Calculating multiple related Custom Factors efficiently

I am trying to calculate the following custom factors.
Enterprise_Value, EBITDA and EV_TO_EBITDA ratio.
The following works.
Many of these calculations are redundant when done in separate factors.

Is there a more efficient of building these 3 factors, possibly reusing the previous custom factors OR calculating multiple factors within the same custom factors.

# Create custom factor to calculate a market cap based on yesterday's close  
# We'll use this to get the top 2000 stocks by market cap  
class EnterpriseValue(CustomFactor):  
    # Pre-declare inputs and window_length  
    inputs = [USEquityPricing.close, valuation.shares_outstanding, balance_sheet.long_term_debt,  
              balance_sheet.long_term_debt_and_capital_lease_obligation,  
              balance_sheet.cash_cash_equivalents_and_marketable_securities]  
    window_length = 1  
    # Compute market cap value  
    def compute(self, today, assets, out, close, shares,  
                long_term_debt, long_term_debt_and_capital_lease_obligation,  
                cash_cash_equivalents_and_marketable_securities):  
        out[:] = close[-1] * shares[-1] + long_term_debt_and_capital_lease_obligation[-1] \  
                                        - cash_cash_equivalents_and_marketable_securities[-1]

# Create custom factor to calculate a market cap based on yesterday's close  
# We'll use this to get the top 2000 stocks by market cap  
class EBITDA(CustomFactor):  
    # Pre-declare inputs and window_length  
    inputs = [income_statement.ebitda]  
    window_length = 200  
    # Compute market cap value  
    def compute(self, today, assets, out, ebitda):  
        out[:] = ebitda[-1]+ebitda[-64]+ebitda[-127]+ebitda[-190]  
#        out[:] = ebitda[-60]

# Create custom factor to calculate a market cap based on yesterday's close  
# We'll use this to get the top 2000 stocks by market cap  
class EV_TO_EBITDA(CustomFactor):  
    # Pre-declare inputs and window_length  
    inputs = [USEquityPricing.close, valuation.shares_outstanding, balance_sheet.long_term_debt,  
              balance_sheet.long_term_debt_and_capital_lease_obligation,  
              balance_sheet.cash_cash_equivalents_and_marketable_securities,  
              income_statement.ebitda]  
    window_length = 200  
    # Compute market cap value  
    def compute(self, today, assets, out, close, shares,  
                long_term_debt, long_term_debt_and_capital_lease_obligation,  
                cash_cash_equivalents_and_marketable_securities,ebitda):  
        ev = close[-1] * shares[-1] + long_term_debt_and_capital_lease_obligation[-1] \  
                                        - cash_cash_equivalents_and_marketable_securities[-1]  
        ebitda = ebitda[-1]+ebitda[-64]+ebitda[-127]+ebitda[-190]  
        out[:] = ev / ebitda  
#        out[:] = ebitda[-60]

pipe = Pipeline() attach_pipeline(pipe, 'example') # declare your ev custom factor ev = EnterpriseValue() pipe.add(ev, 'ent_value') # declare your ebitda custom factor ebitda = EBITDA() pipe.add(ebitda, 'ebitda') # divide ev/ebitda results in a new factor ev_to_ebitda = ev/ebitda pipe.add(ev_to_ebitda, 'ev_to_ebitda')