- All study numerical values can be set for all scenario and/or all timestep - improve documentation with tutorial and new style
0.4.0
In this release: - multi-energies: Hadar can handle multi-network study. Each network has it own energy, user can set `hd.Converter` element to link networks together; - storage: Hadar provides `hd.Storage` element
0.3.1
- Homogenize API by creating a *Fluent API Selector* for `optimizer`, `analyzer` and `viewer`. - Refactor `Remote Optimizer` to be asynchrone and setup a feedback to user during queuing
0.3.0
- Add complet sphinx documentation to understand architecture and mathematics optimization - Add lot of graphics to analyze result
0.2.0
New Hadar has main improvments: - Now hadar can be used like numpy or else like `import hadar as hd`then any object can be called by `hd.*` like optimizer for example`optimizer = hd.LPOptimizer()` - Hadar has also a complet workflow framework to generate timeline for preprocessing