本文整理汇总了Python中hpp.corbaserver.ProblemSolver.clearPathOptimizers方法的典型用法代码示例。如果您正苦于以下问题：Python ProblemSolver.clearPathOptimizers方法的具体用法？Python ProblemSolver.clearPathOptimizers怎么用？Python ProblemSolver.clearPathOptimizers使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类hpp.corbaserver.ProblemSolver的用法示例。
在下文中一共展示了ProblemSolver.clearPathOptimizers方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1:
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import clearPathOptimizers [as 别名]
robot.isConfigValid(q2)
# qf should be invalid
qf = [1, -3, 3, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2, 1.0, -0.4, -1.0, 0.0, -0.2, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -1.5, -0.2, 0.1, -0.3, 0.1, 0.1, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -0.2, 0.6, -0.453786, 0.872665, -0.418879, 0.2, -0.4, 0.0, -0.453786, 0.1, 0.7, 0.0]
robot.isConfigValid(qf)
ps.setInitialConfig (q1); ps.addGoalConfig (q2); ps.solve ()
ps.solve ()
ps.pathLength(0)
ps.addPathOptimizer('RandomShortcut')
ps.optimizePath (0)
ps.pathLength(1)
ps.clearPathOptimizers()
ps.addPathOptimizer("GradientBased")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
pp(ps.numberPaths()-1)
r(ps.configAtParam(0,2))
ps.getWaypoints (0)
# Add light to scene
lightName = "li4"
r.client.gui.addLight (lightName, r.windowId, 0.01, [0.4,0.4,0.4,0.5])示例2: len
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import clearPathOptimizers [as 别名]
ps.pathLength(0)
len(ps.getWaypoints (0))
r(q1)
import numpy as np
"""
ps.addPathOptimizer("Prune")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
len(ps.getWaypoints (ps.numberPaths()-1))
"""
ps.clearPathOptimizers()
cl.problem.setAlphaInit (0.05)
ps.addPathOptimizer("GradientBased")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
tGB = cl.problem.getTimeGB ()
timeValuesGB = cl.problem.getTimeValues ()
gainValuesGB = cl.problem.getGainValues ()
newGainValuesGB = ((1-np.array(gainValuesGB))*100).tolist() #percentage of initial length-value
ps.clearPathOptimizers()
ps.addPathOptimizer('RandomShortcut')
ps.optimizePath (0)
ps.pathLength(ps.numberPaths()-1)