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justheuristic/create_roll_table.py

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Generated with versions bokeh - 3.1.1; numpy - 1.23.5; tqdm - 4.64.1 (pip install bokeh==3.1.1 numpy tqdm)
Raw
create_roll_table.py
"""
This script creates an HTML file that displays success probabilities for Changeling the Dreaming 20th Anniversary Edition.
See lines 27-34 for parameters that you might want to change. Note that large num_attempts will slow down the script.
You can run the code in a Jupyter Notebook or similar to display the roll table interactively in your notebook.
CtD20 differs from prior editions: willpower success can be cancelled by a "1" and speciality grants two successes on 10.
If you want to change how this works (e.g. VtM 3e willpower can't be cancelled), find and modify def roll_dice(...) below.
License: do whatever you want with this file, see Unlicense for details https://en.wikipedia.org/wiki/Unlicense
"""
import random
from enum import Enum
from collections import Counter, defaultdict
import tqdm
import numpy as np
import bokeh
from bokeh.models import ColumnDataSource, HoverTool, LabelSet
from bokeh.models.widgets import RadioButtonGroup, CheckboxGroup
from bokeh.layouts import column, row
from bokeh.models.callbacks import CustomJS
from bokeh.plotting import figure, output_file, output_notebook, reset_output, show
print(f"Versions: bokeh - {bokeh.__version__}\tnumpy - {np.__version__}\ttqdm - {tqdm.__version__}")
difficulties = list(range(3, 11))
dice_pools = list(range(1, 11))
num_attempts = 1_000_000 # number of monte-carlo rolls for each situation
default_outcome = "1_successes_or_more"
output_file_name = "ctd20_roll_table.html"
MAX_SUCCESSES = 6 # if changed, also change the number of SUCCESS values in the Outcome enum below
class Outcome(Enum):
BOTCH, FAILURE, SUCCESS1, SUCCESS2, SUCCESS3, SUCCESS4, SUCCESS5, SUCCESS6_or_more = range(-1, MAX_SUCCESSES + 1)
def roll_dice(dice: int, difficulty: int, specialty: bool = False, willpower: bool = False) -> Outcome:
"""
Roll a dice pool and count the number successes after subtracting all ones and adding special conditions
:param specialty: if True, each roll of "10" counts as 2 successes (CtD 20th edition rule)
:param willpower: if True, you spent 1 willpower point ahead of time to get one automatic success:
"""
rolls = [random.randint(1, 10) for _ in range(dice)]
successes = sum(roll >= difficulty for roll in rolls)
if specialty: # 10s count as two successes
successes += sum(roll == 10 for roll in rolls)
if willpower:
successes += 1
ones = sum(roll == 1 for roll in rolls)
if successes == 0 and ones > 0:
return Outcome.BOTCH
elif successes - ones <= 0:
return Outcome.FAILURE
elif successes - ones > 0:
return Outcome(min(successes - ones, MAX_SUCCESSES))
else:
raise RuntimeError("Unexpected outcome")
def to_percentage_string(probability: float) -> str:
return f"{100 * probability:3.1f}%"
############################
# compute monte-carlo data #
############################
data_dict = defaultdict(list)
with tqdm.trange(len(dice_pools) * len(difficulties) * 4, desc="Gathering statistics...") as progressbar:
for dice_pool in dice_pools:
for difficulty in difficulties:
for willpower in False, True:
prefix = "willpower_" if willpower else ""
for specialty in False, True:
prefix += "specialty_" if specialty else ""
data_dict[prefix + 'dice_pool'].append(dice_pool)
data_dict[prefix + 'difficulty'].append(difficulty)
outcome_counts = Counter((roll_dice(dice_pool, difficulty, specialty, willpower)
for _ in range(num_attempts)))
data_dict[prefix + 'botch'].append(
to_percentage_string(outcome_counts[Outcome.BOTCH] / num_attempts))
data_dict[prefix + 'failure'].append(
to_percentage_string(outcome_counts[Outcome.FAILURE] / num_attempts))
for k in range(1, MAX_SUCCESSES + 1): # n^2 loop; can be done in O(n) but im lazy
data_dict[f"{prefix}{k}_successes"].append(
to_percentage_string(outcome_counts[Outcome(k)] / num_attempts))
data_dict[f"{prefix}{k}_successes_or_more"].append(to_percentage_string(
sum(outcome_counts[Outcome(i)] for i in range(k, MAX_SUCCESSES + 1)) / num_attempts
))
progressbar.update()
assert default_outcome in data_dict
data_dict['cell_text'].append(data_dict[default_outcome][-1])
probability = float(data_dict[default_outcome][-1][:-1]) / 100
brightness = hex(min(max(0, int(round(probability * 256))), 255))[2:].rjust(2, "0")
assert len(brightness) == 2, "brightness must be a 2-digit hex code"
data_dict['cell_color'].append("#" + brightness * 3)
data_dict['text_color'].append("#080808" if probability > 0.5 else "#f8f8f8")
################################
# Arrange data as a Bokeh plot #
################################
reset_output()
output_file(output_file_name)
if hasattr(__builtins__,'__IPYTHON__'):
output_notebook() # show widget if running in a notebook
data_source = ColumnDataSource(data=data_dict)
hover = HoverTool(tooltips = [
('Dice rolled','@dice_pool'),('Difficulty','@difficulty'), ('Botch', '@botch'), ('Failure', '@failure'),
] + [
(f'Success {i}+', f'@{i}_successes_or_more') for i in range(1, MAX_SUCCESSES + 1)
] + [(" ", " "),
("Willpower 1+", "@willpower_1_successes_or_more"),
("Specialty 5+", "@specialty_5_successes_or_more"),
("Will+Spec 5+", "@willpower_specialty_5_successes_or_more")])
fig = figure(
width=720, height=720, tools=[hover],
x_range=(min(difficulties) - 0.5, max(difficulties) + 0.5),
y_range=(min(dice_pools) - 0.5, max(dice_pools) + 0.5))
fig.rect(x="difficulty", y="dice_pool", width=1.01, height=1.01,
fill_color="cell_color", line_width=0.0, source=data_source, )
fig.add_layout(LabelSet(x='difficulty', y='dice_pool', text="cell_text", text_color="text_color",
x_offset=-20, y_offset=-10, text_font_size="12pt", source=data_source,))
fig.xaxis.ticker = difficulties
fig.xaxis.axis_label = "Roll difficulty (3 = trivial, 10 = insane)"
fig.xaxis.axis_label_text_font_size = "16px"
fig.yaxis.ticker = dice_pools
fig.yaxis.axis_label = "Dice pool (number of dice rolled)"
fig.yaxis.axis_label_text_font_size = "16px"
outcome_column_names = ["botch", "failure"] + [f"{i}_successes_or_more" for i in range(1, MAX_SUCCESSES + 1)]
outcome_choice = RadioButtonGroup(
labels=["Botch", "Failure",] + [f"Success {i}+" for i in range(1, MAX_SUCCESSES + 1)],
active=outcome_column_names.index(default_outcome),)
options_checkbox = CheckboxGroup(labels=["Willpower", "Specialty"])
callback = CustomJS(
args=dict(fig=fig, data_source=data_source,
outcome_choice=outcome_choice, options_checkbox=options_checkbox,
outcome_column_names=outcome_column_names),
code="""
// note: we do not use cb_obj (callback object) to make callback work for multiple objects
var data = data_source.data;
var chosen_outcome_index = outcome_choice.properties.active._value // int
var chosen_option_indices = options_checkbox.properties.active._value // Array[int]
var prefix = ""
if (chosen_option_indices.includes(0)) prefix += "willpower_"
if (chosen_option_indices.includes(1)) prefix += "specialty_"
var new_percentage_strings = data[prefix + outcome_column_names[chosen_outcome_index]]
for(let i = 0; i < new_percentage_strings.length; i++){
data["cell_text"][i] = new_percentage_strings[i]
var percentage = parseFloat(new_percentage_strings[i].slice(0, -1))
var brightness = Math.max(0, Math.min(255, Math.round(percentage * 256 / 100)))
data["cell_color"][i] = "#" + brightness.toString(16).padStart(2, "0").repeat(3)
if (percentage > 50) data["text_color"][i] = "#080808"
else data["text_color"][i] = "#f8f8f8"
}
data_source.change.emit();
""")
outcome_choice.js_on_event("button_click", callback)
options_checkbox.js_on_change("active", callback)
show(column(row(outcome_choice, options_checkbox), fig))
Raw
ctd20_roll_table.html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Bokeh Plot</title>
<style>
html, body {
box-sizing: border-box;
height: 100%;
margin: 0;
padding: 0;
}
</style>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div id="b65f5d89-3481-4360-8723-54c31a2eb8dc" data-root-id="p1404" style="display: contents;"></div>
<script type="application/json" id="p1460">
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// note: we do not use cb_obj (callback object) to make callback work for multiple objects\n var data = data_source.data; \n var chosen_outcome_index = outcome_choice.properties.active._value // int\n var chosen_option_indices = options_checkbox.properties.active._value // Array[int]\n \n var prefix = \"\"\n if (chosen_option_indices.includes(0)) prefix += \"willpower_\"\n if (chosen_option_indices.includes(1)) prefix += \"specialty_\"\n \n var new_percentage_strings = data[prefix + outcome_column_names[chosen_outcome_index]]\n \n for(let i = 0; i &lt; new_percentage_strings.length; i++){\n data[\"cell_text\"][i] = new_percentage_strings[i]\n var percentage = parseFloat(new_percentage_strings[i].slice(0, -1))\n var brightness = Math.max(0, Math.min(255, Math.round(percentage * 256 / 100)))\n data[\"cell_color\"][i] = \"#\" + brightness.toString(16).padStart(2, \"0\").repeat(3)\n if (percentage &gt; 50) data[\"text_color\"][i] = \"#080808\"\n else data[\"text_color\"][i] = \"#f8f8f8\"\n }\n data_source.change.emit();\n "}}]]]},"labels":["Botch","Failure","Success 1+","Success 2+","Success 3+","Success 4+","Success 5+"],"active":2}},{"id":"p1401"}]}},{"id":"p1350"}]}}],"callbacks":{"type":"map"}}}
</script>
<script type="text/javascript">
(function() {
const fn = function() {
Bokeh.safely(function() {
(function(root) {
function embed_document(root) {
const docs_json = document.getElementById('p1460').textContent;
const render_items = [{"docid":"c43af86a-fcb3-4129-9f83-fd8dd7fa21fc","roots":{"p1404":"b65f5d89-3481-4360-8723-54c31a2eb8dc"},"root_ids":["p1404"]}];
root.Bokeh.embed.embed_items(docs_json, render_items);
}
if (root.Bokeh !== undefined) {
embed_document(root);
} else {
let attempts = 0;
const timer = setInterval(function(root) {
if (root.Bokeh !== undefined) {
clearInterval(timer);
embed_document(root);
} else {
attempts++;
if (attempts > 100) {
clearInterval(timer);
console.log("Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing");
}
}
}, 10, root)
}
})(window);
});
};
if (document.readyState != "loading") fn();
else document.addEventListener("DOMContentLoaded", fn);
})();
</script>
</body>
</html>
Raw
variant_compact_display_code.py
# Alternative drawing code that arranges the data in a more compact manner, friendly for horizontal smartphone screens
# To enable this mode, find the # Arrange data as a Bokeh plot" comment and replace the code after this comment with the code below:
################################
# Arrange data as a Bokeh plot #
################################
reset_output()
output_file(output_file_name)
if hasattr(__builtins__,'__IPYTHON__'):
output_notebook() # show widget if running in a notebook
data_source = ColumnDataSource(data=data_dict)
hover = HoverTool(tooltips = [
('Dice rolled', '@dice_pool'), ('Difficulty', '@difficulty'), ('Botch', '@botch'), ('Failure', '@failure'),
] + [
(f'Success {i}+', f'@{i}_successes_or_more') for i in range(1, MAX_SUCCESSES + 1)
] + [(" ", " "),
("Willpower 1+", "@willpower_1_successes_or_more"),
("Specialty 5+", "@specialty_5_successes_or_more"),
("Will+Spec 5+", "@willpower_specialty_5_successes_or_more")])
fig = figure(
width=480, height=480, tools=[hover],
x_range=(min(difficulties) - 0.5, max(difficulties) + 0.5),
y_range=(min(dice_pools) - 0.5, max(dice_pools) + 0.5),
)
fig.toolbar_location = None
fig.rect(x="difficulty", y="dice_pool", width=1.01, height=1.01,
fill_color="cell_color", line_width=0.0, source=data_source, )
fig.add_layout(LabelSet(x='difficulty', y='dice_pool', text="cell_text", text_color="text_color",
x_offset=-18, y_offset=-8, text_font_size="10pt", source=data_source,))
fig.xaxis.ticker = difficulties
fig.xaxis.axis_label = "Roll difficulty (3 = trivial, 10 = insane)"
fig.xaxis.axis_label_text_font_size = "16px"
fig.yaxis.ticker = dice_pools
fig.yaxis.axis_label = "Dice pool (number of dice rolled)"
fig.yaxis.axis_label_text_font_size = "16px"
outcome_column_names = ["botch", "failure"] + [f"{i}_successes_or_more" for i in range(1, MAX_SUCCESSES + 1)]
outcome_choice = RadioButtonGroup(
labels=["Botch", "Failure",] + [f"Success {i}+" for i in range(1, MAX_SUCCESSES + 1)],
active=outcome_column_names.index(default_outcome), orientation='vertical', height=380, height_policy="fixed")
options_checkbox = CheckboxGroup(labels=["Willpower", "Specialty"])
callback = CustomJS(
args=dict(fig=fig, data_source=data_source,
outcome_choice=outcome_choice, options_checkbox=options_checkbox,
outcome_column_names=outcome_column_names),
code="""
// note: we do not use cb_obj (callback object) to make callback work for multiple objects
var data = data_source.data;
var chosen_outcome_index = outcome_choice.properties.active._value // int
var chosen_option_indices = options_checkbox.properties.active._value // Array[int]
var prefix = ""
if (chosen_option_indices.includes(0)) prefix += "willpower_"
if (chosen_option_indices.includes(1)) prefix += "specialty_"
var new_percentage_strings = data[prefix + outcome_column_names[chosen_outcome_index]]
for(let i = 0; i < new_percentage_strings.length; i++){
data["cell_text"][i] = new_percentage_strings[i]
var percentage = parseFloat(new_percentage_strings[i].slice(0, -1))
var brightness = Math.max(0, Math.min(255, Math.round(percentage * 256 / 100)))
data["cell_color"][i] = "#" + brightness.toString(16).padStart(2, "0").repeat(3)
if (percentage > 50) data["text_color"][i] = "#080808"
else data["text_color"][i] = "#f8f8f8"
}
data_source.change.emit();
""")
outcome_choice.js_on_event("button_click", callback)
options_checkbox.js_on_change("active", callback)
show(row(fig, column(outcome_choice, options_checkbox)))
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