#!/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 itertools

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, applications, mentors, slots,

               max_slots_per_org, min_slots_per_org, iterative):

    """Initializes the allocator.

    Args:

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

      applications: a dictionary with for each org a list of applicants

      mentors: 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

    """

    all_applications = []

    for _, value in applications.iteritems():

      all_applications += value

    self.locked_slots = {}

    self.adjusted_slots = {}

    self.adjusted_orgs = []

    self.locked_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.applications = applications

    self.mentors = mentors

    self.all_applications = set(all_applications)

    self.iterative = iterative

  def allocate(self, locked_slots, adjusted_slots):

    """Allocates the slots and returns the result.

    Args:

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

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

    """

    self.locked_slots = locked_slots

    self.adjusted_slots = adjusted_slots

    self.buildSets()

    if self.iterative:

      return self.iterativeAllocation()

    else:

      return self.preprocessingAllocation()

  def buildSets(self):

    """Allocates slots with the specified constraints

    """

    # set s

    all_applications = self.all_applications

    locked_slots = self.locked_slots

    adjusted_slots = self.adjusted_slots

    # set a and b

    locked_orgs = set(locked_slots.keys())

    adjusted_orgs = set(adjusted_slots.keys())

    # set a' and b'

    unlocked_orgs = self.orgs.difference(locked_orgs)

    # unadjusted_orgs = self.orgs.difference(adjusted_orgs)

    # set a*b and a'*b'

    locked_and_adjusted_orgs = locked_orgs.intersection(adjusted_orgs)

    # unlocked_and_unadjusted_orgs = unlocked_orgs.intersection(unadjusted_orgs)

    # a+o and b+o should be o

    locked_orgs_or_orgs = self.orgs.union(locked_orgs)

    adjusted_orgs_or_orgs = self.orgs.union(adjusted_orgs)

    # an item can be only a or b, so a*b should be empty

    if locked_and_adjusted_orgs:

      raise Error("Cannot have an org locked and adjusted")

    # 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")

    # same for b+o

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

      raise Error("Unknown org as adjusted slot")

    # set l and l'

    locked_applications = set(itertools.chain(*locked_slots.keys()))

    unlocked_applications = all_applications.difference(locked_applications)

    self.adjusted_orgs = adjusted_orgs

    self.unlocked_orgs = unlocked_orgs

    self.locked_orgs = locked_orgs

    self.unlocked_applications = unlocked_applications

    popularity = ((k, len(v)) for k, v in self.applications.iteritems())

    self.popularity = dict(popularity)

  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

    unlocked_applications = self.unlocked_applications

    unlocked_applications_count = len(unlocked_applications)

    unallocated_applications_count = unlocked_applications_count

    available_slots = self.slots

    allocations = {}

    for org in self.orgs:

      org_applications = self.applications[org]

      org_applications_count = len(org_applications)

      mentors = self.mentors[org]

      if org in locked_orgs:

        slots = locked_slots[org]

      else:

        weight = float(org_applications_count) / unallocated_applications_count

        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_applications_count -= org_applications_count

    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

    unlocked_applications = self.unlocked_applications

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

    available_slots = self.slots

    allocations = {}

    slack = {}

    for org in locked_orgs:

      popularity = self.popularity[org]

      slots = locked_slots[org]

      total_popularity -= popularity

      available_slots -= slots

      allocations[org] = slots

    # adjust the orgs in need of adjusting

    for org in adjusted_orgs:

      slots = adjusted_slots[org]

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

      adjustment = int(math.ceil(adjustment))

      self.popularity[org] += 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

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

      self.popularity[org] = popularity

    # do the actual calculation

    for org in unlocked_orgs:

      org_applications = self.applications[org]

      org_applications_count = len(org_applications)

      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

    return allocations