retrieving nlpsol stats with to_function

demo.m

import casadi.*

opti = Opti();

x = opti.variable(2);

fx = sin(x)-[2;0.3];

opti.minimize(sumsqr(fx));

opti.solver('ipopt');

f = opti.to_function('f',{x},{fx});

f(3);

get_stats(f)

demo.py

# Note: this is very hacky.

from casadi import *

opti = Opti()

x = opti.variable(2)

fx = sin(x)-vertcat(2,0.3)

opti.minimize(sumsqr(fx))

opti.solver('ipopt')

f = opti.to_function('f',[x],[fx])

f(3)

def get_stats(f):
  dep = None
  # Loop over the algorithm
  for k in range(f.n_instructions()):
    if f.instruction_id(k)==OP_CALL:
      d = f.instruction_MX(k).which_function()
      if d.name()=="solver":
        dep = d
        break
  if dep is None:
    return {}
  else:
    return dep.stats(1)

print(get_stats(f))

get_stats.m

function [stats] = get_stats(f)
  dep = 0;
  % Loop over the algorithm
  for k=0:f.n_instructions()-1
    if f.instruction_id(k)==casadi.OP_CALL
      d = f.instruction_MX(k).which_function();
      if d.name()=='solver'
        dep = d;
        break
      end
    end
  end
  if dep==0
    stats = struct;
  else
    stats = dep.stats(1);
  end
end