# -*- coding: utf-8 -*-
"""
===============================================================================
GenericNetwork: Abstract class to construct pore networks
===============================================================================
"""
import itertools
import scipy as sp
import scipy.sparse as sprs
import scipy.spatial as sptl
import OpenPNM.Utilities.misc as misc
from OpenPNM.Utilities import topology
from OpenPNM.Base import Core, Controller, Tools, logging
logger = logging.getLogger(__name__)
ctrl = Controller()
topo = topology()
class GenericNetwork(Core):
r"""
GenericNetwork - Base class to construct pore networks
Parameters
----------
name : string
Unique name for Network object
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
# -*- coding: utf-8 -*-
"""
===============================================================================
MatFile: Subclass to import Networks from a Matlab '.mat' file
===============================================================================
"""
import scipy as sp
import scipy.io as spio
import os
from OpenPNM.Network import GenericNetwork
import OpenPNM.Geometry
import OpenPNM.Utilities.misc as misc
from OpenPNM.Base import logging
logger = logging.getLogger(__name__)
class MatFile(GenericNetwork):
r"""
MatFile - constructs a pore network from a perfectly formatted .mat file (MATLAB)
Create network from Matlab file. Returns OpenPNM.Network.GenericNetwork()
object. The extra data of 'type' will trigger internal and boundary pores.
Parameters
----------
filename : string
filename = 'standard_cubic_5x5x5.mat' (default)
Name of mat file
path : string
path='' (default)
the full path to the mat file on your computer
'''
###############################################################################
ModelsDict: Abstract Class for Containing Models
###############################################################################
'''
import inspect
import scipy as sp
from collections import OrderedDict
from OpenPNM.Base import logging, Controller
logger = logging.getLogger()
class ModelWrapper(dict):
r"""
Accepts a model from the OpenPNM model library, as well as all required
and optional argumnents, then wraps it in a custom dictionary with
various methods for working with the models.
"""
def __init__(self,**kwargs):
self.update(**kwargs)
def __call__(self):
return self['model'](**self)
def __str__(self):
header = '-'*60
print(header)
print(self['model'].__module__+'.'+self['model'].__name__)
print(header)
print("{a:<20s} {b}".format(a='Argument Name',b='Value / (Default)'))
print(header)
"""
###############################################################################
Controller: Overall controller class
###############################################################################
"""
import pickle as _pickle
import copy as _copy
import time
import random
import string
import OpenPNM
from OpenPNM.Base import logging
logger = logging.getLogger()
class Controller(dict):
# The following __instance__ class variable and subclassed __new__ method
# makes the Controller class a 'Singleton'. This way, any instantiation
# of a controller object anywhere in the code will return the same object.
__instance__ = None
def __new__(cls, *args, **kwargs):
if Controller.__instance__ is None:
Controller.__instance__ = dict.__new__(cls)
return Controller.__instance__
def __init__(self):
self.comments = 'Using OpenPNM ' + OpenPNM.__version__
def __str__(self):
lines = []
