit_results.model_params[2]
+        #D = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        #return f, Dstar, D
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
+        
+        return results
\ No newline at end of file
diff --git a/src/standardized/IAR_LU_subtracted.py b/src/standardized/IAR_LU_subtracted.py
index 9db0a03..d5508f2 100644
--- a/src/standardized/IAR_LU_subtracted.py
+++ b/src/standardized/IAR_LU_subtracted.py
@@ -76,8 +76,14 @@ def ivim_fit(self, signals, bvalues, **kwargs):
             
         fit_results = self.IAR_algorithm.fit(signals)
         
-        f = fit_results.model_params[1]
-        Dstar = fit_results.model_params[2]
-        D = fit_results.model_params[3]
+        #f = fit_results.model_params[1]
+        #Dstar = fit_results.model_params[2]
+        #D = fit_results.model_params[3]
         
-        return f, Dstar, D
\ No newline at end of file
+        #return f, Dstar, D
+        results = {}
+        results["f"] = fit_results.model_params[1]
+        results["D*"] = fit_results.model_params[2]
+        results["D"] = fit_results.model_params[3]
+        
+        return results
\ No newline at end of file
diff --git a/src/standardized/OGC_AmsterdamUMC_Bayesian_biexp.py b/src/standardized/OGC_AmsterdamUMC_Bayesian_biexp.py
index dcbb629..1b8c8f9 100644
--- a/src/standardized/OGC_AmsterdamUMC_Bayesian_biexp.py
+++ b/src/standardized/OGC_AmsterdamUMC_Bayesian_biexp.py
@@ -78,8 +78,9 @@ def ivim_fit(self, signals, bvalues, initial_guess=None, **kwargs):
         fit_results=fit_results+(1,)
         fit_results = self.OGC_algorithm(bvalues, signals, self.neg_log_prior, x0=fit_results, fitS0=self.fitS0)
 
-        D = fit_results[0]
-        f = fit_results[1]
-        Dstar = fit_results[2]
+        results = {}
+        results["D"] = fit_results[0]
+        results["f"] = fit_results[1]
+        results["D*"] = fit_results[2]
 
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/OGC_AmsterdamUMC_biexp.py b/src/standardized/OGC_AmsterdamUMC_biexp.py
index d61a50e..66b9e6c 100644
--- a/src/standardized/OGC_AmsterdamUMC_biexp.py
+++ b/src/standardized/OGC_AmsterdamUMC_biexp.py
@@ -68,8 +68,9 @@ def ivim_fit(self, signals, bvalues, initial_guess=None, **kwargs):
         bvalues=np.array(bvalues)
         fit_results = self.OGC_algorithm(bvalues, signals, p0=self.initial_guess, bounds=self.bounds, fitS0=self.fitS0)
 
-        D = fit_results[0]
-        f = fit_results[1]
-        Dstar = fit_results[2]
+        results = {}
+        results["D"] = fit_results[0]
+        results["f"] = fit_results[1]
+        results["D*"] = fit_results[2]
 
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/OGC_AmsterdamUMC_biexp_segmented.py b/src/standardized/OGC_AmsterdamUMC_biexp_segmented.py
index cae609c..c452f7b 100644
--- a/src/standardized/OGC_AmsterdamUMC_biexp_segmented.py
+++ b/src/standardized/OGC_AmsterdamUMC_biexp_segmented.py
@@ -69,8 +69,9 @@ def ivim_fit(self, signals, bvalues, initial_guess=None, **kwargs):
         bvalues=np.array(bvalues)
         fit_results = self.OGC_algorithm(bvalues, signals, bounds=self.bounds, cutoff=self.thresholds, p0=self.initial_guess)
 
-        D = fit_results[0]
-        f = fit_results[1]
-        Dstar = fit_results[2]
+        results = {}
+        results["D"] = fit_results[0]
+        results["f"] = fit_results[1]
+        results["D*"] = fit_results[2]
 
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/OJ_GU_seg.py b/src/standardized/OJ_GU_seg.py
index 03a3cd0..af40be7 100644
--- a/src/standardized/OJ_GU_seg.py
+++ b/src/standardized/OJ_GU_seg.py
@@ -63,9 +63,10 @@ def ivim_fit(self, signals, bvalues=None):
             bthr = self.thresholds[0]
                     
         fit_results = seg(signals, bvalues, bthr)
+
+        results = {} 
+        results["f"] = fit_results['f']
+        results["D*"] = fit_results['Dstar']
+        results["D"] = fit_results['D']
         
-        f = fit_results['f']
-        Dstar = fit_results['Dstar']
-        D = fit_results['D']
-        
-        return f, Dstar, D
\ No newline at end of file
+        return results
\ No newline at end of file
diff --git a/src/standardized/PV_MUMC_biexp.py b/src/standardized/PV_MUMC_biexp.py
index 1425aee..f08ddd1 100644
--- a/src/standardized/PV_MUMC_biexp.py
+++ b/src/standardized/PV_MUMC_biexp.py
@@ -48,9 +48,10 @@ def ivim_fit(self, signals, bvalues=None):
         
             
         fit_results = self.PV_algorithm(bvalues, signals)
+
+        results = {} 
+        results["f"] = fit_results[1]
+        results["D*"] = fit_results[2]
+        results["D"] = fit_results[0]
         
-        f = fit_results[1]
-        Dstar = fit_results[2]
-        D = fit_results[0]
-        
-        return f, Dstar, D
+        return results
diff --git a/src/standardized/PvH_KB_NKI_IVIMfit.py b/src/standardized/PvH_KB_NKI_IVIMfit.py
index 3d21ad5..52eea8d 100644
--- a/src/standardized/PvH_KB_NKI_IVIMfit.py
+++ b/src/standardized/PvH_KB_NKI_IVIMfit.py
@@ -55,8 +55,9 @@ def ivim_fit(self, signals, bvalues=None):
         signals = np.reshape(signals, (1, 1, 1, len(signals)))  # assuming that in this test the signals are always single voxel
         fit_results = self.NKI_algorithm(signals,bvalues)
 
-        D = fit_results[0][0,0,0]/1000
-        f = fit_results[1][0,0,0]
-        Dstar = fit_results[2][0,0,0]/1000
+        results = {}
+        results["D"] = fit_results[0][0,0,0]/1000
+        results["f"] = fit_results[1][0,0,0]
+        results["D*"] = fit_results[2][0,0,0]/1000
 
-        return f, Dstar, D
+        return results
diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index d889b7d..405ed3b 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -84,12 +84,30 @@ def osipi_fit(self, data, bvalues=None, **kwargs):
         #args = [data, use_bvalues, use_initial_guess, use_bounds, use_thresholds]
         #args = [arg for arg in args if arg is not None]
 
+        # Check if there is an attribute that defines the result dictionary keys
+        if hasattr(self, "result_keys"):
+            # result_keys is a list of strings of parameter names, e.g. "S0", "f1", "f2", etc.
+            result_keys = self.result_keys
+        else:
+            # Default is ["f", "D*", "D"]
+            self.result_keys = ["f", "D*", "D"]
+        
+        results = {}
+        for key in self.result_keys:
+            results[key] = np.empty(list(data.shape[:-1]))
+
         # Assuming the last dimension of the data is the signal values of each b-value
-        results = np.empty(list(data.shape[:-1])+[3]) # Create an array with the voxel dimensions + the ones required for the fit
+        #results = np.empty(list(data.shape[:-1])+[3]) # Create an array with the voxel dimensions + the ones required for the fit
+        #for ijk in tqdm(np.ndindex(data.shape[:-1]), total=np.prod(data.shape[:-1])):
+            #args = [data[ijk], use_bvalues]
+            #fit = list(self.ivim_fit(*args, **kwargs))
+            #results[ijk] = fit
+
         for ijk in tqdm(np.ndindex(data.shape[:-1]), total=np.prod(data.shape[:-1])):
             args = [data[ijk], use_bvalues]
-            fit = list(self.ivim_fit(*args, **kwargs))
-            results[ijk] = fit
+            fit = self.ivim_fit(*args, **kwargs) # For single voxel fits, we assume this is a dict with a float value per key.
+            for key in list(fit.keys()):
+                results[key][ijk] = fit[key]
         
         #self.parameter_estimates = self.ivim_fit(data, bvalues)
         return results
diff --git a/tests/IVIMmodels/unit_tests/test_ivim_fit.py b/tests/IVIMmodels/unit_tests/test_ivim_fit.py
index 41a08af..39f2cb8 100644
--- a/tests/IVIMmodels/unit_tests/test_ivim_fit.py
+++ b/tests/IVIMmodels/unit_tests/test_ivim_fit.py
@@ -167,8 +167,9 @@ 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'], f_fit, rtol=tolerances["rtol"]["f"], atol=tolerances["atol"]["f"])
-    npt.assert_allclose(data['D'], D_fit, rtol=tolerances["rtol"]["D"], atol=tolerances["atol"]["D"])
-    npt.assert_allclose(data['Dp'], Dp_fit, rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])
+    #[f_fit, Dp_fit, D_fit] = fit.osipi_fit(signal, bvals)
+    fit = fit.osipi_fit(signal, bvals)
+    npt.assert_allclose(data['f'], fit['f'], rtol=tolerances["rtol"]["f"], atol=tolerances["atol"]["f"])
+    npt.assert_allclose(data['D'], fit['D'], rtol=tolerances["rtol"]["D"], atol=tolerances["atol"]["D"])
+    npt.assert_allclose(data['Dp'], fit['D*'], rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])
 

From aed14cb3e91de582ada21e50099702258e4e849f Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Wed, 14 Aug 2024 12:48:47 +0200
Subject: [PATCH 07/18] Added osipp_fit_full_volume

---
 src/wrappers/OsipiBase.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index 405ed3b..6059f10 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -112,6 +112,37 @@ def osipi_fit(self, data, bvalues=None, **kwargs):
         #self.parameter_estimates = self.ivim_fit(data, bvalues)
         return results
     
+    def osipi_fit_full_volume(self, data, bvalues=None, **kwargs):
+        """Sends a full volume in one go to the fitting algorithm. The osipi_fit method only sends one voxel at a time.
+
+        Args:
+            data (array): 3D (single slice) or 4D (multi slice) DWI data.
+            bvalues (array, optional): The b-values of the DWI data. Defaults to None.
+        """
+        
+        use_bvalues = bvalues if bvalues is not None else self.bvalues
+        if use_bvalues is not None: use_bvalues = np.asarray(use_bvalues) 
+
+        # Check if there is an attribute that defines the result dictionary keys
+        if hasattr(self, "result_keys"):
+            # result_keys is a list of strings of parameter names, e.g. "S0", "f1", "f2", etc.
+            result_keys = self.result_keys
+        else:
+            # Default is ["f", "D*", "D"]
+            self.result_keys = ["f", "D*", "D"]
+
+        # Create the results dictionary
+        results = {}
+        for key in self.result_keys:
+            results[key] = np.empty(list(data.shape[:-1]))
+
+        args = [data, use_bvalues]
+        fit = self.ivim_fit(*args, **kwargs) # Assume this is a dict with an array per key representing the parametric maps
+        for key in list(fit.keys()):
+            results[key] = fit[key]
+
+        return results
+    
     def osipi_print_requirements(self):
         """
         Prints the requirements of the algorithm.

From 0fe7c55fae60a5abba234d973b17d1cdfe9bbf3c Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Wed, 14 Aug 2024 13:33:36 +0200
Subject: [PATCH 08/18] Some adjustments to osipi_fit_full_volume

---
 src/wrappers/OsipiBase.py | 44 +++++++++++++++++++++++----------------
 1 file changed, 26 insertions(+), 18 deletions(-)

diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index 6059f10..4012848 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -120,28 +120,36 @@ def osipi_fit_full_volume(self, data, bvalues=None, **kwargs):
             bvalues (array, optional): The b-values of the DWI data. Defaults to None.
         """
         
-        use_bvalues = bvalues if bvalues is not None else self.bvalues
-        if use_bvalues is not None: use_bvalues = np.asarray(use_bvalues) 
+        try:
+            use_bvalues = bvalues if bvalues is not None else self.bvalues
+            if use_bvalues is not None: use_bvalues = np.asarray(use_bvalues) 
 
-        # Check if there is an attribute that defines the result dictionary keys
-        if hasattr(self, "result_keys"):
-            # result_keys is a list of strings of parameter names, e.g. "S0", "f1", "f2", etc.
-            result_keys = self.result_keys
-        else:
-            # Default is ["f", "D*", "D"]
-            self.result_keys = ["f", "D*", "D"]
+            # Check if there is an attribute that defines the result dictionary keys
+            if hasattr(self, "result_keys"):
+                # result_keys is a list of strings of parameter names, e.g. "S0", "f1", "f2", etc.
+                result_keys = self.result_keys
+            else:
+                # Default is ["f", "D*", "D"]
+                self.result_keys = ["f", "D*", "D"]
 
-        # Create the results dictionary
-        results = {}
-        for key in self.result_keys:
-            results[key] = np.empty(list(data.shape[:-1]))
+            # Create the results dictionary
+            results = {}
+            for key in self.result_keys:
+                results[key] = np.empty(list(data.shape[:-1]))
 
-        args = [data, use_bvalues]
-        fit = self.ivim_fit(*args, **kwargs) # Assume this is a dict with an array per key representing the parametric maps
-        for key in list(fit.keys()):
-            results[key] = fit[key]
+            args = [data, use_bvalues]
+            fit = self.ivim_fit_full_volume(*args, **kwargs) # Assume this is a dict with an array per key representing the parametric maps
+            for key in list(fit.keys()):
+                results[key] = fit[key]
 
-        return results
+            return results
+
+        except: 
+            # Check if the problem is that full volume fitting is simply not supported in the standardized implementation
+            if not hasattr(self, "ivim_fit_full_volume"): #and callable(getattr(self, "ivim_fit_full_volume")):
+                print("Full volume fitting not supported for this algorithm")
+
+            return False
     
     def osipi_print_requirements(self):
         """

From 6d878905479a8a60667e083c245c3bf0834f31ce Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Wed, 14 Aug 2024 13:35:36 +0200
Subject: [PATCH 09/18] Added ivim_fit_full_volume to the class

---
 src/standardized/IAR_LU_biexp.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)

diff --git a/src/standardized/IAR_LU_biexp.py b/src/standardized/IAR_LU_biexp.py
index 110413a..4f4f723 100644
--- a/src/standardized/IAR_LU_biexp.py
+++ b/src/standardized/IAR_LU_biexp.py
@@ -81,4 +81,36 @@ def ivim_fit(self, signals, bvalues, **kwargs):
         results["D*"] = fit_results.model_params[2]
         results["D"] = fit_results.model_params[3]
         
+        return results
+
+    def ivim_fit_full_volume(self, signals, bvalues, **kwargs):
+        """Perform the IVIM fit
+
+        Args:
+            signals (array-like)
+            bvalues (array-like, optional): b-values for the signals. If None, self.bvalues will be used. Default is None.
+
+        Returns:
+            _type_: _description_
+        """
+        
+        if self.IAR_algorithm is None:
+            if bvalues is None:
+                bvalues = self.bvalues
+            else:
+                bvalues = np.asarray(bvalues)
+            
+            bvec = np.zeros((bvalues.size, 3))
+            bvec[:,2] = 1
+            gtab = gradient_table(bvalues, bvec, b0_threshold=0)
+            
+            self.IAR_algorithm = IvimModelBiExp(gtab)
+            
+        fit_results = self.IAR_algorithm.fit(signals)
+        
+        results = {}
+        results["f"] = fit_results.model_params[..., 1]
+        results["D*"] = fit_results.model_params[..., 2]
+        results["D"] = fit_results.model_params[..., 3]
+        
         return results
\ No newline at end of file

From c927dbcb58dfa75bd7eb29cc622f4fc4a87fe02d Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Wed, 14 Aug 2024 13:38:10 +0200
Subject: [PATCH 10/18] Adjusted doc string of osipi_fit_full_volume

---
 src/wrappers/OsipiBase.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/wrappers/OsipiBase.py b/src/wrappers/OsipiBase.py
index 4012848..715f1c4 100644
--- a/src/wrappers/OsipiBase.py
+++ b/src/wrappers/OsipiBase.py
@@ -118,6 +118,9 @@ def osipi_fit_full_volume(self, data, bvalues=None, **kwargs):
         Args:
             data (array): 3D (single slice) or 4D (multi slice) DWI data.
             bvalues (array, optional): The b-values of the DWI data. Defaults to None.
+
+        Returns:
+            results (dict): Dict with key each containing an array which is a parametric map.
         """
         
         try:

From 07a89d2932301036d8a5658dab46fbfd00c8123f Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Tue, 27 Aug 2024 14:50:16 +0200
Subject: [PATCH 11/18] Dictioynary output support

---
 tests/IVIMmodels/unit_tests/test_ivim_fit.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/IVIMmodels/unit_tests/test_ivim_fit.py b/tests/IVIMmodels/unit_tests/test_ivim_fit.py
index c5cd912..9a859b6 100644
--- a/tests/IVIMmodels/unit_tests/test_ivim_fit.py
+++ b/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"])
 

From b62e2c647d711fef9ad63eba96eb41c97b865919 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Tue, 27 Aug 2024 15:35:33 +0200
Subject: [PATCH 12/18] Changed to dictionary outputs

---
 ...ithub_and_IVIM_Analysis_using_Python.ipynb | 114 ++++++++----------
 1 file changed, 52 insertions(+), 62 deletions(-)

diff --git a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
index a211bc6..5020268 100644
--- a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
+++ b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "56273b2a",
    "metadata": {},
    "outputs": [],
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "id": "9654f12d-6cfc-4639-884e-d7f2b23fa59f",
    "metadata": {},
    "outputs": [],
@@ -101,19 +101,10 @@
    "metadata": {},
    "outputs": [
     {
-     "ename": "FileNotFoundError",
-     "evalue": "[WinError 2] The system cannot find the file specified",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[4], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# Download the data. \u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m download_data()\n",
-      "File \u001b[1;32m~\\Documents\\GitHub\\TF2.4_IVIM-MRI_CodeCollection\\doc\\..\\utilities\\data_simulation\\Download_data.py:25\u001b[0m, in \u001b[0;36mdownload_data\u001b[1;34m(force)\u001b[0m\n\u001b[0;32m     23\u001b[0m     \u001b[38;5;66;03m# Change to the specified folder\u001b[39;00m\n\u001b[0;32m     24\u001b[0m os\u001b[38;5;241m.\u001b[39mchdir(os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(base_folder,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdownload\u001b[39m\u001b[38;5;124m'\u001b[39m))\n\u001b[1;32m---> 25\u001b[0m subprocess\u001b[38;5;241m.\u001b[39mcheck_call([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mzenodo_get\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttps://zenodo.org/records/10696605\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m     26\u001b[0m \u001b[38;5;66;03m# Open the zip file\u001b[39;00m\n\u001b[0;32m     27\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m force \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mexists(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mData\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m     28\u001b[0m     \u001b[38;5;66;03m# Unzip the file\u001b[39;00m\n",
-      "File \u001b[1;32m~\\anaconda3\\envs\\OSIPI_IVIM\\Lib\\subprocess.py:408\u001b[0m, in \u001b[0;36mcheck_call\u001b[1;34m(*popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    398\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcheck_call\u001b[39m(\u001b[38;5;241m*\u001b[39mpopenargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m    399\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Run command with arguments.  Wait for command to complete.  If\u001b[39;00m\n\u001b[0;32m    400\u001b[0m \u001b[38;5;124;03m    the exit code was zero then return, otherwise raise\u001b[39;00m\n\u001b[0;32m    401\u001b[0m \u001b[38;5;124;03m    CalledProcessError.  The CalledProcessError object will have the\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    406\u001b[0m \u001b[38;5;124;03m    check_call([\"ls\", \"-l\"])\u001b[39;00m\n\u001b[0;32m    407\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 408\u001b[0m     retcode \u001b[38;5;241m=\u001b[39m call(\u001b[38;5;241m*\u001b[39mpopenargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    409\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m retcode:\n\u001b[0;32m    410\u001b[0m         cmd \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124margs\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "File \u001b[1;32m~\\anaconda3\\envs\\OSIPI_IVIM\\Lib\\subprocess.py:389\u001b[0m, in \u001b[0;36mcall\u001b[1;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    381\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcall\u001b[39m(\u001b[38;5;241m*\u001b[39mpopenargs, timeout\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m    382\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Run command with arguments.  Wait for command to complete or\u001b[39;00m\n\u001b[0;32m    383\u001b[0m \u001b[38;5;124;03m    timeout, then return the returncode attribute.\u001b[39;00m\n\u001b[0;32m    384\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    387\u001b[0m \u001b[38;5;124;03m    retcode = call([\"ls\", \"-l\"])\u001b[39;00m\n\u001b[0;32m    388\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 389\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m Popen(\u001b[38;5;241m*\u001b[39mpopenargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;28;01mas\u001b[39;00m p:\n\u001b[0;32m    390\u001b[0m         \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    391\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m p\u001b[38;5;241m.\u001b[39mwait(timeout\u001b[38;5;241m=\u001b[39mtimeout)\n",
-      "File \u001b[1;32m~\\anaconda3\\envs\\OSIPI_IVIM\\Lib\\subprocess.py:1026\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize, process_group)\u001b[0m\n\u001b[0;32m   1022\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtext_mode:\n\u001b[0;32m   1023\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr \u001b[38;5;241m=\u001b[39m io\u001b[38;5;241m.\u001b[39mTextIOWrapper(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr,\n\u001b[0;32m   1024\u001b[0m                     encoding\u001b[38;5;241m=\u001b[39mencoding, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[1;32m-> 1026\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_execute_child(args, executable, preexec_fn, close_fds,\n\u001b[0;32m   1027\u001b[0m                         pass_fds, cwd, env,\n\u001b[0;32m   1028\u001b[0m                         startupinfo, creationflags, shell,\n\u001b[0;32m   1029\u001b[0m                         p2cread, p2cwrite,\n\u001b[0;32m   1030\u001b[0m                         c2pread, c2pwrite,\n\u001b[0;32m   1031\u001b[0m                         errread, errwrite,\n\u001b[0;32m   1032\u001b[0m                         restore_signals,\n\u001b[0;32m   1033\u001b[0m                         gid, gids, uid, umask,\n\u001b[0;32m   1034\u001b[0m                         start_new_session, process_group)\n\u001b[0;32m   1035\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m   1036\u001b[0m     \u001b[38;5;66;03m# Cleanup if the child failed starting.\u001b[39;00m\n\u001b[0;32m   1037\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m f \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mfilter\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m, (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstdin, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstdout, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr)):\n",
-      "File \u001b[1;32m~\\anaconda3\\envs\\OSIPI_IVIM\\Lib\\subprocess.py:1538\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_gid, unused_gids, unused_uid, unused_umask, unused_start_new_session, unused_process_group)\u001b[0m\n\u001b[0;32m   1536\u001b[0m \u001b[38;5;66;03m# Start the process\u001b[39;00m\n\u001b[0;32m   1537\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 1538\u001b[0m     hp, ht, pid, tid \u001b[38;5;241m=\u001b[39m _winapi\u001b[38;5;241m.\u001b[39mCreateProcess(executable, args,\n\u001b[0;32m   1539\u001b[0m                              \u001b[38;5;66;03m# no special security\u001b[39;00m\n\u001b[0;32m   1540\u001b[0m                              \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   1541\u001b[0m                              \u001b[38;5;28mint\u001b[39m(\u001b[38;5;129;01mnot\u001b[39;00m close_fds),\n\u001b[0;32m   1542\u001b[0m                              creationflags,\n\u001b[0;32m   1543\u001b[0m                              env,\n\u001b[0;32m   1544\u001b[0m                              cwd,\n\u001b[0;32m   1545\u001b[0m                              startupinfo)\n\u001b[0;32m   1546\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m   1547\u001b[0m     \u001b[38;5;66;03m# Child is launched. Close the parent's copy of those pipe\u001b[39;00m\n\u001b[0;32m   1548\u001b[0m     \u001b[38;5;66;03m# handles that only the child should have open.  You need\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1551\u001b[0m     \u001b[38;5;66;03m# pipe will not close when the child process exits and the\u001b[39;00m\n\u001b[0;32m   1552\u001b[0m     \u001b[38;5;66;03m# ReadFile will hang.\u001b[39;00m\n\u001b[0;32m   1553\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_close_pipe_fds(p2cread, p2cwrite,\n\u001b[0;32m   1554\u001b[0m                          c2pread, c2pwrite,\n\u001b[0;32m   1555\u001b[0m                          errread, errwrite)\n",
-      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] The system cannot find the file specified"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Folder 'download' created.\n"
      ]
     }
    ],
@@ -175,7 +166,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x1c8fa52a750>"
+       "<matplotlib.colorbar.Colorbar at 0x234437abb50>"
       ]
      },
      "execution_count": 6,
@@ -184,7 +175,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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Bb33rW47zEydOxLZt2zzz/+tf/0KfPn1y1TyGYZg2Z9++fSk7KGWb48ePo3///tq9bP1y4okn4vDhw45z99xzDxYuXOiaTwiBuXPn4txzz3Xdz7axsTFln9/KykpEo1F88MEH6N27tzFNkH61i/h98MEHiMVivhvf3Nzs2MBYemqLAbDdxzBMPiMAtCCxfV6uiUQiaGxsxL59e1BeXh44f1NTE/r06Y99+/Y58vux+m677Tb86U9/wtatWz3TqpalHPPpeV2aIJ7Adl3n57fxixcvTtnCCkgIH4sfwzCdgbacwikvL09L/NLNf/vtt+P555/Hli1bPK3bqqqqFCPowIEDKCoqwsknn+yaxu3JMCrtEu3Zs2dPhMNh342fP38+Dh48aB/79u1rq6YyDMN0QmIZHP4RQuC2227D2rVr8dvf/lb77E+VMWPGYNOmTY5zGzduxMiRI1FcXOyaZuzYsb7b1i7iV1JSghEjRqQ0ftOmTdrGl5aW2ncamd6xMAzDMG0jfrNmzcKKFSuwcuVKdOvWDY2NjWhsbHQ8cmz+/Pm4/vrr7fczZ87E+++/j7lz5+Kdd97BU089hSeffBJ33nmnnWb27NnYuHEjlixZgr/+9a9YsmQJNm/ejDlz5vhuW7ut85s7dy5+8Ytf4KmnnsI777yDO+64A3v37sXMmTPbq0kMwzAFQtuI37Jly3Dw4EFccMEF6N27t32sWbPGTtPQ0IC9e/fa7/v374+XXnoJr732GoYNG4bvfe97eOihh3D11VfbacaOHYvVq1fj6aefxmc/+1ksX74ca9assZ+X6Yd23d7ssccew/3334+GhgYMHjwYP/3pT41rPyhNTU2oqKhACXjOj2GY/EYAiCCxDCDXXi05dh48+H7aAS8VFf3apK25Ji/39mTxYxims9A+4vd3lJcHjy5tajqEiooBnUL8eG9PhmEYpuDgRxoxDMMUHMHn71rzdQ5Y/BiGYQoOFj8WP4ZhmIIjnjzSydc5YPFjGIYpOKLJI518nQMOeGEYhmEKDrb8GIZhCg6e82PxYxiGKTjiSE/IeM6PYRiGyVvY8mPxYxiGKThY/Fj8GIZhCg6O9uRoT4ZhGKbgYMuPYRim4GC3J4sfwzBMwcHix+LHMAxTcPBSBxY/hmGYgoMtPxY/hmGYgoOjPTnak2EYhik42PJjGIYpONjtyeLHMAxTcLD4sfgxDMMUHBztyeLHMAxTcLDlx+LHMAxTcLD4cbQnwzAMU3Cw5ccwDFNwsOXH4scwDFNwsPix25NhGKbgiGVw+GfLli2YPHkyqqurYVkW1q9f75r+hhtugGVZKcegQYPsNMuXL9emOX78eKC2sfgxDMMUHG0jfkeOHMHQoUPxyCOP+Er/4IMPoqGhwT727duHHj164JprrnGkKy8vd6RraGhAWVlZoLax25NhGKbgiCG9fTqDid+kSZMwadIk3+krKipQUVFhv1+/fj0+/vhj3HjjjY50lmWhqqoqUFtU2PJjGIZhOiRPPvkkLr74YvTr189x/vDhw+jXrx9OPfVUXHHFFdi5c2fgstnyYxiGKTgyC3hpampynC0tLUVpaWnmzSI0NDTg5ZdfxsqVKx3nzzjjDCxfvhxDhgxBU1MTHnzwQYwbNw67du1CTU2N7/LZ8mMYhik4Mpvz69Onj+2irKiowOLFi7PewuXLl6N79+6YMmWK4/zo0aNx3XXXYejQoTjvvPPwq1/9Cp/5zGfw8MMPByqfLT+GYZiCIzPLb9++fSgvL7fPZtvqE0LgqaeewvTp01FSUuKaNhQK4eyzz8a7774bqA4WP4ZhmIIjM/ErLy93iF+2qaurw3vvvYebb77ZM60QAvX19RgyZEigOlj8GIZhCo62ifY8fPgw3nvvPfv9nj17UF9fjx49eqBv376YP38+9u/fj2effdaR78knn8SoUaMwePDglDLvvfdejB49GjU1NWhqasJDDz2E+vp6PProo4HaxuLHMAzD5IQ333wTF154of1+7ty5AIAZM2Zg+fLlaGhowN69ex15Dh48iNraWjz44IPaMj/55BN8/etfR2NjIyoqKjB8+HBs2bIF55xzTqC2WUIIEbA/7U5TUxMqKipQAsBq78YwDMNkgAAQQWLQz6UrEWgdOw8e/AHKy4MtCk/kP46KigVt0tZcw5YfwzBMwcF7e7L4MQzDFBwsfix+TMGiuszzzv/PMGnD4sfixzBJ/M4fqyKpy8dCynRsokgv2jOdPB0TFj+mU9EWAVB+6shmO1hIGSb7sPgxeUuhRPrSfrIQMtlBAIinma9zwOLH5CWFInwqfvrdeYYnJnfwnF/WN7ZevHgxzj77bHTr1g29evXClClTsHv3bkcaIQQWLlyI6upqdOnSBRdccAHefvvtbDeFyVMsH0f2Kkt9IrRlWQiFQsZDlz7IAXrkgKxfI6YT0jYPs+3IZF386urqMGvWLPz+97/Hpk2bEI1GMXHiRBw5csROc//99+OBBx7AI488gjfeeANVVVWYMGECDh06lO3mMHlAzoTNs2LLUZ9DoHye8yV2arX0aAMxZJhUWPxyvsPLv//9b/Tq1Qt1dXU4//zzIYRAdXU15syZg3nz5gEAmpubUVlZiSVLluCWW27xLJN3eMl/2u17SwqMKnpweU/J5N8lo7ythaRdhrFMpl1pnx1ebkV5efAnMTQ1NaOi4rFOscNLzp/nd/DgQQBAjx49ACQ2Nm1sbMTEiRPtNKWlpRg/fjy2bduW6+Yw7US7WHc6SwxASHFvmiw107n0m5O+qzSUPLQu1HTbg3awthmmg5DTgBchBObOnYtzzz3X3p27sbERAFBZWelIW1lZiffff19bTnNzM5qbm+336lOEmY5NuwyuikszccqfiGUicGoZ6Vp7ahtkOWq5FgBhWRlbhBbYEiwsOOAlp+J322234U9/+hO2bt2a8pnun9s06CxevBj33ntvTtrI5I6ciJ5G1MxJ/bszKSbBCiJkmc4m0P8Hr7IsIMUCdOTw2RZeUlFIxJGekKWzPKJjkjO35+23347nn38er776Kk499VT7fFVVFYBWC1By4MCBFGtQMn/+fBw8eNA+9u3bl6tmMxmS84hMuLsPTVGZpihNihDCPtT37fHwE7d6/bhJtUE1Pmm3ICSmjeCAl6yLnxACt912G9auXYvf/va36N+/v+Pz/v37o6qqCps2bbLPRSIR1NXVYezYsdoyS0tL7ScH5/oJwkz6tIWlp42edImsNOXxIhvWX0eCBYxxwuKXdbfnrFmzsHLlSmzYsAHdunWzLbyKigp06dIFlmVhzpw5WLRoEWpqalBTU4NFixaha9euuPbaa7PdHCaHZH1AzWCezs/n/pvRWo4qdtmqoy3QzQ9K6y9o9KjsdX5KP5NKFOnZPry3p5Fly5YBAC644ALH+aeffho33HADAOCuu+7CsWPHcOutt+Ljjz/GqFGjsHHjRnTr1i3bzWFyRNbdmo63qYKnEx0qTLp0XlaaH2ELUl5HRdcHq/XDhKAFEMH8vAoM44Sf5M4EIhfX2y0wJaj40de6n7bbzz0P/xUCY3TnJj70X052msOgvdb5fQnl5SVp5I+gomJ1p1jnx3t7Mp7k0spLnHJfVG5Zli8rThU9mieoEPoln9yggNmS1UaMulwfdoPmOxztyeLHuNJW7k033JbB0PVvXgJni2Lija+6tZB+ZGsdX3uQ7jV1lCHzZLNhTBsQQ3pzfhzwwnRysjY0G9bltcXg72X5mUL/20KWTC7bjgC1oC2fc4K8RjDfYPFj8WNssjIEyzk6x6nMSw4avKI7J9/pXHxBoko9RTUgfsvws2g/m/OWdvlCBAqMYSHMB6JI7z+eoz2ZTka2bA830TNt2ZVtHOLUelI2wtgmPwLoNQcZtEdBrrub+9ezngDbraUskUj2lyM9mc4Ei1+B0pZWXlu69VKWLyTrt5QdXozpDeKoWnumoBpLU2Y2CTIfp8Nv8FAm+R3pZZm+czBtA7s9WfwKiLQliLq/ku91ghdE5IIO3Lr0XtYMbVdRURHC4bBjqzMhBGKxYP/M6pZj8Xjcfh+Pxx3pskVKSbptz8h3EsSF6xcqevZ1T7bFV36wAHYs4kgvcpOjPZlCQB04Xaw6P09JSFcQPCMOFWtEHfzpnp9U/OLxOEKhkO926ZZTqHWl45r0G1FJKkrkay0gIYiG4KJska61aecHC2DHgS0/Fr9OTqaDodfOK+p7v8sN3PC7pRg9HwqFtG2U54uKimzRS37oEO6U4BiXfpiENhwOG/sTdL5T1x7TZtzU+qSWqc5ayxRHmYkTiXpbG+Sen7Y9Ky1i0iOG9EYHFj8mD8haEIvGujPtqEIHx1w+AshSxEs9ADie5BAuKkI4KYRxaSnBaa2p7fbbD7Ve+l4VI1N//YgtFXOaJhqN2gJo12dZthBle85Vd7Pg2C4tgCtUwkLY1rD45fxJ7kz7EOhnbVkph+XiQtNZH+kInqlsnZD5OacTZEvpiyDCp/YhG7i1UdsuxS1LrVO3fpry2ofmmmSznx4XQesid82So6Yw7cuWLVswefJkVFdXw7IsrF+/3jX9a6+9pv2N//Wvf3Wkq62txcCBA1FaWoqBAwdi3bp1gdvGll8nJLDwkTx+XJsq6ax7M7k2TWKR2my9yJhckrZ7EIBQrCSTcKtzeLp+ellVOgFS3ZGhUMi21OT5WCyW4i41XRc6byn7E4/H7QAc6hb1Q8Y3MK0NTpSXKNR3PrYC24K2sfyOHDmCoUOH4sYbb8TVV1/tO9/u3bsde4eecsop9uvt27dj2rRp+N73vocvfOELWLduHaZOnYqtW7di1KhRvutg8WNShM9LeCTpWnuObcbg/BdUHzprbLOL+OkEkLZVnSOTf01BLH766Bbo4taPUChkR6FSMaZtVPuonpN/pcjI/NFoNEXgdW3LptVLoXODgrhhPcsBC2DuaRvxmzRpEiZNmhS4ll69eqF79+7az5YuXYoJEyZg/vz5ABIPO6+rq8PSpUuxatUq33Ww27MTYSHAz1m6N+23/oXPbTB1I0WYAId7To3G9N8Vs2XmZpV6BbAEgbbBS3BU68xxaPLpRJHO8bm1SecWVeckTX0JiqvIJgr2XRa7QXNNZg+zbWpqchzNzc1Zbd3w4cPRu3dvXHTRRXj11Vcdn23fvh0TJ050nLvkkkuwbdu2QHWw5ZfnpDVIKKLnJXhebs10hJDWGw6H7UAOKnxedZnmtHTuTFOwiU74dGn9WIAmS1gXpCLdmiZB1lmnFCpg0nJU2xsOhyGEsKNQZb1UQE2Yrhegt8ocwSs+BNDPb4YtwFyS2VMd+vTp4zh7zz33YOHChRm3qnfv3njiiScwYsQINDc347/+679w0UUX4bXXXsP5558PAGhsbERlZaUjX2Vlpf3gdL+w+OUx2bw7Dip8gV2dan1wio0pcMWrTW6fUyFwi67UuSzpfJ+faE+3stXP1CMejzvq0c1D+hFdXbtUEaPi6hftNaDvpcsVqb9J47UJ4AZlcoCIpXdnIRKCuW/fPsecXGlpaVaadfrpp+P000+3348ZMwb79u3Dj3/8Y1v8AP3vKqjHgsUvD0lb9AxuTi/hy9qcEKmXznVRV5yzuamLxk2BJjK/FBJdP1TXpFvffFkmBivGdG1NlqzJXejmjrUDZdB6nUxzhaobmV5znZXsKfaJQhLpXVOmXnv7O02Wka3fFtO2lJeXt9nDbEePHo0VK1bY76uqqlKsvAMHDqRYg17wnF8Bobo63YJLdBaK11yWV910/ikcDqO4uBjFxcUoKipybD+mi3B0swyli08equs0SD/crDi3dGp63fwabY/unJ+bDerqlIfMI4NcotGo7VZVr09RcTGKS0pQohzy+pvmW03fgTrPbGq5yV3tZenz3F+OiGdwtDE7d+5E79697fdjxozBpk2bHGk2btyIsWPHBiqXLb88I9PBwK9rMZfQNqjWi87ak5/TdGo5ujqooOisviC4uVBNfaR/s1G2W5mq5Waq115OQK4dtZZ119kPdH5OwN/v1FEHu0Hbljba2vPw4cN477337Pd79uxBfX09evTogb59+2L+/PnYv38/nn32WQCJSM7TTjsNgwYNQiQSwYoVK1BbW4va2lq7jNmzZ+P888/HkiVLcOWVV2LDhg3YvHkztm7dGqhtLH55QrZcnW4DJ30dRCT8CmkoFLK3GZOWn2VZdoSjBb2bTK1LdSValtUavWq1RjGq82i6v34svSDXgVq3OiFRLSCv+UFT/+l1oJGfpu9Xt+aPfsfSgqT7nXotCZHtsdvq6yrpcQtusQU7g/IZhdbAzeD5AvDmm2/iwgsvtN/PnTsXADBjxgwsX74cDQ0N2Lt3r/15JBLBnXfeif3796NLly4YNGgQXnzxRVx22WV2mrFjx2L16tW4++678Z3vfAef/vSnsWbNmkBr/ADAEnnodG9qakJFRQVKUDhukXT7qbqXdKLiFmjht3yvNFIUSkpKWl1wRUWwLAuxWMx+uoIccGl7RaJBAGBHK6p9k2XFhUA86fKLx+OeT21QXayUoEEmdKlGuKgoJQKStj3QHBvpJ42Kla/pgnbp7lTdrhLdgndaFnXB6rZNM4mf1/Xy+p3Y1yPxRp/GtYT8RQCIADh48GDO59Hk2HmwcRjKy/V70brnj6Giqr5N2ppr2PLrwGRL2HUurbbCOFekCnG23F5ZupcLek/oNieppsmkfPla11a34B2dSJnaorthojccqjs5m/fPXhZgZxXANqeNLL+ODItfBySbouc2aALBw+pp2X4+p25A3f6VklDSwtO6Aok4al2eSpt1rkXTQB9kEFfLUEWCWloiuZWaallKl6L6KCW/c33qtdNZZLprpPtupaDRtlC3cVFRUYqlSl9TSzZT1LlcY6CRbENWamUKGRa/zorGwpLvg7rz0m9CqgVhsozc3I9S9IQPi9U0t0Zf++mjai2ZyqB9UpcPqP2jwqK6Y/2Kb5AlClT4TG5umtduYygEy2AN6q4T/ZsJjmuQLU8Ao0cgzXV+2W5I+8Hi1wnRWXp+51z8YhIHneA5QuiJ9UStCt2gp7PY3Fx7UPqY7YAdXR5V1GS9psAW3TULammrqd3mDd0sPzUdkAx4Qev3o7uJkH/lDjIyrc5KDIpfAWQXaIaw25PFryORbXcnoH/IK5BeVKcKtRZkXXThOnUD0i2+5GAZjUbtfPbAmmisa9t0QpL8QBuUoeJH7EzXS/1c1zcq7KrFm+lcmRCtUbFqP72EjbZP/Zy2V1qlNJ10jcpgJdlvKYAtLS12sI3uiRQqJhe8/Zn8fbpcC3aBZkAbLXXoyLD4dWLc5vpyUZdufg9wihu1DlSB8IMfl202Xbdu6ERN1u/H8tN97oabuJnmMoOU4fW5bo4zFArZUbW6oJi2+O0xaSCQnpB1ojsNFr8OQjaGCJ0rjqKb60mnfLUuGuKv7q5iD4SJE9oADd3SBb/BIOm2X0cQN6nbHBqtSxfc41eo3Nrpx2I3zfV5pVMxlUF/Z/ZSE40A+hVBrRuY5/6YHMHi1wHIlvD5CSzxK4BSrExzefQ1ndPTRSMmX6QIn0787IALpEai6gZTL4Gn18d03fy6Imk6Xb20bdTdTAd10zXwgt5I+BE0v5/r0nl5DOJCIIRWN7dMS9dVSktQurZNuAlrW1nwBQm7PVn8OiumwVm+pn/9lqUTPr+CaxpI1YAMNR21INzKDOpiU63YdObi/M4LZptM5mmDohVCackr6eS8oGmek+LbGkSn8rR1HFj8WPzam0yHR13ghZtLzk34HHfeiYKM4kbfuz2DT83ncIV6iLCuzEzmxnQDuVfZJotILcNNxFXrVX2dLkGtRy/cbmbUvwKpj0WSvwW5WXk0GrUtQhoNarpp0Z0XQrDrMxew+LH4tSfZju50s67kXz8BD+qgp7rwqOjJ87Qc9a7eMuxzSeul7y1FQFQR9Gs1eAmXKlhu5eiEn/aX1qPrqypUfq1vN7duNq0/WY8pUImKHoQAhEhsJRePA5aFoqT7U4qfEAIW2X4tGo0iFo87XOm0TyaLH0hafyyA2YXFj8WvvciK8LkIHpC5pWGy9uRr+pfW6dZeWrbvfBmSqfvRdB38irFb34K4WYOIfjouYO1fy3I8h5G6PB3ipLF81RskuYuPrp0mAbQ/g9n9ya7RNGDxY/FrD7ImfPAnQl7zWTrLxRTBaarPf7P17lF5joq0yT2p5jG1xTSY6upUz8n0Mg9d30ahSzd07lBT+03zYX7mNtV266zIdATQ/r7DYfu35SbOtA3xeNy28MPyt2MlokDV359uc3Jd32nbvNyfLIBMUFj82phcCZ/qagsa1JJahXOHFnmO4jVw+61HHRzV+Z5sWIUmt7DXHKjDcgmHEbJaH8EEkldnFcvP1DpM6Uzo3LNB3adeUPELu7izVRwilnwcUki5gaL55dwf7ZPue6Gf2WlEaqANkyZs+bH45SN0qPDrPvQzOKpiahrQ/ZTtOCdE4DkbOuC51UPP+5nT9DoH6IOI6KBu73upXCM1r1qHms5NjHXnTQKYDdR5TNWtqyQ2fpciORcI8oBcWb4Uw3g8bu8MQ+vz2VCe+8sGvL0Zi1++4iZMqgj4Daqg25HptikzlelVvtwvUm27ye3n151ncpG6EeQmQD5810paQ9ICBqDdmFonaCarhj4/Tz5JnT5R3ev6pit8OjE2iXBcWrdJT4OdD0jZZJyWG4/FEIczeCYcDsMKhSDIkyRkIIzpO9Rahi7eAHZ9BkAgvYvViS4wi18eku58m4o6sKgWn8768xp01YHMr9i4zb2ZLDpVCL0IajVZlmULnx8rWLWePAq3XYV+rqtbmX6F0C2dtu3SBZ1sr986dDctlmUhbCWezEE3zJaiL1/r2pVNC5dJEkd6Vhy7PZl0yFiyyB14NgRQFTjdk7+pZaKKh9d8maxDlqH7XJfPLa2uHX6uRRChdNwQkPOyXbR9urktt/LsPMl8McCxtEOd68oEPzcqaru9LG8Ajq3qdJ+b1v9RFzKdR1a9AKrFp/vM5P6UV5rl0gOe82PxaytyIXx+AyYo6qBCByK3fShNLkg/9aliIc+bRDOo9ehH2IKKiW6fUvq0A92m3IGsSRo5KlKjXNvS2lEFz+0BtTQtteDcvmP1Jou6j+WuMOrvSyeA8nN7LtjlOrELlPGCxS9PCCJ86nvdYKqW42Y9ZcMCSRm8fObT4XdeLJsIIVIsHl1b/PSPfpemea72wtR+t9+Yn76rbmMrFIKV9CjI836eCt/e16fTwJYfi18+4de9Z3qvc3HqXJ1qnbrPTYOfrg30nGnw8hMoYhJwN3QWhR/U9XsAUhZp6+ryqkdaVvKZd+r8ly5vmwg7qUNnxenSqvl07nNp4RYXF9s7v4TD4USwSyhkb3ytPjiX4nYt3cSQrT8XWPxY/NqC7ISnJMtyESq/c1l0wbabBakOZsmT9lyLTvR084PptFF9HWTOTleeSZjdRFYO7ilzjokPXdN6lQs4BdbUXi+yZZVTF6X6cF5TnTrXtePGKhxGUfKJH0VFRSguLgYAe62fZSUWwUvcBFCWrWu3GyyABlj8WPzyAhfBc0M3qKrzLyYrw4871PWuO6B7Kldu12yIQ4qgucxX+ikvHRHPNX5d0243ESkHUn93yTe2SOo8D6bXTBZh8XMsv8oJixcvhmVZmDNnjn1OCIGFCxeiuroaXbp0wQUXXIC33347103Je4IMBLq7c2nxhcNh2w0ln8WnbmEWUoIybMsmeXeuu+t3a6N2cDQIMO2D7vCTlu4kQsVLrdOrH9JFGYvFEI1GExs0J7fnop9JN6ZXO2WdMg994kE6YpipOKjWFL1+pmtPr2c4HLatuuLiYhQVFyd2wiEL2tXvIUye/FBcXIySkhL7Ybi0XTpXuPa343ENLGTX+9IpiGVwdBJyKn5vvPEGnnjiCXz2s591nL///vvxwAMP4JFHHsEbb7yBqqoqTJgwAYcOHcplc/ITywr8j+t2d04FUBW+IMKklmv667cMtf26AddrMKbp0kXnCqYCZTpM11yWaeqDKW861y3bqH3RuXbl7yeUFMGi5BZwOlGVyDxSOIuKirSRxm44hDJxIr1OMgVLzsTv8OHD+MpXvoKf//znOOmkk+zzQggsXboUCxYswFVXXYXBgwfjmWeewdGjR7Fy5cpcNSev8TOUmwIP6CHTqZYRRTf4+znUNmSC2n5qqUpLQR7qe3lOWhb0KfN+UcVUdy10/fUj1GpZunp073OBn7ljXfu1N0tKXpkn5nbToLHK6W5CQW5kWPoCIjI4Ogk5m/ObNWsWLr/8clx88cX4/ve/b5/fs2cPGhsbMXHiRPtcaWkpxo8fj23btuGWW27JVZM6LepgrC4ipn+l8MkHjVKxowIp/3oN0l7ng0LbEkq6XcNymzEyQNL0tG7qYovFYogm3ZGxpLtSrcvLPam+9iP08hrT/pjKcyvL98AfcH5VbZdb3er8JPUUmG4sYvG4vY2ZDGyh+ahLVHWhhkIhx1Mf3PqYMndq6Re+Mxp4h5fcWH6rV6/GH//4RyxevDjls8bGRgBAZWWl43xlZaX9mUpzczOampocB5PA5GZTLSedNafOxdC8unp0dWXqZtRhtz8pfNQ9plqA9C+1+OTfonDYsT2ZaR7JDTfh87KCvazAoBaO2zXzmy5IcJGubfRaaq1qxbsgf2du7mJY+qdAmNqltocJSDyDIwBbtmzB5MmTUV1dDcuysH79etf0a9euxYQJE3DKKaegvLwcY8aMwSuvvOJIs3z5cu30zPHjxwO1LeuW3759+zB79mxs3LgRZWVlxnTqD1YIc4TZ4sWLce+992a1nW1Btv4l/ZYjr58UC3Wgo4+SkajCJ/+a3Ht+rRSdyPjJQ+ciS0pKbPGmSzPUwAiTmMgQ+3jyUTvRWAwiHkdLS4tne73a6oegeeh3o34vfsrKhgjoytAFolhWYskHXa6h3lTRvPKp79LiA1qDieIiEUiluuolfq+F17IGXvZAaKNozyNHjmDo0KG48cYbcfXVV3um37JlCyZMmIBFixahe/fuePrppzF58mS8/vrrGD58uJ2uvLwcu3fvduR10xsdWRe/HTt24MCBAxgxYoR9LhaLYcuWLXjkkUfsBjc2NqJ37952mgMHDqRYg5L58+dj7ty59vumpib06dMn203PClm7Bw04kNFBqaioCMUlJQgpYkYjEtVBSwqPTky8Xvtpm5/zlmU5olC7dOnieLqEKsoquhso2dfm5ma0tLQgGo3abl83goi8242bW1leNwT0u/AzP5dLHI92CoXs3ycVMp0Va7dbtG4PR9NSoVTnpdXP3UjH9VvQtJH4TZo0CZMmTfKdfunSpY73ixYtwoYNG/DCCy84xM+yLFRVVQVrjELW3Z4XXXQR3nrrLdTX19vHyJEj8ZWvfAX19fUYMGAAqqqqsGnTJjtPJBJBXV0dxo4dqy2ztLQU5eXljqNTo0ay+c5G3FEat0BHiCB0Q+dOo5aAqT/qQfPoolvTvQZBRMwrT7Zoy+/T/v1YyQAXkdjyzeTSpTgETZiXoqTUhbYTeKbjEY/HcejQIfTo0cNx/vDhw+jXrx9OPfVUXHHFFdi5c2fgsrNu+XXr1g2DBw92nDvhhBNw8skn2+fnzJmDRYsWoaamBjU1NVi0aBG6du2Ka6+9NtvNaVOyNgwJkdYSh9bsiQHGEs7dO+QQQoNGTHfZut1HKH4G3aADsxDCfr5bLBaDZVmIRqNGN67bPCR14UqrVr5vaWmx3W9qEAwtw9SfbFi9QfJ71WdyY2cD3Y2TiMcdogfNa5pXIp8PGE96IGgdakSybuNwtWyan84dJhNm6xJ0TjK0/NS4i9LSUpSWlmbcLJWf/OQnOHLkCKZOnWqfO+OMM7B8+XIMGTIETU1NePDBBzFu3Djs2rULNTU1vstulx1e7rrrLhw7dgy33norPv74Y4waNQobN25Et27d2qM5WcHPECd8pkskFlrXp+/BlNyVO8pE6mCpCp4JP3Wb3HR+BmgpftFoFOHktldymYNq1ZksDSl8cs5P1i2XPViWhZKSEltYTW41nfs0yHVw66cf1MHdb9lu7fZbn6kN6nWnImUq0/G9K+5O1cKXNyjySe/SOqR98XShSwH21esCJkPxU6ed7rnnHixcuDDTVjlYtWoVFi5ciA0bNqBXr172+dGjR2P06NH2+3HjxuGss87Cww8/jIceesh3+W0ifq+99prjvWVZWLhwYdYvVkcnXRvAr8syxVVkOUO/28J9lGngiC1eZOCT4e+6J8oHbRsdaL32IVXzFrr7TRcA5Se97rX8nlV3NQBY5KYl23DQS5IMxW/fvn2O6adsW31r1qzBzTffjOeeew4XX3yxa9pQKISzzz4b7777bqA6eG/PLGG7FLNcrtd8ks7SMt2Rm1yEQfCykkxWis5Cc8svg1QA2FuKhUIhlJaW2pYbkPo8ODqI0npk+qKiIpSWltpuVOle9RNYEcQCa4u5Pj83EtmAWmqmsk3fpyqY6ndFNyKQlp8QiehPO0BGCHufUNX6MwYCJQrSfsYCiIzFL5exF6tWrcJNN92EVatW4fLLL/dML4RAfX09hgwZEqgeFr88xSRCunkprzv2tnDjBS1Dzvup0YBy/k/dj1TmUa8BzUsFMBQKIR6PIxKJpKQF/LsPc2ER+v0+3OrO1nelXks3YdPVbZoTlK/p9ynFT97o2PUp89V+YIHzoI2iPQ8fPoz33nvPfr9nzx7U19ejR48e6Nu3L+bPn4/9+/fj2WefBZAQvuuvvx4PPvggRo8eba/97tKlCyoqKgAA9957L0aPHo2amho0NTXhoYceQn19PR599NFAbcv5xtZM5rj9w/txidLgjyBl69LqIil1a7NU3CIB3ZCDIN1cuqWlBS0tLQ5x1G3ErNZP1zmqW7+5BbOkYxG2Be3hhtVd3yDeCXnti4qKEE5uXOC13yw8fuNqcBP5IAs9ZjLhzTffxPDhw+1lCnPnzsXw4cPx3e9+FwDQ0NCAvXv32ul/9rOfIRqNYtasWejdu7d9zJ49207zySef4Otf/zrOPPNMTJw4Efv378eWLVtwzjnnBGqbJfJwIqOpqQkVFRUoQfbdjJmSzfY45kEMLifdEgAqRH6iI/3MJcq/tA41n/p0A7W9ugHTb2CMFC25DjAUCqGsrMx+Rpysk+5oIw8pfGqQRSQSwbFjxxCLxdDc3Gy7WU0Rhm64WT9ueTwDOHzWF/RzP/X5cS/6rZv+TqWlV1RUhC5dutguaPmbPXbsmP29HD161P5eaFvU36RqVdpH4mRqG333JvcIABEABw8ezPkyLjl2HvzVMJR3DQfPfzSGiqn1bdLWXMNuz46EEqDindzfGj46OKgWTpAgGktG5lnOqEuJtNDoe91r+d7NUlTbqu6VGQ6HEYvFUFRUZHSp6cqgg7DuJsFNkLzaGkRw8u2eM8h1MV2LFMuPWHvyvPxdULenm1Wu1pny+0bHEroOg0B6F6YTXUwWv06AehdM509gJdYLUgHxM5DRMunuHurdO73LpkERdABU12zRdsr2yL86K1Ed1KR1KdfrqcKvnpN5orEYQsT1KZc66PY4VdtgIh03qalvaho/rmxTfUEt17ZG/laiyZsly2pdiynQ6u6W4kjd1jo6Yh87NOk+m68TPc+Pxa+jIAerNKw/IHW3fd1m1vSv+tpUtqXZjV+Kn7S65MJ0NSJQFUfZNnWujQoQ3dFfde/Kc/YTKZJBK9KSUK04WX88uZ+nzCfrpQ+TdRNeL/wOvF4Dtyp2JgH0mmPTpdfV4df695vGK788aCRySySCePI3QdsuhTBcVIQiMrer+47c6jSlK3iLkC0/Fr98R+f6dHOBBi7fpU43oTa1wc6HVItV0NdkkFMHbCl4dC2gOtejlqGz7tQ86eDHEgnqEnXDdE2DCFku2uUXOQ+negyAVmsQpC/Z/j0zSdjyY/HLJhn9ewoRKDqNioLqRgT0u+0HGeSpy1LWFYvH7c2yaTi6LuJSipxcn2WRfFY8DhEK2eu3ZFACbZnOCpLnVctNWrn2FmahUKLc5HPlpEVJ1/SllJt0FXtZFtlyjfq16PxaZap1nvwgUb+ys4of97fp+vtpk66/6hPr42SOT7Zb94zJcCiE4uJiRzCVV10M4wcWvyxhGg6Ey2fmwsxLE3QCZg8YctCHc8BThc/vnbTqxqRtok9FUNtkizIAoQxm6l2+ri10rk5nnchBU7pbZfAE/RxJcZQDpjroq9eB3jzQyFD5WVCXmxvq/KTutSm9rm4qfDISluajz8+T35valyCWVTr9p25x+2YquXRFtl3exEiXOr2hkW1Uv4t0rd6Cp43W+XVkWPxyTKB/xwDWn3YwlvldXJFu72nZutemQdjrblwNPlHTSuG2+0DymQRQLYMuYzD10WsOqC3cgEGEL8g5dd2imlYIkdETLXIJtUqlZa7zVPhtu9/vsKDn/Vj8WPyyRVoWnragYNF/dM4ESF0/pxMenUhIa1GtTydk9K8qwNRdKgmFQgglXYoWcV3Jv9JiUcuRD59VhV613KgLlApmWAmkUAdVem1CoRDCyQAeJC1Kei38zuGZrhdtr+4zFa+BXrX26BZhqkUtrT55jeRyFDe3p592eN2QqOW4WbaqZU6/S/V3K93Yah/89CelbhSoALL4sfhlk6wJoM+6dKKgmws0iR8dxIUQiCeDSNQBRPd4GZ0VqLaHWmNyI2mQu3zanqLkUxxUN21cOaf2Q6Lbo5MOlroweVX87HZr3GsqOks2iNXoVwRpuWqeUDiMcDLSVT75Qt30AEg+MT35XUQikRR3rp82+knv2+LS/I7UmziR9GJYluV4KLPc5FymUdvIc4A+YfFj8csmbelQ0tXldeerswYBEhyjzInpBn+7Dqv1eYNuA5BJsBziCaTc6duHoRxdm9S5PfrwWrppMg3iMV0nKpq6funeB3GbWsqAruuTOq9Fvze6FVg4HLbne3UWVlwknqFncicGba9sX7puYj95hGjdzFrWq4q633bLgCqGIJCekHWiy8jilyXaQviC3nULIexdWUyDhtsib7Vs+nkoKSi2e1K07sRPRUwdIOlAb9/Bk3yq68utTToBj0ajaG5utp8AQZ8FKNcl0i3Y1AMAQknXoaxDDZQJYi2Z0siDPqiX9s3+XtB6U0LXRspt3mS/UtzYpE/R5F6oMuDF60HFbu2V+dTvVXU/qqjfl/Y3pbkJoDcHYeV78Wqz7/6hU43pjE9Y/DoZKRYW+UwOYKrQuVkDJmvH4TK0rMRNJCmfplXdsVDSuh1qObo20XNyTovWSS0/KiiqZScJWZa9FAPKM/+y6VajLmE6N6l+N/FQyJ4L1m1koNtqzu6rcC5xCGL10e+M/nbcRC5ouW5pJKrVF3Rej9HAbk8Wv46KXwtC/tXN00mXT4gMGvJRPoDeFZn2HBbMd89UZOxIRJBdPMhuNDp3p04IU+on+Wlgh1yPqD4tgIoCFUlqGSK5HjGoENP2qFaeXIYRTraDhvVTYho3pbqLj0kIZL9kGdFo1F4WooqKLq9O4NR8OgEL8ntRf3tu6dJx0zIesPix+GUD9d+3LQJf1DkY1aUkB6cwkDr4otXlaFnJ9YHKIKdb4+fWFjcxcERionVZgYzwVF1qXpagrl00v9zzUw764XAYxcXFKCkpcQgetYao9SQflyTbK+LOBdpu1rDaHmqhFRcXO9avUctPvQGhNwwO69RKzLXqAlsocks3+belpUVvgRswXWtap85yVl2ifsRNd93o9XZzf5vKDyqWBef6ZPFj8etspMx1+BgELADCsmzXmm5Ox0+9bufsskQiio9+7seCSMeqsEVO5rUsRxAFjfCU4kcX3wNJl24oZLs/de3RCYT8K28u5BwpFT15Xl2XJ+cZ5Zyq+l24iZ4q0rL/6VpPXnl0bfMrsOkQtFy2GA3w9mYsfh2ONAYNnYiobkC6fZTujt2idVuWPdhT15tug2u1HV6iaVqMLtuajaFKtiMWi+H48eMJ0SECo1oX1BITQtiPS6IBIvF4PPEEAuHcwFvnSqTXiLo1S0pKHOIn09P+666fm3Wjc3fLdkcikcR7zbZguu/PzXqn1yqIAOksQN2Ng+k3AVKf6WZJnstE6ApOIgXS63QnulAsfllA93vIxPUZxN2oHnb9whmpSJ9lZ2y3RZYvKI8bkujcbX7bSwdXNa/DMoTevUjT69y8ahopXKrFRd2/1D0po0HpdmBSQGgUqxrRqg7w8ikT1NVJn2FncvPS66Ba4H4EULYtFovZrk639Y1qO+QNg6l8tQy5hEB12Zpw64vu9wukBmzRtH5dq150ovGcCQCLX45IW/joax//1OrAaRIH08AkBzBZt51Cdd35EbsMXVK5cFE53H8k6CbF8rX085ZyPpS6RW13KZzzgbQs+peeN107N+FIuUFw6acaJGO6MaDt0VmufoRFegt0Iu02D+rVF7Ut9vdlWb7c+IbC0s/bGWG3J4tfUOhQoPtXyugeNA3xoAEbXgON11watVxkNGLISuwkAih9F86ntluWcz7NVB/9TG2XbrCm5dPzfgZPWpYMgpE7hNBnDcryqdvNdoEmr0UsKXrUMlSDMeLxOOJC2NG1ajtMLlJTH72ugVq+3ChaHqrVp/MUmATayyUqlPRerlpapvqEB9oHmZZGtRYVFSXELxpFTFO27no46pbnWQBbYbcni19HxfWOW7FSVFeS6s6i6VToeTr404XTcl993aCltkt157n1JS4ELCEc1qfX4B8E2lYa+k8tFWoN0ifW09ey7njS1Sd3SwHgEEEAdtSsrg2674r2S7WctG5AzTWgbYhGoynLJFSr3SFwVqurW02r9iPlNyTTCeEoRwe9prLNumtk99FqjVCWruJYLJZyY6GWwfgkjvSsOI72LExyE7+WXvmmQdJPHplPnks5dIEHSn7djiJ+2uUQg3jcvhun1pPOHaq2l5blB+pCo0+Q110Tuw3qTUbihV2eTizU66DOkfoVNDf3oXpt7PYprk81H/1+Tb8YagGb3NJCCNvl6QiUcsPjZo7+pbveyIAhOc+qy+cXC2z92fBSBxY/v/j9N7PdQYErSF9avdyF8q896IvEXo8A7JB7C86BmuZ1E0pAs/G1ZSGktEt1czrmzpTP/PRDl88tj1zrJ19LS0IVDTd0giahz51TrelQOJziEqa4WVx+3Mh0QX+UPMNQJ3x0PaNamvq9qteGujiFEK2/HRcXqX0dSF5Lee2oP7ktXVlZmR0kJCOVZQCPztVqcglrb5QUAXTMdRcKLH4sfoUAHfgsy0rsXEIGn7DG3eclJrK8lHSWlXD9Wc5ACN2AqD6/Ta1XtV50AmEa9HT9p+vq1MHXS4CpMNB81HVocvnSHXb8WnSmfqikWH5kY29d20GvoUEA6UN9pVBYyvVRb5B0ggQ4A6rUPtD0tI3yRoVG5gbZdEGHn98JU1iw+GWAeseYa7eoo25lQJUDhQ5bbITwZZGpeWPUSiQDFE3jKEve7YfDKS4m3eOR1HLUduv6IsvwO6DJIB51RxXVspH91V0fneWne00xiR7tj84KCoKurcbrQG5a7PRJb4CF1h1pAGXTc/K7UK1I2nfV7RoSznlHaTGmQG4SZN2C5G1pabEDedTlGH6uj3LC+TZQaZ0EtvxY/PwioBe3bAqeqQ77c+JKkwOOvENW3ZA6F56IxxG3NA8OTQ58OuGRa8aEEPY6NdMemfF43PEEArpDCRUqk6jpxBhwCog6cFLLQ2cdqDcHdA0edQFKt6G6AXRLNJryQF3VSpHlOL6LkPMRQybXIG2nlwC6uRfVCFR6XdR2p4gfWgN15NMidNfEvnFJ9o3OzVELTf196fqq+x7pEYvHYQFoiUYBkdhyrrm52RY/v5azl/AVLLzUgcUvCF7ilFnhwjHv5zYQ6qw+eZ7+peWYrAJpqQnLPYzeJE62+BksjxRXm/JZR3RFOfqnWTenXn+JQ3SU79NUPrUI/QzkOgvSr9UHOH8j2u8Kzt+P9mYCTiHVuVRV0VX7bqrX/q0mn74hBV29MdG1zYuO90trRwTSuyCd6CKy+HUkDAOmOpDQB5manuWmBoWoA4X2uXrSbUcGONMARgcjNRBBliHT0rttOk9IBz06z2QaxGV6NfLPzVqUQRlyGQCQWPMHALF4HLHk0w7owEqXCqh16244VFcdTU93daHuVvWaqv2gn+uuB7XypEuQWkQ6ZHpTffLa2tdHJzihEIpJJKbjUVHJ+nWWmZfVT39r9PpHo1FEYzHEk+1S54fdrGFNRcZrU3Cw5cfiF4SsWn2qyPm8a5fuOyl69Flw1C2aKNIcOUmFhLqo6Po2OoA5LA0gsc8lEmve6DZi0g1mcqPqLCaTkKl55Ws6b6j2yySC1H1LRS4Wi7VarZq1Z7St9t9k4Az9TJZH+yBdsdIdatrP03SdTNdBdUlK8TO5uykxQ3ARdbtGyQ0BteqBxJwh/e1J17ZcYE/zqdfHD/RGJB6P265OWm5Q1KAbx/lChS0/6Bd0MW2GSVB1rkvV+lDTBcXLwjK57SBdpZogCCs5yJuWTdC6dQO/m1in3VfpmiWDKp3Xk/3R1amDnvW6ufBqt58+6SxbXRq3Oux6RCLCU5C/QOtYqHVxa+rWpcvGQdus+x0F6bdyEVJP+cvJZMCWLVswefJkVFdXw7IsrF+/3jNPXV0dRowYgbKyMgwYMACPP/54Spra2loMHDgQpaWlGDhwINatWxe4bWz5+SQXVp8s0wJ8Lb7VLZimg6LuNcXkApXndBGjukFHAI49LYuLiwHLQhFZS6eWLV2OXrvEUMtHFxWo9lv3uc5iog9zjWtE274+rZmMbbOvgWgNFKLtVaNiQ+GwHWWpLiVRXXhurlC1ft010bmq1ZsHKWjUQrOf8ygEYvL6yOtBxEm6j+lWb0K0PgNRWopev2X1mobCYRQlf3vSnSo9EcXFxfYTOqh17Rd5RXX/Y2rEdsHQRm7PI0eOYOjQobjxxhtx9dVXe6bfs2cPLrvsMnzta1/DihUr8H//7//FrbfeilNOOcXOv337dkybNg3f+9738IUvfAHr1q3D1KlTsXXrVowaNcp32yyRjh+hnWlqakJFRQVK0HZ3b9kWP7U8OcjoBir1LrikpKTVvUgGvngySEAXpJGoNnVwlVYQLZfmoXNAVBxlPhrlWFRU5BA/WU5zc7Pj6ep0azDzJUqdI5Pt0eVT6wRgu4TtuT+r9eG0QMJ9Kfcw1bke6WuT60xCXdB0OUWIWMJ0GYHqwqR9UOtW5xJVKzYSidhRqVLkaXlyoT1IH9R6tcsPlPrkNaW/PSmCchmC6fp5QV35JSUl9oOHpai2tLTgyJEjrk+k1930eb0H2l/8BIAIgIMHD6K8vDyndcmx8+C8YSgv1S+Ncs3fHEPFkvq02mpZFtatW4cpU6YY08ybNw/PP/883nnnHfvczJkzsWvXLmzfvh0AMG3aNDQ1NeHll1+201x66aU46aSTsGrVKt/tYbdnR8FlkHAbQBwi51GOWpabKFJMc1Q6K5TORaUMRurcmUe9bm4xU1pZLhU9x2G1BsG4bUAdVwQmHouluE0dhzIYq4faX7Xv1Co3uYqp4EhBk4IbNuy2QirQuna90HkU6Dk6L6jLmw6yPJMb1CTUOlL6mME0QadCZHAgIaL0aG5uzkqztm/fjokTJzrOXXLJJXjzzTftm3BTmm3btgWqi92ePhHIrvXnpzxfg7105SiDkprXj4DRQUUnONQCUPPJNV7SmlCfmRcKJZ6GHrf069l0d+i6vTfVtqt5qIUcLiqyXWl0AbrO5QjAdtfFDZazqV4ACAthR0HStYQ616PaDlMAj9pv1bWa8lkyKlJ1pXrdONC0FK99Vulic+oGd7P8vPpoW7XEvSmvmbymuidWuPXP4UWBvymGTk+Gbs8+ffo4Tt9zzz1YuHBhpq1CY2MjKisrHecqKysRjUbxwQcfoHfv3sY0jY2Ngepi8evg0AGMniNv7HPqHbrES2i8LDCajw5GOivFa1NltV5Tm9TzfgZvtS51WzG1rVRg4/F4ytyW2h83S1n9TCe2Onc2ze96s0P6pvaBLtbXtUs3D+gXrZvQRRD95PWy9nV5qYs1iOXHGMhwh5d9+/Y53J6lpaVZaRZgHq/U8URNE/S3zeIXgPaw/gCzVeSWxg1VTE2DuduA7JhHE63uTjnvo1sH5yZ+2n1CPfqgtgVwzknRwBOdFWtbGUI49sRULT+Z3oRMJy0hOo9KXXW671FFtzuLZVn2/IRsIxVXS9lNR136QgcP3U2UKZ3uN+IQ7EQmW5jdLD+aV3djQB9dpG4TR78r1SLXXasgvyMmPcrLy3MyP1lVVZViwR04cABFRUU4+eSTXdOo1qAXLH4dgKD/qqZAkaB3PjKPm/jRdOp7dWE6FT81IEdXr2MDZegHXdkWt35aVmtwDA26US1hup5R1ksDKEyWsx+EEPZCc8uy0NzcDMtKBBEVFxfb4kTTmwSZCoAqmtTVaC+eD4WAZPnhcDjleqpl6/roZnmrNxIAUqJATTcK6l07vSGgqDctVMCp6KkCaPptsQB60EH39hwzZgxeeOEFx7mNGzdi5MiRiajyZJpNmzbhjjvucKQZO3ZsoLpY/DoR6Zj+pnLkX50AUlETojW0XZeeYmqbagXoPteVa7JMdPNquj55ze35gaaV0a90YI7FYrZIedUtPQGqBeMQLMP1US1sNzFze+/HFZ38MO1rBg83u5sXIp0bE0dZaefsZLSR+B0+fBjvvfee/X7Pnj2or69Hjx490LdvX8yfPx/79+/Hs88+CyAR2fnII49g7ty5+NrXvobt27fjySefdERxzp49G+effz6WLFmCK6+8Ehs2bMDmzZuxdevWQG1j8WtHHOv8vNKSu2/dEgCK6Y5e5zNXLSK6bZaKI5iEPhmBLD+QVpcaPENdgSZrUNdOtQ9qe+RfGb0JwNV9KV2cqhURBJpHtaTUJw5QN7AQic3BBeBYjkLX28ky6dZh1A1In8pBvyMZ/VlUlPiXVnfukehuSLx+L243FG43D6og29asxhUtr508ry6hkF4F9Xdk+n60rxMnnGm1JRQAbSR+b775Ji688EL7/dy5cwEAM2bMwPLly9HQ0IC9e/fan/fv3x8vvfQS7rjjDjz66KOorq7GQw895FgjOHbsWKxevRp33303vvOd7+DTn/401qxZE2iNH8Dr/AKTcX1yMFBOqwOGOjjI3fal8NjRfonMjjJMd8i6wcJtYKRlqW2QyC2o4vG4w+VIt76i0XluEYS6wVO+VxemA87F5Lo9TlO2+7IsiGREqk5AdNfEL6bBmK75o210EwvLsmxXKd2/1fS9yutAF4LLpyCoEbMmdH2m7dHN06k3D7rfm8xj/2aTblq6SD4uhCM4ibo9myMRRJN7ekYiEdfIWFNbRGsCZ3rPq9I2CLTDOr//k8E6v2XprfPraLDl1w5kIqAplpMQiUEdSNlPU3dXb7rz1wUaAE4BcZu/k3+pdahDN3gbBy0Pq1UdLFWXnWVZreu6hHDcJGTsPhOp0Zpeloi6qbTdFtkv0epSpqKltlXnEpXQiEgvCzsd1Lak4/ak1992mcM552sLK1lLmUGj08/bWYkjvaUOneh5fjmJGd6/fz+uu+46nHzyyejatSuGDRuGHTt22J8LIbBw4UJUV1ejS5cuuOCCC/D222/noimdAnUui+4WYh/KTiamgU91U0mLpLi4GF27drWjuOTRtWtXx04ptBw5QNHdXUpLS1FaWpqymXOM7O4iD7cF8dRVSsW5qKjIrqukpMSuS7oJ1aO4qMhef6e6dd1E2M93or5XBUq1XKPRKFpaWuyNqO2nMcgj6dqTVtvx48dx/PhxRCIRRCIR2y2oCj61hIuKiuwgG3mt1C3VgogiFSPdofve1JsLKmrS8pbXQfabfh+xWMzucyQSsa9T0JsVgWCizBQWWbf8Pv74Y4wbNw4XXnghXn75ZfTq1Qv/+7//i+7du9tp7r//fjzwwANYvnw5PvOZz+D73/8+JkyYgN27d6Nbt27ZblJeIS04iWrx0IEPcFoVlrQAyaArrQgVaj1JoSgtK0OZsl7Hsiw0RyKIk4FX1kcFVJYjB1spbnTQU0XHazCWeXXbhaluRNVVrLpmHQOwMjDTtmQKvR70HO2PH+GRbaZCTl3eJjdlmER96lysJrysWJ11HtR6pvnU3yStj94U0W3T/Iq23SYWPjMC6fl9O9Elzbr4LVmyBH369MHTTz9tnzvttNPs10IILF26FAsWLMBVV10FAHjmmWdQWVmJlStX4pZbbsl2k/IKt39t3eCtntN9bipLdavRXTpoYEtxURHiyrIEh8uK3LHLTY+phWUKLNEJhOpCBfRh8LJtJiuXWiyq1aerX7XcgtINwKeTf/8fgL1CIGLoo18BlGnlTQQVN7XPOleow+0bAN21VG8S/F4rXTraTvpdygAfKxQCDBtYm9y9atpONEbnBn6eX/bF7/nnn8cll1yCa665BnV1dfjUpz6FW2+9FV/72tcAJEJdGxsbHXuzlZaWYvz48di2bVuHFz/VMgtegEgZkPz8o9LBPEbumumWXEFceVQQ6DxTNBp1PCy3tLTUHoAjkQiam5s9xVcd8GW0nnxv6h9tmwz6oK48x7ykZWktZCoK9CGvsm9qevWapMunAdwB4NNdgdeOCjwsBA5oXKEmTIN5LBaz1wzKa0jdv2pedQ5XCIF4Bv0KKnZqO3TWPXXTlpWV2f2gQTAtmt+tH+FjN6dPOug6v7Yk63N+f//737Fs2TLU1NTglVdewcyZM/GNb3zDXschV+YH2Zutubk5ZSPV9iTTfy+hHL7zyX9wspmwm+Xn5pZS52nkRs5UwKS7kUZxqpYcPaibSj6B27jJNVLnxdTPqMtPtsH+SwRafWoCFW/aR7c2uM2T+qEbEsKHcQkhLIH5xkPFa26Wzo/KQycEutduZXvh9ttxK0O9+TH9JqXrms5Nei3j0dXDgpcG8QyOTkLWLb94PI6RI0di0aJFAIDhw4fj7bffxrJly3D99dfb6dxcKyqLFy/Gvffem+2mtg+KxQI4BdCPZWkP1EiuW4N5sKPuMJMLSgiBeNKyi8fjtvtJ7hZCXaFFRUUJodQ8WojO5bgNYPK7VkWWujVDodZHJdE5L1WkdL8b2eZoNGr3SW1XUCvMrS9AwtX52jEL/7EZ2AqBo5qydO5DUx90dcTjiae2U6vdrkOeSwojtXjTiZR0ExSdK9cvOlenfIyWXIMpy1UFnkWOySZZF7/evXtj4MCBjnNnnnkmamtrAST2ZQMSFmDv3r3tNG57s82fP99eHAkk1qqou4q3NRm7PwkWzBYgHRjV+TCRdKFahnQ0v5s7VA6Ox44dA5DYmiwajdp343S+raSkJBGtJ5xBC7IOr+AEdd5LCOGwLGXUplqvzm2mvgZagyViyXVhcq2b3H3FL34DK2S69wE8AqAUwBHLwifQ/z68LHG3eqn7uKWlRftMR/uBssrWbX7ENR3chEn9nuRBv1+5djQWiwGxmP3UD90NC4tfFmG3Z/bdnuPGjcPu3bsd5/72t7+hX79+ABIr+KuqqrBp0yb780gkgrq6OuPebKWlpSkh+AUNHVTsU6kBEPS86XMgNZydblKti+r0IyIm16uuXSaXZVDhk/XG43HH+jC/g2ZQ1ydNF0Ey0AXAh3AfI9zc0m4uRfod6VyhUvRjLkFGXvVnG9M1Nbmbee6ujWC3Z/YtvzvuuANjx47FokWLMHXqVPzhD3/AE088gSeeeAJA4kc/Z84cLFq0CDU1NaipqcGiRYvQtWtXXHvttdluTt6iusXUvykuIU0ZVDDkwKkGIujSA63BImqwip2XWp8kv9vgJe/6gdQnd0vLjw6CNHqUhvrLMmQ6aeXIv9LaozuCeA2mXm7QbA7GfsXVrU7TvJ+XsOYancjJv/ZB1oyqN1t0TlNdFqObKtG9ZnzAll/2xe/ss8/GunXrMH/+fNx3333o378/li5diq985St2mrvuugvHjh3Drbfeio8//hijRo3Cxo0b826Nn/x3C+T+FAJCM+/nnU20bpwcj0MQ68uyLFgGt5ncUsrSCKjpblwIgZaWFgiRWC8WjUYd83F00FXF1E0AqXjJBfFU/IDWHWXkfJ10v1KXmRQ/6nZtSS4Uj0QiOH78uKfV5yVopkFc1y8vMnHbmfJIkVDb1haka0nblj6x6GWgFb3RcguSkuXo2uJI69HGgpdKFj/e2zMbBG6DHAzIKftrSA4O6nk5F2ZZyX0fZZh7Mh0d7NVnvYXkIOOxpyUVM/k5tbqoy1O3WJ2iEz4ZxCKtPil+ct6HuvWi0ai9TyW1EuU8EdBq/ci0cneU48ePB3bruYmdW9/8lJ8L8fNbZy5wu6FQ39NNCORfGshUWlqKcDiMlpYW21I/duwYjh075qse+h3bfxNv3Pvg2cu2Q6Ad9vacOgzlxWns7dkSQ8WveG9PJkng4Bf5T5q0AN3+Eal7SL63rNRdW9S5MBoybluGIjUaUxUIXYSdycKQ76V1Se/o1cXoNIKTWnCqZSAHSymO0lVL5xmlZdDS0pJYThGN4tixY45d/2lfskW65WUroKStLTxKULexbp5WneeVv2Pq4pbb4OkCdfz03+tKdyTRY9oXFr/2JOkCTT2tn9+QQkDne+Rfx16PybvqFJQByW1OSGcFqvXZokQGNGqdUmvNIX6hECykCrC8iaDCrbNQZf/pPpnNzc2OSFPaD7Vv6eDHus0l6Qifbk7QlMat3myId4rrk3gQ5G+aLs1wc8979iP/nFltD7s9WfzyDS93npxTUSPs4vF4wjq1UrfBMpWlm8ej+ez2xOOAZSEOZR4QqZZlPB53PL1A1yf52rE3qGhdliEFme7gYhroc2WtdeTZgvZum1+hpt+/ulm2X1L+Fzrw99KhiCG9WH/e3ozJGj7dSTpxcBbTeodM18jRtHLPTRq04vfOWr2DVwVJ3s0LACGr9QnmcfIcOvqEhtTL4LRk7QjO5FylXLNmL94WArGkmzNIP2gfguJ2k9CRXZKZ5svE+qP56MOH6VZmDrensnmC6bpqLXGvtgRvfudFIL0L0okuIotfnqMLLFHnyOh5OZCpf01l+3U52QIbj9sLlYUQsDRWnWyPrh9U/Oh6Nil+0tVJ06hRhbrrkglelrF8rau/PQJPcp1XJVAfNd+7EKnb67nVZRQ+tvr8w5Yfi1++oIqVbmsxOnBQoZPv5fPgpIVmacrJBHkHb1mWHblHg1tkO3T9omUAreu/ZF+j8rWyQXZQwXOb8zT1yass3U1CUNELal0Fsdq88pnabnJ1m8pySxMKhezIY/qZfZPjshWb13fMkpcGbPmx+HVU6IBKhU9+Ri0eeU5iWRZCMpIyeU66IWla2zrTlOHlFtUNqnSejj5BwbH0QhMFqCtHd+jyuM1bmtKqVqIpv1/8Cp1JTIK49nLRLpnWj8Cpebyuu/z9WJZlP3CZuuPp7jRB9iF1eAr83MT4KpUpJFj88gTT3J/pM0seLkITdNB2S08HNHqowm0SP7VPun4GbbdbW2mbg+aTZNN1mAvSmQdN15L2aofuPZ3zM/2ugwqytv5AqQsEdnuy+HU4hNDOi+gCTuhfetdsz4WFQggn3ZxxIVKERwiRcEUZBp6g81YmoTVZOX5cin7bko6bUcXLivFy2ZrK0KG7zl5lpCPUbnm8rGmT2HtZ26p1p6vXtKWZrk3Geb4OfvPRoeGlDix++YQqAlT4LMtKEb8QAMj1eMqgJMugR9Awcx000MZN6IJaFUEsEr+Dc1Dc8piExKut2RA6U/50bgjknDAtx83tTPOq5Zj6QNf20QhPv3Owbl4Bxicsfix++Qh1JapzdjSIAHAKo1aAfAqJX0xziG2FH4uRDs5BXJ9u1qLb/Fe+DNBu87vp9M1tbtU0p+vVPsd7zxyMEYH0hKwTXXQWvywhfxO5XO2lBkyoQiMFLhKJQAjh2EuTBqPotgDz44JUrS9TcEJQd6kfggiUH/ENMt8pr6XpUU5erkW3uc1c4tdao9+lesMQIus03cowQa8ZvSGjrk+5fZ5XP+Rrv2LJuBBDeoMVz/kxJui/ZCZDv+6O2WvOSQ4KLS0t9mL2eDyOouQm2LabNE3Xkddcjtpek9Xl1U/da7/tA1oHXDqoqzcOsFr3VXX7nlKCL+SNAFq/E10/TefawxL04wKlG5lL3IKT/JSp+24F4Ijs1HkkTNeMBY/JJix+nRA66OueiA2D8GXDUgqaPlsDmp+B2DFgy3pVUVTa5jiXnDv1soJ0wtBewkfbZXpPkb8d1WWpWtOBAoYsy/7NUc9DkHk+tzpc8wZKXUAIpHdxOtEFZfHLI/y6E+2AF2V9ndyEWpCy/ARc+BWybLo51fLUvrsJkD3gJgdxtTzdYGqan3I82om68DTWiptlTOdd23JOVLXc/HgP5EYFAOz1ovQZinQvVZpPhbqKY2QhO92PNYj4ScvRa56a8QG7PdNa6cG0AekOjMJwh+24y1aEz88gFMTF5WVZpBPsYLJEDImN/9fGqFEaBSrdosrhVa+l5KPtzvaNgR/c2uzWRsd3Iv8aroefNoSST/FQf5vpBLkEET6WSBdEBkdAHnvsMfTv3x9lZWUYMWIEfve73xnT3nDDDSm/M8uyMGjQIDvN8uXLtWmOHz8eqF0sfjkkV/98QefqHCITcO7Ez0CnEyW3IAvdEQQvwRRkYJXWh3wgbjgcTlgzagCLco3kIKuKQjweT8yZkhsKU3+0YuJyPbKJzuLTtc/tu6A3TvR6yGtKH6MVIru3SARaLUXTxtW6a6HDtvp8wsLnQTyDIwBr1qzBnDlzsGDBAuzcuRPnnXceJk2ahL1792rTP/jgg2hoaLCPffv2oUePHrjmmmsc6crLyx3pGhoaUFZWFqht7PbMMZlGgZoCC9wGU10QjO61G2o5fgZnN5ean+AXN9zcs6o1Jw+5n6QF5zMC7cCfeNx2o6kBOqpA0PRCmUeVB31AqxUKAUK/g0k6/U8HPzcYqkjGiatYtp1eR+kCla5zQQKK1BsBCIFYsoxoNGpvTm6cGzSQYoV6wMLngzZyez7wwAO4+eab8dWvfhUAsHTpUrzyyitYtmwZFi9enJK+oqICFRUV9vv169fj448/xo033uhIZ1kWqqqqgrefwJZfgeFlNQWx4nSftZeLj+IQbegtHPq5Ll9rAmXphE8Xsa7coBZ7pgS12E03WbY1TNKGNNdTza9zcwa5CUjnOrHwdRwikQh27NiBiRMnOs5PnDgR27Zt81XGk08+iYsvvhj9+vVznD98+DD69euHU089FVdccQV27twZuH1s+XVAZPg9jRBMV1DkwEOf4Uc/0w160nqRr+Vf06Dld1cXNa9qiann1bb4CbJQ2ywP3TPipBUDwLHFll1/cpAHYFt8bnVLqynonGY2B3+dxar7jlVLV6Kuy1PFi1q44VAIFgmEkUto4pqlDKYAF6++c5BLjsgw2rOpqclxurS0FKWlpY5zH3zwAWKxGCorKx3nKysr0djY6FlVQ0MDXn75ZaxcudJx/owzzsDy5csxZMgQNDU14cEHH8S4ceOwa9cu1NTU+O4Ki19HJPkP72Vxuc57aawN1R1Ky6J/qejK8+pnVJRT5noCDva6utQy3RZC624OqCuSDuBq+XRNoKkO6cKT6UzXkQ7UccUdqEtPr4VOnNJFdw3VGw0q0uq1Vh92TG+E5M0CAMejqujavRiZ25OuTrVPftyc7O7MIRm6Pfv06eM4fc8992DhwoXaLLrftp+b+eXLl6N79+6YMmWK4/zo0aMxevRo+/24ceNw1lln4eGHH8ZDDz3k3YckLH55iJs1pqYB/FtgXmW61eE3vR9XqhtBREHOSwGtC/vVuk2uPlvwfLbTFhIfbdQJtfyrCkRQEdRdX/VmxU+ZbtYi9Uw4zovUh9Km6+q18wXKxfhGIKPtzfbt24fy8nL7tGr1AUDPnj0RDodTrLwDBw6kWIMp1QiBp556CtOnT0dJSYlr2lAohLPPPhvvvvuuz04k8wVKzbQ5mc4TmeZb1Eg9GdQAaObINJF81HLSuTBVi4eml8EnJgGkZVEB8+qnSjwZYdjS0mJbI7o1ajq8QvHVgd3tMPVRXgsZiUqvZTo3B+p3Qtd5ys9p+3V90ZVJ08gHz9IIzmg0ipbkdW6JROxz0pL2cnUa25U4EewiMP7IMNqzvLzccejEr6SkBCNGjMCmTZsc5zdt2oSxY8e6Nq+urg7vvfcebr75Zs+uCCFQX1+P3r17e6alsOXXgVHn/nSY5s1Mbk/dfJhdNrF0HOmgt0J0c0q6u31dnWqbzRfBXfxN18a2+BT3I3WD6trl5aZUz+msSbd0EipU6lMU1HKDWGqq5efHvWh6T+vX7f1J5zipq9NtOQMt19QeNzHW9sN3SkYSQ3rr1YPmmTt3LqZPn46RI0dizJgxeOKJJ7B3717MnDkTADB//nzs378fzz77rCPfk08+iVGjRmHw4MEpZd57770YPXo0ampq0NTUhIceegj19fV49NFHA7WNxS8PMc1xmcRJtUQceTXCpc6/2YOzZsAy5dVZfV7iZ3K1ZRvpnrM0g6w6F0YypaRRy3QbvE1zktlAZ5Xr6tS1x+vmwa0cIRJLGSCcGyp4tVUtn+m8TJs2DR9++CHuu+8+NDQ0YPDgwXjppZfs6M2GhoaUNX8HDx5EbW0tHnzwQW2Zn3zyCb7+9a+jsbERFRUVGD58OLZs2YJzzjknUNsskYe/wqamJlRUVKAE6c3Ztgdpt5NYXtD81WGyTKS7saioCMXFxSmWh3RV0TpCoZC9MXYsFrMHO53I6Vx+sl7VFUeDIWhfZHtodKXbUyhkflmG6ekLqssXgO1upHVQNzG9Zqr72LhhtuY7UDG5JqXVJF/7cXmrNxUhxXXtdh3U6ye/F/XpC+rvQbaZXpOWlhaHm9NkRZow3Th5kXeDlwYBIILEoE/n0XKBHDs/GDYM5SR4yXf+WAw96+vbpK25hi2/jo4QEFYi+EIOOF4Wg+nuOmVwUdx9NJ3cB1R1pVnQDzhuc1yWZTkWSbu5cO26NPWkMzjqoM84pIu65Y1GUITwH0gicbsOfssxuZNVy16dN6NtNd1MuVnlqrVPbxpMffHb184gZvkAP8uWxS8/IHNxQVBFkM7VxGIxWPE4oNz9ybt7aa3J161NSbgMoVgmRtGjBylDTZ2pELjVLZAIfqFlquWGQiGEZH2WlbKmz8/cX7puTFlKuuLp6kJN9kfeTNA5ZId7O2kxUptZvTmQ6al1Sp8RaWqnH+zfRP45ovISFj8WvzZD/ku3tZtWDeRQ3XSCDI7SzRcOh1FSUuLYv1HmisfjsIRAjJTlFhlpu+NUa1TTFvtv0lrx6/aTaVQxkMIthEBUiBRXIi2Xpg0lAzZUV6fjmmkI6uqz83jcRHj1XbX8UtLRv+T6SuQTKyzLgkgGBMWFgKXcMMi/6sNo6edebdWVR056dbk1qe+UjA4WPxa/vEUd7OU5rzzyr+N1PG4PivZAaTmXMZhclm6iR19T0RCGfI45M4/y3fqn1quWbUKd2/IK3sgVun6YAmi8hM8XmjJCSAx0Ope4aQG/2ocg1jyLWdvC4sfilzdIl5AaVGGyRLzEhQa2SNcWDUyheWhwRjgcdoS4q+XTgAv6Wp0fUq0+x0BJrCG1P34EXmvdkTro5/I6WJZlWzGqoEhLKO6yy4xbe9zmOE3nTWLnNqeaTNDaZmXzbRX5/YSsVPHTzedR74GXler3Jolh2gsWvzaGDgGB7tXlXJRHAEEiqbs1RgcuuuVXcXGxI7pR5rH3cgyHHQKhlqtbOE/bI+DiIiVWJ+2HbpD1G0ShXmvdgCz7T28G1GsghIAVjzselWTCj8Vjskh1+XQ3O/Qz6la2reVEYmf7lfocecn3pnvgrozMVSNcM7I2mXalrdb5dWRY/AoI08CsWkpywKNRkXRgVAVJZ8WplhOd21KxNMKXbn/UOSSdEOrKoUKYSfCKX2yrHUkR8TFfqHNBOtKKRGSwJZwBUn5cv+r3brLScwZbhm2KQHqu5s70LbH4tTGZDKkyOEUOFH7dZqbXatny7l5G8Ml1cHJNIN0eTB0Y5WAurSa6FgyAVjjtQZkEm8STIqlzr3m5d1U3rh08Y0hH08pdSWSbZXtkXl173NyTpjbS90IIRxCKvG5qf/3OnemeyODVLgFAkMAVudZTuoRNbmqvtri1m2l/4kjPiuM5P6b9IHf12XCBUuRdvz0XFAo5HvPjNgdEy6WuT3UNmE4s6CFiMe0/mJ85P1WU1McyqfVSYZbYD27VWJTZtIJSbgDgdIfqxIZ+D6Y06lZpdhqDdYnkDYdMK/dC1Qm9TuwdN1ZAynMM/QhgZ7Im8gUOeGHxy1u8BhZ1rsiU3zTI0rmfaDRqu+ggrQUlHx2Qdc+1U9tBA2JC6sBqsCJ0bfZzbbxuEtT2U+FUy/A65xeH9Zd0V9I2qv1V5/pkO01zgLQv6negEzBTv936mumNQJu4UxktLH4sfnmJmzUXxAp0c8fJ13LnfmrRmeqWgRH0nG4Alp+FwmGEXMrVBXv4HTDTtdKESEZ1UosJsINdTH0xlWWsQ3m4LrX8dMLm1l5ajozYdWw6nfwOda7MIBZtyu9Flwbern3VWtRapG75A6VmGD0sfnmMHGj8WIFBxSMejzssPJmXLl8w5dO2VePu1IXY69IGhV4PvyKi5lddpum0yc361t1oeN28+EGNspWCRy07N9e1qQ0OwTJdi3TazsLXLrDlx+LX5vi5M/ZfWOo2YRJTpGCQwVyWoLMM1EHSr7DqXKDqa11dQSw+XcCP+qw8LzefX9RISlq22ib5Wm1vihWpCRiiZUtkcBHQetMRiURsyy8WiyEuEo8bopafl7XnJnTGb8HSR+wGveli2gYWPxa/dkEdBjKOAFXe+5nb8poTpJ/RYBUaSanOMenyqoIjz3vNPaltTmcAle2l6xTVz9J1j8q26Q71mpnapgpwOBy2b47ka5B2yjrVNkhRi5FF+DRqV/2MtsF0TrSe8HMhXH/D2nr8ls3kBBY/Fr+CwxRN6CWAprK8hCMdt6OJdF2QuvQmEdGlcYvAVNO75THVo7tGch5QQH+jYnJNUkHVPR7JD4GubxrfLQtf+8Pix+LXrmRzFZTbgOI3mMRXPR5zVfSvSTRUS9CRJxRCSOMyVOtTy3VrK4AUi1WWI9fVqQEo6vP2pBWluw5qPiFEYruxZNt1mz+bLO+Qcv0c/U8kTuRJvtbN48kyvVy6RotMxeRJcC1dU19rxQFzKvmZjGHxY/HrPCjzfzoLwc0d6izK3c2oDqqq4MlD3d5MdZFSAZGiEbKsxGOWhEhph2W17jajlqHriyBl0AhIOv8n66Vp5Xm67Zfst8lVqz7/UOaRGweYXLlqP+Q5OuenCq3dXvJ9UBenm6VrnMOj5+X3mVKKO1qrVld+QFj0mFzA4tcJUYNqqIgEcUGaXHSe9Sui5TXvBctKPFtQpiUDOxUFKk66vri5cl3n9hRRVq1DVdB1FpV0U7rl93I/0jlVda2k3YfEC4dgq0cQpGuVWnfpeiTSnTtl2h62/JzPrswK0WgUd999N/r3748uXbpgwIABuO+++xwDhhACCxcuRHV1Nbp06YILLrgAb7/9drab0uERhiPzglstAzoHpAZ5pAysyuBpsiBMwS7UBSfXlsm/cucQ+Vq+b2lpQUskgubmZjQ3NyMSiSTSJdPKdWmybvlkiaKiIvvZg/TBuzrhAVqtI1keXcSfsuRCcYvKOoqLi1FcXIyi4mJH/WrdNE9RURFKSkocm4brrq90j0aS1+LYsWM4cuQIjh49ah/Hjh3DseTf48eP20dLS4tj6zkvYVS/Z0s5TJgCfLQ/QbTeyLDV1/GQ25sFPTqT+GXd8luyZAkef/xxPPPMMxg0aBDefPNN3HjjjaioqMDs2bMBAPfffz8eeOABLF++HJ/5zGfw/e9/HxMmTMDu3bvRrVu3bDcp75D/8BnPCVJXqGXZc1Aml1vm1emFUzf/R8/RJyro8qhrC2lZOmtHO5dF3Jo0AlQ7V0nqp+vmZDmWZSFuWQ6x11mI1OKT4muaBwWc+5+a3Jc0r5t70+t6BMnn5S3QWdlMxybdG+3O9M1mXfy2b9+OK6+8EpdffjkA4LTTTsOqVavw5ptvAkj8YyxduhQLFizAVVddBQB45plnUFlZiZUrV+KWW27JdpPyFtV9mVlhCfeibj4viCvUDTdB9ZpHVAdaVaBVkTLV4wedaNKNre39TDXPI3RY0nAKkW7ROE2vW2CuWqfpujDdvsNMv183d7lxjo/p0PAjjXIgfueeey4ef/xx/O1vf8NnPvMZ7Nq1C1u3bsXSpUsBAHv27EFjYyMmTpxo5yktLcX48eOxbds2Fj+FbAqgoAKonkdqcIwfoXELotEJYBDRpYInt02jlphXe03ooiPpfFxLS4td3nGNJSf7ovZNt5aOtokGv7hZrF5zpUH7mw2MNy2tCbJbX1ZLY1TY8suB+M2bNw8HDx7EGWecYT/89Ac/+AG+/OUvAwAaGxsBAJWVlY58lZWVeP/997VlyvkgSVNTU7ab3aHJugUIONyhdCcXLwsiiKtNJxRurlFdGfRzNY36pHiTdWiql4qgaq2pdch5PF07ZP1eT6mX9cnXvty1tB4lrV/xS8cV6sfqlME32aIzDaxMxyfr4rdmzRqsWLECK1euxKBBg1BfX485c+aguroaM2bMsNPprArTP/PixYtx7733ZrupDJCYF9QIoEmYMrU20s1PBYvO3bkJnqkM+l63Ewt9bYrsNJWvCqibW9OtbXZdHnX6wXQjokvnq7zWDGm3iWlf2O2ZA/H75je/iW9961v40pe+BAAYMmQI3n//fSxevBgzZsxAVVUVgIQF2Lt3bzvfgQMHUqxByfz58zF37lz7fVNTE/r06ZPtpndoTBZAdgpPDYxpfavfEi0TgloiOkHxU6bfct2gopuN/nvVmc0bDVpnUEsv21adsd6c18Do4KUOOVjqcPToUUd0HJDYp1DeQffv3x9VVVXYtGmT/XkkEkFdXR3Gjh2rLbO0tBTl5eWOg8kRVAhzgNscoV/UoBDV5agGlzjSCWH8LOWAc27EM70mWMUtgKUtBv4gQTN2nhy0Q1cHC1/7Ec/g6Cxk3fKbPHkyfvCDH6Bv374YNGgQdu7ciQceeAA33XQTgMQgN2fOHCxatAg1NTWoqanBokWL0LVrV1x77bXZbk6nxDRoZHNeULpCvYIuoKTxErF0BmO/yzJcP3MW2PoycGv84Sc61dJ8nilBr6/D3Zs4kdX2OOrKWclMUNjyy4H4Pfzww/jOd76DW2+9FQcOHEB1dTVuueUWfPe737XT3HXXXTh27BhuvfVWfPzxxxg1ahQ2btzIa/wyxG1wCTzEqq7Q5LnWU+anwOcSNzHxnIuSgpSDdjmryc6yg1xfS9M8Z1bryEmpTKbIRe7p5OssZN3t2a1bNyxduhTvv/8+jh07hv/93//F97//fZSUlNhpLMvCwoUL0dDQgOPHj6Ourg6DBw/OdlMYQkaDkBApguK1jCFT/O4mYilWnJU4mXLYi9ez1kJzu/2cUz/36me20d40MEwOeOyxx9C/f3+UlZVhxIgR+N3vfmdM+9prr2n/H/7617860tXW1mLgwIEoLS3FwIEDsW7dusDtyrr4MR2XTAc5Og9mv/dxmITM7TChS5uyvZjmSKcN2Wp3kJsCNUo0G4JonI+U9WV5uYI6V8p0PNTvKcgRhDVr1mDOnDlYsGABdu7cifPOOw+TJk3C3r17XfPt3r0bDQ0N9lFTU2N/tn37dkybNg3Tp0/Hrl27MH36dEydOhWvv/56oLZZIte+lRzQ1NSEiooKlCD3d/KdkZxdM7Jkwi1qUXWR+p3T864+u08M91NWNtqulpENETXly8a8Xt4NGB0cASAC4ODBgzkP5pNj56+HDcMJ5OHOfjkSi+HS+nrfbR01ahTOOussLFu2zD535plnYsqUKVi8eHFK+tdeew0XXnghPv74Y3Tv3l1b5rRp09DU1ISXX37ZPnfppZfipJNOwqpVq3z3hS2/AqStowy9XKSmaEiVtnAHZlJfJmsYdWsEMynf7zVlCpNMLb+mpibHQTchkUQiEezYscOxmxcATJw4Edu2bXNt3/Dhw9G7d29cdNFFePXVVx2fbd++PaXMSy65xLNMFRa/AiUnQ6KyTCCuLEXIxt6VbgKQi4E+qJszE5eu3/a4oXNrOq43iyGD9J7oQBfG9+nTBxUVFfahs+I++OADxGIx7W5ecqcvld69e+OJJ55AbW0t1q5di9NPPx0XXXQRtmzZYqdpbGwMVKYJfp5fASOQQxcoGYCpO1R1dbq5+SRtbfHlmkzds37yt9UidSY/yXSpw759+xxuz9LSUmMeXYS26X/69NNPx+mnn26/HzNmDPbt24cf//jHOP/889Mq0wRbfgVOmwyPxBpsPZWdheLtSXu0RbtYXhPIwsLH5BJ10xGd+PXs2RPhcDjFInPbzUvH6NGj8e6779rvq6qqMi4TYPFj0IYRegaBs3dkcfnMSyC9CLpswr0bqcIclCBrAb1uBlT3ZraFjyM4Ox9tEe1ZUlKCESNGOHbzAoBNmzYZd/PSsXPnTsdWmGPGjEkpc+PGjYHKBNjtyWjIqTvUtWJhu0mhtEG3oJ5+li3XaLYjRk241UFdwzorz37dejK7bctqaUxHpK02tp47dy6mT5+OkSNHYsyYMXjiiSewd+9ezJw5E0Bi3+b9+/fj2WefBQAsXboUp512GgYNGoRIJIIVK1agtrYWtbW1dpmzZ8/G+eefjyVLluDKK6/Ehg0bsHnzZmzdujVQ21j8GC1yAGwvEaRtUMUwnUAZ3bIKk2B6LV8wiZKfYJQguFmV7NpkMqGttjebNm0aPvzwQ9x3331oaGjA4MGD8dJLL6Ffv34AgIaGBseav0gkgjvvvBP79+9Hly5dMGjQILz44ou47LLL7DRjx47F6tWrcffdd+M73/kOPv3pT2PNmjUYNWpUoLbxOj/GN3lxrUlwTeJtapSo36hLV6urDdYTtpfA5d2AkOe0xzq/54YNQ9c01vkdjcVwTYB1fh0ZtvyYzoUQjo2rpUWmWmY6S1D9zO/79Jvq4vpMJMhKPUFg4SsMeGNrFj8mAHRgtAzndZ+3NQ5RkcIHd8HzVVYOcJTeTk4YFjymEGHxY9LCa8A0CWWbo84fon2WKLQHhdFLJh3Y8mPxYxiGKThY/Fj8mDZAtUDyInAmj2GLj/GirZY6dGRY/Jg2p93WEXZiWPCYIKS7YUFn+p2x+DHtAluD2aMzDUgM01aw+DEdgkwGcDfhzGeRZVFjcgW7PVn8mE6A6kZl0WAYdzjghcWPKTDyZb6RBZzJJSx+LH5MJyGIWGQqLKp4piuoLHBMeyGQnpB1pt8six/DZIAgf4MIYGcaRJj8gy0/Fj+GCYxJuFjQGCZ/YPFjGIYpMNjyY/FjGIYpOFj8WPwYhmEKDhY/Fj+GYZiCg8WPxY9hGKbg4B1egFB7N4BhGIZh2hq2/BiGYQoMfqoDix/DMEzBEUd6Lkye82MYhmHyFrb8WPwYhmEKDg54YfFjGIYpOHipA0d7MgzDMAUIW34MwzAFBlt+LH4MwzAFB4sfuz0ZhmEKjlgGR1Aee+wx9O/fH2VlZRgxYgR+97vfGdOuXbsWEyZMwCmnnILy8nKMGTMGr7zyiiPN8uXLYVlWynH8+PFA7WLxYxiGKTBEBkcQ1qxZgzlz5mDBggXYuXMnzjvvPEyaNAl79+7Vpt+yZQsmTJiAl156CTt27MCFF16IyZMnY+fOnY505eXlaGhocBxlZWWB2sZuT4ZhmAKjrZY6PPDAA7j55pvx1a9+FQCwdOlSvPLKK1i2bBkWL16ckn7p0qWO94sWLcKGDRvwwgsvYPjw4fZ5y7JQVVUVtPkO2PJjGIZhsk4kEsGOHTswceJEx/mJEydi27ZtvsqIx+M4dOgQevTo4Th/+PBh9OvXD6eeeiquuOKKFMvQDyx+DMMwBUgmLs+mpibH0dzcnFL+Bx98gFgshsrKSsf5yspKNDY2+mrjT37yExw5cgRTp061z51xxhlYvnw5nn/+eaxatQplZWUYN24c3n33Xd99B1j8GIZhCo54BgcA9OnTBxUVFfahc2FKLMtyvBdCpJzTsWrVKixcuBBr1qxBr1697POjR4/Gddddh6FDh+K8887Dr371K3zmM5/Bww8/7LP3CXjOj2EYpsDIdM5v3759KC8vt8+XlpampO3ZsyfC4XCKlXfgwIEUa1BlzZo1uPnmm/Hcc8/h4osvdk0bCoVw9tln597y27JlCyZPnozq6mpYloX169c7PhdCYOHChaiurkaXLl1wwQUX4O2333akaW5uxu23346ePXvihBNOwOc//3n885//DNoUhmEYJg0yjfYsLy93HDrxKykpwYgRI7Bp0ybH+U2bNmHs2LHGtq1atQo33HADVq5cicsvv9y7L0Kgvr4evXv39kxLCSx+R44cwdChQ/HII49oP7///vvxwAMP4JFHHsEbb7yBqqoqTJgwAYcOHbLTzJkzB+vWrcPq1auxdetWHD58GFdccQVisc60bSrDMEzHpK3W+c2dOxe/+MUv8NRTT+Gdd97BHXfcgb1792LmzJkAgPnz5+P666+3069atQrXX389fvKTn2D06NFobGxEY2MjDh48aKe599578corr+Dvf/876uvrcfPNN6O+vt4u0y+B3Z6TJk3CpEmTtJ8JIbB06VIsWLAAV111FQDgmWeeQWVlJVauXIlbbrkFBw8exJNPPon/+q//ss3ZFStWoE+fPti8eTMuueSSoE1iGIZhOiDTpk3Dhx9+iPvuuw8NDQ0YPHgwXnrpJfTr1w8A0NDQ4Fjz97Of/QzRaBSzZs3CrFmz7PMzZszA8uXLAQCffPIJvv71r6OxsREVFRUYPnw4tmzZgnPOOSdQ2ywhRNqPaLIsC+vWrcOUKVMAAH//+9/x6U9/Gn/84x8dazKuvPJKdO/eHc888wx++9vf4qKLLsJHH32Ek046yU4zdOhQTJkyBffee69nvU1NTaioqEAJAO9pU4ZhmI6LABABcPDgQcc8Wi6QY+ftw4ahNBwOnL85FsPD9fVt0tZck9WAFzmxqQttff/99+00JSUlDuGTaUzhr83NzY5Q2qampmw2m2EYpqDgvT1ztNQhndBWtzSLFy92hNX26dMna21lGIYpNDJd6tAZyKr4ye1m3EJbq6qqEIlE8PHHHxvTqMyfPx8HDx60j3379mWz2QzDMAUFi1+Wxa9///6oqqpyhLZGIhHU1dXZoa0jRoxAcXGxI01DQwP+/Oc/G8NfS0tLU0JrGYZhmPQQSE/40g4Q6YAEnvM7fPgw3nvvPfv9nj17UF9fjx49eqBv376YM2cOFi1ahJqaGtTU1GDRokXo2rUrrr32WgBARUUFbr75Zvznf/4nTj75ZPTo0QN33nknhgwZ4rmYkWEYhmGyQWDxe/PNN3HhhRfa7+fOnQugNRT1rrvuwrFjx3Drrbfi448/xqhRo7Bx40Z069bNzvPTn/4URUVFmDp1Ko4dO4aLLroIy5cvRziN6COGYRgmGG31VIeOTEZLHdoLXurAMExnoT2WOtw0bBhK0jA2IrEYnuKlDgzDMEw+wpYfix/DMEzBwev8WPwYhmEKDhY/fp4fwzAMU4Cw5ccwDFNgsOXH4scwDFNwsPix+DEMwxQccoeXdPJ1Flj8GIZhCgy2/Fj8GIZhCg4WP472ZBiGYQoQtvwYhmEKDLb8WPwYhmEKjhjSc/vx9mYMwzBM3iKQXuQmR3syDMMweQtbfix+DMMwBQdbfhztyTAMwxQgbPkxDMMUGOz2ZPFjGIYpOHh7MxY/hmGYgoPX+bH4MQzDFBwsfix+DMMwBUcMgJVmvs4CR3syDMMwOeOxxx5D//79UVZWhhEjRuB3v/uda/q6ujqMGDECZWVlGDBgAB5//PGUNLW1tRg4cCBKS0sxcOBArFu3LnC7WPwYhmEKDJHBEYQ1a9Zgzpw5WLBgAXbu3InzzjsPkyZNwt69e7Xp9+zZg8suuwznnXcedu7ciW9/+9v4xje+gdraWjvN9u3bMW3aNEyfPh27du3C9OnTMXXqVLz++uuB2mYJIfIugKepqQkVFRUoQXqmO8MwTEdBAIgAOHjwIMrLy3Nalxw7xw4bhqJwOHD+aCyGbfX1vts6atQonHXWWVi2bJl97swzz8SUKVOwePHilPTz5s3D888/j3feecc+N3PmTOzatQvbt28HAEybNg1NTU14+eWX7TSXXnopTjrpJKxatcp3X/LS8pN6ncndCx988MFHRzkAoC3tkJZYDJE0jpZYYtavqanJcTQ3N6fUEYlEsGPHDkycONFxfuLEidi2bZu2Xdu3b09Jf8kll+DNN99ES0uLaxpTmSbyMuDl0KFDAICWdm4HwzBMtjh06BAqKipyWkdJSQmqqqrwxltvpV3GiSeeiD59+jjO3XPPPVi4cKHj3AcffIBYLIbKykrH+crKSjQ2NmrLbmxs1KaPRqP44IMP0Lt3b2MaU5km8lL8qqursW/fPggh0LdvX+zbty/n7oK2pqmpCX369OG+5Rnct/ykPfsmhMChQ4dQXV2d87rKysqwZ88eRCKRtMsQQsCynBNOpaWlxvRqWl1+r/Tq+aBl6shL8QuFQjj11FPR1NQEACgvL+90/4wS7lt+wn3LT9qrb7m2+ChlZWUoKyvLeT09e/ZEOBxOscgOHDiQYrlJqqqqtOmLiopw8sknu6YxlWkiL+f8GIZhmI5NSUkJRowYgU2bNjnOb9q0CWPHjtXmGTNmTEr6jRs3YuTIkSguLnZNYyrTRF5afgzDMEzHZ+7cuZg+fTpGjhyJMWPG4IknnsDevXsxc+ZMAMD8+fOxf/9+PPvsswASkZ2PPPII5s6di6997WvYvn07nnzySUcU5+zZs3H++edjyZIluPLKK7FhwwZs3rwZW7duDdY4kcccP35c3HPPPeL48ePt3ZSsw33LT7hv+Uln7lt78+ijj4p+/fqJkpIScdZZZ4m6ujr7sxkzZojx48c70r/22mti+PDhoqSkRJx22mli2bJlKWU+99xz4vTTTxfFxcXijDPOELW1tYHblZfr/BiGYRgmE3jOj2EYhik4WPwYhmGYgoPFj2EYhik4WPwYhmGYgiNvxS/oYzI6IosXL8bZZ5+Nbt26oVevXpgyZQp2797tSCOEwMKFC1FdXY0uXbrgggsuwNtvv91OLU6fxYsXw7IszJkzxz6Xz33bv38/rrvuOpx88sno2rUrhg0bhh07dtif52vfotEo7r77bvTv3x9dunTBgAEDcN999yEeb32Mab70bcuWLZg8eTKqq6thWRbWr1/v+NxPP5qbm3H77bejZ8+eOOGEE/D5z38e//znP9uwF0zOCBwf2gFYvXq1KC4uFj//+c/FX/7yFzF79mxxwgkniPfff7+9mxaISy65RDz99NPiz3/+s6ivrxeXX3656Nu3rzh8+LCd5oc//KHo1q2bqK2tFW+99ZaYNm2a6N27t2hqamrHlgfjD3/4gzjttNPEZz/7WTF79mz7fL727aOPPhL9+vUTN9xwg3j99dfFnj17xObNm8V7771np8nXvn3/+98XJ598svif//kfsWfPHvHcc8+JE088USxdutROky99e+mll8SCBQtEbW2tACDWrVvn+NxPP2bOnCk+9alPiU2bNok//vGP4sILLxRDhw4V0Wi0jXvDZJu8FL9zzjlHzJw503HujDPOEN/61rfaqUXZ4cCBAwKAvQ4mHo+Lqqoq8cMf/tBOc/z4cVFRUSEef/zx9mpmIA4dOiRqamrEpk2bxPjx423xy+e+zZs3T5x77rnGz/O5b5dffrm46aabHOeuuuoqcd111wkh8rdvqvj56ccnn3wiiouLxerVq+00+/fvF6FQSPz6179us7YzuSHv3J7pPCYjXzh48CAAoEePHgASD3ZsbGx09LW0tBTjx4/Pm77OmjULl19+OS6++GLH+Xzu2/PPP4+RI0fimmuuQa9evTB8+HD8/Oc/tz/P576de+65+M1vfoO//e1vAIBdu3Zh69atuOyyywDkd98ofvqxY8cOtLS0ONJUV1dj8ODBedVXRk/ebW+WzmMy8gEhBObOnYtzzz0XgwcPBgC7P7q+vv/++23exqCsXr0af/zjH/HGG2+kfJbPffv73/+OZcuWYe7cufj2t7+NP/zhD/jGN76B0tJSXH/99Xndt3nz5uHgwYM444wzEA6HEYvF8IMf/ABf/vKXAeT390bx04/GxkaUlJTgpJNOSkmTz2MNkyDvxE+SjUdadCRuu+02/OlPf9LuT5ePfd23bx9mz56NjRs3uu4gn499i8fjGDlyJBYtWgQAGD58ON5++20sW7YM119/vZ0uH/u2Zs0arFixAitXrsSgQYNQX1+POXPmoLq6GjNmzLDT5WPfdKTTj3ztK+Mk79ye6Twmo6Nz++234/nnn8err76KU0891T5fVVUFAHnZ1x07duDAgQMYMWIEioqKUFRUhLq6Ojz00EMoKiqy25+PfevduzcGDhzoOHfmmWdi7969APL7e/vmN7+Jb33rW/jSl76EIUOGYPr06bjjjjuwePFiAPndN4qfflRVVSESieDjjz82pmHyl7wTv3Qek9FREULgtttuw9q1a/Hb3/4W/fv3d3zev39/VFVVOfoaiURQV1fX4ft60UUX4a233kJ9fb19jBw5El/5yldQX1+PAQMG5G3fxo0bl7Ik5W9/+xv69esHIL+/t6NHjyIUcg4L4XDYXuqQz32j+OnHiBEjUFxc7EjT0NCAP//5z3nVV8ZAu4XaZIBc6vDkk0+Kv/zlL2LOnDnihBNOEP/4xz/au2mB+D//5/+IiooK8dprr4mGhgb7OHr0qJ3mhz/8oaioqBBr164Vb731lvjyl7/cIcPK/UCjPYXI37794Q9/EEVFReIHP/iBePfdd8Uvf/lL0bVrV7FixQo7Tb72bcaMGeJTn/qUvdRh7dq1omfPnuKuu+6y0+RL3w4dOiR27twpdu7cKQCIBx54QOzcudNeEuWnHzNnzhSnnnqq2Lx5s/jjH/8oPve5z/FSh05CXoqfEO6PycgXAGiPp59+2k4Tj8fFPffcI6qqqkRpaak4//zzxVtvvdV+jc4AVfzyuW8vvPCCGDx4sCgtLRVnnHGGeOKJJxyf52vfmpqaxOzZs0Xfvn1FWVmZGDBggFiwYIFobm620+RL31599VXt/9eMGTOEEP76cezYMXHbbbeJHj16iC5duogrrrhC7N27tx16w2QbfqQRwzAMU3Dk3ZwfwzAMw2QKix/DMAxTcLD4MQzDMAUHix/DMAxTcLD4MQzDMAUHix/DMAxTcLD4MQzDMAUHix/DMAxTcLD4MQzDMAUHix/DMAxTcLD4MQzDMAUHix/DMAxTcPx/0d+HYEtjo9UAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 700x400 with 2 Axes>"
       ]
@@ -220,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "id": "120fc47a",
    "metadata": {},
    "outputs": [
@@ -230,13 +221,13 @@
        "Text(0.5, 1.0, 'normalized signal as function of b-value')"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 1500x400 with 2 Axes>"
       ]
@@ -279,13 +270,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "8ddef255-88b6-4c79-8f6c-4ee85e931588",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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CogMmTJigTZs2ac2aNU43pVEKl5Taho/9Fa6YRSS+C1vnD8yI2jmDviHx7PvfC7twKP0wB7WufbHpCQWAyMMcRJxQQVGJ1mz7zra0jRkOVm2pUO+zk2yFKzU1Zc6gWfTi77VNKXpx0pxxfXT2/e/ZHoeThsxBBQBEFgIiTsgMh1ldk21LzqzaUmEbRva3d7JvqGiMmpXTNd8jP0zCoSS/cxDDOSQ+vbRM1R4v4RAAIhhDzDih3mcnWcOkZg+huRdzVtdk9T47KeALW/sWxfi+Z7j1WvnOOdz2xNBacxLDSUPnoAIAwp/LMIzonBwWAqqqqpSYmKjKykolJCQ43ZwTMgOaGRJ8g5q5zE3N8Ga+pk+XJM29s/FLutT3nqGuroKUcCxUkcL7XgAAjmlo9qAHEQ1WXw/SJWnJfgOD2RN4SVpywN8z1H1TcVCpbVrWCoFzxvVRapuW+qbioEMtazzf3luzd5gtDwEgchEQ0WD1VTFPqqc3yXf3lUC+Z6i7qXcnle877Lf6t3zfYd3Uu5NDLWscf0P7/qYAAAAiB0UqaJCaIcF3zmFz9eo58Z6BFCnVv757b/ti20MAiFwERJxQXT1IkpotsDnxns0hEqp/I2HbQwBA4zDEjBOqrwepuRbBXlG217asju97ZnVN1oqyvQF/z+YSzvMoAQDRiYCIE2qu+YX16XdOW9uyOiZzeZ1+54TP3s7hPI8SABCdGGJGSIqU+XvhPo8SABCdCIgIWeE+f8/f2pC+n6l4894mrQ0JAEBzY4gZIY35ewAABB8BESEtnOfvzb2zb73bBYZL72FBPWsdFi4pVcHxIXM0L+4DgGBiiBkhKxLm74X7MLkkuWNcfr/vvvcHzY/7ACCYCIgISZGyDqJ0rJ1mOAzHYfJIKRgKd9wHAMFEQERIiqTdO/wNk4fbL/NI6AmNBNwHAMHiMgwjfH7TRpiqqiolJiaqsrJSCQkJTjcHzaCuYfJw/aWeMWWhFXZLpg5xujlRi/sAoKkamj0oUgGaSV3D5DULV8JFOBcMRRLuA4BgYIgZaCaRNkwe7gVDkYD7ACBYCIhAM6lvC8Jw+mUeSQVD4Yz7ACCYCIgA6hVJPaHhjPsAIJgoUnEQRSoAACCYKFIBEBDs4AEA0YeACDSTSAlW5g4eNT+LOSfOHeNyqGUAgObCHESgmUTK1mjs4AEA0YeACDSTSApW4b6DR8Hxnk5/7S1cUiqP16i36hwAog0BEWhG4R6sfIXzntKR0psLAMHCHESgmeXlpFu7XoRbsPIVzjt4+NvBJlx7cwEgGOhBdMCMGTM0Y8YMeTwep5uCIPAXrMItkETCDh6R1JsLAM2NdRAdxDqIka+uYBVOwaSuNofjZ5GkjCkLrcBeMnWI082JOswHBZzV0OxBDyLQTCJla7RI2sEjEnpzwx3zQYHwQEAEmkmkBKtI3VM6HIfJI0EkVfcDkYwhZgcxxAwER6QNk0cC83tv9uZyD4DgYKs9ADhuRdleZXVN9tubm9U1WSvK9jrUsoaLlJ15TJFS3Q9EKgIigIjX75y2Kt5c4Xe7wOLNFep3TluHWtZwkbblYTgvmwREA+YgAoh4kTDvLRI+g4n5oEDoYw6ig5iDCARHgU8PW815b5LCammVcJ+7x3xQwFnMQQSA43yXVvGd9yYp7IZnw33uXiTMBwWiAQERQMTz3WrPd95bOPZYhfvcvUiYDxoJIq3oCYHHHEQACBORMHcvkuZShjMWLMeJEBABRDzfX3rmPsxx7hjdPeCcsAlYkbIzj8S+2KGAoI4TISACiHjmrjaSbMOzkpQ/MCMsdrWJlJ15THk56bawTiAJPoI66sMcRAARz6xQNntHSqYOseYk+j4fyibV84s7Lyc9LD6Dr3CfSxkpwr3oCc2HHkQAES+ShmcjQSTMpYwU/oI69wASARFAFIi04dlwRlgPHQR11IeACKBe5iLT/n5hFC4pDYtFputrH78Ig4uwHhoI6jgRAiKAerEcBhB5COo4EQIigHqxHAYCiT84QgO96jgRAiKAE2I5DAQKf3CEhkiYOoLmRUAE0CCsW4dA4Q8O59GTixNhHUQADcK6dQgk1t9zlu/+5ObPMj258NXoHsSvv/5ar776qj766CNt27ZNhw4d0hlnnKGePXvqqquu0k9+8hO1aNGiOdoKwCEsh+G8SBsSZP0959GTi/o0uAdx/fr1GjhwoC688EJ9+OGH6t27tyZOnKhHH31Ut9xyiwzD0JQpU5SSkqLf//73OnLkSHO2G0CQ3Dxzpd/lMMzeh5tnrnS4hdHBHBKs2XNrhnV3jMuhljWe7x8cvrva0CsdfPTkoi4N7kG89tpr9atf/Urz5s1TUlJSneetXLlSBQUF+uMf/6gHHnggII0EgGgXKcUdrL8XWujJRV0aHBBLS0sVFxd3wvP69u2rvn37qrq6+qQaBiA0zL2zb60h5XAMJpEgEoYEWX8vdDB1BPVxGYbBT6NDqqqqlJiYqMrKSiUkJDjdHKBe5i8Ps6ch3IJJJMmYstDq9SmZOsTp5iAM1fVHHn/8Rb6GZo9GF6kcPHhQc+bMUXFxsXbv3i2Xy6X27durX79+GjFihFq1anVSDQcQWnyLI2oucxOOxRHhjiFBBAI9uTiRRvUgbtq0SQMHDtShQ4fUv39/tW/fXoZhaM+ePVq+fLlatWql999/X927d2/ONkcMehARDswehayuySreXGEFE/MxPQ3BU9eQIPcAQEM1Sw/ihAkTdPnll+ull16qNR+xurpat956qyZMmKBly5Y1rdUAQk5eTrpWbalQ8eYKZXVN1pxxfTRy1irrcTgEk0hYIobiDgDB1KiA+Mknn+jTTz/1W6wSFxenBx54QBdffHHAGgfAeYVLSq0wWLy5wpr/Zj4OhyHOSNg1giFBAMHUqIDYpk0blZaW1jmEXFZWpjZt2gSkYQBCg28w8S2OmDOuj9X7FuoiYYmY+no4w6H9AMJLowLiuHHjNHbsWD344IMaOHCg2rdvL5fLpd27d6uoqEiPP/64Jk6c2ExNBeAEM5iEe3FEJCwRAwDB0qiA+Mgjj6hly5aaPn26Jk+eLJfr2Mr9hmGoQ4cOuv/++zV58uRmaSgA54T7emlUYgNA4zR6mZv77rtP9913n7Zu3ardu3dLkjp06KC0tLSANy5SzZgxQzNmzJDH43G6KcAJRUJxhDkHcdWWClsvqFlsEw5zEAEgmBodEE1paWlWKDx69KgOHDig0047LWANi2QTJkzQhAkTrFJzIJRFQnGEx2sotU1Lv5XYqW1ahsVnAIBgimnMyQsWLNBf//pX27GpU6fqtNNO0+mnn65BgwZp3759AW0gAGdNqmeeXl5OelgMza7Z9p3K9x22QmLGlIVWOCzfd1hrtn3ndBMBIKQ0KiA++eSTqqqqsh4XFxfrN7/5jR566CH9/e9/V3l5uR599NGANxIATkbvs5OU1TVZ5fsOy+1yqdrjldvlUvm+w8rqmqzeZyc53cQTKigqUeGSUr/PFS4pVcHx4X4ACIRGBcQvvvhCWVlZ1uPXXntNAwcO1JQpU3T99dfrj3/8o955552ANxIATsakgRmaM66Psromy3N88yiPYVjDzeHQC2rOo6wZEs05ou4Yl0MtA3AyQvWPv0YFxP379ys5Odl6/PHHH2vAgAHW4x/96EfauXNn4FoHAAFiLvjtPr76gtvlshb6Dgd5OenKH5hhC4nhtpYjgNpC9Y+/RhWppKSk6Msvv1SnTp104MABffbZZyooKLCer6io0KmnnhrwRgLAyahvP+lwqcSWWMsRiEQer1Hr3yLff7OcKqJrVA/iDTfcoIkTJ+qvf/2rxo0bpw4dOqhPnz7W859++qnOPffcgDcSAE6G+Q+wuaRNydQhyh+YYVU1h1MVc15OuhVwzbUcAYQvd4zL+rdoelGJMqYstP1BGxY9iA8//LB27typvLw8dejQQa+88orcbrf1/Kuvvqphw4YFvJEAcDLMf4DrWsuxT5fk+l4eUsJ9RxsAdr7/FvkW0dX8NyvYGhUQvV5vrWVufC1btuykGwQAgRYJazlK4b+jDQD/8nLStWpLhYo3V0j6oYjOyZ/rRgXEtm3bKjs7W8OHD1dubq5SUlKaq10AEDD1VSmHS7CKhB1tAPjnW0TnMQxbEZ1TP9eNmoP49ddf6+qrr9Zrr72mtLQ09e7dW48++qj+9a9/NVf7AACqvxc0f2BG2PSCArCzFaQYhuLcMVYPor/q5mBxGYbRpH9VKisrtWDBAr311lv65z//qTZt2ig3N1fDhw9X//79bXMT4Z+51V5lZaUSEhKcbg4AAAiygqISrdn2nW3OoW9o7H12UkDXam1o9mhUD6KvxMREjRgxQnPnztXevXv1/PPPy+v16rbbbtMZZ5yhv/3tb029NAAAQFSoq4jOXGnBqSrmJvcg1mf9+vU6evSoevfuHehLRxR6EAEAiG4FxxfD9jfXsHBJqTxew5EexEYFxO+++06HDh1Sx44drWMbN27Uk08+qYMHD+raa6/VyJEjT67lUYSACAAAgqlZhpgnTJig6dOnW4/37Nmjyy67TGvWrNGRI0d066231rsMDgAAcF6o7v+L0NGogLhq1Srl5uZaj19++WUlJSVpw4YNeuutt/T4449rxowZAW8kAAAInFDd/xeho1EBcffu3UpLS7MeL126VNddd51iY48tp5ibm6vS0vDY+B4AgGhlFkH4hkR/a20iejVqoeyEhAR9//336ty5syRp9erVuv32263nXS6Xjhw5EtgWAgCAgPNdaP3ppWWq9ngJh7A0qgfx4osvVmFhobxer1577TXt379fAwYMsJ4vKSlRampqwBsJAAACLy8n3drXO84dQziEpVEB8dFHH9Vbb72lli1b6qabbtLkyZPVpk0b6/m5c+eqf//+AW8kAEQ7igrQHAqXlFrhsNrjdWzXDoSeRg0xX3TRRfryyy9VXFysDh066JJLLrE9f/PNN6t79+4BbSAA4IeiAsm+57LvvDGgMWrOOTQfS+zrjUYGREk644wzNHz4cL/PDR069KQbBACozXe+mPmYogI0lb//dvz9N4bo1eCAOHfuXN18880NOre8vFzbt29Xv379mtwwAIAdRQUIFI/X8PvfjvnY4w34JmsIMw3eSaV///769ttvddtttyk3N1fdunWzPV9ZWakVK1bolVde0eLFi/XCCy9o2LBhzdLoSMFOKgCaImPKQmveWMnUIU43B0AYCfhOKsuXL9eTTz6ppUuXqkePHkpISFB6errOP/98dezYUcnJybr99tt19tln64svviAcAkAzCPeiAoptgPDQqDmI11xzja655hpVVFTo448/1rZt23T48GG1bdtWPXv2VM+ePRUT06jCaABAA0VCUQHFNkB4aHSRiiQlJyfXWagCAAi8SCkqoNgGCA9NCogAgOCKpKICim2A0NfgIhVfbdq0kctVeyNvl8ul+Ph4nXPOObr11lt12223BaSRkYoiFQDRjGIbIPgCXqTi6ze/+Y1iYmI0dOhQ/fa3v9UjjzyioUOHKiYmRhMmTFBGRobuuusuzZo1q8kfAADwg0gr7gj3Yhsg0jVpiPnjjz/WY489pvHjx9uOP//883r//ff1+uuv64ILLlBhYaHGjRsXkIYCQDSLpOKOSCi2ASJdk3oQFy1apCuvvLLW8ZycHC1atEiSdPXVV2vLli0n1zoAgKRjwSl/YIam+/QkhmNxR13FNjU/GwBnNSkgJiUl6Z133ql1/J133lFSUpIk6eDBg2rduvXJtS7MXHfddWrTpo1uuOEGp5sCIAL5BqmMKQvDLhxK9Rfb5A/MCKtiGyCSNWmI+aGHHtJdd92lZcuW6eKLL5bL5dLq1au1YMECPffcc5KkoqIi9e/fP6CNDXV5eXn62c9+ppdeesnppgCIUHk56Vblb5w7JqzCoSRNqmcoPNw+CxDJmtSDOG7cOC1fvlytWrXS/Pnz9dprr+nUU0/V8uXLdfvtt0uSfvGLX2jevHkBbWyoy87OjrpeUwDBRXEHgGBo8rYn/fr106uvvqp169Zp/fr1evXVV5WVldWka+3YsUO33HKLkpOTdeqpp+qiiy7S2rVrm9q0Wj788EMNGzZMKSkpcrlcevPNN/2e98wzzygtLU3x8fHKzMzURx99FLA2AMDJ8p2/VzJ1CPP2ADSbJi+U7fF49Oabb+rLL7+Uy+VS9+7dlZubK7fb3ajr7Nu3T/369VN2drYWLlyodu3aafPmzTr99NP9nr9ixQpdfPHFOuWUU2zHv/rqK51++unq0KFDrdccPHhQF154oW677Tb95Cc/8XvdefPmaeLEiXrmmWfUr18/Pf/88xoyZIg2bdqkTp06SZIyMzN15MiRWq99//33lZKS0qjPDQCNESk7qQAID00KiGVlZbr66qu1Y8cOnXvuuTIMQyUlJUpNTdV7772nrl27Nvhav//975WamqrZs2dbx84++2y/53q9Xk2YMEHp6emaO3euFUZLSkqUnZ2tSZMmafLkybVeN2TIEA0ZUv8irNOnT9ftt9+uO+64Q5L01FNPadGiRXr22Wc1bdo0SQporyYANEYk7aQCIPQ1aYg5Ly9PXbt2VXl5uTXEvH37dqWlpSkvL69R13r77bfVq1cv3XjjjWrXrp169uxZ5wLbMTExWrBggdavX68xY8bI6/Vq8+bNGjBggHJzc/2Gw4aorq7W2rVrNWjQINvxQYMGqbi4uEnXrM+MGTPUvXt39e7dO+DXBhCZJtVTrZyXk15v8QcANFaTAuLy5cv1hz/8wVrSRpKSk5P1xBNPaPny5Y261pYtW/Tss88qPT1dixYt0vjx45WXl6eXX37Z7/kpKSlaunSpVqxYoZEjR2rAgAHKycmxqqebYu/evfJ4PGrfvr3tePv27bV79+4GX+eqq67SjTfeqAULFqhjx45as2aN3/MmTJigTZs21fk8AACAk5o0xNyiRQvt37+/1vEDBw4oLi6uUdfyer3q1auXHn/8cUlSz549tXHjRj377LMaM2aM39d06tRJL7/8svr3768uXbrohRde8Ls3dGPVvIZhGI26rrlIOAAAQDhrUg/iNddcozvvvFOffPKJDMOQYRhatWqVxo8fr9zc3EZd68wzz1T37t1tx7p166bt27fX+Zpvv/1Wd955p4YNG6ZDhw5p0qRJTfkYlrZt28rtdtfqLdyzZ0+tXkUAAIBI16SAWFhYqK5du6pv376Kj49XfHy8srKydM455+ipp55q1LX69eunr7/+2naspKREnTt39nv+3r17lZOTo27dumn+/PlaunSp/v73v+uXv/xlUz6KJCkuLk6ZmZkqKiqyHS8qKmry0j0AAADhqklDzKeffrreeustlZWV6csvv5RhGOrevbvOOeecRl9r0qRJysrK0uOPP66f/vSnWr16tWbOnKmZM2fWOtfr9Wrw4MHq3Lmz5s2bp9jYWHXr1k2LFy9Wdna2zjrrLL+9iQcOHFBZWZn1eOvWrdqwYYOSkpKsJWzy8/M1evRo9erVS3379tXMmTO1fft2jR8/vtGfCQAAIJy5DMNo0NoI+fn5Db7o9OnTG9WId999V7/+9a9VWlqqtLQ05efna9y4cX7PLSoq0mWXXab4+Hjb8Q0bNig5OVmpqam1XvPBBx8oOzu71vGxY8fqxRdftB4/88wz+sMf/qBdu3apR48eKigo0OWXX96oz9IYVVVVSkxMVGVlpRISEprtfQAAAKSGZ48GB0R/AcvvBV0uLV26tGGtjHIERADRpqCoRO4Yl98lewqXlMrjNViyB2hGDc0eDR5iXrZsWUAaBgCIXu4Yl9+dX3x3igHgvCZvtQcAQGP52x7Q3zaCAJzV4CFmBB5DzACijTnELB0LiXHuGFV7vFbPIUPMiDbBnnbR0OzRpGVuAABoCt8hZjMcxrmP/Sqa7hMegWhh/kwULim1HTd71p36mWCIGQAQNDWHmM2QyBAzolWoTrsgIAIAADjINyQ+vbTMmnbh5B9MDDEDAILGt2fEd4g5f2CG32E2IFrk5aTbfiac7k0nIAIAgsbjNayCFPMXYbXHK0nKH5ghj5e6yWAoqCeMFy4pVcHx4U4ET+GSUtvPhNN/LBEQAQBBY1Zjmr2IJVOHWL2Hvs+jeYVqYUS08u1Z9/2ZcDIkMgcRABA0/ibf+5ukj+YVqoUR0ShUfyYIiACAoDGHmGv+wjMfM8QcPKFYGBGNQvVngoWyHcRC2QAAp2VMWWjNfSuZOsTp5qCZsVA2AACoV6gVRiB0MMQMAEAUqjn3zXwsMQ8UBEQAAKJOqBZGIHQQEAEAiDKhWhiB0EGRioMoUgEAAMFEkQoAAACahIAIAAAAGwIiAAAAbAiIAAAAsCEgAgAAwIaACAAAABsCIgAAAGwIiAAAALAhIAIAAMCGgAgAAAAbAiIAAABsCIgAAACwISACAADAhoAIAAAAGwIiAAAAbAiIAAAAsCEgAgAAwIaACAAAABsCIgAAAGwIiAAAALAhIAIAEGUKikpUuKTU73OFS0pVUFQS5BYh1BAQAQCIMu4Yl6b7CYmFS0o1vahE7hiXQy1DqIh1ugEAACC48nLSJUnTj/cU5uWkW+Ewf2CG9TyiFwHRATNmzNCMGTPk8XicbgoAIEr5hsSnl5ap2uMlHMLiMgzDcLoR0aqqqkqJiYmqrKxUQkKC080BAESJguPDyHk56cqYslDVHq/i3DEqmTpEhUtK5fEamjQww+lmohk0NHvQgwgAQJQx5yCu2lJhhcNqj1cjZ61S8eYK5RMOox5FKgAARJm8nHRldU1W8eYKZXVNVsnUIbbHDDODgAgAQJQpXFJqhcHizRXKmLLQ9riuJXAQPQiIAABEGY/XUP7ADM0Z18caXo5zx2jOuD7KH5ghj5fyhGjHHEQAAKKMWYBSuKTUNgexcEkpw8uQREAEACAq1Vz30HwsiZAIAiIAANHG36LY/hbPRvQiIAIAEGXMOYg1Q6D5mDmIYKFsB7FQNgAACKaGZg+qmAEAABxSUFRS57JChUtKVXB8yD/YCIgAAAAOMXe1qRkSzXmi7hiXI+1iDiIAAIBD/BUH+SsiCjYCIgAAgIN8Q+LTS8tU7fE6Gg4lhpgBAAAcl5eTbtvVxullhgiIAAAADvO3q42TGGIGAABwUCjuakNABAAAcEio7mpDQAQAAHBIqO5qw04qDmInFQAAEEzspAIAAIAmISACAADAhoAIAAAAGwIiAAAAbAiIAAAAsCEgAgAAwIaACAAAABsCIgAAAGwIiAAAALAhIAIAAMCGgAgAAAAbAiIAAIBDCopKVLik1O9zhUtKVVBUEuQWHUNABAAAcIg7xqXpfkJi4ZJSTS8qkTvG5Ui7Yh15VwAAACgvJ12SNP14T2FeTroVDvMHZljPBxsBEQAAwEG+IfHppWWq9ngdDYcSQ8wAAACOy8tJV5w7RtUer+LcMY6GQ4mACAAA4LjCJaVWOKz2eOssXAkWhpgBAAAcVHPOoflYEnMQAQAAoo2/ghR/hSvBRkAEAABwiMdr+C1IMR97vIYTzZLLMAxn3hmqqqpSYmKiKisrlZCQ4HRzAABAhGto9qBIBQAAADYERAAAANgQEAEAAGBDQAQAAIANAREAAAA2BEQAAADYEBABAABgQ0AEAACADQERAAAANgREAAAA2BAQA+i6665TmzZtdMMNNzjdFAAAgCYjIAZQXl6eXn75ZaebAQAAcFIIiAGUnZ2t1q1bO90MAACAkxJSAXHatGlyuVyaOHFiQK/74YcfatiwYUpJSZHL5dKbb77p97xnnnlGaWlpio+PV2Zmpj766KOAtgMAACAchExAXLNmjWbOnKkLLrig3vNWrFih//3vf7WOf/XVV9q9e7ff1xw8eFAXXnihnn766TqvO2/ePE2cOFFTpkzR+vXrddlll2nIkCHavn27dU5mZqZ69OhR62vnzp0N/JQAAAChLyQC4oEDBzRq1CjNmjVLbdq0qfM8r9erCRMmaOTIkfJ4PNbxkpISZWdn1zn/b8iQIXrsscd0/fXX13nt6dOn6/bbb9cdd9yhbt266amnnlJqaqqeffZZ65y1a9fqiy++qPWVkpLShE8NAAAQmkIiIE6YMEFDhw7VlVdeWe95MTExWrBggdavX68xY8bI6/Vq8+bNGjBggHJzczV58uQmvX91dbXWrl2rQYMG2Y4PGjRIxcXFTbpmfWbMmKHu3burd+/eAb82AADAyYp1ugFz587VunXrtGbNmgadn5KSoqVLl+ryyy/XyJEjtXLlSuXk5Oi5555rchv27t0rj8ej9u3b2463b9++zmFrf6666iqtW7dOBw8eVMeOHfXGG2/4DYETJkzQhAkTVFVVpcTExCa3GwAAoDk4GhDLy8t177336v3331d8fHyDX9epUye9/PLL6t+/v7p06aIXXnhBLpfrpNtT8xqGYTTquosWLTrpNgAAADjN0SHmtWvXas+ePcrMzFRsbKxiY2O1fPlyFRYWKjY21jbP0Ne3336rO++8U8OGDdOhQ4c0adKkk2pH27Zt5Xa7a/UW7tmzp1avIgAAQKRztAcxJydHn3/+ue3YbbfdpvPOO0/33Xef3G53rdfs3btXOTk56tatm/7xj3+otLRUV1xxhVq0aKEnn3yySe2Ii4tTZmamioqKdN1111nHi4qKNHz48CZdEwAAIFw5GhBbt26tHj162I61atVKycnJtY5Lx6qYBw8erM6dO2vevHmKjY1Vt27dtHjxYmVnZ+uss87y25t44MABlZWVWY+3bt2qDRs2KCkpSZ06dZIk5efna/To0erVq5f69u2rmTNnavv27Ro/fnyAPzUAAMAxBUUlcse4lJeTXuu5wiWl8ngNTRqYEfR2OV6k0hgxMTGaNm2aLrvsMsXFxVnHzz//fC1evFjJycl+X/fpp58qOzvbepyfny9JGjt2rF588UVJ0k033aSKigr97ne/065du9SjRw8tWLBAnTt3br4PBAAAopo7xqXpRSWSZAuJhUtKNb2oRPkOhENJchmGYTjyzrCqmCsrK5WQkOB0cwAAgAN8w2BeTnqtx4HU0OwRVj2IAAAAkcYMgdOLSvT00jJVe7zNEg4bIyQWygYAAIhmeTnpinPHqNrjVZw7xtFwKBEQAQAAHFe4pNQKh9UerwqXlDraHoaYAQAAHFTXHERJjvUkEhABAAAc4q8gxXdOou/jYCIgAgAAOMTjNfwWpJiPPV5nFpthmRsHscwNAAAIpoZmD4pUAAAAYENABAAAgA0BEQAAADYERAAAANgQEAEAAGBDQAQAAIANAREAAAA2LJTtIHMJyqqqKodbAgAAooGZOU60DDYB0UH79++XJKWmpjrcEgAAEE3279+vxMTEOp9nJxUHeb1e7dy5U61bt5bL5WqW96iqqlJqaqrKy8vZrcVB3IfQwb0IHdyL0MB9CB3BuBeGYWj//v1KSUlRTEzdMw3pQXRQTEyMOnbsGJT3SkhI4Ac/BHAfQgf3InRwL0ID9yF0NPe9qK/n0ESRCgAAAGwIiAAAALAhIEa4Fi1a6OGHH1aLFi2cbkpU4z6EDu5F6OBehAbuQ+gIpXtBkQoAAABs6EEEAACADQERAAAANgREAAAA2BAQAQAAYENAjGDPPPOM0tLSFB8fr8zMTH300UdONymiTJs2Tb1791br1q3Vrl07XXvttfr6669t5xiGoUceeUQpKSlq2bKlrrjiCm3cuNF2zpEjR3TPPfeobdu2atWqlXJzc/Xvf/87mB8lokybNk0ul0sTJ060jnEfgmfHjh265ZZblJycrFNPPVUXXXSR1q5daz3PvQiOo0eP6sEHH1RaWppatmypLl266He/+528Xq91DveieXz44YcaNmyYUlJS5HK59Oabb9qeD9T3fd++fRo9erQSExOVmJio0aNH6/vvvw/cBzEQkebOnWuccsopxqxZs4xNmzYZ9957r9GqVSvjm2++cbppEeOqq64yZs+ebXzxxRfGhg0bjKFDhxqdOnUyDhw4YJ3zxBNPGK1btzZef/114/PPPzduuukm48wzzzSqqqqsc8aPH2+cddZZRlFRkbFu3TojOzvbuPDCC42jR4868bHC2urVq42zzz7buOCCC4x7773XOs59CI7vvvvO6Ny5s3Hrrbcan3zyibF161Zj8eLFRllZmXUO9yI4HnvsMSM5Odl49913ja1btxr/+Mc/jNNOO8146qmnrHO4F81jwYIFxpQpU4zXX3/dkGS88cYbtucD9X0fPHiw0aNHD6O4uNgoLi42evToYVxzzTUB+xwExAh18cUXG+PHj7cdO++884z777/foRZFvj179hiSjOXLlxuGYRher9fo0KGD8cQTT1jn/Pe//zUSExON5557zjAMw/j++++NU045xZg7d651zo4dO4yYmBjjn//8Z3A/QJjbv3+/kZ6ebhQVFRn9+/e3AiL3IXjuu+8+49JLL63zee5F8AwdOtT42c9+Zjt2/fXXG7fccothGNyLYKkZEAP1fd+0aZMhyVi1apV1zsqVKw1JxldffRWQtjPEHIGqq6u1du1aDRo0yHZ80KBBKi4udqhVka+yslKSlJSUJEnaunWrdu/ebbsPLVq0UP/+/a37sHbtWv3vf/+znZOSkqIePXpwrxppwoQJGjp0qK688krbce5D8Lz99tvq1auXbrzxRrVr1049e/bUrFmzrOe5F8Fz6aWXasmSJSopKZEkffbZZ/r444919dVXS+JeOCVQ3/eVK1cqMTFRl1xyiXVOnz59lJiYGLB7ExuQqyCk7N27Vx6PR+3bt7cdb9++vXbv3u1QqyKbYRjKz8/XpZdeqh49ekiS9b32dx+++eYb65y4uDi1adOm1jncq4abO3eu1q1bpzVr1tR6jvsQPFu2bNGzzz6r/Px8PfDAA1q9erXy8vLUokULjRkzhnsRRPfdd58qKyt13nnnye12y+PxaOrUqRoxYoQkfi6cEqjv++7du9WuXbta12/Xrl3A7g0BMYK5XC7bY8Mwah1DYNx9993617/+pY8//rjWc025D9yrhisvL9e9996r999/X/Hx8XWex31ofl6vV7169dLjjz8uSerZs6c2btyoZ599VmPGjLHO4140v3nz5umVV17RnDlz9KMf/UgbNmzQxIkTlZKSorFjx1rncS+cEYjvu7/zA3lvGGKOQG3btpXb7a71V8SePXtq/dWCk3fPPffo7bff1rJly9SxY0freIcOHSSp3vvQoUMHVVdXa9++fXWeg/qtXbtWe/bsUWZmpmJjYxUbG6vly5ersLBQsbGx1veR+9D8zjzzTHXv3t12rFu3btq+fbskfiaC6Ve/+pXuv/9+3XzzzTr//PM1evRoTZo0SdOmTZPEvXBKoL7vHTp00Lffflvr+v/5z38Cdm8IiBEoLi5OmZmZKioqsh0vKipSVlaWQ62KPIZh6O6779b8+fO1dOlSpaWl2Z5PS0tThw4dbPehurpay5cvt+5DZmamTjnlFNs5u3bt0hdffMG9aqCcnBx9/vnn2rBhg/XVq1cvjRo1Shs2bFCXLl24D0HSr1+/Wks9lZSUqHPnzpL4mQimQ4cOKSbG/ive7XZby9xwL5wRqO973759VVlZqdWrV1vnfPLJJ6qsrAzcvQlIqQtCjrnMzQsvvGBs2rTJmDhxotGqVStj27ZtTjctYtx1111GYmKi8cEHHxi7du2yvg4dOmSd88QTTxiJiYnG/Pnzjc8//9wYMWKE3+UMOnbsaCxevNhYt26dMWDAAJaROEm+VcyGwX0IltWrVxuxsbHG1KlTjdLSUuNvf/ubceqppxqvvPKKdQ73IjjGjh1rnHXWWdYyN/Pnzzfatm1rTJ482TqHe9E89u/fb6xfv95Yv369IcmYPn26sX79emuZuUB93wcPHmxccMEFxsqVK42VK1ca559/PsvcoGFmzJhhdO7c2YiLizN+/OMfW8uvIDAk+f2aPXu2dY7X6zUefvhho0OHDkaLFi2Myy+/3Pj8889t1zl8+LBx9913G0lJSUbLli2Na665xti+fXuQP01kqRkQuQ/B88477xg9evQwWrRoYZx33nnGzJkzbc9zL4KjqqrKuPfee41OnToZ8fHxRpcuXYwpU6YYR44csc7hXjSPZcuW+f3dMHbsWMMwAvd9r6ioMEaNGmW0bt3aaN26tTFq1Chj3759AfscLsMwjMD0RQIAACASMAcRAAAANgREAAAA2BAQAQAAYENABAAAgA0BEQAAADYERAAAANgQEAEAAGBDQAQQ1q644gpNnDgx6O/7yCOP6KKLLmr293G5XHK5XDr99NOb/b0C7Y033lBsbKwyMjK0Z8+eJl1j27Zt1vcgGN9vAMcQEAEgxM2ePVslJSWNes0HH3ygM888U07thbBs2TKNHDlSDz/8sNq1a6fBgwerqqrKds62bdt0++23Ky0tTS1btlTXrl318MMPq7q62jonNTVVu3bt0i9+8YtgfwQgqhEQASDEnX766WrXrl2jXvP2228rNzdXLpermVpVt7Vr1+q6667T9OnT9dBDD2nRokVKSkpSbm6u/vvf/1rnffXVV/J6vXr++ee1ceNGFRQU6LnnntMDDzxgneN2u9WhQweddtppQf8cQDQjIAIIe0ePHtXdd9+t008/XcnJyXrwwQfr7DmrrKxUy5Yt9c9//tN2fP78+WrVqpUOHDggSbrvvvuUkZGhU089VV26dNFDDz2k//3vf3W2wd9Q97XXXqtbb73VelxdXa3JkyfrrLPOUqtWrXTJJZfogw8+aPTn/eyzz5Sdna3WrVsrISFBmZmZ+vTTT23nmAHRbNs999yjiRMnqk2bNmrfvr1mzpypgwcP6rbbblPr1q3VtWtXLVy40Hr9Bx98IJfLpUWLFqlnz55q2bKlBgwYoD179mjhwoXq1q2bEhISNGLECB06dMh63ddff61rrrlGhYWFuuuuuyRJrVq10nvvvaeEhATddNNNOnr0qCRp8ODBmj17tgYNGqQuXbooNzdXv/zlLzV//vxGf08ABBYBEUDYe+mllxQbG6tPPvlEhYWFKigo0F/+8he/5yYmJmro0KH629/+Zjs+Z84cDR8+3Oqpat26tV588UVt2rRJf/rTnzRr1iwVFBScVDtvu+02rVixQnPnztW//vUv3XjjjRo8eLBKS0sbdZ1Ro0apY8eOWrNmjdauXav7779fp5xyivX8xo0btXv3buXk5FjHXnrpJbVt21arV6/WPffco7vuuks33nijsrKytG7dOl111VUaPXq0LexJx+ZaPv300youLlZ5ebl++tOf6qmnntKcOXP03nvvqaioSH/+85+t888991zt2rVLY8aMsV2nRYsWevvtt/XWW28pNja2zs9WWVmppKSkRn0/ADQDAwDCWP/+/Y1u3boZXq/XOnbfffcZ3bp1q/M18+fPN0477TTj4MGDhmEYRmVlpREfH2+89957db7mD3/4g5GZmWk9fvjhh40LL7zQ1o57773X9prhw4cbY8eONQzDMMrKygyXy2Xs2LHDdk5OTo7x61//us73lWS88cYbtmOtW7c2XnzxxTpfM3XqVOP666+3te3SSy+1Hh89etRo1aqVMXr0aOvYrl27DEnGypUrDcMwjGXLlhmSjMWLF1vnTJs2zZBkbN682Tr2f//3f8ZVV11VZ1sao6yszEhISDBmzZpV67ma328AzYseRABhr0+fPra5dn379lVpaak8Ho8ef/xxnXbaadbX9u3bNXToUMXGxurtt9+WJL3++utq3bq1Bg0aZF3jtdde06WXXmrNf3vooYe0ffv2Jrdx3bp1MgxDGRkZtvYsX75cmzdvbtS18vPzdccdd+jKK6/UE088Uev1b731ljW8bLrgggus/+92u5WcnKzzzz/fOta+fXtJqlVt7Pu69u3bW0PuvseaWqHsa+fOnRo8eLBuvPFG3XHHHSd9PQAnh4AIIKKNHz9eGzZssL5SUlIUFxenG264QXPmzJF0bHj5pptusoY+V61apZtvvllDhgzRu+++q/Xr12vKlCm26tqaYmJias179J2z6PV65Xa7tXbtWlt7vvzyS/3pT39q1Gd65JFHtHHjRg0dOlRLly5V9+7d9cYbb0iSdu/erXXr1mno0KG21/gOQUvHls/xPWYGbK/XW+frar7GPFbzNY21c+dOZWdnq2/fvpo5c+ZJXQtAYNQ9EQQAwsSqVatqPU5PT5fb7VZSUpLfOW2jRo3SoEGDtHHjRi1btkyPPvqo9dyKFSvUuXNnTZkyxTr2zTff1NuGM844Q7t27bIeezweffHFF8rOzpYk9ezZUx6PR3v27NFll13WpM/pKyMjQxkZGZo0aZJGjBih2bNn67rrrtPbb7+tvn37qm3btif9HsGwY8cOZWdnKzMzU7Nnz1ZMDP0WQCjgJxFA2CsvL1d+fr6+/vprvfrqq/rzn/+se++9t97X9O/fX+3bt9eoUaN09tlnq0+fPtZz55xzjrZv3665c+dq8+bNKiwstHro6jJgwAC99957eu+99/TVV1/p5z//ub7//nvr+YyMDI0aNUpjxozR/PnztXXrVq1Zs0a///3vtWDBggZ/1sOHD+vuu+/WBx98oG+++UYrVqzQmjVr1K1bN0nHqpeHDx/e4Os5aefOnbriiiuUmpqqJ598Uv/5z3+0e/du7d692+mmAVGPHkQAYW/MmDE6fPiwLr74Yrndbt1zzz268847632Ny+XSiBEj9P/+3//Tb37zG9tzw4cP16RJk3T33XfryJEjGjp0qB566CE98sgjdV7vZz/7mT777DONGTNGsbGxmjRpktV7aJo9e7Yee+wx/eIXv9COHTuUnJysvn376uqrr27wZ3W73aqoqNCYMWP07bffqm3btrr++uv129/+VgcPHtSSJUtOuto6WN5//32VlZWprKxMHTt2tD1Xc7geQHC5DH4KASBkuVwuvfHGG7r22mtPeO78+fP14IMPatOmTc3fsCB75JFH9Oabb2rDhg1ONwWICgREAAhhLpdL8fHxSk5O1r///e96z33//fd15MgRDRs2LEita37bt29X9+7dVV1dre7duxMQgSAhIAJACCsrK5N0bGg5LS3N4dYE39GjR7Vt2zZJxxbbTk1NdbZBQJQgIAIAAMCGKmYAAADYEBABAABgQ0AEAACADQERAAAANgREAAAA2BAQAQAAYENABAAAgA0BEQAAADYERAAAANj8f+L6N76TFUlmAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 700x400 with 1 Axes>"
       ]
@@ -315,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 9,
    "id": "b183a0dc",
    "metadata": {},
    "outputs": [
@@ -325,13 +316,13 @@
        "Text(0.5, 1.0, 'direction 6')"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1500x1500 with 6 Axes>"
       ]
@@ -428,11 +419,9 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "id": "79ac1e5c-ca18-462d-8030-c20fae62a211",
    "metadata": {},
-   "outputs": [],
    "source": [
     "Code submissions are located in the src/original folder, where submissions are named as `<initials>_<institution>`\n",
     "The src/standardized folder contains the standardised version of each code submission. Here, a class is created following a naming convention (`<initials>_<institution>_<algorithm name>`), with `__init__()` and `ivim_fit()` methods that integrate well with the OsipiBase class\n",
@@ -443,7 +432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 11,
    "id": "b7e8872a",
    "metadata": {},
    "outputs": [],
@@ -462,7 +451,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 12,
    "id": "12deef83",
    "metadata": {},
    "outputs": [
@@ -486,7 +475,7 @@
        " '__pycache__']"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -506,7 +495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 13,
    "id": "f695e259",
    "metadata": {},
    "outputs": [],
@@ -517,7 +506,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 14,
    "id": "6b7ab9cb",
    "metadata": {},
    "outputs": [],
@@ -528,7 +517,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 15,
    "id": "7c9060bb",
    "metadata": {},
    "outputs": [
@@ -536,16 +525,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00,  8.70it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 141.32it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "array([0.04609779, 0.01136011, 0.00071134])"
+       "{'f': array(0.04609779), 'D*': array(0.01136011), 'D': array(0.00071134)}"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -565,7 +554,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 16,
    "id": "9fee9a3e",
    "metadata": {},
    "outputs": [
@@ -573,16 +562,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00,  9.37it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 63.74it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "array([0.04611688, 0.01135417, 0.0007113 ])"
+       "{'f': array(0.04611801), 'D*': array(0.0113541), 'D': array(0.0007113)}"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -604,7 +593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 18,
    "id": "e35f4f51",
    "metadata": {},
    "outputs": [
@@ -612,23 +601,24 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 99.68it/s]\n",
-      "100%|██████████| 1/1.0 [00:00<00:00, 21.91it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 251.23it/s]\n",
+      "100%|██████████| 1/1.0 [00:00<00:00, 104.87it/s]\n"
      ]
     },
     {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'algorithm 2')"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "TypeError",
+     "evalue": "unsupported operand type(s) for -: 'int' and 'str'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[18], line 23\u001b[0m\n\u001b[0;32m     21\u001b[0m plt\u001b[38;5;241m.\u001b[39msubplot(\u001b[38;5;241m122\u001b[39m)\n\u001b[0;32m     22\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),signal_1dir,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m---> 23\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),fit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD*\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;241m+\u001b[39m(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mf)\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[0;32m     24\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),fit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD*\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[0;32m     25\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n",
+      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'int' and 'str'"
+     ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x300 with 2 Axes>"
       ]
@@ -641,28 +631,28 @@
     "fig = plt.figure(figsize=(10, 3))\n",
     "\n",
     "#apply algorithm 1 to the diffusion data in 1 direction to obtain f, D* and D\n",
-    "[f, Dstar, D] = OsipiBase.osipi_fit(algorithm1,signal_1dir, np.unique(bval)) #f, D*, D\"\n",
+    "fit = OsipiBase.osipi_fit(algorithm1,signal_1dir, np.unique(bval)) # Dictionary with f, D*, D\"\n",
     "\n",
     "#plot the results of algorithm 1\n",
     "plt.subplot(121)\n",
     "plt.plot(np.unique(bval),signal_1dir,'x')\n",
-    "plt.plot(np.unique(bval),f*np.exp(-np.unique(bval)*Dstar)+(1-f)*np.exp(-np.unique(bval)*D))\n",
-    "plt.plot(np.unique(bval),f*np.exp(-np.unique(bval)*Dstar))\n",
-    "plt.plot(np.unique(bval),(1-f)*np.exp(-np.unique(bval)*D))\n",
+    "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*'])+(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
+    "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*']))\n",
+    "plt.plot(np.unique(bval),(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
     "plt.legend(['measured data','model fit','D','D*'])\n",
     "plt.ylabel('S/S0')\n",
     "plt.xlabel('b-value [s/mm^2]')\n",
     "plt.title('algorithm 1')\n",
     "          \n",
     "#apply algorithm 2 to the diffusion data in 1 direction to obtain f, D* and D\n",
-    "[f, Dstar, D] = OsipiBase.osipi_fit(algorithm2,signal_1dir, np.unique(bval)) #f, D*, D\"\n",
+    "fit = OsipiBase.osipi_fit(algorithm2,signal_1dir, np.unique(bval)) # Dictionary with f, D*, D\"\n",
     "\n",
     "#plot the results of algorithm 2\n",
     "plt.subplot(122)\n",
     "plt.plot(np.unique(bval),signal_1dir,'x')\n",
-    "plt.plot(np.unique(bval),f*np.exp(-np.unique(bval)*Dstar)+(1-f)*np.exp(-np.unique(bval)*D))\n",
-    "plt.plot(np.unique(bval),f*np.exp(-np.unique(bval)*Dstar))\n",
-    "plt.plot(np.unique(bval),(1-f)*np.exp(-np.unique(bval)*D))\n",
+    "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*'])+(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
+    "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*']))\n",
+    "plt.plot(np.unique(bval),(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
     "plt.legend(['measured data','model fit','D','D*'])\n",
     "plt.ylabel('S/S0')\n",
     "plt.xlabel('b-value [s/mm^2]')\n",
@@ -1099,7 +1089,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

From 51e726465eba1c0834e3f446164309fbe942522a Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 27 Sep 2024 11:06:26 +0200
Subject: [PATCH 13/18] new version with fixed dictionary output

---
 ...ithub_and_IVIM_Analysis_using_Python.ipynb | 168 +++++++++---------
 1 file changed, 85 insertions(+), 83 deletions(-)

diff --git a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
index 5020268..23c52cf 100644
--- a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
+++ b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
@@ -45,10 +45,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "56273b2a",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (882689640.py, line 2)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;36m  Cell \u001b[1;32mIn[1], line 2\u001b[1;36m\u001b[0m\n\u001b[1;33m    pip3 install numpy\u001b[0m\n\u001b[1;37m         ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
    "source": [
     "# install packages through anaconda prompt\n",
     "pip3 install numpy\n",
@@ -67,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "9654f12d-6cfc-4639-884e-d7f2b23fa59f",
    "metadata": {},
    "outputs": [],
@@ -123,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "6bd0f61a",
    "metadata": {},
    "outputs": [],
@@ -159,17 +168,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "id": "9c977b4e",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x234437abb50>"
+       "<matplotlib.colorbar.Colorbar at 0x23ba1c0f9d0>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -211,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "id": "120fc47a",
    "metadata": {},
    "outputs": [
@@ -221,7 +230,7 @@
        "Text(0.5, 1.0, 'normalized signal as function of b-value')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -270,7 +279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "id": "8ddef255-88b6-4c79-8f6c-4ee85e931588",
    "metadata": {},
    "outputs": [
@@ -306,7 +315,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "id": "b183a0dc",
    "metadata": {},
    "outputs": [
@@ -316,7 +325,7 @@
        "Text(0.5, 1.0, 'direction 6')"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -432,7 +441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "id": "b7e8872a",
    "metadata": {},
    "outputs": [],
@@ -451,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 9,
    "id": "12deef83",
    "metadata": {},
    "outputs": [
@@ -475,7 +484,7 @@
        " '__pycache__']"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -495,10 +504,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "id": "f695e259",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\ivan5\\Box\\OSIPI\\TF2.4_IVIM-MRI_CodeCollection\\doc\\..\\src\\standardized\\OGC_AmsterdamUMC_Bayesian_biexp.py:54: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
+      "  if len(prior_in) is 4:\n"
+     ]
+    }
+   ],
    "source": [
     "from src.standardized.IAR_LU_biexp import IAR_LU_biexp\n",
     "from src.standardized.OGC_AmsterdamUMC_Bayesian_biexp import OGC_AmsterdamUMC_Bayesian_biexp"
@@ -506,7 +524,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "id": "6b7ab9cb",
    "metadata": {},
    "outputs": [],
@@ -517,7 +535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "id": "7c9060bb",
    "metadata": {},
    "outputs": [
@@ -525,7 +543,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 141.32it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 62.98it/s]\n"
      ]
     },
     {
@@ -534,7 +552,7 @@
        "{'f': array(0.04609779), 'D*': array(0.01136011), 'D': array(0.00071134)}"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -554,7 +572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "id": "9fee9a3e",
    "metadata": {},
    "outputs": [
@@ -562,7 +580,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 63.74it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 55.56it/s]\n"
      ]
     },
     {
@@ -571,7 +589,7 @@
        "{'f': array(0.04611801), 'D*': array(0.0113541), 'D': array(0.0007113)}"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -593,7 +611,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
    "id": "e35f4f51",
    "metadata": {},
    "outputs": [
@@ -601,24 +619,23 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 251.23it/s]\n",
-      "100%|██████████| 1/1.0 [00:00<00:00, 104.87it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 167.24it/s]\n",
+      "100%|██████████| 1/1.0 [00:00<00:00, 82.84it/s]\n"
      ]
     },
     {
-     "ename": "TypeError",
-     "evalue": "unsupported operand type(s) for -: 'int' and 'str'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[18], line 23\u001b[0m\n\u001b[0;32m     21\u001b[0m plt\u001b[38;5;241m.\u001b[39msubplot(\u001b[38;5;241m122\u001b[39m)\n\u001b[0;32m     22\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),signal_1dir,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m---> 23\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),fit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD*\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;241m+\u001b[39m(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mf)\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[0;32m     24\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),fit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD*\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[0;32m     25\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39munique(bval),(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39munique(bval)\u001b[38;5;241m*\u001b[39mfit[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n",
-      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'int' and 'str'"
-     ]
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'algorithm 2')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x300 with 2 Axes>"
       ]
@@ -678,7 +695,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 16,
    "id": "fd1d23a4",
    "metadata": {},
    "outputs": [
@@ -689,13 +706,12 @@
        "        300.,  400.,  500.,  600.,  800., 1000.])"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "slice_data_1dir.shape\n",
     "np.unique(bval)"
    ]
   },
@@ -712,7 +728,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 17,
    "id": "71970925",
    "metadata": {},
    "outputs": [],
@@ -758,23 +774,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 18,
    "id": "d6307930",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x1c884f2eb90>"
+       "<matplotlib.colorbar.Colorbar at 0x23ba76af190>"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1500x400 with 2 Axes>"
       ]
@@ -802,7 +818,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 20,
    "id": "2855a999",
    "metadata": {
     "scrolled": true
@@ -812,30 +828,32 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 4274/4274 [00:02<00:00, 1746.21it/s]\n"
+      "100%|██████████| 4274/4274 [00:00<00:00, 4809.15it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(4274, 3)"
+       "{'f': array([0., 0., 0., ..., 0., 0., 0.]),\n",
+       " 'D*': array([0., 0., 0., ..., 0., 0., 0.]),\n",
+       " 'D': array([0., 0., 0., ..., 0., 0., 0.])}"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "#apply algorithm 2 to the diffusion data to obtain f, D* and D for each voxel in the slice (1 direction)\n",
-    "OsipiBase.osipi_fit(algorithm2,slice_data_norm,bval).shape\n",
+    "OsipiBase.osipi_fit(algorithm2,slice_data_norm,bval)\n",
     "\n",
     "#Algorithm 2 does not seem to give accurate fit paramters using osipi_fit 2D data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 21,
    "id": "f895cf1e",
    "metadata": {},
    "outputs": [
@@ -843,24 +861,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 4274/4274 [00:34<00:00, 123.92it/s]\n"
+      "100%|██████████| 4274/4274 [00:11<00:00, 374.05it/s]\n"
      ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([[3.60661882e-01, 8.97730559e-03, 2.93929425e-04],\n",
-       "       [2.23216905e-01, 3.06544103e-02, 7.61525737e-04],\n",
-       "       [1.87552616e-01, 4.75952785e-02, 8.11624957e-04],\n",
-       "       ...,\n",
-       "       [4.19638602e-13, 5.00080184e-03, 7.05240582e-04],\n",
-       "       [1.15135110e-16, 5.00000000e-03, 5.36429577e-04],\n",
-       "       [6.27625301e-12, 1.00000000e-01, 2.42459625e-04]])"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -870,23 +872,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 29,
    "id": "fe189fb1",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x1c88558d7d0>"
+       "<matplotlib.colorbar.Colorbar at 0x23ba8a3d8d0>"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1500x400 with 6 Axes>"
       ]
@@ -896,9 +898,9 @@
     }
    ],
    "source": [
-    "f_array=maps[:,0]\n",
-    "Dstar_array=maps[:,1]\n",
-    "D_array=maps[:,2]\n",
+    "f_array=maps[\"f\"]\n",
+    "Dstar_array=maps[\"D*\"]\n",
+    "D_array=maps[\"D\"]\n",
     "\n",
     "f_map = np.zeros([sx * sy])\n",
     "f_map[valid_id] = f_array[0:sum(valid_id)]\n",
@@ -959,7 +961,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 30,
    "id": "2a216274",
    "metadata": {},
    "outputs": [
@@ -969,7 +971,7 @@
        "(229120, 15)"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1002,7 +1004,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 31,
    "id": "cee14e22",
    "metadata": {},
    "outputs": [
@@ -1010,7 +1012,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 229120/229120 [30:22<00:00, 125.72it/s] \n"
+      "100%|██████████| 229120/229120 [13:34<00:00, 281.35it/s]\n"
      ]
     }
    ],
@@ -1018,9 +1020,9 @@
     "#apply algorithm 1 to the diffusion data to obtain f, D* and D for each voxel in the slice\n",
     "maps = OsipiBase.osipi_fit(algorithm1,data_norm,np.unique(bval))\n",
     "\n",
-    "f_array=maps[:,0]\n",
-    "Dstar_array=maps[:,1]\n",
-    "D_array=maps[:,2]\n",
+    "f_array=maps[\"f\"]\n",
+    "Dstar_array=maps[\"D*\"]\n",
+    "D_array=maps[\"D\"]\n",
     "\n",
     "f_map = np.zeros([sx * sy * sz])\n",
     "f_map[valid_id] = f_array[0:sum(valid_id)]\n",
@@ -1045,7 +1047,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 32,
    "id": "397d86c9",
    "metadata": {},
    "outputs": [],

From 563205ff6d93b6e0953266c584317fba895c5ed4 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Fri, 27 Sep 2024 14:29:01 +0200
Subject: [PATCH 14/18] Create wrapper_usage_example.ipynb

---
 doc/wrapper_usage_example.ipynb | 165 ++++++++++++++++++++++++++++++++
 1 file changed, 165 insertions(+)
 create mode 100644 doc/wrapper_usage_example.ipynb

diff --git a/doc/wrapper_usage_example.ipynb b/doc/wrapper_usage_example.ipynb
new file mode 100644
index 0000000..594a530
--- /dev/null
+++ b/doc/wrapper_usage_example.ipynb
@@ -0,0 +1,165 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# Organisation of code submissions and standardisation to a common interface\n",
+    "\n",
+    "## General structure\n",
+    "Code submissions are located in the src/original folder, where submissions are named as `<initials>_<institution>`. Due to code submissions having different authors, it is expected that they all vary in their usage, inputs, and outputs. In order to facilitate testing in a larger scale, a common interface has been created in the form of the `OsipiBase` class (src/wrappers). This class acts as a parent class for standardised versions of the different code submissions. Together, they create the common interface of function calls and function outputs that allows us to perform mass testing, but also creates easy usage.\n",
+    "\n",
+    "The src/standardized folder contains the standardised version of each code submission. Here, a class is created following a naming convention (`<initials>_<institution>_<algorithm name>`), with `__init__()` and `ivim_fit()` methods that integrate well with the OsipiBase class. The idea is that every submitted fitting algorithm should be initialised in the same way, and executed in the same way.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## The standardized versions\n",
+    "The standardised versions of each submission is a class that contains two methods. These classes inherit the functionalities of `OsipiBase`.\n",
+    "\n",
+    "### `__init__()`\n",
+    "The `__init__()` method ensures that the algorithm is initiated correctly in accordance with OsipiBase. Custom code is to be inserted below the `super()` call. This method should contain any of the neccessary steps for the following `ivim_fit()` method to only require signals and b-values as input.\n",
+    "\n",
+    "Below is an example from src/standardized/IAR_LU_biexp.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):\n",
+    "    \"\"\"\n",
+    "        Everything this algorithm requires should be implemented here.\n",
+    "        Number of segmentation thresholds, bounds, etc.\n",
+    "            \n",
+    "        Our OsipiBase object could contain functions that compare the inputs with\n",
+    "        the requirements.\n",
+    "    \"\"\"\n",
+    "    super(IAR_LU_biexp, self).__init__(bvalues, thresholds, bounds, initial_guess) ######## On this line, change \"IAR_LU_biexp\" to the name of the class\n",
+    "\n",
+    "    ######## Your code below #########\n",
+    "        \n",
+    "    # Check the inputs\n",
+    "        \n",
+    "    # Initialize the algorithm\n",
+    "    if self.bvalues is not None:\n",
+    "        bvec = np.zeros((self.bvalues.size, 3))\n",
+    "        bvec[:,2] = 1\n",
+    "        gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)\n",
+    "            \n",
+    "        self.IAR_algorithm = IvimModelBiExp(gtab)\n",
+    "    else:\n",
+    "        self.IAR_algorithm = None"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### `ivim_fit()`\n",
+    "The purpose of this method is to take a singe voxel signal and b-values as input, and return IVIM parameters as output. This is where most of the custom code will go that is related to each individual code submission. The idea here is to have calls to submitted functions in the src/originals folder. This ensures that the original code is not tampered with. However if required, the original code could be just pasted in here as well.\n",
+    "\n",
+    "Below is an example from src/standardized/IAR_LU_biexp.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "def ivim_fit(self, signals, bvalues, **kwargs):\n",
+    "    \"\"\"Perform the IVIM fit\n",
+    "\n",
+    "    Args:\n",
+    "        signals (array-like)\n",
+    "        bvalues (array-like, optional): b-values for the signals. If None, self.bvalues will be used. Default is None.\n",
+    "\n",
+    "    Returns:\n",
+    "        _type_: _description_\n",
+    "    \"\"\"\n",
+    "        \n",
+    "    if self.IAR_algorithm is None:\n",
+    "        if bvalues is None:\n",
+    "            bvalues = self.bvalues\n",
+    "        else:\n",
+    "            bvalues = np.asarray(bvalues)\n",
+    "            \n",
+    "        bvec = np.zeros((bvalues.size, 3))\n",
+    "        bvec[:,2] = 1\n",
+    "        gtab = gradient_table(bvalues, bvec, b0_threshold=0)\n",
+    "            \n",
+    "        self.IAR_algorithm = IvimModelBiExp(gtab)\n",
+    "            \n",
+    "    fit_results = self.IAR_algorithm.fit(signals)\n",
+    "        \n",
+    "    results = {}\n",
+    "    results[\"f\"] = fit_results.model_params[1]\n",
+    "    results[\"D*\"] = fit_results.model_params[2]\n",
+    "    results[\"D\"] = fit_results.model_params[3]\n",
+    "        \n",
+    "    return results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## The `OsipiBase` class\n",
+    "The usage of the OsipiBase class mainly consists of running the osipi_fit() method. In this method, the inputs from `__init__()` of the standardised version of a code submission, and the signals and b-values input to `osipi_fit()` is processed and fed into the `ivim_fit()` function.\n",
+    "\n",
+    "It is the `osipi_fit()` method that provides the common interface for model fitting. As one may note, `ivim_fit()` takes a single voxel as input. `OsipiBase.osipi_fit()` supports multidimensional inputs, which is then iteratively fed into `ivim_fit()`, and returns a corresponding output. Support for future types of input will be implemented here. This ensures that the `ivim_fit()` method can be written as simply as possible, which simplifies the inclusion of new code submissions into the standard interface.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Example usage of standardized version of an algorithm\n",
+    "### Using the standardized version directly\n",
+    "The standardised versions can be used directly by\n",
+    "1. Importing the class\n",
+    "2. Initialising the object with the required parameters, e.g. `IAR_LU_biexp(bounds=[(0, 1), (0.005, 0.1), (0, 0.004)])`\n",
+    "3. Call `osipi_fit(signals, bvalues)` for model fitting\n",
+    "\n",
+    "### Using the `OsipiBase` class with algorithm names\n",
+    "Standardised versions can also be initiated using the OsipiBase.osipi_initiate_algorithm() method.\n",
+    "\n",
+    "1. Import `OsipiBase`\n",
+    "2. Initiate `OsipiBase` with the algorithm keyword set to the standardised name of the desired algorithm e.g., `OsipiBase(algorithm=IAR_LU_biexp)`\n",
+    "3. Call `osipi_fit()` for model fitting"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 25051646747be33f4b702b2e1785534b15d6cba6 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Mon, 9 Dec 2024 13:17:43 +0100
Subject: [PATCH 15/18] Changed to dictionary outputs

---
 tests/IVIMmodels/unit_tests/test_ivim_fit.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/tests/IVIMmodels/unit_tests/test_ivim_fit.py b/tests/IVIMmodels/unit_tests/test_ivim_fit.py
index 213dbd7..4e170c9 100644
--- a/tests/IVIMmodels/unit_tests/test_ivim_fit.py
+++ b/tests/IVIMmodels/unit_tests/test_ivim_fit.py
@@ -64,15 +64,16 @@ def test_ivim_fit_saved(name, bvals, data, algorithm, xfail, kwargs, tolerances,
     signal, ratio = signal_helper(data["data"])
     
     tolerances = tolerances_helper(tolerances, ratio, data["noise"])
-    [f_fit, Dp_fit, D_fit] = fit.osipi_fit(signal, bvals)
+    #[f_fit, Dp_fit, D_fit] = fit.osipi_fit(signal, bvals)
+    fit_result = fit.osipi_fit(signal, bvals)
     def to_list_if_needed(value):
         return value.tolist() if isinstance(value, np.ndarray) else value
     test_result = {
         "name": name,
         "algorithm": algorithm,
-        "f_fit": to_list_if_needed(f_fit),
-        "Dp_fit": to_list_if_needed(Dp_fit),
-        "D_fit": to_list_if_needed(D_fit),
+        "f_fit": to_list_if_needed(fit_result['f']),
+        "Dp_fit": to_list_if_needed(fit_result['D*']),
+        "D_fit": to_list_if_needed(fit_result['D']),
         "f": to_list_if_needed(data['f']),
         "Dp": to_list_if_needed(data['Dp']),
         "D": to_list_if_needed(data['D']),
@@ -83,9 +84,9 @@ def to_list_if_needed(value):
 
     record_property('test_data', test_result)
 
-    npt.assert_allclose(data['f'], f_fit, rtol=tolerances["rtol"]["f"], atol=tolerances["atol"]["f"])
+    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_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'], Dp_fit, rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])
+        npt.assert_allclose(data['Dp'], fit_result['D*'], rtol=tolerances["rtol"]["Dp"], atol=tolerances["atol"]["Dp"])

From 5fb922f0a8a408abf2069dcb432f933ac1b7b19d Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Mon, 9 Dec 2024 14:32:53 +0100
Subject: [PATCH 16/18] Dictionary output support + fix of small error

---
 ...ithub_and_IVIM_Analysis_using_Python.ipynb | 123 ++++++++----------
 1 file changed, 53 insertions(+), 70 deletions(-)

diff --git a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
index 23c52cf..63bd908 100644
--- a/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
+++ b/doc/Introduction_to_TF24_IVIM-MRI_CodeCollection_github_and_IVIM_Analysis_using_Python.ipynb
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "id": "56273b2a",
    "metadata": {},
    "outputs": [
@@ -54,7 +54,7 @@
      "evalue": "invalid syntax (882689640.py, line 2)",
      "output_type": "error",
      "traceback": [
-      "\u001b[1;36m  Cell \u001b[1;32mIn[1], line 2\u001b[1;36m\u001b[0m\n\u001b[1;33m    pip3 install numpy\u001b[0m\n\u001b[1;37m         ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
+      "\u001b[1;36m  Cell \u001b[1;32mIn[3], line 2\u001b[1;36m\u001b[0m\n\u001b[1;33m    pip3 install numpy\u001b[0m\n\u001b[1;37m         ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
      ]
     }
    ],
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "id": "9654f12d-6cfc-4639-884e-d7f2b23fa59f",
    "metadata": {},
    "outputs": [],
@@ -105,18 +105,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "d06c9f5a",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Folder 'download' created.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Download the data. \n",
     "download_data()"
@@ -132,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "id": "6bd0f61a",
    "metadata": {},
    "outputs": [],
@@ -168,17 +160,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "id": "9c977b4e",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x23ba1c0f9d0>"
+       "<matplotlib.colorbar.Colorbar at 0x1e89a7df890>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -220,7 +212,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "id": "120fc47a",
    "metadata": {},
    "outputs": [
@@ -230,7 +222,7 @@
        "Text(0.5, 1.0, 'normalized signal as function of b-value')"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -279,7 +271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "id": "8ddef255-88b6-4c79-8f6c-4ee85e931588",
    "metadata": {},
    "outputs": [
@@ -315,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 10,
    "id": "b183a0dc",
    "metadata": {},
    "outputs": [
@@ -325,7 +317,7 @@
        "Text(0.5, 1.0, 'direction 6')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -441,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 11,
    "id": "b7e8872a",
    "metadata": {},
    "outputs": [],
@@ -460,7 +452,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 12,
    "id": "12deef83",
    "metadata": {},
    "outputs": [
@@ -484,7 +476,7 @@
        " '__pycache__']"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -504,19 +496,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "id": "f695e259",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\ivan5\\Box\\OSIPI\\TF2.4_IVIM-MRI_CodeCollection\\doc\\..\\src\\standardized\\OGC_AmsterdamUMC_Bayesian_biexp.py:54: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
-      "  if len(prior_in) is 4:\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from src.standardized.IAR_LU_biexp import IAR_LU_biexp\n",
     "from src.standardized.OGC_AmsterdamUMC_Bayesian_biexp import OGC_AmsterdamUMC_Bayesian_biexp"
@@ -524,7 +507,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "id": "6b7ab9cb",
    "metadata": {},
    "outputs": [],
@@ -535,7 +518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "id": "7c9060bb",
    "metadata": {},
    "outputs": [
@@ -543,7 +526,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 62.98it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 124.94it/s]\n"
      ]
     },
     {
@@ -552,7 +535,7 @@
        "{'f': array(0.04609779), 'D*': array(0.01136011), 'D': array(0.00071134)}"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -572,7 +555,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 16,
    "id": "9fee9a3e",
    "metadata": {},
    "outputs": [
@@ -580,7 +563,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 55.56it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 52.90it/s]\n"
      ]
     },
     {
@@ -589,7 +572,7 @@
        "{'f': array(0.04611801), 'D*': array(0.0113541), 'D': array(0.0007113)}"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -611,7 +594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 18,
    "id": "e35f4f51",
    "metadata": {},
    "outputs": [
@@ -619,8 +602,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1.0 [00:00<00:00, 167.24it/s]\n",
-      "100%|██████████| 1/1.0 [00:00<00:00, 82.84it/s]\n"
+      "100%|██████████| 1/1.0 [00:00<00:00, 175.81it/s]\n",
+      "100%|██████████| 1/1.0 [00:00<00:00, 68.72it/s]\n"
      ]
     },
     {
@@ -629,13 +612,13 @@
        "Text(0.5, 1.0, 'algorithm 2')"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x300 with 2 Axes>"
       ]
@@ -656,7 +639,7 @@
     "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*'])+(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
     "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*']))\n",
     "plt.plot(np.unique(bval),(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
-    "plt.legend(['measured data','model fit','D','D*'])\n",
+    "plt.legend(['measured data','model fit','D*','D'])\n",
     "plt.ylabel('S/S0')\n",
     "plt.xlabel('b-value [s/mm^2]')\n",
     "plt.title('algorithm 1')\n",
@@ -670,7 +653,7 @@
     "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*'])+(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
     "plt.plot(np.unique(bval),fit['f']*np.exp(-np.unique(bval)*fit['D*']))\n",
     "plt.plot(np.unique(bval),(1-fit['f'])*np.exp(-np.unique(bval)*fit['D']))\n",
-    "plt.legend(['measured data','model fit','D','D*'])\n",
+    "plt.legend(['measured data','model fit','D*','D'])\n",
     "plt.ylabel('S/S0')\n",
     "plt.xlabel('b-value [s/mm^2]')\n",
     "plt.title('algorithm 2')\n"
@@ -695,7 +678,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "id": "fd1d23a4",
    "metadata": {},
    "outputs": [
@@ -706,7 +689,7 @@
        "        300.,  400.,  500.,  600.,  800., 1000.])"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -728,7 +711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 42,
    "id": "71970925",
    "metadata": {},
    "outputs": [],
@@ -774,17 +757,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 21,
    "id": "d6307930",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x23ba76af190>"
+       "<matplotlib.colorbar.Colorbar at 0x1e8a0305f50>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -818,7 +801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 23,
    "id": "2855a999",
    "metadata": {
     "scrolled": true
@@ -828,7 +811,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 4274/4274 [00:00<00:00, 4809.15it/s]\n"
+      "100%|██████████| 4274/4274 [00:01<00:00, 2720.79it/s]\n"
      ]
     },
     {
@@ -839,7 +822,7 @@
        " 'D': array([0., 0., 0., ..., 0., 0., 0.])}"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -853,7 +836,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 43,
    "id": "f895cf1e",
    "metadata": {},
    "outputs": [
@@ -861,7 +844,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 4274/4274 [00:11<00:00, 374.05it/s]\n"
+      "100%|██████████| 4274/4274 [00:21<00:00, 195.14it/s]\n"
      ]
     }
    ],
@@ -872,17 +855,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 44,
    "id": "fe189fb1",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x23ba8a3d8d0>"
+       "<matplotlib.colorbar.Colorbar at 0x1e8c72c6cd0>"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -961,7 +944,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 26,
    "id": "2a216274",
    "metadata": {},
    "outputs": [
@@ -971,7 +954,7 @@
        "(229120, 15)"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1004,7 +987,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 27,
    "id": "cee14e22",
    "metadata": {},
    "outputs": [
@@ -1012,7 +995,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 229120/229120 [13:34<00:00, 281.35it/s]\n"
+      "100%|██████████| 229120/229120 [27:40<00:00, 137.94it/s] \n"
      ]
     }
    ],
@@ -1047,7 +1030,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 46,
    "id": "397d86c9",
    "metadata": {},
    "outputs": [],
@@ -1077,7 +1060,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },

From bce6ec7cbbb965811df73c66939993abd475e00f Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Tue, 10 Dec 2024 10:31:40 +0100
Subject: [PATCH 17/18] Changed to dictionary outputs from osipi_fit

---
 tests/IVIMmodels/unit_tests/test_ivim_synthetic.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/IVIMmodels/unit_tests/test_ivim_synthetic.py b/tests/IVIMmodels/unit_tests/test_ivim_synthetic.py
index 42017ff..58f20eb 100644
--- a/tests/IVIMmodels/unit_tests/test_ivim_synthetic.py
+++ b/tests/IVIMmodels/unit_tests/test_ivim_synthetic.py
@@ -37,12 +37,12 @@ def test_generated(ivim_algorithm, ivim_data, SNR, rtol, atol, fit_count, rician
         # else:
         #     signal = data["data"]
         start_time = datetime.datetime.now()
-        [f_fit, Dp_fit, D_fit] = fit.osipi_fit(signal, bvals) #, prior_in=prior
+        fit_result = fit.osipi_fit(signal, bvals) #, prior_in=prior
         time_delta += datetime.datetime.now() - start_time
         if save_file is not None:
-            save_file.writerow([ivim_algorithm, name, SNR, idx, f, Dp, D, f_fit, Dp_fit, D_fit, *signal])
+            save_file.writerow([ivim_algorithm, name, SNR, idx, f, Dp, D, fit_result["f"], fit_result["D*"], fit_result["D"], *signal])
             # save_results(save_file, ivim_algorithm, name, SNR, idx, [f, Dp, D], [f_fit, Dp_fit, D_fit])
-        npt.assert_allclose([f, Dp, D], [f_fit, Dp_fit, D_fit], rtol, atol)
+        npt.assert_allclose([f, Dp, D], [fit_result["f"], fit_result["D*"], fit_result["D"]], rtol, atol)
     if save_duration_file is not None:
         save_duration_file.writerow([ivim_algorithm, name, SNR, time_delta/datetime.timedelta(microseconds=1), fit_count])
         # save_duration(save_duration_file, ivim_algorithm, name, SNR, time_delta, fit_count)

From 8d57500307d92188b4fe997bed3af2a3b4f47610 Mon Sep 17 00:00:00 2001
From: IvanARashid <ivan52x53@gmail.com>
Date: Tue, 10 Dec 2024 10:39:15 +0100
Subject: [PATCH 18/18] Changed to dictionary outputs from osipi_fit

---
 WrapImage/nifti_wrapper.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/WrapImage/nifti_wrapper.py b/WrapImage/nifti_wrapper.py
index 6f43792..150e610 100644
--- a/WrapImage/nifti_wrapper.py
+++ b/WrapImage/nifti_wrapper.py
@@ -109,10 +109,10 @@ def loop_over_first_n_minus_1_dimensions(arr):
         n = data.ndim
         total_iteration = np.prod(data.shape[:n-1])
         for idx, view in tqdm(loop_over_first_n_minus_1_dimensions(data), desc=f"{args.algorithm} is fitting", dynamic_ncols=True, total=total_iteration):
-            [f_fit, Dp_fit, D_fit] = fit.osipi_fit(view, bvals)
-            f_image.append(f_fit)
-            Dp_image.append(Dp_fit)
-            D_image.append(D_fit)
+            fit_result = fit.osipi_fit(view, bvals)
+            f_image.append(fit_result["f"])
+            Dp_image.append(fit_result["D*"])
+            D_image.append(fit_result["D"])
 
         # Convert lists to NumPy arrays
         f_image = np.array(f_image)