Merge pull request ACEsuit#261 from ACEsuit/tutorial_08

WIP: Translate Chuck's Tutorial to 0.8

Author: cortner

docs/make.jl

@@ -71,12 +71,6 @@ makedocs(;
                 "literate_tutorials/dataset_analysis.md",
                 "tutorials/scripting.md", 
                 "literate_tutorials/descriptor.md",
-                # "tutorials/lammps.md",
-                # "tutorials/python_ase.md",
-                # "tutorials/molly.md",
-                # "literate_tutorials/committee.md",
-                # "tutorials/AtomsBase_interface.md",
-                # "literate_tutorials/experimental.md",
             ],
         "Additional Topics" => Any[
             "gettingstarted/parallel-fitting.md",

docs/src/gettingstarted/installation.md

@@ -65,6 +65,19 @@ Depending on your usage you may also need to add other packages, e.g. `AtomsBase
 When returning to a project, there are several methods for reactivating it. One is to simply `activate .` in the package manager, as above. Alternatively set the `JULIA_PROJECT` environment variable to the directory with `Project.toml` before starting julia, or call julia as `julia --project=<dir>`. Special syntax like `JULIA_PROJECT=@.` or `julia --project=@.` searches the current directory and its parents for a `Project.toml` file.
 
 
+### Setting up the tutorial 
+
+As in the instructions described above, install Julia, then create a new folder, start new julia project and in that project add `ACEpotentials` and `IJulia`, then copy the tutorial to the local folder:
+```
+julia -e 'using Pkg; Pkg.add("ACEpotentials"); Pkg.add("IJulia")'
+julia -e 'using ACEpotentials; ACEpotentials.copy_tutorial(@__DIR__())'
+```
+Start Jupyter, e.g. via 
+``` 
+jupyter notebook 
+``` 
+Open the tutorial notebook. If a Julia kernel can be selected make sure it is 1.10 or higher. The follow the instructions in the notebook. 
+
 ### Setting up the Python ASE calculator
 
 !!! warning 

docs/src/tutorials/index.md

@@ -7,36 +7,3 @@
 * [Basic Dataset Analysis](../literate_tutorials/dataset_analysis.md) : basic techniques to visualize training datasets and correlate such observations to the choice of geometric priors
 * [Descriptors](../literate_tutorials/descriptor.md) : `ACEpotentials` can be used as descriptors of atomic environments or structures, which is described here. 
 
-
-```@raw html
-<!-- ### Using `ACEpotentials` Potentials in External Software
-* [ACE descriptors](../literate_tutorials/descriptor.md)
-
-
-* [LAMMPS](lammps.md)
-* [Python with `ase`](python_ase.md)
-* [`Molly.jl`](molly.md) -->
-
-<!-- ### Structure analysis with ACE1 descriptors
-
-
-### Committee Potentials
-
-* [Committee Potentials](../literate_tutorials/committee.md)
-
-### Experimental Features
-
-* [Experimental Features](../literate_tutorials/experimental.md) -->
-```
-
-```@raw html 
-<!---
-### JSON Interface and Command line (OUTDATED)
-
-ACE potentials can be fitted from the command line using a dictionary stored in a `.json` or `.yaml` file to specify the parameters:
-
-* [TiAl Potential (ACEpotentials)](../literate_tutorials/ACEpotentials_TiAl.md)
-* [TiAl Potential (command line JSON)](../outdated/first_example_json.md)
-
--->
-```