This commit is contained in:
Varyngoth
2026-01-28 13:31:49 -04:00
commit 676659e5b9
239 changed files with 7509 additions and 0 deletions

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# -*- coding: utf-8 -*-
"""
E.Drake - ENGN-2220
Thu Jan 22 23:48:50 2026
"""
from pathlib import Path
ROOT = Path(__file__).parent.parent.parent
SOURCE_DIR = ROOT/"source"
ARCHIVE_DIR = ROOT/"archive"
PATH_DIR = ROOT/"path"
AGENTS_DIR = ROOT/SOURCE_DIR/"sim_agents"
GEO_DIR = ROOT/SOURCE_DIR/"sim_geometry"
TEST_DIR = ROOT/SOURCE_DIR/"test"

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import pandas as pd
import numpy as np
from dataclasses import dataclass
grades = {
"Kindergarden":np.array(
[31.43,5.65,1.21,0.24]
),
"Grade 1":np.array(
[32.57,6.27,1.35,0.26]
),
"Grade 2":np.array(
[34.43,6.80,1.42,0.28]
),
"Grade 3":np.array(
[35.43,5.19,1.48,0.23]
),
"Grade 4":np.array(
[34.86,6.77,1.58,0.26]
),
"Grade 5":np.array(
[36.71,7.09,1.59,0.24]
),
"Grade 6":np.array(
[37.71,6.99,1.65,0.24]
),
"Grade 7":np.array(
[40.43,6.02,1.61,0.25]
),
"Grade 8":np.array(
[40.43,5.50,1.66,0.24]
),
"Grade 9":np.array(
[44.14,4.85,1.60,0.24]
),
"Grade 10":np.array(
[46.29,6.29,1.57,0.23]
),
"Grade 11":np.array(
[48.29,3.30,1.51,0.22]
),
"Grade 12":np.array(
[43.71,6.02,1.54,0.23]
)}
df_srs_data=pd.DataFrame({
"Grade Level":(
list(grades.keys())),
"Pop Mean":[
grades[j][0] for j in grades],
"Pop Std Dev":[
grades[j][1] for j in grades],
"Speed Mean":[
grades[j][2] for j in grades],
"Speed Std Dev":[
grades[j][3] for j in grades]})
@dataclass
class AgentConfig:
id:int
grade:str
door:str
speed:float
radius:float

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import numpy as np
from dataclasses import dataclass
from typing import List, Dict, Optional
from collections import defaultdict
##https://censusatschool.ca/data-results/2017-2018/average-height-by-age/
@dataclass
class AgentConfig:
id:int
grade:str
door:int
speed:float
radius:float
def agent_params():
gr_data = {
# [0]: number of students
# [1]: door number
# [2]: speed mean
# [3]: speed standard deviation
# [4]: radius mean
"Kindergarden":np.array(
[34,0,1.21,0.24,0.407]
),
"Grade 1":np.array(
[26,0,1.35,0.26,0.407]
),
"Grade 2":np.array(
[42,0,1.42,0.28,0.407]
),
"Grade 3":np.array(
[39,0,1.48,0.23,0.407]
),
"Grade 4":np.array(
[30,1,1.58,0.26,0.417]
),
"Grade 5":np.array(
[43,1,1.59,0.24,0.434]
),
"Grade 6":np.array(
[29,1,1.65,0.24,0.454]
),
"Grade 7":np.array(
[45,2,1.61,0.25,0.471]
),
"Grade 8":np.array(
[36,2,1.66,0.24,0.488]
),
"Grade 9":np.array(
[44,2,1.60,0.24,0.500]
),
"Grade 10":np.array(
[36,2,1.57,0.23,0.507]
),
"Grade 11":np.array(
[54,2,1.51,0.22,0.515]
),
"Grade 12":np.array(
[46,2,1.54,0.23,0.520]
)}
agent_id = 1
rng = np.random.default_rng(seed=42)
all_agents = []
gr_agents = []
for grade in gr_data:
for num in range(int(gr_data[grade][0])):
door = gr_data[grade][1]
speed = rng.normal(
loc=gr_data[grade][2],
scale=gr_data[grade][3],
size=1)
radius = gr_data[grade][4]
gr_agents.append(
AgentConfig(
id=agent_id,
grade=grade,
door=door,
speed=speed,
radius = radius
))
agent_id += 1
all_agents.append(gr_agents)
gr_agents = []
#for grade in all_agents:
# for agent in grade:
# print(agent)
return all_agents