def import_file(file_name):
base_dir = get_base_dir()
module_path = os.path.dirname(os.path.join(base_dir, file_name))
if module_path not in sys.path:
sys.path.append(module_path)
remove_path = True
else:
remove_path = False
module_name = os.path.splitext(os.path.basename(file_name))[0]
conf = __import__(module_name)
if remove_path:
sys.path.pop(-1)
return conf
def import_file(file_name):
base_dir = get_base_dir()
module_path = os.path.dirname(os.path.join(base_dir, file_name))
if module_path not in sys.path:
sys.path.append(module_path)
remove_path = True
else:
remove_path = False
module_name = os.path.splitext(os.path.basename(file_name))[0]
conf = __import__(module_name)
if remove_path:
sys.path.pop(-1)
return conf
"""
Input file for a scalar linear elliptic problems.
"""
import numpy as np
import os
from general.base import get_base_dir
base_dir = get_base_dir()
dim = 2
N = 5*np.ones(dim, dtype=np.int32)
materials = {'square': {'inclusions': ['square', 'otherwise'],
'positions': [np.zeros(dim), ''],
'params': [0.6*np.ones(dim), ''], # size of sides
'vals': [11*np.eye(dim), 1.*np.eye(dim)],
'Y': np.ones(dim),
'order': None,
},
'square_Ga': {'inclusions': ['square', 'otherwise'],
'positions': [np.zeros(dim), ''],
'params': [0.6*np.ones(dim), ''], # size of sides
'vals': [11*np.eye(dim), 1.*np.eye(dim)],
'Y': np.ones(dim),
'order': 0,
'P': N,
},
'square2': {'inclusions': ['square', 'otherwise'],
'positions': [np.zeros(dim), ''],
'params': [1.2*np.ones(dim), ''], # size of sides
"""
Input file for a scalar linear elliptic problems.
"""
import numpy as np
import os
from general.base import get_base_dir
base_dir = get_base_dir()
input_dir = os.path.dirname(os.path.abspath(__file__))
file_name = os.path.join(input_dir, 'topologie.txt')
def get_topo():
topo = np.loadtxt(file_name)
return topo
topo = get_topo()
P = np.array(topo.shape) # image resolution
dim = P.size
def get_mat(coord=None):
topo = get_topo()
if coord is not None and not (topo.shape == coord.shape[1:]):
raise ValueError()
matrix_phase = np.eye(dim)
inclusion = 11. * np.eye(dim)
mat_vals = np.einsum('ij...,k...->ijk...', matrix_phase, topo == 0)
mat_vals += np.einsum('ij...,k...->ijk...', inclusion, topo == 1)
