update information on getting started page

Author: fsoubelet

docs/packages/omc3/getting_started.md

@@ -1,35 +1,39 @@
 # Getting Started with OMC3
 
-## Quick start
+## Installing
 
-The `omc3` package is `Python 3.7+` compatible, but not yet deployed to PyPI.
-The best way to install is though python -m pip and VCS:
+The package is deployed to `PyPI` and installation is easily done via `pip`:
 
 ```bash
-git clone https://github.com/pylhc/omc3
-python -m pip install /path/to/omc3
+python -m pip install omc3
 ```
 
-Or simply from the online master branch, which is stable:
+Additionally, some features require access to the CERN Technical Network and require CERN-specific dependencies.
+Those are installable from the CERN [Acc-Py][accpy_docs]{target=_blank .cern_internal} index through the `cern` extra, and can be installed from the CERN network or by providing the `index-url`:
 
 ```bash
-python -m pip install git+https://github.com/pylhc/omc3.git
+python -m pip install --index-url http://acc-py-repo.cern.ch:8081/repository/vr-py-releases/simple --trusted-host acc-py-repo.cern.ch "omc3[cern]"
 ```
 
 After installing, codes can be run with either `python -m omc3.SCRIPT --FLAG ARGUMENT` or calling path to the `.py` file directly.
 
 ## Functionality
 
+For detailed information on the various parts of the package, please refer to the [documentation][omc3_docs]{target=_blank}.
+
 ### Main Scripts
 
 Main scripts to be executed lie in the `/omc3` module directly. These include:
 
 - `hole_in_one.py` to perform frequency analysis on turn by turn BPM data and infer optics (and more) for a given accelerator.
-- `madx_wrapper.py` to start a `MAD-X` run with a file or string as input.
-- `model_creator.py` to provide optics models required for optics analysis.
-- `run_kmod.py` to analyse data from K-modulation and return the measured optics functions.
-- `tbt_converter.py` to convert different turn by turn datatypes to sdds, and add noise.
+- `kmod_importer.py` to average, import and calculate lumi-imbalace K-modulation results.
+- `knob_extractor.py` to extract from `NXCALS` the value of given knobs in the machine at a given time.
+- `model_creator.py` to generate optics models required for optics analysis.
+- `global_correction.py` to calculate corrections from measurement files.
+- `response_creator.py` to provide correction response files.
+- `tbt_converter.py` to convert different turn by turn data types to `SDDS`, potentially adding noise.
 - `amplitude_detuning_analysis.py` to perform amp. det. analysis on optics data with tune correction.
+- `madx_wrapper.py` to start a `MAD-X` run with a file or string as input.
 
 ### Plotting Scripts
 
@@ -39,14 +43,25 @@ Plotting scripts for analysis outputs can be found in the `/omc3/plotting` submo
 - `plot_bbq.py` to generate plots from files generated by BBQ analysis.
 - `plot_amplitude_detuning.py` to generate plots from files generated by amplitude detuning analysis.
 - `plot_optics_measurements.py` to generate plots from files generated by optics_measurements.
-- `plot_tfs.py` all purpose tfs-file plotter.
+- `plot_tfs.py` to plot TFS file contents.
+- `plot_kmod_results.py` to plot the beta and waist of the K-modulation results.
 
 ### Other Scripts
 
 Other general utility scripts are in `/omc3/scripts` module:
 
 - `update_nattune_in_linfile.py` to update the natural tune columns in the lin files by finding the highest peak in the spectrum in a given interval.
-- `write_madx_macros.py` to generate `MAD-X` tracking macros with observation points from a twiss file.
-- `merge_kmod_results.py` to merge lsa_results files created by kmod, and add the luminosity imbalance if the 4 needed IP/Beam files combination are present.
+- `write_madx_macros.py` to generate `MAD-X` tracking macros with observation points from a TWISS file.
+- `merge_kmod_results.py` to merge LSA results files created by kmod, and add the luminosity imbalance if the 4 needed IP/Beam files combination are present.
+- `fake_measurement_from_model.py` to create a fake measurement based on a model TWISS file.
+- `betabeatsrc_output_converter.py` to convert outputs from our old codes to `omc3`'s new standardized format.
+- `linfile_clean.py` to automatically clean given columns in lin files.
+- `kmod_average.py` to calculate the average of multiple K-modulation measurements.
+- `kmod_import.py` to import a K-modulation measurement into an optics-measurement directory.
+- `kmod_lumi_imbalace.py` to calculate the luminosity imbalance between two IPs from averaged K-modulation files.
+- `bad_bpms_summary.py` to collect and summarize the bad BPMs from GUI runs.
 
 A typical analysis workflow with `omc3` is described in the [next page](analysis.md).
+
+[accpy_docs]: https://wikis.cern.ch/display/ACCPY/Accelerating+Python+Home
+[omc3_docs]: https://pylhc.github.io/omc3/