Metadata-Version: 2.1
Name: hadar
Version: 0.3.1
Summary: python adequacy library
Home-page: https://github.com/hadar-simulator/hadar
Author: RTE France
Author-email: francois.jolain@rte-international.com
License: UNKNOWN
Description: # Hadar
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        Hadar is a adequacy python library for deterministic and stochastic computation
        
        ## Adequacy problem
        ### Basic
        
        Each kind of network has a needs of adequacy. On one side, some network nodes need to consume
        items such as watt, litter, package. And other side, some network nodes produce items.
        Applying adequacy on network, is tring to find the best available exchanges to avoid any lack at the best cost.
        
        For example, a electric grid can have some nodes wich produce too more power and some nodes which produce not enough power.
        
        ![adequacy](examples/Get%20Started/figure.png)
        
        
        ### Complexity comes soon
        Above example is simple, but problem become very tricky with 10, 20 or 500 nodes !
        
        Moreover all have a price ! Node can have many type of production, and each kind of production has its unit cost. Node can have also many consumptions with specific unavailability cost. Links between node have also max capacity and cost.
        
        Network adequacy is not simple.
        
        ## Hadar
        Hadar computes adequacy from simple to complex network. For example, to compute above network, just few lines need:
        
        ``` python
        import hadar as hd
        
        study = hd.Study(horizon=3)\
            .network()\
                .node('a')\
                    .consumption(cost=10 ** 6, quantity=[20, 20, 20], name='load')\
                    .production(cost=10, quantity=[30, 20, 10], name='prod')\
                .node('b')\
                    .consumption(cost=10 ** 6, quantity=[20, 20, 20], name='load')\
                    .production(cost=10, quantity=[10, 20, 30], name='prod')\
                .link(src='a', dest='b', quantity=[10, 10, 10], cost=2)\
                .link(src='b', dest='a', quantity=[10, 10, 10], cost=2)\
            .build()
        
        optimizer = hd.LPOptimizer()
        res = optimizer.solve(study)
        ```
        
        And few more lines to display graphics results.
        
        ```python
        plot = hd.HTMLPlotting(agg=hd.ResultAnalyzer(study, res),
                               node_coord={'a': [2.33, 48.86], 'b': [4.38, 50.83]})
        plot.network().node('a').stack()
        plot.network().map(t=0, zoom=2.5)
        ```
        
        Get more information and examples at [https://www.hadar-simulator.org/](https://www.hadar-simulator.org/)
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
