Changed variable name: CI -> confidence interval

SURGroup · May 23, 2022 · d78b28b · d78b28b
1 parent e0ad8da
commit d78b28b
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Showing 7 changed files with 51 additions and 33 deletions.
diff --git a/src/UQpy/sensitivity/Chatterjee.py b/src/UQpy/sensitivity/Chatterjee.py
@@ -81,7 +81,7 @@ def __init__(self, runmodel_object, dist_object, random_state=None, **kwargs):
         self.sobol_i = None
         "Sobol indices computed using the rank statistics, :class:`numpy.ndarray` of shape :code:`(num_vars, 1)`"
 
-        self.CI_chatterjee_i = None
+        self.confidence_interval_chatterjee_i = None
         "Confidence intervals for the Chatterjee sensitivity indices, :class:`numpy.ndarray` of shape :code:`(num_vars, 2)`"
 
         self.num_vars = None
@@ -115,7 +115,7 @@ def run(
 
         :return: A :class:`dict` with the following keys: \
             :code:`'chatterjee_i'` of shape :code:`(num_vars, 1)`, \
-            :code:`'CI_chatterjee_i'` of shape :code:`(num_vars, 2)`, \
+            :code:`'confidence_interval_chatterjee_i'` of shape :code:`(num_vars, 2)`, \
             :code:`'sobol_i'` of shape :code:`(num_vars, 1)`.
 
         """
@@ -185,7 +185,7 @@ def run(
 
             estimator_inputs = [A_samples, A_model_evals]
 
-            self.CI_chatterjee_i = self.bootstrapping(
+            self.confidence_interval_chatterjee_i = self.bootstrapping(
                 self.compute_chatterjee_indices,
                 estimator_inputs,
                 computed_indices["chatterjee_i"],
@@ -197,7 +197,9 @@ def run(
                 "UQpy: Confidence intervals for Chatterjee indices computed successfully.\n"
             )
 
-            computed_indices["CI_chatterjee_i"] = self.CI_chatterjee_i
+            computed_indices[
+                "confidence_interval_chatterjee_i"
+            ] = self.confidence_interval_chatterjee_i
 
         return computed_indices
 

diff --git a/src/UQpy/sensitivity/CramervonMises.py b/src/UQpy/sensitivity/CramervonMises.py
@@ -79,7 +79,7 @@ def __init__(
         self.CVM_i = None
         "First order Cramér-von Mises indices, :class:`numpy.ndarray` of shape :code:`(num_vars, 1)`"
 
-        self.CI_CVM_i = None
+        self.confidence_interval_CVM_i = None
         "Confidence intervals of the first order Cramér-von Mises indices, :class:`numpy.ndarray` of shape :code:`(num_vars, 2)`"
 
         self.sobol_i = None
@@ -124,7 +124,7 @@ def run(
 
         :return: A :class:`dict` with the following keys: \
             :code:`CVM_i` of shape :code:`(num_vars, 1)`, \
-            :code:`CI_CVM_i` of shape :code:`(num_vars, 2)`, \
+            :code:`confidence_interval_CVM_i` of shape :code:`(num_vars, 2)`, \
             :code:`sobol_i` of shape :code:`(num_vars, 1)`, \
             :code:`sobol_total_i` of shape :code:`(num_vars, 1)`.
 
@@ -205,7 +205,7 @@ def run(
                 C_i_model_evals,
             ]
 
-            self.CI_CVM_i = self.bootstrapping(
+            self.confidence_interval_CVM_i = self.bootstrapping(
                 self.pick_and_freeze_estimator,
                 estimator_inputs,
                 computed_indices["CVM_i"],
@@ -218,7 +218,9 @@ def run(
             )
 
             # Store the indices in the dictionary
-            computed_indices["CI_CVM_i"] = self.CI_CVM_i
+            computed_indices[
+                "confidence_interval_CVM_i"
+            ] = self.confidence_interval_CVM_i
 
         ################## COMPUTE SOBOL INDICES ##################
 

diff --git a/src/UQpy/sensitivity/GeneralisedSobol.py b/src/UQpy/sensitivity/GeneralisedSobol.py
@@ -113,8 +113,8 @@ def run(
         :return: A :class:`dict` with the following keys: \
             :code:`gen_sobol_i` of shape :code:`(num_vars, 1)`, \
             :code:`gen_sobol_total_i` of shape :code:`(num_vars, 1)`, \
-            :code:`CI_gen_sobol_i` of shape :code:`(num_vars, 2)`, \
-            :code:`CI_gen_sobol_total_i` of shape :code:`(num_vars, 2)`.
+            :code:`confidence_interval_gen_sobol_i` of shape :code:`(num_vars, 2)`, \
+            :code:`confidence_interval_gen_sobol_total_i` of shape :code:`(num_vars, 2)`.
 
         """
 
@@ -225,7 +225,7 @@ def run(
             ]
 
             # First order generalised Sobol indices
-            self.CI_gen_sobol_i = self.bootstrapping(
+            self.confidence_interval_gen_sobol_i = self.bootstrapping(
                 self.compute_first_order_generalised_sobol_indices,
                 estimator_inputs,
                 computed_indices["gen_sobol_i"],
@@ -238,7 +238,7 @@ def run(
             )
 
             # Total order generalised Sobol indices
-            self.CI_gen_sobol_total_i = self.bootstrapping(
+            self.confidence_interval_gen_sobol_total_i = self.bootstrapping(
                 self.compute_total_order_generalised_sobol_indices,
                 estimator_inputs,
                 computed_indices["gen_sobol_total_i"],
@@ -251,8 +251,12 @@ def run(
             )
 
             # Store the indices in the dictionary
-            computed_indices["CI_gen_sobol_i"] = self.CI_gen_sobol_i
-            computed_indices["CI_gen_sobol_total_i"] = self.CI_gen_sobol_total_i
+            computed_indices[
+                "confidence_interval_gen_sobol_i"
+            ] = self.confidence_interval_gen_sobol_i
+            computed_indices[
+                "confidence_interval_gen_sobol_total_i"
+            ] = self.confidence_interval_gen_sobol_total_i
 
         return computed_indices
 

diff --git a/src/UQpy/sensitivity/Sobol.py b/src/UQpy/sensitivity/Sobol.py
@@ -118,13 +118,13 @@ def __init__(
         self.sobol_ij = None
         "Second order Sobol indices, :class:`numpy.ndarray` of shape `(num_second_order_terms, n_outputs)`"
 
-        self.CI_sobol_i = None
+        self.confidence_interval_sobol_i = None
         "Confidence intervals for the first order Sobol indices, :class:`numpy.ndarray` of shape `(num_vars, 2)`"
 
-        self.CI_sobol_total_i = None
+        self.confidence_interval_sobol_total_i = None
         "Confidence intervals for the total order Sobol indices, :class:`numpy.ndarray` of shape `(num_vars, 2)`"
 
-        self.CI_sobol_ij = None
+        self.confidence_interval_sobol_ij = None
         "Confidence intervals for the second order Sobol indices, :class:`numpy.ndarray` of shape `(num_second_order_terms, 2)`"
 
         self.n_samples = None
@@ -176,11 +176,11 @@ def run(
             :code:`sobol_i` of shape :code:`(num_vars, 1)`, \
             :code:`sobol_total_i` of shape :code:`(num_vars, 1)`, \
             :code:`sobol_ij` of shape :code:`(num_second_order_terms, 1)`, \
-            :code:`CI_sobol_i` of shape :code:`(num_vars, 2)`, \
+            :code:`confidence_interval_sobol_i` of shape :code:`(num_vars, 2)`, \
             if multioutput: Shape: `(n_outputs, num_vars, 2)`, \
-            :code:`CI_sobol_total_i` of shape :code:`(num_vars, 2)`, \
+            :code:`confidence_interval_sobol_total_i` of shape :code:`(num_vars, 2)`, \
             if multioutput: Shape: `(n_outputs, num_vars, 2)`, \
-            :code:`CI_sobol_ij` of shape :code:`(num_second_order_terms, 2)`
+            :code:`confidence_interval_sobol_ij` of shape :code:`(num_second_order_terms, 2)`
             if multioutput: Shape: `(n_outputs, num_second_order_terms, 2)`, \
 
         """
@@ -321,7 +321,7 @@ def run(
             ]
 
             # First order Sobol indices
-            self.CI_sobol_i = self.bootstrapping(
+            self.confidence_interval_sobol_i = self.bootstrapping(
                 compute_first_order,
                 estimator_inputs,
                 computed_indices["sobol_i"],
@@ -334,10 +334,12 @@ def run(
                 "UQpy: Confidence intervals for First order Sobol indices computed successfully."
             )
 
-            computed_indices["CI_sobol_i"] = self.CI_sobol_i
+            computed_indices[
+                "confidence_interval_sobol_i"
+            ] = self.confidence_interval_sobol_i
 
             # Total order Sobol indices
-            self.CI_sobol_total_i = self.bootstrapping(
+            self.confidence_interval_sobol_total_i = self.bootstrapping(
                 compute_total_order,
                 estimator_inputs,
                 computed_indices["sobol_total_i"],
@@ -350,11 +352,13 @@ def run(
                 "UQpy: Confidence intervals for Total order Sobol indices computed successfully."
             )
 
-            computed_indices["CI_sobol_total_i"] = self.CI_sobol_total_i
+            computed_indices[
+                "confidence_interval_sobol_total_i"
+            ] = self.confidence_interval_sobol_total_i
 
             # Second order Sobol indices
             if estimate_second_order:
-                self.CI_sobol_ij = self.bootstrapping(
+                self.confidence_interval_sobol_ij = self.bootstrapping(
                     compute_second_order,
                     estimator_inputs,
                     computed_indices["sobol_ij"],
@@ -368,7 +372,9 @@ def run(
                     "UQpy: Confidence intervals for Second order Sobol indices computed successfully."
                 )
 
-                computed_indices["CI_sobol_ij"] = self.CI_sobol_ij
+                computed_indices[
+                    "confidence_interval_sobol_ij"
+                ] = self.confidence_interval_sobol_ij
 
         return computed_indices
 

diff --git a/tests/unit_tests/sensitivity/test_cramer_von_mises.py b/tests/unit_tests/sensitivity/test_cramer_von_mises.py
@@ -152,7 +152,7 @@ def bootstrap_CVM_index_variance(CVM_object, NUM_SAMPLES):
     )
 
     First_order = computed_indices["CVM_i"].ravel()
-    upper_bound_first_order = computed_indices["CI_CVM_i"][:, 1]
+    upper_bound_first_order = computed_indices["confidence_interval_CVM_i"][:, 1]
 
     #### Compute variance ####
     std_bootstrap_first_order = (upper_bound_first_order - First_order) / delta

diff --git a/tests/unit_tests/sensitivity/test_generalised_sobol.py b/tests/unit_tests/sensitivity/test_generalised_sobol.py
@@ -209,8 +209,10 @@ def bootstrap_generalised_sobol_index_variance(
 
     gen_sobol_i = computed_indices["gen_sobol_i"].ravel()
     gen_sobol_total_i = computed_indices["gen_sobol_total_i"].ravel()
-    upper_bound_first_order = computed_indices["CI_gen_sobol_i"][:, 1]
-    upper_bound_total_order = computed_indices["CI_gen_sobol_total_i"][:, 1]
+    upper_bound_first_order = computed_indices["confidence_interval_gen_sobol_i"][:, 1]
+    upper_bound_total_order = computed_indices["confidence_interval_gen_sobol_total_i"][
+        :, 1
+    ]
 
     std_bootstrap_first_order = (upper_bound_first_order - gen_sobol_i) / delta
     std_bootstrap_total_order = (upper_bound_total_order - gen_sobol_total_i) / delta

diff --git a/tests/unit_tests/sensitivity/test_sobol.py b/tests/unit_tests/sensitivity/test_sobol.py
@@ -183,12 +183,14 @@ def bootstrap_sobol_index_variance(sobol_object, NUM_SAMPLES):
 
     First_order = computed_indices["sobol_i"].ravel()
     Total_order = computed_indices["sobol_total_i"].ravel()
-    CI_first_order = computed_indices["CI_sobol_i"]
-    CI_total_order = computed_indices["CI_sobol_total_i"]
+    confidence_interval_first_order = computed_indices["confidence_interval_sobol_i"]
+    confidence_interval_total_order = computed_indices[
+        "confidence_interval_sobol_total_i"
+    ]
 
     #### Compute variance ####
-    upper_bound_first_order = CI_first_order[:, 1]
-    upper_bound_total_order = CI_total_order[:, 1]
+    upper_bound_first_order = confidence_interval_first_order[:, 1]
+    upper_bound_total_order = confidence_interval_total_order[:, 1]
 
     std_bootstrap_first_order = (upper_bound_first_order - First_order) / delta
     std_bootstrap_total_order = (upper_bound_total_order - Total_order) / delta