docs: def set_parameters(self):
          """Setup all the parameters for the binaries to be evaluated.
  
          Grid values and store necessary parameters for input into the SNR function.
  
          """
  
          # declare 1D arrays of both paramters
          if self.xscale != 'lin':
              self.xvals = np.logspace(np.log10(float(self.x_low)),
                                       np.log10(float(self.x_high)),
                                       self.num_x)
  
          else:
              self.xvals = np.linspace(float(self.x_low),
                                       float(self.x_high),
                                       self.num_x)
  
          if self.yscale != 'lin':
              self.yvals = np.logspace(np.log10(float(self.y_low)),
                                       np.log10(float(self.y_high)),
                                       self.num_y)
  
          else:
              self.yvals = np.linspace(float(self.y_low),
                                       float(self.y_high),
                                       self.num_y)
  
          self.xvals, self.yvals = np.meshgrid(self.xvals, self.yvals)
          self.xvals, self.yvals = self.xvals.ravel(), self.yvals.ravel()
  
          for which in ['x', 'y']:
              setattr(self, getattr(self, which + 'val_name'), getattr(self, which + 'vals'))
  
          self.ecc = 'eccentricity' in self.__dict__
          if self.ecc:
              if 'observation_time' not in self.__dict__:
                  if 'start_time' not in self.__dict__:
                      raise ValueError('If no observation time is provided, the time before'
                                       + 'merger must be the inital starting condition.')
                  self.observation_time = self.start_time  # small number so it is not zero
          else:
              if 'spin' in self.__dict__:
                  self.spin_1 = self.spin
                  self.spin_2 = self.spin
  
          for key in ['redshift', 'luminosity_distance', 'comoving_distance']:
              if key in self.__dict__:
                  self.dist_type = key
                  self.z_or_dist = getattr(self, key)
  
              if self.ecc:
                  for key in ['start_frequency', 'start_time', 'start_separation']:
                      if key in self.__dict__:
                          self.initial_cond_type = key.split('_')[-1]
                          self.initial_point = getattr(self, key)
  
          # add m1 and m2
          self.m1 = (self.total_mass / (1. + self.mass_ratio))
          self.m2 = (self.total_mass * self.mass_ratio / (1. + self.mass_ratio))
          return