ODL 0.6.0
Creators
- 1. KTH Royal institute of Technology
- 2. Centrum Wiskunde & Informatica
- 3. KTH - Royal Institute of Technology
Description
ODL
Operator Discretization Library (ODL) is a Python library for fast prototyping focusing on (but not restricted to) inverse problems. ODL is being developed at KTH Royal Institute of Technology, Stockholm, and Centrum Wiskunde & Informatica (CWI), Amsterdam.
The main intent of ODL is to enable mathematicians and applied scientists to use different numerical methods on real-world problems without having to implement all necessary parts from the bottom up. This is reached by an Operator structure which encapsulates all application-specific parts, and a high-level formulation of solvers which usually expect an operator, data and additional parameters. The main advantages of this approach are that
- Different problems can be solved with the same method (e.g. TV regularization) by simply switching operator and data.
- The same problem can be solved with different methods by simply calling into different solvers.
- Solvers and application-specific code need to be written only once, in one place, and can be tested individually.
- Adding new applications or solution methods becomes a much easier task.
Files
odlgroup/odl-v0.6.0.zip
Files
(1.4 MB)
Name | Size | Download all |
---|---|---|
md5:15fa27184eb58ec2e0c09a9c25b46d6e
|
1.4 MB | Preview Download |
Additional details
Related works
- Is supplement to
- https://github.com/odlgroup/odl/tree/v0.6.0 (URL)