def set_up(props=None):
"""
A func to set up run that can also be used by test code.
"""
global sandpile_env
global groups
global group_indices
pa = get_props(MODEL_NAME, props)
width = pa.get('grid_width', DEF_WIDTH)
height = pa.get('grid_height', DEF_HEIGHT)
groups = []
group_indices = {}
for i in range(NUM_GROUPS):
groups.append(Composite("Group" + str(i), {"marker": CIRCLE}))
group_indices[groups[i].name] = i
for y in range(height):
for x in range(width):
groups[0] += create_grain(x, y)
sandpile_env = Env("Sandpile",
action=sandpile_action,
height=height,
width=width,
members=groups,
attrs={"size": 65,
"hide_axes": True,
"hide_legend": True},
random_placing=False,
props=pa)
sandpile_env.attrs["center_agent"] = sandpile_env.get_agent_at(height // 2,
width // 2)
return sandpile_env, groups, group_indices
def set_up(props=None):
"""
A func to set up run that can also be used by test code.
"""
global groups
pa = get_props(MODEL_NAME, props)
height = pa.get("grid_height", DEF_HEIGHT)
width = pa.get("grid_width", DEF_WIDTH)
simulation = pa.get("simulation", 0)
black = Composite("Black", {"color": BLACK, "marker": SQUARE})
groups = [black]
Env("Game of Life",
action=gameoflife_action,
height=height,
width=width,
members=groups,
attrs={"size": 100,
"change_grid_spacing": (0.5, 1),
"hide_xy_ticks": True,
"hide_legend": True},
random_placing=False,
props=pa)
populate_board_dict[simulation](width, height)
return groups
def set_up(props=None):
"""
A func to set up run that can also be used by test code.
"""
pa = get_props(MODEL_NAME, props)
flock = Composite(BIRD_GROUP, {
"color": BLUE,
"marker": TREE
},
member_creator=create_bird,
num_members=pa.get('num_birds', DEF_NUM_BIRDS))
Env("the_sky",
height=pa.get('grid_height', DEF_HEIGHT),
width=pa.get('grid_width', DEF_WIDTH),
members=[flock])
def set_up(props=None):
"""
A func to set up run that can also be used by test code.
"""
pa = get_props(MODEL_NAME, props)
blue_group = Composite("Blues", {"color": BLUE},
member_creator=create_agent,
num_members=pa.get('num_blue', DEF_NUM_BLUE))
red_group = Composite("Reds", {"color": RED},
member_creator=create_agent,
num_members=pa.get('num_red', DEF_NUM_RED))
env = Env("env",
height=pa.get('grid_height', DEF_HEIGHT),
width=pa.get('grid_width', DEF_WIDTH),
members=[blue_group, red_group],
props=pa)
return (env, blue_group, red_group)
def set_up(props=None):
"""
Create an Env for Big box.
"""
global groups
global mp_pref
global hood_size
global store_census
global period
global bb_capital
pa = get_props(MODEL_NAME, props)
width = pa.get("grid_width", DEF_WIDTH)
height = pa.get("grid_height", DEF_HEIGHT)
num_consumers = pa.get("consumer_num", NUM_OF_CONSUMERS)
num_mp = pa.get("mp_num", NUM_OF_MP)
mp_pref = pa.get("mp_pref", MP_PREF)
hood_size = pa.get("hood_size", HOOD_SIZE)
multiplier = pa.get("multiple", MULTIPLIER)
bb_capital = multiplier * STANDARD
period = pa.get("period", PERIOD)
consumer_group = Composite("Consumer", {"color": GRAY},
member_creator=create_consumer,
num_members=num_consumers)
bb_group = Composite("Big box", {"color": BLUE})
groups = [consumer_group, bb_group]
for stores in range(0, len(mp_stores)):
store_name = list(mp_stores.keys())[stores]
groups.append(
Composite(store_name,
{"color": mp_stores[store_name][COLOR_INDX]}))
for m in range(0, num_mp):
rand = random.randint(2, len(groups) - 1)
groups[rand] += create_mp(groups[rand], m)
Env("Town",
action=town_action,
members=groups,
height=height,
width=width,
props=pa)
return (groups)
def set_up(props=None):
"""
A func to set up run that can also be used by test code.
"""
global groups
global curr_row
global rule_dict
global rule_num
pa = get_props(MODEL_NAME, props)
width = pa.get('grid_width', DEF_WIDTH)
rule_num = pa.get('rule_number', DEF_RULE)
rule_dict = get_rule(rule_num)
height = 0
height = (width // 2) + (width % 2)
white = Composite("White", {"color": WHITE})
black = Composite("Black", {"color": BLACK, "marker": SQUARE})
groups = [white, black]
for y in range(height):
for x in range(width):
groups[W] += create_wolf_cell(x, y)
wolfram_env = Env("Wolfram Model",
action=wolfram_action,
height=height,
width=width,
members=groups,
attrs={
"size": 50,
"hide_grid_lines": True,
"hide_legend": True
},
random_placing=False,
props=pa)
wolfram_env.exclude_menu_item("line_graph")
wolfram_env.now_switch(wolfram_env.get_agent_at(width // 2, height - 1),
groups[W], groups[B])
curr_row = wolfram_env.get_row_hood(wolfram_env.height - 1)
return (wolfram_env, groups, rule_dict)
"""
import os
import json
import random
from numpy import random as np_random
from indra.utils import get_props
MODEL_NAME = "dealer_car_generator"
MIN_CAR_LIFE = .2
POS_EMOJIS = ["smiley", "laughing", "relaxing", "wink"]
NEG_EMOJIS = ["unnatural", "ambiguous", "hesitate", "eye rolling"]
MEAN_SCORE = 3
dealers = {}
pa = get_props(MODEL_NAME, None, model_dir="ml")
dealer_num = pa.get("num_dealers", 10)
car_num = pa.get("num_cars", 50)
for i in range(dealer_num):
center_score = np_random.uniform(1, 5)
lst = [
max(round(random.gauss(center_score, 0.7), 1), MIN_CAR_LIFE)
for i in range(car_num)
]
dealer = {}
dealer_name = "dealer" + str(i)
if center_score >= MEAN_SCORE:
emoji = random.choice(POS_EMOJIS)
else:
emoji = random.choice(NEG_EMOJIS)
dealers[dealer_name] = {'emoji': emoji, 'scores': lst}