Modify pipeline

README.md

@@ -1,53 +1,47 @@
 ![pytest](https://github.com/N3PDF/pycompressor/workflows/pytest/badge.svg)
 [![documentation](https://github.com/N3PDF/pycompressor/workflows/docs/badge.svg)](https://n3pdf.github.io/pycompressor/)
 
-### pycompressor
+## pycompressor
 
-Fast and efficient python implementation of PDF set **compressor** (https://arxiv.org/abs/1504.06469). 
+Fast and efficient python implementation of PDF **compression** (https://arxiv.org/abs/1504.06469). 
 
-#### New features
-
-Additional new features have been added to the following python package. The two main features are:
-- **Covariance Matrix Adaptation-Evlotion strategy (CMA-ES):** in addition to the Genetic 
-Algorithm (GA), there is now the possibility to choose as a minimizer the CMA. The choice
-of minimizer can be defined in the `runcard.yml` file.
-- **Generative Adversarial Strategy (GANs):** this is a standalone python [package](https://github.com/N3PDF/ganpdfs/tree/master)
-that can enhance the statistics of the prior PDF replicas before compression by generating 
-synthetic replicas. For more details, refer to the [documentation](https://n3pdf.github.io/ganpdfs/) 
-(still has to be done). In a similar way, in order to trigger the enhancement, one just has to set 
-the value of `enhance` in the runcard to be `True`. Setting this value to `False` will just run the 
-standard compression. The GANs also requires extra-parameters (as shown in the example 
-[runcard.yml](https://github.com/N3PDF/pycompressor/blob/master/runcard.yml)) that defines
-the structure of the networks.
-
-#### Installation
+### How to install
 
 To install `pyCompressor`, just type:
 ```bash
-python setup.py install
-```
-or if you are a developer:
-```bash
-python setup.py develop
+python setup.py install # or python setup.py develop (if you want development mode)
 ```
 
-#### How to use
+### How to use
+
+#### Standard compression
 
-The input parameters that define the compression is contained in a YAML file. To run
-the `pycompressor` code, just type the following: 
+The input parameters that define the compression is contained in a YAML file. To run the standard compression,
+use the reference [runcard](https://github.com/N3PDF/pycompressor/blob/master/runcards/runcard.yml) as it is by 
+just replacing the entry of the `pdf` key with the name of the PDF set, then run the following:
 ```bash
 pycomp runcards/runcard.yml [--threads NUMB_THREADS]
 ```
-A detailed instruction on how to set the different parameters in the runcard can be found here.
 
-#### Generating compressed PDF set & post-analysis
+#### Using GAN and/or Compressing from an enhanced set
+
+Although it is advised to run the [ganpdfs](https://github.com/N3PDF/ganpdfs) independently, it is possible
+to generate enhanced PDF replicas within the `pycompressor`. To do so, just set the entry `enhance` in the
+runcard to `True` and specify the total number of replicas (prior+synthetics).
+
+Finally, in  order to perform a compression with an enhanced set, set the entry `existing_enhanced` to `True`.
+
+A detailed instruction on how to set the different parameters in the runcard can be found 
+[here](https://n3pdf.github.io/pycompressor/howto/howto.html).
+
+### Generating compressed PDF set & post-analysis
 
 The code will create a folder named after the prior PDF sets. To generate the
 compressed PDF grid, run the following command:
 ```bash
 get-grid -i <PDF_NAME>/compressed_<PDF_NAME>_<NB_COMPRESSED>_output.dat
 ```
-Note that if the compression is done from an enhanced set, the output folder will be append by `_enhanced`.
+Note that if the compression is done from an enhanced set, the output folder will be appended by `_enhanced`.
 
 Finally, in order to generate ERF plots, enter in the `erfs_output` directory and run the following:
 ```bash
@@ -56,7 +50,7 @@ validate --random erf_randomized.dat --reduced erf_reduced.dat
 This script can also plot the ERF validation from the old compressor code by adding the flag
 `--format ccomp`.
 
-#### Warning
+### Warning
 
 This package cannot be installed with python 3.9 yet due to the numba dependency. This will be resolved
 soon according to [#6579](https://github.com/numba/numba/pull/6579).