import random
import time
import goals.explorer.tools.splittree as splittree
render = True
#render = False
bounds = ((0.0, 2.0), (0.0, 2.0))
min_size = (0.01, 0.01)
st = splittree.SplitTree(bounds, 5, min_size=min_size)
if render:
import goals.gfx.areas_gfx as areas_gfx
import goals.gfx.render as render
window = render.PygameWindow((600, 600))
strender = areas_gfx.SplitTreeRenderer(window,
st,
draw_dp=True,
offset=(100, 100))
window.update()
for i in xrange(20):
time.sleep(0.1)
x = random.random()
y = random.random()
st.add((x, y))
window.update()
for i in xrange(100):
st.add((0.4, 0.4))
self.draw_grid(self.testgrid, color = self.testcolor)
for i, rg in enumerate(self.resgrids):
self.draw_grid(rg, color = self.colors[i%len(self.colors)])
def coo2screen(self, x, y):
return int(50+700*x), int(50+700*y)
if __name__ == "__main__":
datadir = "~/Research/local/data/interact"
datadir = os.path.expanduser(datadir)
filename = "primary[0_0001].test"
data = exp.load_test(datadir, filename)
ticks = data["ticks"]
testset = data["testset"]
presults = data["results"]
filename = "secondary[0_0001][0_0001].test"
data = exp.load_test(datadir, filename)
ticks = data["ticks"]
testset = data["testset"]
sresults = data["results"]
window = render.PygameWindow(size = (800, 800))
tgrid = TestGridRenderer(window, testset, [sresults[-1]])
window.update()
while True:
time.sleep(1.0)
import random, sys, time
import treedict
from goals.explorer import datalog
from goals.explorer.effect import cellrider
import goals.gfx.cellrider_gfx as cellrider_gfx
import goals.gfx.render as render
cfg = treedict.TreeDict()
cfg.s_bounds = ((0, 1), (0, 1))
cfg.crit_size = 10
cr = cellrider.CellRider(cfg=cfg)
window = render.PygameWindow((1500, 1000))
dl = datalog.DataLog(None)
crrender = cellrider_gfx.CellRiderRenderer(window, cr, dl, offset=(100, 100))
window.renderers.append(crrender)
for _ in xrange(100):
effect = (random.random(), random.random())
goal = (random.random(), random.random())
prediction = (random.random(), random.random())
dl.manual_feedback(effect, goal=goal, prediction=prediction)
cr.add_effect(effect, goal=goal, prediction=prediction)
window.update()
while True:
cr.next_goal()
window.update()
import testenv
import random
import time
import goals.explorer.effect.cell as cell
from goals.gfx import cell_gfx, render
dcell = cell.DualCell(((-100.0, 100.0),), None, None, w = [1.0])
window = render.PygameWindow((500, 700))
c_gfx = cell_gfx.CellRenderer(window, dcell)
window.renderers.append(c_gfx)
goal = (10.0,)
for i in xrange(100):
effect = (10.0 + random.uniform(-(10-i), 10-i),)
prediction = (10.0 + random.uniform(-(10-i), 10-i),)
dcell.add(effect, goal = goal, prediction = prediction)
window.update()
time.sleep(0.1)
raw_input()