def plot_graph_using_guessed_statespace(self, pylab, # @UnusedVariable
plan2color=None, plan2label=None, cmap=None, origin=None, show_plan=None):
ss = guess_state_space(self.id_dds, self.dds)
def plan2xy(plan):
commands = self.dds.indices_to_commands(plan)
state = ss.state_from_commands(commands, start=origin)
xy = ss.xy_from_state(state)
return 5 * xy
if show_plan is not None:
points = []
for i in range(len(show_plan)):
partial = show_plan[:i]
points.append(plan2xy(partial))
points = np.array(points).T
pylab.plot(points[0], points[1], 'r-')
if plan2color is None:
plan2color = lambda plan: [0, 0, 0] # @UnusedVariable
if plan2label is None:
plan2label = lambda plan: '' # @UnusedVariable
nodes = list(self.G.nodes())
pos = dict((n, plan2xy(n)) for n in nodes)
all_positions = map(tuple, pos.values())
node_color = map(plan2color, nodes)
labels = dict((n, plan2label(n)) for n in self.G)
if False:
if len(all_positions) != len(set(all_positions)):
print('Warning, overlapping nodes')
y = collections.Counter(all_positions)
for p, num in y.items():
if num > 1:
print('- %d for %s' % (num, p))
for node, node_pos in pos.items():
if tuple(node_pos) == p:
print(' - %s ' % str(node))
nx.draw_networkx(self.G, with_labels=True, pos=pos, labels=labels,
node_color=node_color, cmap=cmap)
def plan_report(self, report, result, tc):
"""
We pass the testcase structure, so we can use the ground
truth (if available) to make a nicer visualization.
"""
from matplotlib.cm import get_cmap
f = report.figure(cols=3)
plan2length = lambda x: len(x)
cmap_start = get_cmap('bones')
cmap_goal = get_cmap('jet')
def distance_to(tree, y, node):
image = tree.plan2image(node)
return self.metric_goal.distance(image, y)
from functools import partial
start_dist_y0 = partial(distance_to, self.start_tree, self.y0)
goal_dist_y0 = partial(distance_to, self.goal_tree, self.y0)
start_dist_y1 = partial(distance_to, self.start_tree, self.y1)
goal_dist_y1 = partial(distance_to, self.goal_tree, self.y1)
if result.success:
# Plot the distance as a function of step
steps = plan_steps(result.plan) # (), (0,) (0, 1), etc.
distance_to_y0 = map(start_dist_y0, steps)
distance_to_y1 = map(start_dist_y1, steps)
with f.plot('distances_along_path') as pylab:
lenghts = map(len, steps)
pylab.plot(lenghts, distance_to_y0, 'r-', label='to $y_0$')
pylab.plot(lenghts, distance_to_y1, 'b-', label='to $y_1$')
pylab.xlabel('subplan length')
pylab.legend()
with f.plot('start_tree') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab,
plan2color=plan2length,
cmap=cmap_start,
show_plan=tc.true_plan)
pylab.title('plan length')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_goal)
pylab.title('plan length')
turn_all_axes_off(pylab)
pylab.colorbar()
true_plan = tc.true_plan
ss = guess_state_space(self.id_dds, self._dds)
u0 = self.get_dds().indices_to_commands(true_plan)
origin = ss.state_from_commands(u0)
with f.plot('joint') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('start_tree_y0') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y0, cmap=cmap_start)
pylab.title('distance to $y_0$')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree_y0') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y0, cmap=cmap_goal, origin=origin)
pylab.title('distance to y_0')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('joint_y0') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y0, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y0, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('start_tree_y1') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y1, cmap=cmap_start)
pylab.title('distance to $y_1$')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree_y1') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y1, cmap=cmap_goal)
pylab.title('distance to y_1')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('joint_y1') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y1, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y1, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
def draw_graph(self, r):
def label_plan_length(n):
return len(n)
open_nodes = set(self.open_nodes)
def label_child_open(n):
# number of children in the open list
children = self.G[n]
return len(set(children) & open_nodes)
ss = guess_state_space(self.id_dds, self.dds)
def point_func(plan):
commands = self.dds.indices_to_commands(plan)
state = ss.state_from_commands(commands)
xy = ss.xy_from_state(state)
return 5 * xy
f = r.figure(cols=2)
nolabel = lambda _: ''
with f.data_file('planlength', MIME_PNG) as filename:
draw_node_graph(filename=filename,
G=self.G,
pos_func=point_func,
# label_func=label_plan_length,
label_func=nolabel,
color_func=label_plan_length)
with f.data_file('nchildopen', MIME_PNG) as filename:
draw_node_graph(filename=filename,
G=self.G,
pos_func=point_func,
# label_func=label_child_open,
label_func=nolabel,
color_func=label_child_open)
with f.data_file('info', MIME_PNG) as filename:
draw_node_graph(filename=filename,
G=self.G,
pos_func=point_func,
# label_func=lambda x: '%.2f' % self.visibility(x),
label_func=nolabel,
color_func=self.visibility)
with f.plot('visible') as pylab:
v = map(self.visibility, self.G)
pylab.hist(v, 100)
with r.subsection('embedding') as s:
self.draw_embeddings(s)
all_plans = list(self.G.nodes())
random.shuffle(all_plans)
random_plans = all_plans[:3]
for pi, ref_plan in enumerate(random_plans):
color_func = lambda p2: self.plan_distance(ref_plan, p2)
# diffeoaction_distance_L2_infow)
name = 'random%d' % pi
with f.data_file(name, MIME_PNG) as filename:
draw_node_graph(filename=filename,
G=self.G,
pos_func=point_func,
# label_func=lambda x: '%.2f' % self.visibility(x),
label_func=nolabel,
color_func=color_func)
def plan_report(self, report, result, tc):
"""
We pass the testcase structure, so we can use the ground
truth (if available) to make a nicer visualization.
"""
from matplotlib.cm import get_cmap
f = report.figure(cols=3)
plan2length = lambda x: len(x)
cmap_start = get_cmap('bones')
cmap_goal = get_cmap('jet')
def distance_to(tree, y, node):
image = tree.plan2image(node)
return self.metric_goal.distance(image, y)
from functools import partial
start_dist_y0 = partial(distance_to, self.start_tree, self.y0)
goal_dist_y0 = partial(distance_to, self.goal_tree, self.y0)
start_dist_y1 = partial(distance_to, self.start_tree, self.y1)
goal_dist_y1 = partial(distance_to, self.goal_tree, self.y1)
if result.success:
# Plot the distance as a function of step
steps = plan_steps(result.plan) # (), (0,) (0, 1), etc.
distance_to_y0 = map(start_dist_y0, steps)
distance_to_y1 = map(start_dist_y1, steps)
with f.plot('distances_along_path') as pylab:
lenghts = map(len, steps)
pylab.plot(lenghts, distance_to_y0, 'r-', label='to $y_0$')
pylab.plot(lenghts, distance_to_y1, 'b-', label='to $y_1$')
pylab.xlabel('subplan length')
pylab.legend()
with f.plot('start_tree') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_start,
show_plan=tc.true_plan)
pylab.title('plan length')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_goal)
pylab.title('plan length')
turn_all_axes_off(pylab)
pylab.colorbar()
true_plan = tc.true_plan
ss = guess_state_space(self.id_dds, self._dds)
u0 = self.get_dds().indices_to_commands(true_plan)
origin = ss.state_from_commands(u0)
with f.plot('joint') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=plan2length, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('start_tree_y0') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y0, cmap=cmap_start)
pylab.title('distance to $y_0$')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree_y0') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y0, cmap=cmap_goal, origin=origin)
pylab.title('distance to y_0')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('joint_y0') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y0, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y0, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('start_tree_y1') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y1, cmap=cmap_start)
pylab.title('distance to $y_1$')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('goal_tree_y1') as pylab:
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y1, cmap=cmap_goal)
pylab.title('distance to y_1')
turn_all_axes_off(pylab)
pylab.colorbar()
with f.plot('joint_y1') as pylab:
self.start_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=start_dist_y1, cmap=cmap_start)
self.goal_tree.plot_graph_using_guessed_statespace(
pylab, plan2color=goal_dist_y1, cmap=cmap_goal, origin=origin)
turn_all_axes_off(pylab)
pylab.colorbar()
def draw_graph(self, r):
def label_plan_length(n):
return len(n)
open_nodes = set(self.open_nodes)
def label_child_open(n):
# number of children in the open list
children = self.G[n]
return len(set(children) & open_nodes)
ss = guess_state_space(self.id_dds, self.dds)
def point_func(plan):
commands = self.dds.indices_to_commands(plan)
state = ss.state_from_commands(commands)
xy = ss.xy_from_state(state)
return 5 * xy
f = r.figure(cols=2)
nolabel = lambda _: ''
with f.data_file('planlength', MIME_PNG) as filename:
draw_node_graph(
filename=filename,
G=self.G,
pos_func=point_func,
# label_func=label_plan_length,
label_func=nolabel,
color_func=label_plan_length)
with f.data_file('nchildopen', MIME_PNG) as filename:
draw_node_graph(
filename=filename,
G=self.G,
pos_func=point_func,
# label_func=label_child_open,
label_func=nolabel,
color_func=label_child_open)
with f.data_file('info', MIME_PNG) as filename:
draw_node_graph(
filename=filename,
G=self.G,
pos_func=point_func,
# label_func=lambda x: '%.2f' % self.visibility(x),
label_func=nolabel,
color_func=self.visibility)
with f.plot('visible') as pylab:
v = map(self.visibility, self.G)
pylab.hist(v, 100)
with r.subsection('embedding') as s:
self.draw_embeddings(s)
all_plans = list(self.G.nodes())
random.shuffle(all_plans)
random_plans = all_plans[:3]
for pi, ref_plan in enumerate(random_plans):
color_func = lambda p2: self.plan_distance(
ref_plan, p2, diffeoaction_distance_L2_infow)
name = 'random%d' % pi
with f.data_file(name, MIME_PNG) as filename:
draw_node_graph(
filename=filename,
G=self.G,
pos_func=point_func,
# label_func=lambda x: '%.2f' % self.visibility(x),
label_func=nolabel,
color_func=color_func)