Verdandi is a generic C++ library for data assimilation.

Verdandi is currently developed at INRIA. It aims at providing methods and tools for data assimilation. It is designed to be relevant to a large class of problems involving high-dimensional numerical models.

To guarantee the highest performance, the library is implemented in C++. In addition, Verdandi provides a Python interface generated by Swig.

Models implemented in Fortran, C, C++, Python, ... can be plugged to Verdandi using either a C++ or Python interface.

Verdandi is provided under the GNU Lesser General Public License (LGPL).

Scientific Context

Data assimilation is the process of combining different sources of information in order to better estimate the state of a system. By extension, some parameters can also be estimated. These methods were originally introduced to deal with uncertainties present in models pertaining mostly to geophysics, but it is now widely recognized that they have a tremendous potential in many other applications (see euHeart example below).

Whether the system be biological, environmental, mechanical, etc., the main sources of information are always a numerical model, observations and error statistics. Data assimilation methods can be written independently of the system to which they are applied, and each method can be applied to a wide class of systems. Therefore methods are generic and can be put together in a library.

What is Verdandi for?

What is Verdandi designed for?

Who can be a Verdandi user?

The users provide the numerical model and the observations with the appropriate interface.


The development of Verdandi has been financially supported by the European research initiative euHeart (2008-2012), which aimed at developing, sharing and integrating patient-specific multi-physics and multi-level models of the heart and great vessels in normal and pathological conditions to address clinical challenges. In this project, data assimilation was thus a means to allow the personalization of the biophysical models considered in order to perform genuinely patient-specific simulations.

Verdandi has also been partly supported by the European research initiative VPH-Share (2011-2015), specifically as regards high-performance computing features. The global objectives of VPH-Share were to develop the infostructure and integrate the optimized services to expose and share data and knowledge, jointly develop multiscale models for the composition of new VPH workflows, and facilitate collaborations within the VPH community.

Since 2013, Verdandi is also partly supported by the European research initiative VP2HF. Specifically targeted on heart failure and the patient-specific modeling thereof, the primary aim of VP2HF is to bring together image and data processing tools with statistical and integrated biophysical models mainly developed in previous VPH projects, into a single clinical workflow to improve therapy selection and treatment optimization.