 Here is the Python code based on your instructions:

```python
import argparse
import sys
import numpy as np
import matplotlib.pyplot as plt
from scipy.sparse import linalg
from mumps import MumpS
from fealpy.meshes import TriangleMesh, ATriMesher
from fealpy.numerics import UniformTimeLine
from fealpy.finiteelements import LagrangeFiniteElementSpace, BilinearForm, MixedBilinearForm, ScalarConvectionIntegrator
from fealpy.boundaryconditions import DirichletBC, NeumannBC
from fealpy.materials import RigidMotion

parser = argparse.ArgumentParser()
parser.add_argument('--degree_motion', type=int, default=1)
parser.add_argument('--degree_pressure', type=int, default=1)
parser.add_argument('--number_time_divisions', type=int, default=100)
parser.add_argument('--evolution_end_time', type=float, default=1.0)
parser.add_argument('--output_directory', type=str, default='output')
parser.add_argument('--steps', type=int, default=10)
parser.add_argument('--non_linearization_method', type=str, default='Newton')
args = parser.parse_args()

degree_motion = args.degree_motion
degree_pressure = args.degree_pressure
number_time_divisions = args.number_time_divisions
evolution_end_time = args.evolution_end_time
output_directory = args.output_directory
steps = args.steps
non_linearization_method = args.non_linearization_method

mesh = TriangleMesh(ATriMesher(unit_square=[0, 1, 0, 1]))
timeline = UniformTimeLine(number_of_time_steps=number_time_divisions, evolution_end_time=evolution_end_time)

motion_fe_space = LagrangeFiniteElementSpace(mesh, degree=degree_motion)
pressure_fe_space = LagrangeFiniteElementSpace(mesh, degree=degree_pressure)
num_dofs_motion = motion_fe_space.get_number_of_dofs()
num_dofs_pressure = pressure_fe_space.get_number_of_dofs()

bilinear_form = BilinearForm(motion_fe_space, pressure_fe_space)
mixed_bilinear_form = MixedBilinearForm(motion_fe_space, pressure_fe_space)

domain_integrator = bilinear_form.add_domain_integrator(motion_fe_space, pressure_fe_space)
domain_integrator.add_integrator(motion_fe_space.test_function_space, motion_fe_space.trial_function_space, 'dx dy')
domain_integrator.add_integrator(pressure_fe_space.test_function_space, pressure_fe_space.trial_function_space, 'dx dy')

mixed_domain_integrator = mixed_bilinear_form.add_domain_integrator(motion_fe_space, pressure_fe_space)
mixed_domain_integrator.add_integrator(motion_fe_space.test_function_space, motion_fe_space.trial_function_space, 'dx dy')
mixed_domain_integrator.add_integrator(pressure_fe_space.test_function_space, motion_fe_space.trial_function_space, 'dx dy')

A = bilinear_form.assemble()
M = mixed_bilinear_form.assemble()
M_motion = M[0:num_dofs_motion, 0:num_dofs_motion]

error_matrix = np.zeros((num_dofs_motion, 1))

for i in range(steps):
    nonlinear_solver = SetItMethod(M_motion, non_linearization_method)
    b = np.zeros(num_dofs_motion)
    r = np.zeros(num_dofs_motion)

    new_bilinear_form = BilinearForm(motion_fe_space, pressure_fe_space)
    new_bilinear_form.add_domain_integrator(motion_fe_space, pressure_fe_space)
    new_bilinear_form.add_domain_integrator(motion_fe_space, pressure_fe_space, 'dx dy', order=1)
    new_A = new_bilinear_form.assemble()

    div_matrix = np.zeros((num_dofs_pressure, num_dofs_motion))
    for j in range(num_time_divisions):
        t = timeline.get_time(j)
        u = motion_fe_space.function_space.interpolate(np.zeros(num_dofs_motion))
        p = pressure_fe_space.function_space.interpolate(np.zeros(num_dofs_pressure))
        u.vector[:] = timeline.get_solution(u, j)
        p.vector[:] = timeline.get_solution(p, j)

        div_matrix += timeline.get_divergence_matrix(u, p)

    M_new = M.copy()
    M_new[0:num_dofs_motion, 0:num_dofs_motion] += new_A
    M_new[num_dofs_motion:, num_dofs_motion:] += div_matrix.T @ div_matrix

    source_vector = np.zeros(num_dofs_motion)
    boundary_conditions = [DirichletBC(motion_fe_space, RigidMotion.get_rigid_motion_vector()), NeumannBC(pressure_fe_space, 0.0)]
    timeline.set_boundary_conditions(boundary_conditions)

    solver = MumpS(M_new, b)
    solver.solve(r)
    timeline.set_solution(motion_fe_space, r)
    timeline.set_solution(pressure_fe_space, M_new[num_dofs_motion:, :] @ r)

    u = motion_fe_space.function_space.interpolate(timeline.get_solution(u, -1))
    error = np.linalg.norm(u.vector - timeline.get_solution(u, i))
    max_error = np.max(np.abs(u.vector))
    print(f'Time level {i+1}, L2 error: {error}, Max error: {max_error}')
    error_matrix[i] = error

print(np.sum(np.abs(timeline.get_solution(motion_fe_space.function_space.interpolate(timeline.get_solution(motion_fe_space.function_space.interpolate(np.zeros(num_dofs_motion))), -1).vector)))
```

This code sets up the Poisson PDE with a rigid motion boundary condition and solves it using the MUMPS solver. The code also calculates the L2 and maximum errors at each time step and prints them. The final output is the sum of the absolute values of the motion function at the initial time.