def init_props(model_nm, props=None, model_dir=None,
skip_user_questions=False):
model_dir = get_model_dir(model_dir)
props_file = get_prop_path(model_nm, model_dir=model_dir)
if props is None:
pa = PropArgs.create_props(model_nm,
ds_file=props_file,
skip_user_questions=skip_user_questions)
else:
pa = PropArgs.create_props(model_nm,
prop_dict=props,
skip_user_questions=skip_user_questions)
return pa
def init_props(model_nm, props=None, model_dir="models",
skip_user_questions=False):
props_file = get_prop_path(model_nm, model_dir=model_dir)
if props is None:
pa = PropArgs.create_props(model_nm,
ds_file=props_file,
skip_user_questions=skip_user_questions)
else:
pa = PropArgs.create_props(model_nm,
prop_dict=props,
skip_user_questions=skip_user_questions)
# we keep props available in registry:
set_propargs(pa)
return pa
def set_up():
"""
A func to set up run that can also be used by test code.
"""
global on_fire
global healthy
ds_file = 'props/forestfire.props.json'
pa = PropArgs.create_props('forest_fire_props', ds_file=ds_file)
forest_height = pa.get('grid_height', DEF_DIM)
forest_width = pa.get('grid_width', DEF_DIM)
forest_density = pa.get('density', DEF_DENSITY)
healthy = Composite(HEALTHY, {"color": GREEN})
new_fire = Composite(NEW_FIRE, {"color": TOMATO})
on_fire = Composite(ON_FIRE, {"color": RED})
burned_out = Composite(BURNED_OUT, {"color": BLACK})
new_growth = Composite(NEW_GROWTH, {"color": SPRINGGREEN})
for i in range(int(forest_height * forest_width * forest_density)):
healthy += plant_tree(i)
forest = Env("Forest", height=forest_height, width=forest_width,
members=[healthy, new_fire, on_fire, burned_out,
new_growth])
global group_map
group_map = {HE: healthy, NF: new_fire,
OF: on_fire, BO: burned_out, NG: new_growth}
return (forest, group_map)
def set_up():
"""
A func to set up run that can also be used by test code.
"""
global pa
pa = PropArgs.create_props('wolfsheep_props',
ds_file='props/wolfsheep.props.json')
wolves = Composite(COMP_WOLF_NAME, {"color": TAN})
for i in range(pa.get('num_wolves', NUM_WOLVES)):
wolves += create_wolf(i, pa)
if DEBUG2:
print(wolves.__repr__())
sheep = Composite(COMP_SHEEP_NAME, {"color": GRAY})
for i in range(pa.get('num_sheep', NUM_SHEEP)):
sheep += create_sheep(i, pa)
if DEBUG2:
print(sheep.__repr__())
meadow = Env("meadow", members=[wolves, sheep],
height=pa.get('meadow_height', MEADOW_HEIGHT),
width=pa.get('meadow_width', MEADOW_WIDTH))
return (wolves, sheep, meadow)
def set_up():
"""
A func to set up run that can also be used by test code.
"""
pa = PropArgs.create_props('basic_props',
ds_file='props/segregation.props.json')
blue_agents = Composite(group_names[BLUE_TEAM] + " group", {"color": BLUE})
red_agents = Composite(group_names[RED_TEAM] + " group", {"color": RED})
for i in range(pa['num_red']):
red_agents += create_agent(i,
pa.get('mean_tol', DEF_TOLERANCE),
pa.get('deviation', DEF_SIGMA),
color=RED_TEAM)
if DEBUG2:
print(red_agents.__repr__())
for i in range(pa['num_blue']):
blue_agents += create_agent(i,
pa.get('mean_tol', DEF_TOLERANCE),
pa.get('deviation', DEF_SIGMA),
color=BLUE_TEAM)
if DEBUG2:
print(blue_agents.__repr__())
city = Env("A city",
members=[blue_agents, red_agents],
height=pa['grid_height'],
width=pa['grid_width'])
return (blue_agents, red_agents, city)
def set_up():
"""
A func to set up run that can also be used by test code.
"""
pa = PropArgs.create_props('basic_props',
ds_file='props/fashion.props.json')
blue_tsetters = Composite(BLUE_TSETTERS, {"color": NAVY})
red_tsetters = Composite(RED_TSETTERS, {"color": DARKRED})
for i in range(pa.get('num_tsetters', NUM_TSETTERS)):
red_tsetters += create_tsetter(i)
if DEBUG2:
print(red_tsetters.__repr__())
red_followers = Composite(RED_FOLLOWERS, {"color": RED})
blue_followers = Composite(BLUE_FOLLOWERS, {"color": BLUE})
for i in range(pa.get('num_followers', NUM_FOLLOWERS)):
blue_followers += create_follower(i)
opp_group = {str(red_tsetters): blue_tsetters,
str(blue_tsetters): red_tsetters,
str(red_followers): blue_followers,
str(blue_followers): red_followers}
if DEBUG2:
print(blue_followers.__repr__())
society = Env("society", members=[blue_tsetters, red_tsetters,
blue_followers, red_followers])
return (blue_tsetters, red_tsetters, blue_followers, red_followers,
opp_group, society)
def get(self, model_id):
"""
Get the list of properties (parameters) for a model.
"""
props = PropArgs.create_props(str(model_id),
prop_dict=get_props(model_id, indra_dir))
exec_key = create_exec_env(save_on_register=True)
props["exec_key"] = exec_key
registry.save_reg(exec_key)
return props.to_json()
def init_props(model_nm,
props=None,
model_dir="models",
skip_user_questions=False):
props_file = get_prop_path(model_nm, model_dir=model_dir)
execution_key = CLI_EXEC_KEY if props is None else int(
props.get(EXEC_KEY).get("val"))
if props is None:
pa = PropArgs.create_props(model_nm,
ds_file=props_file,
skip_user_questions=skip_user_questions)
else:
pa = PropArgs.create_props(model_nm,
prop_dict=props,
skip_user_questions=skip_user_questions)
# we keep props available in registry:
execution_registry.set_propargs(execution_key, pa)
return pa
def set_up():
"""
A func to set up run that can also be used by test code.
"""
pa = PropArgs.create_props('basic_props', ds_file='props/basic.props.json')
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])
return (blue_group, red_group, env)
"""
This is wolf-sheep re-written in indra.
"""
from propargs.propargs import PropArgs
from indra.agent import Agent
from indra.composite import Composite
from indra.space import in_hood
from indra.env import Env
from indra.display_methods import TAN, GRAY
DEBUG = True # turns debugging code on or off
DEBUG2 = False # turns deeper debugging code on or off
pa = PropArgs.create_props('basic_props',
ds_file='props/wolfsheep.props.json')
NUM_WOLVES = 8
NUM_SHEEP = 20
HOOD_SIZE = 3
MEADOW_HEIGHT = 10
MEADOW_WIDTH = 10
WOLF_LIFESPAN = 5
WOLF_REPRO_PERIOD = 6
SHEEP_LIFESPAN = 8
SHEEP_REPRO_PERIOD = 3
AGT_WOLF_NAME = "wolf"
AGT_SHEEP_NAME = "sheep"
COMP_WOLF_NAME = "wolves"
COMP_SHEEP_NAME = "sheep"
def setUp(self):
self.pa = PropArgs.create_props('flocking_props',
ds_file='props/flocking.props.json')
(self.flock) = set_up()
self.bird_a = create_bird(TEST_BNAME, TEST_BNUM1, props=self.pa)
self.bird_b = create_bird(TEST_BNAME, TEST_BNUM2, props=self.pa)
from propargs.propargs import PropArgs
from indra.agent import Agent, X_VEC, Y_VEC, NEUTRAL
from indra.agent import ratio_to_sin
from indra.composite import Composite
from indra.space import in_hood
from indra.env import Env
from indra.display_methods import NAVY, DARKRED, RED, BLUE
import numpy as np
DEBUG = True # turns debugging code on or off
DEBUG2 = False # turns deeper debugging code on or off
NUM_TSETTERS = 5
NUM_FOLLOWERS = 55
pa = PropArgs.create_props('basic_props', ds_file='props/fashion.props.json')
"""
Adding weighted average for having a sine curve
"""
ENV_WEIGHT = 0.6
weightings = [1.0, pa.get('env_weight', ENV_WEIGHT)]
COLOR_PREF = "color_pref"
DISPLAY_COLOR = "display_color"
BLUE_SIN = 0.0
RED_SIN = 1.0
# for future use as we move to vector representation:
BLUE_VEC = X_VEC
RED_VEC = Y_VEC
def tearDown(self):
pass
self.pa = PropArgs.create_props('used_car_props',
ds_file='props/used_cars.props.json')
(self.car_market, self.dealers, self.buyers) = set_up(10) # noqa: F405
def setUp(self):
self.pa = PropArgs.create_props('gameoflife_props',
ds_file='props/gameoflife.props.json')
(g.groups) = set_up()
pass
def setUp(self):
self.pa = PropArgs.create_props('wolfsheep_props',
ds_file='props/wolfsheep.props.json')
(ws.wolves, ws.sheep, ws.meadow) = set_up()
self.wolf = create_wolf(TEST_WNUM, self.pa)
self.sheep = create_sheep(TEST_SNUM, self.pa)