code: def create_simulation_parameters(
      year=2016,
      start=None,
      end=None,
      capital_base=float("1.0e5"),
      num_days=None,
      data_frequency="daily",
      emission_rate="daily",
      trading_calendar=None,
  ):
      if not trading_calendar:
          trading_calendar = get_calendar("OPEN")
  
      if start is None:
          start = pd.Timestamp("{0}-01-01".format(year), tz="UTC")
      elif type(start) == datetime:
          start = pd.Timestamp(start)
  
      if end is None:
          if num_days:
              start_index = trading_calendar.all_sessions.searchsorted(
                  start
              )
              end = trading_calendar.all_sessions[
                  start_index + num_days - 1
              ]
          else:
              end = pd.Timestamp("{0}-12-31".format(year), tz="UTC")
      elif type(end) == datetime:
          end = pd.Timestamp(end)
  
      sim_params = SimulationParameters(
          start_session=start,
          end_session=end,
          capital_base=capital_base,
          data_frequency=data_frequency,
          emission_rate=emission_rate,
          trading_calendar=trading_calendar,
      )
  
      return sim_params
  
imports: import pandas
  import numpy
  from datetime import timedelta, datetime
  from catalyst.assets import Asset
  from catalyst.finance.transaction import Transaction
  from catalyst.protocol import Event, DATASOURCE_TYPE
  from catalyst.sources import SpecificEquityTrades
  from catalyst.finance.trading import SimulationParameters
  from catalyst.sources.test_source import create_trade
  from catalyst.data.loader import load_from_yahoo, load_bars_from_yahoo
  from catalyst.utils.calendars import get_calendar
  from catalyst.utils.input_validation import expect_types
label_desc: Use image node_id 1 for calling a global function with example usage: create_simulation_parameters(year, start, end, capital_base, num_days, data_frequency, emission_rate, trading_calendar) and returns: sim_params