Best Python code snippet using localstack_python
skeleton.py
Source:skeleton.py  
...133                new_bindings[opt] = obj134        new_cost = cost135        if type(result) is FunctionResult:136            new_cost += (result.value - opt_result.value)137        queue.add_skeleton(new_stream_plan, new_plan_attempts, new_bindings, plan_index, new_cost)138    if (plan_attempts[index] == 0) and isinstance(opt_result, SynthStreamResult): # TODO: only add if failure?139        raise NotImplementedError()140        #new_stream_plan = stream_plan[:index] + opt_result.decompose() + stream_plan[index+1:]141        #queue.add_skeleton(new_stream_plan, bindings, plan_index, cost)142    if not opt_result.instance.enumerated:143        plan_attempts[index] = opt_result.instance.num_calls144        queue.add_skeleton(*skeleton)145    return new_values146##################################################147# TODO: want to minimize number of new sequences as they induce overhead148def compute_sampling_cost(stream_plan, stats_fn=get_stream_stats):149    # TODO: we are in a POMDP. If not the case, then the geometric cost policy is optimal150    if stream_plan is None:151        return INF152    expected_cost = 0153    for result in reversed(stream_plan):154        p_success, overhead = stats_fn(result)155        expected_cost += geometric_cost(overhead, p_success)156    return expected_cost157    # TODO: mix between geometric likelihood and learned distribution158    # Sum tail distribution for number of future159    # Distribution on the number of future attempts until successful160    # Average the tail probability mass161def compute_effort(plan_attempts):162    attempts = sum(plan_attempts)163    return attempts, len(plan_attempts)164def compute_belief(attempts, p_obs):165    return pow(p_obs, attempts)166def compute_score(plan_attempts, p_obs=.9):167    beliefs = [compute_belief(attempts, p_obs) for attempts in plan_attempts]168    prior = 1.169    for belief in beliefs:170        prior *= belief171    return -prior172def compute_score2(plan_attempts, overhead=1, p_obs=.9):173    # TODO: model the decrease in belief upon each failure174    # TODO: what if stream terminates? Assign high cost175    expected_cost = 0176    for attempts in plan_attempts:177        p_success = compute_belief(attempts, p_obs)178        expected_cost += geometric_cost(overhead, p_success)179    return expected_cost180##################################################181SkeletonKey = namedtuple('SkeletonKey', ['attempted', 'effort'])182Skeleton = namedtuple('Skeleton', ['stream_plan', 'plan_attempts',183                                   'bindings', 'plan_index', 'cost'])184SkeletonPlan = namedtuple('SkeletonPlan', ['stream_plan', 'action_plan', 'cost'])185class SkeletonQueue(Sized):186    def __init__(self, store, evaluations):187        self.store = store188        self.evaluations = evaluations189        self.queue = []190        self.skeleton_plans = []191        # TODO: include eager streams in the queue?192        # TODO: make an "action" for returning to the search (if it is the best decision)193    def add_skeleton(self, stream_plan, plan_attempts, bindings, plan_index, cost):194        stream_plan = instantiate_plan(bindings, stream_plan)195        #score = score_stream_plan(stream_plan)196        attempted = sum(plan_attempts) != 0197        effort = compute_effort(plan_attempts)198        #effort = compute_score(plan_attempts)199        #effort = compute_score2(plan_attempts)200        key = SkeletonKey(attempted, effort)201        skeleton = Skeleton(stream_plan, plan_attempts, bindings, plan_index, cost)202        heappush(self.queue, HeapElement(key, skeleton))203    def new_skeleton(self, stream_plan, action_plan, cost):204        plan_index = len(self.skeleton_plans)205        self.skeleton_plans.append(SkeletonPlan(stream_plan, action_plan, cost))206        plan_attempts = [0]*len(stream_plan)207        self.add_skeleton(stream_plan, plan_attempts, {}, plan_index, cost)208    ####################209    def is_active(self):210        return self.queue and (not self.store.is_terminated())211    def greedily_process(self):212        # TODO: search until new disabled or new evaluation?213        while self.is_active():214            key, _ = self.queue[0]215            if key.attempted:216                break217            _, skeleton = heappop(self.queue)218            process_stream_plan(skeleton, self)219    def process_until_success(self):220        success = False221        while self.is_active() and (not success):...load_skel_test.py
Source:load_skel_test.py  
...22world.set_gravity([0.0, -10.0, 0.0])23world.set_collision_detector(world.BULLET_COLLISION_DETECTOR)24print('pydart create_world OK')25# floor_name = "./assets/ground.urdf"26# floor = world.add_skeleton(floor_name)27#28# filename = "./assets/hopper_my_box.urdf"29# robot = world.add_skeleton(filename)30# print('pydart add_skeleton OK')31# https://github.com/dartsim/dart/blob/v6.3.0/dart/constraint/ContactConstraint.cpp32for i in range(0, len(world.skeletons[0].bodynodes)):33    world.skeletons[0].bodynodes[i].set_friction_coeff(1.0)34    world.skeletons[0].bodynodes[i].set_restitution_coeff(0.2)35for i in range(0, len(world.skeletons[1].bodynodes)):36    world.skeletons[1].bodynodes[i].set_friction_coeff(1.0)37    world.skeletons[1].bodynodes[i].set_restitution_coeff(1.0)38# win = pydart.gui.pyqt5.window.PyQt5Window(world)39# win.scene.set_camera(1)  # Z-up Camera40# win.run()41for jt in range(0, len(robot.joints)):42    for dof in range(len(robot.joints[jt].dofs)):43        if robot.joints[jt].has_position_limit(dof):...__init__.py
Source:__init__.py  
1# ##### BEGIN GPL LICENSE BLOCK #####2#3#  This program is free software; you can redistribute it and/or4#  modify it under the terms of the GNU General Public License5#  as published by the Free Software Foundation; either version 26#  of the License, or (at your option) any later version.7#8#  This program is distributed in the hope that it will be useful,9#  but WITHOUT ANY WARRANTY; without even the implied warranty of10#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the11#  GNU General Public License for more details.12#13#  You should have received a copy of the GNU General Public License14#  along with this program; if not, write to the Free Software Foundation,15#  Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.16#17# ##### END GPL LICENSE BLOCK #####18bl_info = {19    "name": "Plywood Cube",20    "category": "System",21    "author": "Félix",22    "version": (2, 0, 1),23    "blender": (3, 1, 2),24    "location": "View3D > Add > Second Life Rig",25    "description": "Various Second Life tools"26}27import bpy28import importlib29from . import add_skeleton30from . import puppetry31importlib.reload(add_skeleton)32importlib.reload(puppetry)33def register():34    add_skeleton.register()35    puppetry.register()36def unregister():37    add_skeleton.unregister()38    puppetry.unregister()39if __name__ == "__main__":...Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.
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