From 2f0f50dc758eb9638318de4f483914b696d0436b Mon Sep 17 00:00:00 2001
From: Vincent Wieland <90847066+vwiela@users.noreply.github.com>
Date: Mon, 9 Oct 2023 18:28:54 +0200
Subject: [PATCH] Update ensemble.py (#1124)

* Update ensemble.py

Add an option for computing cutoff values for pointwise confidence regions. Needed for ensemble simulations.

* Update ensemble.py

Fix string literal.

* Style changes ensemble.py

Change style of string representation.

* Fix string name & black

* Update C.py

Add simultaneous and pointwise strings for the choice of confidence regions.

* Update strings ensemble.py

Changed strings to constants stored in C.py.

* Fix typo C.py

Fix typo.

* Style and quality ensemble.py

Use black for consistent code style.

---------

Co-authored-by: Doresic <domagoj.doresic@gmail.com>
Co-authored-by: Paul Jonas Jost <70631928+PaulJonasJost@users.noreply.github.com>
---
 pypesto/C.py                 |  3 +++
 pypesto/ensemble/ensemble.py | 27 +++++++++++++++++++++++----
 2 files changed, 26 insertions(+), 4 deletions(-)

diff --git a/pypesto/C.py b/pypesto/C.py
index 61f4eb449..c5b65452a 100644
--- a/pypesto/C.py
+++ b/pypesto/C.py
@@ -35,6 +35,9 @@
 ENSEMBLE_TYPE = 'ensemble_type'
 PREDICTIONS = 'predictions'
 
+SIMULTANEOUS = 'simultaneous'
+POINTWISE = 'pointwise'
+
 LOWER_BOUND = 'lower_bound'
 UPPER_BOUND = 'upper_bound'
 PREEQUILIBRATION_CONDITION_ID = 'preequilibrationConditionId'
diff --git a/pypesto/ensemble/ensemble.py b/pypesto/ensemble/ensemble.py
index 178c1c2b1..d2ab53df9 100644
--- a/pypesto/ensemble/ensemble.py
+++ b/pypesto/ensemble/ensemble.py
@@ -29,12 +29,14 @@
     OUTPUT,
     OUTPUT_SENSI,
     PERCENTILE,
+    POINTWISE,
     PREDICTION_ARRAYS,
     PREDICTION_ID,
     PREDICTION_RESULTS,
     PREDICTION_SUMMARY,
     PREDICTIONS,
     PREDICTOR,
+    SIMULTANEOUS,
     STANDARD_DEVIATION,
     SUMMARY,
     TIMEPOINTS,
@@ -1204,7 +1206,11 @@ def get_percentile_label(percentile: Union[float, int, str]) -> str:
     return f'{PERCENTILE} {percentile}'
 
 
-def calculate_cutoff(result: Result, percentile: float = 0.95):
+def calculate_cutoff(
+    result: Result,
+    percentile: float = 0.95,
+    cr_option: str = SIMULTANEOUS,
+):
     """
     Calculate the cutoff of the ensemble.
 
@@ -1220,6 +1226,10 @@ def calculate_cutoff(result: Result, percentile: float = 0.95):
         The percentile of the chi^2 distribution. Between 0 and 100.
         Higher values will result in a more lax cutoff. If the value is greater
         than 100, the cutoff will be returned as np.inf.
+    cr_option:
+        The type of confidence region, which determines the degree of freedom of
+        the chi^2 distribution for the cutoff value. It can take 'simultaneous' or
+        'pointwise'.
 
     Returns
     -------
@@ -1230,10 +1240,19 @@ def calculate_cutoff(result: Result, percentile: float = 0.95):
             f"percentile={percentile} is too large. Choose "
             f"0<=percentile<=100."
         )
+    if cr_option not in [SIMULTANEOUS, POINTWISE]:
+        raise ValueError(
+            "Confidence region must be either simultaneous or pointwise."
+        )
+
     # optimal point as base:
     fval_opt = result.optimize_result[0].fval
-    # degrees of freedom is equal to the number of parameters
-    df = result.problem.dim
-    range = chi2.ppf(q=percentile / 100, df=df)
+    if cr_option == SIMULTANEOUS:
+        # degrees of freedom is equal to the number of parameters
+        df = result.problem.dim
+    elif cr_option == POINTWISE:
+        # degrees of freedom is equal to 1
+        df = 1
 
+    range = chi2.ppf(q=percentile / 100, df=df)
     return fval_opt + range