Switched to PyRoboViz for visualization

README.md

@@ -83,8 +83,8 @@ map and robot trajctory for the Lidar scan and odometry data in the log file
 you can also try the <b><tt>log2png.py</tt></b> script to generate a
 a PNG file instead.
 
-If you have installed Matplotlib, you can see a &ldquo;live&rdquo; animation
+If you have installed [PyRoboViz]()https://github.com/simondlevy/PyRoboViz),
-by doing
+you can see a &ldquo;live&rdquo; animation by doing
 
 <pre>
 make movie

examples/logmovie.py

@@ -40,7 +40,7 @@ MAP_SIZE_METERS          = 32
 
 from breezyslam.algorithms import Deterministic_SLAM, RMHC_SLAM
 from mines import MinesLaser, Rover, load_data
-from pltslamshow import SlamShow
+from roboviz import Visualizer
 
 from sys import argv, exit
 from time import sleep
@@ -112,7 +112,7 @@ def main():
            else Deterministic_SLAM(MinesLaser(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
 
     # Set up a SLAM display, named by dataset
-    display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, dataset)
+    display = Visualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, dataset)
 
     # Pose will be modified in our threaded code
     pose = [0,0,0]

examples/pltslamshow.py

@@ -1,150 +0,0 @@
-'''
-pltslamshow.py - Pyplot classes for displaying maps and robots in SLAM projects
-
-Copyright (C) 2016 Simon D. Levy, Matt Lubas, and Alfredo Rwagaju
-
-This code is free software: you can redistribute it and/or modify
-it under the terms of the GNU Lesser General Public License as 
-published by the Free Software Foundation, either version 3 of the 
-License, or (at your option) any later version.
-
-This code is distributed in the hope that it will be useful,     
-but WITHOUT ANY WARRANTY without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU Lesser General Public License 
-along with this code.  If not, see <http://www.gnu.org/licenses/>.
-'''
-
-# Robot display params
-ROBOT_HEIGHT_MM = 500
-ROBOT_WIDTH_MM  = 300
-
-# This helps with Raspberry Pi
-import matplotlib
-matplotlib.use('TkAgg')
-
-import matplotlib.pyplot as plt
-import matplotlib.cm as colormap
-from math import sin, cos, radians
-import numpy as np
-from time import sleep
-
-class SlamShow(object):
-
-    def __init__(self, map_size_pixels, map_scale_mm_per_pixel, title):
-    
-        # Store constants for update
-        self.map_size_pixels = map_size_pixels
-        self.map_scale_mm_per_pixel = map_scale_mm_per_pixel
-
-        # Create a byte array to display the map with a color overlay
-        self.bgrbytes = bytearray(map_size_pixels * map_size_pixels * 3)
-        
-        # Make a nice big (10"x10") figure
-        fig = plt.figure(figsize=(10,10))
-
-        # Store Python ID of figure to detect window close
-        self.figid = id(fig)
-
-        fig.canvas.set_window_title('SLAM')
-        plt.title(title)
-
-        self.ax = fig.gca()
-        self.ax.set_aspect("auto")
-        self.ax.set_autoscale_on(True)
-
-        # Use an "artist" to speed up map drawing
-        self.img_artist = None
-
-        # We base the axis on pixels, to support displaying the map
-        self.ax.set_xlim([0, map_size_pixels])
-        self.ax.set_ylim([0, map_size_pixels])
-
-        # Hence we must relabel the axis ticks to show millimeters
-        ticks = np.arange(0,self.map_size_pixels+100,100)
-        labels = [str(self.map_scale_mm_per_pixel * tick) for tick in ticks]
-        self.ax.xaxis.set_ticks(ticks)
-        self.ax.set_xticklabels(labels)
-        self.ax.yaxis.set_ticks(ticks)
-        self.ax.set_yticklabels(labels)
-
-        self.ax.set_xlabel('X (mm)')
-        self.ax.set_ylabel('Y (mm)')
-
-        self.ax.grid(False)
-
-        # Start vehicle at center
-        map_center_mm = map_scale_mm_per_pixel * map_size_pixels
-        self._add_vehicle(map_center_mm,map_center_mm,0)
-
-    def displayMap(self, mapbytes):
-
-        mapimg = np.reshape(np.frombuffer(mapbytes, dtype=np.uint8), (self.map_size_pixels, self.map_size_pixels))
-
-        # Pause to allow display to refresh
-        sleep(.001)
-
-        if self.img_artist is None:
-
-            self.img_artist = self.ax.imshow(mapimg, cmap=colormap.gray)
-
-        else:
-
-            self.img_artist.set_data(mapimg)
-
-    def setPose(self, x_mm, y_mm, theta_deg):
-        '''
-        Sets vehicle pose:
-        X:      left/right   (cm)
-        Y:      forward/back (cm)
-        theta:  rotation (degrees)
-        '''
-        #remove old arrow
-        self.vehicle.remove()
-        
-        #create a new arrow
-        self._add_vehicle(x_mm, y_mm, theta_deg)
-
-    def _add_vehicle(self, x_mm, y_mm, theta_deg):
-
-        #Use a very short arrow shaft to orient the head of the arrow
-        dx, dy = plt_rotate(0, 0, 0.1, theta_deg)
-
-        s = self.map_scale_mm_per_pixel
-
-        self.vehicle=self.ax.arrow(x_mm/s, y_mm/s, 
-                dx, dy, head_width=ROBOT_WIDTH_MM/s, head_length=ROBOT_HEIGHT_MM/s, fc='r', ec='r')
-
-    def refresh(self):                   
-
-        # If we have a new figure, something went wrong (closing figure failed)
-        if self.figid != id(plt.gcf()):
-            return False
-
-        # Redraw current objects without blocking
-        plt.draw()
-
-        # Refresh display, setting flag on window close or keyboard interrupt
-        try:
-            plt.pause(.01) # Arbitrary pause to force redraw
-            return True
-        except:
-            return False
-
-        return True
-    
-    # Converts millimeters to pixels
-    def mm2pix(self, mm):
-        return int(mm / float(self.map_scale_mm_per_pixel))
-                
-# Helpers -------------------------------------------------------------        
-
-def plt_rotate(x, y, r, deg):
-    rad = radians(deg)
-    c = cos(rad)
-    s = sin(rad)
-    dx = r * c
-    dy = r * s
-    return x+dx, y+dy 

examples/rpslam.py

@@ -32,7 +32,7 @@ MIN_SAMPLES   = 200
 from breezyslam.algorithms import RMHC_SLAM
 from breezyslam.sensors import RPLidarA1 as LaserModel
 from rplidar import RPLidar as Lidar
-from pltslamshow import SlamShow
+from roboviz import Visualizer
 
 if __name__ == '__main__':
 
@@ -43,7 +43,7 @@ if __name__ == '__main__':
     slam = RMHC_SLAM(LaserModel(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
 
     # Set up a SLAM display
-    display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
+    display = Visualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
 
     # Initialize an empty trajectory
     trajectory = []

examples/rpslam_scipy.py

@@ -33,7 +33,7 @@ from breezyslam.sensors import RPLidarA1 as LaserModel
 
 from rplidar import RPLidar as Lidar
 
-from pltslamshow import SlamShow
+from roboviz import Visualizer
 
 from scipy.interpolate import interp1d
 import numpy as np
@@ -47,7 +47,7 @@ if __name__ == '__main__':
     slam = RMHC_SLAM(LaserModel(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
 
     # Set up a SLAM display
-    display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
+    display = Visualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
 
     # Initialize an empty trajectory
     trajectory = []

examples/urgslam.py

@@ -28,7 +28,7 @@ from breezyslam.sensors import URG04LX as LaserModel
 
 from breezylidar import URG04LX as Lidar
 
-from pltslamshow import SlamShow
+from roboviz import Visualizer
        
 if __name__ == '__main__':
 
@@ -39,7 +39,7 @@ if __name__ == '__main__':
     slam = RMHC_SLAM(LaserModel(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
 
     # Set up a SLAM display
-    display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
+    display = Visualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
 
     # Initialize empty map
     mapbytes = bytearray(MAP_SIZE_PIXELS * MAP_SIZE_PIXELS)

examples/xvslam.py

@@ -28,7 +28,7 @@ from breezyslam.sensors import XVLidar as LaserModel
 
 from xvlidar import XVLidar as Lidar
 
-from pltslamshow import SlamShow
+from roboviz import Visualizer
 
 from sys import stdout
 
@@ -41,7 +41,7 @@ if __name__ == '__main__':
     slam = RMHC_SLAM(LaserModel(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
 
     # Set up a SLAM display
-    display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
+    display = Visualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, 'SLAM')
 
     # Initialize an empty trajectory
     trajectory = []