def write_fee_schedule(operations, path, sort=True, n_significant_figures=2):
if sort:
operations = sorted(operations, key=lambda x: x.name)
group_dict = SortedDict()
for op in operations:
if op.group is not None and op.get_model_input_size(
) == 0 and op.get_n_model_param() == 1:
if op.group not in group_dict:
group_dict[op.group] = []
group_dict[op.group].append(op)
with open(path, "w") as ofile:
ofile.write("# Fee Schedule\n")
ofile.write("\n")
ofile.write("| Operation | Gas cost |\n")
ofile.write("|-----------|----------|\n")
for op in operations:
expr = op.get_gas_cost_expr(
n_significant_figures=n_significant_figures)
if expr is None:
continue
ofile.write("| `%s` | `%s` |\n" % (op.name, expr))
if group_dict:
ofile.write("\n")
ofile.write("## Grouped Operations\n")
ofile.write("\n")
ofile.write("| Group | Maximum Gas cost |\n")
ofile.write("|-------|------------------|\n")
for key, ops in group_dict.items():
# We should only get operations with 0 input variable and 1
# parameter at this point
max_cost = max(op.latest_param[0] for op in ops)
expr = "{:_}".format(round_up(max_cost, n_significant_figures))
ofile.write("| `%s` | `%s` |\n" % (key, expr))
def recheduleChangePriority(jobsListExportPrevious, rescheduleTime,
priorItinerary, machinesList):
"""
:param jobsListExportPrevious: 初始调度结果
:param rescheduleTime: 重调度时间
:param priorItinerary: 优先的任务序号
:param machinesList: 可用机器列表
:return: jobsListToExportNew: 重调度方案
"""
time = {}
allPreviousOperations = {}
rescheduleOperations = {}
rescheduleJobsList = []
currentTimeOnMachines = {}
jobsListToExportNew = []
unchangedOperations = {}
# 遍历机器，生成每个机器前工序集合和需要重调度的工序集合
for machine in machinesList:
allPreviousOperations[machine.name] = [
job for job in jobsListExportPrevious
if job.assignedMachine == machine.name
]
allPreviousOperations[machine.name].sort(key=lambda j: j.startTime)
rescheduleOperations[machine.name] = [
job for job in jobsListExportPrevious
if job.assignedMachine == machine.name
and job.startTime >= rescheduleTime
]
rescheduleOperations[machine.name].sort(key=lambda j: j.startTime)
# 重调度时刻机器时间更新
unchangedLength = len(allPreviousOperations[machine.name]) - len(
rescheduleOperations[machine.name])
unchangedOperations[machine.name] = allPreviousOperations[
machine.name][0:unchangedLength]
currentTimeOnMachines[machine.name] = unchangedOperations[
machine.name][-1].endTime
if currentTimeOnMachines[machine.name] < rescheduleTime:
currentTimeOnMachines[machine.name] = rescheduleTime
# 初始化各机器时间
time[currentTimeOnMachines[machine.name]] = {}
# 更新各机器下重调度工序状态
unchangedOperations[machine.name][-1].completed = True
for job in rescheduleOperations[machine.name]:
job.startTime = 0
job.completed = False
# 输出无需重调度的任务结果
for job in unchangedOperations[machine.name]:
jobsListToExportNew.append(job)
for machine in machinesList:
# 生成重调度列表
for job in rescheduleOperations[machine.name]:
if job.idItinerary == priorItinerary:
job.priority = 5
rescheduleJobsList.append(job)
allJobsList = jobsListToExportNew + rescheduleJobsList
# 调度时间初始化
time = SortedDict(time)
while len(jobsListToExportNew) < len(jobsListExportPrevious):
for t, operations in time.items():
operations = GetWaitingOperationsSPT(allJobsList, float(t),
machinesList,
currentTimeOnMachines)
for keyMach, tasks in operations.items():
if len(tasks):
if float(t) < currentTimeOnMachines[keyMach]:
continue
tasks[0].startTime = float(t)
tasks[0].completed = True
tasks[0].assignedMachine = keyMach
jobsListToExportNew.append(tasks[0])
currentTimeOnMachines[keyMach] = tasks[0].getEndTime()
time[currentTimeOnMachines[keyMach]] = {}
del time[t]
break
time = SortedDict(time) # chronological order
return jobsListToExportNew
class TimingDiagram:
"""Two-state (True/False or 1/0) timing diagram with boolean algebra operations."""
def __init__(self, time_state_pairs):
"""Creates a timing diagram out of a series of (time, state) pairs.
Notes
=====
The input states can be any truthy/falsey values.
The input times can be any type with a partial ordering.
The input sequence does not need to be sorted (input is sorted during initialization).
Compresses duplicate sequential states and stores them in the `timeline` attribute.
Example
=======
>>> diagram = TimingDiagram([(0, True), (1, False), (5, False), (10, True)])
>>> print(~diagram)
TimingDiagram([(0, False), (1, True), (10, False)])
"""
self.timeline = SortedDict(
_compress(time_state_pairs, key=operator.itemgetter(1))
)
def __getitem__(self, item):
return self.timeline[item]
def __matmul__(self, time):
"""Alias for at()"""
return self.at(time)
def __eq__(self, other):
"""Returns a new timing diagram, True where the two diagrams are equal."""
return self.compare(other, key=operator.eq)
def __ne__(self, other):
"""Returns a new timing diagram, True where the two diagrams are equal."""
return ~(self == other)
def __and__(self, other):
"""Returns a new timing diagram, True where the two diagrams are both True."""
return self.compare(other, key=operator.and_)
def __or__(self, other):
"""Returns a new timing diagram, True where either diagram is True."""
return self.compare(other, key=operator.or_)
def __xor__(self, other):
"""Returns a new timing diagram, True where the two diagrams are not equal."""
return self != other
def __invert__(self):
"""Returns a new timing diagram with states flipped."""
return TimingDiagram(((t, not s) for t, s in self.timeline.items()))
def at(self, time):
"""Returns the state at a particular time. Uses bisection for search (binary search)."""
idx = max(0, self.timeline.bisect(time) - 1)
return self.timeline.values()[idx]
def compare(self, other, key):
"""Constructs a new timing diagram based on comparisons between two diagrams,
with (time, key(self[time], other[time])) for each time in the timelines.
"""
# TODO: Implement linear algorithm instead of .at() for each time, which is O(n log n).
return TimingDiagram(
(
(k, key(self.at(k), other.at(k)))
for k in merge(self.timeline.keys(), other.timeline.keys())
)
)
def __repr__(self):
return f"{self.__class__.__qualname__}({list(self.timeline.items())})"
def recheduleMachineFault(jobsListExportPrevious, rescheduleTime,
faultyMachine, machinesList):
pass
#TODO
time = {}
allPreviousOperations = {}
rescheduleOperations = {}
rescheduleJobsList = []
currentTimeOnMachines = {}
jobsListToExportNew = []
unchangedOperations = {}
unscheduleItinerarys = []
# 遍历机器，生成每个机器前工序集合和需要重调度的工序集合
for machine in machinesList:
allPreviousOperations[machine.name] = [
job for job in jobsListExportPrevious
if job.assignedMachine == machine.name
]
allPreviousOperations[machine.name].sort(key=lambda j: j.startTime)
rescheduleOperations[machine.name] = [
job for job in jobsListExportPrevious
if job.assignedMachine == machine.name
and job.startTime >= rescheduleTime
]
rescheduleOperations[machine.name].sort(key=lambda j: j.startTime)
# 重调度时刻机器时间更新
unchangedLength = len(allPreviousOperations[machine.name]) - len(
rescheduleOperations[machine.name])
unchangedOperations[machine.name] = allPreviousOperations[
machine.name][0:unchangedLength]
#如果故障机器上有未完工任务，则把该任务工艺路线后续任务不参与重调度
currentTimeOnMachines[machine.name] = unchangedOperations[
machine.name][-1].endTime
if currentTimeOnMachines[machine.name] < rescheduleTime:
currentTimeOnMachines[machine.name] = rescheduleTime
# 初始化各机器时间
time[currentTimeOnMachines[machine.name]] = {}
# 更新各机器下重调度工序状态
unchangedOperations[machine.name][-1].completed = True
for job in rescheduleOperations[machine.name]:
job.completed = False
# 输出无需重调度的任务结果
for job in unchangedOperations[machine.name]:
jobsListToExportNew.append(job)
# 1.先识别出故障机器前未完工任务（包括正在加工的）
# 2. 遍历上述任务列表：
# 如果任务可选机器列表长度为1，则重调度任务列表中不加入该任务；
# 并且记录该任务的工艺路线号，后续是该工艺路线号的任务不参与调度；
# 否则将任务加入重调度任务列表
if unchangedOperations[faultyMachine][-1].endTime > rescheduleTime:
unscheduleItinerarys.append(
unchangedOperations[faultyMachine][-1].idItinerary)
# 生成重调度初始列表
for machine in machinesList:
for job in rescheduleOperations[machine.name]:
rescheduleJobsList.append(job)
rescheduleJobsList.sort(key=lambda j: j.startTime)
#得到受影响的工艺路线号
for job in rescheduleOperations[faultyMachine]:
if len(job.machine) == 1:
unscheduleItinerarys.append(job.idItinerary)
#去除受机器故障影响的任务
rescheduleJobsListUpdate = []
for job in rescheduleJobsList:
if job.idItinerary in unscheduleItinerarys:
continue
else:
rescheduleJobsListUpdate.append(job)
# 机器列表更新
machinesAvailableList = [
machine for machine in machinesList if machine.name != faultyMachine
]
allJobsList = jobsListToExportNew + rescheduleJobsListUpdate
# 调度时间初始化
time = SortedDict(time)
while len(jobsListToExportNew) < len(allJobsList):
for t, operations in time.items():
operations = GetWaitingOperationsSPT(allJobsList, float(t),
machinesAvailableList,
currentTimeOnMachines,
faultyMachine)
for keyMach, tasks in operations.items():
if len(tasks):
if float(t) < currentTimeOnMachines[keyMach]:
continue
tasks[0].startTime = float(t)
tasks[0].completed = True
tasks[0].assignedMachine = keyMach
jobsListToExportNew.append(tasks[0])
currentTimeOnMachines[keyMach] = tasks[0].getEndTime()
time[currentTimeOnMachines[keyMach]] = {}
del time[t]
break
time = SortedDict(time) # chronological order
return jobsListToExportNew