Python PlotData示例

示例#1

#!/usr/bin/env python

import rospy
from jsk_recognition_msgs.msg import DepthErrorResult, PlotData
import numpy as np
import csv

grid = 0.1  # 10 cm
bins = {}

data = PlotData()


def callback(msg):
    bin_index = int(msg.true_depth / grid)
    if not bins.has_key(bin_index):
        bins[bin_index] = []
    err = msg.true_depth - msg.observed_depth
    bins[bin_index].append((msg, err))
    for bin_index, msg_and_errs in bins.items():
        if len(msg_and_errs) < 5:
            continue
        print "Bin: {0}m ~ {1}m".format(grid * bin_index,
                                        grid * (bin_index + 1))
        print "   Sample:", len(msg_and_errs)
        errs = [err for (msg, err) in msg_and_errs]
        mean = np.mean(errs, axis=0)
        stddev = np.std(errs, axis=0)
        print "   Mean:", mean
        print "   Stddev:", stddev
    data.xs.append(msg.true_depth)

示例#2

文件： sample_3d_plot.py 项目： peizhe/sandbox-github-clone

#!/usr/bin/env python

from jsk_recognition_msgs.msg import PlotData
import numpy as np
import rospy
import math

if __name__ == "__main__":
    rospy.init_node("sample_2d_plot")
    pub = rospy.Publisher("~output", PlotData)
    r = rospy.Rate(10)
    offset = 0
    while not rospy.is_shutdown():
        msg = PlotData()
        msg.xs = np.arange(0, 5, 0.1)
        msg.ys = [math.sin(x + offset) for x in msg.xs]
        pub.publish(msg)
        offset = offset + 0.1
        r.sleep()

示例#3

文件： sample_2d_plot_2.py 项目： reinforcementdriving/jsk_visualization_packages

#!/usr/bin/env python

from jsk_recognition_msgs.msg import PlotData
import numpy as np
import rospy
from numpy.random import *
import math

if __name__ == "__main__":
    rospy.init_node("sample_2d_plot")
    pub = rospy.Publisher("~output", PlotData)
    r = rospy.Rate(10)
    offset = 0
    while not rospy.is_shutdown():
        msg = PlotData()
        msg.xs = randn(50)
        msg.ys = randn(50)

        pub.publish(msg)
        offset = offset + 0.1
        r.sleep()

示例#4

#!/usr/bin/env python

from jsk_recognition_msgs.msg import PlotData
import numpy as np
import rospy
import math
from random import random

if __name__ == "__main__":
    rospy.init_node("sample_2d_plot")
    pub = rospy.Publisher("~output", PlotData)
    r = rospy.Rate(10)
    offset = 0
    while not rospy.is_shutdown():
        msg = PlotData()
        msg.xs = np.arange(0, 5, 0.1)
        msg.ys = [math.sin(x + offset) for x in msg.xs]
        msg.label = "sample data"
        if random() < 0.5:
            msg.type = PlotData.LINE
        else:
            msg.type = PlotData.SCATTER
        msg.fit_line = random() < 0.5
        msg.fit_line_ransac = random() < 0.5
        pub.publish(msg)
        offset = offset + 0.1
        r.sleep()