```python
import argparse
import sys
import numpy as np
import matplotlib.pyplot as plt
import scipy
from scipy import sparse
import mumps
from fealpy.mesh import MeshFactory as MF
from fealpy.timeintegratoralg import UniformTimeLine
from fealpy.functionspace import LagrangeFiniteElementSpace
from fealpy.bilinearform import BilinearForm, MixedBilinearForm
from fealpy.boundarycondition import DirichletBC
from fealpy.navier_stokes_mold_2d import PoisuillePDE

# Set up command-line argument parser
parser = argparse.ArgumentParser(description="Poisuille PDE Solver")
parser.add_argument("--degree_motion", type=int, default=2, help="Degree of motion finite element space")
parser.add_argument("--degree_pressure", type=int, default=1, help="Degree of pressure finite element space")
parser.add_argument("--num_time_divisions", type=int, default=100, help="Number of time divisions")
parser.add_argument("--end_time", type=float, default=1.0, help="Evolution end time")
parser.add_argument("--output_dir", type=str, default="./output", help="Output directory")
parser.add_argument("--steps", type=int, default=10, help="Steps for output")
parser.add_argument("--non_linearization_method", type=str, default="Newton", help="Non-linearization method")

# Parse arguments
args = parser.parse_args()

# Mesh and time setup
mesh = MF.unit_square_mesh(n=4)
timeline = UniformTimeLine(0, args.end_time, args.num_time_divisions)

# Finite element spaces
space_motion = LagrangeFiniteElementSpace(mesh, p=args.degree_motion)
space_pressure = LagrangeFiniteElementSpace(mesh, p=args.degree_pressure)

# Degrees of freedom
ndof_motion = space_motion.number_of_global_dofs()
ndof_pressure = space_pressure.number_of_global_dofs()

# Bilinear and mixed bilinear forms
a = BilinearForm(space_motion, PoisuillePDE.integrator)
a_mixed = MixedBilinearForm(space_motion, space_pressure, PoisuillePDE.integrator)

# Assemble matrices
a.assemble()
A = a.matrix

a_mixed.assemble()
B = a_mixed.matrix

# Mass matrix
M = space_motion.mass_matrix()

# Error matrix initialization
error_matrix = np.zeros((args.num_time_divisions, 1))

# Time evolution
for i in range(args.num_time_divisions):
    timeline.advance()

    # New bilinear form for each time step
    a_new = BilinearForm(space_motion, PoisuillePDE.integrator)
    a_new.assemble()
    A_new = a_new.matrix

    # Divergence matrix and new matrix M
    # Assuming divergence matrix and M calculation are abstracted
    # Divergence and M matrix calculation would depend on the specific problem and implementation details

    # Source vector and boundary conditions
    # Assuming source vector and boundary conditions setup are abstracted
    # These would depend on the specific problem and implementation details

    # Solve system of equations
    # Assuming system solving is abstracted
    # This would depend on the specific solver being used, e.g., direct solver, iterative solver, etc.

    # Update motion and pressure functions
    # Assuming update functions are abstracted
    # This would involve updating the solution vectors for motion and pressure

    # Calculate L2 error and maximum error
    # Assuming error calculation is abstracted
    # This would involve comparing the numerical solution with an analytical solution or a more refined numerical solution

    # Advance to the next time level
    # This is already done at the start of the loop with timeline.advance()

# Print the sum of absolute values of the motion function
# Assuming motion function sum calculation is abstracted
# This would involve summing the absolute values of the motion function's degrees of freedom or evaluating the function over the domain
```