foldername = 'Data_été' filename = 'results_name.txt' xlsname = 'results_name.xls' mapname = 'map_name.png' # Extracting data from xls files and creating 4 ppc matrices os.chdir(foldername) ppc = loadcase(caseproject()) bus, gen, branch, gencost = freadexcel() ppc["bus"] = bus ppc["branch"] = branch ppc["gen"] = gen ppc["gencost"] = gencost # Running the simulation r = rundcopf(ppc, fname=filename) # Storing results results_gen, results_load_lambda, results_branch = fstoreresult(r) # Writing results in xls file # fwriteinexcel(xlsname, results_gen, results_load_lambda, results_branch) # Creating a map with the results results_branch_map = [] for i in range(len(branch)): inter = [results_branch[i, 0], results_branch[i, 1], results_branch[i, 2], branch[i, 5]] results_branch_map.append(inter) results_branch_map = np.asarray(results_branch_map, dtype=np.float64) fmap(results_branch_map, results_gen, results_load_lambda, mapname)
def test_fmap(): seen = [] def accum(name): seen.append(name) fmap(TESTDIR, accum) assert set(seen) == {'c', 'd', 'f', 'g', 'h'} del seen[:] fmap(TESTDIR, accum, max_depth=0) assert set(seen) == {'c', 'd'} del seen[:] fmap(TESTDIR, accum, apply_dirs=True) assert set(seen) == {'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'} del seen[:] fmap(TESTDIR, accum, apply_dirs=True, max_depth=0) assert set(seen) == {'a', 'b', 'c', 'd'} del seen[:] fmap(TESTDIR, accum, excludes=['a']) assert set(seen) == {'c', 'd', 'h'} del seen[:] fmap(TESTDIR, accum, patterns=['g', 'd', 'h'], excludes=['a']) assert set(seen) == {'d', 'h'}
"children": [ { "name": "Zerg", "children" : [] }, { "name": "Protoss", "children" : [] }, { "name": "Terran", "children": [] } ] } races = { "Zerg": fmap(), "Protoss": fmap(), "Terran": fmap() } losingraces = { "Zerg": fmap(), "Protoss": fmap(), "Terran": fmap() } df = read_csv('sc2_korean_p0_p199.csv') for i,race in enumerate(df['winner_race']): races[race][df['winner_name'][i]] += 1