app/soc/logic/allocations.py
author Daniel Hans <Daniel.M.Hans@gmail.com>
Fri, 07 Aug 2009 01:27:24 +0200
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parent 2366 1a954e80d444
permissions -rw-r--r--
Argument store added to updateEntityProperties. This argument determines if an entity should be stored in the data model after its properties are updated. It may be useful, for example, along with tasks (Task Queue API). One may want to make some modifications to an entity during execution of a task, but the developer is sure that at least one new task, which also wants to modify the entity, will be queued, so he or she can just update the entity without saving the changes to the data model, set the entity in memcache and the following task (which is to be executed very shortly) is to retrive the current entity from the memcache (without any expensive calls to the actual data model).
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#!/usr/bin/python2.5
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#
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# Copyright 2009 the Melange authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#   http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Slot allocation logic.
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"""
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__authors__ = [
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  '"Sverre Rabbelier" <sverre@rabbelier.nl>',
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  ]
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import math
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class Error(Exception):
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  """Error class for the Allocation module.
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  """
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  pass
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class Allocator(object):
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  """A simple student slots allocator.
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  The buildSets method is used to validate the allocation data as well as
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  construct the sets that the algorithm then uses to distribute the slots.
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  By separating these steps it is possible to write a different allocation
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  algorithm but re-use the sets and validation logic.
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  """
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  # I tried to write explicit code that does not require any
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  # additional comments (with the exception of the set notation for
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  # the convenience of any mathematicians that happen to read this
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  # piece of code ;).
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  def __init__(self, orgs, popularity, max, slots,
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               max_slots_per_org, min_slots_per_org, algorithm):
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    """Initializes the allocator.
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    Args:
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      orgs: a list of all the orgs that need to be allocated
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      popularity: the amount of applications per org
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      max: the amount of assigned mentors per org
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      slots: the total amount of available slots
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      max_slots_per_org: how many slots an org should get at most
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      min_slots_per_org: how many slots an org should at least get
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      algorithm: the algorithm to use
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    """
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    self.locked_slots = {}
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    self.adjusted_slots = {}
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    self.adjusted_orgs = []
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    self.locked_orgs = []
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    self.unlocked_orgs = []
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    self.unlocked_applications = []
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    self.slots = slots
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    self.mentors = {}
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    self.max_slots_per_org = max_slots_per_org
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    self.min_slots_per_org = min_slots_per_org
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    self.orgs = set(orgs)
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    self.popularity = None
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    self.total_popularity = None
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    self.initial_popularity = popularity
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    self.max = max
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    self.algorithm = algorithm
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  def allocate(self, locked_slots):
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    """Allocates the slots and returns the result.
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    Args:
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      locked_slots: a dict with orgs and the number of slots they get
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    """
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    self.locked_slots = locked_slots
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    self.buildSets()
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    if not sum(self.popularity.values()) or not sum(self.max.values()):
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      return dict([(i, 0) for i in self.orgs])
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    if self.algorithm == 1:
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      return self.preprocessingAllocation()
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    if self.algorithm == 2:
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      return self.reliableAlgorithm()
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    return self.iterativeAllocation()
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  def buildSets(self):
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    """Allocates slots with the specified constraints.
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    """
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    popularity = self.initial_popularity.copy()
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    # set s
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    locked_slots = self.locked_slots
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    # set a and b
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    locked_orgs = set(locked_slots.keys())
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    # set a' and b'
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    unlocked_orgs = self.orgs.difference(locked_orgs)
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    # a+o and b+o should be o
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    locked_orgs_or_orgs = self.orgs.union(locked_orgs)
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    total_popularity = sum(popularity.values())
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    # a+o should be o, testing length is enough though
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    if len(locked_orgs_or_orgs) != len(self.orgs):
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      raise Error("Unknown org as locked slot")
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    self.unlocked_orgs = unlocked_orgs
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    self.locked_orgs = locked_orgs
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    self.popularity = popularity
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    self.total_popularity = total_popularity
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  def rangeSlots(self, slots, org):
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    """Returns the amount of slots for the org within the required bounds.
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    """
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    slots = int(math.floor(float(slots)))
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    slots = min(slots, self.max_slots_per_org)
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    slots = max(slots, self.min_slots_per_org)
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    slots = min(slots, self.max[org])
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    return slots
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  def iterativeAllocation(self):
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    """A simple iterative algorithm.
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    """
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    adjusted_orgs = self.adjusted_orgs
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    adjusted_slots = self.adjusted_slots
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    locked_orgs = self.locked_orgs
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    locked_slots = self.locked_slots
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    unallocated_popularity = self.total_popularity - len(locked_slots)
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    available_slots = self.slots
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    allocations = {}
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    for org in self.orgs:
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      popularity = self.popularity[org]
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      mentors = self.mentors[org]
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      if org in locked_orgs:
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        slots = locked_slots[org]
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      elif unallocated_popularity:
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        weight = float(popularity) / float(unallocated_popularity)
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        slots = int(math.floor(weight*available_slots))
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      if org in adjusted_orgs:
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        slots += adjusted_slots[org]
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      slots = min(slots, self.max_slots_per_org)
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      slots = min(slots, mentors)
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      slots = min(slots, available_slots)
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      allocations[org] = slots
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      available_slots -= slots
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      unallocated_popularity -= popularity
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    return allocations
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  def preprocessingAllocation(self):
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    """An algorithm that pre-processes the input before running as normal.
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    """
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    adjusted_orgs = self.adjusted_orgs
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    adjusted_slots = self.adjusted_slots
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    locked_orgs = self.locked_orgs
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    locked_slots = self.locked_slots
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    unlocked_orgs = self.unlocked_orgs
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    total_popularity = self.total_popularity
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    available_slots = self.slots
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    allocations = {}
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    slack = {}
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    for org in locked_orgs:
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      popularity = self.popularity[org]
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      slots = locked_slots[org]
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      slots = self.rangeSlots(slots, org)
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      total_popularity -= popularity
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      available_slots -= slots
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      allocations[org] = slots
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      del self.popularity[org]
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    # adjust the orgs in need of adjusting
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    for org in adjusted_orgs:
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      slots = float(adjusted_slots[org])
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      adjustment = (float(total_popularity)/float(available_slots))*slots
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      adjustment = int(math.ceil(adjustment))
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      self.popularity[org] += adjustment
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      total_popularity += adjustment
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    # adjust the popularity so that the invariants are always met
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    for org in unlocked_orgs:
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      popularity = self.popularity[org]
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      # mentors = self.mentors[org]
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      slots = (float(popularity)/float(total_popularity))*available_slots
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      slots = self.rangeSlots(slots, org)
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      popularity = (float(total_popularity)/float(available_slots))*slots
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      self.popularity[org] = popularity
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    total_popularity = sum(self.popularity.values())
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    # do the actual calculation
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    for org in unlocked_orgs:
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      popularity = self.popularity[org]
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      raw_slots = (float(popularity)/float(total_popularity))*available_slots
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      slots = int(math.floor(raw_slots))
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      slack[org] = raw_slots - slots
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      allocations[org] = slots
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    slots_left = available_slots - sum(allocations.values())
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    # add leftover slots, sorted by slack, decending
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    for org, slack in sorted(slack.iteritems(), 
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        key=lambda (k, v): v, reverse=True):
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      if slots_left < 1:
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        break
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      current = allocations[org]
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      slots = self.rangeSlots(current + 1, org)
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      slots_left += slots - current
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      allocations[org] = slots
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    return allocations
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  def reliableAlgorithm(self):
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    """An algorithm that reliable calculates the slots assignments.
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    """
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    # adjusted_orgs = self.adjusted_orgs
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    # adjusted_slots = self.adjusted_slots
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    locked_orgs = self.locked_orgs
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    locked_slots = self.locked_slots
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    unlocked_orgs = self.unlocked_orgs
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    total_popularity = self.total_popularity
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    available_slots = self.slots
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    allocations = {}
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    # slack = {}
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    # take out the easy ones
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    for org in locked_orgs:
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      popularity = self.popularity[org]
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      slots = locked_slots[org]
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      slots = float(slots)
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      slots = self.rangeSlots(slots, org)
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      total_popularity -= popularity
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      available_slots -= slots
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      allocations[org] = slots
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      del self.popularity[org]
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    total_popularity = sum(self.popularity.values())
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    # all orgs have been locked, nothing to do
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    if total_popularity <= 0:
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      return allocations
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    pop_per_slot = float(available_slots)/float(total_popularity)
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    # slack = 0
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    wanted = {}
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    # filter out all those that deserve more than their maximum
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    for org in unlocked_orgs:
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      popularity = self.popularity[org]
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      raw_slots = float(popularity)*pop_per_slot
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      slots = int(math.floor(raw_slots))
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      slots = self.rangeSlots(slots, org)
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      max = self.max[org]
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      if max > slots:
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        wanted[org] = max - slots
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      allocations[org] = slots
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    available_slots = self.slots - sum(allocations.values())
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    # distribute the slack
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    while available_slots > 0 and (sum(wanted.values()) > 0):
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      for org, _ in wanted.iteritems():
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        available_slots = self.slots - sum(allocations.values())
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        if available_slots <= 0:
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          break
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        if wanted[org] <= 0:
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          continue
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        current = allocations[org]
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        slots = self.rangeSlots(current + 1, org)
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        extra = current - slots
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        wanted[org] += extra
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        allocations[org] = slots
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    return allocations