xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

c5c81be66863e31fe8a324d12e820c393d8c2e6e

214

py

Python

scripts/external_libs/elasticsearch7/elasticsearch/helpers/__init__.py

timgates42/trex-core

efe94752fcb2d0734c83d4877afe92a3dbf8eccd

[ "Apache-2.0" ]

956

2015-06-24T15:04:55.000Z

2022-03-30T06:25:04.000Z

scripts/external_libs/elasticsearch7/elasticsearch/helpers/__init__.py

angelyouyou/trex-core

fddf78584cae285d9298ef23f9f5c8725e16911e

[ "Apache-2.0" ]

782

2015-09-20T15:19:00.000Z

2022-03-31T23:52:05.000Z

scripts/external_libs/elasticsearch7/elasticsearch/helpers/__init__.py

angelyouyou/trex-core

fddf78584cae285d9298ef23f9f5c8725e16911e

[ "Apache-2.0" ]

429

2015-06-27T19:34:21.000Z

2022-03-23T11:02:51.000Z

from .errors import BulkIndexError, ScanError from .actions import expand_action, streaming_bulk, bulk, parallel_bulk from .actions import scan, reindex from .actions import _chunk_actions, _process_bulk_chunk

23.777778

71

0.831776

28

214

6.071429

0.535714

0.194118

0.3

0

0.121495

214

8

72

26.75

0.904255

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

c5e1efba7737a78ed613753973a75d60572c52dc

44

py

Python

mlswarm/infrastructure/services/__init__.py

lucasdavid/mlswarm-infrastructure

d52c4c6c6f41a85272acf098c7a152eb66aed337

[ "MIT" ]

2

2018-06-18T09:53:50.000Z

2019-02-01T13:02:12.000Z

mlswarm/infrastructure/services/__init__.py

lucasdavid/mlswarm-infrastructure

d52c4c6c6f41a85272acf098c7a152eb66aed337

[ "MIT" ]

null

mlswarm/infrastructure/services/__init__.py

lucasdavid/mlswarm-infrastructure

d52c4c6c6f41a85272acf098c7a152eb66aed337

[ "MIT" ]

null

from .service_builder import ServiceBuilder

22

43

0.886364

5

44

7.6

1

0

0.090909

44

1

44

0.95

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

68048cada33db149f4ee9b5060025502a701d6bb

51

py

Python

Chapter05/demo/__init__.py

jvstinian/Python-Reinforcement-Learning-Projects

6c97c68351fc4af426cb5c3583d75aebfabac8aa

[ "MIT" ]

114

2018-10-20T15:32:59.000Z

2022-03-21T14:16:25.000Z

Chapter05/demo/__init__.py

jvstinian/Python-Reinforcement-Learning-Projects

6c97c68351fc4af426cb5c3583d75aebfabac8aa

[ "MIT" ]

11

2018-10-18T12:39:42.000Z

2022-02-10T03:28:19.000Z

Chapter05/demo/__init__.py

jvstinian/Python-Reinforcement-Learning-Projects

6c97c68351fc4af426cb5c3583d75aebfabac8aa

[ "MIT" ]

72

2018-10-12T13:02:32.000Z

2022-03-11T13:03:26.000Z

''' Created on Nov 10, 2016 @author: a0096049 '''

8.5

23

0.627451

7

51

4.571429

1

0

0.317073

0.196078

51

5

24

10.2

0.463415

0.823529

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

a879a99e7d9d55d665a7d43858779953988691bb

731

py

Python

resource_tracker/models/__init__.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

112

2021-04-21T08:52:55.000Z

2022-03-01T15:09:19.000Z

resource_tracker/models/__init__.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

216

2021-04-21T09:06:47.000Z

2022-03-30T14:21:28.000Z

resource_tracker/models/__init__.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

21

2021-04-20T13:53:54.000Z

2022-03-30T21:43:04.000Z

from resource_tracker.models.exceptions import ExceptionResourceTracker from resource_tracker.models.resource import Resource from resource_tracker.models.resource_attribute import ResourceAttribute from resource_tracker.models.resource_text_attribute import ResourceTextAttribute from resource_tracker.models.resource_group_attribute_definition import ResourceGroupAttributeDefinition from resource_tracker.models.resource_group_text_attribute_definition import ResourceGroupTextAttributeDefinition from resource_tracker.models.resource_group import ResourceGroup from resource_tracker.models.resource_pool_attribute_definition import ResourcePoolAttributeDefinition from resource_tracker.models.resource_pool import ResourcePool

73.1

113

0.926129

78

731

8.371795

0.24359

0.165391

0.261868

0.344564

0.43951

0.287902

0

0.049248

731

9

114

81.222222

0.939568

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

765af13f74c9ed55c7ce4c7c2f44bc321a894bf1

59

py

Python

mi/abc/__init__.py

gitter-badger/Mi.py

ef6611c93c8a5237ec9d51ff89e845b85771e070

[ "MIT" ]

13

2021-09-14T02:47:23.000Z

2022-02-27T16:48:09.000Z

mi/abc/__init__.py

gitter-badger/Mi.py

ef6611c93c8a5237ec9d51ff89e845b85771e070

[ "MIT" ]

62

2021-08-28T10:56:55.000Z

2022-03-30T06:47:28.000Z

mi/abc/__init__.py

gitter-badger/Mi.py

ef6611c93c8a5237ec9d51ff89e845b85771e070

[ "MIT" ]

3

2021-12-23T20:10:57.000Z

2022-03-30T13:19:49.000Z

from .chat import * from .ext import * from .note import *

14.75

19

0.694915

9

59

4.555556

0.555556

0.487805

0

0.20339

59

3

20

19.666667

0.87234

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7668f32defd7a9ed4e43a2e6123d7e149e477e34

18,140

py

Python

burton/database/test/sqlitetests.py

Extensis/Burton

a948f045a021f468ef34d6e8e6b8a5caaa132e27

[ "MIT" ]

2

2018-01-09T23:32:35.000Z

2018-08-10T23:48:33.000Z

burton/database/test/sqlitetests.py

Extensis/Burton

a948f045a021f468ef34d6e8e6b8a5caaa132e27

[ "MIT" ]

null

burton/database/test/sqlitetests.py

Extensis/Burton

a948f045a021f468ef34d6e8e6b8a5caaa132e27

[ "MIT" ]

5

2017-03-23T16:49:46.000Z

2022-02-18T12:06:59.000Z

import codecs import cStringIO import mock import os import sqlite3 import unittest from burton import database class SQLiteTests(unittest.TestCase): def tearDown(self): if os.path.exists('some_filename.db'): os.remove('some_filename.db') def test_write_string_mapping_for_platform(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:20:00')" ) db.connect() db.write_string_mapping_for_platform( "Mac", { "SomeString" : "Translation for some string", "OtherString" : "Translation for some other string", } ) cursor = db.dbh.cursor() self.assertEquals( cursor.execute("select * from translation_keys").fetchall(), [ (1, u"SomeString", u"2010-12-02 02:20:00"), (2, u"OtherString", u"2010-12-02 02:20:00") ], ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, u"Translation for some string"), (2, 2, 1, u"Translation for some other string") ], ) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:21:00')" ) db.write_string_mapping_for_platform( "Win", { "SomeString" : "Translation for some string", "OtherString" : "Translation for some other string", } ) self.assertEquals( cursor.execute("select * from translation_keys").fetchall(), [ (1, u"SomeString", u"2010-12-02 02:21:00"), (2, u"OtherString", u"2010-12-02 02:21:00") ], ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, u"Translation for some string"), (2, 2, 1, u"Translation for some other string"), (3, 1, 2, u"Translation for some string"), (4, 2, 2, u"Translation for some other string") ], ) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:22:00')" ) db.write_string_mapping_for_platform( "Mac", { "SomeString" : "New translation for some string", "OtherString" : "Translation for some other string", } ) self.assertEquals( cursor.execute("select * from translation_keys").fetchall(), [ (1, u"SomeString", u"2010-12-02 02:22:00"), (2, u"OtherString", u"2010-12-02 02:21:00") ], ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, u"New translation for some string"), (2, 2, 1, u"Translation for some other string"), (3, 1, 2, u"Translation for some string"), (4, 2, 2, u"Translation for some other string") ], ) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:23:00')" ) db.write_string_mapping_for_platform( "Win", { "SomeString" : "New translation for some string", } ) self.assertEquals( cursor.execute("select * from translation_keys").fetchall(), [ (1, u"SomeString", u"2010-12-02 02:23:00"), (2, u"OtherString", u"2010-12-02 02:23:00") ], ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, u"New translation for some string"), (2, 2, 1, u"Translation for some other string"), (3, 1, 2, u"New translation for some string") ], ) db.disconnect() def test_write_string_mapping_for_platform_translates_params(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:20:00')" ) db.connect() db.write_string_mapping_for_platform( "Mac", { "SomeString" : "%03d of %03.3lld for {0} %@", } ) cursor = db.dbh.cursor() self.assertEquals( cursor.execute("select * from translation_keys").fetchall(), [ (1, u"SomeString", u"2010-12-02 02:20:00"), ], ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, "%03d of %03.3lld for {0} %@"), ], ) self.assertEquals( cursor.execute("select * from replaced_params").fetchall(), [ (1, 1, 1, 0, u"%03d" ), (2, 1, 1, 1, u"%03.3lld"), (3, 1, 1, 2, u"{0}" ), (4, 1, 1, 3, u"%@" ), ], ) db.write_string_mapping_for_platform( "Mac", { "SomeString" : "%03d of %03.3lld", } ) self.assertEquals( cursor.execute("select * from native_translations").fetchall(), [ (1, 1, 1, "%03d of %03.3lld"), ], ) self.assertEquals( cursor.execute("select * from replaced_params").fetchall(), [ (1, 1, 1, 0, u"%03d" ), (2, 1, 1, 1, u"%03.3lld"), ], ) db.disconnect() @mock.patch.object(os.path, "abspath") def test_update_from_vcs(self, mock_function): mock_function.return_value = "some_full_path" vcs = mock.Mock() db = database.SQLite("some_filename") submodule_path = "submodule" db.update_from_vcs(vcs, submodule_path) vcs.add_file.assert_called_with("some_full_path", submodule_path) @mock.patch.object(os.path, "exists") def test_connect_loads_schema_if_new_database(self, mock_function): mock_function.return_value = False db = database.SQLite("some_filename") db._save_database = mock.Mock() orig_load_schema = db._load_schema db._load_schema = mock.Mock(side_effect = orig_load_schema) db._schema_file = mock.Mock( return_value = cStringIO.StringIO("""create table test_table ( test_column INTEGER NOT NULL );""") ) db.connect() db._load_schema.assert_called_with() cursor = db.dbh.cursor() cursor.execute("insert into test_table (test_column) values(1)") cursor.close() db.disconnect() @mock.patch.object(os.path, "exists") def test_connect_loads_existing_database(self, mock_function): mock_function.return_value = True db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) orig_load_database = db._load_database db._load_database = mock.Mock(side_effect = orig_load_database) db._open_for_reading = mock.Mock( return_value = cStringIO.StringIO("""create table test_table ( test_column INTEGER NOT NULL ); insert into test_table(test_column) values(1); """) ) db.connect() db._load_database.assert_called_with() db._open_for_reading.assert_called_with("some_filename") cursor = db.dbh.cursor() cursor.execute("select test_column from test_table") self.assertEquals(cursor.fetchall(), [(1,)]) cursor.close() db.disconnect() def test_disconnect_saves_existing_database(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") lines = [] def _write(line): lines.append(line) db.connect = mock.Mock(side_effect = _connect) output_file = mock.Mock() output_file.write = mock.Mock(side_effect = _write) db._open_for_writing = mock.Mock(return_value = output_file) db._remove_temporary_file = mock.Mock() db.connect() cursor = db.dbh.cursor() cursor.execute( "create table test_table (test_column INTEGER NOT NULL);" ) cursor.execute("insert into test_table (test_column) values(1);") db.disconnect() db._open_for_writing.assert_called_with("some_filename") db._remove_temporary_file.assert_called_with() self.assertEquals( "".join(lines), """BEGIN TRANSACTION; CREATE TABLE test_table (test_column INTEGER NOT NULL); INSERT INTO "test_table" VALUES(1); COMMIT; """.replace(" ", "") ) def test_remove_old_unmapped_strings(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db.connect() db.write_string_mapping_for_platform( "Mac", { "SomeString" : "Translation for some string", "OtherString" : "Translation for some other string", } ) cursor = db.dbh.cursor() self.assertEquals( cursor.execute(""" select translation_key_no, translation_key from translation_keys""" ).fetchall(), [ (2, u"OtherString"), (1, u"SomeString") ], ) cursor.execute(""" delete from native_translations where translation_key_no = 1 """) db.remove_old_unmapped_strings() self.assertEquals( cursor.execute(""" select translation_key_no, translation_key from translation_keys""" ).fetchall(), [ (2, u"OtherString"), (1, u"SomeString") ], ) cursor.execute(""" update translation_keys set last_updated = datetime('now', '-89 days') """) db.remove_old_unmapped_strings() self.assertEquals( cursor.execute(""" select translation_key_no, translation_key from translation_keys""" ).fetchall(), [ (2, u"OtherString"), (1, u"SomeString") ], ) cursor.execute(""" update translation_keys set last_updated = datetime('now', '-91 days') """) db.remove_old_unmapped_strings() self.assertEquals( cursor.execute(""" select translation_key_no, translation_key from translation_keys""" ).fetchall(), [ (2, u"OtherString") ], ) db.disconnect() def test_get_platforms(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db.connect() db.write_string_mapping_for_platform( "Mac", { u"SomeString" : u"Mac translation for some string", u"OtherString" : u"Mac translation for some other string", } ) db.write_string_mapping_for_platform( "Win", { u"SomeString" : u"Win translation for some string", u"OtherString" : u"Win translation for some other string", } ) self.assertEquals(db.get_platforms(), [ u"Mac", u"Win" ]) db.disconnect() def test_get_string_mapping_for_platform(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db.connect() db.write_string_mapping_for_platform( "Mac", { u"SomeString" : u"Mac translation for some string", u"OtherString" : u"Mac translation for some other string", } ) db.write_string_mapping_for_platform( "Win", { u"SomeString" : u"Win translation for some string", u"OtherString" : u"Win translation for some other string", } ) self.assertEquals( db.get_string_mapping_for_platform("Mac"), { u"SomeString" : u"Mac translation for some string", u"OtherString" : u"Mac translation for some other string", } ) self.assertEquals( db.get_string_mapping_for_platform("Win"), { u"SomeString" : u"Win translation for some string", u"OtherString" : u"Win translation for some other string", } ) db.disconnect() def test_get_all_translation_keys(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db.connect() db.write_string_mapping_for_platform( "Mac", { u"SomeString" : u"Mac translation for some string", u"OtherString" : u"Mac translation for some other string", } ) self.assertEquals( db.get_all_translation_keys(), [ u"OtherString", u"SomeString", ], ) db.disconnect() def test_get_all_native_translations(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db.connect() db.write_string_mapping_for_platform( "Mac", { u"SomeString" : u"Mac translation for some string", u"OtherString" : u"Mac translation for some other string" } ) self.assertEquals( db.get_all_native_translations(), [ u"Mac translation for some string", u"Mac translation for some other string" ], ) db.disconnect() def test_get_native_translations_for_platform(self): db = database.SQLite("some_filename") def _connect(*args, **kwargs): db.dbh = sqlite3.connect(":memory:") def _disconnect(*args, **kwargs): db.dbh.close() db._connect = mock.Mock(side_effect = _connect) db.disconnect = mock.Mock(side_effect = _disconnect) db._get_current_time = mock.Mock( return_value = "datetime('2010-12-02 02:20:00')" ) db.connect() db.write_string_mapping_for_platform( "Mac", { "SomeString" : "%03d of %03.3lld for {0} %@", } ) self.assertEquals( db.get_native_translations_for_platform("Mac"), [ "%03d of %03.3lld for {0} %@" ] ) db.disconnect() @mock.patch("__builtin__.open") def test_open_for_reading(self, open_func): db = database.SQLite("some_filename") db._open_for_reading("filename") open_func.assert_called_with("filename", "r") @mock.patch.object(codecs, "open") def test_open_for_writing(self, open_func): db = database.SQLite("some_filename") db._open_for_writing("filename") open_func.assert_called_with("filename", "w", "utf-8") @mock.patch.object(os.path, "exists") def test_deletes_existing_temp_file_on_connect(self, exists_func): exists_func.return_value = True db = database.SQLite("some_filename") db._remove_temporary_file = mock.Mock() db._load_database = mock.Mock() db.connect() db._remove_temporary_file.assert_called_with()

29.835526

75

0.533572

1,903

18,140

4.862323

0.079348

0.060521

0.077813

0.042797

0.869124

0.829461

0.799957

0.754782

0.72852

0.708419

0

0.030683

0.349614

18,140

607

76

29.884679

0.753602

0

0.586639

0

0.240942

0.00128

0

0.070981

1

0.075157

false

0

0.014614

0

0.091858

0

null

0

1

0

null

0

6

4f4ff57a02e20840df6f45a253f2a007e5a10498

133

py

Python

core/dl_framework/__init__.py

MarcelMoczarski/template_project

126ca7e1749158bf3adb00eddffb289b6b88fea3

[ "MIT" ]

null

core/dl_framework/__init__.py

MarcelMoczarski/template_project

126ca7e1749158bf3adb00eddffb289b6b88fea3

[ "MIT" ]

null

core/dl_framework/__init__.py

MarcelMoczarski/template_project

126ca7e1749158bf3adb00eddffb289b6b88fea3

[ "MIT" ]

null

from . import callbacks from . import data from . import learner from . import loss_functions from . import model from . import utils

22.166667

28

0.781955

19

133

5.421053

0.473684

0.582524

0

0.172932

133

6

29

22.166667

0.936364

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

4f59a198c3bde0f50d5e15cd6fee42198b31cf3e

85

py

Python

xpart/linear_normal_form.py

xbuffat/xpart

482208e6aa964e98337b93bac8f604b8789ac8cc

[ "MIT" ]

null

xpart/linear_normal_form.py

xbuffat/xpart

482208e6aa964e98337b93bac8f604b8789ac8cc

[ "MIT" ]

null

xpart/linear_normal_form.py

xbuffat/xpart

482208e6aa964e98337b93bac8f604b8789ac8cc

[ "MIT" ]

null

from xtrack.linear_normal_form import healy_symplectify, compute_linear_normal_form

28.333333

83

0.905882

12

85

5.916667

0.75

0.338028

0.450704

0

0.070588

85

2

84

42.5

0.898734

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

4f6bb8ed8732eeead8a7c8d428954de424ee3d13

506

py

Python

propsettings/setting_types/list_setting_type.py

mnicolas94/propsettings

2ec905bd045bf45a45e644846b098b64fb283130

[ "MIT" ]

null

propsettings/setting_types/list_setting_type.py

mnicolas94/propsettings

2ec905bd045bf45a45e644846b098b64fb283130

[ "MIT" ]

null

propsettings/setting_types/list_setting_type.py

mnicolas94/propsettings

2ec905bd045bf45a45e644846b098b64fb283130

[ "MIT" ]

null

from propsettings.setting_type import SettingType class List(SettingType): def __init__(self, list_type: type, elements_setting_type: SettingType = None): self._type = list_type self._elements_setting_type = elements_setting_type @property def type(self): return self._type @property def elements_setting_type(self): return self._elements_setting_type def has_elements_setting_type(self): return self._elements_setting_type is not None

25.3

83

0.729249

63

506

5.428571

0.285714

0.25731

0.388889

0.201754

0.304094

0

0.211462

506

19

84

26.631579

0.857143

0

0.153846

0

1

0.307692

false

0

0.076923

0.230769

0.692308

0

null

1

0

null

0

1

0

1

0

6

96c514bd91738ca4d5d7995ce73db811c99d5bd8

53,257

py

Python

api_tests/nodes/views/test_node_comments_list.py

h-ci-user01/osf.h-test

a61db2c639a26031aa5b7f58c4dd719919aa5ece

[ "Apache-2.0" ]

null

api_tests/nodes/views/test_node_comments_list.py

h-ci-user01/osf.h-test

a61db2c639a26031aa5b7f58c4dd719919aa5ece

[ "Apache-2.0" ]

18

2020-03-24T15:26:02.000Z

2022-03-08T21:30:39.000Z

api_tests/nodes/views/test_node_comments_list.py

h-ci-user01/osf.h-test

a61db2c639a26031aa5b7f58c4dd719919aa5ece

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import pytest import mock from addons.wiki.tests.factories import NodeWikiFactory from api.base.settings import osf_settings from api.base.settings.defaults import API_BASE from api_tests import utils as test_utils from framework.auth import core from osf.models import Guid from osf_tests.factories import ( ProjectFactory, RegistrationFactory, AuthUserFactory, CommentFactory, ) from rest_framework import exceptions @pytest.fixture() def user(): return AuthUserFactory() @pytest.mark.django_db class NodeCommentsListMixin(object): @pytest.fixture() def user_non_contrib(self): return AuthUserFactory() @pytest.fixture() def project_private_dict(self): raise NotImplementedError @pytest.fixture() def project_public_dict(self): raise NotImplementedError @pytest.fixture() def registration_dict(self): raise NotImplementedError def test_return_comments(self, app, user, user_non_contrib, project_public_dict, project_private_dict, registration_dict): # test_return_public_node_comments_logged_out_user res = app.get(project_public_dict['url']) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert len(comment_json) == 1 assert project_public_dict['comment']._id in comment_ids # test_return_public_node_comments_logged_in_user res = app.get(project_public_dict['url'], auth=user_non_contrib) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert len(comment_json) == 1 assert project_public_dict['comment']._id in comment_ids # test_return_private_node_comments_logged_out_user res = app.get(project_private_dict['url'], expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail # test_return_private_node_comments_logged_in_non_contributor res = app.get(project_private_dict['url'], auth=user_non_contrib, expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail # test_return_private_node_comments_logged_in_contributor res = app.get(project_private_dict['url'], auth=user.auth) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert len(comment_json) == 1 assert project_private_dict['comment']._id in comment_ids # test_return_registration_comments_logged_in_contributor res = app.get(registration_dict['url'], auth=user.auth) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert len(comment_json) == 1 assert registration_dict['comment']._id in comment_ids def test_return_both_deleted_and_undeleted_comments(self, app, user, project_private_dict, mock_update_search=None): deleted_comment = CommentFactory(node=project_private_dict['project'], user=user, target=project_private_dict['comment'].target, is_deleted=True) res = app.get(project_private_dict['url'], auth=user.auth) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert project_private_dict['comment']._id in comment_ids assert deleted_comment._id in comment_ids def test_node_comments_pagination(self, app, user, project_public_dict): # test_node_comments_list_pagination url = '{}?filter[target]={}&related_counts=False'.format(project_public_dict['url'], project_public_dict['project']._id) res = app.get(url, user=user, auth=user.auth) assert res.status_code == 200 assert res.json['links']['meta']['unread'] == 0 # test_node_comments_list_updated_pagination url = '{}?filter[target]={}&related_counts=False&version=2.1'.format(project_public_dict['url'], project_public_dict['project']._id) res = app.get(url, user=user, auth=user.auth) assert res.status_code == 200 assert res.json['meta']['unread'] == 0 @pytest.mark.django_db class TestNodeCommentsList(NodeCommentsListMixin): @pytest.fixture() def project_private_dict(self, user): project_private = ProjectFactory(is_public=False, creator=user) comment_private = CommentFactory(node=project_private, user=user) url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) return {'project': project_private, 'comment': comment_private, 'url': url_private} @pytest.fixture() def project_public_dict(self, user): project_public = ProjectFactory(is_public=True, creator=user) comment_public = CommentFactory(node=project_public, user=user) url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) return {'project': project_public, 'comment': comment_public, 'url': url_public} @pytest.fixture() def registration_dict(self, user): registration = RegistrationFactory(creator=user) comment_registration = CommentFactory(node=registration, user=user) url_registration = '/{}registrations/{}/comments/'.format(API_BASE, registration._id) return {'registration': registration, 'comment': comment_registration, 'url': url_registration} @pytest.mark.django_db class TestNodeCommentsListFiles(NodeCommentsListMixin): @pytest.fixture() def project_private_dict(self, user): project_private = ProjectFactory(is_public=False, creator=user) file_private = test_utils.create_test_file(project_private, user) comment_private = CommentFactory(node=project_private, user=user, target=file_private.get_guid(), page='files') url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) return {'project': project_private, 'file': file_private, 'comment': comment_private, 'url': url_private} @pytest.fixture() def project_public_dict(self, user): project_public = ProjectFactory(is_public=True, creator=user) file_public = test_utils.create_test_file(project_public, user) comment_public = CommentFactory(node=project_public, user=user, target=file_public.get_guid(), page='files') url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) return {'project': project_public, 'file': file_public, 'comment': comment_public, 'url': url_public} @pytest.fixture() def registration_dict(self, user): registration = RegistrationFactory(creator=user) file_registration = test_utils.create_test_file(registration, user) comment_registration = CommentFactory(node=registration, user=user, target=file_registration.get_guid(), page='files') url_registration = '/{}registrations/{}/comments/'.format(API_BASE, registration._id) return {'registration': registration, 'file': file_registration, 'comment': comment_registration, 'url': url_registration} def test_comments_on_deleted_files_are_not_returned(self, app, user, project_private_dict): # Delete commented file osfstorage = project_private_dict['project'].get_addon('osfstorage') root_node = osfstorage.get_root() # root_node.delete(project_private_dict['file']) project_private_dict['file'].delete(user=user) res = app.get(project_private_dict['url'], auth=user.auth) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert project_private_dict['comment']._id not in comment_ids @pytest.mark.django_db class TestNodeCommentsListWiki(NodeCommentsListMixin): @pytest.fixture() def project_private_dict(self, user): project_private = ProjectFactory(is_public=False, creator=user) wiki_private = NodeWikiFactory(node=project_private, user=user) comment_private = CommentFactory(node=project_private, user=user, target=Guid.load(wiki_private._id), page='wiki') url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) return {'project': project_private, 'wiki': wiki_private, 'comment': comment_private, 'url': url_private} @pytest.fixture() def project_public_dict(self, user): project_public = ProjectFactory(is_public=True, creator=user) wiki_public = NodeWikiFactory(node=project_public, user=user) comment_public = CommentFactory(node=project_public, user=user, target=Guid.load(wiki_public._id), page='wiki') url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) return {'project': project_public, 'wiki': wiki_public, 'comment': comment_public, 'url': url_public} @pytest.fixture() def registration_dict(self, user): registration = RegistrationFactory(creator=user) wiki_registration = NodeWikiFactory(node=registration, user=user) comment_registration = CommentFactory(node=registration, user=user, target=Guid.load(wiki_registration._id), page='wiki') url_registration = '/{}registrations/{}/comments/'.format(API_BASE, registration._id) return {'registration': registration, 'wiki': wiki_registration, 'comment': comment_registration, 'url': url_registration} def test_comments_on_deleted_wikis_are_not_returned(self, app, user, project_private_dict, mock_update_search=None): # Delete wiki project_private_dict['project'].delete_node_wiki(project_private_dict['wiki'].page_name, core.Auth(user)) res = app.get(project_private_dict['url'], auth=user.auth) assert res.status_code == 200 comment_json = res.json['data'] comment_ids = [comment['id'] for comment in comment_json] assert project_private_dict['comment']._id not in comment_ids @pytest.mark.django_db class NodeCommentsCreateMixin(object): @pytest.fixture() def user_read_contrib(self): return AuthUserFactory() @pytest.fixture() def user_non_contrib(self): return AuthUserFactory() @pytest.fixture() def payload(self): raise NotImplementedError @pytest.fixture() def project_private_comment_private(self): raise NotImplementedError @pytest.fixture() def project_public_comment_private(self): raise NotImplementedError @pytest.fixture() def project_public_comment_public(self): raise NotImplementedError @pytest.fixture() def project_private_comment_public(self): raise NotImplementedError def test_node_comments(self, app, user, user_read_contrib, user_non_contrib, project_private_comment_private, project_private_comment_public, project_public_comment_public, project_public_comment_private): # test_private_node_private_comment_level_logged_in_admin_can_comment project_dict = project_private_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_private_node_private_comment_level_logged_in_read_contributor_can_comment project_dict = project_private_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_read_contrib.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_private_node_private_comment_level_non_contributor_cannot_comment project_dict = project_private_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_non_contrib.auth, expect_errors=True) assert res.status_code == 403 assert res.json['errors'][0]['detail'] == exceptions.PermissionDenied.default_detail # test_private_node_private_comment_level_logged_out_user_cannot_comment project_dict = project_private_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail # test_private_node_with_public_comment_level_admin_can_comment # Test admin contributors can still comment on a private project with comment_level == 'public' project_dict = project_private_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_private_node_with_public_comment_level_read_only_contributor_can_comment # Test read-only contributors can still comment on a private project with comment_level == 'public' project_dict = project_private_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_read_contrib.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_private_node_with_public_comment_level_non_contributor_cannot_comment # Test non-contributors cannot comment on a private project with comment_level == 'public' project_dict = project_private_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_non_contrib.auth, expect_errors=True) assert res.status_code == 403 # test_private_node_with_public_comment_level_logged_out_user_cannot_comment # Test logged out users cannot comment on a private project with comment_level == 'public' project_dict = project_private_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail # test_public_project_with_public_comment_level_admin_can_comment # Test admin contributor can still comment on a public project when it is configured so any logged-in user can comment (comment_level == 'public') project_dict = project_public_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_public_project_with_public_comment_level_read_only_contributor_can_comment # Test read-only contributor can still comment on a public project when it is configured so any logged-in user can comment (comment_level == 'public') project_dict = project_public_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_read_contrib.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_public_project_with_public_comment_level_non_contributor_can_comment # Test non-contributors can comment on a public project when it is configured so any logged-in user can comment (comment_level == 'public') project_dict = project_public_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_non_contrib.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_public_project_with_public_comment_level_logged_out_user_cannot_comment # Test logged out users cannot comment on a public project when it is configured so any logged-in user can comment (comment_level == 'public') project_dict = project_public_comment_public res = app.post_json_api(project_dict['url'], project_dict['payload'], expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail # test_public_node_private_comment_level_admin_can_comment # Test only contributors can comment on a public project when it is configured so only contributors can comment (comment_level == 'private') project_dict = project_public_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_public_node_private_comment_level_read_only_contributor_can_comment project_dict = project_public_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_read_contrib.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == project_dict['payload']['data']['attributes']['content'] # test_public_node_private_comment_level_non_contributor_cannot_comment project_dict = project_public_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], auth=user_non_contrib.auth, expect_errors=True) assert res.status_code == 403 assert res.json['errors'][0]['detail'] == exceptions.PermissionDenied.default_detail # test_public_node_private_comment_level_logged_out_user_cannot_comment project_dict = project_public_comment_private res = app.post_json_api(project_dict['url'], project_dict['payload'], expect_errors=True) assert res.status_code == 401 assert res.json['errors'][0]['detail'] == exceptions.NotAuthenticated.default_detail @pytest.mark.django_db class TestNodeCommentCreate(NodeCommentsCreateMixin): @pytest.fixture() def payload(self): def make_payload(target_id): return { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': target_id } } } } } return make_payload @pytest.fixture() def project_private_comment_private(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user, comment_level='private') project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) payload_private = payload(project_private._id) return {'project': project_private, 'url': url_private, 'payload': payload_private} @pytest.fixture() def project_public_comment_private(self, user, user_read_contrib, payload): project_public = ProjectFactory(is_public=True, creator=user, comment_level='private') project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) payload_public = payload(project_public._id) return {'project': project_public, 'url': url_public, 'payload': payload_public} @pytest.fixture() def project_public_comment_public(self, user, user_read_contrib, payload): """ Public project configured so that any logged-in user can comment.""" project_public = ProjectFactory(is_public=True, creator=user) project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) payload_public = payload(project_public._id) return {'project': project_public, 'url': url_public, 'payload': payload_public} @pytest.fixture() def project_private_comment_public(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user) project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) payload_private = payload(project_private._id) return {'project': project_private, 'url': url_private, 'payload': payload_private} def test_create_comment_errors(self, app, user, payload, project_private_comment_private): # test_create_comment_invalid_data project_dict = project_private_comment_private res = app.post_json_api(project_dict['url'], 'Incorrect data', auth=user.auth, expect_errors=True) assert res.status_code == 400 # test_create_comment_no_relationships project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': '4:44' } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Request must include /data/relationships.' assert res.json['errors'][0]['source']['pointer'] == '/data/relationships' # test_create_comment_empty_relationships project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'Center for Closed Logic' }, 'relationships': {} } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Request must include /data/relationships.' assert res.json['errors'][0]['source']['pointer'] == '/data/relationships' # test_create_comment_relationship_is_a_list project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': [{'id': project_dict['project']._id}] } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == exceptions.ParseError.default_detail # test_create_comment_target_no_data_in_relationships project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': {} } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Request must include /data.' assert res.json['errors'][0]['source']['pointer'] == 'data/relationships/target/data' # test_create_comment_no_target_key_in_relationships project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == exceptions.ParseError.default_detail # test_create_comment_blank_target_id project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': '' } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Invalid comment target \'\'.' # test_create_comment_invalid_target_id project_dict = project_private_comment_private project_id = ProjectFactory()._id payload_project = payload(project_id) res = app.post_json_api(project_dict['url'], payload_project, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Invalid comment target \'' + str(project_id) + '\'.' # test_create_comment_invalid_target_type project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'Invalid', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 409 assert res.json['errors'][0]['detail'] == 'The target resource has a type of "nodes", but you set the json body\'s type field to "Invalid". You probably need to change the type field to match the target resource\'s type.' # test_create_comment_no_target_type_in_relationships project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Request must include /type.' # test_create_comment_no_type project_dict = project_private_comment_private payload_req = { 'data': { 'type': '', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'This field may not be blank.' assert res.json['errors'][0]['source']['pointer'] == '/data/type' # test_create_comment_no_content project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': '' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'This field may not be blank.' assert res.json['errors'][0]['source']['pointer'] == '/data/attributes/content' # test_create_comment_trims_whitespace project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': ' ' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'This field may not be blank.' # test_create_comment_exceeds_max_length project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': ('c' * (osf_settings.COMMENT_MAXLENGTH + 3)) }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Ensure this field has no more than {} characters.'.format(str(osf_settings.COMMENT_MAXLENGTH)) # test_create_comment_invalid_target_node url_fake = '/{}nodes/{}/comments/'.format(API_BASE, 'abcde') payload_fake = payload('abcde') res = app.post_json_api(url_fake, payload_fake, auth=user.auth, expect_errors=True) assert res.status_code == 404 assert res.json['errors'][0]['detail'] == exceptions.NotFound.default_detail def test_create_comment_with_allowed_tags(self, app, user, project_private_comment_private): project_dict = project_private_comment_private payload = { 'data': { 'type': 'comments', 'attributes': { 'content': 'Logic Reason' }, 'relationships': { 'target': { 'data': { 'type': 'nodes', 'id': project_dict['project']._id } } } } } res = app.post_json_api(project_dict['url'], payload, auth=user.auth) assert res.status_code == 201 assert res.json['data']['attributes']['content'] == payload['data']['attributes']['content'] @pytest.mark.django_db class TestFileCommentCreate(NodeCommentsCreateMixin): @pytest.fixture() def payload(self): def make_payload(target_id): return { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'files', 'id': target_id } } } } } return make_payload @pytest.fixture() def project_private_comment_private(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user, comment_level='private') project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) file_private = test_utils.create_test_file(project_private, user) payload_private = payload(file_private.get_guid()._id) return {'project': project_private, 'url': url_private, 'file': file_private, 'payload': payload_private} @pytest.fixture() def project_public_comment_private(self, user, user_read_contrib, payload): project_public = ProjectFactory(is_public=True, creator=user, comment_level='private') project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) file_public = test_utils.create_test_file(project_public, user) payload_public = payload(file_public.get_guid()._id) return {'project': project_public, 'url': url_public, 'file': file_public, 'payload': payload_public} @pytest.fixture() def project_public_comment_public(self, user, user_read_contrib, payload): """ Public project configured so that any logged-in user can comment.""" project_public = ProjectFactory(is_public=True, creator=user) project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) file_public = test_utils.create_test_file(project_public, user) payload_public = payload(file_public.get_guid()._id) return {'project': project_public, 'url': url_public, 'file': file_public, 'payload': payload_public} @pytest.fixture() def project_private_comment_public(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user) project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) file_private = test_utils.create_test_file(project_private, user) payload_private = payload(file_private.get_guid()._id) return {'project': project_private, 'url': url_private, 'file': file_private, 'payload': payload_private} def test_create_file_comment_errors(self, app, user, payload, project_private_comment_private): # test_create_file_comment_invalid_target_id project_dict = project_private_comment_private file = test_utils.create_test_file(ProjectFactory(), user) payload_req = payload(file._id) res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Invalid comment target \'' + str(file._id) + '\'.' # test_create_file_comment_invalid_target_type project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'Invalid', 'id': project_dict['file'].get_guid()._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 409 assert res.json['errors'][0]['detail'] == 'The target resource has a type of "files", but you set the json body\'s type field to "Invalid". You probably need to change the type field to match the target resource\'s type.' @pytest.mark.django_db class TestWikiCommentCreate(NodeCommentsCreateMixin): @pytest.fixture() def payload(self): def make_payload(target_id): return { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'wiki', 'id': target_id } } } } } return make_payload @pytest.fixture() def project_private_comment_private(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user, comment_level='private') project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) wiki = NodeWikiFactory(node=project_private, user=user) payload_private = payload(wiki._id) return {'project': project_private, 'url': url_private, 'wiki': wiki, 'payload': payload_private} @pytest.fixture() def project_public_comment_private(self, user, user_read_contrib, payload): project_public = ProjectFactory(is_public=True, creator=user, comment_level='private') project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) wiki = NodeWikiFactory(node=project_public, user=user) payload_public = payload(wiki._id) return {'project': project_public, 'url': url_public, 'wiki': wiki, 'payload': payload_public} @pytest.fixture() def project_public_comment_public(self, user, user_read_contrib, payload): """ Public project configured so that any logged-in user can comment.""" project_public = ProjectFactory(is_public=True, creator=user) project_public.add_contributor(user_read_contrib, permissions=['read']) project_public.save() url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) wiki = NodeWikiFactory(node=project_public, user=user) payload_public = payload(wiki._id) return {'project': project_public, 'url': url_public, 'wiki': wiki, 'payload': payload_public} @pytest.fixture() def project_private_comment_public(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user) project_private.add_contributor(user_read_contrib, permissions=['read']) project_private.save() url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) wiki = NodeWikiFactory(node=project_private, user=user) payload_private = payload(wiki._id) return {'project': project_private, 'url': url_private, 'wiki': wiki, 'payload': payload_private} def test_create_wiki_comment_errors(self, app, user, payload, project_private_comment_private, mock_update_search=None): # test_create_wiki_comment_invalid_target_id project_dict = project_private_comment_private wiki = NodeWikiFactory(node=ProjectFactory(), user=user) payload_req = payload(wiki._id) res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Invalid comment target \'' + str(wiki._id) + '\'.' # test_create_wiki_comment_invalid_target_type project_dict = project_private_comment_private payload_req = { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'Invalid', 'id': project_dict['wiki']._id } } } } } res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 409 assert res.json['errors'][0]['detail'] == 'The target resource has a type of "wiki", but you set the json body\'s type field to "Invalid". You probably need to change the type field to match the target resource\'s type.' @pytest.mark.django_db class TestCommentRepliesCreate(NodeCommentsCreateMixin): @pytest.fixture() def payload(self): def make_payload(comment_id): return { 'data': { 'type': 'comments', 'attributes': { 'content': 'This is a comment' }, 'relationships': { 'target': { 'data': { 'type': 'comments', 'id': comment_id } } } } } return make_payload @pytest.fixture() def project_private_comment_private(self, user, user_read_contrib, payload): project_private = ProjectFactory.create(is_public=False, creator=user, comment_level='private') project_private.add_contributor(user_read_contrib, permissions=['read'], save=True) comment_private = CommentFactory(node=project_private, user=user) url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) payload_private = payload(comment_private._id) return {'project': project_private, 'comment': comment_private, 'url': url_private, 'payload': payload_private} @pytest.fixture() def project_public_comment_private(self, user, user_read_contrib, payload): project_public = ProjectFactory.create(is_public=True, creator=user, comment_level='private') project_public.add_contributor(user_read_contrib, permissions=['read'], save=True) comment_public = CommentFactory(node=project_public, user=user) url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) payload_public = payload(comment_public._id) return {'project': project_public, 'comment': comment_public, 'url': url_public, 'payload': payload_public} @pytest.fixture() def project_private_comment_public(self, user, user_read_contrib, payload): project_private = ProjectFactory(is_public=False, creator=user) project_private.add_contributor(user_read_contrib, permissions=['read'], save=True) comment_private = CommentFactory(node=project_private, user=user) comment_reply = CommentFactory(node=project_private, target=Guid.load(comment_private._id), user=user) url_private = '/{}nodes/{}/comments/'.format(API_BASE, project_private._id) payload_private = payload(comment_reply._id) return {'project': project_private, 'comment': comment_private, 'reply': comment_reply, 'url': url_private, 'payload': payload_private} @pytest.fixture() def project_public_comment_public(self, user, user_read_contrib, payload): project_public = ProjectFactory(is_public=True, creator=user) project_public.add_contributor(user_read_contrib, permissions=['read'], save=True) comment_public = CommentFactory(node=project_public, user=user) comment_reply = CommentFactory(node=project_public, target=Guid.load(comment_public._id), user=user) url_public = '/{}nodes/{}/comments/'.format(API_BASE, project_public._id) payload_public = payload(comment_reply._id) return {'project': project_public, 'comment': comment_public, 'reply': comment_reply, 'url': url_public, 'payload': payload_public} def test_create_comment_reply_invalid_target_id(self, app, user, payload, project_private_comment_private): project_dict = project_private_comment_private target_comment = CommentFactory(node=ProjectFactory(), user=user) payload_req = payload(target_comment._id) res = app.post_json_api(project_dict['url'], payload_req, auth=user.auth, expect_errors=True) assert res.status_code == 400 assert res.json['errors'][0]['detail'] == 'Invalid comment target \'' + str(target_comment._id) + '\'.' @pytest.mark.django_db class TestCommentFiltering: @pytest.fixture() def project(self, user): return ProjectFactory(creator=user) @pytest.fixture() def comment(self, user, project): return CommentFactory(node=project, user=user, page='node') @pytest.fixture() def comment_deleted(self, user, project): return CommentFactory(node=project, user=user, is_deleted=True, page='node') @pytest.fixture() def url_base(self, project): return '/{}nodes/{}/comments/'.format(API_BASE, project._id) @pytest.fixture() def date_created_formatted(self, comment): return comment.created.strftime('%Y-%m-%dT%H:%M:%S.%f') @pytest.fixture() def date_modified_formatted(self, user, comment): comment.edit('Edited comment', auth=core.Auth(user), save=True) return comment.modified.strftime('%Y-%m-%dT%H:%M:%S.%f') def test_filtering(self, app, user, project, comment, comment_deleted, date_created_formatted, date_modified_formatted, url_base): # test_node_comments_with_no_filter_returns_all_comments res = app.get(url_base, auth=user.auth) assert len(res.json['data']) == 2 # test_filtering_for_deleted_comments assert comment assert comment_deleted url = url_base + '?filter[deleted]=True' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert res.json['data'][0]['attributes']['deleted'] # test_filtering_for_non_deleted_comments assert comment assert comment_deleted url = url_base + '?filter[deleted]=False' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert not res.json['data'][0]['attributes']['deleted'] # test_filtering_comments_created_before_date url = url_base + '?filter[date_created][lt]={}'.format(date_created_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 0 # test_filtering_comments_created_on_date url = url_base + '?filter[date_created][eq]={}'.format(date_created_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 # test_filtering_comments_created_on_or_before_date url = url_base + '?filter[date_created][lte]={}'.format(date_created_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 # test_filtering_comments_created_after_date url = url_base + '?filter[date_created][gt]={}'.format(date_created_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 # test_filtering_comments_created_on_or_after_date url = url_base + '?filter[date_created][gte]={}'.format(date_created_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 2 # test_filtering_comments_modified_before_date url = url_base + '?filter[date_modified][lt]={}'.format(date_modified_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 # test_filtering_comments_modified_on_date url = url_base + '?filter[date_modified][eq]={}'.format(date_modified_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 # test_filtering_comments_modified_after_date url = url_base + '?filter[date_modified][gt]={}'.format(date_modified_formatted) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 0 # test_filtering_by_target_node url = url_base + '?filter[target]=' + str(project._id) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 2 assert project._id in res.json['data'][0]['relationships']['target']['links']['related']['href'] assert project._id in res.json['data'][1]['relationships']['target']['links']['related']['href'] # test_filtering_by_target_no_results url = url_base + '?filter[target]=' + 'fakeid' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 0 # test_filtering_by_target_no_results_with_related_counts url = '{}?filter[target]=fakeid&related_counts=True'.format(url_base) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 0 # test_filtering_by_page_node url = url_base + '?filter[page]=node' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 2 assert 'node' == res.json['data'][0]['attributes']['page'] assert 'node' == res.json['data'][1]['attributes']['page'] def test_filtering_for_comment_replies(self, app, user, project, comment, comment_deleted, url_base): reply = CommentFactory(node=project, user=user, target=Guid.load(comment._id)) url = url_base + '?filter[target]=' + str(comment._id) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert comment._id in res.json['data'][0]['relationships']['target']['links']['related']['href'] def test_filtering_by_target_file(self, app, user, project, comment, comment_deleted, url_base): test_file = test_utils.create_test_file(project, user) target = test_file.get_guid() file_comment = CommentFactory(node=project, user=user, target=target) url = url_base + '?filter[target]=' + str(target._id) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert test_file._id in res.json['data'][0]['relationships']['target']['links']['related']['href'] def test_filtering_by_target_wiki(self, app, user, project, comment, comment_deleted, url_base): test_wiki = NodeWikiFactory(node=project, user=user) wiki_comment = CommentFactory(node=project, user=user, target=Guid.load(test_wiki._id), page='wiki') url = url_base + '?filter[target]=' + str(test_wiki._id) res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert test_wiki.get_absolute_url() == res.json['data'][0]['relationships']['target']['links']['related']['href'] def test_filtering_by_page_files(self, app, user, project, comment, comment_deleted, url_base): test_file = test_utils.create_test_file(project, user) file_comment = CommentFactory(node=project, user=user, target=test_file.get_guid(), page='files') url = url_base + '?filter[page]=files' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert 'files' == res.json['data'][0]['attributes']['page'] def test_filtering_by_page_wiki(self, app, user, project, comment, comment_deleted, url_base): test_wiki = NodeWikiFactory(node=project, user=user) wiki_comment = CommentFactory(node=project, user=user, target=Guid.load(test_wiki._id), page='wiki') url = url_base + '?filter[page]=wiki' res = app.get(url, auth=user.auth) assert len(res.json['data']) == 1 assert 'wiki' == res.json['data'][0]['attributes']['page']

47.764126

230

0.633701

6,009

53,257

5.31586

0.041937

0.057415

0.019535

0.028551

0.897474

0.866137

0.845036

0.818834

0.793413

0.768369

0

0.005494

0.248155

53,257

1,114

231

47.807002

0.792263

0.083557

0

0.669265

0

0.123589

0.022599

0

0.154788

1

0.075724

false

0

0.011136

0.014477

0.14588

0

null

0

1

0

null

0

6

96f4765fec2d42431d835dc10a27c16df38b9656

45

py

Python

aptenodytes/__init__.py

yongrenjie/aptenodytes

0eb33b89c2358be42e9c3c4aa554618c6b2809e2

[ "MIT" ]

null

aptenodytes/__init__.py

yongrenjie/aptenodytes

0eb33b89c2358be42e9c3c4aa554618c6b2809e2

[ "MIT" ]

null

aptenodytes/__init__.py

yongrenjie/aptenodytes

0eb33b89c2358be42e9c3c4aa554618c6b2809e2

[ "MIT" ]

null

from .main import * from .molecules import *

15

24

0.733333

6

45

5.5

0.666667

0

0.177778

45

2

25

22.5

0.891892

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

8c4d647782b5eb6d5eb6afa7f6e3f26d90eaef78

9,497

py

Python

mpf/tests/test_Autofire.py

enteryourinitials/mpf

8fa529aacc1b163c71557adb61b591077d66c77e

[ "MIT" ]

null

mpf/tests/test_Autofire.py

enteryourinitials/mpf

8fa529aacc1b163c71557adb61b591077d66c77e

[ "MIT" ]

null

mpf/tests/test_Autofire.py

enteryourinitials/mpf

8fa529aacc1b163c71557adb61b591077d66c77e

[ "MIT" ]

null

from unittest.mock import MagicMock from mpf.platforms.interfaces.driver_platform_interface import PulseSettings from mpf.core.platform import SwitchSettings, DriverSettings from mpf.tests.MpfTestCase import MpfTestCase class TestAutofire(MpfTestCase): def get_config_file(self): return 'config.yaml' def get_machine_path(self): return 'tests/machine_files/autofire/' def test_hw_rule_pulse(self): self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=False, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=False, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True)) def test_hw_rule_overwrites(self): self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test_overwrites"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=False, debounce=True), DriverSettings(hw_driver=self.machine.coils["c_test"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=False) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test_overwrites"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=False, debounce=True), DriverSettings(hw_driver=self.machine.coils["c_test"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=False)) self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test_overwrites2"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_debounce_on"].hw_switch, invert=False, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test_recycle_off"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=10), hold_settings=None, recycle=True) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test_overwrites2"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_debounce_on"].hw_switch, invert=False, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test_recycle_off"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=10), hold_settings=None, recycle=True)) def test_hw_rule_coil_and_switch_defaults(self): self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test_defaults"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_debounce_on"].hw_switch, invert=False, debounce=True), DriverSettings(hw_driver=self.machine.coils["c_test_recycle_off"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=10), hold_settings=None, recycle=False) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test_defaults"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_debounce_on"].hw_switch, invert=False, debounce=True), DriverSettings(hw_driver=self.machine.coils["c_test_recycle_off"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=10), hold_settings=None, recycle=False)) def test_hw_rule_pulse_inverted_switch(self): self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test_inverted"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_nc"].hw_switch, invert=True, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test2"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test_inverted"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test_nc"].hw_switch, invert=True, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test2"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True)) def test_hw_rule_pulse_inverted_autofire(self): self.machine.default_platform.set_pulse_on_hit_rule = MagicMock() self.machine.autofires["ac_test_inverted2"].enable() self.machine.default_platform.set_pulse_on_hit_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=True, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test2"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True) ) self.machine.default_platform.clear_hw_rule = MagicMock() self.machine.autofires["ac_test_inverted2"].disable() self.machine.default_platform.clear_hw_rule.assert_called_once_with( SwitchSettings(hw_switch=self.machine.switches["s_test"].hw_switch, invert=True, debounce=False), DriverSettings(hw_driver=self.machine.coils["c_test2"].hw_driver, pulse_settings=PulseSettings(power=1.0, duration=23), hold_settings=None, recycle=True)) def test_disabled(self): """Verify that a disabled autofire coil doesn't post 'playfield_active'.""" self.mock_event("playfield_active") self.machine_run() self.hit_and_release_switch("s_test_disabled") self.machine_run() self.assertEventNotCalled("playfield_active") self.machine.autofires["ac_test_disabled"].enable() self.hit_and_release_switch("s_test_disabled") self.machine_run() self.assertEventCalled("playfield_active", times=1) self.machine.autofires["ac_test_disabled"].disable() self.hit_and_release_switch("s_test_disabled") self.machine_run() self.assertEventCalled("playfield_active", times=1) def test_timeout(self): self.machine.autofires["ac_test_timeout"].enable() self.machine_run() # 9 hits are ok for _ in range(9): self.hit_and_release_switch("s_test") self.machine_run() self.assertTrue(self.machine.autofires["ac_test_timeout"]._enabled) # 10th hit should disable it self.hit_and_release_switch("s_test") self.machine_run() self.assertFalse(self.machine.autofires["ac_test_timeout"]._enabled) # reenable after 500ms self.advance_time_and_run(.6) self.assertTrue(self.machine.autofires["ac_test_timeout"]._enabled) # exire the older hits self.advance_time_and_run(1) # 9 hits are ok for _ in range(9): self.hit_and_release_switch("s_test") self.machine_run() self.assertTrue(self.machine.autofires["ac_test_timeout"]._enabled) # wait 1s self.advance_time_and_run(1) # another 9 hits are ok for _ in range(9): self.hit_and_release_switch("s_test") self.machine_run() self.assertTrue(self.machine.autofires["ac_test_timeout"]._enabled) # 10th hit should disable it self.hit_and_release_switch("s_test") self.machine_run() self.assertFalse(self.machine.autofires["ac_test_timeout"]._enabled) self.advance_time_and_run(.2) # disable manually while disabled by too many hits self.machine.autofires["ac_test_timeout"].disable() self.assertFalse(self.machine.autofires["ac_test_timeout"]._enabled) # should not reenable self.advance_time_and_run(.4) self.assertFalse(self.machine.autofires["ac_test_timeout"]._enabled)

48.208122

122

0.703591

1,195

9,497

5.256904

0.104603

0.143585

0.068768

0.099331

0.894142

0.881248

0.846705

0.83206

0.803884

0

0.010023

0.191113

9,497

196

123

48.454082

0.807732

0.030852

0

0.639706

0

0.086734

0.003156

0

0.169118

1

0.066176

false

0

0.029412

0.014706

0.117647

0

null

0

1

0

null

0

6

8c573598212723c34d72d9c5a33a303fd85f3976

11,043

py

Python

app/api/random_positions.py

justinycho-business/battleships

e53f7dc8fa5af36d417d7694e07f9b20397f093e

[ "MIT" ]

null

app/api/random_positions.py

justinycho-business/battleships

e53f7dc8fa5af36d417d7694e07f9b20397f093e

[ "MIT" ]

null

app/api/random_positions.py

justinycho-business/battleships

e53f7dc8fa5af36d417d7694e07f9b20397f093e

[ "MIT" ]

null

import random def get_block_square_positions(currentlyoccupiedpositions): positions = [] square_orientation_dic = [ "UpperLeft", "UpperRight", "LowerLeft", "LowerRight" ] block_square_not_positioned = True list_of_block_square_indexes = [] while block_square_not_positioned: block_square_not_positioned = False square_orietation = random.choice(square_orientation_dic) print(square_orietation) index_to_start = random.randrange(63) print(index_to_start) intital_block_position = index_to_start currentIdx = intital_block_position if square_orietation == "UpperLeft": list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx-8) list_of_block_square_indexes.append(currentIdx-9) list_of_block_square_indexes.append(currentIdx-1) elif square_orietation == "UpperRight": list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx-8) list_of_block_square_indexes.append(currentIdx-7) list_of_block_square_indexes.append(currentIdx+1) elif square_orietation == 'LowerLeft': list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx+8) list_of_block_square_indexes.append(currentIdx+7) list_of_block_square_indexes.append(currentIdx-1) elif square_orietation == 'LowerRight': list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx+8) list_of_block_square_indexes.append(currentIdx+9) list_of_block_square_indexes.append(currentIdx+1) for i in list_of_block_square_indexes: if (i > 63) or (i < 0) or (i in currentlyoccupiedpositions): block_square_not_positioned = True if block_square_not_positioned: list_of_block_square_indexes = [] positions = list_of_block_square_indexes return positions def get_block_L_positions(): positions = [] l_orietation_dic = [ "DownDownLeft", "DownDownRight", "UpUpRight", "UpUpLeft", "LeftDownDown", "LeftUpUp", "RightDownDown", "RightUpUp", "UpLeftLeft", "UpRightRight", "DownRightRight", "DownLeftLeft", "LeftLeftUp", "RightRightUp", "RightRightDown", "LeftLeftDown" ] block_L_not_positioned = True list_of_block_L_indexes = [] while block_L_not_positioned: block_L_not_positioned = False l_orietation = random.choice(l_orietation_dic) print(l_orietation) index_to_start = random.randrange(63) print(index_to_start) intital_block_L_position = index_to_start currentIdx = intital_block_L_position if l_orietation == "DownDownLeft": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx-1) elif l_orietation == "DownDownRight": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+1) elif l_orietation == "UpUpRight": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx+1) elif l_orietation == "UpUpLeft": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-1) elif l_orietation == "LeftDownDown": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+8) elif l_orietation == "LeftUpUp": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-8) elif l_orietation == "RightDownDown": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+8) elif l_orietation == "RightUpUp": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-8) elif l_orietation == "UpLeftLeft": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-1) elif l_orietation == "UpRightRight": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-8) currentIdx -= 8 list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+1) elif l_orietation == "DownRightRight": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+1) elif l_orietation == "DownLeftLeft": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+8) currentIdx += 8 list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-1) elif l_orietation == "LeftLeftUp": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-8) elif l_orietation == "RightRightUp": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx-8) elif l_orietation == "RightRightDown": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+1) currentIdx += 1 list_of_block_L_indexes.append(currentIdx+8) elif l_orietation == "LeftLeftDown": list_of_block_L_indexes.append(currentIdx) list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx-1) currentIdx -= 1 list_of_block_L_indexes.append(currentIdx+8) for i in list_of_block_L_indexes: if i > 63 or i < 0: block_L_not_positioned = True if block_L_not_positioned: list_of_block_L_indexes = [] positions = list_of_block_L_indexes return positions def get_random_positions_for_blocks(): allpositions = [] dic_of_positions = {} for i in get_block_L_positions(): allpositions.append(i) dic_of_positions[i] = i for j in get_block_square_positions(dic_of_positions): allpositions.append(j) dic_of_positions[j] = j for x in get_block_line_positions(dic_of_positions): allpositions.append(x) dic_of_positions[x] = x for z in get_block_line_positions(dic_of_positions): allpositions.append(z) dic_of_positions[z] = z return allpositions def get_block_line_positions(currentlyoccupiedpositions): positions = [] line_orientation_dic = [ "Up", "Down", "Left", "Right" ] block_line_not_positioned = True list_of_block_square_indexes = [] while block_line_not_positioned: block_line_not_positioned = False line_orietation = random.choice(line_orientation_dic) print(line_orietation) index_to_start = random.randrange(63) print(index_to_start) intital_block_position = index_to_start currentIdx = intital_block_position if line_orietation == "Up": list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx-8) list_of_block_square_indexes.append(currentIdx-16) list_of_block_square_indexes.append(currentIdx-24) elif line_orietation == "Down": list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx+8) list_of_block_square_indexes.append(currentIdx+16) list_of_block_square_indexes.append(currentIdx+24) elif line_orietation == 'Left': list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx-1) list_of_block_square_indexes.append(currentIdx-2) list_of_block_square_indexes.append(currentIdx-3) elif line_orietation == 'Right': list_of_block_square_indexes.append(currentIdx) list_of_block_square_indexes.append(currentIdx+1) list_of_block_square_indexes.append(currentIdx+2) list_of_block_square_indexes.append(currentIdx+3) for i in list_of_block_square_indexes: if (i > 63) or (i < 0) or (i in currentlyoccupiedpositions): block_line_not_positioned = True if block_line_not_positioned: list_of_block_square_indexes = [] positions = list_of_block_square_indexes return positions

36.81

72

0.662139

1,311

11,043

5.125858

0.058734

0.096429

0.176786

0.121429

0.812946

0.781696

0.768899

0.760268

0

0.015187

0.266594

11,043

299

73

36.93311

0.814545

0

0.614754

0

0.042199

0

1

0.016393

false

0

0.004098

0

0.036885

0.02459

0

null

0

1

0

null

0

6

4fc9e8e3a8b5fd8bb22e8aee1521e1bbf2275aa0

39,313

py

Python

tests/test_qmock.py

fds-ajacobs/qmock-py

6c6e7d1d2e8e3be26b36b475d1c7ad6088615a23

[ "Apache-2.0" ]

null

tests/test_qmock.py

fds-ajacobs/qmock-py

6c6e7d1d2e8e3be26b36b475d1c7ad6088615a23

[ "Apache-2.0" ]

2

2020-01-23T23:51:29.000Z

2020-02-03T17:20:28.000Z

tests/test_qmock.py

fds-ajacobs/qmock-py

6c6e7d1d2e8e3be26b36b475d1c7ad6088615a23

[ "Apache-2.0" ]

1

2020-01-23T23:36:50.000Z

from collections import OrderedDict import signal import sys from threading import Thread import unittest import qmock from qmock._python_compat import get_thread_id, mock # arbitrary targets for qmock.patch() tests import datetime, json, xml.etree.ElementTree DATETIME_DATE = "datetime.date" JSON_LOADS = "json.loads" XML_ETREE_ELEMENTTREE = "xml.etree.ElementTree" PY2 = sys.version_info[0] < 3 class QMockErrorsInThreadsTests(unittest.TestCase): def test_str(self): error = qmock.QMockErrorsInThreads( [RuntimeError("foo"), ValueError("bar"), KeyError("baz")] ) self.assertEqual( str(error), "Unhandled QMock errors raised in other threads:" " [" + repr(RuntimeError("foo")) + ", " + repr(ValueError("bar")) + ", " + repr(KeyError("baz")) + "]" ) class patchTests(unittest.TestCase): def setUp(self): self._assert_no_patches() def tearDown(self): self._assert_no_patches() def _assert_no_patches(self): self._assert_datetime_is_not_patched() self._assert_json_is_not_patched() self._assert_xml_etree_is_not_patched() def _assert_datetime_is_not_patched(self): self.assertEqual( str(datetime.date(1, 2, 3)), "0001-02-03" ) def _assert_json_is_not_patched(self): self.assertEqual( json.loads("[1,2,3]"), [1, 2, 3] ) def _assert_xml_etree_is_not_patched(self): self.assertEqual( xml.etree.ElementTree.fromstring("<foo />").tag, "foo" ) def _force_unexpected_call_in_thread(self, qm): try: thread = Thread(target=qm.an_unknown_call) thread.start() # we expect the thread to die immediately because of an # UnexpectedCall. the alarms are an abundance of caution. signal.alarm(1) thread.join() signal.alarm(0) except BaseException as ex: self.fail("Thread setup caught: {0!r}".format(ex)) def _assert_thread_qmock_errors(self, errors_in_thread_error): """ QMockErrorsInThreads.errors should contain a single UnexpectedCall raised in a different thread. """ qmock_errors_from_threads = errors_in_thread_error.errors self.assertEqual(len(qmock_errors_from_threads), 1) qmock_error_tid, qmock_error = qmock_errors_from_threads[0] self.assertNotEqual(qmock_error_tid, get_thread_id()) self.assertIsInstance(qmock_error, qmock.UnexpectedCall) def _assert_patched_func_error(self, errors_in_thread_error, expected_func_error_type): """ in Python 3, when multiple exceptions are being handled at once, each exception has a __context__ which is the last exception raised before this one (or `None`, if this is the first exception in the current batch of active exceptions). so QMockErrorsInThreads.__context__ should be the exception raised by the function/scope being patched. """ if PY2: # Python 2 has no __context__ return patched_func_error = errors_in_thread_error.__context__ if expected_func_error_type is None: self.assertIsNone(patched_func_error) else: self.assertIsInstance(patched_func_error, expected_func_error_type) def test_empty_function_decorator_succeeds(self): @qmock.patch() def foo(qm): self._assert_no_patches() qm.call_queue.push(qmock.call.bar(), 5) self.assertEqual(qm.bar(), 5) foo() # no raise == success # a little silly because nothing is being patched, but just in case. def test_empty_function_decorator_cleans_up_on_func_exception(self): @qmock.patch() def foo(qm): self._assert_no_patches() raise RuntimeError("TEST") self.assertRaises(RuntimeError, foo) def test_empty_function_decorator_raises_on_exit_if_queue_not_empty(self): @qmock.patch() def foo(qm): self._assert_no_patches() qm.call_queue.push(qmock.call.bar(), 5) self.assertRaises(qmock.CallQueueNotEmpty, foo) def test_empty_function_decorator_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): @qmock.patch() def foo(qm): self._assert_no_patches() # would raise CallQueueNotEmpty if not handling RuntimeError qm.call_queue.push(qmock.call.bar(), 5) raise RuntimeError("TEST") self.assertRaises(RuntimeError, foo) def test_empty_function_decorator_raises_on_exit_if_errors_in_threads(self): @qmock.patch() def foo(qm): self._assert_no_patches() self._force_unexpected_call_in_thread(qm) with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_empty_function_decorator_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): @qmock.patch() def foo(qm): self._assert_no_patches() # raises QMockErrorsInThreads on top of RuntimeError self._force_unexpected_call_in_thread(qm) raise RuntimeError("TEST") with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, RuntimeError) def test_single_patch_function_decorator_succeeds(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) self.assertEqual(datetime.date(1, 2, 3), 7) self._assert_no_patches() foo() def test_single_patch_function_decorator_cleans_up_on_func_exception(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): raise ValueError("TEST") self._assert_no_patches() self.assertRaises(ValueError, foo) def test_single_patch_function_decorator_cleans_up_on_bad_patch(self): @qmock.patch(dt="datetime.BAD") def foo(qm): self.fail("This test function should not run.") self._assert_no_patches() self.assertRaises(AttributeError, foo) def test_single_patch_function_decorator_raises_on_exit_if_queue_not_empty(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) self._assert_no_patches() self.assertRaises(qmock.CallQueueNotEmpty, foo) def test_single_patch_function_decorator_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): # would raise CallQueueNotEmpty if not handling ValueError qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) raise ValueError("TEST") self._assert_no_patches() self.assertRaises(ValueError, foo) def test_single_patch_function_decorator_raises_on_exit_if_errors_in_threads(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): self._force_unexpected_call_in_thread(qm) self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_single_patch_function_decorator_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE) def foo(qm): # raises QMockErrorsInThreads on top of ValueError self._force_unexpected_call_in_thread(qm) raise ValueError("TEST") self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, ValueError) def test_multi_patch_function_decorator_succeeds(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(xml.etree.ElementTree.fromstring("<foo />"), "b") self.assertEqual(json.loads("[1,2,3]"), "c") self._assert_no_patches() foo() def test_multi_patch_function_decorator_cleans_up_on_func_exception(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): raise KeyError("TEST") self._assert_no_patches() self.assertRaises(KeyError, foo) def test_multi_patch_function_decorator_cleans_up_on_bad_patch(self): @qmock.patch(dt=DATETIME_DATE, json="json.BAD", et=XML_ETREE_ELEMENTTREE) def foo(qm): self.fail("This test function should not run.") self._assert_no_patches() self.assertRaises(AttributeError, foo) def test_multi_patch_function_decorator_raises_on_exit_if_queue_not_empty(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self._assert_no_patches() self.assertRaises(qmock.CallQueueNotEmpty, foo) def test_multi_patch_function_decorator_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): # would raise CallQueueNotEmpty if not handling KeyError qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") raise KeyError("TEST") self._assert_no_patches() self.assertRaises(KeyError, foo) def test_multi_patch_function_decorator_raises_on_exit_if_errors_in_threads(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): self._force_unexpected_call_in_thread(qm) self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_multi_patch_function_decorator_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE) def foo(qm): # raises QMockErrorsInThreads on top of KeyError self._force_unexpected_call_in_thread(qm) raise KeyError("TEST") self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, KeyError) def test_stacked_function_decorator_succeeds(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(xml.etree.ElementTree.fromstring("<foo />"), "b") self.assertEqual(json.loads("[1,2,3]"), "c") self._assert_no_patches() foo() def test_stacked_function_decorator_cleans_up_on_func_exception(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): raise IndexError("TEST") self._assert_no_patches() self.assertRaises(IndexError, foo) def test_stacked_function_decorator_cleans_up_on_bad_patch(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json="json.BAD") @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): self.fail("This test function should not run.") self._assert_no_patches() self.assertRaises(AttributeError, foo) def test_stacked_function_decorator_raises_on_exit_if_queue_not_empty(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self._assert_no_patches() self.assertRaises(qmock.CallQueueNotEmpty, foo) def test_stacked_function_decorator_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): # would raise CallQueueNotEmpty if not handling IndexError qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") raise IndexError("TEST") self._assert_no_patches() self.assertRaises(IndexError, foo) def test_stacked_function_decorator_raises_on_exit_if_errors_in_threads(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): self._force_unexpected_call_in_thread(qm) self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_stacked_function_decorator_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(json=JSON_LOADS) @qmock.patch(et=XML_ETREE_ELEMENTTREE) def foo(qm): # raises QMockErrorsInThreads on top of IndexError self._force_unexpected_call_in_thread(qm) raise IndexError("TEST") self._assert_no_patches() with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: foo() self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, IndexError) def test_class_decorator_only_patches_test_methods(self): @qmock.patch(dt=DATETIME_DATE) class Foo(object): fizz = "a" test_buzz = "b" def bar(foo_self): self._assert_no_patches() def test_baz(foo_self, qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) self.assertEqual(datetime.date(1, 2, 3), 7) self._assert_no_patches() f = Foo() self._assert_no_patches() self.assertEqual(f.fizz, "a") self._assert_no_patches() self.assertEqual(f.test_buzz, "b") self._assert_no_patches() f.bar() self._assert_no_patches() f.test_baz() def test_mixed_decorator_patches(self): @qmock.patch(dt=DATETIME_DATE, json=JSON_LOADS) class Foo(object): @qmock.patch(et=XML_ETREE_ELEMENTTREE) def test_mixed(foo_self, qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(xml.etree.ElementTree.fromstring("<foo />"), "b") self.assertEqual(json.loads("[1,2,3]"), "c") def test_no_cross_mix_between_methods(foo_self, qm): self._assert_xml_etree_is_not_patched() qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(json.loads("[1,2,3]"), "c") @qmock.patch(et="xml.etree.BAD") def test_bad_patch(foo_self, qm): self.fail("This test function should not run.") self._assert_no_patches() f = Foo() self._assert_no_patches() f.test_mixed() self._assert_no_patches() f.test_no_cross_mix_between_methods() self._assert_no_patches() self.assertRaises(AttributeError, f.test_bad_patch) def test_empty_context_manager_succeeds(self): with qmock.patch() as qm: self._assert_no_patches() qm.call_queue.push(qmock.call.bar(), 5) self.assertEqual(qm.bar(), 5) # a little silly because nothing is being patched, but just in case. def test_empty_context_manager_cleans_up_on_func_exception(self): with self.assertRaises(RuntimeError): with qmock.patch() as qm: self._assert_no_patches() raise RuntimeError("TEST") def test_empty_context_manager_raises_on_exit_if_queue_not_empty(self): with self.assertRaises(qmock.CallQueueNotEmpty): with qmock.patch() as qm: self._assert_no_patches() qm.call_queue.push(qmock.call.bar(), 5) def test_empty_context_manager_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): with self.assertRaises(RuntimeError): with qmock.patch() as qm: self._assert_no_patches() # would raise CallQueueNotEmpty if not handling RuntimeError qm.call_queue.push(qmock.call.bar(), 5) raise RuntimeError("TEST") def test_empty_context_manager_raises_on_exit_if_errors_in_threads(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch() as qm: self._assert_no_patches() self._force_unexpected_call_in_thread(qm) self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_empty_context_manager_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch() as qm: self._assert_no_patches() # raises QMockErrorsInThreads on top of RuntimeError self._force_unexpected_call_in_thread(qm) raise RuntimeError("TEST") self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, RuntimeError) def test_single_patch_context_manager_succeeds(self): with qmock.patch(dt=DATETIME_DATE) as qm: qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) self.assertEqual(datetime.date(1, 2, 3), 7) def test_single_patch_context_manager_cleans_up_on_func_exception(self): with self.assertRaises(ValueError): with qmock.patch(dt=DATETIME_DATE) as qm: raise ValueError("TEST") def test_single_patch_context_manager_cleans_up_on_bad_patch(self): with self.assertRaises(AttributeError): with qmock.patch(dt="datetime.BAD") as qm: self.fail("This context should not be entered.") def test_single_patch_context_manager_raises_on_exit_if_queue_not_empty(self): with self.assertRaises(qmock.CallQueueNotEmpty): with qmock.patch(dt=DATETIME_DATE) as qm: qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) def test_single_patch_context_manager_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): with self.assertRaises(ValueError): with qmock.patch(dt=DATETIME_DATE) as qm: # would raise CallQueueNotEmpty if not handling ValueError qm.call_queue.push(qmock.call.dt(1, 2, 3), 7) raise ValueError("TEST") def test_single_patch_context_manager_raises_on_exit_if_errors_in_threads(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch(dt=DATETIME_DATE) as qm: self._force_unexpected_call_in_thread(qm) self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_single_patch_context_manager_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch(dt=DATETIME_DATE) as qm: # raises QMockErrorsInThreads on top of ValueError self._force_unexpected_call_in_thread(qm) raise ValueError("TEST") self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, ValueError) def test_multi_patch_function_decorator_succeeds(self): with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(xml.etree.ElementTree.fromstring("<foo />"), "b") self.assertEqual(json.loads("[1,2,3]"), "c") def test_multi_patch_context_manager_cleans_up_on_func_exception(self): with self.assertRaises(KeyError): with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: raise KeyError("TEST") def test_multi_patch_context_manager_cleans_up_on_bad_patch(self): with self.assertRaises(AttributeError): with qmock.patch( dt=DATETIME_DATE, json="json.BAD", et=XML_ETREE_ELEMENTTREE ) as qm: self.fail("This context should not be entered.") def test_multi_patch_context_manager_raises_on_exit_if_queue_not_empty(self): with self.assertRaises(qmock.CallQueueNotEmpty): with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") def test_multi_patch_context_manager_doesnt_raise_on_exit_if_queue_not_empty_and_func_exception(self): with self.assertRaises(KeyError): with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: # would raise CallQueueNotEmpty if not handling KeyError qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.et.fromstring("<foo />"), "b") qm.call_queue.push(qmock.call.json("[1,2,3]"), "c") raise KeyError("TEST") def test_multi_patch_context_manager_raises_on_exit_if_errors_in_threads(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: self._force_unexpected_call_in_thread(qm) self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, None) def test_multi_patch_context_manager_still_raises_on_exit_if_errors_in_threads_and_func_exception(self): with self.assertRaises(qmock.QMockErrorsInThreads) as assertion: with qmock.patch( dt=DATETIME_DATE, json=JSON_LOADS, et=XML_ETREE_ELEMENTTREE ) as qm: # raises QMockErrorsInThreads on top of KeyError self._force_unexpected_call_in_thread(qm) raise KeyError("TEST") self._assert_thread_qmock_errors(assertion.exception) self._assert_patched_func_error(assertion.exception, KeyError) # # degenerate cases # def test_duplicate_patch_succeeds(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(dt=DATETIME_DATE) def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") self.assertEqual(datetime.date(1, 2, 3), "a") self._assert_no_patches() foo() # this also indirectly tests that stacked patches are applied strictly # bottom-up. def test_same_patch_on_different_attr_is_weird(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(date=DATETIME_DATE) def foo(qm): # this is the wrong call to expect because the last patch for # datetime.date was assigned to the `dt` attr qm.call_queue.push(qmock.call.date(1, 2, 3), "a") with self.assertRaises(qmock.UnexpectedCall): datetime.date(1, 2, 3) qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") self.assertEqual(datetime.date(1, 2, 3), "a") self._assert_no_patches() foo() def test_different_patch_on_same_attr_is_also_weird(self): @qmock.patch(dt=DATETIME_DATE) @qmock.patch(dt="datetime.datetime") def foo(qm): qm.call_queue.push(qmock.call.dt(1, 2, 3), "a") qm.call_queue.push(qmock.call.dt(4, 5, 6), "b") qm.call_queue.push(qmock.call.dt(7, 8, 9), "c") self.assertEqual(datetime.date(1, 2, 3), "a") self.assertEqual(datetime.datetime(4, 5, 6), "b") self.assertEqual(datetime.date(7, 8, 9), "c") self._assert_no_patches() foo() class QMockTests(unittest.TestCase): def test_root_assigned_attributes(self): qm = qmock.QMock() qm.foo = 5 self.assertIs(qm.foo, 5) # retained across accesses self.assertIsInstance(qm.foo, int) self.assertRaises(TypeError, qm.foo) # not callable def test_root_generated_attributes(self): qm = qmock.QMock() self.assertIsNot(qm.foo, qm.baz) self.assertIs(qm.foo, qm.foo) # retained across accesses self.assertIsInstance(qm.foo, qmock._qmock._CallProxy) with self.assertRaises(qmock.UnexpectedCall): qm.foo() # empty CallQueue qm.call_queue.push(qmock.call.foo(), 5) self.assertIs(qm.foo(), 5) with self.assertRaises(qmock.UnexpectedCall): qm.foo() # empty CallQueue def test_nested_assigned_attributes(self): qm = qmock.QMock() qm.foo.bar = 5 self.assertIs(qm.foo.bar, 5) # retained across accesses self.assertIsInstance(qm.foo.bar, int) self.assertRaises(TypeError, qm.foo.bar) # not callable self.assertIsNot(qm.foo, qm.baz) self.assertIs(qm.foo, qm.foo) # retained across accesses self.assertIsInstance(qm.foo, qmock._qmock._CallProxy) with self.assertRaises(qmock.UnexpectedCall): qm.foo() # empty CallQueue def test_nested_generated_attributes(self): qm = qmock.QMock() self.assertIsNot(qm.foo.bar, qm.foo.baz) self.assertIsNot(qm.foo.bar, qm.baz.bar) self.assertIs(qm.foo.bar, qm.foo.bar) # retained across accesses self.assertIsInstance(qm.foo.bar, qmock._qmock._CallProxy) with self.assertRaises(qmock.UnexpectedCall): qm.foo.bar() # empty CallQueue self.assertIsNot(qm.foo, qm.baz) self.assertIs(qm.foo, qm.foo) # retained across accesses self.assertIsInstance(qm.foo, qmock._qmock._CallProxy) with self.assertRaises(qmock.UnexpectedCall): qm.foo() # empty CallQueue qm.call_queue.push(qmock.call.foo.bar(), 5) self.assertIs(qm.foo.bar(), 5) with self.assertRaises(qmock.UnexpectedCall): qm.foo.bar() # empty CallQueue def test_assigned_attributes_are_attached(self): qm = qmock.QMock() m = mock.Mock() qm.foo = m with self.assertRaises(qmock.UnexpectedCall): m() def test_root_magic_methods(self): qm = qmock.QMock() with self.assertRaises(qmock.UnexpectedCall): str(qm) # empty CallQueue qm.call_queue.push(qmock.call.__getattr__("__str__")(qm), "test") self.assertEqual(str(qm), "test") with self.assertRaises(qmock.UnexpectedCall): str(qm) # empty CallQueue def test_nested_magic_methods(self): qm = qmock.QMock() with self.assertRaises(qmock.UnexpectedCall): qm.foo < 5 # empty CallQueue qm.call_queue.push(qmock.call.foo.__getattr__("__lt__")(qm.foo, 5), "test") self.assertEqual((qm.foo < 5), "test") with self.assertRaises(qmock.UnexpectedCall): qm.foo < 5 # empty CallQueue def test_magic_methods_are_always_the_same_object(self): qm = qmock.QMock() method = qm.__len__ self.assertIs(method, qm.__len__) self.assertIs(method, qm.__len__) self.assertIs(method, qm.__len__) def test_magic_methods_are_unique(self): qm = qmock.QMock() self.assertIsNot(qm.__len__, qm.foo.__len__) self.assertIsNot(qm.__len__, qm.bar.__len__) self.assertIsNot(qm.foo.__len__, qm.bar.__len__) qm.call_queue.assert_empty() qm.call_queue.push(qmock.call.__getattr__("__len__")(qm), 1) qm.call_queue.push(qmock.call.foo.__getattr__("__len__")(qm.foo), 2) qm.call_queue.push(qmock.call.bar.__getattr__("__len__")(qm.bar), 3) qm.call_queue.push(qmock.call.bar.__getattr__("__len__")(qm.bar), 4) with self.assertRaises(qmock.UnexpectedCall): len(qm.foo) # wrong call; expected len(qm) self.assertEqual(len(qm.foo), 2) with self.assertRaises(qmock.UnexpectedCall): len(qm.foo) # wrong call; expected len(qm.bar) self.assertEqual(len(qm.bar), 4) qm.call_queue.assert_empty() def test_can_be_a_context_manager(self): qm = qmock.QMock() qm.call_queue.assert_empty() with self.assertRaises(qmock.UnexpectedCall): with qm as foo: # empty CallQueue pass qm.call_queue.assert_empty() qm.call_queue.push(qmock.call.__getattr__("__enter__")(qm), qm.foo) qm.call_queue.push(qmock.call.foo(), 7357) qm.call_queue.push(qmock.call.__getattr__("__exit__")(qm, None, None, None), None) with qm as foo: self.assertEqual(foo(), 7357) qm.call_queue.assert_empty() def test_mock_calls_returns_proxy(self): qm = qmock.QMock() self.assertIsInstance(qm.mock_calls, qmock._qmock._MockCallsProxy) def test_eq(self): alpha = qmock.QMock() bravo = qmock.QMock() self.assertTrue(alpha == alpha) self.assertTrue(bravo == bravo) self.assertFalse(alpha == bravo) self.assertFalse(bravo == alpha) def test_is_callable(self): qm = qmock.QMock() with self.assertRaises(qmock.UnexpectedCall): qm() # empty CallQueue qm.call_queue.push(qmock.call(), 5) self.assertIs(qm(), 5) def test_mock_return_assigned_attributes(self): qm = qmock.QMock() qm.foo = 5 self.assertIs( qm.mock_return(qmock.call.foo), 5 ) qm = qmock.QMock() qm.foo.return_value = 6 self.assertIs( qm.mock_return(qmock.call.foo()), 6 ) qm = qmock.QMock() qm.return_value = 7 self.assertIs( qm.mock_return(qmock.call()), 7 ) qm = qmock.QMock() qm.return_value.foo = 8 self.assertIs( qm.mock_return(qmock.call().foo), 8 ) qm = qmock.QMock() qm.return_value.foo.return_value.bar.return_value.baz.barf.return_value = 9 self.assertIs( qm.mock_return(qmock.call(x=1).foo(y=2).bar(5).baz.barf(z={6: 7}, w=8)), 9 ) def test_mock_return_generated_attributes(self): qm = qmock.QMock() self.assertIs( qm.mock_return(qmock.call.foo), qm.foo ) self.assertIs( qm.mock_return(qmock.call.foo()), qm.foo.return_value ) self.assertIs( qm.mock_return(qmock.call()), qm.return_value ) self.assertIs( qm.mock_return(qmock.call().foo), qm.return_value.foo ) self.assertIs( qm.mock_return(qmock.call(x=1).foo(y=2).bar(5).baz.barf(z={6: 7}, w=8)), qm.return_value.foo.return_value.bar.return_value.baz.barf.return_value ) def test_mock_return_null_call(self): qm = qmock.QMock() self.assertRaises( AttributeError, qm.mock_return, qmock.call ) class CallQueueTests(unittest.TestCase): def test_push_attribute_call(self): qm = qmock.QMock() cq = qm.call_queue self.assertRaises( qmock.BadCall, cq.push, qmock.call.foo, "bar" ) self.assertEqual(len(cq.pop_errors), 0) def test_push_function_call(self): qm = qmock.QMock() cq = qm.call_queue self.assertEqual(len(cq._queue), 0) cq.push(qmock.call.foo(), "bar") self.assertEqual( tuple( (expected_call, self._copy_mock_side_effect(mock_result)) for expected_call, mock_result in cq._queue ), ( (qmock.call.foo(), ("bar",)), ) ) self.assertEqual(len(cq._queue), 1) self.assertEqual(qm.foo(), "bar") cq.assert_empty() self.assertEqual(len(cq.pop_errors), 0) def test_push_all_attribute_call(self): qm = qmock.QMock() cq = qm.call_queue self.assertRaises( qmock.BadCall, cq.push_all, qmock.call(x=1).foo(y=2).bar(5).baz.barf, 10 ) self.assertEqual(len(cq.pop_errors), 0) def test_push_all_function_call(self): qm = qmock.QMock() cq = qm.call_queue cq.push_all(qmock.call(x=1).foo(y=2).bar(5).baz.barf(z={6: 7}, w=8), 10) self.assertEqual( tuple( (expected_call, self._copy_mock_side_effect(mock_result)) for expected_call, mock_result in cq._queue ), ( ( qmock.call(x=1), (qm.return_value,) ), ( qmock.call(x=1).foo(y=2), (qm.return_value.foo.return_value,) ), ( qmock.call(x=1).foo(y=2).bar(5), (qm.return_value.foo.return_value.bar.return_value,) ), ( qmock.call(x=1).foo(y=2).bar(5).baz.barf(z={6: 7}, w=8), (10,) ) ) ) self.assertEqual(len(cq._queue), 4) self.assertEqual(qm(x=1).foo(y=2).bar(5).baz.barf(z={6: 7}, w=8), 10) cq.assert_empty() self.assertEqual(len(cq.pop_errors), 0) def test_pop_value_result(self): qm = qmock.QMock() cq = qm.call_queue cq.push(qmock.call.foo(), 7357) self.assertEqual(cq._pop(qmock.call.foo()), 7357) cq.assert_empty() self.assertEqual(len(cq.pop_errors), 0) def test_pop_exception_result(self): qm = qmock.QMock() cq = qm.call_queue cq.push(qmock.call.foo(), ValueError("test")) with self.assertRaises(ValueError) as assertion: cq._pop(qmock.call.foo()) self.assertEqual(str(assertion.exception), "test") cq.assert_empty() self.assertEqual(len(cq.pop_errors), 0) def test_pop_raises_when_empty(self): qm = qmock.QMock() cq = qm.call_queue self.assertRaises(qmock.UnexpectedCall, cq._pop, qmock.call.foo()) self.assertEqual(len(cq.pop_errors), 1) record = cq.pop_errors[0] self.assertEqual(record.thread_id, get_thread_id()) self.assertIsInstance(record.error, qmock.UnexpectedCall) self.assertEqual( str(record.error), "Queue is empty. call: call.foo()" ) def test_pop_raises_when_call_doesnt_match_expectation(self): qm = qmock.QMock() cq = qm.call_queue cq.push(qmock.call.foo(), 7357) self.assertRaises(qmock.UnexpectedCall, cq._pop, qmock.call.not_foo()) self.assertEqual(len(cq.pop_errors), 1) record = cq.pop_errors[0] self.assertEqual(record.thread_id, get_thread_id()) self.assertIsInstance(record.error, qmock.UnexpectedCall) self.assertEqual( str(record.error), "Call does not match expectation. actual: call.not_foo(); expected: call.foo()" ) def test_assert_empty(self): qm = qmock.QMock() cq = qm.call_queue cq.assert_empty() cq.push(qmock.call.foo(), "bar") self.assertRaises(qmock.CallQueueNotEmpty, cq.assert_empty) cq._pop(qmock.call.foo()) cq.assert_empty() self.assertEqual(len(cq.pop_errors), 0) def _copy_mock_side_effect(self, m): """ mock.Mock.side_effect is stored as a <tupleiterator>, so iterating consumes it. so we'll consume it, store a copy, re-populate it, and return the copy """ side_effect = tuple(m.side_effect) m.side_effect = side_effect return side_effect

36.266605

112

0.631267

4,969

39,313

4.697122

0.057758

0.035476

0.03629

0.040488

0.843273

0.809854

0.784619

0.752442

0.729692

0.703985

0

0.010986

0.261389

39,313

1,083

113

36.300092

0.792816

0.058403

0

0.633005

0

0.027562

0.000571

0

0.331281

1

0.151478

false

0.001232

0.009852

0

0.171182

0

null

0

1

0

null

0

6

4fcf0cd5093a44923cd6237b41fe34b181ee1bef

10,280

py

Python

src/explanation/views.py

fleur101/predict-python

d40c876d919232bbb77904e050b182c875bc36fa

[ "MIT" ]

12

2018-06-27T08:09:18.000Z

2021-10-10T22:19:04.000Z

src/explanation/views.py

fleur101/predict-python

d40c876d919232bbb77904e050b182c875bc36fa

[ "MIT" ]

17

2018-06-12T17:36:11.000Z

2020-11-16T21:23:22.000Z

src/explanation/views.py

fleur101/predict-python

d40c876d919232bbb77904e050b182c875bc36fa

[ "MIT" ]

16

2018-08-02T14:40:17.000Z

2021-11-12T12:28:46.000Z

from rest_framework import status from rest_framework.decorators import api_view from rest_framework.response import Response from src.explanation.explanation import explanation, explanation_temporal_stability from src.explanation.models import Explanation, ExplanationTypes from src.jobs.models import Job import pandas as pd @api_view(['GET']) def get_lime(request, pk, explanation_target): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.LIME.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'lime' not in exp.results: exp.results.update({'lime': dict()}) if explanation_target in exp.results['lime']: return Response(exp.results['lime'][explanation_target], status=200) else: error, result = explanation(exp.id, explanation_target) exp.results['lime'].update({explanation_target: result}) exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) @api_view(['GET']) def get_lime_temporal_stability(request, pk, explanation_target=None): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.LIME.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'lime_temporal' not in exp.results: exp.results.update({'lime_temporal': dict()}) if explanation_target: if explanation_target in exp.results['lime_temporal']: return Response(exp.results['lime_temporal'][explanation_target], status=200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) exp.results['lime_temporal'].update({explanation_target: result}) exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) elif 'no_target' in explanation_target: return Response(exp.results['lime_temporal']['no_target'], status=200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) exp.results['lime_temporal'].update({'no_target': result}) exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) @api_view(['GET']) def get_shap_temporal_stability(request, pk, explanation_target=None): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.SHAP.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'shap_temporal' not in exp.results: exp.results.update({'shap_temporal': dict()}) if explanation_target: if explanation_target in exp.results['shap_temporal']: return Response(exp.results['shap_temporal'][explanation_target], status=200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) #exp.results['shap_temporal'].update({explanation_target: pd.Series(result).to_json(orient='values')}) #exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) elif 'no_target' in explanation_target: return Response(exp.results['shap_temporal']['no_target'], status=200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) #exp.results['shap_temporal'].update({'no_target': pd.Series(result).to_json(orient='values')}) #exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) @api_view(['GET']) def get_temporal_stability(request, pk, explanation_target=None): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.TEMPORAL_STABILITY.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'temporal' not in exp.results: exp.results.update({'temporal': dict()}) if explanation_target: if explanation_target in exp.results['temporal']: return Response(pd.read_json(exp.results['temporal'][explanation_target], typ='series', orient='records'), status = 200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) exp.results['temporal'].update({explanation_target: result}) exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) elif 'no_target' in explanation_target: return Response(exp.results['temporal']['no_target'], status=200) else: error, result = explanation_temporal_stability(exp.id, explanation_target=explanation_target) exp.results['temporal'].update({'no_target': result}) exp.save() if error == 'True': return Response({'error': 'Explanation Target cannot be greater than ' + str(result)}, status=status.HTTP_416_REQUESTED_RANGE_NOT_SATISFIABLE) else: return Response(result, status=200) @api_view(['GET']) def get_shap(request, pk, explanation_target, prefix_target): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.SHAP.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'shap' not in exp.results: exp.results.update({'shap': dict()}) if explanation_target not in exp.results['shap']: exp.results['shap'] = {explanation_target: dict()} if explanation_target in exp.results['shap'] and prefix_target in exp.results['shap'][explanation_target].keys(): return Response(pd.read_json(exp.results['shap'][explanation_target][prefix_target], typ='series', orient='records'), status=200) else: result = explanation(exp.id, explanation_target, prefix_target) exp.results['shap'][explanation_target].update({prefix_target: pd.Series(result).to_json(orient='values')}) exp.save() return Response(result, status=200) @api_view(['GET']) def get_skater(request, pk): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.SKATER.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'skater' in exp.results: return Response(exp.results['skater'], status=200) else: result = explanation(exp.id, explanation_target = None) exp.results['skater'] = result exp.save() return Response(result, status=200) @api_view(['GET']) def get_ice(request, pk, explanation_target): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.ICE.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'ice' not in exp.results: exp.results.update({'ice': dict()}) if explanation_target in exp.results['ice']: return Response(exp.results['ice'][explanation_target], status=200) else: result = explanation(exp.id, explanation_target) exp.results['ice'].update({explanation_target: result}) exp.save() return Response(result, status=200) @api_view(['GET']) def get_cmfeedback(request, pk, top_k): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.CMFEEDBACK.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() result = explanation(exp.id, int(top_k)) return Response(result, status=200) @api_view(['POST']) def get_retrain(request, pk): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.RETRAIN.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() target = request.data result = explanation(exp.id, target) return Response(result, status=200) @api_view(['GET']) def get_anchor(request, pk): job = Job.objects.filter(pk=pk)[0] exp, _ = Explanation.objects.get_or_create(type=ExplanationTypes.ANCHOR.value, split=job.split, predictive_model=job.predictive_model, job=job) exp.save() if 'anchor' in exp.results: return Response(exp.results['anchor'], status=200) else: result = explanation(exp.id, explanation_target=None) exp.results['anchor'] = result exp.save() return Response(result, status=200)

42.833333

137

0.643872

1,199

10,280

5.341952

0.071726

0.151288

0.056206

0.052771

0.892116

0.86292

0.845589

0.794379

0.733958

0.717721

0

0.013158

0.238521

10,280

239

138

43.012552

0.805059

0.020914

0

0.617801

0

0.080211

0

1

0.052356

false

0

0.036649

0

0.251309

0

null

0

1

0

null

0

6

4fd0caaf9300b1b12e193f81be84cbbd50b3eab5

7,430

py

Python

tests/test_plot.py

davebulaval/python2latex

da35bb8260e13d29dde5c81e363be2fc43abeba4

[ "MIT" ]

null

tests/test_plot.py

davebulaval/python2latex

da35bb8260e13d29dde5c81e363be2fc43abeba4

[ "MIT" ]

null

tests/test_plot.py

davebulaval/python2latex

da35bb8260e13d29dde5c81e363be2fc43abeba4

[ "MIT" ]

null

import os import shutil from inspect import cleandoc from python2latex.color import Color from python2latex.document import Document from python2latex.plot import Plot, LinePlot, MatrixPlot, _Plot class TestPlot: def teardown(self): _Plot.plot_count = 0 def test_default_plot(self): assert Plot(plot_name='plot_test').build() == cleandoc(r''' \begin{figure}[h!] \centering \begin{tikzpicture} \begin{axis}[grid style={dashed,gray!50}, axis y line*=left, axis x line*=bottom, every axis plot/.append style={line width=1.25pt, mark size=0pt}, width=.8\textwidth, height=.45\textwidth, grid=major] \end{axis} \end{tikzpicture} \end{figure} ''') os.remove('plot_test.csv') def test_add_plot_with_legend(self): plot = Plot(plot_name='plot_test') plot.add_plot(list(range(10)), list(range(10)), 'red', legend='Legend', line_width='2pt') assert plot.build() == cleandoc(r''' \begin{figure}[h!] \centering \begin{tikzpicture} \begin{axis}[grid style={dashed,gray!50}, axis y line*=left, axis x line*=bottom, every axis plot/.append style={line width=1.25pt, mark size=0pt}, width=.8\textwidth, height=.45\textwidth, grid=major] \addplot[red, line width=2pt] table[x=x0, y=y0, col sep=comma]{./plot_test.csv}; \addlegendentry{Legend}; \end{axis} \end{tikzpicture} \end{figure} ''') os.remove('plot_test.csv') def test_add_plot_without_legend(self): plot = Plot(plot_name='plot_test') plot.add_plot(list(range(10)), list(range(10)), 'red', line_width='2pt') assert plot.build() == cleandoc(r''' \begin{figure}[h!] \centering \begin{tikzpicture} \begin{axis}[grid style={dashed,gray!50}, axis y line*=left, axis x line*=bottom, every axis plot/.append style={line width=1.25pt, mark size=0pt}, width=.8\textwidth, height=.45\textwidth, grid=major] \addplot[red, forget plot, line width=2pt] table[x=x0, y=y0, col sep=comma]{./plot_test.csv}; \end{axis} \end{tikzpicture} \end{figure} ''') os.remove('plot_test.csv') def test_add_plot_with_color_obj(self): plot = Plot(plot_name='plot_test') color = Color(.1, .2, .3, 'spam') plot.add_plot(list(range(10)), list(range(10)), color, legend='Legend', line_width='2pt') assert plot.build() == cleandoc(r''' \begin{figure}[h!] \centering \begin{tikzpicture} \begin{axis}[grid style={dashed,gray!50}, axis y line*=left, axis x line*=bottom, every axis plot/.append style={line width=1.25pt, mark size=0pt}, width=.8\textwidth, height=.45\textwidth, grid=major] \addplot[spam, line width=2pt] table[x=x0, y=y0, col sep=comma]{./plot_test.csv}; \addlegendentry{Legend}; \end{axis} \end{tikzpicture} \end{figure} ''') os.remove('plot_test.csv') def test_save_csv_to_right_path(self): filepath = './some_doc_path/' plotpath = filepath + 'plot_path/' plot_name = 'plot_name' plot = Plot([1, 2, 3], [1, 2, 3], plot_name=plot_name, plot_path=plotpath) plot.build() assert os.path.exists(plotpath + plot_name + '.csv') shutil.rmtree(filepath) def test_build_pdf_to_other_relative_path(self): filepath = './some_doc_path/' plotpath = filepath + 'plot_path/' doc_name = 'Doc name' plot_name = 'plot_name' doc = Document(doc_name, filepath=filepath) plot = doc.new(Plot([1, 2, 3], [1, 2, 3], plot_name=plot_name, plot_path=plotpath)) try: doc.build(show_pdf=False) assert os.path.exists(filepath + doc_name + '.tex') assert os.path.exists(filepath + doc_name + '.pdf') assert os.path.exists(plotpath + plot_name + '.csv') finally: shutil.rmtree('./some_doc_path/') def test_add_matrix_plot(self): plot = Plot(plot_name='matrix_plot_test', grid=False, lines=False) plot.add_matrix_plot(list(range(10)), list(range(10)), [[i for i in range(10)] for _ in range(10)]) assert plot.build() == cleandoc(r''' \begin{figure}[h!] \centering \begin{tikzpicture} \begin{axis}[grid style={dashed,gray!50}, axis y line*=left, axis x line*=bottom, colorbar, every axis plot/.append style={line width=0pt, mark size=0pt}, width=.8\textwidth, height=.45\textwidth, grid=none] \addplot[matrix plot*, point meta=explicit, mesh/rows=10, mesh/cols=10] table[x=x0, y=y0, meta=z0, col sep=comma]{./matrix_plot_test.csv}; \end{axis} \end{tikzpicture} \end{figure} ''') os.remove('matrix_plot_test.csv') def test_build_pdf_with_matrix_plot(self): filepath = './some_doc_path/' plotpath = filepath + 'plot_path/' doc_name = 'Doc name' plot_name = 'plot_name' doc = Document(doc_name, filepath=filepath) X = list(range(10)) Y = list(range(10)) Z = [[i for i in range(10)] for _ in range(10)] plot = doc.new(Plot(plot_name=plot_name, plot_path=plotpath, grid=False, lines=False, enlargelimits='false')) plot.add_matrix_plot(X, Y, Z) try: doc.build(show_pdf=False) assert os.path.exists(filepath + doc_name + '.tex') assert os.path.exists(filepath + doc_name + '.pdf') assert os.path.exists(plotpath + plot_name + '.csv') finally: shutil.rmtree('./some_doc_path/') class TestLinePlot: def teardown(self): _Plot.plot_count = 0 def test_build_with_legend(self): lineplot = LinePlot([1, 2, 3], [4, 5, 6], 'red', 'dashed', legend='Legend', line_width='2pt') lineplot.plot_filepath = './some/path/file.csv' assert lineplot.build() == cleandoc(r""" \addplot[red, dashed, line width=2pt] table[x=x0, y=y0, col sep=comma]{./some/path/file.csv}; \addlegendentry{Legend}; """) def test_build_without_legend(self): lineplot = LinePlot([1, 2, 3], [4, 5, 6], 'red', 'dashed', line_width='2pt') lineplot.plot_filepath = './some/path/file.csv' assert lineplot.build() == cleandoc(r""" \addplot[red, dashed, forget plot, line width=2pt] table[x=x0, y=y0, col sep=comma]{./some/path/file.csv}; """) def test_lineplot_id_number_correctly_increments(self): l1 = LinePlot([1], [2]) l2 = LinePlot([1], [2]) l3 = LinePlot([1], [2]) assert l1.id_number == 0 assert l2.id_number == 1 assert l3.id_number == 2 class TestMatrixPlot: def teardown(self): _Plot.plot_count = 0 def test_build_with_legend(self): lineplot = MatrixPlot([1, 2, 3], [4, 5, 6], [list(range(3)) for _ in range(3)]) lineplot.plot_filepath = './some/path/file.csv' assert lineplot.build() == cleandoc(r""" \addplot[matrix plot*, point meta=explicit, mesh/rows=3, mesh/cols=3] table[x=x0, y=y0, meta=z0, col sep=comma]{./some/path/file.csv}; """)

43.450292

219

0.591925

993

7,430

4.289023

0.127895

0.037568

0.039446

0.014792

0.822259

0.791735

0.790326

0.758864

0.732097

0.715896

0

0.028799

0.256931

7,430

170

220

43.705882

0.742619

0

0.649007

0

0.07947

0.451952

0.068641

0

0.119205

1

0.099338

false

0

0.039735

0

0.15894

0

null

0

1

0

null

0

6

8c6a92c14a6d1bdc3e7e8bd7a9571a056c234662

159

py

Python

backend/posts/admin.py

Soumithri/website

de813cfd20f3b9e28b92c089524f998956ced3d9

[ "MIT" ]

2

2019-08-07T03:28:51.000Z

2019-08-07T07:32:25.000Z

backend/posts/admin.py

Soumithri/website

de813cfd20f3b9e28b92c089524f998956ced3d9

[ "MIT" ]

7

2019-12-04T23:54:04.000Z

2022-02-10T10:57:58.000Z

backend/posts/admin.py

Soumithri/website

de813cfd20f3b9e28b92c089524f998956ced3d9

[ "MIT" ]

null

from django.contrib import admin from .models import Post, Project, Author admin.site.register(Post) admin.site.register(Project) admin.site.register(Author)

22.714286

41

0.811321

23

159

5.608696

0.478261

0.209302

0.395349

0

0.08805

159

6

42

26.5

0.889655

0

1

0

true

0

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

8ce4762487e38a171d2873f8dd9b3608a24a3448

12,719

py

Python

apps/gsuite/mail_syncer/tests/apiclient_utils_tests.py

Kpaubert/onlineweb4

9ac79f163bc3a816db57ffa8477ea88770d97807

[ "MIT" ]

32

2017-02-22T13:38:38.000Z

2022-03-31T23:29:54.000Z

apps/gsuite/mail_syncer/tests/apiclient_utils_tests.py

Kpaubert/onlineweb4

9ac79f163bc3a816db57ffa8477ea88770d97807

[ "MIT" ]

694

2017-02-15T23:09:52.000Z

2022-03-31T23:16:07.000Z

apps/gsuite/mail_syncer/tests/apiclient_utils_tests.py

Kpaubert/onlineweb4

9ac79f163bc3a816db57ffa8477ea88770d97807

[ "MIT" ]

35

2017-09-02T21:13:09.000Z

2022-02-21T11:30:30.000Z

from django.conf import settings from django.contrib.auth.models import Group from django.test import TestCase, override_settings from django_dynamic_fixture import G from googleapiclient.errors import HttpError from mock import patch from apps.authentication.models import OnlineUser from apps.gsuite.mail_syncer.tests.test_utils import create_http_error from apps.gsuite.mail_syncer.utils import ( check_amount_of_members_ow4_g_suite, get_appropriate_g_suite_group_names_for_user, get_excess_groups_for_user, get_excess_users_in_g_suite, get_g_suite_groups_for_user, get_g_suite_users_for_group, get_missing_g_suite_group_names_for_user, get_missing_ow4_users_for_g_suite, get_ow4_users_for_group, insert_email_into_g_suite_group, insert_ow4_user_into_g_suite_group, ) class GSuiteAPIUtilsTestCase(TestCase): """Tests for ow4-side utils of G Suite app, like "get excess groups for user".""" def setUp(self): self.domain = "example.org" self.group = "dotkom" @patch("logging.Logger.info") @patch("apps.gsuite.mail_syncer.utils.setup_g_suite_client", autospec=True) def test_insert_ow4_user_into_g_suite_group(self, mocked_insert, mocked_logger): user = G(OnlineUser, online_mail="firstname.lastname") group_email = self.group + "@" + self.domain ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = True ow4_gsuite_sync["ENABLE_INSERT"] = True mocked_insert.return_value.members.return_value.insert.return_value.execute.return_value = { "email": user.online_mail } with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): resp = insert_email_into_g_suite_group( self.domain, self.group, user.online_mail ) self.assertEqual(user.online_mail, resp.get("email")) mocked_logger.assert_called_with( f"Inserting '{user.online_mail}' into G Suite group '{group_email}'.", extra={"email": user.online_mail, "group": group_email}, ) @patch("logging.Logger.error") def test_insert_ow4_user_into_g_suite_group_no_online_mail(self, mocked_logger): user = G(OnlineUser, online_mail=None) insert_ow4_user_into_g_suite_group(self.domain, self.group, user) mocked_logger.assert_called_with( f"OW4 User '{user}' ({user.pk}) missing Online email address! " f"(current: '{user.online_mail}')", extra={"user": user, "group": self.group}, ) def test_get_ow4_users_for_group(self): group = G(Group) user1 = G(OnlineUser) user2 = G(OnlineUser) user3 = G(OnlineUser) ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user1, user2, user3) resp = get_ow4_users_for_group(group.name) self.assertIn(user1, resp) self.assertIn(user2, resp) self.assertIn(user3, resp) def test_get_appropriate_g_suite_group_names_for_user(self): user = G(OnlineUser) G(Group, name="appkom") dotkom = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): dotkom.user_set.add(user) groups = get_appropriate_g_suite_group_names_for_user(self.domain, user) self.assertEqual(1, len(groups)) self.assertIn(dotkom.name.lower(), groups) def test_check_amount_of_members_equal(self): g_suite_members = [{"email": "test@example.org"}] user = G(OnlineUser) group = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user) self.assertTrue( check_amount_of_members_ow4_g_suite( g_suite_members, group.user_set.all(), quiet=False ) ) @patch("logging.Logger.debug") def test_check_amount_of_members_ow4_dominates(self, mocked_logger): g_suite_members = [{"email": "test@example.org"}] user = G(OnlineUser) user2 = G(OnlineUser) group = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user) group.user_set.add(user2) self.assertFalse( check_amount_of_members_ow4_g_suite( g_suite_members, group.user_set.all(), quiet=False ) ) mocked_logger.assert_called_with( f"There are more users on OW4 ({group.user_set.count()}) than in G Suite ({len(g_suite_members)}). " "Need to update G Suite with new members." ) @patch("logging.Logger.debug") def test_check_amount_of_members_gsuite_dominates(self, mocked_logger): g_suite_members = [ {"email": "test@example.org"}, {"email": "test2@example.org"}, ] user = G(OnlineUser) group = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user) self.assertFalse( check_amount_of_members_ow4_g_suite( g_suite_members, group.user_set.all(), quiet=False ) ) mocked_logger.assert_called_with( f"There are more users in G Suite ({len(g_suite_members)}) than on OW4 ({group.user_set.count()}). " "Need to trim inactive users from G Suite." ) def test_get_excess_users_in_gsuite(self): g_suite_members = [ {"email": "test@example.org"}, {"email": "test2@example.org"}, ] user = G(OnlineUser, online_mail="test") G(OnlineUser, online_mail="test2") group = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user) users = get_excess_users_in_g_suite(g_suite_members, group.user_set.all()) self.assertIn({"email": "test2@example.org"}, users) def test_get_missing_ow4_users_for_g_suite(self): g_suite_members = [{"email": "test@%s" % self.domain}] user = G(OnlineUser, online_mail="test") user2 = G(OnlineUser, online_mail="test2") group = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["DOMAIN"] = self.domain ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): group.user_set.add(user, user2) users = get_missing_ow4_users_for_g_suite( g_suite_members, group.user_set.all() ) self.assertIn(user2, users) @patch("apps.gsuite.mail_syncer.utils.get_g_suite_groups_for_user") def test_get_missing_g_suite_group_names_for_user(self, mocked_client): user = G(OnlineUser) dotkom = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} mocked_client.return_value = [{"name": "dotkom@" + self.domain}] with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): dotkom.user_set.add(user) groups = get_missing_g_suite_group_names_for_user(self.domain, user) self.assertEqual(1, len(groups)) self.assertIn(dotkom.name.lower(), groups) @patch("apps.gsuite.mail_syncer.utils.get_g_suite_groups_for_user") def test_get_excess_groups_for_user(self, mocked_client): user = G(OnlineUser) dotkom = G(Group, name="dotkom") ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = False ow4_gsuite_sync["GROUPS"] = {"appkom": "appkom", "dotkom": "dotkom"} mocked_client.return_value = [{"name": "dotkom"}] with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): groups = get_excess_groups_for_user(self.domain, user) self.assertEqual(1, len(groups)) self.assertIn(dotkom.name.lower(), groups) @patch("apps.gsuite.mail_syncer.utils.setup_g_suite_client", autospec=True) def test_get_g_suite_users_for_group(self, mocked_g_suite_client): ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = True with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): mocked_g_suite_client.return_value.members.return_value.list.return_value.execute.return_value.get.return_value = [ {"email": "1@" + self.domain} ] resp = get_g_suite_users_for_group( self.domain, self.group, suppress_http_errors=True ) self.assertEqual(1, len(resp)) http_error = create_http_error(400, "Error", "Error") mocked_g_suite_client.return_value.members.return_value.list.return_value.execute.return_value.get.side_effect = ( http_error ) self.assertRaises( HttpError, lambda: get_g_suite_users_for_group(self.domain, self.group) ) @patch("apps.gsuite.mail_syncer.utils.setup_g_suite_client", autospec=True) def test_get_g_suite_users_for_group_no_members(self, mocked_g_suite_client): ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = True mocked_g_suite_client.return_value.members.return_value.list.return_value.execute.return_value.get.return_value = ( None ) with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): resp = get_g_suite_users_for_group(self.domain, self.group) self.assertEqual(0, len(resp)) @patch("apps.gsuite.mail_syncer.utils.setup_g_suite_client", autospec=True) def test_get_g_suite_groups_for_user(self, mocked_g_suite_client): user = G( OnlineUser, first_name="Test", last_name="Testesen", online_mail="test.testesen", ) ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = True with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): mocked_g_suite_client.return_value.groups.return_value.list.return_value.execute.return_value.get.return_value = [ {"name": "dotkom@" + self.domain} ] resp = get_g_suite_groups_for_user( self.domain, user, suppress_http_errors=True ) self.assertEqual(1, len(resp)) http_error = create_http_error(400, "Error", "Error") mocked_g_suite_client.return_value.groups.return_value.list.return_value.execute.return_value.get.side_effect = ( http_error ) self.assertRaises( HttpError, lambda: get_g_suite_groups_for_user(self.domain, user) ) @patch("apps.gsuite.mail_syncer.utils.setup_g_suite_client", autospec=True) def test_get_g_suite_groups_for_user_no_members(self, mocked_g_suite_client): user = G( OnlineUser, first_name="Test", last_name="Testesen", online_mail="test.testesen", ) ow4_gsuite_sync = settings.OW4_GSUITE_SYNC ow4_gsuite_sync["ENABLED"] = True mocked_g_suite_client.return_value.groups.return_value.list.return_value.execute.return_value.get.return_value = ( None ) with override_settings(OW4_GSUITE_SYNC=ow4_gsuite_sync): resp = get_g_suite_groups_for_user(self.domain, user) self.assertEqual(0, len(resp))

39.135385

127

0.65925

1,634

12,719

4.747246

0.082007

0.092819

0.134072

0.075803

0.843238

0.805208

0.756478

0.721026

0.706072

0.674101

0

0.013605

0.237204

12,719

324

128

39.256173

0.78592

0.005897

0

0.501916

0

0.007663

0.129767

0.038535

0

0.095785

1

0.061303

false

0

0.034483

0

0.099617

0

null

0

1

0

null

0

6

509eb99170f7979bc15c8c53dd4453ae0961d897

403

py

Python

Hira/tester.py

homologus/2020-intermediate-class

4eba7c6cc4d90b5e320f0750092e4a10844fc96e

[ "MIT" ]

3

2020-07-03T14:38:00.000Z

2020-07-31T22:31:13.000Z

Hira/tester.py

VP-Seahawks/2020-intermediate-class

7614d46fdfd206f6dc07b7eef48ff800e67f2e06

[ "MIT" ]

null

Hira/tester.py

VP-Seahawks/2020-intermediate-class

7614d46fdfd206f6dc07b7eef48ff800e67f2e06

[ "MIT" ]

5

2020-07-03T14:26:17.000Z

2020-07-30T23:00:30.000Z

from Bio.Seq import Seq from Bio import SeqIO sequence = Seq("""GAAATTTGACAATTTCACAGGGGAATGTCCAAACTTTGTCTTCCCACTAAATTCTACAATCAAGACCATTCAACCACGTGTTGAAAAGAAAAAGCTTGAGGGTTTTATGGGTACGAATTCGATCTGTCTATCCTGTTGCATCACCAAATGAATGCAACCCAATGCACCTTTCGACGCTTATGAAGTGTGAACATTGTAGTGAAACTTCATGGCAAACTGGTGACTTCCTTAAAGCCACTTGTGAATTTTGTGGTACTGAAAATCAAGTCAAAGAAGGACCTACCACTTGTGGTTACCTTC""") print(sequence.translate())

36.636364

322

0.918114

15

403

24.666667

0.6

0.037838

0

0.044665

403

10

323

40.3

0.961039

0

0.75

0

1

0

1

0

false

0

0.5

0

0.5

0.25

1

0

1

null

0

1

null

1

0

1

0

6

50a9aebd26f43f9282ed527c688df3ebf1ed87bd

32

py

Python

src/util/__init__.py

Stanford-ILIAD/lila

8ea05d0faabc8da69d5e1c8c3926f194ccc86ddc

[ "MIT" ]

6

2021-11-30T14:04:44.000Z

2022-03-21T19:00:42.000Z

src/util/__init__.py

Stanford-ILIAD/lila

8ea05d0faabc8da69d5e1c8c3926f194ccc86ddc

[ "MIT" ]

null

src/util/__init__.py

Stanford-ILIAD/lila

8ea05d0faabc8da69d5e1c8c3926f194ccc86ddc

[ "MIT" ]

1

2022-03-03T16:50:24.000Z

from .paths import create_paths

16

31

0.84375

5

32

5.2

0.8

0

0.125

32

1

32

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

0fe59919216eb52a1169ed18359282d0d8f9d3e9

6,873

py

Python

test_autolens/pipeline/phase/point_source/test_analysis_point_source.py

arfon/PyAutoLens

e1a886fa0cbd9620efc1f88457d3f2c5afdae622

[ "MIT" ]

null

test_autolens/pipeline/phase/point_source/test_analysis_point_source.py

arfon/PyAutoLens

e1a886fa0cbd9620efc1f88457d3f2c5afdae622

[ "MIT" ]

null

test_autolens/pipeline/phase/point_source/test_analysis_point_source.py

arfon/PyAutoLens

e1a886fa0cbd9620efc1f88457d3f2c5afdae622

[ "MIT" ]

null

from os import path import autolens as al import pytest from autolens.mock import mock pytestmark = pytest.mark.filterwarnings( "ignore:Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of " "`arr[seq]`. In the future this will be interpreted as an arrays index, `arr[np.arrays(seq)]`, which will result " "either in an error or a different result." ) directory = path.dirname(path.realpath(__file__)) class TestFit: def test__fit_using_positions( self, positions_x2, positions_x2_noise_map, samples_with_result ): phase_positions_x2 = al.PhasePointSource( galaxies=dict( lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic), source=al.GalaxyModel(redshift=1.0, point=al.ps.PointSource), ), search=mock.MockSearch(samples=samples_with_result), positions_solver=mock.MockPositionsSolver(model_positions=positions_x2), ) result = phase_positions_x2.run( positions=positions_x2, positions_noise_map=positions_x2_noise_map, results=mock.MockResults(), ) assert isinstance(result.instance.galaxies[0], al.Galaxy) assert isinstance(result.instance.galaxies[0], al.Galaxy) def test__figure_of_merit__matches_correct_fit_given_galaxy_profiles( self, positions_x2, positions_x2_noise_map ): lens_galaxy = al.Galaxy( redshift=0.5, light=al.ps.PointSource(centre=(0.0, 0.0)) ) phase_positions_x2 = al.PhasePointSource( galaxies=dict(lens=lens_galaxy), settings=al.SettingsPhasePositions(), search=mock.MockSearch(), positions_solver=mock.MockPositionsSolver(model_positions=positions_x2), ) analysis = phase_positions_x2.make_analysis( positions=positions_x2, positions_noise_map=positions_x2_noise_map, results=mock.MockResults(), ) instance = phase_positions_x2.model.instance_from_unit_vector([]) fit_figure_of_merit = analysis.log_likelihood_function(instance=instance) tracer = analysis.tracer_for_instance(instance=instance) positions_solver = mock.MockPositionsSolver(model_positions=positions_x2) fit_positions = al.FitPositionsImage( positions=positions_x2, noise_map=positions_x2_noise_map, tracer=tracer, positions_solver=positions_solver, ) assert fit_positions.chi_squared == 0.0 assert fit_positions.log_likelihood == fit_figure_of_merit model_positions = al.Grid2DIrregular([(0.0, 1.0), (1.0, 2.0)]) positions_solver = mock.MockPositionsSolver(model_positions=model_positions) phase_positions_x2 = al.PhasePointSource( galaxies=dict(lens=lens_galaxy), settings=al.SettingsPhasePositions(), search=mock.MockSearch(), positions_solver=positions_solver, ) analysis = phase_positions_x2.make_analysis( positions=positions_x2, positions_noise_map=positions_x2_noise_map, results=mock.MockResults(), ) instance = phase_positions_x2.model.instance_from_unit_vector([]) fit_figure_of_merit = analysis.log_likelihood_function(instance=instance) fit_positions = al.FitPositionsImage( positions=positions_x2, noise_map=positions_x2_noise_map, tracer=tracer, positions_solver=positions_solver, ) assert fit_positions.residual_map.in_list == [1.0, 1.0] assert fit_positions.chi_squared == 2.0 assert fit_positions.log_likelihood == fit_figure_of_merit def test__figure_of_merit__includes_fit_fluxes( self, positions_x2, positions_x2_noise_map, fluxes_x2, fluxes_x2_noise_map ): lens_galaxy = al.Galaxy( redshift=0.5, sis=al.mp.SphericalIsothermal(einstein_radius=1.0), light=al.ps.PointSourceFlux(flux=1.0), ) phase_positions_x2 = al.PhasePointSource( galaxies=dict(lens=lens_galaxy), settings=al.SettingsPhasePositions(), search=mock.MockSearch(), positions_solver=mock.MockPositionsSolver(model_positions=positions_x2), ) analysis = phase_positions_x2.make_analysis( positions=positions_x2, positions_noise_map=positions_x2_noise_map, fluxes=fluxes_x2, fluxes_noise_map=fluxes_x2_noise_map, results=mock.MockResults(), ) instance = phase_positions_x2.model.instance_from_unit_vector([]) fit_figure_of_merit = analysis.log_likelihood_function(instance=instance) tracer = analysis.tracer_for_instance(instance=instance) positions_solver = mock.MockPositionsSolver(model_positions=positions_x2) fit_positions = al.FitPositionsImage( positions=positions_x2, noise_map=positions_x2_noise_map, tracer=tracer, positions_solver=positions_solver, ) fit_fluxes = al.FitFluxes( fluxes=fluxes_x2, noise_map=fluxes_x2_noise_map, positions=positions_x2, tracer=tracer, ) assert ( fit_positions.log_likelihood + fit_fluxes.log_likelihood == fit_figure_of_merit ) model_positions = al.Grid2DIrregular([(0.0, 1.0), (1.0, 2.0)]) positions_solver = mock.MockPositionsSolver(model_positions=model_positions) phase_positions_x2 = al.PhasePointSource( galaxies=dict(lens=lens_galaxy), settings=al.SettingsPhasePositions(), search=mock.MockSearch(), positions_solver=positions_solver, ) analysis = phase_positions_x2.make_analysis( positions=positions_x2, positions_noise_map=positions_x2_noise_map, results=mock.MockResults(), ) instance = phase_positions_x2.model.instance_from_unit_vector([]) fit_figure_of_merit = analysis.log_likelihood_function(instance=instance) fit_positions = al.FitPositionsImage( positions=positions_x2, noise_map=positions_x2_noise_map, tracer=tracer, positions_solver=positions_solver, ) assert fit_positions.residual_map.in_list == [1.0, 1.0] assert fit_positions.chi_squared == 2.0 assert fit_positions.log_likelihood == fit_figure_of_merit

36.951613

119

0.646879

737

6,873

5.682497

0.16825

0.115568

0.047755

0.072588

0.812321

0.790831

0.773639

0.751671

0.702245

0

0.020056

0.274553

6,873

185

120

37.151351

0.819896

0

0.646259

0

0.013605

0.039623

0.003289

0

0.07483

1

0.020408

false

0

0.027211

0

0.054422

0

null

0

1

0

null

0

6

0feaef50dcef0b9f7cc05964e9823837a1512a5e

263

py

Python

run_tests.py

luzfcb/sqlalchemy-access

9e6d2db8b0612917ccb5879a80efdf466ebd57ec

[ "MIT" ]

8

2016-03-08T08:27:12.000Z

2018-11-29T09:01:31.000Z

awvspy/packages/sqlalchemy_access/run_tests.py

wcc526/awvspy

e4ed47a4c8db3afd9c07251579c4ac8b8b45dcb5

[ "Apache-2.0" ]

null

awvspy/packages/sqlalchemy_access/run_tests.py

wcc526/awvspy

e4ed47a4c8db3afd9c07251579c4ac8b8b45dcb5

[ "Apache-2.0" ]

7

2016-11-06T07:17:26.000Z

2018-11-29T09:02:52.000Z

from sqlalchemy.dialects import registry registry.register("access", "sqlalchemy_access.pyodbc", "AccessDialect_pyodbc") registry.register("access.pyodbc", "sqlalchemy_access.pyodbc", "AccessDialect_pyodbc") from sqlalchemy.testing import runner runner.main()

29.222222

86

0.81749

29

263

7.275862

0.413793

0.170616

0.208531

0.331754

0.388626

0

0.068441

263

8

87

32.875

0.861224

0

0.406844

0.18251

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

ba1915d9fb4e4244a55d4829f54d99d7097d8bb7

179

py

Python

hataripy/pest/__init__.py

cclauss/hataripy

7db7869f34b875c9f76d42b7a4801b0c23738448

[ "MIT" ]

3

2019-12-23T06:45:58.000Z

2021-01-06T20:14:58.000Z

hataripy/pest/__init__.py

cclauss/hataripy

7db7869f34b875c9f76d42b7a4801b0c23738448

[ "MIT" ]

2

2021-01-12T08:57:17.000Z

2021-01-21T18:06:12.000Z

hataripy/pest/__init__.py

cclauss/hataripy

7db7869f34b875c9f76d42b7a4801b0c23738448

[ "MIT" ]

1

2021-08-05T19:11:27.000Z

from .tplarray import Util3dTpl from .params import Params, zonearray2params from .templatewriter import TemplateWriter from .tplarray import Transient2dTpl, Util2dTpl, Util3dTpl

35.8

58

0.854749

19

179

8.052632

0.473684

0.156863

0.235294

0

0.03125

0.106145

179

4

59

44.75

0.925

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

e8c684226a268330301ad2c47d4e9b1fd6ee08d2

69,902

py

Python

hops/pylightcurve3/exoplanet_lc_fitting.py

ExoWorldsSpies/hops

a33e434befe17318c064210a289b453c6f91b44f

[ "MIT" ]

5

2020-02-22T13:51:47.000Z

2021-12-10T20:24:11.000Z

hops/pylightcurve3/exoplanet_lc_fitting.py

ExoWorldsSpies/hops

a33e434befe17318c064210a289b453c6f91b44f

[ "MIT" ]

6

2020-02-24T16:29:11.000Z

2021-11-27T22:57:19.000Z

hops/pylightcurve3/exoplanet_lc_fitting.py

ExoWorldsSpies/hops

a33e434befe17318c064210a289b453c6f91b44f

[ "MIT" ]

2

2020-04-04T17:33:05.000Z

2021-03-04T20:10:23.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import numpy as np import pickle import matplotlib if os.environ.get('DISPLAY', '') == '': print('no display found. Using non-interactive Agg backend') matplotlib.use('Agg') else: try: matplotlib.use('TkAgg') except ImportError: print('matplotlib.pyplot has been already imported. Tk features will not be supported') pass import matplotlib.pyplot as plt from ._0errors import * from .exoplanet_orbit import transit_projected_distance, transit_duration from .exoplanet_lc import transit_flux_drop from .analysis_emcee_fitting import EmceeFitting class TransitAndPolyFitting: def __init__(self, data, method, limb_darkening_coefficients, rp_over_rs, period, sma_over_rs, eccentricity, inclination, periastron, mid_time, iterations, walkers, burn, precision=3, exp_time=0, time_factor=1, fit_first_order=False, fit_second_order=False, fit_rp_over_rs=False, fit_period=False, fit_sma_over_rs=False, fit_eccentricity=False, fit_inclination=False, fit_periastron=False, fit_mid_time=False, counter='auto', function_to_call=None): # TODO check input parameters self.data = data self.total_sets = len(self.data) self.method = method self.limb_darkening_coefficients = limb_darkening_coefficients self.fit_ld = False if isinstance(self.limb_darkening_coefficients, str): if self.limb_darkening_coefficients == 'fit': self.fit_ld = True if self.method == 'linear': self.limb_darkening_coefficients = [0.5] elif self.method in ['quad', 'sqrt']: self.limb_darkening_coefficients = [0.5, 0.5] elif self.method == 'claret': self.limb_darkening_coefficients = [0.5, 0.5, 0.5, 0.5] if self.method == 'claret': self.total_ldcs = 4 elif self.method in ['quad', 'sqrt']: self.total_ldcs = 2 elif self.method == 'linear': self.total_ldcs = 1 self.rp_over_rs = rp_over_rs self.period = period self.sma_over_rs = sma_over_rs self.eccentricity = eccentricity self.inclination = inclination self.periastron = periastron self.mid_time = mid_time self.precision = precision self.exp_time = exp_time / (60.0 * 60.0 * 24.0) self.time_factor = time_factor self.fit_first_order = fit_first_order self.fit_second_order = fit_second_order self.fit_rp_over_rs = fit_rp_over_rs self.fit_period = fit_period self.fit_sma_over_rs = fit_sma_over_rs self.fit_eccentricity = fit_eccentricity self.fit_inclination = fit_inclination self.fit_periastron = fit_periastron self.fit_mid_time = fit_mid_time self.iterations = iterations self.walkers = walkers self.burn = burn self.counter = counter self.data_time = np.array([]) self.data_flux = np.array([]) self.data_flux_error = np.array([]) self.data_set_number = np.array([]) self.data_set_dt = np.array([]) for set_number, set_arrays in enumerate(self.data): if set_number == 0: time_shift = round((np.mean(set_arrays[0]) - self.mid_time) / self.period) self.mid_time += time_shift * self.period if self.fit_mid_time: self.fit_mid_time[0] += time_shift * self.period self.fit_mid_time[1] += time_shift * self.period self.data_time = np.append(self.data_time, set_arrays[0]) self.data_flux = np.append(self.data_flux, set_arrays[1]) self.data_flux_error = np.append(self.data_flux_error, set_arrays[2]) self.data_set_number = np.append(self.data_set_number, np.ones_like(set_arrays[0]) * set_number) self.data_set_dt = np.append(self.data_set_dt, set_arrays[0] - set_arrays[0][0]) self.data_set_number = np.int_(self.data_set_number) self.names = [] self.print_names = [] self.limits1 = [] self.limits2 = [] self.initial = [] for set_number, set_arrays in enumerate(self.data): max_limit = (10 * (max(set_arrays[1]) - min(set_arrays[1])) / (max(set_arrays[0]) - min(set_arrays[0])) / np.mean(set_arrays[1])) self.names.append('N{0}'.format(str(set_number))) self.print_names.append('N_{0}'.format(str(set_number))) self.initial.append(np.mean(set_arrays[1])) self.limits1.append(0.9 * np.min(set_arrays[1])) self.limits2.append(1.1 * np.max(set_arrays[1])) self.names.append('L{0}'.format(str(set_number))) self.print_names.append('L_{0}'.format(str(set_number))) self.initial.append(0) if self.fit_first_order: self.limits1.append(-3) self.limits2.append(3) else: self.limits1.append(np.nan) self.limits2.append(np.nan) self.names.append('Q{0}'.format(str(set_number))) self.print_names.append('Q_{0}'.format(str(set_number))) self.initial.append(0) if self.fit_second_order: self.limits1.append(-3) self.limits2.append(3) else: self.limits1.append(np.nan) self.limits2.append(np.nan) self.names.append('ldc1') self.print_names.append('ldc_1') self.initial.append(self.limb_darkening_coefficients[0]) if self.fit_ld: self.limits1.append(0.000001) self.limits2.append(0.999999) else: self.limits1.append(np.nan) self.limits2.append(np.nan) if self.method in ['claret', 'quad', 'sqrt']: self.names.append('ldc2') self.print_names.append('ldc_2') self.initial.append(self.limb_darkening_coefficients[1]) if self.fit_ld: self.limits1.append(0.000001) self.limits2.append(0.999999) else: self.limits1.append(np.nan) self.limits2.append(np.nan) if self.method == 'claret': self.names.append('ldc3') self.print_names.append('ldc_3') self.initial.append(self.limb_darkening_coefficients[2]) if self.fit_ld: self.limits1.append(0.000001) self.limits2.append(0.999999) else: self.limits1.append(np.nan) self.limits2.append(np.nan) self.names.append('ldc4') self.print_names.append('ldc_4') self.initial.append(self.limb_darkening_coefficients[3]) if self.fit_ld: self.limits1.append(0.000001) self.limits2.append(0.999999) else: self.limits1.append(np.nan) self.limits2.append(np.nan) self.names += ['rp', 'P', 'a', 'e', 'i', 'w', 'mt'] self.print_names += ['R_\mathrm{p}/R_*', 'P', 'a/R_*', 'e', 'i', '\omega', 'T_{mid}'] self.initial += [self.rp_over_rs, self.period, self.sma_over_rs, self.eccentricity, self.inclination, self.periastron, self.mid_time] limits = self.limits1 + [self.fit_rp_over_rs, self.fit_period, self.fit_sma_over_rs, self.fit_eccentricity, self.fit_inclination, self.fit_periastron, self.fit_mid_time] for var in range(3 * self.total_sets + self.total_ldcs, len(self.names)): try: self.initial[var] = float(self.initial[var]) except: raise PyLCInputError('Improper value for {0}'.format(self.names[var])) if limits[var] is False: self.limits1.append(np.nan) self.limits2.append(np.nan) elif limits[var] is None: self.limits1.append(np.nan) self.limits2.append(np.nan) else: try: if len(np.array(limits[var])) != 2: raise RuntimeError('Improper limits for {0}'.format(self.names[var])) except: raise RuntimeError('Improper limits for {0}'.format(self.names[var])) if self.initial[var] < np.array(limits[var])[0] or self.initial[var] > np.array(limits[var])[1]: raise RuntimeError('Initial value for {0} is outside the range of the prior.'.format( self.names[var])) else: self.limits1.append(np.array(limits[var])[0]) self.limits2.append(np.array(limits[var])[1]) if self.exp_time == 0: self.data_time_hr = self.data_time else: self.data_time_hr = np.array([]) for i in range(self.time_factor): self.data_time_hr = np.append(self.data_time_hr, self.data_time - self.exp_time / 2.0 + (i + 0.5) * self.exp_time / self.time_factor) self.fitting = EmceeFitting([self.data_flux, self.data_flux_error], self.full_model, self.initial, self.limits1, self.limits2, self.walkers, self.iterations, self.burn, names=self.names, print_names=self.print_names, counter=self.counter, function_to_call=function_to_call) self.results = 0 self.mcmc_run_complete = False def detrend_model(self, *model_variables): detrend_zero = np.array([model_variables[3 * xx] for xx in range(self.total_sets)]) detrend_zero = detrend_zero[self.data_set_number] detrend_one = np.array([model_variables[3 * xx + 1] for xx in range(self.total_sets)]) detrend_one = detrend_one[self.data_set_number] detrend_two = np.array([model_variables[3 * xx + 2] for xx in range(self.total_sets)]) detrend_two = detrend_two[self.data_set_number] return detrend_zero * (1 + detrend_one * self.data_set_dt + detrend_two * self.data_set_dt * self.data_set_dt) def transit_model(self, *model_variables): limb_darkening_coefficients = list(model_variables)[3 * self.total_sets: 3 * self.total_sets + self.total_ldcs] rp_over_rs = list(model_variables)[3 * self.total_sets + self.total_ldcs] z_over_rs = transit_projected_distance(*model_variables[3 * self.total_sets + self.total_ldcs + 1:], time_array=self.data_time_hr) transit_hr = transit_flux_drop(self.method, limb_darkening_coefficients, rp_over_rs, z_over_rs, precision=self.precision) return np.mean(np.reshape(transit_hr, (self.time_factor, len(self.data_time))), 0) def full_model(self, *model_variables): return self.detrend_model(*model_variables) * self.transit_model(*model_variables) def run_mcmc(self): self.fitting.run_mcmc() def rerun_mcmc(self): self.fitting.rerun_mcmc() def get_results(self): self.fitting.get_results() self.results = self.fitting.results self.mcmc_run_complete = True self.results['input_series']['hjd'] = self.data_time period = self.results['parameters']['P']['value'] mt = self.results['parameters']['mt']['value'] self.results['output_series']['phase'] = \ (self.data_time - mt) / period - np.round((self.data_time - mt) / period) self.results['detrended_input_series'] = { 'hjd': self.results['input_series']['hjd'], 'value': self.results['input_series']['value'] / self.detrend_model(*self.results['parameters_final']), 'error': self.results['input_series']['error'] / self.detrend_model(*self.results['parameters_final'])} self.results['detrended_output_series'] = { 'phase': self.results['output_series']['phase'], 'model': self.results['output_series']['model'] / self.detrend_model(*self.results['parameters_final']), 'residuals': (self.results['output_series']['residuals'] / self.detrend_model(*self.results['parameters_final']))} self.results['detrended_statistics'] = {ff: self.results['statistics'][ff] for ff in self.results['statistics']} self.results['detrended_statistics']['res_std'] = np.std(self.results['detrended_output_series']['residuals']) def save_all(self, export_file): if not self.mcmc_run_complete: raise PyLCProcessError('MCMC not completed') pickle.dump(self.results, open(export_file, 'wb')) def save_results(self, export_file): self.fitting.save_results(export_file) def plot_corner(self, export_file): self.fitting.plot_corner(export_file) def plot_traces(self, export_file): self.fitting.plot_traces(export_file) def plot_models(self, export_file, target=None, data_dates=None): if not self.mcmc_run_complete: raise PyLCProcessError('MCMC not completed') if target is None: target = ' ' if data_dates is None: data_dates = list(map(str, ['set_{0}'.format(str(ff)) for ff in range(1, self.total_sets + 1)])) for set_number in range(self.total_sets): fig = plt.figure(set_number + 1) fig.set_tight_layout(False) self.results = {ff: self.results[ff] for ff in self.results} period = self.results['parameters']['P']['value'] mt = self.results['parameters']['mt']['value'] mt += round((np.mean(self.data[set_number][0]) - mt) / period) * period prediction = (self.mid_time + round((np.mean(self.data[set_number][0]) - self.mid_time) / self.period) * self.period) duration = transit_duration(self.rp_over_rs, self.period, self.sma_over_rs, self.inclination, self.eccentricity, self.periastron) ingress = prediction - duration / 2 egress = prediction + duration / 2 set_indices = np.where(self.data_set_number == set_number) plt.subplot2grid((4, 1), (0, 0), rowspan=3) plt.plot(self.results['output_series']['phase'][set_indices], self.results['input_series']['value'][set_indices], 'ko', ms=2) plt.plot(self.results['output_series']['phase'][set_indices], self.results['output_series']['model'][set_indices], 'r-') plt.ylim(min(self.results['output_series']['model'][set_indices]) - 5 * np.std(self.results['output_series']['residuals'][set_indices]), max(self.results['output_series']['model'][set_indices]) + 5 * np.std(self.results['output_series']['residuals'][set_indices])) plt.yticks(plt.yticks()[0][1:]) plt.ylabel(r'$\mathrm{relative} \ \mathrm{flux}$', fontsize=15) plt.ylim(min(self.results['output_series']['model'][set_indices]) - 5 * np.std(self.results['output_series']['residuals'][set_indices]), max(self.results['output_series']['model'][set_indices]) + 5 * np.std(self.results['output_series']['residuals'][set_indices])) x_max = max(np.abs(self.results['output_series']['phase'][set_indices]) + 0.05 * (max(self.results['output_series']['phase'][set_indices]) - min(self.results['output_series']['phase'][set_indices]))) plt.xlim(-x_max, x_max) plt.tick_params(labelbottom='off') rpstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( r'$R_\mathrm{p}/R_* = ', self.results['parameters']['rp']['print_value'], '_{-', self.results['parameters']['rp']['print_m_error'], '}', '^{+', self.results['parameters']['rp']['print_p_error'], '}$') mtstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( r'$T_\mathrm{HJD} = ', self.results['parameters']['mt']['print_value'], '_{-', self.results['parameters']['mt']['print_m_error'], '}', '^{+', self.results['parameters']['mt']['print_p_error'], '}$') plt.text(plt.xlim()[0] + 0.5 * (plt.xlim()[-1] - plt.xlim()[0]), plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), '{0}\n{1}'.format(rpstr, mtstr), ha='center', va='center', fontsize=10) plt.axvline((ingress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) plt.text((ingress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{ingress}$', '\n', r'$\mathrm{start}$'), ha='right', va='top', fontsize=10) plt.axvline((egress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) plt.text((egress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{egress}$', '\n', r'$\mathrm{end}$'), ha='left', va='top', fontsize=10) plt.suptitle('{0}{1}{2}'.format(r'$\mathbf{', target, '}$'), fontsize=20) plt.text(plt.xlim()[1], plt.ylim()[1], '{0}{1}{2}'.format(r'$', data_dates[set_number], '$'), fontsize=12, ha='right', va='bottom') plt.subplot(4, 1, 4) plt.cla() plt.plot(self.results['output_series']['phase'][set_indices], self.results['output_series']['residuals'][set_indices], 'ko', ms=2) plt.plot(self.results['output_series']['phase'][set_indices], np.zeros_like(self.results['output_series']['phase'][set_indices]), 'r-') plt.ylim(- 5 * np.std(self.results['output_series']['residuals'][set_indices]), 5 * np.std(self.results['output_series']['residuals'][set_indices])) plt.xlabel(r'$\mathrm{phase}$', fontsize=15) plt.ylabel(r'$\mathrm{residuals}$', fontsize=15) plt.xlim(-x_max, x_max) plt.text(plt.xlim()[0] + 0.02 * (plt.xlim()[-1] - plt.xlim()[0]), plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), r'$\mathrm{rms}_\mathrm{res} = %.1e$' % np.std(self.results['output_series']['residuals'][set_indices]), fontsize=10) plt.subplots_adjust(left=0.15, right=0.975, bottom=0.12, top=0.9, hspace=0.0) plt.savefig(os.path.join(os.path.split(export_file)[0], 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), transparent=True) plt.close('all') def plot_detrended_models(self, export_file, target=None, data_dates=None, return_plot=False): if not self.mcmc_run_complete: raise PyLCProcessError('MCMC not completed') if target is None: target = ' ' if data_dates is None: data_dates = list(map(str, ['set_{0}'.format(str(ff)) for ff in range(1, self.total_sets + 1)])) for set_number in range(self.total_sets): fig = plt.figure(set_number + 1) fig.set_tight_layout(False) self.results = {ff: self.results[ff] for ff in self.results} period = self.results['parameters']['P']['value'] mt = self.results['parameters']['mt']['value'] mt += round((np.mean(self.data[set_number][0]) - mt) / period) * period prediction = (self.mid_time + round((np.mean(self.data[set_number][0]) - self.mid_time) / self.period) * self.period) duration = transit_duration(self.rp_over_rs, self.period, self.sma_over_rs, self.inclination, self.eccentricity, self.periastron) ingress = prediction - duration / 2 egress = prediction + duration / 2 set_indices = np.where(self.data_set_number == set_number) plt.subplot2grid((4, 1), (0, 0), rowspan=3) plt.plot(self.results['detrended_output_series']['phase'][set_indices], self.results['detrended_input_series']['value'][set_indices], 'ko', ms=2) plt.plot(self.results['detrended_output_series']['phase'][set_indices], self.results['detrended_output_series']['model'][set_indices], 'r-') plt.ylim(min(self.results['detrended_output_series']['model'][set_indices]) - 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), max(self.results['detrended_output_series']['model'][set_indices]) + 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) plt.yticks(plt.yticks()[0][1:]) plt.ylabel(r'$\mathrm{relative} \ \mathrm{flux}$', fontsize=15) plt.ylim(min(self.results['detrended_output_series']['model'][set_indices]) - 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), max(self.results['detrended_output_series']['model'][set_indices]) + 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) plt.ylim(-1.17647 * (- plt.ylim()[0] + 0.15 * plt.ylim()[1]), plt.ylim()[1]) x_max = max(np.abs(self.results['detrended_output_series']['phase'][set_indices]) + 0.05 * (max(self.results['detrended_output_series']['phase'][set_indices]) - min(self.results['detrended_output_series']['phase'][set_indices]))) plt.xlim(-x_max, x_max) plt.tick_params(labelbottom='off') rpstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( r'$R_\mathrm{p}/R_* = ', self.results['parameters']['rp']['print_value'], '_{-', self.results['parameters']['rp']['print_m_error'], '}', '^{+', self.results['parameters']['rp']['print_p_error'], '}$') mtstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( r'$T_\mathrm{HJD} = ', self.results['parameters']['mt']['print_value'], '_{-', self.results['parameters']['mt']['print_m_error'], '}', '^{+', self.results['parameters']['mt']['print_p_error'], '}$') plt.text(plt.xlim()[0] + 0.5 * (plt.xlim()[-1] - plt.xlim()[0]), plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), '{0}{1}{2}'.format(rpstr, '\n', mtstr), ha='center', va='center', fontsize=10) plt.axvline((ingress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) plt.text((ingress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{ingress}$', '\n', r'$\mathrm{start}$'), ha='right', va='top', fontsize=10) plt.axvline((egress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) plt.text((egress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{egress}$', '\n', r'$\mathrm{end}$'), ha='left', va='top', fontsize=10) plt.suptitle('{0}{1}{2}'.format(r'$\mathbf{', target, '}$'), fontsize=20) plt.text(plt.xlim()[1], plt.ylim()[1], '{0}{1}{2}'.format(r'$', data_dates[set_number], '$'), fontsize=12, ha='right', va='bottom') plt.subplot(4, 1, 4) plt.cla() plt.plot(self.results['detrended_output_series']['phase'][set_indices], self.results['detrended_output_series']['residuals'][set_indices], 'ko', ms=2) plt.plot(self.results['detrended_output_series']['phase'][set_indices], np.zeros_like(self.results['detrended_output_series']['phase'][set_indices]), 'r-') plt.ylim(- 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) plt.xlabel(r'$\mathrm{phase}$', fontsize=15) plt.ylabel(r'$\mathrm{residuals}$', fontsize=15) plt.xlim(-x_max, x_max) plt.text(plt.xlim()[0] + 0.02 * (plt.xlim()[-1] - plt.xlim()[0]), plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), r'$\mathrm{rms}_\mathrm{res} = %.1e$' % np.std(self.results['detrended_output_series']['residuals'][set_indices]), fontsize=10) plt.subplots_adjust(left=0.15, right=0.975, bottom=0.12, top=0.9, hspace=0.0) plt.savefig(os.path.join(os.path.split(export_file)[0], 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), transparent=True) if return_plot: return [plt.figure(ff + 1) for ff in range(self.total_sets)] else: plt.close('all') def save_models(self, export_file): if not self.mcmc_run_complete: raise PyLCProcessError('MCMC not completed') for set_number in range(self.total_sets): self.results = {ff: self.results[ff] for ff in self.results} set_indices = np.where(self.data_time == self.data[set_number][0]) np.savetxt(os.path.join(os.path.split(export_file)[0], 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), np.swapaxes([self.results['input_series']['hjd'][set_indices], self.results['output_series']['phase'][set_indices], self.results['input_series']['value'][set_indices], self.results['input_series']['error'][set_indices], self.results['output_series']['model'][set_indices], self.results['output_series']['residuals'][set_indices] ], 0, 1)) def save_detrended_models(self, export_file): if not self.mcmc_run_complete: raise PyLCProcessError('MCMC not completed') for set_number in range(self.total_sets): self.results = {ff: self.results[ff] for ff in self.results} set_indices = np.where(self.data_time == self.data[set_number][0]) np.savetxt(os.path.join(os.path.split(export_file)[0], 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), np.swapaxes([self.results['detrended_input_series']['hjd'][set_indices], self.results['detrended_output_series']['phase'][set_indices], self.results['detrended_input_series']['value'][set_indices], self.results['detrended_input_series']['error'][set_indices], self.results['detrended_output_series']['model'][set_indices], self.results['detrended_output_series']['residuals'][set_indices] ], 0, 1)) # # class TransitAndHubbleFitting: # # def __init__(self, data, # apply_up_down_stream_correction, # exclude_initial_orbits, exclude_final_orbits, exclude_initial_orbit_points, # first_orbit_ramp, second_order_ramp, mid_orbit_ramps, # method, limb_darkening_coefficients, # rp_over_rs, period, sma_over_rs, eccentricity, inclination, periastron, mid_time, # iterations, walkers, burn, precision=3, # exp_time=0, time_factor=1, # fit_rp_over_rs=False, fit_period=False, fit_sma_over_rs=False, # fit_eccentricity=False, fit_inclination=False, fit_periastron=False, fit_mid_time=False, # counter=True, counter_window=False): # # # TODO check input parameters # # self.method = method # self.limb_darkening_coefficients = limb_darkening_coefficients # self.fit_ld = False # # if isinstance(self.limb_darkening_coefficients, str): # if self.limb_darkening_coefficients == 'fit': # self.fit_ld = True # if self.method == 'linear': # self.limb_darkening_coefficients = [0.5] # elif self.method in ['quad', 'sqrt']: # self.limb_darkening_coefficients = [0.5, 0.5] # elif self.method == 'claret': # self.limb_darkening_coefficients = [0.5, 0.5, 0.5, 0.5] # # if self.method == 'claret': # self.total_ldcs = 4 # elif self.method in ['quad', 'sqrt']: # self.total_ldcs = 2 # elif self.method == 'linear': # self.total_ldcs = 1 # # self.rp_over_rs = rp_over_rs # self.period = period # self.sma_over_rs = sma_over_rs # self.eccentricity = eccentricity # self.inclination = inclination # self.periastron = periastron # self.mid_time = mid_time # self.precision = precision # self.time_factor = time_factor # # self.fit_second_order_ramp = second_order_ramp # # self.fit_rp_over_rs = fit_rp_over_rs # self.fit_period = fit_period # self.fit_sma_over_rs = fit_sma_over_rs # self.fit_eccentricity = fit_eccentricity # self.fit_inclination = fit_inclination # self.fit_periastron = fit_periastron # self.fit_mid_time = fit_mid_time # # self.data = {} # self.sets = ['set_{0}'.format(str(ff).zfill(2)) for ff in range(len(data))] # self.total_sets = len(data) # self.data_set_number = np.array([]) # self.data_time = np.array([]) # data_flux = np.array([]) # data_flux_error = np.array([]) # # for set_number, set_arrays in enumerate(data): # # new_set_arrays = [ff for ff in set_arrays] # # # up-stream / down-stream correction # # star_y_position_array = new_set_arrays[1] # spectrum_direction_array = new_set_arrays[2] # scan_length_array = new_set_arrays[3] # # if apply_up_down_stream_correction: # test1 = star_y_position_array[0] - 507 # test2 = test1 + spectrum_direction_array[0] * scan_length_array[0] # if test1 * test2 < 0: # apply_up_down_stream_correction = True # else: # apply_up_down_stream_correction = False # # if apply_up_down_stream_correction: # for scan_direction in [1.0, -1.0]: # fr = np.where(spectrum_direction_array == scan_direction)[0] # if len(fr) > 0: # zerofr = star_y_position_array.value[fr] # sigmfr = scan_length_array.value[fr] # begnfr = zerofr # fitfr = np.poly1d(np.polyfit(begnfr, sigmfr, 1)) # for ii in range(4, len(new_set_arrays)): # new_set_arrays[ii][fr] = new_set_arrays[ii][fr] * fitfr(begnfr[0]) / fitfr(begnfr) # new_set_arrays[ii][fr] = new_set_arrays[ii][fr] * fitfr(begnfr[0]) / fitfr(begnfr) # # # exclude orbits / points # # heliocentric_julian_date_array = new_set_arrays[0] # # indices_to_remain = np.arange(len(heliocentric_julian_date_array)) # # if exclude_initial_orbits > 0: # htime = heliocentric_julian_date_array # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # indices_to_remain = indices_to_remain[orbits[exclude_initial_orbits]:] # # if exclude_final_orbits > 0: # htime = heliocentric_julian_date_array[indices_to_remain] # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # indices_to_remain = indices_to_remain[:orbits[-exclude_final_orbits]] # # if exclude_initial_orbit_points > 0: # htime = heliocentric_julian_date_array[indices_to_remain] # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # indices_to_remain = np.delete(indices_to_remain, # np.concatenate( # [orbits + i for i in range(exclude_initial_orbit_points)])) # # new_set_arrays = [ff[indices_to_remain] for ff in new_set_arrays] # # # define hst orbital phases # # heliocentric_julian_date_array = new_set_arrays[0] # # if mid_orbit_ramps: # htime = heliocentric_julian_date_array # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # dumps = np.where(abs(htime - np.roll(htime, 1)) > 5.0 / 60.0 / 24.0)[0] # dphase = np.zeros(len(htime)) # for i in range(1, len(dumps)): # if dumps[i] not in orbits: # if i != len(dumps) - 1: # for j in range(dumps[i], dumps[i + 1]): # dphase[j] = 1 # else: # for j in range(dumps[i], len(dphase)): # dphase[j] = 1 # else: # htime = heliocentric_julian_date_array # dphase = np.zeros(len(htime)) # # if first_orbit_ramp: # htime = heliocentric_julian_date_array # if mid_orbit_ramps: # orbits = np.where(abs(htime - np.roll(htime, 1)) > 5.0 / 60.0 / 24.0)[0] # else: # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # orbits = htime[orbits] # fphase = np.where(htime < orbits[1], 1, 0) # # else: # htime = heliocentric_julian_date_array # fphase = np.zeros(len(htime)) # # htime = heliocentric_julian_date_array # if mid_orbit_ramps: # orbits = np.where(abs(htime - np.roll(htime, 1)) > 5.0 / 60.0 / 24.0)[0] # else: # orbits = np.where(abs(htime - np.roll(htime, 1)) > 30.0 / 60.0 / 24.0)[0] # t0s = htime[orbits] # ophase = [] # for pp in t0s: # ppp = htime - pp # ppp = np.where(ppp < 0, 1000, ppp) # ophase.append(ppp) # # ophase = np.min(ophase, 0) # # # outliers filter # # lightcurves = [ff for ff in new_set_arrays[6::2]] # ica = FastICA(n_components=len(lightcurves), max_iter=1000) # components = ica.fit_transform(np.array(lightcurves).T).T # # indices_to_remain = [] # for i in components: # indices_to_remain.append( # np.array(np.abs(i - np.median(i)) < 20 * np.median(np.abs(i - np.median(i))))) # indices_to_remain = np.where(np.product(indices_to_remain, 0))[0] # indices_to_remain = np.sort(np.unique(np.array(indices_to_remain))) # # new_set_arrays = [ff[indices_to_remain] for ff in new_set_arrays] # ophase = ophase[indices_to_remain] # dphase = dphase[indices_to_remain] # fphase = fphase[indices_to_remain] # # # match forward and reverse scans # # spectrum_direction_array = new_set_arrays[2] # flux_array = new_set_arrays[4] # # fr = np.where(spectrum_direction_array > 0)[0] # if len(fr) != len(spectrum_direction_array): # # fr_out = np.where(spectrum_direction_array > 0)[0] # rv_out = np.where(spectrum_direction_array < 0)[0] # shift = np.mean(flux_array[fr_out]) / np.mean(flux_array[rv_out]) # for ii in range(4, len(new_set_arrays)): # new_set_arrays[ii][fr] = new_set_arrays[ii][fr] / shift # # if set_number == 0: # time_shift = round((np.mean(new_set_arrays[0]) - self.mid_time) / self.period) # self.mid_time += time_shift * self.period # if self.fit_mid_time: # self.fit_mid_time[0] += time_shift * self.period # self.fit_mid_time[1] += time_shift * self.period # # data_flux = np.append(data_flux, new_set_arrays[4]) # data_flux_error = np.append(data_flux_error, new_set_arrays[5]) # self.data_time = np.append(self.data_time, new_set_arrays[0]) # self.data_set_number = np.int_(np.append(self.data_set_number, # np.ones_like(new_set_arrays[0]) * set_number)) # # if exp_time == 0: # hjd_hd = new_set_arrays[0] # # else: # hjd_hd = np.array([]) # for i in range(self.time_factor): # hjd_hd = np.append(hjd_hd, new_set_arrays[0] - (exp_time / (60.0 * 60.0 * 24.0)) / 2.0 + # (i + 0.5) * (exp_time / (60.0 * 60.0 * 24.0)) / self.time_factor) # # epoch = round((np.mean(new_set_arrays[0]) - self.mid_time) / self.period) # # self.data[self.sets[set_number]] = {'epoch': epoch, # 'hjd': new_set_arrays[0], # 'ophase': ophase, # 'dphase': dphase, # 'fphase': fphase, # 'scan': new_set_arrays[2], # 'hjd_hd': hjd_hd, # 'flux': new_set_arrays[4], # 'error': new_set_arrays[5], # 'pindices': []} # # names = [] # print_names = [] # limits1 = [] # limits2 = [] # initial = [] # # for set_number, set_name in enumerate(self.sets): # # flux = self.data[set_name]['flux'] # scan = self.data[set_name]['scan'] # fphase = self.data[set_name]['fphase'] # dphase = self.data[set_name]['dphase'] # # # forward scans normalisation factors # names.append('n_w_for_{0}'.format(str(set_number))) # print_names.append('n{}{}{}'.format('w', 'for', str(set_number))) # initial.append(np.max(flux)) # if (scan < 0).all(): # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(np.max(flux) * 0.99) # limits2.append(np.max(flux) * 1.01) # self.data[set_name]['pindices'].append(len(names) - 1) # # print(np.median(flux), np.max(flux), np.max(flux) * 0.99, np.max(flux) * 1.01) # # # reverse scans normalisation factors # names.append('n_w_rev_{0}'.format(str(set_number))) # print_names.append('n{}{}{}'.format('w', 'rev', str(set_number))) # initial.append(np.max(flux)) # if (scan > 0).all(): # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(np.max(flux) * 0.99) # limits2.append(np.max(flux) * 1.01) # self.data[set_name]['pindices'].append(len(names) - 1) # # # long term ramp - 1st order # names.append('r_a1_{0}'.format(str(set_number))) # print_names.append('r{}{}'.format('a1', str(set_number))) # initial.append(0.001) # limits1.append(-1.0) # limits2.append(1.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # long term ramp - 2nd order # names.append('r_a2_{0}'.format(str(set_number))) # print_names.append('r{}{}'.format('a2', str(set_number))) # initial.append(0.0) # if self.fit_second_order_ramp: # limits1.append(-1.0) # limits2.append(1.0) # else: # limits1.append(np.nan) # limits2.append(np.nan) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term ramp - amplitude # names.append('r_b1_{0}'.format(str(set_number))) # print_names.append('r{}{}'.format('b1', str(set_number))) # initial.append(0.001) # limits1.append(-1.0) # limits2.append(1.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term mid-orbit ramp - amplitude # names.append('mor_b1_{0}'.format(str(set_number))) # print_names.append('mor{}{}'.format('b1', str(set_number))) # initial.append(0.001) # if np.sum(dphase ** 2) == 0: # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(-1.0) # limits2.append(1.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term first-orbit ramp - amplitude # names.append('for_b1_{0}'.format(str(set_number))) # print_names.append('for{}{}'.format('b1', str(set_number))) # initial.append(0.001) # if np.sum(fphase ** 2) == 0: # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(-1.0) # limits2.append(1.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term ramp - decay # names.append('r_b2_{0}'.format(str(set_number))) # print_names.append('r{}{}'.format('b2', str(set_number))) # initial.append(250.0) # limits1.append(50.0) # limits2.append(500.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term mid-orbit ramp - decay # names.append('mor_b2_{0}'.format(str(set_number))) # print_names.append('mor{}{}'.format('b2', str(set_number))) # initial.append(250.0) # if np.sum(dphase ** 2) == 0: # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(50.0) # limits2.append(500.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # sort term first-orbit ramp - decay # names.append('for_b2_{0}'.format(str(set_number))) # print_names.append('for{}{}'.format('b2', str(set_number))) # initial.append(150.0) # if np.sum(fphase ** 2) == 0: # limits1.append(np.nan) # limits2.append(np.nan) # else: # limits1.append(50.0) # limits2.append(500.0) # self.data[set_name]['pindices'].append(len(names) - 1) # # # rp # names.append('rp_{0}'.format(str(set_number))) # print_names.append('Rp/R*{}'.format(str(set_number))) # initial.append(self.rp_over_rs) # limits1.append(self.fit_rp_over_rs[0]) # limits2.append(self.fit_rp_over_rs[1]) # self.data[set_name]['pindices'].append(len(names) - 1) # # self.len_systematics = int(len(names) / self.total_sets) # # names.append('ldc1') # print_names.append('ldc_1') # initial.append(self.limb_darkening_coefficients[0]) # if self.fit_ld: # limits1.append(0.000001) # limits2.append(0.999999) # else: # limits1.append(np.nan) # limits2.append(np.nan) # # for set_name in self.sets: # self.data[set_name]['pindices'].append(len(names) - 1) # # if self.method in ['claret', 'quad', 'sqrt']: # # names.append('ldc2') # print_names.append('ldc_2') # initial.append(self.limb_darkening_coefficients[1]) # if self.fit_ld: # limits1.append(0.000001) # limits2.append(0.999999) # else: # limits1.append(np.nan) # limits2.append(np.nan) # # for set_name in self.sets: # self.data[set_name]['pindices'].append(len(names) - 1) # # if self.method == 'claret': # # names.append('ldc3') # print_names.append('ldc_3') # initial.append(self.limb_darkening_coefficients[2]) # if self.fit_ld: # limits1.append(0.000001) # limits2.append(0.999999) # else: # limits1.append(np.nan) # limits2.append(np.nan) # # for set_name in self.sets: # self.data[set_name]['pindices'].append(len(names) - 1) # # names.append('ldc4') # print_names.append('ldc_4') # initial.append(self.limb_darkening_coefficients[3]) # if self.fit_ld: # limits1.append(0.000001) # limits2.append(0.999999) # else: # limits1.append(np.nan) # limits2.append(np.nan) # # for set_name in self.sets: # self.data[set_name]['pindices'].append(len(names) - 1) # # for pindex in range(len(names), len(names) + 6): # for set_name in self.sets: # self.data[set_name]['pindices'].append(pindex) # # for set_name in self.sets: # self.data[set_name]['pindices'] = np.int_(self.data[set_name]['pindices']) # # names += ['P', 'a', 'e', 'i', 'w', 'mt'] # print_names += ['P', 'a/R_*', 'e', 'i', '\omega', 'T_0'] # # initial += [self.period, self.sma_over_rs, self.eccentricity, # self.inclination, self.periastron, self.mid_time] # # limits = limits1 + [self.fit_period, self.fit_sma_over_rs, self.fit_eccentricity, # self.fit_inclination, self.fit_periastron, self.fit_mid_time] # # for var in range(self.len_systematics * self.total_sets + self.total_ldcs, len(names)): # # try: # initial[var] = float(initial[var]) # except: # raise RuntimeError('Improper value for {0}'.format(names[var])) # # if limits[var] is False: # limits1.append(np.nan) # limits2.append(np.nan) # # elif limits[var] is None: # limits1.append(np.nan) # limits2.append(np.nan) # # else: # try: # if len(np.array(limits[var])) != 2: # raise RuntimeError('Improper limits for {0}'.format(names[var])) # except: # raise RuntimeError('Improper limits for {0}'.format(names[var])) # # if initial[var] < np.array(limits[var])[0] or initial[var] > np.array(limits[var])[1]: # raise RuntimeError('Initial value for {0} is outside the range of the prior.'.format( # names[var])) # else: # limits1.append(np.array(limits[var])[0]) # limits2.append(np.array(limits[var])[1]) # # self.fitting = EmceeFitting([data_flux, data_flux_error], # self.full_model, initial, limits1, limits2, # walkers, iterations, burn, # names=names, print_names=print_names, # counter=counter, counter_window=counter_window, strech_prior=1.0) # # self.results = {} # self.mcmc_run_complete = False # # def detrend_model(self, *model_variables): # # model = [] # # for set_name in self.sets: # # (model_norm_f, model_norm_r, model_r_a1, model_r_a2, model_r_b1, model_mor_b1, model_for_b1, model_r_b2, # model_mor_b2, model_for_b2, model_rp) = np.array( # model_variables)[self.data[set_name]['pindices']][:self.len_systematics] # model_period = np.array( # model_variables)[self.data[set_name]['pindices']][self.len_systematics + self.total_ldcs] # model_mid_time = np.array(model_variables)[self.data[set_name]['pindices']][-1] # # model_ophase = self.data[set_name]['ophase'] # model_dphase = self.data[set_name]['dphase'] # model_fphase = self.data[set_name]['fphase'] # model_scan = self.data[set_name]['scan'] # model_hjd = self.data[set_name]['hjd'] # model_epoch = self.data[set_name]['epoch'] # model_vtime = model_hjd - (model_mid_time + model_epoch * model_period) # # normalisation = np.where(model_scan > 0, model_norm_f, model_norm_r) # detrend1 = (1.0 - model_r_a1 * model_vtime + model_r_a2 * (model_vtime ** 2)) # ramp_ampl = np.where(model_dphase == 0, model_r_b1, model_mor_b1) # ramp_ampl = np.where(model_fphase == 0, ramp_ampl, model_for_b1) # ramp_decay = np.where(model_dphase == 0, model_r_b2, model_mor_b2) # ramp_decay = np.where(model_fphase == 0, ramp_decay, model_for_b2) # detrend2 = 1.0 - ramp_ampl * np.exp(- ramp_decay * model_ophase) # # model.append(normalisation * detrend1 * detrend2) # # return np.concatenate(model) # # def transit_model(self, *model_variables): # # model = [] # # for set_name in self.sets: # model_rp_over_rs = np.array(model_variables)[self.data[set_name]['pindices']][10] # # model_hjd = self.data[set_name]['hjd'] # model_hjd_hd = self.data[set_name]['hjd_hd'] # # limb_darkening_coefficients = np.array( # model_variables)[self.data[set_name]['pindices']][self.len_systematics: # self.len_systematics + self.total_ldcs] # # z_over_rs = transit_projected_distance(*np.array( # model_variables)[self.data[set_name]['pindices']][self.len_systematics + self.total_ldcs:], # time_array=model_hjd_hd) # # transit_hr = transit_flux_drop(self.method, limb_darkening_coefficients, model_rp_over_rs, z_over_rs, # precision=self.precision) # # model.append(np.mean(np.reshape(transit_hr, (self.time_factor, len(model_hjd))), 0)) # # return np.concatenate(model) # # def full_model(self, *model_variables): # # return self.detrend_model(*model_variables) * self.transit_model(*model_variables) # # def run_mcmc(self): # # self.fitting.run_mcmc() # self.results = self.fitting.results # self.mcmc_run_complete = True # # self.results['input_series']['hjd'] = self.data_time # # period = self.results['parameters']['P']['value'] # mt = self.results['parameters']['mt']['value'] # self.results['output_series']['phase'] = \ # (self.data_time - mt) / period - np.round((self.data_time - mt) / period) # # self.results['detrended_input_series'] = { # 'hjd': self.results['input_series']['hjd'], # 'value': self.results['input_series']['value'] / self.detrend_model(*self.results['parameters_final']), # 'error': self.results['input_series']['error'] / self.detrend_model(*self.results['parameters_final'])} # # self.results['detrended_output_series'] = { # 'phase': self.results['output_series']['phase'], # 'model': self.results['output_series']['model'] / self.detrend_model(*self.results['parameters_final']), # 'residuals': (self.results['output_series']['residuals'] # / self.detrend_model(*self.results['parameters_final']))} # # self.results['detrended_statistics'] = {ff: self.results['statistics'][ff] for ff in self.results['statistics']} # self.results['detrended_statistics']['res_std'] = np.std(self.results['detrended_output_series']['residuals']) # # def save_all(self, export_file): # # pickle.dump(self.results, open(export_file, 'wb')) # # def save_results(self, export_file): # # self.fitting.save_results(export_file) # # def plot_corner(self, export_file): # # self.fitting.plot_corner(export_file) # # def plot_traces(self, export_file): # # self.fitting.plot_traces(export_file) # # def plot_models(self, export_file, target=None, data_dates=None): # # if target is None: # target = ' ' # # if data_dates is None: # data_dates = map(str, ['set_{0}'.format(str(ff)) for ff in range(1, self.total_sets + 1)]) # # for set_number in range(self.total_sets): # # set_indices = np.where(self.data_set_number == set_number) # # fig = plt.figure(set_number + 1) # fig.set_tight_layout(False) # # self.results = {ff: self.results[ff] for ff in self.results} # # period = self.results['parameters']['P']['value'] # mt = self.results['parameters']['mt']['value'] # # mt += round((np.mean(self.data_time[set_indices]) - mt) / period) * period # # prediction = (self.mid_time + # round((np.mean(self.data_time[set_indices]) - self.mid_time) / self.period) * self.period) # # duration = transit_duration(self.rp_over_rs, self.period, self.sma_over_rs, # self.inclination, self.eccentricity, self.periastron) # # ingress = prediction - duration / 2 # egress = prediction + duration / 2 # # plt.subplot2grid((4, 1), (0, 0), rowspan=3) # # plt.plot(self.results['output_series']['phase'][set_indices], # self.results['input_series']['value'][set_indices], 'ko', ms=2) # plt.plot(self.results['output_series']['phase'][set_indices], # self.results['output_series']['model'][set_indices], 'r-') # # plt.ylim(min(self.results['output_series']['model'][set_indices]) # - 5 * np.std(self.results['output_series']['residuals'][set_indices]), # max(self.results['output_series']['model'][set_indices]) # + 5 * np.std(self.results['output_series']['residuals'][set_indices])) # # plt.yticks(plt.yticks()[0][1:]) # plt.ylabel(r'$\mathrm{relative} \ \mathrm{flux}$', fontsize=15) # # plt.ylim(min(self.results['output_series']['model'][set_indices]) # - 5 * np.std(self.results['output_series']['residuals'][set_indices]), # max(self.results['output_series']['model'][set_indices]) # + 5 * np.std(self.results['output_series']['residuals'][set_indices])) # # x_max = max(np.abs(self.results['output_series']['phase'][set_indices]) + # 0.05 * (max(self.results['output_series']['phase'][set_indices]) - # min(self.results['output_series']['phase'][set_indices]))) # plt.xlim(-x_max, x_max) # plt.tick_params(labelbottom='off') # # rpstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( # r'$R_\mathrm{p}/R_* = ', self.results['parameters']['rp_{0}'.format(str(set_number))]['print_value'], # '_{-', self.results['parameters']['rp_{0}'.format(str(set_number))]['print_m_error'], '}', '^{+', # self.results['parameters']['rp_{0}'.format(str(set_number))]['print_p_error'], '}$') # mtstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( # r'$T_\mathrm{HJD} = ', self.results['parameters']['mt']['print_value'], '_{-', # self.results['parameters']['mt']['print_m_error'], '}', '^{+', # self.results['parameters']['mt']['print_p_error'], '}$') # # plt.text(plt.xlim()[0] + 0.5 * (plt.xlim()[-1] - plt.xlim()[0]), # plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), # '{0}\n{1}'.format(rpstr, mtstr), ha='center', va='center', fontsize=10) # # plt.axvline((ingress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) # plt.text((ingress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), # '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{ingress}$', '\n', # r'$\mathrm{start}$'), # ha='right', va='top', fontsize=10) # plt.axvline((egress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) # plt.text((egress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), # '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{egress}$', '\n', # r'$\mathrm{end}$'), # ha='left', va='top', fontsize=10) # # plt.suptitle('{0}{1}{2}'.format(r'$\mathbf{', target, '}$'), fontsize=20) # plt.text(plt.xlim()[1], plt.ylim()[1], '{0}{1}{2}'.format(r'$', data_dates[set_number], '$'), # fontsize=12, ha='right', va='bottom') # # plt.subplot(4, 1, 4) # plt.cla() # plt.plot(self.results['output_series']['phase'][set_indices], # self.results['output_series']['residuals'][set_indices], 'ko', ms=2) # plt.plot(self.results['output_series']['phase'][set_indices], # np.zeros_like(self.results['output_series']['phase'][set_indices]), 'r-') # # plt.ylim(- 5 * np.std(self.results['output_series']['residuals'][set_indices]), # 5 * np.std(self.results['output_series']['residuals'][set_indices])) # # plt.xlabel(r'$\mathrm{phase}$', fontsize=15) # plt.ylabel(r'$\mathrm{residuals}$', fontsize=15) # # plt.xlim(-x_max, x_max) # plt.text(plt.xlim()[0] + 0.02 * (plt.xlim()[-1] - plt.xlim()[0]), # plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), # r'$\mathrm{rms}_\mathrm{res} = %.1e$' % # np.std(self.results['output_series']['residuals'][set_indices]), fontsize=10) # # plt.subplots_adjust(left=0.15, right=0.975, bottom=0.12, top=0.9, hspace=0.0) # # plt.savefig(os.path.join(os.path.split(export_file)[0], # 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), # transparent=True) # plt.close('all') # # def plot_detrended_models(self, export_file, target=None, data_dates=None, return_plot=False): # # if target is None: # target = ' ' # # if data_dates is None: # data_dates = map(str, ['set_{0}'.format(str(ff)) for ff in range(1, self.total_sets + 1)]) # # for set_number in range(self.total_sets): # # set_indices = np.where(self.data_set_number == set_number) # # fig = plt.figure(set_number + 1) # fig.set_tight_layout(False) # # self.results = {ff: self.results[ff] for ff in self.results} # # period = self.results['parameters']['P']['value'] # mt = self.results['parameters']['mt']['value'] # mt += round((np.mean(self.data_time[set_indices]) - mt) / period) * period # # prediction = (self.mid_time + # round((np.mean(self.data_time[set_indices]) - self.mid_time) / self.period) * self.period) # # duration = transit_duration(self.rp_over_rs, self.period, self.sma_over_rs, # self.inclination, self.eccentricity, self.periastron) # # ingress = prediction - duration / 2 # egress = prediction + duration / 2 # # plt.subplot2grid((4, 1), (0, 0), rowspan=3) # # plt.plot(self.results['detrended_output_series']['phase'][set_indices], # self.results['detrended_input_series']['value'][set_indices], 'ko', ms=2) # plt.plot(self.results['detrended_output_series']['phase'][set_indices], # self.results['detrended_output_series']['model'][set_indices], 'r-') # # plt.ylim(min(self.results['detrended_output_series']['model'][set_indices]) # - 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), # max(self.results['detrended_output_series']['model'][set_indices]) # + 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) # # plt.yticks(plt.yticks()[0][1:]) # plt.ylabel(r'$\mathrm{relative} \ \mathrm{flux}$', fontsize=15) # # plt.ylim(min(self.results['detrended_output_series']['model'][set_indices]) # - 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), # max(self.results['detrended_output_series']['model'][set_indices]) # + 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) # # plt.ylim(-1.17647 * (- plt.ylim()[0] + 0.15 * plt.ylim()[1]), plt.ylim()[1]) # # x_max = max(np.abs(self.results['detrended_output_series']['phase'][set_indices]) + # 0.05 * (max(self.results['detrended_output_series']['phase'][set_indices]) - # min(self.results['detrended_output_series']['phase'][set_indices]))) # plt.xlim(-x_max, x_max) # plt.tick_params(labelbottom='off') # # rpstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( # r'$R_\mathrm{p}/R_* = ', self.results['parameters']['rp_{0}'.format(str(set_number))]['print_value'], # '_{-', self.results['parameters']['rp_{0}'.format(str(set_number))]['print_m_error'], '}', '^{+', # self.results['parameters']['rp_{0}'.format(str(set_number))]['print_p_error'], '}$') # mtstr = '{0}{1}{2}{3}{4}{5}{6}{7}'.format( # r'$T_\mathrm{HJD} = ', self.results['parameters']['mt']['print_value'], '_{-', # self.results['parameters']['mt']['print_m_error'], '}', '^{+', # self.results['parameters']['mt']['print_p_error'], '}$') # # plt.text(plt.xlim()[0] + 0.5 * (plt.xlim()[-1] - plt.xlim()[0]), # plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), # '{0}{1}{2}'.format(rpstr, '\n', mtstr), ha='center', va='center', fontsize=10) # # plt.axvline((ingress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) # plt.text((ingress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), # '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{ingress}$', '\n', # r'$\mathrm{start}$'), # ha='right', va='top', fontsize=10) # plt.axvline((egress - mt) / period, 0.3, 1.0, ls='--', c='k', lw=0.75) # plt.text((egress - mt) / period, plt.ylim()[0] + 0.3 * (plt.ylim()[1] - plt.ylim()[0]), # '{0}{1}{2}{3}{4}'.format(r'$\mathrm{predicted}$', '\n', r'$\mathrm{egress}$', '\n', # r'$\mathrm{end}$'), # ha='left', va='top', fontsize=10) # # plt.suptitle('{0}{1}{2}'.format(r'$\mathbf{', target, '}$'), fontsize=20) # plt.text(plt.xlim()[1], plt.ylim()[1], '{0}{1}{2}'.format(r'$', data_dates[set_number], '$'), # fontsize=12, ha='right', va='bottom') # # plt.subplot(4, 1, 4) # plt.cla() # plt.plot(self.results['detrended_output_series']['phase'][set_indices], # self.results['detrended_output_series']['residuals'][set_indices], 'ko', ms=2) # plt.plot(self.results['detrended_output_series']['phase'][set_indices], # np.zeros_like(self.results['detrended_output_series']['phase'][set_indices]), 'r-') # # plt.ylim(- 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices]), # 5 * np.std(self.results['detrended_output_series']['residuals'][set_indices])) # # plt.xlabel(r'$\mathrm{phase}$', fontsize=15) # plt.ylabel(r'$\mathrm{residuals}$', fontsize=15) # # plt.xlim(-x_max, x_max) # # plt.text(plt.xlim()[0] + 0.02 * (plt.xlim()[-1] - plt.xlim()[0]), # plt.ylim()[0] + 0.07 * (plt.ylim()[-1] - plt.ylim()[0]), # r'$\mathrm{rms}_\mathrm{res} = %.1e$' % # np.std(self.results['detrended_output_series']['residuals'][set_indices]), # fontsize=10) # # plt.subplots_adjust(left=0.15, right=0.975, bottom=0.12, top=0.9, hspace=0.0) # # plt.savefig(os.path.join(os.path.split(export_file)[0], # 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), # transparent=True) # if return_plot: # return [plt.figure(ff + 1) for ff in range(self.total_sets)] # else: # plt.close('all') # # def save_models(self, export_file): # # for set_number in range(self.total_sets): # # self.results = {ff: self.results[ff] for ff in self.results} # # set_indices = np.where(self.data_set_number == set_number) # # np.savetxt(os.path.join(os.path.split(export_file)[0], # 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), # np.swapaxes([self.results['input_series']['hjd'][set_indices], # self.results['output_series']['phase'][set_indices], # self.results['input_series']['value'][set_indices], # self.results['input_series']['error'][set_indices], # self.results['output_series']['model'][set_indices], # self.results['output_series']['residuals'][set_indices] # ], 0, 1)) # # def save_detrended_models(self, export_file): # # for set_number in range(self.total_sets): # # self.results = {ff: self.results[ff] for ff in self.results} # # set_indices = np.where(self.data_set_number == set_number) # # np.savetxt(os.path.join(os.path.split(export_file)[0], # 'set_{0}_{1}'.format(str(set_number + 1), os.path.split(export_file)[1])), # np.swapaxes([self.results['detrended_input_series']['hjd'][set_indices], # self.results['detrended_output_series']['phase'][set_indices], # self.results['detrended_input_series']['value'][set_indices], # self.results['detrended_input_series']['error'][set_indices], # self.results['detrended_output_series']['model'][set_indices], # self.results['detrended_output_series']['residuals'][set_indices] # ], 0, 1))

47.943759

122

0.532617

8,374

69,902

4.243014

0.048722

0.066871

0.037151

0.03625

0.874363

0.833244

0.806394

0.783597

0.766598

0.737441

0

0.029128

0.307988

69,902

1,457

123

47.976664

0.705394

0.56821

0

0.4859

0

0.123341

0.029198

0

0.000686

0

1

0.032538

false

0.002169

0.030369

0.002169

0.073753

0.05423

0

null

0

1

0

null

0

6

2cf10dfbae5b4271c8144721dc28aca8dc63bea9

126

py

Python

tests/_site/import_error_app/catalogue/import_error_module.py

Jean1508/ya-madoa

1ffb1d11e15bf33e4c3a09698675a4357e887eaa

[ "BSD-3-Clause" ]

null

tests/_site/import_error_app/catalogue/import_error_module.py

Jean1508/ya-madoa

1ffb1d11e15bf33e4c3a09698675a4357e887eaa

[ "BSD-3-Clause" ]

5

2021-05-28T19:38:28.000Z

2022-03-12T00:45:39.000Z

tests/_site/import_error_app/catalogue/import_error_module.py

Jean1508/ya-madoa

1ffb1d11e15bf33e4c3a09698675a4357e887eaa

[ "BSD-3-Clause" ]

null

# On purpose raise ImportError from django import NonExistingClass class ImportErrorClass(NonExistingClass): pass

18

42

0.777778

12

126

8.166667

0.916667

0

0.190476

126

6

43

21

0.960784

0.222222

0

1

0

true

0.333333

0.666667

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

2cf4dec9649ecc658fb27dfaccc14b2acef9b7c3

107

py

Python

Python/Tests/TestData/Grammar/Calls.py

nanshuiyu/pytools

9f9271fe8cf564b4f94e9456d400f4306ea77c23

[ "Apache-2.0" ]

null

Python/Tests/TestData/Grammar/Calls.py

nanshuiyu/pytools

9f9271fe8cf564b4f94e9456d400f4306ea77c23

[ "Apache-2.0" ]

null

Python/Tests/TestData/Grammar/Calls.py

nanshuiyu/pytools

9f9271fe8cf564b4f94e9456d400f4306ea77c23

[ "Apache-2.0" ]

null

fob() fob(1) fob(oar = 1) fob(*oar) fob(**oar) fob(*oar, **baz) fob(oar = 1, baz = 2) fob(oar, baz)

13.375

22

0.514019

22

107

2.545455

0.272727

0.642857

0.25

0.428571

0

0.047619

0.214953

107

8

23

13.375

0.607143

0

null

0

null

0

1

0

null

1

0

1

0

null

0

1

0

6

fa22418ffaa5036d4cf65d5adf1e44a4817ca9a4

201

py

Python

JumpscalePortalClassic/portal/docgenerator/macros/pagebreak/1_main.py

threefoldtech/jumpscale_portal_classic

d14fe4a17c0486df7a87d149e900746654091fda

[ "Apache-2.0" ]

2

2016-04-14T14:05:01.000Z

2016-04-21T07:20:36.000Z

JumpscalePortalClassic/portal/docgenerator/macros/pagebreak/1_main.py

threefoldtech/jumpscale_portal_classic

d14fe4a17c0486df7a87d149e900746654091fda

[ "Apache-2.0" ]

74

2015-12-28T16:17:20.000Z

2021-09-08T12:28:59.000Z

lib/portal/docgenerator/macros/pagebreak/1_main.py

Jumpscale/jumpscale_portal8

3a4d56a1ba985b68fe9b525aed2486a54808332f

[ "Apache-2.0" ]

5

2016-03-08T07:49:51.000Z

2018-10-19T13:57:04.000Z

def main(j, params, service, tags, tasklet): page = params.page tags = params.tags page.addPageBreak() return params def match(j, params, service, tags, tasklet): return True

14.357143

45

0.651741

26

201

5.038462

0.461538

0.10687

0.21374

0.274809

0.381679

0

0.243781

201

13

46

15.461538

0.861842

0

1

0.285714

false

0

0.142857

0.571429

0

1

0

null

0

1

0

null

0

1

0

1

0

6

fa2fd3d61b1475189c206f62d45019e39d62f248

29

py

Python

padqc/compiler/__init__.py

qis-unipr/padqc

94599db20711dc755b53425951fa3cb15b749f64

[ "Apache-2.0" ]

1

2022-01-10T05:46:45.000Z

src/unv/__init__.py

UnvLabs/Python

27e26983199fd732854bdfb699efb7cf2f803f22

[ "MIT" ]

null

src/unv/__init__.py

UnvLabs/Python

27e26983199fd732854bdfb699efb7cf2f803f22

[ "MIT" ]

1

2021-02-18T22:11:18.000Z

from .compile import compile

14.5

28

0.827586

4

29

6

0.75

0

0.137931

29

1

29

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

fa671dcd24dc8f232001532ece907a12ef856fd8

94

py

Python

vagga2lithos/main.py

tailhook/vagga2lithos

fc174479b953b382e097dd51643ac2b4c2d56dee

[ "Apache-2.0", "MIT" ]

5

2016-11-18T03:19:02.000Z

2019-04-16T19:52:50.000Z

vagga2lithos/main.py

tailhook/vagga2lithos

fc174479b953b382e097dd51643ac2b4c2d56dee

[ "Apache-2.0", "MIT" ]

1

2018-03-15T18:23:50.000Z

vagga2lithos/main.py

tailhook/vagga2lithos

fc174479b953b382e097dd51643ac2b4c2d56dee

[ "Apache-2.0", "MIT" ]

null

import click @click.group() def main(): pass # load commands from . import gen, update

9.4

25

0.670213

13

94

4.846154

0.846154

0

0.223404

94

9

26

10.444444

0.863014

0.138298

0

1

0.2

true

0.2

0.4

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

6

d747be90fd0a556230fe9bd49bc10f0ed43b8306

29

py

Python

code/tmp_rtrip/sqlite3/__init__.py

emilyemorehouse/ast-and-me

3f58117512e125e1ecbe3c72f2f0d26adb80b7b3

[ "MIT" ]

24

2018-01-23T05:28:40.000Z

2021-04-13T20:52:59.000Z

code/tmp_rtrip/sqlite3/__init__.py

emilyemorehouse/ast-and-me

3f58117512e125e1ecbe3c72f2f0d26adb80b7b3

[ "MIT" ]

17

2017-12-21T18:32:31.000Z

2018-12-18T17:09:50.000Z

code/tmp_rtrip/sqlite3/__init__.py

emilyemorehouse/ast-and-me

3f58117512e125e1ecbe3c72f2f0d26adb80b7b3

[ "MIT" ]

null

from sqlite3.dbapi2 import *

14.5

28

0.793103

4

29

5.75

1

0

0.08

0.137931

29

1

29

0.84

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d75a20a8ee214be41ea183e350258f791d82b15e

135

py

Python

framework/layers/__init__.py

lukovnikov/transformer_generalization

a538bfbba6877cd7a21e710f2535df2e9236ba52

[ "MIT" ]

47

2021-08-30T00:41:15.000Z

2022-01-24T02:49:17.000Z

framework/layers/__init__.py

lukovnikov/transformer_generalization

a538bfbba6877cd7a21e710f2535df2e9236ba52

[ "MIT" ]

null

framework/layers/__init__.py

lukovnikov/transformer_generalization

a538bfbba6877cd7a21e710f2535df2e9236ba52

[ "MIT" ]

5

2021-09-04T23:51:51.000Z

2022-03-10T14:03:24.000Z

from .positional_encoding import PositionalEncoding, sinusoidal_pos_embedding from .cross_entropy_label_smoothing import cross_entropy

45

77

0.911111

16

135

7.25

0.75

0.206897

0

0.066667

135

2

78

67.5

0.920635

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

d7613c67dab581482379e6ee5a47c6fb6204d3d8

26

py

Python

tests/__init__.py

zapp-oz/AutoGit

a2894af75ee51bf84e656d4f842901e9f5940b6d

[ "MIT" ]

null

tests/__init__.py

zapp-oz/AutoGit

a2894af75ee51bf84e656d4f842901e9f5940b6d

[ "MIT" ]

null

tests/__init__.py

zapp-oz/AutoGit

a2894af75ee51bf84e656d4f842901e9f5940b6d

[ "MIT" ]

null

from . import test_git_ops

26

0.846154

5

26

4

1

0

0.115385

26

1

26

0.869565

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d76c33b1e8fbc893158b8149cd4916e80cdc6ba4

45

py

Python

corehq/apps/hqwebapp/tests/__init__.py

johan--/commcare-hq

86ee99c54f55ee94e4c8f2f6f30fc44e10e69ebd

[ "BSD-3-Clause" ]

null

corehq/apps/hqwebapp/tests/__init__.py

johan--/commcare-hq

86ee99c54f55ee94e4c8f2f6f30fc44e10e69ebd

[ "BSD-3-Clause" ]

1

2022-03-12T01:03:25.000Z

corehq/apps/hqwebapp/tests/__init__.py

johan--/commcare-hq

86ee99c54f55ee94e4c8f2f6f30fc44e10e69ebd

[ "BSD-3-Clause" ]

null

from .test_hq_shared_tags import TestCaseTag

22.5

44

0.888889

7

45

5.285714

1

0

0.088889

45

1

45

0.902439

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ad02f6a572e847592a66b596b845c260779c4e3e

75

py

Python

py_tdlib/constructors/notification_group_type_calls.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/notification_group_type_calls.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/notification_group_type_calls.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Type class notificationGroupTypeCalls(Type): pass

12.5

39

0.8

8

75

7.5

0.875

0

0.133333

75

5

40

15

0.923077

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

ad0a6e266fa6266ac564b6e321125a23c42b0d64

128,605

py

Python

test/water_clusters/make_input.py

susilehtola/aquarius

9160e73bd7e3e0d8d97b10d00d9a4860aee709d2

[ "BSD-3-Clause" ]

18

2015-02-11T15:02:39.000Z

2021-09-24T13:10:12.000Z

test/water_clusters/make_input.py

susilehtola/aquarius

9160e73bd7e3e0d8d97b10d00d9a4860aee709d2

[ "BSD-3-Clause" ]

21

2015-06-23T13:32:29.000Z

2022-02-15T20:14:42.000Z

test/water_clusters/make_input.py

susilehtola/aquarius

9160e73bd7e3e0d8d97b10d00d9a4860aee709d2

[ "BSD-3-Clause" ]

8

2016-01-09T23:36:21.000Z

2019-11-19T14:22:34.000Z

#!/usr/bin/python import sys if ( len(sys.argv) != 4 ): print "Usage: ./make_input.py <cluster> <basis> <method>" print "<cluster> can be: w1 w2 w3 w4 w5 w6cage w6book w6prism w6cyclic w7 w8s4 w8d2d" print " w9 w10 w11i434 w11i4412 w11i443 w11i515 w11i551 w12 w13 w14" print " w15 w16 w17int w17surf w18 w19 w20dode w20fused w20face w20edge" print " rubrene" print "<basis> can be 6-31G 6-311G cc-pVDZ cc-pVTZ cc-pVQZ aug-cc-pVDZ aug-cc-pVTZ aug-cc-pVQZ etc." print "Note that <basis> is case sensitive and must correspond to a file in AQUARIUS/basis." print "<method> can be ccd, ccsd, or ccsdt" sys.exit() #------------ # Rubrene #------------ def print_rubrene(file): file.write('\tatom {C, 0.0000000000, 0.0000000000, 0.7386629749 },\n') file.write('\tatom {C, -1.2483730887, 0.0888707092, 1.4320804162 },\n') file.write('\tatom {C, -2.4387379231, 0.3562298522, 0.7287080969 },\n') file.write('\tatom {C, -3.6963513178, 0.5360669578, 1.4047565975 },\n') file.write('\tatom {C, -4.8565917531, 0.7574126966, 0.7195212871 },\n') file.write('\tatom {C, -1.4047304272, -0.2925466203, 2.8766766348 },\n') file.write('\tatom {C, -1.4608851165, -1.6566002050, 3.2010433539 },\n') file.write('\tatom {C, -1.7156969530, -2.0726251992, 4.5078354542 },\n') file.write('\tatom {C, -1.9273173957, -1.1294519924, 5.5139696863 },\n') file.write('\tatom {C, -1.8847258306, 0.2305869075, 5.2017074868 },\n') file.write('\tatom {C, -1.6318196804, 0.6445713746, 3.8942551073 },\n') file.write('\tatom {H, -3.7136001469, 0.5055498407, 2.4859255482 },\n') file.write('\tatom {H, -5.7860241262, 0.9079508679, 1.2609572299 },\n') file.write('\tatom {H, -1.3092313361, -2.3929774307, 2.4170229637 },\n') file.write('\tatom {H, -1.7566049358, -3.1338521657, 4.7371683252 },\n') file.write('\tatom {H, -2.1277721044, -1.4503977356, 6.5320681783 },\n') file.write('\tatom {H, -2.0489582393, 0.9729207845, 5.9774668901 },\n') file.write('\tatom {H, -1.5985958139, 1.7035156402, 3.6590400764 },\n') file.write('\tatom {C, 0.0000000000, 0.0000000000, -0.7355835217 },\n') file.write('\tatom {C, 1.2483730887, -0.0888707092, 1.4320804162 },\n') file.write('\tatom {C, -2.4372856050, 0.3712368198, -0.7172953151 },\n') file.write('\tatom {C, -4.8542635050, 0.7786660597, -0.7038756087 },\n') file.write('\tatom {C, 1.2487664643, -0.1076096437, -1.4258829382 },\n') file.write('\tatom {C, -1.2487664643, 0.1076096437, -1.4258829382 },\n') file.write('\tatom {C, 2.4387379231, -0.3562298522, 0.7287080969 },\n') file.write('\tatom {C, 1.4047304272, 0.2925466203, 2.8766766348 },\n') file.write('\tatom {C, -3.6924121455, 0.5742247089, -1.3916349861 },\n') file.write('\tatom {H, -5.7816030635, 0.9471760195, -1.2436128745 },\n') file.write('\tatom {C, 2.4372856050, -0.3712368198, -0.7172953151 },\n') file.write('\tatom {C, 1.4161903836, 0.2432248114, -2.8773546944 },\n') file.write('\tatom {C, -1.4161903836, -0.2432248114, -2.8773546944 },\n') file.write('\tatom {C, 3.6963513178, -0.5360669578, 1.4047565975 },\n') file.write('\tatom {C, 1.4608851165, 1.6566002050, 3.2010433539 },\n') file.write('\tatom {C, 1.6318196804, -0.6445713746, 3.8942551073 },\n') file.write('\tatom {H, -3.7063324227, 0.5748189620, -2.4732886534 },\n') file.write('\tatom {C, 3.6924121455, -0.5742247089, -1.3916349861 },\n') file.write('\tatom {C, 1.5338943044, 1.5975040689, -3.2246030980 },\n') file.write('\tatom {C, 1.6007048957, -0.7204065916, -3.8785605231 },\n') file.write('\tatom {C, -1.5338943044, -1.5975040689, -3.2246030980 },\n') file.write('\tatom {C, -1.6007048957, 0.7204065916, -3.8785605231 },\n') file.write('\tatom {C, 4.8565917531, -0.7574126966, 0.7195212871 },\n') file.write('\tatom {H, 3.7136001469, -0.5055498407, 2.4859255482 },\n') file.write('\tatom {C, 1.7156969530, 2.0726251992, 4.5078354542 },\n') file.write('\tatom {H, 1.3092313361, 2.3929774307, 2.4170229637 },\n') file.write('\tatom {C, 1.8847258306, -0.2305869075, 5.2017074868 },\n') file.write('\tatom {H, 1.5985958139, -1.7035156402, 3.6590400764 },\n') file.write('\tatom {C, 4.8542635050, -0.7786660597, -0.7038756087 },\n') file.write('\tatom {H, 3.7063324227, -0.5748189620, -2.4732886534 },\n') file.write('\tatom {C, 1.8050372220, 1.9795794408, -4.5385104659 },\n') file.write('\tatom {H, 1.4175312323, 2.3531485506, -2.4529473087 },\n') file.write('\tatom {C, 1.8705463877, -0.3404309422, -5.1929267030 },\n') file.write('\tatom {H, 1.5225138636, -1.7726479350, -3.6245598182 },\n') file.write('\tatom {C, -1.8050372220, -1.9795794408, -4.5385104659 },\n') file.write('\tatom {H, -1.4175312323, -2.3531485506, -2.4529473087 },\n') file.write('\tatom {C, -1.8705463877, 0.3404309422, -5.1929267030 },\n') file.write('\tatom {H, -1.5225138636, 1.7726479350, -3.6245598182 },\n') file.write('\tatom {H, 5.7860241262, -0.9079508679, 1.2609572299 },\n') file.write('\tatom {C, 1.9273173957, 1.1294519924, 5.5139696863 },\n') file.write('\tatom {H, 1.7566049358, 3.1338521657, 4.7371683252 },\n') file.write('\tatom {H, 2.0489582393, -0.9729207845, 5.9774668901 },\n') file.write('\tatom {H, 5.7816030635, -0.9471760195, -1.2436128745 },\n') file.write('\tatom {C, 1.9731362015, 1.0109252482, -5.5283824054 },\n') file.write('\tatom {H, 1.8931818096, 3.0338872143, -4.7857992482 },\n') file.write('\tatom {H, 2.0016371726, -1.1023529188, -5.9559253229 },\n') file.write('\tatom {C, -1.9731362015, -1.0109252482, -5.5283824054 },\n') file.write('\tatom {H, -1.8931818096, -3.0338872143, -4.7857992482 },\n') file.write('\tatom {H, -2.0016371726, 1.1023529188, -5.9559253229 },\n') file.write('\tatom {H, 2.1277721044, 1.4503977356, 6.5320681783 },\n') file.write('\tatom {H, 2.1867218297, 1.3050773503, -6.5519186432 },\n') file.write('\tatom {H, -2.1867218297, -1.3050773503, -6.5519186432 },\n') #------------ #Monomer *** C2v #------------ def print_w1(file,ycor): file.write('\tatom {O, 0.00000000, '+str(ycor)+', 0.11726921 },\n') file.write('\tatom {H, 0.75698224, '+str(ycor)+', -0.46907685 },\n') file.write('\tatom {H, -0.75698224, '+str(ycor)+', -0.46907685 },\n') #------------ #Dimer *** Cs #------------ def print_w2(file): file.write('\tatom {O, -0.000545, 1.517541, 0.000000 },\n') file.write('\tatom {H, 0.094538, 0.553640, 0.000000 },\n') file.write('\tatom {H, 0.901237, 1.847958, 0.000000 },\n') file.write('\tatom {O, -0.000545, -1.389760, 0.000000 },\n') file.write('\tatom {H, -0.493527, -1.711924, 0.761014 },\n') file.write('\tatom {H, -0.493527, -1.711924, -0.761014 },\n') #------------- #Trimer *** C1 #------------- def print_w3(file): file.write('\tatom {H, 1.218038, 0.017442, -0.022009 },\n') file.write('\tatom {O, 1.295683, -0.951662, -0.092916 },\n') file.write('\tatom {H, 1.961236, -1.203127, 0.552608 },\n') file.write('\tatom {H, 0.093268, 2.241120, -0.596056 },\n') file.write('\tatom {O, 0.179908, 1.594249, 0.109280 },\n') file.write('\tatom {H, -0.624503, 1.046616, 0.055883 },\n') file.write('\tatom {H, -2.030801, -1.071624, 0.569877 },\n') file.write('\tatom {O, -1.476402, -0.636452, -0.082957 },\n') file.write('\tatom {H, -0.610755, -1.079506, -0.027553 },\n') #--------------- #Tetramer *** S4 #--------------- def print_w4(file): file.write('\tatom {O, -1.367062, 1.364510, 0.007273 },\n') file.write('\tatom {O, -1.364510, -1.367062, -0.007273 },\n') file.write('\tatom {O, 1.364510, 1.367062, -0.007273 },\n') file.write('\tatom {O, 1.367062, -1.364510, 0.007273 },\n') file.write('\tatom {H, -0.395152, 1.503429, -0.005375 },\n') file.write('\tatom {H, -1.503429, -0.395152, 0.005375 },\n') file.write('\tatom {H, 1.503429, 0.395152, 0.005375 },\n') file.write('\tatom {H, 0.395152, -1.503429, -0.005375 },\n') file.write('\tatom {H, -1.687281, 1.875361, 0.755434 },\n') file.write('\tatom {H, -1.875361, -1.687281, -0.755434 },\n') file.write('\tatom {H, 1.875361, 1.687281, -0.755434 },\n') file.write('\tatom {H, 1.687281, -1.875361, 0.755434 },\n') #--------------- #Pentamer *** C1 #--------------- def print_w5(file): file.write('\tatom {O, 2.289015, 0.225784, 0.175030 },\n') file.write('\tatom {H, 1.837891, -0.638872, 0.046444 },\n') file.write('\tatom {H, 2.811304, 0.122451, 0.974687 },\n') file.write('\tatom {O, 0.929887, -2.095904, -0.167528 },\n') file.write('\tatom {H, -0.037083, -1.936553, -0.084181 },\n') file.write('\tatom {H, 1.034959, -2.583078, -0.988978 },\n') file.write('\tatom {O, -1.718101, -1.549268, 0.073447 },\n') file.write('\tatom {H, -1.882083, -0.580570, 0.056990 },\n') file.write('\tatom {H, -2.170566, -1.871677, 0.857083 },\n') file.write('\tatom {O, -1.987637, 1.157925, -0.077866 },\n') file.write('\tatom {H, -1.103971, 1.590183, -0.076556 },\n') file.write('\tatom {H, -2.534625, 1.699982, 0.496152 },\n') file.write('\tatom {O, 0.498426, 2.249945, -0.063688 },\n') file.write('\tatom {H, 1.178269, 1.547359, 0.044627 },\n') file.write('\tatom {H, 0.773193, 2.742924, -0.841426 },\n') #------------------- #Hexamer_cage *** C1 #------------------- def print_w6cage(file): file.write('\tatom {O, .87746626, 1.70810837, .47631700\n') file.write('\tatom {H, 1.69363812, 1.19357153, .28997545\n') file.write('\tatom {H, 1.16537360, 2.60804843, .65262299\n') file.write('\tatom {O, -.81592121, .61034772, -1.61581462 },\n') file.write('\tatom {H, -.26718594, 1.17109579, -1.04349788 },\n') file.write('\tatom {H, -.36582905, -.24649881, -1.56526881 },\n') file.write('\tatom {O, -.63660726, -.48685974, 1.61880639 },\n') file.write('\tatom {H, -.19581869, .37060555, 1.51121727 },\n') file.write('\tatom {H, -1.53977900, -.32481815, 1.28377278 },\n') file.write('\tatom {O, .57958746, -1.69528831, -.42798860\n') file.write('\tatom {H, .43229451, -2.64323542, -.48817257\n') file.write('\tatom {H, .09134000, -1.38625895, .38012967\n') file.write('\tatom {O, 2.79390774, -.10315373, -.17926594\n') file.write('\tatom {H, 3.44976591, -.44577598, .43415635\n') file.write('\tatom {H, 2.14838286, -.82929443, -.30024187\n') file.write('\tatom {O, -2.88225438, -.06267425, .06008357\n') file.write('\tatom {H, -2.28540757, .26575834, -.64623972\n') file.write('\tatom {H, -3.65812342, .50275705, .03758316\n') #------------------- #Hexamer_book *** C1 #------------------- def print_w6book(file): file.write('\tatom {O, .12690919, 1.55143405, .88294964 },\n') file.write('\tatom {H, .97284357, 1.51744599, .37215837 },\n') file.write('\tatom {H, .28507553, 2.15693315, 1.61278908 },\n') file.write('\tatom {O, 2.40793689, 1.19494170, -.47593962 },\n') file.write('\tatom {H, 2.47425116, .21052194 -.50791280 },\n') file.write('\tatom {H, 2.52608509, 1.48774408, -1.38342225 },\n') file.write('\tatom {O, 2.26093548, -1.48582803, -.45281407 },\n') file.write('\tatom {H, 2.87900544, -2.06214604, .00406231 },\n') file.write('\tatom {H, 1.40693434, -1.57230106, .03667764 },\n') file.write('\tatom {O, -2.46634492, -1.39738447, -.44099696 },\n') file.write('\tatom {H, -2.53313762, -.42400253, -.50763215 },\n') file.write('\tatom {H, -3.27971184, -1.67686815, -.01242165 },\n') file.write('\tatom {O, -2.30167782, 1.36485164, -.44449265 },\n') file.write('\tatom {H, -1.44118213, 1.54197674, -.01689196 },\n') file.write('\tatom {H, -2.29684418, 1.88395767, -1.25295402 },\n') file.write('\tatom {O, -.03575629, -1.36737375, .93305473 },\n') file.write('\tatom {H, -.05262084, -.41957364, 1.13558028 },\n') file.write('\tatom {H, -.88407140, -1.52142902, .47340296 },\n') #-------------------- #Hexamer_prism *** C1 #-------------------- def print_w6prism(file): file.write('\tatom {O, -1.98809642, 1.07259854, -.17008272 },\n') file.write('\tatom {H, -2.65432215, 1.75406534, -.29457427 },\n') file.write('\tatom {H, -1.12410682, 1.54133723, -.16808174 },\n') file.write('\tatom {O, -1.01210730, -1.16226196, 1.41783859 },\n') file.write('\tatom {H, -1.00300319, -1.51670753, .50465897 },\n') file.write('\tatom {H, -1.58053367, -.38562387, 1.30626941 },\n') file.write('\tatom {O, 1.45258039, -.19062642, 1.46779070 },\n') file.write('\tatom {H, .54824824, -.59584398, 1.56580550 },\n') file.write('\tatom {H, 1.93276785, -.40081928, 2.27333290 },\n') file.write('\tatom {O, -.94561210, -1.39646518, -1.35471457 },\n') file.write('\tatom {H, -1.43675949, -.56245450, -1.30670239 },\n') file.write('\tatom {H, -.02948938, -1.11988543, -1.51719299 },\n') file.write('\tatom {O, 1.78328499, -.40814713, -1.26763066 },\n') file.write('\tatom {H, 2.55647293, -.82448997, -1.65880940 },\n') file.write('\tatom {H, 1.89247505, -.49176846, -.30058670 },\n') file.write('\tatom {O, .57696197, 2.02004218, -.11301203 },\n') file.write('\tatom {H, 1.02072837, 1.61701116, -.87156630 },\n') file.write('\tatom {H, .94398492, 1.51061477, .62833682 },\n') #--------------------- #Hexamer_Cyclic *** S6 #--------------------- def print_w6cyclic(file): file.write('\tatom {O, .00023538, 2.69029255, .14950471 },\n') file.write('\tatom {O, -2.32998012, -1.34494169, .14950441 },\n') file.write('\tatom {O, 2.32998012, 1.34494169, -.14950441 },\n') file.write('\tatom {O, -2.32974435, 1.34535112, -.14950375 },\n') file.write('\tatom {O, -.00023538, -2.69029255, -.14950471 },\n') file.write('\tatom {O, 2.32974435, -1.34535112, .14950375 },\n') file.write('\tatom {H, .84303260, 2.19639176, .03463900 },\n') file.write('\tatom {H, -2.32364786, -.36810840, .03463888 },\n') file.write('\tatom {H, 2.32364786, .36810840, -.03463888 },\n') file.write('\tatom {H, -1.48061559, 1.82828372, -.03463790 },\n') file.write('\tatom {H, -.84303260, -2.19639176, -.03463900 },\n') file.write('\tatom {H, 1.48061559, -1.82828372, .03463790 },\n') file.write('\tatom {H, .12287628, 3.21232017, .94654204 },\n') file.write('\tatom {H, -2.84339064, -1.49974629, .94654344 },\n') file.write('\tatom {H, 2.84339064, 1.49974629, -.94654344 },\n') file.write('\tatom {H, -2.72051496, 1.71257699, -.94654475 },\n') file.write('\tatom {H, -.12287628, -3.21232017, -.94654204 },\n') file.write('\tatom {H, 2.72051496, -1.71257699, .94654475 },\n') #-------------- #Heptamer (n=7) #-------------- def print_w7(file): file.write('\tatom {O, -0.46306507, -2.84560143, 0.34712980 },\n') file.write('\tatom {H, -0.31185448, -3.74723642, 0.05234746 },\n') file.write('\tatom {H, -0.60259983, -2.31575342, -0.47038548 },\n') file.write('\tatom {O, 1.84489062, 0.25067396, -1.20027152 },\n') file.write('\tatom {H, 2.63515099, 0.41824386, -1.72121662 },\n') file.write('\tatom {H, 1.46223315, 1.13476086, -0.99006607 },\n') file.write('\tatom {O, -0.36089385, 1.06267739, 1.87503037 },\n') file.write('\tatom {H, -0.44058089, 1.21621663, 2.82039947 },\n') file.write('\tatom {H, 0.24249561, 0.27291766, 1.77033787 },\n') file.write('\tatom {O, 1.25770268, -0.94282108, 1.34833194 },\n') file.write('\tatom {H, 0.73624113, -1.73036585, 1.09041584 },\n') file.write('\tatom {H, 1.67299069, -0.65240393, 0.51959506 },\n') file.write('\tatom {O, 0.51098073, 2.46987019, -0.40854717 },\n') file.write('\tatom {H, 0.33154661, 2.21905129, 0.51484431 },\n') file.write('\tatom {H, -0.36738878, 2.41346155, -0.80745002 },\n') file.write('\tatom {O, -0.68279808, -1.06009111, -1.69106587 },\n') file.write('\tatom {H, -1.23658236, -0.35698007, -1.31005956 },\n') file.write('\tatom {H, 0.20346941, -0.66506167, -1.72575016 },\n') file.write('\tatom {O, -2.06529537, 1.02745574, -0.29419144 },\n') file.write('\tatom {H, -1.67380330, 0.97232115, 0.60004746 },\n') file.write('\tatom {H, -3.01776458, 0.99606215, -0.16747231 },\n') #-------------- #Octamer *** S4 #-------------- def print_w8s4(file): file.write('\tatom {O, 1.99300294, -.06309578, 1.47601417 },\n') file.write('\tatom {O, -1.99300294, .06309578, 1.47601417 },\n') file.write('\tatom {O, -.06309578, -1.99300294, -1.47601417 },\n') file.write('\tatom {O, .06309578, 1.99300294, -1.47601417 },\n') file.write('\tatom {H, 2.69237274, -.27127359, 2.10172647 },\n') file.write('\tatom {H, -2.69237274, .27127359, 2.10172647 },\n') file.write('\tatom {H, -.27127359, -2.69237274, -2.10172647 },\n') file.write('\tatom {H, .27127359, 2.69237274, -2.10172647 },\n') file.write('\tatom {H, 1.34051465, -.80936971, 1.52652079 },\n') file.write('\tatom {H, -1.34051465, .80936971, 1.52652079 },\n') file.write('\tatom {H, -.80936971, -1.34051465, -1.52652079 },\n') file.write('\tatom {H, .80936971, 1.34051465, -1.52652079 },\n') file.write('\tatom {O, 1.89520992, .06259188, -1.35912522 },\n') file.write('\tatom {O, -1.89520992, -.06259188, -1.35912522 },\n') file.write('\tatom {O, .06259188, -1.89520992, 1.35912522 },\n') file.write('\tatom {O, -.06259188, 1.89520992, 1.35912522 },\n') file.write('\tatom {H, 1.38132939, -.74888632, -1.51574883 },\n') file.write('\tatom {H, -1.38132939, .74888632, -1.51574883 },\n') file.write('\tatom {H, -.74888632, -1.38132939, 1.51574883 },\n') file.write('\tatom {H, .74888632, 1.38132939, 1.51574883 },\n') file.write('\tatom {H, 2.13830549, .01009435, -.41812902 },\n') file.write('\tatom {H, -2.13830549, -.01009435, -.41812902 },\n') file.write('\tatom {H, .01009435, -2.13830549, .41812902 },\n') file.write('\tatom {H, -.01009435, 2.13830549, .41812902 },\n') #--------------- #Octamer *** D2d #--------------- def print_w8d2d(file): file.write('\tatom {O, -1.46966769, 1.46966769, 1.34326600 },\n') file.write('\tatom {O, 1.46966769, -1.46966769, 1.34326600 },\n') file.write('\tatom {O, 1.46966769, 1.46966769, -1.34326600 },\n') file.write('\tatom {O, -1.46966769, -1.46966769, -1.34326600 },\n') file.write('\tatom {O, -1.36565412, 1.36565412, -1.32090835 },\n') file.write('\tatom {O, 1.36565412, -1.36565412, -1.32090835 },\n') file.write('\tatom {O, 1.36565412, 1.36565412, 1.32090835 },\n') file.write('\tatom {O, -1.36565412, -1.36565412, 1.32090835 },\n') file.write('\tatom {H, -2.10464162, 2.10464162, 1.68605609 },\n') file.write('\tatom {H, 2.10464162, -2.10464162, 1.68605609 },\n') file.write('\tatom {H, 2.10464162, 2.10464162, -1.68605609 },\n') file.write('\tatom {H, -2.10464162, -2.10464162, -1.68605609 },\n') file.write('\tatom {H, -1.52398844, 1.52398844, 0.35383543 },\n') file.write('\tatom {H, 1.52398844, -1.52398844, 0.35383543 },\n') file.write('\tatom {H, 1.52398844, 1.52398844, -0.35383543 },\n') file.write('\tatom {H, -1.52398844, -1.52398844, -0.35383543 },\n') file.write('\tatom {H, 1.51043211, 0.42340972, 1.51629003 },\n') file.write('\tatom {H, -1.51043211, -0.42340972, 1.51629003 },\n') file.write('\tatom {H, 0.42340972, -1.51043211, -1.51629003 },\n') file.write('\tatom {H, -0.42340972, 1.51043211, -1.51629003 },\n') file.write('\tatom {H, -1.51043211, 0.42340972, -1.51629003 },\n') file.write('\tatom {H, 1.51043211, -0.42340972, -1.51629003 },\n') file.write('\tatom {H, -0.42340972, -1.51043211, 1.51629003 },\n') file.write('\tatom {H, 0.42340972, 1.51043211, 1.51629003 },\n') #------------- #Nonamer (n=9) #------------- def print_w9(file): file.write('\tatom {O, -0.14423567, -3.30115048, 0.03928978 },\n') file.write('\tatom {H, -0.32449295, -3.99879230, -0.59601201 },\n') file.write('\tatom {H, -0.88532777, -2.65077353, -0.06170448 },\n') file.write('\tatom {O, 1.49264094, 0.37393128, -1.75371713 },\n') file.write('\tatom {H, 1.64172129, 1.15033975, -1.18630321 },\n') file.write('\tatom {H, 1.74950109, -0.38438355, -1.19944121 },\n') file.write('\tatom {O, -2.01172471, -1.40607776, -0.18016347 },\n') file.write('\tatom {H, -1.80580932, -0.80898258, -0.92073297 },\n') file.write('\tatom {H, -1.96360403, -0.83667527, 0.60810472 },\n') file.write('\tatom {O, 1.98006129, -1.70338387, 0.11260098 },\n') file.write('\tatom {H, 1.26037502, -2.38156679, 0.05360476 },\n') file.write('\tatom {H, 2.79676709, -2.19376994, 0.24208099 },\n') file.write('\tatom {O, 1.38609229, 2.47288083, 0.14383518 },\n') file.write('\tatom {H, 0.40159688, 2.58065033, 0.06882204 },\n') file.write('\tatom {H, 1.75448436, 3.35910354, 0.19570425 },\n') file.write('\tatom {O, 1.14877099, 0.30157502, 1.95056315 },\n') file.write('\tatom {H, 1.48584111, -0.43780643, 1.41385840 },\n') file.write('\tatom {H, 1.39709310, 1.09729015, 1.44893216 },\n') file.write('\tatom {O, -1.14485510, 0.46396139, -2.12809929 },\n') file.write('\tatom {H, -1.37650220, 0.49988809, -3.06029252 },\n') file.write('\tatom {H, -0.15553827, 0.39121296, -2.08870291 },\n') file.write('\tatom {O, -1.51553094, 0.41505867, 1.93078837 },\n') file.write('\tatom {H, -0.53309190, 0.32662137, 2.03998763 },\n') file.write('\tatom {H, -1.88760438, 0.40212138, 2.81700243 },\n') file.write('\tatom {O, -1.26689128, 2.40738706, -0.06733177 },\n') file.write('\tatom {H, -1.40034323, 1.84974182, -0.85380574 },\n') file.write('\tatom {H, -1.53577697, 1.83794512, 0.67494834 },\n') #-------------- #Decamer (n=10) #-------------- def print_w10(file): file.write('\tatom {O, -1.55682959, 1.99913676, 1.22533588 },\n') file.write('\tatom {H, -0.59298827, 2.17569825, 1.30499409 },\n') file.write('\tatom {H, -1.99557150, 2.68355859, 1.73849182 },\n') file.write('\tatom {O, 2.32177282, -0.76277855, -1.42669411 },\n') file.write('\tatom {H, 1.59105553, -1.43353953, -1.36423833 },\n') file.write('\tatom {H, 3.00556104, -1.16198054, -1.97170813 },\n') file.write('\tatom {O, -1.61325150, 1.37598702, -1.60947581 },\n') file.write('\tatom {H, -0.65665433, 1.53734850, -1.76954163 },\n') file.write('\tatom {H, -1.75324957, 1.73531947, -0.71955514 },\n') file.write('\tatom {O, 1.15495708, 2.25580534, 1.16165925 },\n') file.write('\tatom {H, 1.56205957, 1.35383240, 1.29633057 },\n') file.write('\tatom {H, 1.70314455, 2.86626909, 1.66309307 },\n') file.write('\tatom {O, 2.20709492, -0.14872772, 1.32313726 },\n') file.write('\tatom {H, 1.58553666, -0.84077746, 1.61628226 },\n') file.write('\tatom {H, 2.42610789, -0.39646359, 0.40641496 },\n') file.write('\tatom {O, 0.33228679, -2.46089610, -0.99370195 },\n') file.write('\tatom {H, 0.30884918, -2.53777465, -0.02476291 },\n') file.write('\tatom {H, -0.54269598, -2.09681688, -1.22506306 },\n') file.write('\tatom {O, 1.09994277, 1.78719573, -1.72521459 },\n') file.write('\tatom {H, 1.25026245, 2.11505418, -0.82532285 },\n') file.write('\tatom {H, 1.57602755, 0.93864515, -1.74674617 },\n') file.write('\tatom {O, 0.23664110, -2.08073213, 1.83761839 },\n') file.write('\tatom {H, 0.16506577, -2.69854162, 2.57058807 },\n') file.write('\tatom {H, -0.63561742, -1.60693505, 1.78751007 },\n') file.write('\tatom {O, -2.04501919, -0.79447205, 1.43251978 },\n') file.write('\tatom {H, -1.94086906, 0.17294968, 1.45336493 },\n') file.write('\tatom {H, -2.25772766, -0.99361260, 0.50281358 },\n') file.write('\tatom {O, -2.14305333, -1.18847857, -1.36396916 },\n') file.write('\tatom {H, -2.85215622, -1.44851554, -1.95857066 },\n') file.write('\tatom {H, -1.95986968, -0.22568719, -1.55342417 },\n') #---------------------------- #Endecamer (n=11), 434 Isomer #---------------------------- def print_w11i434(file): file.write('\tatom {O, -2.08119667, -2.26673485, -0.52122025 },\n') file.write('\tatom {H, -2.87105167, -2.78737932, -0.69063304 },\n') file.write('\tatom {H, -2.37048203, -1.48052425, 0.00808991 },\n') file.write('\tatom {O, 0.02632908, 2.46420106, 1.43136415 },\n') file.write('\tatom {H, -0.79872021, 2.51272310, 0.91403477 },\n') file.write('\tatom {H, 0.03392860, 1.56479884, 1.79448727 },\n') file.write('\tatom {O, -0.10639962, -1.18952211, -2.30993496 },\n') file.write('\tatom {H, -0.83122588, -1.60450407, -1.81428466 },\n') file.write('\tatom {H, 0.70146823, -1.55647816, -1.91492397 },\n') file.write('\tatom {O, -2.53660296, -0.13426118, 1.00652753 },\n') file.write('\tatom {H, -1.76448175, -0.10778780, 1.59108568 },\n') file.write('\tatom {H, -2.48980443, 0.70013958, 0.50025834 },\n') file.write('\tatom {O, 0.15122048, -2.65188991, 1.10644184 },\n') file.write('\tatom {H, -0.65274681, -2.72021834, 0.55885102 },\n') file.write('\tatom {H, 0.88417011, -2.67183587, 0.46397298 },\n') file.write('\tatom {O, 2.13888494, -2.13440481, -0.78805319 },\n') file.write('\tatom {H, 2.93049477, -2.60943049, -1.05525823 },\n') file.write('\tatom {H, 2.44486586, -1.33305502, -0.29341074 },\n') file.write('\tatom {O, 2.64879913, 0.01324964, 0.70328241 },\n') file.write('\tatom {H, 2.54120429, 0.87044707, 0.25037000 },\n') file.write('\tatom {H, 1.93995918, 0.00174018, 1.36408007 },\n') file.write('\tatom {O, 0.14754784, -0.31377914, 2.31635550 },\n') file.write('\tatom {H, 0.20756983, -0.48066858, 3.26302056 },\n') file.write('\tatom {H, 0.15063221, -1.21915761, 1.88819098 },\n') file.write('\tatom {O, 1.91413653, 2.45179984, -0.46204184 },\n') file.write('\tatom {H, 2.44614529, 3.25118653, -0.50821174 },\n') file.write('\tatom {H, 1.25730486, 2.59531756, 0.26467692 },\n') file.write('\tatom {O, -0.24381434, 1.54060642, -2.15574462 },\n') file.write('\tatom {H, 0.59881902, 1.83276745, -1.77386015 },\n') file.write('\tatom {H, -0.16451956, 0.56552049, -2.25620710 },\n') file.write('\tatom {O, -2.06702886, 2.20623002, -0.40395822 },\n') file.write('\tatom {H, -2.70789898, 2.81776225, -0.77656938 },\n') file.write('\tatom {H, -1.43251084, 1.96924165, -1.14177635 },\n') #----------------------------- #Endecamer (n=11), 4412 Isomer #----------------------------- def print_w11i4412(file): file.write('\tatom {O, 2.51766192, 0.53321759, -1.03874478 },\n') file.write('\tatom {H, 1.86897322, -0.14656265, -1.30684503 },\n') file.write('\tatom {H, 2.10586438, 1.37269025, -1.30696563 },\n') file.write('\tatom {O, 0.09186913, -3.91493968, -1.43866648 },\n') file.write('\tatom {H, -0.63507120, -4.36739448, -1.87482259 },\n') file.write('\tatom {H, -0.09209872, -3.99592562, -0.48063299 },\n') file.write('\tatom {O, 0.32703371, -1.16364690, -1.31684672 },\n') file.write('\tatom {H, 0.13127551, -1.13520548, -0.35997468 },\n') file.write('\tatom {H, 0.26100450, -2.11400425, -1.54213322 },\n') file.write('\tatom {O, -3.14387363, 1.26147659, -0.42032986 },\n') file.write('\tatom {H, -3.86548867, 0.69632883, -0.70791922 },\n') file.write('\tatom {H, -2.44492123, 1.18076397, -1.12217955 },\n') file.write('\tatom {O, 0.47853440, 2.65740808, 1.32203064 },\n') file.write('\tatom {H, 1.16509807, 2.02396937, 1.59193637 },\n') file.write('\tatom {H, -0.35810118, 2.21752307, 1.55341863 },\n') file.write('\tatom {O, -0.38383453, -3.73443912, 1.27525999 },\n') file.write('\tatom {H, -0.24715696, -2.78828153, 1.48248464 },\n') file.write('\tatom {H, 0.10371081, -4.21710263, 1.94780289 },\n') file.write('\tatom {O, 0.87004108, 2.83536075, -1.32288658 },\n') file.write('\tatom {H, 0.68996872, 2.87849856, -0.35019650 },\n') file.write('\tatom {H, 1.02267666, 3.74028357, -1.60867794 },\n') file.write('\tatom {O, 2.30679745, 0.49649996, 1.58743619 },\n') file.write('\tatom {H, 3.14934829, 0.37991303, 2.03505313 },\n') file.write('\tatom {H, 2.50246697, 0.49675828, 0.60818176 },\n') file.write('\tatom {O, -1.16215513, 1.03600785, -2.17353723 },\n') file.write('\tatom {H, -0.50300472, 1.73372032, -2.01577333 },\n') file.write('\tatom {H, -0.67893807, 0.20527170, -2.00103239 },\n') file.write('\tatom {O, -1.82487473, 1.05756029, 1.85950069 },\n') file.write('\tatom {H, -2.39730527, 1.23843669, 2.61044765 },\n') file.write('\tatom {H, -2.40369356, 1.10993284, 1.05336169 },\n') file.write('\tatom {O, -0.01673943, -1.01280507, 1.47458520 },\n') file.write('\tatom {H, -0.70957776, -0.36504575, 1.70952012 },\n') file.write('\tatom {H, 0.83050856, -0.56712969, 1.67070259 },\n') #---------------------------- #Endecamer (n=11), 443 Isomer #---------------------------- def print_w11i443(file): file.write('\tatom {O, 1.73475650, -0.85921782, 0.23574306 },\n') file.write('\tatom {H, 1.99137662, -1.80301680, 0.20404462 },\n') file.write('\tatom {H, 1.09679422, -0.75299981, -0.49721552 },\n') file.write('\tatom {O, -1.27206733, 2.80496529, -0.28891370 },\n') file.write('\tatom {H, -0.60578303, 2.73702447, -0.99559039 },\n') file.write('\tatom {H, -1.85281734, 2.03754617, -0.42166837 },\n') file.write('\tatom {O, 1.80695587, -3.59833500, 0.10205169 },\n') file.write('\tatom {H, 0.90799062, -3.57655532, -0.29039582 },\n') file.write('\tatom {H, 2.30634942, -4.22659696, -0.42572346 },\n') file.write('\tatom {O, -0.12145988, -0.34334066, -1.82442778 },\n') file.write('\tatom {H, -1.01224699, -0.07152574, -1.53856364 },\n') file.write('\tatom {H, 0.28597604, 0.48223462, -2.14348423 },\n') file.write('\tatom {O, -0.68915241, -3.05982185, -0.92595481 },\n') file.write('\tatom {H, -0.48761997, -2.30734376, -1.50128800 },\n') file.write('\tatom {H, -1.21188699, -2.66470042, -0.20777354 },\n') file.write('\tatom {O, -2.09346332, -1.53869676, 1.12610210 },\n') file.write('\tatom {H, -2.65480582, -1.94698273, 1.79161381 },\n') file.write('\tatom {H, -1.35671709, -1.08133288, 1.63037003 },\n') file.write('\tatom {O, -0.07309071, -0.34388533, 2.26037947 },\n') file.write('\tatom {H, -0.05911794, 0.62899126, 2.29089374 },\n') file.write('\tatom {H, 0.65655267, -0.57380442, 1.64756926 },\n') file.write('\tatom {O, -2.63803429, 0.33061937, -0.73147324 },\n') file.write('\tatom {H, -2.61897591, -0.34347822, -0.01382400 },\n') file.write('\tatom {H, -3.46549831, 0.19948696, -1.20336761 },\n') file.write('\tatom {O, 0.18483579, 2.45864040, 1.92403542 },\n') file.write('\tatom {H, 0.06120028, 3.16461555, 2.56459630 },\n') file.write('\tatom {H, -0.41609360, 2.66417962, 1.16372425 },\n') file.write('\tatom {O, 2.38148885, 1.84471789, 0.19406847 },\n') file.write('\tatom {H, 1.79701667, 2.13193373, 0.91636607 },\n') file.write('\tatom {H, 2.41047829, 0.87440971, 0.28367310 },\n') file.write('\tatom {O, 0.93495023, 2.24386326, -1.99438054 },\n') file.write('\tatom {H, 1.39152819, 2.77646464, -2.65162264 },\n') file.write('\tatom {H, 1.56204030, 2.14910646, -1.22690927 },\n') #---------------------------- #Endecamer (n=11), 515 Isomer #---------------------------- def print_w11i515(file): file.write('\tatom {O, -2.05673439, -2.24219020, -0.59070364 },\n') file.write('\tatom {H, -2.85960922, -2.71216775, -0.83194231 },\n') file.write('\tatom {H, -2.31170553, -1.28779385, -0.48591844 },\n') file.write('\tatom {O, -0.98862801, 1.95925008, -1.83773516 },\n') file.write('\tatom {H, -0.19283865, 1.37440617, -2.01112532 },\n') file.write('\tatom {H, -1.29755299, 2.23666864, -2.70520182 },\n') file.write('\tatom {O, 2.66280215, 0.39906851, 0.20966910 },\n') file.write('\tatom {H, 2.08355904, 0.96354359, 0.80225504 },\n') file.write('\tatom {H, 3.54563537, 0.77481870, 0.27490790 },\n') file.write('\tatom {O, 1.06868130, 1.83557079, 1.69995394 },\n') file.write('\tatom {H, 0.67959226, 2.57153073, 1.18638819 },\n') file.write('\tatom {H, 0.30513953, 1.31840872, 2.01606330 },\n') file.write('\tatom {O, -2.53128977, 0.33175948, -0.12780056 },\n') file.write('\tatom {H, -2.13323649, 0.47156951, 0.74880817 },\n') file.write('\tatom {H, -2.05400844, 0.93018332, -0.73176080 },\n') file.write('\tatom {O, 1.08781287, 0.41236202, -2.19211365 },\n') file.write('\tatom {H, 0.84687752, -0.54078875, -2.18986670 },\n') file.write('\tatom {H, 1.72278337, 0.49296329, -1.46078319 },\n') file.write('\tatom {O, -1.15112537, 0.25247267, 2.36996011 },\n') file.write('\tatom {H, -1.55537396, 0.28585363, 3.24176955 },\n') file.write('\tatom {H, -0.89254563, -0.69703881, 2.22643531 },\n') file.write('\tatom {O, -0.49712938, -2.24331355, 1.75305582 },\n') file.write('\tatom {H, -1.06939703, -2.43283192, 0.98789289 },\n') file.write('\tatom {H, 0.40945281, -2.29856980, 1.40271776 },\n') file.write('\tatom {O, 2.04540085, -2.23631883, 0.50229127 },\n') file.write('\tatom {H, 2.37809812, -1.31209245, 0.44946491 },\n') file.write('\tatom {H, 2.78652001, -2.76976241, 0.80287332 },\n') file.write('\tatom {O, -0.06400653, 3.75127132, 0.05294777 },\n') file.write('\tatom {H, -0.45593357, 3.21878933, -0.66844882 },\n') file.write('\tatom {H, -0.76376844, 4.33868360, 0.35046421 },\n') file.write('\tatom {O, 0.45431479, -2.24545424, -1.91816312 },\n') file.write('\tatom {H, -0.44734756, -2.32049949, -1.56054149 },\n') file.write('\tatom {H, 1.02921350, -2.45754244, -1.16678636 },\n') #---------------------------- #Endecamer (n=11), 551 Isomer #---------------------------- def print_w11i551(file): file.write('\tatom {O, -0.44679161, -3.11807829, 0.07512616 },\n') file.write('\tatom {H, -0.47083707, -4.07016462, 0.20484203 },\n') file.write('\tatom {H, 0.42313859, -2.80647073, 0.44156921 },\n') file.write('\tatom {O, -2.35251345, 0.21241407, -1.60292564 },\n') file.write('\tatom {H, -3.05945992, 0.42843604, -2.21751584 },\n') file.write('\tatom {H, -2.11917220, 1.06597654, -1.14137673 },\n') file.write('\tatom {O, 1.31710665, 0.30426889, 2.33990874 },\n') file.write('\tatom {H, 0.35015548, 0.47690198, 2.40278925 },\n') file.write('\tatom {H, 1.67238486, 0.46144257, 3.21951216 },\n') file.write('\tatom {O, -1.73684436, 2.32662913, -0.16337063 },\n') file.write('\tatom {H, -0.92055454, 2.80785030, -0.41888592 },\n') file.write('\tatom {H, -1.56262439, 1.96862966, 0.72107433 },\n') file.write('\tatom {O, -2.38411323, -1.23726570, 0.79868253 },\n') file.write('\tatom {H, -2.54009043, -0.83325760, -0.07504919 },\n') file.write('\tatom {H, -1.77228445, -1.97564874, 0.62010912 },\n') file.write('\tatom {O, -0.17324707, -1.45158813, -2.22676968 },\n') file.write('\tatom {H, -0.36520499, -2.15007361, -1.57874892 },\n') file.write('\tatom {H, -0.90468026, -0.81520501, -2.12113096 },\n') file.write('\tatom {O, -1.36748202, 0.71922094, 2.22797547 },\n') file.write('\tatom {H, -1.76670368, -0.05892347, 1.74309966 },\n') file.write('\tatom {H, -1.93319318, 0.86376513, 2.99231898 },\n') file.write('\tatom {O, 2.36975031, 1.61090235, -0.00285760 },\n') file.write('\tatom {H, 2.40195538, 0.85131693, -0.61167306 },\n') file.write('\tatom {H, 2.06201153, 1.23292448, 0.83660922 },\n') file.write('\tatom {O, 0.62759029, 3.47102875, -0.89433062 },\n') file.write('\tatom {H, 0.94894654, 4.34198164, -0.64844645 },\n') file.write('\tatom {H, 1.31674156, 2.83691024, -0.58655002 },\n') file.write('\tatom {O, 1.85407828, -2.07329571, 0.87955296 },\n') file.write('\tatom {H, 2.20126219, -1.67906179, 0.05906797 },\n') file.write('\tatom {H, 1.70832841, -1.31284908, 1.46909879 },\n') file.write('\tatom {O, 2.29907574, -0.74002506, -1.56453742 },\n') file.write('\tatom {H, 2.89440767, -0.90673150, -2.30064806 },\n') file.write('\tatom {H, 1.38566882, -0.94096379, -1.89934988 },\n') #---------------- #Dodecamer (n=12) #---------------- def print_w12(file): file.write('\tatom {O, 1.79799517, -2.87189360, -0.91374020 },\n') file.write('\tatom {O, 0.96730604, -2.75911220, 1.62798799 },\n') file.write('\tatom {O, 1.65380168, -0.07006642, -1.01974524 },\n') file.write('\tatom {O, 1.02235809, 0.07175530, 1.65572815 },\n') file.write('\tatom {O, -1.02223258, 0.06714841, -1.65231025 },\n') file.write('\tatom {O, -1.65303657, -0.06953734, 1.02328922 },\n') file.write('\tatom {O, -1.79714075, -2.87225082, 0.91489225 },\n') file.write('\tatom {O, -0.96714604, -2.76268933, -1.62695366 },\n') file.write('\tatom {O, -0.91046484, 2.86984708, -1.80205865 },\n') file.write('\tatom {O, 1.62976535, 2.75963881, -0.96492508 },\n') file.write('\tatom {O, 0.90962365, 2.87584732, 1.79706100 },\n') file.write('\tatom {O, -1.63064745, 2.76057720, 0.96075175 },\n') file.write('\tatom {H, 1.58187452, -2.90533857, 0.05372043 },\n') file.write('\tatom {H, 2.45880812, -3.55319457, -1.06640225 },\n') file.write('\tatom {H, -1.58013630, -2.90956053, -0.05228132 },\n') file.write('\tatom {H, -2.45728026, -3.55363054, 1.07010099 },\n') file.write('\tatom {H, 0.05632428, 2.90394112, -1.58314254 },\n') file.write('\tatom {H, -1.06231290, 3.55393270, -2.46019459 },\n') file.write('\tatom {H, -1.56680088, 2.89107809, -0.00131897 },\n') file.write('\tatom {H, -1.92210192, 1.83983329, 1.06475175 },\n') file.write('\tatom {H, 1.34757079, 0.06744042, 0.72858318 },\n') file.write('\tatom {H, 1.14627218, 0.98941003, 1.95482520 },\n') file.write('\tatom {H, -1.14676057, 0.98295160, -1.95675717 },\n') file.write('\tatom {H, -1.34650335, 0.06810117, -0.72482129 },\n') file.write('\tatom {H, 0.72810518, -0.06186014, -1.34872142 },\n') file.write('\tatom {H, 1.95057642, -0.98833069, -1.14558354 },\n') file.write('\tatom {H, -0.72703573, -0.06575415, 1.35156867 },\n') file.write('\tatom {H, -1.95270073, -0.98745311, 1.14464678 },\n') file.write('\tatom {H, 1.56681459, 2.89291882, -0.00316599 },\n') file.write('\tatom {H, 1.92433921, 1.83958829, -1.06611724 },\n') file.write('\tatom {H, -0.00511757, -2.89477284, -1.56679971 },\n') file.write('\tatom {H, -1.07087869, -1.84139535, -1.91693517 },\n') file.write('\tatom {H, -0.05748186, 2.90789148, 1.57927484 },\n') file.write('\tatom {H, 1.06103881, 3.56065162, 2.45452965 },\n') file.write('\tatom {H, 0.00532585, -2.89179177, 1.56768173 },\n') file.write('\tatom {H, 1.07022772, -1.83898762, 1.92167783 },\n') #---- #n=13 #---- def print_w13(file): file.write('\tatom {O, -1.72139424, 0.02340552, -0.51045640 },\n') file.write('\tatom {H, -1.41945833, -0.19918539, 0.39792084 },\n') file.write('\tatom {H, -2.08410215, 0.92470087, -0.43342046 },\n') file.write('\tatom {O, 0.79400268, -0.08355426, -1.61800002 },\n') file.write('\tatom {H, 0.85565631, -0.95150633, -2.05523841 },\n') file.write('\tatom {H, -0.14478345, -0.00666204, -1.33941210 },\n') file.write('\tatom {O, 1.88539825, -0.54493346, 0.86793990 },\n') file.write('\tatom {H, 2.21705660, 0.30661953, 1.20298967 },\n') file.write('\tatom {H, 1.59162060, -0.34584233, -0.04812200 },\n') file.write('\tatom {O, -0.64782869, -0.70695809, 1.91336684 },\n') file.write('\tatom {H, -0.88546275, -1.64565072, 2.00988548 },\n') file.write('\tatom {H, 0.29356130, -0.71474515, 1.63126766 },\n') file.write('\tatom {O, -2.22834883, 2.72190764, 0.03221480 },\n') file.write('\tatom {H, -3.04149905, 3.21574821, 0.17116033 },\n') file.write('\tatom {H, -1.68594256, 3.26002244, -0.60000827 },\n') file.write('\tatom {O, 2.04408786, 2.18396164, 1.49754959 },\n') file.write('\tatom {H, 2.55607055, 2.75644150, 2.07583412 },\n') file.write('\tatom {H, 1.10896828, 2.23076729, 1.82358766 },\n') file.write('\tatom {O, -1.05731510, -3.42939005, 1.37368402 },\n') file.write('\tatom {H, -1.46149517, -3.24864692, 0.48556168 },\n') file.write('\tatom {H, -1.55071838, -4.16328069, 1.75065962 },\n') file.write('\tatom {O, 0.73767926, -2.83126196, -2.17334751 },\n') file.write('\tatom {H, 1.13682533, -3.08129264, -1.30009612 },\n') file.write('\tatom {H, 1.13848219, -3.40938044, -2.82862428 },\n') file.write('\tatom {O, -0.52701249, 2.09999519, 2.24761959 },\n') file.write('\tatom {H, -1.14290984, 2.39298709, 1.55267539 },\n') file.write('\tatom {H, -0.73272120, 1.15964649, 2.37541234 },\n') file.write('\tatom {O, 1.66707873, 2.57920642, -1.30440517 },\n') file.write('\tatom {H, 1.90731745, 2.52069656, -0.36318855 },\n') file.write('\tatom {H, 1.48843837, 1.66087626, -1.56929781 },\n') file.write('\tatom {O, -1.89504769, -2.73577319, -1.06875216 },\n') file.write('\tatom {H, -1.10057794, -2.82795469, -1.62235556 },\n') file.write('\tatom {H, -2.06282681, -1.77825357, -1.03951486 },\n') file.write('\tatom {O, 1.59082367, -3.30613578, 0.31610668 },\n') file.write('\tatom {H, 0.77253863, -3.47637118, 0.81436194 },\n') file.write('\tatom {H, 1.92467277, -2.46573318, 0.67066967 },\n') file.write('\tatom {O, -0.55535266, 4.04413293, -1.54810837 },\n') file.write('\tatom {H, -0.69073489, 4.23058735, -2.48075953 },\n') file.write('\tatom {H, 0.29356952, 3.53504382, -1.50101232 },\n') #---- #n=14 #---- def print_w14(file): file.write('\tatom {O, 0.16950902, -3.62933548, -1.48729544 },\n') file.write('\tatom {H, 0.98770719, -3.06650603, -1.47350004 },\n') file.write('\tatom {H, 0.36558718, -4.36990691, -2.06811647 },\n') file.write('\tatom {O, -1.52323398, 3.36629878, 1.22298734 },\n') file.write('\tatom {H, -2.14947133, 4.03669098, 1.51064704 },\n') file.write('\tatom {H, -1.51379808, 3.40165005, 0.22855923 },\n') file.write('\tatom {O, -1.38450391, 0.59271033, 1.38535936 },\n') file.write('\tatom {H, -1.59520556, 1.53608251, 1.51638084 },\n') file.write('\tatom {H, -0.41143176, 0.52234858, 1.52061238 },\n') file.write('\tatom {O, -2.21575526, -2.09500069, -1.60759835 },\n') file.write('\tatom {H, -1.43074012, -2.66745000, -1.67194669 },\n') file.write('\tatom {H, -2.48611802, -2.16671557, -0.67923326 },\n') file.write('\tatom {O, 2.15060733, -2.17256087, 1.68850765 },\n') file.write('\tatom {H, 2.69633884, -2.61992730, 2.34129044 },\n') file.write('\tatom {H, 1.29846370, -2.68196763, 1.64355580 },\n') file.write('\tatom {O, 1.33448057, 3.27996304, 1.33570608 },\n') file.write('\tatom {H, 0.38389554, 3.42353471, 1.48218741 },\n') file.write('\tatom {H, 1.48036085, 2.35283381, 1.59102534 },\n') file.write('\tatom {O, 1.58589874, 3.35889207, -1.32735114 },\n') file.write('\tatom {H, 2.21639392, 4.01653613, -1.63431500 },\n') file.write('\tatom {H, 1.58831112, 3.41125226, -0.33696278 },\n') file.write('\tatom {O, 1.32875257, 0.45891643, 1.39808185 },\n') file.write('\tatom {H, 1.70543594, -0.39526632, 1.68375482 },\n') file.write('\tatom {H, 1.43974701, 0.46154170, 0.42083419 },\n') file.write('\tatom {O, -1.29975022, 0.46035814, -1.41593042 },\n') file.write('\tatom {H, -1.40711360, 0.48254384, -0.44404161 },\n') file.write('\tatom {H, -1.67541854, -0.41580686, -1.66369858 },\n') file.write('\tatom {O, -2.47970188, -1.87944259, 1.30541875 },\n') file.write('\tatom {H, -2.20856342, -0.94697656, 1.45198105 },\n') file.write('\tatom {H, -3.21435381, -2.03835724, 1.90502812 },\n') file.write('\tatom {O, 2.31621387, -2.08571364, -1.18509816 },\n') file.write('\tatom {H, 2.47470999, -2.11418880, -0.22679247 },\n') file.write('\tatom {H, 2.14511234, -1.14607629, -1.37705261 },\n') file.write('\tatom {O, -0.13052795, -3.47566330, 1.30871260 },\n') file.write('\tatom {H, -0.09494258, -3.70864151, 0.36353304 },\n') file.write('\tatom {H, -0.95412877, -2.96588919, 1.40500302 },\n') file.write('\tatom {O, -1.26899342, 3.25761821, -1.42008891 },\n') file.write('\tatom {H, -0.32004927, 3.39833567, -1.58010994 },\n') file.write('\tatom {H, -1.42111317, 2.32652422, -1.66237216 },\n') file.write('\tatom {O, 1.41628336, 0.55716143, -1.34563941 },\n') file.write('\tatom {H, 0.44624959, 0.49805311, -1.50659495 },\n') file.write('\tatom {H, 1.64976997, 1.48057920, -1.54747866 },\n') #---- #n=15 #---- def print_w15(file): file.write('\tatom {O, -0.41037728, 3.06338557, -2.19453935 },\n') file.write('\tatom {H, -1.10225722, 3.15700229, -1.50322402 },\n') file.write('\tatom {H, -0.55868201, 3.78135241, -2.81686194 },\n') file.write('\tatom {O, -0.34214882, 0.20087415, -2.29863851 },\n') file.write('\tatom {H, 0.52678420, 0.10051353, -1.84576600 },\n') file.write('\tatom {H, -0.36804153, 1.13006533, -2.57601866 },\n') file.write('\tatom {O, -2.23196288, 3.01297353, -0.14410577 },\n') file.write('\tatom {H, -2.92179851, 3.66294562, 0.01954583 },\n') file.write('\tatom {H, -1.73818286, 2.92285986, 0.71848955 },\n') file.write('\tatom {O, -2.36727601, -2.73235161, -0.30448997 },\n') file.write('\tatom {H, -2.67970705, -1.81681475, -0.35802889 },\n') file.write('\tatom {H, -1.73980002, -2.80584683, -1.05791736 },\n') file.write('\tatom {O, 1.60775457, -0.06745560, 1.64608103 },\n') file.write('\tatom {H, 0.63325622, -0.07453825, 1.78914481 },\n') file.write('\tatom {H, 1.88844716, 0.82956238, 1.89432294 },\n') file.write('\tatom {O, -2.30250596, 0.14897737, -0.40481292 },\n') file.write('\tatom {H, -2.58514101, 1.07692660, -0.37282923 },\n') file.write('\tatom {H, -1.60883631, 0.13892784, -1.10403419 },\n') file.write('\tatom {O, -1.14781983, -2.99211225, 2.01614355 },\n') file.write('\tatom {H, -1.63218518, -2.97754098, 1.14324747 },\n') file.write('\tatom {H, -1.57112536, -3.67596952, 2.54301254 },\n') file.write('\tatom {O, 2.13161682, 2.66193894, -0.94063605 },\n') file.write('\tatom {H, 1.30281644, 2.87721472, -1.40185307 },\n') file.write('\tatom {H, 2.30155821, 1.73012958, -1.16100356 },\n') file.write('\tatom {O, 2.03863122, -0.14910922, -1.03750931 },\n') file.write('\tatom {H, 2.29027066, -1.06413710, -1.25777871 },\n') file.write('\tatom {H, 1.89247851, -0.16323798, -0.06343480 },\n') file.write('\tatom {O, -1.07959061, -0.19223930, 2.00451613 },\n') file.write('\tatom {H, -1.53139246, -0.12237038, 1.13212592 },\n') file.write('\tatom {H, -1.21282358, -1.11848311, 2.27583104 },\n') file.write('\tatom {O, -0.54129318, -2.69118030, -2.36237717 },\n') file.write('\tatom {H, -0.53101580, -1.76517125, -2.64617762 },\n') file.write('\tatom {H, 0.36452643, -2.85595028, -2.04808200 },\n') file.write('\tatom {O, 1.60493380, -2.91090837, 1.40237411 },\n') file.write('\tatom {H, 1.80909034, -2.00751362, 1.69164607 },\n') file.write('\tatom {H, 0.67031170, -3.03851425, 1.65171826 },\n') file.write('\tatom {O, 1.87438878, 2.74300689, 1.71123562 },\n') file.write('\tatom {H, 2.48187829, 3.37972572, 2.09828615 },\n') file.write('\tatom {H, 2.01080637, 2.79193943, 0.72916891 },\n') file.write('\tatom {O, -0.91062230, 2.61943091, 2.10670728 },\n') file.write('\tatom {H, -1.02038252, 1.68324940, 2.34467938 },\n') file.write('\tatom {H, 0.05362613, 2.74889220, 2.03849853 },\n') file.write('\tatom {O, 2.07248122, -2.94084258, -1.22138117 },\n') file.write('\tatom {H, 1.91566855, -3.02563145, -0.24488011 },\n') file.write('\tatom {H, 2.71120402, -3.62293405, -1.44731277 },\n') #---- #n=16 #---- def print_w16(file): file.write('\tatom {O, 1.41406651, 1.47898306, 1.34080339 },\n') file.write('\tatom {H, 1.49686076, 1.45044122, 0.36223864 },\n') file.write('\tatom {H, 1.62064251, 2.40207704, 1.57178605 },\n') file.write('\tatom {O, -1.41406651, -1.47898306, 1.34080339 },\n') file.write('\tatom {H, -1.62064251, -2.40207704, 1.57178605 },\n') file.write('\tatom {H, -1.49686076, -1.45044122, 0.36223864 },\n') file.write('\tatom {O, 1.39000816, -4.15918450, 1.27951492 },\n') file.write('\tatom {H, 0.45245028, -4.28804192, 1.50630410 },\n') file.write('\tatom {H, 1.57669938, -3.23997897, 1.53183841 },\n') file.write('\tatom {O, 1.33400994, -1.32197720, 1.41420070 },\n') file.write('\tatom {H, 1.59995522, -0.42479230, 1.67545887 },\n') file.write('\tatom {H, 0.35477253, -1.32600182, 1.49428525 },\n') file.write('\tatom {O, -1.33400994, -1.32197720, -1.41420070 },\n') file.write('\tatom {H, -1.59995522, -0.42479230, -1.67545887 },\n') file.write('\tatom {H, -0.35477253, -1.32600182, -1.49428525 },\n') file.write('\tatom {O, 1.39000816, 4.15918450, -1.27951492 },\n') file.write('\tatom {H, 0.45245028, 4.28804192, -1.50630410 },\n') file.write('\tatom {H, 1.57669938, 3.23997897, -1.53183841 },\n') file.write('\tatom {O, -1.45801073, 4.28844406, -1.38716611 },\n') file.write('\tatom {H, -1.52043672, 4.32892728, -0.39770335 },\n') file.write('\tatom {H, -2.05158507, 4.96664049, -1.72209901 },\n') file.write('\tatom {O, 1.45801073, -4.28844406, -1.38716611 },\n') file.write('\tatom {H, 2.05158507, -4.96664049, -1.72209901 },\n') file.write('\tatom {H, 1.52043672, -4.32892728, -0.39770335 },\n') file.write('\tatom {O, -1.45801073, -4.28844406, 1.38716611 },\n') file.write('\tatom {H, -1.52043672, -4.32892728, 0.39770335 },\n') file.write('\tatom {H, -2.05158507, -4.96664049, 1.72209901 },\n') file.write('\tatom {O, -1.39000816, 4.15918450, 1.27951492 },\n') file.write('\tatom {H, -0.45245028, 4.28804192, 1.50630410 },\n') file.write('\tatom {H, -1.57669938, 3.23997897, 1.53183841 },\n') file.write('\tatom {O, 1.41406651, -1.47898306, -1.34080339 },\n') file.write('\tatom {H, 1.49686076, -1.45044122, -0.36223864 },\n') file.write('\tatom {H, 1.62064251, -2.40207704, -1.57178605 },\n') file.write('\tatom {O, -1.41406651, 1.47898306, -1.34080339 },\n') file.write('\tatom {H, -1.62064251, 2.40207704, -1.57178605 },\n') file.write('\tatom {H, -1.49686076, 1.45044122, -0.36223864 },\n') file.write('\tatom {O, 1.45801073, 4.28844406, 1.38716611 },\n') file.write('\tatom {H, 1.52043672, 4.32892728, 0.39770335 },\n') file.write('\tatom {H, 2.05158507, 4.96664049, 1.72209901 },\n') file.write('\tatom {O, -1.39000816, -4.15918450, -1.27951492 },\n') file.write('\tatom {H, -0.45245028, -4.28804192, -1.50630410 },\n') file.write('\tatom {H, -1.57669938, -3.23997897, -1.53183841 },\n') file.write('\tatom {O, 1.33400994, 1.32197720, -1.41420070 },\n') file.write('\tatom {H, 1.59995522, 0.42479230, -1.67545887 },\n') file.write('\tatom {H, 0.35477253, 1.32600182, -1.49428525 },\n') file.write('\tatom {O, -1.33400994, 1.32197720, 1.41420070 },\n') file.write('\tatom {H, -0.35477253, 1.32600182, 1.49428525 },\n') file.write('\tatom {H, -1.59995522, 0.42479230, 1.67545887 },\n') #--------------- #n=17 (Interior) #--------------- def print_w17int(file): file.write('\tatom {O, -0.01493103, -0.11597399, 0.08504794 },\n') file.write('\tatom {H, -0.54830827, -0.79672051, 0.54924004 },\n') file.write('\tatom {H, 0.26142249, 0.50039437, 0.79799914 },\n') file.write('\tatom {O, -1.40600079, -2.02486637, 1.51449118 },\n') file.write('\tatom {H, -1.97744278, -2.38235975, 0.80783724 },\n') file.write('\tatom {H, -0.70270740, -2.69031204, 1.63619275 },\n') file.write('\tatom {O, 0.69995502, 1.48523512, 2.19778076 },\n') file.write('\tatom {H, 0.72668055, 2.39089850, 1.83196509 },\n') file.write('\tatom {H, 1.62972317, 1.18983224, 2.22697611 },\n') file.write('\tatom {O, 1.71882695, -1.36674740, -1.60938263 },\n') file.write('\tatom {H, 1.92559761, -0.71100080, -2.29699013 },\n') file.write('\tatom {H, 1.14742176, -0.86778248, -0.98574738 },\n') file.write('\tatom {O, -0.82892133, 1.17597634, -2.17815471 },\n') file.write('\tatom {H, -0.53754194, 0.70230668, -1.36963306 },\n') file.write('\tatom {H, -0.02586849, 1.20790698, -2.72499002 },\n') file.write('\tatom {O, -2.62491952, -2.63028076, -0.89040553 },\n') file.write('\tatom {H, -3.36659624, -3.18288446, -1.15368648 },\n') file.write('\tatom {H, -2.87552044, -1.70311641, -1.15589515 },\n') file.write('\tatom {O, 3.22568486, 0.51580834, 1.60184690 },\n') file.write('\tatom {H, 3.15887363, -0.44655664, 1.35468137 },\n') file.write('\tatom {H, 4.07147791, 0.60462248, 2.05102255 },\n') file.write('\tatom {O, 0.70024553, 3.77012031, 0.65875677 },\n') file.write('\tatom {H, -0.17945986, 3.66970044, 0.19378959 },\n') file.write('\tatom {H, 0.79432527, 4.70654786, 0.85464147 },\n') file.write('\tatom {O, -3.27899902, 1.54471635, 0.80788480 },\n') file.write('\tatom {H, -2.78624126, 1.14871181, 1.57540152 },\n') file.write('\tatom {H, -4.12274660, 1.83521150, 1.16718828 },\n') file.write('\tatom {O, -1.56776961, 3.32426908, -0.57758859 },\n') file.write('\tatom {H, -2.20888987, 2.82483943, -0.03976389 },\n') file.write('\tatom {H, -1.33373669, 2.69714016, -1.29006638 },\n') file.write('\tatom {O, 2.63519585, 2.18068693, -0.67386812 },\n') file.write('\tatom {H, 2.92050546, 1.60093117, 0.05353762 },\n') file.write('\tatom {H, 2.01063301, 2.80736955, -0.26724530 },\n') file.write('\tatom {O, -3.22522739, -0.12727675, -1.49339530 },\n') file.write('\tatom {H, -3.31981827, 0.42898292, -0.69813308 },\n') file.write('\tatom {H, -2.51643255, 0.30332052, -2.00099814 },\n') file.write('\tatom {O, 0.79609848, -3.71439238, 1.25117393 },\n') file.write('\tatom {H, 0.54477356, -3.77685417, 0.28988842 },\n') file.write('\tatom {H, 0.93625080, -4.61883181, 1.54705505 },\n') file.write('\tatom {O, 1.89827284, 1.08163047, -2.99757387 },\n') file.write('\tatom {H, 2.22210990, 1.53460165, -2.17874904 },\n') file.write('\tatom {H, 2.42264308, 1.43810302, -3.72002788 },\n') file.write('\tatom {O, -1.89000594, 0.44196341, 2.79825366 },\n') file.write('\tatom {H, -0.98912297, 0.80774296, 2.80111040 },\n') file.write('\tatom {H, -1.77219591, -0.48917214, 2.54168817 },\n') file.write('\tatom {O, 0.04909521, -3.57372894, -1.29036379 },\n') file.write('\tatom {H, 0.60452184, -2.85690908, -1.64983740 },\n') file.write('\tatom {H, -0.86368532, -3.23847512, -1.32330854 },\n') file.write('\tatom {O, 3.05559597, -1.98916361, 0.75928244 },\n') file.write('\tatom {H, 2.36653504, -2.59144463, 1.08898534 },\n') file.write('\tatom {H, 2.80846963, -1.85697748, -0.17499773 },\n') #-------------- #n=17 (Surface) #-------------- def print_w17surf(file): file.write('\tatom {O, 0.23692669, -4.65683721, 0.48774215 },\n') file.write('\tatom {H, -0.51925947, -4.31137465, 1.03257353 },\n') file.write('\tatom {H, 0.41856682, -5.54767870, 0.79964933 },\n') file.write('\tatom {O, -2.08586139, -0.05117740, 0.04583617 },\n') file.write('\tatom {H, -1.50756298, 0.28226837, -0.67576496 },\n') file.write('\tatom {H, -2.50701356, -0.85944526, -0.30189210 },\n') file.write('\tatom {O, 3.57542689, 0.17848797, -1.39307975 },\n') file.write('\tatom {H, 4.46764291, 0.24313009, -1.74576954 },\n') file.write('\tatom {H, 3.67350147, -0.03196931, -0.42827831 },\n') file.write('\tatom {O, 1.54422957, -2.21962678, 0.54684888 },\n') file.write('\tatom {H, 1.29549099, -3.16244212, 0.56351294 },\n') file.write('\tatom {H, 1.37067696, -1.91517279, -0.36731664 },\n') file.write('\tatom {O, 1.16595877, -1.22238147, -2.02560843 },\n') file.write('\tatom {H, 2.05251088, -0.82228813, -2.06847549 },\n') file.write('\tatom {H, 0.55256907, -0.47502704, -2.14975084 },\n') file.write('\tatom {O, -0.57175754, 3.55391445, 2.10626722 },\n') file.write('\tatom {H, -1.39115075, 3.18839567, 1.68000593 },\n') file.write('\tatom {H, -0.87411109, 4.03719665, 2.88085344 },\n') file.write('\tatom {O, -1.76131856, -3.43767851, 1.74722883 },\n') file.write('\tatom {H, -2.32962276, -3.17202142, 1.00434061 },\n') file.write('\tatom {H, -1.40135001, -2.59813718, 2.08528286 },\n') file.write('\tatom {O, -0.63093208, -3.48491822, -1.94302346 },\n') file.write('\tatom {H, -0.23829063, -4.03664137, -1.24468989 },\n') file.write('\tatom {H, 0.04495724, -2.82066258, -2.15250417 },\n') file.write('\tatom {O, -0.45520628, 1.05871738, -1.83625961 },\n') file.write('\tatom {H, 0.30663738, 1.47711374, -1.36797287 },\n') file.write('\tatom {H, -0.97787375, 1.81828666, -2.14816799 },\n') file.write('\tatom {O, 0.29947130, 4.50820655, -0.44394424 },\n') file.write('\tatom {H, 0.06150883, 4.39973198, 0.49330177 },\n') file.write('\tatom {H, 0.98230459, 3.82762475, -0.57671799 },\n') file.write('\tatom {O, -2.86315640, -2.59367438, -0.76458985 },\n') file.write('\tatom {H, -2.08742294, -2.92276141, -1.28622298 },\n') file.write('\tatom {H, -3.64710413, -2.87417039, -1.24542095 },\n') file.write('\tatom {O, 3.47461432, -0.34625855, 1.22144547 },\n') file.write('\tatom {H, 2.94262697, 0.30871211, 1.69912297 },\n') file.write('\tatom {H, 2.90241444, -1.13387509, 1.17616012 },\n') file.write('\tatom {O, -2.65823268, 2.60253978, 0.73991459 },\n') file.write('\tatom {H, -2.56743584, 2.96397951, -0.15815229 },\n') file.write('\tatom {H, -2.64863471, 1.63809077, 0.60365680 },\n') file.write('\tatom {O, 1.21442507, 1.36709466, 2.01026056 },\n') file.write('\tatom {H, 0.60933196, 0.60337976, 2.13396618 },\n') file.write('\tatom {H, 0.67766394, 2.14516345, 2.24988227 },\n') file.write('\tatom {O, -1.77828582, 3.54903590, -1.82004078 },\n') file.write('\tatom {H, -2.15107605, 4.18713341, -2.43497442 },\n') file.write('\tatom {H, -1.01812491, 4.00751351, -1.37534830 },\n') file.write('\tatom {O, 1.68793160, 2.08055151, -0.57030338 },\n') file.write('\tatom {H, 2.46208845, 1.61030075, -0.92691453 },\n') file.write('\tatom {H, 1.59018131, 1.77711776, 0.36267192 },\n') file.write('\tatom {O, -0.38604848, -0.89729623, 2.02255122 },\n') file.write('\tatom {H, -1.00819445, -0.57102949, 1.33531575 },\n') file.write('\tatom {H, 0.29367122, -1.38422097, 1.51134834 },\n') #-------------- #n=18 (Surface) #-------------- def print_w18(file): file.write('\tatom {O, 2.05847074, -4.03432286, 1.31047808 },\n') file.write('\tatom {H, 1.18052907, -4.40859785, 1.49696787 },\n') file.write('\tatom {H, 1.97818927, -3.09758325, 1.55869811 },\n') file.write('\tatom {O, -0.68550781, -4.83729972, 1.31015757 },\n') file.write('\tatom {H, -0.70328898, -4.89129151, 0.31638823 },\n') file.write('\tatom {H, -1.11637156, -5.63356464, 1.63343528 },\n') file.write('\tatom {O, 2.22632201, -4.10379025, -1.35943877 },\n') file.write('\tatom {H, 2.99202269, -4.58639542, -1.68332186 },\n') file.write('\tatom {H, 2.27696713, -4.13004153, -0.36932902 },\n') file.write('\tatom {O, -0.56478868, -4.71945768, -1.33892371 },\n') file.write('\tatom {H, 0.38273906, -4.62558121, -1.53662053 },\n') file.write('\tatom {H, -0.94951761, -3.85608537, -1.57625912 },\n') file.write('\tatom {O, 1.33879793, -1.30403906, 1.34452743 },\n') file.write('\tatom {H, 1.42232421, -1.30311909, 0.36540415 },\n') file.write('\tatom {H, 1.48885980, -0.37546505, 1.60171284 },\n') file.write('\tatom {O, -1.25874146, -2.12218316, 1.43553426 },\n') file.write('\tatom {H, -0.33672027, -1.79275214, 1.53850102 },\n') file.write('\tatom {H, -1.20250156, -3.08617156, 1.57815253 },\n') file.write('\tatom {O, 1.36668067, -1.43692881, -1.41628685 },\n') file.write('\tatom {H, 1.80905971, -2.28248970, -1.61108093 },\n') file.write('\tatom {H, 0.40661967, -1.61694172, -1.54039121 },\n') file.write('\tatom {O, 1.26137413, 1.45144982, 1.48016252 },\n') file.write('\tatom {H, 0.29511972, 1.62130277, 1.53065802 },\n') file.write('\tatom {H, 1.68061979, 2.30534131, 1.69188388 },\n') file.write('\tatom {O, -1.29056761, -2.01779296, -1.36363982 },\n') file.write('\tatom {H, -1.94815102, -1.32895426, -1.61450342 },\n') file.write('\tatom {H, -1.35420222, -2.04415886, -0.38795315 },\n') file.write('\tatom {O, -3.15828768, -0.19083915, 1.39452665 },\n') file.write('\tatom {H, -2.55834478, -0.95735314, 1.52883846 },\n') file.write('\tatom {H, -3.89144535, -0.31843982, 2.00328132 },\n') file.write('\tatom {O, 1.42751515, 1.32626524, -1.29381126 },\n') file.write('\tatom {H, 1.58986208, 0.39946517, -1.54887549 },\n') file.write('\tatom {H, 1.44702551, 1.31497135, -0.31339551 },\n') file.write('\tatom {O, 2.09948977, 4.11570775, 1.47267075 },\n') file.write('\tatom {H, 2.84262212, 4.59723418, 1.84681981 },\n') file.write('\tatom {H, 2.21399375, 4.14503392, 0.48656745 },\n') file.write('\tatom {O, -1.41028187, 1.99418107, 1.23220378 },\n') file.write('\tatom {H, -1.41183312, 2.03209564, 0.24932954 },\n') file.write('\tatom {H, -2.07418914, 1.31583240, 1.45388990 },\n') file.write('\tatom {O, -3.05625916, 0.04693188, -1.57157373 },\n') file.write('\tatom {H, -2.52147097, 0.85316155, -1.67721407 },\n') file.write('\tatom {H, -3.31630766, 0.05278117, -0.63821070 },\n') file.write('\tatom {O, 2.11573205, 4.05999364, -1.19395405 },\n') file.write('\tatom {H, 1.25583413, 4.44145521, -1.44153843 },\n') file.write('\tatom {H, 2.05218034, 3.12604891, -1.45774007 },\n') file.write('\tatom {O, -0.68334809, 4.72256431, 1.28552964 },\n') file.write('\tatom {H, 0.25096857, 4.62581480, 1.53805303 },\n') file.write('\tatom {H, -1.07856344, 3.85501436, 1.47993924 },\n') file.write('\tatom {O, -1.18486931, 2.16167975, -1.49247911 },\n') file.write('\tatom {H, -1.12164442, 3.11883584, -1.66399249 },\n') file.write('\tatom {H, -0.26395756, 1.82978079, -1.56957718 },\n') file.write('\tatom {O, -0.60255064, 4.89711964, -1.37747275 },\n') file.write('\tatom {H, -0.70253095, 4.93857234, -0.39094048 },\n') file.write('\tatom {H, -1.01614374, 5.69108795, -1.72765539 },\n') #--------------- #n=19 (Interior) #--------------- def print_w19(file): file.write('\tatom {O, -1.78991610, 1.51321269, -1.17846555 },\n') file.write('\tatom {H, -2.63160242, 1.02336537, -1.09895002 },\n') file.write('\tatom {H, -1.15355746, 0.93276870, -0.69523130 },\n') file.write('\tatom {O, 0.03256222, -0.00540767, 0.13005355 },\n') file.write('\tatom {H, -0.35332650, -0.69045565, 0.71966335 },\n') file.write('\tatom {H, 0.46829712, 0.62864405, 0.73986929 },\n') file.write('\tatom {O, -0.85363152, -1.95142647, 1.87846743 },\n') file.write('\tatom {H, -1.07489331, -2.75816424, 1.37330312 },\n') file.write('\tatom {H, 0.02089709, -2.13528375, 2.27440873 },\n') file.write('\tatom {O, 1.06520757, 1.83756967, 1.91953561 },\n') file.write('\tatom {H, 1.23064218, 2.66505116, 1.42920907 },\n') file.write('\tatom {H, 0.22568412, 1.99214094, 2.39570811 },\n') file.write('\tatom {O, 1.73641639, -1.51936110, -1.41953903 },\n') file.write('\tatom {H, 2.58546662, -1.04462702, -1.40085287 },\n') file.write('\tatom {H, 1.15706906, -0.95156367, -0.86611967 },\n') file.write('\tatom {O, -2.27744615, -2.15163174, -1.65043961 },\n') file.write('\tatom {H, -1.59433767, -1.86047183, -2.29534636 },\n') file.write('\tatom {H, -1.86597712, -2.85818716, -1.12471521 },\n') file.write('\tatom {O, -1.55144695, 2.21537273, 2.78981610 },\n') file.write('\tatom {H, -1.87911716, 2.47582356, 3.65565516 },\n') file.write('\tatom {H, -2.06409590, 1.39428925, 2.54987946 },\n') file.write('\tatom {O, 1.82080978, -2.38163840, 2.50934536 },\n') file.write('\tatom {H, 2.22141601, -2.68867558, 3.32788975 },\n') file.write('\tatom {H, 2.31922415, -1.55504333, 2.26618345 },\n') file.write('\tatom {O, 2.08894260, 2.25089574, -1.78461216 },\n') file.write('\tatom {H, 1.73510916, 2.91356802, -1.16536237 },\n') file.write('\tatom {H, 1.34533352, 2.00852733, -2.36458106 },\n') file.write('\tatom {O, -3.74023115, -0.30841120, -0.52601984 },\n') file.write('\tatom {H, -4.65837809, -0.45104294, -0.77304433 },\n') file.write('\tatom {H, -3.22439128, -1.05537029, -0.94802780 },\n') file.write('\tatom {O, -2.83434488, -0.00223514, 2.14908380 },\n') file.write('\tatom {H, -3.24076521, -0.08692872, 1.26703331 },\n') file.write('\tatom {H, -2.21210378, -0.74986342, 2.19814876 },\n') file.write('\tatom {O, 3.06440299, -0.12777184, 1.87382466 },\n') file.write('\tatom {H, 3.37404420, 0.01256554, 0.96071756 },\n') file.write('\tatom {H, 2.45581921, 0.61399336, 2.03583308 },\n') file.write('\tatom {O, -1.09132068, -4.04631153, 0.09570936 },\n') file.write('\tatom {H, -1.39785255, -4.95681845, 0.12755242 },\n') file.write('\tatom {H, -0.09658303, -4.08390695, 0.02715018 },\n') file.write('\tatom {O, 1.10324680, 4.00937316, 0.18579009 },\n') file.write('\tatom {H, 0.10637553, 4.03389639, 0.23220530 },\n') file.write('\tatom {H, 1.40258859, 4.92066185, 0.25049313 },\n') file.write('\tatom {O, 3.71505267, 0.36947883, -0.85503621 },\n') file.write('\tatom {H, 4.60499009, 0.55744977, -1.16647114 },\n') file.write('\tatom {H, 3.14623717, 1.10223053, -1.20829228 },\n') file.write('\tatom {O, -1.50650441, 3.76858590, 0.40424706 },\n') file.write('\tatom {H, -1.64831105, 3.36993687, 1.28085968 },\n') file.write('\tatom {H, -1.72104185, 3.03906481, -0.21217906 },\n') file.write('\tatom {O, 1.53279435, -3.84248704, 0.05530571 },\n') file.write('\tatom {H, 1.76399279, -3.48323592, 0.92861203 },\n') file.write('\tatom {H, 1.70697057, -3.09136967, -0.54939068 },\n') file.write('\tatom {O, -0.20825966, 1.56738878, -3.34458330 },\n') file.write('\tatom {H, -0.91555776, 1.62269461, -2.65996381 },\n') file.write('\tatom {H, -0.47499620, 2.15875012, -4.05447009 },\n') file.write('\tatom {O, -0.29205805, -1.32680854, -3.36251707 },\n') file.write('\tatom {H, -0.28330368, -0.37130281, -3.53034185 },\n') file.write('\tatom {H, 0.52826469, -1.47084962, -2.85809049 },\n') #------------------------ #n=20 Dodecahedron *** C1 #------------------------ #MP2/aug-cc-pVTZ delta E=209.28, kcal/mol def print_w20dode(file): file.write('\tatom {O, 2.21363671, 3.19691705, 0.68721850 },\n') file.write('\tatom {O, 3.65057365, 0.72957220, 0.88213303 },\n') file.write('\tatom {O, 0.12378993, 3.10718406, 2.42529051 },\n') file.write('\tatom {O, 1.04255648, 3.11293656, -1.89832518 },\n') file.write('\tatom {O, 2.66039031, -0.78644391, 2.76500519 },\n') file.write('\tatom {O, 0.36138214, 0.55170878, 3.71095844 },\n') file.write('\tatom {O, 3.44677186, -0.54403736, -1.51310232 },\n') file.write('\tatom {O, -2.09205528, 2.96824738, 1.03881140 },\n') file.write('\tatom {O, 1.84970876, 0.88709177, -3.35373862 },\n') file.write('\tatom {O, -1.57543181, 3.18469944, -1.67774247 },\n') file.write('\tatom {O, 1.60954259, -3.04290753, 1.53036305 },\n') file.write('\tatom {O, -1.84749768, -0.92916854, 3.16936612 },\n') file.write('\tatom {O, 2.22513624, -3.09413850, -0.99837469 },\n') file.write('\tatom {O, -3.57764895, 0.60042916, 1.46505684 },\n') file.write('\tatom {O, -0.29188080, -0.56461668, -3.75259415 },\n') file.write('\tatom {O, -2.48971046, 0.73765115, -2.78470750 },\n') file.write('\tatom {O, -1.14768291, -3.15619582, 2.01547295 },\n') file.write('\tatom {O, -0.08921585, -3.08042930, -2.39438070 },\n') file.write('\tatom {O, -3.76178142, -0.88923220, -0.79127141 },\n') file.write('\tatom {O, -2.21900716, -2.98260021, -0.54081277 },\n') file.write('\tatom {H, 1.48860041, 3.23998239, 1.35127815 },\n') file.write('\tatom {H, 2.75181797, 3.98041800, 0.83609425 },\n') file.write('\tatom {H, 3.18060821, 1.57490928, 0.79640718 },\n') file.write('\tatom {H, 3.59581278, 0.30392539, -0.00375389 },\n') file.write('\tatom {H, -0.02806528, 3.77888401, 3.09713154 },\n') file.write('\tatom {H, -0.72822476, 3.05806149, 1.90367024 },\n') file.write('\tatom {H, 1.49860445, 3.10177065, -1.03934799 },\n') file.write('\tatom {H, 1.37545271, 2.34187778, -2.39860402 },\n') file.write('\tatom {H, 3.36310551, -0.92937961, 3.40603010 },\n') file.write('\tatom {H, 3.06263115, -0.20906586, 2.05191259 },\n') file.write('\tatom {H, 1.17914609, 0.11628774, 3.40878159 },\n') file.write('\tatom {H, 0.34157730, 1.40897869, 3.25477828 },\n') file.write('\tatom {H, 3.01239546, -1.40402339, -1.38931272 },\n') file.write('\tatom {H, 2.91496939, -0.07998757, -2.18428610 },\n') file.write('\tatom {H, -1.95886631, 3.07079722, 0.07599025 },\n') file.write('\tatom {H, -2.61516021, 2.15456166, 1.14902557 },\n') file.write('\tatom {H, 1.03290046, 0.33689971, -3.53115236 },\n') file.write('\tatom {H, 2.23582115, 1.05936690, -4.21764861 },\n') file.write('\tatom {H, -1.87075714, 3.96859381, -2.15053933 },\n') file.write('\tatom {H, -0.58252407, 3.17084169, -1.77960923 },\n') file.write('\tatom {H, 0.65842849, -3.07749678, 1.74545916 },\n') file.write('\tatom {H, 1.96710620, -2.26663730, 2.00507084 },\n') file.write('\tatom {H, -2.42366840, -0.37434822, 2.61890681 },\n') file.write('\tatom {H, -1.06369958, -0.37190759, 3.38436481 },\n') file.write('\tatom {H, 2.88227181, -3.79105733, -1.08977609 },\n') file.write('\tatom {H, 1.99017082, -3.07948303, -0.02275854 },\n') file.write('\tatom {H, -4.44765215, 0.74838340, 1.84831745 },\n') file.write('\tatom {H, -3.73087280, 0.05697639, 0.65771307 },\n') file.write('\tatom {H, -0.25280203, -1.42086828, -3.29625616 },\n') file.write('\tatom {H, -1.10573897, -0.12324754, -3.42072712 },\n') file.write('\tatom {H, -2.22307731, 1.58423051, -2.38534021 },\n') file.write('\tatom {H, -2.93898411, 0.24358925, -2.07959638 },\n') file.write('\tatom {H, -1.43114729, -3.86916980, 2.59572095 },\n') file.write('\tatom {H, -1.42737601, -2.30951496, 2.47633957 },\n') file.write('\tatom {H, -0.13586670, -3.83927742, -2.98398146 },\n') file.write('\tatom {H, 0.77934548, -3.15444337, -1.93321293 },\n') file.write('\tatom {H, -4.59832291, -1.22537007, -1.12737541 },\n') file.write('\tatom {H, -3.17257126, -1.69388848, -0.69954170 },\n') file.write('\tatom {H, -1.46763166, -3.03149906, -1.15878165 },\n') file.write('\tatom {H, -1.83957475, -3.10072588, 0.35232980 },\n') #----------------------- #n=20 Fused Cubes *** C2 #----------------------- #MP2/aug-cc-pVTZ delta E=217.88, kcal/mol def print_w20fused(file): file.write('\tatom {O, -0.00011170, 1.89124892, 5.56014624 },\n') file.write('\tatom {O, 2.01365707, -0.13154392, 5.65472774 },\n') file.write('\tatom {O, 0.13154392, 2.01365707, -5.65472774 },\n') file.write('\tatom {O, 1.89124892, 0.00011170, -5.56014624 },\n') file.write('\tatom {O, 1.94859527, 0.02560379, -2.73064080 },\n') file.write('\tatom {O, -1.94859527, -0.02560379, -2.73064080 },\n') file.write('\tatom {O, 1.94851071, 0.02903527, 2.85767511 },\n') file.write('\tatom {O, -1.94851071, -0.02903527, 2.85767511 },\n') file.write('\tatom {O, 0.00011170, -1.89124892, 5.56014624 },\n') file.write('\tatom {O, -2.01365707, 0.13154392, 5.65472774 },\n') file.write('\tatom {O, -0.13154392, -2.01365707, -5.65472774 },\n') file.write('\tatom {O, -1.89124892, -0.00011170, -5.56014624 },\n') file.write('\tatom {O, -1.95562639, 0.07896636, 0.06622882 },\n') file.write('\tatom {O, -0.02560379, 1.94859527, 2.73064080 },\n') file.write('\tatom {O, -0.02903527, 1.94851071, -2.85767511 },\n') file.write('\tatom {O, 0.02903527, -1.94851071, -2.85767511 },\n') file.write('\tatom {O, 0.07896636, 1.95562639, -0.06622882 },\n') file.write('\tatom {O, -0.07896636, -1.95562639, -0.06622882 },\n') file.write('\tatom {O, 0.02560379, -1.94859527, 2.73064080 },\n') file.write('\tatom {O, 1.95562639, -0.07896636, 0.06622882 },\n') file.write('\tatom {H, 0.79989605, 1.35280911, 5.68906262 },\n') file.write('\tatom {H, 0.06198380, 2.20521176, 4.64309683 },\n') file.write('\tatom {H, 1.32913877, -0.84798431, 5.70007128 },\n') file.write('\tatom {H, 2.66479384, -0.33786677, 6.33131988 },\n') file.write('\tatom {H, 0.33786677, 2.66479384, -6.33131988 },\n') file.write('\tatom {H, 0.84798431, 1.32913877, -5.70007128 },\n') file.write('\tatom {H, 1.35280911, -0.79989605, -5.68906262 },\n') file.write('\tatom {H, 2.20521176, -0.06198380, -4.64309683 },\n') file.write('\tatom {H, 2.31173867, 0.01944289, -1.82913594 },\n') file.write('\tatom {H, 1.32886723, 0.78738104, -2.74525907 },\n') file.write('\tatom {H, -2.31173867, -0.01944289, -1.82913594 },\n') file.write('\tatom {H, -1.32886723, -0.78738104, -2.74525907 },\n') file.write('\tatom {H, 2.25842437, -0.00766951, 3.78016786 },\n') file.write('\tatom {H, 1.32470791, 0.78779803, 2.83722371 },\n') file.write('\tatom {H, -1.32470791, -0.78779803, 2.83722371 },\n') file.write('\tatom {H, -2.25842437, 0.00766951, 3.78016786 },\n') file.write('\tatom {H, -0.06198380, -2.20521176, 4.64309683 },\n') file.write('\tatom {H, -0.79989605, -1.35280911, 5.68906262 },\n') file.write('\tatom {H, -1.32913877, 0.84798431, 5.70007128 },\n') file.write('\tatom {H, -2.66479384, 0.33786677, 6.33131988 },\n') file.write('\tatom {H, -0.84798431, -1.32913877, -5.70007128 },\n') file.write('\tatom {H, -0.33786677, -2.66479384, -6.33131988 },\n') file.write('\tatom {H, -1.35280911, 0.79989605, -5.68906262 },\n') file.write('\tatom {H, -2.20521176, 0.06198380, -4.64309683 },\n') file.write('\tatom {H, -1.31495188, 0.82267561, 0.04672494 },\n') file.write('\tatom {H, -2.30533139, 0.08017087, 0.97354165 },\n') file.write('\tatom {H, -0.01944289, 2.31173867, 1.82913594 },\n') file.write('\tatom {H, -0.78738104, 1.32886723, 2.74525907 },\n') file.write('\tatom {H, -0.78779803, 1.32470791, -2.83722371 },\n') file.write('\tatom {H, 0.00766951, 2.25842437, -3.78016786 },\n') file.write('\tatom {H, -0.00766951, -2.25842437, -3.78016786 },\n') file.write('\tatom {H, 0.78779803, -1.32470791, -2.83722371 },\n') file.write('\tatom {H, 0.82267561, 1.31495188, -0.04672494 },\n') file.write('\tatom {H, 0.08017087, 2.30533139, -0.97354165 },\n') file.write('\tatom {H, -0.08017087, -2.30533139, -0.97354165 },\n') file.write('\tatom {H, -0.82267561, -1.31495188, -0.04672494 },\n') file.write('\tatom {H, 0.01944289, -2.31173867, 1.82913594 },\n') file.write('\tatom {H, 0.78738104, -1.32886723, 2.74525907 },\n') file.write('\tatom {H, 2.30533139, -0.08017087, 0.97354165 },\n') file.write('\tatom {H, 1.31495188, -0.82267561, 0.04672494 },\n') #------------------------------------------ #n=20 Face-sharing pentagonal prisms *** C1 #------------------------------------------ #MP2/aug-cc-pVTZ delta E=218.45, kcal/mol def print_w20face(file): file.write('\tatom {O, 0.52945249, -1.32341961, -2.30158189 },\n') file.write('\tatom {H, 0.57230430, -0.42717289, -2.66988776 },\n') file.write('\tatom {H, 1.20070409, -1.32066723, -1.58236699 },\n') file.write('\tatom {O, 1.15049608, -4.32687653, 2.04924411 },\n') file.write('\tatom {H, 1.57542699, -5.00739601, 2.57892027 },\n') file.write('\tatom {H, 1.60949740, -4.34253049, 1.16189634 },\n') file.write('\tatom {O, 0.43806402, -4.20372761, -2.32782506 },\n') file.write('\tatom {H, 0.44787429, -3.28142680, -2.62541858 },\n') file.write('\tatom {H, -0.45932379, -4.33561864, -1.97710108 },\n') file.write('\tatom {O, 2.35781728, -1.30466145, -0.25541273 },\n') file.write('\tatom {H, 2.72470105, -0.40693996, -0.27646674 },\n') file.write('\tatom {H, 1.86671290, -1.35451305, 0.59543217 },\n') file.write('\tatom {O, 0.96735180, -1.54034611, 2.09783423 },\n') file.write('\tatom {H, 0.00404971, -1.51159356, 1.90135129 },\n') file.write('\tatom {H, 1.13621383, -2.47031437, 2.33758076 },\n') file.write('\tatom {O, -1.62143181, -4.23624316, 1.51666252 },\n') file.write('\tatom {H, -0.68246122, -4.36821795, 1.74577177 },\n') file.write('\tatom {H, -1.80536731, -3.31735200, 1.76945516 },\n') file.write('\tatom {O, 2.31463680, -4.17464923, -0.30755498 },\n') file.write('\tatom {H, 1.67602063, -4.26997138, -1.04828109 },\n') file.write('\tatom {H, 2.63435439, -3.26358668, -0.39274644 },\n') file.write('\tatom {O, -1.70526253, -1.39791294, 1.52170484 },\n') file.write('\tatom {H, -1.80917617, -1.40893550, 0.54278325 },\n') file.write('\tatom {H, -1.98575126, -0.50890908, 1.79217826 },\n') file.write('\tatom {O, -1.95876773, -1.53963091, -1.19559330 },\n') file.write('\tatom {H, -1.06418216, -1.49619064, -1.60411429 },\n') file.write('\tatom {H, -2.24140869, -2.46507811, -1.31525881 },\n') file.write('\tatom {O, -2.14759768, -4.31870400, -1.09600433 },\n') file.write('\tatom {H, -2.81592119, -4.98319666, -1.28498287 },\n') file.write('\tatom {H, -1.97069280, -4.37663278, -0.12078047 },\n') file.write('\tatom {O, 0.47462142, 4.36989186, -2.26500408 },\n') file.write('\tatom {H, 0.64332081, 5.05859373, -2.91474547 },\n') file.write('\tatom {H, 1.15332550, 4.48635526, -1.56420801 },\n') file.write('\tatom {O, 1.04744580, 1.25382475, 2.07656068 },\n') file.write('\tatom {H, 1.20137037, 0.34809551, 2.39608938 },\n') file.write('\tatom {H, 1.50864481, 1.29478677, 1.20898789 },\n') file.write('\tatom {O, 0.36246279, 1.51681328, -2.28083815 },\n') file.write('\tatom {H, -0.51589979, 1.43165665, -1.84405298 },\n') file.write('\tatom {H, 0.40074983, 2.44105957, -2.57548934 },\n') file.write('\tatom {O, 2.25856065, 4.37564134, -0.17806446 },\n') file.write('\tatom {H, 1.75221775, 4.32182058, 0.68054568 },\n') file.write('\tatom {H, 2.95320011, 5.02386318, -0.02770403 },\n') file.write('\tatom {O, 0.90843697, 4.07580627, 2.06792242 },\n') file.write('\tatom {H, -0.05337760, 4.21506749, 1.98795378 },\n') file.write('\tatom {H, 1.00425702, 3.15139572, 2.35266656 },\n') file.write('\tatom {O, -1.65298960, 1.41022398, 1.65281057 },\n') file.write('\tatom {H, -0.68490739, 1.37364478, 1.82298417 },\n') file.write('\tatom {H, -1.90699229, 2.32674767, 1.85706401 },\n') file.write('\tatom {O, 2.29898253, 1.52003111, -0.34503957 },\n') file.write('\tatom {H, 2.58424894, 2.44853098, -0.33251102 },\n') file.write('\tatom {H, 1.61192718, 1.49454437, -1.04947491 },\n') file.write('\tatom {O, -1.86712930, 4.21917278, 1.62359977 },\n') file.write('\tatom {H, -2.47864145, 4.86605383, 1.98706675 },\n') file.write('\tatom {H, -1.98950935, 4.24471119, 0.63900806 },\n') file.write('\tatom {O, -2.09773771, 4.06193394, -1.02689536 },\n') file.write('\tatom {H, -2.29133429, 3.12966308, -1.22336514 },\n') file.write('\tatom {H, -1.26407666, 4.24453134, -1.49235316 },\n') file.write('\tatom {O, -2.05469277, 1.24139297, -1.04290791 },\n') file.write('\tatom {H, -2.34397200, 0.33343012, -1.23979408 },\n') file.write('\tatom {H, -1.92043436, 1.25492362, -0.06791205 },\n') #------------------------------------------ #n=20 Edge-sharing pentagonal prisms *** C1 #------------------------------------------ #MP2/aug-cc-pVTZ delta E=220.32, kcal/mol def print_w20edge(file): file.write('\tatom {O, -1.39543275, 2.31657627, 1.37046631 },\n') file.write('\tatom {H, -0.92662369, 1.46817589, 1.52206631 },\n') file.write('\tatom {H, -2.32442996, 2.12591716, 1.59673517 },\n') file.write('\tatom {O, -1.32982068, 2.51637315, -1.37954570 },\n') file.write('\tatom {H, -1.36882754, 2.54005044, -0.39789671 },\n') file.write('\tatom {H, -0.65200515, 3.17800652, -1.61031691 },\n') file.write('\tatom {O, -0.01733366, -0.02086307, 1.42288405 },\n') file.write('\tatom {H, -0.39379156, -0.91808476, 1.55793838 },\n') file.write('\tatom {H, 0.95427978, -0.07116580, 1.55922563 },\n') file.write('\tatom {O, 2.70141424, 0.02680068, 1.34938542 },\n') file.write('\tatom {H, 2.75656934, 0.02328537, 0.36773137 },\n') file.write('\tatom {H, 2.96101409, 0.93225671, 1.60318599 },\n') file.write('\tatom {O, -4.03268277, -1.36044802, -1.47184098 },\n') file.write('\tatom {H, -4.78522154, -1.60751488, -2.01683073 },\n') file.write('\tatom {H, -3.97489677, -0.37132077, -1.52599292 },\n') file.write('\tatom {O, 0.89946758, -4.24052125, 1.48696795 },\n') file.write('\tatom {H, 1.06572432, -5.00858815, 2.04076342 },\n') file.write('\tatom {H, 1.73078849, -3.69863929, 1.51444552 },\n') file.write('\tatom {O, 3.12169441, -2.79383799, -1.56662762 },\n') file.write('\tatom {H, 3.69601882, -3.27637364, -2.16793827 },\n') file.write('\tatom {H, 2.24825705, -3.26645164, -1.58986551 },\n') file.write('\tatom {O, -0.08687104, 0.08739608, -1.30493909 },\n') file.write('\tatom {H, -0.52989350, 0.93922436, -1.51509713 },\n') file.write('\tatom {H, -0.08003457, 0.07934656, -0.31956773 },\n') file.write('\tatom {O, -1.39615176, -2.28999690, -1.40973862 },\n') file.write('\tatom {H, -2.33616644, -2.12129946, -1.60528195 },\n') file.write('\tatom {H, -0.96468677, -1.41450889, -1.52550547 },\n') file.write('\tatom {O, -4.01405126, 1.35720135, 1.50706655 },\n') file.write('\tatom {H, -4.75134581, 1.59164800, 2.07791242 },\n') file.write('\tatom {H, -3.93675624, 0.36921416, 1.55883498 },\n') file.write('\tatom {O, 0.78524496, -4.05592492, -1.37112947 },\n') file.write('\tatom {H, 0.73646675, -4.29406759, -0.42971134 },\n') file.write('\tatom {H, -0.02972066, -3.55028342, -1.54040588 },\n') file.write('\tatom {O, 2.63041510, -0.04600633, -1.40445880 },\n') file.write('\tatom {H, 2.89071090, -0.95485093, -1.64456265 },\n') file.write('\tatom {H, 1.65651502, -0.01485283, -1.52765948 },\n') file.write('\tatom {O, 3.13906504, 2.71354684, -1.28081039 },\n') file.write('\tatom {H, 3.10239157, 1.76228567, -1.48429784 },\n') file.write('\tatom {H, 3.32533139, 2.75043550, -0.32691209 },\n') file.write('\tatom {O, -1.23232183, -2.45173072, 1.34110243 },\n') file.write('\tatom {H, -0.60298141, -3.16346609, 1.56144181 },\n') file.write('\tatom {H, -1.30491352, -2.48082581, 0.36147818 },\n') file.write('\tatom {O, 0.92255596, 4.17488519, -1.52804515 },\n') file.write('\tatom {H, 1.11093701, 4.93710992, -2.08306670 },\n') file.write('\tatom {H, 1.74878456, 3.62425684, -1.53602828 },\n') file.write('\tatom {O, 3.11084510, -2.76903827, 1.29472370 },\n') file.write('\tatom {H, 3.09043382, -1.82589836, 1.53137113 },\n') file.write('\tatom {H, 3.30883978, -2.77464518, 0.34210251 },\n') file.write('\tatom {O, -3.90092000, 1.30179294, -1.35091239 },\n') file.write('\tatom {H, -3.09681655, 1.79496369, -1.58474282 },\n') file.write('\tatom {H, -4.03470630, 1.48678957, -0.40518202 },\n') file.write('\tatom {O, 3.12357086, 2.78007575, 1.58228565 },\n') file.write('\tatom {H, 2.24950517, 3.25165854, 1.58673980 },\n') file.write('\tatom {H, 3.69419494, 3.28034834, 2.17303947 },\n') file.write('\tatom {O, 0.80305370, 4.06443682, 1.32921270 },\n') file.write('\tatom {H, -0.02269679, 3.58096491, 1.50807247 },\n') file.write('\tatom {H, 0.76332278, 4.27139378, 0.37953183 },\n') file.write('\tatom {O, -3.82938205, -1.29987979, 1.37976151 },\n') file.write('\tatom {H, -3.00615211, -1.77303605, 1.58824604 },\n') file.write('\tatom {H, -3.98755690, -1.48869245, 0.43855016 },\n') #-------------- #n=21 (Surface) #-------------- def print_w21(file): file.write('\tatom {O, 2.88102880, 1.35617710, -1.35936865 },\n') file.write('\tatom {H, 2.58653411, 2.28696609, -1.45609052 },\n') file.write('\tatom {H, 3.32093709, 1.29343465, -0.49116710 },\n') file.write('\tatom {O, 0.32179453, 0.62629846, -0.94851226 },\n') file.write('\tatom {H, 1.26447032, 0.88843717, -1.07026883 },\n') file.write('\tatom {H, -0.21718807, 1.36563667, -1.31919284 },\n') file.write('\tatom {O, -0.16007111, -1.63872066, -2.31840571 },\n') file.write('\tatom {H, 0.01823460, -0.80812840, -1.82332661 },\n') file.write('\tatom {H, 0.10093174, -2.33288028, -1.67894566 },\n') file.write('\tatom {O, -2.84753775, -0.70659788, 1.22536498 },\n') file.write('\tatom {H, -2.82066138, -1.51379494, 1.77020749 },\n') file.write('\tatom {H, -2.78672686, -1.02520290, 0.29442139 },\n') file.write('\tatom {O, -1.28347305, 2.64257815, -1.71714330 },\n') file.write('\tatom {H, -1.51430450, 2.88443923, -0.79572381 },\n') file.write('\tatom {H, -2.09726640, 2.24298480, -2.07172804 },\n') file.write('\tatom {O, -3.72092200, 1.16535937, -2.05155378 },\n') file.write('\tatom {H, -3.96467209, 1.40975690, -1.12274906 },\n') file.write('\tatom {H, -4.48373842, 1.39703848, -2.59023807 },\n') file.write('\tatom {O, -2.75707813, -1.44066167, -1.41017665 },\n') file.write('\tatom {H, -3.20125609, -0.67001218, -1.80694890 },\n') file.write('\tatom {H, -1.88535531, -1.49090783, -1.86154221 },\n') file.write('\tatom {O, -2.18430745, -4.00503366, -0.11745556 },\n') file.write('\tatom {H, -2.58170529, -3.32141555, -0.67897787 },\n') file.write('\tatom {H, -1.24901286, -4.03122679, -0.38234526 },\n') file.write('\tatom {O, 3.76378263, 0.84987648, 1.25359107 },\n') file.write('\tatom {H, 4.64925014, 0.99382151, 1.60153466 },\n') file.write('\tatom {H, 3.59269678, -0.12230330, 1.37734803 },\n') file.write('\tatom {O, 3.25939067, -1.73586556, 1.54809767 },\n') file.write('\tatom {H, 2.38789220, -1.97346725, 1.90398296 },\n') file.write('\tatom {H, 3.34047461, -2.24000005, 0.71725832 },\n') file.write('\tatom {O, 0.47067808, -2.08139855, 2.05406984 },\n') file.write('\tatom {H, -0.31565776, -2.51643817, 2.42960695 },\n') file.write('\tatom {H, 0.20916882, -1.14318846, 1.97673663 },\n') file.write('\tatom {O, 0.84341794, 4.45219154, 1.19543335 },\n') file.write('\tatom {H, 1.22169208, 3.69174389, 1.70700542 },\n') file.write('\tatom {H, 1.12534416, 5.24681772, 1.65820509 },\n') file.write('\tatom {O, 3.29073454, -3.06649080, -0.92760728 },\n') file.write('\tatom {H, 4.01092916, -3.62238167, -1.23916202 },\n') file.write('\tatom {H, 3.16110064, -2.37099393, -1.62514329 },\n') file.write('\tatom {O, -2.13311585, -3.15170259, 2.41174304 },\n') file.write('\tatom {H, -2.19514114, -3.57941119, 1.51889439 },\n') file.write('\tatom {H, -2.56149431, -3.75503610, 3.02609742 },\n') file.write('\tatom {O, 1.49292018, 3.74546296, -1.50486304 },\n') file.write('\tatom {H, 1.31323368, 4.10353119, -0.61794466 },\n') file.write('\tatom {H, 0.61187301, 3.56898981, -1.86464476 },\n') file.write('\tatom {O, -0.48284790, 0.54531195, 1.58871855 },\n') file.write('\tatom {H, -0.15462414, 0.54530283, 0.65343103 },\n') file.write('\tatom {H, -1.36928803, 0.11358922, 1.52480652 },\n') file.write('\tatom {O, 2.72236852, -1.18342053, -2.72120243 },\n') file.write('\tatom {H, 1.76763800, -1.29146509, -2.86748821 },\n') file.write('\tatom {H, 2.83269882, -0.26932242, -2.40792605 },\n') file.write('\tatom {O, 1.64182263, 2.24659436, 2.46745517 },\n') file.write('\tatom {H, 2.41153336, 1.77257628, 2.10024166 },\n') file.write('\tatom {H, 0.91471507, 1.60671414, 2.41570272 },\n') file.write('\tatom {O, -4.10080206, 1.73028823, 0.54526604 },\n') file.write('\tatom {H, -3.83492913, 0.90816710, 0.99225907 },\n') file.write('\tatom {H, -3.44369737, 2.38297040, 0.83399222 },\n') file.write('\tatom {O, -1.60618492, 3.09549014, 1.00019438 },\n') file.write('\tatom {H, -0.94029673, 3.78712081, 1.16680637 },\n') file.write('\tatom {H, -1.18360076, 2.28420300, 1.34174432 },\n') file.write('\tatom {O, 0.57200422, -3.46363889, -0.35742274 },\n') file.write('\tatom {H, 0.57764102, -2.95313709, 0.47874423 },\n') file.write('\tatom {H, 1.51287263, -3.60041770, -0.56712755 },\n') #-------------- #n=64 (Graham Fletcher) #-------------- def print_w64(file): file.write('\tatom { O, 5.3341355614, 2.2822875147, 2.5569123279 },\n') file.write('\tatom { H, 6.1242446995, 2.3804428156, 3.0638359324 },\n') file.write('\tatom { H, 4.6164505920, 2.2847341851, 3.1699382266 },\n') file.write('\tatom { O, -4.9828260569, 6.5645399222, -1.4305048434 },\n') file.write('\tatom { H, -5.7327448357, 6.5144561802, -2.0014618453 },\n') file.write('\tatom { H, -4.9037228691, 5.7222103356, -1.0120529257 },\n') file.write('\tatom { O, -3.6227640662, -2.0094049926, -3.5842035387 },\n') file.write('\tatom { H, -3.5704397802, -2.5983493456, -2.8484826866 },\n') file.write('\tatom { H, -4.5389553668, -1.8307904854, -3.7240921110 },\n') file.write('\tatom { O, 3.1392579772, 2.4144865880, -4.5706452556 },\n') file.write('\tatom { H, 2.8184642359, 3.2470917478, -4.8784414178 },\n') file.write('\tatom { H, 3.3782568871, 2.5337043355, -3.6653579510 },\n') file.write('\tatom { O, -6.0971764862, -1.1475458408, -3.2398107026 },\n') file.write('\tatom { H, -5.8105777311, -0.6248900075, -2.5079838873 },\n') file.write('\tatom { H, -6.8392216912, -1.6486367323, -2.9412218779 },\n') file.write('\tatom { O, -4.7437455608, 0.2406638067, -1.4425658527 },\n') file.write('\tatom { H, -5.1439053474, 0.8961107449, -0.8938036906 },\n') file.write('\tatom { H, -4.1189937486, 0.6893944851, -1.9895616530 },\n') file.write('\tatom { O, -1.3905594340, 0.6003032181, 1.6523328323 },\n') file.write('\tatom { H, -1.0076438736, -0.2571121741, 1.5569757518 },\n') file.write('\tatom { H, -1.0031627095, 1.1459707668, 0.9867134529 },\n') file.write('\tatom { O, -2.9506051416, -2.0575020924, 2.2939955486 },\n') file.write('\tatom { H, -2.0162828847, -2.1275710915, 2.4080600466 },\n') file.write('\tatom { H, -3.0925674007, -1.6978547015, 1.4329619109 },\n') file.write('\tatom { O, -1.4892138488, 4.9887537665, -3.2733984712 },\n') file.write('\tatom { H, -0.5572623487, 5.0949966526, -3.1682447519 },\n') file.write('\tatom { H, -1.8837342524, 5.8159639054, -3.0476652410 },\n') file.write('\tatom { O, 0.9956287780, 2.8403164571, -1.8268350733 },\n') file.write('\tatom { H, 1.9163773315, 2.6332485532, -1.8118872182 },\n') file.write('\tatom { H, 0.9290176036, 3.7698996404, -1.9762221903 },\n') file.write('\tatom { O, -2.5570429685, 7.1678424798, -2.1041651892 },\n') file.write('\tatom { H, -2.4346193763, 8.0661032604, -2.3668788894 },\n') file.write('\tatom { H, -3.4798399701, 7.0565619038, -1.9400287177 },\n') file.write('\tatom { O, 1.9364331416, 0.8087408534, 1.8554569521 },\n') file.write('\tatom { H, 1.4707676717, 0.8191552420, 2.6763867084 },\n') file.write('\tatom { H, 1.9844358212, 1.7036938663, 1.5594277280 },\n') file.write('\tatom { O, -0.8237869838, 6.5422485997, -0.2172900020 },\n') file.write('\tatom { H, -1.0773967082, 5.8227010871, 0.3384184997 },\n') file.write('\tatom { H, -1.5172520267, 6.6558571044, -0.8474310942 },\n') file.write('\tatom { O, -1.1636685123, 4.5053778469, 1.4336238815 },\n') file.write('\tatom { H, -0.9421345969, 3.7303124294, 0.9426302185 },\n') file.write('\tatom { H, -2.0469731124, 4.3864670806, 1.7442871514 },\n') file.write('\tatom { O, -0.4673817162, -0.9650433991, -1.0753723663 },\n') file.write('\tatom { H, -1.3292040099, -0.9969136435, -0.6918034996 },\n') file.write('\tatom { H, -0.4411881520, -0.1946487172, -1.6200597862 },\n') file.write('\tatom { O, -2.7498569237, 0.5798645061, -3.2061586058 },\n') file.write('\tatom { H, -2.9949221552, -0.3106733578, -3.4004877068 },\n') file.write('\tatom { H, -1.8071593424, 0.6147993766, -3.2374520413 },\n') file.write('\tatom { O, -2.9697982126, -1.3746742901, -0.2808320442 },\n') file.write('\tatom { H, -3.6357151582, -0.7980251231, -0.6198140699 },\n') file.write('\tatom { H, -3.0855526381, -2.2060771209, -0.7123974507 },\n') file.write('\tatom { O, 1.8148526783, 0.1245102111, -4.6237838221 },\n') file.write('\tatom { H, 2.2429426431, 0.9556874312, -4.7532514430 },\n') file.write('\tatom { H, 2.4707150376, -0.4704553354, -4.2970744432 },\n') file.write('\tatom { O, -0.8261033555, 2.4323079020, -0.0832596083 },\n') file.write('\tatom { H, -1.5269390763, 2.5208697741, -0.7092504559 },\n') file.write('\tatom { H, -0.0196120782, 2.4648804414, -0.5725338701 },\n') file.write('\tatom { O, -1.3817049691, -5.0352329774, -2.4232812447 },\n') file.write('\tatom { H, -0.7684293116, -4.3182706978, -2.4504199904 },\n') file.write('\tatom { H, -1.4545340129, -5.3634550894, -3.3052362490 },\n') file.write('\tatom { O, 1.9215826085, -1.0921763125, 0.1197749095 },\n') file.write('\tatom { H, 1.0849945087, -1.2270160735, -0.2959377849 },\n') file.write('\tatom { H, 1.7847739979, -0.4579975452, 0.8053251625 },\n') file.write('\tatom { O, -1.0018623482, -5.1120322982, -5.0837566752 },\n') file.write('\tatom { H, -1.3933176067, -5.5582077871, -5.8176290536 },\n') file.write('\tatom { H, -1.1664244625, -4.1908496790, -5.2071274443 },\n') file.write('\tatom { O, 3.5172957950, 2.3202722362, -1.9688149465 },\n') file.write('\tatom { H, 3.9976007522, 2.8596853436, -1.3611809269 },\n') file.write('\tatom { H, 3.7014504726, 1.4233801808, -1.7395767524 },\n') file.write('\tatom { O, -2.6102841193, 3.0430679155, -1.9350734213 },\n') file.write('\tatom { H, -2.8695431759, 2.3270909601, -2.4927831979 },\n') file.write('\tatom { H, -2.2135983071, 3.6922269672, -2.4937426848 },\n') file.write('\tatom { O, 0.9098841921, 5.4361164481, -2.0327307748 },\n') file.write('\tatom { H, 1.8021902964, 5.7117315130, -1.8959659902 },\n') file.write('\tatom { H, 0.3966346177, 5.8268238497, -1.3436726824 },\n') file.write('\tatom { O, -0.1396389829, 0.8002592786, -2.9481938727 },\n') file.write('\tatom { H, 0.1803973363, 1.6461091339, -2.6780212784 },\n') file.write('\tatom { H, 0.4842490367, 0.4598789293, -3.5693085246 },\n') file.write('\tatom { O, -4.3860363431, 4.2720576892, -0.3433107406 },\n') file.write('\tatom { H, -3.7336474223, 3.8267809447, -0.8600270757 },\n') file.write('\tatom { H, -4.0487873372, 4.3197159157, 0.5369564095 },\n') file.write('\tatom { O, -0.3551237102, -1.8527769523, 2.0684277226 },\n') file.write('\tatom { H, -0.0920198226, -2.5657488890, 1.5086725835 },\n') file.write('\tatom { H, 0.2994391739, -1.7831738698, 2.7448752784 },\n') file.write('\tatom { O, -3.4203294336, -3.7199007883, -1.3994806141 },\n') file.write('\tatom { H, -2.7432687765, -4.3024393603, -1.7046299754 },\n') file.write('\tatom { H, -3.7574552271, -4.0910677065, -0.5998183277 },\n') file.write('\tatom { O, -0.0519252874, -2.8278717444, -2.8209994698 },\n') file.write('\tatom { H, -0.5501145679, -2.5647894176, -3.5782798566 },\n') file.write('\tatom { H, -0.2137034959, -2.1819475862, -2.1520538463 },\n') file.write('\tatom { O, 3.9326972172, -0.1447916343, -1.2323267086 },\n') file.write('\tatom { H, 4.6265233238, -0.0736418998, -0.5963852781 },\n') file.write('\tatom { H, 3.1862113709, -0.5043840273, -0.7802972336 },\n') file.write('\tatom { O, 3.7401140949, -0.5820784924, 3.2346232262 },\n') file.write('\tatom { H, 3.4109667678, 0.0010845580, 2.5694455449 },\n') file.write('\tatom { H, 4.4887698990, -1.0213950985, 2.8639564478 },\n') file.write('\tatom { O, 1.6035214145, 7.5332271460, 0.5500656116 },\n') file.write('\tatom { H, 0.7804662926, 7.4203968594, 0.1020387745 },\n') file.write('\tatom { H, 1.6492220601, 8.4396260189, 0.8093550024 },\n') file.write('\tatom { O, 4.4003916363, 3.8226598525, 0.0069188393 },\n') file.write('\tatom { H, 5.2612591295, 3.6986968994, 0.3735505340 },\n') file.write('\tatom { H, 3.7823167909, 3.6072717418, 0.6869702355 },\n') file.write('\tatom { O, -3.5834193506, 3.9852493421, 2.1840448160 },\n') file.write('\tatom { H, -3.7291009199, 3.0645550013, 2.3322921269 },\n') file.write('\tatom { H, -3.7812015565, 4.4252777695, 2.9953004084 },\n') file.write('\tatom { O, 3.4936095435, -3.1058523194, 0.9291805120 },\n') file.write('\tatom { H, 3.3712294837, -3.7693386248, 0.2691142293 },\n') file.write('\tatom { H, 2.9197575006, -2.3908543652, 0.7047919818 },\n') file.write('\tatom { O, -3.7164915636, -0.3806762095, 4.1363149244 },\n') file.write('\tatom { H, -4.3366135314, -0.6984719984, 4.7729726312 },\n') file.write('\tatom { H, -3.5133359239, -1.1073635653, 3.5692772474 },\n') file.write('\tatom { O, -3.8937397475, -4.4355904336, 1.1000366022 },\n') file.write('\tatom { H, -3.6344581178, -3.7269260008, 1.6669988693 },\n') file.write('\tatom { H, -3.4115082598, -5.1971956457, 1.3798378660 },\n') file.write('\tatom { O, 5.7005647273, 0.3190826622, 0.6496630329 },\n') file.write('\tatom { H, 5.5135869586, 0.9928593935, 1.2836525316 },\n') file.write('\tatom { H, 5.8969239381, -0.4650189811, 1.1370090366 },\n') file.write('\tatom { O, 0.3840099694, -4.1137118300, 0.7819986172 },\n') file.write('\tatom { H, 1.0860882843, -4.1283857388, 0.1513250327 },\n') file.write('\tatom { H, -0.1978841279, -4.8218905579, 0.5566974790 },\n') file.write('\tatom { O, -3.8748255878, 1.3976416485, 2.1437263758 },\n') file.write('\tatom { H, -3.0861576019, 1.0303095317, 1.7777367885 },\n') file.write('\tatom { H, -4.0796022953, 0.8893530343, 2.9122233757 },\n') file.write('\tatom { O, 5.6156770347, -2.0418229061, 1.9133661087 },\n') file.write('\tatom { H, 6.2490773326, -2.6191226940, 2.3088499537 },\n') file.write('\tatom { H, 4.9780399179, -2.5908451139, 1.4857307772 },\n') file.write('\tatom { O, -0.6231302264, -6.3802894242, -0.3460579667 },\n') file.write('\tatom { H, 0.1618029347, -6.8320433206, -0.6119090598 },\n') file.write('\tatom { H, -1.0156082384, -6.0333732407, -1.1312258633 },\n') file.write('\tatom { O, -3.3285808216, 4.9913954097, 4.6233326842 },\n') file.write('\tatom { H, -2.4414687619, 4.6895031048, 4.7363445590 },\n') file.write('\tatom { H, -3.3912517639, 5.8217440407, 5.0677108542 },\n') file.write('\tatom { O, -1.4311111886, 1.2081374480, 4.1811948741 },\n') file.write('\tatom { H, -1.4049614958, 1.0234543269, 3.2559452902 },\n') file.write('\tatom { H, -2.1760032331, 0.7446962855, 4.5293853176 },\n') file.write('\tatom { O, 3.2736711954, 6.0672313090, -1.0775623608 },\n') file.write('\tatom { H, 3.0040606059, 6.6267462176, -0.3668362173 },\n') file.write('\tatom { H, 3.7758538289, 5.3655843574, -0.6949625541 },\n') file.write('\tatom { O, 2.3742924087, -3.5008642086, -3.2237852560 },\n') file.write('\tatom { H, 2.9884781739, -2.8117693661, -3.4207690065 },\n') file.write('\tatom { H, 1.5253394643, -3.0948867370, -3.1507123820 },\n') file.write('\tatom { O, -0.9668503726, 3.7985207601, 4.3145144878 },\n') file.write('\tatom { H, -1.1550049065, 2.8768954373, 4.3925086527 },\n') file.write('\tatom { H, -0.8388155195, 3.9724514381, 3.3956926064 },\n') file.write('\tatom { O, 2.4466289510, -4.6602701167, -0.8846294398 },\n') file.write('\tatom { H, 2.3411313009, -5.5896999919, -1.0107595591 },\n') file.write('\tatom { H, 2.4976467404, -4.2739068426, -1.7442799849 },\n') file.write('\tatom { O, 2.5305065060, 3.3990198177, 1.7380162868 },\n') file.write('\tatom { H, 2.8139586713, 3.1626575111, 2.6067315359 },\n') file.write('\tatom { H, 1.9901367993, 4.1675619150, 1.8286919663 },\n') file.write('\tatom { O, 2.0604372566, -4.3421927104, 2.9544881392 },\n') file.write('\tatom { H, 1.3133508954, -4.4899706086, 2.3969021675 },\n') file.write('\tatom { H, 2.7485484168, -4.0061983788, 2.4026826530 },\n') file.write('\tatom { O, -1.4732015151, -2.5280373896, -4.9717166508 },\n') file.write('\tatom { H, -1.1453908577, -1.8601111236, -5.5524860802 },\n') file.write('\tatom { H, -2.3506759588, -2.2741409052, -4.7341169248 },\n') file.write('\tatom { O, 1.1220256376, 5.5421086354, 2.2765980287 },\n') file.write('\tatom { H, 0.2228618163, 5.3651637598, 2.0506038086 },\n') file.write('\tatom { H, 1.3717300800, 6.3212767322, 1.8060417384 },\n') file.write('\tatom { O, 3.1317154301, 2.5492758922, 4.1628199793 },\n') file.write('\tatom { H, 2.7683876916, 3.2785666929, 4.6392717988 },\n') file.write('\tatom { H, 2.6043521159, 1.7961017823, 4.3761158982 },\n') file.write('\tatom { O, 1.1372281976, 0.6885852150, 4.3813162371 },\n') file.write('\tatom { H, 1.2494192006, -0.2236936306, 4.5958831050 },\n') file.write('\tatom { H, 0.2369780196, 0.9023734278, 4.5676564399 },\n') file.write('\tatom { O, -0.1016378554, -0.6926890421, -6.2527824769 },\n') file.write('\tatom { H, 0.1702908401, -0.6992191681, -7.1566024789 },\n') file.write('\tatom { H, 0.6406347495, -0.4004969649, -5.7482692223 },\n') file.write('\tatom { O, -2.3285161725, -6.5511603803, 1.6473226256 },\n') file.write('\tatom { H, -1.6896078368, -6.6733975054, 0.9634127793 },\n') file.write('\tatom { H, -2.6495824264, -7.4090128354, 1.8751033974 },\n') file.write('\tatom { O, 1.4527752549, -5.8880275983, -4.0675040894 },\n') file.write('\tatom { H, 0.6343187338, -5.6701343479, -4.4840733017 },\n') file.write('\tatom { H, 1.9234004643, -5.0778176061, -3.9537054302 },\n') file.write('\tatom { O, 1.5983976737, -1.9057788553, 3.9163341508 },\n') file.write('\tatom { H, 2.4379449939, -1.5554994781, 3.6646535812 },\n') file.write('\tatom { H, 1.6912564086, -2.8448470595, 3.9364989058 },\n') file.write('\tatom { O, 1.6232603136, 4.6427291861, 4.8129279939 },\n') file.write('\tatom { H, 0.7443920087, 4.3339913767, 4.9650789773 },\n') file.write('\tatom { H, 1.5954824854, 5.1634302425, 4.0261769175 },\n') file.write('\tatom { O, 1.6169447310, -7.0971132635, -1.7472363134 },\n') file.write('\tatom { H, 1.4837903359, -6.7909864629, -2.6300923283 },\n') file.write('\tatom { H, 2.0775965422, -7.9184244668, -1.8114723640 },\n') file.write('\tatom { O, 3.8562197281, -1.2815791583, -3.5491264929 },\n') file.write('\tatom { H, 4.0398199763, -0.8915958844, -2.7094346155 },\n') file.write('\tatom { H, 4.6633269012, -1.2650987669, -4.0381917871 },\n') file.write('\tatom { O, -5.6995689859, 1.9293266748, 0.2651776192 },\n') file.write('\tatom { H, -5.5321355459, 2.8335349273, 0.0524526011 },\n') file.write('\tatom { H, -5.1861533360, 1.7315023768, 1.0320859394 },\n') file.write('\tatom { O, -0.8806597750, 9.1048813981, 0.6911891481 },\n') file.write('\tatom { H, -1.5189059755, 9.4074827100, 1.3172503972 },\n') file.write('\tatom { H, -1.0704878524, 8.1947118324, 0.5286003513 },\n') def print_geom(file,cluster): file.write('molecule\n{\n') file.write('\tcoords cartesian,\n') if cluster == "rubrene": print_rubrene(file) if cluster == "w1": print_w1(file,0.0) elif cluster == "w2": print_w2(file) elif cluster == "w3": print_w3(file) elif cluster == "w4": print_w4(file) elif cluster == "w5": print_w5(file) elif cluster == "w6cage": print_w6cage(file) elif cluster == "w6book": print_w6book(file) elif cluster == "w6prism": print_w6prism(file) elif cluster == "w6cyclic": print_w6cyclic(file) elif cluster == "w7": print_w7(file) elif cluster == "w8s4": print_w8s4(file) elif cluster == "w8d2d": print_w8d2d(file) elif cluster == "w9": print_w9(file) elif cluster == "w10": print_w10(file) elif cluster == "w11i434": print_w11i434(file) elif cluster == "w11i4412": print_w11i4412(file) elif cluster == "w11i443": print_w11i443(file) elif cluster == "w11i515": print_w11i515(file) elif cluster == "w11i551": print_w11i551(file) elif cluster == "w12": print_w12(file) elif cluster == "w13": print_w13(file) elif cluster == "w14": print_w14(file) elif cluster == "w15": print_w15(file) elif cluster == "w16": print_w16(file) elif cluster == "w17int": print_w17int(file) elif cluster == "w17surf": print_w17surf(file) elif cluster == "w18": print_w18(file) elif cluster == "w19": print_w19(file) elif cluster == "w20dode": print_w20dode(file) elif cluster == "w20fused": print_w20fused(file) elif cluster == "w20face": print_w20face(file) elif cluster == "w20edge": print_w20edge(file) elif cluster == "w21": print_w21(file) elif cluster == "w64": print_w64(file) elif cluster[0] == "w": n = int(cluster[1:]) for i in range(0,n): print_w1(file,1.0*i) def print_basis(file,basis): file.write('\tbasis\n') file.write('\t\tbasis_set '+basis+'\n},\n') def print_scf(file): file.write('1eints,\n') file.write('2eints,\n') file.write('localaoscf\n{\n') file.write('\tconvergence 1e-9,\n') file.write('\tfrozen_core on,\n') file.write('\tmax_iterations 100,\n') file.write('\tdiis\n\t{\n') file.write('\t\torder 6,\n') file.write('\t\tstart 8\n\t}\n},\n') file.write('aomoints,\n') def print_cc(file,method): file.write(method+'\n{\n') file.write('\tdiis order 5,\n') file.write('\tconvergence 1e-9,\n') file.write('\tmax_iterations 5\n}\n') cluster = str(sys.argv[1]) basis = str(sys.argv[2]) method = str(sys.argv[3]) name = cluster+'_'+basis+'_'+method filename = name+'.aq' file = open(filename,'w\n') print name print_geom(file,cluster) print_basis(file,basis) print_scf(file) print_cc(file,method) file.close()

75.295667

108

0.502585

16,028

128,605

4.027015

0.240766

0.197165

0.302797

0.316291

0.482563

0.475157

0.181532

0.18051

0.179658

0.177628

0

0.430611

0.290829

128,605

1,707

109

75.339777

0.277096

0.015886

0

0.00129

0

0.108387

0.723879

0

null

0

0.000645

null

0.056774

0

null

0

1

0

1

0

1

0

1

0

null

0

1

0

6

ad2f65f10e71a271b7da7f9a84665da3d7f0bfd1

209

py

Python

src/whylogs/proto/__init__.py

bernease/whylogs-python

cfd2a2f71280537aae584cbd40a752fbe7da647b

[ "Apache-2.0" ]

null

src/whylogs/proto/__init__.py

bernease/whylogs-python

cfd2a2f71280537aae584cbd40a752fbe7da647b

[ "Apache-2.0" ]

null

src/whylogs/proto/__init__.py

bernease/whylogs-python

cfd2a2f71280537aae584cbd40a752fbe7da647b

[ "Apache-2.0" ]

null

""" Auto-generated protobuf class definitions. Protobuf allows us to serialize/deserialize classes across languages """ from .messages_pb2 import * from .summaries_pb2 import * from .constraints_pb2 import *

23.222222

68

0.799043

26

209

6.307692

0.730769

0.164634

0.158537

0

0.016484

0.129187

209

8

69

26.125

0.884615

0.535885

0

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

d1481ace914e84853809b76e231ba79394985def

400

py

Python

soccminer/environment.py

M3SOulu/soccminer

f8a5930ee1164e485bed5e6f712b323ed0b42b9b

[ "MIT" ]

2

2021-12-19T12:55:05.000Z

2022-01-25T13:14:42.000Z

soccminer/environment.py

M3SOulu/soccminer

f8a5930ee1164e485bed5e6f712b323ed0b42b9b

[ "MIT" ]

null

soccminer/environment.py

M3SOulu/soccminer

f8a5930ee1164e485bed5e6f712b323ed0b42b9b

[ "MIT" ]

1

2021-12-19T12:55:17.000Z

import sys class Platform: @staticmethod def fetch_platform(): return sys.platform @staticmethod def is_windows_platform(): return Platform.fetch_platform() == "win32" @staticmethod def is_unix_platform(): if Platform.fetch_platform() == "aix" or Platform.fetch_platform() == "linux": return True else: return False

21.052632

86

0.6175

41

400

5.829268

0.463415

0.217573

0.263598

0

0.007042

0.29

400

18

87

22.222222

0.834507

0

0.214286

0

0.0325

0

1

0.214286

true

0

0.071429

0.142857

0.642857

0

null

1

0

null

0

1

0

1

0

6

0f0110d66672563fb984df3a74cb02dd13d4ee9c

31,301

py

Python

st/clitests/rollback_spec.py

RakeshVaghasiya/cortx-s3server

356c00f7523883300f3271b365545f4ff8b4c2be

[ "Apache-2.0" ]

null

st/clitests/rollback_spec.py

RakeshVaghasiya/cortx-s3server

356c00f7523883300f3271b365545f4ff8b4c2be

[ "Apache-2.0" ]

null

st/clitests/rollback_spec.py

RakeshVaghasiya/cortx-s3server

356c00f7523883300f3271b365545f4ff8b4c2be

[ "Apache-2.0" ]

null

# # Copyright (c) 2020 Seagate Technology LLC and/or its Affiliates # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # For any questions about this software or licensing, # please email opensource@seagate.com or cortx-questions@seagate.com. # #!/usr/bin/python3.6 from framework import Config from framework import S3PyCliTest from s3cmd import S3cmdTest from s3fi import S3fiTest from jclient import JClientTest from s3client_config import S3ClientConfig from s3kvstool import S3kvTest import s3kvs import yaml # Helps debugging # Config.log_enabled = True # Config.dummy_run = True # Config.client_execution_timeout = 300 * 1000 # Config.request_timeout = 300 * 1000 # Config.socket_timeout = 300 * 1000 # Enable retry flag to limit retries on failure Config.s3cmd_max_retries = 2 # Set time_readable_format to False if you want to display the time in milli seconds. # Config.time_readable_format = False # TODO # DNS-compliant bucket names should not contains underscore or other special characters. # The allowed characters are [a-zA-Z0-9.-]* # # Add validations to S3 server and write system tests for the same. # ***MAIN ENTRY POINT # Run before all to setup the test environment. print("Configuring LDAP") S3PyCliTest('Before_all').before_all() # Set pathstyle =false to run jclient for partial multipart upload S3ClientConfig.pathstyle = False S3ClientConfig.access_key_id = 'AKIAJPINPFRBTPAYOGNA' S3ClientConfig.secret_key = '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' # Path style tests. Config.config_file = "pathstyle.s3cfg" # ************ Create bucket Fail ************ # Note: We clean kvs entries using cqlsh(cassandra-kvs) for this test to work S3fiTest('s3cmd enable FI create index fail').enable_fi("enable", "always", "motr_idx_create_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot create bucket').create_bucket("seagatebucket").execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_idx_create_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI PUT KV').enable_fi("enable", "always", "motr_kv_put_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot create bucket').create_bucket("seagatebucket").execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_put_fail").execute_test().command_is_successful() # ************ Create bucket ************ S3cmdTest('s3cmd can create bucket').create_bucket("seagatebucket").execute_test().command_is_successful() # ************ List buckets ************ S3cmdTest('s3cmd can list buckets').list_buckets().execute_test().command_is_successful().command_response_should_have('s3://seagatebucket') # ************ Multi delete empty bucket test ********* JClientTest('Jclient multiple delete should succeed when objects not present').delete_multiple_objects("seagatebucket", ["8kfile", "700Kfile", "18MBfile"]).execute_test().command_is_successful() # ************ 18MB FILE Multipart Rollback TEST *********** # function to cleanup multipart upload def clean_18mb_multipart(): result = S3cmdTest('s3cmd can list multipart uploads in progress').list_multipart_uploads("seagatebucket").execute_test() if '18MBfile' in result.status.stdout: upload_id = result.status.stdout.split('\n')[2].split('\t')[2] S3cmdTest('S3cmd can abort multipart upload').abort_multipart("seagatebucket", "18MBfile", upload_id).execute_test().command_is_successful() else: raise AssertionError("Failed to find multipart info.") return S3fiTest('s3cmd enable FI create index fail').enable_fi("enable", "always", "motr_idx_create_fail").execute_test().command_is_successful() S3cmdTest('s3cmd can upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd should not have objects after rollback').list_objects('seagatebucket').execute_test().command_is_successful().command_response_should_not_have('18MBfile') S3fiTest('s3cmd can disable Fault injection').disable_fi("motr_idx_create_fail").execute_test().command_is_successful() # Set second rollback checkpoint in multipart upload S3fiTest('s3cmd enable FI create index fail').enable_fi_enablen("enable", "motr_idx_create_fail", "1").execute_test().command_is_successful() S3cmdTest('s3cmd can upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd should not have objects after rollback').list_objects('seagatebucket').execute_test().command_is_successful().command_response_should_not_have('18MBfile') S3fiTest('s3cmd can disable Fault injection').disable_fi("motr_idx_create_fail").execute_test().command_is_successful() is_object_leak_track_enabled=yaml.load(open("/opt/seagate/cortx/s3/conf/s3config.yaml"))["S3_SERVER_CONFIG"]["S3_SERVER_ENABLE_OBJECT_LEAK_TRACKING"] fi_off="2" if is_object_leak_track_enabled: fi_off="4" S3fiTest('s3cmd enable FI PUT KV').enable_fi_offnonm("enable", "motr_kv_put_fail", fi_off, "99").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_put_fail").execute_test().command_is_successful() clean_18mb_multipart() S3fiTest('s3cmd enable FI GET KV').enable_fi_offnonm("enable", "motr_kv_get_fail", "3", "99").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() clean_18mb_multipart() S3fiTest('s3cmd enable FI GET KV').enable_fi_offnonm("enable", "motr_kv_get_fail", "5", "99").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() clean_18mb_multipart() S3fiTest('s3cmd enable FI GET KV').enable_fi_offnonm("enable", "motr_kv_get_fail", "9", "99").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() clean_18mb_multipart() S3fiTest('s3cmd enable FI GET KV').enable_fi_offnonm("enable", "motr_kv_get_fail", "19", "99").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() clean_18mb_multipart() S3fiTest('s3cmd enable FI fail_save_part_mdata').enable_fi("enable", "always", "fail_save_part_mdata").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3cmdTest('s3cmd should not have objects after rollback').list_objects('seagatebucket').execute_test().command_is_successful().command_response_should_not_have('18MBfile') S3fiTest('s3cmd can disable Fault injection').disable_fi("fail_save_part_mdata").execute_test().command_is_successful() # ************ auth FI *************** S3fiTest('s3cmd enable FI auth').enable_fi("enable", "always", "fake_authentication_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test(negative_case=True).command_should_fail().command_error_should_have("InvalidAccessKeyId") JClientTest('JClient cannot upload 3k file').put_object("seagatebucket", "3kfile", 3000, chunked=True).execute_test(negative_case=True).command_should_fail().command_error_should_have("InvalidAccessKeyId") S3fiTest('s3cmd disable Fault injection').disable_fi("fake_authentication_fail").execute_test().command_is_successful() #S3cmdTest('Stop s3authserver service').stop_s3authserver_test().execute_test().command_is_successful().command_is_successful() #S3cmdTest('s3cmd cannot upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test(negative_case=True).command_should_fail().command_error_should_have("ServiceUnavailable") #S3cmdTest('Start s3authserver service').start_s3authserver_test().execute_test().command_is_successful().command_is_successful() # ************ OBJ open FI *************** S3fiTest('s3cmd enable FI Obj open').enable_fi("enable", "always", "motr_obj_open_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot download 18MB nonexistent file').download_test("seagatebucket", "18MBfile").download_test("seagatebucket", "18MBfile").execute_test(negative_case=True).command_should_fail().command_error_should_have("Not Found") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_open_fail").execute_test().command_is_successful() result = S3cmdTest('s3cmd can list multipart uploads in progress').list_multipart_uploads("seagatebucket").execute_test() result.command_response_should_have('18MBfile') upload_id = result.status.stdout.split('\n')[2].split('\t')[2] S3cmdTest('S3cmd can abort multipart upload').abort_multipart("seagatebucket", "18MBfile", upload_id). execute_test().command_is_successful() # ************ OBJ open FI *************** S3cmdTest('s3cmd can upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test().command_is_successful() S3fiTest('s3cmd enable FI Obj open').enable_fi("enable", "always", "motr_obj_open_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot download 3k file').download_test("seagatebucket", "3kfile").execute_test(negative_case=True).command_error_should_have("Internal Server Error") S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_open_fail").execute_test().command_is_successful() S3cmdTest('s3cmd can delete 3k file').delete_test("seagatebucket", "3kfile").execute_test().command_is_successful() # ************ OBJ open FI *************** S3cmdTest('s3cmd can upload file-overwrite file').upload_test("seagatebucket", "file-overwrite", 3000).execute_test().command_is_successful() S3fiTest('s3cmd enable FI Obj open').enable_fi("enable", "always", "motr_obj_open_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload file-overwrite file').upload_test("seagatebucket", "file-overwrite", 18000000).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_open_fail").execute_test().command_is_successful() S3cmdTest('s3cmd list old file-overwrite object').list_objects('seagatebucket').execute_test().command_is_successful().command_response_should_have('3000') S3cmdTest('s3cmd can delete file-overwrite file').delete_test("seagatebucket", "file-overwrite").execute_test().command_is_successful() # ************ OBJ create FI *************** S3fiTest('s3cmd enable FI Obj create').enable_fi("enable", "always", "motr_obj_create_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_create_fail").execute_test().command_is_successful() #************* PUT KV FI *************** S3fiTest('s3cmd enable FI PUT KV').enable_fi("enable", "always", "motr_kv_put_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_put_fail").execute_test().command_is_successful() #************** upload objects ************* S3cmdTest('s3cmd upload 3k file').upload_test("seagatebucket", "3kfile", 3000).execute_test().command_is_successful() S3cmdTest('s3cmd upload 18MB file').upload_test("seagatebucket", "18MBfile", 18000000).execute_test().command_is_successful() # **************** OBJ DELETE FI **************** S3fiTest('s3cmd enable FI OBJ Delete').enable_fi("enable", "always", "motr_kv_delete_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot delete 3k file').delete_test("seagatebucket", "3kfile").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot delete 18MB file').delete_test("seagatebucket", "18MBfile").execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_delete_fail").execute_test().command_is_successful() #**************** GET KV FI **************** S3fiTest('s3cmd enable FI GET KV').enable_fi("enable", "always", "motr_kv_get_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot download 3k file').download_test("seagatebucket", "3kfile").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot download 18MB file').download_test("seagatebucket", "18MBfile").execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() # **************** OBJ DELETE FI **************** S3fiTest('s3cmd enable FI OBJ Delete').enable_fi("enable", "always", "motr_obj_delete_fail").execute_test().command_is_successful() S3cmdTest('s3cmd can delete 3k file').delete_test("seagatebucket", "3kfile").execute_test().command_is_successful() S3cmdTest('s3cmd can delete 18MB file').delete_test("seagatebucket", "18MBfile").execute_test().command_is_successful() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_delete_fail").execute_test().command_is_successful() # ************ Multiple Delete bucket TEST ************ file_name = "3kfile" for num in range(0, 2): new_file_name = '%s%d' % (file_name, num) S3cmdTest('s3cmd can upload 3k file').upload_test("seagatebucket", new_file_name, 3000).execute_test().command_is_successful() S3fiTest('s3cmd enable fail_fetch_bucket_info').enable_fi("enable", "always", "fail_fetch_bucket_info").execute_test().command_is_successful() S3cmdTest('s3cmd cannot delete multiple objects').multi_delete_test("seagatebucket").execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("fail_fetch_bucket_info").execute_test().command_is_successful() S3fiTest('s3cmd enable fail_fetch_objects_info').enable_fi("enable", "always", "fail_fetch_objects_info").execute_test().command_is_successful() S3cmdTest('s3cmd cannot delete multiple objects').multi_delete_test("seagatebucket").execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("fail_fetch_objects_info").execute_test().command_is_successful() S3fiTest('s3cmd enable fail_delete_objects_metadata').enable_fi("enable", "always", "fail_delete_objects_metadata").execute_test().command_is_successful() S3cmdTest('s3cmd cannot delete multiple objects').multi_delete_test("seagatebucket").execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('s3cmd disable Fault injection').disable_fi("fail_delete_objects_metadata").execute_test().command_is_successful() S3cmdTest('s3cmd can delete multiple objects').multi_delete_test("seagatebucket").execute_test().command_is_successful().command_response_should_have('delete: \'s3://seagatebucket/3kfile0\'').command_response_should_have('delete: \'s3://seagatebucket/3kfile1\'') # This test will leave stale objects in motr. S3fiTest('s3cmd enable FI OBJ Delete').enable_fi("enable", "always", "motr_obj_delete_fail").execute_test().command_is_successful() file_name = "3kfile" for num in range(0, 2): new_file_name = '%s%d' % (file_name, num) S3cmdTest('s3cmd can upload 3k file').upload_test("seagatebucket", new_file_name, 3000).execute_test().command_is_successful() S3cmdTest('s3cmd can delete multiple objects').multi_delete_test("seagatebucket").execute_test().command_is_successful().command_response_should_have('delete: \'s3://seagatebucket/3kfile0\'').command_response_should_have('delete: \'s3://seagatebucket/3kfile1\'') S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_delete_fail").execute_test().command_is_successful() # ************ Cleanup bucket + Object ************ S3cmdTest('s3cmd can delete bucket').delete_bucket("seagatebucket").execute_test().command_is_successful() # ******************* multipart and partial parts ********************* S3cmdTest('s3cmd can create bucket').create_bucket("seagatebucket").execute_test().command_is_successful() S3fiTest('s3cmd enable FI Obj create').enable_fi("enable", "always", "motr_obj_create_fail").execute_test().command_is_successful() JClientTest('Jclient cannot upload partial parts.').partial_multipart_upload("seagatebucket", "18MBfile", 18000000, 1, 2).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_create_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI Obj open').enable_fi("enable", "always", "motr_obj_open_fail").execute_test().command_is_successful() JClientTest('Jclient cannot upload partial parts.').partial_multipart_upload("seagatebucket", "18MBfile", 18000000, 1, 2).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_obj_open_fail").execute_test().command_is_successful() result = JClientTest('Jclient can list all multipart uploads.').list_multipart("seagatebucket").execute_test() result.command_response_should_have('18MBfile') upload_id = result.status.stdout.split("id - ")[1] JClientTest('Jclient can abort multipart upload').abort_multipart("seagatebucket", "18MBfile", upload_id)\ .execute_test().command_is_successful() S3fiTest('s3cmd enable FI PUT KV').enable_fi("enable", "always", "motr_kv_put_fail").execute_test().command_is_successful() JClientTest('Jclient cannot upload partial parts.').partial_multipart_upload("seagatebucket", "18MBfile", 18000000, 1, 2).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_put_fail").execute_test().command_is_successful() JClientTest('Jclient can upload partial parts to test abort and list multipart.').partial_multipart_upload("seagatebucket", "18MBfile", 18000000, 1, 2).execute_test().command_is_successful() S3fiTest('s3cmd enable FI GET KV').enable_fi("enable", "always", "motr_kv_get_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot list multipart uploads in progress').list_multipart_uploads("seagatebucket").execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() result = S3cmdTest('s3cmd can list multipart uploads in progress').list_multipart_uploads("seagatebucket").execute_test() result.command_response_should_have('18MBfile') upload_id = result.status.stdout.split('\n')[2].split('\t')[2] S3fiTest('s3cmd enable FI GET KV').enable_fi("enable", "always", "motr_kv_get_fail").execute_test().command_is_successful() result = S3cmdTest('S3cmd cannot list parts of multipart upload.').list_parts("seagatebucket", "18MBfile", upload_id).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI GET KV').enable_fi_offnonm("enable", "motr_kv_get_fail", "4", "99").execute_test().command_is_successful() result = S3cmdTest('S3cmd cannot list parts of multipart upload.').list_parts("seagatebucket", "18MBfile", upload_id).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI GET KV').enable_fi("enable", "always", "motr_kv_get_fail").execute_test().command_is_successful() S3cmdTest('S3cmd cannot abort multipart upload').abort_multipart("seagatebucket", "18MBfile", upload_id).execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI fail_remove_part_mindex').enable_fi("enable", "always", "fail_remove_part_mindex").execute_test().command_is_successful() S3cmdTest('S3cmd can abort multipart upload').abort_multipart("seagatebucket", "18MBfile", upload_id).execute_test().command_is_successful() S3fiTest('s3cmd can disable Fault injection').disable_fi("fail_remove_part_mindex").execute_test().command_is_successful() S3cmdTest('s3cmd can test the multipart was aborted.').list_multipart_uploads('seagatebucket').execute_test().command_is_successful().command_response_should_not_have('18MBfile') S3cmdTest('s3cmd can delete bucket').delete_bucket("seagatebucket").execute_test().command_is_successful() # ****************************************************************** # *************** Unused FI APIs above ************* # NOTE: Remove FI API if they are used in any test above in future S3fiTest('s3cmd enable FI random test').enable_fi_random("enable", "unused_fail", "10").execute_test().command_is_successful() S3fiTest('s3cmd disable Fault injection').disable_fi("unused_fail").execute_test().command_is_successful() S3fiTest('s3cmd enable FI once test').enable_fi("enable", "once", "unused_fail").execute_test().command_is_successful() S3fiTest('s3cmd disable Fault injection').disable_fi("unused_fail").execute_test().command_is_successful() # ************ Negative ACL/Policy TESTS ************ S3cmdTest('s3cmd can create bucket').create_bucket("seagatebucket").execute_test().command_is_successful() S3cmdTest('s3cmd can upload 3k file with default acl').upload_test("seagatebucket", "3kfile", 3000).execute_test().command_is_successful() S3fiTest('s3cmd enable FI PUT KV').enable_fi("enable", "always", "motr_kv_put_fail").execute_test().command_is_successful() S3cmdTest('s3cmd cannot set acl on bucket').setacl_bucket("seagatebucket","read:123").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot set acl on object').setacl_object("seagatebucket","3kfile", "read:123").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot revoke acl on bucket').revoke_acl_bucket("seagatebucket","read:123").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot revoke acl on object').revoke_acl_object("seagatebucket","3kfile","read:123").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd cannot set policy on bucket').setpolicy_bucket("seagatebucket","policy.txt").execute_test(negative_case=True).command_should_fail() S3cmdTest('s3cmd can set policy on bucket').delpolicy_bucket("seagatebucket").execute_test(negative_case=True).command_should_fail() S3fiTest('s3cmd disable Fault injection').disable_fi("motr_kv_put_fail").execute_test().command_is_successful() S3cmdTest('s3cmd can delete 3kfile after setting acl').delete_test("seagatebucket", "3kfile").execute_test().command_is_successful() S3cmdTest('s3cmd can delete bucket after setting policy/acl').delete_bucket("seagatebucket").execute_test().command_is_successful() # ************************************************ # Path style tests. pathstyle_values = [True, False] for i, val in enumerate(pathstyle_values): S3ClientConfig.pathstyle = val print("\nPath style = " + str(val) + "\n") # ************ Create bucket ************ JClientTest('Jclient can create bucket').create_bucket("seagatebucket").execute_test().command_is_successful() # ************ List buckets ************ JClientTest('Jclient can list buckets').list_buckets().execute_test().command_is_successful().command_response_should_have('seagatebucket') # ************ OBJ Create FI: CHUNK UPLOAD ************ S3fiTest('S3Fi enable FI Obj create').enable_fi("enable", "always", "motr_obj_create_fail")\ .execute_test().command_is_successful() JClientTest('JClient cannot upload 3k file').put_object("seagatebucket", "3kfile", 3000, chunked=True)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") JClientTest('JClient cannot upload 18MB file').put_object("seagatebucket", "18MBfile", 18000000, chunked=True)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_obj_create_fail").execute_test().command_is_successful() # ************ OBJ Write FI: CHUNK UPLOAD ************ S3fiTest('S3Fi enable FI Obj write').enable_fi("enable", "always", "motr_obj_write_fail")\ .execute_test().command_is_successful() JClientTest('JClient cannot upload 3k file').put_object("seagatebucket", "3kfile", 3000, chunked=True)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") JClientTest('JClient cannot upload 18MB file').put_object("seagatebucket", "18MBfile", 18000000, chunked=True)\ .execute_test(negative_case=True).command_should_fail() S3fiTest('S3Fi disable Fault injection').disable_fi("motr_obj_write_fail").execute_test().command_is_successful() # ************ OBJ Create FI: Multipart ************ S3fiTest('S3Fi enable FI Obj create').enable_fi("enable", "always", "motr_obj_create_fail")\ .execute_test().command_is_successful() JClientTest('JClient cannot upload 18MB file (Multipart)').put_object_multipart("seagatebucket", "18MBfile", 18000000, 15)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_obj_create_fail").execute_test().command_is_successful() # ************ OBJ Open FI ************ S3fiTest('S3Fi enable FI Obj open').enable_fi("enable", "always", "motr_obj_open_fail")\ .execute_test().command_is_successful() JClientTest('Jclient cannot download non existent 3kfile file').get_object("seagatebucket", "3kfile").execute_test(negative_case=True).command_should_fail().command_error_should_have("NoSuchKey") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_obj_open_fail").execute_test().command_is_successful() # ************ OBJ Write FI: Multipart ************ S3fiTest('S3Fi enable FI Obj write').enable_fi("enable", "always", "motr_obj_write_fail")\ .execute_test().command_is_successful() JClientTest('JClient cannot upload 18MB file (Multipart)').put_object_multipart("seagatebucket", "18MBfile", 18000000, 15)\ .execute_test(negative_case=True).command_should_fail() #.command_error_should_have("Multipart upload failed") JClientTest('JClient cannot upload 18MB file (Multipart)').put_object_multipart("seagatebucket", "18MBfile", 18000000, 15, chunked=True)\ .execute_test(negative_case=True).command_should_fail() #.command_error_should_have("Multipart upload failed") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_obj_write_fail").execute_test().command_is_successful() # ************ Partial Multipart Upload ************ JClientTest('JClient can upload parts of 18MB file').partial_multipart_upload("seagatebucket", "18MBfile", 18000000, 5, 2)\ .execute_test().command_is_successful() # ************ OBJ LIST FI: Partial Multipart ************ result = JClientTest('Jclient can list all multipart uploads.').list_multipart("seagatebucket").execute_test() result.command_response_should_have('18MBfile') upload_id = result.status.stdout.split("id - ")[1] print(upload_id) S3fiTest('S3Fi enable FI get KV').enable_fi("enable", "always", "motr_kv_get_fail").execute_test() JClientTest('Jclient cannot list all multipart uploads.').list_multipart("seagatebucket")\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") JClientTest('Jclient cannot list parts of multipart upload.').list_parts("seagatebucket", "18MBfile", upload_id)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_kv_get_fail").execute_test().command_is_successful() # ************ OBJ DELETE FI: Multipart ************ S3fiTest('S3Fi enable FI delete').enable_fi("enable", "always", "motr_kv_delete_fail")\ .execute_test().command_is_successful() JClientTest('Jclient cannot abort multipart upload.').abort_multipart("seagatebucket", "18MBfile", upload_id)\ .execute_test(negative_case=True).command_should_fail().command_error_should_have("InternalError") S3fiTest('S3Fi disable Fault injection').disable_fi("motr_kv_delete_fail").execute_test().command_is_successful() # ************ Abort multipart upload ************ JClientTest('Jclient can abort multipart upload.').abort_multipart("seagatebucket", "18MBfile", upload_id)\ .execute_test().command_is_successful() # ************ Delete bucket TEST ************ JClientTest('Jclient can delete bucket').delete_bucket("seagatebucket").execute_test().command_is_successful()

74.52619

262

0.768218

4,033

31,301

5.654104

0.084057

0.085866

0.101653

0.105249

0.848134

0.836293

0.827479

0.82112

0.813007

0.78744

0

0.030461

0.076004

31,301

419

263

74.704057

0.75797

0.124661

0

0.581967

0

0.357739

0.016584

0

0.002387

0.004098

1

0.004098

false

0

0.036885

0

0.045082

0.012295

0

null

0

1

0

null

0

6

0f6930bfb95c978ad229e1271a9b5d373809e3b4

115

py

Python

templates/django/__APPNAME__/settings/__init__.py

ba1dr/tplgenerator

f05b6f9a32cf825d326dd2faf551d1e156d2df37

[ "MIT" ]

null

templates/django/__APPNAME__/settings/__init__.py

ba1dr/tplgenerator

f05b6f9a32cf825d326dd2faf551d1e156d2df37

[ "MIT" ]

null

templates/django/__APPNAME__/settings/__init__.py

ba1dr/tplgenerator

f05b6f9a32cf825d326dd2faf551d1e156d2df37

[ "MIT" ]

null

from __future__ import absolute_import from .settings import * # from .celery_settings import app as celery_app

16.428571

48

0.808696

16

115

5.375

0.5

0.232558

0

0.156522

115

6

49

19.166667

0.886598

0.4

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7e4783408789cb4782b121175bbbe766bee7189c

24

py

Python

slinga/__init__.py

hemebond/slinga

6584bbf5260b0afb5898a3965a21356e334d8f79

[ "MIT" ]

null

slinga/__init__.py

hemebond/slinga

6584bbf5260b0afb5898a3965a21356e334d8f79

[ "MIT" ]

null

slinga/__init__.py

hemebond/slinga

6584bbf5260b0afb5898a3965a21356e334d8f79

[ "MIT" ]

null

from .slinga import app

12

23

0.791667

4

24

4.75

1

0

0.166667

24

1

24

0.95

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7e8ec77be1467e447d18fc27e2242b76fb776332

45

py

Python

mw2fcitx/utils/normalize.py

outloudvi/mw2fcitx

a4fbbcd5e8068ee1f08714f0e18b46c8b289a42c

[ "Unlicense" ]

67

2020-08-13T13:58:03.000Z

2022-03-29T11:33:51.000Z

mw2fcitx/utils/normalize.py

outloudvi/fcitx5-pinyin-moegirl

c62d3f7d049143a4d8726f408bdd345f53ff3347

[ "Unlicense" ]

5

2020-11-16T01:48:32.000Z

2022-02-18T08:04:32.000Z

mw2fcitx/utils/normalize.py

outloudvi/fcitx5-pinyin-moegirl

c62d3f7d049143a4d8726f408bdd345f53ff3347

[ "Unlicense" ]

3

2020-10-08T15:44:30.000Z

2022-03-23T12:40:11.000Z

def normalize(word): return word.strip()

15

23

0.688889

6

45

5.166667

0.833333

0

0.177778

45

2

24

22.5

0.837838

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

7e906e1fe6c141d951c3e406097b9228fa67c0c7

104

py

Python

examples/test_pytest.py

danibaena/expects

296203a3fb07cf3061b8f7b348136c9208195d93

[ "Apache-2.0" ]

189

2015-01-05T13:26:40.000Z

2021-09-27T12:44:48.000Z

examples/test_pytest.py

danibaena/expects

296203a3fb07cf3061b8f7b348136c9208195d93

[ "Apache-2.0" ]

38

2015-02-13T16:08:23.000Z

2022-02-14T12:14:28.000Z

examples/test_pytest.py

danibaena/expects

296203a3fb07cf3061b8f7b348136c9208195d93

[ "Apache-2.0" ]

32

2015-03-12T08:06:47.000Z

2022-03-08T18:16:28.000Z

# -*- coding: utf-8 -*- from expects import * def test_failing(): expect("foo").to(equal("bar"))

13

34

0.586538

14

104

4.285714

1

0

0.011765

0.182692

104

7

35

14.857143

0.694118

0.201923

0

0.074074

0

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

0e79ce37189c490053e827e66ae6ba83776fde9c

527

py

Python

usr/callbacks/logical/logical.py

uwitec/LEHome

a959a2fe64a23c58de7c0ff3254eae8c27732320

[ "Apache-2.0" ]

151

2015-01-25T10:25:29.000Z

2022-03-15T10:04:09.000Z

usr/callbacks/logical/logical.py

legendmohe/LEHome

a959a2fe64a23c58de7c0ff3254eae8c27732320

[ "Apache-2.0" ]

null

usr/callbacks/logical/logical.py

legendmohe/LEHome

a959a2fe64a23c58de7c0ff3254eae8c27732320

[ "Apache-2.0" ]

70

2015-02-02T02:35:48.000Z

2021-05-13T09:51:08.000Z

#!/usr/bin/env python # encoding: utf-8 from util.log import * from lib.model import Callback class logical_callback(Callback.Callback): def callback(self, aValue, bValue): DEBUG("logical callback invoke.") return aValue and bValue class and_callback(Callback.Callback): def callback(self, aValue, bValue): # import pdb # pdb.set_trace() return aValue and bValue class or_callback(Callback.Callback): def callback(self, aValue, bValue): return aValue or bValue

22.913043

42

0.686907

67

527

5.343284

0.41791

0.268156

0.201117

0.226257

0.572626

0.427374

0

0.002439

0.222011

527

22

43

23.954545

0.870732

0.119545

0

0.416667

0

0.052174

0

1

0.25

false

0

0.166667

0.916667

0

null

1

0

null

0

1

0

1

0

6

0e81a4703d1f7cd37171b48a9d10365e3c3d9830

267

py

Python

packages/watchmen-meta/src/watchmen_meta/console/__init__.py

Indexical-Metrics-Measure-Advisory/watchmen

c54ec54d9f91034a38e51fd339ba66453d2c7a6d

[ "MIT" ]

null

packages/watchmen-meta/src/watchmen_meta/console/__init__.py

Indexical-Metrics-Measure-Advisory/watchmen

c54ec54d9f91034a38e51fd339ba66453d2c7a6d

[ "MIT" ]

null

packages/watchmen-meta/src/watchmen_meta/console/__init__.py

Indexical-Metrics-Measure-Advisory/watchmen

c54ec54d9f91034a38e51fd339ba66453d2c7a6d

[ "MIT" ]

null

from .connected_space_graphic_service import ConnectedSpaceGraphicService from .connected_space_service import ConnectedSpaceService from .dashboard_service import DashboardService from .report_service import ReportService from .subject_service import SubjectService

44.5

73

0.906367

28

267

8.357143

0.5

0.277778

0.153846

0

0.074906

267

5

74

53.4

0.947368

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7ee300585b96b0a9c09ba9d785ea0f6eb2e8048f

23,926

py

Python

utils/processors/utils_blue.py

sy-wada/blue_benchmark_with_transformers

fbf6236db5a4fb7affde94a05a5c875cc5ee948b

[ "Apache-2.0" ]

17

2020-05-18T06:40:26.000Z

2022-03-23T08:34:27.000Z

utils/processors/utils_blue.py

sy-wada/blue_benchmark_with_transformers

fbf6236db5a4fb7affde94a05a5c875cc5ee948b

[ "Apache-2.0" ]

3

2020-05-18T23:24:13.000Z

2021-05-27T07:12:14.000Z

utils/processors/utils_blue.py

sy-wada/blue_benchmark_with_transformers

fbf6236db5a4fb7affde94a05a5c875cc5ee948b

[ "Apache-2.0" ]

2

2020-05-18T20:26:15.000Z

2021-11-09T14:21:11.000Z

# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ GLUE processors and helpers. Import from https://github.com/huggingface/transformers/blob/master/src/transformers/data/processors/glue.py and Modify to fit BLUE datasets. __version__ = "2.5.1" BlueBERT processors are imported from https://github.com/ncbi-nlp/bluebert/blob/master/bluebert/run_bluebert.py """ import logging import os import csv from .tokenization import convert_to_unicode from .file_utils import is_tf_available from .utils import DataProcessor, InputExample, InputFeatures if is_tf_available(): import tensorflow as tf logger = logging.getLogger(__name__) def blue_convert_examples_to_features( examples, tokenizer, max_length=512, task=None, label_list=None, output_mode=None, pad_on_left=False, pad_token=0, pad_token_segment_id=0, mask_padding_with_zero=True, ): """ Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.data.Dataset`` containing the examples. tokenizer: Instance of a tokenizer that will tokenize the examples max_length: Maximum example length task: GLUE task label_list: List of labels. Can be obtained from the processor using the ``processor.get_labels()`` method output_mode: String indicating the output mode. Either ``regression`` or ``classification`` pad_on_left: If set to ``True``, the examples will be padded on the left rather than on the right (default) pad_token: Padding token pad_token_segment_id: The segment ID for the padding token (It is usually 0, but can vary such as for XLNet where it is 4) mask_padding_with_zero: If set to ``True``, the attention mask will be filled by ``1`` for actual values and by ``0`` for padded values. If set to ``False``, inverts it (``1`` for padded values, ``0`` for actual values) Returns: If the ``examples`` input is a ``tf.data.Dataset``, will return a ``tf.data.Dataset`` containing the task-specific features. If the input is a list of ``InputExamples``, will return a list of task-specific ``InputFeatures`` which can be fed to the model. """ is_tf_dataset = False if is_tf_available() and isinstance(examples, tf.data.Dataset): is_tf_dataset = True if task is not None: processor = glue_processors[task]() if label_list is None: label_list = processor.get_labels() logger.info("Using label list %s for task %s" % (label_list, task)) if output_mode is None: output_mode = glue_output_modes[task] logger.info("Using output mode %s for task %s" % (output_mode, task)) label_map = {label: i for i, label in enumerate(label_list)} features = [] for (ex_index, example) in enumerate(examples): len_examples = 0 if is_tf_dataset: example = processor.get_example_from_tensor_dict(example) example = processor.tfds_map(example) len_examples = tf.data.experimental.cardinality(examples) else: len_examples = len(examples) if ex_index % 10000 == 0: logger.info("Writing example %d/%d" % (ex_index, len_examples)) inputs = tokenizer.encode_plus(example.text_a, example.text_b, add_special_tokens=True, max_length=max_length,) input_ids, token_type_ids = inputs["input_ids"], inputs["token_type_ids"] # The mask has 1 for real tokens and 0 for padding tokens. Only real # tokens are attended to. attention_mask = [1 if mask_padding_with_zero else 0] * len(input_ids) # Zero-pad up to the sequence length. padding_length = max_length - len(input_ids) if pad_on_left: input_ids = ([pad_token] * padding_length) + input_ids attention_mask = ([0 if mask_padding_with_zero else 1] * padding_length) + attention_mask token_type_ids = ([pad_token_segment_id] * padding_length) + token_type_ids else: input_ids = input_ids + ([pad_token] * padding_length) attention_mask = attention_mask + ([0 if mask_padding_with_zero else 1] * padding_length) token_type_ids = token_type_ids + ([pad_token_segment_id] * padding_length) assert len(input_ids) == max_length, "Error with input length {} vs {}".format(len(input_ids), max_length) assert len(attention_mask) == max_length, "Error with input length {} vs {}".format( len(attention_mask), max_length ) assert len(token_type_ids) == max_length, "Error with input length {} vs {}".format( len(token_type_ids), max_length ) if output_mode == "classification": label = label_map[example.label] elif output_mode == "regression": label = float(example.label) else: raise KeyError(output_mode) if ex_index < 5: logger.info("*** Example ***") logger.info("guid: %s" % (example.guid)) logger.info("tokens: %s", " ".join(tokenizer.convert_ids_to_tokens(input_ids))) logger.info("input_ids: %s" % " ".join([str(x) for x in input_ids])) logger.info("attention_mask: %s" % " ".join([str(x) for x in attention_mask])) logger.info("token_type_ids: %s" % " ".join([str(x) for x in token_type_ids])) logger.info("label: %s (id = %d)" % (example.label, label)) features.append( InputFeatures( input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, label=label ) ) if is_tf_available() and is_tf_dataset: def gen(): for ex in features: yield ( { "input_ids": ex.input_ids, "attention_mask": ex.attention_mask, "token_type_ids": ex.token_type_ids, }, ex.label, ) return tf.data.Dataset.from_generator( gen, ({"input_ids": tf.int32, "attention_mask": tf.int32, "token_type_ids": tf.int32}, tf.int64), ( { "input_ids": tf.TensorShape([None]), "attention_mask": tf.TensorShape([None]), "token_type_ids": tf.TensorShape([None]), }, tf.TensorShape([]), ), ) return features def convert_multi_label_examples_to_features( examples, tokenizer, max_length=512, task=None, label_list=None, output_mode=None, pad_on_left=False, pad_token=0, pad_token_segment_id=0, mask_padding_with_zero=True, ): """ Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.data.Dataset`` containing the examples. tokenizer: Instance of a tokenizer that will tokenize the examples max_length: Maximum example length task: GLUE task label_list: List of labels. Can be obtained from the processor using the ``processor.get_labels()`` method output_mode: String indicating the output mode. Either ``regression`` or ``classification`` pad_on_left: If set to ``True``, the examples will be padded on the left rather than on the right (default) pad_token: Padding token pad_token_segment_id: The segment ID for the padding token (It is usually 0, but can vary such as for XLNet where it is 4) mask_padding_with_zero: If set to ``True``, the attention mask will be filled by ``1`` for actual values and by ``0`` for padded values. If set to ``False``, inverts it (``1`` for padded values, ``0`` for actual values) Returns: If the ``examples`` input is a ``tf.data.Dataset``, will return a ``tf.data.Dataset`` containing the task-specific features. If the input is a list of ``InputExamples``, will return a list of task-specific ``InputFeatures`` which can be fed to the model. """ is_tf_dataset = False if is_tf_available() and isinstance(examples, tf.data.Dataset): is_tf_dataset = True if task is not None: processor = glue_processors[task]() if label_list is None: label_list = processor.get_labels() logger.info("Using label list %s for task %s" % (label_list, task)) if output_mode is None: output_mode = glue_output_modes[task] logger.info("Using output mode %s for task %s" % (output_mode, task)) # label_map = {label: i for i, label in enumerate(label_list)} features = [] for (ex_index, example) in enumerate(examples): len_examples = 0 if is_tf_dataset: example = processor.get_example_from_tensor_dict(example) example = processor.tfds_map(example) len_examples = tf.data.experimental.cardinality(examples) else: len_examples = len(examples) if ex_index % 10000 == 0: logger.info("Writing example %d/%d" % (ex_index, len_examples)) inputs = tokenizer.encode_plus(example.text_a, example.text_b, add_special_tokens=True, max_length=max_length,) input_ids, token_type_ids = inputs["input_ids"], inputs["token_type_ids"] # The mask has 1 for real tokens and 0 for padding tokens. Only real # tokens are attended to. attention_mask = [1 if mask_padding_with_zero else 0] * len(input_ids) # Zero-pad up to the sequence length. padding_length = max_length - len(input_ids) if pad_on_left: input_ids = ([pad_token] * padding_length) + input_ids attention_mask = ([0 if mask_padding_with_zero else 1] * padding_length) + attention_mask token_type_ids = ([pad_token_segment_id] * padding_length) + token_type_ids else: input_ids = input_ids + ([pad_token] * padding_length) attention_mask = attention_mask + ([0 if mask_padding_with_zero else 1] * padding_length) token_type_ids = token_type_ids + ([pad_token_segment_id] * padding_length) assert len(input_ids) == max_length, "Error with input length {} vs {}".format(len(input_ids), max_length) assert len(attention_mask) == max_length, "Error with input length {} vs {}".format( len(attention_mask), max_length ) assert len(token_type_ids) == max_length, "Error with input length {} vs {}".format( len(token_type_ids), max_length ) # if output_mode == "classification": # label = label_map[example.label] # elif output_mode == "regression": # label = float(example.label) # else: # raise KeyError(output_mode) label = example.label if ex_index < 5: logger.info("*** Example ***") logger.info("guid: %s" % (example.guid)) logger.info("tokens: %s", " ".join(tokenizer.convert_ids_to_tokens(input_ids))) logger.info("input_ids: %s" % " ".join([str(x) for x in input_ids])) logger.info("attention_mask: %s" % " ".join([str(x) for x in attention_mask])) logger.info("token_type_ids: %s" % " ".join([str(x) for x in token_type_ids])) logger.info("label: %s " % (','.join(['{}_{}'.format(i, l) for i, l in enumerate(label)]))) features.append( InputFeatures( input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, label=label ) ) if is_tf_available() and is_tf_dataset: def gen(): for ex in features: yield ( { "input_ids": ex.input_ids, "attention_mask": ex.attention_mask, "token_type_ids": ex.token_type_ids, }, ex.label, ) return tf.data.Dataset.from_generator( gen, ({"input_ids": tf.int32, "attention_mask": tf.int32, "token_type_ids": tf.int32}, tf.int64), ( { "input_ids": tf.TensorShape([None]), "attention_mask": tf.TensorShape([None]), "token_type_ids": tf.TensorShape([None]), }, tf.TensorShape([]), ), ) return features class DataProcessor(object): """Base class for data converters for sequence classification data sets.""" def get_train_examples(self, data_dir): """Gets a collection of `InputExample`s for the train set.""" raise NotImplementedError() def get_dev_examples(self, data_dir): """Gets a collection of `InputExample`s for the dev set.""" raise NotImplementedError() def get_test_examples(self, data_dir): """Gets a collection of `InputExample`s for prediction.""" raise NotImplementedError() def get_labels(self): """Gets the list of labels for this data set.""" raise NotImplementedError() @classmethod def _read_tsv(cls, input_file, quotechar=None): """Reads a tab separated value file.""" with open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) lines = [] for line in reader: lines.append(line) return lines class BlueBERTProcessor(DataProcessor): """Processor for the BLUE data set.""" def get_train_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "train.tsv")), "train") def get_dev_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev") def get_test_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "test.tsv")), "test") def _create_examples(self, lines, set_type): """Creates examples for the training and dev sets.""" examples = [] for (i, line) in enumerate(lines): # skip header if i == 0: continue guid = line[0] text_a = convert_to_unicode(line[1]) if set_type == "test": # MODIFY: # We add the option "--predict" to calculate metrics and to describe outputs. # label = self.get_labels()[-1] try: label = convert_to_unicode(line[2]) except IndexError: logging.exception(line) exit(1) else: try: label = convert_to_unicode(line[2]) except IndexError: logging.exception(line) exit(1) examples.append(InputExample(guid=guid, text_a=text_a, text_b=None, label=label)) return examples #ADD: def get_y_true(self, data_dir, set_type, quotechar=None): """Read labels for evaluation.""" input_file = os.path.join(data_dir, "{}.tsv".format(set_type)) with open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) labels = [] for i, line in enumerate(reader): # skip header if i == 0: continue labels.append(convert_to_unicode(line[2])) return labels class ChemProtProcessor(BlueBERTProcessor): def get_labels(self): """See base class.""" return ["CPR:3", "CPR:4", "CPR:5", "CPR:6", "CPR:9", "false"] class DDI2013Processor(BlueBERTProcessor): def get_labels(self): return ["DDI-advise", "DDI-effect", "DDI-int", "DDI-mechanism", 'DDI-false'] class I2b2_2010_Processor(BlueBERTProcessor): def get_labels(self): return ['PIP', 'TeCP', 'TeRP', 'TrAP', 'TrCP', 'TrIP', 'TrNAP', 'TrWP', 'false'] class StsProcessor(DataProcessor): """Processor for the STS-B data set.""" def get_example_from_tensor_dict(self, tensor_dict): """See base class.""" return InputExample( tensor_dict["idx"].numpy(), tensor_dict["sentence1"].numpy().decode("utf-8"), tensor_dict["sentence2"].numpy().decode("utf-8"), str(tensor_dict["label"].numpy()), ) def get_train_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "train.tsv")), "train") def get_dev_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev") # ADDED def get_test_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "test.tsv")), "test") def get_labels(self): """See base class.""" return [None] def _create_examples(self, lines, set_type): """Creates examples for the training and dev sets.""" examples = [] for (i, line) in enumerate(lines): if i == 0: continue guid = "%s-%s" % (set_type, convert_to_unicode(line[0])) text_a = convert_to_unicode(line[-3]) text_b = convert_to_unicode(line[-2]) label = float(line[-1]) examples.append(InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label)) return examples #ADD: def get_y_true(self, data_dir, set_type, quotechar=None): """Read labels for evaluation.""" input_file = os.path.join(data_dir, "{}.tsv".format(set_type)) with open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) labels = [] for i, line in enumerate(reader): # skip header if i == 0: continue labels.append(convert_to_unicode(line[-1])) return labels class HoCProcessor(DataProcessor): """Processor for the HoC data set.""" def get_train_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "train.tsv")), "train") def get_dev_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev") def get_test_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "test.tsv")), "test") def get_labels(self): """See base class.""" return list(range(10)) # return ['activating invasion and metastasis', 'avoiding immune destruction', # 'cellular energetics', 'enabling replicative immortality', 'evading growth suppressors', # 'genomic instability and mutation', 'inducing angiogenesis', 'resisting cell death', # 'sustaining proliferative signaling', 'tumor promoting inflammation'] def _create_examples(self, lines, set_type): """Creates examples for the training and dev sets.""" #ADD: # convert the format of 'labels' from str to list. def convert_str_to_list(labels): cols = labels.split(',') res = [int(v[-1]) for v in cols] return res examples = [] for (i, line) in enumerate(lines): # Only the test set has a header if i == 0: continue guid = "%s-%s" % (set_type, i) # if set_type == "test": # text_a = tokenization.convert_to_unicode(line[1]) # label = "0" # else: # text_a = tokenization.convert_to_unicode(line[3]) # label = tokenization.convert_to_unicode(line[1]) label = convert_str_to_list(line[0]) text_a = convert_to_unicode(line[1]) examples.append( InputExample(guid=guid, text_a=text_a, text_b=None, label=label)) return examples class MedNLIProcessor(DataProcessor): def get_train_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "train.tsv")), "train") def get_dev_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev") def get_test_examples(self, data_dir): """See base class.""" return self._create_examples( self._read_tsv(os.path.join(data_dir, "test.tsv")), "test") def get_labels(self): """See base class.""" return ['contradiction', 'entailment', 'neutral'] def _create_examples(self, lines, set_type): """Creates examples for the training and dev sets.""" examples = [] for (i, line) in enumerate(lines): if i == 0: continue guid = "%s-%s" % (set_type, convert_to_unicode(line[0])) text_a = convert_to_unicode(line[-3]) text_b = convert_to_unicode(line[-2]) label = convert_to_unicode(line[-1]) # guid = line[1] # text_a = convert_to_unicode(line[2]) # text_b = convert_to_unicode(line[3]) # if set_type == "test": # label = self.get_labels()[-1] # else: # label = convert_to_unicode(line[0]) examples.append( InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label)) return examples #ADD: def get_y_true(self, data_dir, set_type, quotechar=None): """Read labels for evaluation.""" input_file = os.path.join(data_dir, "{}.tsv".format(set_type)) with open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) labels = [] for i, line in enumerate(reader): # skip header if i == 0: continue labels.append(convert_to_unicode(line[-1])) return labels blue_processors = { "medsts": StsProcessor, "biosses": StsProcessor, "ddi2013": DDI2013Processor, "chemprot": ChemProtProcessor, "i2b2_2010": I2b2_2010_Processor, "hoc": HoCProcessor, "mednli": MedNLIProcessor, } blue_output_modes = { "medsts": "regression", "biosses": "regression", "ddi2013": "classification", "chemprot": "classification", "i2b2_2010": "classification", "hoc": "classification", "mednli": "classification", }

39.287356

130

0.599557

2,990

23,926

4.588294

0.124415

0.022159

0.02799

0.029157

0.793134

0.779722

0.768059

0.754938

0.75246

0.746483

0

0.010203

0.287219

23,926

609

131

39.287356

0.794242

0.255496

0

0.733681

0

0.081367

0

0.015666

1

0.093995

false

0

0.018277

0.005222

0.21671

0

null

0

1

0

1

0

null

0

6

7eef211f9e8703e97cc87836a6537ac6971629c3

138

py

Python

stock_management/products/models/__init__.py

hitenjadeja/stock-management

fe542efc7a7b4f870f280cc20f52d7d92c45fc7f

[ "MIT" ]

null

stock_management/products/models/__init__.py

hitenjadeja/stock-management

fe542efc7a7b4f870f280cc20f52d7d92c45fc7f

[ "MIT" ]

null

stock_management/products/models/__init__.py

hitenjadeja/stock-management

fe542efc7a7b4f870f280cc20f52d7d92c45fc7f

[ "MIT" ]

null

from model_product import Product from model_location import Location from model_stock import Stock from model_warehouse import Warehouse

27.6

37

0.884058

20

138

5.9

0.35

0.305085

0

0.115942

138

4

38

34.5

0.967213

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7d2306adee377a9b95d0e9bd45d087c562163faa

8,936

py

Python

usaspending_api/disaster/tests/integration/test_cfda_loans.py

jbuendiallc/usaspending-api

f827870cbca4b6a6e16f1c5272bb2ff73a113d76

[ "CC0-1.0" ]

1

2020-08-14T04:14:32.000Z

usaspending_api/disaster/tests/integration/test_cfda_loans.py

jbuendiallc/usaspending-api

f827870cbca4b6a6e16f1c5272bb2ff73a113d76

[ "CC0-1.0" ]

null

usaspending_api/disaster/tests/integration/test_cfda_loans.py

jbuendiallc/usaspending-api

f827870cbca4b6a6e16f1c5272bb2ff73a113d76

[ "CC0-1.0" ]

null

import pytest from rest_framework import status from usaspending_api.search.tests.data.utilities import setup_elasticsearch_test url = "/api/v2/disaster/cfda/loans/" @pytest.mark.django_db def test_correct_response_defc_no_results( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, award_type_codes=["07", "08"], def_codes=["N"]) expected_results = [] assert resp.status_code == status.HTTP_200_OK assert resp.json()["results"] == expected_results @pytest.mark.django_db def test_correct_response_single_defc( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes=["L"]) expected_results = [ { "code": "20.200", "award_count": 1, "description": "CFDA 2", "face_value_of_loan": 30.0, "id": 200, "obligation": 20.0, "outlay": 0.0, "resource_link": "www.example.com/200", }, { "code": "10.100", "award_count": 1, "description": "CFDA 1", "face_value_of_loan": 3.0, "id": 100, "obligation": 2.0, "outlay": 0.0, "resource_link": None, }, ] assert resp.status_code == status.HTTP_200_OK assert resp.json()["results"] == expected_results @pytest.mark.django_db def test_correct_response_multiple_defc( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes=["L", "M"]) expected_results = [ { "code": "20.200", "award_count": 2, "description": "CFDA 2", "face_value_of_loan": 330.0, "id": 200, "obligation": 220.0, "outlay": 100.0, "resource_link": "www.example.com/200", }, { "code": "10.100", "award_count": 1, "description": "CFDA 1", "face_value_of_loan": 3.0, "id": 100, "obligation": 2.0, "outlay": 0.0, "resource_link": None, }, ] assert resp.status_code == status.HTTP_200_OK assert resp.json()["results"] == expected_results @pytest.mark.django_db def test_correct_response_with_query( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes=["L", "M"], query="GIBBERISH") expected_results = [] assert resp.status_code == status.HTTP_200_OK assert resp.json()["results"] == expected_results resp = helpers.post_for_spending_endpoint(client, url, def_codes=["L", "M"], query="2") expected_results = [ { "code": "20.200", "award_count": 2, "description": "CFDA 2", "face_value_of_loan": 330.0, "id": 200, "obligation": 220.0, "outlay": 100.0, "resource_link": "www.example.com/200", } ] assert resp.status_code == status.HTTP_200_OK assert resp.json()["results"] == expected_results @pytest.mark.django_db def test_invalid_defc(client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes=["ZZ"]) assert resp.status_code == status.HTTP_400_BAD_REQUEST assert resp.data["detail"] == "Field 'filter|def_codes' is outside valid values ['L', 'M', 'N']" @pytest.mark.django_db def test_invalid_defc_type(client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes="100") assert resp.status_code == status.HTTP_400_BAD_REQUEST assert resp.data["detail"] == "Invalid value in 'filter|def_codes'. '100' is not a valid type (array)" @pytest.mark.django_db def test_missing_defc(client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url) assert resp.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY assert resp.data["detail"] == "Missing value: 'filter|def_codes' is a required field" @pytest.mark.django_db def test_pagination_page_and_limit( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, def_codes=["L", "M"], page=2, limit=1) expected_results = { "results": [ { "code": "10.100", "award_count": 1, "description": "CFDA 1", "face_value_of_loan": 3.0, "id": 100, "obligation": 2.0, "outlay": 0.0, "resource_link": None, } ], "page_metadata": { "hasNext": False, "hasPrevious": True, "limit": 1, "next": None, "page": 2, "previous": 1, "total": 2, }, "messages": [ "Notice! API Request to sort on 'id' field isn't fully " "implemented. Results were actually sorted using 'description' " "field." ], } assert resp.status_code == status.HTTP_200_OK assert resp.json() == expected_results @pytest.mark.django_db def test_invalid_award_type_codes( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint(client, url, award_type_codes=["ZZ", "08"], def_codes=["L", "M"]) assert resp.status_code == status.HTTP_400_BAD_REQUEST assert resp.data["detail"] == "Field 'filter|award_type_codes' is outside valid values ['07', '08']" @pytest.mark.django_db def test_correct_response_with_award_type_codes( client, monkeypatch, helpers, elasticsearch_award_index, cfda_awards_and_transactions ): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) resp = helpers.post_for_spending_endpoint( client, url, award_type_codes=["07"], def_codes=["L", "M"], sort="description" ) expected_results = { "results": [ { "code": "20.200", "award_count": 1, "description": "CFDA 2", "face_value_of_loan": 30.0, "id": 200, "obligation": 20.0, "outlay": 0.0, "resource_link": "www.example.com/200", }, { "code": "10.100", "award_count": 1, "description": "CFDA 1", "face_value_of_loan": 3.0, "id": 100, "obligation": 2.0, "outlay": 0.0, "resource_link": None, }, ], "page_metadata": { "hasNext": False, "hasPrevious": False, "limit": 10, "next": None, "page": 1, "previous": None, "total": 2, }, } assert resp.status_code == status.HTTP_200_OK assert resp.json() == expected_results resp = helpers.post_for_spending_endpoint( client, url, award_type_codes=["08"], def_codes=["L", "M"], sort="description" ) expected_results = { "results": [ { "code": "20.200", "award_count": 1, "description": "CFDA 2", "face_value_of_loan": 300.0, "id": 200, "obligation": 200.0, "outlay": 100.0, "resource_link": "www.example.com/200", } ], "page_metadata": { "hasNext": False, "hasPrevious": False, "limit": 10, "next": None, "page": 1, "previous": None, "total": 1, }, } assert resp.status_code == status.HTTP_200_OK assert resp.json() == expected_results

33.219331

114

0.597359

999

8,936

5.037037

0.132132

0.047695

0.091415

0.042925

0.884141

0.871423

0.855525

0.853935

0.838831

0.821542

0

0.039359

0.280662

8,936

268

115

33.343284

0.743466

0

0.691304

0

0.179834

0.005931

0

0.104348

1

0.043478

false

0

0.013043

0

0.056522

0

null

0

1

0

null

0

6

7d272f97eaee966a565f80142fded04cf63e5b4b

49

py

Python

AutoTicketsBot/__init__.py

y95847frank/AutomatedTicketBot

66754758430c7a1240b69259e32fcb452639c134

[ "MIT" ]

1

2021-03-26T05:07:20.000Z

AutoTicketsBot/__init__.py

y95847frank/AutomatedTicketBot

66754758430c7a1240b69259e32fcb452639c134

[ "MIT" ]

null

AutoTicketsBot/__init__.py

y95847frank/AutomatedTicketBot

66754758430c7a1240b69259e32fcb452639c134

[ "MIT" ]

null

from .AutoTicketsBot import * from .util import *

24.5

29

0.77551

6

49

6.333333

0.666667

0

0.142857

49

2

30

24.5

0.904762

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7d2a3061458192e2da2fadac9a5416dd47f7340c

95

py

Python

CodeForces/Round541Div2/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

1

2018-11-25T04:15:45.000Z

CodeForces/Round541Div2/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

null

CodeForces/Round541Div2/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

2

2018-08-08T13:01:14.000Z

2018-11-25T12:38:36.000Z

w1, h1, w2, h2 = map(int, input().split()) print(w2 + h2 * 2 + 2 + w1 + 2 * h1 + 2 + w1 - w2)

23.75

50

0.473684

19

95

2.368421

0.526316

0.177778

0

0.205882

0.284211

95

3

51

31.666667

0.455882

0

1

0

true

0

0.5

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

6

adabcbeedbe23959d9a13d6e966dd4bd43c70522

10,207

py

Python

Smart-Licensing-Dashboard-Backend/WBXTeamsMeetingRoom/test/test_teamroommeetingcreation.py

bhavanaraya/ciscodashboard

50ac8fd57e3dbfd215f012bdaa1c8e581f14fcf1

[ "CECILL-B" ]

6

2019-07-26T14:56:19.000Z

2020-12-21T13:43:40.000Z

Smart-Licensing-Dashboard-Backend/WBXTeamsMeetingRoom/test/test_teamroommeetingcreation.py

bhavanaraya/ciscodashboard

50ac8fd57e3dbfd215f012bdaa1c8e581f14fcf1

[ "CECILL-B" ]

4

2021-10-06T04:31:59.000Z

2022-02-18T06:29:50.000Z

Smart-Licensing-Dashboard-Backend/WBXTeamsMeetingRoom/test/test_teamroommeetingcreation.py

bhavanaraya/ciscodashboard

50ac8fd57e3dbfd215f012bdaa1c8e581f14fcf1

[ "CECILL-B" ]

5

2020-07-26T22:53:18.000Z

2021-07-01T12:57:29.000Z

""" Copyright (c) 2019 Cisco and/or its affiliates. This software is licensed to you under the terms of the Cisco Sample Code License, Version 1.0 (the "License"). You may obtain a copy of the License at https://developer.cisco.com/docs/licenses All use of the material herein must be in accordance with the terms of the License. All rights not expressly granted by the License are reserved. Unless required by applicable law or agreed to separately in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. """ import unittest import json import WBXTeamsMeetingRoom as wbxtm_meeting __author__ = "Tim Taylor <timtayl@cisco.com>" __contributors__ = [] __copyright__ = "Copyright (c) 2019 Cisco and/or its affiliates." __license__ = "Cisco Sample Code License, Version 1.0" class WBXTeamsMeetingRoomTest(unittest.TestCase): def test_WBXTeamsMeetingRoomExists(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') self.assertIsNotNone(meeting_room_maker, 'test_WBXTeamsMeetingRoomExits should return an object') def test_creates_correct_object(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') self.assertIsInstance(meeting_room_maker, wbxtm_meeting.WBXTeamsMeetingRoom, 'test_creates_correct_object should return correct object.\nExpected: {}\n' \ 'Result: {}'.format(type(wbxtm_meeting.WBXTeamsMeetingRoom), type(meeting_room_maker))) def test_message_json_creation_is_correct(self): meeting_room_maker= wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = { "toPersonEmail": "timtayl@cisco.com", "markdown": "This is the **Smart Dashboard Bot**. Welcome to the Smart Licensing Dashboard! Please stand by while we get things setup." } result = json.loads(meeting_room_maker.message_json()) self.assertEqual(result, expected, 'test_message_json_creation_is_correct should return correct message json.\n' 'Expected: {}\nResult: {}'.format(expected, result)) def test_message_creation_response_returns_proper_personId_returns_string(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "somePersonIDalskd3" input_json = { "id": "someID", "roomId": "someMeetingRoomID1q3qerwerqew", "toPersonEmail": "timtayl@cisco.com", "roomType": "direct", "text": "This is the Smart Dashboard Bot. Welcome to the Smart Licensing Dashboard! Please stand by while we get things setup.", "personId": "somePersonID", "personEmail": "SLDBot@webex.bot", "markdown": "some Mark Down", "html": "Some html", "created": "2019-06-20T15:05:09.544Z" } result = meeting_room_maker.roomId_from_response_json(input_json) self.assertIsInstance(result, str, 'test_message_creation_response_returns_proper_personId_returns_string.\n' 'Expected: {}\nResult: {}'.format(type(""), type(result))) def test_message_creation_response_parsing_returns_roomID_sending_dict(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "someMeetingRoomID1q3qerwerqew" input_json = { "id": "someID", "roomId": "someMeetingRoomID1q3qerwerqew", "toPersonEmail": "timtayl@cisco.com", "roomType": "direct", "text": "This is the Smart Dashboard Bot. Welcome to the Smart Licensing Dashboard! Please stand by while we get things setup.", "personId": "somePersonID", "personEmail": "SLDBot@webex.bot", "markdown": "some Mark Down", "html": "Some html", "created": "2019-06-20T15:05:09.544Z" } result = meeting_room_maker.roomId_from_response_json(input_json) print(expected) self.assertEqual(result, expected, 'test_message_creation_response_parsing_returns_roomID.\nExpected: {}\n' 'Result: {}'.format(expected, result)) def test_message_creation_response_parsing_returns_roomID_sending_string(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "someMeetingRoomID1q3qerwerqew" input_json = { "id": "someID", "roomId": "someMeetingRoomID1q3qerwerqew", "toPersonEmail": "timtayl@cisco.com", "roomType": "direct", "text": "This is the Smart Dashboard Bot. Welcome to the Smart Licensing Dashboard! Please stand by while we get things setup.", "personId": "somePersonID", "personEmail": "SLDBot@webex.bot", "markdown": "some Mark Down", "html": "Some html", "created": "2019-06-20T15:05:09.544Z" } result = meeting_room_maker.roomId_from_response_json(json.dumps(input_json)) print(expected) self.assertEqual(result, expected, 'test_message_creation_response_parsing_returns_roomID.\nExpected: {}\n' 'Result: {}'.format(expected, result)) def test_membership_check_response_returns_proper_personId_returns_string(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "somePersonIDalskd3" input_json = { "items": [ { "id": "someID1", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDalskd3", "personEmail": "timtayl@cisco.com", "personDisplayName": "Tim Taylor", "personOrgId": "somePersonORgID1", "created": "2019-06-07T17:14:33.919Z" }, { "id": "someID2", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDaladskfpkj4", "personEmail": "SLDBot@webex.bot", "personDisplayName": "SmartLicensingBot", "personOrgId": "somePersonORgID2", "created": "2019-06-07T17:14:33.919Z" } ] } result = meeting_room_maker.personId_from_response_json(input_json) self.assertIsInstance(result, str, 'test_membership_check_response_returns_proper_personId_returns_string.\n' 'Expected: {}\nResult: {}'.format(type(""), type(result))) def test_membership_check_response_returns_proper_personId_sending_dict(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "somePersonIDalskd3" input_json = { "items": [ { "id": "someID1", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDalskd3", "personEmail": "timtayl@cisco.com", "personDisplayName": "Tim Taylor", "personOrgId": "somePersonORgID1", "created": "2019-06-07T17:14:33.919Z" }, { "id": "someID2", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDaladskfpkj4", "personEmail": "SLDBot@webex.bot", "personDisplayName": "SmartLicensingBot", "personOrgId": "somePersonORgID2", "created": "2019-06-07T17:14:33.919Z" } ] } result = meeting_room_maker.personId_from_response_json(input_json) self.assertEqual(result, expected, 'test_membership_check_response_returns_proper_personId_sending_dict returns ' 'correct value.\nExpected: {}\nResult: {}'.format(expected, result)) def test_membership_check_response_returns_proper_personId_sending_string(self): meeting_room_maker = wbxtm_meeting.WBXTeamsMeetingRoom('sample_bot_token', 'timtayl@cisco.com') expected = "somePersonIDalskd3" input_json = { "items": [ { "id": "someID1", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDalskd3", "personEmail": "timtayl@cisco.com", "personDisplayName": "Tim Taylor", "personOrgId": "somePersonORgID1", "created": "2019-06-07T17:14:33.919Z" }, { "id": "someID2", "roomId": "someMeetingRoomID1q3qerwerqew", "personId": "somePersonIDaladskfpkj4", "personEmail": "SLDBot@webex.bot", "personDisplayName": "SmartLicensingBot", "personOrgId": "somePersonORgID2", "created": "2019-06-07T17:14:33.919Z" } ] } result = meeting_room_maker.personId_from_response_json(json.dumps(input_json)) self.assertEqual(result, expected, 'test_membership_check_response_returns_proper_personId_sending_string returns ' 'correct value.\nExpected: {}\nResult: {}'.format(expected, result)) if __name__ == '__main__': unittest.main()

43.99569

149

0.59567

930

10,207

6.287097

0.192473

0.035745

0.051992

0.035916

0.829143

0.803318

0.789636

0.757654

0.747563

0

0.029358

0.302537

10,207

231

150

44.186147

0.791965

0.061037

0

0.668639

0

0.023669

0.382494

0.115626

0

0.053254

1

0.053254

false

0

0.017751

0

0.076923

0.011834

0

null

0

1

0

null

0

6

70c036350fb41fa26b288744499304bfac8f6e7b

179

py

Python

gary/coordinates/__init__.py

adrn/gary-old

065b371534baa03deeb860893640068d90ba5881

[ "MIT" ]

null

gary/coordinates/__init__.py

adrn/gary-old

065b371534baa03deeb860893640068d90ba5881

[ "MIT" ]

null

gary/coordinates/__init__.py

adrn/gary-old

065b371534baa03deeb860893640068d90ba5881

[ "MIT" ]

null

from .core import * from .sgr import * from .orphan import * from .propermotion import * from .velocity_transforms import * from .poincarepolar import * from .quaternion import *

22.375

34

0.765363

22

179

6.181818

0.454545

0.441176

0

0.156425

179

7

35

25.571429

0.900662

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

70f47270c6833fc5ac69352202b94a4364ce4c60

86

py

Python

uncertify/utils/io.py

matthaeusheer/uncertify

dfc2df16fb07ee8d7d17906827e0f0c8b2747532

[ "MIT" ]

1

2021-07-09T00:06:55.000Z

uncertify/utils/io.py

matthaeusheer/uncertify

dfc2df16fb07ee8d7d17906827e0f0c8b2747532

[ "MIT" ]

1

2021-04-29T21:55:32.000Z

uncertify/utils/io.py

matthaeusheer/uncertify

dfc2df16fb07ee8d7d17906827e0f0c8b2747532

[ "MIT" ]

null

from pathlib import Path def load_pytorch_checkpoint(checkpoint_path: Path): pass

21.5

51

0.813953

12

86

5.583333

0.75

0

0.139535

86

4

52

21.5

0.905405

0

1

0.333333

false

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

cb6fa2c4208e62e09262ea3b635901a0fbb165bb

31

py

Python

src/originexample/technology/__init__.py

project-origin/example-backend

13d9b528533dcaada8b0f0b93bbe2ef6a25c38ae

[ "MIT" ]

1

2021-04-23T08:19:49.000Z

src/datahub/technology/__init__.py

project-origin/datahub-service

0c3f27ee4fa0381ce3147f1fffef1108f13dc2c2

[ "MIT" ]

1

2021-02-10T02:28:52.000Z

src/originexample/technology/__init__.py

project-origin/example-backend

13d9b528533dcaada8b0f0b93bbe2ef6a25c38ae

[ "MIT" ]

null

from .models import Technology

15.5

30

0.83871

4

31

6.5

1

0

0.129032

31

1

31

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

cb9f1c2ded9b63f36a7f394156ac4d869aea5864

28,099

py

Python

capsul/pipeline/test/test_pipeline_parameters.py

denisri/capsul

ea1b41f08ab1acc95e50d90916c1e282807874ca

[ "CECILL-B" ]

null

capsul/pipeline/test/test_pipeline_parameters.py

denisri/capsul

ea1b41f08ab1acc95e50d90916c1e282807874ca

[ "CECILL-B" ]

null

capsul/pipeline/test/test_pipeline_parameters.py

denisri/capsul

ea1b41f08ab1acc95e50d90916c1e282807874ca

[ "CECILL-B" ]

null

# -*- coding: utf-8 -*- from __future__ import print_function from __future__ import absolute_import import os import json import shutil import unittest import tempfile from datetime import date, time, datetime import sys from capsul.api import Process, Pipeline from capsul.pipeline.pipeline_tools import save_pipeline_parameters, load_pipeline_parameters from traits.api import Float, File, String, Int, List, TraitListObject, Time, Date, Undefined, TraitError import six def load_pipeline_dictionary(filename): """ Just a part of load_pipeline_parameters to check if the values stored in the dictionary are correct. :param filename: the json filename """ if filename: kwargs = {} if sys.version_info[0] >= 3: kwargs['encoding'] = 'utf8' with open(filename, 'r', **kwargs) as file: dic = json.load(file) return dic ############################################################# # TEST PROCESSES DEFINITION # ############################################################# class TestInt(Process): def __init__(self): super(TestInt, self).__init__() self.add_trait("in_1", Int(output=False)) self.add_trait("in_2", Int(output=False)) self.add_trait("out", Int(output=True)) def _run_process(self): self.out = self.in_1 + self.in_2 class TestFloat(Process): def __init__(self): super(TestFloat, self).__init__() self.add_trait("in_1", Float(output=False)) self.add_trait("in_2", Float(output=False)) self.add_trait("out", Float(output=True)) def _run_process(self): self.out = self.in_1 - self.in_2 class TestString(Process): def __init__(self): super(TestString, self).__init__() self.add_trait("in_1", String(output=False)) self.add_trait("in_2", String(output=False)) self.add_trait("out", String(output=True)) def _run_process(self): self.out = self.in_1 + self.in_2 class TestFile(Process): def __init__(self): super(TestFile, self).__init__() self.add_trait("in_1", File(output=False)) self.add_trait("in_2", File(output=False)) self.add_trait("out", List(File(), output=True)) def _run_process(self): self.out = [self.in_1, self.in_2] class TestListInt(Process): def __init__(self): super(TestListInt, self).__init__() self.add_trait("in_1", List(Int(), output=False)) self.add_trait("in_2", List(Int(), output=False)) self.add_trait("out", List(Int(), output=True)) def _run_process(self): l = [] for idx, i in enumerate(self.in_1): l.append(i + self.in_2[idx]) self.out = l class TestListFloat(Process): def __init__(self): super(TestListFloat, self).__init__() self.add_trait("in_1", List(Float(), output=False)) self.add_trait("in_2", List(Float(), output=False)) self.add_trait("out", List(Float(), output=True)) def _run_process(self): l = [] for idx, i in enumerate(self.in_1): l.append(i - self.in_2[idx]) self.out = l class TestListString(Process): def __init__(self): super(TestListString, self).__init__() self.add_trait("in_1", List(String(), output=False)) self.add_trait("in_2", List(String(), output=False)) self.add_trait("out", List(String(), output=True)) def _run_process(self): l = [] for idx, i in enumerate(self.in_1): l.append(i + self.in_2[idx]) self.out = l class TestListFile(Process): def __init__(self): super(TestListFile, self).__init__() self.add_trait("in_1", List(File(), output=False)) self.add_trait("in_2", List(File(), output=False)) self.add_trait("out", List(File(), output=True)) def _run_process(self): self.out = [self.in_1[0], self.in_2[0]] class TestListList(Process): def __init__(self): super(TestListList, self).__init__() self.add_trait("in_1", List(List(Int()), output=False)) self.add_trait("in_2", List(List(Int()), output=False)) self.add_trait("out", List(Int(), output=True)) def _run_process(self): l = [] for idx, i in enumerate(self.in_1): l.append(i[0] + self.in_2[idx][0]) self.out = l class TestDateTime(Process): def __init__(self): super(TestDateTime, self).__init__() self.add_trait("in_1", Date(output=False)) self.add_trait("in_2", Time(output=False)) self.add_trait("out", List(output=True)) def _run_process(self): self.out = [self.in_1, self.in_2] ############################################################# # UNITTESTS DEFINITION # ############################################################# class TestPipelineMethods(unittest.TestCase): """ Class executing the unit tests of load_pipeline_parameters and save_pipeline_parameters """ def setUp(self): """ Called before every unit test Creates a temporary folder containing the json file that will be used for the test """ self.temp_folder = tempfile.mkdtemp() self.path = os.path.join(self.temp_folder, "test.json") def tearDown(self): """ Called after every unit test Deletes the temporary folder created for the test """ shutil.rmtree(self.temp_folder) def test_int(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestInt()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = 2 in_2 = 4 out = 6 pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), int) self.assertEqual(type(pipeline1.in_2), int) self.assertEqual(type(pipeline1.out), int) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), int) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), int) self.assertEqual(type(dic["pipeline_parameters"]["out"]), int) def test_float(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestFloat()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") pipeline1 = Pipeline1() pipeline1.in_1 = 2.0 pipeline1.in_2 = 4.0 pipeline1() in_1 = 2.0 in_2 = 4.0 out = -2.0 pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), float) self.assertEqual(type(pipeline1.in_2), float) self.assertEqual(type(pipeline1.out), float) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), float) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), float) self.assertEqual(type(dic["pipeline_parameters"]["out"]), float) def test_string(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestString()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = "This is " in_2 = "a test" out = "This is " + "a test" pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), str) self.assertEqual(type(pipeline1.in_2), str) self.assertEqual(type(pipeline1.out), str) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["out"]), six.text_type) def test_file(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestFile()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = '/tmp/yolo.nii' in_2 = '/tmp/yolo2.nii' out = ['/tmp/yolo.nii', '/tmp/yolo2.nii'] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), six.text_type) self.assertEqual(type(pipeline1.in_2), six.text_type) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), six.text_type) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) def test_list_int(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestListInt()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = [2, 4, 5] in_2 = [4, 8, 9] out = [6, 12, 14] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), TraitListObject) self.assertEqual(type(pipeline1.in_2), TraitListObject) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.in_1): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), int) for idx, element in enumerate(pipeline1.in_2): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), int) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), int) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), list) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), list) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_1"]): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), int) for idx, element in enumerate(dic["pipeline_parameters"]["in_2"]): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), int) for idx, element in enumerate(dic["pipeline_parameters"]["out"]): self.assertEqual(element, out[idx]) self.assertEqual(type(element), int) def test_list_float(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestListFloat()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = [2.0, 4.0, 5.0] in_2 = [4.0, 8.0, 9.0] out = [-2.0, -4.0, -4.0] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), TraitListObject) self.assertEqual(type(pipeline1.in_2), TraitListObject) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.in_1): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), float) for idx, element in enumerate(pipeline1.in_2): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), float) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), float) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), list) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), list) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_1"]): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), float) for idx, element in enumerate(dic["pipeline_parameters"]["in_2"]): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), float) for idx, element in enumerate(dic["pipeline_parameters"]["out"]): self.assertEqual(element, out[idx]) self.assertEqual(type(element), float) def test_list_string(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestListString()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = ["hello ", "hey "] in_2 = ["salut", "coucou"] out = ["hello salut", "hey coucou"] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), TraitListObject) self.assertEqual(type(pipeline1.in_2), TraitListObject) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.in_1): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), str) for idx, element in enumerate(pipeline1.in_2): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), str) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), str) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), list) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), list) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_1"]): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(dic["pipeline_parameters"]["in_2"]): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(dic["pipeline_parameters"]["out"]): self.assertEqual(element, out[idx]) self.assertEqual(type(element), six.text_type) def test_list_file(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestListFile()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = ["/tmp/yolo.txt", "/tmp/yolo2.txt"] in_2 = ["/tmp/yolo.nii", "/tmp/yolo2.nii"] out = ["/tmp/yolo.txt", "/tmp/yolo.nii"] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), TraitListObject) self.assertEqual(type(pipeline1.in_2), TraitListObject) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.in_1): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(pipeline1.in_2): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), six.text_type) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), list) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), list) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_1"]): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(dic["pipeline_parameters"]["in_2"]): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), six.text_type) for idx, element in enumerate(dic["pipeline_parameters"]["out"]): self.assertEqual(element, out[idx]) self.assertEqual(type(element), six.text_type) def test_list_list(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestListList()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = [[1, 1, 1], [2, 2, 2], [3, 3, 3]] in_2 = [[2, 2, 2], [3, 3, 3], [4, 4, 4]] out = [3, 5, 7] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, in_1) self.assertEqual(pipeline1.in_2, in_2) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.in_1), TraitListObject) self.assertEqual(type(pipeline1.in_2), TraitListObject) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.in_1): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), TraitListObject) for idx, element in enumerate(pipeline1.in_2): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), TraitListObject) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), int) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], in_1) self.assertEqual(dic["pipeline_parameters"]["in_2"], in_2) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), list) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), list) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_1"]): self.assertEqual(element, in_1[idx]) self.assertEqual(type(element), list) for idx, element in enumerate(dic["pipeline_parameters"]["in_2"]): self.assertEqual(element, in_2[idx]) self.assertEqual(type(element), list) for idx, element in enumerate(dic["pipeline_parameters"]["out"]): self.assertEqual(element, out[idx]) self.assertEqual(type(element), int) def test_date_time(self): class Pipeline1(Pipeline): def pipeline_definition(self): # Create processes self.add_process("node_1", TestDateTime()) # Exports self.export_parameter("node_1", "in_1", "in_1") self.export_parameter("node_1", "in_2", "in_2") self.export_parameter("node_1", "out", "out") in_1 = date(2008, 6, 5) in_2 = time(14, 4, 5) out = ['2008-06-05', '14:04:05'] pipeline1 = Pipeline1() pipeline1.in_1 = in_1 pipeline1.in_2 = in_2 pipeline1() save_pipeline_parameters(self.path, pipeline1) # Reinitializing pipeline and loading parameters pipeline1 = Pipeline1() load_pipeline_parameters(self.path, pipeline1) self.assertEqual(pipeline1.in_1, None) self.assertEqual(pipeline1.in_2, None) self.assertEqual(pipeline1.out, out) self.assertEqual(type(pipeline1.out), TraitListObject) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, out[idx]) self.assertEqual(type(element), six.text_type) # Verifying the dictionary dic = load_pipeline_dictionary(self.path) self.assertEqual(dic["pipeline_parameters"]["in_1"], six.text_type(in_1)) self.assertEqual(dic["pipeline_parameters"]["in_2"], six.text_type(in_2)) self.assertEqual(dic["pipeline_parameters"]["out"], out) self.assertEqual(type(dic["pipeline_parameters"]["in_1"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["in_2"]), six.text_type) self.assertEqual(type(dic["pipeline_parameters"]["out"]), list) for idx, element in enumerate(pipeline1.out): self.assertEqual(element, six.text_type(out[idx])) self.assertEqual(type(element), six.text_type) # a function test*() has to be defined in a test module in order to be # taken into account by the main test module capsul.test.test_capsul def test(): suite = unittest.TestLoader().loadTestsFromTestCase(TestPipelineMethods) runtime = unittest.TextTestRunner(verbosity=2).run(suite) return runtime.wasSuccessful() if __name__ == '__main__': test()

35.840561

105

0.61536

3,375

28,099

4.907259

0.053333

0.166647

0.104396

0.069436

0.879

0.855271

0.841867

0.813489

0.782695

0.775752

0

0.029331

0.248941

28,099

783

106

35.886335

0.755449

0.059148

0

0.69962

0

0.096832

0

0.001901

0

0.34981

1

0.08365

false

0

0.024715

0

0.152091

0.001901

0

null

0

1

0

null

0

6

1de87f45aa5eddeb764b1954037128c438044bab

113

py

Python

tests/test_dice.py

Beltro39/ci-me-dice-on-demand

48ca68da2ba897482624039ed469ca14a1a69df7

[ "MIT" ]

null

tests/test_dice.py

Beltro39/ci-me-dice-on-demand

48ca68da2ba897482624039ed469ca14a1a69df7

[ "MIT" ]

null

tests/test_dice.py

Beltro39/ci-me-dice-on-demand

48ca68da2ba897482624039ed469ca14a1a69df7

[ "MIT" ]

null

import unittest import app def test_test(): assert app.test() == "Works2!" #assert "Works!" == "Works!"

16.142857

34

0.619469

14

113

4.928571

0.571429

0

0.011111

0.20354

113

6

35

18.833333

0.755556

0.238938

0

0.082353

0

0.25

1

0.25

true

0

0.5

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

38487c314c15d4bad825dab4546ec7f23ac689e6

28

py

Python

methods/raft/model/__init__.py

awaelchli/torch-optical-flow

1f48d95b8f3412052f7c35eb2ec1fa7cb739efe1

[ "MIT" ]

null

methods/raft/model/__init__.py

awaelchli/torch-optical-flow

1f48d95b8f3412052f7c35eb2ec1fa7cb739efe1

[ "MIT" ]

null

methods/raft/model/__init__.py

awaelchli/torch-optical-flow

1f48d95b8f3412052f7c35eb2ec1fa7cb739efe1

[ "MIT" ]

1

2021-11-14T09:13:03.000Z

from model.raft import RAFT

14

27

0.821429

5

28

4.6

0.8

0

0.142857

28

1

28

0.958333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

69c1e61166db7ff7dbc9f4aa028f7c8407a9a40a

31

py

Python

app/__init__.py

chengxianga2008/abn_amro

66172747328b33a591ea4e4fcbb902cb823b91e0

[ "BSD-2-Clause" ]

null

app/__init__.py

chengxianga2008/abn_amro

66172747328b33a591ea4e4fcbb902cb823b91e0

[ "BSD-2-Clause" ]

null

app/__init__.py

chengxianga2008/abn_amro

66172747328b33a591ea4e4fcbb902cb823b91e0

[ "BSD-2-Clause" ]

null

from .core import daily_summary

31

0.870968

5

31

5.2

1

0

0.096774

31

1

31

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

69ca3c7f1b94eaf970a1efb39d86b5d093ac421d

82

py

Python

Kasa/__init__.py

Hotlynn2/kasa

aa4d18723451608bd4f008552d645b2b38b7daba

[ "MIT" ]

1

2021-03-28T18:32:07.000Z

Kasa/__init__.py

Hotlynn2/kasa

aa4d18723451608bd4f008552d645b2b38b7daba

[ "MIT" ]

null

Kasa/__init__.py

Hotlynn2/kasa

aa4d18723451608bd4f008552d645b2b38b7daba

[ "MIT" ]

null

from .preprocessing import * from .berttokenizer import * from .trainbert import *

27.333333

28

0.792683

9

82

7.222222

0.555556

0.307692

0

0.134146

82

3

29

27.333333

0.915493

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

3888171cad13e1ba81220af2a99577d7590f3b2c

71

py

Python

python/src/test/resources/pyfunc/math_log10_test.py

maropu/lljvm-translator

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

70

2017-12-12T10:54:00.000Z

2022-03-22T07:45:19.000Z

python/src/test/resources/pyfunc/math_log10_test.py

maropu/lljvm-as

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

14

2018-02-28T01:29:46.000Z

2019-12-10T01:42:22.000Z

python/src/test/resources/pyfunc/math_log10_test.py

maropu/lljvm-as

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

4

2019-07-21T07:58:25.000Z

2021-02-01T09:46:59.000Z

import math def math_log10_test(x, y): return 2 * y + math.log10(x)

14.2

30

0.676056

14

71

3.285714

0.642857

0.391304

0

0.087719

0.197183

71

4

31

17.75

0.719298

0

1

0.333333

false

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

38974a0e5002dfbe4f9e89c704a3bb19b7dd1c25

17,456

py

Python

userbot/plugins/animazioni3.py

Kazutettoh/strafattinoh-bot

e8ab44b6e720c8133fd43695355fabf20d37fe1c

[ "MIT" ]

null

userbot/plugins/animazioni3.py

Kazutettoh/strafattinoh-bot

e8ab44b6e720c8133fd43695355fabf20d37fe1c

[ "MIT" ]

null

userbot/plugins/animazioni3.py

Kazutettoh/strafattinoh-bot

e8ab44b6e720c8133fd43695355fabf20d37fe1c

[ "MIT" ]

null

""" Commands: .avast .avast1 .call .hack .linux .macos .stock .windows """ import asyncio from telethon import events from platform import uname from userbot import CMD_HELP, ALIVE_NAME from userbot.utils import admin_cmd DEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else "I'M STUPID" @borg.on(admin_cmd(pattern=f"avast", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 0.1 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "avast": await event.edit("avast") animation_chars = [ "`Downloading File..`", "`File Downloaded....`", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 4%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 8%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 20%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 36%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 52%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 84%\n█████████████████████▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 100%\n█████████████████████████ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nRicerca: 01 of 01 Files Scansione...\n\nSTATUS: Nessun Virus Rilevato...`" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11]) @borg.on(admin_cmd(pattern=f"avast1", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 1 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "avast1": await event.edit(input_str) animation_chars = [ "`Downloading File..`", "`File Downloaded....`", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 4%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 8%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 20%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 36%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 52%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 84%\n█████████████████████▒▒▒▒ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nFile Scanned... 100%\n█████████████████████████ `", "`Avast Security Checkup\n\n\nAccount: User Pro\nScadenza: 31/12/2099\n\nRicerca: 01 of 01 Scansione...\n\nSTATUS:⚠️Virus Rilevato⚠️\nINFO: Torzan, Spyware, Adware`" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11]) @borg.on(admin_cmd(pattern=f"call", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 3 animation_ttl = range(0, 18) #input_str = event.pattern_match.group(1) #if input_str == "call": await event.edit("call") animation_chars = [ "`Chiamata alla sede di Telegram...`", "`Chiamata Connessa`", "`Telegram: Salve, risponde la sede di Telegram. Chi è lei?`", f"{DEFAULTUSER}:`Salve sono` {DEFAULTUSER} ,`Devo parlare con il mio socio ,Pavel Durov`", "`User Autorizzato`", "`Chiamata a Pavel Durov` `+3969696969`", "`Chiamata Connessa`", f"{DEFAULTUSER}:`Banna questo account da Telegram`", "`Pavel: Posso sapere chi sei?`", f"{DEFAULTUSER}:`Yo bro, sono il tuo socio`", "`Pavel: OMG!!! Ma è da tanto che non ci vediamo, bro...\nMi assicurerò io che l'account venga bloccato entro 24 ore.`", f"{DEFAULTUSER}:`Grazie, a dopo bro.`", "`Pavel: Ma va bro, telegram è nostro. Chiamami quando sei libero`", f"{DEFAULTUSER}:`C'è qualche problema bro?🤔`", "`Pavel: Sì bro, c'è un bug in telegram v8.6.9.\nNon sono in grado di risolverlo. Mi, aiuti a correggere il bug?`", f"{DEFAULTUSER}:`Inviami tutto in chat, risolverò il bug.`", "`Pavel: Grazie bro \nCi sentiamo :)`", "`Chiamata Disconnessa.`" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 18]) @borg.on(admin_cmd(pattern=f"hack", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 2 animation_ttl = range(0, 12) #input_str = event.pattern_match.group(1) #if input_str == "hack": await event.edit("hack") animation_chars = [ "**Connessione a Telegram Data Center**", f"Target Selected By Hacker: {DEFAULTUSER}", "`Hacking... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)", "`Hacking... 4%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package", "`Hacking... 8%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)", "`Hacking... 20%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'", "`Hacking... 36%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'\nCreated wheel for telegram: filename=Telegram-Data-Sniffer-0.0.1-py3-none-any.whl size=1306 sha256=cb224caad7fe01a6649188c62303cd4697c1869fa12d280570bb6ac6a88e6b7e", "`Hacking... 52%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'\nCreated wheel for telegram: filename=Telegram-Data-Sniffer-0.0.1-py3-none-any.whl size=1306 sha256=cb224caad7fe01a6649188c62303cd4697c1869fa12d280570bb6ac6a88e6b7e\n Stored in directory: /app/.cache/pip/wheels/a2/9f/b5/650dd4d533f0a17ca30cc11120b176643d27e0e1f5c9876b5b", "`Hacking... 84%\n█████████████████████▒▒▒▒ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'\nCreated wheel for telegram: filename=Telegram-Data-Sniffer-0.0.1-py3-none-any.whl size=1306 sha256=cb224caad7fe01a6649188c62303cd4697c1869fa12d280570bb6ac6a88e6b7e\n Stored in directory: /app/.cache/pip/wheels/a2/9f/b5/650dd4d533f0a17ca30cc11120b176643d27e0e1f5c9876b5b\n\n **Successfully Hacked Telegram Server Database**", "`Hacking... 100%\n█████████HACKED███████████ `\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'\nCreated wheel for telegram: filename=Telegram-Data-Sniffer-0.0.1-py3-none-any.whl size=1306 sha256=cb224caad7fe01a6649188c62303cd4697c1869fa12d280570bb6ac6a88e6b7e\n Stored in directory: /app/.cache/pip/wheels/a2/9f/b5/650dd4d533f0a17ca30cc11120b176643d27e0e1f5c9876b5b\n\n **Successfully Hacked Telegram Server Database**\n\n\n🔹Output: Generating.....", f"`Account Hackerato...\n\nPaga 699€ a` {DEFAULTUSER} o @strafattino .`Per Rimuovere questo VIRUS`\n\n\n TERMINAL:\nDownloading Bruteforce-Telegram-0.1.tar.gz (9.3 kB)\nCollecting Data Package\n Downloading Telegram-Data-Sniffer-7.1.1-py2.py3-none-any.whl (82 kB)\nBuilding wheel for Tg-Bruteforcing (setup.py): finished with status 'done'\nCreated wheel for telegram: filename=Telegram-Data-Sniffer-0.0.1-py3-none-any.whl size=1306 sha256=cb224caad7fe01a6649188c62303cd4697c1869fa12d280570bb6ac6a88e6b7e\n Stored in directory: /app/.cache/pip/wheels/a2/9f/b5/650dd4d533f0a17ca30cc11120b176643d27e0e1f5c9876b5b\n\n **Successfully Hacked Telegram Server Database**\n\n\n🔹**Output:** Successful" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 12]) @borg.on(admin_cmd(pattern=f"linux", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 0.5 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "linux": await event.edit("linux") animation_chars = [ "`Connessione a Linux...`", "`Inizializza Linux Login.`", "`Loading Linux... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 3%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 9%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 23%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 39%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 69%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Linux... 89%\n█████████████████████▒▒▒▒ `", "`Loading Linux... 100%\n█████████████████████████ `", "`Welcome...\n\nStock OS: Symbian OS\nCurrent OS: Linux`\n\n**My PC Specs:**\n\n **CPU:** __2.9GHz Intel Core i9-8950HK (hexa-core, 12MB cache, up to 4.8GHz)__\n\n**Graphics:** __Nvidia GeForce GTX 1080 OC (8GB GDDR5X)__\n\n**RAM:** __32GB DDR4 (2,666MHz)__\n\n**Screen:** __17.3-inch, QHD (2,560 x 1,440) 120Hz G-Sync__\n\n**Storage:** __512GB PCIe SSD, 1TB HDD (7,200 rpm)__\n\n**Ports:** __2 x USB 3.0, 1 x USB-C 3.0, 1 x USB-C (Thunderbolt 3), HDMI, mini DisplayPort, Ethernet, headphone jack, microphone jack__\n\n**Connectivity:** __Killer 1550 802.11ac Wi-Fi, Bluetooth 5.0__\n\n**Camera:** __Alienware FHD camera, Tobii IR Eye-tracking with Windows Hello__\n\n**Size:** __16.7 x 13.1 x 1.18 inches (42.4 x 33.2 x 2.99cm; W x D x H)__" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11]) @borg.on(admin_cmd(pattern=f"macos", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 0.5 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "macos": await event.edit("macos") animation_chars = [ "`Connessione a Hackintosh...`", "`Inizializza Hackintosh Login.`", "`Loading Hackintosh... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 3%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 9%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 23%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 39%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 69%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Hackintosh... 89%\n█████████████████████▒▒▒▒ `", "`Loading Hackintosh... 100%\n█████████████████████████ `", "`Welcome...\n\nStock OS: Symbian OS\nCurrent OS: Hackintosh`\n\n**My PC Specs:**\n\n **CPU:** __2.9GHz Intel Core i9-8950HK (hexa-core, 12MB cache, up to 4.8GHz)__\n\n**Graphics:** __Nvidia GeForce GTX 1080 OC (8GB GDDR5X)__\n\n**RAM:** __32GB DDR4 (2,666MHz)__\n\n**Screen:** __17.3-inch, QHD (2,560 x 1,440) 120Hz G-Sync__\n\n**Storage:** __512GB PCIe SSD, 1TB HDD (7,200 rpm)__\n\n**Ports:** __2 x USB 3.0, 1 x USB-C 3.0, 1 x USB-C (Thunderbolt 3), HDMI, mini DisplayPort, Ethernet, headphone jack, microphone jack__\n\n**Connectivity:** __Killer 1550 802.11ac Wi-Fi, Bluetooth 5.0__\n\n**Camera:** __Alienware FHD camera, Tobii IR Eye-tracking with Windows Hello__\n\n**Size:** __16.7 x 13.1 x 1.18 inches (42.4 x 33.2 x 2.99cm; W x D x H)__" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11]) @borg.on(admin_cmd(pattern=f"stock", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 0.5 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "stock": await event.edit("stock") animation_chars = [ "`Connessione a Symbian OS...`", "`Inizializza Symbian OS Login.`", "`Loading Symbian OS... 0%\n█████████████████████████ `", "`Loading Symbian OS... 3%\n█████████████████████▒▒▒▒ `", "`Loading Symbian OS... 9%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Symbian OS... 23%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Symbian OS... 39%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Symbian OS... 69%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Symbian OS... 89%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Symbian OS... 100%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Welcome...\n\nStock OS: Symbian OS\nCurrent OS: Symbian OS`\n\n**My PC Specs:**\n\n **CPU:** __2.9GHz Intel Core i9-8950HK (hexa-core, 12MB cache, up to 4.8GHz)__\n\n**Graphics:** __Nvidia GeForce GTX 1080 OC (8GB GDDR5X)__\n\n**RAM:** __32GB DDR4 (2,666MHz)__\n\n**Screen:** __17.3-inch, QHD (2,560 x 1,440) 120Hz G-Sync__\n\n**Storage:** __512GB PCIe SSD, 1TB HDD (7,200 rpm)__\n\n**Ports:** __2 x USB 3.0, 1 x USB-C 3.0, 1 x USB-C (Thunderbolt 3), HDMI, mini DisplayPort, Ethernet, headphone jack, microphone jack__\n\n**Connectivity:** __Killer 1550 802.11ac Wi-Fi, Bluetooth 5.0__\n\n**Camera:** __Alienware FHD camera, Tobii IR Eye-tracking with Windows Hello__\n\n**Size:** __16.7 x 13.1 x 1.18 inches (42.4 x 33.2 x 2.99cm; W x D x H)__" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11]) @borg.on(admin_cmd(pattern=f"windows", outgoing=True)) async def _(event): if event.fwd_from: return animation_interval = 0.5 animation_ttl = range(0, 11) #input_str = event.pattern_match.group(1) #if input_str == "windows": await event.edit("windows") animation_chars = [ "`Connessione a Windows 10...`", "`Inizializza Windows 10 Login.`", "`Loading Windows 10... 0%\n▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 3%\n█▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 9%\n██▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 23%\n█████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 39%\n█████████▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 69%\n█████████████▒▒▒▒▒▒▒▒▒▒▒▒ `", "`Loading Windows 10... 89%\n█████████████████████▒▒▒▒ `", "`Loading Windows 10... 100%\n█████████████████████████ `", "`Welcome...\n\nStock OS: Symbian OS\nCurrent OS: Windows 10`\n\n**My PC Specs:**\n\n **CPU:** __2.9GHz Intel Core i9-8950HK (hexa-core, 12MB cache, up to 4.8GHz)__\n\n**Graphics:** __Nvidia GeForce GTX 1080 OC (8GB GDDR5X)__\n\n**RAM:** __32GB DDR4 (2,666MHz)__\n\n**Screen:** __17.3-inch, QHD (2,560 x 1,440) 120Hz G-Sync__\n\n**Storage:** __512GB PCIe SSD, 1TB HDD (7,200 rpm)__\n\n**Ports:** __2 x USB 3.0, 1 x USB-C 3.0, 1 x USB-C (Thunderbolt 3), HDMI, mini DisplayPort, Ethernet, headphone jack, microphone jack__\n\n**Connectivity:** __Killer 1550 802.11ac Wi-Fi, Bluetooth 5.0__\n\n**Camera:** __Alienware FHD camera, Tobii IR Eye-tracking with Windows Hello__\n\n**Size:** __16.7 x 13.1 x 1.18 inches (42.4 x 33.2 x 2.99cm; W x D x H)__" ] for i in animation_ttl: await asyncio.sleep(animation_interval) await event.edit(animation_chars[i % 11])

66.372624

759

0.587477

2,386

17,456

4.7829

0.145013

0.014546

0.031546

0.033123

0.711795

0.706011

0.702944

0

0.083032

0.19277

17,456

262

760

66.625954

0.62728

0.033799

0

0.436548

0

0.167513

0.710918

0.267767

0

1

0

false

0

0.025381

0

0.06599

0

null

0

1

0

1

0

null

0

6

2a16d1f1e10a6df0758b91d080a65afcafce61f8

3,631

py

Python

tests/test_modules/test_arcface.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

null

tests/test_modules/test_arcface.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

null

tests/test_modules/test_arcface.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

null

from copy import deepcopy import pytest import torch from mmgen.models.architectures import IDLossModel # yapf:disable from mmgen.models.architectures.arcface.model_irse import Backbone # yapf:enable class TestArcFace: @classmethod def setup_class(cls): cls.default_cfg = dict( input_size=224, num_layers=50, mode='ir', drop_ratio=0.4, affine=True) def test_arcface_cpu(self): model = Backbone(**self.default_cfg) x = torch.randn((2, 3, 224, 224)) y = model(x) assert y.shape == (2, 512) # test different input size cfg = deepcopy(self.default_cfg) cfg.update(dict(input_size=112)) model = Backbone(**cfg) x = torch.randn((2, 3, 112, 112)) y = model(x) assert y.shape == (2, 512) # test different num_layers cfg = deepcopy(self.default_cfg) cfg.update(dict(num_layers=50)) model = Backbone(**cfg) x = torch.randn((2, 3, 224, 224)) y = model(x) assert y.shape == (2, 512) # test different mode cfg = deepcopy(self.default_cfg) cfg.update(dict(mode='ir_se')) model = Backbone(**cfg) x = torch.randn((2, 3, 224, 224)) y = model(x) assert y.shape == (2, 512) # test different drop ratio cfg = deepcopy(self.default_cfg) cfg.update(dict(drop_ratio=0.8)) model = Backbone(**cfg) x = torch.randn((2, 3, 224, 224)) y = model(x) assert y.shape == (2, 512) # test affine=False cfg = deepcopy(self.default_cfg) cfg.update(dict(affine=False)) model = Backbone(**cfg) x = torch.randn((2, 3, 224, 224)) y = model(x) assert y.shape == (2, 512) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_arcface_cuda(self): model = Backbone(**self.default_cfg).cuda() x = torch.randn((2, 3, 224, 224)).cuda() y = model(x) assert y.shape == (2, 512) # test different input size cfg = deepcopy(self.default_cfg) cfg.update(dict(input_size=112)) model = Backbone(**cfg).cuda() x = torch.randn((2, 3, 112, 112)).cuda() y = model(x) assert y.shape == (2, 512) # test different num_layers cfg = deepcopy(self.default_cfg) cfg.update(dict(num_layers=50)) model = Backbone(**cfg).cuda() x = torch.randn((2, 3, 224, 224)).cuda() y = model(x) assert y.shape == (2, 512) # test different mode cfg = deepcopy(self.default_cfg) cfg.update(dict(mode='ir_se')) model = Backbone(**cfg).cuda() x = torch.randn((2, 3, 224, 224)).cuda() y = model(x) assert y.shape == (2, 512) # test different drop ratio cfg = deepcopy(self.default_cfg) cfg.update(dict(drop_ratio=0.8)) model = Backbone(**cfg).cuda() x = torch.randn((2, 3, 224, 224)).cuda() y = model(x) assert y.shape == (2, 512) # test affine=False cfg = deepcopy(self.default_cfg) cfg.update(dict(affine=False)) model = Backbone(**cfg).cuda() x = torch.randn((2, 3, 224, 224)).cuda() y = model(x) assert y.shape == (2, 512) # test loss model id_loss_model = IDLossModel() x1 = torch.randn((2, 3, 224, 224)).cuda() x2 = torch.randn((2, 3, 224, 224)).cuda() y, _ = id_loss_model(pred=x1, gt=x2) assert y >= 0

29.520325

78

0.544754

485

3,631

4

0.146392

0.072165

0.079381

0.086598

0.775773

0.746907

0.729381

0.710825

0.702062

0

0.074489

0.312311

3,631

122

79

29.762295

0.702443

0.07491

0

0.711111

0

0.007474

0

0.144444

1

0.033333

false

0

0.055556

0

0.1

0

null

0

1

0

1

0

null

0

6

2a2b78e6147109360dd2adb3dd25ac9a990ef925

29

py

Python

mydip/__init__.py

kommunium/dip-lab

2c8e08a994fb34b87da55da48a7b72b7c13d9c81

[ "MIT" ]

null

mydip/__init__.py

kommunium/dip-lab

2c8e08a994fb34b87da55da48a7b72b7c13d9c81

[ "MIT" ]

null

mydip/__init__.py

kommunium/dip-lab

2c8e08a994fb34b87da55da48a7b72b7c13d9c81

[ "MIT" ]

null

import numpy as np import PIL

14.5

18

0.827586

6

29

4

0.833333

0

0.172414

29

2

19

14.5

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

2a5b0dc0ffe6c61566679afaae519f65c95f4c02

14,155

py

Python

loaderscript.py

sayanmutd/Project-DeepView

3c9fd134085b38e42f3439e2eda97f4a1606c9e6

[ "MIT" ]

4

2019-05-11T12:22:11.000Z

2020-06-22T05:28:18.000Z

loaderscript.py

sayanmutd/Project-DeepView

3c9fd134085b38e42f3439e2eda97f4a1606c9e6

[ "MIT" ]

null

loaderscript.py

sayanmutd/Project-DeepView

3c9fd134085b38e42f3439e2eda97f4a1606c9e6

[ "MIT" ]

2

2019-05-11T12:22:17.000Z

2021-12-18T22:32:38.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat Aug 11 13:29:25 2018 @author: rishav """ import json import pandas as pd import os from sklearn.metrics import accuracy_score import pickle #creating dummy row file = open('Violent/rgb_000350_keypoints.json','r') datastore = json.load(file) person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; #print(len(rperson1)) for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df=pd.DataFrame([datamerge]) df2=pd.DataFrame([datamerge]) df3=pd.DataFrame([datamerge]) df4=pd.DataFrame([datamerge]) #print(df) ## REPLACE ALL THESE MULTIPLE CALLS WITH A SINGLE FUNCTION WITH PASSED PARAMETERS AFASP for file in os.listdir("Violent"): if file.endswith(".json"): dir=os.path.join("Violent/", file) file = open(dir,'r') datastore = json.load(file) person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("NonViolent"): if file.endswith(".json"): dir=os.path.join("NonViolent/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("NV2"): if file.endswith(".json"): dir=os.path.join("NV2/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("NV3"): if file.endswith(".json"): dir=os.path.join("NV3/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("NV4"): if file.endswith(".json"): dir=os.path.join("NV4/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("NV5"): if file.endswith(".json"): dir=os.path.join("NV5/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("NV6"): if file.endswith(".json"): dir=os.path.join("NV6/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df.loc[len(df)]=datamerge for file in os.listdir("V2"): if file.endswith(".json"): dir=os.path.join("V2/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("V3"): if file.endswith(".json"): dir=os.path.join("V3/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("V4"): if file.endswith(".json"): dir=os.path.join("V4/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("V5"): if file.endswith(".json"): dir=os.path.join("V5/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("V6"): if file.endswith(".json"): dir=os.path.join("V6/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df.loc[len(df)]=datamerge for file in os.listdir("V7"): if file.endswith(".json"): dir=os.path.join("V7/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(1) df2.loc[len(df2)]=datamerge for file in os.listdir("NV7"): if file.endswith(".json"): dir=os.path.join("NV7/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df3.loc[len(df3)]=datamerge for file in os.listdir("TestO"): if file.endswith(".json"): dir=os.path.join("TestO/", file) file = open(dir,'r') datastore = json.load(file) try: person1=datastore['people'][0]['pose_keypoints_2d'] person2=datastore['people'][1]['pose_keypoints_2d'] except: print() rperson1=[] rperson2=[] counter=1; for dat in person1: if counter%3 !=0: rperson1.append(dat); counter=counter+1; counter=1; for dat in person2: if counter%3 !=0: rperson2.append(dat); counter=counter+1; datamerge=rperson1+rperson2 datamerge.append(0) df4.loc[len(df4)]=datamerge df=df.sort_values(by=[72]) df=df.reset_index(drop=True) X = df.iloc[363:, 0:72].values y = df.iloc[363:, 72].values XTEST = df2.iloc[1:, 0:72].values yTEST = df3.iloc[1:, 0:72].values Custom= df4.iloc[1:,0:72].values # Splitting the dataset into the Training set and Test set from sklearn.cross_validation import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 42) # Feature Scaling #from sklearn.preprocessing import MinMaxScaler #sc = MinMaxScaler(feature_range=(0,1)) #X_train = sc.fit_transform(X_train) #X_test = sc.transform(X_test) #######Linear SVM Classification: # Fitting SVM to the Training set #from sklearn.svm import SVC from sklearn.naive_bayes import GaussianNB #classifier = SVC(kernel = 'linear', random_state = 0) ####RBF SVM Classification: #classifier = SVC(kernel = 'sigmoid', random_state = 42) ###### POLYNOMIAL######## #classifier = SVC(kernel = 'poly', random_state = 0, degree = 3) ######SIGMOID ############################ classifier= GaussianNB() classifier.fit(X_train, y_train) filename="RBF.sav" pickle.dump(classifier, open(filename, 'wb')) # Visualising the Test set results ######SIGMOID ############################ # Visualising the Test set results predicted_test=classifier.predict(X_test) predicted_train=classifier.predict(X_train) predicted_violent=classifier.predict(XTEST) predicted_nonviolent=classifier.predict(yTEST) predicted_Custom=classifier.predict(Custom) #get the accuracy score test_accuracy=accuracy_score(y_test,predicted_test) train_accuracy=accuracy_score(y_train,predicted_train) print(test_accuracy,train_accuracy)

30.053079

95

0.552172

1,662

14,155

4.637184

0.098676

0.066433

0.062281

0.045673

0.79071

0.775658

0.768652

0.708317

0.706371

0

0.047336

0.310491

14,155

470

96

30.117021

0.742316

0.059626

0

0.845606

0

0.074911

0.002502

0

1

0

false

0

0.016627

0

0.016627

0.035629

0

null

0

1

0

1

0

null

0

6

2a92f3938aa70fe13b295276ca4cac3ad5cb4fdd

100

py

Python

dual_rocks/user_profile/context_processors.py

dual-rocks/dual.rocks

6231833fcc36839b1dc6de79edda99d9d15c2cfe

[ "MIT" ]

null

dual_rocks/user_profile/context_processors.py

dual-rocks/dual.rocks

6231833fcc36839b1dc6de79edda99d9d15c2cfe

[ "MIT" ]

10

2020-02-18T00:37:32.000Z

2022-03-12T00:17:58.000Z

dual_rocks/user_profile/context_processors.py

dual-rocks/dual.rocks

6231833fcc36839b1dc6de79edda99d9d15c2cfe

[ "MIT" ]

null

def current_profile(request): return { 'current_profile': request.current_profile }

20

50

0.68

10

100

6.5

0.5

0.646154

0

0.23

100

4

51

25

0.844156

0

0.15

0

1

0.25

false

0

0.25

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

aa625cc2c3be65bfc42c780631044500aac6d0d9

8,045

py

Python

code/trainUtils.py

AnilOsmanTur/Classifying-The-ID-Visibility

58516ffa91bd15e968a54fc4e7a21730ceda8e36

[ "MIT" ]

null

code/trainUtils.py

AnilOsmanTur/Classifying-The-ID-Visibility

58516ffa91bd15e968a54fc4e7a21730ceda8e36

[ "MIT" ]

null

code/trainUtils.py

AnilOsmanTur/Classifying-The-ID-Visibility

58516ffa91bd15e968a54fc4e7a21730ceda8e36

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sat Jan 18 17:19:52 2020 @author: anilosmantur """ import numpy as np import time import torch import torch.optim as optim from Model import CardModel from sklearn import metrics def init_model(path='../artifacts/modified_mobilenet_v2_features_state_dict.pth', load_model=False, cuda=False, lr=1e-3, decay_points=[], decay=0.1): print('initizalizing Model...') model = CardModel(path=path, load=(not load_model)) if load_model: model.load_state_dict(torch.load(path), strict=True) if cuda: model.cuda() optimizer = optim.Adam(filter(lambda p: p.requires_grad, model.parameters()), lr=lr, betas=(0.9,0.999)) scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=decay_points, gamma=decay) print('Model loaded...') return model, optimizer, scheduler def calculate_predictions(out): predicted = np.argmax(out, axis=1) return predicted def train(model, optimizer, loader, epoch_i, cuda=False): model.train() loss = 0.0 avg = 0.0 start = time.time() loss_hist = [] predictions = [] labels = [] for batch_idx, data in enumerate(loader, 1): batch_time_s = time.time() y = torch.squeeze(data['label']) x = data['image'] if cuda: x = x.cuda() y = y.cuda() optimizer.zero_grad() out = model(x) loss = model.criter(out, y) loss.backward() optimizer.step() out = out.cpu().detach().numpy() preds = calculate_predictions(out) predictions += list(preds) y = y.cpu().detach().numpy() labels += list(y) # metrics accuracy = metrics.accuracy_score(y, preds) precision = metrics.precision_score(y, preds, average='weighted',zero_division=1) recall = metrics.recall_score(y, preds, average='weighted',zero_division=1) f1_score = metrics.f1_score(y, preds, average='weighted',zero_division=1) loss = float(loss.detach()) loss_hist.append(loss) avg += loss spent_time = time.time() - batch_time_s out_str = '\rTRAIN Epoch: {} Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( epoch_i, loss, 100*accuracy, precision, recall, f1_score, spent_time, 10*' ') print('\r'+out_str, end='') labels = np.array(labels) predictions = np.array(predictions) accuracy = metrics.accuracy_score(labels, predictions) precision = metrics.precision_score(labels, predictions, average='weighted',zero_division=1) recall = metrics.recall_score(labels, predictions, average='weighted',zero_division=1) f1_score = metrics.f1_score(labels, predictions, average='weighted',zero_division=1) total_time = time.time() - start avg /= len(loader) out_str = 'TRAIN Epoch: {} Avg Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( epoch_i, avg, 100*accuracy, precision, recall, f1_score, total_time, 10*' ') print('\r'+out_str) return loss_hist, avg, accuracy, precision, recall, f1_score def validation(model, loader, epoch_i, cuda=False, type_t='VAL'): with torch.no_grad(): model.eval() loss = 0.0 avg = 0.0 start = time.time() loss_hist = [] predictions = [] labels = [] for batch_idx, data in enumerate(loader, 1): batch_time_s = time.time() y = torch.squeeze(data['label']) x = data['image'] if cuda: x = x.cuda() y = y.cuda() out = model(x) loss = float(model.criter(out, y).detach_()) loss_hist.append(loss) avg += loss out = out.cpu().detach().numpy() preds = calculate_predictions(out) predictions += list(preds) y = y.cpu().detach().numpy() labels += list(y) # metrics accuracy = metrics.accuracy_score(y, preds) precision = metrics.precision_score(y, preds, average='weighted',zero_division=1) recall = metrics.recall_score(y, preds, average='weighted',zero_division=1) f1_score = metrics.f1_score(y, preds, average='weighted',zero_division=1) spent_time = time.time() - batch_time_s out_str = '\r{} Epoch: {} Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( type_t, epoch_i, loss, 100*accuracy, precision, recall, f1_score, spent_time, 10*' ') print('\r'+out_str, end='') labels = np.array(labels) predictions = np.array(predictions) accuracy = metrics.accuracy_score(labels, predictions) precision = metrics.precision_score(labels, predictions, average='weighted',zero_division=1) recall = metrics.recall_score(labels, predictions, average='weighted',zero_division=1) f1_score = metrics.f1_score(labels, predictions, average='weighted',zero_division=1) total_time = time.time() - start avg /= len(loader) out_str = '{} Epoch: {} Avg Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( type_t, epoch_i, avg, 100*accuracy, precision, recall, f1_score, total_time, 10*' ') print('\r'+out_str) return loss_hist, avg, accuracy, precision, recall, f1_score def predict_from_loader(model, loader, cuda=False): with torch.no_grad(): model.eval() loss = 0.0 avg = 0.0 start = time.time() loss_hist = [] predictions = [] labels = [] for batch_idx, data in enumerate(loader, 1): batch_time_s = time.time() y = torch.squeeze(data['label']) x = data['image'] if cuda: x = x.cuda() y = y.cuda() out = model(x) loss = float(model.criter(out, y).detach_()) loss_hist.append(loss) avg += loss out = out.cpu().detach().numpy() preds = calculate_predictions(out) predictions += list(preds) y = y.cpu().detach().numpy() labels += list(y) # metrics accuracy = metrics.accuracy_score(y, preds) precision = metrics.precision_score(y, preds, average='weighted',zero_division=1) recall = metrics.recall_score(y, preds, average='weighted',zero_division=1) f1_score = metrics.f1_score(y, preds, average='weighted',zero_division=1) spent_time = time.time() - batch_time_s out_str = '\r{:5.2f}% {}/{} Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( 100*batch_idx/len(loader), batch_idx, len(loader), loss, 100*accuracy, precision, recall, f1_score, spent_time, 10*' ') print('\r'+out_str, end='') labels = np.array(labels) predictions = np.array(predictions) accuracy = metrics.accuracy_score(labels, predictions) precision = metrics.precision_score(labels, predictions, average='weighted',zero_division=1) recall = metrics.recall_score(labels, predictions, average='weighted',zero_division=1) f1_score = metrics.f1_score(labels, predictions, average='weighted',zero_division=1) total_time = time.time() - start avg /= len(loader) out_str = 'Avg Loss: {:.6f} Acc: {:5.2f} preci: {:.3f} recall: {:.3f} f1 score: {:.3f} time: {:.2f}{}'.format( avg, 100*accuracy, precision, recall, f1_score, total_time, 10*' ') print('\r'+out_str) return labels, predictions

39.436275

153

0.576134

976

8,045

4.605533

0.143443

0.040489

0.076085

0.10812

0.798888

0.789544

0.782647

0.775306

0

0.027821

0.280671

8,045

204

154

39.436275

0.74892

0.013052

0

0.740506

0

0.037975

0.113115

0.007314

0

1

0.031646

false

0

0.037975

0

0.101266

0.050633

0

null

0

1

0

1

0

null

0

6

aaad629bc99d200a6033466bedfde4c405906ab6

57,874

py

Python

freecad/Commands.py

Halfmuh/ef

22fcb912da2c8b904fc9b5542d65718e6a0883f6

[ "MIT" ]

13

2016-08-09T13:38:35.000Z

2021-11-14T11:25:57.000Z

freecad/Commands.py

Halfmuh/ef

22fcb912da2c8b904fc9b5542d65718e6a0883f6

[ "MIT" ]

18

2018-04-21T19:26:34.000Z

2019-02-14T10:51:37.000Z

freecad/Commands.py

Halfmuh/ef

22fcb912da2c8b904fc9b5542d65718e6a0883f6

[ "MIT" ]

7

2017-02-22T09:12:42.000Z

2019-07-07T07:49:02.000Z

import os import FreeCAD, FreeCADGui import Part from math import * from pivy import coin from PySide import QtGui, QtCore import subprocess class CreateEfConfig(): """Create objects for new ef config""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/new_conf_template.svg', 'Accel' : "Shift+N", # a default shortcut (optional) 'MenuText': "New minimal ef config", 'ToolTip' : "New minimal ef config"} def Activated(self): ef_conf_group = FreeCAD.ActiveDocument.addObject( "App::DocumentObjectGroup", "ef_conf" ) time_grid_conf = ef_conf_group.newObject( "App::FeaturePython", "Time grid" ) TimeGridConfigPart( time_grid_conf ) outfile_conf = ef_conf_group.newObject( "App::FeaturePython", "Output filename") OutputFilenameConfigPart( outfile_conf ) particle_interaction_conf = ef_conf_group.newObject( "App::FeaturePython", "Particle interaction model") ParticleInteractionModelConfigPart( particle_interaction_conf ) spat_mesh_conf = ef_conf_group.newObject( "App::FeaturePython", "Spatial mesh" ) SpatialMeshConfigPart( spat_mesh_conf ) boundary_cond_conf = ef_conf_group.newObject( "App::FeaturePython", "Boundary conditions" ) BoundaryConditionsConfigPart( boundary_cond_conf ) magn_field_conf = ef_conf_group.newObject( "App::FeaturePython", "Magnetic field" ) MagneticFieldConfigPart( magn_field_conf ) run_ef = ef_conf_group.newObject( "App::FeaturePython", "Run_Ef" ) RunEfConfig( run_ef ) FreeCAD.ActiveDocument.recompute() return def IsActive(self): return (FreeCAD.ActiveDocument is not None) class AddSourceRegion(): """Add box-shaped source of particles""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/add_box_source.svg', 'Accel' : "Shift+S", # a default shortcut (optional) 'MenuText': "Add box-shaped source of particles", 'ToolTip' : "Add box-shaped source of particles"} def Activated(self): for ef_conf_group in self.selected_ef_conf_groups: source_conf = ef_conf_group.newObject( "App::FeaturePython", "Source" ) ParticleSourceConfigPart( source_conf ) FreeCAD.ActiveDocument.recompute() return def IsActive(self): # Add source only if ef-group is selected # todo: check if selected object is ef-conf group # or directly belongs to ef-conf group sel = FreeCADGui.Selection.getSelection() self.selected_ef_conf_groups = [] active = False for obj in sel: if "ef" in obj.Name: self.selected_ef_conf_groups.append( obj ) active = True else: for parent_obj in obj.InList: if "ef" in parent_obj.Name: self.selected_ef_conf_groups.append( parent_obj ) active = True return active class AddCylindricalSource(): """Add cylindrical-shaped source of particles""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/add_cylindrical_source.ico', 'Accel' : "Shift+C", # a default shortcut (optional) 'MenuText': "Add cylindrical-shaped source of particles", 'ToolTip' : "Add cylindrical-shaped source of particles"} def Activated(self): for ef_conf_group in self.selected_ef_conf_groups: source_conf = ef_conf_group.newObject( "App::FeaturePython", "Cylindrical Source" ) ParticleCylindricalSourceConfigPart( source_conf ) FreeCAD.ActiveDocument.recompute() return def IsActive(self): # Add source only if ef-group is selected # todo: check if selected object is ef-conf group # or directly belongs to ef-conf group sel = FreeCADGui.Selection.getSelection() self.selected_ef_conf_groups = [] active = False for obj in sel: if "ef" in obj.Name: self.selected_ef_conf_groups.append( obj ) active = True else: for parent_obj in obj.InList: if "ef" in parent_obj.Name: self.selected_ef_conf_groups.append( parent_obj ) active = True return active class AddInnerRegionBox(): """Add box inner region""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/add_box_inner_region.svg', 'Accel' : "Shift+R", # a default shortcut (optional) 'MenuText': "Add box-shaped inner region", 'ToolTip' : "Add box-shaped inner region"} def Activated(self): for ef_conf_group in self.selected_ef_conf_groups: inner_reg_conf = ef_conf_group.newObject( "App::FeaturePython", "Inner_region_box" ) InnerRegionBoxConfigPart( inner_reg_conf ) FreeCAD.ActiveDocument.recompute() return def IsActive(self): # Add source only if ef-group is selected # todo: check if selected object is ef-conf group # or directly belongs to ef-conf group sel = FreeCADGui.Selection.getSelection() self.selected_ef_conf_groups = [] active = False for obj in sel: if "ef" in obj.Name: self.selected_ef_conf_groups.append( obj ) active = True else: for parent_obj in obj.InList: if "ef" in parent_obj.Name: self.selected_ef_conf_groups.append( parent_obj ) active = True return active class GenerateConfFile(): """Generate .conf file suitable for ef""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/generate_config.svg', 'Accel' : "Shift+G", # a default shortcut (optional) 'MenuText': "Generate .conf file", 'ToolTip' : "Generate .conf file"} def IsActive(self): # Add source only if ef-group is selected # todo: check if selected object is ef-conf group # or directly belongs to ef-conf group sel = FreeCADGui.Selection.getSelection() self.selected_ef_conf_groups = [] active = False for obj in sel: if "ef" in obj.Name: self.selected_ef_conf_groups.append( obj ) active = True else: for parent_obj in obj.InList: if "ef" in parent_obj.Name: self.selected_ef_conf_groups.append( parent_obj ) active = True return active def Activated(self): for ef_grp in self.selected_ef_conf_groups: ### Generate and write config config_text = self.generate_config_text( ef_grp ) config_filename = self.write_config( config_text, ef_grp.Name ) def generate_config_text( self, ef_group ): config_text = [] config_text.append( "; Generated by FreeCAD module\n" ) config_text.append( "\n" ) objects_in_grp = ef_group.Group for obj in objects_in_grp: config_text.extend( obj.Proxy.generate_config_part() ) return config_text def write_config( self, config_text, ef_group_name ): default_dialog_path = "./" default_conf_name = ef_group_name + ".conf" conf_filename, filename_filter = QtGui.QFileDialog.getSaveFileName( None, "Generate ef config", default_dialog_path + default_conf_name, "*.conf" ) if conf_filename == "": FreeCAD.Console.PrintMessage( "Config generation aborted: " "file to write was not selected" + "\n" ) else: with open( conf_filename, 'w') as f: f.writelines( config_text ) return conf_filename class RunEf(): """Run Ef""" def GetResources(self): moddir = os.path.expanduser("~") + "/.FreeCAD/Mod/ef" return {'Pixmap' : moddir + '/icons/run_ef.svg', 'Accel' : "Shift+S", # a default shortcut (optional) 'MenuText': "Run Ef", 'ToolTip' : "Run Ef"} def Activated(self): for ef_conf_group in self.selected_ef_conf_groups: # todo: generate config to temp file in temp directory, run ef on this config # Rename 'command' to 'ef_command' run_ef = ef_conf_group.getObject("Run_Ef") freecad_workdir = os.getcwd() os.chdir( run_ef.change_workdir_to ) stdout = subprocess.Popen( run_ef.command, shell = True, stdout = subprocess.PIPE ).stdout.read() FreeCAD.Console.PrintMessage( stdout ) # https://stackoverflow.com/questions/803265/getting-realtime-output-using-subprocess # realtime output for subprocess os.chdir( freecad_workdir ) FreeCAD.ActiveDocument.recompute() return def IsActive(self): # Add source only if ef-group is selected # todo: check if selected object is ef-conf group # or directly belongs to ef-conf group sel = FreeCADGui.Selection.getSelection() self.selected_ef_conf_groups = [] active = False for obj in sel: if "ef" in obj.Name: self.selected_ef_conf_groups.append( obj ) active = True else: for parent_obj in obj.InList: if "ef" in parent_obj.Name: self.selected_ef_conf_groups.append( parent_obj ) active = True return active ### class TimeGridConfigPart: """Properties and representation of time_grid config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "total_time", "Time grid", "Total simulation time" ).total_time = "1.0" obj.addProperty( "App::PropertyString", "time_save_step", "Time grid", "Time step between checkpoints" ).time_save_step = "1e-3" obj.addProperty( "App::PropertyString", "time_step_size", "Time grid", "Time step" ).time_step_size = "1e-5" obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): ''' Setup the scene sub-graph of the view provider, this method is mandatory ''' # todo: represent time grid as text on 3d-screen # self.text = coin.SoGroup() # self.t1 = coin.SoAsciiText() # self.t1.string = "arghk" # self.text.addChild( self.t1 ) return def generate_config_part( self ): conf_part = [] conf_part.append( "[TimeGrid]\n" ) export_property_names = [ "total_time", "time_save_step", "time_step_size" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part def __getstate__(self): '''When saving the document this object gets stored using Python's json module. Since we have some un-serializable parts here -- the Coin stuff -- we must define this method to return a tuple of all serializable objects or None.''' doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): '''When restoring the serialized object from document we have the chance to set some internals here. Since no data were serialized nothing needs to be done here.''' doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None class OutputFilenameConfigPart(): """Properties and representation of output_filename config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "output_filename_suffix", "Output filename", "Output filename extension").output_filename_suffix = ".h5" obj.addProperty( "App::PropertyString", "output_filename_prefix", "Output filename", "Output filename basename").output_filename_prefix = "out_" obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): '''Setup the scene sub-graph of the view provider, this method is mandatory''' # todo: represent output_filename as text on 3d-screen return def generate_config_part( self ): conf_part = [] conf_part.append( "[OutputFilename]\n" ) export_property_names = [ "output_filename_suffix", "output_filename_prefix" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part def __getstate__(self): '''When saving the document this object gets stored using Python's json module. Since we have some un-serializable parts here -- the Coin stuff -- we must define this method to return a tuple of all serializable objects or None.''' doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): '''When restoring the serialized object from document we have the chance to set some internals here. Since no data were serialized nothing needs to be done here.''' doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None class ParticleInteractionModelConfigPart(): """Properties and representation of output_filename config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyEnumeration", "particle_interaction_model", "Base", "Interaction of particles").particle_interaction_model = ["noninteracting", "PIC"] obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): '''Setup the scene sub-graph of the view provider, this method is mandatory''' return def generate_config_part( self ): conf_part = [] conf_part.append( "[ParticleInteractionModel]\n" ) export_property_names = [ "particle_interaction_model" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part def __getstate__(self): '''When saving the document this object gets stored using Python's json module. Since we have some un-serializable parts here -- the Coin stuff -- we must define this method to return a tuple of all serializable objects or None.''' doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): '''When restoring the serialized object from document we have the chance to set some internals here. Since no data were serialized nothing needs to be done here.''' doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None class SpatialMeshConfigPart(): """Properties and representation of spatial_mesh config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "grid_x_size", "Spatial mesh", "Computational volume X-size" ).grid_x_size = "1.0" obj.addProperty( "App::PropertyString", "grid_x_step", "Spatial mesh", "X-step size" ).grid_x_step = "0.1" obj.addProperty( "App::PropertyString", "grid_y_size", "Spatial mesh", "Computational volume Y-size" ).grid_y_size = "1.0" obj.addProperty( "App::PropertyString", "grid_y_step", "Spatial mesh", "Y-step size" ).grid_y_step = "0.1" obj.addProperty( "App::PropertyString", "grid_z_size", "Spatial mesh", "Computational volume Z-size" ).grid_z_size = "1.0" obj.addProperty( "App::PropertyString", "grid_z_step", "Spatial mesh", "Z-step size" ).grid_z_step = "0.1" obj.addProperty("Part::PropertyPartShape", "Shape", "Spatial mesh", "Computational volume box") obj.ViewObject.addProperty("App::PropertyColor", "Color", "Spatial mesh", "Volume box color").Color=(1.0,0.0,0.0) obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def attach(self, obj): self.shaded = coin.SoGroup() self.wireframe = coin.SoGroup() self.color = coin.SoBaseColor() self.trans = coin.SoTranslation() self.box = coin.SoCube() self.shaded.addChild( self.color ) self.shaded.addChild( self.trans ) self.shaded.addChild( self.box ) obj.addDisplayMode( self.shaded, "Shaded" ); style = coin.SoDrawStyle() style.style = coin.SoDrawStyle.LINES self.wireframe.addChild( style ) self.wireframe.addChild( self.color ) self.wireframe.addChild( self.trans ) self.wireframe.addChild( self.box ) obj.addDisplayMode( self.wireframe, "Wireframe" ); self.onChanged( obj, "Color" ) return def updateData(self, obj, prop ): "Executed when propery in field 'data' is changed" # todo: recompute only 'prop' x_size = float( obj.getPropertyByName("grid_x_size") ) y_size = float( obj.getPropertyByName("grid_y_size") ) z_size = float( obj.getPropertyByName("grid_z_size") ) self.trans.translation.setValue( [ x_size/2, y_size/2, z_size/2 ] ) self.box.width.setValue( x_size ) self.box.height.setValue( y_size ) self.box.depth.setValue( z_size ) def getDisplayModes(self,obj): "Return a list of display modes." modes=[] modes.append("Shaded") modes.append("Wireframe") return modes def getDefaultDisplayMode(self): '''Return the name of the default display mode. It must be defined in getDisplayModes.''' return "Wireframe" def setDisplayMode(self,mode): return mode def onChanged(self, vp, prop): "Executed if any property is changed" if prop == "Color": c = vp.getPropertyByName("Color") self.color.rgb.setValue( c[0], c[1], c[2] ) def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None def generate_config_part( self ): conf_part = [] conf_part.append( "[SpatialMesh]\n" ) export_property_names = [ "grid_x_size", "grid_x_step", "grid_y_size", "grid_y_step", "grid_z_size", "grid_z_step" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part class BoundaryConditionsConfigPart(): """Properties and representation of boundary_conditions config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "boundary_phi_left", "Boundary conditions", "Potential on left boundary").boundary_phi_left = "0.0" obj.addProperty( "App::PropertyString", "boundary_phi_right", "Boundary conditions", "Potential on right boundary").boundary_phi_right = "0.0" obj.addProperty( "App::PropertyString", "boundary_phi_top", "Boundary conditions", "Potential on top boundary").boundary_phi_top = "0.0" obj.addProperty( "App::PropertyString", "boundary_phi_bottom", "Boundary conditions", "Potential on bottom boundary").boundary_phi_bottom = "0.0" obj.addProperty( "App::PropertyString", "boundary_phi_near", "Boundary conditions", "Potential on near boundary").boundary_phi_near = "0.0" obj.addProperty( "App::PropertyString", "boundary_phi_far", "Boundary conditions", "Potential on far boundary").boundary_phi_far = "0.0" obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): '''Setup the scene sub-graph of the view provider, this method is mandatory''' return def generate_config_part( self ): conf_part = [] conf_part.append( "[BoundaryConditions]\n" ) export_property_names = [ "boundary_phi_left", "boundary_phi_right", "boundary_phi_top" , "boundary_phi_bottom", "boundary_phi_near", "boundary_phi_far" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None class MagneticFieldConfigPart(): """Properties and representation of magnetic_field config part""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "magnetic_field_x", "External magnetic field", "Field magnitude along X axis").magnetic_field_x = "0.0" obj.addProperty( "App::PropertyString", "magnetic_field_y", "External magnetic field", "Field magnitude along Y axis").magnetic_field_y = "0.0" obj.addProperty( "App::PropertyString", "magnetic_field_z", "External magnetic field", "Field magnitude along Z axis").magnetic_field_z = "0.0" obj.addProperty( "App::PropertyString", "speed_of_light", "External magnetic field", "Speed of light").speed_of_light = "3.0e10" obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): '''Setup the scene sub-graph of the view provider, this method is mandatory''' return def generate_config_part( self ): conf_part = [] conf_part.append( "[ExternalMagneticField]\n" ) export_property_names = [ "magnetic_field_x", "magnetic_field_y", "magnetic_field_z", "speed_of_light" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None class ParticleSourceConfigPart(): """Particle source region""" def __init__( self, obj ): obj.addProperty( "App::PropertyEnumeration", "individual_charge_or_total_current", "Base", "Specify particles' charge or total source current") obj.individual_charge_or_total_current = ["Particles' charge", "Source current"] obj.addProperty( "App::PropertyEnumeration", "mass_or_charge_to_mass", "Base", "Specify particles' mass or charge-to-mass ratio") obj.mass_or_charge_to_mass = [ "Mass", "Charge-to-mass" ] obj.addProperty( "App::PropertyString", "initial_number_of_particles", "Number of particles", "Initial number of particles" ).initial_number_of_particles = "1000" obj.addProperty( "App::PropertyString", "particles_to_generate_each_step", "Number of particles", "Number of particles to add at each time step" ).particles_to_generate_each_step = "1000" obj.addProperty( "App::PropertyString", "current", "Number of particles", "I = q * N / dt" ).current = "10" # default value is unimportant; it will be recalculated. obj.addProperty( "App::PropertyString", "box_x_left", "Position", "Position of the left side of the source" ).box_x_left = "0.6" obj.addProperty( "App::PropertyString", "box_x_right", "Position", "Position of the right side of the source" ).box_x_right = "0.4" obj.addProperty( "App::PropertyString", "box_y_bottom", "Position", "Position of the bottom side of the source" ).box_y_bottom = "0.4" obj.addProperty( "App::PropertyString", "box_y_top", "Position", "Position of the top side of the source" ).box_y_top = "0.6" obj.addProperty( "App::PropertyString", "box_z_near", "Position", "Position of the near side of the source" ).box_z_near = "0.4" obj.addProperty( "App::PropertyString", "box_z_far", "Position", "Position of the far side of the source" ).box_z_far = "0.6" obj.addProperty( "App::PropertyString", "mean_momentum_x", "Momentum", "Mean momentum in X direction" ).mean_momentum_x = "1.0" obj.addProperty( "App::PropertyString", "mean_momentum_y", "Momentum", "Mean momentum in Y direction" ).mean_momentum_y = "1.0" obj.addProperty( "App::PropertyString", "mean_momentum_z", "Momentum", "Mean momentum in Z direction" ).mean_momentum_z = "1.0" obj.addProperty( "App::PropertyString", "temperature", "Momentum", "Temperature" ).temperature = "1.0" obj.addProperty( "App::PropertyString", "charge", "Particle properties", "Particles' charge" ).charge = "1.0" obj.addProperty( "App::PropertyString", "mass", "Particle properties", "Particles' mass (calculated automatically from q and q/m)" ).mass = "1.0" obj.addProperty( "App::PropertyString", "charge_to_mass_ratio", "Particle properties", "Particles' charge to mass ratio" ).charge_to_mass_ratio = "1.0" obj.ViewObject.addProperty( "App::PropertyColor", "Color", "Spatial mesh", "Volume box color").Color=(0.0, 0.0, 1.0) obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute( self, obj ): '''Executed when document is recomputated. This method is mandatory''' dt = self.get_time_step( obj ) N = int( obj.particles_to_generate_each_step ) individual_charge_or_total_current = obj.getPropertyByName( "individual_charge_or_total_current") mass_or_charge_to_mass = obj.getPropertyByName( "mass_or_charge_to_mass") if individual_charge_or_total_current == "Particles' charge": # todo: make certain fields read-only # e.g., obj.setEditorMode( "current", readonly ) q = float( obj.charge ) I = q * N / dt obj.current = str( I ) elif individual_charge_or_total_current == "Source current": I = float( obj.current ) q = I * dt / N obj.charge = str( q ) if mass_or_charge_to_mass == "Mass": # todo: make certain fields read-only # e.g., obj.setEditorMode( "current", readonly ) m = float( obj.mass ) q_to_m = q / m obj.charge_to_mass_ratio = str( q_to_m ) elif mass_or_charge_to_mass == "Charge-to-mass": q_to_m = float( obj.charge_to_mass_ratio ) m = abs( 1 / q_to_m * q ) obj.mass = str( m ) return def attach(self, obj): self.shaded = coin.SoGroup() self.wireframe = coin.SoGroup() self.trans = coin.SoTranslation() self.color = coin.SoBaseColor() self.box = coin.SoCube() self.shaded.addChild( self.color ) self.shaded.addChild( self.trans ) self.shaded.addChild( self.box ) obj.addDisplayMode( self.shaded, "Shaded" ) style = coin.SoDrawStyle() style.style = coin.SoDrawStyle.LINES self.wireframe.addChild( style ) self.wireframe.addChild( self.color ) self.wireframe.addChild( self.trans ) self.wireframe.addChild( self.box ) obj.addDisplayMode( self.wireframe, "Wireframe" ) self.onChanged( obj, "Color" ) return def updateData( self, obj, prop ): "Executed when propery in field 'data' is changed" # todo: move charge-current recomputation here from 'execute' x0 = float( obj.getPropertyByName("box_x_right") ) y0 = float( obj.getPropertyByName("box_y_bottom") ) z0 = float( obj.getPropertyByName("box_z_near") ) xlen = float( obj.getPropertyByName("box_x_left") ) - x0 ylen = float( obj.getPropertyByName("box_y_top") ) - y0 zlen = float( obj.getPropertyByName("box_z_far") ) - z0 self.trans.translation.setValue( [ x0 + xlen / 2, y0 + ylen / 2, z0 + zlen / 2 ] ) self.box.width.setValue( xlen ) self.box.height.setValue( ylen ) self.box.depth.setValue( zlen ) return def getDisplayModes(self,obj): "Return a list of display modes." modes=[] modes.append("Shaded") modes.append("Wireframe") return modes def getDefaultDisplayMode(self): '''Return the name of the default display mode. It must be defined in getDisplayModes.''' return "Wireframe" def setDisplayMode(self,mode): return mode def onChanged(self, vp, prop): "Executed if any property is changed" if prop == "Color": c = vp.getPropertyByName("Color") self.color.rgb.setValue( c[0], c[1], c[2] ) def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None def get_time_step( self, obj ): # todo: to get dt, get object named "Time_grid" from the first # group which the source belongs to. # Instead, pass reference to "Time_grid" object in the source-constructor. # todo: source properties are not recomputed when dt is changed. do something about it. dt = float( obj.InList[0].getObject("Time_grid").getPropertyByName("time_step_size") ) return dt def generate_config_part( self ): conf_part = [] source_name = self.doc_object.getPropertyByName( "Label" ) conf_part.append( "[ParticleSourceBox.{0}]\n".format( source_name ) ) export_property_names = [ "initial_number_of_particles", "particles_to_generate_each_step", "box_x_left", "box_x_right", "box_y_bottom", "box_y_top", "box_z_near", "box_z_far", "mean_momentum_x", "mean_momentum_y", "mean_momentum_z", "temperature", "charge", "mass" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) comments = [ "individual_charge_or_total_current", "mass_or_charge_to_mass", "charge_to_mass_ratio", "current" ] for x in comments: conf_part.append( ";{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part class ParticleCylindricalSourceConfigPart(): """Particle cylindrical source region""" def __init__( self, obj ): obj.addProperty( "App::PropertyEnumeration", "individual_charge_or_total_current", "Base", "Specify particles' charge or total source current") obj.individual_charge_or_total_current = ["Particles' charge", "Source current"] obj.addProperty( "App::PropertyEnumeration", "mass_or_charge_to_mass", "Base", "Specify particles' mass or charge-to-mass ratio") obj.mass_or_charge_to_mass = [ "Mass", "Charge-to-mass" ] obj.addProperty( "App::PropertyString", "initial_number_of_particles", "Number of particles", "Initial number of particles" ).initial_number_of_particles = "1000" obj.addProperty( "App::PropertyString", "particles_to_generate_each_step", "Number of particles", "Number of particles to add at each time step" ).particles_to_generate_each_step = "1000" obj.addProperty( "App::PropertyString", "current", "Number of particles", "I = q * N / dt" ).current = "10" # default value is unimportant; # it will be recalculated. ### Size obj.addProperty( "App::PropertyEnumeration", "cylinder_axis_direction", "Size", "Cylinder along axis").cylinder_axis_direction = ["X", "Y", "Z"] obj.addProperty( "App::PropertyString", "cylinder_length", "Size", "Cylinder axis length").cylinder_length = "0.5" obj.addProperty( "App::PropertyString", "cylinder_radius", "Size", "Cylinder radius" ).cylinder_radius = "0.05" ### obj.addProperty( "App::PropertyString", "cylinder_axis_start_x", "Size", "Position of the left side of the source" ).cylinder_axis_start_x = "0.0" obj.addProperty( "App::PropertyString", "cylinder_axis_start_y", "Size", "Position of the right side of the source" ).cylinder_axis_start_y = "0.0" obj.addProperty( "App::PropertyString", "cylinder_axis_start_z", "Size", "Position of the bottom side of the source" ).cylinder_axis_start_z = "0.0" obj.addProperty( "App::PropertyString", "cylinder_axis_end_x", "Size", "Position of the top side of the source" ).cylinder_axis_end_x = "0.2" obj.addProperty( "App::PropertyString", "cylinder_axis_end_y", "Size", "Position of the near side of the source" ).cylinder_axis_end_y = "0.2" obj.addProperty( "App::PropertyString", "cylinder_axis_end_z", "Size", "Position of the far side of the source" ).cylinder_axis_end_z = "0.3" ### obj.addProperty( "App::PropertyString", "mean_momentum_x", "Momentum", "Mean momentum in X direction" ).mean_momentum_x = "1.0" obj.addProperty( "App::PropertyString", "mean_momentum_y", "Momentum", "Mean momentum in Y direction" ).mean_momentum_y = "1.0" obj.addProperty( "App::PropertyString", "mean_momentum_z", "Momentum", "Mean momentum in Z direction" ).mean_momentum_z = "1.0" obj.addProperty( "App::PropertyString", "temperature", "Momentum", "Temperature" ).temperature = "1.0" obj.addProperty( "App::PropertyString", "charge", "Particle properties", "Particles' charge" ).charge = "1.0" obj.addProperty( "App::PropertyString", "mass", "Particle properties", "Particles' mass (calculated automatically from q and q/m)" ).mass = "1.0" obj.addProperty( "App::PropertyString", "charge_to_mass_ratio", "Particle properties", "Particles' charge to mass ratio" ).charge_to_mass_ratio = "1.0" obj.ViewObject.addProperty( "App::PropertyColor", "Color", "Spatial mesh", "Volume box color").Color=(0.0, 0.0, 1.0) # hide axis-end obj.setEditorMode( "cylinder_axis_end_x", 1 ) obj.setEditorMode( "cylinder_axis_end_y", 1 ) obj.setEditorMode( "cylinder_axis_end_z", 1 ) obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute( self, obj ): '''Executed when document is recomputated. This method is mandatory''' dt = self.get_time_step( obj ) N = int( obj.particles_to_generate_each_step ) individual_charge_or_total_current = obj.getPropertyByName( "individual_charge_or_total_current") mass_or_charge_to_mass = obj.getPropertyByName( "mass_or_charge_to_mass") if individual_charge_or_total_current == "Particles' charge": # todo: make certain fields read-only # e.g., obj.setEditorMode( "current", readonly ) q = float( obj.charge ) I = q * N / dt obj.current = str( I ) elif individual_charge_or_total_current == "Source current": I = float( obj.current ) q = I * dt / N obj.charge = str( q ) if mass_or_charge_to_mass == "Mass": # todo: make certain fields read-only # e.g., obj.setEditorMode( "current", readonly ) m = float( obj.mass ) q_to_m = q / m obj.charge_to_mass_ratio = str( q_to_m ) elif mass_or_charge_to_mass == "Charge-to-mass": q_to_m = float( obj.charge_to_mass_ratio ) m = abs( 1 / q_to_m * q ) obj.mass = str( m ) cylinder_axis_direction = obj.cylinder_axis_direction cylinder_length = float( obj.cylinder_length ) cylinder_axis_start_x = float( obj.cylinder_axis_start_x ) cylinder_axis_start_y = float( obj.cylinder_axis_start_y ) cylinder_axis_start_z = float( obj.cylinder_axis_start_z ) if cylinder_axis_direction == 'X': obj.cylinder_axis_end_x = str( cylinder_axis_start_x + cylinder_length ) obj.cylinder_axis_end_y = str( cylinder_axis_start_y ) obj.cylinder_axis_end_z = str( cylinder_axis_start_z ) elif cylinder_axis_direction == 'Y': obj.cylinder_axis_end_x = str( cylinder_axis_start_x ) obj.cylinder_axis_end_y = str( cylinder_axis_start_y + cylinder_length ) obj.cylinder_axis_end_z = str( cylinder_axis_start_z ) elif cylinder_axis_direction == 'Z': obj.cylinder_axis_end_x = str( cylinder_axis_start_x ) obj.cylinder_axis_end_y = str( cylinder_axis_start_y ) obj.cylinder_axis_end_z = str( cylinder_axis_start_z + cylinder_length ) return def attach(self, obj): self.trans = coin.SoTranslation() self.rot_xyz = coin.SoRotationXYZ() self.color = coin.SoBaseColor() self.cyl = coin.SoCylinder() self.shaded = coin.SoGroup() self.shaded.addChild( self.color ) self.shaded.addChild( self.trans ) self.shaded.addChild( self.rot_xyz ) self.shaded.addChild( self.cyl ) obj.addDisplayMode( self.shaded, "Shaded" ) style = coin.SoDrawStyle() style.style = coin.SoDrawStyle.LINES self.wireframe = coin.SoGroup() self.wireframe.addChild( style ) self.wireframe.addChild( self.color ) self.wireframe.addChild( self.trans ) self.wireframe.addChild( self.rot_xyz ) self.wireframe.addChild( self.cyl ) obj.addDisplayMode( self.wireframe, "Wireframe" ) self.onChanged( obj, "Color" ) return def updateData( self, obj, prop ): "Executed when propery in field 'data' is changed" cylinder_axis_direction = obj.getPropertyByName("cylinder_axis_direction") cylinder_length = float( obj.getPropertyByName("cylinder_length") ) cylinder_radius = float( obj.getPropertyByName("cylinder_radius") ) cylinder_axis_start_x = float( obj.getPropertyByName("cylinder_axis_start_x") ) cylinder_axis_start_y = float( obj.getPropertyByName("cylinder_axis_start_y") ) cylinder_axis_start_z = float( obj.getPropertyByName("cylinder_axis_start_z") ) if cylinder_axis_direction == 'X': self.rot_xyz.axis.setValue( 2 ) self.rot_xyz.angle.setValue( pi / 2 ) self.trans.translation.setValue( [ cylinder_axis_start_x + cylinder_length / 2, cylinder_axis_start_y, cylinder_axis_start_z ] ) elif cylinder_axis_direction == 'Y': self.rot_xyz.axis.setValue( 1 ) self.rot_xyz.angle.setValue( 0 ) self.trans.translation.setValue( [ cylinder_axis_start_x, cylinder_axis_start_y + cylinder_length / 2, cylinder_axis_start_z ] ) elif cylinder_axis_direction == 'Z': self.rot_xyz.axis.setValue( 0 ) self.rot_xyz.angle.setValue( pi / 2 ) self.trans.translation.setValue( [ cylinder_axis_start_x, cylinder_axis_start_y, cylinder_axis_start_z + cylinder_length / 2 ] ) self.cyl.radius.setValue( cylinder_radius ) self.cyl.height.setValue( cylinder_length ) return def getDisplayModes(self,obj): "Return a list of display modes." modes=[] modes.append("Shaded") modes.append("Wireframe") return modes def getDefaultDisplayMode(self): '''Return the name of the default display mode. It must be defined in getDisplayModes.''' return "Wireframe" def setDisplayMode(self,mode): return mode def onChanged(self, vp, prop): "Executed if any property is changed" if prop == "Color": c = vp.getPropertyByName("Color") self.color.rgb.setValue( c[0], c[1], c[2] ) def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None def get_time_step( self, obj ): # todo: to get dt, get object named "Time_grid" from the first # group which the source belongs to. # Instead, pass reference to "Time_grid" object in the source-constructor. # todo: source properties are not recomputed when dt is changed. # do something about it. dt = float( obj.InList[0].getObject("Time_grid").getPropertyByName("time_step_size") ) return dt def generate_config_part( self ): conf_part = [] source_name = self.doc_object.getPropertyByName( "Label" ) conf_part.append( "[ParticleSourceCylinder.{0}]\n".format( source_name ) ) export_property_names = [ "initial_number_of_particles", "particles_to_generate_each_step", "cylinder_axis_start_x", "cylinder_axis_start_y", "cylinder_axis_start_z", "cylinder_axis_end_x", "cylinder_axis_end_y", "cylinder_axis_end_z", "cylinder_radius", "mean_momentum_x", "mean_momentum_y", "mean_momentum_z", "temperature", "charge", "mass" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) comments = [ "individual_charge_or_total_current", "mass_or_charge_to_mass", "charge_to_mass_ratio", "current", "cylinder_axis_direction", "cylinder_length" ] for x in comments: conf_part.append( ";{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part class InnerRegionBoxConfigPart(): """Box inner region""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "box_x_right", "Position", "Box right side position" ).box_x_right = "0.1" obj.addProperty( "App::PropertyString", "box_x_left", "Position", "Box left side position" ).box_x_left = "0.9" obj.addProperty( "App::PropertyString", "box_y_bottom", "Position", "Box bottom side position" ).box_y_bottom = "0.1" obj.addProperty( "App::PropertyString", "box_y_top", "Position", "Box top side position" ).box_y_top = "0.9" obj.addProperty( "App::PropertyString", "box_z_near", "Position", "Box near side position" ).box_z_near = "0.1" obj.addProperty( "App::PropertyString", "box_z_far", "Position", "Box far side position" ).box_z_far = "0.2" obj.addProperty( "App::PropertyString", "potential", "Potential", "Inner region potential" ).potential = "0.0" obj.ViewObject.addProperty( "App::PropertyColor", "Color", "Inner region color", "Inner region color").Color=(0.5, 0.5, 0.0) obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): return def attach(self, obj): self.shaded = coin.SoGroup() self.wireframe = coin.SoGroup() self.trans = coin.SoTranslation() self.color = coin.SoBaseColor() self.box = coin.SoCube() self.shaded.addChild( self.color ) self.shaded.addChild( self.trans ) self.shaded.addChild( self.box ) obj.addDisplayMode( self.shaded, "Shaded" ) style = coin.SoDrawStyle() style.style = coin.SoDrawStyle.LINES self.wireframe.addChild( style ) self.wireframe.addChild( self.color ) self.wireframe.addChild( self.trans ) self.wireframe.addChild( self.box ) obj.addDisplayMode( self.wireframe, "Wireframe" ) self.onChanged( obj, "Color" ) return def updateData(self, obj, prop ): "Executed when propery in field 'data' is changed" x0 = float( obj.getPropertyByName("box_x_right") ) y0 = float( obj.getPropertyByName("box_y_bottom") ) z0 = float( obj.getPropertyByName("box_z_near") ) xlen = float( obj.getPropertyByName("box_x_left") ) - x0 ylen = float( obj.getPropertyByName("box_y_top") ) - y0 zlen = float( obj.getPropertyByName("box_z_far") ) - z0 self.trans.translation.setValue( [ x0 + xlen / 2, y0 + ylen / 2, z0 + zlen / 2 ] ) self.box.width.setValue( xlen ) self.box.height.setValue( ylen ) self.box.depth.setValue( zlen ) def getDisplayModes(self,obj): "Return a list of display modes." modes=[] modes.append("Shaded") modes.append("Wireframe") return modes def getDefaultDisplayMode(self): '''Return the name of the default display mode. It must be defined in getDisplayModes.''' return "Shaded" def setDisplayMode(self,mode): return mode def onChanged(self, vp, prop): "Executed if any property is changed" if prop == "Color": c = vp.getPropertyByName("Color") self.color.rgb.setValue( c[0],c[1],c[2] ) def __getstate__(self): doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None def generate_config_part( self ): conf_part = [] conf_part.append( "[InnerRegionBox.{0}]\n".format( self.doc_object.getPropertyByName( "Label" ) ) ) export_property_names = [ "box_x_left", "box_x_right", "box_y_bottom", "box_y_top", "box_z_near", "box_z_far", "potential" ] for x in export_property_names: conf_part.append( "{0} = {1}\n".format( x, self.doc_object.getPropertyByName( x ) ) ) conf_part.append("\n") return conf_part class RunEfConfig: """Parameters to run computation""" def __init__( self, obj ): obj.addProperty( "App::PropertyString", "current_workdir", "Run Parameters", "Path to working directory" ).current_workdir = os.getcwd() obj.setEditorMode( "current_workdir", 1 ) obj.addProperty( "App::PropertyString", "change_workdir_to", "Run Parameters", "Path to working directory" ).change_workdir_to = "/tmp/" obj.addProperty( "App::PropertyString", "command", "Run Parameters", "Command to execute" ).command = "./ef.out test.conf" obj.Proxy = self obj.ViewObject.Proxy = self self.doc_object = obj self.view_object = obj.ViewObject def execute(self, fp): '''Executed when document is recomputated. This method is mandatory''' return def updateData(self, fp, prop): '''If a property of the handled feature has changed we have the chance to handle this here''' return def attach(self, obj): ''' Setup the scene sub-graph of the view provider, this method is mandatory ''' return def __getstate__(self): '''When saving the document this object gets stored using Python's json module. Since we have some un-serializable parts here -- the Coin stuff -- we must define this method to return a tuple of all serializable objects or None.''' doc_object_name = self.doc_object.Name return { "doc_object_name": doc_object_name } def __setstate__(self, state): '''When restoring the serialized object from document we have the chance to set some internals here. Since no data were serialized nothing needs to be done here.''' doc_object_name = state[ "doc_object_name" ] self.doc_object = FreeCAD.ActiveDocument.getObject( doc_object_name ) self.view_object = self.doc_object.ViewObject return None def generate_config_part( self ): # no need to add something to config; return empty list # todo: avoid calling this method for this class return [] FreeCADGui.addCommand( 'CreateEfConfig', CreateEfConfig() ) FreeCADGui.addCommand( 'AddSourceRegion', AddSourceRegion() ) FreeCADGui.addCommand( 'AddCylindricalSource', AddCylindricalSource() ) FreeCADGui.addCommand( 'AddInnerRegionBox', AddInnerRegionBox() ) FreeCADGui.addCommand( 'GenerateConfFile', GenerateConfFile() ) FreeCADGui.addCommand( 'RunEf', RunEf() )

38.685829

102

0.578429

6,358

57,874

5.048128

0.067789

0.031967

0.037606

0.06278

0.816737

0.785643

0.758038

0.736073

0.683855

0.66946

0

0.006333

0.323323

57,874

1,495

103

38.711706

0.813237

0.120745

0

0.768166

0

0.201945

0.028585

0

0.005351

0

1

0.093426

false

0

0.006055

0.192042

0

null

0

1

0

1

0

1

0

null

0

6

2aa63dd82f508e9240a1d2542bd18c69d46d55de

134

py

Python

src/Domains/__init__.py

MarcelFox/api-modelo

1ca862446893d0f0d079cde1b10931b8fd188c57

[ "CC0-1.0" ]

1

2020-09-29T14:55:08.000Z

src/Domains/__init__.py

MarcelFox/api-modelo

1ca862446893d0f0d079cde1b10931b8fd188c57

[ "CC0-1.0" ]

null

src/Domains/__init__.py

MarcelFox/api-modelo

1ca862446893d0f0d079cde1b10931b8fd188c57

[ "CC0-1.0" ]

null

from .File.Controller import FileController from .File.Service import FileService # from .File.Repository import RepositoryController

33.5

51

0.850746

15

134

7.6

0.6

0.210526

0

0.097015

134

3

52

44.666667

0.942149

0.365672

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

2aac48af090d8f87d2477053e500b4d733aa29aa

466

py

Python

ports/esp32/modules/ili9341.py

amirgon/lv_mpy

9b4e5b35d809380efd397f0287aa22957071d978

[ "MIT" ]

150

2020-05-24T17:42:24.000Z

2022-03-28T12:47:53.000Z

ports/esp32/modules/ili9341.py

amirgon/lv_mpy

9b4e5b35d809380efd397f0287aa22957071d978

[ "MIT" ]

24

2020-05-19T10:46:39.000Z

2022-01-25T22:47:44.000Z

ports/esp32/modules/ili9341.py

amirgon/lv_mpy

9b4e5b35d809380efd397f0287aa22957071d978

[ "MIT" ]

81

2020-05-19T03:57:34.000Z

2022-03-18T03:34:08.000Z

############################################################################## # # Wrapper function for backward compatibility with new ILI9XXX library. # ############################################################################## print(""" *************************************** * This library is obsoled now! * Please, use ili9XXX library instead: * * from ili9XXX import ili9341 * *************************************** """) from ili9XXX import ili9341

24.526316

78

0.356223

28

466

5.928571

0.714286

0.168675

0.204819

0.289157

0

0.028571

0.098712

466

18

79

25.888889

0.366667

0.148069

0

0.2

0

0.790598

0.333333

0

1

0

true

0

0.2

0

0.2

0.1

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

6300e0b878545e3f2ee0f5a213236791c6ae0cae

44

py

Python

tradester/feeds/__init__.py

wrieg123/tradester

440210940f80e94fde4d43841c729f63b05f597d

[ "MIT" ]

5

2020-11-11T14:54:59.000Z

2020-11-13T04:00:25.000Z

tradester/feeds/__init__.py

wrieg123/tradester

440210940f80e94fde4d43841c729f63b05f597d

[ "MIT" ]

null

tradester/feeds/__init__.py

wrieg123/tradester

440210940f80e94fde4d43841c729f63b05f597d

[ "MIT" ]

null

from .active import * from .static import *

14.666667

21

0.727273

6

44

5.333333

0.666667

0

0.181818

44

2

22

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

63126686eebae63ae76aa5c37157b70be17b435d

3,571

py

Python

imcsdk/mometa/storage/StorageControllerHealth.py

ecoen66/imcsdk

b10eaa926a5ee57cea7182ae0adc8dd1c818b0ab

[ "Apache-2.0" ]

31

2016-06-14T07:23:59.000Z

2021-09-12T17:17:26.000Z

imcsdk/mometa/storage/StorageControllerHealth.py

sthagen/imcsdk

1831eaecb5960ca03a8624b1579521749762b932

[ "Apache-2.0" ]

109

2016-05-25T03:56:56.000Z

2021-10-18T02:58:12.000Z

imcsdk/mometa/storage/StorageControllerHealth.py

sthagen/imcsdk

1831eaecb5960ca03a8624b1579521749762b932

[ "Apache-2.0" ]

67

2016-05-17T05:53:56.000Z

2022-03-24T15:52:53.000Z

"""This module contains the general information for StorageControllerHealth ManagedObject.""" from ...imcmo import ManagedObject from ...imccoremeta import MoPropertyMeta, MoMeta from ...imcmeta import VersionMeta class StorageControllerHealthConsts: pass class StorageControllerHealth(ManagedObject): """This is StorageControllerHealth class.""" consts = StorageControllerHealthConsts() naming_props = set([]) mo_meta = { "classic": MoMeta("StorageControllerHealth", "storageControllerHealth", "controller-health", VersionMeta.Version2013e, "OutputOnly", 0xf, [], ["admin", "read-only", "user"], ['storageController'], [], ["Get"]), "modular": MoMeta("StorageControllerHealth", "storageControllerHealth", "controller-health", VersionMeta.Version2013e, "OutputOnly", 0xf, [], ["admin", "read-only", "user"], ['storageController'], [], ["Get"]) } prop_meta = { "classic": { "child_action": MoPropertyMeta("child_action", "childAction", "string", VersionMeta.Version2013e, MoPropertyMeta.INTERNAL, None, None, None, None, [], []), "dn": MoPropertyMeta("dn", "dn", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x2, 0, 255, None, [], []), "health": MoPropertyMeta("health", "health", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, None, 0, 510, None, [], []), "id": MoPropertyMeta("id", "id", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, None, 0, 510, None, [], []), "rn": MoPropertyMeta("rn", "rn", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x4, 0, 255, None, [], []), "status": MoPropertyMeta("status", "status", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x8, None, None, None, ["", "created", "deleted", "modified", "removed"], []), }, "modular": { "child_action": MoPropertyMeta("child_action", "childAction", "string", VersionMeta.Version2013e, MoPropertyMeta.INTERNAL, None, None, None, None, [], []), "dn": MoPropertyMeta("dn", "dn", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x2, 0, 255, None, [], []), "health": MoPropertyMeta("health", "health", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, None, 0, 510, None, [], []), "id": MoPropertyMeta("id", "id", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, None, 0, 510, None, [], []), "rn": MoPropertyMeta("rn", "rn", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x4, 0, 255, None, [], []), "status": MoPropertyMeta("status", "status", "string", VersionMeta.Version2013e, MoPropertyMeta.READ_ONLY, 0x8, None, None, None, ["", "created", "deleted", "modified", "removed"], []), }, } prop_map = { "classic": { "childAction": "child_action", "dn": "dn", "health": "health", "id": "id", "rn": "rn", "status": "status", }, "modular": { "childAction": "child_action", "dn": "dn", "health": "health", "id": "id", "rn": "rn", "status": "status", }, } def __init__(self, parent_mo_or_dn, **kwargs): self._dirty_mask = 0 self.child_action = None self.health = None self.id = None self.status = None ManagedObject.__init__(self, "StorageControllerHealth", parent_mo_or_dn, **kwargs)

46.376623

218

0.605713

317

3,571

6.706625

0.22082

0.151458

0.163688

0.242709

0.752587

0.735654

0

0.036891

0.218146

3,571

76

219

46.986842

0.72457

0.035284

0

0.509091

0

0.20769

0.033498

0

0.006991

0

1

0.018182

false

0.018182

0.054545

0

0.2

0

null

0

1

0

1

0

null

0

6

6317ca905effd6bb713f614fbc8008b2f6731854

41

py

Python

botTest.py

JacobJW/MakeNutritionGreatAgain

d26df0f039cf6120f1ab5e533a0e58879382e911

[ "MIT" ]

null

botTest.py

JacobJW/MakeNutritionGreatAgain

d26df0f039cf6120f1ab5e533a0e58879382e911

[ "MIT" ]

null

botTest.py

JacobJW/MakeNutritionGreatAgain

d26df0f039cf6120f1ab5e533a0e58879382e911

[ "MIT" ]

null

def excite(s: str): return s.upper()

13.666667

20

0.609756

7

41

3.571429

0.857143

0

0.219512

41

2

21

20.5

0.78125

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

631b5d482c8dc668a5f99c21645ce3e6e61a9ceb

10,197

py

Python

knee/evaluation.py

Yifei-Liu/knee

7c2c7092a2c2dc4c4dac5ebc3b623c5725e0339b

[ "MIT" ]

null

knee/evaluation.py

Yifei-Liu/knee

7c2c7092a2c2dc4c4dac5ebc3b623c5725e0339b

[ "MIT" ]

null

knee/evaluation.py

Yifei-Liu/knee

7c2c7092a2c2dc4c4dac5ebc3b623c5725e0339b

[ "MIT" ]

null

# coding: utf-8 __author__ = 'Mário Antunes' __version__ = '0.1' __email__ = 'mariolpantunes@gmail.com' __status__ = 'Development' import enum import math import logging import numpy as np import knee.linear_fit as lf logger = logging.getLogger(__name__) class Strategy(enum.Enum): """ Enum data type that represents the strategy of MAE, MSE and RMSE """ knees = 'knees' expected = 'expected' best = 'best' worst = 'worst' def __str__(self): return self.value def get_neighbourhood_points(points: np.ndarray, a: int, b: int, t: float) -> tuple: """Get the neighbourhood (closest points) from a to b. The neighbourhood is defined as the longest straitgh line (defined by R2). Args: points (np.ndarray): numpy array with the points (x, y) a (int): the initial point of the search b (int): the left limit of the search t (float): R2 threshold Returns: tuple: (neighbourhood index, r2, slope) """ x = points[:, 0] y = points[:, 1] return get_neighbourhood(x, y, a, b, t) def get_neighbourhood(x: np.ndarray, y: np.ndarray, a: int, b: int, t: float = 0.7) -> tuple: """Get the neighbourhood (closest points) from a to b. The neighbourhood is defined as the longest straitgh line (defined by R2). Args: x (np.ndarray): the value of the points in the x axis coordinates y (np.ndarray): the value of the points in the y axis coordinates a (int): the initial point of the search b (int): the left limit of the search t (float): R2 threshold Returns: tuple: (neighbourhood index, r2, slope) """ r2 = 1.0 i = a - 1 _, slope = lf.linear_fit(x[i:a+1], y[i:a+1]) while r2 > t and i > b: previous_res = (i, r2, slope) i -= 1 coef = lf.linear_fit(x[i:a+1], y[i:a+1]) r2 = lf.linear_r2(x[i:a+1], y[i:a+1], coef) _, slope = coef if r2 > t: return i, r2, slope else: return previous_res def accuracy_knee(points: np.ndarray, knees: np.ndarray) -> tuple: """Compute the accuracy heuristic for a set of knees. The heuristic is based on the average distance of X and Y axis, the slope and the R2. In this version it is used the left neighbourhood of the knee. Args: points (np.ndarray): numpy array with the points (x, y) knees (np.ndarray): knees indexes Returns: tuple: (average_x, average_y, average_slope, average_coeffients, cost) """ x = points[:, 0] y = points[:, 1] total_x = math.fabs(x[-1] - x[0]) total_y = math.fabs(y[-1] - y[0]) distances_x = [] distances_y = [] slopes = [] coeffients = [] previous_knee = 0 for i in range(len(knees)): idx, r2, slope = get_neighbourhood(x, y, knees[i], previous_knee) delta_x = x[idx] - x[knees[i]] delta_y = y[idx] - y[knees[i]] distances_x.append(math.fabs(delta_x)) distances_y.append(math.fabs(delta_y)) slopes.append(math.fabs(slope)) coeffients.append(r2) previous_knee = knees[i] slopes = np.array(slopes) slopes = slopes/slopes.max() coeffients = np.array(coeffients) coeffients = coeffients/coeffients.max() distances_x = np.array(distances_x)/total_x distances_y = np.array(distances_y)/total_y average_x = np.average(distances_x) average_y = np.average(distances_y) average_slope = np.average(slopes) average_coeffients = np.average(coeffients) #p = slopes * distances_y * coeffients p = slopes * distances_y #cost = (average_x * average_y) / (average_slope) cost = average_x / np.average(p) return average_x, average_y, average_slope, average_coeffients, cost def accuracy_trace(points: np.ndarray, knees: np.ndarray) -> tuple: """Compute the accuracy heuristic for a set of knees. The heuristic is based on the average distance of X and Y axis, the slope and the R2. In this version it is used the points from the current knee to the previous. Args: points (np.ndarray): numpy array with the points (x, y) knees (np.ndarray): knees indexes Returns: tuple: (average_x, average_y, average_slope, average_coeffients, cost) """ x = points[:, 0] y = points[:, 1] distances_x = [] distances_y = [] slopes = [] coeffients = [] total_x = math.fabs(x[-1] - x[0]) total_y = math.fabs(y[-1] - y[0]) previous_knee_x = x[knees[0]] previous_knee_y = y[knees[0]] delta_x = x[0] - previous_knee_x delta_y = y[0] - previous_knee_y distances_x.append(math.fabs(delta_x)) distances_y.append(math.fabs(delta_y)) coef = lf.linear_fit(x[0:knees[0]+1], y[0:knees[0]+1]) r2 = lf.linear_r2(x[0:knees[0]+1], y[0:knees[0]+1], coef) coeffients.append(r2) _, slope = coef slopes.append(math.fabs(slope)) for i in range(1, len(knees)): knee_x = x[knees[i]] knee_y = y[knees[i]] delta_x = previous_knee_x - knee_x delta_y = previous_knee_y - knee_y coef = lf.linear_fit(x[knees[i-1]:knees[i]+1], y[knees[i-1]:knees[i]+1]) r2 = lf.linear_r2(x[knees[i-1]:knees[i]+1], y[knees[i-1]:knees[i]+1], coef) distances_x.append(math.fabs(delta_x)) distances_y.append(math.fabs(delta_y)) _, slope = coef slopes.append(math.fabs(slope)) coeffients.append(r2) previous_knee_x = knee_x previous_knee_y = knee_y distances_x = np.array(distances_x)/total_x distances_y = np.array(distances_y)/total_y slopes = np.array(slopes) slopes = slopes/slopes.max() coeffients = np.array(coeffients) coeffients = coeffients/coeffients.max() coeffients[coeffients < 0] = 0.0 p = slopes * distances_y * coeffients #p = slopes * distances_y average_x = np.average(distances_x) average_y = np.average(distances_y) average_slope = np.average(slopes) average_coeffients = np.average(coeffients) cost = average_x / np.average(p) return average_x, average_y, average_slope, average_coeffients, cost def mae(points: np.ndarray, knees: np.ndarray, expected: np.ndarray, s: Strategy = Strategy.expected) -> float: """ Estimates the worst case Mean Absolute Error (MAE) for the given knee and expected points. Suppports different size arrays, and estimates the MAE based on the worst case. It uses the euclidean distance to find the closer points, and computes the error based on the closest point. Args: points (np.ndarray): numpy array with the points (x, y) knees (np.ndarray): knees indexes expected (np.ndarray): numpy array with the expected knee points (x, y) s (Strategy): enum that controls the point matching (default Strategy.expected) Returns: float: the worst case MAE """ # get the knee points knee_points = points[knees] error = 0.0 if s is Strategy.knees: a = knee_points b = expected elif s is Strategy.expected: a = expected b = knee_points elif s is Strategy.best: if len(expected) <= len(knee_points): a = expected b = knee_points else: a = knee_points b = expected else: if len(expected) >= len(knee_points): a = expected b = knee_points else: a = knee_points b = expected for p in a: distances = np.linalg.norm(b-p, axis=1) idx = np.argmin(distances) error += np.sum(np.abs(p-b[idx])) return error / (len(a)*2.0) def mse(points: np.ndarray, knees: np.ndarray, expected: np.ndarray, s: Strategy = Strategy.expected) -> float: """ Estimates the worst case Mean Squared Error (MSE) for the given knee and expected points. Suppports different size arrays, and estimates the MSE based on the worst case. It uses the euclidean distance to find the closer points, and computes the error based on the closest point. Args: points (np.ndarray): numpy array with the points (x, y) knees (np.ndarray): knees indexes expected (np.ndarray): numpy array with the expected knee points (x, y) s (Strategy): enum that controls the point matching (default Strategy.expected) Returns: float: the worst case MSE """ # get the knee points knee_points = points[knees] error = 0.0 if s is Strategy.knees: a = knee_points b = expected elif s is Strategy.expected: a = expected b = knee_points elif s is Strategy.best: if len(expected) <= len(knee_points): a = expected b = knee_points else: a = knee_points b = expected else: if len(expected) >= len(knee_points): a = expected b = knee_points else: a = knee_points b = expected for p in a: distances = np.linalg.norm(b-p, axis=1) idx = np.argmin(distances) error += np.sum(np.square(p-b[idx])) print(error) return error / (len(a)*2.0) def rmse(points: np.ndarray, knees: np.ndarray, expected: np.ndarray, s: Strategy = Strategy.expected) -> float: """ Estimates the worst case Root Mean Squared Error (RMSE) for the given knee and expected points. Suppports different size arrays, and estimates the RMSE based on the worst case. It uses the euclidean distance to find the closer points, and computes the error based on the closest point. Args: points (np.ndarray): numpy array with the points (x, y) knees (np.ndarray): knees indexes expected (np.ndarray): numpy array with the expected knee points (x, y) s (Strategy): enum that controls the point matching (default Strategy.expected) Returns: float: the worst case RMSE """ return math.sqrt(mse(points, knees, expected, s))

28.886686

112

0.618908

1,471

10,197

4.17947

0.104691

0.046845

0.029278

0.027814

0.822056

0.811809

0.782043

0.768543

0.759759

0.734873

0

0.012322

0.275767

10,197

352

113

28.96875

0.820176

0.352947

0

0.625

0

0.011729

0.003856

0

1

0.045455

false

0

0.028409

0.005682

0.153409

0.005682

0

null

0

1

0

null

0

6

2d4e41215c98a48e0964b2c092bc8164d49cf735

40

py

Python

Common/Python/Data-Structures/Hashs/__init__.py

MattiKemp/Data-Structures-And-Algorithms

37a4eb4f092f5a058643ef5ac302fe16d97f84dc

[ "Unlicense" ]

null

Common/Python/Data-Structures/Hashs/__init__.py

MattiKemp/Data-Structures-And-Algorithms

37a4eb4f092f5a058643ef5ac302fe16d97f84dc

[ "Unlicense" ]

null

Common/Python/Data-Structures/Hashs/__init__.py

MattiKemp/Data-Structures-And-Algorithms

37a4eb4f092f5a058643ef5ac302fe16d97f84dc

[ "Unlicense" ]

null

from . import HashMap from . import Set

13.333333

21

0.75

6

40

5

0.666667

0

0.2

40

2

22

20

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

2d659f465ff8ae7814c6603d5bb08d08067d9d4e

11,936

py

Python

tests/integration/mongodb/factory/ar_conn/ar_other.py

RaenonX/Jelly-Bot-API

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

5

2020-08-26T20:12:00.000Z

2020-12-11T16:39:22.000Z

tests/integration/mongodb/factory/ar_conn/ar_other.py

RaenonX/Jelly-Bot

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

234

2019-12-14T03:45:19.000Z

2020-08-26T18:55:19.000Z

tests/integration/mongodb/factory/ar_conn/ar_other.py

RaenonX/Jelly-Bot-API

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

2

2019-10-23T15:21:15.000Z

2020-05-22T09:35:55.000Z

import time from flags import AutoReplyContentType from models import AutoReplyContentModel, AutoReplyModuleModel from models.ar import UniqueKeywordCountEntry from mongodb.factory.ar_conn import AutoReplyManager, AutoReplyModuleManager from tests.base import TestModelMixin from ._base_ar import TestAutoReplyManagerBase __all__ = ["TestAutoReplyManagerOther"] class TestAutoReplyManagerOther(TestAutoReplyManagerBase.TestClass, TestModelMixin): def test_get_count_call(self): mdl = AutoReplyManager.add_conn(**self.get_mdl_1_args()).model self.assertEqual(mdl.called_count, 0) for i in range(1, 4): AutoReplyManager.get_responses( self.get_mdl_1().keyword.content, self.get_mdl_1().keyword.content_type, self.get_mdl_1().channel_oid, update_async=False ) mdl = AutoReplyModuleManager.find_one_casted({ AutoReplyModuleModel.KEY_KW_CONTENT: self.get_mdl_1().keyword.content, AutoReplyModuleModel.KEY_KW_TYPE: self.get_mdl_1().keyword.content_type }) self.assertEqual(mdl.called_count, i) def test_get_after_add_multi(self): AutoReplyManager.add_conn(**self.get_mdl_1_args()) AutoReplyManager.add_conn(**self.get_mdl_4_args()) AutoReplyManager.add_conn(**self.get_mdl_6_args()) resp = AutoReplyManager.get_responses( self.get_mdl_1().keyword.content, self.get_mdl_1().keyword.content_type, self.get_mdl_1().channel_oid)[0][0] resp_expected = self.get_mdl_1().responses[0] self.assertModelEqual(resp, resp_expected) resp = AutoReplyManager.get_responses( self.get_mdl_4().keyword.content, self.get_mdl_4().keyword.content_type, self.get_mdl_4().channel_oid)[0][0] resp_expected = self.get_mdl_4().responses[0] self.assertModelEqual(resp, resp_expected) resp = AutoReplyManager.get_responses( self.get_mdl_6().keyword.content, self.get_mdl_6().keyword.content_type, self.get_mdl_6().channel_oid)[0][0] resp_expected = self.get_mdl_6().responses[0] self.assertModelEqual(resp, resp_expected) def test_get_on_cooldown(self): AutoReplyManager.add_conn(**self.get_mdl_3_args()) # Call once to record last used time AutoReplyManager.get_responses( self.get_mdl_3().keyword.content, self.get_mdl_3().keyword.content_type, self.get_mdl_3().channel_oid, update_async=False) resp = AutoReplyManager.get_responses( self.get_mdl_3().keyword.content, self.get_mdl_3().keyword.content_type, self.get_mdl_3().channel_oid, update_async=False) self.assertEqual(resp, []) mdl = AutoReplyModuleManager.find_one_casted({ AutoReplyModuleModel.KEY_KW_CONTENT: self.get_mdl_3().keyword.content, AutoReplyModuleModel.KEY_KW_TYPE: self.get_mdl_3().keyword.content_type }) self.assertEqual(mdl.called_count, 1) def test_get_after_cooldown(self): AutoReplyManager.add_conn(**self.get_mdl_3_args()) # Call once to record last used time AutoReplyManager.get_responses( self.get_mdl_3().keyword.content, self.get_mdl_3().keyword.content_type, self.get_mdl_3().channel_oid, update_async=False ) time.sleep(1.1) # Cooldown of model #3 is 1 sec resp = AutoReplyManager.get_responses( self.get_mdl_3().keyword.content, self.get_mdl_3().keyword.content_type, self.get_mdl_3().channel_oid, update_async=False ) self.assertEqual(resp, [(self.get_mdl_3().responses[0], False)]) mdl = AutoReplyModuleManager.find_one_casted({ AutoReplyModuleModel.KEY_KW_CONTENT: self.get_mdl_3().keyword.content, AutoReplyModuleModel.KEY_KW_TYPE: self.get_mdl_3().keyword.content_type }) self.assertEqual(mdl.called_count, 2) def test_get_list_by_keyword_including_inactive(self): expected_oids = self._add_call_module_kw_a() for idx, actual_mdl in enumerate(AutoReplyManager.get_conn_list(self.channel_oid, "A", active_only=False)): with self.subTest(expected=expected_oids[idx], actual=actual_mdl): self.assertEqual(expected_oids[idx], actual_mdl.id) def test_get_list_by_keyword_active_only(self): expected_oids = self._add_call_module_kw_a()[2:] for idx, actual_mdl in enumerate(AutoReplyManager.get_conn_list(self.channel_oid, "A")): with self.subTest(expected=expected_oids[idx], actual=actual_mdl): self.assertEqual(expected_oids[idx], actual_mdl.id) def test_get_list_by_oids(self): mdl_oids = self._add_call_module_kw_a() expected_kw_resp = ( (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT)]), (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT)]), (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="D", ContentType=AutoReplyContentType.TEXT)]) ) for mdl, kw_resp in zip(AutoReplyManager.get_conn_list_oids(mdl_oids), expected_kw_resp): kw, resp = kw_resp self.assertEqual(mdl.keyword, kw) self.assertEqual(mdl.responses, resp) def test_get_response_no_redirect(self): AutoReplyManager.add_conn(**self.get_mdl_17_args()) self.assertEqual(AutoReplyManager.get_responses("A", AutoReplyContentType.TEXT, self.channel_oid), [(AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT), True)]) def test_get_response_should_redirect(self): AutoReplyManager.add_conn(**self.get_mdl_1_args()) self.assertEqual(AutoReplyManager.get_responses("A", AutoReplyContentType.TEXT, self.channel_oid), [(AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT), False)]) def test_get_response_multiple_responses(self): AutoReplyManager.add_conn(Keyword=AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), Responses=[AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT), AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT), AutoReplyContentModel(Content="D", ContentType=AutoReplyContentType.TEXT)], ChannelOid=self.channel_oid, CreatorOid=self.CREATOR_OID) self.assertEqual(AutoReplyManager.get_responses("A", AutoReplyContentType.TEXT, self.channel_oid), [(AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT), False), (AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT), False), (AutoReplyContentModel(Content="D", ContentType=AutoReplyContentType.TEXT), False)]) def test_stats_module_count_length_limited(self): self._add_call_module_kw_a() expected_kw_resp = { "1": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT)]), "2": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT)]), } # Not using `zip()` to ensure that exceptions will be raised if len(actual) > len(expected) # which means the tests is not completed for rk, mdl in AutoReplyManager.get_module_count_stats(self.channel_oid, 2): kw, resp = expected_kw_resp[rk] self.assertEqual(kw, mdl.keyword) self.assertEqual(resp, mdl.responses) def test_stats_module_count_length_overlimit(self): self._add_call_module_kw_a() expected_kw_resp = { "1": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT)]), "2": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT)]), "3": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="D", ContentType=AutoReplyContentType.TEXT)]), } for rk, mdl in AutoReplyManager.get_module_count_stats(self.channel_oid, 5): kw, resp = expected_kw_resp[rk] self.assertEqual(kw, mdl.keyword) self.assertEqual(resp, mdl.responses) def test_stats_module_count_length_no_limit(self): self._add_call_module_kw_a() expected_kw_resp = { "1": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="B", ContentType=AutoReplyContentType.TEXT)]), "2": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="C", ContentType=AutoReplyContentType.TEXT)]), "3": (AutoReplyContentModel(Content="A", ContentType=AutoReplyContentType.TEXT), [AutoReplyContentModel(Content="D", ContentType=AutoReplyContentType.TEXT)]), } for rk, mdl in AutoReplyManager.get_module_count_stats(self.channel_oid): kw, resp = expected_kw_resp[rk] self.assertEqual(kw, mdl.keyword) self.assertEqual(resp, mdl.responses) def test_stats_unique_count_length_limited(self): self._add_call_module_multi() expected = [ UniqueKeywordCountEntry("B", AutoReplyContentType.TEXT, 9, 1, "1"), UniqueKeywordCountEntry("A", AutoReplyContentType.TEXT, 7, 3, "2"), UniqueKeywordCountEntry("C", AutoReplyContentType.TEXT, 0, 2, "3") ] result = AutoReplyManager.get_unique_keyword_count_stats(self.channel_oid, 3) self.assertEqual(result.limit, 3) self.assertEqual(result.data, expected) def test_stats_unique_count_length_overlimit(self): self._add_call_module_multi() expected = [ UniqueKeywordCountEntry("B", AutoReplyContentType.TEXT, 9, 1, "1"), UniqueKeywordCountEntry("A", AutoReplyContentType.TEXT, 7, 3, "2"), UniqueKeywordCountEntry("C", AutoReplyContentType.TEXT, 0, 2, "T3"), UniqueKeywordCountEntry("D", AutoReplyContentType.TEXT, 0, 1, "T3") ] result = AutoReplyManager.get_unique_keyword_count_stats(self.channel_oid, 5) self.assertEqual(result.limit, 5) self.assertEqual(result.data, expected) def test_stats_unique_count_length_no_limit(self): self._add_call_module_multi() expected = [ UniqueKeywordCountEntry("B", AutoReplyContentType.TEXT, 9, 1, "1"), UniqueKeywordCountEntry("A", AutoReplyContentType.TEXT, 7, 3, "2"), UniqueKeywordCountEntry("C", AutoReplyContentType.TEXT, 0, 2, "T3"), UniqueKeywordCountEntry("D", AutoReplyContentType.TEXT, 0, 1, "T3") ] result = AutoReplyManager.get_unique_keyword_count_stats(self.channel_oid) self.assertIsNone(result.limit) self.assertEqual(result.data, expected)

49.733333

119

0.676692

1,276

11,936

6.047806

0.105016

0.139951

0.054425

0.027083

0.858235

0.848775

0.800441

0.784243

0.755475

0.706103

0

0.011791

0.218415

11,936

239

120

49.941423

0.815414

0.019018

0

0.513369

0

0.008118

0.002136

0

0.149733

1

0.085562

false

0

0.037433

0

0.128342

0

null

0

1

0

null

0

6

2d873eb0a635cdfce4f99b3e1a4d175aab132eaf

17,244

py

Python

osm_multiplex/tests/test_lstm_preprocessing.py

SoftwareDevEngResearch/osm_multiplex

620b1072387428a8bc864c6b0e45416b2cfdc9fe

[ "MIT" ]

null

osm_multiplex/tests/test_lstm_preprocessing.py

SoftwareDevEngResearch/osm_multiplex

620b1072387428a8bc864c6b0e45416b2cfdc9fe

[ "MIT" ]

null

osm_multiplex/tests/test_lstm_preprocessing.py

SoftwareDevEngResearch/osm_multiplex

620b1072387428a8bc864c6b0e45416b2cfdc9fe

[ "MIT" ]

1

2019-04-20T19:46:58.000Z

# third-party libraries import pandas as pd import pytest # local imports from .. import lstm_preprocessing class TestSpatialGrouping: """Tests the output of a single location for the record""" def test_selection_1(self): """Select the default, which is choosing the location from dataset 1""" data_list = [[11.22, 33.44, 55.66, 77.88], [99.00, 11.22, 33.44, 55.66]] target_list = [[11.22, 33.44], [99.00, 11.22]] data = pd.DataFrame(data_list, columns=['lat1', 'lon1', 'lat2', 'lon2']) target = pd.DataFrame(target_list, columns=['lat', 'lon']) test = lstm_preprocessing.spatial_grouping(data) assert test.equals(target) def test_selection_2(self): """Select the location from dataset 2""" data_list = [[11.22, 33.44, 55.66, 77.88], [99.00, 11.22, 33.44, 55.66]] target_list = [[55.66, 77.88], [33.44, 55.66]] data = pd.DataFrame(data_list, columns=['lat1', 'lon1', 'lat2', 'lon2']) target = pd.DataFrame(target_list, columns=['lat', 'lon']) test = lstm_preprocessing.spatial_grouping(data, location_selection='2') assert test.equals(target) def test_selection_osm(self): """Select the location by finding the nearest OSM node to the average""" data_list = [[44.594487, -123.262589, 44.562769, -123.267733], [44.594528, -123.261476, 44.563046, -123.268784]] target_list = [[36921149, 44.57822, -123.264745], [36921149, 44.57822, -123.264745]] data = pd.DataFrame(data_list, columns=['lat1', 'lon1', 'lat2', 'lon2']) target = pd.DataFrame(target_list, columns=['osm_id', 'lat', 'lon']) test = lstm_preprocessing.spatial_grouping(data, location_selection='osm') assert test.equals(target) class TestAssignOsm: """Find the nearest OSM node to the average of the two dataset locations""" def test_find_nearest(self): data_list = [[44.594487, -123.262589, 44.562769, -123.267733], [44.594528, -123.261476, 44.563046, -123.268784]] target_list = [[36921149, 44.57822, -123.264745], [36921149, 44.57822, -123.264745]] data = pd.DataFrame(data_list, columns=['lat1', 'lon1', 'lat2', 'lon2']) target = pd.DataFrame(target_list, columns=['osm_id', 'lat', 'lon']) test = lstm_preprocessing.assign_osm(data) assert test.equals(target) class TestOccupancyLevel: """Tests the output of occupancy levels for both grouped and single user data""" def test_both_individual(self): """Both datasets have individual identifiers""" data_list = [['bike1', 'scooter1']] target_list = [['bike1', 'scooter1', 1, 1]] data = pd.DataFrame(data_list, columns=['element_id1', 'element_id2']) target = pd.DataFrame(target_list, columns=['element_id1', 'element_id2', 'occupancy1', 'occupancy2']) test = lstm_preprocessing.occupancy_level(data) assert test.equals(target) def test_both_grouped(self): """Both datasets have grouped counts""" data_list = [['bike1', 'scooter1', 1519330080, 1519330081, 2, 1, 3, 1], ['bike1', 'scooter1', 1519330085, 1519330086, 3, 0, 2, 1], ['bike1', 'scooter1', 1519430080, 1519430081, 3, 1, 4, 2], ['bike1', 'scooter1', 1519430085, 1519430086, 1, 2, 0, 1]] target_list = [['bike1', 'scooter1', '2018-02-22 20:08:00', '2018-02-22 20:08:01', 1, 2], ['bike1', 'scooter1', '2018-02-22 20:08:05', '2018-02-22 20:08:06', 4, 3], ['bike1', 'scooter1', '2018-02-23 23:54:40', '2018-02-23 23:54:41', 2, 2], ['bike1', 'scooter1', '2018-02-23 23:54:45', '2018-02-23 23:54:46', 1, 1]] data = pd.DataFrame(data_list, columns=['element_id1', 'element_id2', 'timestamp1', 'timestamp2', 'boardings1', 'alightings1', 'boardings2', 'alightings2']) target = pd.DataFrame(target_list, columns=['element_id1', 'element_id2', 'timestamp1', 'timestamp2', 'occupancy1', 'occupancy2']) target['timestamp1'] = pd.to_datetime(target['timestamp1']) target['timestamp2'] = pd.to_datetime(target['timestamp2']) test = lstm_preprocessing.occupancy_level(data) assert test.equals(target) class TestDailyCumulative: """Test the cumulative sum of grouped data to derive occupancy""" def test_summing_1_timestamp(self): """Test cumulative sum for dataset 1 with timestamp""" data_list = [['bob1', 1519330080, 2, 1], ['bob1', 1519330085, 3, 0], ['bob1', 1519430080, 3, 1], ['bob1', 1519430085, 1, 2]] target_list = [['bob1', '2018-02-22 20:08:00', 1], ['bob1', '2018-02-22 20:08:05', 4], ['bob1', '2018-02-23 23:54:40', 2], ['bob1', '2018-02-23 23:54:45', 1]] data = pd.DataFrame(data_list, columns=['element_id1', 'timestamp1', 'boardings1', 'alightings1']) target = pd.DataFrame(target_list, columns=['element_id1', 'timestamp1', 'occupancy1']) target['timestamp1'] = pd.to_datetime(target['timestamp1']) test = lstm_preprocessing.daily_cumulative(data, '1') assert test.equals(target) def test_summing_2_timestamp(self): """Test cumulative sum for dataset 2 with timestamp""" data_list = [['bob2', 1519330080, 2, 1], ['bob2', 1519330085, 3, 0], ['bob2', 1519430080, 3, 1], ['bob2', 1519430085, 1, 2]] target_list = [['bob2', '2018-02-22 20:08:00', 1], ['bob2', '2018-02-22 20:08:05', 4], ['bob2', '2018-02-23 23:54:40', 2], ['bob2', '2018-02-23 23:54:45', 1]] data = pd.DataFrame(data_list, columns=['element_id2', 'timestamp2', 'boardings2', 'alightings2']) target = pd.DataFrame(target_list, columns=['element_id2', 'timestamp2', 'occupancy2']) target['timestamp2'] = pd.to_datetime(target['timestamp2']) test = lstm_preprocessing.daily_cumulative(data, '2') assert test.equals(target) def test_summing_1_session(self): """Test cumulative sum for dataset 1 with session times""" data_list = [['bob1', 1519330080, 1519330081, 2, 1], ['bob1', 1519330085, 1519330086, 3, 0], ['bob1', 1519430080, 1519430081, 3, 1], ['bob1', 1519430085, 1519430086, 1, 2]] target_list = [['bob1', '2018-02-22 20:08:00', '2018-02-22 20:08:01', 1], ['bob1', '2018-02-22 20:08:05', '2018-02-22 20:08:06', 4], ['bob1', '2018-02-23 23:54:40', '2018-02-23 23:54:41', 2], ['bob1', '2018-02-23 23:54:45', '2018-02-23 23:54:46', 1]] data = pd.DataFrame(data_list, columns=['element_id1', 'session_start1', 'session_end1', 'boardings1', 'alightings1']) target = pd.DataFrame(target_list, columns=['element_id1', 'session_start1', 'session_end1', 'occupancy1']) target['session_start1'] = pd.to_datetime(target['session_start1']) target['session_end1'] = pd.to_datetime(target['session_end1']) test = lstm_preprocessing.daily_cumulative(data, '1') assert test.equals(target) def test_summing_2_session(self): """Test cumulative sum for dataset 2 with session times""" data_list = [['bob2', 1519330080, 1519330081, 2, 1], ['bob2', 1519330085, 1519330086, 3, 0], ['bob2', 1519430080, 1519430081, 3, 1], ['bob2', 1519430085, 1519430086, 1, 2]] target_list = [['bob2', '2018-02-22 20:08:00', '2018-02-22 20:08:01', 1], ['bob2', '2018-02-22 20:08:05', '2018-02-22 20:08:06', 4], ['bob2', '2018-02-23 23:54:40', '2018-02-23 23:54:41', 2], ['bob2', '2018-02-23 23:54:45', '2018-02-23 23:54:46', 1]] data = pd.DataFrame(data_list, columns=['element_id2', 'session_start2', 'session_end2', 'boardings2', 'alightings2']) target = pd.DataFrame(target_list, columns=['element_id2', 'session_start2', 'session_end2', 'occupancy2']) target['session_start2'] = pd.to_datetime(target['session_start2']) target['session_end2'] = pd.to_datetime(target['session_end2']) test = lstm_preprocessing.daily_cumulative(data, '2') assert test.equals(target) def test_invalid_identifier(self): """Tests if exception is raised when identifier parameter is not valid""" data_list = [['bob2', 1519330080, 1519330081, 2, 1], ['bob2', 1519330085, 1519330086, 3, 0], ['bob2', 1519430080, 1519430081, 3, 1], ['bob2', 1519430085, 1519430086, 1, 2]] target_list = [['bob2', '2018-02-22 20:08:00', '2018-02-22 20:08:01', 1], ['bob2', '2018-02-22 20:08:05', '2018-02-22 20:08:06', 4], ['bob2', '2018-02-23 23:54:40', '2018-02-23 23:54:41', 2], ['bob2', '2018-02-23 23:54:45', '2018-02-23 23:54:46', 1]] data = pd.DataFrame(data_list, columns=['element_id2', 'session_start2', 'session_end2', 'boardings2', 'alightings2']) with pytest.raises(Exception): lstm_preprocessing.daily_cumulative(data, '3') class TestTimeGrouping: """Tests the grouping of records into specified time intervals""" def test_timestamp1_session2_interval15_selection1(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:45:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['timestamp1', 'session_start2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='15T', time_selection='1') assert test.equals(target_multi) def test_timestamp1_session2_interval15_selection2(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:45:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['timestamp1', 'session_start2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='15T', time_selection='2') assert test.equals(target_multi) def test_session1_timestamp2_interval60_selection2(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:00:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['session_start1', 'timestamp2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='60T', time_selection='2') assert test.equals(target_multi) def test_session1_timestamp2_interval60_selection1(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:00:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['session_start1', 'timestamp2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='60T', time_selection='1') assert test.equals(target_multi) def test_session1_timestamp2_interval30_selectionavg(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:30:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['session_start1', 'timestamp2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='30T', time_selection='avg') assert test.equals(target_multi) def test_timestamp1_session2_interval30_selectionavg(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] target_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:30:00', 44.44, 55.55, 5, 8]] data = pd.DataFrame(data_list, columns=['timestamp1', 'session_start2', 'lat', 'lon', 'occupancy1', 'occupancy2']) target = pd.DataFrame(target_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) target['time'] = pd.to_datetime(target['time']) target_multi = target.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.time_grouping(data, interval='30T', time_selection='avg') assert test.equals(target_multi) def test_invalid_time_selection(self): data_list = [[1519330080, 1519330090, 44.44, 55.55, 2, 3], [1519330081, 1519330030, 44.44, 55.55, 1, 4], [1519430080, 1519430090, 44.44, 55.55, 3, 2], [1519430081, 1519430030, 44.44, 55.55, 2, 6]] data = pd.DataFrame(data_list, columns=['timestamp1', 'session_start2', 'lat', 'lon', 'occupancy1', 'occupancy2']) with pytest.raises(Exception): lstm_preprocessing.time_grouping(data, interval='30T', time_selection='3') class TestWeeklyDifferenceDataframes: def test_two_weeks(self): data_list = [['2018-02-22 20:00:00', 44.44, 55.55, 3, 7], ['2018-02-23 23:30:00', 44.44, 55.55, 5, 8], ['2018-02-24 00:00:00', 44.44, 55.55, 4, 3], ['2018-02-24 00:30:00', 44.44, 55.55, 2, 3], ['2018-02-24 01:00:00', 66.66, 77.77, 5, 5], ['2018-02-24 01:30:00', 66.66, 77.77, 3, 3], ['2018-02-24 02:00:00', 66.66, 77.77, 7, 8], ['2018-02-24 02:30:00', 66.66, 77.77, 3, 5], ['2018-02-24 03:00:00', 66.66, 77.77, 4, 5], ['2018-03-24 03:30:00', 44.44, 55.55, 7, 8], ['2018-03-24 04:00:00', 44.44, 55.55, 6, 5], ['2018-03-24 04:30:00', 44.44, 55.55, 9, 8], ['2018-03-24 05:00:00', 44.44, 55.55, 2, 2], ['2018-03-24 05:30:00', 44.44, 55.55, 8, 8], ['2018-03-24 06:00:00', 44.44, 55.55, 6, 5], ['2018-03-24 06:30:00', 44.44, 55.55, 7, 8], ['2018-03-24 07:00:00', 44.44, 55.55, 2, 4], ['2018-03-24 07:30:00', 44.44, 55.55, 5, 4],] data = pd.DataFrame(data_list, columns=['time', 'lat', 'lon', 'occupancy1', 'occupancy2']) data['time'] = pd.to_datetime(data['time']) data_multi = data.set_index(['time', 'lat', 'lon']) test = lstm_preprocessing.weekly_dataframes(data_multi) assert test != None # need a better assertion, but can't find how to hash a dictionary of dataframes

56.352941

166

0.579564

2,290

17,244

4.253275

0.093013

0.037577

0.032649

0.043532

0.814476

0.784394

0.760986

0.717146

0.676797

0.66232

0

0.245328

0.245941

17,244

305

167

56.537705

0.50373

0.055034

0

0.5671

0

0.200728

0

0.073593

1

0.082251

false

0

0.012987

0

0.121212

0

null

0

1

0

1

0

1

0

null

0

6

2daac25556b612e3453a8ae5fd9bb82c85dfe889

7,124

py

Python

posts/tests.py

BattleMageBro/yatube

667686aead6ae4ce9de6847fe2fd23fb14767c32

[ "BSD-3-Clause" ]

null

posts/tests.py

BattleMageBro/yatube

667686aead6ae4ce9de6847fe2fd23fb14767c32

[ "BSD-3-Clause" ]

null

posts/tests.py

BattleMageBro/yatube

667686aead6ae4ce9de6847fe2fd23fb14767c32

[ "BSD-3-Clause" ]

null

from django.test import TestCase, Client, override_settings from .models import User, Post, Group, Follow from django.urls import reverse TEST_CACHE = { 'default': { 'BACKEND': 'django.core.cache.backends.dummy.DummyCache', } } # Create your tests here. class ViewsTests(TestCase): def setUp(self): self.client = Client() self.user = User.objects.create_user(username='pupa', email='pupa@mail.ru', password='12345678') self.post = Post.objects.create(text="Привет, давно не виделись!", author=self.user) def test_profile_view(self): response = self.client.get('/pupa/') self.assertEqual(response.status_code, 200) self.assertEqual(response.context['post_count'], 1) self.assertIsInstance(response.context['user_profile'], User) self.assertEqual(response.context['user_profile'].username, self.user.username) def test_new_post(self): self.client.login(username='pupa', password='12345678') response = self.client.post('/new/', {'text': 'Создаю Новый пост!'}, follow=True) self.assertRedirects(response, '/') response = self.client.get(reverse('profile', kwargs={'username': self.user.username})) self.assertEqual(response.status_code, 200) self.assertEqual(response.context['post_count'],2) self.assertIsInstance(response.context['user_profile'], User) self.assertEqual(response.context['user_profile'].username, self.user.username) def test_new_post_no_auth(self): response = self.client.post(reverse('new_post'), follow=True) self.assertRedirects(response, '/auth/login/?next=%2Fnew%2F') def test_tripple_post_index(self): self.client.login(username='pupa', password='12345678') response = self.client.get('/') self.assertContains(response, self.post.text, count=1) def test_tripple_post_profile(self): self.client.force_login(self.user) response = self.client.get(reverse('profile', kwargs={'username': self.user.username})) self.assertContains(response, self.post.text, count=1) def test_tripple_post_post_view(self): self.client.force_login(self.user) response = self.client.get(reverse('posts', kwargs={'username': self.user.username, 'post_id': self.post.id})) self.assertContains(response, self.post.text, count=1) @override_settings(CACHES=TEST_CACHE) def test_tripple_post_edit_index(self): self.client.login(username='pupa', password='12345678') self.client.post(f'/{self.user.username}/{self.post.id}/edit/', {'text': 'О, это снова Вы!'}, follow=False) response = self.client.get('/') self.assertContains(response, 'О, это снова Вы!', count=1) @override_settings(CACHES=TEST_CACHE) def test_tripple_post_edit_profile(self): self.client.force_login(self.user) self.client.post(f'/{self.user.username}/{self.post.id}/edit/', {'text': 'О, это снова Вы!'}, follow=False) response = self.client.get(reverse('profile', kwargs={'username': self.user.username})) self.assertContains(response, 'О, это снова Вы!', count=1) @override_settings(CACHES=TEST_CACHE) def test_tripple_post_edit_post_view(self): self.client.force_login(self.user) self.client.post(f'/{self.user.username}/{self.post.id}/edit/', {'text': 'О, это снова Вы!'}, follow=False) response = self.client.get(reverse('posts', kwargs={'username': self.user.username, 'post_id': self.post.id})) self.assertContains(response, 'О, это снова Вы!', count=1) class FollowTest(TestCase): def setUp(self): self.client = Client() self.user1 = User.objects.create_user(username='pupa', email='pupa@mail.ru', password='12345') self.user2 = User.objects.create_user(username='lupa', email='lupa@mail.ru', password='54321') self.user3 = User.objects.create_user(username='kamon', email='kam@mail.ru', password='15243') self.post = Post.objects.create(text='Для всех моих подписчиков', author=self.user2) def test_follow(self): self.client.force_login(self.user1) self.client.get(reverse('profile_follow', kwargs={'username': self.user2.username})) self.assertEqual(Follow.objects.count(), 1) def test_unfollow(self): self.client.force_login(self.user1) self.client.get(reverse('profile_follow', kwargs={'username': self.user2.username})) self.client.get(reverse('profile_unfollow', kwargs={'username': self.user2.username})) self.assertEqual(Follow.objects.count(), 0) def test_follow_post(self): self.client.force_login(self.user1) self.client.get(reverse('profile_follow', kwargs={'username': self.user2.username})) response = self.client.get('/follow/') self.assertContains(response, self.post.text, status_code=200) self.client.force_login(self.user3) response = self.client.get('/follow/') self.assertNotContains(response, self.post.text, status_code=200) class CommentTest(TestCase): def setUp(self): self.client = Client() self.user = User.objects.create_user(username='pupa', email='pupa@mail.ru', password='12345') self.post = Post.objects.create(text='Для комментиков=)', author=self.user) def test_add_comment_no_auth(self): response = self.client.post(reverse('add_comment', kwargs={'username': self.user.username, 'post_id': self.post.id }), follow=True) self.assertRedirects(response, '/auth/login/?next=%2Fpupa%2F1%2Fcomment%2F') def test_add_comment(self): self.client.force_login(self.user) response = self.client.post(reverse('add_comment', kwargs={'username': self.user.username, 'post_id': self.post.id }), {'text': 'Комментик=)'}, follow=True) self.assertContains(response, 'Комментик=)') class ImageTest(TestCase): def setUp(self): self.client = Client() self.user = User.objects.create_user(username='pupa', email='pupa@mail.ru', password='12345') self.post = Post.objects.create(text='Картиночка подъехала', author=self.user) self.group = Group.objects.create(title='Любители картинок', slug='Love', description='lovelove') @override_settings(CACHES=TEST_CACHE) def test_image_post(self): self.client.force_login(self.user) with open('media/tests/Test.jpg', 'rb') as fp: response = self.client.post(reverse('post_edit', kwargs={'username': self.user.username, 'post_id': self.post.id}), {'text': self.post.text, 'image': fp, 'group': self.group.id}, follow=True) response_dec = response.content.decode('utf-8') self.assertIn('<img', response_dec) response = self.client.get('/') response_dec = response.content.decode('utf-8') self.assertIn('<img', response_dec) response = self.client.get(reverse('profile', kwargs={'username': self.user.username})) response_dec = response.content.decode('utf-8') self.assertIn('<img', response_dec)

50.524823

203

0.676025

904

7,124

5.219027

0.149336

0.086901

0.064858

0.053412

0.81348

0.768334

0.746079

0.707503

0.661933

0.642857

0

0.017023

0.167181

7,124

140

204

50.885714

0.77819

0.003229

0

0.525862

0

0.158614

0.033526

0

0.215517

1

0.163793

false

0.077586

0.025862

0

0.224138

0

null

0

1

0

1

0

null

0

1

0

6

2de1a1338befa83c884d88161eaf1c15388d4d32

95

py

Python

electronics_lib/DigikeyCapacitorTable.py

lab11/PolymorphicBlocks

52e5ee332fddc9a9f583ebabfca863365e873bf7

[ "BSD-3-Clause" ]

null

electronics_lib/DigikeyCapacitorTable.py

lab11/PolymorphicBlocks

52e5ee332fddc9a9f583ebabfca863365e873bf7

[ "BSD-3-Clause" ]

null

electronics_lib/DigikeyCapacitorTable.py

lab11/PolymorphicBlocks

52e5ee332fddc9a9f583ebabfca863365e873bf7

[ "BSD-3-Clause" ]

null

from .DigikeyTable import * class DigikeyCapacitorTable(DigikeyTable, CapacitorTable): pass

19

58

0.821053

8

95

9.75

0.875

0

0.115789

95

4

59

23.75

0.928571

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

2dff1856c65ee11c439ff5ca92b77217605fe7ef

141

py

Python

Local_debug.py

Doreamonsky/Shnu

b052dd21c2dd6c8f51fa83da0a3504eaa16aedcf

[ "Apache-2.0" ]

10

2018-01-18T11:45:55.000Z

2021-01-26T08:44:16.000Z

Local_debug.py

Doreamonsky/Shnu

b052dd21c2dd6c8f51fa83da0a3504eaa16aedcf

[ "Apache-2.0" ]

1

2018-02-18T13:56:19.000Z

Local_debug.py

Doreamonsky/Shnu

b052dd21c2dd6c8f51fa83da0a3504eaa16aedcf

[ "Apache-2.0" ]

2

2018-02-07T11:47:36.000Z

2018-04-05T11:45:58.000Z

#!/usr/bin/python # -*- coding: UTF-8 -*- import Function_adapter print Function_adapter.MyAdapter().run('courses_list_by_keywords', '数学')

20.142857

72

0.730496

19

141

5.157895

0.894737

0.306122

0

0.007813

0.092199

141

6

73

23.5

0.757813

0.269504

0

0.257426

0.237624

0

null

0

0.5

null

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

93225a8d1b5d52dbb1f2766c63847b04de55edac

47

py

Python

vizbert/extract/__init__.py

daemon/vizbert

e40b7d1529f8857050313f8d87ff03b1b7226c9e

[ "MIT" ]

null

vizbert/extract/__init__.py

daemon/vizbert

e40b7d1529f8857050313f8d87ff03b1b7226c9e

[ "MIT" ]

null

vizbert/extract/__init__.py

daemon/vizbert

e40b7d1529f8857050313f8d87ff03b1b7226c9e

[ "MIT" ]

null

from .base import * from .transformer import *

15.666667

26

0.744681

6

47

5.833333

0.666667

0

0.170213

47

2

27

23.5

0.897436

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

933ab1657fdf5d2dc8022857df9f531b8fef800c

166,895

py

Python

pirates/leveleditor/worldData/pvpShipIsland2.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

3

2021-02-25T06:38:13.000Z

2022-03-22T07:00:15.000Z

pirates/leveleditor/worldData/pvpShipIsland2.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

null

pirates/leveleditor/worldData/pvpShipIsland2.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

1

2021-02-25T06:38:17.000Z

# uncompyle6 version 3.2.0 # Python bytecode 2.4 (62061) # Decompiled from: Python 2.7.14 (v2.7.14:84471935ed, Sep 16 2017, 20:19:30) [MSC v.1500 32 bit (Intel)] # Embedded file name: pirates.leveleditor.worldData.pvpShipIsland2 from pandac.PandaModules import Point3, VBase3, Vec4, Vec3 objectStruct = {'AmbientColors': {0: Vec4(0.207843, 0.243137, 0.447059, 1), 2: Vec4(0.666667, 0.721569, 0.792157, 1), 4: Vec4(0.721569, 0.611765, 0.619608, 1), 6: Vec4(0.207843, 0.243137, 0.447059, 1), 8: Vec4(0.384314, 0.419608, 0.564706, 1)}, 'DirectionalColors': {0: Vec4(0.956863, 0.909804, 0.894118, 1), 2: Vec4(1, 1, 1, 1), 4: Vec4(0.439216, 0.176471, 0, 1), 6: Vec4(0.513726, 0.482353, 0.639216, 1), 8: Vec4(0.447059, 0.439216, 0.537255, 1)}, 'FogColors': {0: Vec4(0.172549, 0.180392, 0.290196, 1), 2: Vec4(0.894118, 0.894118, 1, 1), 4: Vec4(0.231373, 0.203922, 0.184314, 1), 6: Vec4(0.172549, 0.180392, 0.290196, 1), 8: Vec4(0.129412, 0.137255, 0.203922, 1)}, 'FogRanges': {0: 0.000699999975040555, 2: 0.00019999999494757503, 4: 0.00039999998989515007, 6: 0.000699999975040555, 8: 0.0}, 'Objects': {'1196970035.53sdnaik': {'Type': 'Island', 'Name': 'pvpShipIsland2', 'File': '', 'Environment': 'OpenSky', 'Minimap': False, 'Objects': {'1201551808.32kmuller': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(42.304, 291.037, 0.81), 'Hpr': VBase3(-149.207, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(-8.509, -280.365, 0.81), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1201551834.96kmuller': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(8.739, -231.852, 0.612), 'Hpr': VBase3(-136.695, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(-64.569, 222.851, 0.612), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1201551889.37kmuller': {'Type': 'Player Spawn Node', 'GridPos': Point3(62.095, -172.567, 3.658), 'Hpr': VBase3(129.217, 0.0, 0.0), 'Index': 1, 'Pos': Point3(-101.998, 152.419, 3.658), 'Scale': VBase3(1.0, 1.0, 1.0), 'Spawnables': 'All', 'Visual': {'Color': (0.5, 0.5, 0.5, 1), 'Model': 'models/misc/smiley'}}, '1201551915.76kmuller': {'Type': 'Player Spawn Node', 'GridPos': Point3(405.977, 55.544, 6.652), 'Hpr': VBase3(69.496, 0.0, 0.0), 'Index': 1, 'Pos': Point3(492.088, 16.466, 2.257), 'Scale': VBase3(1.0, 1.0, 1.0), 'Spawnables': 'All', 'Visual': {'Color': (0.5, 0.5, 0.5, 1), 'Model': 'models/misc/smiley'}}, '1201558997.82kmuller': {'Type': 'Player Spawn Node', 'GridPos': Point3(186.876, -349.348, 1.25), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Index': -1, 'Pos': Point3(-265.84, 293.761, 1.25), 'Scale': VBase3(1.0, 1.0, 1.0), 'Spawnables': 'All', 'Visual': {'Color': (0.5, 0.5, 0.5, 1), 'Model': 'models/misc/smiley'}}, '1201559007.18kmuller': {'Type': 'Player Spawn Node', 'GridPos': Point3(-229.903, -58.379, 1.835), 'Hpr': VBase3(-147.259, 0.0, 0.0), 'Index': -1, 'Pos': Point3(208.951, 112.263, 1.835), 'Scale': VBase3(1.0, 1.0, 1.0), 'Spawnables': 'All', 'Visual': {'Color': (0.5, 0.5, 0.5, 1), 'Model': 'models/misc/smiley'}}, '1201559028.84kmuller': {'Type': 'Player Spawn Node', 'GridPos': Point3(-454.921, -16.539, 56.948), 'Hpr': VBase3(-117.589, 0.0, 0.0), 'Index': -1, 'Pos': Point3(-417.183, 182.286, 1.761), 'Scale': VBase3(1.0, 1.0, 1.0), 'Spawnables': 'All', 'Visual': {'Color': (0.5, 0.5, 0.5, 1), 'Model': 'models/misc/smiley'}}, '1202414940.17akelts': {'Type': 'Building Exterior', 'File': '', 'ExtUid': '1202414940.17akelts0', 'GridPos': Point3(91.131, -360.491, 0.586), 'Hpr': VBase3(-104.772, 0.0, 0.0), 'Objects': {}, 'Pos': Point3(-175.635, 327.736, 0.586), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Door': 'models/buildings/shanty_guildhall_door', 'Model': 'models/buildings/shanty_repairshop_exterior', 'SignFrame': 'models/buildings/sign1_shanty_a_frame', 'SignImage': 'models/buildings/sign1_eng_a_icon_shipwright'}}, '1203114290.45akelts': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(420.918, 330.9, -0.561), 'Hpr': VBase3(167.783, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(-328.363, -422.9, -0.561), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1203114330.25akelts': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(-246.537, -87.543, -0.021), 'Hpr': VBase3(162.527, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(218.035, 144.585, -0.021), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1203114365.52akelts': {'Type': 'Building Exterior', 'File': '', 'ExtUid': '1203114365.52akelts0', 'GridPos': Point3(-374.828, 18.538, 5.551), 'Hpr': VBase3(-127.2, -0.354, -1.185), 'Objects': {'1210373727.44akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-180.0, 0.0, 0.0), 'Pos': Point3(-0.277, -13.756, 1.561), 'Scale': VBase3(1.0, 1.0, 1.0)}}, 'Pos': Point3(368.179, 72.692, 5.551), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.89, 0.82, 0.807843137254902, 1.0), 'Door': 'models/buildings/shanty_guildhall_door', 'Model': 'models/buildings/shanty_guildhall_exterior', 'SignFrame': '', 'SignImage': 'models/buildings/sign1_eng_a_icon_barber'}}, '1203114365.58akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'GridPos': Point3(-345.867, -4.901, 7.173), 'Hpr': VBase3(142.807, 1.185, -0.354), 'Pos': Point3(357.407, 81.242, 6.653), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1203114419.42akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-370.33, 40.493, 50.666), 'Hpr': VBase3(-36.749, 10.145, 0.354), 'Objects': {}, 'Pos': Point3(369.126, 50.301, 50.666), 'Scale': VBase3(0.487, 0.487, 0.487), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1203114463.95akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-353.885, 53.931, 46.962), 'Hpr': VBase3(-36.894, -2.657, 0.493), 'Objects': {}, 'Pos': Point3(356.42, 33.283, 46.962), 'Scale': VBase3(0.487, 0.487, 0.487), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1203114579.48akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-337.185, 67.472, 48.024), 'Hpr': VBase3(-35.933, -14.761, 0.771), 'Objects': {}, 'Pos': Point3(343.492, 16.105, 48.024), 'Scale': VBase3(0.487, 0.487, 0.487), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1203114754.3akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-317.877, 77.461, 54.14), 'Hpr': VBase3(-36.042, -20.792, -2.004), 'Pos': Point3(327.174, 1.741, 54.14), 'Scale': VBase3(0.481, 0.481, 0.481), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1203114815.91akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-323.541, 84.152, 53.696), 'Hpr': VBase3(-36.042, -20.792, -2.004), 'Pos': Point3(334.289, -3.381, 53.696), 'Scale': VBase3(0.481, 0.481, 0.481), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1203114862.61akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-367.832, 37.147, 51.229), 'Hpr': VBase3(136.33, -14.593, 0.248), 'Pos': Point3(365.892, 52.943, 51.229), 'Scale': VBase3(0.5, 0.5, 0.5), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1203114895.23akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-373.097, 43.489, 51.215), 'Hpr': VBase3(141.84, -16.787, -4.14), 'Pos': Point3(372.535, 48.063, 51.215), 'Scale': VBase3(0.5, 0.5, 0.5), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1203115389.72akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'GridPos': Point3(-0.277, -13.756, 1.023), 'Hpr': VBase3(104.0, 0.0, 0.0), 'Pos': Point3(-3.059, 13.414, 1.023), 'Scale': VBase3(1.0, 1.0, 1.0), 'TargetUIDs': []}, '1203115424.56akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(133.745, -12.642, 1.974), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-132.831, -20.089, 1.974), 'Scale': VBase3(0.643, 0.643, 0.819), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_med'}}, '1203115489.25akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(297.026, -66.639, 10.052), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-304.324, -7.198, 10.052), 'Scale': VBase3(0.795, 0.795, 1.013), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_med2'}}, '1203115525.55akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(375.859, 82.108, 1.086), 'Hpr': VBase3(-104.124, 0.0, 0.0), 'Pos': Point3(-344.831, -170.598, 1.086), 'Scale': VBase3(0.456, 0.418, 0.71), 'Visual': {'Color': (0.42, 0.42, 0.33725490196078434, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1203115567.8akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-587.491, 312.528, -68.942), 'Hpr': VBase3(119.847, 0.0, 0.0), 'Pos': Point3(645.647, -161.118, -68.942), 'Scale': VBase3(1.183, 0.52, 0.922), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1203115686.2akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(297.269, -154.801, 13.946), 'Hpr': VBase3(170.573, 0.0, 0.0), 'Pos': Point3(-325.889, 78.287, 12.489), 'Scale': VBase3(4.557, 4.557, 5.809), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/rock_group_1_sphere'}}, '1203115759.17akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-157.444, 3.644, -7.311), 'Pos': Point3(-151.091, 9.738, 14.816), 'Scale': VBase3(4.774, 4.774, 5.353), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1203115821.75akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(46.003, -344.332, -12.418), 'Hpr': VBase3(-94.124, 0.0, 0.0), 'Pos': Point3(-127.938, 322.975, -12.418), 'Scale': VBase3(8.653, 8.653, 11.031), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1203115874.03akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(139.745, -358.255, -6.141), 'Hpr': VBase3(-32.416, 2.665, -0.967), 'Pos': Point3(-222.264, 313.806, -6.141), 'Scale': VBase3(5.931, 5.931, 7.562), 'Visual': {'Color': (0.592156862745098, 0.56, 0.4823529411764706, 1.0), 'Model': 'models/props/rock_group_4_sphere'}}, '1203115947.03akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-129.25, 211.145, 50.427), 'Hpr': VBase3(-157.196, 0.865, 0.447), 'Pos': Point3(174.89, -179.16, 50.079), 'Scale': VBase3(9.385, 9.385, 11.96), 'Visual': {'Color': (0.35, 0.38, 0.3058823529411765, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1203449603.97akelts': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'drunk', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'models/char/pls_zero', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'GridPos': Point3(-374.192, 13.788, 34.359), 'Hpr': VBase3(-138.897, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '6.7229', 'Pos': Point3(365.602, 88.526, 34.033), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1203450135.28akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-400.776, 18.298, 6.526), 'Hpr': VBase3(144.474, 0.0, 0.0), 'Pos': Point3(393.298, 79.202, 6.526), 'Scale': VBase3(1.207, 1.207, 1.207), 'Visual': {'Color': (0.85, 0.81, 0.7529411764705882, 1.0), 'Model': 'models/props/rock_group_1_floor'}}, '1203450324.03akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(351.431, -9.522, 54.483), 'Hpr': VBase3(178.296, 2.576, -9.081), 'Objects': {}, 'Pos': Point3(-343.296, -75.78, 54.483), 'Scale': VBase3(5.002, 5.002, 5.002), 'Visual': {'Color': (0.3, 0.35, 0.3, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1203450370.69akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(361.155, -135.951, 48.755), 'Hpr': VBase3(-21.612, -2.135, 5.69), 'Pos': Point3(-390.559, 40.931, 49.518), 'Scale': VBase3(8.698, 8.698, 8.698), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1203450461.55akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(449.294, 105.752, 64.957), 'Hpr': VBase3(-5.986, 0.294, -10.694), 'Objects': {}, 'Pos': Point3(-409.993, -223.993, 59.841), 'Scale': VBase3(4.115, 4.115, 8.62), 'Visual': {'Color': (0.33, 0.37, 0.3176470588235294, 1.0), 'Model': 'models/props/rock_group_2_sphere'}}, '1203450511.61akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(322.479, 227.694, 71.845), 'Hpr': VBase3(27.235, 0.0, 0.0), 'Pos': Point3(-257.816, -298.945, 70.312), 'Scale': VBase3(3.53, 3.53, 4.525), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/rock_group_2_sphere'}}, '1203450582.5akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-6.969, 263.14, 4.355), 'Hpr': VBase3(-40.113, 4.317, -0.99), 'Pos': Point3(92.861, -245.087, 6.142), 'Scale': VBase3(9.619, 9.619, 9.619), 'Visual': {'Color': (0.5098039215686274, 0.5372549019607843, 0.4392156862745098, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1203450682.05akelts': {'Type': 'Building Exterior', 'File': '', 'ExtUid': '1203450682.05akelts0', 'GridPos': Point3(353.227, -178.718, 9.399), 'Hpr': VBase3(141.203, -1.558, 3.891), 'Pos': Point3(-385.97, 87.956, 9.399), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Door': 'models/buildings/shanty_guildhall_door', 'Model': 'models/buildings/shanty_leanto_A', 'SignImage': 'models/buildings/sign1_eng_a_icon_barber'}}, '1203450740.25akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(333.47, -178.47, 10.924), 'Hpr': VBase3(47.086, 0.0, 0.0), 'Pos': Point3(-366.74, 92.495, 10.924), 'Scale': VBase3(1.22, 1.0, 1.566), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1203450762.45akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(357.347, -195.137, 7.301), 'Hpr': VBase3(-146.231, 0.0, 0.0), 'Pos': Point3(-393.94, 102.891, 7.301), 'Scale': VBase3(2.302, 1.0, 1.885), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1203450800.73akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(340.836, -195.321, 9.411), 'Hpr': VBase3(162.554, 1.558, 3.797), 'Pos': Point3(-377.964, 107.063, 9.411), 'Scale': VBase3(1.404, 1.0, 1.566), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1203450923.8akelts': {'Type': 'Building Exterior', 'File': '', 'ExtUid': '1203450923.8akelts0', 'GridPos': Point3(341.222, -202.965, 8.089), 'Hpr': VBase3(144.815, 0.0, 0.0), 'Pos': Point3(-380.188, 114.387, 8.089), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6862745098039216, 0.5, 0.32941176470588235, 1.0), 'Door': 'models/buildings/shanty_guildhall_door', 'Model': 'models/buildings/shanty_signpost', 'SignFrame': 'models/buildings/sign1_shanty_a_frame', 'SignImage': 'models/buildings/sign1_eng_a_icon_weapons'}}, '1203451028.89akelts': {'Type': 'Townsperson', 'Category': 'Shipwright', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'GridPos': Point3(100.489, -340.513, 0.586), 'Hpr': VBase3(167.771, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(-179.882, 306.088, 0.586), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1203451240.81akelts': {'Type': 'Townsperson', 'Category': 'Gunsmith', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'GridPos': Point3(-376.905, 109.44, 9.91), 'Hpr': VBase3(-77.345, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '6.0361', 'Pos': Point3(-376.905, 109.44, 9.91), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Walk', 'StartFrame': '0', 'Team': 'Player', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1203458158.53akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-30.979, -42.476, -11.649), 'Hpr': VBase3(-1.111, 0.0, 7.587), 'Objects': {}, 'Pos': Point3(19.783, 48.709, -11.649), 'Scale': VBase3(8.698, 8.698, 16.174), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1203458673.23akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-355.289, 97.381, 3.857), 'Hpr': VBase3(147.426, 0.124, 0.966), 'Pos': Point3(367.145, -11.612, 2.787), 'Scale': VBase3(4.598, 4.598, 5.857), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1203459119.77akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-186.002, 32.546, 3.202), 'Hpr': VBase3(-89.834, 0.746, -0.627), 'Pos': Point3(156.072, 19.876, 2.711), 'Scale': VBase3(4.305, 4.305, 3.492), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_1_floor'}}, '1203459408.59akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(424.827, 249.321, 1.111), 'Hpr': VBase3(-25.022, 0.0, 0.0), 'Pos': Point3(-271.045, -331.897, -3.821), 'Scale': VBase3(22.905, 22.905, 28.86), 'Visual': {'Color': (0.29, 0.31, 0.24705882352941178, 1.0), 'Model': 'models/props/rock_3_sphere'}}, '1203460758.22akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(363.854, -188.935, 8.585), 'Hpr': VBase3(-146.382, 0.0, 0.0), 'Pos': Point3(-398.753, 95.299, 8.585), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/prop_group02'}}, '1203460800.05akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(358.97, -190.561, 8.857), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-394.408, 98.058, 8.857), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/prop_group_A'}}, '1203460826.44akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(352.288, -173.771, 10.092), 'Hpr': VBase3(130.335, 0.0, 0.0), 'Pos': Point3(-383.863, 83.383, 10.092), 'Scale': VBase3(0.69, 0.69, 0.69), 'Visual': {'Color': (0.30000001192092896, 0.30000001192092896, 0.30000001192092896, 1.0), 'Model': 'models/props/prop_group_B'}}, '1203460870.59akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(348.056, -178.842, 10.229), 'Hpr': VBase3(150.939, 0.0, 0.0), 'Pos': Point3(-380.983, 89.327, 10.229), 'Scale': VBase3(0.631, 0.631, 0.631), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/prop_group_D'}}, '1203460917.47akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(351.876, -190.764, 9.379), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-387.574, 99.971, 9.379), 'Scale': VBase3(0.558, 0.558, 0.558), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/prop_group_E'}}, '1203460945.09akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(347.804, -184.813, 10.016), 'Hpr': VBase3(158.209, 0.0, 0.0), 'Pos': Point3(-382.183, 95.182, 10.016), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/cannon_broken_prop'}}, '1203461019.36akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(337.989, -181.537, 10.92), 'Hpr': VBase3(124.125, -2.653, 4.877), 'Pos': Point3(-371.867, 94.378, 10.92), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.7, 0.7, 0.7, 1.0), 'Model': 'models/props/cannon_stack_01'}}, '1203461073.42akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(340.919, -184.568, 10.57), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-375.443, 96.61, 10.57), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/cannonball_stack_square'}}, '1203461085.86akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(343.709, -188.02, 10.21), 'Hpr': VBase3(155.309, 0.0, 0.0), 'Pos': Point3(-378.986, 99.284, 10.21), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/cannonball_stack_square'}}, '1203461128.5akelts': {'Type': 'Ship_Props', 'DisableCollision': False, 'GridPos': Point3(345.912, -196.447, 9.393), 'Hpr': VBase3(116.749, 0.0, 0.0), 'Pos': Point3(-383.162, 106.928, 9.393), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/cannon_stack_02'}}, '1203461179.58akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(339.897, -188.054, 10.496), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-375.295, 100.24, 10.496), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/cannonball_stack_triangle'}}, '1203461241.98akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(80.016, -299.305, 0.909), 'Hpr': VBase3(-67.45, 72.134, -81.692), 'Pos': Point3(-150.048, 271.057, 0.909), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/anchor'}}, '1203461317.66akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(81.515, -305.43, -2.556), 'Hpr': VBase3(-114.141, 0.0, 0.0), 'Pos': Point3(-152.984, 276.637, -2.556), 'Scale': VBase3(2.901, 2.8, 2.541), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_cube'}}, '1203461390.23akelts': {'Type': 'Ship_Props', 'DisableCollision': True, 'GridPos': Point3(356.1, -191.262, 12.71), 'Hpr': VBase3(37.994, 25.166, 8.484), 'Pos': Point3(-391.793, 99.432, 12.71), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/wheel_wallprop'}}, '1203461510.47akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(367.133, -187.329, 7.703), 'Hpr': VBase3(-62.834, 0.0, 0.0), 'Pos': Point3(-401.547, 92.947, 7.703), 'Scale': VBase3(0.858, 1.158, 1.814), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1203464268.55akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-248.872, 56.43, 53.321), 'Hpr': VBase3(80.59, 0.0, 0.0), 'Pos': Point3(255.131, 5.454, 53.321), 'Scale': VBase3(0.277, 0.277, 0.277), 'Visual': {'Color': (0.6666666666666666, 0.6862745098039216, 0.6196078431372549, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1203464436.53akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(634.943, 474.118, -28.164), 'Hpr': VBase3(60.475, 0.0, 0.0), 'Pos': Point3(-501.383, -613.641, -28.164), 'Scale': VBase3(2.127, 4.157, 1.658), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_med'}}, '1203464470.73akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-480.084, -150.307, -10.216), 'Holiday': '', 'Hpr': VBase3(-79.144, 0.0, 0.0), 'Pos': Point3(429.461, 261.985, -10.216), 'Scale': VBase3(0.795, 0.795, 1.328), 'VisSize': '', 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_med2'}}, '1203464494.17akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-364.214, -186.04, -46.772), 'Hpr': VBase3(119.847, 0.0, 0.0), 'Pos': Point3(308.388, 268.625, -46.772), 'Scale': VBase3(0.496, 0.218, 0.387), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1203464564.14akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-397.039, -82.45, -12.623), 'Hpr': VBase3(29.204, -2.384, -1.67), 'Pos': Point3(344.939, 241.389, -14.999), 'Scale': VBase3(10.312, 10.312, 13.142), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1204059355.98akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(378.365, -98.236, 55.701), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-390.891, 3.783, 55.701), 'Scale': VBase3(0.63, 0.63, 0.63), 'Visual': {'Model': 'models/vegetation/jungle_tree_a'}}, '1204059414.83akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(436.083, 152.175, 68.61), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-386.315, -253.153, 67.418), 'Scale': VBase3(0.886, 0.886, 0.886), 'Visual': {'Model': 'models/vegetation/jungle_tree_b'}}, '1204059436.81akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(434.287, 150.665, 153.061), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-384.938, -251.253, 153.061), 'Scale': VBase3(2.376, 2.376, 2.376), 'Visual': {'Model': 'models/vegetation/gen_tree_canopy'}}, '1204059462.52akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(373.505, -95.759, 108.721), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-385.576, 2.556, 108.721), 'Scale': VBase3(1.822, 1.822, 1.822), 'Visual': {'Model': 'models/vegetation/gen_tree_canopy'}}, '1204059672.03akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(429.505, 171.393, 65.983), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-385.97, -260.881, 65.983), 'Scale': VBase3(1.425, 1.425, 1.425), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059711.06akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(418.896, 149.38, 70.456), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-369.404, -245.119, 70.456), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059712.09akelts': {'Type': 'Jungle_Props', 'DisableCollision': True, 'GridPos': Point3(442.281, 124.117, 68.171), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-399.117, -227.428, 68.171), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059713.08akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(389.753, 118.221, 74.347), 'Hpr': VBase3(-49.308, 0.0, 0.0), 'Pos': Point3(-349.575, -208.999, 74.347), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059716.5akelts': {'Type': 'Jungle_Props', 'DisableCollision': True, 'GridPos': Point3(320.185, 136.75, 72.585), 'Hpr': VBase3(94.213, 0.0, 0.0), 'Pos': Point3(-263.212, -198.348, 69.211), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059717.45akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(308.702, -18.82, 50.535), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-304.085, -56.421, 50.535), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059719.28akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(334.166, -11.613, 55.404), 'Hpr': VBase3(-25.785, 0.0, 0.0), 'Pos': Point3(-327.049, -69.574, 55.404), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059720.05akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(366.624, -93.04, 54.728), 'Hpr': VBase3(46.146, 0.0, 0.0), 'Pos': Point3(-378.242, 1.582, 54.728), 'Scale': VBase3(2.142, 2.142, 2.142), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059724.55akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(365.774, -126.676, 52.054), 'Hpr': VBase3(-74.251, 0.0, 0.0), 'Pos': Point3(-402.137, 14.514, 56.562), 'Scale': VBase3(1.447, 1.447, 1.447), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059729.58akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(303.472, 235.871, 70.807), 'Hpr': VBase3(-114.87, 0.0, 0.0), 'Pos': Point3(-237.395, -302.281, 70.807), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059732.36akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(332.631, 217.935, 72.079), 'Hpr': VBase3(154.057, 0.0, 0.0), 'Pos': Point3(-270.378, -293.44, 72.079), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059735.73akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-135.625, 167.256, 59.099), 'Hpr': VBase3(-91.621, 0.0, 0.0), 'Pos': Point3(172.059, -129.477, 59.099), 'Scale': VBase3(3.215, 3.215, 3.215), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059738.44akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-311.632, 72.085, 54.836), 'Hpr': VBase3(34.577, -2.462, 2.937), 'Pos': Point3(319.814, 5.447, 54.836), 'Scale': VBase3(2.543, 2.543, 2.543), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059742.03akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-204.7, 64.536, 59.859), 'Hpr': VBase3(-62.086, 0.0, 0.0), 'Pos': Point3(214.232, -13.098, 59.859), 'Scale': VBase3(1.31, 1.31, 1.31), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204059934.52akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(416.271, 106.319, 70.657), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-383.295, -227.551, 69.176), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059949.56akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(356.348, 227.762, 71.117), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-290.662, -307.205, 71.117), 'Scale': VBase3(1.786, 1.786, 1.786), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059953.34akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(362.621, -33.439, 55.184), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-359.939, -55.28, 55.184), 'Scale': VBase3(1.842, 1.842, 1.842), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059956.41akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(443.025, 46.973, 51.688), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-418.501, -152.755, 51.688), 'Scale': VBase3(1.416, 1.416, 1.416), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059960.55akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(86.091, 6.299, 44.858), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(-82.01, -26.939, 44.858), 'Scale': VBase3(1.716, 1.716, 1.716), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059962.81akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(177.224, -122.102, 59.848), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059966.33akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(10.566, 200.632, 54.196), 'Hpr': VBase3(17.523, 4.607, 0.0), 'Pos': Point3(-0.087, -202.037, 51.809), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1204059991.02akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-71.176, 148.108, 57.32), 'Hpr': VBase3(-39.873, -6.618, 0.0), 'Pos': Point3(103.179, -147.109, 58.268), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_b'}}, '1204060027.94akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(427.862, -97.178, 59.092), 'Hpr': VBase3(-39.873, 0.0, 0.0), 'Pos': Point3(-438.662, -9.218, 59.092), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_b'}}, '1204060031.36akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(287.315, 208.111, 69.716), 'Hpr': VBase3(-39.873, 0.0, 0.0), 'Pos': Point3(-238.041, -273.163, 70.456), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_b'}}, '1204060033.45akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(81.244, 50.514, 45.215), 'Hpr': VBase3(-39.873, 0.0, 0.0), 'Pos': Point3(-66.61, -68.668, 45.215), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_b'}}, '1204060035.7akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-176.185, 67.495, 58.068), 'Hpr': VBase3(-39.873, 0.0, 0.0), 'Pos': Point3(187.28, -22.867, 58.068), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_b'}}, '1204060039.77akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(288.688, -139.356, 15.846), 'Hpr': VBase3(-107.761, 0.0, 0.0), 'Pos': Point3(-313.826, 65.377, 15.846), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060065.31akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(375.752, -140.106, 53.385), 'Hpr': VBase3(-38.721, 0.0, 0.0), 'Pos': Point3(-398.485, 45.042, 53.385), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060071.86akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(450.016, 164.31, 64.582), 'Hpr': VBase3(86.499, 0.0, 0.0), 'Pos': Point3(-396.898, -268.298, 64.582), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060074.63akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(301.719, 233.301, 72.271), 'Hpr': VBase3(-141.78, 0.0, 0.0), 'Pos': Point3(-236.316, -299.363, 72.271), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060078.2akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-205.21, 62.988, 60.031), 'Hpr': VBase3(22.412, 0.0, 0.0), 'Pos': Point3(214.353, -11.472, 60.031), 'Scale': VBase3(1.784, 1.784, 1.784), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060082.56akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-160.916, 25.381, 7.156), 'Hpr': VBase3(-21.407, 0.0, 0.0), 'Pos': Point3(173.497, 29.662, 5.825), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_c'}}, '1204060470.2akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-264.603, 85.234, 60.517), 'Hpr': VBase3(-59.9, 0.0, 0.0), 'Pos': Point3(277.363, -18.689, 60.517), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060505.48akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-312.242, 71.998, 54.357), 'Hpr': VBase3(40.51, -1.437, 10.232), 'Pos': Point3(320.385, 5.679, 54.357), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060511.89akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(10.953, 200.962, 54.248), 'Hpr': VBase3(-142.944, 0.0, 0.0), 'Pos': Point3(-0.594, -202.56, 53.115), 'Scale': VBase3(2.628, 2.628, 2.628), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060515.3akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(421.854, 142.243, 70.26), 'Hpr': VBase3(-108.413, 0.0, 0.0), 'Pos': Point3(-374.911, -240.073, 70.26), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060521.22akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(349.687, -40.622, 54.939), 'Hpr': VBase3(-59.227, 0.0, 0.0), 'Pos': Point3(-349.127, -45.182, 54.939), 'Scale': VBase3(2.331, 2.331, 2.331), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060524.36akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(410.33, 220.943, 59.965), 'Hpr': VBase3(-42.318, 0.0, 0.0), 'Pos': Point3(-273.769, -210.245, 71.375), 'Scale': VBase3(2.365, 2.365, 2.365), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204060821.13akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-50.908, 145.155, 55.857), 'Hpr': VBase3(17.523, 0.0, 0.0), 'Pos': Point3(127.591, -134.276, 58.11), 'Scale': VBase3(3.621, 3.621, 3.621), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_a'}}, '1204060855.45akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(378.983, 48.666, 51.35), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(-355.952, -138.905, 51.35), 'Scale': VBase3(0.862, 0.862, 0.862), 'Visual': {'Color': (0.9098039215686274, 0.91, 0.8823529411764706, 1.0), 'Model': 'models/props/cliff_jungle_high'}}, '1204060956.09akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(391.222, 24.473, 84.037), 'Hpr': VBase3(-173.107, 0.0, 0.0), 'Pos': Point3(-373.68, -118.391, 84.037), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204061028.02akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(363.031, 32.413, 120.982), 'Hpr': VBase3(100.37, 0.0, 0.0), 'Pos': Point3(-344.406, -119.275, 120.982), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204061061.27akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-253.02, 39.159, 4.524), 'Hpr': VBase3(177.321, 0.0, 0.0), 'Pos': Point3(254.978, 23.215, 4.524), 'Scale': VBase3(0.517, 0.806, 1.208), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_low'}}, '1204134204.59akelts': {'Type': 'Wall_Hangings', 'DisableCollision': False, 'GridPos': Point3(-361.086, 2.343, 33.233), 'Hpr': VBase3(-127.141, 0.0, 0.0), 'Pos': Point3(350.927, 85.082, 33.233), 'Scale': VBase3(1.265, 1.265, 1.265), 'Visual': {'Model': 'models/props/flag_hanging_spanish'}}, '1204134436.16akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(331.941, -187.044, 10.127), 'Hpr': VBase3(137.858, 0.0, 0.0), 'Pos': Point3(-367.331, 101.184, 10.127), 'Scale': VBase3(1.312, 1.312, 2.355), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1204134561.33akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-386.568, 32.712, 34.035), 'Hpr': VBase3(51.145, 36.797, 3.04), 'Objects': {}, 'Pos': Point3(382.999, 61.779, 34.035), 'Scale': VBase3(0.487, 0.487, 0.487), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1204134680.02akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-397.012, 46.512, 21.197), 'Hpr': VBase3(51.774, 26.09, 2.71), 'Objects': {}, 'Pos': Point3(396.471, 50.915, 21.197), 'Scale': VBase3(0.487, 0.487, 0.487), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1204134735.98akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-408.907, 61.839, 11.764), 'Hpr': VBase3(52.383, 13.484, 2.503), 'Objects': {}, 'Pos': Point3(411.721, 38.921, 11.764), 'Scale': VBase3(0.489, 0.485, 0.485), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1204134910.91akelts': {'Type': 'Stairs', 'DisableCollision': False, 'GridPos': Point3(-424.124, 81.44, 5.888), 'Hpr': VBase3(-127.584, -16.059, -2.35), 'Objects': {}, 'Pos': Point3(431.228, 23.584, 5.888), 'Scale': VBase3(1.408, 1.354, 1.0), 'Visual': {'Color': (0.7900000214576721, 0.7799999713897705, 0.699999988079071, 1.0), 'Model': 'models/buildings/landing_double'}}, '1204135098.84akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-426.176, 75.798, 7.394), 'Hpr': VBase3(67.466, 0.0, 0.0), 'Pos': Point3(431.854, 29.555, 7.394), 'Scale': VBase3(0.467, 0.467, 0.467), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1204135135.33akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(-418.286, 82.472, 7.667), 'Hpr': VBase3(41.78, 0.0, 0.0), 'Pos': Point3(425.813, 21.17, 7.667), 'Scale': VBase3(0.467, 0.467, 0.467), 'Visual': {'Model': 'models/props/shanty_rope_bridge_post'}}, '1204237124.22akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'GridPos': Point3(302.232, 58.179, 61.849), 'Hpr': VBase3(-24.821, 0.0, 0.0), 'Pos': Point3(-249.919, -140.602, 65.961), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1204237124.2akelts': {'Type': 'Building Exterior', 'File': 'pvpShipIsland2_int_tavern', 'ExtUid': '1204237124.2akelts0', 'GridPos': Point3(279.715, 79.133, 65.009), 'Hpr': VBase3(155.008, 0.0, 0.0), 'Objects': {'1210373723.53akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-179.829, 0.0, 0.0), 'Pos': Point3(-0.498, -4.914, 0.952), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1210373725.94akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(-6.626, 20.947, 1.006), 'Scale': VBase3(1.0, 1.0, 1.0)}}, 'Pos': Point3(-252.262, -144.452, 65.009), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Door': 'models/buildings/shanty_guildhall_door', 'Model': 'models/buildings/shanty_tavern_exterior', 'SignFrame': 'models/buildings/sign1_shanty_a_frame', 'SignImage': 'models/buildings/sign1_eng_a_icon_tavern'}}, '1204237223.91akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(300.519, 59.182, 55.163), 'Hpr': VBase3(49.106, -7.069, 0.377), 'Objects': {}, 'Pos': Point3(-277.275, -130.126, 55.163), 'Scale': VBase3(4.034, 4.034, 4.034), 'Visual': {'Color': (0.3, 0.35, 0.3, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1204237285.34akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(297.582, 77.276, 60.49), 'Hpr': VBase3(139.493, 0.0, 0.0), 'Pos': Point3(-270.048, -146.972, 60.49), 'Scale': VBase3(2.085, 2.085, 2.085), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1204237296.23akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(310.905, 61.79, 58.761), 'Hpr': VBase3(89.852, 0.0, 0.0), 'Pos': Point3(-286.721, -135.169, 58.761), 'Scale': VBase3(2.365, 2.365, 2.365), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1204237768.98akelts': {'Type': 'Bridge', 'DisableCollision': False, 'GridPos': Point3(273.809, 71.426, 65.813), 'Hpr': VBase3(155.336, 32.331, 0.0), 'Pos': Point3(-248.396, -135.545, 65.813), 'Scale': VBase3(0.357, 0.357, 0.357), 'Visual': {'Model': 'models/props/shanty_rope_bridge'}}, '1204237956.03akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': True, 'GridPos': Point3(-20.251, 72.751, -29.831), 'Hpr': VBase3(-175.338, 0.0, 0.0), 'Pos': Point3(37.25, -65.691, -29.831), 'Scale': VBase3(0.512, 0.798, 0.891), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_low'}}, '1208535913.67akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(155.008, 0.0, 0.0), 'Pos': Point3(-255.062, -166.14, 66.015), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208535916.31akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'GridPos': Point3(-6.626, 20.841, 1.006), 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(-6.626, 20.947, 1.006), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208551336.89akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-90.0, 0.0, 0.0), 'Pos': Point3(-0.277, -13.756, 1.023), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208551339.09akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-6.626, 20.841, 1.006), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208796482.19akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-180.0, 0.0, 0.0), 'Pos': Point3(-0.277, -13.756, 1.561), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208796484.09akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(-6.626, 20.841, 1.006), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1208796484.17akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-90.0, 0.0, 0.0), 'Pos': Point3(-0.277, -13.756, 1.023), 'Scale': VBase3(1.0, 1.0, 1.0), 'TargetUIDs': []}, '1208808622.33akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(373.505, -95.759, 108.721), 'Hpr': VBase3(-120.335, 0.0, 0.0), 'Pos': Point3(-389.709, 3.032, 83.613), 'Scale': VBase3(2.475, 2.475, 2.475), 'Visual': {'Model': 'models/vegetation/gen_tree_canopy'}}, '1208808661.47akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(434.287, 150.665, 153.061), 'Hpr': VBase3(165.025, 0.0, 0.0), 'Pos': Point3(-381.695, -252.656, 120.228), 'Scale': VBase3(3.921, 3.921, 3.921), 'Visual': {'Model': 'models/vegetation/gen_tree_canopy'}}, '1208808732.92akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(378.365, -98.236, 55.701), 'Hpr': VBase3(-166.0, 0.0, 0.0), 'Pos': Point3(32.495, -74.501, 48.622), 'Scale': VBase3(0.63, 0.63, 0.63), 'Visual': {'Model': 'models/vegetation/jungle_tree_a'}}, '1208808760.67akelts': {'Type': 'Tree', 'DisableCollision': False, 'GridPos': Point3(434.287, 150.665, 153.061), 'Hpr': VBase3(165.025, 0.0, 0.0), 'Pos': Point3(32.367, -75.712, 86.151), 'Scale': VBase3(2.483, 2.483, 2.483), 'Visual': {'Model': 'models/vegetation/gen_tree_canopy'}}, '1208808898.64akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(47.91, 0.0, 0.0), 'Pos': Point3(-261.705, -126.077, 59.113), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_c'}}, '1208808939.75akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(125.315, 0.0, 0.0), 'Pos': Point3(143.923, -142.808, 58.141), 'Scale': VBase3(1.618, 1.618, 1.618), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_b'}}, '1208808963.02akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(22.689, 0.0, 0.0), 'Pos': Point3(188.042, -1.397, 55.796), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/vegetation/fern_tree_e'}}, '1208808997.63akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(22.689, 0.0, 0.0), 'Pos': Point3(-95.527, -45.699, 44.614), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_e'}}, '1208809009.36akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(22.689, 0.0, 0.0), 'Pos': Point3(-251.118, -214.264, 68.142), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_d'}}, '1208809176.83akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-152.604, 9.484, -0.719), 'Pos': Point3(-393.582, -127.052, 106.869), 'Scale': VBase3(0.768, 0.768, 0.768), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208809279.59akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(170.168, 6.682, 0.702), 'Pos': Point3(-345.264, -108.754, 77.239), 'Scale': VBase3(0.611, 0.611, 0.611), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208809368.11akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-89.621, 5.143, -0.989), 'Pos': Point3(-380.451, -75.759, 89.566), 'Scale': VBase3(0.768, 0.768, 0.768), 'Visual': {'Model': 'models/vegetation/jungle_vine_b_200'}}, '1208809472.88akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-89.723, -0.81, -0.985), 'Pos': Point3(-405.017, -228.593, 101.856), 'Scale': VBase3(0.499, 0.499, 0.499), 'Visual': {'Model': 'models/vegetation/jungle_vine_a_200'}}, '1208809510.83akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-88.774, 4.11, -1.05), 'Pos': Point3(-378.834, -85.961, 66.476), 'Scale': VBase3(0.768, 0.768, 0.768), 'Visual': {'Model': 'models/vegetation/jungle_vine_b'}}, '1208809617.05akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-50.908, 145.155, 55.857), 'Hpr': VBase3(7.579, -15.377, -21.436), 'Pos': Point3(43.315, -214.982, 98.948), 'Scale': VBase3(3.621, 3.621, 3.621), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_a'}}, '1208809694.8akelts': {'Type': 'Tree', 'DisableCollision': False, 'Hpr': VBase3(176.031, 3.973, 3.375), 'Pos': Point3(-416.074, -131.345, 48.889), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_e'}}, '1208809918.53akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-138.094, 0.0, 0.0), 'Pos': Point3(7.654, -39.037, 1.044), 'Scale': VBase3(4.081, 3.438, 3.438), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208809947.38akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(135.041, 0.0, 0.0), 'Pos': Point3(70.424, -43.033, 1.374), 'Scale': VBase3(4.466, 3.438, 3.438), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208809958.27akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(176.825, 0.0, 0.0), 'Pos': Point3(38.433, -26.713, 1.435), 'Scale': VBase3(3.411, 3.438, 3.438), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208809992.67akelts': {'Type': 'Tree', 'DisableCollision': True, 'Hpr': VBase3(96.609, 0.0, 0.0), 'Pos': Point3(64.792, -40.461, 3.8), 'Scale': VBase3(1.618, 1.618, 1.618), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/fern_tree_b'}}, '1208810053.52akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(26.944, -20.071, 27.201), 'Pos': Point3(-324.041, -128.121, 124.495), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1208810085.05akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(-44.557, -6.521, -19.024), 'Pos': Point3(-384.556, -122.727, 70.807), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1208810147.31akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(-44.557, -6.521, -32.391), 'Pos': Point3(-319.36, 28.518, 83.478), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1208810201.73akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(126.499, 14.847, -27.086), 'Pos': Point3(-273.456, 11.863, 112.912), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1208810269.45akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(2.536, 27.623, 19.921), 'Pos': Point3(-289.021, -16.521, 115.903), 'Scale': VBase3(1.764, 1.764, 1.764), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1208810310.83akelts': {'Type': 'Jungle_Props', 'DisableCollision': True, 'GridPos': Point3(334.166, -11.613, 55.404), 'Hpr': VBase3(-25.785, 0.0, 0.0), 'Pos': Point3(-316.557, -36.24, 78.313), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1208810354.47akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(89.22, 0.0, 0.0), 'Pos': Point3(-268.512, -167.831, 64.81), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_a'}}, '1208810406.28akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(42.896, 0.0, 0.0), 'Pos': Point3(-263.945, -170.113, 65.123), 'Scale': VBase3(1.751, 1.528, 2.106), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208810445.06akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(-120.367, 0.0, 0.0), 'Pos': Point3(-227.166, -141.207, 60.731), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_b'}}, '1208810495.61akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(5.202, 0.0, 0.0), 'Pos': Point3(-227.969, -151.672, 61.043), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_a'}}, '1208810525.34akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(-177.316, 0.0, 0.0), 'Pos': Point3(-237.907, -168.971, 64.36), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_c'}}, '1208810579.08akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(116.707, 0.0, 0.0), 'Pos': Point3(-289.16, -214.182, 71.69), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208810621.84akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(67.606, -13.881, -3.556), 'Pos': Point3(-415.072, -184.363, 63.056), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208810658.95akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(143.61, -4.213, 1.999), 'Pos': Point3(-372.745, -218.333, 70.758), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208810807.19akelts': {'Type': 'Bush', 'DisableCollision': False, 'Hpr': VBase3(16.68, 0.933, -4.568), 'Pos': Point3(-409.053, -250.846, 63.391), 'Scale': VBase3(1.494, 1.494, 1.494), 'Visual': {'Model': 'models/vegetation/bush_a'}}, '1208810877.0akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-14.393, 0.0, -0.641), 'Pos': Point3(-376.852, -191.819, 113.669), 'Scale': VBase3(0.967, 0.967, 0.967), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208810934.53akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-14.379, 1.321, -0.642), 'Pos': Point3(-361.836, -195.187, 110.096), 'Scale': VBase3(0.991, 0.991, 0.991), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208811023.73akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(320.185, 136.75, 72.585), 'Hpr': VBase3(-28.499, 0.0, 0.0), 'Pos': Point3(-309.069, -193.754, 138.788), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1208811068.98akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(26.995, 0.0, 0.0), 'Pos': Point3(-253.548, -274.59, 71.384), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208811084.52akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(114.363, 0.0, 0.0), 'Pos': Point3(-260.596, -277.698, 71.062), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/bush_a'}}, '1208811112.3akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(114.363, 0.0, 0.0), 'Pos': Point3(-255.875, -312.572, 73.767), 'Scale': VBase3(1.64, 1.64, 1.64), 'Visual': {'Model': 'models/vegetation/bush_f'}}, '1208811262.97akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-104.857, 8.588, 0.554), 'Pos': Point3(70.866, -289.357, 41.508), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208811381.53akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-140.417, 8.37, -0.751), 'Pos': Point3(96.405, -188.832, 124.112), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208811429.42akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-156.372, 4.411, 1.348), 'Pos': Point3(49.123, -205.952, 87.759), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_b'}}, '1208811768.8akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-144.406, -3.176, -2.17), 'Pos': Point3(130.64, -158.195, 55.691), 'Scale': VBase3(4.774, 4.774, 3.344), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811772.16akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-164.65, -7.956, -5.292), 'Pos': Point3(25.948, -214.116, 50.396), 'Scale': VBase3(4.774, 4.774, 5.112), 'Visual': {'Color': (0.396078431372549, 0.42, 0.3803921568627451, 1.0), 'Model': 'models/props/rock_group_4_sphere'}}, '1208811773.16akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(17.497, -8.36, -3.957), 'Pos': Point3(6.864, -72.534, 43.129), 'Scale': VBase3(4.774, 4.774, 6.087), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1208811773.94akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-142.664, -17.303, 4.712), 'Pos': Point3(-72.831, -222.386, 41.214), 'Scale': VBase3(3.184, 3.184, 3.243), 'Visual': {'Color': (0.396078431372549, 0.42, 0.3411764705882353, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811776.03akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-161.098, 4.104, -7.064), 'Pos': Point3(-105.811, -43.819, 40.714), 'Scale': VBase3(3.622, 3.622, 4.618), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_1_sphere'}}, '1208811776.83akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-18.803, -7.562, -6.653), 'Pos': Point3(-130.606, -50.685, 41.261), 'Scale': VBase3(4.774, 4.774, 6.087), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811777.47akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-124.532, -11.815, -8.258), 'Pos': Point3(-201.207, -171.957, 58.879), 'Scale': VBase3(3.248, 3.231, 3.649), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_4_sphere'}}, '1208811779.14akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-6.284, -22.385, -2.016), 'Pos': Point3(217.209, -16.696, 52.7), 'Scale': VBase3(4.774, 4.774, 6.087), 'Visual': {'Color': (0.40784313725490196, 0.4666666666666667, 0.4666666666666667, 1.0), 'Model': 'models/props/rock_group_4_sphere'}}, '1208811781.34akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-168.086, -1.639, -2.347), 'Pos': Point3(-343.132, -111.009, 54.7), 'Scale': VBase3(2.781, 2.781, 4.177), 'Visual': {'Color': (0.3, 0.33, 0.3, 1.0), 'Model': 'models/props/rock_group_2_floor'}}, '1208811783.25akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(148.652, 2.572, -1.384), 'Pos': Point3(-275.718, 60.876, 16.415), 'Scale': VBase3(4.774, 4.774, 4.154), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_2_floor'}}, '1208811785.25akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-105.1, -3.598, -12.609), 'Pos': Point3(-253.606, -58.999, 43.976), 'Scale': VBase3(4.774, 4.774, 4.447), 'Visual': {'Color': (0.31, 0.35, 0.33725490196078434, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208811787.06akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-78.513, -6.5, -4.951), 'Pos': Point3(-207.322, -279.756, 65.605), 'Scale': VBase3(3.573, 3.573, 4.555), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208811787.67akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(76.484, 3.8, 7.232), 'Pos': Point3(-198.1, -264.836, 62.839), 'Scale': VBase3(2.14, 2.14, 2.729), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_1_sphere'}}, '1208811788.55akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-81.471, 0.288, 2.826), 'Objects': {}, 'Pos': Point3(-347.282, -359.77, 2.243), 'Scale': VBase3(4.774, 4.774, 2.502), 'Visual': {'Color': (0.51, 0.56, 0.4117647058823529, 1.0), 'Model': 'models/props/rock_group_3_floor'}}, '1208811791.69akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-144.212, -3.487, 1.627), 'Objects': {}, 'Pos': Point3(-439.805, -46.958, 51.483), 'Scale': VBase3(4.774, 4.774, 3.13), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811792.56akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-103.908, 5.818, -0.009), 'Pos': Point3(-440.195, -134.889, 4.905), 'Scale': VBase3(5.184, 5.184, 3.887), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208811794.17akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-53.521, 0.061, 4.353), 'Objects': {}, 'Pos': Point3(-284.11, -361.855, -5.75), 'Scale': VBase3(4.774, 4.774, 6.592), 'Visual': {'Color': (0.51, 0.54, 0.4392156862745098, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811795.17akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-54.019, -2.465, 3.047), 'Pos': Point3(-312.574, -358.779, -1.533), 'Scale': VBase3(4.774, 4.774, 2.621), 'Visual': {'Color': (0.38, 0.37, 0.3254901960784314, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811800.08akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(72.206, 1.431, 3.479), 'Pos': Point3(-95.254, 45.803, 6.346), 'Scale': VBase3(4.774, 4.774, 5.603), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_2_sphere'}}, '1208811801.2akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(13.261, -4.517, 3.1), 'Pos': Point3(-127.097, 70.881, 8.023), 'Scale': VBase3(5.456, 5.456, 6.378), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208811802.09akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(164.573, 7.369, -3.526), 'Pos': Point3(-246.819, 286.594, 1.077), 'Scale': VBase3(2.204, 2.204, 1.801), 'Visual': {'Color': (0.59, 0.59, 0.49, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811803.81akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-44.474, -0.255, -3.966), 'Pos': Point3(262.736, 64.252, 4.217), 'Scale': VBase3(4.774, 4.774, 8.168), 'Visual': {'Color': (0.4, 0.44, 0.4, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1208811804.59akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(82.765, 2.384, -5.346), 'Pos': Point3(399.969, 43.546, 5.943), 'Scale': VBase3(2.154, 2.154, 1.875), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208811805.2akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Holiday': '', 'Hpr': VBase3(162.426, 1.496, 3.991), 'Pos': Point3(340.371, 163.849, -8.271), 'Scale': VBase3(5.11, 5.11, 6.515), 'VisSize': '', 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208811806.67akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-169.822, -0.966, 6.1), 'Pos': Point3(407.35, 4.291, 2.735), 'Scale': VBase3(4.774, 4.774, 3.419), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_4_floor'}}, '1208811976.0akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-109.949, 0.17, 14.322), 'Objects': {}, 'Pos': Point3(-59.92, -209.918, 43.193), 'Scale': VBase3(3.184, 3.184, 3.243), 'Visual': {'Color': (0.41, 0.43, 0.37254901960784315, 1.0), 'Model': 'models/props/rock_group_1_floor'}}, '1208812034.0akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-119.258, -1.685, -7.991), 'Pos': Point3(-212.892, -172.3, 61.45), 'Scale': VBase3(3.248, 3.248, 2.144), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_floor'}}, '1208817172.09akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(322.479, 227.694, 71.845), 'Hpr': VBase3(39.268, 0.0, -3.187), 'Pos': Point3(-336.356, -361.238, 2.893), 'Scale': VBase3(1.529, 1.529, 1.96), 'Visual': {'Color': (0.54, 0.53, 0.4392156862745098, 1.0), 'Model': 'models/props/rock_group_2_floor'}}, '1208817254.27akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-132.321, 8.184, -1.918), 'Pos': Point3(194.072, 26.594, 40.152), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1208817508.89akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(120.805, -3.248, -1.273), 'Pos': Point3(210.092, -42.115, 59.432), 'Scale': VBase3(1.86, 1.86, 2.372), 'Visual': {'Color': (0.36, 0.41, 0.40784313725490196, 1.0), 'Model': 'models/props/rock_group_1_floor'}}, '1208817704.22akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(113.954, -0.344, 3.212), 'Pos': Point3(50.036, -76.127, 48.039), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208817733.41akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(-96.242, 1.914, -2.603), 'Pos': Point3(92.744, -66.711, 51.079), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_d'}}, '1208817744.48akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(-44.302, -0.872, -7.43), 'Pos': Point3(102.097, -61.139, 51.013), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_a'}}, '1208817783.52akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-30.979, -42.476, -11.649), 'Hpr': VBase3(-127.745, 8.254, -2.493), 'Objects': {}, 'Pos': Point3(126.418, -59.327, 50.686), 'Scale': VBase3(4.171, 4.171, 7.842), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1208817904.31akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(104.912, -5.654, -1.867), 'Pos': Point3(-259.361, -212.369, 66.971), 'Scale': VBase3(2.14, 2.14, 2.729), 'Visual': {'Color': (0.4, 0.45, 0.4, 1.0), 'Model': 'models/props/rock_group_2_sphere'}}, '1208818191.44akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-49.797, -4.814, -2.614), 'Pos': Point3(-55.816, -11.111, 3.947), 'Scale': VBase3(5.456, 5.456, 5.724), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1208818217.42akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(361.155, -135.951, 48.755), 'Hpr': VBase3(80.349, -8.033, -1.43), 'Pos': Point3(-468.491, 13.451, 0.893), 'Scale': VBase3(10.925, 10.925, 10.376), 'Visual': {'Color': (0.29, 0.31, 0.25, 1.0), 'Model': 'models/props/rock_group_3_sphere'}}, '1208818540.86akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-20.251, 72.751, -29.831), 'Hpr': VBase3(102.073, 0.0, 0.0), 'Pos': Point3(-267.897, 2.215, -9.048), 'Scale': VBase3(0.462, 0.798, 1.253), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_low'}}, '1208818602.13akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(0.358, 7.602, 15.859), 'Pos': Point3(-240.404, 22.504, 61.208), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1208818653.27akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(-40.754, -17.65, 30.399), 'Pos': Point3(-259.388, -9.174, 86.627), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1208818734.8akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-20.251, 72.751, -29.831), 'Hpr': VBase3(-157.802, 0.0, 0.0), 'Pos': Point3(92.958, -191.914, 27.716), 'Scale': VBase3(0.877, 0.877, 0.877), 'Visual': {'Color': (0.95, 1.0, 0.95, 1.0), 'Model': 'models/props/cliff_jungle_high'}}, '1208824971.89akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(76.961, 2.914, -5.078), 'Pos': Point3(414.891, 42.336, 5.732), 'Scale': VBase3(1.342, 1.342, 1.711), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_3_floor'}}, '1208825047.78akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(142.674, 0.0, 0.0), 'Pos': Point3(411.115, 48.001, 6.511), 'Scale': VBase3(1.562, 1.562, 1.562), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208825097.28akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(398.265, 45.218, 6.763), 'Hpr': VBase3(-87.855, 0.0, 0.0), 'Pos': Point3(398.265, 45.218, 6.763), 'Scale': VBase3(0.827, 1.562, 1.562), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208825126.22akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(-40.0, 0.0, 0.0), 'Pos': Point3(403.249, 37.278, 6.682), 'Scale': VBase3(1.288, 1.562, 1.562), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208825212.38akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(-152.232, 0.0, 0.0), 'Pos': Point3(401.61, 50.943, 6.664), 'Scale': VBase3(0.817, 1.562, 1.562), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1208825312.16akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(-40.0, 0.0, 0.0), 'Pos': Point3(380.069, -12.385, 6.999), 'Scale': VBase3(5.23, 5.23, 5.23), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1208825386.56akelts': {'Type': 'Rock', 'DisableCollision': True, 'Hpr': VBase3(23.665, 0.0, 0.0), 'Pos': Point3(391.334, 0.09, 2.161), 'Scale': VBase3(7.302, 7.302, 13.415), 'Visual': {'Color': (0.42, 0.42, 0.4235294117647059, 1.0), 'Model': 'models/props/rock_4_floor'}}, '1208892989.37akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-20.251, 72.751, -29.831), 'Hpr': VBase3(153.104, -12.027, 0.0), 'Pos': Point3(444.135, -28.345, -18.929), 'Scale': VBase3(0.512, 0.86, 0.891), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_low'}}, '1208893039.39akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-253.02, 39.159, 4.524), 'Hpr': VBase3(11.801, 0.0, 0.0), 'Pos': Point3(374.794, -157.153, -11.709), 'Scale': VBase3(0.732, 0.737, 0.857), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_high'}}, '1208893077.73akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-253.02, 39.159, 4.524), 'Hpr': VBase3(35.111, 0.0, 0.0), 'Pos': Point3(152.822, -265.197, -2.141), 'Scale': VBase3(1.117, 1.629, 1.308), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_high'}}, '1208893136.55akelts': {'Type': 'Jungle_Props_large', 'DisableCollision': False, 'GridPos': Point3(-253.02, 39.159, 4.524), 'Hpr': VBase3(42.802, 0.0, 0.0), 'Pos': Point3(250.256, -179.188, -1.664), 'Scale': VBase3(0.958, 1.397, 1.34), 'Visual': {'Color': (1.0, 1.0, 1.0, 1.0), 'Model': 'models/props/cliff_jungle_low'}}, '1208906898.45akelts': {'Type': 'Shanty Tents', 'Hpr': VBase3(-151.762, 0.0, 0.0), 'Pos': Point3(45.696, -178.938, 55.527), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/buildings/shanty_tent_house_facade'}}, '1208906917.51akelts': {'Type': 'Shanty Tents', 'Hpr': VBase3(-151.762, 0.0, 0.0), 'Pos': Point3(45.449, -178.828, 54.51), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/buildings/shanty_tent_house_body'}}, '1208908188.33akelts': {'Type': 'Furniture', 'DisableCollision': False, 'Hpr': VBase3(178.593, 0.0, 0.0), 'Objects': {}, 'Pos': Point3(34.017, -172.752, 55.733), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.39, 0.42, 0.32941176470588235, 1.0), 'Model': 'models/props/bench_shanty_2'}}, '1208908264.25akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'Hpr': VBase3(42.9, 0.0, 0.0), 'Pos': Point3(48.883, -162.468, 55.873), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6784313725490196, 0.72, 0.7372549019607844, 1.0), 'Model': 'models/props/prop_group01'}}, '1208908273.23akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'Hpr': VBase3(91.545, 0.0, 0.0), 'Pos': Point3(57.282, -162.22, 55.76), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.7254901960784313, 0.86, 1.0, 1.0), 'Model': 'models/props/prop_group02'}}, '1208908304.17akelts': {'Type': 'Prop_Groups', 'DisableCollision': False, 'Hpr': VBase3(-72.238, 0.0, 0.0), 'Pos': Point3(19.111, -187.636, 55.085), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6, 0.65, 0.7, 1.0), 'Model': 'models/props/prop_group_A'}}, '1208908477.73akelts': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'axe_chop', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'GridPos': Point3(30.598, -172.947, 55.786), 'Hpr': VBase3(116.347, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '6.3795', 'Pos': Point3(65.15, -167.037, 55.695), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Player', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1208980254.31akelts': {'Type': 'Log_Stack', 'DisableCollision': False, 'Hpr': VBase3(27.629, 0.0, 0.0), 'Pos': Point3(60.091, -169.355, 55.448), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/gen_log02'}}, '1208985003.56akelts': {'Type': 'Furniture', 'DisableCollision': True, 'Hpr': VBase3(-72.826, 0.0, 0.0), 'Pos': Point3(54.273, -180.641, 55.071), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/bed_shantyB'}}, '1208985185.81akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(0.0, 0.0, -7.77), 'Pos': Point3(88.1, -75.872, 51.497), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985214.58akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(28.731, -3.753, 1.341), 'Pos': Point3(64.877, -82.739, 50.505), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985234.61akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(11.467, -0.188, 5.517), 'Pos': Point3(-83.433, -39.622, 44.559), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985272.09akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-30.18, -3.812, 3.995), 'Pos': Point3(-65.186, -47.953, 43.053), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985300.27akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(82.607, 5.162, 6.442), 'Pos': Point3(-232.561, -177.407, 63.937), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985322.83akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(65.033, 2.97, 3.21), 'Pos': Point3(-275.027, -207.207, 69.057), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/grass_18feet'}}, '1208985344.06akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(65.033, 2.97, 3.21), 'Pos': Point3(-274.887, -207.771, 70.266), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/vegetation/grass_8feet'}}, '1208985360.09akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(77.525, 3.594, 2.492), 'Pos': Point3(-265.904, -185.256, 66.955), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/grass_8feet'}}, '1208985376.95akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(77.525, 3.594, -4.742), 'Pos': Point3(-360.566, -215.821, 70.994), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985400.34akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(33.262, 5.88, -0.894), 'Pos': Point3(-361.461, -226.025, 69.61), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_8feet'}}, '1208985418.14akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-40.745, 2.488, 3.514), 'Pos': Point3(-369.478, -287.912, 63.513), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985454.22akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-86.597, -1.881, 3.859), 'Pos': Point3(-363.642, -251.563, 68.713), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985479.5akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-1.089, 14.411, -6.92), 'Pos': Point3(-316.819, -299.837, 67.223), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985517.81akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-2.635, 4.975, -1.055), 'Pos': Point3(246.537, -24.978, 59.993), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985544.53akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-148.536, -3.532, -2.452), 'Pos': Point3(272.652, -18.391, 59.866), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208985576.95akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(34.877, 3.488, 1.698), 'Pos': Point3(287.409, -14.742, 58.774), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208986572.17akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-124.66, -1.746, -0.668), 'Pos': Point3(148.161, -34.548, 52.598), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208986622.69akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(56.594, 1.761, 2.697), 'Pos': Point3(132.288, -56.048, 53.743), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208986646.89akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-142.604, -0.775, -0.615), 'Pos': Point3(112.824, -74.133, 54.446), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1208987108.2akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(-39.598, -1.124, -3.029), 'Pos': Point3(70.991, -74.959, 48.354), 'Scale': VBase3(1.246, 1.246, 1.246), 'Visual': {'Model': 'models/vegetation/bush_c'}}, '1208987212.84akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(10.566, 200.632, 54.196), 'Hpr': VBase3(17.523, 20.035, 0.0), 'Pos': Point3(91.882, -70.332, 51.882), 'Scale': VBase3(2.025, 2.025, 2.025), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1208991300.13akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(634.943, 474.118, -28.164), 'Hpr': VBase3(110.042, 0.0, 0.0), 'Pos': Point3(-204.673, -607.881, -41.891), 'Scale': VBase3(0.964, 1.112, 0.751), 'Visual': {'Color': (0.5899999737739563, 0.5899999737739563, 0.49000000953674316, 1.0), 'Model': 'models/props/mound_light_med2'}}, '1209140730.86akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(375.859, 82.108, 1.086), 'Hpr': VBase3(-171.208, 0.0, 0.0), 'Pos': Point3(-416.916, -181.892, -16.305), 'Scale': VBase3(0.761, 0.697, 1.033), 'Visual': {'Color': (0.42, 0.42, 0.33725490196078434, 1.0), 'Model': 'models/props/mound_light_med2'}}, '1209141015.28akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(375.859, 82.108, 1.086), 'Hpr': VBase3(90.399, 0.0, 0.0), 'Pos': Point3(-317.008, -321.238, -0.51), 'Scale': VBase3(0.247, 0.292, 0.554), 'Visual': {'Color': (0.42, 0.42, 0.33725490196078434, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1209141425.34akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(39.251, -4.673, -0.399), 'Pos': Point3(-246.574, -305.059, 2.045), 'Scale': VBase3(10.453, 10.453, 13.328), 'Visual': {'Color': (0.33, 0.35, 0.2784313725490196, 1.0), 'Model': 'models/props/rock_4_sphere'}}, '1209141691.17akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(-6.969, 263.14, 4.355), 'Hpr': VBase3(-43.967, -0.265, 8.111), 'Pos': Point3(-66.052, -233.064, 4.105), 'Scale': VBase3(14.765, 14.765, 14.765), 'Visual': {'Color': (0.32, 0.34, 0.2784313725490196, 1.0), 'Model': 'models/props/rock_3_sphere'}}, '1209141904.02akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-33.642, 4.487, -0.17), 'Pos': Point3(-346.824, -342.296, 36.594), 'Scale': VBase3(0.991, 0.991, 0.991), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1209142119.19akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-186.002, 32.546, 3.202), 'Hpr': VBase3(-13.372, -0.435, -0.872), 'Pos': Point3(197.41, 31.295, -2.443), 'Scale': VBase3(6.958, 6.958, 11.792), 'Visual': {'Color': (0.38, 0.4, 0.3254901960784314, 1.0), 'Model': 'models/props/rock_2_sphere'}}, '1209146067.22akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(322.479, 227.694, 71.845), 'Hpr': VBase3(-169.429, -14.405, 5.089), 'Pos': Point3(-372.955, -303.33, 59.802), 'Scale': VBase3(2.157, 2.157, 2.025), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/rock_group_2_floor'}}, '1209146181.89akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(170.771, 6.668, -7.352), 'Pos': Point3(-30.527, -67.842, 37.103), 'Scale': VBase3(5.456, 5.456, 6.378), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1209160185.02akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(-40.0, 0.0, 0.0), 'Pos': Point3(402.251, 10.911, 6.754), 'Scale': VBase3(2.494, 2.494, 2.494), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209160274.7akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-163.903, 8.208, -4.85), 'Pos': Point3(207.547, 35.805, 43.107), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_a'}}, '1209160379.91akelts': {'Type': 'Tree', 'DisableCollision': True, 'Hpr': VBase3(139.806, 0.0, 0.0), 'Pos': Point3(132.217, -53.285, 53.637), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.800000011920929, 0.800000011920929, 0.800000011920929, 1.0), 'Model': 'models/vegetation/fern_tree_c'}}, '1209160555.83akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(10.566, 200.632, 54.196), 'Hpr': VBase3(-157.393, 31.58, 2.796), 'Pos': Point3(90.158, -59.378, 48.938), 'Scale': VBase3(2.617, 2.617, 2.617), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_fern_b'}}, '1209160596.69akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(10.566, 200.632, 54.196), 'Hpr': VBase3(17.523, -1.265, 5.946), 'Pos': Point3(-15.443, -69.225, 43.767), 'Scale': VBase3(1.581, 1.581, 1.581), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1209160629.69akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-43.413, 9.327, -11.599), 'Pos': Point3(-25.643, -78.851, 41.809), 'Scale': VBase3(3.465, 3.465, 6.651), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_1_sphere'}}, '1209160682.22akelts': {'Type': 'Grass', 'DisableCollision': False, 'Hpr': VBase3(-36.445, 1.806, -11.462), 'Pos': Point3(12.577, -87.779, 46.959), 'Scale': VBase3(2.014, 2.014, 2.014), 'Visual': {'Model': 'models/vegetation/grass_18feet'}}, '1209160719.84akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(-11.599, 0.0, 0.0), 'Pos': Point3(-18.532, -47.773, 40.314), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_short_leaf_c_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_short_leaf_d_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_short_trunk_d_idle', 'Model': 'models/vegetation/fern_short_trunk_e_hi', 'PartName': 'trunk'}}, '1209160827.09akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(-11.599, 0.0, 0.0), 'Pos': Point3(-444.551, -208.964, 60.502), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_leaf_a_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_leaf_a_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_trunk_a_idle', 'Model': 'models/vegetation/fern_trunk_a_hi', 'PartName': 'trunk'}}, '1209160837.58akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(-11.599, 0.0, 0.0), 'Pos': Point3(-449.297, 15.15, 58.09), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_short_leaf_c_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_short_leaf_c_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_short_trunk_d_idle', 'Model': 'models/vegetation/fern_short_trunk_d_hi', 'PartName': 'trunk'}}, '1209160864.06akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(1.669, 0.0, 0.0), 'Pos': Point3(-359.654, 38.796, 48.389), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_short_leaf_c_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_short_leaf_c_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_short_trunk_d_idle', 'Model': 'models/vegetation/fern_short_trunk_d_hi', 'PartName': 'trunk'}}, '1209160896.47akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(36.166, 0.0, 0.0), 'Pos': Point3(254.104, 78.285, 6.637), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_short_leaf_c_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_short_leaf_c_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_short_trunk_d_idle', 'Model': 'models/vegetation/fern_short_trunk_d_hi', 'PartName': 'trunk'}}, '1209160973.97akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(253.975, 78.719, 6.253), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1209161079.81akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(-155.962, 302.425, 9.518), 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(-155.962, 302.425, 9.518), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/prop_group_A'}}, '1209161092.23akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(-200.172, 324.753, 9.442), 'Hpr': VBase3(89.343, 0.0, 0.0), 'Pos': Point3(-200.173, 324.753, 9.442), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/prop_group_B'}}, '1209161143.61akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(-179.92, 309.712, 7.794), 'Hpr': VBase3(-12.669, 0.0, 0.0), 'Pos': Point3(-179.92, 309.713, 7.794), 'Scale': VBase3(5.45, 2.8, 2.541), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209161288.52akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-246.642, -281.739, 69.556), 'Scale': VBase3(4.657, 4.657, 4.657), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161340.83akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(322.479, 227.694, 71.845), 'Hpr': VBase3(-170.939, 2.793, 4.934), 'Pos': Point3(-431.925, -244.179, 58.528), 'Scale': VBase3(6.838, 6.838, 6.42), 'Visual': {'Color': (0.5, 0.5, 0.5, 1.0), 'Model': 'models/props/rock_3_sphere'}}, '1209161440.44akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-144.282, -1.023, -1.323), 'Objects': {}, 'Pos': Point3(-365.81, 0.376, 51.849), 'Scale': VBase3(4.774, 4.774, 3.13), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_2_sphere'}}, '1209161477.69akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-0.015, 0.058, 1.671), 'Objects': {}, 'Pos': Point3(-409.894, 17.425, 56.048), 'Scale': VBase3(7.288, 7.288, 4.778), 'Visual': {'Color': (0.4000000059604645, 0.4000000059604645, 0.4000000059604645, 1.0), 'Model': 'models/props/rock_4_floor'}}, '1209161531.03akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-449.28, 14.967, 58.265), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1209161544.22akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-438.996, -8.506, 57.961), 'Scale': VBase3(1.801, 1.801, 1.801), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161579.78akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-359.211, -56.039, 55.448), 'Scale': VBase3(1.571, 1.571, 1.571), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161595.84akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-347.367, -45.613, 55.072), 'Scale': VBase3(1.972, 1.972, 1.972), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161621.64akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(0.169, -201.995, 52.27), 'Scale': VBase3(1.778, 1.778, 1.778), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161638.92akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-66.046, -68.342, 45.16), 'Scale': VBase3(2.372, 2.372, 2.372), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161654.92akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(102.793, -146.8, 58.166), 'Scale': VBase3(2.372, 2.372, 2.372), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161657.44akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(128.546, -133.474, 58.518), 'Scale': VBase3(2.954, 2.954, 2.954), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161671.08akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(186.798, -22.386, 56.978), 'Scale': VBase3(2.524, 2.524, 2.524), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1209161686.61akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-13.52, 0.0, 0.0), 'Pos': Point3(273.201, -21.641, 59.928), 'Scale': VBase3(1.174, 1.174, 1.416), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209161710.03akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(14.597, 0.128, -5.824), 'Pos': Point3(82.206, -75.41, 50.078), 'Scale': VBase3(6.705, 2.85, 2.85), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209487843.45akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-129.25, 211.145, 50.427), 'Hpr': VBase3(140.127, 0.0, 0.974), 'Pos': Point3(275.008, -69.766, 53.784), 'Scale': VBase3(11.352, 11.352, 20.379), 'Visual': {'Color': (0.35, 0.38, 0.3058823529411765, 1.0), 'Model': 'models/props/rock_4_sphere'}}, '1209487882.58akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-129.25, 211.145, 50.427), 'Hpr': VBase3(-103.375, 0.871, -0.434), 'Pos': Point3(263.141, -79.951, 54.999), 'Scale': VBase3(4.386, 4.386, 2.489), 'Visual': {'Color': (0.35, 0.38, 0.3058823529411765, 1.0), 'Model': 'models/props/rock_3_sphere'}}, '1209488311.5akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(-129.25, 211.145, 50.427), 'Hpr': VBase3(97.047, 11.992, 12.247), 'Pos': Point3(341.282, -16.655, 48.54), 'Scale': VBase3(11.352, 11.352, 25.765), 'Visual': {'Color': (0.33, 0.39, 0.29411764705882354, 1.0), 'Model': 'models/props/rock_4_sphere'}}, '1209488450.56akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(10.238, 5.609, -4.441), 'Pos': Point3(397.278, -167.751, 10.629), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1209488472.47akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(10.238, 5.609, -4.441), 'Pos': Point3(177.615, -288.955, 76.916), 'Scale': VBase3(2.879, 2.879, 2.879), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_d'}}, '1209488483.22akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(1.748, 40.407, 14.612), 'Pos': Point3(351.268, -169.859, 19.653), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1209488503.27akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(0.238, 27.161, -5.002), 'Pos': Point3(380.178, -175.757, 38.526), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1209488515.72akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(212.329, -282.354, 30.754), 'Hpr': VBase3(0.237, 27.161, 12.904), 'Pos': Point3(212.329, -282.354, 30.754), 'Scale': VBase3(2.077, 2.077, 2.077), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1209488525.33akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(2.517, 23.367, 28.041), 'Pos': Point3(272.536, -231.389, 52.873), 'Scale': VBase3(2.543, 2.543, 2.543), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1209488617.81akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(212.329, -282.354, 30.754), 'Hpr': VBase3(-47.475, 1.66, 9.606), 'Pos': Point3(182.742, -297.231, -5.17), 'Scale': VBase3(1.933, 1.933, 1.933), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1209488652.98akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(212.329, -282.354, 30.754), 'Hpr': VBase3(-47.475, 1.659, 9.606), 'Pos': Point3(330.473, -171.451, -6.221), 'Scale': VBase3(1.933, 1.933, 1.933), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1209488661.19akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'GridPos': Point3(212.329, -282.354, 30.754), 'Hpr': VBase3(-47.475, 1.659, 9.606), 'Pos': Point3(474.988, -113.093, -7.282), 'Scale': VBase3(1.933, 1.933, 1.933), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1209493265.22akelts': {'Type': 'Vines', 'DisableCollision': False, 'Hpr': VBase3(-113.398, -4.875, -0.412), 'Pos': Point3(323.594, -34.059, 75.885), 'Scale': VBase3(1.204, 1.204, 1.204), 'Visual': {'Model': 'models/vegetation/moss_b'}}, '1209493343.03akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(-248.872, 56.43, 53.321), 'Hpr': VBase3(-172.407, 0.0, 0.0), 'Pos': Point3(344.013, -68.194, 70.628), 'Scale': VBase3(0.22, 0.22, 0.239), 'Visual': {'Color': (0.42, 0.49, 0.35294117647058826, 1.0), 'Model': 'models/props/mound_light_lrg'}}, '1209494722.42akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(155.008, 0.0, 0.0), 'Pos': Point3(37.059, -28.77, 5.11), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1209494725.34akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(155.008, 0.0, 0.0), 'Pos': Point3(37.059, -28.77, 5.11), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1209494725.63akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-127.2, -0.354, -1.185), 'Pos': Point3(37.059, -28.77, 5.11), 'Scale': VBase3(1.0, 1.0, 1.0), 'TargetUIDs': []}, '1209494966.0akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(155.393, 0.0, 0.0), 'Pos': Point3(-255.159, -127.722, 59.195), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495088.03akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'Hpr': VBase3(32.31, 0.0, 0.0), 'Pos': Point3(-256.78, -131.618, 59.952), 'Scale': VBase3(0.447, 0.447, 0.447), 'Visual': {'Model': 'models/vegetation/jungle_plant_b'}}, '1209495118.52akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'Hpr': VBase3(-61.885, 0.0, 0.0), 'Pos': Point3(-257.172, -131.645, 59.971), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/jungle_fern_a'}}, '1209495145.86akelts': {'Type': 'Jungle_Props', 'DisableCollision': False, 'Hpr': VBase3(32.31, 0.0, 0.0), 'Pos': Point3(-257.161, -131.858, 60.009), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/vegetation/jungle_fern_c'}}, '1209495327.36akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-16.321, 0.0, 0.0), 'Pos': Point3(-274.376, -215.222, 71.008), 'Scale': VBase3(1.547, 1.547, 1.547), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495367.36akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(-130.758, 0.0, 0.0), 'Pos': Point3(-265.362, -191.332, 69.757), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.6000000238418579, 0.6000000238418579, 0.6000000238418579, 1.0), 'Model': 'models/vegetation/bush_b'}}, '1209495433.5akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(126.526, 0.0, 0.0), 'Pos': Point3(-261.988, -195.283, 67.94), 'Scale': VBase3(1.216, 1.547, 1.547), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495577.41akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-35.753, 0.0, 0.0), 'Pos': Point3(-75.592, -245.691, 4.261), 'Scale': VBase3(1.979, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495606.77akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(35.201, 0.0, 0.0), 'Pos': Point3(-57.12, -243.858, 4.318), 'Scale': VBase3(2.619, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495623.19akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(73.064, 0.0, 0.0), 'Pos': Point3(-44.884, -230.551, 4.319), 'Scale': VBase3(1.309, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495656.72akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-69.933, 0.0, 0.0), 'Pos': Point3(-84.664, -236.663, 4.305), 'Scale': VBase3(0.785, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495679.92akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-169.896, 0.0, 0.0), 'Pos': Point3(-66.491, -226.737, 40.084), 'Scale': VBase3(1.521, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495696.53akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-114.055, 0.0, 0.0), 'Pos': Point3(-75.191, -231.723, 40.01), 'Scale': VBase3(0.854, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209495721.25akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(158.79, 0.0, 0.0), 'Pos': Point3(-55.338, -226.91, 39.976), 'Scale': VBase3(0.854, 1.979, 1.979), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1209507473.88akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-24.821, 0.0, 0.0), 'Pos': Point3(-249.918, -140.602, 65.961), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1209507475.38akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(155.008, 0.0, 0.0), 'Pos': Point3(-255.062, -166.141, 66.015), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1209507476.16akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(142.807, 1.185, -0.354), 'Pos': Point3(357.407, 81.242, 6.653), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1210017193.42akelts': {'Type': 'Jungle_Props', 'DisableCollision': True, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(1.392, -0.182, 7.522), 'Pos': Point3(19.089, -40.189, 20.17), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_c'}}, '1210017223.89akelts': {'Type': 'Jungle_Props', 'DisableCollision': True, 'GridPos': Point3(-142.421, 161.349, 59.848), 'Hpr': VBase3(-44.557, -6.521, -11.794), 'Pos': Point3(44.922, -38.239, 7.918), 'Scale': VBase3(1.435, 1.435, 1.435), 'Visual': {'Color': (1.0, 1.0, 0.8799999952316284, 1.0), 'Model': 'models/vegetation/jungle_plant_a'}}, '1210017262.44akelts': {'Type': 'Tree - Animated', 'DisableCollision': True, 'Hpr': VBase3(71.785, 0.0, 0.0), 'Pos': Point3(25.245, -31.096, 1.557), 'Scale': VBase3(1.367, 1.367, 1.367), 'SubObjs': {'Top Model': {'Visual': {'Animate': 'models/vegetation/fern_short_leaf_c_idle', 'Attach': ['trunk', 'def_trunk_attach'], 'Model': 'models/vegetation/fern_short_leaf_d_hi', 'PartName': 'leaf'}}}, 'Visual': {'Animate': 'models/vegetation/fern_trunk_a_idle', 'Model': 'models/vegetation/fern_trunk_a_hi', 'PartName': 'trunk'}}, '1210017823.92akelts': {'Type': 'Bush', 'DisableCollision': True, 'Hpr': VBase3(135.643, 0.869, 3.112), 'Pos': Point3(13.659, -38.481, 3.898), 'Scale': VBase3(1.551, 1.551, 1.551), 'Visual': {'Model': 'models/vegetation/bush_f'}}, '1210017888.88akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(-251.946, -134.4, 62.218), 'Hpr': VBase3(75.504, 0.0, 0.0), 'Pos': Point3(-251.947, -134.4, 62.218), 'Scale': VBase3(1.0, 1.0, 1.821), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210017910.42akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(-251.847, -134.015, 62.218), 'Hpr': VBase3(-112.592, 0.0, 0.0), 'Pos': Point3(-244.564, -137.166, 61.987), 'Scale': VBase3(1.038, 1.0, 1.821), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210018066.84akelts': {'Type': 'Prop_Groups', 'DisableCollision': False, 'Hpr': VBase3(-53.61, -7.082, -8.069), 'Pos': Point3(-233.941, -140.802, 59.899), 'Scale': VBase3(0.947, 0.947, 0.947), 'Visual': {'Color': (0.81, 0.78, 0.7333333333333333, 1.0), 'Model': 'models/props/prop_group_H'}}, '1210018194.59akelts': {'Type': 'Crate', 'DisableCollision': True, 'Hpr': VBase3(-117.317, 0.0, 0.0), 'Pos': Point3(-241.587, -140.234, 60.102), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.7019607843137254, 0.73, 0.6745098039215687, 1.0), 'Model': 'models/props/crates_group_1'}}, '1210018229.25akelts': {'Type': 'Crate', 'DisableCollision': True, 'Hpr': VBase3(144.285, 0.0, 0.0), 'Pos': Point3(-237.053, -142.568, 60.168), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.8, 0.82, 0.7686274509803922, 1.0), 'Model': 'models/props/crates_group_2'}}, '1210018327.55akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(-251.847, -134.015, 62.218), 'Hpr': VBase3(-112.592, 0.0, 0.0), 'Pos': Point3(-228.241, -144.497, 59.732), 'Scale': VBase3(0.727, 0.727, 0.727), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1210018399.53akelts': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'Hpr': VBase3(0.0, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '6.7229', 'Pos': Point3(-225.996, -133.769, 58.773), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Walk', 'StartFrame': '0', 'Team': 'Player', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1210018587.17akelts': {'Type': 'Furniture', 'DisableCollision': False, 'Hpr': VBase3(0.0, -3.702, 0.0), 'Pos': Point3(365.553, 88.805, 34.002), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.75, 0.73, 0.6823529411764706, 1.0), 'Model': 'models/props/chair_shanty'}}, '1210018730.95akelts': {'Type': 'Furniture', 'DisableCollision': False, 'GridPos': Point3(367.558, 85.376, 33.907), 'Hpr': VBase3(143.779, 2.988, 2.187), 'Pos': Point3(367.558, 85.377, 33.907), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (0.75, 0.73, 0.6823529411764706, 1.0), 'Model': 'models/props/table_shanty_2'}}, '1210018803.45akelts': {'Type': 'Jugs_and_Jars', 'DisableCollision': False, 'GridPos': Point3(369.89, 86.872, 36.791), 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(369.89, 86.872, 36.792), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/winebottle_A'}}, '1210018806.36akelts': {'Type': 'Jugs_and_Jars', 'DisableCollision': False, 'GridPos': Point3(366.932, 82.924, 37.046), 'Hpr': VBase3(127.203, 0.73, -0.998), 'Pos': Point3(366.932, 82.924, 37.046), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/winebottle_B'}}, '1210018832.0akelts': {'Type': 'Cups', 'DisableCollision': False, 'Hpr': VBase3(-127.2, -0.354, -1.185), 'Pos': Point3(368.358, 85.514, 36.875), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/beerstein'}}, '1210018838.19akelts': {'Type': 'Cups', 'DisableCollision': False, 'GridPos': Point3(367.707, 84.2, 36.964), 'Hpr': VBase3(-82.374, 0.0, 0.0), 'Pos': Point3(367.706, 84.2, 36.964), 'Scale': VBase3(0.443, 0.443, 0.443), 'Visual': {'Model': 'models/props/cup_tin'}}, '1210018876.3akelts': {'Type': 'Prop_Groups', 'DisableCollision': False, 'GridPos': Point3(361.028, 85.78, 49.797), 'Hpr': VBase3(-102.398, 0.0, 0.0), 'Pos': Point3(361.028, 85.78, 49.797), 'Scale': VBase3(0.639, 0.639, 0.639), 'Visual': {'Color': (0.800000011920929, 0.800000011920929, 0.800000011920929, 1.0), 'Model': 'models/props/prop_group_C'}}, '1210018938.13akelts': {'Type': 'Prop_Groups', 'DisableCollision': False, 'GridPos': Point3(381.373, 75.1, 49.771), 'Hpr': VBase3(58.938, 1.198, 0.308), 'Pos': Point3(381.373, 75.101, 49.771), 'Scale': VBase3(0.639, 0.639, 0.639), 'Visual': {'Model': 'models/props/prop_group_B'}}, '1210018967.11akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(374.945, 53.671, 34.579), 'Hpr': VBase3(42.768, -0.081, 1.097), 'Pos': Point3(374.945, 53.671, 34.579), 'Scale': VBase3(0.866, 0.866, 0.866), 'Visual': {'Color': (0.67, 0.71, 0.7294117647058823, 1.0), 'Model': 'models/props/prop_group_A'}}, '1210018986.64akelts': {'Type': 'Prop_Groups', 'DisableCollision': True, 'GridPos': Point3(363.019, 68.391, 34.731), 'Hpr': VBase3(169.961, -0.222, -0.132), 'Pos': Point3(363.019, 68.391, 34.73), 'Scale': VBase3(0.866, 0.866, 0.866), 'Visual': {'Color': (0.52, 0.56, 0.4392156862745098, 1.0), 'Model': 'models/props/prop_group_A'}}, '1210019029.05akelts': {'Type': 'Jugs_and_Jars', 'DisableCollision': False, 'GridPos': Point3(365.81, 60.824, 37.802), 'Hpr': VBase3(-105.601, -0.506, -0.976), 'Pos': Point3(365.81, 60.824, 37.802), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/winebottle_B'}}, '1210019045.88akelts': {'Type': 'Jugs_and_Jars', 'DisableCollision': False, 'GridPos': Point3(365.692, 59.988, 37.787), 'Hpr': VBase3(21.597, 0.259, -0.005), 'Pos': Point3(365.691, 59.988, 37.788), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/winebottle_A'}}, '1210019110.2akelts': {'Type': 'Light_Fixtures', 'DisableCollision': False, 'GridPos': Point3(365.28, 83.918, 36.929), 'Hpr': VBase3(0.0, 0.0, 0.0), 'Pos': Point3(365.28, 83.918, 36.93), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/props/lamp_table_hurricane_candle'}}, '1210352028.39akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-24.821, 0.0, 0.0), 'Pos': Point3(-249.918, -140.602, 65.961), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1210352029.53akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator_2', 'Hpr': VBase3(155.008, 0.0, 0.0), 'Pos': Point3(-255.062, -166.141, 66.015), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1210352034.06akelts': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(142.807, 1.185, -0.354), 'Pos': Point3(357.407, 81.242, 6.653), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1210352211.14akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-455.967, -32.178, 2.633), 'Scale': VBase3(5.225, 5.225, 5.225), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1210352223.39akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-449.488, 30.519, 4.783), 'Scale': VBase3(4.118, 4.118, 2.416), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1210352237.56akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-469.793, 6.73, 4.417), 'Scale': VBase3(2.399, 2.399, 2.399), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1210353447.2akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-66.77, 0.0, 0.0), 'Pos': Point3(52.623, -166.21, 55.787), 'Scale': VBase3(1.941, 1.941, 1.941), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1210354351.36akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(85.441, 0.0, 0.0), 'Pos': Point3(282.365, -15.541, 59.381), 'Scale': VBase3(1.174, 1.174, 1.416), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210354363.27akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(29.095, 0.0, 0.0), 'Pos': Point3(280.303, -22.024, 59.813), 'Scale': VBase3(0.427, 1.174, 1.416), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210354405.92akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(29.095, 0.0, 0.0), 'Pos': Point3(230.144, -24.458, 59.865), 'Scale': VBase3(0.427, 1.174, 1.416), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210354500.67akelts': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(-246.537, -87.543, -0.021), 'Hpr': VBase3(89.833, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(530.695, 29.685, 0.115), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1210354564.08akelts': {'Type': 'Dinghy', 'Aggro Radius': '20.0000', 'GridPos': Point3(8.739, -231.852, 0.612), 'Hpr': VBase3(-136.695, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(-286.469, 318.366, 0.91), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1210354586.39akelts': {'Type': 'Dinghy', 'Aggro Radius': '19.8795', 'GridPos': Point3(8.739, -231.852, 0.612), 'Hpr': VBase3(-65.781, 0.0, 0.0), 'Location': 'Water', 'Pos': Point3(-464.754, 160.717, 0.509), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Model': 'models/shipparts/dingy-geometry_High'}}, '1210356705.42akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'GridPos': Point3(411.062, 47.92, 6.511), 'Hpr': VBase3(-52.401, 0.0, 0.0), 'Pos': Point3(339.491, -13.104, 54.117), 'Scale': VBase3(2.023, 2.023, 2.023), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1210358375.59akelts': {'Type': 'Crate', 'DisableCollision': True, 'Hpr': VBase3(12.252, 0.0, 0.0), 'Pos': Point3(60.212, -165.713, 55.673), 'Scale': VBase3(0.832, 0.832, 0.832), 'Visual': {'Model': 'models/props/crate'}}, '1210612073.56akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(51.889, 0.0, 0.0), 'Pos': Point3(-253.468, -343.007, 2.973), 'Scale': VBase3(3.106, 4.657, 4.657), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210612087.31akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(87.795, 0.0, 0.0), 'Pos': Point3(-244.103, -321.737, 2.983), 'Scale': VBase3(2.049, 4.657, 4.657), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210612184.25akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-3.518, 0.0, 0.0), 'Pos': Point3(-280.058, -353.778, 3.092), 'Scale': VBase3(3.602, 4.657, 4.657), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210612337.41akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-6.919, 0.0, 0.0), 'Pos': Point3(-287.009, -370.072, -5.466), 'Scale': VBase3(2.242, 2.242, 2.242), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_tube'}}, '1210612360.47akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-6.919, 0.0, 0.0), 'Pos': Point3(-308.201, -345.997, 5.321), 'Scale': VBase3(2.941, 2.941, 2.941), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1210613067.88akelts': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(-248.226, -303.587, 7.437), 'Scale': VBase3(2.512, 2.512, 2.512), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1210614180.44akelts': {'Type': 'Rock', 'DisableCollision': True, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-153.888, -21.83, -4.597), 'Pos': Point3(-221.129, -286.486, 0.739), 'Scale': VBase3(3.573, 3.573, 4.555), 'Visual': {'Color': (0.22, 0.25, 0.22745098039215686, 1.0), 'Model': 'models/props/rock_group_5_sphere'}}, '1210614230.94akelts': {'Type': 'Rock', 'DisableCollision': False, 'GridPos': Point3(146.575, -48.43, 17.034), 'Hpr': VBase3(-150.378, -10.878, 0.083), 'Pos': Point3(-229.862, -293.394, 5.386), 'Scale': VBase3(2.597, 2.597, 1.992), 'Visual': {'Color': (0.28, 0.32, 0.3058823529411765, 1.0), 'Model': 'models/props/rock_group_1_floor'}}, '1210978646.84kmuller': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(-163.082, 0.0, 0.0), 'Pos': Point3(-298.715, 81.667, 14.685), 'Scale': VBase3(5.033, 4.636, 7.816), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210978775.87kmuller': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(88.931, 0.0, 0.0), 'Pos': Point3(-242.472, 47.559, 17.589), 'Scale': VBase3(2.49, 2.134, 7.212), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1210978826.82kmuller': {'Type': 'Jungle_Props', 'DisableCollision': False, 'Hpr': VBase3(4.725, -17.22, 15.599), 'Pos': Point3(-264.896, 70.594, 17.81), 'Scale': VBase3(2.16, 2.16, 2.16), 'Visual': {'Model': 'models/vegetation/jungle_fern_b'}}, '1210978861.2kmuller': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Hpr': VBase3(138.584, 0.0, 0.0), 'Pos': Point3(-258.687, 74.265, 16.954), 'Scale': VBase3(4.496, 4.859, 7.409), 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1211929216.0WDIG1': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'DNA': '1211929216.0WDIG1', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'HelpID': 'SHIP_PVP_HELP_SPAINISH_A', 'Hpr': VBase3(80.821, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(-209.305, 197.314, 10.122), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Player', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1211929472.0WDIG': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'DNA': '1211929472.0WDIG', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'HelpID': 'SHIP_PVP_HELP_SPAINISH_B', 'Hpr': VBase3(67.311, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(327.55, 81.314, 6.205), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Player', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1216249894.26aapatel': {'Type': 'Townsperson', 'Category': 'PvPRewards', 'AnimSet': 'default', 'AuraFX': 'None', 'Boss': False, 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'HelpID': 'NONE', 'Holiday': '', 'Hpr': VBase3(-42.606, 0.0, 0.0), 'Instanced World': 'None', 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(-321.07, 88.839, 14.807), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropFXLeft': 'None', 'PropFXRight': 'None', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PRIVATEER_TATTOOS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'VisSize': '', 'Zombie': False, 'spawnTimeAlt': '', 'spawnTimeBegin': 0.0, 'spawnTimeEnd': 0.0}, '1259623459.69caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(443.924, 227.799, -6.924), 'Scale': VBase3(5.736, 5.736, 5.736), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_sphere'}}, '1259623493.53caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(32.551, 0.0, 0.0), 'Pos': Point3(387.081, 216.027, -17.705), 'Scale': VBase3(1.952, 1.952, 4.363), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1259623521.7caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(80.439, 0.0, 0.0), 'Pos': Point3(381.85, 177.893, -9.613), 'Scale': VBase3(2.279, 2.624, 5.355), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1259623563.36caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': Point3(0.0, 0.0, 0.0), 'Pos': Point3(322.954, 164.741, -1.891), 'Scale': VBase3(2.252, 2.252, 2.252), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1259623576.63caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(-90.398, 0.0, 0.0), 'Pos': Point3(300.603, 216.858, -18.215), 'Scale': VBase3(2.122, 2.122, 4.718), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}, '1259623610.39caoconno': {'Type': 'Collision Barrier', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(-179.301, 0.0, 0.0), 'Pos': Point3(358.649, 267.315, -20.517), 'Scale': VBase3(6.469, 6.469, 10.613), 'VisSize': '', 'Visual': {'Model': 'models/misc/pir_m_prp_lev_cambarrier_plane'}}}, 'PVPTeam': '2', 'Team': 2, 'Undockable': False, 'Visibility': 'Grid', 'Visual': {'Model': 'models/islands/pir_m_are_isl_pvpSpanish'}}}, 'Node Links': [], 'Layers': {'Collisions': ['1184008208.59kmuller', '1184016064.62kmuller', '1184013852.84kmuller', '1185822696.06kmuller', '1184006140.32kmuller', '1184002350.98kmuller', '1184007573.29kmuller', '1184021176.59kmuller', '1184005963.59kmuller', '1188324241.31akelts', '1184006537.34kmuller', '1184006605.81kmuller', '1187139568.33kmuller', '1188324186.98akelts', '1184006730.66kmuller', '1184007538.51kmuller', '1184006188.41kmuller', '1184021084.27kmuller', '1185824396.94kmuller', '1185824250.16kmuller', '1185823630.52kmuller', '1185823760.23kmuller', '1185824497.83kmuller', '1185824751.45kmuller', '1187739103.34akelts', '1188323993.34akelts', '1184016538.29kmuller', '1185822200.97kmuller', '1184016225.99kmuller', '1195241421.34akelts', '1195242796.08akelts', '1184020642.13kmuller', '1195237994.63akelts', '1184020756.88kmuller', '1184020833.4kmuller', '1185820992.97kmuller', '1185821053.83kmuller', '1184015068.54kmuller', '1184014935.82kmuller', '1185821432.88kmuller', '1185821701.86kmuller', '1195240137.55akelts', '1195241539.38akelts', '1195238422.3akelts', '1195238473.22akelts', '1185821453.17kmuller', '1184021269.96kmuller', '1185821310.89kmuller', '1185821165.59kmuller', '1185821199.36kmuller', '1185822035.98kmuller', '1184015806.59kmuller', '1185822059.48kmuller', '1185920461.76kmuller', '1194984449.66akelts', '1185824206.22kmuller', '1184003446.23kmuller', '1184003254.85kmuller', '1184003218.74kmuller', '1184002700.44kmuller', '1186705073.11kmuller', '1187658531.86akelts', '1186705214.3kmuller', '1185824927.28kmuller', '1184014204.54kmuller', '1184014152.84kmuller']}, 'ObjectIds': {'1196970035.53sdnaik': '["Objects"]["1196970035.53sdnaik"]', '1201551808.32kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201551808.32kmuller"]', '1201551834.96kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201551834.96kmuller"]', '1201551889.37kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201551889.37kmuller"]', '1201551915.76kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201551915.76kmuller"]', '1201558997.82kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201558997.82kmuller"]', '1201559007.18kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201559007.18kmuller"]', '1201559028.84kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1201559028.84kmuller"]', '1202414940.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1202414940.17akelts"]', '1202414940.17akelts0': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1202414940.17akelts"]', '1203114290.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114290.45akelts"]', '1203114330.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114330.25akelts"]', '1203114365.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114365.52akelts"]', '1203114365.52akelts0': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114365.52akelts"]', '1203114365.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114365.58akelts"]', '1203114419.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114419.42akelts"]', '1203114463.95akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114463.95akelts"]', '1203114579.48akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114579.48akelts"]', '1203114754.3akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114754.3akelts"]', '1203114815.91akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114815.91akelts"]', '1203114862.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114862.61akelts"]', '1203114895.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114895.23akelts"]', '1203115389.72akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115389.72akelts"]', '1203115424.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115424.56akelts"]', '1203115489.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115489.25akelts"]', '1203115525.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115525.55akelts"]', '1203115567.8akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115567.8akelts"]', '1203115686.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115686.2akelts"]', '1203115759.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115759.17akelts"]', '1203115821.75akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115821.75akelts"]', '1203115874.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115874.03akelts"]', '1203115947.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203115947.03akelts"]', '1203449603.97akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203449603.97akelts"]', '1203450135.28akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450135.28akelts"]', '1203450324.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450324.03akelts"]', '1203450370.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450370.69akelts"]', '1203450461.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450461.55akelts"]', '1203450511.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450511.61akelts"]', '1203450582.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450582.5akelts"]', '1203450682.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450682.05akelts"]', '1203450682.05akelts0': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450682.05akelts"]', '1203450740.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450740.25akelts"]', '1203450762.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450762.45akelts"]', '1203450800.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450800.73akelts"]', '1203450923.8akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450923.8akelts"]', '1203450923.8akelts0': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203450923.8akelts"]', '1203451028.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203451028.89akelts"]', '1203451240.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203451240.81akelts"]', '1203458158.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203458158.53akelts"]', '1203458673.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203458673.23akelts"]', '1203459119.77akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203459119.77akelts"]', '1203459408.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203459408.59akelts"]', '1203460758.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460758.22akelts"]', '1203460800.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460800.05akelts"]', '1203460826.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460826.44akelts"]', '1203460870.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460870.59akelts"]', '1203460917.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460917.47akelts"]', '1203460945.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203460945.09akelts"]', '1203461019.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461019.36akelts"]', '1203461073.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461073.42akelts"]', '1203461085.86akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461085.86akelts"]', '1203461128.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461128.5akelts"]', '1203461179.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461179.58akelts"]', '1203461241.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461241.98akelts"]', '1203461317.66akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461317.66akelts"]', '1203461390.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461390.23akelts"]', '1203461510.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203461510.47akelts"]', '1203464268.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203464268.55akelts"]', '1203464436.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203464436.53akelts"]', '1203464470.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203464470.73akelts"]', '1203464494.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203464494.17akelts"]', '1203464564.14akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203464564.14akelts"]', '1204059355.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059355.98akelts"]', '1204059414.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059414.83akelts"]', '1204059436.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059436.81akelts"]', '1204059462.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059462.52akelts"]', '1204059672.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059672.03akelts"]', '1204059711.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059711.06akelts"]', '1204059712.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059712.09akelts"]', '1204059713.08akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059713.08akelts"]', '1204059716.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059716.5akelts"]', '1204059717.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059717.45akelts"]', '1204059719.28akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059719.28akelts"]', '1204059720.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059720.05akelts"]', '1204059724.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059724.55akelts"]', '1204059729.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059729.58akelts"]', '1204059732.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059732.36akelts"]', '1204059735.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059735.73akelts"]', '1204059738.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059738.44akelts"]', '1204059742.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059742.03akelts"]', '1204059934.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059934.52akelts"]', '1204059949.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059949.56akelts"]', '1204059953.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059953.34akelts"]', '1204059956.41akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059956.41akelts"]', '1204059960.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059960.55akelts"]', '1204059962.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059962.81akelts"]', '1204059966.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059966.33akelts"]', '1204059991.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204059991.02akelts"]', '1204060027.94akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060027.94akelts"]', '1204060031.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060031.36akelts"]', '1204060033.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060033.45akelts"]', '1204060035.7akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060035.7akelts"]', '1204060039.77akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060039.77akelts"]', '1204060065.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060065.31akelts"]', '1204060071.86akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060071.86akelts"]', '1204060074.63akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060074.63akelts"]', '1204060078.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060078.2akelts"]', '1204060082.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060082.56akelts"]', '1204060470.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060470.2akelts"]', '1204060505.48akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060505.48akelts"]', '1204060511.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060511.89akelts"]', '1204060515.3akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060515.3akelts"]', '1204060521.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060521.22akelts"]', '1204060524.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060524.36akelts"]', '1204060821.13akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060821.13akelts"]', '1204060855.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060855.45akelts"]', '1204060956.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204060956.09akelts"]', '1204061028.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204061028.02akelts"]', '1204061061.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204061061.27akelts"]', '1204134204.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134204.59akelts"]', '1204134436.16akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134436.16akelts"]', '1204134561.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134561.33akelts"]', '1204134680.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134680.02akelts"]', '1204134735.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134735.98akelts"]', '1204134910.91akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204134910.91akelts"]', '1204135098.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204135098.84akelts"]', '1204135135.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204135135.33akelts"]', '1204237124.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237124.22akelts"]', '1204237124.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237124.2akelts"]', '1204237124.2akelts0': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237124.2akelts"]', '1204237223.91akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237223.91akelts"]', '1204237285.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237285.34akelts"]', '1204237296.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237296.23akelts"]', '1204237768.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237768.98akelts"]', '1204237956.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237956.03akelts"]', '1208535913.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208535913.67akelts"]', '1208535916.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208535916.31akelts"]', '1208551336.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208551336.89akelts"]', '1208551339.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208551339.09akelts"]', '1208796482.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208796482.19akelts"]', '1208796484.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208796484.09akelts"]', '1208796484.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208796484.17akelts"]', '1208808622.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808622.33akelts"]', '1208808661.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808661.47akelts"]', '1208808732.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808732.92akelts"]', '1208808760.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808760.67akelts"]', '1208808898.64akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808898.64akelts"]', '1208808939.75akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808939.75akelts"]', '1208808963.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808963.02akelts"]', '1208808997.63akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208808997.63akelts"]', '1208809009.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809009.36akelts"]', '1208809176.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809176.83akelts"]', '1208809279.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809279.59akelts"]', '1208809368.11akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809368.11akelts"]', '1208809472.88akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809472.88akelts"]', '1208809510.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809510.83akelts"]', '1208809617.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809617.05akelts"]', '1208809694.8akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809694.8akelts"]', '1208809918.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809918.53akelts"]', '1208809947.38akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809947.38akelts"]', '1208809958.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809958.27akelts"]', '1208809992.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208809992.67akelts"]', '1208810053.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810053.52akelts"]', '1208810085.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810085.05akelts"]', '1208810147.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810147.31akelts"]', '1208810201.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810201.73akelts"]', '1208810269.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810269.45akelts"]', '1208810310.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810310.83akelts"]', '1208810354.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810354.47akelts"]', '1208810406.28akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810406.28akelts"]', '1208810445.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810445.06akelts"]', '1208810495.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810495.61akelts"]', '1208810525.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810525.34akelts"]', '1208810579.08akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810579.08akelts"]', '1208810621.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810621.84akelts"]', '1208810658.95akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810658.95akelts"]', '1208810807.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810807.19akelts"]', '1208810877.0akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810877.0akelts"]', '1208810934.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208810934.53akelts"]', '1208811023.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811023.73akelts"]', '1208811068.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811068.98akelts"]', '1208811084.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811084.52akelts"]', '1208811112.3akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811112.3akelts"]', '1208811262.97akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811262.97akelts"]', '1208811381.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811381.53akelts"]', '1208811429.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811429.42akelts"]', '1208811768.8akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811768.8akelts"]', '1208811772.16akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811772.16akelts"]', '1208811773.16akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811773.16akelts"]', '1208811773.94akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811773.94akelts"]', '1208811776.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811776.03akelts"]', '1208811776.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811776.83akelts"]', '1208811777.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811777.47akelts"]', '1208811779.14akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811779.14akelts"]', '1208811781.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811781.34akelts"]', '1208811783.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811783.25akelts"]', '1208811785.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811785.25akelts"]', '1208811787.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811787.06akelts"]', '1208811787.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811787.67akelts"]', '1208811788.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811788.55akelts"]', '1208811791.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811791.69akelts"]', '1208811792.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811792.56akelts"]', '1208811794.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811794.17akelts"]', '1208811795.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811795.17akelts"]', '1208811800.08akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811800.08akelts"]', '1208811801.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811801.2akelts"]', '1208811802.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811802.09akelts"]', '1208811803.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811803.81akelts"]', '1208811804.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811804.59akelts"]', '1208811805.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811805.2akelts"]', '1208811806.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811806.67akelts"]', '1208811976.0akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208811976.0akelts"]', '1208812034.0akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208812034.0akelts"]', '1208817172.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817172.09akelts"]', '1208817254.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817254.27akelts"]', '1208817508.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817508.89akelts"]', '1208817704.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817704.22akelts"]', '1208817733.41akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817733.41akelts"]', '1208817744.48akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817744.48akelts"]', '1208817783.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817783.52akelts"]', '1208817904.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208817904.31akelts"]', '1208818191.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818191.44akelts"]', '1208818217.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818217.42akelts"]', '1208818540.86akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818540.86akelts"]', '1208818602.13akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818602.13akelts"]', '1208818653.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818653.27akelts"]', '1208818734.8akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208818734.8akelts"]', '1208824971.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208824971.89akelts"]', '1208825047.78akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825047.78akelts"]', '1208825097.28akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825097.28akelts"]', '1208825126.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825126.22akelts"]', '1208825212.38akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825212.38akelts"]', '1208825312.16akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825312.16akelts"]', '1208825386.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208825386.56akelts"]', '1208892989.37akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208892989.37akelts"]', '1208893039.39akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208893039.39akelts"]', '1208893077.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208893077.73akelts"]', '1208893136.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208893136.55akelts"]', '1208906898.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208906898.45akelts"]', '1208906917.51akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208906917.51akelts"]', '1208908188.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208908188.33akelts"]', '1208908264.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208908264.25akelts"]', '1208908273.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208908273.23akelts"]', '1208908304.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208908304.17akelts"]', '1208908477.73akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208908477.73akelts"]', '1208980254.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208980254.31akelts"]', '1208985003.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985003.56akelts"]', '1208985185.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985185.81akelts"]', '1208985214.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985214.58akelts"]', '1208985234.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985234.61akelts"]', '1208985272.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985272.09akelts"]', '1208985300.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985300.27akelts"]', '1208985322.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985322.83akelts"]', '1208985344.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985344.06akelts"]', '1208985360.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985360.09akelts"]', '1208985376.95akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985376.95akelts"]', '1208985400.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985400.34akelts"]', '1208985418.14akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985418.14akelts"]', '1208985454.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985454.22akelts"]', '1208985479.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985479.5akelts"]', '1208985517.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985517.81akelts"]', '1208985544.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985544.53akelts"]', '1208985576.95akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208985576.95akelts"]', '1208986572.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208986572.17akelts"]', '1208986622.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208986622.69akelts"]', '1208986646.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208986646.89akelts"]', '1208987108.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208987108.2akelts"]', '1208987212.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208987212.84akelts"]', '1208991300.13akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1208991300.13akelts"]', '1209140730.86akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209140730.86akelts"]', '1209141015.28akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209141015.28akelts"]', '1209141425.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209141425.34akelts"]', '1209141691.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209141691.17akelts"]', '1209141904.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209141904.02akelts"]', '1209142119.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209142119.19akelts"]', '1209146067.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209146067.22akelts"]', '1209146181.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209146181.89akelts"]', '1209160185.02akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160185.02akelts"]', '1209160274.7akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160274.7akelts"]', '1209160379.91akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160379.91akelts"]', '1209160555.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160555.83akelts"]', '1209160596.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160596.69akelts"]', '1209160629.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160629.69akelts"]', '1209160682.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160682.22akelts"]', '1209160719.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160719.84akelts"]', '1209160827.09akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160827.09akelts"]', '1209160837.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160837.58akelts"]', '1209160864.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160864.06akelts"]', '1209160896.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160896.47akelts"]', '1209160973.97akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209160973.97akelts"]', '1209161079.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161079.81akelts"]', '1209161092.23akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161092.23akelts"]', '1209161143.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161143.61akelts"]', '1209161288.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161288.52akelts"]', '1209161340.83akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161340.83akelts"]', '1209161440.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161440.44akelts"]', '1209161477.69akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161477.69akelts"]', '1209161531.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161531.03akelts"]', '1209161544.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161544.22akelts"]', '1209161579.78akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161579.78akelts"]', '1209161595.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161595.84akelts"]', '1209161621.64akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161621.64akelts"]', '1209161638.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161638.92akelts"]', '1209161654.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161654.92akelts"]', '1209161657.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161657.44akelts"]', '1209161671.08akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161671.08akelts"]', '1209161686.61akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161686.61akelts"]', '1209161710.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209161710.03akelts"]', '1209487843.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209487843.45akelts"]', '1209487882.58akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209487882.58akelts"]', '1209488311.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488311.5akelts"]', '1209488450.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488450.56akelts"]', '1209488472.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488472.47akelts"]', '1209488483.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488483.22akelts"]', '1209488503.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488503.27akelts"]', '1209488515.72akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488515.72akelts"]', '1209488525.33akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488525.33akelts"]', '1209488617.81akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488617.81akelts"]', '1209488652.98akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488652.98akelts"]', '1209488661.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209488661.19akelts"]', '1209493265.22akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209493265.22akelts"]', '1209493343.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209493343.03akelts"]', '1209494722.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209494722.42akelts"]', '1209494725.34akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209494725.34akelts"]', '1209494725.63akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209494725.63akelts"]', '1209494966.0akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209494966.0akelts"]', '1209495088.03akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495088.03akelts"]', '1209495118.52akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495118.52akelts"]', '1209495145.86akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495145.86akelts"]', '1209495327.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495327.36akelts"]', '1209495367.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495367.36akelts"]', '1209495433.5akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495433.5akelts"]', '1209495577.41akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495577.41akelts"]', '1209495606.77akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495606.77akelts"]', '1209495623.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495623.19akelts"]', '1209495656.72akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495656.72akelts"]', '1209495679.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495679.92akelts"]', '1209495696.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495696.53akelts"]', '1209495721.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209495721.25akelts"]', '1209507473.88akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209507473.88akelts"]', '1209507475.38akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209507475.38akelts"]', '1209507476.16akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1209507476.16akelts"]', '1210017193.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017193.42akelts"]', '1210017223.89akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017223.89akelts"]', '1210017262.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017262.44akelts"]', '1210017823.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017823.92akelts"]', '1210017888.88akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017888.88akelts"]', '1210017910.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210017910.42akelts"]', '1210018066.84akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018066.84akelts"]', '1210018194.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018194.59akelts"]', '1210018229.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018229.25akelts"]', '1210018327.55akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018327.55akelts"]', '1210018399.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018399.53akelts"]', '1210018587.17akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018587.17akelts"]', '1210018730.95akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018730.95akelts"]', '1210018803.45akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018803.45akelts"]', '1210018806.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018806.36akelts"]', '1210018832.0akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018832.0akelts"]', '1210018838.19akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018838.19akelts"]', '1210018876.3akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018876.3akelts"]', '1210018938.13akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018938.13akelts"]', '1210018967.11akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018967.11akelts"]', '1210018986.64akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210018986.64akelts"]', '1210019029.05akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210019029.05akelts"]', '1210019045.88akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210019045.88akelts"]', '1210019110.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210019110.2akelts"]', '1210352028.39akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352028.39akelts"]', '1210352029.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352029.53akelts"]', '1210352034.06akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352034.06akelts"]', '1210352211.14akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352211.14akelts"]', '1210352223.39akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352223.39akelts"]', '1210352237.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210352237.56akelts"]', '1210353447.2akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210353447.2akelts"]', '1210354351.36akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354351.36akelts"]', '1210354363.27akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354363.27akelts"]', '1210354405.92akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354405.92akelts"]', '1210354500.67akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354500.67akelts"]', '1210354564.08akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354564.08akelts"]', '1210354586.39akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210354586.39akelts"]', '1210356705.42akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210356705.42akelts"]', '1210358375.59akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210358375.59akelts"]', '1210373723.53akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237124.2akelts"]["Objects"]["1210373723.53akelts"]', '1210373725.94akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1204237124.2akelts"]["Objects"]["1210373725.94akelts"]', '1210373727.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1203114365.52akelts"]["Objects"]["1210373727.44akelts"]', '1210612073.56akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210612073.56akelts"]', '1210612087.31akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210612087.31akelts"]', '1210612184.25akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210612184.25akelts"]', '1210612337.41akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210612337.41akelts"]', '1210612360.47akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210612360.47akelts"]', '1210613067.88akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210613067.88akelts"]', '1210614180.44akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210614180.44akelts"]', '1210614230.94akelts': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210614230.94akelts"]', '1210978646.84kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210978646.84kmuller"]', '1210978775.87kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210978775.87kmuller"]', '1210978826.82kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210978826.82kmuller"]', '1210978861.2kmuller': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1210978861.2kmuller"]', '1211929216.0WDIG1': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1211929216.0WDIG1"]', '1211929472.0WDIG': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1211929472.0WDIG"]', '1216249894.26aapatel': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1216249894.26aapatel"]', '1259623459.69caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623459.69caoconno"]', '1259623493.53caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623493.53caoconno"]', '1259623521.7caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623521.7caoconno"]', '1259623563.36caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623563.36caoconno"]', '1259623576.63caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623576.63caoconno"]', '1259623610.39caoconno': '["Objects"]["1196970035.53sdnaik"]["Objects"]["1259623610.39caoconno"]'}} extraInfo = {'camPos': Point3(-317.436, 96.8385, 20.2355), 'camHpr': VBase3(146.894, -10.8979, 0), 'focalLength': 0.791999995708, 'skyState': 2, 'fog': 0}

23,842.142857

166,452

0.666838

23,325

166,895

4.718671

0.082872

0.015936

0.014855

0.11746

0.66203

0.516295

0.478835

0.410547

0.374567

0.363565

0

0.300607

0.070955

166,895

7

166,453

23,842.142857

0.409234

0.001318

0

0.510647

0.244836

0

1

0

false

0

0.333333

0

0.333333

0

null

0

1

0

1

0

null

0

1

0

6

934678c3c01f03f5a0a5fc9b6fd2c6f69ded1c17

136

py

Python

src/UQpy/reliability/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

src/UQpy/reliability/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

src/UQpy/reliability/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

from UQpy.reliability.SubsetSimulation import SubsetSimulation from UQpy.reliability.taylor_series import * from . import TaylorSeries

27.2

62

0.860294

15

136

7.733333

0.533333

0.137931

0.327586

0

0.095588

136

4

63

34

0.943089

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

934745fda52dc20c4927f5177c133911e979dc44

167

py

Python

mysite/mysite/modelmysite/author/models.py

lz1988/django-web2015

79bcc9fc83b487915da6230e0ab7d5c599a33a9d

[ "BSD-2-Clause" ]

null

mysite/mysite/modelmysite/author/models.py

lz1988/django-web2015

79bcc9fc83b487915da6230e0ab7d5c599a33a9d

[ "BSD-2-Clause" ]

null

mysite/mysite/modelmysite/author/models.py

lz1988/django-web2015

79bcc9fc83b487915da6230e0ab7d5c599a33a9d

[ "BSD-2-Clause" ]

null

#filename models.py from django.db import models class author(models.Model): name = models.CharField(max_length=30) address = models.CharField(max_length=30)

23.857143

45

0.760479

24

167

5.208333

0.666667

0.24

0.288

0.384

0.416

0

0.027778

0.137725

167

6

46

27.833333

0.840278

0.107784

0

1

0

false

0

0.25

0

1

0

1

0

null

1

0

1

0

null

0

1

0

6

936c3b70a6fca1149f5615adb2c8c08f13d4f5ae

35

py

Python

mdm_inventory/address/tests/factories/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

mdm_inventory/address/tests/factories/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

mdm_inventory/address/tests/factories/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

from .address import AddressFactory

35

0.885714

4

35

7.75

1

0

0.085714

35

1

35

0.96875

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

4f035a3805e762ff5933f530ad54542c68d67376

52,500

py

Python

if/py/gen-py/fbnet/command_runner_asyncio/CommandRunner/ttypes.py

vdonga/FCR

59c4c27d6974f55730cd9f6d219214c090928c7c

[ "BSD-3-Clause" ]

null

if/py/gen-py/fbnet/command_runner_asyncio/CommandRunner/ttypes.py

vdonga/FCR

59c4c27d6974f55730cd9f6d219214c090928c7c

[ "BSD-3-Clause" ]

null

if/py/gen-py/fbnet/command_runner_asyncio/CommandRunner/ttypes.py

vdonga/FCR

59c4c27d6974f55730cd9f6d219214c090928c7c

[ "BSD-3-Clause" ]

null

# # Autogenerated by Thrift # # DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING # @generated # from __future__ import absolute_import import six from thrift.util.Recursive import fix_spec from thrift.Thrift import * from thrift.protocol.TProtocol import TProtocolException import fb303_asyncio.fb303.ttypes import pprint import warnings from thrift import Thrift from thrift.transport import TTransport from thrift.protocol import TBinaryProtocol from thrift.protocol import TCompactProtocol from thrift.protocol import THeaderProtocol fastproto = None if not '__pypy__' in sys.builtin_module_names: try: from thrift.protocol import fastproto except: pass all_structs = [] UTF8STRINGS = bool(0) or sys.version_info.major >= 3 __all__ = ['UTF8STRINGS', 'SessionType', 'FBNetDataException', 'UnsupportedDeviceException', 'SessionException', 'UnsupportedCommandException', 'InstanceOverloaded', 'SessionData', 'Device', 'CommandResult', 'Session'] class SessionType: SSH = 1 SSH_NETCONF = 2 _VALUES_TO_NAMES = { 1: "SSH", 2: "SSH_NETCONF", } _NAMES_TO_VALUES = { "SSH": 1, "SSH_NETCONF": 2, } class FBNetDataException(TException): """ Attributes: - message """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.message = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('FBNetDataException') if self.message != None: oprot.writeFieldBegin('message', TType.STRING, 1) oprot.writeString(self.message.encode('utf-8')) if UTF8STRINGS and not isinstance(self.message, bytes) else oprot.writeString(self.message) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __str__(self): return repr(self) def __repr__(self): L = [] padding = ' ' * 4 if self.message is not None: value = pprint.pformat(self.message, indent=0) value = padding.join(value.splitlines(True)) L.append(' message=%s' % (value)) if 'message' not in self.__dict__: message = getattr(self, 'message', None) if message: L.append('message=%r' % message) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class UnsupportedDeviceException(TException): """ Attributes: - message """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.message = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('UnsupportedDeviceException') if self.message != None: oprot.writeFieldBegin('message', TType.STRING, 1) oprot.writeString(self.message.encode('utf-8')) if UTF8STRINGS and not isinstance(self.message, bytes) else oprot.writeString(self.message) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __str__(self): return repr(self) def __repr__(self): L = [] padding = ' ' * 4 if self.message is not None: value = pprint.pformat(self.message, indent=0) value = padding.join(value.splitlines(True)) L.append(' message=%s' % (value)) if 'message' not in self.__dict__: message = getattr(self, 'message', None) if message: L.append('message=%r' % message) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class SessionException(TException): """ Attributes: - message """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.message = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('SessionException') if self.message != None: oprot.writeFieldBegin('message', TType.STRING, 1) oprot.writeString(self.message.encode('utf-8')) if UTF8STRINGS and not isinstance(self.message, bytes) else oprot.writeString(self.message) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __str__(self): return repr(self) def __repr__(self): L = [] padding = ' ' * 4 if self.message is not None: value = pprint.pformat(self.message, indent=0) value = padding.join(value.splitlines(True)) L.append(' message=%s' % (value)) if 'message' not in self.__dict__: message = getattr(self, 'message', None) if message: L.append('message=%r' % message) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class UnsupportedCommandException(TException): """ Attributes: - message """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.message = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('UnsupportedCommandException') if self.message != None: oprot.writeFieldBegin('message', TType.STRING, 1) oprot.writeString(self.message.encode('utf-8')) if UTF8STRINGS and not isinstance(self.message, bytes) else oprot.writeString(self.message) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __str__(self): return repr(self) def __repr__(self): L = [] padding = ' ' * 4 if self.message is not None: value = pprint.pformat(self.message, indent=0) value = padding.join(value.splitlines(True)) L.append(' message=%s' % (value)) if 'message' not in self.__dict__: message = getattr(self, 'message', None) if message: L.append('message=%r' % message) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class InstanceOverloaded(TException): """ Attributes: - message """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.message = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('InstanceOverloaded') if self.message != None: oprot.writeFieldBegin('message', TType.STRING, 1) oprot.writeString(self.message.encode('utf-8')) if UTF8STRINGS and not isinstance(self.message, bytes) else oprot.writeString(self.message) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __str__(self): return repr(self) def __repr__(self): L = [] padding = ' ' * 4 if self.message is not None: value = pprint.pformat(self.message, indent=0) value = padding.join(value.splitlines(True)) L.append(' message=%s' % (value)) if 'message' not in self.__dict__: message = getattr(self, 'message', None) if message: L.append('message=%r' % message) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class SessionData: """ Attributes: - subsystem - exec_command """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.subsystem = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 2: if ftype == TType.STRING: self.exec_command = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('SessionData') if self.subsystem != None: oprot.writeFieldBegin('subsystem', TType.STRING, 1) oprot.writeString(self.subsystem.encode('utf-8')) if UTF8STRINGS and not isinstance(self.subsystem, bytes) else oprot.writeString(self.subsystem) oprot.writeFieldEnd() if self.exec_command != None: oprot.writeFieldBegin('exec_command', TType.STRING, 2) oprot.writeString(self.exec_command.encode('utf-8')) if UTF8STRINGS and not isinstance(self.exec_command, bytes) else oprot.writeString(self.exec_command) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __repr__(self): L = [] padding = ' ' * 4 if self.subsystem is not None: value = pprint.pformat(self.subsystem, indent=0) value = padding.join(value.splitlines(True)) L.append(' subsystem=%s' % (value)) if self.exec_command is not None: value = pprint.pformat(self.exec_command, indent=0) value = padding.join(value.splitlines(True)) L.append(' exec_command=%s' % (value)) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class Device: """ Attributes: - hostname - username - password - console - mgmt_ip - command_prompts - ip_address - session_type - session_data """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.hostname = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 10: if ftype == TType.STRING: self.username = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 11: if ftype == TType.STRING: self.password = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 13: if ftype == TType.STRING: self.console = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 14: if ftype == TType.BOOL: self.mgmt_ip = iprot.readBool() else: iprot.skip(ftype) elif fid == 15: if ftype == TType.MAP: self.command_prompts = {} (_ktype1, _vtype2, _size0 ) = iprot.readMapBegin() if _size0 >= 0: for _i4 in six.moves.range(_size0): _key5 = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() _val6 = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() self.command_prompts[_key5] = _val6 else: while iprot.peekMap(): _key7 = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() _val8 = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() self.command_prompts[_key7] = _val8 iprot.readMapEnd() else: iprot.skip(ftype) elif fid == 16: if ftype == TType.STRING: self.ip_address = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 17: if ftype == TType.I32: self.session_type = iprot.readI32() else: iprot.skip(ftype) elif fid == 18: if ftype == TType.STRUCT: self.session_data = SessionData() self.session_data.read(iprot) else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): if self.hostname == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'hostname' was not found in serialized data! Struct: Device") if self.username == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'username' was not found in serialized data! Struct: Device") if self.password == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'password' was not found in serialized data! Struct: Device") return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('Device') if self.hostname != None: oprot.writeFieldBegin('hostname', TType.STRING, 1) oprot.writeString(self.hostname.encode('utf-8')) if UTF8STRINGS and not isinstance(self.hostname, bytes) else oprot.writeString(self.hostname) oprot.writeFieldEnd() if self.username != None: oprot.writeFieldBegin('username', TType.STRING, 10) oprot.writeString(self.username.encode('utf-8')) if UTF8STRINGS and not isinstance(self.username, bytes) else oprot.writeString(self.username) oprot.writeFieldEnd() if self.password != None: oprot.writeFieldBegin('password', TType.STRING, 11) oprot.writeString(self.password.encode('utf-8')) if UTF8STRINGS and not isinstance(self.password, bytes) else oprot.writeString(self.password) oprot.writeFieldEnd() if self.console != None and self.console != self.thrift_spec[13][4]: oprot.writeFieldBegin('console', TType.STRING, 13) oprot.writeString(self.console.encode('utf-8')) if UTF8STRINGS and not isinstance(self.console, bytes) else oprot.writeString(self.console) oprot.writeFieldEnd() if self.mgmt_ip != None and self.mgmt_ip != self.thrift_spec[14][4]: oprot.writeFieldBegin('mgmt_ip', TType.BOOL, 14) oprot.writeBool(self.mgmt_ip) oprot.writeFieldEnd() if self.command_prompts != None: oprot.writeFieldBegin('command_prompts', TType.MAP, 15) oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.command_prompts)) for kiter9,viter10 in self.command_prompts.items(): oprot.writeString(kiter9.encode('utf-8')) if UTF8STRINGS and not isinstance(kiter9, bytes) else oprot.writeString(kiter9) oprot.writeString(viter10.encode('utf-8')) if UTF8STRINGS and not isinstance(viter10, bytes) else oprot.writeString(viter10) oprot.writeMapEnd() oprot.writeFieldEnd() if self.ip_address != None: oprot.writeFieldBegin('ip_address', TType.STRING, 16) oprot.writeString(self.ip_address.encode('utf-8')) if UTF8STRINGS and not isinstance(self.ip_address, bytes) else oprot.writeString(self.ip_address) oprot.writeFieldEnd() if self.session_type != None: oprot.writeFieldBegin('session_type', TType.I32, 17) oprot.writeI32(self.session_type) oprot.writeFieldEnd() if self.session_data != None: oprot.writeFieldBegin('session_data', TType.STRUCT, 18) self.session_data.write(oprot) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __repr__(self): L = [] padding = ' ' * 4 if self.hostname is not None: value = pprint.pformat(self.hostname, indent=0) value = padding.join(value.splitlines(True)) L.append(' hostname=%s' % (value)) if self.username is not None: value = pprint.pformat(self.username, indent=0) value = padding.join(value.splitlines(True)) L.append(' username=%s' % (value)) if self.password is not None: value = pprint.pformat(self.password, indent=0) value = padding.join(value.splitlines(True)) L.append(' password=%s' % (value)) if self.console is not None: value = pprint.pformat(self.console, indent=0) value = padding.join(value.splitlines(True)) L.append(' console=%s' % (value)) if self.mgmt_ip is not None: value = pprint.pformat(self.mgmt_ip, indent=0) value = padding.join(value.splitlines(True)) L.append(' mgmt_ip=%s' % (value)) if self.command_prompts is not None: value = pprint.pformat(self.command_prompts, indent=0) value = padding.join(value.splitlines(True)) L.append(' command_prompts=%s' % (value)) if self.ip_address is not None: value = pprint.pformat(self.ip_address, indent=0) value = padding.join(value.splitlines(True)) L.append(' ip_address=%s' % (value)) if self.session_type is not None: value = pprint.pformat(self.session_type, indent=0) value = padding.join(value.splitlines(True)) L.append(' session_type=%s' % (value)) if self.session_data is not None: value = pprint.pformat(self.session_data, indent=0) value = padding.join(value.splitlines(True)) L.append(' session_data=%s' % (value)) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class CommandResult: """ Attributes: - output - status - command """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.STRING: self.output = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 2: if ftype == TType.STRING: self.status = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 3: if ftype == TType.STRING: self.command = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): if self.output == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'output' was not found in serialized data! Struct: CommandResult") if self.status == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'status' was not found in serialized data! Struct: CommandResult") if self.command == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'command' was not found in serialized data! Struct: CommandResult") return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('CommandResult') if self.output != None: oprot.writeFieldBegin('output', TType.STRING, 1) oprot.writeString(self.output.encode('utf-8')) if UTF8STRINGS and not isinstance(self.output, bytes) else oprot.writeString(self.output) oprot.writeFieldEnd() if self.status != None: oprot.writeFieldBegin('status', TType.STRING, 2) oprot.writeString(self.status.encode('utf-8')) if UTF8STRINGS and not isinstance(self.status, bytes) else oprot.writeString(self.status) oprot.writeFieldEnd() if self.command != None: oprot.writeFieldBegin('command', TType.STRING, 3) oprot.writeString(self.command.encode('utf-8')) if UTF8STRINGS and not isinstance(self.command, bytes) else oprot.writeString(self.command) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __repr__(self): L = [] padding = ' ' * 4 if self.output is not None: value = pprint.pformat(self.output, indent=0) value = padding.join(value.splitlines(True)) L.append(' output=%s' % (value)) if self.status is not None: value = pprint.pformat(self.status, indent=0) value = padding.join(value.splitlines(True)) L.append(' status=%s' % (value)) if self.command is not None: value = pprint.pformat(self.command, indent=0) value = padding.join(value.splitlines(True)) L.append(' command=%s' % (value)) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ class Session: """ Attributes: - id - name - hostname """ thrift_spec = None thrift_field_annotations = None thrift_struct_annotations = None __init__ = None @staticmethod def isUnion(): return False def read(self, iprot): if (isinstance(iprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0) self.checkRequired() return if (isinstance(iprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(iprot, THeaderProtocol.THeaderProtocolAccelerate) and iprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None and fastproto is not None: fastproto.decode(self, iprot.trans, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2) self.checkRequired() return iprot.readStructBegin() while True: (fname, ftype, fid) = iprot.readFieldBegin() if ftype == TType.STOP: break if fid == 1: if ftype == TType.I64: self.id = iprot.readI64() else: iprot.skip(ftype) elif fid == 2: if ftype == TType.STRING: self.name = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) elif fid == 3: if ftype == TType.STRING: self.hostname = iprot.readString().decode('utf-8') if UTF8STRINGS else iprot.readString() else: iprot.skip(ftype) else: iprot.skip(ftype) iprot.readFieldEnd() iprot.readStructEnd() self.checkRequired() def checkRequired(self): if self.id == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'id' was not found in serialized data! Struct: Session") if self.name == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'name' was not found in serialized data! Struct: Session") if self.hostname == None: raise TProtocolException(TProtocolException.MISSING_REQUIRED_FIELD, "Required field 'hostname' was not found in serialized data! Struct: Session") return def write(self, oprot): if (isinstance(oprot, TBinaryProtocol.TBinaryProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_BINARY_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=0)) return if (isinstance(oprot, TCompactProtocol.TCompactProtocolAccelerated) or (isinstance(oprot, THeaderProtocol.THeaderProtocolAccelerate) and oprot.get_protocol_id() == THeaderProtocol.THeaderProtocol.T_COMPACT_PROTOCOL)) and self.thrift_spec is not None and fastproto is not None: oprot.trans.write(fastproto.encode(self, [self.__class__, self.thrift_spec, False], utf8strings=UTF8STRINGS, protoid=2)) return oprot.writeStructBegin('Session') if self.id != None: oprot.writeFieldBegin('id', TType.I64, 1) oprot.writeI64(self.id) oprot.writeFieldEnd() if self.name != None: oprot.writeFieldBegin('name', TType.STRING, 2) oprot.writeString(self.name.encode('utf-8')) if UTF8STRINGS and not isinstance(self.name, bytes) else oprot.writeString(self.name) oprot.writeFieldEnd() if self.hostname != None: oprot.writeFieldBegin('hostname', TType.STRING, 3) oprot.writeString(self.hostname.encode('utf-8')) if UTF8STRINGS and not isinstance(self.hostname, bytes) else oprot.writeString(self.hostname) oprot.writeFieldEnd() oprot.writeFieldStop() oprot.writeStructEnd() def __repr__(self): L = [] padding = ' ' * 4 if self.id is not None: value = pprint.pformat(self.id, indent=0) value = padding.join(value.splitlines(True)) L.append(' id=%s' % (value)) if self.name is not None: value = pprint.pformat(self.name, indent=0) value = padding.join(value.splitlines(True)) L.append(' name=%s' % (value)) if self.hostname is not None: value = pprint.pformat(self.hostname, indent=0) value = padding.join(value.splitlines(True)) L.append(' hostname=%s' % (value)) return "%s(%s)" % (self.__class__.__name__, "\n" + ",\n".join(L) if L else '') def __eq__(self, other): if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other) # Override the __hash__ function for Python3 - t10434117 if not six.PY2: __hash__ = object.__hash__ all_structs.append(FBNetDataException) FBNetDataException.thrift_spec = ( None, # 0 (1, TType.STRING, 'message', True, None, 2, ), # 1 ) FBNetDataException.thrift_struct_annotations = { } FBNetDataException.thrift_field_annotations = { } def FBNetDataException__init__(self, message=None,): self.message = message FBNetDataException.__init__ = FBNetDataException__init__ def FBNetDataException__setstate__(self, state): state.setdefault('message', None) self.__dict__ = state FBNetDataException.__getstate__ = lambda self: self.__dict__.copy() FBNetDataException.__setstate__ = FBNetDataException__setstate__ all_structs.append(UnsupportedDeviceException) UnsupportedDeviceException.thrift_spec = ( None, # 0 (1, TType.STRING, 'message', True, None, 2, ), # 1 ) UnsupportedDeviceException.thrift_struct_annotations = { } UnsupportedDeviceException.thrift_field_annotations = { } def UnsupportedDeviceException__init__(self, message=None,): self.message = message UnsupportedDeviceException.__init__ = UnsupportedDeviceException__init__ def UnsupportedDeviceException__setstate__(self, state): state.setdefault('message', None) self.__dict__ = state UnsupportedDeviceException.__getstate__ = lambda self: self.__dict__.copy() UnsupportedDeviceException.__setstate__ = UnsupportedDeviceException__setstate__ all_structs.append(SessionException) SessionException.thrift_spec = ( None, # 0 (1, TType.STRING, 'message', True, None, 2, ), # 1 ) SessionException.thrift_struct_annotations = { } SessionException.thrift_field_annotations = { } def SessionException__init__(self, message=None,): self.message = message SessionException.__init__ = SessionException__init__ def SessionException__setstate__(self, state): state.setdefault('message', None) self.__dict__ = state SessionException.__getstate__ = lambda self: self.__dict__.copy() SessionException.__setstate__ = SessionException__setstate__ all_structs.append(UnsupportedCommandException) UnsupportedCommandException.thrift_spec = ( None, # 0 (1, TType.STRING, 'message', True, None, 2, ), # 1 ) UnsupportedCommandException.thrift_struct_annotations = { } UnsupportedCommandException.thrift_field_annotations = { } def UnsupportedCommandException__init__(self, message=None,): self.message = message UnsupportedCommandException.__init__ = UnsupportedCommandException__init__ def UnsupportedCommandException__setstate__(self, state): state.setdefault('message', None) self.__dict__ = state UnsupportedCommandException.__getstate__ = lambda self: self.__dict__.copy() UnsupportedCommandException.__setstate__ = UnsupportedCommandException__setstate__ all_structs.append(InstanceOverloaded) InstanceOverloaded.thrift_spec = ( None, # 0 (1, TType.STRING, 'message', True, None, 2, ), # 1 ) InstanceOverloaded.thrift_struct_annotations = { } InstanceOverloaded.thrift_field_annotations = { } def InstanceOverloaded__init__(self, message=None,): self.message = message InstanceOverloaded.__init__ = InstanceOverloaded__init__ def InstanceOverloaded__setstate__(self, state): state.setdefault('message', None) self.__dict__ = state InstanceOverloaded.__getstate__ = lambda self: self.__dict__.copy() InstanceOverloaded.__setstate__ = InstanceOverloaded__setstate__ all_structs.append(SessionData) SessionData.thrift_spec = ( None, # 0 (1, TType.STRING, 'subsystem', True, None, 1, ), # 1 (2, TType.STRING, 'exec_command', True, None, 1, ), # 2 ) SessionData.thrift_struct_annotations = { } SessionData.thrift_field_annotations = { } def SessionData__init__(self, subsystem=None, exec_command=None,): self.subsystem = subsystem self.exec_command = exec_command SessionData.__init__ = SessionData__init__ def SessionData__setstate__(self, state): state.setdefault('subsystem', None) state.setdefault('exec_command', None) self.__dict__ = state SessionData.__getstate__ = lambda self: self.__dict__.copy() SessionData.__setstate__ = SessionData__setstate__ all_structs.append(Device) Device.thrift_spec = ( None, # 0 (1, TType.STRING, 'hostname', True, None, 0, ), # 1 None, # 2 None, # 3 None, # 4 None, # 5 None, # 6 None, # 7 None, # 8 None, # 9 (10, TType.STRING, 'username', True, None, 0, ), # 10 (11, TType.STRING, 'password', True, None, 0, ), # 11 None, # 12 (13, TType.STRING, 'console', True, "", 1, ), # 13 (14, TType.BOOL, 'mgmt_ip', None, False, 1, ), # 14 (15, TType.MAP, 'command_prompts', (TType.STRING,True,TType.STRING,True), None, 1, ), # 15 (16, TType.STRING, 'ip_address', True, None, 1, ), # 16 (17, TType.I32, 'session_type', SessionType, None, 1, ), # 17 (18, TType.STRUCT, 'session_data', [SessionData, SessionData.thrift_spec, False], None, 1, ), # 18 ) Device.thrift_struct_annotations = { } Device.thrift_field_annotations = { } def Device__init__(self, hostname=None, username=None, password=None, console=Device.thrift_spec[13][4], mgmt_ip=Device.thrift_spec[14][4], command_prompts=None, ip_address=None, session_type=None, session_data=None,): self.hostname = hostname self.username = username self.password = password self.console = console self.mgmt_ip = mgmt_ip self.command_prompts = command_prompts self.ip_address = ip_address self.session_type = session_type self.session_data = session_data Device.__init__ = Device__init__ def Device__setstate__(self, state): state.setdefault('hostname', None) state.setdefault('username', None) state.setdefault('password', None) state.setdefault('console', "") state.setdefault('mgmt_ip', False) state.setdefault('command_prompts', None) state.setdefault('ip_address', None) state.setdefault('session_type', None) state.setdefault('session_data', None) self.__dict__ = state Device.__getstate__ = lambda self: self.__dict__.copy() Device.__setstate__ = Device__setstate__ all_structs.append(CommandResult) CommandResult.thrift_spec = ( None, # 0 (1, TType.STRING, 'output', True, None, 0, ), # 1 (2, TType.STRING, 'status', True, None, 0, ), # 2 (3, TType.STRING, 'command', True, None, 0, ), # 3 ) CommandResult.thrift_struct_annotations = { } CommandResult.thrift_field_annotations = { } def CommandResult__init__(self, output=None, status=None, command=None,): self.output = output self.status = status self.command = command CommandResult.__init__ = CommandResult__init__ def CommandResult__setstate__(self, state): state.setdefault('output', None) state.setdefault('status', None) state.setdefault('command', None) self.__dict__ = state CommandResult.__getstate__ = lambda self: self.__dict__.copy() CommandResult.__setstate__ = CommandResult__setstate__ all_structs.append(Session) Session.thrift_spec = ( None, # 0 (1, TType.I64, 'id', None, None, 0, ), # 1 (2, TType.STRING, 'name', True, None, 0, ), # 2 (3, TType.STRING, 'hostname', True, None, 0, ), # 3 ) Session.thrift_struct_annotations = { } Session.thrift_field_annotations = { } def Session__init__(self, id=None, name=None, hostname=None,): self.id = id self.name = name self.hostname = hostname Session.__init__ = Session__init__ def Session__setstate__(self, state): state.setdefault('id', None) state.setdefault('name', None) state.setdefault('hostname', None) self.__dict__ = state Session.__getstate__ = lambda self: self.__dict__.copy() Session.__setstate__ = Session__setstate__ fix_spec(all_structs) del all_structs

41.047694

339

0.715429

6,116

52,500

5.910726

0.03826

0.026279

0.023402

0.018811

0.792669

0.771508

0.752089

0.734938

0.724979

0.697206

0

0.012561

0.173581

52,500

1,278

340

41.079812

0.820638

0.020133

0

0.655832

1

0

0.044941

0.002068

0

1

0.082218

false

0.013384

0.027725

0.234226

0.021989

0

null

0

1

0

1

0

null

0

6

87a35ff42afe92edef9ef204919e56ac5f577673

544

py

Python

desafio109/teste109.py

marcelocmedeiros/RevisaoPython

04c602bf17e8ab37c9660337a8f8497eb498e10d

[ "MIT" ]

null

desafio109/teste109.py

marcelocmedeiros/RevisaoPython

04c602bf17e8ab37c9660337a8f8497eb498e10d

[ "MIT" ]

null

desafio109/teste109.py

marcelocmedeiros/RevisaoPython

04c602bf17e8ab37c9660337a8f8497eb498e10d

[ "MIT" ]

null

import moeda109 p = float(input('Digite o preço: R$ ')) # quando eu chamar True(3° parametro) estou pedindo para todos os preços virem formatados print(f'A metade de {moeda109.moeda(p)} é {moeda109.metade(p, True)}') print(f'A dobro de {moeda109.moeda(p)} é {moeda109.dobro(p, True)}') # parametros p = preço, taxa = 10 ou qualquer valor e formatado = True p ter preço formatado print(f'Aumentado 10% de {moeda109.moeda(p)} é {moeda109.aumentar(p, 10, True)}') print(f'Diminuindo 20% de {moeda109.moeda(p)} é {moeda109.diminuir(p, 20, True)}')

60.444444

92

0.716912

93

544

4.204301

0.494624

0.061381

0.153453

0.163683

0.255754

0

0.080508

0.132353

544

9

93

60.444444

0.745763

0.327206

0

0.333333

0.769231

0.115385

0

0.111111

0

1

0

false

0

0.166667

0

0.166667

0.666667

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

6

87b4ed66ccc845cebe820315829ff91c20ec33b3

4,861

py

Python

modelzoo/migrations/0025_auto_20201015_1628.py

SuperElastix/ElastixModelZooWebsite

00d7b4aec8eb04c285d3771d53310079a3443fab

[ "Apache-2.0" ]

1

2021-11-15T07:30:24.000Z

modelzoo/migrations/0025_auto_20201015_1628.py

SuperElastix/ElastixModelZooWebsite

00d7b4aec8eb04c285d3771d53310079a3443fab

[ "Apache-2.0" ]

null

modelzoo/migrations/0025_auto_20201015_1628.py

SuperElastix/ElastixModelZooWebsite

00d7b4aec8eb04c285d3771d53310079a3443fab

[ "Apache-2.0" ]

null

# Generated by Django 3.0.3 on 2020-10-15 14:28 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('modelzoo', '0024_auto_20201014_1425'), ] operations = [ migrations.RemoveField( model_name='model', name='parameter_file1', ), migrations.RemoveField( model_name='model', name='parameter_file10', ), migrations.RemoveField( model_name='model', name='parameter_file11', ), migrations.RemoveField( model_name='model', name='parameter_file12', ), migrations.RemoveField( model_name='model', name='parameter_file13', ), migrations.RemoveField( model_name='model', name='parameter_file14', ), migrations.RemoveField( model_name='model', name='parameter_file15', ), migrations.RemoveField( model_name='model', name='parameter_file16', ), migrations.RemoveField( model_name='model', name='parameter_file17', ), migrations.RemoveField( model_name='model', name='parameter_file18', ), migrations.RemoveField( model_name='model', name='parameter_file19', ), migrations.RemoveField( model_name='model', name='parameter_file2', ), migrations.RemoveField( model_name='model', name='parameter_file20', ), migrations.RemoveField( model_name='model', name='parameter_file21', ), migrations.RemoveField( model_name='model', name='parameter_file22', ), migrations.RemoveField( model_name='model', name='parameter_file23', ), migrations.RemoveField( model_name='model', name='parameter_file24', ), migrations.RemoveField( model_name='model', name='parameter_file25', ), migrations.RemoveField( model_name='model', name='parameter_file26', ), migrations.RemoveField( model_name='model', name='parameter_file27', ), migrations.RemoveField( model_name='model', name='parameter_file28', ), migrations.RemoveField( model_name='model', name='parameter_file29', ), migrations.RemoveField( model_name='model', name='parameter_file3', ), migrations.RemoveField( model_name='model', name='parameter_file30', ), migrations.RemoveField( model_name='model', name='parameter_file31', ), migrations.RemoveField( model_name='model', name='parameter_file32', ), migrations.RemoveField( model_name='model', name='parameter_file33', ), migrations.RemoveField( model_name='model', name='parameter_file34', ), migrations.RemoveField( model_name='model', name='parameter_file4', ), migrations.RemoveField( model_name='model', name='parameter_file5', ), migrations.RemoveField( model_name='model', name='parameter_file6', ), migrations.RemoveField( model_name='model', name='parameter_file7', ), migrations.RemoveField( model_name='model', name='parameter_file8', ), migrations.RemoveField( model_name='model', name='parameter_file9', ), migrations.AlterField( model_name='model', name='content', field=models.CharField(blank=True, choices=[('Head', 'Head'), ('Brain', 'Brain'), ('Neck', 'Neck'), ('Carotid', 'Carotid'), ('Chest', 'Chest'), ('Lung', 'Lung'), ('Cardiac', 'Cardiac'), ('Abdomen', 'Abdomen'), ('Liver', 'Liver'), ('Cervix', 'Cervix'), ('Prostate', 'Prostate'), ('Pelvis', 'Pelvis'), ('Knee', 'Knee'), ('Cervical', 'Cervix'), ('Pelvic', 'Pelvis')], default='', max_length=15), ), migrations.AlterField( model_name='model', name='modality', field=models.CharField(blank=True, choices=[('CT', 'CT'), ('Ultrasound', 'Ultrasound'), ('MRI', 'MRI'), ('PET', 'PET'), ('X-Ray', 'X-Ray'), ('MR', 'MRI'), ('US', 'Ultrasound')], default='', max_length=15), ), ]

30.38125

404

0.5108

381

4,861

6.32021

0.254593

0.269103

0.209302

0.269103

0.739203

0.677741

0

0.029851

0.352191

4,861

159

405

30.572327

0.734836

0.009257

0

0.705882

1

0

0.206481

0.004778

0

1

0

false

0

0.006536

0

0.026144

0

null

1

0

1

0

1

0

null

0

6

87cd79f0f1db4152c3226ab7f49974cf7638173b

90,994

py

Python

Plot_modules/plottingSHIPcal.py

mihaipx/SHIPcal

45d108c82ca845546ef854c4624ac2d4f981cf0a

[ "MIT" ]

5

2019-12-21T10:41:37.000Z

2022-03-14T19:22:23.000Z

Plot_modules/plottingSHIPcal.py

mihaipx/SHIPcal

45d108c82ca845546ef854c4624ac2d4f981cf0a

[ "MIT" ]

17

2022-03-02T05:08:11.000Z

2022-03-23T15:43:58.000Z

Plot_modules/plottingSHIPcal.py

mihaipx/SHIPcal

45d108c82ca845546ef854c4624ac2d4f981cf0a

[ "MIT" ]

8

2022-02-03T16:00:50.000Z

2022-03-14T15:05:32.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat May 19 14:53:58 2018 @author: miguel """ from matplotlib import pyplot as plt from matplotlib.sankey import Sankey import numpy as np import pandas as pd from iapws import IAPWS97 from General_modules.func_General import bar_MPa,thermalOil,moltenSalt import io import base64 import os def SankeyPlot(sender,origin,lang,Production_max,Production_lim,Perd_term_anual,DNI_anual_irradiation,Area,num_loops,imageQlty,plotPath,**kwargs): #Proportions for Sankey raw_potential=DNI_anual_irradiation*Area*num_loops/1000 #MWh Utilization=(Production_max-Production_lim)/1000 #En Mwh Utilization_ratio=100*(Utilization/raw_potential) #Utilization ratio Thermal_loss=Perd_term_anual/1000 #Thermal loss over lim production Thermal_loss_ratio=100*(Thermal_loss/raw_potential) #Thermal loss over lim production Global_eff=100*(Production_lim/1000)/raw_potential Optic_loss_ratio=Global_eff-Thermal_loss_ratio-Utilization_ratio Production=Production_lim/1000 #en MWh sankeyDict={'Production':Production,'raw_potential':raw_potential,'Thermal_loss':Thermal_loss,'Utilization':Utilization} fig = plt.figure(figsize=(8, 8)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[],title="Diagrama Sankey producción solar") if lang=="eng": ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[],title="Solar production - Sankey diagram") sankey = Sankey(ax=ax, unit=None) if lang=="spa": sankey.add(flows=[raw_potential/Production, -raw_potential/Production], #DNI_anual_irradiation/(Production*2) es lo que debería estar, se ha puesto el 1.1 del raw sólo por mostrarlo gráficamente mejor fc='#F2FA52', pathlengths = [0.95,0.375], patchlabel='\n\n\n'+(str(int(DNI_anual_irradiation))+' kWh/m2 - Radiación solar en el emplazamiento'), trunklength=2, labels=['',' \n\n'+(str(int(raw_potential))+' MWh \n Radiación Solar*Area de colectores ('+str(int(Area*num_loops))+' m2)')], label='Radiación solar', orientations=[0, 0], rotation=-90) if lang=="eng": sankey.add(flows=[raw_potential/Production, -raw_potential/Production], #DNI_anual_irradiation/(Production*2) es lo que debería estar, se ha puesto el 1.1 del raw sólo por mostrarlo gráficamente mejor fc='#F2FA52', pathlengths = [0.95,0.375], patchlabel='\n\n\n'+(str(int(DNI_anual_irradiation))+' kWh/m2 - Solar radiation at the location'), trunklength=2, labels=['',' \n\n'+(str(int(raw_potential))+' MWh \n Solar Radiation*Area of collectors ('+str(int(Area*num_loops))+' m2)')], label='Solar radiation', orientations=[0, 0], rotation=-90) if lang=="spa": sankey.add(flows=[raw_potential/Production,-(raw_potential-Production-Thermal_loss-Utilization)/Production,-Utilization/Production,-Thermal_loss/Production, -Production/Production], fc='#FA9E52', pathlengths = [3,0.6,0.6,0.3,0.3], label='Instalación solar', labels=['', (''+str(round(raw_potential-Utilization-Production-Thermal_loss,1))+' MWh - No puede concentrarse'),(' '+str(round(Utilization,1))+' MWh - No puede utilizarse por la industria \n (no hay consumo cuando se produce)'),('\n '+str(round(Thermal_loss,1))+' MWh - Pérdidas térmicas'), ' '+(str(round(Production,1))+' MWh - Producción neta')], orientations=[0, 1,1,1, 0],rotation=-90, prior=0, connect=(1, 0)) if lang=="eng": sankey.add(flows=[raw_potential/Production,-(raw_potential-Production-Thermal_loss-Utilization)/Production,-Utilization/Production,-Thermal_loss/Production, -Production/Production], fc='#FA9E52', pathlengths = [3,0.6,0.6,0.3,0.3], label='Solar plant', labels=['', (''+str(round(raw_potential-Utilization-Production-Thermal_loss,1))+' MWh - Spillage'),(' '+str(round(Utilization,1))+' MWh - Industry cannot use the energy \n (There is no demand when it is produced)'),('\n '+str(round(Thermal_loss,1))+' MWh - Thermal losses'), ' '+(str(round(Production,1))+' MWh - Net production')], orientations=[0, 1,1,1, 0],rotation=-90, prior=0, connect=(1, 0)) diagrams = sankey.finish() plt.legend(loc='upper left') plt.tight_layout() if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64,sankeyDict if origin==-1: fig.savefig(str(plotPath)+'Sankey.png', format='png', dpi=imageQlty) return 0,sankeyDict if origin==0: return 0,sankeyDict def mollierPlotST(sender,origin,lang,type_integration,in_s,out_s,T_in_flag,T_in_C,T_in_C_AR,T_out_C,outProcess_s,T_out_process_C,P_op_bar,x_design,plotPath,imageQlty,**kwargs): P_op_Mpa=P_op_bar/10 sat_liq=IAPWS97(P=P_op_Mpa, x=0) sat_vap=IAPWS97(P=P_op_Mpa, x=1) mollier=pd.read_csv(os.path.dirname(__file__)+'/mollierWater.csv',sep=',',encoding = "ISO-8859-1",header=None) processEntropy=[] processEntropy.append(in_s) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processEntropy.append(sat_liq.s) processEntropy.append(out_s) processTemperature=[] if T_in_flag==1: processTemperature.append(T_in_C) else: processTemperature.append(np.average(T_in_C_AR)) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processTemperature.append(sat_liq.T-273) processTemperature.append(T_out_C) if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": processEntropy2=[] processTemperature2=[] processEntropy2.append(out_s) processEntropy2.append(sat_liq.s) processEntropy2.append(sat_vap.s) processTemperature2.append(T_out_C) processTemperature2.append(sat_vap.T-273) processTemperature2.append(sat_vap.T-273) if type_integration=="SL_L_RF": processEntropy2=[] processTemperature2=[] processEntropy2.append(out_s) processEntropy2.append(outProcess_s) processTemperature2.append(T_out_C) processTemperature2.append(T_out_process_C) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processEntropy2=[] processTemperature2=[] processEntropy2.append(out_s) processEntropy2.append(outProcess_s) processTemperature2.append(T_out_C) processTemperature2.append(T_out_C) i=0 s=0.1 s_max=8 s_step=0.1 P_isobar=P_op_bar #bar isobar=pd.DataFrame(np.zeros((int((s_max-s)/s_step),3)), columns=["T","h","s"]) while (s<s_max): stateIsobar=IAPWS97(P=bar_MPa(P_isobar), s=s) isobar["T"][i]=stateIsobar.T-273 isobar["h"][i]=stateIsobar.h isobar["s"][i]=s s=s+s_step i=i+1 fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) plt.text(7.5, 350, str(int(P_isobar))+"bar", size=10, color='k', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="spa": plt.title("Diagrama T-s en una fila de colectores") if lang=="eng": plt.title("T-s diagram in one array of solar collectors") plt.plot(processEntropy,processTemperature, color='r',lw=3,markersize=50,zorder=10 ) if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": plt.plot(processEntropy2,processTemperature2, color='m',lw=2,markersize=50,zorder=10 ) if type_integration=="SL_L_RF": plt.plot(processEntropy2,processTemperature2, color='m',lw=2,markersize=50,zorder=10 ) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": plt.plot(processEntropy2,processTemperature2, color='m',lw=2,markersize=50,zorder=10 ) plt.plot(mollier[1],mollier[0],':',lw=2) plt.plot(isobar["s"],isobar["T"]) if lang=="spa": if T_in_flag==1: plt.text(processEntropy[0]-1.5, processTemperature[0], "Entrada "+str(int(T_in_C))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) else: plt.text(processEntropy[0]-1.5, processTemperature[0], "Entrada "+str(int(np.average(T_in_C_AR)))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": if T_in_flag==1: plt.text(processEntropy[0]-1.5, processTemperature[0], "Input "+str(int(T_in_C))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) else: plt.text(processEntropy[0]-1.5, processTemperature[0], "Input "+str(int(np.average(T_in_C_AR)))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": if lang=="spa": plt.text(processEntropy[2]-1, processTemperature[2]+20, "Salida "+str(int(P_op_bar))+"bar x="+str(x_design), size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1], processTemperature2[1]-15, "Salida "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy[2]-1, processTemperature[2]+20, "Output "+str(int(P_op_bar))+"bar x="+str(x_design), size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1], processTemperature2[1]-15, "Output "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) else: if lang=="spa": plt.text(processEntropy[1]-1.3, processTemperature[1]+10, "Salida "+str(int(T_out_C))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy[1]-1.3, processTemperature[1]+10, "Output "+str(int(T_out_C))+"ºC", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": if lang=="spa": plt.text(processEntropy2[2], processTemperature2[2]+20, "Salida "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy2[2], processTemperature2[2]+20, "Output "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_L_RF": if lang=="spa": plt.text(processEntropy2[1]-1.3, processTemperature2[1]+10, "Salida "+str(int(T_out_process_C))+"ºC", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy2[1]-1.3, processTemperature2[1]+10, "Output "+str(int(T_out_process_C))+"ºC", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="spa": plt.text(-2,200, "Liquido" , size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(4.5,20, "Liquido + Vapor", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(10,200, "Vapor", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) # plt.scatter(modules["s"],modules["T"]) plt.xlabel(r'Entropía (kJ/K/kg)') plt.ylabel(r'Temperatura (C)') if lang=="eng": plt.text(-2,200, "Liquid" , size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(4.5,20, "Liquid + Steam", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(10,200, "Steam", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) # plt.scatter(modules["s"],modules["T"]) plt.xlabel(r'Entropy (kJ/K/kg)') plt.ylabel(r'Temperature (C)') axes = plt.gca() axes.set_ylim([0,400]) axes.set_xlim([-3,11]) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin== -1: fig.savefig(str(plotPath)+'Mollier.png', format='png', dpi=imageQlty) #Save image for the report for the report def mollierPlotSH(sender,origin,lang,type_integration,h_in,h_out,hProcess_out,outProcess_h,in_s,out_s,T_in_flag,T_in_C,T_in_C_AR,T_out_C,outProcess_s,T_out_process_C,P_op_bar,x_design,plotPath,imageQlty,**kwargs): mollier=pd.read_csv(os.path.dirname(__file__)+'/mollierWater.csv',sep=',',encoding = "ISO-8859-1",header=None) P_op_Mpa=P_op_bar/10 sat_liq=IAPWS97(P=P_op_Mpa, x=0) sat_vap=IAPWS97(P=P_op_Mpa, x=1) processEntropy=[] processEntropy.append(in_s) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processEntropy.append(sat_liq.s) processEntropy.append(out_s) processEnthalpy=[] processEnthalpy.append(h_in) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processEnthalpy.append(sat_liq.h) processEnthalpy.append(h_out) if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": processEntropy2=[] processEnthalpy2=[] processEntropy2.append(out_s) processEntropy2.append(sat_vap.s) processEnthalpy2.append(h_out) processEnthalpy2.append(sat_vap.h) if type_integration=="SL_L_RF": processEntropy2=[] processEnthalpy2=[] processEntropy2.append(out_s) processEntropy2.append(outProcess_s) processEnthalpy2.append(h_out) processEnthalpy2.append(hProcess_out) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": processEntropy2=[] processEnthalpy2=[] processEntropy2.append(out_s) processEntropy2.append(outProcess_s) processEnthalpy2.append(h_out) processEnthalpy2.append(outProcess_h) i=0 s=0.1 s_max=8 s_step=0.1 P_isobar=P_op_bar #bar isobar=pd.DataFrame(np.zeros((int((s_max-s)/s_step),3)), columns=["T","h","s"]) while (s<s_max): stateIsobar=IAPWS97(P=bar_MPa(P_isobar), s=s) isobar["h"][i]=stateIsobar.h isobar["s"][i]=s s=s+s_step i=i+1 fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) plt.text(5, IAPWS97(P=bar_MPa(P_isobar),s=5).h-500, str(int(P_isobar))+"bar", size=10, color='k', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="spa": plt.title("Diagrama h-s en una fila de colectores") if lang=="eng": plt.title("H-s diagram in one array of solar collectors") if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": plt.plot(processEntropy2,processEnthalpy2, color='m',lw=2,markersize=50,zorder=10 ) if type_integration=="SL_L_RF": plt.plot(processEntropy2,processEnthalpy2, color='m',lw=2,markersize=50,zorder=10 ) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": plt.plot(processEntropy2,processEnthalpy2, color='m',lw=2,markersize=50,zorder=10 ) plt.plot(processEntropy,processEnthalpy, color='r',lw=3,markersize=50,zorder=10 ) plt.plot(mollier[1],mollier[2],':',lw=2) plt.plot(isobar["s"],isobar["h"]) if lang=="spa": plt.text(processEntropy[0]-1.8, processEnthalpy[0]+100, "Entrada "+str(int(h_in))+" kJ/kg", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy[0]-1.8, processEnthalpy[0]+100, "Inlet "+str(int(h_in))+" kJ/kg", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_S_PD" or type_integration=="SL_S_PDS": if lang=="spa": plt.text(processEntropy[2]+1.8, processEnthalpy[2]-100, "Salida "+str(int(P_op_bar))+"bar x="+str(x_design), size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-100, "Salida "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy[2]+1.8, processEnthalpy[2]-100, "Output "+str(int(P_op_bar))+"bar x="+str(x_design), size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-100, "Output "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) else: if lang=="spa": plt.text(processEntropy[1]-1.5, processEnthalpy[1]+150, "Salida "+str(int(h_out))+" kJ/kg", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy[1]-1.5, processEnthalpy[1]+150, "Output "+str(int(h_out))+" kJ/kg", size=10, color='r', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_S_FWS" or type_integration=="SL_S_FW": if lang=="spa": plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-100, "Salida "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-300, "Salida "+str(int(sat_vap.h))+" kJ/kg", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-100, "Output "+str(int(P_op_bar))+"bar Sat.", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(processEntropy2[1]+1.8, processEnthalpy2[1]-300, "Output "+str(int(sat_vap.h))+" kJ/kg", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if type_integration=="SL_L_RF": if lang=="spa": plt.text(processEntropy2[1]-1.5, processEnthalpy2[1]+150, "Salida "+str(int(hProcess_out))+" kJ/kg", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="eng": plt.text(processEntropy2[1]-1.5, processEnthalpy2[1]+150, "Output "+str(int(hProcess_out))+" kJ/kg", size=10, color='m', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) if lang=="spa": plt.text(-1,1500, "Liquido" , size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(4.5,200, "Liquido + Vapor", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(10,2000, "Vapor", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) # plt.scatter(modules["s"],modules["T"]) plt.xlabel(r'Entropía (kJ/K/kg)') plt.ylabel(r'Entalpía (kJ/Kg)') if lang=="eng": plt.text(-1,1500, "Liquid" , size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(4.5,200, "Liquid + Steam", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) plt.text(10,2000, "Steam", size=10, color='b', ha='center', va='center', horizontalalignment='center', verticalalignment='center', rotation= 0) # plt.scatter(modules["s"],modules["T"]) plt.xlabel(r'Entropy (kJ/K/kg)') plt.ylabel(r'Enthalpy (kJ/Kg)') axes = plt.gca() axes.set_ylim([0,3000]) axes.set_xlim([-3,11]) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'Mollier2.png', format='png', dpi=imageQlty) #Save for the report def thetaAnglesPlot(sender,origin,step_sim,steps_sim,theta_i_deg,theta_transv_deg,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Ángulos theta', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(step_sim, theta_i_deg,'.r-',label="Ang_incidencia") ax1 .plot(step_sim, theta_transv_deg,'.b-',label="Incidencia_transversal") ax1 .axhline(y=0,xmin=0,xmax=steps_sim,c="blue",linewidth=0.5,zorder=0) ax1.set_xlabel('Simulación (hora del año)') ax1.set_ylabel('Grados') plt.legend( loc='upper left', borderaxespad=0.) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'tetha.png', format='png', dpi=imageQlty) def IAMAnglesPlot(sender,origin,step_sim,IAM_long,IAM_t,IAM,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('IAMs', fontsize=14, fontweight='bold') ax2 = fig.add_subplot(111) ax2 .plot(step_sim, IAM_long,'.-',color = 'b',label="IAM_long") ax2 .plot(step_sim, IAM_t,'.-',color = 'r',label="IAM_transv") ax2 .plot(step_sim, IAM,'.-',color = '#39B8E3',label="IAM") ax2.set_xlabel('Simulación (hora del año)') ax2.set_ylabel('Grados') plt.legend(loc='upper left', borderaxespad=0.) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'IAM.png', format='png', dpi=imageQlty) def demandVsRadiation(sender,origin,lang,step_sim,Demand,Q_prod,Q_prod_lim,Q_prod_rec,steps_sim,DNI,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Demanda vs Radiación solar', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(step_sim, Demand,'.k-',label="Demanda") ax1 .plot(step_sim, Q_prod,'.r-',label="Produccion solar total") ax1 .plot(step_sim, Q_prod_lim,'.b-',label="Produccion util") ax1 .plot(step_sim, Q_prod_rec,'.g-',label="Produccion Rec") ax1 .axhline(y=0,xmin=0,xmax=steps_sim,c="blue",linewidth=0.5,zorder=0) ax1.set_xlabel('Simulación (hora del año)') ax1.set_ylabel('Demanda - kWh',color="blue") ax1.set_ylim([0,max(np.max(Q_prod),np.max(Demand))*1.2]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, DNI,'.-',color = 'orange',label="DNI") ax2.set_ylabel('Radiación solar - W/m2',color='red') ax2.set_ylim([0,np.max(DNI)*1.2]) plt.legend(loc='upper right', borderaxespad=0.) if lang=="eng": fig.suptitle('Demand vs Solar Radiation', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(step_sim, Demand,'.k-',label="Demand") ax1 .plot(step_sim, Q_prod,'.r-',label="Total solar production") ax1 .plot(step_sim, Q_prod_lim,'.b-',label="Net production") ax1 .plot(step_sim, Q_prod_rec,'.g-',label="Production Rec") ax1 .axhline(y=0,xmin=0,xmax=steps_sim,c="blue",linewidth=0.5,zorder=0) ax1.set_xlabel('simulation time (hour of the year)') ax1.set_ylabel('Demand - kWh',color="blue") ax1.set_ylim([0,np.max(Demand)*1.2]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, DNI,'.-',color = 'orange',label="DNI") ax2.set_ylabel('Solar Radiaton - W/m2',color='red') plt.legend(loc='upper right', borderaxespad=0.) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'demandProduction.png', format='png', dpi=imageQlty) def rhoTempPlotSalt(sender,origin,lang,T_out_C,plotPath,imageQlty,**kwargs): rhoList=[] CpList=[] T_step=[] for T in range(100+273,600+273,5): T_step.append(T-273) [rho,Cp,k,Dv]=moltenSalt(T) rhoList.append(rho) CpList.append(Cp) fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Propiedades de las sales fundidas', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(rhoList)), rhoList,'.k-',label="Densidad") [rho,Cp,k,Dv]=moltenSalt(T_out_C+273) plt .hlines(y=rho,xmin=0,xmax=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),c="r") ax1.set_xlabel('Temperatura ºC') ax1.set_ylabel('Densidad - kg/m3') ax2 = ax1.twinx() ax2 .plot(np.arange(len(rhoList)), CpList,'.b-',label="Calor específico") ax2.set_ylabel('Calor Específico - KJ/kgK', color="blue") plt.xticks(list(np.arange(len(rhoList)))[1::8], T_step[1::8]) plt .hlines(y=Cp,xmin=min(range(len(CpList)), key=lambda i: abs(CpList[i]-Cp)),xmax=len(T_step),color="blue",linewidth=1,zorder=0) if lang=="eng": fig.suptitle('Molten Salt properties', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(rhoList)), rhoList,'.k-',label="Density") [rho,Cp,k,Dv]=moltenSalt(T_out_C+273) plt .hlines(y=rho,xmin=0,xmax=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),c="r") ax1.set_xlabel('Temperature ºC') ax1.set_ylabel('Density - kg/m3') ax2 = ax1.twinx() ax2 .plot(np.arange(len(rhoList)), CpList,'.b-',label="Specific heat") ax2.set_ylabel('Specific heat - lKJ/kgK', color="blue") plt.xticks(list(np.arange(len(rhoList)))[1::8], T_step[1::8]) plt .hlines(y=Cp,xmin=min(range(len(CpList)), key=lambda i: abs(CpList[i]-Cp)),xmax=len(T_step),color="blue",linewidth=1,zorder=0) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'Salt.png', format='png', dpi=imageQlty) def rhoTempPlotOil(sender,origin,lang,T_out_C,plotPath,imageQlty,**kwargs): rhoList=[] CpList=[] T_step=[] for T in range(-20+273,320+273,5): T_step.append(T-273) [rho,Cp,k_av,Dv_av,Kv_av,thermalDiff_av,Prant_av]=thermalOil(T) rhoList.append(rho) CpList.append(Cp) fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Propiedades del Aceite térmico', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(rhoList)), rhoList,'.k-',label="Densidad") [rho,Cp,k_av,Dv_av,Kv_av,thermalDiff_av,Prant_av]=thermalOil(T_out_C+273) plt .hlines(y=rho,xmin=0,xmax=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),c="r") ax1.set_xlabel('Temperatura ºC') ax1.set_ylabel('Densidad - kg/m3') ax2 = ax1.twinx() ax2 .plot(np.arange(len(rhoList)), CpList,'.b-',label="Calor específico") ax2.set_ylabel('Calor Específico - KJ/kgK', color="blue") plt.xticks(list(np.arange(len(rhoList)))[1::8], T_step[1::8]) plt .hlines(y=Cp,xmin=min(range(len(CpList)), key=lambda i: abs(CpList[i]-Cp)),xmax=len(T_step),color="blue",linewidth=1,zorder=0) if lang=="eng": fig.suptitle('Thermal Oil properties', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(rhoList)), rhoList,'.k-',label="Density") [rho,Cp,k_av,Dv_av,Kv_av,thermalDiff_av,Prant_av]=thermalOil(T_out_C+273) plt .hlines(y=rho,xmin=0,xmax=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(rhoList)), key=lambda i: abs(rhoList[i]-rho)),c="r") ax1.set_xlabel('Temperature ºC') ax1.set_ylabel('Density - kg/m3') ax2 = ax1.twinx() ax2 .plot(np.arange(len(rhoList)), CpList,'.b-',label="Specific heat") ax2.set_ylabel('Specific heat - KJ/kgK', color="blue") plt.xticks(list(np.arange(len(rhoList)))[1::8], T_step[1::8]) plt .hlines(y=Cp,xmin=min(range(len(CpList)), key=lambda i: abs(CpList[i]-Cp)),xmax=len(T_step),color="blue",linewidth=1,zorder=0) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'Oil.png', format='png', dpi=imageQlty) def viscTempPlotSalt(sender,origin,lang,T_out_C,plotPath,imageQlty,**kwargs): DvList=[] T_step=[] for T in range(100+273,600+273,5): T_step.append(T-273) [rho,Cp,k,Dv]=moltenSalt(T) DvList.append(Dv*1e3) DvList=DvList[4:] fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Viscosidad de las sales fudidas', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(DvList)), DvList,'.k-',label="Viscosidad dinámica") [rho,Cp,k,Dv]=moltenSalt(T_out_C+273) plt .hlines(y=Dv*1e3,xmin=0,xmax=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3)),color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3)),c="r") ax1.set_xlabel('Temperatura ºC') ax1.set_ylabel('Viscosidad dinámica*1e3 - Ns/m2') ax1.set_yscale('log') plt.xticks(list(np.arange(len(T_step)))[1::8], T_step[1::8]) if lang=="eng": fig.suptitle('Molten Salt Viscosity', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(DvList)), DvList,'.k-',label="Dynamic viscosity") [rho,Cp,k,Dv]=moltenSalt(T_out_C+273) plt .hlines(y=Dv*1e3,xmin=0,xmax=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,c="r") ax1.set_xlabel('Temperature ºC') ax1.set_ylabel('Dynamic viscosity*1e3 - Ns/m2') ax1.set_yscale('log') if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'Salt2.png', format='png', dpi=imageQlty) def viscTempPlotOil(sender,origin,lang,T_out_C,plotPath,imageQlty,**kwargs): DvList=[] KvList=[] T_step=[] for T in range(-20+273,320+273,5): T_step.append(T-273) [rho,Cp,k,Dv,Kv,thermalDiff,Prant]=thermalOil(T) DvList.append(Dv*1e3) KvList.append(Kv*1e6) DvList=DvList[4:] KvList=KvList[4:] fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Viscosidad del Aceite térmico', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(DvList)), DvList,'.k-',label="Viscosidad dinámica") [rho,Cp,k,Dv,Kv,thermalDiff,Prant]=thermalOil(T_out_C+273) plt .hlines(y=Dv*1e3,xmin=0,xmax=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,c="r") ax1.set_xlabel('Temperatura ºC') ax1.set_ylabel('Viscosidad dinámica*1e3 - Ns/m2') ax1.set_yscale('log') ax2 = ax1.twinx() ax2 .plot(np.arange(len(KvList)), KvList,'.b-',label="Viscosidad cinemática") ax2.set_ylabel('Viscosidad cinemática*1e6 - m2/s', color="blue") ax2.set_yscale('log') plt.xticks(list(np.arange(len(T_step)))[1::8], T_step[1::8]) plt .hlines(y=Kv*1e6,xmin=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,xmax=len(T_step),color="blue",linewidth=1,zorder=0) if lang=="eng": fig.suptitle('Thermal Oil Viscosity', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(len(DvList)), DvList,'.k-',label="Dynamic viscosity") [rho,Cp,k,Dv,Kv,thermalDiff,Prant]=thermalOil(T_out_C+273) plt .hlines(y=Dv*1e3,xmin=0,xmax=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,color="#362510",linewidth=1,zorder=0) plt .axvline(x=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,c="r") ax1.set_xlabel('Temperature ºC') ax1.set_ylabel('Dynamic viscosity*1e3 - Ns/m2') ax1.set_yscale('log') ax2 = ax1.twinx() ax2 .plot(np.arange(len(KvList)), KvList,'.b-',label="Kinematic viscosity") ax2.set_ylabel('Kinematic viscosity*1e6 - m2/s', color="blue") ax2.set_yscale('log') plt.xticks(list(np.arange(len(T_step)))[1::8], T_step[1::8]) plt .hlines(y=Kv*1e6,xmin=min(range(len(DvList)), key=lambda i: abs(DvList[i]-Dv*1e3))+4,xmax=len(T_step),color="blue",linewidth=1,zorder=0) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'Oil2.png', format='png', dpi=imageQlty) def flowRatesPlot(sender,origin,step_sim,steps_sim,flow_rate_kgs,flow_rate_rec,num_loops,flowDemand,flowToHx,flowToMix,m_dot_min_kgs,T_in_K,T_toProcess_C,T_out_K,T_alm_K,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Caudales & temperaturas', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(step_sim, flow_rate_kgs,'m:',label="Caudal solar array") ax1 .plot(step_sim, flow_rate_rec,'g:',label="Caudal recirculación array") ax1 .plot(step_sim, flow_rate_kgs*num_loops,'.m-',label="Caudal solar SF") ax1 .plot(step_sim, flow_rate_rec*num_loops,'.g-',label="Caudal recirculación SF") ax1 .plot(step_sim, flowDemand,'.k-',label="Caudal demanda") ax1 .plot(step_sim, flowToHx,'.y-',label="Caudal flowToHx") ax1 .plot(step_sim, flowToMix,'.-',color='#6BD703',label="Caudal flowToMix") ax1 .axhline(y=m_dot_min_kgs,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_ylim([0,(np.max(flow_rate_kgs*num_loops))*1.1]) ax1.set_xlabel('Simulación (hora del año)') ax1.set_ylabel('Caudal - kg/s') plt.legend(bbox_to_anchor=(1.15, .5), loc=2, borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, T_in_K-273,'-',color = '#1F85DE',label="Temp_in Solar") ax2 .plot(step_sim, T_toProcess_C,'-',color = 'brown',label="Tem to Process") ax2 .plot(step_sim, T_out_K-273,'-',color = 'red',label="Temp_out Solar") ax2 .plot(step_sim, T_alm_K-273,':',color = 'orange',label="Temp_alm") ax2.set_ylabel('Temp - C') ax2.set_ylim([0,(np.max([np.max(T_toProcess_C)+273,np.max(T_out_K)])-273)*1.1]) plt.legend(bbox_to_anchor=(1.15, 1), loc=2, borderaxespad=0.) # output1=pd.DataFrame(flow_rate_kgs) # output1.columns=['Flow_rate'] # output2=pd.DataFrame(T_in_K) # output2.columns=['T_in_K'] # output3=pd.DataFrame(T_out_K) # output3.columns=['T_out_K'] # output_excel_FlowratesTemps=pd.concat([output1,output2,output3], axis=1) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'flowrates.png', format='png', dpi=imageQlty) def prodWinterPlot(sender,origin,lang,Demand,Q_prod,Q_prod_lim,type_integration,Q_charg,Q_discharg,DNI,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Producción solar primera semana Enero', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot(np.arange(167), DNI[0:167],color='#CA6A16',linestyle='solid',label="Radiación solar") ax1.set_xlabel('simulación (hora del año)') ax1.set_ylabel('Radiación Solar - W/m2') ax1.set_ylim([0,1200]) plt.legend(loc='upper left', borderaxespad=0.,frameon=False) ax2 = ax1.twinx() ax2.fill_between( np.arange(167), Demand[0:167], color="grey", alpha=0.2,label="Demanda") ax2 .plot(np.arange(167), Demand[0:167],'.-',color = '#362510',label="Demanda") if sender =='CIMAV': ax2 .plot(np.arange(167), Q_prod[0:167],'.-',color = 'red',label="Disipación") else: ax2 .plot(np.arange(167), Q_prod[0:167],'.-',color = 'red',label="Desenfoque") ax2 .plot(np.arange(167), Q_prod_lim[0:167],'.-',color = 'blue',label="Producción solar") if type_integration=="SL_L_PS" or type_integration=='SL_S_FWS': ax2 .plot(np.arange(167), Q_charg[0:167],'.-',color = '#FFAE00',label="Carga") ax2 .plot(np.arange(167), Q_discharg[0:167],'.-',color = '#2EAD23',label="Descarga") ax2.set_ylabel('Producción y Demanda - kWh') ax2.set_ylim([0,np.max(Q_prod)*4.2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) # plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0) plt.tight_layout() if lang=="eng": fig.suptitle('Solar production first week January', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot(np.arange(167), DNI[0:167],color='#CA6A16',linestyle='solid',label="Solar Radiation") ax1.set_xlabel('simulation time (hour of the year)') ax1.set_ylabel('Solar Radiation - W/m2') ax1.set_ylim([0,1200]) plt.legend(loc='upper left', borderaxespad=0.,frameon=False) ax2 = ax1.twinx() plt.fill_between( np.arange(167), Demand[0:167], color="grey", alpha=0.2,label="Demand") ax2 .plot(np.arange(167), Demand[0:167],'.-',color = '#362510',label="Demand") ax2 .plot(np.arange(167), Q_prod[0:167],'.-',color = 'red',label="Defocused") ax2 .plot(np.arange(167), Q_prod_lim[0:167],'.-',color = 'blue',label="Solar production") if type_integration=="SL_L_PS" or type_integration=='SL_S_FWS': ax2 .plot(np.arange(167), Q_charg[0:167],'.-',color = '#FFAE00',label="Charge") ax2 .plot(np.arange(167), Q_discharg[0:167],'.-',color = '#2EAD23',label="Discharge") ax2.set_ylabel('Production & Demand - kWh') ax2.set_ylim([0,np.max(Q_prod)*4.2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) # plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0) plt.tight_layout() # output4=pd.DataFrame(DNI) # output4.columns=['DNI'] # output5=pd.DataFrame(Demand) # output5.columns=['Demand'] # output6=pd.DataFrame(Q_prod) # output6.columns=['Q_prod'] # output_excel_Prod_wee_Jan=pd.concat([output1,output2,output3,output4,output5,output6], axis=1) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'produccion_solar1weekWinter.png', format='png', dpi=imageQlty) def prodSummerPlot(sender,origin,lang,Demand,Q_prod,Q_prod_lim,type_integration,Q_charg,Q_discharg,DNI,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Producción solar primera semana Junio', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot((np.arange(3624,3624+167,1)), DNI[3624:3791],color='#CA6A16',linestyle='solid',label="Radiación solar") ax1.set_xlabel('simulación (hora del año)') ax1.set_ylabel('Radiación Solar - W/m2') ax1.set_ylim([0,1200]) plt.legend(loc='upper left', borderaxespad=0.,frameon=False) ax2 = ax1.twinx() ax2.fill_between( np.arange(3624,3624+167,1), Demand[3624:3791], color="grey", alpha=0.2,label="Demanda") ax2 .plot((np.arange(3624,3624+167,1)), Demand[3624:3791],'.-',color = '#362510',label="Demanda") if sender =='CIMAV': ax2 .plot((np.arange(3624,3624+167,1)), Q_prod[3624:3791],'.-',color = 'red',label="Disipación") else: ax2 .plot((np.arange(3624,3624+167,1)), Q_prod[3624:3791],'.-',color = 'red',label="Desenfoque") ax2 .plot((np.arange(3624,3624+167,1)), Q_prod_lim[3624:3791],'.-',color = 'blue',label="Producción solar") if type_integration=="SL_L_PS" or type_integration=='SL_S_FWS': ax2 .plot((np.arange(3624,3624+167,1)), Q_charg[3624:3791],'.-',color = '#FFAE00',label="Carga") ax2 .plot((np.arange(3624,3624+167,1)), Q_discharg[3624:3791],'.-',color = '#2EAD23',label="Descarga") ax2.set_ylabel('Producción y Demanda - kWh') ax2.set_ylim([0,np.max(Q_prod)*4.2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) plt.tight_layout() if lang=="eng": fig.suptitle('Solar production first week of June', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot((np.arange(3624,3624+167,1)), DNI[3624:3791],color='#CA6A16',linestyle='solid',label="Solar Radiation") ax1.set_xlabel('simulation time (hour of the year)') ax1.set_ylabel('Solar Radiation - W/m2') ax1.set_ylim([0,1200]) plt.legend(loc='upper left', borderaxespad=0.,frameon=False) ax2 = ax1.twinx() ax2.fill_between( np.arange(3624,3624+167,1), Demand[3624:3791], color="grey", alpha=0.2,label="Demand") ax2 .plot((np.arange(3624,3624+167,1)), Demand[3624:3791],'.-',color = '#362510',label="Demand") ax2 .plot((np.arange(3624,3624+167,1)), Q_prod[3624:3791],'.-',color = 'red',label="Defocused") ax2 .plot((np.arange(3624,3624+167,1)), Q_prod_lim[3624:3791],'.-',color = 'blue',label="Solar Production") if type_integration=="SL_L_PS" or type_integration=='SL_S_FWS': ax2 .plot((np.arange(3624,3624+167,1)), Q_charg[3624:3791],'.-',color = '#FFAE00',label="Charge") ax2 .plot((np.arange(3624,3624+167,1)), Q_discharg[3624:3791],'.-',color = '#2EAD23',label="Discharge") ax2.set_ylabel('Production & Demand - kWh') ax2.set_ylim([0,np.max(Q_prod)*4.2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) plt.tight_layout() # output4=pd.DataFrame(DNI) # output4.columns=['DNI'] # output5=pd.DataFrame(Demand) # output5.columns=['Demand'] # output6=pd.DataFrame(Q_prod) # output6.columns=['Q_prod'] # # output_excel_Prod_week_Jun=pd.concat([output1,output2,output3,output4,output5,output6], axis=1) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'produccion_solar1weekSummer.png', format='png', dpi=imageQlty) def productionSolar(sender,origin,lang,step_sim,DNI,m_dot_min_kgs,steps_sim,Demand,Q_prod,Q_prod_lim,Q_charg,Q_discharg,type_integration,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Producción anual', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot(step_sim, DNI,'.r-',label="Radiación solar") # ax1 .axhline(y=m_dot_min_kgs,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_xlabel('Simulación (hora del año)') ax1.set_ylabel('Solar radiation - W/m2',color='red') legend =plt.legend(bbox_to_anchor=(0.12, -.07), loc=1, borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, Demand,'.-',color = '#362510',label="Demanda") ax2 .plot(step_sim, Q_prod,'.-',color = '#831896',label="Producción solar") ax2 .plot(step_sim, Q_prod_lim,'.-',color = 'blue',label="Energía suministrada") if type_integration=="SL_L_PS" or type_integration=="SL_S_FWS": ax2 .plot(step_sim, Q_charg,'.-',color = '#FFAE00',label="Carga") ax2 .plot(step_sim, Q_discharg,'.-',color = '#2EAD23',label="Descarga") ax2.set_ylabel('Producción & Demanda - kWh') ax2.set_ylim([0,np.max(Q_prod)*2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) plt.tight_layout() if lang=="eng": fig.suptitle('Annual Production', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) ax1 .plot(step_sim, DNI,'.r-',label="Solar Radiation") # ax1 .axhline(y=m_dot_min_kgs,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_xlabel('simulation time (hour of the year)') ax1.set_ylabel('Solar radiation - W/m2',color='red') legend =plt.legend(bbox_to_anchor=(0.12, -.07), loc=1, borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, Demand,'.-',color = '#362510',label="Demand") ax2 .plot(step_sim, Q_prod,'.-',color = '#831896',label="Solar production") ax2 .plot(step_sim, Q_prod_lim,'.-',color = 'blue',label="Net production") if type_integration=="SL_L_PS" or type_integration=="SL_S_FWS": ax2 .plot(step_sim, Q_charg,'.-',color = '#FFAE00',label="Charge") ax2 .plot(step_sim, Q_discharg,'.-',color = '#2EAD23',label="Discharge") ax2.set_ylabel('Production & Demand - kWh') ax2.set_ylim([0,np.max(Q_prod)*2]) plt.legend(bbox_to_anchor=(1.00, 1), loc=1, borderaxespad=0.) plt.tight_layout() # output4=pd.DataFrame(DNI) # output4.columns=['DNI'] # output5=pd.DataFrame(Demand) # output5.columns=['Demand'] # output6=pd.DataFrame(Q_prod) # output6.columns=['Q_prod'] # # output_excel_Prod_annual=pd.concat([output1,output2,output3,output4,output5,output6], axis=1) # fig.savefig('/home/miguel/Desktop/Python_files/PLAT_VIRT/fresnel/Report/images/produccion_solar.png', format='png', dpi=imageQlty) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'produccion_solar.png', format='png', dpi=imageQlty) def storageWinter(sender,origin,lang,Q_prod,Q_charg,Q_prod_lim,Q_useful,Demand,Q_defocus,Q_discharg,type_integration,T_alm_K,SOC,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Almacenamiento primera semana Enero', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.fill_between( np.arange(167), Demand[0:167], color="grey", alpha=0.2) plt.bar(np.arange(167), np.array(Q_prod[0:167])-np.array(Q_charg[0:167]),color = 'blue',label="Producción Solar",align='center') # ax1 .plot(np.arange(167), Q_prod_lim[0:167],color = 'blue',label="Energía suministrada",linewidth=4) # ax1 .plot(np.arange(167), Q_useful[0:167],color = 'green',label="Energía útil",linewidth=2) ax1 .plot(np.arange(167), Demand[0:167],color = '#362510',label="Demanda",linewidth=2.0) if sender =='CIMAV': plt.bar(np.arange(167), Q_defocus[0:167],color = 'red',label="Disipación",bottom=np.array(Q_prod[0:167])-np.array(Q_defocus[0:167]),align='center') else: plt.bar(np.arange(167), Q_defocus[0:167],color = 'red',label="Desenfoque",bottom=np.array(Q_prod[0:167])-np.array(Q_defocus[0:167]),align='center') plt.bar(np.arange(167), Q_charg[0:167],color = '#FFAE00',label="Carga",bottom=np.array(Q_prod[0:167])-np.array(Q_charg[0:167])-np.array(Q_defocus[0:167]),align='center') plt.bar(np.arange(167), Q_discharg[0:167],color = '#2EAD23',label="Descarga",bottom=np.array(Q_prod[0:167]),align='center') ax1.set_ylabel('Producción & Demanda - kWh') ax1.set_ylim([0,np.max([np.max(Q_prod[0:167]),np.max(Demand[0:167])])*1.1]) ax1.set_xlim([0,167]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() if type_integration=="SL_L_S" or type_integration=="SL_L_S_PH": ax2 .plot(np.arange(167), np.array(T_alm_K[0:167])-273,'r',label="Temperatura",linewidth=2.0) ax2 .plot(np.arange(167), SOC[0:167],color='orange',linestyle=':',label="Carga del almacenamiento",linewidth=2.0) ax2.set_xlabel('simulación (hora del año)') ax2.set_ylabel('Estado de carga almacenamiento %',color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([0,167]) if lang=="eng": fig.suptitle('Storage during the first week of January', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.fill_between( np.arange(167), Demand[0:167], color="grey", alpha=0.2) plt.bar(np.arange(167), np.array(Q_prod[0:167])-np.array(Q_charg[0:167]),color = 'blue',label="Solar Production",align='center') # ax1 .plot(np.arange(167), Q_prod_lim[0:167],color = 'blue',label="Net production",linewidth=4) # ax1 .plot(np.arange(167), Q_useful[0:167],color = 'green',label="Useful energy",linewidth=2) ax1 .plot(np.arange(167), Demand[0:167],color = '#362510',label="Demand",linewidth=2.0) plt.bar(np.arange(167), Q_defocus[0:167],color = 'red',label="Defocused",bottom=np.array(Q_prod[0:167])-np.array(Q_defocus[0:167]),align='center') plt.bar(np.arange(167), Q_charg[0:167],color = '#FFAE00',label="Charge",bottom=np.array(Q_prod[0:167])-np.array(Q_charg[0:167])-np.array(Q_defocus[0:167]),align='center') plt.bar(np.arange(167), Q_discharg[0:167],color = '#2EAD23',label="Discharge",bottom=np.array(Q_prod[0:167]),align='center') ax1.set_ylabel('Production & Demand - kWh') ax1.set_ylim([0,np.max([np.max(Q_prod[0:167]),np.max(Demand[0:167])])*1.1]) ax1.set_xlim([0,167]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() if type_integration=="SL_L_S" or type_integration=="SL_L_S_PH": ax2 .plot(np.arange(167), np.array(T_alm_K[0:167])-273,'r',label="Temperature",linewidth=2.0) ax2 .plot(np.arange(167), SOC[0:167],color='orange',linestyle=':',label="Storage's state of charge",linewidth=2.0) ax2.set_xlabel('simulation time (hour of the year)') ax2.set_ylabel("Storage's state of charge %",color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([0,167]) plt.tight_layout() if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'almacenamiento_Enero.png', format='png', dpi=imageQlty) def storageSummer(sender,origin,lang,Q_prod,Q_charg,Q_prod_lim,Q_useful,Demand,Q_defocus,Q_discharg,type_integration,T_alm_K,SOC,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) #np.array(in list) is because Django need it since Q_prod, Q_prod_lim,.. are passed as lists if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Almacenamiento primera semana Junio', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.fill_between( np.arange(3624,3624+167,1), Demand[3624:3791], color="grey", alpha=0.2) plt.bar((np.arange(3624,3624+167,1)), np.array(Q_prod[3624:3791])-np.array(Q_charg[3624:3791]),color = 'blue',label="Producción Solar",align='center') #ax1 .plot((np.arange(3624,3624+167,1)), Q_prod_lim[3624:3791],color = 'blue',label="Energía suministrada",linewidth=4) #ax1 .plot((np.arange(3624,3624+167,1)), Q_useful[3624:3791],color = 'green',label="Energía útil",linewidth=2) ax1 .plot((np.arange(3624,3624+167,1)), Demand[3624:3791],color = '#362510',label="Demanda",linewidth=2.0) if sender =='CIMAV': plt.bar((np.arange(3624,3624+167,1)), Q_defocus[3624:3791],color = 'red',label="Disipación",bottom=np.array(Q_prod[3624:3791])-np.array(Q_defocus[3624:3791]),align='center') else: plt.bar((np.arange(3624,3624+167,1)), Q_defocus[3624:3791],color = 'red',label="Desenfoque",bottom=np.array(Q_prod[3624:3791])-np.array(Q_defocus[3624:3791]),align='center') plt.bar((np.arange(3624,3624+167,1)), Q_charg[3624:3791],color = '#FFAE00',label="Carga",bottom=np.array(Q_prod[3624:3791])-np.array(Q_charg[3624:3791])-np.array(Q_defocus[3624:3791]),align='center') plt.bar((np.arange(3624,3624+167,1)), Q_discharg[3624:3791],color = '#2EAD23',label="Descarga",bottom=Q_prod[3624:3791],align='center') ax1.set_ylabel('Producción & Demanda - kWh') ax1.set_ylim([0,np.max([np.max(Q_prod[3624:3791]),np.max(Demand[3624:3791])])*1.1]) ax1.set_xlim([3624,3624+167]) ax1.legend(loc='upper left', borderaxespad=0.).set_zorder(99) ax2 = ax1.twinx() if type_integration=="SL_L_S" or type_integration=="SL_L_S_PH": ax2 .plot((np.arange(3624,3624+167,1)), np.array(T_alm_K[3624:3791])-273,'r',label="Carga del almacenamiento",linewidth=2.0,zorder=11) ax2 .plot((np.arange(3624,3624+167,1)), SOC[3624:3791],color='orange',linestyle=':',label="Carga del almacenamiento",linewidth=2.0,zorder=11) ax2.set_xlabel('simulación (hora del año)') ax2.set_ylabel('Estado de carga almacenamiento %',color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([3624,3624+167]) if lang=="eng": fig.suptitle('Storage during the first week of June', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.fill_between( np.arange(3624,3624+167,1), Demand[3624:3791], color="grey", alpha=0.2) plt.bar((np.arange(3624,3624+167,1)), np.array(Q_prod[3624:3791])-np.array(Q_charg[3624:3791]),color = 'blue',label="Solar Production",align='center') #ax1 .plot((np.arange(3624,3624+167,1)), Q_prod_lim[3624:3791],color = 'blue',label="Net Production",linewidth=4) #ax1 .plot((np.arange(3624,3624+167,1)), Q_useful[3624:3791],color = 'green',label="Useful energy",linewidth=2) ax1 .plot((np.arange(3624,3624+167,1)), Demand[3624:3791],color = '#362510',label="Demand",linewidth=2.0) plt.bar((np.arange(3624,3624+167,1)), Q_defocus[3624:3791],color = 'red',label="Defocused",bottom=np.array(Q_prod[3624:3791])-np.array(Q_defocus[3624:3791]),align='center') plt.bar((np.arange(3624,3624+167,1)), Q_charg[3624:3791],color = '#FFAE00',label="Charge",bottom=np.array(Q_prod[3624:3791])-np.array(Q_charg[3624:3791])-np.array(Q_defocus[3624:3791]),align='center') plt.bar((np.arange(3624,3624+167,1)), Q_discharg[3624:3791],color = '#2EAD23',label="Discharge",bottom=Q_prod[3624:3791],align='center') ax1.set_ylabel('Production & Demand - kWh') ax1.set_ylim([0,np.max([np.max(Q_prod[3624:3791]),np.max(Demand[3624:3791])])*1.1]) ax1.set_xlim([3624,3624+167]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot((np.arange(3624,3624+167,1)), SOC[3624:3791],color='orange',linestyle=':',label="Storage's state of charge %",linewidth=2.0) ax2.set_xlabel('simulation time (hour of the year)') ax2.set_ylabel("Storage's state of charge %",color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([3624,3624+167]) plt.tight_layout() if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'almacenamiento_Junio.png', format='png', dpi=imageQlty) def storageNonAnnual(sender,origin,SOC,Q_useful,Q_prod,Q_charg,Q_prod_lim,step_sim,Demand,Q_defocus,Q_discharg,steps_sim,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Almacenamiento', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.bar(step_sim, Q_prod-Q_charg,color = '#1F85DE',label="Producción Solar",align='center') ax1 .plot(step_sim, Q_prod_lim,color = 'blue',label="Energía suministrada",linewidth=4) ax1 .plot(step_sim, Q_useful,color = 'green',label="Energía útil",linewidth=2) ax1 .plot(step_sim, Demand,color = '#362510',label="Demanda") if sender =='CIMAV': plt.bar(step_sim, Q_defocus,color = 'red',label="Disipación",bottom=Q_prod-Q_defocus,align='center') else: plt.bar(step_sim, Q_defocus,color = 'red',label="Desenfoque",bottom=Q_prod-Q_defocus,align='center') plt.bar(step_sim, Q_charg,color = '#FFAE00',label="Carga",bottom=Q_prod-Q_charg-Q_defocus,align='center') plt.bar(step_sim, Q_discharg,color = '#2EAD23',label="Descarga",bottom=Q_prod,align='center') ax1.set_ylabel('Producción & Demanda - kWh') ax1.set_ylim([0,max(np.max(Q_prod),np.max(Demand))*1.2]) ax1.set_xlim([0,steps_sim]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, SOC,'.r-',label="Carga del almacenamiento") ax2.set_xlabel('simulación (hora del año)') ax2.set_ylabel('Estado de carga almacenamiento %',color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([0,steps_sim]) plt.tight_layout() if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'almacenamiento_Anual.png', format='png', dpi=imageQlty) def storageNonAnnualSL_S_PDR(sender,origin,SOC,Q_useful,Q_prod_steam,Q_prod,Q_drum,Q_charg,Q_prod_lim,step_sim,Demand,Q_defocus,Q_discharg,steps_sim,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Almacenamiento', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.bar(step_sim, Q_prod-Q_charg,color = '#1F85DE',label="Producción solar en el campo",align='center') plt.bar(step_sim, Q_prod_steam,color = '#7EE4E9',label="Producción de Vapor",align='center') ax1 .plot(step_sim, Q_prod_lim,color = 'blue',label="Energía suministrada",linewidth=4) ax1 .plot(step_sim, Q_useful,color = 'green',label="Energía útil",linewidth=2) ax1 .plot(step_sim, Demand,color = '#362510',label="Demanda") plt.bar(step_sim, Q_drum,color = '#FFAE00',label="Energía al drum",bottom=Q_prod_steam,align='center') plt.bar(step_sim, Q_defocus,color = 'red',label="Desenfoque",bottom=Q_prod_steam+Q_drum,align='center') ax1.set_ylabel('Producción & Demanda - kWh') ax1.set_ylim([0,max(np.max(Q_prod_steam+Q_drum+Q_defocus),np.max(Demand))*1.2]) ax1.set_xlim([0,steps_sim]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, SOC,'.r-',label="Carga del almacenamiento") ax2.set_xlabel('simulación (hora del año)') ax2.set_ylabel('Estado de carga almacenamiento %',color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([0,steps_sim]) plt.tight_layout() if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'almacenamiento_Anual.png', format='png', dpi=imageQlty) def storageNonAnnualSL_S_PDR(sender,origin,SOC,Q_useful,Q_prod_steam,Q_prod,Q_drum,Q_charg,Q_prod_lim,step_sim,Demand,Q_defocus,Q_discharg,steps_sim,plotPath,imageQlty,**kwargs): fig = plt.figure(figsize=(14, 3.5)) if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Almacenamiento', fontsize=14, fontweight='bold',y=1) ax1 = fig.add_subplot(111) plt.bar(step_sim, Q_prod-Q_charg,color = '#1F85DE',label="Producción solar en el campo",align='center') plt.bar(step_sim, Q_prod_steam,color = '#7EE4E9',label="Producción de Vapor",align='center') ax1 .plot(step_sim, Q_prod_lim,color = 'blue',label="Energía suministrada",linewidth=4) ax1 .plot(step_sim, Q_useful,color = 'green',label="Energía útil",linewidth=2) ax1 .plot(step_sim, Demand,color = '#362510',label="Demanda") plt.bar(step_sim, Q_drum,color = '#FFAE00',label="Energía al drum",bottom=Q_prod_steam,align='center') plt.bar(step_sim, Q_defocus,color = 'red',label="Desenfoque",bottom=Q_prod_steam+Q_drum,align='center') ax1.set_ylabel('Producción & Demanda - kWh') ax1.set_ylim([0,max(np.max(Q_prod_steam+Q_drum+Q_defocus),np.max(Demand))*1.2]) ax1.set_xlim([0,steps_sim]) plt.legend(loc='upper left', borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, SOC,'.r-',label="Carga del almacenamiento") ax2.set_xlabel('simulación (hora del año)') ax2.set_ylabel('Estado de carga almacenamiento %',color = '#CA6A16') ax2.set_ylim([0,101]) ax2.set_xlim([0,steps_sim]) plt.tight_layout() if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'almacenamiento_Anual.png', format='png', dpi=imageQlty) def financePlot(sender,origin,lang,n_years_sim,Acum_FCF,FCF,m_dot_min_kgs,steps_sim,AmortYear,Selling_price,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": fig.suptitle('Estudio financiero', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(n_years_sim), Acum_FCF,'.k-',label="Cash Flow acumulado") ax1 .plot(np.arange(n_years_sim), FCF,'.b-',label="Cash Flow") ax1 .axhline(y=m_dot_min_kgs,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_xlabel('años') if origin == -3: ax1.set_ylabel('$') else: ax1.set_ylabel('€') plt.legend(bbox_to_anchor=(1.15, .5), loc=2, borderaxespad=0.) plt.text(int(AmortYear),-Selling_price, "Año de retorno= "+str(int(AmortYear))) if lang=="eng": fig.suptitle('Financial study', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(np.arange(n_years_sim), Acum_FCF,'.k-',label="Accumulated Free Cash Flows") ax1 .plot(np.arange(n_years_sim), FCF,'.b-',label="Free Cash Flows") ax1 .axhline(y=m_dot_min_kgs,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_xlabel('years') if origin == -3: ax1.set_ylabel('$') else: ax1.set_ylabel('€') plt.legend(bbox_to_anchor=(1.15, .5), loc=2, borderaxespad=0.) plt.text(int(AmortYear),-Selling_price, "Payback period= "+str(int(AmortYear))) # plt.text(1,Acum_FCF[n_years_sim-1]*.55,"IRR: "+ str(round(IRR,2))+"%", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # plt.text(1,Acum_FCF[n_years_sim-1]*.35,"Solar_fraction: "+ str(round(solar_fraction_lim,1))+"%", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # plt.text(1,Acum_FCF[n_years_sim-1]*.85,"Energy_bill: "+ str(round(energy_bill))+"€", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # plt.text(1,Acum_FCF[n_years_sim-1]*.7,"Savings: "+ str(round(Solar_savings_lim))+"€", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # plt.text(1,Acum_FCF[n_years_sim-1]*.45,"Investment: "+ str(round(Selling_price))+"€", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # plt.text(1,Acum_FCF[n_years_sim-1],"Solar Irradiation: "+ str(round(DNI_anual_irradiation,1))+"kWh/m2", bbox={'boxstyle':'square', 'color':'#A0D8EB'}) # # ax2 = ax1.twinx() # ax2 .plot(step_sim, Demand,'.-',color = 'red',label="Demand") # ax2 .plot(step_sim, Q_prod,'.-',color = '#617824',label="Q_prod") # ax2 .plot(step_sim, Q_prod_lim,'.-',color = 'blue',label="Q_prod_lim") # ax2.set_ylabel('QProd vs DEmand - kWh') plt.legend(bbox_to_anchor=(0, 1), loc=2, borderaxespad=0.) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'finance.png', format='png', dpi=imageQlty) def arraysMonth(Q_prod,Q_prod_lim,DNI,Demand,**kwargs): #Para resumen mensual Ene_prod=np.zeros(8760) Feb_prod=np.zeros(8760) Mar_prod=np.zeros(8760) Abr_prod=np.zeros(8760) May_prod=np.zeros(8760) Jun_prod=np.zeros(8760) Jul_prod=np.zeros(8760) Ago_prod=np.zeros(8760) Sep_prod=np.zeros(8760) Oct_prod=np.zeros(8760) Nov_prod=np.zeros(8760) Dic_prod=np.zeros(8760) Ene_prod_lim=np.zeros(8760) Feb_prod_lim=np.zeros(8760) Mar_prod_lim=np.zeros(8760) Abr_prod_lim=np.zeros(8760) May_prod_lim=np.zeros(8760) Jun_prod_lim=np.zeros(8760) Jul_prod_lim=np.zeros(8760) Ago_prod_lim=np.zeros(8760) Sep_prod_lim=np.zeros(8760) Oct_prod_lim=np.zeros(8760) Nov_prod_lim=np.zeros(8760) Dic_prod_lim=np.zeros(8760) Ene_DNI=np.zeros(8760) Feb_DNI=np.zeros(8760) Mar_DNI=np.zeros(8760) Abr_DNI=np.zeros(8760) May_DNI=np.zeros(8760) Jun_DNI=np.zeros(8760) Jul_DNI=np.zeros(8760) Ago_DNI=np.zeros(8760) Sep_DNI=np.zeros(8760) Oct_DNI=np.zeros(8760) Nov_DNI=np.zeros(8760) Dic_DNI=np.zeros(8760) Ene_demd=np.zeros(8760) Feb_demd=np.zeros(8760) Mar_demd=np.zeros(8760) Abr_demd=np.zeros(8760) May_demd=np.zeros(8760) Jun_demd=np.zeros(8760) Jul_demd=np.zeros(8760) Ago_demd=np.zeros(8760) Sep_demd=np.zeros(8760) Oct_demd=np.zeros(8760) Nov_demd=np.zeros(8760) Dic_demd=np.zeros(8760) for i in range(0,8759): if (i<=744-1): Ene_prod[i]=Q_prod[i] Ene_prod_lim[i]=Q_prod_lim[i] Ene_DNI[i]=DNI[i] Ene_demd[i]=Demand[i] if (i>744-1) and (i<=1416-1): Feb_prod[i]=Q_prod[i] Feb_prod_lim[i]=Q_prod_lim[i] Feb_DNI[i]=DNI[i] Feb_demd[i]=Demand[i] if (i>1416-1) and (i<=2160-1): Mar_prod[i]=Q_prod[i] Mar_prod_lim[i]=Q_prod_lim[i] Mar_DNI[i]=DNI[i] Mar_demd[i]=Demand[i] if (i>2160-1) and (i<=2880-1): Abr_prod[i]=Q_prod[i] Abr_prod_lim[i]=Q_prod_lim[i] Abr_DNI[i]=DNI[i] Abr_demd[i]=Demand[i] if (i>2880-1) and (i<=3624-1): May_prod[i]=Q_prod[i] May_prod_lim[i]=Q_prod_lim[i] May_DNI[i]=DNI[i] May_demd[i]=Demand[i] if (i>3624-1) and (i<=4344-1): Jun_prod[i]=Q_prod[i] Jun_prod_lim[i]=Q_prod_lim[i] Jun_DNI[i]=DNI[i] Jun_demd[i]=Demand[i] if (i>4344-1) and (i<=5088-1): Jul_prod[i]=Q_prod[i] Jul_prod_lim[i]=Q_prod_lim[i] Jul_DNI[i]=DNI[i] Jul_demd[i]=Demand[i] if (i>5088-1) and (i<=5832-1): Ago_prod[i]=Q_prod[i] Ago_prod_lim[i]=Q_prod_lim[i] Ago_DNI[i]=DNI[i] Ago_demd[i]=Demand[i] if (i>5832-1) and (i<=6552-1): Sep_prod[i]=Q_prod[i] Sep_prod_lim[i]=Q_prod_lim[i] Sep_DNI[i]=DNI[i] Sep_demd[i]=Demand[i] if (i>6552-1) and (i<=7296-1): Oct_prod[i]=Q_prod[i] Oct_prod_lim[i]=Q_prod_lim[i] Oct_DNI[i]=DNI[i] Oct_demd[i]=Demand[i] if (i>7296-1) and (i<=8016-1): Nov_prod[i]=Q_prod[i] Nov_prod_lim[i]=Q_prod_lim[i] Nov_DNI[i]=DNI[i] Nov_demd[i]=Demand[i] if (i>8016-1): Dic_prod[i]=Q_prod[i] Dic_prod_lim[i]=Q_prod_lim[i] Dic_DNI[i]=DNI[i] Dic_demd[i]=Demand[i] array_de_meses=[np.sum(Ene_prod),np.sum(Feb_prod),np.sum(Mar_prod),np.sum(Abr_prod),np.sum(May_prod),np.sum(Jun_prod),np.sum(Jul_prod),np.sum(Ago_prod),np.sum(Sep_prod),np.sum(Oct_prod),np.sum(Nov_prod),np.sum(Dic_prod)] array_de_meses_lim=[np.sum(Ene_prod_lim),np.sum(Feb_prod_lim),np.sum(Mar_prod_lim),np.sum(Abr_prod_lim),np.sum(May_prod_lim),np.sum(Jun_prod_lim),np.sum(Jul_prod_lim),np.sum(Ago_prod_lim),np.sum(Sep_prod_lim),np.sum(Oct_prod_lim),np.sum(Nov_prod_lim),np.sum(Dic_prod_lim)] array_de_DNI=[np.sum(Ene_DNI),np.sum(Feb_DNI),np.sum(Mar_DNI),np.sum(Abr_DNI),np.sum(May_DNI),np.sum(Jun_DNI),np.sum(Jul_DNI),np.sum(Ago_DNI),np.sum(Sep_DNI),np.sum(Oct_DNI),np.sum(Nov_DNI),np.sum(Dic_DNI)] array_de_demd=[np.sum(Ene_demd),np.sum(Feb_demd),np.sum(Mar_demd),np.sum(Abr_demd),np.sum(May_demd),np.sum(Jun_demd),np.sum(Jul_demd),np.sum(Ago_demd),np.sum(Sep_demd),np.sum(Oct_demd),np.sum(Nov_demd),np.sum(Dic_demd)] array_de_fraction=np.zeros(12) return array_de_meses,array_de_meses_lim,array_de_DNI,array_de_demd,array_de_fraction def prodMonths(sender,origin,Q_prod,Q_prod_lim,DNI,Demand,lang,plotPath,imageQlty,**kwargs): array_de_meses,array_de_meses_lim,array_de_DNI,array_de_demd,array_de_fraction=arraysMonth(Q_prod,Q_prod_lim,DNI,Demand) for m in range(0,12): if array_de_demd[m]==0: array_de_fraction[m]=0 else: array_de_fraction[m]=100*array_de_meses[m]/array_de_demd[m] output1=pd.DataFrame(array_de_meses) output1.columns=['Prod.mensual'] output2=pd.DataFrame(array_de_DNI)/1000 output2.columns=['DNI'] output3=pd.DataFrame(array_de_demd) output3.columns=['Demanda'] output4=pd.DataFrame(array_de_meses_lim) output4.columns=['Prod.mensual_lim'] output_excel=pd.concat([output1,output2,output3,output4], axis=1) meses=["Ene","Feb","Mar","Abr","May","Jun","Jul","Ago","Sep","Oct","Nov","Dec"] meses_index=np.arange(0,12) fig,ax = plt.subplots() if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": meses=["Ene","Feb","Mar","Abr","May","Jun","Jul","Ago","Sep","Oct","Nov","Dec"] fig.suptitle('Producción & Demanda energía de proceso', fontsize=14, fontweight='bold') ax.set_ylabel('Producción y Demanda en kWh',color = 'black') ax.bar(meses_index, output3['Demanda'], width=0.8, color='#362510',label="Demanda") if sender =='CIMAV': ax.bar(meses_index, output1['Prod.mensual'], width=0.8, color='red',label="Disipada") else: ax.bar(meses_index, output1['Prod.mensual'], width=0.8, color='red',label="Desenfocada") ax.bar(meses_index, output4['Prod.mensual_lim'], width=0.8, color='blue',label="Producción solar") plt.legend(loc=9, bbox_to_anchor=(0.5, -0.05), ncol=3) ax2 = ax.twinx() ax2 .plot([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], output2['DNI'],'-',color = '#CA6A16',label="Radiación solar",linewidth=2.0) ax2.set_ylabel('Radiacion solar [kWh/m2]',color = '#CA6A16') ax.set_xticks(meses_index+.4) # set the x ticks to be at the middle of each bar since the width of each bar is 0.8 ax.set_xticklabels(meses) #replace the name of the x ticks with your Groups name plt.legend(loc='upper right', borderaxespad=0.,frameon=True) if lang=="eng": meses=["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"] fig.suptitle('Production & Demand process energy', fontsize=14, fontweight='bold') ax.set_ylabel('Production & Demand kWh',color = 'black') ax.bar(meses_index, output3['Demanda'], width=0.8, color='#362510',label="Demand") ax.bar(meses_index, output1['Prod.mensual'], width=0.8, color='red',label="Defocused") ax.bar(meses_index, output4['Prod.mensual_lim'], width=0.8, color='blue',label="Solar production") plt.legend(loc=9, bbox_to_anchor=(0.5, -0.05), ncol=3) ax2 = ax.twinx() ax2 .plot([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], output2['DNI'],'-',color = '#CA6A16',label="Solar Radiation",linewidth=2.0) ax2.set_ylabel('Solar Radiation [kWh/m2]',color = '#CA6A16') ax.set_xticks(meses_index+.4) # set the x ticks to be at the middle of each bar since the width of each bar is 0.8 ax.set_xticklabels(meses) #replace the name of the x ticks with your Groups name plt.legend(loc='upper right', borderaxespad=0.,frameon=True) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'prodMonths.png', format='png', dpi=imageQlty) if origin==0: plt.show() return output_excel def arrays_Savings_Month(Q_prod_lim,Demand,Fuel_price,Boiler_eff,**kwargs): #Para resumen mensual Ene_sav_lim=np.zeros(8760) Feb_sav_lim=np.zeros(8760) Mar_sav_lim=np.zeros(8760) Abr_sav_lim=np.zeros(8760) May_sav_lim=np.zeros(8760) Jun_sav_lim=np.zeros(8760) Jul_sav_lim=np.zeros(8760) Ago_sav_lim=np.zeros(8760) Sep_sav_lim=np.zeros(8760) Oct_sav_lim=np.zeros(8760) Nov_sav_lim=np.zeros(8760) Dic_sav_lim=np.zeros(8760) Ene_demd=np.zeros(8760) Feb_demd=np.zeros(8760) Mar_demd=np.zeros(8760) Abr_demd=np.zeros(8760) May_demd=np.zeros(8760) Jun_demd=np.zeros(8760) Jul_demd=np.zeros(8760) Ago_demd=np.zeros(8760) Sep_demd=np.zeros(8760) Oct_demd=np.zeros(8760) Nov_demd=np.zeros(8760) Dic_demd=np.zeros(8760) Ene_frac=np.zeros(8760) Feb_frac=np.zeros(8760) Mar_frac=np.zeros(8760) Abr_frac=np.zeros(8760) May_frac=np.zeros(8760) Jun_frac=np.zeros(8760) Jul_frac=np.zeros(8760) Ago_frac=np.zeros(8760) Sep_frac=np.zeros(8760) Oct_frac=np.zeros(8760) Nov_frac=np.zeros(8760) Dic_frac=np.zeros(8760) for i in range(0,8759): if (i<=744-1): Ene_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Ene_demd[i]=Fuel_price*Demand[i] if Ene_demd[i] == 0: Ene_frac[i] = 0 else: Ene_frac[i]=Ene_sav_lim[i]/Ene_demd[i] if (i>744-1) and (i<=1416-1): Feb_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Feb_demd[i]=Fuel_price*Demand[i] if Feb_demd[i] == 0: Feb_frac[i] = 0 else: Feb_frac[i]=Feb_sav_lim[i]/Feb_demd[i] if (i>1416-1) and (i<=2160-1): Mar_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Mar_demd[i]=Fuel_price*Demand[i] if Mar_demd[i] == 0: Mar_frac[i] = 0 else: Mar_frac[i]=Mar_sav_lim[i]/Mar_demd[i] if (i>2160-1) and (i<=2880-1): Abr_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Abr_demd[i]=Fuel_price*Demand[i] if Abr_demd[i] == 0: Abr_frac[i] = 0 else: Abr_frac[i]=Abr_sav_lim[i]/Abr_demd[i] if (i>2880-1) and (i<=3624-1): May_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff May_demd[i]=Fuel_price*Demand[i] if May_demd[i] == 0: May_frac[i] = 0 else: May_frac[i]=May_sav_lim[i]/May_demd[i] if (i>3624-1) and (i<=4344-1): Jun_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Jun_demd[i]=Fuel_price*Demand[i] if Jun_demd[i] == 0: Jun_frac[i] = 0 else: Jun_frac[i]=Jun_sav_lim[i]/Jun_demd[i] if (i>4344-1) and (i<=5088-1): Jul_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Jul_demd[i]=Fuel_price*Demand[i] if Jul_demd[i] == 0: Jul_frac[i] = 0 else: Jul_frac[i]=Jul_sav_lim[i]/Jul_demd[i] if (i>5088-1) and (i<=5832-1): Ago_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Ago_demd[i]=Fuel_price*Demand[i] if Ago_demd[i] == 0: Ago_frac[i] = 0 else: Ago_frac[i]=Ago_sav_lim[i]/Ago_demd[i] if (i>5832-1) and (i<=6552-1): Sep_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Sep_demd[i]=Fuel_price*Demand[i] if Sep_demd[i] == 0: Sep_frac[i] = 0 else: Sep_frac[i]=Sep_sav_lim[i]/Sep_demd[i] if (i>6552-1) and (i<=7296-1): Oct_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Oct_demd[i]=Fuel_price*Demand[i] if Oct_demd[i] == 0: Oct_frac[i] = 0 else: Oct_frac[i]=Oct_sav_lim[i]/Oct_demd[i] if (i>7296-1) and (i<=8016-1): Nov_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Nov_demd[i]=Fuel_price*Demand[i] if Nov_demd[i] == 0: Nov_frac[i] = 0 else: Nov_frac[i]=Nov_sav_lim[i]/Nov_demd[i] if (i>8016-1): Dic_sav_lim[i]=Fuel_price*Q_prod_lim[i]/Boiler_eff Dic_demd[i]=Fuel_price*Demand[i] if Dic_demd[i] == 0: Dic_frac[i] = 0 else: Dic_frac[i]=Dic_sav_lim[i]/Dic_demd[i] array_de_meses_lim=[np.sum(Ene_sav_lim),np.sum(Feb_sav_lim),np.sum(Mar_sav_lim),np.sum(Abr_sav_lim),np.sum(May_sav_lim),np.sum(Jun_sav_lim),np.sum(Jul_sav_lim),np.sum(Ago_sav_lim),np.sum(Sep_sav_lim),np.sum(Oct_sav_lim),np.sum(Nov_sav_lim),np.sum(Dic_sav_lim)] array_de_demd=[np.sum(Ene_demd),np.sum(Feb_demd),np.sum(Mar_demd),np.sum(Abr_demd),np.sum(May_demd),np.sum(Jun_demd),np.sum(Jul_demd),np.sum(Ago_demd),np.sum(Sep_demd),np.sum(Oct_demd),np.sum(Nov_demd),np.sum(Dic_demd)] array_de_fraction=[np.sum(Ene_frac),np.sum(Feb_frac),np.sum(Mar_frac),np.sum(Abr_frac),np.sum(May_frac),np.sum(Jun_frac),np.sum(Jul_frac),np.sum(Ago_frac),np.sum(Sep_frac),np.sum(Oct_frac),np.sum(Nov_frac),np.sum(Dic_frac)] return array_de_meses_lim,array_de_demd,array_de_fraction def savingsMonths(sender,origin,Q_prod_lim,Demand,Fuel_price,Boiler_eff,lang,plotPath,imageQlty,**kwargs): array_de_meses_lim,array_de_demd,array_de_fraction=arrays_Savings_Month(Q_prod_lim,Demand,Fuel_price,Boiler_eff) output2=pd.DataFrame(array_de_fraction) output2.columns=['Fraccion'] output3=pd.DataFrame(array_de_demd) output3.columns=['Demanda'] output4=pd.DataFrame(array_de_meses_lim) output4.columns=['Ahorro mensual'] output_excel=pd.concat([output3,output4], axis=1) meses=["Ene","Feb","Mar","Abr","May","Jun","Jul","Ago","Sep","Oct","Nov","Dic"] meses_index=np.arange(0,12) fig = plt.figure(figsize=(10, 5)) # fig = plt.figure() # fig,ax = plt.subplots() ax = fig.add_subplot(111) if origin==-2 or origin == -3: fig.patch.set_alpha(0) if lang=="spa": meses=["Ene","Feb","Mar","Abr","May","Jun","Jul","Ago","Sep","Oct","Nov","Dec"] fig.suptitle('Ahorro solar', fontsize=14, fontweight='bold') if origin == -3: ax.set_ylabel('Ahorro solar / Factura actual $') else: ax.set_ylabel('Ahorro solar / Factura actual €') ax.bar(meses_index, output3['Demanda'], width=0.8, color='#362510',label="Factura mensual") ax.bar(meses_index, output4['Ahorro mensual'], width=0.8, color='blue',label="Ahorro solar") ax.set_xticks(meses_index) ax.set_xticklabels(meses) #replace the name of the x ticks with your Groups name L=plt.legend(loc=9, bbox_to_anchor=(0.5, -0.05), ncol=3) if lang=="eng": meses=["Jan","Feb","Mar","Abr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"] fig.suptitle('Solar savings', fontsize=14, fontweight='bold') if origin == -3: ax.set_ylabel('Solar savings / Monthly energy cost $') else: ax.set_ylabel('Solar savings / Monthly energy cost €') ax.bar(meses_index, output3['Demanda'], width=0.8, color='#362510',label="Monthly energy cost") ax.bar(meses_index, output4['Ahorro mensual'], width=0.8, color='blue',label="Solar savings") ax.set_xticks(meses_index) ax.set_xticklabels(meses) #replace the name of the x ticks with your Groups name L=plt.legend(loc=9, bbox_to_anchor=(0.5, -0.05), ncol=3) if origin==-2 or origin == -3 or (origin==1 and sender=='SHIPcal'): f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'savMonths.png', format='png', dpi=imageQlty) if origin==0: plt.show() return output_excel def SL_S_PDR_Plot(sender,origin,step_sim,steps_sim,SD_min_energy,SD_max_energy,Q_prod,Q_prod_steam,SD_energy,T_in_K,T_out_K,T_SD_K,plotPath,imageQlty,**kwargs): fig = plt.figure() if origin==-2 or origin == -3: fig.patch.set_alpha(0) fig.suptitle('Direct steam Generation RECIRCULATION', fontsize=14, fontweight='bold') ax1 = fig.add_subplot(111) ax1 .plot(step_sim, Q_prod,'m:',label="Producción solar") ax1 .plot(step_sim, Q_prod_steam,'g:',label="Producción vapor") ax1 .plot(step_sim, SD_energy,color='orange',label="Energia en SD") ax1 .axhline(y=SD_min_energy,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1 .axhline(y=SD_max_energy,xmin=0,xmax=steps_sim,c="black",linewidth=0.5,zorder=0) ax1.set_ylim([0,max(SD_max_energy,max(Q_prod_steam))*1.1]) ax1.set_xlabel('Simulación (hora del año)') ax1.set_ylabel('Energía - kWh') plt.legend(bbox_to_anchor=(1.15, .5), loc=2, borderaxespad=0.) ax2 = ax1.twinx() ax2 .plot(step_sim, T_in_K-273,'-',color = '#1F85DE',label="Temp_in Solar") ax2 .plot(step_sim, T_out_K-273,'-',color = 'red',label="Temp_out Solar") ax2 .plot(step_sim, T_SD_K-273,':',color = 'orange',label="Temp_alm") ax2.set_ylabel('Temp - C') ax2.set_ylim([0,(np.max([np.max(T_SD_K),np.max(T_out_K)])-273)*1.2]) plt.legend(bbox_to_anchor=(1.15, 1), loc=2, borderaxespad=0.) # output1=pd.DataFrame(flow_rate_kgs) # output1.columns=['Flow_rate'] # output2=pd.DataFrame(T_in_K) # output2.columns=['T_in_K'] # output3=pd.DataFrame(T_out_K) # output3.columns=['T_out_K'] # output_excel_FlowratesTemps=pd.concat([output1,output2,output3], axis=1) if origin==-2 or origin == -3: f = io.BytesIO() # Python 3 plt.savefig(f, format="png", facecolor=(0.95,0.95,0.95)) plt.clf() image_base64 = base64.b64encode(f.getvalue()).decode('utf-8').replace('\n', '') f.close() return image_base64 if origin==-1: fig.savefig(str(plotPath)+'flowrates.png', format='png', dpi=imageQlty)

52.355581

549

0.625008

13,641

90,994

4.021406

0.04941

0.014128

0.016844

0.009224

0.875984

0.843973

0.825124

0.794407

0.779824

0.76267

0

0.066527

0.197002

90,994

1,737

550

52.385723

0.68413

0.058301

0

0.627424

0

0.132318

0.002384

0

1

0.017313

false

0

0.006233

0

0.043629

0

null

0

1

0

null

0

6

35820aee046bab9529ab1971f2993f8434856f87

113

py

Python

smff/analysis/__init__.py

ismael2395/Research-NoiseBias

1511b65d23f03bbe7d55b114984740ab9d75110f

[ "MIT" ]

1

2017-11-20T22:25:12.000Z

smff/analysis/__init__.py

ismael2395/ShapeMeasurementFisherFormalism

1511b65d23f03bbe7d55b114984740ab9d75110f

[ "MIT" ]

null

smff/analysis/__init__.py

ismael2395/ShapeMeasurementFisherFormalism

1511b65d23f03bbe7d55b114984740ab9d75110f

[ "MIT" ]

1

2016-08-11T23:33:09.000Z

from . import fisher from . import gparameters from . import images from . import models from . import readfits

16.142857

25

0.769912

15

113

5.8

0.466667

0.574713

0

0.185841

113

6

26

18.833333

0.945652

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

35879403098135051ed74d76f0d62005b32eafb5

11,705

py

Python

pesummary/tests/summaryplots_test.py

pesummary/pesummary

99e3c450ecbcaf5a23564d329bdf6e0080f6f2a8

[ "MIT" ]

1

2021-08-03T05:58:20.000Z

pesummary/tests/summaryplots_test.py

pesummary/pesummary

99e3c450ecbcaf5a23564d329bdf6e0080f6f2a8

[ "MIT" ]

1

2020-06-13T13:29:35.000Z

2020-06-15T12:45:04.000Z

pesummary/tests/summaryplots_test.py

pesummary/pesummary

99e3c450ecbcaf5a23564d329bdf6e0080f6f2a8

[ "MIT" ]

3

2021-07-08T08:31:28.000Z

2022-03-31T14:08:58.000Z

# Licensed under an MIT style license -- see LICENSE.md import os import shutil from glob import glob from pesummary.core.command_line import command_line from pesummary.gw.command_line import insert_gwspecific_option_group from pesummary.gw.inputs import GWInput from pesummary.cli.summaryplots import _GWPlotGeneration as GWPlotGeneration from pesummary.gw.file.meta_file import GWMetaFile from pesummary.cli.summarypages import _GWWebpageGeneration as GWWebpageGeneration from .base import make_result_file, get_list_of_plots, data_dir import pytest __author__ = ["Charlie Hoy <charlie.hoy@ligo.org>"] class TestPlotGeneration(object): def setup(self): directories = ["./.outdir_bilby", "./.outdir_lalinference", "./.outdir_comparison", "./.outdir_add_to_existing2", ".outdir_comparison_no_comparison", ".outdir_add_to_existing_no_comparison"] for i in directories: if os.path.isdir(i): shutil.rmtree(i) os.makedirs(i) def test_plot_generation_for_bilby_structure(self): with open("./.outdir_bilby/psd.dat", "w") as f: f.writelines(["1.00 3.44\n"]) f.writelines(["100.00 4.00\n"]) f.writelines(["1000.00 5.00\n"]) f.writelines(["2000.00 6.00\n"]) with open("./.outdir_bilby/calibration.dat", "w") as f: f.writelines(["1.0 2.0 3.0 4.0 5.0 6.0 7.0\n"]) f.writelines(["2000.0 2.0 3.0 4.0 5.0 6.0 7.0"]) parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", bilby=True, outdir="./.outdir_bilby/", n_samples=10 ) os.rename("./.outdir_bilby/test.h5", "./.outdir_bilby/bilby_example.h5") default_arguments = [ "--approximant", "IMRPhenomPv2", "--webdir", "./.outdir_bilby", "--samples", "./.outdir_bilby/bilby_example.h5", "--config", data_dir + "/config_bilby.ini", "--psd", "./.outdir_bilby/psd.dat", "--calibration", "./.outdir_bilby/calibration.dat", "--labels", "H10", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_bilby/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", outdir=".outdir_bilby", psd=True, calibration=False ) for i, j in zip(expected_plots, plots): print(i, j) assert all(i == j for i,j in zip(sorted(expected_plots), sorted(plots))) def test_plot_generation_for_lalinference_structure(self): parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", lalinference=True, outdir="./.outdir_lalinference/", n_samples=10 ) os.rename( "./.outdir_lalinference/test.hdf5", "./.outdir_lalinference/lalinference_example.h5" ) default_arguments = [ "--approximant", "IMRPhenomPv2", "--webdir", "./.outdir_lalinference", "--samples", "./.outdir_lalinference/lalinference_example.h5", "--config", data_dir + "/config_lalinference.ini", "--labels", "H10", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_lalinference/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", outdir=".outdir_lalinference" ) assert all(i == j for i,j in zip(sorted(expected_plots), sorted(plots))) def test_plot_generation_for_comparison(self): parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", lalinference=True, outdir="./.outdir_comparison/", n_samples=10 ) os.rename( "./.outdir_comparison/test.hdf5", "./.outdir_comparison/lalinference_example.h5" ) make_result_file( gw=True, extension="hdf5", bilby=True, outdir="./.outdir_comparison/", n_samples=10 ) os.rename( "./.outdir_comparison/test.h5", "./.outdir_comparison/bilby_example.h5" ) default_arguments = [ "--approximant", "IMRPhenomPv2", "IMRPhenomP", "--webdir", "./.outdir_comparison", "--samples", "./.outdir_comparison/bilby_example.h5", "./.outdir_comparison/lalinference_example.h5", "--labels", "H10", "H11", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_comparison/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", number=2, outdir=".outdir_comparison" ) for i,j in zip(sorted(plots), sorted(expected_plots)): print(i, j) assert all(i == j for i,j in zip(sorted(plots), sorted(expected_plots))) def test_plot_generation_for_add_to_existing(self): parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", lalinference=True, outdir="./.outdir_add_to_existing2/", n_samples=10 ) os.rename( "./.outdir_add_to_existing2/test.hdf5", "./.outdir_add_to_existing2/lalinference_example.h5" ) make_result_file( gw=True, extension="hdf5", bilby=True, outdir="./.outdir_add_to_existing2/", n_samples=10 ) os.rename( "./.outdir_add_to_existing2/test.h5", "./.outdir_add_to_existing2/bilby_example.h5" ) default_arguments = [ "--approximant", "IMRPhenomPv2", "--webdir", "./.outdir_add_to_existing2", "--samples", "./.outdir_add_to_existing2/bilby_example.h5", "--labels", "H10", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() webpage = GWWebpageGeneration(inputs) webpage.generate_webpages() meta_file = GWMetaFile(inputs) parser = command_line() insert_gwspecific_option_group(parser) default_arguments = [ "--approximant", "IMRPhenomP", "--existing_webdir", "./.outdir_add_to_existing2", "--samples", "./.outdir_add_to_existing2/lalinference_example.h5", "--labels", "H11", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_add_to_existing2/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", number=2, outdir=".outdir_add_to_existing2" ) assert all(i == j for i, j in zip(sorted(plots), sorted(expected_plots))) def test_plot_generation_for_multiple_without_comparison(self): parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", lalinference=True, outdir="./.outdir_comparison_no_comparison/", n_samples=10 ) os.rename( "./.outdir_comparison_no_comparison/test.hdf5", "./.outdir_comparison_no_comparison/lalinference_example.h5" ) make_result_file( gw=True, extension="hdf5", bilby=True, outdir="./.outdir_comparison_no_comparison/", n_samples=10 ) os.rename( "./.outdir_comparison_no_comparison/test.h5", "./.outdir_comparison_no_comparison/bilby_example.h5" ) default_arguments = [ "--approximant", "IMRPhenomPv2", "IMRPhenomP", "--webdir", "./.outdir_comparison_no_comparison", "--samples", "./.outdir_comparison_no_comparison/bilby_example.h5", "./.outdir_comparison_no_comparison/lalinference_example.h5", "--labels", "H10", "H11", "--no_ligo_skymap", "--disable_comparison", "--disable_expert" ] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_comparison/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", number=2, outdir=".outdir_comparison_no_comparison", comparison=False ) for i,j in zip(sorted(plots), sorted(expected_plots)): print(i, j) assert all(i == j for i,j in zip(sorted(plots), sorted(expected_plots))) def test_plot_generation_for_add_to_existing_without_comparison(self): parser = command_line() insert_gwspecific_option_group(parser) make_result_file( gw=True, extension="hdf5", lalinference=True, outdir="./.outdir_add_to_existing_no_comparison/", n_samples=10 ) os.rename( "./.outdir_add_to_existing_no_comparison/test.hdf5", "./.outdir_add_to_existing_no_comparison/lalinference_example.h5" ) make_result_file( gw=True, extension="hdf5", bilby=True, outdir="./.outdir_add_to_existing_no_comparison/", n_samples=10 ) os.rename( "./.outdir_add_to_existing_no_comparison/test.h5", "./.outdir_add_to_existing_no_comparison/bilby_example.h5" ) default_arguments = [ "--approximant", "IMRPhenomPv2", "--webdir", "./.outdir_add_to_existing_no_comparison", "--samples", "./.outdir_add_to_existing_no_comparison/bilby_example.h5", "--labels", "H10", "--no_ligo_skymap", "--disable_expert"] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() webpage = GWWebpageGeneration(inputs) webpage.generate_webpages() meta_file = GWMetaFile(inputs) parser = command_line() insert_gwspecific_option_group(parser) default_arguments = [ "--approximant", "IMRPhenomP", "--existing_webdir", "./.outdir_add_to_existing_no_comparison", "--samples", "./.outdir_add_to_existing_no_comparison/lalinference_example.h5", "--labels", "H11", "--no_ligo_skymap", "--disable_comparison", "--disable_expert" ] opts = parser.parse_args(default_arguments) inputs = GWInput(opts) webpage = GWPlotGeneration(inputs) webpage.generate_plots() plots = sorted(glob("./.outdir_add_to_existing_no_comparison/plots/*.png")) expected_plots = get_list_of_plots( gw=True, label="H1", number=2, outdir=".outdir_add_to_existing_no_comparison", comparison=False ) assert all(i == j for i, j in zip(sorted(plots), sorted(expected_plots)))

43.191882

91

0.614267

1,274

11,705

5.324961

0.110675

0.020637

0.042158

0.038325

0.828567

0.802919

0.774175

0.746167

0.737323

0.712117

0

0.019768

0.256642

11,705

270

92

43.351852

0.759913

0.004528

0

0.515625

0

0.007813

0.29897

0.202403

0

0.023438

1

0.027344

false

0

0.042969

0

0.074219

0.011719

0

null

0

1

0

null

0

6

35bb38862ef69c170a0d860cade779b1208e450c

146

py

Python

OpenGLCffi/GLX/EXT/SGIX/swap_group.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/GLX/EXT/SGIX/swap_group.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/GLX/EXT/SGIX/swap_group.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

from OpenGLCffi.GLX import params @params(api='glx', prms=['dpy', 'drawable', 'member']) def glXJoinSwapGroupSGIX(dpy, drawable, member): pass

20.857143

54

0.726027

18

146

5.888889

0.722222

0.207547

0.320755

0

0.109589

146

6

55

24.333333

0.815385

0

0.138889

0

1

0.25

false

0.25

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

ea2ab2739fa57d60f95b344b324fe270168f1baa

122

py

Python

emailmgr/defaults.py

RileyGibbs/django-emailmgr

82dae79aceab20ac2146103067d31b01ee51731a

[ "BSD-3-Clause" ]

6

2015-10-12T09:02:56.000Z

2022-02-25T12:55:01.000Z

emailmgr/defaults.py

Pradip369/django-emailmgr

eae29514fded1200607b93759064338e91e6d6b4

[ "BSD-3-Clause" ]

null

emailmgr/defaults.py

Pradip369/django-emailmgr

eae29514fded1200607b93759064338e91e6d6b4

[ "BSD-3-Clause" ]

6

2015-09-14T20:33:49.000Z

2020-09-07T17:28:33.000Z

from django.conf import settings EMAIL_MGR_TEMPLATE_PATH = getattr(settings, "EMAIL_MGR_TEMPLATE_PATH", "emailmgr")

13.555556

82

0.795082

16

122

5.6875

0.6875

0.285714

0.351648

0.527473

0.615385

0

0.122951

122

8

83

15.25

0.850467

0

0.264957

0.196581

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

6

ea60b69d9c0ccc94194dfb00331393c46fe62c2e

30

py

Python

ditto/tickets/api/__init__.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

null

ditto/tickets/api/__init__.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

9

2015-11-10T15:17:22.000Z

2015-11-12T11:07:02.000Z

ditto/users/api/__init__.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

null

from .urls import urlpatterns

15

29

0.833333

4

30

6.25

1

0

0.133333

30

1

30

0.961538

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ea6c92723996192c40d1ed3ba531dc76134f0dfd

79

py

Python

toir/formats/mapdata/__init__.py

FistingUranus/innocence-r

786e1fca75155027e5875363f0b17e7c3cdefced

[ "MIT" ]

2

2021-06-26T16:44:58.000Z

2021-09-09T22:32:13.000Z

toir/formats/mapdata/__init__.py

FistingUranus/innocence-r

786e1fca75155027e5875363f0b17e7c3cdefced

[ "MIT" ]

4

2021-08-29T18:12:17.000Z

2022-03-28T08:54:29.000Z

toir/formats/mapdata/__init__.py

FistingUranus/innocence-r

786e1fca75155027e5875363f0b17e7c3cdefced

[ "MIT" ]

3

2021-07-20T01:00:19.000Z

2021-09-09T22:32:14.000Z

from .extract import extract_map_data from .recompile import recompile_map_data

39.5

41

0.886076

12

79

5.5

0.5

0.212121

0

0.088608

79

2

41

39.5

0.916667

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

576adeb519172c497782aee89c7469149a1fe2cf

6,195

py

Python

Source Code/playlist_downloader.py

moiSentineL/Youtube-Download-Tools

27e43b5cdd6e7ea87125144e7f8e8c05abdec1ec

[ "Apache-2.0" ]

1

2021-04-02T07:44:57.000Z

Source Code/playlist_downloader.py

moiSentineL/Youtube-Download-Tools

27e43b5cdd6e7ea87125144e7f8e8c05abdec1ec

[ "Apache-2.0" ]

null

Source Code/playlist_downloader.py

moiSentineL/Youtube-Download-Tools

27e43b5cdd6e7ea87125144e7f8e8c05abdec1ec

[ "Apache-2.0" ]

null

_author__ = "moiSentinel" __license__ = "Apache License 2.0" __version__ = "1.0.1" __maintainer__ = "moiSentinel" __status__ = "In Progress" from pytube import * import os print("\nmoiSentineL's Youtube Bulk Video Downloader\nStable 1.0.1 / YDT 2.1.1") print("This program will download playlists from Youtube.\n") def download(): try: userinputlink = input("Enter Youtube Playlist Link:\n>> ") p= Playlist(userinputlink) choosefileformat = int(input("\nChoose File Format:\n1 for .mp4 (video).\n2 for .mp3 (audio).\n>> ")) if choosefileformat == 1: choosequality = int(input("\nChoose Video Quality:\n1 for 720p.\n2 for 480p.\n3 for 360p\n>> ")) if choosequality == 1: try: destinationinput = input("\nEnter path for the file to save (e.g. E:\Movies), press enter for default directory:\n>> ") if destinationinput == '': if not os.path.exists('downloads'): os.makedirs('downloads') currentdirectory = os.getcwd() destination = currentdirectory +'\downloads' else: destination = destinationinput print ('Playlist found.\nName: ', p.title) proceed = input('Proceed? (y/n)\n>> ').lower() if proceed == 'y': for video in p.videos: filesize = format(int(video.filesize)/1000000, ".2f") + " MB" video.streams.filter(res='720p').first().download(destination) print(video.title + " has been successfully downloaded with the size of " , filesize) else: pass except Exception as e: print('Something went wrong\n') print(e.args) elif choosequality == 2: try: destinationinput = input("\nEnter path for the file to save (e.g. E:\Movies), press enter for default directory:\n>> ") if destinationinput == '': if not os.path.exists('downloads'): os.makedirs('downloads') currentdirectory = os.getcwd() destination = currentdirectory +'\downloads' else: destination = destinationinput print ('Playlist found.\nName: ', p.title) proceed = input('Proceed? (y/n)\n>> ').lower() if proceed == 'y': for video in p.videos: filesize = format(int(video.filesize)/1000000, ".2f") + " MB" video.streams.filter(res='480p').first().download(destination) print(video.title + " has been successfully downloaded with the size of " , filesize) else: pass except Exception as e: print('Something went wrong\n') print(e.args) else: try: destinationinput = input("\nEnter path for the file to save (e.g. E:\Movies), press enter for default directory:\n>> ") if destinationinput == '': if not os.path.exists('downloads'): os.makedirs('downloads') currentdirectory = os.getcwd() destination = currentdirectory +'\downloads' else: destination = destinationinput print ('Playlist found.\nName: ', p.title) proceed = input('Proceed? (y/n)\n>> ').lower() if proceed == 'y': for video in p.videos: filesize = format(int(video.filesize)/1000000, ".2f") + " MB" video.streams.filter(res='480p').first().download(destination) print(video.title + " has been successfully downloaded with the size of " , filesize) else: pass except Exception as e: print('Something went wrong\n') print(e.args) else: try: destinationinput = input("\nEnter path for the file to save (e.g. E:\Movies), press enter for default directory:\n>> ") if destinationinput == '': if not os.path.exists('downloads'): os.makedirs('downloads') currentdirectory = os.getcwd() destination = currentdirectory +'\downloads' else: destination = destinationinput print ('Playlist found.\nName: ', p.title) proceed = input('Proceed? (y/n)\n>> ').lower() if proceed == 'y': for video in p.videos: videos = video.streams.filter(only_audio=True).first() filesize = format(int(videos.filesize)/1000000, ".2f") + " MB" out_file = videos.download(output_path=destination) base, ext = os.path.splitext(out_file) new_file = base + '.mp3' os.rename(out_file, new_file) print(videos.title + " has been successfully downloaded with the size of " , filesize) except Exception as e: print('Something went wrong\n') print(e.args) print('\nTask Completed!') except Exception as e: print('Something went wrong\n') print(e.args) download() k = input('Press <Enter> key to exit.')

48.398438

140

0.465214

557

6,195

5.127469

0.219031

0.022409

0.029762

0.031513

0.739496

0

0.020519

0.433575

6,195

127

141

48.779528

0.793388

0

0.75

0

0.053571

0.229311

0

1

0.008929

false

0.026786

0.017857

0

0.026786

0.1875

0

null

0

1

0

1

0

null

0

6

57858020cbd5000e8cd268ae1a2abc15fd688c0c

24

py

Python

catbars/__init__.py

ConstantinLenoir/catbars

de03ca9fdca0b8d0fc24929537639a55eff3c711

[ "MIT" ]

1

2020-03-25T20:23:37.000Z

catbars/__init__.py

ConstantinLenoir/catbars

de03ca9fdca0b8d0fc24929537639a55eff3c711

[ "MIT" ]

null

catbars/__init__.py

ConstantinLenoir/catbars

de03ca9fdca0b8d0fc24929537639a55eff3c711

[ "MIT" ]

null

from .bars import Bars

8

22

0.75

4

24

4.5

0.75

0

0.208333

24

2

23

12

0.947368

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

17e4a840e32dccad6d96ea2c54579ae0d30241a2

51

py

Python

tests/unit_tests/rf_client_test_resources/primary_dependencies/secondary_dependencies/tertiary_dependencies/Lib2.py

adiroiban/robotframework-remoterunner

2815672823872c6e5e014131bc0e7f622e9a986e

[ "MIT" ]

null

tests/unit_tests/rf_client_test_resources/primary_dependencies/secondary_dependencies/tertiary_dependencies/Lib2.py

adiroiban/robotframework-remoterunner

2815672823872c6e5e014131bc0e7f622e9a986e

[ "MIT" ]

null

tests/unit_tests/rf_client_test_resources/primary_dependencies/secondary_dependencies/tertiary_dependencies/Lib2.py

adiroiban/robotframework-remoterunner

2815672823872c6e5e014131bc0e7f622e9a986e

[ "MIT" ]

null

def Keyword_34543534(): print('Keyword 1')

12.75

24

0.627451

6

51

5.166667

0.833333

0

0.230769

0.235294

51

4

25

12.75

0.564103

0

0.191489

0

1

0.5

true

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

aa0884ebce4cd0ed3594a121f8cb2fa7003e4dbc

13,096

py

Python

register/tests/test_translations.py

SmartElect/SmartElect

d6d35f2fa8f60e756ad5247f8f0a5f05830e92f8

[ "Apache-2.0" ]

23

2015-10-28T14:08:23.000Z

2021-09-11T21:38:41.000Z

register/tests/test_translations.py

SmartElect/SmartElect

d6d35f2fa8f60e756ad5247f8f0a5f05830e92f8

[ "Apache-2.0" ]

4

2019-12-05T20:36:10.000Z

2020-06-05T18:41:54.000Z

register/tests/test_translations.py

SmartElect/SmartElect

d6d35f2fa8f60e756ad5247f8f0a5f05830e92f8

[ "Apache-2.0" ]

11

2015-10-28T15:49:56.000Z

2021-09-14T14:18:36.000Z

# -*- coding: utf-8 -*- import datetime from unittest.mock import patch from django.conf import settings from django.test.utils import override_settings from civil_registry.tests.factories import CitizenFactory from libya_elections import constants from libya_elections.utils import get_random_number_string from libya_elections.phone_numbers import get_random_phone_number from polling_reports.models import StaffPhone from register.tests.factories import RegistrationFactory, RegistrationCenterFactory, \ SMSFactory from voting.tests.factories import RegistrationPeriodFactory from .. import utils from ..tests.base import LibyaRapidTest, TranslationTest, FUTURE_DAY, PAST_DAY @override_settings(OUTGOING_MESSAGE_LANGUAGE='ar', LANGUAGE_CODE='en') @patch.object(utils, "tool_1_enabled") class ResponseTest(TranslationTest, LibyaRapidTest): # Test response messages (Arabic) def setUp(self): self.number = "919-999-9999" self.center = RegistrationCenterFactory() self.conn = self.create_connection(data={'identity': self.number}) self.citizen = CitizenFactory() self.good_nid = self.citizen.national_id self.bad_nid = get_random_number_string(length=constants.NID_LENGTH) self.short_nid = get_random_number_string(length=constants.NID_LENGTH - 1) self.good_center_id = self.center.center_id self.bad_center_id = get_random_number_string(length=constants.CENTER_ID_LENGTH) self.long_center_id = get_random_number_string(length=constants.CENTER_ID_LENGTH + 1) self.fields = {'to_addr': settings.REGISTRATION_SHORT_CODE} RegistrationPeriodFactory(start_time=PAST_DAY, end_time=FUTURE_DAY) def test_garbage(self, registration_open): self.receive("PING", self.conn, fields=self.fields) expected = self.translate(constants.MESSAGE_INCORRECT) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_garbage_enhanced(self, registration_open): for i in range(1, 5): # last iteration should get an enhanced message self.receive("PING", self.conn, fields=self.fields) expected = self.translate(constants.MESSAGE_INCORRECT, enhanced=True) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_wrong_length_nid(self, registration_open): msg = "{nid}#{center}".format(nid=self.short_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_NID_WRONG_LENGTH) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_wrong_length_nid_enhanced(self, registration_open): msg = "{nid}#{center}".format(nid=self.short_nid, center=self.good_center_id) for i in range(1, 5): # last iteration should get an enhanced message self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_NID_WRONG_LENGTH, enhanced=True) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_wrong_length_center_id(self, registration_open): msg = "{nid}#{center}".format(nid=self.good_nid, center=self.long_center_id) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_CENTER_ID_WRONG_LENGTH) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_wrong_length_center_id_enhanced(self, registration_open): msg = "{nid}#{center}".format(nid=self.good_nid, center=self.long_center_id) for i in range(1, 5): # last iteration should get an enhanced message self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_CENTER_ID_WRONG_LENGTH, enhanced=True) self.assertEqual(self.get_last_response_message(), expected) def test_wrong_length_nid_query(self, registration_open): msg = "{nid}".format(nid=self.short_nid) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.VOTER_QUERY_NID_WRONG_LENGTH) self.assertEqual(self.get_last_response_message(), expected) def test_citizen_under_18(self, registration_open): self.citizen.birth_date = datetime.datetime.today() self.citizen.save() msg = "{nid}#{center}".format(nid=self.good_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_NID_INVALID) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_center_does_not_exist(self, registration_open): msg = "{nid}#{center}".format(nid=self.good_nid, center=self.bad_center_id) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_CENTER_ID_INVALID) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_nid_does_not_exist(self, registration_open): msg = "{nid}#{center}".format(nid=self.bad_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) expected = self.translate(constants.RESPONSE_NID_INVALID) # arabic self.assertEqual(self.get_last_response_message(), expected) @override_settings(MAX_REGISTRATIONS_PER_PHONE=5) def test_good_registration(self, registration_open): msg = "{nid}#{center}".format(nid=self.good_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) context = {'person': str(self.citizen), 'centre': self.center.name, 'code': self.center.center_id} expected = self.translate(constants.MESSAGE_1, context=context) # arabic self.assertEqual(self.get_last_response_message(), expected) @override_settings(MAX_REGISTRATIONS_PER_PHONE=5) def test_good_registration_enhanced(self, registration_open): msg = "{nid}#{center}".format(nid=self.good_nid, center=self.good_center_id) for i in range(1, 5): # last iteration should get an enhanced message self.receive(msg, self.conn, fields=self.fields) context = {'person': str(self.citizen), 'centre': self.center.name, 'code': self.center.center_id} expected = self.translate(constants.MESSAGE_1, context=context, enhanced=True) # arabic self.assertEqual(self.get_last_response_code(), constants.MESSAGE_1) self.assertEqual(self.get_last_response_message(), expected) def test_good_update(self, registration_open): new_center = RegistrationCenterFactory() msg = "{nid}#{center}".format(nid=self.good_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) # registers msg = "{nid}#{center}".format(nid=self.good_nid, center=new_center.center_id) self.receive(msg, self.conn, fields=self.fields) # updates context = {'person': str(self.citizen), 'centre': new_center.name, 'code': new_center.center_id} # 1st update - message 1 expected = self.translate(constants.MESSAGE_1, context=context) # arabic self.assertEqual(self.get_last_response_message(), expected) # 2nd update - message 4 msg = "{nid}#{center}".format(nid=self.good_nid, center=self.good_center_id) self.receive(msg, self.conn, fields=self.fields) # updates again context = {'person': str(self.citizen), 'centre': new_center.name, 'code': self.good_center_id} expected = self.translate(constants.MESSAGE_4, context=context) # arabic # 3rd and final update - message 5 msg = "{nid}#{center}".format(nid=self.good_nid, center=new_center.center_id) self.receive(msg, self.conn, fields=self.fields) # updates context = {'person': str(self.citizen), 'centre': new_center.name, 'code': new_center.center_id} expected = self.translate(constants.MESSAGE_5, context=context) # arabic def test_attempt_update_wrong_from_number(self, registration_open): # create a valid registration sms = SMSFactory(from_number=self.number, citizen=self.citizen) RegistrationFactory( citizen=self.citizen, registration_center=self.center, archive_time=None, sms=sms) # try to register at a new center with a new number new_center = RegistrationCenterFactory() new_number = '919-888-8888' msg = "{nid}#{center}".format(nid=self.good_nid, center=new_center.center_id) new_conn = self.create_connection(data={'identity': new_number}) self.receive(msg, new_conn, fields=self.fields) # message should have the existing number in it (not new_number) context = {'centre': self.center.name, 'number': self.number[-4:]} expected = self.translate(constants.MESSAGE_2, context=context) # arabic self.assertEqual(self.get_last_response_message(), expected) def test_attempt_update_wrong_from_number_same_center(self, registration_open): # create a valid registration sms = SMSFactory(from_number=self.number, citizen=self.citizen) RegistrationFactory( citizen=self.citizen, registration_center=self.center, archive_time=None, sms=sms) # try to register at same center with a new number new_number = '919-888-8888' msg = "{nid}#{center}".format(nid=self.good_nid, center=self.center.center_id) new_conn = self.create_connection(data={'identity': new_number}) self.receive(msg, new_conn, fields=self.fields) # message should have the existing number in it (not new_number) context = {'centre': self.center.name, 'number': self.number[-4:]} expected = self.translate(constants.MESSAGE_2, context=context) # arabic self.assertEqual(self.get_last_response_message(), expected) @override_settings(OUTGOING_MESSAGE_LANGUAGE='ar') @override_settings(LANGUAGE_CODE='en') class ResponseVoterQueryTest(TranslationTest, LibyaRapidTest): def setUp(self): self.number = get_random_phone_number() self.center = RegistrationCenterFactory() self.citizen = CitizenFactory() self.staffphone = StaffPhone.objects.create(phone_number=self.number, registration_center=self.center) self.conn = self.create_connection(data={'identity': self.number}) self.good_nid = self.citizen.national_id self.bad_nid = get_random_number_string(length=constants.NID_LENGTH) self.short_nid = get_random_number_string(length=constants.NID_LENGTH - 1) self.fields = {'to_addr': settings.REGISTRATION_SHORT_CODE} def test_wrong_length_nid(self): msg = "{nid}".format(nid=self.short_nid) self.receive(msg, self.conn, fields=self.fields) self.assertEqual(self.get_last_response_code(), constants.VOTER_QUERY_NID_WRONG_LENGTH) expected = self.translate(constants.VOTER_QUERY_NID_WRONG_LENGTH) # Arabic self.assertEqual(self.get_last_response_message(), expected) def test_citizen_registered(self): # citizen has been registered RegistrationFactory(citizen=self.citizen, registration_center=self.center, archive_time=None) # let's query for the registration msg = "{nid}".format(nid=self.good_nid) self.receive(msg, self.conn, fields=self.fields) self.assertEqual(self.get_last_response_code(), constants.VOTER_QUERY_REGISTERED_AT) context = {"person": str(self.citizen), "centre": self.center.name, "code": self.center.center_id} expected = self.translate(constants.VOTER_QUERY_REGISTERED_AT, context) # Arabic self.assertEqual(self.get_last_response_message(), expected) def test_citizen_not_registered(self): # let's query for the registration citizen2 = CitizenFactory() # unregistered msg = "{nid}".format(nid=citizen2.national_id) self.receive(msg, self.conn, fields=self.fields) self.assertEqual(self.get_last_response_code(), constants.VOTER_QUERY_NOT_REGISTERED) context = {'person': str(citizen2)} expected = self.translate(constants.VOTER_QUERY_NOT_REGISTERED, context) # Arabic self.assertEqual(self.get_last_response_message(), expected) def test_nlid_does_not_exist(self): msg = "{nid}".format(nid=self.bad_nid) self.receive(msg, self.conn, fields=self.fields) self.assertEqual(self.get_last_response_code(), constants.VOTER_QUERY_NOT_FOUND) expected = self.translate(constants.VOTER_QUERY_NOT_FOUND) # Arabic self.assertEqual(self.get_last_response_message(), expected)

53.453061

96

0.701665

1,628

13,096

5.405405

0.103808

0.029091

0.051818

0.06

0.810682

0.797159

0.764659

0.742614

0.736932

0.717273

0

0.006241

0.192425

13,096

244

97

53.672131

0.825832

0.066967

0

0.588832

0

0.038847

0

0.121827

1

0.106599

false

0

0.06599

0

0.182741

0

null

0

1

0

null

0

6

aa303fe9e82d5b91e080a3ff4a02dc376ead3fc4

756

py

Python

pymontecarlo/options/model/__init__.py

pymontecarlo/pymontecarlo

87050041724feb17f1ccff5794e9830c3209244e

[ "Apache-2.0" ]

5

2018-04-10T07:15:06.000Z

2021-07-01T15:40:29.000Z

pymontecarlo/options/model/__init__.py

pymontecarlo/pymontecarlo

87050041724feb17f1ccff5794e9830c3209244e

[ "Apache-2.0" ]

73

2015-09-04T09:48:29.000Z

2022-01-03T17:49:01.000Z

pymontecarlo/options/model/__init__.py

pymontecarlo/pymontecarlo

87050041724feb17f1ccff5794e9830c3209244e

[ "Apache-2.0" ]

4

2016-05-17T12:57:20.000Z

2021-01-31T10:55:24.000Z

""" Models. """ from pymontecarlo.options.model.base import * from pymontecarlo.options.model.bremsstrahlung_emission import * from pymontecarlo.options.model.direction_cosine import * from pymontecarlo.options.model.elastic_cross_section import * from pymontecarlo.options.model.energy_loss import * from pymontecarlo.options.model.fluorescence import * from pymontecarlo.options.model.inelastic_cross_section import * from pymontecarlo.options.model.ionization_cross_section import * from pymontecarlo.options.model.ionization_potential import * from pymontecarlo.options.model.mass_absorption_coefficient import * from pymontecarlo.options.model.photon_scattering_cross_section import * from pymontecarlo.options.model.random_number_generator import *

44.470588

72

0.858466

90

756

7.022222

0.311111

0.303797

0.436709

0.531646

0.699367

0.322785

0.177215

0

0.068783

756

16

73

47.25

0.897727

0.009259

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

a4bc4533b229603f4b09e164bb0cb8232bc01688

55

py

Python

involution_pytorch/__init__.py

rish-16/involution-pytorch

90766013ee1a74fc7fd7db0822a61e2c338754b1

[ "MIT" ]

1

2021-07-06T21:07:44.000Z

involution_pytorch/__init__.py

rish-16/involution-pytorch

90766013ee1a74fc7fd7db0822a61e2c338754b1

[ "MIT" ]

null

involution_pytorch/__init__.py

rish-16/involution-pytorch

90766013ee1a74fc7fd7db0822a61e2c338754b1

[ "MIT" ]

null

from involution_pytorch.involution_pytorch import Inv2d

55

0.927273

7

55

7

0.714286

0.693878

0

0.019231

0.054545

55

1

55

0.923077

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

3532ab40a1d326d0caed24b9c91a549ff872bbdd

546

py

Python

opennmt/layers/__init__.py

mfomicheva/OpenNMT-tf

a367676a16f9e77f76bc58e138e78614eb4add1e

[ "MIT" ]

4

2020-06-21T13:56:27.000Z

2021-05-07T06:03:35.000Z

opennmt/layers/__init__.py

mfomicheva/OpenNMT-tf

a367676a16f9e77f76bc58e138e78614eb4add1e

[ "MIT" ]

1

2020-06-22T23:38:33.000Z

2020-06-23T02:06:45.000Z

opennmt/layers/__init__.py

mfomicheva/OpenNMT-tf

a367676a16f9e77f76bc58e138e78614eb4add1e

[ "MIT" ]

2

2021-04-15T08:51:30.000Z

2022-03-08T07:44:32.000Z

"""Module defining reusable and model specific layers.""" from opennmt.layers.common import Dense from opennmt.layers.reducer import SumReducer from opennmt.layers.reducer import MultiplyReducer from opennmt.layers.reducer import ConcatReducer from opennmt.layers.reducer import JoinReducer from opennmt.layers.bridge import CopyBridge from opennmt.layers.bridge import ZeroBridge from opennmt.layers.bridge import DenseBridge from opennmt.layers.position import PositionEmbedder from opennmt.layers.position import SinusoidalPositionEncoder

34.125

61

0.857143

67

546

6.985075

0.358209

0.235043

0.363248

0.205128

0.574786

0

0.093407

546

15

62

36.4

0.945455

0.093407

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6