formatting_drift_dm.md
In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

print.drift_dm works as expected

Code
  print(a_dmc_model)
Output
  Class(es): dmc_dm, drift_dm

  Current Parameter Matrix:
         muc   b non_dec sd_non_dec  tau a    A alpha
  comp     4 0.6     0.3       0.02 0.04 2  0.1     4
  incomp   4 0.6     0.3       0.02 0.04 2 -0.1     4

  Unique Parameters:
         muc b non_dec sd_non_dec tau a A alpha
  comp   1   2 3       4          5   0 6 7    
  incomp 1   2 3       4          5   0 d 7

  Special Dependencies:
  A ~ incomp == -(A ~ comp)

  Custom Parameters:
         peak_l
  comp     0.04
  incomp   0.04

  Deriving PDFs:
    solver: kfe
    values: sigma=1, t_max=3, dt=0.001, dx=0.001, nt=3000, nx=2000

  Observed Data: 300 trials comp; 300 trials incomp

summary.drift_dm works as expected

Code
  print(summary_model)
Output
  Class(es): dmc_dm, drift_dm

  Current Parameter Matrix:
         muc   b non_dec sd_non_dec  tau a    A alpha
  comp     4 0.6     0.3       0.02 0.04 2  0.1     4
  incomp   4 0.6     0.3       0.02 0.04 2 -0.1     4

  Unique Parameters:
         muc b non_dec sd_non_dec tau a A alpha
  comp   1   2 3       4          5   0 6 7    
  incomp 1   2 3       4          5   0 d 7

  Special Dependencies:
  A ~ incomp == -(A ~ comp)

  Custom Parameters:
         peak_l
  comp     0.04
  incomp   0.04

  Observed Data:
               min. 1st qu. median  mean 3rd qu.  max.   n
  corr comp   0.331   0.436  0.479 0.507   0.549 1.075 292
  corr incomp 0.313   0.474  0.528 0.543   0.592 0.879 268
  err comp    0.428   0.458  0.526 0.564   0.621 0.871   8
  err incomp  0.302   0.398  0.452 0.458   0.498 0.771  32

  Fit Indices:
  Log_Like      AIC      BIC 
   137.067 -260.133 -229.355

  -------
  Deriving PDFs:
    solver: kfe
    values: sigma=1, t_max=3, dt=0.001, dx=0.001, nt=3000, nx=2000

  Boundary Coding:
    upper: corr 
    lower: err 
    expected data column: Error (corr = 0; err = 1)