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()