dnd 5e – Does the effectiveness of a harpy’s song fluctuate based on its Charisma score?

You can make your monsters however you like

Originally, I was very into making consistent monsters where the hit points align with the size category and con modifier. Similarly, the calculation of save DCs. This is nice for published material. I do not do it anymore for my own games since it takes time but does not add any value. My players never get to see the nice alignment of numbers.

In the end the question is what you want to achieve. If you want to build the harpy bard like a player character, it seems reasonable to assume that the luring song is a race feature. In this case you could adopt a calculation like for a dragon born breath weapon, i.e. 8 + proficiency + ability, except you would use charisma instead of constitution. If you just want to be consistent with the MM, the same calculation method is also good.

The MM save DCs are consistent with spell save DCs

In my consistent monster days I disassembled all the DCs in the MM, and found that the vast majority is consistent with 8 + proficiency + ability.

The ability changes depending on the feature. Pushing, pulling and knocking prone uses str, charm and fright use charisma. Some abilities of spellcasters use their spellcasting ability. Almost everything else uses con, including breath weapons and poisons.

It is not explicitly stated in the MM and I cannot prove it, but it mostly works out.

There are some exceptions. The solar and the gas spore have DCs which seem to be set differently. Some, e.g. the dragon turtle and demilich seem miscalculated. But these are few and far between.

dnd 5e – Does the effectiveness of a harpy’s song fluctuate based on her charisma score?

You can make your monsters however you like

Originally, I was very into making consistent monsters where the hit points align with the size category and con modifier. Similarly, the calculation of save DCs. This is nice for published material. I do not do it anymore for my own games since it takes time but does not add any value. My players never get to see the nice alignment of numbers.

In the end the question is what you want to achieve. If you want to build the harpy bard like a player character, it seems reasonable to assume that the luring song is a race feature. In this case you could adopt a calculation like for a dragon born breath weapon, i.e. 8 + proficiency + ability, except you would use charisma instead of constitution. If you just want to be consistent with the MM, the same calculation method is also good.

The MM save DCs are consistent with spell save DCs

In my consistent monster days I disassembled all the DCs in the MM, and found that the vast majority is consistent with 8 + proficiency + ability.

The ability changes depending on the feature. Pushing, pulling and knocking prone uses str, charm and fright use charisma. Some abilities of spellcasters use their spellcasting ability. Almost everything else uses con, including breath weapons and poisons.

It is not explicitly stated in the MM and I cannot prove it, but it mostly works out.

There are some exceptions. The solar and the gas spore have DCs which seem to be set differently. Some, e.g. the dragon turtle and demilich seem miscalculated. But these are few and far between.

Beginner: Would anyone be willing to comment on the structure, design, and effectiveness of my Python program?

The essence of my program is to simulate the growth of some viruses. I used to (tried) using OOP concepts to break the problem into chunks and make the chunks talk to each other. I'm not sure if my implementation is effective but it seems to work quite well. Currently, the bottleneck appears to be in the plot. I am still learning about matplotlib, so it doesn't surprise me.

The program has five classes. The first class just keeps track of the simulation details, nothing too fancy.

class Details():
    def __init__(self,num_people_1d,fig_size):
        self.num_people_1d = num_people_1d
        self.total_people = self.num_people_1d**2

        self.fig_size = fig_size

        self.x_length = self.fig_size(0)/num_people_1d
        self.y_length = self.fig_size(0)/num_people_1d

The second class is the screen. In each iteration, the 2D grid is updated with details about the people who are infected or have perished. The display class is updated with the information.

import matplotlib.pyplot as plt
import matplotlib.patches as patches

class Display():
    def __init__(self,details_instance):
        self.size_x,self.size_y = details_instance.fig_size
        self.length_1d = details_instance.num_people_1d


        self.x_length = details_instance.x_length
        self.y_length = details_instance.y_length

    def create_plot(self,plot_size = (5,5)):
        self.fig = plt.figure(figsize = plot_size)
        self.ax = self.fig.subplots()

        canvas = patches.Rectangle((0,0),1,1,fill=True,
                           edgecolor='none',facecolor='g')
        self.ax.add_patch(canvas)

    def update_plot(self,infected_table=None,kill_table = None): 
        #Transposing tables
        infected_table = list(map(list, zip(*infected_table)))
        kill_table = list(map(list, zip(*kill_table)))

        for i,row in enumerate(infected_table):
            for j,col in enumerate(row):
                infected_person = col
                dead_person = kill_table(i)(j)
                if dead_person:
                    coord = i*self.x_length,j*self.y_length
                    square = patches.Rectangle(coord,
                                       self.x_length,self.y_length,
                                       fill=True,
                                       edgecolor = 'none',
                                       facecolor = 'r')
                    self.ax.add_patch(square)
                if infected_person and not dead_person:
                    coord = i*self.x_length,j*self.y_length
                    square = patches.Rectangle(coord,
                                       self.x_length,self.y_length,
                                       fill=True,
                                       edgecolor = 'none',
                                       facecolor = 'y')
                    self.ax.add_patch(square)
        plt.show()
        plt.pause(0.1)

The next class is the virus class. Not much happens, just the infection and mortality rate.

class Virus():

    def __init__(self,infectionRate = 0.1,mortalityRate = 0.01):
        self.IR = infectionRate
        self.MR = mortalityRate

So he's the kind of person. This class only stores basic information. Whether the person is infected or dead, and some simple methods.

import random

class Person():

    def __init__(self,id = None,discrete_location = None,infected = False):
        self.id = id
        if discrete_location:
            self.dl_x,self.dl_y = discrete_location
        else:
            raise Exception()
        self.infected = infected
        self.neighbors = ()
        self.dead = False

    def become_infected(self,virus):
        if not self.dead:
            self.infected = True
            self.virus = virus

    def do_i_live(self):
        return random.random()>self.virus.MR

    def kill(self):
        self.dead = True
        self.infected = False

The last class is the population class. This class contains most of the code that actually does things because it is what updates all individuals.

from person import Person
import random

class Population():
    def __init__(self,persons=(),details_instance =None,virus_strain=None):
        if len(persons)<1:
            print('There is no population! Adding a member')
            self.persons = persons
            self.count = 0
            self.add_person()

        else:
            self.persons = persons
        self.details_instance = details_instance
        self.virus_strain = virus_strain
        self.dead_persons = (())

    def add_person(self):
        if len(self.persons)<1:
            self.persons.append(Person(id=self.count,
                                  discrete_location = (0,0),
                                  infected = False)
                           )
            self.count +=1
        else:
            loc_x = self.details_instance.x_length*(self.count%self.details_instance.num_people_1d)
            loc_y = self.details_instance.y_length*((self.count - self.count%self.details_instance.num_people_1d)/self.details_instance.num_people_1d)
            person = Person(id = self.count,
                             discrete_location = (loc_x,loc_y),
                             infected = False)
            self.count +=1
            self.persons.append(person)


    def get_infected_table(self):
        truth_table = ()
        current_list = ()
        i = 0
        while i < self.count:
            current_list.append(self.persons(i).infected)
            i+=1
            if (i)%(self.details_instance.num_people_1d) ==0:
                truth_table.append(current_list)
                current_list = ()
        if self.count%(self.details_instance.num_people_1d) !=0:
            truth_table.append(current_list)
        return truth_table

    def get_dead_table(self):
        truth_table = ()
        current_list = ()
        i = 0
        while i < self.count:
            current_list.append(self.persons(i).dead)
            i+=1
            if (i)%(self.details_instance.num_people_1d) ==0:
                truth_table.append(current_list)
                current_list = ()
        if self.count%(self.details_instance.num_people_1d) !=0:
            truth_table.append(current_list)

        return truth_table


    def kill_infected(self,infected_table):
        linear_indices = self.get_infected_indices(infected_table)
        for index in linear_indices:
            still_living = self.persons(index).do_i_live()
            if not still_living:
                self.persons(index).kill()
                self.dead_persons.append(index)

    def add_neighbors(self):
        #Currently returns the linear index! Compatible with persons!!
        if len(self.persons)<=1:
            return

        #One method:
            #Use self.count and modulos to identify neighbors
        #Possibly a better method that I do not follow:
            #Using discrete location to identify neighbors

        #Using first method
        for i in range(self.count):
            #at left boundary
            if i%self.details_instance.num_people_1d==0:
                left = -1
            else:
                left = i-1
            #at right boundary
            if (i+1)%self.details_instance.num_people_1d==0:
                right = -1
            else:
                right = i+1

            up = i+self.details_instance.num_people_1d
            down = i - self.details_instance.num_people_1d

            #First build potential neighbors
            potential_neighbors = (left,right,up,down)

            #Second identify if any potential neighbors don't exist
            neighbor_list = ()
            for j in potential_neighbors:
                if (j >= 0) and (j

To run all this code, I wrote the following script:

from person import Person
from virus import Virus
from display import Display
from details import Details
from population import Population

import random
num_people_1d = 10

simul_details = Details(num_people_1d = num_people_1d,fig_size = (1,1))
virus_strain1 = Virus()
pop = Population(details_instance = simul_details,virus_strain=virus_strain1)

number_people = num_people_1d**2-1
for i in range(number_people):
    pop.add_person()
pop.add_neighbors()
starting_person = random.randint(0,number_people-1)
print('The starting person is %d' % starting_person)

pop.persons(starting_person).become_infected(virus_strain1)
current_infected = pop.get_infected_table()
current_dead = pop.get_dead_table()

simul_display = Display(details_instance=simul_details)
simul_display.create_plot()

total = 100
for iter in range(total):
    infected_people = pop.get_infected_count()
    dead_people = pop.get_dead_count()
    print('The iteration we are on is %d with %d infected' %(iter,infected_people))
    simul_display.update_plot(current_infected,current_dead)

    pop.spread_infection(current_infected)
    current_infected=pop.get_infected_table()
    pop.kill_infected(current_infected)
    current_dead = pop.get_dead_table()

    if infected_people+dead_people > number_people:
        print('All individuals are infected or dead!')
        break

This is all the code. Any comments will be appreciated. Thank you!

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Database design: how is the effectiveness of a data model measured objectively?

I am not sure which topic this belongs to, but I am investigating the theory behind the following questions:

What is the best data model for a particular data set (let's say this data set is large, but arranged for simplicity)?

Are there any universal measures that are optimized with respect to data compression?

What are the variables that affect & # 39; effectiveness & # 39; of a data model?

I have done some research on the subject, and the concept of entropy is often mentioned in relation to information coding in general and text compression in particular. Has anyone in the world of database / content modeling explored a similar topic?

Any pointer would be much appreciated.

Your opinion on the effectiveness of mobile applications in business.

I am interested in your opinion on the effectiveness of mobile applications in business. Should I request your development for a small online store or is it a waste of money?

privacy: Is there any study on the effectiveness of government cybersecurity agencies to prevent terrorist attacks?

Government cybersecurity agencies are blatantly spying on their own citizens. They justify all data collection by stating that they are capable of identifying terrorist threats. So, are there statistics from non-governmental cybersecurity agencies about the terrorist attack plan that these agencies have captured?

The reason why I ask is because I understand that the lack of intelligence means a greater risk for all citizens. However, excessive information is another concern due to a possible abuse of power (for example, the government of China) and individual privacy. If the argument is reduced to a conceptual argument of people who renounce Privacy (data) for Security (against Threats / Terrorists), how do we know that it is mainly a security theater as the failure rate of 80% of the TSA to detect terrorists or have adverse effects? For example, as the government collects more data, more tools are developed to protect privacy. As more tools are developed to protect privacy, criminals and terrorists will adapt to the use of those tools and the government will only be spying on an innocent civilian.

dnd 5e – Do I correctly evaluate the effectiveness of a mystic's skills in CQC, fighting a jellyfish?

Descriptions

Petrifying look.

When a creature that can watch Medusa's eyes begin their turn 30 feet from the jellyfish, the jellyfish can force her to make a DC 14 Constitution save roll if the jellyfish is not Disabled and can see the creature.

Tremorsense.

A monster with tremorsense can. detect and identify the origin of the vibrations within a specific radius, provided that the monster and the source of the vibrations are in contact with the same background or substance.

Blind view

A creature with blind vision can perceive Your environment without depending on the view, within a specific radius.

The perfect senses

You get an acute sense of smell and an instinct to detect prey. You can watch Creatures and invisible objects within 10 feet of you, even if you are blinded.

Explanations

A creature that only uses the tremor sense can only indicate the location of the Medusa. Because of this, such a creature could not see his eyes, and therefore would not be affected by his face. Even if she stays still, she still has a throbbing heart or other functions that could create vibrations.

As for Perceiving the sight, if you look through your own blindfold and see their eyes, you can be petrified. Nowhere in Petrifying Gaze's text do you see that your eyes must see, only you, that you have not hidden yourself.
Perceiving the invisible is essentially the same. If you can avoid seeing their eyes, just by looking at their auras, you should be fine.

The blind view is funny, but RAW, does not "see" it. Affirms that instead perceive. Because of this, and because it specifically says that one must "see" the eyes of the jellyfish in petrifying gaze, the blind characters are quite safe from that attack.

In the Perfect Senses text, we see that the word "see" is used explicitly. If you had this and looked at the Medusa, you are a gonner.

Spells and attacks

Most spells require you to see your objective. These spells would not work against Medusa like RAW while you were using only the trembling sense. However, if your DM is good, they can allow you to cast the spell at a disadvantage on your roll or give the Medusa the advantage of their salvation, or a similar mechanic, just to see if you can point to the right place.

As for the attacks with weapons that use only the sense of trembling, you will again be at a disadvantage, since the rules say that you must be able to see your target.

When you attack a target that you can not see, you have a disadvantage in the attack roll. This is true if you are guessing the location of the target or if you are targeting a creature that you can hear but can not see. If the target is not in the location that you targeted, you fail automatically, but the GM usually only says that the attack was not made, not if you guessed the location of the target correctly.

BUT NEVERTHELESS, this tweet by Jeremy Crawford It establishes that creatures with blind vision can see effectively. This means that targeting creatures with spells and attacks that require you to see the individual are not at a disadvantage.