Scenario simulation

[cfraces]

Create a generate_secnario() method in Economics that takes as arguments:

• n_sce: number of samples (ex: 1000)
• param: dictionary with variable to be simulated (ex: param={"gas_price_start": {"type:'normal', 'loc':0.5, 'scale':0.01}})
• We will follow scipy.stats API for distribution definition And runs Monte Carlo simulation of economics based on input variables

[dungnguyensarasota]

Dear @cfraces Please review the generate_scenario() method and the way I vectorize the computation

[cfraces]

@dungnguyensarasota Please operate a true vectorization of your compute() method input should be np.array([[value]])

[cfraces]

@dungnguyensarasota Exemple:
project_length = np.array([[20],[21],[19]], dtype=int) production_arr = np.array([[36500, 21900, 17520, 14016, 12614, 11353, 10218, 9196, 8736, 8299, 7884, 7490, 7116, 6760, 6422, 6101, 5796, 5506, 5231, 4969], [30000, 21000, 17000, 14000, 12000, 11353, 10218, 9196, 8736, 8299, 7884, 7490, 7116, 6760, 6422, 6101, 5796, 5506, 5231, 4969], [36500, 21900, 17520, 14016, 12614, 11353, 10218, 9196, 8736, 8299, 7884, 7490, 7116, 6760, 6422, 6101, 5796, 5506, 5231, 4969]], dtype=float)

[dungnguyensarasota]

Dear @cfraces I've created compute_vectorize method for a base case of gas_price_start simulation Please review

[dungnguyensarasota]

Dear @cfraces I've updated compute_vectorize which can run on all cases of simulation Please review

[cfraces]

@dungnguyensarasota compute_vectorize has the wrong input. It should not have any simulation parameters or n_sce. Just params. The generate_scenario function takes care of the generation of simulated inputs