from random import shuffle
import random

#Config
simulation_iteration=8 #How much statistical iterations should the evaluation have, the higher is more precise

capacity= 5 #How much tasks can you take once
cur_tasks=[110,300,300,90,1000] #current tasks and how long do they take from now on (in days)
forward_thinking_in_days=600 #Do you want to know if an opportunity is worth it in the long or short term?
task_weight_in_days=180 #How much should the new task take to finish?

sample_yearspan=19 #Previous sample length in years.
meta_tasks=[1000,10,10,10,10,10,10,10,10,10,100,100,300,300,90,30,110] #The tasks so far you have received in your life.
#END config

DAYS_YEAR=365
day_chance=len(meta_tasks)/(DAYS_YEAR*sample_yearspan)

missed_tasks=0

def try_insert_task(start_tasks,task):
    global missed_tasks
    
    if len(start_tasks)<capacity:
        start_tasks.append(task)
        #print("Added a task")
    else:
        #print("Missed a task")
        missed_tasks+=1
    
    return start_tasks

def simulate_get_meta_task(start_tasks):
    if(random.uniform(0.0,1.0)<day_chance):
        new_task = meta_tasks[random.randint(0, len(meta_tasks)-1)]
        try_insert_task(start_tasks,new_task)
    return start_tasks

#check if how much tasks would we miss if we did or did not take a task which lasts for X days.
def shuffle_array(arr):
    shuffled=[]
    for n in range(0,len(arr)):
        shuffled.append(arr[n])
    
    shuffle(shuffled)
    return shuffled

def age_tasks(tasks=[]):
    new_tasks=[]

    for n in range(0,len(tasks)):
        tasks[n]-=1
        if tasks[n]>0:
            new_tasks.append(tasks[n])
    return new_tasks

def simulate_next_days(start_tasks=[],day_count=10):
    global missed_tasks
    
    missed_tasks=0
    for n in range(0,day_count): #Integrate over each day passed
        start_tasks=age_tasks(start_tasks)
        start_tasks = simulate_get_meta_task(start_tasks)
        #print(start_tasks)
    return missed_tasks

def simulate_N_tasks(start_tasks=[],day_count=10,N=1):
    total_missed_tasks=0
    for n in range(0,N):
        total_missed_tasks+=simulate_next_days(start_tasks,day_count)
    
    return (total_missed_tasks)
    
def is_opportunity_worth(cur_tasks=[],day_overtime=10,opportunity_completion_time=100):
    t1=cur_tasks.copy()
    avg_no_opp=simulate_N_tasks(t1,day_overtime,simulation_iteration)
    
    t2=cur_tasks.copy()
    t2.append(opportunity_completion_time)
    avg_yes_opp=simulate_N_tasks(t2,day_overtime,simulation_iteration)
   
    
    if avg_yes_opp<=avg_no_opp:
        return True
    return False
    
print("Is opportunity worth it: "+str(is_opportunity_worth(cur_tasks,forward_thinking_in_days,task_weight_in_days)))