class_docstr: Tracks the performance of the algorithm.
code: def process_capital_change(self, capital_change_amount, is_interday):
      self.cumulative_performance.set_current_subperiod_starting_values(
          capital_change_amount
      )
  
      if is_interday:
          # Change comes between days
          self.todays_performance.adjust_period_starting_capital(
              capital_change_amount
          )
      else:
          # Change comes in the middle of day
          self.todays_performance.set_current_subperiod_starting_values(
              capital_change_amount
          )
  
imports: from __future__ import division
  import logbook
  import pandas
  from pandas.tseries.tools import normalize_date
  from catalyst.finance.performance.period import PerformancePeriod
  from catalyst.errors import NoFurtherDataError
  import catalyst.finance.risk
  from .position_tracker import PositionTracker
  from catalyst.constants import LOG_LEVEL
label_desc: Use image node_id 11 for calling the PerformanceTracker obj's underlying member method code with example usage: obj.process_capital_change(capital_change_amount, is_interday) without return types