postprocessor.py 文件源码

def aggregate_regions(fp):

  # aggregate regions and supply portfolios
  # easier to do this with pandas by just reading the CSVs again
  sc = pd.read_csv(fp + '/shortage_cost.csv', index_col=0, parse_dates=True)
  sv = pd.read_csv(fp + '/shortage_volume.csv', index_col=0, parse_dates=True)
  flow = pd.read_csv(fp + '/flow.csv', index_col=0, parse_dates=True)
  demand_nodes = pd.read_csv('calvin/data/demand_nodes.csv', index_col = 0)
  portfolio = pd.read_csv('calvin/data/portfolio.csv', index_col = 0)

  for R in demand_nodes.region.unique():
    for t in demand_nodes.type.unique():
      ix = demand_nodes.index[(demand_nodes.region == R) & 
                              (demand_nodes.type == t)]
      sc['%s_%s' % (R,t)] = sc[ix].sum(axis=1)
      sv['%s_%s' % (R,t)] = sv[ix].sum(axis=1)

  for P in portfolio.region.unique():
    for k in portfolio.supplytype.unique():
      for t in portfolio.type.unique():
        ix = portfolio.index[(portfolio.region == P) & 
                             (portfolio.type ==t) & 
                             (portfolio.supplytype == k)]
        flow['%s_%s_%s' % (P,k,t)] = flow[ix].sum(axis=1)

  sc.to_csv(fp + '/shortage_cost.csv')
  sv.to_csv(fp + '/shortage_volume.csv')
  flow.to_csv(fp + '/flow.csv')