import time
import warnings
from collections import deque
from enum import IntEnum
import numpy as np
from numpy import array
from recordtype import recordtype
from flatland.utils.graphics_pgl import PGLGL
from flatland.utils.graphics_pil import PILGL, PILSVG
# TODO: suggested renaming to RailEnvRenderTool, as it will only work with RailEnv!
[docs]
class AgentRenderVariant(IntEnum):
BOX_ONLY = 0
ONE_STEP_BEHIND = 1
AGENT_SHOWS_OPTIONS = 2
ONE_STEP_BEHIND_AND_BOX = 3
AGENT_SHOWS_OPTIONS_AND_BOX = 4
[docs]
class RenderBase(object):
def __init__(self, env):
pass
[docs]
def render_env(self):
pass
[docs]
def close_window(self):
pass
[docs]
def set_new_rail(self):
""" Signal to the renderer that the env has changed and will need re-rendering.
"""
pass
[docs]
def update_background(self):
""" A lesser version of set_new_rail?
TODO: can update_background be pruned for simplicity?
"""
pass
[docs]
class RenderLocal(RenderBase):
""" Class to render the RailEnv and agents.
Uses two layers, layer 0 for rails (mostly static), layer 1 for agents etc (dynamic)
The lower / rail layer 0 is only redrawn after set_new_rail() has been called.
Created with a "GraphicsLayer" or gl - now either PIL or PILSVG
"""
visit = recordtype("visit", ["rc", "iDir", "iDepth", "prev"])
color_list = list("brgcmyk")
# \delta RC for NESW
transitions_row_col = np.array([[-1, 0], [0, 1], [1, 0], [0, -1]])
pix_per_cell = 1 # misnomer...
half_pix_per_cell = pix_per_cell / 2
x_y_half = array([half_pix_per_cell, -half_pix_per_cell])
row_col_to_xy = array([[0, -pix_per_cell], [pix_per_cell, 0]])
grid = array(np.meshgrid(np.arange(10), -np.arange(10))) * array([[[pix_per_cell]], [[pix_per_cell]]])
theta = np.linspace(0, np.pi / 2, 5)
arc = array([np.cos(theta), np.sin(theta)]).T # from [1,0] to [0,1]
def __init__(self, env, gl="PILSVG", jupyter=False,
agent_render_variant=AgentRenderVariant.ONE_STEP_BEHIND,
show_debug=False, clear_debug_text=True, screen_width=800, screen_height=600):
self.env = env
self.frame_nr = 0
self.start_time = time.time()
self.times_list = deque()
self.agent_render_variant = agent_render_variant
self.gl_str = gl
if gl == "PIL":
self.gl = PILGL(env.width, env.height, jupyter, screen_width=screen_width, screen_height=screen_height)
elif gl == "PILSVG":
self.gl = PILSVG(env.width, env.height, jupyter, screen_width=screen_width, screen_height=screen_height)
else:
if gl != "PGL":
print("[", gl, "] not found, switch to PGL, PILSVG")
print("Using PGL")
self.gl = PGLGL(env.width, env.height, jupyter, screen_width=screen_width, screen_height=screen_height)
self.new_rail = True
self.show_debug = show_debug
self.clear_debug_text = clear_debug_text
self.update_background()
[docs]
def reset(self):
"""
Resets the environment
:return:
"""
self.set_new_rail()
self.frame_nr = 0
self.start_time = time.time()
self.times_list = deque()
return
[docs]
def update_background(self):
# create background map
targets = {}
for agent_idx, agent in enumerate(self.env.agents):
if agent is None:
continue
#print(f"updatebg: {agent_idx} {agent.target}")
targets[tuple(agent.target)] = agent_idx
self.gl.build_background_map(targets)
[docs]
def resize(self):
self.gl.resize(self.env)
[docs]
def set_new_rail(self):
""" Tell the renderer that the rail has changed.
eg when the rail has been regenerated, or updated in the editor.
"""
self.new_rail = True
[docs]
def plot_agents(self, targets=True, selected_agent=None):
color_map = self.gl.get_cmap('hsv', lut=(len(self.env.agents) + 1))
for agent_idx, agent in enumerate(self.env.agents):
if agent is None:
continue
color = color_map(agent_idx)
self.plot_single_agent(agent.position, agent.direction, color, target=agent.target if targets else None,
static=True, selected=agent_idx == selected_agent)
for agent_idx, agent in enumerate(self.env.agents):
if agent is None:
continue
color = color_map(agent_idx)
self.plot_single_agent(agent.position, agent.direction, color, target=agent.target if targets else None)
[docs]
def get_transition_row_col(self, row_col_pos, direction, bgiTrans=False):
"""
Get the available transitions for row_col_pos in direction direction,
as row & col deltas.
If bgiTrans is True, return a grid of indices of available transitions.
eg for a cell row_col_pos = (4,5), in direction direction = 0 (N),
where the available transitions are N and E, returns:
[[-1,0], [0,1]] ie N=up one row, and E=right one col.
and if bgiTrans is True, returns a tuple:
(
[[-1,0], [0,1]], # deltas as before
[0, 1] # available transition indices, ie N, E
)
"""
transitions = self.env.rail.get_transitions((row_col_pos, direction))
transition_list = np.where(transitions)[0] # RC list of transitions
# HACK: workaround dead-end transitions
if len(transition_list) == 0:
reverse_direciton = (direction + 2) % 4
transitions = tuple(int(tmp_dir == reverse_direciton) for tmp_dir in range(4))
transition_list = np.where(transitions)[0] # RC list of transitions
transition_grid = self.__class__.transitions_row_col[transition_list]
if bgiTrans:
return transition_grid, transition_list
else:
return transition_grid
[docs]
def plot_single_agent(self, position_row_col, direction, color="r", target=None, static=False, selected=False):
"""
Plot a simple agent.
Assumes a working graphics layer context (cf a MPL figure).
"""
if position_row_col is None:
return
rt = self.__class__
direction_row_col = rt.transitions_row_col[direction] # agent direction in RC
direction_xy = np.matmul(direction_row_col, rt.row_col_to_xy) # agent direction in xy
xyPos = np.matmul(position_row_col - direction_row_col / 2, rt.row_col_to_xy) + rt.x_y_half
if static:
color = self.gl.adapt_color(color, lighten=True)
color = color
self.gl.scatter(*xyPos, color=color, layer=1, marker="o", s=100) # agent location
xy_dir_line = array([xyPos, xyPos + direction_xy / 2]).T # line for agent orient.
self.gl.plot(*xy_dir_line, color=color, layer=1, lw=5, ms=0, alpha=0.6)
if selected:
self._draw_square(xyPos, 1, color)
if target is not None:
target_row_col = array(target)
target_xy = np.matmul(target_row_col, rt.row_col_to_xy) + rt.x_y_half
self._draw_square(target_xy, 1 / 3, color, layer=1)
[docs]
def plot_transition(self, position_row_col, transition_row_col, color="r", depth=None):
"""
plot the transitions in transition_row_col at position position_row_col.
transition_row_col is a 2d numpy array containing a list of RC transitions,
eg [[-1,0], [0,1]] means N, E.
"""
rt = self.__class__
position_xy = np.matmul(position_row_col, rt.row_col_to_xy) + rt.x_y_half
transition_xy = position_xy + np.matmul(transition_row_col, rt.row_col_to_xy / 2.4)
self.gl.scatter(*transition_xy.T, color=color, marker="o", s=50, alpha=0.2)
if depth is not None:
for x, y in transition_xy:
self.gl.text(x, y, depth)
[docs]
def draw_transition(self,
line,
center,
rotation,
dead_end=False,
curves=False,
color="gray",
arrow=True,
spacing=0.1):
"""
gLine is a numpy 2d array of points,
in the plotting space / coords.
eg:
[[0,.5],[1,0.2]] means a line
from x=0, y=0.5
to x=1, y=0.2
"""
if not curves and not dead_end:
# just a straigt line, no curve nor dead_end included in this basic rail element
self.gl.plot(
[line[0][0], line[1][0]], # x
[line[0][1], line[1][1]], # y
color=color
)
else:
# it was not a simple line to draw: the rail has a curve or dead_end included.
rt = self.__class__
straight = rotation in [0, 2]
dx, dy = np.squeeze(np.diff(line, axis=0)) * spacing / 2
if straight:
if color == "auto":
if dx > 0 or dy > 0:
color = "C1" # N or E
else:
color = "C2" # S or W
if dead_end:
line_xy = array([
line[1] + [dy, dx],
center,
line[1] - [dy, dx],
])
self.gl.plot(*line_xy.T, color=color)
else:
line_xy = line + [-dy, dx]
self.gl.plot(*line_xy.T, color=color)
if arrow:
middle_xy = np.sum(line_xy * [[1 / 4], [3 / 4]], axis=0)
arrow_xy = array([
middle_xy + [-dx - dy, +dx - dy],
middle_xy,
middle_xy + [-dx + dy, -dx - dy]])
self.gl.plot(*arrow_xy.T, color=color)
else:
middle_xy = np.mean(line, axis=0)
dxy = middle_xy - center
corner = middle_xy + dxy
if rotation == 1:
arc_factor = 1 - spacing
color_auto = "C1"
else:
arc_factor = 1 + spacing
color_auto = "C2"
dxy2 = (center - corner) * arc_factor # for scaling the arc
if color == "auto":
color = color_auto
self.gl.plot(*(rt.arc * dxy2 + corner).T, color=color)
if arrow:
dx, dy = np.squeeze(np.diff(line, axis=0)) / 20
iArc = int(len(rt.arc) / 2)
middle_xy = corner + rt.arc[iArc] * dxy2
arrow_xy = array([
middle_xy + [-dx - dy, +dx - dy],
middle_xy,
middle_xy + [-dx + dy, -dx - dy]])
self.gl.plot(*arrow_xy.T, color=color)
[docs]
def render_observation(self, agent_handles, observation_dict):
"""
Render the extent of the observation of each agent. All cells that appear in the agent
observation will be highlighted.
:param agent_handles: List of agent indices to adapt color and get correct observation
:param observation_dict: dictionary containing sets of cells of the agent observation
"""
rt = self.__class__
# Check if the observation builder provides an observation
if len(observation_dict) < 1:
warnings.warn(
"Predictor did not provide any predicted cells to render. \
Observation builder needs to populate: env.dev_obs_dict")
else:
for agent in agent_handles:
color = self.gl.get_agent_color(agent)
for visited_cell in observation_dict[agent]:
cell_coord = array(visited_cell[:2])
cell_coord_trans = np.matmul(cell_coord, rt.row_col_to_xy) + rt.x_y_half
self._draw_square(cell_coord_trans, 1 / (agent + 1.1), color, layer=1, opacity=100)
[docs]
def render_prediction(self, agent_handles, prediction_dict):
"""
Render the extent of the observation of each agent. All cells that appear in the agent
observation will be highlighted.
:param agent_handles: List of agent indices to adapt color and get correct observation
:param observation_dict: dictionary containing sets of cells of the agent observation
"""
rt = self.__class__
if len(prediction_dict) < 1:
warnings.warn(
"Predictor did not provide any predicted cells to render. \
Predictors builder needs to populate: env.dev_pred_dict")
else:
for agent in agent_handles:
color = self.gl.get_agent_color(agent)
for visited_cell in prediction_dict[agent]:
cell_coord = array(visited_cell[:2])
if type(self.gl) is PILSVG:
# TODO : Track highlighting (Adrian)
r = cell_coord[0]
c = cell_coord[1]
transitions = self.env.rail.grid[r, c]
self.gl.set_predicion_path_at(r, c, transitions, agent_rail_color=color)
else:
cell_coord_trans = np.matmul(cell_coord, rt.row_col_to_xy) + rt.x_y_half
self._draw_square(cell_coord_trans, 1 / (agent + 1.1), color, layer=1, opacity=100)
[docs]
def render_rail(self, spacing=False, rail_color="gray", curves=True, arrows=False):
cell_size = 1 # TODO: remove cell_size
env = self.env
# Draw cells grid
grid_color = [0.95, 0.95, 0.95]
for row in range(env.height + 1):
self.gl.plot([0, (env.width + 1) * cell_size],
[-row * cell_size, -row * cell_size],
color=grid_color, linewidth=2)
for col in range(env.width + 1):
self.gl.plot([col * cell_size, col * cell_size],
[0, -(env.height + 1) * cell_size],
color=grid_color, linewidth=2)
# Draw each cell independently
for row in range(env.height):
for col in range(env.width):
# bounding box of the grid cell
x0 = cell_size * col # left
x1 = cell_size * (col + 1) # right
y0 = cell_size * -row # top
y1 = cell_size * -(row + 1) # bottom
# centres of cell edges
coords = [
((x0 + x1) / 2.0, y0), # N middle top
(x1, (y0 + y1) / 2.0), # E middle right
((x0 + x1) / 2.0, y1), # S middle bottom
(x0, (y0 + y1) / 2.0) # W middle left
]
# cell centre
center_xy = array([x0, y1]) + cell_size / 2
# cell transition values
cell = env.rail.get_full_transitions(row, col)
cell_valid = env.rail.cell_neighbours_valid((row, col), check_this_cell=True)
# Special Case 7, with a single bit; terminate at center
nbits = 0
tmp = cell
while tmp > 0:
nbits += (tmp & 1)
tmp = tmp >> 1
# as above - move the from coord to the centre
# it's a dead env.
is_dead_end = nbits == 1
if not cell_valid:
self.gl.scatter(*center_xy, color="r", s=30)
for orientation in range(4): # ori is where we're heading
from_ori = (orientation + 2) % 4 # 0123=NESW -> 2301=SWNE
from_xy = coords[from_ori]
moves = env.rail.get_transitions(((row, col), orientation))
for to_ori in range(4):
to_xy = coords[to_ori]
rotation = (to_ori - from_ori) % 4
if (moves[to_ori]): # if we have this transition
self.draw_transition(
array([from_xy, to_xy]), center_xy,
rotation, dead_end=is_dead_end, curves=curves and not is_dead_end, spacing=spacing,
color=rail_color)
[docs]
def render_env(self,
show=False, # whether to call matplotlib show() or equivalent after completion
show_agents=True, # whether to include agents
show_inactive_agents=False,
show_observations=True, # whether to include observations
show_predictions=False, # whether to include predictions
show_rowcols=False, # label the rows and columns
frames=False, # frame counter to show (intended since invocation)
episode=None, # int episode number to show
step=None, # int step number to show in image
selected_agent=None, # indicate which agent is "selected" in the editor
return_image=False): # indicate if image is returned for use in monitor:
""" Draw the environment using the GraphicsLayer this RenderTool was created with.
(Use show=False from a Jupyter notebook with %matplotlib inline)
"""
# if type(self.gl) is PILSVG:
if self.gl_str in ["PILSVG", "PGL"]:
return self.render_env_svg(show=show,
show_observations=show_observations,
show_predictions=show_predictions,
selected_agent=selected_agent,
show_agents=show_agents,
show_inactive_agents=show_inactive_agents,
show_rowcols=show_rowcols,
return_image=return_image
)
else:
return self.render_env_pil(show=show,
show_agents=show_agents,
show_inactive_agents=show_inactive_agents,
show_observations=show_observations,
show_predictions=show_predictions,
show_rowcols=show_rowcols,
frames=frames,
episode=episode,
step=step,
selected_agent=selected_agent,
return_image=return_image
)
def _draw_square(self, center, size, color, opacity=255, layer=0):
x0 = center[0] - size / 2
x1 = center[0] + size / 2
y0 = center[1] - size / 2
y1 = center[1] + size / 2
self.gl.plot([x0, x1, x1, x0, x0], [y0, y0, y1, y1, y0], color=color, layer=layer, opacity=opacity)
[docs]
def get_image(self):
return self.gl.get_image()
[docs]
def render_env_pil(self,
show=False, # whether to call matplotlib show() or equivalent after completion
# use false when calling from Jupyter. (and matplotlib no longer supported!)
show_agents=True, # whether to include agents
show_inactive_agents=False,
show_observations=True, # whether to include observations
show_predictions=False, # whether to include predictions
show_rowcols=False, # label the rows and columns
frames=False, # frame counter to show (intended since invocation)
episode=None, # int episode number to show
step=None, # int step number to show in image
selected_agent=None, # indicate which agent is "selected" in the editor
return_image=False # indicate if image is returned for use in monitor:
):
if type(self.gl) is PILGL:
self.gl.begin_frame()
env = self.env
self.render_rail()
# Draw each agent + its orientation + its target
if show_agents:
self.plot_agents(targets=True, selected_agent=selected_agent)
if show_observations:
self.render_observation(range(env.get_num_agents()), env.dev_obs_dict)
if show_predictions and len(env.dev_pred_dict) > 0:
self.render_prediction(range(env.get_num_agents()), env.dev_pred_dict)
# Draw some textual information like fps
text_y = [-0.3, -0.6, -0.9]
if frames:
self.gl.text(0.1, text_y[2], "Frame:{:}".format(self.frame_nr))
self.frame_nr += 1
if episode is not None:
self.gl.text(0.1, text_y[1], "Ep:{}".format(episode))
if step is not None:
self.gl.text(0.1, text_y[0], "Step:{}".format(step))
time_now = time.time()
self.gl.text(2, text_y[2], "elapsed:{:.2f}s".format(time_now - self.start_time))
self.times_list.append(time_now)
if len(self.times_list) > 20:
self.times_list.popleft()
if len(self.times_list) > 1:
rFps = (len(self.times_list) - 1) / (self.times_list[-1] - self.times_list[0])
self.gl.text(2, text_y[1], "fps:{:.2f}".format(rFps))
self.gl.prettify2(env.width, env.height, self.pix_per_cell)
# TODO: for MPL, we don't want to call clf (called by endframe)
# if not show:
if show and type(self.gl) is PILGL:
self.gl.show()
self.gl.pause(0.00001)
if return_image:
return self.get_image()
return
[docs]
def render_env_svg(
self, show=False, show_observations=True, show_predictions=False, selected_agent=None,
show_agents=True, show_inactive_agents=False, show_rowcols=False, return_image=False
):
"""
Renders the environment with SVG support (nice image)
"""
env = self.env
self.gl.begin_frame()
if self.new_rail:
self.new_rail = False
self.gl.clear_rails()
# store the targets
targets = {}
selected = {}
for agent_idx, agent in enumerate(self.env.agents):
if agent is None:
continue
targets[tuple(agent.target)] = agent_idx
selected[tuple(agent.target)] = (agent_idx == selected_agent)
# Draw each cell independently
for r in range(env.height):
for c in range(env.width):
transitions = env.rail.grid[r, c]
if (r, c) in targets:
target = targets[(r, c)]
is_selected = selected[(r, c)]
else:
target = None
is_selected = False
self.gl.set_rail_at(r, c, transitions, target=target, is_selected=is_selected,
rail_grid=env.rail.grid, num_agents=env.get_num_agents(),
show_debug=self.show_debug)
self.gl.build_background_map(targets)
if show_rowcols:
# label rows, cols
for iRow in range(env.height):
self.gl.text_rowcol((iRow, 0), str(iRow), layer=self.gl.RAIL_LAYER)
for iCol in range(env.width):
self.gl.text_rowcol((0, iCol), str(iCol), layer=self.gl.RAIL_LAYER)
if show_agents:
for agent_idx, agent in enumerate(self.env.agents):
if agent is None:
continue
# Show an agent even if it hasn't already started
if agent.position is None:
if show_inactive_agents:
# print("agent ", agent_idx, agent.position, agent.old_position, agent.initial_position)
self.gl.set_agent_at(agent_idx, *(agent.initial_position),
agent.initial_direction, agent.initial_direction,
is_selected=(selected_agent == agent_idx),
rail_grid=env.rail.grid,
show_debug=self.show_debug, clear_debug_text=self.clear_debug_text,
malfunction=False)
continue
is_malfunction = agent.malfunction_handler.malfunction_down_counter > 0
if self.agent_render_variant == AgentRenderVariant.BOX_ONLY:
self.gl.set_cell_occupied(agent_idx, *(agent.position))
elif self.agent_render_variant == AgentRenderVariant.ONE_STEP_BEHIND or \
self.agent_render_variant == AgentRenderVariant.ONE_STEP_BEHIND_AND_BOX: # noqa: E125
# Most common case - the agent has been running for >1 steps
if agent.old_position is not None:
position = agent.old_position
direction = agent.direction
old_direction = agent.old_direction
# the agent's first step - it doesn't have an old position yet
elif agent.position is not None:
position = agent.position
direction = agent.direction
old_direction = agent.direction
# When the editor has just added an agent
elif agent.initial_position is not None:
position = agent.initial_position
direction = agent.initial_direction
old_direction = agent.initial_direction
# set_agent_at uses the agent index for the color
if self.agent_render_variant == AgentRenderVariant.ONE_STEP_BEHIND_AND_BOX:
self.gl.set_cell_occupied(agent_idx, *(agent.position))
self.gl.set_agent_at(agent_idx, *position, old_direction, direction,
selected_agent == agent_idx, rail_grid=env.rail.grid,
show_debug=self.show_debug, clear_debug_text=self.clear_debug_text,
malfunction=is_malfunction)
else:
position = agent.position
direction = agent.direction
for possible_direction in range(4):
# Is a transition along movement `desired_movement_from_new_cell` to the current cell possible?
isValid = env.rail.get_transition((agent.position, agent.direction), possible_direction)
if isValid:
direction = possible_direction
# set_agent_at uses the agent index for the color
self.gl.set_agent_at(agent_idx, *position, agent.direction, direction,
selected_agent == agent_idx, rail_grid=env.rail.grid,
show_debug=self.show_debug, clear_debug_text=self.clear_debug_text,
malfunction=is_malfunction)
# set_agent_at uses the agent index for the color
if self.agent_render_variant == AgentRenderVariant.AGENT_SHOWS_OPTIONS_AND_BOX:
self.gl.set_cell_occupied(agent_idx, *(agent.position))
if show_inactive_agents:
show_this_agent = True
else:
show_this_agent = agent.state.is_on_map_state()
if show_this_agent:
self.gl.set_agent_at(agent_idx, *position, agent.direction, direction,
selected_agent == agent_idx,
rail_grid=env.rail.grid, malfunction=is_malfunction)
if show_observations:
self.render_observation(range(env.get_num_agents()), env.dev_obs_dict)
if show_predictions:
self.render_prediction(range(env.get_num_agents()), env.dev_pred_dict)
if show:
self.gl.show()
for i in range(3):
self.gl.process_events()
self.frame_nr += 1
if return_image:
return self.get_image()
return
[docs]
def close_window(self):
self.gl.close_window()
