from __future__ import absolute_import
import numpy as nm
from sfepy.base.base import assert_, OneTypeList, Container, Struct
import six
[docs]class Functions(Container):
"""Container to hold all user-defined functions."""
[docs] def from_conf(conf):
objs = OneTypeList(Function)
for key, fc in six.iteritems(conf):
fun = Function(name = fc.name,
function = fc.function,
is_constant = False,
extra_args = {})
objs.append(fun)
obj = Functions(objs)
return obj
from_conf = staticmethod(from_conf)
[docs]class Function(Struct):
"""Base class for user-defined functions."""
def __init__(self, name, function, is_constant=False, extra_args=None):
Struct.__init__(self, name = name, function = function,
is_constant = is_constant)
if extra_args is None:
extra_args = {}
self.extra_args = extra_args
def __call__(self, *args, **kwargs):
_kwargs = dict(kwargs)
_kwargs.update(self.extra_args)
return self.function(*args, **_kwargs)
[docs] def set_function(self, function, is_constant=False):
self.function = function
self.is_constant = is_constant
[docs]def make_sfepy_function(fun_or_name=None):
"""
Convenience decorator to quickly create
:class:`sfepy.discrete.functions.Function` objects.
Has two modes of use either without parameter::
@make_sfepy_function
def my_function(...):
...
or with name::
@make_sfepy_function("new_name_for_my_function")
def my_function(...):
...
Parameters
----------
fun_or_name : string, optional
Name to be saved within `Function` instance,
if None name of decorated function is used.
Returns
-------
new_fun : `sfepy.discrete.functions.Function`
With attribute name set to provided name or original function name.
"""
if callable(fun_or_name):
return Function(fun_or_name.__name__, fun_or_name)
def functionizer(fun):
"""
Internal decorator.
Parameters
----------
fun : callable
Will be converted to sfepy.discrete.functions.Function.
Returns
-------
new_fun : Function instance
The `sfepy.discrete.functions.Function` object.
"""
if fun_or_name is not None:
return Function(fun_or_name, fun)
return Function(fun.__name__, fun)
return functionizer
[docs]class ConstantFunction(Function):
"""Function with constant values."""
def __init__(self, values, no_tile=False):
"""Make a function out of a dictionary of constant values. When
called with coors argument, the values are repeated for each
coordinate. Not repeated if `no_tile` is True."""
name = '_'.join(['get_constants'] + list(values.keys()))
def get_constants(ts=None, coors=None, mode=None, **kwargs):
out = {}
if mode == 'special':
for key, val in six.iteritems(values):
if '.' in key:
vkey = key.split('.')[1]
out[vkey] = val
elif (mode == 'qp'):
for key, val in six.iteritems(values):
if '.' in key: continue
dtype = nm.float64 if nm.isrealobj(val) else nm.complex128
val = nm.array(val, dtype=dtype, ndmin=3)
nc = 1 if no_tile else coors.shape[0]
out[key] = nm.tile(val, (nc, 1, 1))
elif (mode == 'special_constant') or (mode is None):
for key, val in six.iteritems(values):
if '.' in key: continue
out[key] = val
else:
raise ValueError('unknown function mode! (%s)' % mode)
return out
Function.__init__(self, name = name, function = get_constants,
is_constant = True)
[docs]class ConstantFunctionByRegion(Function):
"""
Function with constant values in regions.
"""
def __init__(self, values):
"""
Make a function out of a dictionary of constant values per region. When
called with coors argument, the values are repeated for each
coordinate in each of the given regions.
"""
name = '_'.join(['get_constants_by_region'] + list(values.keys()))
def get_constants(ts=None, coors=None, mode=None,
term=None, problem=None, **kwargs):
out = {}
if mode == 'qp':
qps = term.get_physical_qps()
assert_(qps.num == coors.shape[0])
for key, val in six.iteritems(values):
if '.' in key: continue
rval = nm.array(val[list(val.keys())[0]], ndmin=3)
s0 = rval.shape[1:]
dtype = nm.float64 if nm.isrealobj(rval) else nm.complex128
matdata = nm.zeros(qps.shape[:2] + s0, dtype=dtype)
for rkey, rval in six.iteritems(val):
region = problem.domain.regions[rkey]
rval = nm.array(rval, dtype=dtype, ndmin=3)
cells = region.get_cells(true_cells_only=False)
tcells = term.region.get_cells(true_cells_only=False)
ii = nm.isin(tcells, cells)
matdata[ii] = rval
out[key] = matdata.reshape((-1,) + s0)
return out
Function.__init__(self, name=name, function=get_constants,
is_constant=True)