Update build_install.rst (#2379)

<!-- Please make sure your PR follows our [contribution
guidelines](https://github.com/arbor-sim/arbor/tree/master/doc/contrib)
and agree to the terms outlined in the [PR
procedure](https://github.com/arbor-sim/arbor/tree/master/doc/contrib/pr.rst).
-->

doc/install/build_install.rst

@@ -969,71 +969,49 @@ If you hope to install Arbor from source in a virtual environment in order not t
 
 .. code-block:: bash
 
-#create a virtual environment
-
-conda create --name arbor_test
-conda activate arbor_test
-
-
-#go to the folder and clone the Arbor source package from GitHub
-
-cd ~/miniconda3/envs/arbor_test/
-mkdir src
-cd src
-git clone https://github.com/arbor-sim/arbor.git --recurse-submodules
-
-
-#install python and numpy in this environment
-
-conda install python=3.12.2
-conda install numpy
-
-
-#start the build
-
-cd arbor
-mkdir build
-cd build
-
-cmake .. -GNinja -DCMAKE_CXX_COMPILER=$(which g++) -DCMAKE_C_COMPILER=$(which gcc) -DARB_WITH_PYTHON=ON -DARB_VECTORIZE=ON -DPython3_EXECUTABLE=$(which python3) -DARB_USE_BUNDLED_LIBS=ON
-
-
-#activate ninja to install
-
-ninja
-sudo ninja install
-
-
-#correct the path to the site packages and the libc files
-#first request the right Python site package path
-
-python -c 'import numpy; print(numpy.__path__)'
-
-#load the right path to the one used for installing
-
-cp -r ~/miniconda3/envs/arbor_test/src/arbor/build/python/arbor <site-packages>
-Replace <site-packages> with the path you get in the previous operation before ‘/numpy’
-
-#redirect the libc files such that the miniconda environment can access it
-
-ln -sf /lib/x86_64-linux-gnu/libstdc++.so.6 ~/miniconda3/envs/arbor_test/bin/../lib/libstdc++.so.6
-
-
-#go to any working directory to try if you successfully installed arbor, by starting python and importing arbor.
-
-One thing to add here could be testing for the version, i.e.
-
-python -c 'import arbor; print(arbor.__version__)'
-
-should work without errors and print something like 0.91-dev.
-
+    #create a virtual environment    
+    conda create --name arbor_test
+    conda activate arbor_test
+    
+    #go to the folder and clone the Arbor source package from GitHub
+    cd ~/miniconda3/envs/arbor_test/
+    mkdir src
+    cd src
+    git clone https://github.com/arbor-sim/arbor.git --recurse-submodules
+    
+    #install python and numpy in this environment
+    conda install python=3.12.2
+    conda install numpy
+    
+    #start the build
+    cd arbor
+    mkdir build
+    cd build
+    cmake .. -GNinja -DCMAKE_CXX_COMPILER=$(which g++) -DCMAKE_C_COMPILER=$(which gcc) -DARB_WITH_PYTHON=ON -DARB_VECTORIZE=ON -DPython3_EXECUTABLE=$(which python3) -DARB_USE_BUNDLED_LIBS=ON
+    
+    #activate ninja to install
+    ninja
+    sudo ninja install
+    
+    #correct the path to the site packages and the libc files
+    #first request the right Python site package path
+    python -c 'import numpy; print(numpy.__path__)'
 
-python
-import arbor
+    #load the right path to the one used for installing    
+    #replace <site-packages> with the path you get in the previous operation before ‘/numpy’
+    cp -r ~/miniconda3/envs/arbor_test/src/arbor/build/python/arbor <site-packages>
+    
+    #redirect the libc files such that the miniconda environment can access it    
+    ln -sf /lib/x86_64-linux-gnu/libstdc++.so.6 ~/miniconda3/envs/arbor_test/bin/../lib/libstdc++.so.6
+    
+    #go to any working directory to try if you successfully installed arbor, by starting python and importing arbor.
+    #one thing to add here could be testing for the version, i.e.,
+    python -c 'import arbor; print(arbor.__version__)'
+    #should work without errors and print something like 0.91-dev.
 
-#then deactivate the environment if no more actions are planned. In the future, always first activate the virtual environment with and then use arbor in this environment with:
 
-conda activate arbor_test
-python
->>>import arbor
+    #then deactivate the environment if no more actions are planned. In the future, always first activate the virtual environment with and then use arbor in this environment with:
+    conda activate arbor_test
+    python
+    >>>import arbor