sergiolucero · December 4, 2017 20:05 · fanyang-ceg · Dec 4, 2017
diff --git a/cplex_demo.py b/cplex_demo.py
 from forestry import ForestryLinearProgram      # this is project-specific
 from PuLP.solvers import CBC            # open-source LinearProgramming library and solver
 from creds import BASE_URL, API_KEY     # these are used to id with IBM
 from docloud.job import JobClient

 my_problem = ForestryLinearProgram('forestry_test.xlsx')    # input file contains all relevant tree data

 #my_problem.solve(CBC)     # this is how we used to work, until our problems grew too big for open-source

 my_problem.save_to_MPS('forestry_LP.mps')     # here we export to a format that IBM CPLEX can recognize
 client = JobClient(BASE_URL, API_KEY)
 resp = client.execute(input = 'forestry_LP.mps', output = 'solution.json')
	from forestry import ForestryLinearProgram # this is project-specific
	from PuLP.solvers import CBC # open-source LinearProgramming library and solver
	from creds import BASE_URL, API_KEY # these are used to id with IBM
	from docloud.job import JobClient

	my_problem = ForestryLinearProgram('forestry_test.xlsx') # input file contains all relevant tree data

	#my_problem.solve(CBC) # this is how we used to work, until our problems grew too big for open-source

	my_problem.save_to_MPS('forestry_LP.mps') # here we export to a format that IBM CPLEX can recognize
	client = JobClient(BASE_URL, API_KEY)
	resp = client.execute(input = 'forestry_LP.mps', output = 'solution.json')