#!/usr/bin/python2.5

#

# Copyright 2009 the Melange authors.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#   http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

"""Slot allocation logic.

"""

__authors__ = [

  '"Sverre Rabbelier" <sverre@rabbelier.nl>',

  ]

import math

class Error(Exception):

  """Error class for the Allocation module.

  """

  pass

class Allocator(object):

  """A simple student slots allocator.

  The buildSets method is used to validate the allocation data as well as

  construct the sets that the algorithm then uses to distribute the slots.

  By separating these steps it is possible to write a different allocation

  algorithm but re-use the sets and validation logic.

  """

  # I tried to write explicit code that does not require any

  # additional comments (with the exception of the set notation for

  # the convenience of any mathematicians that happen to read this

  # piece of code ;).

  def __init__(self, orgs, popularity, max, slots,

               max_slots_per_org, min_slots_per_org, algorithm):

    """Initializes the allocator.

    Args:

      orgs: a list of all the orgs that need to be allocated

      popularity: the amount of applications per org

      max: the amount of assigned mentors per org

      slots: the total amount of available slots

      max_slots_per_org: how many slots an org should get at most

      min_slots_per_org: how many slots an org should at least get

      algorithm: the algorithm to use

    """

    self.locked_slots = {}

    self.adjusted_slots = {}

    self.adjusted_orgs = []

    self.locked_orgs = []

    self.unlocked_orgs = []

    self.unlocked_applications = []

    self.slots = slots

    self.max_slots_per_org = max_slots_per_org

    self.min_slots_per_org = min_slots_per_org

    self.orgs = set(orgs)

    self.popularity = None

    self.total_popularity = None

    self.initial_popularity = popularity

    self.max = max

    self.algorithm = algorithm

  def allocate(self, locked_slots):

    """Allocates the slots and returns the result.

    Args:

      locked_slots: a dict with orgs and the number of slots they get

    """

    self.locked_slots = locked_slots

    self.buildSets()

    if not sum(self.popularity.values()) or not sum(self.max.values()):

      return dict([(i, 0) for i in self.orgs])

    if self.algorithm == 1:

      return self.preprocessingAllocation()

    return self.iterativeAllocation()

  def buildSets(self):

    """Allocates slots with the specified constraints.

    """

    popularity = self.initial_popularity.copy()

    # set s

    locked_slots = self.locked_slots

    # set a and b

    locked_orgs = set(locked_slots.keys())

    # set a' and b'

    unlocked_orgs = self.orgs.difference(locked_orgs)

    # a+o and b+o should be o

    locked_orgs_or_orgs = self.orgs.union(locked_orgs)

    total_popularity = sum(popularity.values())

    # a+o should be o, testing length is enough though

    if len(locked_orgs_or_orgs) != len(self.orgs):

      raise Error("Unknown org as locked slot")

    self.unlocked_orgs = unlocked_orgs

    self.locked_orgs = locked_orgs

    self.popularity = popularity

    self.total_popularity = total_popularity

  def rangeSlots(self, slots, org):

    """Returns the amount of slots for the org within the required bounds.

    """

    slots = int(math.floor(float(slots)))

    slots = min(slots, self.max_slots_per_org)

    slots = max(slots, self.min_slots_per_org)

    slots = min(slots, self.max[org])

    return slots

  def iterativeAllocation(self):

    """A simple iterative algorithm.

    """

    adjusted_orgs = self.adjusted_orgs

    adjusted_slots = self.adjusted_slots

    locked_orgs = self.locked_orgs

    locked_slots = self.locked_slots

    unallocated_popularity = self.total_popularity - len(locked_slots)

    available_slots = self.slots

    allocations = {}

    for org in self.orgs:

      popularity = self.popularity[org]

      mentors = self.mentors[org]

      if org in locked_orgs:

        slots = locked_slots[org]

      elif unallocated_popularity:

        weight = float(popularity) / float(unallocated_popularity)

        slots = int(math.floor(weight*available_slots))

      if org in adjusted_orgs:

        slots += adjusted_slots[org]

      slots = min(slots, self.max_slots_per_org)

      slots = min(slots, mentors)

      slots = min(slots, available_slots)

      allocations[org] = slots

      available_slots -= slots

      unallocated_popularity -= popularity

    return allocations

  def preprocessingAllocation(self):

    """An algorithm that pre-processes the input before running as normal.

    """

    adjusted_orgs = self.adjusted_orgs

    adjusted_slots = self.adjusted_slots

    locked_orgs = self.locked_orgs

    locked_slots = self.locked_slots

    unlocked_orgs = self.unlocked_orgs

    total_popularity = self.total_popularity

    available_slots = self.slots

    allocations = {}

    slack = {}

    for org in locked_orgs:

      popularity = self.popularity[org]

      slots = locked_slots[org]

      slots = self.rangeSlots(slots, org)

      total_popularity -= popularity

      available_slots -= slots

      allocations[org] = slots

      del self.popularity[org]

    # adjust the orgs in need of adjusting

    for org in adjusted_orgs:

      slots = float(adjusted_slots[org])

      adjustment = (float(total_popularity)/float(available_slots))*slots

      adjustment = int(math.ceil(adjustment))

      self.popularity[org] += adjustment

      total_popularity += adjustment

    # adjust the popularity so that the invariants are always met

    for org in unlocked_orgs:

      popularity = self.popularity[org]

      # mentors = self.mentors[org]

      slots = (float(popularity)/float(total_popularity))*available_slots

      slots = self.rangeSlots(slots, org)

      popularity = (float(total_popularity)/float(available_slots))*slots

      self.popularity[org] = popularity

    total_popularity = sum(self.popularity.values())

    # do the actual calculation

    for org in unlocked_orgs:

      popularity = self.popularity[org]

      raw_slots = (float(popularity)/float(total_popularity))*available_slots

      slots = int(math.floor(raw_slots))

      slack[org] = raw_slots - slots

      allocations[org] = slots

    slots_left = available_slots - sum(allocations.values())

    # add leftover slots, sorted by slack, decending

    for org, slack in sorted(slack.iteritems(), 

        key=lambda (k, v): v, reverse=True):

      if slots_left < 1:

        break

      current = allocations[org]

      slots = self.rangeSlots(current + 1, org)

      slots_left += slots - current

      allocations[org] = slots

    return allocations