How to use results_dir_basename method in avocado

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1#!/usr/bin/env python2# Copyright (c) 2012 The Chromium Authors. All rights reserved.3# Use of this source code is governed by a BSD-style license that can be4# found in the LICENSE file.5"""A tool to archive layout test results.6To archive files on Google Storage, pass a GS bucket name via --gs-bucket.7To control access to archives, pass a value for --gs-acl (e.g. 'public-read',8see other supported canned-acl values). If no gs_acl key is given,10then the bucket's default object ACL will be applied (see11 this is run, the current directory (cwd) should be the outer build13directory (e.g., chrome-release/build/).14For a list of command-line options, call this script with '--help'.15"""16import logging17import argparse18import os19import re20import socket21import sys22from common import archive_utils23from common import chromium_utils24from slave import build_directory25from slave import slave_utils26def _CollectZipArchiveFiles(output_dir):27 """Returns a list of layout test result files to archive in a zip file."""28 file_list = []29 for path, _, files in os.walk(output_dir):30 rel_path = path[len(output_dir + '\\'):]31 for name in files:32 if _IsIncludedInZipArchive(name):33 file_list.append(os.path.join(rel_path, name))34 if os.path.exists(os.path.join(output_dir, 'results.html')):35 file_list.append('results.html')36 if sys.platform == 'win32':37 if os.path.exists(os.path.join(output_dir, 'access_log.txt')):38 file_list.append('access_log.txt')39 if os.path.exists(os.path.join(output_dir, 'error_log.txt')):40 file_list.append('error_log.txt')41 return file_list42def _IsIncludedInZipArchive(name):43 """Returns True if a file should be included in the zip, False otherwise."""44 if '-stack.' in name or '-crash-log.' in name:45 return True46 extension = os.path.splitext(name)[1]47 if '-actual.' in name and extension in ('.txt', '.png', '.checksum', '.wav'):48 return True49 if '-expected.' in name:50 return True51 if '-wdiff.' in name:52 return True53 if name.endswith('-diff.txt') or name.endswith('-diff.png'):54 return True55 if name.endswith('.json'):56 return True57 return False58def archive_layout(args):59 chrome_dir = os.path.abspath(args.build_dir)60 results_dir_basename = os.path.basename(args.results_dir)61 args.results_dir = os.path.abspath(args.results_dir)62 print 'Archiving results from %s' % args.results_dir63 staging_dir = args.staging_dir or slave_utils.GetStagingDir(chrome_dir)64 print 'Staging in %s' % staging_dir65 if not os.path.exists(staging_dir):66 os.makedirs(staging_dir)67 file_list = _CollectZipArchiveFiles(args.results_dir)68 zip_file = chromium_utils.MakeZip(staging_dir,69 results_dir_basename,70 file_list,71 args.results_dir)[1]72 wc_dir = os.path.dirname(chrome_dir)73 last_change = slave_utils.GetHashOrRevision(wc_dir)74 builder_name = re.sub('[ .()]', '_', args.builder_name)75 build_number = str(args.build_number)76 print 'last change: %s' % last_change77 print 'build name: %s' % builder_name78 print 'build number: %s' % build_number79 print 'host name: %s' % socket.gethostname()80 # Create a file containing last_change revision. This file will be uploaded81 # after all layout test results are uploaded so the client can check this82 # file to see if the upload for the revision is complete.83 # See for more details.84 last_change_file = os.path.join(staging_dir, 'LAST_CHANGE')85 with open(last_change_file, 'w') as f:86 f.write(last_change)87 # Copy the results to a directory archived by build number.88 gs_base = '/'.join([args.gs_bucket, builder_name, build_number])89 gs_acl = args.gs_acl90 # These files never change, cache for a year.91 cache_control = "public, max-age=31556926"92 slave_utils.GSUtilCopyFile(zip_file, gs_base, gs_acl=gs_acl,93 cache_control=cache_control,94 add_quiet_flag=True)95 slave_utils.GSUtilCopyDir(args.results_dir, gs_base, gs_acl=gs_acl,96 cache_control=cache_control,97 add_quiet_flag=True)98 slave_utils.GSUtilCopyFile(last_change_file,99 gs_base + '/' + results_dir_basename,100 gs_acl=gs_acl,101 cache_control=cache_control,102 add_quiet_flag=True)103 # And also to the 'results' directory to provide the 'latest' results104 # and make sure they are not cached at all (Cloud Storage defaults to105 # caching w/ a max-age=3600).106 gs_base = '/'.join([args.gs_bucket, builder_name, 'results'])107 cache_control = 'no-cache'108 slave_utils.GSUtilCopyFile(zip_file, gs_base, gs_acl=gs_acl,109 cache_control=cache_control,110 add_quiet_flag=True)111 slave_utils.GSUtilCopyDir(args.results_dir, gs_base, gs_acl=gs_acl,112 cache_control=cache_control,113 add_quiet_flag=True)114 slave_utils.GSUtilCopyFile(last_change_file,115 gs_base + '/' + results_dir_basename,116 gs_acl=gs_acl,117 cache_control=cache_control,118 add_quiet_flag=True)119 return 0120def _ParseArgs():121 parser = argparse.ArgumentParser()122 # TODO( Make --build-dir not ignored.123 parser.add_argument('--build-dir', help='ignored')124 parser.add_argument('--results-dir', required=True,125 help='path to layout test results')126 parser.add_argument('--builder-name', required=True,127 help='The name of the builder running this script.')128 parser.add_argument('--build-number', type=int, required=True,129 help='Build number of the builder running this script.')130 parser.add_argument('--gs-bucket', required=True,131 help='The Google Storage bucket to upload to.')132 parser.add_argument('--gs-acl',133 help='The access policy for Google Storage files.')134 parser.add_argument('--staging-dir',135 help='Directory to use for staging the archives. '136 'Default behavior is to automatically detect '137 'slave\'s build directory.')138 slave_utils_callback = slave_utils.AddArgs(parser)139 args = parser.parse_args()140 args.build_dir = build_directory.GetBuildOutputDirectory()141 slave_utils_callback(args)142 return args143def main():144 args = _ParseArgs()145 logging.basicConfig(level=logging.INFO,146 format='%(asctime)s %(filename)s:%(lineno)-3d'147 ' %(levelname)s %(message)s',148 datefmt='%y%m%d %H:%M:%S')149 return archive_layout(args)150if '__main__' == __name__:...

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1# load URDFs and get the canonical height for eachaabb = p.getAABB(obj_id)2# load directory3# for each episode, if the stable height is higher than the canonical height, we will treat it as a success4# otherwise, it will be a failure5# this corresponds with royal-brook-1975_checkpoint506import sys7import pybullet as p8import glob9from pathlib import Path10from utils import bandu_util11import os12from utils.pb_util import get_object_height13from bandu.config import TABLE_HEIGHT14import numpy as np15def stddev(binary_list_of_success_failures):16 import pdb17 pdb.set_trace()18 binary_list_of_success_failures = np.array(binary_list_of_success_failures)19 # calculate the mean20 mean = np.sum(binary_list_of_success_failures) / len(binary_list_of_success_failures)21 var = np.sum((binary_list_of_success_failures - mean)**2)/(len(binary_list_of_success_failures) - 1)22 return np.sqrt(var)23urdf_dir = sys.argv[1]24results_dir = sys.argv[2]25results_dir_basename = os.path.basename(os.path.normpath(results_dir))26max_trials = int(sys.argv[3]) # maximum number of trials before trials get ignored27# urdf_dir = "/home/richard/data/engmikedset/urdfs"28urdfs = [f for f in glob.glob(str(Path(urdf_dir) / "**/*.urdf"), recursive=True)]29urdfs += [f for f in glob.glob(str(Path(urdf_dir) / "**/*.URDF"), recursive=True)]30# mapping name to height31height_dict = dict()32best_theta_list_dict = dict()33results_save_dir = "../out/bandu_results"34p.connect(p.DIRECT)35for urdf_path in urdfs:36 print("ln34 urdf_path")37 print(urdf_path)38 obj_id = p.loadURDF(urdf_path, globalScaling=1.5)39 # aabb = p.getAABB(obj_id)40 #41 # aabbMinVec = aabb[0]42 # aabbMaxVec = aabb[1]43 #44 # obj_height = aabbMaxVec[-1] - aabbMinVec[-1]45 obj_height = get_object_height(obj_id)46 object_name = bandu_util.parse_urdf_xml_for_object_name(os.path.dirname(urdf_path) + "/model.config")47 height_dict[object_name] = obj_height48import json49with open(str(Path(results_save_dir) / "height_dict.json"), "w") as fp:50 json.dump(height_dict, fp, indent=4)51# results_dir = "/home/richard/data/results/engmikedset_dgcnn_mog5_unitvar"52height_success_dict = dict()53num_stacked_success_dict = dict()54json_paths = [f for f in glob.glob(str(Path(results_dir) / "**/*.json"), recursive=True)]55step_1_json_paths = [f for f in json_paths if "_1_" in f]56height_object_successes_dict = dict()57total_trials_dict = dict()58num_stacked_successes_dict = dict()59for k in height_dict.keys():60 height_object_successes_dict[k] = 061 total_trials_dict[k] = 062 best_theta_list_dict[k] = []63 num_stacked_successes_dict[k] = 064import torch65for path in sorted(step_1_json_paths):66 # extract object names67 objects_folder_name = os.path.basename(os.path.dirname(path))68 non_foundation_obj_name = objects_folder_name.split("foundation_")[1]69 obj_height = height_dict[non_foundation_obj_name]70 with open(path, "r") as fp:71 dic = json.load(fp)72 urdf_path = Path(urdf_dir) / non_foundation_obj_name73 if "best_theta" not in dic.keys():74 best_theta_list_dict[non_foundation_obj_name].append(99)75 else:76 if np.isnan(dic['best_theta']):77 continue78 best_theta_list_dict[non_foundation_obj_name].append(dic['best_theta'])79 # pkl = torch.load(Path(os.path.dirname(path)) / f"ep0_2_o3d.pkl")80 #81 # assert pkl['batch']['pybullet_object_ids'][0] == 282 #83 # # multiply relrot to get the target pose84 # # apply target pose to the normal vectors85 # pkl['batch']['current_quats']86 recorded_tower_height = dic['tower_height'] - TABLE_HEIGHT87 gt_tower_height = obj_height + height_dict['foundation']88 if total_trials_dict[non_foundation_obj_name] < max_trials:89 if recorded_tower_height > gt_tower_height * .98:90 height_object_successes_dict[non_foundation_obj_name] += 191 assert dic['num_stacked'] <= 2, dic['num_stacked']92 if dic['num_stacked'] == 2:93 num_stacked_successes_dict[non_foundation_obj_name] += 194 total_trials_dict[non_foundation_obj_name] += 195best_theta_means_dict = dict()96best_theta_stddevs_dict = dict()97for obj_name in total_trials_dict.keys():98 # each obj name should have exactly max trials99 assert total_trials_dict[obj_name] == max_trials, total_trials_dict[obj_name]100for obj_name in height_dict.keys():101 height_success_dict[obj_name] = height_object_successes_dict[obj_name] / total_trials_dict[obj_name]102 num_stacked_success_dict[obj_name] = num_stacked_successes_dict[obj_name] / total_trials_dict[obj_name]103 best_theta_means_dict[obj_name] = np.mean(best_theta_list_dict[obj_name])104 best_theta_stddevs_dict[obj_name] = np.std(best_theta_list_dict[obj_name])105 assert num_stacked_successes_dict[obj_name] >= height_success_dict[obj_name]106# for object_name in height_dict.keys():107# obj_dir = Path(results_dir) / object_name108#109# json_paths = [f for f in glob.glob(str(Path(obj_dir) / "**/*.json"), recursive=True)]110#111# object_successes = 0112# object_total = 0113#114# for pth in json_paths:115# with open(pth, "r") as fp:116# dic = json.load(fp)117#118# logged_obj_height = float(dic['tower_height']) - TABLE_HEIGHT119#120# if logged_obj_height > height_dict[object_name] * .98:121# object_successes += 1122# object_total += 1123#124# height_success_dict[object_name] = object_successes/object_total125import pprint126rdb = Path(results_save_dir) / results_dir_basename127rdb.mkdir(exist_ok=True, parents=True)128with open(str(Path(results_save_dir) / results_dir_basename / f"maxtrials{max_trials}_height_success_means_dict.json"), "w") as fp:129 json.dump(height_success_dict, fp, indent=4)130with open(str(Path(results_save_dir) / results_dir_basename / f"maxtrials{max_trials}_num_stacked_success_dict.json"), "w") as fp:131 json.dump(num_stacked_success_dict, fp, indent=4)132with open(str(Path(results_save_dir) / results_dir_basename / f"maxtrials{max_trials}_best_theta_means_dict.json"), "w") as fp:133 json.dump(best_theta_means_dict, fp, indent=4)134with open(str(Path(results_save_dir) / results_dir_basename / f"maxtrials{max_trials}_best_theta_stddevs_dict.json"), "w") as fp:135 json.dump(best_theta_stddevs_dict, fp, indent=4)136print("Height success dict")137pprint.pprint(height_success_dict)138print("Best theta means dict")139pprint.pprint(best_theta_means_dict)140print("Best theta stddevs dict")141pprint.pprint(best_theta_stddevs_dict)142# pprint.pprint(num_stacked_success_dict)143# print("num trials total")144# # pprint.pprint(len(step_1_json_paths))...

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