def getSynapse(self, id=-1, fromId=-1, toId=-1):
'''
取得特定突触
:param id: str or int 突触id
:param fromId: str or int 输入神经元
:param toId: str or int 输出神经元
:return:
'''
if id != -1:
return collections.first(self.synapses, lambda s: s.id == id)
return collections.first(
self.synapses, lambda s: s.fromId == fromId and s.toId == toId)
def getVariable(self,name):
'''
取得变量
:param name: str 变量名
:return:
'''
return collections.first(self.variables, lambda var: var.nameInfo.hasName(name))
def getVariableValue(self,name,default=0.0):
'''
取得变量的值
:param name: str 变量名
:param default: float 缺省值 0.0
:return:
'''
var = collections.first(self.variables, lambda var: var.nameInfo.hasName(name))
if var is None: return default
return var.value
def __setitem__(self, key, value):
# 在变量集合中查找
var = collections.first(self.variables, lambda var: var.nameInfo.hasName(key))
if var is not None:
var.value = value
return
# 在状态集合中查找
self.states[key] = value
def getNeuron(self, id=-1, layer=-1, xhInLayer=-1, coord=None):
'''
查找满足特定条件神经元（先按id，再按坐标，在按层和层内序号)
:param id: 神经元id，有效则会优先查找
:param layer: 所在层
:param xhInLayer: 层内序号
:param coord: 坐标
:return:
'''
if id > 0: #优先按照id查找
ns = self.getNeurons()
return collections.first(ns, lambda n: n.id == id)
if coord is not None: #其次按照特定坐标寻找
ns = self.getNeurons()
return collections.first(ns, lambda n: n.coord == coord)
#查找特定层中某个序号的神经元
ns = self.getNeurons(layer=layer)
if not collections.isEmpty(ns): return None
if xhInLayer >= len(ns): return None
return ns[xhInLayer]
def _get_grid_by_value(self,
values,
activation_intensity_list,
createifnotexisted=True):
'''
计算值在特征空间所属的网格
:param values: Union(list,array) 值
:param activation_intensity_list: list values对所有节点的激活强度列表
:param createifnotexisted: Bool 若网格不存在则创建一个
:return: tuple grid元组,
list grid各维的序号
list grid中心点值
float values最大激活强度
int values最大激活强度对应的节点序号
'''
dimension = len(values)
no, center = [], []
for i in range(dimension):
clip = self.gene.clip[i] if len(self.gene.clip) > i else [0., 1.]
grid_width = (clip[1] -
clip[0]) / self.net.definition.box.grid_size
index = int((values[i] - clip[0]) / grid_width)
no.append(index)
center.append(
(index * grid_width + (index + 1) * grid_width) / 2.0)
grid = collections.first(self.grids,
lambda x: np.equal(x['grid_xh'], no))
if grid is None and createifnotexisted:
node_index = -1
if len(activation_intensity_list) > 0:
asc_index = np.argsort(activation_intensity_list)
max_intersity, node_index = activation_intensity_list[
asc_index[-1]], asc_index[-1]
grid = {
'grid_xh': no,
'grid_center': center,
'samples_count': 0,
'node_id': self.nodes[node_index].id if node_index >= 0 else -1
}
self.grids.append(grid)
grid['samples_count'] += 1
return grid, no, center
def __getitem__(self, item):
'''
取索引
:param item:如果索引项是变量集合中的名字，则返回该变量的值；如果是状态集合中状态的名称，则返回状态的值
:return:
'''
# 在变量集合中查找
var = collections.first(self.variables,lambda var:var.nameInfo.hasName(item))
if var is not None:return var.value
# 在状态集合中查找
#if item in self.states.keys():
if item in self.states:
return self.states[item]
# 在参数集合中查找
if item in self.params.keys():
return self.params[item]
return super.__getitem__(item)
def dump_resume(self):
# Check if the data exists
save_resume_data: bool = False
try:
# Destructive unpacking of the tuple
# Discarding start and end since they are not required
for (_, _), data in self.data_unfinished:
# Check if there is any element is None
# Since there is no need to create resume file otherwise
if data is not None:
save_resume_data = True
except (NameError, ValueError, AttributeError):
# Exists if the variable doesn't exists or data is incompatible
pass
# If there is data
if save_resume_data:
print('Saving resume data ...')
with open('resume.pyb', 'wb') as f:
# Dump the data using serialization hook
dump(ClientInfo(first(self.checks), self.data_unfinished), f)
else:
print('No data was fetched ...')
def getAttention(cls,name):
return collections.first(attention_operations,lambda x:x.name == name)
def getSpecie(self, specieId):
return collections.first(self.species, lambda s: s.id == specieId)
def getInd(self, id):
return collections.first(self.inds, lambda ind: ind.id == id)
def test_first(self):
self.assertEqual(first([x for x in range(10)]), 0)
self.assertEqual(first([]), None)
def get_file_size(self) -> None:
self.generate_connections(sockets=(0, ))
self.file_size = int(
notnone(first(notnone(self._get(self.conns[0],
Request.FILE_SIZE)))))
def get_file_name(self):
self.generate_connections(sockets=(0, ))
self.file_name = str(
notnone(first(notnone(self._get(self.conns[0],
Request.FILE_NAME)))))
