.. Modelflow documentation master file, created by
   sphinx-quickstart on Tue Jul 26 14:43:11 2022.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.


Welcome to ModelFlow's documentation!
######################################

A Python toolkit to manage models


The **Pandas** library is a great library to handle all kinds of datamanipulation and transformations. 

However when it comes to models which contains lags or models which requires solving simultanous equations, Pandas is not quite helpful. 

ModelFlow extends Pandas to handle a range of such models. And they can be large.  

It requires you to specify the *model* specified as equations (the **business logic**) and place the *data* in a Pandas  **DataFrame**.  ModelFlow allows the model to meet the data and return the result as a new DataFrame. 

A number of **analytical tools for model and result analytic** helps to understand the model and its results.

The user can **extend and modify the tools** to her or his needs.

**Onboarding models and combining models from different sources**. Creating a Macro prudential model often entails recycling several models specified in different ways: Excel, Latex, Dynare, Python or other languages. Python's ecosystem makes it possible to transform many different models into ModelFlow models or to wrap them into functions which can be called from ModelFlow models.

**Models can be specified in a high level Business logic language (a Domain Specific language)**. This allows the formulation of a model in a concise and expressive language which is close to the economic of the model. The user can concentrate on the economic or financial content - not the coding of the solution. The code for solving the model is generated by the tool. Then you can *solve the
simultaneous* (or *non-simultaneous* model) in an efficient way. 



If you need a feature or have a model which can't be handled in ModelFlow,
you are encouraged to improve ModelFlow. Please share the
improvement, other users may have the same need, or can be inspired by
your work.

Bear in mind that ModelFlow is experimental. It is provided ”as is”, without any representation or warranty of any kind either express or implied.   

You will find a tutorial here: https://ibhansen.github.io/index.html



Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

Modules
==================


.. toctree::
   :maxdepth: 3
   :caption: content:
   :glob:

   Introduction
   Installation
   core/Core
   onboard/onboard
   attribution/Attribution
   Quick result visualization <vis/modelvis>
   report/modelreport
   Dashboard <plotly/modeldashsidebar>
   jupyter/jupyter
   Targets and instruments <used/modelinvert>
   Enrich dataframes with modelflow <used/modelmf>
   Convex optimization <used/model_cvx>
   Template for a user defined  model class based on the model class <used/modelsandbox>



.. .. toctree::
..    :maxdepth: 3
..    :caption: Unsorted:
..    :glob:

.. ..   unsorted/*