Update readme

Makefile

@@ -15,24 +15,15 @@ doc:
 clean:
 	rm -r dist
 
-package-pip:
+package:
 	python setup.py sdist bdist_wheel --universal
 
-package-conda :
-	conda build --py 3.9 conda-recipe
-
-package : package-pip package-conda
-
-tst-upload-pip:
+tst-upload:
 	twine upload --repository-url https://test.pypi.org/legacy/ dist/lca_algebraic*
 
-upload-pip:
+upload:
 	twine upload dist/lca_algebraic*
 
-upload-conda:
-	anaconda upload --force ~/mambaforge/conda-bld/noarch/lca_algebraic-$(VERSION)-py_0.tar.bz2
-
-upload : upload-pip upload-conda
 
 pytest:
 	pytest test

README.md

@@ -1,16 +1,14 @@
-
 # Introduction
 
 This library is a layer above [**brightway2**](https://brightway.dev/) designed for the definition of **parametric inventories** 
-with fast computation of LCA impacts, suitable for **monte-carlo** analyis.
+with fast computation of LCA impacts, suitable for **monte-carlo** / global sensitivity analysis 
 
-It integrates the magic of [Sympy](https://www.sympy.org/en/index.html) in order 
-to write parametric formulas as regular Python expressions.
+It integrates the magic of [Sympy](https://www.sympy.org/en/index.html) in order to write parametric formulas as regular Python expressions.
 
-**lca-algebraic** provides a set of  **helper functions** for : 
-* **compact** & **human readable** definition of activites :  
+**lca-algebraic** provides a set of **helper functions** for : 
+* **compact** & **human readable** definition of activities :  
     * search background (tech and biosphere) activities 
-    * create new foreground activites with parametrized amounts
+    * create new foreground activities with parametrized amounts
     * parametrize / update existing background activities (extending the class **Activity**)
 * Definition of parameters
 * Fast computation of LCAs
@@ -19,13 +17,14 @@ to write parametric formulas as regular Python expressions.
 # Installation
 
 We don't provide conda package anymore.
-Please use pip for installation
+
+This packages is available via [pip /pypi](https://pypi.org/project/lca-algebraic/)
 
 ## 1) Setup separate environement
 
 First create a python environment, with **Python** [>=3.9] :
 
-**With Conda or mamba**
+**With Conda (or [mamba](https://mamba.readthedocs.io/en/latest/index.html))**
 
 ```bash
 conda env create -n lca python==3.10
@@ -39,51 +38,18 @@ python3.10 -m venv .venv
 source .venv/bin/activate
 ```
 
-
 ## 2) Install lca_algebraic
 
 > pip install lca_algebraic
 
 
-# Usage & documentation 
-
-Please refer to the [online documentation](https://lca_algebraic.readthedocs.org/)
-
 # Licence & Copyright
 
-This library has been developed by [OIE - MinesParistech](http://www.oie.mines-paristech.fr), for the project *INCER-ACV*, 
+This library has been developed by [OIE - MinesParistech](http://www.oie.mines-paristech.fr), for the project [*INCER-ACV*](https://librairie.ademe.fr/energies-renouvelables-reseaux-et-stockage/4448-incer-acv.html), 
 lead by [ADEME](https://www.ademe.fr/). 
 
-It is distributed under the **[BSD licence](/LICENSE)**.
-
-
-# Principles 
-
-The main idea of this libray is to move from **procedural definition** of models (slow and prone to errors) to a **declarative / purely functionnal** definition of parametric models (models as **pure functions**). 
-
-This enables **fast computation of LCA impacts**. 
-We leverage the **power of symbolic calculus** provided by the great libary [SymPy](https://www.sympy.org/en/index.html).
-
-We define our model in a **separate DB**, as a nested combination of : 
-* other foreground activities
-* background activities :
-    * Technical, refering **ecoinvent DB**
-    * Biopshere, refering **brightway2** biosphere activities
-
-The **amounts** in exchanges are expressed either as **static amounts**, or **symbolic expressions** of pre-defined **parameters**.
-
-Each activity of our **root model** is defined as a **parametrized combination** of the **foreground activities**, which can themselves be expressed by the **background activities**.
-
-When computing LCA for foreground models, the library develops the model as a combination of **only background activities**. It computes **once for all** the impact of **background activities** and compiles a **fast numpy** (vectorial) function for each impact, replacing each background activity by the **static value of the corresponding impact**.
-
-By providing **large vectors** of **parameter values** to those numpy functions, we can compute LCA for **thousands of values** at a time.
-
-
-# Compatibility with brightway2 
-
-Under the hood, the activities we define with **lca-algebraic** are standard **brightway2** activities. 
-The amounts of exchanges are stored as **float values** or **serialized as string** in the property **formula**.
+It is distributed under the [BSD License](./LICENSE)
 
-Parameters are also stored in the **brightay2** projets, making it fully compatible with **brightway**.
+# Documentation
 
-Thus, a model defined with **lca-algebraic** is stored as a regular **bw2** projet. We can use **bw2** native support for [parametrized dataset](https://2.docs.brightway.dev/intro.html#parameterized-datasets) for computing LCAs, even if much more slower than the method explain here.
+Full documentation and example notebooks are [hosted on **readthedocs**](https://lca-algebraic.readthedocs.io/)