def test_transform_real_shopmodel():
with open('./test/gams/real-shopmodel.gms', 'r') as in_file:
gp = GamsParser(in_file)
model = gp.transform()
print("\nModel\n")
print(model)
print("\nSymbols:\n")
for s in model.symbol():
print(s)
def test_transform_real_shopmodel():
with open('./test/gams/inject-datagen.inc','r') as gen_file, \
open('./test/gams/inject-datademand.inc','r') as demand_file, \
open('./test/gams/inject-siteanalysis.gms','r') as main_file:
gp_main = GamsParser(main_file)
gp_gen = GamsParser(gen_file)
gp_demand = GamsParser(demand_file)
model_main = gp_main.transform()
model_gen = gp_gen.transform()
model_demand = gp_gen.transform()
model = model_main + model_gen + model_demand
print("\nModel\n")
print(model)
print("\nSymbols:\n")
for s in model.symbol():
print(s)
def test_transform_equation_def():
with open('./test/gams/equation-basic.gms', 'r') as in_file:
gp = GamsParser(in_file)
parse_tree = gp.parse()
print(parse_tree.pretty())
model = gp.transform()
print("\nModel\n")
print(model)
print("\nSymbols:\n")
for s in model.symbol():
print(s)
def test_transform_model_siteanalysis():
with open('./test/gams/real-siteanalysis.gms', 'r') as in_file:
gp = GamsParser(in_file)
model = gp.transform()
print("\nModel\n")
print(model)
print("\nSymbols:\n")
for s in model.symbol():
print(s)
dm = model.toJSON()
#print("\nmodel.toJSON\n")
#print(dm)
print("\nmodel.toDict Hack\n")
m = model.toDict()
scrub_meta(m)
pprint.pprint(m)