hospital.py

""" HOSPITAL MODEL CREATION """
from scipy.stats import truncnorm
from classes import Localization, TypeLocalization
import config
import random


def distribute_rooms(beds, services, min_rooms):
    if beds % 2 != 0:
        return "The number of beds must be pair."
    if beds < 0 or services < 0 or min_rooms < 0:
        return "All parameters must be positive."
    
    total_rooms = beds // 2
    max_rooms = total_rooms // services
    rooms_per_service = []
    
    for _ in range(services - 1):
        rooms = random.randint(min_rooms, max_rooms)
        rooms_per_service.append(rooms)
        total_rooms -= rooms
    
    #if (total_rooms > 0):
    rooms_per_service.append(total_rooms)  # Asigna las habitaciones restantes al último servicio
    
    if any(h < min_rooms or h > max_rooms for h in rooms_per_service[:-1]):
        return "It is not possible to distribute rooms within the specified limits."

    return rooms_per_service


# Function that initialize a new hospital
# er_nbeds = nº beds in the ER
# icu_nbeds = nº beds in the ICU
# nwards = nº of wards
# wards_nrooms = nº of rooms in each ward
# room_nbeds = nº of beds in each ward room
# sx_nrooms = nº of operation rooms
# rx_nrooms = nº of radiology rooms
# rx_nbeds = nº of beds in each radiology room
def initialize_hospital(er_nbeds, icu_nbeds, nwards, wards_nrooms, sx_nrooms, rx_nrooms, room_nbeds, rx_nbeds):
    wards_nrooms = distribute_rooms(186, nwards, 5)
    print(wards_nrooms)

    # ER, ICU
    er = Localization(0, TypeLocalization.ER)
    icu = Localization(1, TypeLocalization.ICU)
    L = [er, icu]

    # WARDS
    index = 2
    wards = []
    for i in range(nwards):
        ward = Localization(index, TypeLocalization.Ward)
        wards.append(ward)
        L.append(ward)
        index = index + 1

    # OPERATING ROOMS
    for i in range(sx_nrooms):
        surgery = Localization(index, TypeLocalization.Surgery)
        L.append(surgery)
        index = index + 1

    # RADIOLOGY ROOMS
    rxs = []
    for i in range(rx_nrooms):
        rx = Localization(index, TypeLocalization.Radiology)
        rxs.append(rx)
        L.append(rx)
        index = index + 1

    # ER AND ICU BEDS
    beds_er, index = create_beds(er_nbeds, index, er, 0)
    L = L + beds_er
    beds_icu, index = create_beds(icu_nbeds, index, icu, 1)
    L = L + beds_icu

    # WARDS ROOMS AND BEDS
    for i in range(nwards):
        rooms, beds, index = create_rooms(wards_nrooms[i], room_nbeds, index, wards[i])
        L = L + rooms
        L = L + beds

    # RADIOLOGY ROOMS BEDS
    for i in range(rx_nrooms):
        beds, index = create_beds(rx_nbeds, index, rxs[i], 0)
        L = L + beds


    # We save the hospital in a csv file
    fichero = open('locations.csv', 'w')
    fichero.write("id_location; infected; ids_adjacents; ids_children; name; id_parent; floor; service\n")

    for localization in L:
        fichero.write(localization.print_to_csv() + "\n")

    return L


# Function that returns new nbeds beds following the id index, located in located_in and in the floor floor
def create_beds(nbeds, index, located_in, floor):
    beds = []
    for i in range(nbeds):
        beds.append(Localization(index, TypeLocalization.Bed, located_in))
        index = index + 1
    for b in beds:
        b.adjacent = [bed for bed in beds if bed is not b]
    located_in.children = beds
    return beds, index


# Function that returns new nrooms rooms with room_nbeds beds following the id index, located in located_in
def create_rooms(nrooms, room_nbeds, index, located_in):
    rooms = []
    beds = []
    for i in range(nrooms):
        r = Localization(index, TypeLocalization.Room, located_in)
        rooms.append(r)
        index = index + 1
        bs, index = create_beds(room_nbeds, index, r, 1)
        beds.extend(bs)

    located_in.children = rooms
    return rooms, beds, index


# Function that returns the daily hospital occupancy rate following a normal distribution
def normal_distr_occupancy_rate():
    max_beds = round(config.hosp_occupancy_rate / config.required_parameters['n_patients'])
    mean = config.hosp_occupancy_rate
    sd = 30
    tn = truncnorm((0 - mean) / sd, (max_beds - mean) / sd, loc=mean, scale=sd)
    return int(tn.rvs())