Merge pull request #20 from SpeysideHEP/issue19

Align ```UnCorrStatisticsCombiner``` with recent updates

README.md

@@ -17,12 +17,20 @@
 
 ## Installation
 
-If you are using a specific branch you can either use `make install` or `pip install -e .`. **Note that `main` branch is not the stable version.** Stable version can either be downloaded from the [releases](https://github.com/SpeysideHEP/spey/releases) section or via pypi using the following command
+Spey can be found in [PyPi library](https://pypi.org/project/spey/) and can be downloaded using
 
 ```bash
 pip install spey
 ```
 
+If you like to use a specific branch you can either use `make install` or `pip install -e .` after cloning the repository or use the following command
+
+```bash
+python -m pip install --upgrade "git+https://github.com/SpeysideHEP/spey"
+```
+
+**Note that `main` branch is not the stable version.**
+
 ## What is Spey?
 
 Spey is a plug-in based statistics tool which aims to collect all likelihood prescriptions under one roof. This provides user the workspace to freely combine different statistical models and study them through a single interface. In order to achieve a module that can be used both with statistical model prescriptions which has been proposed in the past and will be used in the future, Spey uses so-called plug-in system where developers can propose their own statistical model prescription and allow spey to use them.

docs/index.rst

@@ -20,7 +20,7 @@ Welcome to the documentation of Spey
    contributing
    known_issues
    outreach
-   releases/changelog-v0.1.1
+   release_notes
    bibliography
 
 

docs/plugins.rst

@@ -286,12 +286,14 @@ Once again, the exclusion limit can be computed as
 External Plug-ins
 -----------------
 
-    * ``spey-pyhf`` plugin allows pyhf's likelihood prescription to be used within ``spey``.
-      for details, see the `dedicated GitHub Repository <https://github.com/SpeysideHEP/spey-pyhf>`_ and
-      `spey-pyhf documentation <https://speysidehep.github.io/spey-pyhf/>`_ :cite:`pyhf_joss`.
-
-        * `pyhf documentation <https://pyhf.readthedocs.io>`_.
-
-    * ``spey-fastprof``: TBA :cite:`Berger:2023bat`.
+.. toctree::
+
+   Spey-pyhf plug-in documentation <https://speysidehep.github.io/spey-pyhf/>
+   Spey-fastprof: TBA <https://speysidehep.github.io/spey/>
+
+**Useful links:**
 
-        * `fastprof documentation <https://fastprof.web.cern.ch/fastprof/>`_.
+* `pyhf documentation <https://pyhf.readthedocs.io>`_ :cite:`pyhf_joss`.
+* `Spey-pyhf plug-in GitHub Repository <https://github.com/SpeysideHEP/spey-pyhf>`_
+* ``spey-fastprof``: TBA :cite:`Berger:2023bat`.
+* `fastprof documentation <https://fastprof.web.cern.ch/fastprof/>`_.

docs/release_notes.rst

@@ -0,0 +1,7 @@
+Release Notes
+=============
+
+.. toctree::
+   :maxdepth: 2
+
+   releases/changelog-v0.1

docs/releases/changelog-v0.1.1.md → docs/releases/changelog-v0.1.md

@@ -1,4 +1,4 @@
-# Release notes v0.1.1
+# Release notes v0.1.2
 
 ## New features since last release
 
@@ -17,6 +17,12 @@
 * Backend inspection has been converted to inheritance property via ``ConverterBase``.
   ([#17](https://github.com/SpeysideHEP/spey/pull/17))
 
+## Bug Fixes
+
+* In accordance to the latest updates ```UnCorrStatisticsCombiner``` has been updated with
+  chi-square computer. See issue [#19](https://github.com/SpeysideHEP/spey/issues/19).
+  ([#20](https://github.com/SpeysideHEP/spey/pull/20))
+
 ## Contributors
 
 This release contains contributions from (in alphabetical order):

src/spey/_version.py

@@ -1,3 +1,3 @@
 """Version number (major.minor.patch[-label])"""
 
-__version__ = "0.1.1"
+__version__ = "0.1.2"

src/spey/combiner/uncorrelated_statistics_combiner.py

@@ -143,6 +143,11 @@ def is_toy_calculator_available(self) -> bool:
         """Check if Toy calculator is available for the backend"""
         return False
 
+    @property
+    def is_chi_square_calculator_available(self) -> bool:
+        r"""Check if :math:`\chi^2` calculator is available for the backend"""
+        return all(model.is_chi_square_calculator_available for model in self)
+
     def __getitem__(self, item: Union[Text, int]) -> StatisticalModel:
         """Retrieve a statistical model"""
         if isinstance(item, int):