parameters: (b, a, z)
return_statement: return(area)
docstring: The function computes the region of absolute stability based upon the
      coefficients 'a' and 'b' characterizing an integration method.  The
      given complex vector 'z' should be the unity circle.
docstring_summary: The function computes the region of absolute stability based upon the
      coefficients 'a' and 'b' characterizing an integration method.  The
      given complex vector 'z' should be the unity circle.
docstring_tokens: The function computes the region of absolute stability based upon the coefficients a and b characterizing an integration method . The given complex vector z should be the unity circle .
function: def zpoly (b, a, z):
      '''The function computes the region of absolute stability based upon the
      coefficients 'a' and 'b' characterizing an integration method.  The
      given complex vector 'z' should be the unity circle.
      '''
      # go through complex vectorz
      area = np.zeros(len(z), dtype=complex)
      for k in range(len(z)):
        bsum = 0
        asum = 0
        # sum denominator polynomial
        for i in range(len(b)):
          bsum = bsum + b[i] * power(z[k], -i)
        # sum numerator polynomial
        for i in range(len(a)):
          asum = asum + a[i] * power(z[k], -i)
        if (bsum == 0):
          bsum = 1
        area[k] = - asum / bsum
      return(area)
function_tokens: def zpoly ( b , a , z ) : # go through complex vectorz area = np . zeros ( len ( z ) , dtype = complex ) for k in range ( len ( z ) ) : bsum = 0 asum = 0 # sum denominator polynomial for i in range ( len ( b ) ) : bsum = bsum + b [ i ] * power ( z [ k ] , - i ) # sum numerator polynomial for i in range ( len ( a ) ) : asum = asum + a [ i ] * power ( z [ k ] , - i ) if ( bsum == 0 ) : bsum = 1 area [ k ] = - asum / bsum return ( area )