import random
import simpy
import statistics

class DiagnosticsSimulator:
    
    def __init__(self):            
        self.nr_patients = 0 # the number of patients that arrived
        self.nr_patients_processed = 0 # the number of patients that was processed until completion
        self.nr_ultrasounds = 0 # the number of patients that received an ultrasound
        self.sojourn_time_per_patient = 0 # the average sojourn time per patient
        self.sojourn_lst = [] # list storing all sojourn times
    
    def patient(self, env, bed, receptionist, nurse, lab_assistant):
        arrival_time = env.now
        rr = receptionist.request()
        yield rr # wait for receptionist to become available
        wait_for_form = random.uniform(0.5, 1.5)
        yield env.timeout(wait_for_form) # time it takes waiting for the form
        receptionist.release()
        fill_out_form = random.uniform(15, 25)
        yield env.timeout(fill_out_form) # time it takes for filling out the form
        rr = receptionist.request()
        yield rr # wait for receptionist to become available
        return_and_brief = random.uniform(2, 4)
        yield env.timeout(return_and_brief) # time is takes to return form and receive briefing
        receptionist.release()
        br = bed.request()
        yield br # wait for bed to become available
        nr = nurse.request()
        yield nr # wait for nurse to become available
        preparation = random.uniform(2, 8)
        yield env.timeout(preparation) # time it takes to get prepared
        nurse.release()
        lr = lab_assistant.request()
        yield lr # wait for lab assistant to become available
        take_blood = random.uniform(4, 6)
        yield env.timeout(take_blood) # time it takes to take blood
        lab_assistant.release()
        if random.randint(0,100) < 30:
            nr = nurse.request()
            yield nr # wait for nurse to become available
            ultrasound = random.uniform(7, 13)
            yield env.timeout(ultrasound)
            self.nr_ultrasounds += 1
            nurse.release()
        bed.release()
        completion_time = env.now
        self.nr_patients_processed += 1
        
        sojourn_time_per_per_patient = completion_time - arrival_time # calculate the sojourntime 
        self.sojourn_lst.append(sojourn_time_per_per_patient)
        self.sojourn_time_per_patient = statistics.mean(self.sojourn_lst)
            

    def patient_generator(self, env, bed, receptionist, nurse, lab_assistant):
        while True:
            p = self.patient(env, bed, receptionist, nurse, lab_assistant) # create a new patient
            env.process(p) # start the simulation of the patient
            interarrivalTime = random.expovariate(1/6) # exponential interarrival
            yield env.timeout(interarrivalTime) # wait for the sampled interarrival time

            
    # seed: the random seed with which the simulator is initiated
    # duration: the amount of simulation time for which the simulator has to run
    def simulate(self, seed, duration):
        random.seed(seed)
        env = simpy.Environment()

        bed = simpy.Resource(env, capacity = 12)
        receptionist = simpy.Resource(env, capacity = 1)
        nurse = simpy.Resource(env, capacity = 2)
        lab_assistant = simpy.Resource(env, capacity = 1)
        env.process(self.patient_generator(env, bed, receptionist, nurse, lab_assistant)) # start patient generation process
        env.run(duration)

        return env

diags = DiagnosticsSimulator()
env = diags.simulate(2019, 10000)
print(diags.nr_patients_processed, diags.sojourn_time_per_patient)