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RwaNet.py
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import networkx as nx
import os
import numpy as np
import graphviz as gz
from PIL import Image
import subprocess as sp
import io
from networkx import shortest_simple_paths
from utils import file_prefix
from draw import PltRwa
from args import args
class RwaNetwork(nx.Graph):
"""
RWA network
"""
def __init__(self, filename: str, wave_num: int, append_route: bool=args.append_route.startswith("True"), k: int=args.k, weight=None,
file_prefix=file_prefix):
"""
:param filename: 标明网络的md文件，其中前两行是表头和md表格的标志“|:---|”，内容为index，src，dst，weight
:param wave_num: 每条链路包含的波长个数
:param append_route: 在生成网络图像的时候，是否把路由信息也加进去
:param k: 如果加路由信息，则加几个路由
"""
super(RwaNetwork, self).__init__()
self.net_name = filename.split('.')[0]
self.wave_num = wave_num
self.append_route = append_route
if append_route:
print("open append-route option")
self.k = k
self.weight = weight
else:
self.k = 1
self.weight = None
filepath = os.path.join(file_prefix, filename)
if os.path.isfile(filepath):
datas = np.loadtxt(filepath, delimiter='|', skiprows=2, dtype=str)
self.origin_data = datas[:, 1:(datas.shape[1]-1)]
for i in range(self.origin_data.shape[0]):
wave_avai = [True for i in range(wave_num)]
self.add_edge(self.origin_data[i, 1], self.origin_data[i, 2],
weight=float(self.origin_data[i, 3]),
is_wave_avai=wave_avai)
else:
raise FileExistsError("file {} doesn't exists.".format(filepath))
self.draw = PltRwa(img_width=args.img_width, img_height=args.img_height, dpi=args.dpi,
line_width=args.line_width, node_size=args.node_size, net_name=filename,
prefix=file_prefix)
def gen_img(self, width: int, height: int, src: str, dst: str, mode: str) -> np.ndarray:
"""
将网络当前的状态先生成channels张灰度图片，然后以CHW的格式表示出来
:param width 生成图片后，resize图片到指定宽度
:param height 生成图片后，resize图片到指定高度
:param src 网络中到达业务的源点，为None表示不取源点，此时dst也应该为None
:param dst 网络中到达业务的宿点，为None表示不取宿点，此时src也应该为None
:param mode 返回状态的模式选择，如果为learning，则返回CHW的stacked灰度图像；如果为alg，则返回源宿点请求
"""
if mode.startswith('alg'):
return np.array([src, dst])
elif mode.startswith('learning'):
rtn = None
for wave_index in range(self.wave_num):
img = self.draw.draw(self, src, dst, None, wave_index)
if rtn is not None:
rtn = np.concatenate((rtn, img), axis=0)
else:
rtn = np.array(img)
# 判断是否将路由信息也放进去
if self.append_route:
if src is not None and dst is not None:
paths = self.k_shortest_paths(src, dst)
for nodes in paths:
img = self.draw.draw(self, src, dst, nodes, -1)
rtn = np.concatenate((rtn, img), axis=0)
return rtn
else:
raise ValueError("wrong mode parameter")
def k_shortest_paths(self, source, target):
"""
如果源宿点是None，则返回len为1的None数组
:param source:
:param target:
:return:
"""
if source is None:
return [None]
generator = shortest_simple_paths(self, source, target, weight=self.weight)
rtn = []
index = 0
for i in generator:
index += 1
if index > self.k:
break
rtn.append(i)
return rtn
def set_wave_state(self, wave_index, nodes: list, state: bool, check: bool=True):
"""
设置一条路径上的某个波长的可用状态
:param wave_index: 编号从0开始
:param nodes: 路径经过的节点序列
:param state: 要设置的状态
:param check: 是否检验状态
:return:
"""
assert len(nodes) >= 2
start_node = nodes[0]
for i in range(1, len(nodes)):
end_node = nodes[i]
if check:
assert self.get_edge_data(start_node, end_node)['is_wave_avai'][wave_index] != state
self.get_edge_data(start_node, end_node)['is_wave_avai'][wave_index] = state
start_node = end_node
def get_avai_waves(self, nodes: list) -> list:
"""
获取指定路径上的可用波长下标
:param nodes: 路径经过的节点序列
:return:
"""
rtn = np.array([True for i in range(self.wave_num)])
assert len(nodes) >= 2
start_node = nodes[0]
for i in range(1, len(nodes)):
end_node = nodes[i]
rtn = np.logical_and(rtn,
np.array(self.get_edge_data(start_node, end_node)['is_wave_avai']))
start_node = end_node
return np.where(rtn == True)[0].tolist()
def exist_rw_allocation(self, path_list: list) -> [bool, int, int]:
"""
扫描path_list中所有路径上的所有波长，按照FirstFit判断是否存在可分配方案
:param path_list:
:return: 是否存在路径，路径index，波长index
"""
if len(path_list) == 0 or path_list[0] is None:
return False, -1, -1
for path_index, nodes in enumerate(path_list):
edges = self.extract_path(nodes)
# print(edges)
for wave_index in range(self.wave_num):
is_avai = True
for edge in edges:
if self.get_edge_data(edge[0], edge[1])['is_wave_avai'][wave_index] is False:
is_avai = False
break
if is_avai is True:
return True, path_index, wave_index
return False, -1, -1
def is_allocable(self, path: list, wave_index: int) -> bool:
"""
判断路由path上wave_index波长的路径是否可分配。
:param path:
:param wave_index:
:return:
"""
edges = self.extract_path(path)
is_avai = True
for edge in edges:
if self.get_edge_data(edge[0], edge[1])['is_wave_avai'][wave_index] is False:
is_avai = False
break
return is_avai
def extract_path(self, nodes):
assert len(nodes) >= 2
rtn = []
start_node = nodes[0]
for i in range(1, len(nodes)):
end_node = nodes[i]
rtn.append((start_node, end_node))
start_node = end_node
return rtn