xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

e168ddd7b9e9aadd608c8c885e99f558d5137d2f

102

py

Python

hooks/actions.py

projectcalico/charm-bird

3224e887329c527f6bed2520346e66fb4e795fe8

[ "Apache-2.0" ]

null

hooks/actions.py

projectcalico/charm-bird

3224e887329c527f6bed2520346e66fb4e795fe8

[ "Apache-2.0" ]

null

hooks/actions.py

projectcalico/charm-bird

3224e887329c527f6bed2520346e66fb4e795fe8

[ "Apache-2.0" ]

1

2022-03-16T16:12:32.000Z

from charmhelpers.core import hookenv def log_start(service_name): hookenv.log('bird starting')

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py

Python

sigmoid.py

SchlachterSchmidt/mlApplications

f6ed6012ba872ea5ce57dc6ee377e045c298ee4e

[ "MIT" ]

null

sigmoid.py

SchlachterSchmidt/mlApplications

f6ed6012ba872ea5ce57dc6ee377e045c298ee4e

[ "MIT" ]

null

sigmoid.py

SchlachterSchmidt/mlApplications

f6ed6012ba872ea5ce57dc6ee377e045c298ee4e

[ "MIT" ]

null

"""Module contains sigmoid function.""" import numpy as np def sigmoid(z): """Sigmoid function.""" g = 1 / (1 + np.exp(-z)) return g

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py

Python

test-data/TESET.py

jdunleav/prm-migrator

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[ "Apache-2.0" ]

null

test-data/TESET.py

jdunleav/prm-migrator

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[ "Apache-2.0" ]

null

test-data/TESET.py

jdunleav/prm-migrator

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[ "Apache-2.0" ]

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2021-04-11T07:29:08.000Z

OrderedDict([('@classCode', 'COMPOSITION'), ('@moodCode', 'EVN'), ('id', OrderedDict([('@root', 'CF5EB3C7-4D1C-11E3-A2DD-010000000161')])), ('code', OrderedDict([('@code', '37351000000107'), ('@codeSystem', '2.16.840.1.113883.2.1.3.2.4.15'), ('@displayName', 'Administration Note')])), ('statusCode', OrderedDict([('@code', 'COMPLETE')])), ('effectiveTime', OrderedDict([('center', OrderedDict([('@nullFlavor', 'NI')]))])), ('availabilityTime', OrderedDict([('@nullFlavor', 'UNK')])), ('author', OrderedDict([('@typeCode', 'AUT'), ('@contextControlCode', 'OP'), ('time', OrderedDict([('@value', '20110216164801')])), ('agentRef', OrderedDict([('@classCode', 'AGNT'), ('id', OrderedDict([('@root', 'CFE8F261-4D1C-11E3-9E6B-010000001205')]))]))])), ('location', OrderedDict([('@typeCode', 'LOC'), ('locatedEntity', OrderedDict([('@classCode', 'LOCE'), ('locatedPlace', OrderedDict([('@classCode', 'PLC'), ('@determinerCode', 'INSTANCE'), ('name', 'Testvale Surgery'), ('telecom', OrderedDict([('@use', 'WP'), ('@value', 'tel:01414221031'), ('useablePeriod', OrderedDict([('low', OrderedDict([('@value', '20131114')]))]))])), ('addr', OrderedDict([('@use', 'WP'), ('streetAddressLine', ['22 Northern Parade', 'Portsmouth', 'Hampshire']), ('postalCode', 'PO2 9PF'), ('useablePeriod', OrderedDict([('low', OrderedDict([('@value', '20131114')]))]))]))]))]))])), ('Participant2', OrderedDict([('@typeCode', 'PRF'), ('@contextControlCode', 'OP'), ('agentRef', OrderedDict([('@classCode', 'AGNT'), ('id', OrderedDict([('@root', 'CFE8F261-4D1C-11E3-9E6B-010000001205')]))]))])), ('component', OrderedDict([('@typeCode', 'COMP'), ('MedicationStatement', OrderedDict([('@classCode', 'SBADM'), ('@moodCode', 'ORD'), ('id', OrderedDict([('@root', 'D04E43E6-4D1C-11E3-A2DD-010000000161')])), ('statusCode', OrderedDict([('@code', 'COMPLETE')])), ('effectiveTime', OrderedDict([('center', OrderedDict([('@nullFlavor', 'NI')]))])), ('availabilityTime', OrderedDict([('@value', '20110216164801')])), ('consumable', OrderedDict([('@typeCode', 'CSM'), ('manufacturedProduct', OrderedDict([('@classCode', 'MANU'), ('manufacturedMaterial', OrderedDict([('@classCode', 'MMAT'), ('@determinerCode', 'KIND'), ('code', OrderedDict([('@code', '03890005'), ('@codeSystem', '2.16.840.1.113883.2.1.6.4'), ('@displayName', 'Birkbeck elastic waistband and shield LM725238 38mm (DBT Medical Ltd)'), ('translation', OrderedDict([('@code', '7089411000001103'), ('@codeSystem', '2.16.840.1.113883.2.1.3.2.4.15'), ('@displayName', 'Birkbeck elastic waistband and shield LM725238 38mm (DBT Medical Ltd)')]))]))]))]))])), ('component', [OrderedDict([('@typeCode', 'COMP'), ('ehrSupplyAuthorise', OrderedDict([('@classCode', 'SPLY'), ('@moodCode', 'INT'), ('id', OrderedDict([('@root', 'D04E43E5-4D1C-11E3-A2DD-010000000161')])), ('code', OrderedDict([('@code', '394823007'), ('@codeSystem', '2.16.840.1.113883.2.1.3.2.4.15'), ('@displayName', 'NHS prescription')])), ('statusCode', OrderedDict([('@code', 'COMPLETE')])), ('effectiveTime', OrderedDict([('center', OrderedDict([('@nullFlavor', 'NI')]))])), ('availabilityTime', OrderedDict([('@value', '20110216164801')])), ('repeatNumber', OrderedDict([('@value', '0')])), ('quantity', OrderedDict([('@value', '5'), ('@unit', '1'), ('translation', OrderedDict([('@value', '5'), ('originalText', 'belt')]))]))]))]), OrderedDict([('@typeCode', 'COMP'), ('ehrSupplyPrescribe', OrderedDict([('@classCode', 'SPLY'), ('@moodCode', 'RQO'), ('id', OrderedDict([('@root', 'D04E43E4-4D1C-11E3-A2DD-010000000161')])), ('code', OrderedDict([('@code', '394823007'), ('@codeSystem', '2.16.840.1.113883.2.1.3.2.4.15'), ('@displayName', 'NHS prescription')])), ('statusCode', OrderedDict([('@code', 'COMPLETE')])), ('availabilityTime', OrderedDict([('@value', '20110216164801')])), ('quantity', OrderedDict([('@value', '5'), ('@unit', '1'), ('translation', OrderedDict([('@value', '5'), ('originalText', 'belt')]))])), ('inFulfillmentOf', OrderedDict([('@typeCode', 'FLFS'), ('priorMedicationRef', OrderedDict([('@classCode', 'SBADM'), ('@moodCode', 'INT'), ('id', OrderedDict([('@root', 'D04E43E5-4D1C-11E3-A2DD-010000000161')]))]))]))]))])]), ('pertinentInformation', OrderedDict([('@typeCode', 'PERT'), ('pertinentMedicationDosage', OrderedDict([('@classCode', 'SBADM'), ('@moodCode', 'RMD'), ('text', 'use As directed')]))]))]))]))])

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py

Python

tests/ut_repytests_badcallname-test.py

SeattleTestbed/repy_v1

f40a02e2e398b1ec67fede84b41a264ae7356d2c

[ "MIT" ]

1

2021-08-18T05:58:17.000Z

tests/ut_repytests_badcallname-test.py

SeattleTestbed/repy_v1

f40a02e2e398b1ec67fede84b41a264ae7356d2c

[ "MIT" ]

3

2015-11-17T21:01:03.000Z

2016-07-14T09:08:04.000Z

tests/ut_repytests_badcallname-test.py

SeattleTestbed/repy_v1

f40a02e2e398b1ec67fede84b41a264ae7356d2c

[ "MIT" ]

5

2015-07-02T13:29:23.000Z

2021-09-25T07:48:30.000Z

#pragma error #pragma repy restrictions.badcallname pass

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py

Python

tests/test_AnomalyDetector.py

ChoonSiang/som-anomaly-detector

9234958dd187ae0f0cadef403c696d55c3320d67

[ "MIT" ]

null

tests/test_AnomalyDetector.py

ChoonSiang/som-anomaly-detector

9234958dd187ae0f0cadef403c696d55c3320d67

[ "MIT" ]

null

tests/test_AnomalyDetector.py

ChoonSiang/som-anomaly-detector

9234958dd187ae0f0cadef403c696d55c3320d67

[ "MIT" ]

1

2020-01-22T15:30:08.000Z

class TestAnomalyDetector(object): # Lets make some dummy tests to test our Travis-CI configuration def test_pass(self): assert 1 == 1 def nothing(self): print('This does nothing');

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py

Python

app/blueprints/users_bp/__init__.py

BlackIQ/web_flask

3e775aaef8a725b78bc3aafdac90e1259021a0b0

[ "MIT" ]

5

2021-11-21T10:59:51.000Z

2022-01-16T11:58:11.000Z

app/blueprints/users_bp/__init__.py

BlackIQ/web_flask

3e775aaef8a725b78bc3aafdac90e1259021a0b0

[ "MIT" ]

null

app/blueprints/users_bp/__init__.py

BlackIQ/web_flask

3e775aaef8a725b78bc3aafdac90e1259021a0b0

[ "MIT" ]

null

from flask import render_template, session, Blueprint from ... import sqlalchemy_db blueprint_users = Blueprint("users", __name__, url_prefix='/user/') from . import view_users, view_signup_login

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830e255fc3b822e042a573501f175b68a771d0f0

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py

Python

run.py

KnuckVlad/CoinCareBot

84c6de50a93544ee43529578a0b1f13173d63083

[ "MIT" ]

null

run.py

KnuckVlad/CoinCareBot

84c6de50a93544ee43529578a0b1f13173d63083

[ "MIT" ]

1

2018-03-18T10:54:02.000Z

run.py

KnuckVlad/CoinCareBot

84c6de50a93544ee43529578a0b1f13173d63083

[ "MIT" ]

1

2018-03-17T21:00:31.000Z

# Run a test server. # Module from production

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55c517b54681d4f2b41a111f3aedaa4dd13eedaa

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py

Python

mle_monitor/dashboard/__init__.py

mle-infrastructure/mle-monitor

5451986d3ca6855ec78be343a8147235f893ef8f

[ "MIT" ]

107

2021-12-09T15:31:44.000Z

2022-03-29T20:43:10.000Z

mle_monitor/dashboard/__init__.py

mle-infrastructure/mle-monitor

5451986d3ca6855ec78be343a8147235f893ef8f

[ "MIT" ]

1

2022-01-09T14:51:02.000Z

mle_monitor/dashboard/__init__.py

mle-infrastructure/mle-monitor

5451986d3ca6855ec78be343a8147235f893ef8f

[ "MIT" ]

3

2021-12-10T03:35:21.000Z

2022-01-19T11:43:15.000Z

from .layout import layout_dashboard from .update import update_dashboard __all__ = ["layout_dashboard", "update_dashboard"]

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Python

projects/g3h1-cp-fml-interpreter/src/fml_parser/__init__.py

keybrl/xdu-coursework

9d0e905bef28c18d87d3b97643de0d32f9f08ee0

[ "MIT" ]

null

projects/g3h1-cp-fml-interpreter/src/fml_parser/__init__.py

keybrl/xdu-coursework

9d0e905bef28c18d87d3b97643de0d32f9f08ee0

[ "MIT" ]

null

projects/g3h1-cp-fml-interpreter/src/fml_parser/__init__.py

keybrl/xdu-coursework

9d0e905bef28c18d87d3b97643de0d32f9f08ee0

[ "MIT" ]

null

from .grammar import NonTerminals, Terminals from .parser import Parser __all__ = ['NonTerminals', 'Terminals', 'Parser']

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Python

cookery/stdlib/assign.py

mikolajb/cookery

00d88685dc9931210c6274969e82c88753f3c3b0

[ "MIT" ]

1

2016-01-07T19:56:54.000Z

cookery/stdlib/assign.py

mikolajb/cookery

00d88685dc9931210c6274969e82c88753f3c3b0

[ "MIT" ]

7

2015-02-10T02:54:45.000Z

2015-03-09T16:14:05.000Z

cookery/stdlib/assign.py

mikolajb/cookery

00d88685dc9931210c6274969e82c88753f3c3b0

[ "MIT" ]

null

@cookery.action('(.*)') def assign(subject, var): return var

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Python

ns-allinone-3.27/ns-3.27/.waf-1.8.19-b1fc8f7baef51bd2db4c2971909a568d/waflib/extras/__init__.py

zack-braun/4607_NS

43c8fb772e5552fb44bd7cd34173e73e3fb66537

[ "MIT" ]

2,151

2020-04-18T07:31:17.000Z

2022-03-31T08:39:18.000Z

ns-allinone-3.27/ns-3.27/.waf-1.8.19-b1fc8f7baef51bd2db4c2971909a568d/waflib/extras/__init__.py

zack-braun/4607_NS

43c8fb772e5552fb44bd7cd34173e73e3fb66537

[ "MIT" ]

395

2020-04-18T08:22:18.000Z

2021-12-08T13:04:49.000Z

ns-allinone-3.27/ns-3.27/.waf-1.8.19-b1fc8f7baef51bd2db4c2971909a568d/waflib/extras/__init__.py

zack-braun/4607_NS

43c8fb772e5552fb44bd7cd34173e73e3fb66537

[ "MIT" ]

338

2020-04-18T08:03:10.000Z

2022-03-29T12:33:22.000Z

#! /usr/bin/env python # encoding: utf-8 # WARNING! Do not edit! https://waf.io/book/index.html#_obtaining_the_waf_file

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py

Python

callback/forms.py

grecof88/callbackurl

9a3afbfad0b7317ac306c310bcfccf73ca831159

[ "CC0-1.0" ]

null

callback/forms.py

grecof88/callbackurl

9a3afbfad0b7317ac306c310bcfccf73ca831159

[ "CC0-1.0" ]

null

callback/forms.py

grecof88/callbackurl

9a3afbfad0b7317ac306c310bcfccf73ca831159

[ "CC0-1.0" ]

null

from django import forms class LogForm(forms.Form): api_url = forms.CharField(label='URL', max_length=300) username = forms.CharField(label='Username', max_length=100) password = forms.CharField(label='Password', max_length=32, widget=forms.PasswordInput)

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py

Python

src/exception.py

ssaru/pytorch-XNOR-YOLO

2c02429d6ee052fe70a17ced4755d5814a4ef60a

[ "MIT" ]

1

2021-05-22T09:29:44.000Z

src/exception.py

ssaru/pytorch-XNOR-YOLO

2c02429d6ee052fe70a17ced4755d5814a4ef60a

[ "MIT" ]

null

src/exception.py

ssaru/pytorch-XNOR-YOLO

2c02429d6ee052fe70a17ced4755d5814a4ef60a

[ "MIT" ]

null

class InitializationError(Exception): pass

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362d26d442bb306be45e7fdfdaff78145e877399

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py

Python

news_site/authapp/admin.py

ObukhovVladislav/news-site

9eddbc435caad6c192b4bb6e1b38a26ded57776b

[ "Apache-2.0" ]

1

2021-09-02T10:21:35.000Z

news_site/authapp/admin.py

ObukhovVladislav/news-site

9eddbc435caad6c192b4bb6e1b38a26ded57776b

[ "Apache-2.0" ]

1

2020-11-14T05:15:16.000Z

2020-11-14T05:30:41.000Z

news_site/authapp/admin.py

ObukhovVladislav/news-site

9eddbc435caad6c192b4bb6e1b38a26ded57776b

[ "Apache-2.0" ]

2

2021-03-14T07:44:18.000Z

2021-04-25T18:18:02.000Z

from django.contrib import admin from authapp.models import UserProfile admin.site.register(UserProfile)

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py

Python

discovery/api/__init__.py

amenezes/discovery-client

9c41456d1cc14f4aab34628ad4e13423e00bc4be

[ "Apache-2.0" ]

2

2019-07-18T22:43:49.000Z

2020-03-09T03:27:41.000Z

discovery/api/__init__.py

amenezes/discovery-client

9c41456d1cc14f4aab34628ad4e13423e00bc4be

[ "Apache-2.0" ]

20

2019-02-27T19:08:03.000Z

2021-06-22T16:47:32.000Z

discovery/api/__init__.py

amenezes/discovery-client

9c41456d1cc14f4aab34628ad4e13423e00bc4be

[ "Apache-2.0" ]

null

# ACL from discovery.api.acl import Acl from discovery.api.agent import Agent from discovery.api.area import Area from discovery.api.auth_method import AuthMethod from discovery.api.autopilot import AutoPilot from discovery.api.binding_rule import BindingRule from discovery.api.ca import CA from discovery.api.catalog import Catalog from discovery.api.checks import Checks from discovery.api.config import Config from discovery.api.connect import Connect from discovery.api.coordinate import Coordinate from discovery.api.events import Events from discovery.api.health import Health from discovery.api.intention import Intentions from discovery.api.keyring import Keyring from discovery.api.kv import Kv from discovery.api.license import License from discovery.api.namespace import Namespace from discovery.api.operator import Operator from discovery.api.policy import Policy from discovery.api.query import Query from discovery.api.raft import Raft from discovery.api.role import Role from discovery.api.segment import Segment from discovery.api.service import Service from discovery.api.session import Session from discovery.api.snapshot import Snapshot from discovery.api.status import Status from discovery.api.token import Token from discovery.api.txn import Txn

38.454545

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5.703704

0.21164

0.37384

0.460111

0.03525

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0.099291

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51

39.65625

0.943132

0.002364

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true

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null

1

0

null

0

1

0

1

0

1

0

5

367d004e4d1247b09e718b7468baa06420d817f4

234

py

Python

edhoc/messages/__init__.py

geonnave/py-edhoc

c656fba49e939bbf86372844125790fa2d5fcb9f

[ "BSD-3-Clause" ]

2

2022-01-20T11:35:39.000Z

2022-03-11T15:49:36.000Z

edhoc/messages/__init__.py

TimothyClaeys/EDHOC-PYTHON

cd7a66ab407b4c4302e9937f5569b9de73d734b7

[ "BSD-3-Clause" ]

18

2021-03-02T15:10:11.000Z

2022-02-10T11:46:25.000Z

edhoc/messages/__init__.py

TimothyClaeys/EDHOC-PYTHON

cd7a66ab407b4c4302e9937f5569b9de73d734b7

[ "BSD-3-Clause" ]

3

2021-02-05T11:52:17.000Z

2021-12-08T20:49:49.000Z

from .message1 import MessageOne # noqa: F401 from .message2 import MessageTwo # noqa: F401 from .message3 import MessageThree # noqa: F401 from .base import EdhocMessage # noqa: F401 from .error import MessageError # noqa: F401

39

48

0.764957

30

234

5.966667

0.466667

0.223464

0.268156

0

0.092784

0.17094

234

5

49

46.8

0.829897

0.230769

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

368bac6adfa8f34a4aa42a3a28eea3750a8d05de

321

py

Python

internal/information/core/service/readpath/configfile/ports.py

julianVelandia/Eureka

b7cfea2d7fbc9f4dbb0d08f0b6dd547b6367602e

[ "MIT" ]

2

2022-01-29T17:56:42.000Z

2022-02-05T01:33:01.000Z

internal/information/core/service/readpath/configfile/ports.py

Turing-Core-Team/Eureka-v1.0

b7cfea2d7fbc9f4dbb0d08f0b6dd547b6367602e

[ "MIT" ]

null

internal/information/core/service/readpath/configfile/ports.py

Turing-Core-Team/Eureka-v1.0

b7cfea2d7fbc9f4dbb0d08f0b6dd547b6367602e

[ "MIT" ]

null

from abc import abstractmethod, ABCMeta from typing import List from internal.information.core.entity.path import Path from internal.information.core.query.get_config import GetConfig class ServiceGetPathInterface(metaclass=ABCMeta): @abstractmethod def get(self, query: GetConfig) -> List[Path]: pass

26.75

64

0.785047

39

321

6.435897

0.564103

0.095618

0.183267

0.215139

0

0.143302

321

11

65

29.181818

0.912727

0

1

0.125

false

0.125

0.5

0

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null

0

1

0

null

0

1

0

1

0

5

36a261023717a2b05be9004ae7b796c53162ca0b

54

py

Python

cjam/__init__.py

tadejaversic/cjam

392486d328521415386f1ccaf3a140438223f00f

[ "BSD-2-Clause" ]

12

2016-05-27T06:10:56.000Z

2021-12-18T12:50:31.000Z

cjam/__init__.py

tadejaversic/cjam

392486d328521415386f1ccaf3a140438223f00f

[ "BSD-2-Clause" ]

null

cjam/__init__.py

tadejaversic/cjam

392486d328521415386f1ccaf3a140438223f00f

[ "BSD-2-Clause" ]

2

2019-07-25T09:30:07.000Z

2022-03-02T13:33:21.000Z

from ._jam_axi import axi_vel, axi_rms, axisymmetric

18

52

0.814815

9

54

4.444444

0.777778

0

0.12963

54

2

53

27

0.851064

0

1

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true

0

1

0

1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

5

36acca15735f005ef2a612565c4cd934b99b472c

4,749

py

Python

jVMC/util/symmetries.py

markusschmitt/vmc_jax

53eb70989ac39033388b03633142d34ccdbd4bb0

[ "MIT" ]

30

2020-10-07T07:42:39.000Z

2022-03-29T04:25:26.000Z

jVMC/util/symmetries.py

markusschmitt/vmc_jax

53eb70989ac39033388b03633142d34ccdbd4bb0

[ "MIT" ]

11

2021-02-12T10:22:40.000Z

2022-03-04T09:42:12.000Z

jVMC/util/symmetries.py

markusschmitt/vmc_jax

53eb70989ac39033388b03633142d34ccdbd4bb0

[ "MIT" ]

10

2020-08-25T17:15:36.000Z

2022-03-17T05:38:33.000Z

import numpy as np import jax.numpy as jnp import jax def get_point_orbit_2d_square(L, rotation, reflection): ''' This function generates the group of point symmetries in a two-dimensional square lattice. Arguments: * ``L``: Linear dimension of the lattice. * ``rotation``: Boolean to indicate whether rotations are to be included * ``reflection``: Boolean to indicate whether reflections are to be included Returns: A three-dimensional ``jax.numpy.array``, where the first dimension corresponds to the different symmetry operations and the following two dimensions correspond to the corresponding permuation matrix. ''' trafos = [] idx = np.arange(L * L).reshape((L, L)) for _ in range(2 if reflection else 1): for _ in range(4 if rotation else 1): trafos.append(idx) idx = np.array(list(zip(*idx[::-1]))) # rotation idx = np.transpose(idx) # reflection orbit = [] idx = np.arange(L * L) for t in trafos: o = np.zeros((L * L, L * L), dtype=np.int32) o[idx, t.ravel()] = 1 orbit.append(o) orbit = jnp.array(orbit) return orbit def get_translation_orbit_2d_square(L, translation): ''' This function generates the group of translations in a two-dimensional square lattice. Arguments: * ``L``: Linear dimension of the lattice. * ``translation``: Boolean to indicate whether translations are to be included Returns: A three-dimensional ``jax.numpy.array``, where the first dimension corresponds to the different translations and the following two dimensions correspond to the corresponding permuation matrix. ''' idx = np.arange(L**2, dtype=np.int32).reshape((L, L)) trafos = [] for lx in range(L if translation else 1): for ly in range(L if translation else 1): trafos.append(idx) idx = np.roll(idx, 1, axis=1) idx = np.roll(idx, 1, axis=0) orbit = [] idx = np.arange(L * L) for t in trafos: o = np.zeros((L * L, L * L), dtype=np.int32) o[idx, t.ravel()] = 1 orbit.append(o) orbit = jnp.array(orbit) return orbit def get_orbit_2d_square(L, rotation=True, reflection=True, translation=True): ''' This function generates the group of lattice symmetries in a two-dimensional square lattice. Arguments: * ``L``: Linear dimension of the lattice. * ``rotation``: Boolean to indicate whether rotations are to be included * ``reflection``: Boolean to indicate whether reflections are to be included * ``translation``: Boolean to indicate whether translations are to be included Returns: A three-dimensional ``jax.numpy.array``, where the first dimension corresponds to the different symmetry operations and the following two dimensions correspond to the corresponding permuation matrix. ''' po = get_point_orbit_2d_square(L, rotation, reflection) to = get_translation_orbit_2d_square(L, translation) orbit = jax.vmap(lambda x, y: jax.vmap(lambda a, b: jnp.dot(b, a), in_axes=(None, 0))(x, y), in_axes=(0, None))(to, po) orbit = orbit.reshape((-1, L**2, L**2)) newOrbit = [tuple(x.ravel()) for x in orbit] uniqueOrbit = np.unique(newOrbit, axis=0).reshape(-1, L**2, L**2) return jnp.array(uniqueOrbit) def get_orbit_1d(L, translation=True, reflection=True, **kwargs): ''' This function generates the group of lattice symmetries in a one-dimensional lattice. Arguments: * ``L``: Linear dimension of the lattice. * ``reflection``: Boolean to indicate whether reflections are to be included * ``translation``: Boolean to indicate whether translations are to be included Returns: A three-dimensional ``jax.numpy.array``, where the first dimension corresponds to the different symmetry operations and the following two dimensions correspond to the corresponding permuation matrix. ''' def get_point_orbit_1D(L, reflection): return jnp.array([jnp.eye(L), jnp.fliplr(jnp.eye(L))]) if reflection else jnp.array([jnp.eye(L)]) def get_translation_orbit_1D(L, translation): to = np.array([np.eye(L)] * L) for idx, t in enumerate(to): to[idx] = np.roll(t, idx, axis=1) return jnp.array(to) if translation else jnp.array([jnp.eye(L)]) po = get_point_orbit_1D(L, reflection) to = get_translation_orbit_1D(L, translation) orbit = jax.vmap(lambda x, y: jax.vmap(lambda a, b: jnp.dot(a, b), in_axes=(None, 0))(x, y), in_axes=(0, None))(to, po) orbit = orbit.reshape((-1, L, L)) return orbit.astype(np.int32)

32.751724

123

0.652769

673

4,749

4.548291

0.156018

0.008494

0.04443

0.062725

0.809539

0.791898

0.710225

0.657955

0.617445

0

0.01239

0.235207

4,749

144

124

32.979167

0.830396

0.44641

0

0.357143

1

0

1

0.107143

false

0

0.053571

0.017857

0.267857

0

null

0

1

0

1

0

1

0

null

0

5

36be04d96164c0a71c1a0e8cf5bc25a4c4f9c872

83

py

Python

pyqt_checkbox_table_widget/__init__.py

yjg30737/pyqt-checkbox-table-widget

2d3650858c7a0e0b91b52cc1918525f8a7f17a22

[ "MIT" ]

null

pyqt_checkbox_table_widget/__init__.py

yjg30737/pyqt-checkbox-table-widget

2d3650858c7a0e0b91b52cc1918525f8a7f17a22

[ "MIT" ]

null

pyqt_checkbox_table_widget/__init__.py

yjg30737/pyqt-checkbox-table-widget

2d3650858c7a0e0b91b52cc1918525f8a7f17a22

[ "MIT" ]

null

from .checkBoxTableWidget import CheckBoxTableWidget from .checkBox import CheckBox

41.5

52

0.891566

8

83

9.25

0.5

0

0.084337

83

2

53

41.5

0.973684

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7fdbe1c18d70dcc4d0343a13e4c021a6fb9e5df3

54

py

Python

python/bag/__init__.py

blanton144/bag

29e45edcd24c593b84c74b5f68a22f3f8d724c8d

[ "BSD-3-Clause" ]

null

python/bag/__init__.py

blanton144/bag

29e45edcd24c593b84c74b5f68a22f3f8d724c8d

[ "BSD-3-Clause" ]

null

python/bag/__init__.py

blanton144/bag

29e45edcd24c593b84c74b5f68a22f3f8d724c8d

[ "BSD-3-Clause" ]

null

import bag.night as night from .asinh_image import *

13.5

26

0.777778

9

54

4.555556

0.777778

0

0.166667

54

3

27

18

0.911111

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7feb4a902bfa39a4e7fb830f1803f14c26e2c1a2

429

py

Python

src/test/data/pa2/AdditionalTestCases_pa2/bad_class_redefined_with_diff_superclass.py

Leo-Enrique-Wu/chocopy_compiler_semantic_analysis

e89f6434dd7d274d4838457316143f312226495f

[ "BSD-2-Clause" ]

null

src/test/data/pa2/AdditionalTestCases_pa2/bad_class_redefined_with_diff_superclass.py

Leo-Enrique-Wu/chocopy_compiler_semantic_analysis

e89f6434dd7d274d4838457316143f312226495f

[ "BSD-2-Clause" ]

null

src/test/data/pa2/AdditionalTestCases_pa2/bad_class_redefined_with_diff_superclass.py

Leo-Enrique-Wu/chocopy_compiler_semantic_analysis

e89f6434dd7d274d4838457316143f312226495f

[ "BSD-2-Clause" ]

null

class B(object): b:int =1 a:int =1 d:int =1 class C(object): c:int =1 class A(B): a:int = 1 #attr redefined in B b:int = 1 #attr redefined in B # this declaration will be ignore class A(C): a:int = 1 #ok,check attr in C c:int = 1 #attr redefined class D(A): a:int = 1 #attr redefined b:int = 1 #attr redefined c:int = 1 #no problem d:int = 1 #attr redefined in B

20.428571

36

0.564103

81

429

2.987654

0.246914

0.198347

0.421488

0.404959

0.247934

0

0.041237

0.321678

429

21

37

20.428571

0.790378

0.370629

0

0.705882

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

7ffa96513475a582dce975565af9fda8b0cb5f6e

54

py

Python

tf_al/stats/stochastic/__init__.py

ExLeonem/active-learning

0c4527fccb01c43e40a476fe93fda901a35a61e8

[ "MIT" ]

1

2021-11-23T03:30:04.000Z

tf_al/stats/stochastic/__init__.py

ExLeonem/tf-al

0c4527fccb01c43e40a476fe93fda901a35a61e8

[ "MIT" ]

null

tf_al/stats/stochastic/__init__.py

ExLeonem/tf-al

0c4527fccb01c43e40a476fe93fda901a35a61e8

[ "MIT" ]

null

from .accuracy import Accuracy from .loss import Loss

18

30

0.814815

8

54

5.5

0.5

0

0.148148

54

3

31

18

0.956522

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3d608860d3b9c25702cf58a1c9d6b4f6db2a3a3c

25

py

Python

idk/common/__init__.py

Samsung/ADBI

3e424c45386b0a36c57211da819021cb1929775a

[ "Apache-2.0" ]

312

2016-02-04T11:03:17.000Z

2022-03-18T11:30:10.000Z

idk/common/__init__.py

NickHardwood/ADBI

3e424c45386b0a36c57211da819021cb1929775a

[ "Apache-2.0" ]

4

2016-02-04T11:05:40.000Z

2017-07-27T04:22:27.000Z

idk/common/__init__.py

NickHardwood/ADBI

3e424c45386b0a36c57211da819021cb1929775a

[ "Apache-2.0" ]

85

2016-02-04T12:48:30.000Z

2021-01-14T06:23:24.000Z

import deco import mixin

12.5

12

0.84

4

25

5.25

0.75

0

0.16

25

2

13

12.5

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

18015984dff32663ab62f947f842eec57a6c1783

61

py

Python

1.py

FreiheitalsAutonomie/Learning-git-and-github

d0f902bbb67a0e24b2daeb85b89b43435507212c

[ "Apache-2.0" ]

null

1.py

FreiheitalsAutonomie/Learning-git-and-github

d0f902bbb67a0e24b2daeb85b89b43435507212c

[ "Apache-2.0" ]

null

1.py

FreiheitalsAutonomie/Learning-git-and-github

d0f902bbb67a0e24b2daeb85b89b43435507212c

[ "Apache-2.0" ]

null

print('hello world!') print('This is a try of using commit')

20.333333

38

0.704918

11

61

3.909091

0.909091

0

0.147541

61

2

39

30.5

0.826923

0

0.672131

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

181270f57f1a2f5eae42513b2d122e44d97cb052

103

py

Python

python_polar_coding/polar_codes/fast_ssc/__init__.py

MingxuZhang/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

2

2021-12-07T09:52:15.000Z

2022-01-06T14:35:37.000Z

python_polar_coding/polar_codes/fast_ssc/__init__.py

manhduc1811/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

null

python_polar_coding/polar_codes/fast_ssc/__init__.py

manhduc1811/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

4

2020-07-03T14:20:04.000Z

2021-07-04T13:20:40.000Z

from .codec import FastSSCPolarCodec from .decoder import FastSSCDecoder from .node import FastSSCNode

25.75

36

0.854369

12

103

7.333333

0.666667

0

0.116505

103

3

37

34.333333

0.967033

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

1816ae64142ac6df162b2bc80cb75d863085ac1b

171

py

Python

02 - Arithmetic operators/Des_008.py

o-Ian/Practice-Python

1e4b2d0788e70006096a53a7cf038db3148ba4b7

[ "MIT" ]

4

2021-04-23T18:07:58.000Z

2021-05-12T11:38:14.000Z

02 - Arithmetic operators/Des_008.py

o-Ian/Practice-Python

1e4b2d0788e70006096a53a7cf038db3148ba4b7

[ "MIT" ]

null

02 - Arithmetic operators/Des_008.py

o-Ian/Practice-Python

1e4b2d0788e70006096a53a7cf038db3148ba4b7

[ "MIT" ]

null

m = float(input('Digite um valor em metros: ')) print('{:.3f} metros é igual a {:.3f} centrímetros.\n{:.3f} metros é igual a {:.3f} milímetros' .format(m,m*100,m,m*1000))

57

122

0.649123

31

171

3.580645

0.612903

0.144144

0.162162

0.252252

0.306306

0

0.073826

0.128655

171

2

123

85.5

0.671141

0

0.5

0.666667

0.122807

0

1

0

false

0

0.5

0

null

0

1

0

1

0

1

0

null

0

1

0

5

186fa6b2fa7aefce399575167d80b0863f49e4b7

8,266

py

Python

nefct/functions/back_project.py

bill52547/CT-NEF

f8b29452ab376069218284f95603a0cc6c7e96ac

[ "Apache-2.0" ]

null

nefct/functions/back_project.py

bill52547/CT-NEF

f8b29452ab376069218284f95603a0cc6c7e96ac

[ "Apache-2.0" ]

null

nefct/functions/back_project.py

bill52547/CT-NEF

f8b29452ab376069218284f95603a0cc6c7e96ac

[ "Apache-2.0" ]

null

from nefct import nef_class, Any from nefct.utils import tqdm from nefct.data.image import Image2D, Image3D, Image from nefct.data.projection import ProjectionSequence2D, ProjectionSequence3D from nefct.geometry.scanner_config import ScannerConfig, ScannerConfig2D, ScannerConfig3D import numpy as np import tensorflow as tf __all__ = ('BackProject', 'BackProject2D', 'BackProject3D') dist_mod_3d = tf.load_op_library( '/home/bill52547/Github/tensorflow/bazel-bin/tensorflow/core/user_ops/dist_3d_mod.so' ) dist_back_proj_3d_flat = dist_mod_3d.back_project_flat_three dist_back_proj_3d_cyli = dist_mod_3d.back_project_cyli_three dist_mod_2d = tf.load_op_library( '/home/bill52547/Github/tensorflow/bazel-bin/tensorflow/core/user_ops/dist_2d_mod.so' ) dist_back_proj_2d_flat = dist_mod_2d.back_project_flat_two dist_back_proj_2d_cyli = dist_mod_2d.back_project_cyli_two @nef_class class BackProject: config: ScannerConfig def __call__(self, *args, **kwargs) -> Image: pass @nef_class class BackProject2D(BackProject): config: ScannerConfig2D shape: list unit_size: float def __call__(self, proj: ProjectionSequence2D) -> Image2D: mode = self.config.mode from nefct.utils import declare_eager_execution declare_eager_execution() config = { 'shape': self.shape, 'angles': proj.angles, 'SID': self.config.SID / self.unit_size, 'SAD': self.config.SAD / self.unit_size, 'na': self.config.detector.number, 'da': self.config.detector.unit_size, 'ai': self.config.detector.offset } if mode == 'flat': dist_back_proj_2d = dist_back_proj_2d_flat config['da'] /= self.unit_size config['ai'] /= self.unit_size else: dist_back_proj_2d = dist_back_proj_2d_cyli bproj_data = dist_back_proj_2d(proj.data.transpose(), **config).numpy().transpose() return Image2D(bproj_data * self.unit_size, [0, 0], [s * self.unit_size for s in self.shape]) # # # @nef_class # class BackProject2DT(BackProject): # config: ScannerConfig2D # shape: list # unit_size: float # timestamps: list # deformer: Any # # def __call__(self, proj: ProjectionSequence2D) -> Image2D: # mode = self.config.mode # from nefct.utils import declare_eager_execution # declare_eager_execution() # # config = { # 'shape': self.shape, # 'angles': proj.angles, # 'SID': self.config.SID, # 'SAD': self.config.SAD, # 'na': self.config.detector.number, # 'da': self.config.detector.unit_size, # 'ai': self.config.detector.offset # } # if mode == 'flat': # dist_back_proj_2d = dist_back_proj_2d_flat # config['da'] /= self.unit_size # config['ai'] /= self.unit_size # else: # dist_back_proj_2d = dist_back_proj_2d_cyli # bproj_data = np.zeros(self.shape, np.float32) # for i, time_ in enumerate(proj.timestamps): # config['angles'] = [proj.angles[i]] # bproj_data_ = dist_back_proj_2d(proj.data[:, i].transpose(), # **config).numpy().transpose() # bproj_data += self.deformer(bproj_data_, time_, self.timestamps) # # return Image2D(bproj_data * self.unit_size, [0, 0], # [s * self.unit_size for s in self.shape]) # # # @nef_class # class BackProject2DNT(BackProject): # config: ScannerConfig2D # shape: list # unit_size: float # timestamps: list # # def __call__(self, proj: ProjectionSequence2D) -> list: # mode = self.config.mode # from nefct.utils import declare_eager_execution # declare_eager_execution() # # config = { # 'shape': self.shape, # 'angles': proj.angles, # 'SID': self.config.SID / self.unit_size, # 'SAD': self.config.SAD / self.unit_size, # 'na': self.config.detector.number, # 'da': self.config.detector.unit_size, # 'ai': self.config.detector.offset # } # if mode == 'flat': # dist_back_proj_2d = dist_back_proj_2d_flat # config['da'] /= self.unit_size # config['ai'] /= self.unit_size # else: # dist_back_proj_2d = dist_back_proj_2d_cyli # tmp_size = self.timestamps.size # bproj_data = [np.zeros(self.shape, np.float32)] * tmp_size # for i, time_ in enumerate(self.timestamps): # inds = np.where(proj.timestamps == time_)[0] # config['angles'] = proj.angles[inds] # bproj_data_ = dist_back_proj_2d(proj.data[:, inds].transpose(), # **config).numpy().transpose() # bproj_data[i] += bproj_data_ # # return [Image2D(bproj_data[i] * self.unit_size, [0, 0], # [s * self.unit_size for s in self.shape]) for i in range(tmp_size)] @nef_class class BackProject3D(BackProject): config: ScannerConfig3D shape: list unit_size: float def __call__(self, proj: ProjectionSequence3D) -> Image3D: mode = self.config.mode config = { 'shape': self.shape, 'offsets': [off / self.unit_size for off in proj.offsets], 'angles': proj.angles, 'SID': self.config.SID / self.unit_size, 'SAD': self.config.SAD / self.unit_size, 'na': self.config.detector_a.number, 'da': self.config.detector_a.unit_size, 'ai': self.config.detector_a.offset, 'nb': self.config.detector_b.number, 'db': self.config.detector_b.unit_size / self.unit_size, 'bi': self.config.detector_b.offset / self.unit_size } if mode == 'flat': dist_back_proj_3d = dist_back_proj_3d_flat config['da'] /= self.unit_size config['ai'] /= self.unit_size else: dist_back_proj_3d = dist_back_proj_3d_cyli bproj_data = dist_back_proj_3d(proj.data.transpose(), **config).numpy().transpose() return Image3D(bproj_data * self.unit_size, [0, 0], [s * self.unit_size for s in self.shape]) # # @nef_class # class BackProject3DT(BackProject): # config: ScannerConfig3D # shape: list # unit_size: float # timestamps: list # deformer: Any # # def __call__(self, proj: ProjectionSequence3D) -> Image3D: # mode = self.config.mode # # config = { # 'shape': self.shape, # 'offsets': proj.offsets, # 'angles': proj.angles, # 'SID': self.config.SID / self.unit_size, # 'SAD': self.config.SAD / self.unit_size, # 'na': self.config.detector_a.number, # 'da': self.config.detector_a.unit_size, # 'ai': self.config.detector_a.offset, # 'nb': self.config.detector_b.number, # 'db': self.config.detector_b.unit_size / self.unit_size, # 'bi': self.config.detector_b.offset / self.unit_size # } # # if mode == 'flat': # dist_back_proj_3d = dist_back_proj_3d_flat # config['da'] /= self.unit_size # config['ai'] /= self.unit_size # else: # dist_back_proj_3d = dist_back_proj_3d_cyli # # bproj_data = np.zeros(self.shape, np.float32) # for i in tqdm(range(len(proj.timestamps))): # time_ = proj.timestamps[i] # config['angles'] = [proj.angles[i]] # config['offsets'] = [proj.offsets[i] / self.unit_size] # bproj_data_ = dist_back_proj_3d(proj.data[:, :, i].transpose(), # **config).numpy().transpose() # bproj_data += self.deformer(bproj_data_, time_, self.timestamps) # return Image3D(bproj_data * self.unit_size, [0, 0, 0], # [s * self.unit_size for s in self.shape])

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187d3f995b85de285f36309cc4750a7656215155

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py

Python

pypki3/exceptions.py

nbgallery/pypki3

87ea624d9e191f463e05bf7be66f3959840d9f52

[ "MIT" ]

null

pypki3/exceptions.py

nbgallery/pypki3

87ea624d9e191f463e05bf7be66f3959840d9f52

[ "MIT" ]

4

2021-08-13T16:57:33.000Z

2021-10-14T10:48:37.000Z

pypki3/exceptions.py

nbgallery/pypki3

87ea624d9e191f463e05bf7be66f3959840d9f52

[ "MIT" ]

null

class Pypki3Exception(Exception): pass

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1

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null

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1

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5

a11700537edadfde240c42f7a84858abf2467da4

1,219

py

Python

wrappers/python/tests/non_secrets/test_delete_wallet_record_tags.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

wrappers/python/tests/non_secrets/test_delete_wallet_record_tags.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

wrappers/python/tests/non_secrets/test_delete_wallet_record_tags.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

import pytest from indy import error from tests.non_secrets.common import * @pytest.mark.asyncio async def test_delete_wallet_record_tags_works(wallet_handle): await non_secrets.add_wallet_record(wallet_handle, type_, id1, value1, tags1) await check_record_field(wallet_handle, "tags", tags1) await non_secrets.delete_wallet_record_tags(wallet_handle, type_, id1, '["tagName1"]') expected_tags = '{"tagName2": "5", "tagName3": "12"}' await check_record_field(wallet_handle, "tags", expected_tags) @pytest.mark.asyncio async def test_delete_wallet_record_tags_works_for_delete_all(wallet_handle): await non_secrets.add_wallet_record(wallet_handle, type_, id1, value1, tags1) await check_record_field(wallet_handle, "tags", tags1) await non_secrets.delete_wallet_record_tags(wallet_handle, type_, id1, '["tagName1", "tagName2", "tagName3"]') await check_record_field(wallet_handle, "tags", tags_empty) @pytest.mark.asyncio async def test_delete_wallet_record_tags_works_for_not_found_record(wallet_handle): with pytest.raises(error.WalletItemNotFound): await non_secrets.delete_wallet_record_tags(wallet_handle, type_, id1, '["tagName1", "tagName2", "tagName3"]')

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a1ac3635e4783180059e31613dea7ae8bce58bc7

163

py

Python

python/katana/local/__init__.py

yshalabi/katana

e0e5dbd82ec389ea927a756b6256f7e52f629458

[ "BSD-3-Clause" ]

null

python/katana/local/__init__.py

yshalabi/katana

e0e5dbd82ec389ea927a756b6256f7e52f629458

[ "BSD-3-Clause" ]

null

python/katana/local/__init__.py

yshalabi/katana

e0e5dbd82ec389ea927a756b6256f7e52f629458

[ "BSD-3-Clause" ]

null

from katana.barrier import SimpleBarrier, get_fast_barrier from ._shared_mem_sys import initialize __all__ = ["initialize", "get_fast_barrier", "SimpleBarrier"]

27.166667

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62fca37ebe0fef4801e8faa591a5d1e6e2439360

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py

Python

deep_utils/utils/utils/__init__.py

Vargha-Kh/deep_utils

30bcef4f5869b5b7c7333612d6c219d5399f819b

[ "MIT" ]

5

2021-07-29T16:35:20.000Z

2022-03-27T18:24:44.000Z

deep_utils/utils/utils/__init__.py

MenuaB/deep_utils

b1b936f4780ea7dc52224f53f5116288c5b0a804

[ "MIT" ]

null

deep_utils/utils/utils/__init__.py

MenuaB/deep_utils

b1b936f4780ea7dc52224f53f5116288c5b0a804

[ "MIT" ]

null

from .main import shift_lst, dictnamedtuple, easy_argparse from .pickles import dump_pickle, load_pickle from .unzip import unzip

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1

0

1

0

5

1a0b8143cceb47aa3dfc554c4b964acdab3d6202

25

py

Python

text/_cascade/element/_box/block.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_cascade/element/_box/block.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_cascade/element/_box/block.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

class BlockBox: pass

8.333333

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null

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5

1a23fcd5dea5a412f440b554e035a8644bbb0abd

517

py

Python

collection/models/status_enum.py

Chansazm/Project_20_Money_Transfer_App

f215c9f6fa4004ec44bc9009d717adaede4d98a9

[ "MIT" ]

null

collection/models/status_enum.py

Chansazm/Project_20_Money_Transfer_App

f215c9f6fa4004ec44bc9009d717adaede4d98a9

[ "MIT" ]

null

collection/models/status_enum.py

Chansazm/Project_20_Money_Transfer_App

f215c9f6fa4004ec44bc9009d717adaede4d98a9

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ collection This file was automatically generated by APIMATIC v2.0 ( https://apimatic.io ). """ class StatusEnum(object): """Implementation of the 'Status' enum. TODO: type enum description here. Attributes: PENDING: TODO: type description here. SUCCESSFUL: TODO: type description here. FAILED: TODO: type description here. """ PENDING = 'PENDING' SUCCESSFUL = 'SUCCESSFUL' FAILED = 'FAILED'

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5

1a267fea8686238ff22d195f965954ef7c84da97

182

py

Python

packs/jenkins/actions/get_job_info.py

userlocalhost2000/st2contrib

1a5f759e76401743ed9023d298a3d767e3885db1

[ "Apache-2.0" ]

164

2015-01-17T16:08:33.000Z

2021-08-03T02:34:07.000Z

packs/jenkins/actions/get_job_info.py

userlocalhost2000/st2contrib

1a5f759e76401743ed9023d298a3d767e3885db1

[ "Apache-2.0" ]

442

2015-01-01T11:19:01.000Z

2017-09-06T23:26:17.000Z

packs/jenkins/actions/get_job_info.py

userlocalhost2000/st2contrib

1a5f759e76401743ed9023d298a3d767e3885db1

[ "Apache-2.0" ]

202

2015-01-13T00:37:40.000Z

2020-11-07T11:30:10.000Z

from lib import action class GetJobInfo(action.JenkinsBaseAction): def run(self, project): return self.jenkins.get_job_info(project, depth=0, fetch_all_builds='False')

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5

a7f6c0f68e27794e1621e6b6237ec5dbf31fccd5

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py

Python

Application/src/flowcharts/Connector.py

AO-StreetArt/AOWorkflowDeveloper

ac041b46a9cc9c346c46d2c061f9588c21bf9948

[ "MIT" ]

null

Application/src/flowcharts/Connector.py

AO-StreetArt/AOWorkflowDeveloper

ac041b46a9cc9c346c46d2c061f9588c21bf9948

[ "MIT" ]

35

2015-10-09T02:42:31.000Z

2015-12-13T21:39:53.000Z

src/flowcharts/Connector.py

balex1/TestScriptBuilder

f9bfd3ca6aa267e685c1748c5cb3f3e680a5a76f

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Tue Oct 20 19:05:49 2015 @author: alex """ from kivy.graphics import Color, Line from kivy.uix.widget import Widget from kivy.properties import ListProperty, NumericProperty from kivy.logger import Logger #This class defines the line drawn between two nodes class Connector(Widget): #Front and Back vertices, the line is drawn in between #2 Entry Lists front = ListProperty([0, 0]) back = ListProperty([1, 1]) #The color of the lines #3 Entry Lists line_color = ListProperty([1, 1, 1]) line_width = NumericProperty(1.5) ellipse_diameter = NumericProperty(20) arrow_offset = NumericProperty(1) def __init__(self, **kwargs): super(Connector, self).__init__(**kwargs) self.bind(front=self.set_front, back=self.set_back, line_color=self.set_color, line_width=self.set_color) Logger.debug('Flowchart: Connector: Connector initialized with front = %s and back = %s' % (self.front, self.back)) def set_front(self, *args): self.canvas.clear() with self.canvas: Color(self.line_color[0], self.line_color[1], self.line_color[2]) Line(points=[self.front[0], self.front[1], self.back[0], self.back[1]], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 6) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 10) + self.arrow_offset], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 10) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 6) + self.arrow_offset], width=self.line_width) Logger.debug('Flowchart: Connector: Connector updated with front = %s and back = %s' % (self.front, self.back)) def set_back(self, *args): self.canvas.clear() with self.canvas: Color(self.line_color[0], self.line_color[1], self.line_color[2]) Line(points=[self.front[0], self.front[1], self.back[0], self.back[1]], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 6) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 10) + self.arrow_offset], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 10) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 6) + self.arrow_offset], width=self.line_width) Logger.debug('Flowchart: Connector: Connector initialized with front = %s and back = %s' % (self.front, self.back)) def set_color(self, *args): self.canvas.clear() with self.canvas: Color(self.line_color[0], self.line_color[1], self.line_color[2]) Line(points=[self.front[0], self.front[1], self.back[0], self.back[1]], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 6) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 10) + self.arrow_offset], width=self.line_width) Line(points=[self.back[0], self.back[1], self.back[0] + ((self.front[0] - self.back[0]) / 10) + self.arrow_offset, self.back[1] + ((self.front[1] - self.back[1]) / 6) + self.arrow_offset], width=self.line_width) Logger.debug('Flowchart: Connector: Connector color updated with color = %s, %s, %s' % (self.line_color[0], self.line_color[1], self.line_color[2]))

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3d6c75caab1051fdd5437f4e84d024cd87524da0

72

py

Python

ssher/core/entities/__init__.py

maximkir/ssher

46a4f1542ae214e777d48757cbf4a41d1519f54d

[ "Apache-2.0" ]

null

ssher/core/entities/__init__.py

maximkir/ssher

46a4f1542ae214e777d48757cbf4a41d1519f54d

[ "Apache-2.0" ]

null

ssher/core/entities/__init__.py

maximkir/ssher

46a4f1542ae214e777d48757cbf4a41d1519f54d

[ "Apache-2.0" ]

null

from .ssh.conn import ShhConnection from .identities import IdentityKey

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5

3dbb5691bad6a2aa6ce6bf82d3f2777f5ec05dfb

7,184

py

Python

src/matlab2cpp/rules/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

src/matlab2cpp/rules/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

src/matlab2cpp/rules/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

62.469565

85

0.322244

422

7,184

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null

0

1

0

5

3df1976e4b775fee9aeb8ac8363732aab2ca31ee

225

py

Python

muz/frontend/curses/__init__.py

Akaricchi/muz

87c443ae26fc287dda38ca1066856048642295a6

[ "WTFPL" ]

9

2016-09-20T16:53:55.000Z

2018-07-06T06:47:12.000Z

muz/frontend/curses/__init__.py

Akaricchi/muz

87c443ae26fc287dda38ca1066856048642295a6

[ "WTFPL" ]

null

muz/frontend/curses/__init__.py

Akaricchi/muz

87c443ae26fc287dda38ca1066856048642295a6

[ "WTFPL" ]

null

from __future__ import absolute_import from __future__ import print_function from __future__ import division from __future__ import unicode_literals from ..pygame.audio import Music, Sound from .main import Clock, Frontend

25

39

0.848889

30

225

5.733333

0.533333

0.232558

0.372093

0

0.124444

225

8

40

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0

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null

0

1

0

1

0

5

9a9c1542277635afed1a854bc2c99620a6e0c4b1

137

py

Python

featuretools/variable_types/api.py

rohit901/featuretools

20bee224782acf94909c2bf33239fd5332a8c1de

[ "BSD-3-Clause" ]

2

2021-07-13T07:40:20.000Z

2021-08-19T04:57:24.000Z

featuretools/variable_types/api.py

rohit901/featuretools

20bee224782acf94909c2bf33239fd5332a8c1de

[ "BSD-3-Clause" ]

13

2021-03-04T19:29:21.000Z

2022-01-21T10:49:20.000Z

featuretools/variable_types/api.py

rohit901/featuretools

20bee224782acf94909c2bf33239fd5332a8c1de

[ "BSD-3-Clause" ]

2

2021-02-09T21:37:48.000Z

2021-12-22T16:13:27.000Z

# flake8: noqa from .utils import ( find_variable_types, graph_variable_types, list_variable_types ) from .variable import *

17.125

25

0.737226

17

137

5.588235

0.588235

0.410526

0

0.009091

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137

7

26

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1

0

null

0

1

0

1

0

5

9aa45f7bc04d101d78137fa82d2b369ed446b880

67

py

Python

tests/test_config.py

dougbenjamin/ray

6f01cb1af4eb2fdd3c32fb3ebf21bb6405c4b540

[ "Apache-2.0" ]

3

2019-10-08T22:56:35.000Z

2021-07-21T23:31:48.000Z

tests/test_config.py

dougbenjamin/ray

6f01cb1af4eb2fdd3c32fb3ebf21bb6405c4b540

[ "Apache-2.0" ]

4

2020-07-07T12:30:08.000Z

2020-09-25T14:18:38.000Z

tests/test_config.py

dougbenjamin/ray

6f01cb1af4eb2fdd3c32fb3ebf21bb6405c4b540

[ "Apache-2.0" ]

5

2020-07-06T12:10:36.000Z

2022-03-09T22:25:25.000Z

class TestConfig: def test_config(self, config): pass

13.4

34

0.641791

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67

5.25

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0.283582

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4

35

16.75

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false

0.333333

0

0.666667

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null

0

1

0

null

0

1

0

1

0

1

0

5

9ad90c655c7b314c9b9a8c7a8021fe60f71df3d3

41

py

Python

test3.py

cvendeirinho/HelloWorld

cee78dc5dfc154cdcbaf8f01cf34c3de50230cdb

[ "Apache-2.0" ]

null

test3.py

cvendeirinho/HelloWorld

cee78dc5dfc154cdcbaf8f01cf34c3de50230cdb

[ "Apache-2.0" ]

null

test3.py

cvendeirinho/HelloWorld

cee78dc5dfc154cdcbaf8f01cf34c3de50230cdb

[ "Apache-2.0" ]

null

print("test3.py") print("pynet Class1")

10.25

21

0.682927

6

41

4.666667

0.833333

0

0.054054

0.097561

41

3

22

13.666667

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0.5

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1

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true

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null

0

1

0

null

0

1

0

1

0

5

9ade2bdcf8faf6e25d4ccc39bbb35b8d39cf3ced

156

py

Python

bacpypes/service/__init__.py

cbergmiller/bacpypes

7b1f2e989787c2c1f807680fee5ee7a71b3689ab

[ "MIT" ]

1

2018-01-11T13:10:15.000Z

bacpypes/service/__init__.py

cbergmiller/bacpypes

7b1f2e989787c2c1f807680fee5ee7a71b3689ab

[ "MIT" ]

null

bacpypes/service/__init__.py

cbergmiller/bacpypes

7b1f2e989787c2c1f807680fee5ee7a71b3689ab

[ "MIT" ]

null

#!/usr/bin/env python """ Service Subpackage """ from .detect import * from .device import * from .object import * from .cov import * from .file import *

13

21

0.685897

21

156

5.095238

0.619048

0.373832

0

0.179487

156

11

22

14.181818

0.835938

0.25

0

1

0

true

0

1

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1

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1

0

null

1

0

null

0

1

0

1

0

1

0

5

b10e532240d62257666a7ab4f46c877f0112eb59

2,724

py

Python

tests/dynamics/helper/dynamics_class_test.py

WeitaoZC/iflow

404ffdbeb27d9fae7d1350de6af84ed7bfdaad99

[ "MIT" ]

11

2020-11-01T06:03:57.000Z

2022-03-10T01:14:03.000Z

tests/dynamics/helper/dynamics_class_test.py

WeitaoZC/iflow

404ffdbeb27d9fae7d1350de6af84ed7bfdaad99

[ "MIT" ]

1

2022-03-14T21:32:51.000Z

tests/dynamics/helper/dynamics_class_test.py

WeitaoZC/iflow

404ffdbeb27d9fae7d1350de6af84ed7bfdaad99

[ "MIT" ]

2

2021-02-03T02:41:14.000Z

2021-06-08T16:31:02.000Z

import numpy as np import matplotlib.pyplot as plt import torch from iflow.utils.generic import to_numpy class TestClass(): def __init__(self, dynamics): self.dynamics = dynamics self.N = 100 def points_evolution(self): x0 = torch.ones(1, 3) trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=False) trj_n_np = to_numpy(trj_n) plt.plot(trj_n_np[:, 0], '*') plt.show() def noise_forward_evaluation(self): x0 = torch.ones(100, 3) trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=True) trj_n_np = to_numpy(trj_n) for i in range(10): plt.plot(trj_n_np[:, i, 0]) plt.show() def noise_backward_evaluation(self): x0 = torch.ones(1, 3)*0.1 trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=False) x0 = torch.ones(100, 3) * trj_n[-1, 0, :] trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=True, reverse=True) trj_n_np = to_numpy(trj_n) for i in range(100): plt.plot(trj_n_np[:, i, 0]) plt.show() def forward_density(self): x0 = torch.ones(1, 3) tr_mu, tr_var = self.dynamics.generate_trj_density(x0, self.N, reverse=False) print(tr_mu.shape) print(tr_var.shape) tr_mu = to_numpy(tr_mu) tr_var = to_numpy(tr_var) l_trj = tr_mu[:, 0, 0] - 3 * np.sqrt(tr_var[:, 0, 0, 0]) h_trj = tr_mu[:, 0, 0] + 3 * np.sqrt(tr_var[:, 0, 0, 0]) t = np.linspace(0, tr_mu.shape[0], tr_mu.shape[0]) plt.plot(t, tr_mu[:, 0, 0]) plt.fill_between(t, l_trj, h_trj, alpha=0.3) x0 = torch.ones(30, 3) trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=True, reverse=False) trj_n_np = to_numpy(trj_n) for i in range(10): plt.plot(trj_n_np[:, i, 0]) plt.show() def backward_density(self): x0 = torch.ones(1, 3) * 0.01 tr_mu, tr_var = self.dynamics.generate_trj_density(x0, self.N, reverse=True) print(tr_mu.shape) print(tr_var.shape) tr_mu = to_numpy(tr_mu) tr_var = to_numpy(tr_var) l_trj = tr_mu[:, 0, 0] - 3 * np.sqrt(tr_var[:, 0, 0, 0]) h_trj = tr_mu[:, 0, 0] + 3 * np.sqrt(tr_var[:, 0, 0, 0]) t = np.linspace(0, tr_mu.shape[0], tr_mu.shape[0]) plt.plot(t, tr_mu[:, 0, 0]) plt.fill_between(t, l_trj, h_trj, alpha=0.3) ### Random TRJS #### x0 = torch.ones(30, 3) * 0.01 trj_n = self.dynamics.generate_trj(x0, T=self.N, noise=True, reverse=True) trj_n_np = to_numpy(trj_n) for i in range(10): plt.plot(trj_n_np[:, i, 0]) plt.show()

34.05

85

0.567181

465

2,724

3.101075

0.133333

0.061026

0.041609

0.127601

0.843273

0.784327

0.773232

0.703884

0.688627

0

0.052685

0.282305

2,724

80

86

34.05

0.68491

0.004038

0

0.621212

0

0.00037

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1

0.090909

false

0

0.060606

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0.166667

0.060606

0

null

0

1

0

1

0

null

0

5

b13e87312809ffcbbbdbaca3115dd900bd4ecb66

206

py

Python

fibonacci recursion/fibonacci.py

Neiva07/Algorithms

cc2b22d1f69f0af7b91a8326550e759abfba79c8

[ "MIT" ]

199

2019-12-01T01:23:34.000Z

2022-02-28T10:30:40.000Z

fibonacci recursion/fibonacci.py

Neiva07/Algorithms

cc2b22d1f69f0af7b91a8326550e759abfba79c8

[ "MIT" ]

35

2020-06-08T17:59:22.000Z

2021-11-11T04:00:29.000Z

fibonacci recursion/fibonacci.py

Neiva07/Algorithms

cc2b22d1f69f0af7b91a8326550e759abfba79c8

[ "MIT" ]

106

2020-02-05T01:28:19.000Z

2022-03-11T05:38:54.000Z

def iter(n, prev, curr): if n == 0: return curr return iter(n-1, curr, prev + curr) def fibonacci(n): return iter(n, 1, 0) if __name__ == '__main__': print(fibonacci(int(input())))

20.6

39

0.582524

32

206

3.5

0.46875

0.133929

0.196429

0.214286

0

0.025974

0.252427

206

10

40

20.6

0.701299

0

0.038647

0

1

0.25

false

0

0.125

0.625

0.125

0

null

0

1

0

null

0

1

0

1

0

5

b14b35e1ca9f953da33080d72cc08cb6529f4052

141

py

Python

DataFlowPipeline/src/tweetpipesupreme/language/models/__init__.py

lauri-lehtovaara/tweet-pipe-supreme

d3aed99bab0c4fe5f106afc45c744d9af7f71acf

[ "MIT" ]

null

DataFlowPipeline/src/tweetpipesupreme/language/models/__init__.py

lauri-lehtovaara/tweet-pipe-supreme

d3aed99bab0c4fe5f106afc45c744d9af7f71acf

[ "MIT" ]

null

DataFlowPipeline/src/tweetpipesupreme/language/models/__init__.py

lauri-lehtovaara/tweet-pipe-supreme

d3aed99bab0c4fe5f106afc45c744d9af7f71acf

[ "MIT" ]

null

"""Model for language detection DoFn""" from .base import BaseModel from .dummy import DummyModel from .fasttext import FastTextLid176Model

23.5

41

0.808511

17

141

6.705882

0.764706

0

0.02439

0.12766

141

5

42

28.2

0.902439

0.234043

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b15a4a883f6d326ca9b9502323237850c950080b

47

py

Python

torchlambda/subcommands/__init__.py

medric49/torchlambda

3122c4366fe629c911d67b2ec4fc22e50fd2f981

[ "MIT" ]

104

2020-03-16T21:40:55.000Z

2022-02-03T19:09:43.000Z

torchlambda/subcommands/__init__.py

medric49/torchlambda

3122c4366fe629c911d67b2ec4fc22e50fd2f981

[ "MIT" ]

16

2020-04-06T20:59:57.000Z

2021-07-15T04:30:55.000Z

torchlambda/subcommands/__init__.py

medric49/torchlambda

3122c4366fe629c911d67b2ec4fc22e50fd2f981

[ "MIT" ]

5

2020-04-06T06:24:35.000Z

2021-03-17T15:21:34.000Z

from . import build, layer, settings, template

23.5

46

0.765957

6

47

6

1

0

0.148936

47

1

47

0.9

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

b17d1308a2ecd542481b8999755846e7356cb3f3

67

py

Python

modules/__init__.py

nishathussain/ssd.pytorch

6547e7522b4f0fdc9b6d12a58045023a95195cb0

[ "MIT" ]

2

2020-10-24T09:57:42.000Z

2021-11-11T01:20:08.000Z

ssd/nn/__init__.py

Guillem96/ssd-pytorch

ffbb64d60c6e72c8126c2943f46b0e17298c8f81

[ "MIT" ]

null

ssd/nn/__init__.py

Guillem96/ssd-pytorch

ffbb64d60c6e72c8126c2943f46b0e17298c8f81

[ "MIT" ]

2

2019-12-17T11:22:28.000Z

2020-11-17T14:04:33.000Z

from .l2norm import L2Norm from .multibox_loss import MultiBoxLoss

22.333333

39

0.850746

9

67

6.222222

0.666667

0

0.033898

0.119403

67

2

40

33.5

0.915254

0

1

0

true

0

1

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1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

5

b19dfae497571fc1953d2f18748c7f36fa5785ca

63

py

Python

src/ecr/__init__.py

eXceediDeaL/edl-coderunner

52f7eedd0727b8a428b61640cd9fad33c083d0fc

[ "Apache-2.0" ]

1

2018-11-18T09:30:11.000Z

src/ecr/__init__.py

eXceediDeaL/edl-coderunner

52f7eedd0727b8a428b61640cd9fad33c083d0fc

[ "Apache-2.0" ]

6

2018-11-23T10:44:58.000Z

2018-12-04T03:44:00.000Z

src/ecr/__init__.py

eXceediDeaL/edl-coderunner

52f7eedd0727b8a428b61640cd9fad33c083d0fc

[ "Apache-2.0" ]

null

import enum from . import core __version__ = core.__version__

12.6

30

0.793651

8

63

5.25

0.625

0.52381

0

0.15873

63

4

31

15.75

0.792453

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

490ccf5c3a3b7949e590e5dde8e440319a8b6d22

40

py

Python

ibeam/__init__.py

f-hj/ibeam

d85971887936b3edd7357ba1b5ff743f9da4cf9a

[ "Apache-2.0" ]

null

ibeam/__init__.py

f-hj/ibeam

d85971887936b3edd7357ba1b5ff743f9da4cf9a

[ "Apache-2.0" ]

null

ibeam/__init__.py

f-hj/ibeam

d85971887936b3edd7357ba1b5ff743f9da4cf9a

[ "Apache-2.0" ]

null

import ibeam.config config.initialize()

13.333333

19

0.825

5

40

6.6

0.8

0

0.075

40

2

20

0.891892

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

4911df25b0f048d6fb141100034928addd96e13b

115

py

Python

HTTPServer/index.py

MarcPartensky/Python-2020

1a4ef2edfea6efb353249d5e32c06b230b293c62

[ "MIT" ]

1

2020-09-02T10:41:49.000Z

HTTPServer/index.py

MarcPartensky/Python-2020

1a4ef2edfea6efb353249d5e32c06b230b293c62

[ "MIT" ]

null

HTTPServer/index.py

MarcPartensky/Python-2020

1a4ef2edfea6efb353249d5e32c06b230b293c62

[ "MIT" ]

null

#!/usr/bin/env python #coding:utf-8 import cgi print("Content-type: text/html; charset=utf-8\n") print("Bonjour")

16.428571

49

0.713043

20

115

4.1

0.85

0.097561

0

0.019048

0.086957

115

6

50

19.166667

0.761905

0.278261

0

0.580247

0

1

0

true

0

0.333333

0

0.333333

0.666667

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

491d4249aa4a0877a6755edbc2ad8e892bebe8a2

138

py

Python

pyborot/lib/controllers/__init__.py

quocdat32461997/borot

5622267cd59b8f1b87ffbacb39f7b120ebb98a12

[ "MIT" ]

1

2020-11-01T06:08:40.000Z

pyborot/lib/controllers/__init__.py

quocdat32461997/borot

5622267cd59b8f1b87ffbacb39f7b120ebb98a12

[ "MIT" ]

1

2020-10-29T08:07:46.000Z

pyborot/lib/controllers/__init__.py

quocdat32461997/borot

5622267cd59b8f1b87ffbacb39f7b120ebb98a12

[ "MIT" ]

null

# controllers from .initialization import connect2db from .routing import * from .user_execution import * from .agent_execution import *

19.714286

38

0.804348

16

138

6.8125

0.5625

0.183486

0

0.008403

0.137681

138

6

39

23

0.907563

0.07971

0

1

0

true

0

1

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1

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1

0

null

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1

0

null

0

1

0

1

0

1

0

5

49254f2d363e1d7182db499408452910b761d4d6

34

py

Python

lanedet/models/net/__init__.py

ztjsw/lanedet

c957e1f70695e39063231612637e22fcad2769f5

[ "Apache-2.0" ]

1

2021-05-22T09:36:17.000Z

lanedet/models/net/__init__.py

ztjsw/lanedet

c957e1f70695e39063231612637e22fcad2769f5

[ "Apache-2.0" ]

null

lanedet/models/net/__init__.py

ztjsw/lanedet

c957e1f70695e39063231612637e22fcad2769f5

[ "Apache-2.0" ]

null

from .segmentor import Segmentor

17

33

0.823529

4

34

7

0.75

0

0.147059

34

1

34

0.965517

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

49328934f25be0c76a850197e7ac9c6cab835432

149

py

Python

champ/__init__.py

sgherbst/champ

e2e9b7edb117ce45828ba1542e26870b41e81a66

[ "MIT" ]

2

2020-07-08T09:23:32.000Z

2022-01-21T09:23:43.000Z

champ/__init__.py

sgherbst/champ

e2e9b7edb117ce45828ba1542e26870b41e81a66

[ "MIT" ]

null

champ/__init__.py

sgherbst/champ

e2e9b7edb117ce45828ba1542e26870b41e81a66

[ "MIT" ]

1

2020-10-09T22:03:36.000Z

from .s4p import s4p_to_tf from .imp import tf_to_imp from .step import imp_to_step from .pulse import step_to_pulse, center_pulse, get_pulse_coeffs

29.8

64

0.838926

29

149

3.931034

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0

0.015267

0.120805

149

4

65

37.25

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1

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true

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1

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null

0

1

0

1

0

1

0

5

493c4400733ce6fbf0ff984ca7d55c8d25d270fe

196

py

Python

extractor/aextractor.py

dev-ejc/automated_financial_analysis

d68f842a5cbd54509e6f0df3ae7cc52d520f76eb

[ "MIT" ]

2

2021-08-12T03:56:34.000Z

2021-08-14T18:18:28.000Z

extractor/aextractor.py

dev-ejc/automated_financial_analysis

d68f842a5cbd54509e6f0df3ae7cc52d520f76eb

[ "MIT" ]

null

extractor/aextractor.py

dev-ejc/automated_financial_analysis

d68f842a5cbd54509e6f0df3ae7cc52d520f76eb

[ "MIT" ]

null

from extractor.iextractor import IExtractor from requests import get class AExtractor(IExtractor): def extract(self,api,params): return requests.get("https://github.com/dev-ejc/")

32.666667

58

0.739796

25

196

5.8

0.76

0

0.153061

196

6

58

32.666667

0.873494

0

0.137056

0

1

0.2

false

0

0.4

0.2

1

0

1

0

null

0

1

0

null

0

1

0

5

4978cf9faa84b0ab38de5b1f0d6a1f0a053adf93

112

py

Python

vnpy/api/xtp/__init__.py

hzypage/TestPy

2646bbd07b90c8a1795001a6712e1d5d1aabda90

[ "MIT" ]

18

2019-02-21T05:42:41.000Z

2022-03-31T10:17:51.000Z

vnpy/api/xtp/__init__.py

conglin/vnpy

4f0a07bddf81ec87c1e00cefcc92678e2b99b6b4

[ "MIT" ]

null

vnpy/api/xtp/__init__.py

conglin/vnpy

4f0a07bddf81ec87c1e00cefcc92678e2b99b6b4

[ "MIT" ]

5

2017-12-20T09:57:17.000Z

2021-08-01T19:47:14.000Z

# encoding: UTF-8 from vnxtpquote import QuoteApi from vnxtptrader import TraderApi from xtp_data_type import *

22.4

33

0.830357

16

112

5.6875

0.75

0

0.010309

0.133929

112

5

34

22.4

0.927835

0.133929

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b8d0d16533cdfaed475152261979dc4fc17dad13

2,378

py

Python

scuole/campuses/migrations/0009_auto_20190808_2208.py

texastribune/scuole

8ab316ee50ef0d8e71b94b50dc889d10c6e83412

[ "MIT" ]

1

2019-03-12T04:30:02.000Z

scuole/campuses/migrations/0009_auto_20190808_2208.py

texastribune/scuole

8ab316ee50ef0d8e71b94b50dc889d10c6e83412

[ "MIT" ]

616

2017-08-18T21:15:39.000Z

2022-03-25T11:17:10.000Z

scuole/campuses/migrations/0009_auto_20190808_2208.py

texastribune/scuole

8ab316ee50ef0d8e71b94b50dc889d10c6e83412

[ "MIT" ]

null

# Generated by Django 2.2.4 on 2019-08-08 22:08 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('campuses', '0008_auto_20190328_1526'), ] operations = [ migrations.AlterField( model_name='campusstats', name='accountability_rating', field=models.CharField(blank=True, choices=[('M', 'Met standard'), ('A', 'Met alternative standard'), ('T', 'Met alternative standard'), ('I', 'Improvement required'), ('X', 'Not rated'), ('Z', 'Not rated'), ('Q', 'Not rated (data integrity issue)'), ('T', 'Not rated (Annexed)'), ('H', 'Not rated (Harvey provision)'), ('', None)], default='', max_length=1, verbose_name='Accountability rating'), ), migrations.AlterField( model_name='campusstats', name='closing_the_gaps_rating', field=models.CharField(blank=True, choices=[('M', 'Met standard'), ('A', 'Met alternative standard'), ('T', 'Met alternative standard'), ('I', 'Improvement required'), ('X', 'Not rated'), ('Z', 'Not rated'), ('Q', 'Not rated (data integrity issue)'), ('T', 'Not rated (Annexed)'), ('H', 'Not rated (Harvey provision)'), ('', None)], default='', max_length=1, verbose_name='Closing the gaps rating'), ), migrations.AlterField( model_name='campusstats', name='school_progress_rating', field=models.CharField(blank=True, choices=[('M', 'Met standard'), ('A', 'Met alternative standard'), ('T', 'Met alternative standard'), ('I', 'Improvement required'), ('X', 'Not rated'), ('Z', 'Not rated'), ('Q', 'Not rated (data integrity issue)'), ('T', 'Not rated (Annexed)'), ('H', 'Not rated (Harvey provision)'), ('', None)], default='', max_length=1, verbose_name='School progress rating'), ), migrations.AlterField( model_name='campusstats', name='student_achievement_rating', field=models.CharField(blank=True, choices=[('M', 'Met standard'), ('A', 'Met alternative standard'), ('T', 'Met alternative standard'), ('I', 'Improvement required'), ('X', 'Not rated'), ('Z', 'Not rated'), ('Q', 'Not rated (data integrity issue)'), ('T', 'Not rated (Annexed)'), ('H', 'Not rated (Harvey provision)'), ('', None)], default='', max_length=1, verbose_name='Student achievement rating'), ), ]

69.941176

414

0.606392

269

2,378

5.275093

0.252788

0.112755

0.124031

0.081748

0.824524

0.804792

0.773784

0.668076

0

0.018154

0.189235

2,378

33

415

72.060606

0.717842

0.018923

0

0.444444

1

0

0.430287

0.049335

0

1

0

false

0

0.037037

0

0.148148

0

null

0

1

0

1

0

1

0

null

0

5

b8d9d7fcb20c83efa7ce518435a74dde2d37c10e

42

py

Python

bobsled/exceptions.py

civic-eagle/bobsled

b9700f937a729713356d3532c34a6c1e847d2094

[ "MIT" ]

8

2019-10-30T18:41:52.000Z

2022-01-31T03:42:46.000Z

bobsled/exceptions.py

civic-eagle/bobsled

b9700f937a729713356d3532c34a6c1e847d2094

[ "MIT" ]

151

2019-07-31T19:14:19.000Z

2021-12-03T17:35:23.000Z

bobsled/exceptions.py

openstates/bobsled

1ff57eae2124c8eeb7cc04fc64cba1da18ed8493

[ "MIT" ]

1

2021-01-22T04:13:32.000Z

class AlreadyRunning(Exception): pass

14

32

0.761905

4

42

8

1

0

0.166667

42

2

33

21

0.914286

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

b8fb04239b59300b05afb17978083d264744216a

164

py

Python

lib/optimizer/optimizer/ensemble/__init__.py

spaenigs/ensemble-performance

f2d6f61e71a4369b73d01cb58d3d05541609e78d

[ "MIT" ]

1

2021-09-29T08:21:35.000Z

lib/optimizer/optimizer/ensemble/__init__.py

spaenigs/ensemble-performance

f2d6f61e71a4369b73d01cb58d3d05541609e78d

[ "MIT" ]

null

lib/optimizer/optimizer/ensemble/__init__.py

spaenigs/ensemble-performance

f2d6f61e71a4369b73d01cb58d3d05541609e78d

[ "MIT" ]

null

from ._stacking import StackingClassifier from ._voting import VotingClassifier from ._forest import RandomForestClassifier from .diversity import kappa_error_plot

32.8

43

0.878049

18

164

7.722222

0.666667

0

0.097561

164

5

44

32.8

0.939189

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

772637f0aa1c9ae40b7609b1e972e115c5508a47

58,329

py

Python

etl/parsers/etw/Microsoft_AppV_Client.py

IMULMUL/etl-parser

76b7c046866ce0469cd129ee3f7bb3799b34e271

[ "Apache-2.0" ]

104

2020-03-04T14:31:31.000Z

2022-03-28T02:59:36.000Z

etl/parsers/etw/Microsoft_AppV_Client.py

IMULMUL/etl-parser

76b7c046866ce0469cd129ee3f7bb3799b34e271

[ "Apache-2.0" ]

7

2020-04-20T09:18:39.000Z

2022-03-19T17:06:19.000Z

etl/parsers/etw/Microsoft_AppV_Client.py

IMULMUL/etl-parser

76b7c046866ce0469cd129ee3f7bb3799b34e271

[ "Apache-2.0" ]

16

2020-03-05T18:55:59.000Z

2022-03-01T10:19:28.000Z

# -*- coding: utf-8 -*- """ Microsoft-AppV-Client GUID : e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245 """ from construct import Int8sl, Int8ul, Int16ul, Int16sl, Int32sl, Int32ul, Int64sl, Int64ul, Bytes, Double, Float32l, Struct from etl.utils import WString, CString, SystemTime, Guid from etl.dtyp import Sid from etl.parsers.etw.core import Etw, declare, guid @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=3, version=1) class Microsoft_AppV_Client_3_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4, version=1) class Microsoft_AppV_Client_4_1(Etw): pattern = Struct( "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=5, version=1) class Microsoft_AppV_Client_5_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6, version=1) class Microsoft_AppV_Client_6_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=7, version=1) class Microsoft_AppV_Client_7_1(Etw): pattern = Struct( "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8, version=1) class Microsoft_AppV_Client_8_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=9, version=1) class Microsoft_AppV_Client_9_1(Etw): pattern = Struct( "CurrentImpersonationLevel" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11, version=1) class Microsoft_AppV_Client_11_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=12, version=1) class Microsoft_AppV_Client_12_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13, version=0) class Microsoft_AppV_Client_13_0(Etw): pattern = Struct( "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=16, version=1) class Microsoft_AppV_Client_16_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17, version=1) class Microsoft_AppV_Client_17_1(Etw): pattern = Struct( "StringParam1" / WString, "StringParam2" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=101, version=1) class Microsoft_AppV_Client_101_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=102, version=1) class Microsoft_AppV_Client_102_1(Etw): pattern = Struct( "Name" / WString, "HResult" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1001, version=1) class Microsoft_AppV_Client_1001_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1002, version=1) class Microsoft_AppV_Client_1002_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "Folder" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1003, version=1) class Microsoft_AppV_Client_1003_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1004, version=1) class Microsoft_AppV_Client_1004_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1005, version=1) class Microsoft_AppV_Client_1005_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1006, version=1) class Microsoft_AppV_Client_1006_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1007, version=1) class Microsoft_AppV_Client_1007_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1008, version=1) class Microsoft_AppV_Client_1008_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "Folder" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1009, version=1) class Microsoft_AppV_Client_1009_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1010, version=1) class Microsoft_AppV_Client_1010_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1011, version=1) class Microsoft_AppV_Client_1011_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1012, version=1) class Microsoft_AppV_Client_1012_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1013, version=1) class Microsoft_AppV_Client_1013_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1014, version=1) class Microsoft_AppV_Client_1014_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1015, version=1) class Microsoft_AppV_Client_1015_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1016, version=1) class Microsoft_AppV_Client_1016_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1017, version=1) class Microsoft_AppV_Client_1017_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1018, version=1) class Microsoft_AppV_Client_1018_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1019, version=1) class Microsoft_AppV_Client_1019_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1020, version=1) class Microsoft_AppV_Client_1020_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1021, version=1) class Microsoft_AppV_Client_1021_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1022, version=1) class Microsoft_AppV_Client_1022_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1023, version=1) class Microsoft_AppV_Client_1023_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1024, version=1) class Microsoft_AppV_Client_1024_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1025, version=1) class Microsoft_AppV_Client_1025_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1026, version=1) class Microsoft_AppV_Client_1026_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1027, version=1) class Microsoft_AppV_Client_1027_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1028, version=1) class Microsoft_AppV_Client_1028_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1029, version=1) class Microsoft_AppV_Client_1029_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1030, version=1) class Microsoft_AppV_Client_1030_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1031, version=1) class Microsoft_AppV_Client_1031_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1032, version=1) class Microsoft_AppV_Client_1032_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1033, version=1) class Microsoft_AppV_Client_1033_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1034, version=1) class Microsoft_AppV_Client_1034_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1035, version=1) class Microsoft_AppV_Client_1035_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1036, version=1) class Microsoft_AppV_Client_1036_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1037, version=1) class Microsoft_AppV_Client_1037_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1038, version=1) class Microsoft_AppV_Client_1038_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1039, version=1) class Microsoft_AppV_Client_1039_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1040, version=1) class Microsoft_AppV_Client_1040_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1041, version=1) class Microsoft_AppV_Client_1041_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1042, version=1) class Microsoft_AppV_Client_1042_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1043, version=1) class Microsoft_AppV_Client_1043_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1044, version=1) class Microsoft_AppV_Client_1044_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "GroupVersion" / Guid, "Package" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1045, version=1) class Microsoft_AppV_Client_1045_1(Etw): pattern = Struct( "Id" / Guid, "Version" / Guid, "Path" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1046, version=1) class Microsoft_AppV_Client_1046_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1047, version=1) class Microsoft_AppV_Client_1047_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1048, version=1) class Microsoft_AppV_Client_1048_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "GroupVersion" / Guid, "Package" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1049, version=1) class Microsoft_AppV_Client_1049_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1050, version=1) class Microsoft_AppV_Client_1050_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1051, version=1) class Microsoft_AppV_Client_1051_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1052, version=1) class Microsoft_AppV_Client_1052_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1053, version=1) class Microsoft_AppV_Client_1053_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1054, version=1) class Microsoft_AppV_Client_1054_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1055, version=1) class Microsoft_AppV_Client_1055_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1056, version=1) class Microsoft_AppV_Client_1056_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1057, version=1) class Microsoft_AppV_Client_1057_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1058, version=1) class Microsoft_AppV_Client_1058_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1059, version=1) class Microsoft_AppV_Client_1059_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1060, version=1) class Microsoft_AppV_Client_1060_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1061, version=1) class Microsoft_AppV_Client_1061_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1062, version=1) class Microsoft_AppV_Client_1062_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1063, version=1) class Microsoft_AppV_Client_1063_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1064, version=1) class Microsoft_AppV_Client_1064_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1065, version=1) class Microsoft_AppV_Client_1065_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1066, version=1) class Microsoft_AppV_Client_1066_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1067, version=1) class Microsoft_AppV_Client_1067_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1068, version=1) class Microsoft_AppV_Client_1068_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1069, version=1) class Microsoft_AppV_Client_1069_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1070, version=1) class Microsoft_AppV_Client_1070_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1071, version=1) class Microsoft_AppV_Client_1071_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1072, version=1) class Microsoft_AppV_Client_1072_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1073, version=1) class Microsoft_AppV_Client_1073_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1074, version=1) class Microsoft_AppV_Client_1074_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1075, version=1) class Microsoft_AppV_Client_1075_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ActivityID" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1076, version=1) class Microsoft_AppV_Client_1076_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1077, version=1) class Microsoft_AppV_Client_1077_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1078, version=1) class Microsoft_AppV_Client_1078_1(Etw): pattern = Struct( "PackageId" / Guid, "PackageVersion" / Guid, "GroupId" / Guid, "GroupVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1079, version=1) class Microsoft_AppV_Client_1079_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1080, version=1) class Microsoft_AppV_Client_1080_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1082, version=1) class Microsoft_AppV_Client_1082_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=1083, version=1) class Microsoft_AppV_Client_1083_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2001, version=1) class Microsoft_AppV_Client_2001_1(Etw): pattern = Struct( "LastFolder" / WString, "ReqFolder" / WString, "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2002, version=1) class Microsoft_AppV_Client_2002_1(Etw): pattern = Struct( "LastFolder" / WString, "ReqFolder" / WString, "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2003, version=1) class Microsoft_AppV_Client_2003_1(Etw): pattern = Struct( "LastFolder" / WString, "ReqFolder" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2004, version=1) class Microsoft_AppV_Client_2004_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2005, version=1) class Microsoft_AppV_Client_2005_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=2006, version=1) class Microsoft_AppV_Client_2006_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=3001, version=1) class Microsoft_AppV_Client_3001_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=3002, version=1) class Microsoft_AppV_Client_3002_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4001, version=1) class Microsoft_AppV_Client_4001_1(Etw): pattern = Struct( "ScriptScope" / Int32ul, "EventType" / WString, "CommandLine" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4002, version=1) class Microsoft_AppV_Client_4002_1(Etw): pattern = Struct( "Timeout" / Int64ul, "ScriptScope" / Int32ul, "EventType" / WString, "CommandLine" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4004, version=1) class Microsoft_AppV_Client_4004_1(Etw): pattern = Struct( "ScriptScope" / Int32ul, "Package" / Guid, "EventType" / WString, "UserSid" / WString, "CommandLine" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4005, version=1) class Microsoft_AppV_Client_4005_1(Etw): pattern = Struct( "ScriptScope" / Int32ul, "Package" / Guid, "EventType" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4006, version=1) class Microsoft_AppV_Client_4006_1(Etw): pattern = Struct( "tGuid" / Guid, "tString" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4007, version=1) class Microsoft_AppV_Client_4007_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4008, version=1) class Microsoft_AppV_Client_4008_1(Etw): pattern = Struct( "Timeout" / Int64ul, "ScriptScope" / Int32ul, "EventType" / WString, "CommandLine" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4009, version=1) class Microsoft_AppV_Client_4009_1(Etw): pattern = Struct( "ScriptScope" / Int32ul, "EventType" / WString, "CommandLine" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=4010, version=1) class Microsoft_AppV_Client_4010_1(Etw): pattern = Struct( "ScriptScope" / Int32ul, "EventType" / WString, "CommandLine" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=5003, version=1) class Microsoft_AppV_Client_5003_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6001, version=1) class Microsoft_AppV_Client_6001_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6002, version=1) class Microsoft_AppV_Client_6002_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6006, version=1) class Microsoft_AppV_Client_6006_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6007, version=1) class Microsoft_AppV_Client_6007_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6008, version=1) class Microsoft_AppV_Client_6008_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6009, version=1) class Microsoft_AppV_Client_6009_1(Etw): pattern = Struct( "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6010, version=1) class Microsoft_AppV_Client_6010_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6011, version=1) class Microsoft_AppV_Client_6011_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6012, version=1) class Microsoft_AppV_Client_6012_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=6015, version=1) class Microsoft_AppV_Client_6015_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=7001, version=1) class Microsoft_AppV_Client_7001_1(Etw): pattern = Struct( "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8001, version=1) class Microsoft_AppV_Client_8001_1(Etw): pattern = Struct( "Error" / Int32ul, "Reason" / WString, "line" / Int64sl, "column" / Int64sl, "offset" / Int64sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8002, version=1) class Microsoft_AppV_Client_8002_1(Etw): pattern = Struct( "Error" / Int32sl, "Reason" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8003, version=1) class Microsoft_AppV_Client_8003_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8004, version=1) class Microsoft_AppV_Client_8004_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8005, version=1) class Microsoft_AppV_Client_8005_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8006, version=1) class Microsoft_AppV_Client_8006_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8007, version=1) class Microsoft_AppV_Client_8007_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8008, version=1) class Microsoft_AppV_Client_8008_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8009, version=1) class Microsoft_AppV_Client_8009_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8010, version=1) class Microsoft_AppV_Client_8010_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8011, version=1) class Microsoft_AppV_Client_8011_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8012, version=1) class Microsoft_AppV_Client_8012_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "GroupVersion" / Guid, "Package" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8013, version=1) class Microsoft_AppV_Client_8013_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul, "Sid" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8014, version=1) class Microsoft_AppV_Client_8014_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul, "Sid" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8015, version=1) class Microsoft_AppV_Client_8015_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=8016, version=1) class Microsoft_AppV_Client_8016_1(Etw): pattern = Struct( "tString" / WString, "PackageId" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=9001, version=1) class Microsoft_AppV_Client_9001_1(Etw): pattern = Struct( "Command" / WString, "ErrorWarning" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=9002, version=1) class Microsoft_AppV_Client_9002_1(Etw): pattern = Struct( "Command" / WString, "ErrorWarning" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=9009, version=1) class Microsoft_AppV_Client_9009_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=9010, version=1) class Microsoft_AppV_Client_9010_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=10001, version=1) class Microsoft_AppV_Client_10001_1(Etw): pattern = Struct( "PID" / Int32ul, "Package" / Guid, "Version" / Guid, "SubsystemName" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=10002, version=1) class Microsoft_AppV_Client_10002_1(Etw): pattern = Struct( "Value" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11002, version=1) class Microsoft_AppV_Client_11002_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11003, version=1) class Microsoft_AppV_Client_11003_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11004, version=1) class Microsoft_AppV_Client_11004_1(Etw): pattern = Struct( "Package" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11005, version=1) class Microsoft_AppV_Client_11005_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11006, version=1) class Microsoft_AppV_Client_11006_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11007, version=1) class Microsoft_AppV_Client_11007_1(Etw): pattern = Struct( "Package" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11008, version=1) class Microsoft_AppV_Client_11008_1(Etw): pattern = Struct( "Package" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11009, version=1) class Microsoft_AppV_Client_11009_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11010, version=1) class Microsoft_AppV_Client_11010_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11011, version=1) class Microsoft_AppV_Client_11011_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=11012, version=1) class Microsoft_AppV_Client_11012_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=12001, version=1) class Microsoft_AppV_Client_12001_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13001, version=1) class Microsoft_AppV_Client_13001_1(Etw): pattern = Struct( "Package" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13002, version=1) class Microsoft_AppV_Client_13002_1(Etw): pattern = Struct( "Package" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13003, version=1) class Microsoft_AppV_Client_13003_1(Etw): pattern = Struct( "ProcessName" / WString, "Package" / Guid, "Pid" / Int32ul, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13004, version=1) class Microsoft_AppV_Client_13004_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13005, version=1) class Microsoft_AppV_Client_13005_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13006, version=1) class Microsoft_AppV_Client_13006_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13007, version=1) class Microsoft_AppV_Client_13007_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13008, version=1) class Microsoft_AppV_Client_13008_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul, "ProcessID" / Int64ul, "PackageId" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13009, version=1) class Microsoft_AppV_Client_13009_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13010, version=1) class Microsoft_AppV_Client_13010_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13011, version=1) class Microsoft_AppV_Client_13011_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=13012, version=1) class Microsoft_AppV_Client_13012_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14005, version=1) class Microsoft_AppV_Client_14005_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14010, version=1) class Microsoft_AppV_Client_14010_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "Folder" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14011, version=1) class Microsoft_AppV_Client_14011_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14012, version=1) class Microsoft_AppV_Client_14012_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14013, version=1) class Microsoft_AppV_Client_14013_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14014, version=1) class Microsoft_AppV_Client_14014_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14015, version=1) class Microsoft_AppV_Client_14015_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "Folder" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14016, version=1) class Microsoft_AppV_Client_14016_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14017, version=1) class Microsoft_AppV_Client_14017_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "Hresult" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14018, version=1) class Microsoft_AppV_Client_14018_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14019, version=1) class Microsoft_AppV_Client_14019_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14020, version=1) class Microsoft_AppV_Client_14020_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14021, version=1) class Microsoft_AppV_Client_14021_1(Etw): pattern = Struct( "tGuid" / Guid, "tString" / WString, "HResult" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14022, version=1) class Microsoft_AppV_Client_14022_1(Etw): pattern = Struct( "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14023, version=1) class Microsoft_AppV_Client_14023_1(Etw): pattern = Struct( "File" / WString, "Pid" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14024, version=1) class Microsoft_AppV_Client_14024_1(Etw): pattern = Struct( "File" / WString, "Pid" / Int64ul, "Sid" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=14029, version=1) class Microsoft_AppV_Client_14029_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=15001, version=1) class Microsoft_AppV_Client_15001_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=15002, version=1) class Microsoft_AppV_Client_15002_1(Etw): pattern = Struct( "HResult" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=15003, version=1) class Microsoft_AppV_Client_15003_1(Etw): pattern = Struct( "VirtualEnvironmentId" / Guid, "VirtualEnvironmentVersion" / Guid, "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=16001, version=1) class Microsoft_AppV_Client_16001_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=16002, version=1) class Microsoft_AppV_Client_16002_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=16003, version=1) class Microsoft_AppV_Client_16003_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=16004, version=1) class Microsoft_AppV_Client_16004_1(Etw): pattern = Struct( "PackageId" / Guid, "PackageVersion" / Guid, "GroupId" / Guid, "GroupVersion" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17001, version=1) class Microsoft_AppV_Client_17001_1(Etw): pattern = Struct( "Item" / WString, "Error" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17002, version=1) class Microsoft_AppV_Client_17002_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17003, version=1) class Microsoft_AppV_Client_17003_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17004, version=1) class Microsoft_AppV_Client_17004_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17006, version=1) class Microsoft_AppV_Client_17006_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17007, version=1) class Microsoft_AppV_Client_17007_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17008, version=1) class Microsoft_AppV_Client_17008_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17009, version=1) class Microsoft_AppV_Client_17009_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17010, version=1) class Microsoft_AppV_Client_17010_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17011, version=1) class Microsoft_AppV_Client_17011_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=17012, version=1) class Microsoft_AppV_Client_17012_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18001, version=1) class Microsoft_AppV_Client_18001_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18002, version=1) class Microsoft_AppV_Client_18002_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18003, version=1) class Microsoft_AppV_Client_18003_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18004, version=1) class Microsoft_AppV_Client_18004_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18005, version=1) class Microsoft_AppV_Client_18005_1(Etw): pattern = Struct( "StringParam1" / WString, "StringParam2" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=18006, version=1) class Microsoft_AppV_Client_18006_1(Etw): pattern = Struct( "ConnectionGroup" / Guid, "GroupVersion" / Guid, "Package" / Guid, "PackageVersion" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19001, version=1) class Microsoft_AppV_Client_19001_1(Etw): pattern = Struct( "String" / WString, "Flag" / Int8ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19002, version=1) class Microsoft_AppV_Client_19002_1(Etw): pattern = Struct( "String" / WString, "Flag" / Int8ul, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19010, version=1) class Microsoft_AppV_Client_19010_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19011, version=1) class Microsoft_AppV_Client_19011_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19101, version=1) class Microsoft_AppV_Client_19101_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19102, version=1) class Microsoft_AppV_Client_19102_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19103, version=1) class Microsoft_AppV_Client_19103_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19104, version=1) class Microsoft_AppV_Client_19104_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19105, version=1) class Microsoft_AppV_Client_19105_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19106, version=1) class Microsoft_AppV_Client_19106_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19107, version=1) class Microsoft_AppV_Client_19107_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19108, version=1) class Microsoft_AppV_Client_19108_1(Etw): pattern = Struct( "Guid1" / Guid, "Guid2" / Guid, "Guid3" / Guid ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19201, version=1) class Microsoft_AppV_Client_19201_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19202, version=1) class Microsoft_AppV_Client_19202_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19203, version=1) class Microsoft_AppV_Client_19203_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19204, version=1) class Microsoft_AppV_Client_19204_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19205, version=1) class Microsoft_AppV_Client_19205_1(Etw): pattern = Struct( "StringParam" / WString, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19301, version=1) class Microsoft_AppV_Client_19301_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19302, version=1) class Microsoft_AppV_Client_19302_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19303, version=1) class Microsoft_AppV_Client_19303_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19304, version=1) class Microsoft_AppV_Client_19304_1(Etw): pattern = Struct( "Package" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19401, version=1) class Microsoft_AppV_Client_19401_1(Etw): pattern = Struct( "Value" / Int32ul, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19402, version=1) class Microsoft_AppV_Client_19402_1(Etw): pattern = Struct( "Value" / Int32ul, "String" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19403, version=1) class Microsoft_AppV_Client_19403_1(Etw): pattern = Struct( "Value" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19404, version=1) class Microsoft_AppV_Client_19404_1(Etw): pattern = Struct( "Value" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19405, version=1) class Microsoft_AppV_Client_19405_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19406, version=1) class Microsoft_AppV_Client_19406_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19407, version=1) class Microsoft_AppV_Client_19407_1(Etw): pattern = Struct( "Value1" / Int32ul, "Value2" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19408, version=1) class Microsoft_AppV_Client_19408_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19501, version=1) class Microsoft_AppV_Client_19501_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19502, version=1) class Microsoft_AppV_Client_19502_1(Etw): pattern = Struct( "Item" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19801, version=1) class Microsoft_AppV_Client_19801_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19802, version=1) class Microsoft_AppV_Client_19802_1(Etw): pattern = Struct( "String" / WString, "Flag1" / Int8ul, "Flag2" / Int8ul, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19803, version=1) class Microsoft_AppV_Client_19803_1(Etw): pattern = Struct( "String" / WString, "Flag1" / Int8ul, "Flag2" / Int8ul, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=19805, version=1) class Microsoft_AppV_Client_19805_1(Etw): pattern = Struct( "ErrorHigh" / Int64ul, "ErrorLow" / Int64ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=20001, version=1) class Microsoft_AppV_Client_20001_1(Etw): pattern = Struct( "PackageGroup" / Guid, "Version" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=20002, version=1) class Microsoft_AppV_Client_20002_1(Etw): pattern = Struct( "PackageId" / Guid, "PackageVersion" / Guid, "GroupId" / Guid, "GroupVersion" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=20101, version=1) class Microsoft_AppV_Client_20101_1(Etw): pattern = Struct( "PackageId" / Guid, "PackageVersion" / Guid, "GroupId" / Guid, "GroupVersion" / Guid, "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=21001, version=1) class Microsoft_AppV_Client_21001_1(Etw): pattern = Struct( "ErrorHigh" / Int32ul, "ErrorLow" / Int32ul ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=22001, version=1) class Microsoft_AppV_Client_22001_1(Etw): pattern = Struct( "Item1" / WString, "Item2" / WString ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=24001, version=1) class Microsoft_AppV_Client_24001_1(Etw): pattern = Struct( "Error" / Int32sl ) @declare(guid=guid("e4f68870-5ae8-4e5b-9ce7-ca9ed75b0245"), event_id=24002, version=1) class Microsoft_AppV_Client_24002_1(Etw): pattern = Struct( "Error" / Int32sl )

26.842614

123

0.660255

6,913

58,329

5.387241

0.050919

0.089012

0.130095

0.136942

0.92291

0.700849

0.691746

0

0.174092

0.203809

58,329

2,172

124

26.854972

0.627829

0.001509

0

0.5193

0

0.243148

0.157886

0

1

0

false

0

0.002413

0

0.308806

0

null

0

1

0

1

0

null

0

5

91f36ee293cf46072cbc367607a647e3b40445dc

2,422

py

Python

enot/pac_cache/cache.py

comtihon/valrus

d01c380348a18b67dbb73f429464b454165a7ec3

[ "Apache-2.0" ]

16

2018-02-14T00:22:41.000Z

2022-02-04T23:38:52.000Z

enot/pac_cache/cache.py

comtihon/valrus

d01c380348a18b67dbb73f429464b454165a7ec3

[ "Apache-2.0" ]

36

2017-04-26T20:15:23.000Z

2018-02-13T16:45:32.000Z

enot/pac_cache/cache.py

comtihon/valrus

d01c380348a18b67dbb73f429464b454165a7ec3

[ "Apache-2.0" ]

2

2019-02-14T07:57:12.000Z

2019-03-28T17:30:01.000Z

import tarfile from abc import ABCMeta, abstractmethod from enum import Enum from os.path import join from enot.pac_cache import Static from enot.packages.package import Package from enot.utils.file_utils import ensure_empty, copy_file from enot.utils.logger import info class CacheType(Enum): LOCAL = 'local' ENOT = 'enot' class Cache(metaclass=ABCMeta): def __init__(self, name, temp_dir, path, default_erlang: str, cache_type: CacheType): self._erlang_version = Static.get_erlang_version(default_erlang) self._temp_dir = temp_dir self._path = path self._name = name self._cache_type = cache_type @property def cache_type(self) -> CacheType: return self._cache_type @property def temp_dir(self) -> str: return self._temp_dir @property def path(self) -> str: return self._path @property def name(self) -> str: return self._name @property def erlang_version(self) -> str: return self._erlang_version @abstractmethod def exists(self, package: Package) -> bool: pass @abstractmethod def fetch_package(self, package: Package): # fetch package to system temp dir pass @abstractmethod def add_package(self, package: Package, rewrite=True) -> bool: # add package to cache pass @abstractmethod def get_versions(self, fullname: str) -> list: # get available package's versions pass @abstractmethod def get_erl_versions(self, fullname: str, version: str) -> list: # get available package's erlang versions pass # Take ep package archived file from package, extract it to temp dir # and update package's path to point to extracted dir def unpackage(self, package: Package): # TODO move me to package? use current dir + <something> instead of temp unpack_dir = join(self.temp_dir, package.fullname) enotpack = join(package.path, package.name + '.ep') ensure_empty(unpack_dir) info('Extract ' + enotpack) with tarfile.open(enotpack) as pack: pack.extractall(unpack_dir) package.path = unpack_dir # update path pointer copy_file(enotpack, join(unpack_dir, package.name + '.ep')) def get_package_path(self, package: Package) -> str or None: return join(package.fullname, package.git_vsn, self.erlang_version)

30.658228

116

0.678778

315

2,422

5.053968

0.273016

0.035176

0.056533

0.042714

0.03392

0

0.238233

2,422

78

117

31.051282

0.862873

0.138728

0

0.254237

0

0.011074

0

0.012821

0

1

0.220339

false

0.084746

0.135593

0.101695

0.525424

0

null

0

null

0

1

0

1

0

1

0

1

0

5

91ff4626d2377d5a843cc7f14a8d8faefb4d3cae

230

py

Python

src/icemac/addressbook/generations/evolve23.py

icemac/icemac.addressbook

6197e6e01da922feb100dd0943576523050cd703

[ "BSD-2-Clause" ]

1

2020-03-26T20:16:44.000Z

src/icemac/addressbook/generations/evolve23.py

icemac/icemac.addressbook

6197e6e01da922feb100dd0943576523050cd703

[ "BSD-2-Clause" ]

2

2020-02-21T13:04:23.000Z

2020-02-21T13:06:10.000Z

src/icemac/addressbook/generations/evolve23.py

icemac/icemac.addressbook

6197e6e01da922feb100dd0943576523050cd703

[ "BSD-2-Clause" ]

null

import icemac.addressbook.generations.utils def evolve(context): """Install update default preferences to new prefs structure.""" icemac.addressbook.generations.utils.update_address_book_infrastructure( context)

28.75

76

0.778261

25

230

7.04

0.76

0.193182

0.318182

0.375

0

0.13913

230

7

77

32.857143

0.888889

0.252174

0

1

0.25

false

0

0.25

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

5

62911b0bd434707d4173d1231f3ee83dde8b1d44

185

py

Python

easy/pangram.py

YANG007SUN/hackerrank_challenge

0c055c9e5129f1625fe86174435a89c141d256d6

[ "Apache-2.0" ]

null

easy/pangram.py

YANG007SUN/hackerrank_challenge

0c055c9e5129f1625fe86174435a89c141d256d6

[ "Apache-2.0" ]

null

easy/pangram.py

YANG007SUN/hackerrank_challenge

0c055c9e5129f1625fe86174435a89c141d256d6

[ "Apache-2.0" ]

null

# https://www.hackerrank.com/challenges/pangrams/problem?h_r=next-challenge&h_v=zen def pangrams(s): return (len(set(s.lower().replace(' ','')))==26 and 'pangram' or 'not pangram')

46.25

83

0.697297

29

185

4.37931

0.862069

0

0.011834

0.086486

185

4

84

46.25

0.739645

0.437838

0

0.184466

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

6553465fe8b1b9bfe63c155d2c7c02033388682d

218

py

Python

tests/test_general.py

Solstice-Short-Film/solstice-config

00fae932e9c46770479e25d11da58325a0444d81

[ "MIT" ]

null

tests/test_general.py

Solstice-Short-Film/solstice-config

00fae932e9c46770479e25d11da58325a0444d81

[ "MIT" ]

null

tests/test_general.py

Solstice-Short-Film/solstice-config

00fae932e9c46770479e25d11da58325a0444d81

[ "MIT" ]

null

#! /usr/bin/env python # -*- coding: utf-8 -*- """ Module that contains tests for solstice-config """ import pytest from solstice.config import __version__ def test_version(): assert __version__.get_version()

14.533333

46

0.711009

28

218

5.178571

0.785714

0.193103

0.275862

0

0.005464

0.16055

218

14

47

15.571429

0.786885

0.412844

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

5

65610ba43b36150793b9032d2cab0a4df900f007

381,674

py

Python

diana/classes/goatools/test_data/goids_GOATOOLS_Transient_Increase.py

quimaguirre/diana

930da0ea91ad87e354061af18db6c437a3318366

[ "MIT" ]

3

2019-07-11T05:32:13.000Z

2021-03-12T01:10:21.000Z

diana/classes/goatools/test_data/goids_GOATOOLS_Transient_Increase.py

quimaguirre/diana

930da0ea91ad87e354061af18db6c437a3318366

[ "MIT" ]

null

diana/classes/goatools/test_data/goids_GOATOOLS_Transient_Increase.py

quimaguirre/diana

930da0ea91ad87e354061af18db6c437a3318366

[ "MIT" ]

1

2019-02-12T13:45:42.000Z

"""GOATOOLS GOEA on 2015 Gjoneska data using go-basic.obo: fmt(1.2) rel(2017-01-12) 47,943 GO Terms""" # Created: 2017-01-13 import collections as cx nt_fields = [ "p_uncorrected", "study_count", "study_n", "namespace", "p_fdr_bh", "study_items", "NS", "pop_items", "pop_n", "p_sm_bonferroni", "is_obsolete", "GO", "name", "pop_count", "alt_ids", "level", "depth", "enrichment", "Cluster", "geneid_set", "symbols", "symbol_set", "geneids", "format_txt", "hdr_idx", "is_hdrgo", "is_usrgo", "hdr1usr01", "dcnt", "D1", "GO_name", ] Nt = cx.namedtuple("Nt", " ".join(nt_fields)) # 147 items nts = [ Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0019222', name='', pop_count='', alt_ids='', level=3, depth=3, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=3356, D1='A', GO_name='regulation of metabolic process'), Nt(p_uncorrected=1.3624160646516914e-07, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=2.7160481309918127e-05, study_items=set([u'ENSMUSG00000001517', u'ENSMUSG00000029521', u'ENSMUSG00000027715', u'ENSMUSG00000054115', u'ENSMUSG00000032113', u'ENSMUSG00000023067', u'ENSMUSG00000017716', u'ENSMUSG00000030867', u'ENSMUSG00000026779', u'ENSMUSG00000020525']), NS='BP', pop_items=set([u'ENSMUSG00000029516', u'ENSMUSG00000054115', u'ENSMUSG00000027425', u'ENSMUSG00000017716', u'ENSMUSG00000036438', u'ENSMUSG00000030752', u'ENSMUSG00000040584', u'ENSMUSG00000032113', u'ENSMUSG00000001175', u'ENSMUSG00000035390', u'ENSMUSG00000030867', u'ENSMUSG00000040021', u'ENSMUSG00000026779', u'ENSMUSG00000019370', u'ENSMUSG00000025226', u'ENSMUSG00000024286', u'ENSMUSG00000001517', u'ENSMUSG00000029521', u'ENSMUSG00000037343', u'ENSMUSG00000020525', u'ENSMUSG00000000296', u'ENSMUSG00000053046', u'ENSMUSG00000027715', u'ENSMUSG00000023067', u'ENSMUSG00000028926', u'ENSMUSG00000007656', u'ENSMUSG00000051177']), pop_n=13836, p_sm_bonferroni=0.0020641965795537777, is_obsolete=False, GO='GO:0000086', name='G2/M transition of mitotic cell cycle', pop_count=27, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000001517', u'ENSMUSG00000029521', u'ENSMUSG00000027715', u'ENSMUSG00000023067', u'ENSMUSG00000032113', u'ENSMUSG00000054115', u'ENSMUSG00000017716', u'ENSMUSG00000030867', u'ENSMUSG00000026779', u'ENSMUSG00000020525']), symbols=u'Birc5 Ccna2 Cdkn1a Chek1 Chek2 Foxm1 Mastl Plk1 Ppm1d Skp2', symbol_set=set([u'Ppm1d', u'Ccna2', u'Plk1', u'Cdkn1a', u'Mastl', u'Foxm1', u'Skp2', u'Chek2', u'Birc5', u'Chek1']), geneids='ENSMUSG00000001517 ENSMUSG00000029521 ENSMUSG00000054115 ENSMUSG00000027715 ENSMUSG00000017716 ENSMUSG00000032113 ENSMUSG00000023067 ENSMUSG00000030867 ENSMUSG00000026779 ENSMUSG00000020525', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='B', GO_name='G2/M transition of mitotic cell cycle'), Nt(p_uncorrected=3.5260394490306786e-07, study_count=13, study_n=624, namespace='biological_process', p_fdr_bh=6.211979499100444e-05, study_items=set([u'ENSMUSG00000028896', u'ENSMUSG00000028212', u'ENSMUSG00000032477', u'ENSMUSG00000041238', u'ENSMUSG00000023067', u'ENSMUSG00000028068', u'ENSMUSG00000054115', u'ENSMUSG00000002068', u'ENSMUSG00000025358', u'ENSMUSG00000028551', u'ENSMUSG00000050410', u'ENSMUSG00000033364', u'ENSMUSG00000007080']), NS='BP', pop_items=set([u'ENSMUSG00000079259', u'ENSMUSG00000028333', u'ENSMUSG00000053819', u'ENSMUSG00000028068', u'ENSMUSG00000028680', u'ENSMUSG00000020516', u'ENSMUSG00000032119', u'ENSMUSG00000050410', u'ENSMUSG00000024617', u'ENSMUSG00000057897', u'ENSMUSG00000003031', u'ENSMUSG00000005732', u'ENSMUSG00000040957', u'ENSMUSG00000033364', u'ENSMUSG00000007080', u'ENSMUSG00000028156', u'ENSMUSG00000041238', u'ENSMUSG00000021379', u'ENSMUSG00000000532', u'ENSMUSG00000032405', u'ENSMUSG00000033016', u'ENSMUSG00000040021', u'ENSMUSG00000070348', u'ENSMUSG00000021820', u'ENSMUSG00000039960', u'ENSMUSG00000022018', u'ENSMUSG00000040274', u'ENSMUSG00000028212', u'ENSMUSG00000054115', u'ENSMUSG00000021701', u'ENSMUSG00000025809', u'ENSMUSG00000026836', u'ENSMUSG00000002068', u'ENSMUSG00000027552', u'ENSMUSG00000033417', u'ENSMUSG00000031155', u'ENSMUSG00000017561', u'ENSMUSG00000022105', u'ENSMUSG00000000184', u'ENSMUSG00000021959', u'ENSMUSG00000028896', u'ENSMUSG00000041229', u'ENSMUSG00000032477', u'ENSMUSG00000023067', u'ENSMUSG00000028161', u'ENSMUSG00000021103', u'ENSMUSG00000028551', u'ENSMUSG00000025358', u'ENSMUSG00000006728', u'ENSMUSG00000028495', u'ENSMUSG00000043866', u'ENSMUSG00000031490']), pop_n=13836, p_sm_bonferroni=0.005342302369226381, is_obsolete=False, GO='GO:0000082', name='G1/S transition of mitotic cell cycle', pop_count=52, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028896', u'ENSMUSG00000028212', u'ENSMUSG00000028551', u'ENSMUSG00000032477', u'ENSMUSG00000041238', u'ENSMUSG00000054115', u'ENSMUSG00000028068', u'ENSMUSG00000023067', u'ENSMUSG00000002068', u'ENSMUSG00000025358', u'ENSMUSG00000050410', u'ENSMUSG00000033364', u'ENSMUSG00000007080']), symbols=u'Ccne1 Ccne2 Cdc25a Cdk2 Cdkn1a Cdkn2c Iqgap3 Pole Rbbp8 Rcc1 Skp2 Tcf19 Usp37', symbol_set=set([u'Rcc1', u'Rbbp8', u'Skp2', u'Cdkn2c', u'Ccne2', u'Cdc25a', u'Ccne1', u'Pole', u'Cdk2', u'Usp37', u'Tcf19', u'Cdkn1a', u'Iqgap3']), geneids='ENSMUSG00000028896 ENSMUSG00000028212 ENSMUSG00000028551 ENSMUSG00000032477 ENSMUSG00000041238 ENSMUSG00000054115 ENSMUSG00000028068 ENSMUSG00000023067 ENSMUSG00000002068 ENSMUSG00000025358 ENSMUSG00000050410 ENSMUSG00000033364 ENSMUSG00000007080', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='B', GO_name='G1/S transition of mitotic cell cycle'), Nt(p_uncorrected=2.512388532377029e-11, study_count=24, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000032661', u'ENSMUSG00000046718', u'ENSMUSG00000036986', u'ENSMUSG00000074896', u'ENSMUSG00000041827', u'ENSMUSG00000023341', u'ENSMUSG00000039236', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000024079', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000034855', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000035692', u'ENSMUSG00000034459', u'ENSMUSG00000032344', u'ENSMUSG00000040296', u'ENSMUSG00000020641', u'ENSMUSG00000040033', u'ENSMUSG00000045932', u'ENSMUSG00000020108', u'ENSMUSG00000000386']), NS='BP', pop_items=set([u'ENSMUSG00000029826', u'ENSMUSG00000045322', u'ENSMUSG00000070583', u'ENSMUSG00000024079', u'ENSMUSG00000009585', u'ENSMUSG00000020455', u'ENSMUSG00000024978', u'ENSMUSG00000021494', u'ENSMUSG00000022476', u'ENSMUSG00000066568', u'ENSMUSG00000061298', u'ENSMUSG00000017707', u'ENSMUSG00000037523', u'ENSMUSG00000038628', u'ENSMUSG00000020115', u'ENSMUSG00000000776', u'ENSMUSG00000026395', u'ENSMUSG00000056144', u'ENSMUSG00000039236', u'ENSMUSG00000066800', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000061286', u'ENSMUSG00000078566', u'ENSMUSG00000003234', u'ENSMUSG00000045932', u'ENSMUSG00000020108', u'ENSMUSG00000000275', u'ENSMUSG00000027951', u'ENSMUSG00000036986', u'ENSMUSG00000056851', u'ENSMUSG00000041415', u'ENSMUSG00000035834', u'ENSMUSG00000003184', u'ENSMUSG00000047123', u'ENSMUSG00000036908', u'ENSMUSG00000057948', u'ENSMUSG00000021703', u'ENSMUSG00000022901', u'ENSMUSG00000030789', u'ENSMUSG00000044583', u'ENSMUSG00000034855', u'ENSMUSG00000024349', u'ENSMUSG00000032369', u'ENSMUSG00000035692', u'ENSMUSG00000034459', u'ENSMUSG00000034453', u'ENSMUSG00000022865', u'ENSMUSG00000020641', u'ENSMUSG00000040033', u'ENSMUSG00000025532', u'ENSMUSG00000000386', u'ENSMUSG00000079339', u'ENSMUSG00000032661', u'ENSMUSG00000029417', u'ENSMUSG00000030314', u'ENSMUSG00000027427', u'ENSMUSG00000026928', u'ENSMUSG00000046718', u'ENSMUSG00000030793', u'ENSMUSG00000074896', u'ENSMUSG00000031639', u'ENSMUSG00000062488', u'ENSMUSG00000028099', u'ENSMUSG00000022971', u'ENSMUSG00000032178', u'ENSMUSG00000030880', u'ENSMUSG00000035086', u'ENSMUSG00000027514', u'ENSMUSG00000033450', u'ENSMUSG00000030247', u'ENSMUSG00000029561', u'ENSMUSG00000029165', u'ENSMUSG00000020783', u'ENSMUSG00000030249', u'ENSMUSG00000025492', u'ENSMUSG00000027598', u'ENSMUSG00000032344', u'ENSMUSG00000057329', u'ENSMUSG00000027639', u'ENSMUSG00000040296', u'ENSMUSG00000032690', u'ENSMUSG00000032691', u'ENSMUSG00000022965', u'ENSMUSG00000022967', u'ENSMUSG00000019726', u'ENSMUSG00000022969', u'ENSMUSG00000037921', u'ENSMUSG00000029771', u'ENSMUSG00000020009', u'ENSMUSG00000040264', u'ENSMUSG00000043279', u'ENSMUSG00000024810', u'ENSMUSG00000041827', u'ENSMUSG00000022051', u'ENSMUSG00000017830', u'ENSMUSG00000023341', u'ENSMUSG00000040613', u'ENSMUSG00000018899', u'ENSMUSG00000060591', u'ENSMUSG00000010047', u'ENSMUSG00000005102', u'ENSMUSG00000034259', u'ENSMUSG00000038884']), pop_n=13836, p_sm_bonferroni=3.806519865404436e-07, is_obsolete=False, GO='GO:0051607', name='defense response to virus', pop_count=104, alt_ids=[], level=3, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000024079', u'ENSMUSG00000046718', u'ENSMUSG00000036986', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000074896', u'ENSMUSG00000034855', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000041827', u'ENSMUSG00000035692', u'ENSMUSG00000034459', u'ENSMUSG00000032344', u'ENSMUSG00000023341', u'ENSMUSG00000040296', u'ENSMUSG00000020641', u'ENSMUSG00000040033', u'ENSMUSG00000045932', u'ENSMUSG00000020108', u'ENSMUSG00000000386']), symbols=u'Bst2 Cxcl10 Ddit4 Ddx58 Dhx58 Eif2ak2 Ifih1 Ifit1 Ifit2 Ifit3 Irf1 Isg15 Isg20 Mb21d1 Mx1 Mx2 Oas1b Oas3 Oasl1 Oasl2 Pml Rsad2 Stat2 Zbp1', symbol_set=set(['Mb21d1', u'Mx1', u'Irf1', u'Zbp1', u'Eif2ak2', u'Oas3', u'Isg20', u'Stat2', u'Oasl2', u'Ifih1', u'Oasl1', u'Ddx58', u'Ddit4', u'Dhx58', u'Mx2', u'Rsad2', u'Isg15', u'Bst2', u'Pml', u'Cxcl10', u'Oas1b', u'Ifit3', u'Ifit2', u'Ifit1']), geneids='ENSMUSG00000032661 ENSMUSG00000023341 ENSMUSG00000024079 ENSMUSG00000036986 ENSMUSG00000074896 ENSMUSG00000041827 ENSMUSG00000017830 ENSMUSG00000039236 ENSMUSG00000018899 ENSMUSG00000027514 ENSMUSG00000046718 ENSMUSG00000029561 ENSMUSG00000034855 ENSMUSG00000029605 ENSMUSG00000026896 ENSMUSG00000035692 ENSMUSG00000034459 ENSMUSG00000032344 ENSMUSG00000040296 ENSMUSG00000020641 ENSMUSG00000040033 ENSMUSG00000045932 ENSMUSG00000020108 ENSMUSG00000000386', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='FL', GO_name='defense response to virus'), Nt(p_uncorrected=0.000352948400217597, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.025224156658947224, study_items=set([u'ENSMUSG00000026622', u'ENSMUSG00000032113', u'ENSMUSG00000012443']), NS='BP', pop_items=set([u'ENSMUSG00000026622', u'ENSMUSG00000012443', u'ENSMUSG00000037443', u'ENSMUSG00000032113']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0046602', name='regulation of mitotic centrosome separation', pop_count=4, alt_ids=[], level=7, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000026622', u'ENSMUSG00000032113', u'ENSMUSG00000012443']), symbols=u'Chek1 Kif11 Nek2', symbol_set=set([u'Nek2', u'Kif11', u'Chek1']), geneids='ENSMUSG00000026622 ENSMUSG00000012443 ENSMUSG00000032113', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='A', GO_name='regulation of mitotic centrosome separation'), Nt(p_uncorrected=0.00012860653072037162, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000019214', u'ENSMUSG00000033970', u'ENSMUSG00000029363', u'ENSMUSG00000022881']), NS='BP', pop_items=set([u'ENSMUSG00000023104', u'ENSMUSG00000057113', u'ENSMUSG00000019214', u'ENSMUSG00000022881', u'ENSMUSG00000046691', u'ENSMUSG00000033970', u'ENSMUSG00000029363']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:1900264', name='positive regulation of DNA-directed DNA polymerase activity', pop_count=7, alt_ids=[], level=6, depth=10, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000019214', u'ENSMUSG00000033970', u'ENSMUSG00000029363', u'ENSMUSG00000022881']), symbols=u'Chtf18 Rfc3 Rfc4 Rfc5', symbol_set=set([u'Rfc5', u'Rfc4', u'Rfc3', u'Chtf18']), geneids='ENSMUSG00000019214 ENSMUSG00000033970 ENSMUSG00000029363 ENSMUSG00000022881', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='A', GO_name='positive regulation of DNA-directed DNA polymerase activity'), Nt(p_uncorrected=1.2205757473020354e-08, study_count=15, study_n=624, namespace='biological_process', p_fdr_bh=3.3652195774610893e-06, study_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000021569', u'ENSMUSG00000029521', u'ENSMUSG00000022906', u'ENSMUSG00000020380', u'ENSMUSG00000028702', u'ENSMUSG00000033762', u'ENSMUSG00000034206', u'ENSMUSG00000049502', u'ENSMUSG00000035958', u'ENSMUSG00000017146', u'ENSMUSG00000002748', u'ENSMUSG00000059552', u'ENSMUSG00000041147', u'ENSMUSG00000022034']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000025932', u'ENSMUSG00000060657', u'ENSMUSG00000026496', u'ENSMUSG00000021569', u'ENSMUSG00000029003', u'ENSMUSG00000025878', u'ENSMUSG00000033762', u'ENSMUSG00000031201', u'ENSMUSG00000020697', u'ENSMUSG00000031583', u'ENSMUSG00000059552', u'ENSMUSG00000028411', u'ENSMUSG00000031715', u'ENSMUSG00000073436', u'ENSMUSG00000024926', u'ENSMUSG00000003549', u'ENSMUSG00000049717', u'ENSMUSG00000020380', u'ENSMUSG00000031820', u'ENSMUSG00000028886', u'ENSMUSG00000034206', u'ENSMUSG00000017146', u'ENSMUSG00000021144', u'ENSMUSG00000002748', u'ENSMUSG00000090083', u'ENSMUSG00000032705', u'ENSMUSG00000023249', u'ENSMUSG00000022034', u'ENSMUSG00000035234', u'ENSMUSG00000025612', u'ENSMUSG00000026648', u'ENSMUSG00000022906', u'ENSMUSG00000029521', u'ENSMUSG00000031928', u'ENSMUSG00000034154', u'ENSMUSG00000041147', u'ENSMUSG00000022672', u'ENSMUSG00000035958', u'ENSMUSG00000028452', u'ENSMUSG00000026187', u'ENSMUSG00000043535', u'ENSMUSG00000037032', u'ENSMUSG00000024151', u'ENSMUSG00000022471', u'ENSMUSG00000030051', u'ENSMUSG00000037761', u'ENSMUSG00000021177', u'ENSMUSG00000022314', u'ENSMUSG00000028702', u'ENSMUSG00000052139', u'ENSMUSG00000049502', u'ENSMUSG00000014074', u'ENSMUSG00000021615', u'ENSMUSG00000037149']), pop_n=13836, p_sm_bonferroni=0.00018492943147373138, is_obsolete=False, GO='GO:0006302', name='double-strand break repair', pop_count=55, alt_ids=[], level=6, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028224', u'ENSMUSG00000021569', u'ENSMUSG00000022034', u'ENSMUSG00000029521', u'ENSMUSG00000022906', u'ENSMUSG00000020380', u'ENSMUSG00000028702', u'ENSMUSG00000033762', u'ENSMUSG00000034206', u'ENSMUSG00000049502', u'ENSMUSG00000035958', u'ENSMUSG00000017146', u'ENSMUSG00000002748', u'ENSMUSG00000059552', u'ENSMUSG00000041147']), symbols=u'Baz1b Brca1 Brca2 Chek2 Dtx3l Esco2 Nbn Parp9 Polq Rad50 Rad54l Recql4 Tdp2 Trip13 Trp53', symbol_set=set([u'Dtx3l', u'Recql4', u'Brca2', u'Parp9', u'Polq', u'Trp53', u'Rad54l', u'Esco2', u'Brca1', u'Baz1b', u'Nbn', u'Rad50', u'Trip13', u'Chek2', u'Tdp2']), geneids='ENSMUSG00000028224 ENSMUSG00000021569 ENSMUSG00000029521 ENSMUSG00000022906 ENSMUSG00000020380 ENSMUSG00000028702 ENSMUSG00000033762 ENSMUSG00000034206 ENSMUSG00000049502 ENSMUSG00000035958 ENSMUSG00000017146 ENSMUSG00000002748 ENSMUSG00000059552 ENSMUSG00000041147 ENSMUSG00000022034', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=11, D1='BDF', GO_name='double-strand break repair'), Nt(p_uncorrected=8.726761340227559e-12, study_count=17, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000041827', u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000032508', u'ENSMUSG00000034459', u'ENSMUSG00000024079', u'ENSMUSG00000079017', u'ENSMUSG00000023341', u'ENSMUSG00000046718', u'ENSMUSG00000040296', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000020641', u'ENSMUSG00000045932', u'ENSMUSG00000026896', u'ENSMUSG00000029605', u'ENSMUSG00000000386']), NS='BP', pop_items=set([u'ENSMUSG00000032661', u'ENSMUSG00000023341', u'ENSMUSG00000045322', u'ENSMUSG00000007659', u'ENSMUSG00000027951', u'ENSMUSG00000070583', u'ENSMUSG00000046718', u'ENSMUSG00000026469', u'ENSMUSG00000031639', u'ENSMUSG00000041827', u'ENSMUSG00000010051', u'ENSMUSG00000032508', u'ENSMUSG00000053175', u'ENSMUSG00000079017', u'ENSMUSG00000029826', u'ENSMUSG00000040725', u'ENSMUSG00000033777', u'ENSMUSG00000052776', u'ENSMUSG00000026896', u'ENSMUSG00000039236', u'ENSMUSG00000017830', u'ENSMUSG00000024079', u'ENSMUSG00000060591', u'ENSMUSG00000029561', u'ENSMUSG00000029605', u'ENSMUSG00000008683', u'ENSMUSG00000010047', u'ENSMUSG00000025492', u'ENSMUSG00000030421', u'ENSMUSG00000034459', u'ENSMUSG00000020075', u'ENSMUSG00000000787', u'ENSMUSG00000027770', u'ENSMUSG00000040296', u'ENSMUSG00000032690', u'ENSMUSG00000020641', u'ENSMUSG00000051451', u'ENSMUSG00000045932', u'ENSMUSG00000037921', u'ENSMUSG00000037149', u'ENSMUSG00000000386']), pop_n=13836, p_sm_bonferroni=1.3221916106578775e-07, is_obsolete=False, GO='GO:0009615', name='response to virus', pop_count=41, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000017830', u'ENSMUSG00000046718', u'ENSMUSG00000024079', u'ENSMUSG00000029561', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000041827', u'ENSMUSG00000032508', u'ENSMUSG00000034459', u'ENSMUSG00000079017', u'ENSMUSG00000023341', u'ENSMUSG00000040296', u'ENSMUSG00000020641', u'ENSMUSG00000045932', u'ENSMUSG00000000386']), symbols=u'Bst2 Ddx58 Dhx58 Eif2ak2 Ifi27l2a Ifih1 Ifit1 Ifit2 Isg20 Mx1 Mx2 Myd88 Oas1b Oas3 Oasl1 Oasl2 Rsad2', symbol_set=set([u'Ifit2', u'Ifih1', u'Myd88', u'Dhx58', u'Mx2', u'Mx1', u'Eif2ak2', u'Oasl2', u'Ddx58', u'Oasl1', u'Oas3', u'Bst2', u'Isg20', u'Ifi27l2a', u'Oas1b', u'Rsad2', u'Ifit1']), geneids='ENSMUSG00000041827 ENSMUSG00000032661 ENSMUSG00000039236 ENSMUSG00000032508 ENSMUSG00000017830 ENSMUSG00000046718 ENSMUSG00000079017 ENSMUSG00000023341 ENSMUSG00000024079 ENSMUSG00000040296 ENSMUSG00000034459 ENSMUSG00000029561 ENSMUSG00000020641 ENSMUSG00000045932 ENSMUSG00000000386 ENSMUSG00000029605 ENSMUSG00000026896', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=13, D1='F', GO_name='response to virus'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0009617', name='', pop_count='', alt_ids='', level=5, depth=5, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=12, D1='F', GO_name='response to bacterium'), Nt(p_uncorrected=0.0002480312688115781, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.01888402891338804, study_items=set([u'ENSMUSG00000024056', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000040599']), NS='BP', pop_items=set([u'ENSMUSG00000047710', u'ENSMUSG00000029554', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000029253', u'ENSMUSG00000024056', u'ENSMUSG00000079614', u'ENSMUSG00000040599']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0051315', name='attachment of mitotic spindle microtubules to kinetochore', pop_count=8, alt_ids=['GO:0051314'], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000024056', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000040599']), symbols=u'Cenpe Kif2c Mis12 Ndc80', symbol_set=set([u'Mis12', u'Cenpe', u'Ndc80', u'Kif2c']), geneids='ENSMUSG00000024056 ENSMUSG00000028678 ENSMUSG00000045328 ENSMUSG00000040599', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='B', GO_name='attachment of mitotic spindle microtubules to kinetochore'), Nt(p_uncorrected=2.327303960478811e-06, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=0.0003326507764642874, study_items=set([u'ENSMUSG00000069910', u'ENSMUSG00000041431', u'ENSMUSG00000028873', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000041498', u'ENSMUSG00000068744', u'ENSMUSG00000027115', u'ENSMUSG00000030677']), NS='BP', pop_items=set([u'ENSMUSG00000033916', u'ENSMUSG00000045328', u'ENSMUSG00000025371', u'ENSMUSG00000028419', u'ENSMUSG00000038467', u'ENSMUSG00000009907', u'ENSMUSG00000030677', u'ENSMUSG00000024370', u'ENSMUSG00000041431', u'ENSMUSG00000028678', u'ENSMUSG00000004364', u'ENSMUSG00000041498', u'ENSMUSG00000032264', u'ENSMUSG00000001440', u'ENSMUSG00000027115', u'ENSMUSG00000035086', u'ENSMUSG00000069910', u'ENSMUSG00000068744', u'ENSMUSG00000004771', u'ENSMUSG00000021958', u'ENSMUSG00000061024', u'ENSMUSG00000022064', u'ENSMUSG00000028873', u'ENSMUSG00000034190', u'ENSMUSG00000031913', u'ENSMUSG00000004843', u'ENSMUSG00000000743', u'ENSMUSG00000079614']), pop_n=13836, p_sm_bonferroni=0.03526098230521446, is_obsolete=False, GO='GO:0007080', name='mitotic metaphase plate congression', pop_count=28, alt_ids=[], level=4, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000069910', u'ENSMUSG00000041431', u'ENSMUSG00000028873', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000041498', u'ENSMUSG00000068744', u'ENSMUSG00000027115', u'ENSMUSG00000030677']), symbols=u'Ccnb1 Cdca8 Cenpe Kif14 Kif18a Kif22 Kif2c Psrc1 Spdl1', symbol_set=set([u'Ccnb1', 'Spdl1', u'Cenpe', u'Kif18a', u'Psrc1', u'Kif22', u'Kif14', u'Cdca8', u'Kif2c']), geneids='ENSMUSG00000069910 ENSMUSG00000041431 ENSMUSG00000028873 ENSMUSG00000028678 ENSMUSG00000045328 ENSMUSG00000041498 ENSMUSG00000068744 ENSMUSG00000027115 ENSMUSG00000030677', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BG', GO_name='mitotic metaphase plate congression'), Nt(p_uncorrected=3.898358886864664e-11, study_count=54, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000002297', u'ENSMUSG00000046591', u'ENSMUSG00000030528', u'ENSMUSG00000022881', u'ENSMUSG00000029730', u'ENSMUSG00000033762', u'ENSMUSG00000024691', u'ENSMUSG00000019214', u'ENSMUSG00000024833', u'ENSMUSG00000002835', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000041859', u'ENSMUSG00000029363', u'ENSMUSG00000007080', u'ENSMUSG00000030978', u'ENSMUSG00000028884', u'ENSMUSG00000042557', u'ENSMUSG00000026355', u'ENSMUSG00000031821', u'ENSMUSG00000030726', u'ENSMUSG00000002870', u'ENSMUSG00000056394', u'ENSMUSG00000034206', u'ENSMUSG00000028587', u'ENSMUSG00000017146', u'ENSMUSG00000027353', u'ENSMUSG00000040204', u'ENSMUSG00000027342', u'ENSMUSG00000033970', u'ENSMUSG00000024742', u'ENSMUSG00000038644', u'ENSMUSG00000028693', u'ENSMUSG00000026669', u'ENSMUSG00000022673', u'ENSMUSG00000031669', u'ENSMUSG00000000028', u'ENSMUSG00000021668', u'ENSMUSG00000023953', u'ENSMUSG00000031353', u'ENSMUSG00000017499', u'ENSMUSG00000027067', u'ENSMUSG00000037474', u'ENSMUSG00000005410', u'ENSMUSG00000045102', u'ENSMUSG00000026134', u'ENSMUSG00000031697', u'ENSMUSG00000022945', u'ENSMUSG00000036875', u'ENSMUSG00000006585', u'ENSMUSG00000020471', u'ENSMUSG00000025395', u'ENSMUSG00000020649', u'ENSMUSG00000027454']), NS='BP', pop_items=set([u'ENSMUSG00000046591', u'ENSMUSG00000029191', u'ENSMUSG00000021668', u'ENSMUSG00000020697', u'ENSMUSG00000031583', u'ENSMUSG00000001911', u'ENSMUSG00000046691', u'ENSMUSG00000038425', u'ENSMUSG00000046101', u'ENSMUSG00000058301', u'ENSMUSG00000007080', u'ENSMUSG00000031353', u'ENSMUSG00000027067', u'ENSMUSG00000020718', u'ENSMUSG00000028587', u'ENSMUSG00000006678', u'ENSMUSG00000017146', u'ENSMUSG00000020752', u'ENSMUSG00000019841', u'ENSMUSG00000033717', u'ENSMUSG00000030685', u'ENSMUSG00000033762', u'ENSMUSG00000025218', u'ENSMUSG00000035726', u'ENSMUSG00000036875', u'ENSMUSG00000002835', u'ENSMUSG00000048170', u'ENSMUSG00000029012', u'ENSMUSG00000037991', u'ENSMUSG00000029730', u'ENSMUSG00000024691', u'ENSMUSG00000019214', u'ENSMUSG00000045102', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000002870', u'ENSMUSG00000025209', u'ENSMUSG00000030978', u'ENSMUSG00000028884', u'ENSMUSG00000052751', u'ENSMUSG00000033970', u'ENSMUSG00000027430', u'ENSMUSG00000057236', u'ENSMUSG00000008575', u'ENSMUSG00000029703', u'ENSMUSG00000026970', u'ENSMUSG00000037262', u'ENSMUSG00000024854', u'ENSMUSG00000055053', u'ENSMUSG00000040044', u'ENSMUSG00000037474', u'ENSMUSG00000030779', u'ENSMUSG00000026134', u'ENSMUSG00000026037', u'ENSMUSG00000006585', u'ENSMUSG00000020649', u'ENSMUSG00000026761', u'ENSMUSG00000002297', u'ENSMUSG00000032740', u'ENSMUSG00000024137', u'ENSMUSG00000024833', u'ENSMUSG00000030528', u'ENSMUSG00000029363', u'ENSMUSG00000070544', u'ENSMUSG00000026283', u'ENSMUSG00000000028', u'ENSMUSG00000042557', u'ENSMUSG00000049717', u'ENSMUSG00000038909', u'ENSMUSG00000026355', u'ENSMUSG00000031821', u'ENSMUSG00000034206', u'ENSMUSG00000020228', u'ENSMUSG00000040204', u'ENSMUSG00000024742', u'ENSMUSG00000039176', u'ENSMUSG00000022292', u'ENSMUSG00000035367', u'ENSMUSG00000000934', u'ENSMUSG00000017615', u'ENSMUSG00000026669', u'ENSMUSG00000022881', u'ENSMUSG00000028565', u'ENSMUSG00000023104', u'ENSMUSG00000031546', u'ENSMUSG00000005410', u'ENSMUSG00000029014', u'ENSMUSG00000027342', u'ENSMUSG00000021392', u'ENSMUSG00000025395', u'ENSMUSG00000027454', u'ENSMUSG00000030330', u'ENSMUSG00000039738', u'ENSMUSG00000021400', u'ENSMUSG00000020471', u'ENSMUSG00000041859', u'ENSMUSG00000063550', u'ENSMUSG00000031536', u'ENSMUSG00000030726', u'ENSMUSG00000056394', u'ENSMUSG00000027353', u'ENSMUSG00000000751', u'ENSMUSG00000038644', u'ENSMUSG00000011114', u'ENSMUSG00000068428', u'ENSMUSG00000021276', u'ENSMUSG00000028693', u'ENSMUSG00000022673', u'ENSMUSG00000031669', u'ENSMUSG00000023953', u'ENSMUSG00000017499', u'ENSMUSG00000029911', u'ENSMUSG00000012483', u'ENSMUSG00000031697', u'ENSMUSG00000022945']), pop_n=13836, p_sm_bonferroni=5.906403549488652e-07, is_obsolete=False, GO='GO:0006260', name='DNA replication', pop_count=115, alt_ids=['GO:0055133'], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000002297', u'ENSMUSG00000046591', u'ENSMUSG00000031669', u'ENSMUSG00000029730', u'ENSMUSG00000033762', u'ENSMUSG00000024691', u'ENSMUSG00000019214', u'ENSMUSG00000024833', u'ENSMUSG00000002835', u'ENSMUSG00000035842', u'ENSMUSG00000030528', u'ENSMUSG00000041859', u'ENSMUSG00000038685', u'ENSMUSG00000007080', u'ENSMUSG00000030978', u'ENSMUSG00000028884', u'ENSMUSG00000042557', u'ENSMUSG00000026355', u'ENSMUSG00000031821', u'ENSMUSG00000030726', u'ENSMUSG00000029363', u'ENSMUSG00000056394', u'ENSMUSG00000034206', u'ENSMUSG00000028587', u'ENSMUSG00000017146', u'ENSMUSG00000027353', u'ENSMUSG00000040204', u'ENSMUSG00000031697', u'ENSMUSG00000033970', u'ENSMUSG00000024742', u'ENSMUSG00000038644', u'ENSMUSG00000028693', u'ENSMUSG00000026669', u'ENSMUSG00000022673', u'ENSMUSG00000022881', u'ENSMUSG00000000028', u'ENSMUSG00000021668', u'ENSMUSG00000023953', u'ENSMUSG00000031353', u'ENSMUSG00000017499', u'ENSMUSG00000027067', u'ENSMUSG00000037474', u'ENSMUSG00000005410', u'ENSMUSG00000045102', u'ENSMUSG00000026134', u'ENSMUSG00000002870', u'ENSMUSG00000027342', u'ENSMUSG00000027454', u'ENSMUSG00000036875', u'ENSMUSG00000006585', u'ENSMUSG00000020471', u'ENSMUSG00000025395', u'ENSMUSG00000020649', u'ENSMUSG00000022945']), symbols=u'Blm Brca1 Cdc45 Cdc6 Cdt1 Chaf1a Chaf1b Chtf18 Dbf4 Ddx11 Dna2 Dtl Fam111a Fen1 Gins1 Gins2 Gins3 Lig1 Mcm10 Mcm2 Mcm3 Mcm4 Mcm5 Mcm6 Mcm7 Mcm8 Nasp Orc1 Orc6 Pclaf Pcna Pola2 Pold1 Pold2 Pold3 Pole Polh Polk Poln Polq Prim1 Prim2 Rbbp7 Recql4 Rfc3 Rfc4 Rfc5 Rpa2 Rrm1 Rrm2 Rtel1 Sin3a Ssrp1 Ticrr', symbol_set=set([u'Mcm7', u'Mcm10', 'Ticrr', u'Recql4', u'Rfc5', u'Rfc4', u'Chaf1b', u'Rbbp7', u'Rfc3', u'Orc1', u'Blm', u'Mcm6', u'Mcm5', u'Pold3', u'Chaf1a', u'Mcm2', u'Prim2', u'Pold1', u'Cdc6', u'Sin3a', u'Brca1', u'Cdt1', u'Rpa2', u'Orc6', u'Lig1', u'Chtf18', 'Pclaf', u'Mcm8', u'Gins2', u'Gins3', u'Nasp', u'Gins1', u'Dtl', u'Fen1', u'Rrm2', u'Rrm1', u'Poln', u'Fam111a', u'Pcna', u'Pola2', u'Dna2', u'Polq', u'Ddx11', u'Ssrp1', u'Pold2', u'Pole', u'Mcm4', u'Dbf4', u'Cdc45', u'Mcm3', u'Rtel1', u'Polk', u'Prim1', u'Polh']), geneids='ENSMUSG00000002297 ENSMUSG00000046591 ENSMUSG00000038685 ENSMUSG00000056394 ENSMUSG00000031669 ENSMUSG00000029730 ENSMUSG00000021668 ENSMUSG00000024691 ENSMUSG00000019214 ENSMUSG00000024833 ENSMUSG00000002835 ENSMUSG00000035842 ENSMUSG00000030528 ENSMUSG00000041859 ENSMUSG00000002870 ENSMUSG00000007080 ENSMUSG00000030978 ENSMUSG00000000028 ENSMUSG00000031353 ENSMUSG00000026355 ENSMUSG00000031821 ENSMUSG00000030726 ENSMUSG00000029363 ENSMUSG00000027067 ENSMUSG00000034206 ENSMUSG00000028587 ENSMUSG00000017146 ENSMUSG00000027353 ENSMUSG00000040204 ENSMUSG00000031697 ENSMUSG00000033970 ENSMUSG00000024742 ENSMUSG00000038644 ENSMUSG00000028693 ENSMUSG00000026669 ENSMUSG00000022673 ENSMUSG00000022881 ENSMUSG00000028884 ENSMUSG00000033762 ENSMUSG00000023953 ENSMUSG00000042557 ENSMUSG00000017499 ENSMUSG00000037474 ENSMUSG00000005410 ENSMUSG00000045102 ENSMUSG00000026134 ENSMUSG00000027342 ENSMUSG00000027454 ENSMUSG00000036875 ENSMUSG00000006585 ENSMUSG00000020471 ENSMUSG00000025395 ENSMUSG00000020649 ENSMUSG00000022945', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=23, D1='BD', GO_name='DNA replication'), Nt(p_uncorrected=2.8613647443791696e-09, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=9.223944094061446e-07, study_items=set([u'ENSMUSG00000030726', u'ENSMUSG00000034206', u'ENSMUSG00000045102', u'ENSMUSG00000020471', u'ENSMUSG00000022881', u'ENSMUSG00000031697', u'ENSMUSG00000033970', u'ENSMUSG00000029363', u'ENSMUSG00000038644']), NS='BP', pop_items=set([u'ENSMUSG00000023104', u'ENSMUSG00000024854', u'ENSMUSG00000034206', u'ENSMUSG00000020228', u'ENSMUSG00000018449', u'ENSMUSG00000030726', u'ENSMUSG00000035021', u'ENSMUSG00000045102', u'ENSMUSG00000031697', u'ENSMUSG00000022881', u'ENSMUSG00000020471', u'ENSMUSG00000048170', u'ENSMUSG00000033970', u'ENSMUSG00000029363', u'ENSMUSG00000038644']), pop_n=13836, p_sm_bonferroni=4.3352537242088796e-05, is_obsolete=False, GO='GO:0006261', name='DNA-dependent DNA replication', pop_count=15, alt_ids=['GO:0006262', 'GO:0006263'], level=6, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000030726', u'ENSMUSG00000034206', u'ENSMUSG00000045102', u'ENSMUSG00000020471', u'ENSMUSG00000022881', u'ENSMUSG00000031697', u'ENSMUSG00000033970', u'ENSMUSG00000029363', u'ENSMUSG00000038644']), symbols=u'Orc6 Pold1 Pold2 Pold3 Poln Polq Rfc3 Rfc4 Rfc5', symbol_set=set([u'Polq', u'Pold1', u'Orc6', u'Rfc4', u'Rfc3', u'Rfc5', u'Pold2', u'Pold3', u'Poln']), geneids='ENSMUSG00000030726 ENSMUSG00000034206 ENSMUSG00000045102 ENSMUSG00000031697 ENSMUSG00000022881 ENSMUSG00000020471 ENSMUSG00000033970 ENSMUSG00000029363 ENSMUSG00000038644', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=19, D1='BD', GO_name='DNA-dependent DNA replication'), Nt(p_uncorrected=4.462381350505715e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.004599288424592659, study_items=set([u'ENSMUSG00000028896', u'ENSMUSG00000031004', u'ENSMUSG00000045328', u'ENSMUSG00000024795', u'ENSMUSG00000022070', u'ENSMUSG00000019773']), NS='BP', pop_items=set([u'ENSMUSG00000035198', u'ENSMUSG00000028896', u'ENSMUSG00000041117', u'ENSMUSG00000018965', u'ENSMUSG00000031004', u'ENSMUSG00000040327', u'ENSMUSG00000045328', u'ENSMUSG00000019773', u'ENSMUSG00000035576', u'ENSMUSG00000024795', u'ENSMUSG00000015095', u'ENSMUSG00000022070', u'ENSMUSG00000029062', u'ENSMUSG00000006699', u'ENSMUSG00000038545', u'ENSMUSG00000033900']), pop_n=13836, p_sm_bonferroni=0.6760953984151209, is_obsolete=False, GO='GO:0007088', name='regulation of mitotic nuclear division', pop_count=16, alt_ids=[], level=6, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028896', u'ENSMUSG00000022070', u'ENSMUSG00000031004', u'ENSMUSG00000024795', u'ENSMUSG00000045328', u'ENSMUSG00000019773']), symbols=u'Bora Cenpe Fbxo5 Kif20b Mki67 Rcc1', symbol_set=set([u'Rcc1', u'Mki67', u'Cenpe', u'Fbxo5', u'Kif20b', 'Bora']), geneids='ENSMUSG00000028896 ENSMUSG00000031004 ENSMUSG00000045328 ENSMUSG00000024795 ENSMUSG00000022070 ENSMUSG00000019773', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=63, D1='A', GO_name='regulation of mitotic nuclear division'), Nt(p_uncorrected=6.144408662089696e-07, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.00010118906047752281, study_items=set([u'ENSMUSG00000026355', u'ENSMUSG00000029730', u'ENSMUSG00000020914', u'ENSMUSG00000027323', u'ENSMUSG00000022673', u'ENSMUSG00000002870']), NS='BP', pop_items=set([u'ENSMUSG00000025209', u'ENSMUSG00000026355', u'ENSMUSG00000029730', u'ENSMUSG00000020914', u'ENSMUSG00000017485', u'ENSMUSG00000022673', u'ENSMUSG00000043991', u'ENSMUSG00000027323', u'ENSMUSG00000002870']), pop_n=13836, p_sm_bonferroni=0.009309393563932098, is_obsolete=False, GO='GO:0006268', name='DNA unwinding involved in DNA replication', pop_count=9, alt_ids=[], level=8, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000002870', u'ENSMUSG00000022673', u'ENSMUSG00000026355', u'ENSMUSG00000029730', u'ENSMUSG00000020914', u'ENSMUSG00000027323']), symbols=u'Mcm2 Mcm4 Mcm6 Mcm7 Rad51 Top2a', symbol_set=set([u'Mcm7', u'Mcm6', u'Mcm4', u'Mcm2', u'Rad51', u'Top2a']), geneids='ENSMUSG00000026355 ENSMUSG00000029730 ENSMUSG00000020914 ENSMUSG00000027323 ENSMUSG00000022673 ENSMUSG00000002870', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=5, D1='BH', GO_name='DNA unwinding involved in DNA replication'), Nt(p_uncorrected=0.000352948400217597, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.025224156658947224, study_items=set([u'ENSMUSG00000035842', u'ENSMUSG00000005413', u'ENSMUSG00000039994']), NS='BP', pop_items=set([u'ENSMUSG00000035842', u'ENSMUSG00000005413', u'ENSMUSG00000066150', u'ENSMUSG00000039994']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0072719', name='cellular response to cisplatin', pop_count=4, 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u'ENSMUSG00000020471', u'ENSMUSG00000032815', u'ENSMUSG00000034023', u'ENSMUSG00000045102', u'ENSMUSG00000002835', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000049932', u'ENSMUSG00000056394', u'ENSMUSG00000044702', u'ENSMUSG00000028884', u'ENSMUSG00000032113', u'ENSMUSG00000019942', u'ENSMUSG00000030726', u'ENSMUSG00000030677', u'ENSMUSG00000027353', u'ENSMUSG00000061607', u'ENSMUSG00000032409', u'ENSMUSG00000038644', u'ENSMUSG00000022906', u'ENSMUSG00000001517', u'ENSMUSG00000030346', u'ENSMUSG00000027433', u'ENSMUSG00000073705', u'ENSMUSG00000035958', u'ENSMUSG00000045751', u'ENSMUSG00000031311', u'ENSMUSG00000023953', u'ENSMUSG00000051768', u'ENSMUSG00000036097', u'ENSMUSG00000027323', u'ENSMUSG00000049502', u'ENSMUSG00000005370', u'ENSMUSG00000042489', u'ENSMUSG00000020608', u'ENSMUSG00000034218', u'ENSMUSG00000022945', u'ENSMUSG00000038774']), symbols=u'Apitd1 Ascc3 Atm Atr Bard1 Blm Brca1 Brca2 Brip1 Cdk1 Cdk2 Chaf1a Chaf1b Chek1 Chek2 Clspn Ddx11 Dna2 Dtx3l Exo1 Fam178a Fanca Fancd2 Fanci Fen1 Foxm1 Gen1 H2afx Kif22 Lig1 Mcm8 Mdc1 Mms22l Msh6 Nbn Nono Palb2 Parp9 Parpbp Paxip1 Pclaf Pcna Pold1 Pold2 Pold3 Pole Polh Polk Poln Polq Rad18 Rad50 Rad51 Rad51ap1 Rad54l Rbbp8 Rpa2 Rtel1 Smc1a Smc3 Smc6 Ssrp1 Tdp2 Tex15 Ticrr Topbp1 Trim28 Uhrf1 Usp1 Xrcc1 Xrn2 Zranb3', symbol_set=set([u'Rbbp8', 'Ticrr', 'Parpbp', u'Usp1', u'Palb2', u'Mdc1', u'H2afx', u'Msh6', u'Gen1', u'Blm', u'Pold1', u'Pold2', u'Pold3', u'Chaf1a', u'Dtx3l', u'Chaf1b', u'Ascc3', u'Kif22', u'Chek2', u'Tdp2', u'Chek1', u'Brca1', u'Brca2', u'Topbp1', u'Bard1', u'Smc3', u'Clspn', u'Cdk2', u'Rpa2', u'Rad54l', u'Foxm1', u'Lig1', u'Xrn2', u'Rad50', u'Xrcc1', u'Brip1', u'Mcm8', u'Mms22l', u'Pcna', u'Apitd1', u'Atm', u'Rad51', u'Zranb3', u'Tex15', u'Nono', u'Rad18', u'Smc6', u'Fen1', u'Rad51ap1', u'Fancd2', 'Pclaf', u'Paxip1', u'Fam178a', u'Smc1a', u'Atr', u'Dna2', u'Trim28', u'Parp9', u'Polq', u'Ddx11', u'Ssrp1', u'Exo1', u'Cdk1', u'Pole', u'Nbn', u'Fanca', u'Poln', u'Rtel1', u'Polk', u'Uhrf1', u'Fanci', u'Polh']), geneids='ENSMUSG00000028224 ENSMUSG00000032815 ENSMUSG00000019942 ENSMUSG00000038685 ENSMUSG00000039748 ENSMUSG00000045102 ENSMUSG00000034023 ENSMUSG00000021668 ENSMUSG00000024974 ENSMUSG00000026196 ENSMUSG00000025358 ENSMUSG00000002835 ENSMUSG00000035842 ENSMUSG00000030528 ENSMUSG00000049932 ENSMUSG00000030677 ENSMUSG00000007080 ENSMUSG00000036086 ENSMUSG00000031311 ENSMUSG00000028884 ENSMUSG00000041238 ENSMUSG00000032113 ENSMUSG00000020380 ENSMUSG00000039187 ENSMUSG00000030726 ENSMUSG00000056394 ENSMUSG00000027067 ENSMUSG00000034206 ENSMUSG00000035958 ENSMUSG00000017146 ENSMUSG00000027353 ENSMUSG00000040204 ENSMUSG00000034329 ENSMUSG00000041133 ENSMUSG00000044702 ENSMUSG00000024742 ENSMUSG00000032409 ENSMUSG00000038644 ENSMUSG00000022906 ENSMUSG00000001517 ENSMUSG00000029521 ENSMUSG00000035365 ENSMUSG00000051768 ENSMUSG00000030346 ENSMUSG00000027433 ENSMUSG00000041147 ENSMUSG00000073705 ENSMUSG00000005566 ENSMUSG00000030254 ENSMUSG00000045751 ENSMUSG00000028560 ENSMUSG00000023953 ENSMUSG00000009628 ENSMUSG00000051235 ENSMUSG00000061607 ENSMUSG00000046591 ENSMUSG00000001228 ENSMUSG00000032555 ENSMUSG00000036097 ENSMUSG00000028702 ENSMUSG00000027323 ENSMUSG00000002221 ENSMUSG00000049502 ENSMUSG00000005370 ENSMUSG00000027342 ENSMUSG00000042489 ENSMUSG00000020608 ENSMUSG00000036875 ENSMUSG00000034218 ENSMUSG00000020471 ENSMUSG00000022945 ENSMUSG00000038774', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=45, D1='BDF', GO_name='DNA repair'), Nt(p_uncorrected=0.0006920361223044611, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.0468082111117629, study_items=set([u'ENSMUSG00000034394', u'ENSMUSG00000020185', u'ENSMUSG00000046179', u'ENSMUSG00000025758']), NS='BP', pop_items=set([u'ENSMUSG00000034394', u'ENSMUSG00000030551', u'ENSMUSG00000020185', u'ENSMUSG00000035247', u'ENSMUSG00000053113', u'ENSMUSG00000022855', u'ENSMUSG00000027087', u'ENSMUSG00000046179', u'ENSMUSG00000040857', u'ENSMUSG00000025758']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0060707', name='trophoblast giant cell differentiation', pop_count=10, alt_ids=[], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034394', u'ENSMUSG00000020185', u'ENSMUSG00000046179', u'ENSMUSG00000025758']), symbols=u'E2f7 E2f8 Lif Plk4', symbol_set=set([u'E2f7', u'Lif', u'Plk4', u'E2f8']), geneids='ENSMUSG00000034394 ENSMUSG00000020185 ENSMUSG00000046179 ENSMUSG00000025758', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCEK', GO_name='trophoblast giant cell differentiation'), Nt(p_uncorrected=0.0002480312688115781, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.01888402891338804, study_items=set([u'ENSMUSG00000035842', u'ENSMUSG00000039994', u'ENSMUSG00000030528', u'ENSMUSG00000027323']), NS='BP', pop_items=set([u'ENSMUSG00000000838', u'ENSMUSG00000029110', u'ENSMUSG00000031229', u'ENSMUSG00000039994', u'ENSMUSG00000027323', u'ENSMUSG00000035842', u'ENSMUSG00000041974', u'ENSMUSG00000030528']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0072711', name='cellular response to hydroxyurea', pop_count=8, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000035842', u'ENSMUSG00000039994', u'ENSMUSG00000030528', u'ENSMUSG00000027323']), symbols=u'Blm Ddx11 Rad51 Timeless', symbol_set=set([u'Blm', u'Timeless', u'Rad51', u'Ddx11']), geneids='ENSMUSG00000035842 ENSMUSG00000039994 ENSMUSG00000030528 ENSMUSG00000027323', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BF', GO_name='cellular response to hydroxyurea'), Nt(p_uncorrected=1.4034325060506728e-08, study_count=12, study_n=624, namespace='biological_process', p_fdr_bh=3.797036767709597e-06, study_items=set([u'ENSMUSG00000030978', u'ENSMUSG00000067455', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000074403', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000020649']), NS='BP', pop_items=set([u'ENSMUSG00000067455', u'ENSMUSG00000063887', u'ENSMUSG00000017390', u'ENSMUSG00000060678', u'ENSMUSG00000060639', u'ENSMUSG00000074403', u'ENSMUSG00000041936', u'ENSMUSG00000005534', u'ENSMUSG00000030978', u'ENSMUSG00000022471', u'ENSMUSG00000026245', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000091405', u'ENSMUSG00000027253', u'ENSMUSG00000069305', u'ENSMUSG00000069306', u'ENSMUSG00000060981', u'ENSMUSG00000031641', u'ENSMUSG00000003808', u'ENSMUSG00000024109', u'ENSMUSG00000038240', u'ENSMUSG00000063895', u'ENSMUSG00000034826', u'ENSMUSG00000032231', u'ENSMUSG00000026784', u'ENSMUSG00000041959', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000020649']), pop_n=13836, p_sm_bonferroni=0.00021263405899173742, is_obsolete=False, GO='GO:0051290', name='protein heterotetramerization', pop_count=34, alt_ids=[], level=8, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000030978', u'ENSMUSG00000067455', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000074403', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000020649']), symbols=u'Hist1h3a Hist1h3b Hist1h3e Hist1h4a Hist1h4b Hist1h4d Hist1h4f Hist1h4j Hist1h4k Hist2h3b Rrm1 Rrm2', symbol_set=set([u'Hist1h4b', u'Hist1h4a', u'Hist1h4f', u'Hist1h4d', u'Hist1h4k', u'Hist1h4j', u'Hist1h3b', u'Hist1h3a', u'Hist2h3b', u'Rrm1', u'Hist1h3e', u'Rrm2']), geneids='ENSMUSG00000030978 ENSMUSG00000067455 ENSMUSG00000069267 ENSMUSG00000069266 ENSMUSG00000069265 ENSMUSG00000069273 ENSMUSG00000069274 ENSMUSG00000061482 ENSMUSG00000074403 ENSMUSG00000060093 ENSMUSG00000064288 ENSMUSG00000020649', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BH', GO_name='protein heterotetramerization'), Nt(p_uncorrected=0.0004954910889564514, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.03427938579351231, study_items=set([u'ENSMUSG00000058385', u'ENSMUSG00000054717', u'ENSMUSG00000032508', u'ENSMUSG00000047246', u'ENSMUSG00000040253', u'ENSMUSG00000062727', u'ENSMUSG00000006445', u'ENSMUSG00000069268']), NS='BP', pop_items=set([u'ENSMUSG00000058385', u'ENSMUSG00000040264', u'ENSMUSG00000015950', u'ENSMUSG00000028874', u'ENSMUSG00000026928', u'ENSMUSG00000067212', u'ENSMUSG00000035279', u'ENSMUSG00000028362', u'ENSMUSG00000062727', u'ENSMUSG00000028268', u'ENSMUSG00000022191', u'ENSMUSG00000022575', u'ENSMUSG00000052593', u'ENSMUSG00000032508', u'ENSMUSG00000069516', u'ENSMUSG00000079641', u'ENSMUSG00000016024', u'ENSMUSG00000020115', u'ENSMUSG00000041135', u'ENSMUSG00000029298', u'ENSMUSG00000054717', u'ENSMUSG00000029468', u'ENSMUSG00000072115', u'ENSMUSG00000068854', u'ENSMUSG00000040253', u'ENSMUSG00000027695', u'ENSMUSG00000037071', u'ENSMUSG00000021194', u'ENSMUSG00000003283', u'ENSMUSG00000028270', u'ENSMUSG00000018102', u'ENSMUSG00000062210', u'ENSMUSG00000006445', u'ENSMUSG00000060802', u'ENSMUSG00000027995', u'ENSMUSG00000047246', u'ENSMUSG00000020399', u'ENSMUSG00000038058', u'ENSMUSG00000024300', u'ENSMUSG00000079614', u'ENSMUSG00000032041', u'ENSMUSG00000069268']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0050830', name='defense response to Gram-positive bacterium', pop_count=42, alt_ids=[], level=6, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000058385', u'ENSMUSG00000054717', u'ENSMUSG00000032508', u'ENSMUSG00000047246', u'ENSMUSG00000040253', u'ENSMUSG00000062727', u'ENSMUSG00000006445', u'ENSMUSG00000069268']), symbols=u'Epha2 Gbp7 Hist1h2be Hist1h2bf Hist1h2bg Hist1h2bk Hmgb2 Myd88', symbol_set=set([u'Hmgb2', u'Gbp7', u'Epha2', u'Hist1h2be', u'Hist1h2bf', u'Hist1h2bg', u'Myd88', u'Hist1h2bk']), geneids='ENSMUSG00000058385 ENSMUSG00000054717 ENSMUSG00000032508 ENSMUSG00000047246 ENSMUSG00000040253 ENSMUSG00000062727 ENSMUSG00000006445 ENSMUSG00000069268', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='F', GO_name='defense response to Gram-positive bacterium'), Nt(p_uncorrected=0.0002480312688115781, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.01888402891338804, study_items=set([u'ENSMUSG00000039356', u'ENSMUSG00000031527', u'ENSMUSG00000027752', u'ENSMUSG00000030929']), NS='BP', pop_items=set([u'ENSMUSG00000031527', u'ENSMUSG00000027752', u'ENSMUSG00000027714', u'ENSMUSG00000033423', u'ENSMUSG00000028322', u'ENSMUSG00000039356', u'ENSMUSG00000025785', u'ENSMUSG00000030929']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0000467', name="exonucleolytic trimming to generate mature 3'-end of 5.8S rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)", pop_count=8, alt_ids=[], level=8, depth=11, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000039356', u'ENSMUSG00000031527', u'ENSMUSG00000027752', u'ENSMUSG00000030929']), symbols=u'Eri1 Eri2 Exosc2 Exosc8', symbol_set=set([u'Exosc2', u'Exosc8', u'Eri2', u'Eri1']), geneids='ENSMUSG00000039356 ENSMUSG00000031527 ENSMUSG00000027752 ENSMUSG00000030929', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BD', GO_name="exonucleolytic trimming to generate mature 3'-end of 5.8S rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)"), Nt(p_uncorrected=1.0342107187712268e-07, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=2.176295361125397e-05, study_items=set([u'ENSMUSG00000028312', u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000027306', u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000015880']), NS='BP', pop_items=set([u'ENSMUSG00000047777', u'ENSMUSG00000028312', u'ENSMUSG00000002625', u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000027306', u'ENSMUSG00000024045', u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000015880', u'ENSMUSG00000000743']), pop_n=13836, p_sm_bonferroni=0.0015669326600102858, is_obsolete=False, GO='GO:0007076', name='mitotic chromosome condensation', pop_count=11, alt_ids=[], level=4, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000028312', u'ENSMUSG00000015880', u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000027306']), symbols=u'Ncapd2 Ncapd3 Ncapg Ncaph Nusap1 Smc2 Smc4', symbol_set=set([u'Nusap1', u'Smc2', u'Smc4', u'Ncapd2', u'Ncapd3', u'Ncaph', u'Ncapg']), geneids='ENSMUSG00000028312 ENSMUSG00000038252 ENSMUSG00000034349 ENSMUSG00000027306 ENSMUSG00000034906 ENSMUSG00000035024 ENSMUSG00000015880', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='BH', GO_name='mitotic chromosome condensation'), Nt(p_uncorrected=1.8374158794264207e-07, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=3.569062562716628e-05, study_items=set([u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000035024', u'ENSMUSG00000034906', u'ENSMUSG00000028312']), NS='BP', pop_items=set([u'ENSMUSG00000034906', u'ENSMUSG00000034349', u'ENSMUSG00000035024', u'ENSMUSG00000038252', u'ENSMUSG00000028312']), pop_n=13836, p_sm_bonferroni=0.00278386879891897, is_obsolete=False, GO='GO:0010032', name='meiotic chromosome condensation', pop_count=5, alt_ids=[], level=4, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000035024', u'ENSMUSG00000034906', u'ENSMUSG00000028312']), symbols=u'Ncapd2 Ncapd3 Ncaph Smc2 Smc4', symbol_set=set([u'Smc2', u'Ncaph', u'Smc4', u'Ncapd2', u'Ncapd3']), geneids='ENSMUSG00000034906 ENSMUSG00000034349 ENSMUSG00000035024 ENSMUSG00000038252 ENSMUSG00000028312', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BHK', GO_name='meiotic chromosome condensation'), Nt(p_uncorrected=0.00013052614287701152, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.010689738328268117, study_items=set([u'ENSMUSG00000027699', u'ENSMUSG00000003779', u'ENSMUSG00000032254', u'ENSMUSG00000017716', u'ENSMUSG00000041147', u'ENSMUSG00000030867', u'ENSMUSG00000038943', u'ENSMUSG00000024660']), NS='BP', pop_items=set([u'ENSMUSG00000026491', u'ENSMUSG00000029516', u'ENSMUSG00000029518', u'ENSMUSG00000027937', u'ENSMUSG00000033628', u'ENSMUSG00000017716', u'ENSMUSG00000017639', u'ENSMUSG00000031729', u'ENSMUSG00000025035', u'ENSMUSG00000070923', u'ENSMUSG00000022443', u'ENSMUSG00000003779', u'ENSMUSG00000028447', u'ENSMUSG00000036580', u'ENSMUSG00000066440', u'ENSMUSG00000030867', u'ENSMUSG00000015932', u'ENSMUSG00000002233', u'ENSMUSG00000037098', u'ENSMUSG00000024660', u'ENSMUSG00000004771', u'ENSMUSG00000036782', u'ENSMUSG00000035086', u'ENSMUSG00000027699', u'ENSMUSG00000033900', u'ENSMUSG00000041147', u'ENSMUSG00000021375', u'ENSMUSG00000038943', u'ENSMUSG00000004451', u'ENSMUSG00000032254', u'ENSMUSG00000008859', u'ENSMUSG00000054364', u'ENSMUSG00000026276', u'ENSMUSG00000032322', u'ENSMUSG00000007659']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0000910', name='cytokinesis', pop_count=35, alt_ids=['GO:0007104', 'GO:0016288', 'GO:0033205'], level=3, depth=3, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027699', u'ENSMUSG00000003779', u'ENSMUSG00000032254', u'ENSMUSG00000017716', u'ENSMUSG00000041147', u'ENSMUSG00000030867', u'ENSMUSG00000038943', u'ENSMUSG00000024660']), symbols=u'Birc5 Brca2 Ect2 Incenp Kif20a Kif23 Plk1 Prc1', symbol_set=set([u'Incenp', u'Brca2', u'Ect2', u'Plk1', u'Birc5', u'Kif23', u'Prc1', u'Kif20a']), geneids='ENSMUSG00000027699 ENSMUSG00000003779 ENSMUSG00000032254 ENSMUSG00000017716 ENSMUSG00000041147 ENSMUSG00000030867 ENSMUSG00000038943 ENSMUSG00000024660', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=10, D1='B', GO_name='cytokinesis'), Nt(p_uncorrected=9.131151172475021e-05, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.008090413532992342, study_items=set([u'ENSMUSG00000038685', u'ENSMUSG00000027342', u'ENSMUSG00000036875']), NS='BP', pop_items=set([u'ENSMUSG00000038685', u'ENSMUSG00000027342', u'ENSMUSG00000036875']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:1902990', name='mitotic telomere maintenance via semi-conservative replication', pop_count=3, alt_ids=[], level=4, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000038685', u'ENSMUSG00000027342', u'ENSMUSG00000036875']), symbols=u'Dna2 Pcna Rtel1', symbol_set=set([u'Pcna', u'Rtel1', u'Dna2']), geneids='ENSMUSG00000038685 ENSMUSG00000027342 ENSMUSG00000036875', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='ABCDH', GO_name='mitotic telomere maintenance via semi-conservative replication'), Nt(p_uncorrected=9.548068345280445e-07, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.00015389657819079151, study_items=set([u'ENSMUSG00000008976', u'ENSMUSG00000067455', u'ENSMUSG00000069266', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288']), NS='BP', pop_items=set([u'ENSMUSG00000008976', u'ENSMUSG00000067455', u'ENSMUSG00000060981', u'ENSMUSG00000060678', u'ENSMUSG00000060639', u'ENSMUSG00000069266', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000030538', u'ENSMUSG00000064288', u'ENSMUSG00000069305', u'ENSMUSG00000069306', u'ENSMUSG00000091405']), pop_n=13836, p_sm_bonferroni=0.014466278349934403, is_obsolete=False, GO='GO:0045653', name='negative regulation of megakaryocyte differentiation', pop_count=14, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000008976', u'ENSMUSG00000069266', u'ENSMUSG00000067455', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288']), symbols=u'Gabpa Hist1h4a Hist1h4b Hist1h4d Hist1h4f Hist1h4j Hist1h4k', symbol_set=set([u'Hist1h4b', u'Hist1h4a', u'Hist1h4f', u'Hist1h4d', u'Hist1h4k', u'Hist1h4j', u'Gabpa']), geneids='ENSMUSG00000008976 ENSMUSG00000067455 ENSMUSG00000069266 ENSMUSG00000069274 ENSMUSG00000061482 ENSMUSG00000060093 ENSMUSG00000064288', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='A', GO_name='negative regulation of megakaryocyte differentiation'), Nt(p_uncorrected=0.000722549994700679, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.048439623759778706, study_items=set([u'ENSMUSG00000020290', u'ENSMUSG00000047735', u'ENSMUSG00000011179', u'ENSMUSG00000029521', u'ENSMUSG00000020184']), NS='BP', pop_items=set([u'ENSMUSG00000027654', u'ENSMUSG00000020290', u'ENSMUSG00000017221', u'ENSMUSG00000044734', u'ENSMUSG00000029521', u'ENSMUSG00000020349', u'ENSMUSG00000006699', u'ENSMUSG00000006058', u'ENSMUSG00000020184', u'ENSMUSG00000030530', u'ENSMUSG00000010517', u'ENSMUSG00000020634', u'ENSMUSG00000011179', u'ENSMUSG00000055116', u'ENSMUSG00000006998', u'ENSMUSG00000047735', u'ENSMUSG00000026229']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0042176', name='regulation of protein catabolic process', pop_count=17, alt_ids=[], level=5, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000020290', u'ENSMUSG00000047735', u'ENSMUSG00000011179', u'ENSMUSG00000020184', u'ENSMUSG00000029521']), symbols=u'Chek2 Mdm2 Odc1 Samd9l Xpo1', symbol_set=set([u'Xpo1', u'Samd9l', u'Mdm2', u'Chek2', u'Odc1']), geneids='ENSMUSG00000020290 ENSMUSG00000047735 ENSMUSG00000011179 ENSMUSG00000029521 ENSMUSG00000020184', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=65, D1='A', GO_name='regulation of protein catabolic process'), Nt(p_uncorrected=6.018241857743234e-09, study_count=33, study_n=624, namespace='biological_process', p_fdr_bh=1.8236476477333547e-06, study_items=set([u'ENSMUSG00000032661', u'ENSMUSG00000070034', u'ENSMUSG00000024079', u'ENSMUSG00000074151', u'ENSMUSG00000036986', u'ENSMUSG00000074896', u'ENSMUSG00000041827', u'ENSMUSG00000032508', u'ENSMUSG00000023341', u'ENSMUSG00000028633', u'ENSMUSG00000054072', u'ENSMUSG00000021624', u'ENSMUSG00000039748', u'ENSMUSG00000039236', u'ENSMUSG00000054717', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000046718', u'ENSMUSG00000046879', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000037321', u'ENSMUSG00000034459', u'ENSMUSG00000032344', u'ENSMUSG00000040296', u'ENSMUSG00000025498', u'ENSMUSG00000020641', u'ENSMUSG00000001123', u'ENSMUSG00000045932', u'ENSMUSG00000034218', u'ENSMUSG00000000386']), NS='BP', pop_items=set([u'ENSMUSG00000035834', u'ENSMUSG00000045322', u'ENSMUSG00000028874', u'ENSMUSG00000004730', u'ENSMUSG00000021703', u'ENSMUSG00000024079', u'ENSMUSG00000074151', u'ENSMUSG00000060586', u'ENSMUSG00000016481', u'ENSMUSG00000024338', u'ENSMUSG00000055172', u'ENSMUSG00000036887', u'ENSMUSG00000009585', u'ENSMUSG00000031805', u'ENSMUSG00000022476', u'ENSMUSG00000024371', u'ENSMUSG00000042228', u'ENSMUSG00000017707', u'ENSMUSG00000032035', u'ENSMUSG00000071369', u'ENSMUSG00000026399', u'ENSMUSG00000037523', u'ENSMUSG00000038628', u'ENSMUSG00000020115', u'ENSMUSG00000000776', u'ENSMUSG00000019843', u'ENSMUSG00000015217', u'ENSMUSG00000035629', u'ENSMUSG00000039748', u'ENSMUSG00000039236', u'ENSMUSG00000049686', u'ENSMUSG00000024164', u'ENSMUSG00000035279', u'ENSMUSG00000024045', u'ENSMUSG00000038128', u'ENSMUSG00000075705', u'ENSMUSG00000041187', u'ENSMUSG00000038517', u'ENSMUSG00000046034', u'ENSMUSG00000062593', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000037321', u'ENSMUSG00000037649', u'ENSMUSG00000014599', u'ENSMUSG00000000275', u'ENSMUSG00000024789', u'ENSMUSG00000051439', u'ENSMUSG00000038058', u'ENSMUSG00000025512', u'ENSMUSG00000050199', u'ENSMUSG00000034889', u'ENSMUSG00000024621', u'ENSMUSG00000027951', u'ENSMUSG00000020437', u'ENSMUSG00000070390', u'ENSMUSG00000036986', u'ENSMUSG00000030751', u'ENSMUSG00000025139', u'ENSMUSG00000000134', u'ENSMUSG00000026883', u'ENSMUSG00000015837', u'ENSMUSG00000032691', u'ENSMUSG00000018446', u'ENSMUSG00000018899', u'ENSMUSG00000028885', u'ENSMUSG00000029826', u'ENSMUSG00000028633', u'ENSMUSG00000027646', u'ENSMUSG00000003184', u'ENSMUSG00000047123', u'ENSMUSG00000024767', u'ENSMUSG00000016024', u'ENSMUSG00000054072', u'ENSMUSG00000036908', u'ENSMUSG00000037860', u'ENSMUSG00000036905', u'ENSMUSG00000032312', u'ENSMUSG00000061232', u'ENSMUSG00000001123', u'ENSMUSG00000031392', u'ENSMUSG00000028099', u'ENSMUSG00000055204', u'ENSMUSG00000022901', u'ENSMUSG00000045932', u'ENSMUSG00000033777', u'ENSMUSG00000059883', u'ENSMUSG00000027598', u'ENSMUSG00000030263', u'ENSMUSG00000039936', u'ENSMUSG00000003283', u'ENSMUSG00000051212', u'ENSMUSG00000044583', u'ENSMUSG00000023915', u'ENSMUSG00000002688', u'ENSMUSG00000022636', u'ENSMUSG00000021583', u'ENSMUSG00000078942', u'ENSMUSG00000031838', u'ENSMUSG00000078945', u'ENSMUSG00000025702', u'ENSMUSG00000027639', u'ENSMUSG00000033307', u'ENSMUSG00000024610', u'ENSMUSG00000000787', u'ENSMUSG00000034453', u'ENSMUSG00000026288', u'ENSMUSG00000028793', u'ENSMUSG00000034218', u'ENSMUSG00000023990', u'ENSMUSG00000025532', u'ENSMUSG00000060550', u'ENSMUSG00000000386', u'ENSMUSG00000052384', u'ENSMUSG00000070034', u'ENSMUSG00000028064', u'ENSMUSG00000027427', u'ENSMUSG00000026928', u'ENSMUSG00000000732', u'ENSMUSG00000020399', u'ENSMUSG00000046718', u'ENSMUSG00000013707', u'ENSMUSG00000030793', u'ENSMUSG00000021457', u'ENSMUSG00000074896', u'ENSMUSG00000024948', u'ENSMUSG00000031639', u'ENSMUSG00000020823', u'ENSMUSG00000025498', u'ENSMUSG00000047798', u'ENSMUSG00000026285', u'ENSMUSG00000032508', u'ENSMUSG00000024339', u'ENSMUSG00000002602', u'ENSMUSG00000053647', u'ENSMUSG00000060591', u'ENSMUSG00000041439', u'ENSMUSG00000032076', u'ENSMUSG00000024235', u'ENSMUSG00000001150', u'ENSMUSG00000027508', u'ENSMUSG00000036896', u'ENSMUSG00000071203', u'ENSMUSG00000079547', u'ENSMUSG00000030880', u'ENSMUSG00000041135', u'ENSMUSG00000024392', u'ENSMUSG00000022575', u'ENSMUSG00000021624', u'ENSMUSG00000020707', u'ENSMUSG00000038213', u'ENSMUSG00000057058', u'ENSMUSG00000027514', u'ENSMUSG00000037731', u'ENSMUSG00000030122', u'ENSMUSG00000024349', u'ENSMUSG00000033454', u'ENSMUSG00000022514', u'ENSMUSG00000022887', u'ENSMUSG00000036469', u'ENSMUSG00000023973', u'ENSMUSG00000043496', u'ENSMUSG00000020573', u'ENSMUSG00000034652', u'ENSMUSG00000036712', u'ENSMUSG00000025492', u'ENSMUSG00000032109', u'ENSMUSG00000060802', u'ENSMUSG00000029798', u'ENSMUSG00000032344', u'ENSMUSG00000059456', u'ENSMUSG00000026117', u'ENSMUSG00000040296', u'ENSMUSG00000032690', u'ENSMUSG00000040751', u'ENSMUSG00000032905', u'ENSMUSG00000020476', u'ENSMUSG00000004707', u'ENSMUSG00000038160', u'ENSMUSG00000038495', u'ENSMUSG00000001128', u'ENSMUSG00000029771', u'ENSMUSG00000058818', u'ENSMUSG00000040264', u'ENSMUSG00000056851', u'ENSMUSG00000032661', u'ENSMUSG00000067212', u'ENSMUSG00000038521', u'ENSMUSG00000036594', u'ENSMUSG00000031750', u'ENSMUSG00000022508', u'ENSMUSG00000073421', u'ENSMUSG00000041827', u'ENSMUSG00000050335', u'ENSMUSG00000044811', u'ENSMUSG00000026471', u'ENSMUSG00000017830', u'ENSMUSG00000019256', u'ENSMUSG00000023341', u'ENSMUSG00000023224', u'ENSMUSG00000015947', u'ENSMUSG00000020641', u'ENSMUSG00000026778', u'ENSMUSG00000039005', u'ENSMUSG00000026648', u'ENSMUSG00000028059', u'ENSMUSG00000028191', u'ENSMUSG00000054717', u'ENSMUSG00000038260', u'ENSMUSG00000046879', u'ENSMUSG00000021277', u'ENSMUSG00000030748', u'ENSMUSG00000033538', u'ENSMUSG00000028291', u'ENSMUSG00000029217', u'ENSMUSG00000051256', u'ENSMUSG00000066839', u'ENSMUSG00000073411', u'ENSMUSG00000005102', u'ENSMUSG00000029561', u'ENSMUSG00000029915', u'ENSMUSG00000027995', u'ENSMUSG00000044827', u'ENSMUSG00000043279', u'ENSMUSG00000027164', u'ENSMUSG00000026365', u'ENSMUSG00000032322', u'ENSMUSG00000032041', u'ENSMUSG00000034459', u'ENSMUSG00000045038', u'ENSMUSG00000021423', u'ENSMUSG00000038147', u'ENSMUSG00000052889', u'ENSMUSG00000050132', u'ENSMUSG00000032737']), pop_n=13836, p_sm_bonferroni=9.118238238666775e-05, is_obsolete=False, GO='GO:0002376', name='immune system process', pop_count=235, alt_ids=[], level=1, depth=1, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032661', u'ENSMUSG00000070034', u'ENSMUSG00000024079', u'ENSMUSG00000074151', u'ENSMUSG00000036986', u'ENSMUSG00000074896', u'ENSMUSG00000041827', u'ENSMUSG00000032508', u'ENSMUSG00000023341', u'ENSMUSG00000028633', u'ENSMUSG00000054072', u'ENSMUSG00000021624', u'ENSMUSG00000039748', u'ENSMUSG00000039236', u'ENSMUSG00000054717', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000046718', u'ENSMUSG00000046879', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000037321', u'ENSMUSG00000034459', u'ENSMUSG00000032344', u'ENSMUSG00000040296', u'ENSMUSG00000025498', u'ENSMUSG00000020641', u'ENSMUSG00000001123', u'ENSMUSG00000045932', u'ENSMUSG00000034218', u'ENSMUSG00000000386']), symbols=u'Atm Bst2 Cd180 Ctps Ddx58 Dhx58 Eif2ak2 Exo1 Hmgb2 Ifih1 Ifit1 Ifit2 Ifit3 Iigp1 Irf1 Irf7 Irgm1 Isg20 Lgals9 Mb21d1 Mx1 Mx2 Myd88 Nlrc5 Oas1b Oas3 Oasl1 Oasl2 Pml Rsad2 Sp110 Tap1 Zbp1', symbol_set=set([u'Lgals9', 'Mb21d1', u'Sp110', u'Mx1', u'Iigp1', u'Irf1', u'Irf7', u'Zbp1', u'Eif2ak2', u'Oas3', u'Isg20', u'Nlrc5', u'Tap1', u'Atm', u'Ddx58', u'Oas1b', u'Oasl2', u'Ifih1', u'Oasl1', u'Irgm1', u'Ctps', u'Myd88', u'Dhx58', u'Hmgb2', u'Exo1', u'Mx2', u'Ifit2', u'Bst2', u'Pml', u'Cd180', u'Ifit3', u'Rsad2', u'Ifit1']), geneids='ENSMUSG00000032661 ENSMUSG00000023341 ENSMUSG00000070034 ENSMUSG00000024079 ENSMUSG00000074151 ENSMUSG00000036986 ENSMUSG00000074896 ENSMUSG00000041827 ENSMUSG00000032508 ENSMUSG00000017830 ENSMUSG00000028633 ENSMUSG00000054072 ENSMUSG00000021624 ENSMUSG00000039748 ENSMUSG00000039236 ENSMUSG00000054717 ENSMUSG00000018899 ENSMUSG00000027514 ENSMUSG00000046718 ENSMUSG00000046879 ENSMUSG00000029561 ENSMUSG00000029605 ENSMUSG00000026896 ENSMUSG00000037321 ENSMUSG00000034459 ENSMUSG00000032344 ENSMUSG00000040296 ENSMUSG00000025498 ENSMUSG00000020641 ENSMUSG00000001123 ENSMUSG00000045932 ENSMUSG00000034218 ENSMUSG00000000386', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=572, D1='L', GO_name='immune system process'), Nt(p_uncorrected=1.976111142578265e-05, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.002185405833664474, study_items=set([u'ENSMUSG00000007080', u'ENSMUSG00000038644', u'ENSMUSG00000030726', u'ENSMUSG00000021668']), NS='BP', pop_items=set([u'ENSMUSG00000007080', u'ENSMUSG00000038644', u'ENSMUSG00000030726', u'ENSMUSG00000049717', u'ENSMUSG00000021668']), pop_n=13836, p_sm_bonferroni=0.29940059921203294, is_obsolete=False, GO='GO:0006297', name='nucleotide-excision repair, DNA gap filling', pop_count=5, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000021668', u'ENSMUSG00000038644', u'ENSMUSG00000030726', u'ENSMUSG00000007080']), symbols=u'Pold1 Pold3 Pole Polk', symbol_set=set([u'Pold1', u'Pole', u'Pold3', u'Polk']), geneids='ENSMUSG00000021668 ENSMUSG00000038644 ENSMUSG00000030726 ENSMUSG00000007080', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BD', GO_name='nucleotide-excision repair, DNA gap filling'), Nt(p_uncorrected=2.7262250045263463e-11, study_count=15, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000028212', u'ENSMUSG00000032555', u'ENSMUSG00000005410', u'ENSMUSG00000026355', u'ENSMUSG00000022673', u'ENSMUSG00000002068', u'ENSMUSG00000026669', u'ENSMUSG00000024833', u'ENSMUSG00000031697', u'ENSMUSG00000029283', u'ENSMUSG00000000028', u'ENSMUSG00000029730', u'ENSMUSG00000041859', u'ENSMUSG00000002870']), NS='BP', pop_items=set([u'ENSMUSG00000029730', u'ENSMUSG00000024833', u'ENSMUSG00000041859', u'ENSMUSG00000002870', u'ENSMUSG00000000028', u'ENSMUSG00000021597', u'ENSMUSG00000026355', u'ENSMUSG00000006678', u'ENSMUSG00000026761', u'ENSMUSG00000028212', u'ENSMUSG00000068428', u'ENSMUSG00000002068', u'ENSMUSG00000026669', u'ENSMUSG00000022673', u'ENSMUSG00000031546', u'ENSMUSG00000017499', u'ENSMUSG00000032555', u'ENSMUSG00000040044', u'ENSMUSG00000005410', u'ENSMUSG00000031697', u'ENSMUSG00000029283', u'ENSMUSG00000029012']), pop_n=13836, p_sm_bonferroni=4.130503504357867e-07, is_obsolete=False, GO='GO:0006270', name='DNA replication initiation', pop_count=22, alt_ids=['GO:0042024'], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000017499', u'ENSMUSG00000028212', u'ENSMUSG00000032555', u'ENSMUSG00000005410', u'ENSMUSG00000026355', u'ENSMUSG00000024833', u'ENSMUSG00000002068', u'ENSMUSG00000026669', u'ENSMUSG00000022673', u'ENSMUSG00000031697', u'ENSMUSG00000029283', u'ENSMUSG00000000028', u'ENSMUSG00000029730', u'ENSMUSG00000041859', u'ENSMUSG00000002870']), symbols=u'Ccne1 Ccne2 Cdc45 Cdc6 Cdc7 Mcm10 Mcm2 Mcm3 Mcm4 Mcm5 Mcm6 Mcm7 Orc6 Pola2 Topbp1', symbol_set=set([u'Pola2', u'Orc6', u'Mcm10', u'Topbp1', u'Ccne2', u'Ccne1', u'Mcm7', u'Mcm6', u'Mcm5', u'Mcm4', u'Mcm3', u'Mcm2', u'Cdc45', u'Cdc6', u'Cdc7']), geneids='ENSMUSG00000017499 ENSMUSG00000028212 ENSMUSG00000000028 ENSMUSG00000005410 ENSMUSG00000026355 ENSMUSG00000024833 ENSMUSG00000002068 ENSMUSG00000026669 ENSMUSG00000022673 ENSMUSG00000031697 ENSMUSG00000029283 ENSMUSG00000032555 ENSMUSG00000029730 ENSMUSG00000041859 ENSMUSG00000002870', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=7, D1='BD', GO_name='DNA replication initiation'), Nt(p_uncorrected=1.0053914461965553e-06, study_count=11, study_n=624, namespace='biological_process', p_fdr_bh=0.00016034406106656853, study_items=set([u'ENSMUSG00000028211', u'ENSMUSG00000030641', u'ENSMUSG00000003873', u'ENSMUSG00000057789', u'ENSMUSG00000059552', u'ENSMUSG00000032477', u'ENSMUSG00000027342', u'ENSMUSG00000020897', u'ENSMUSG00000022033', u'ENSMUSG00000032409', u'ENSMUSG00000038644']), NS='BP', pop_items=set([u'ENSMUSG00000020366', u'ENSMUSG00000003873', u'ENSMUSG00000073616', u'ENSMUSG00000029535', u'ENSMUSG00000022521', u'ENSMUSG00000021264', u'ENSMUSG00000059552', u'ENSMUSG00000059263', u'ENSMUSG00000030641', u'ENSMUSG00000029026', u'ENSMUSG00000041417', u'ENSMUSG00000028914', u'ENSMUSG00000032267', u'ENSMUSG00000036940', u'ENSMUSG00000004655', u'ENSMUSG00000014074', u'ENSMUSG00000020897', u'ENSMUSG00000022033', u'ENSMUSG00000026142', u'ENSMUSG00000032409', u'ENSMUSG00000038644', u'ENSMUSG00000028211', u'ENSMUSG00000000838', u'ENSMUSG00000030268', u'ENSMUSG00000034154', u'ENSMUSG00000003868', u'ENSMUSG00000033454', u'ENSMUSG00000055024', u'ENSMUSG00000019889', u'ENSMUSG00000031314', u'ENSMUSG00000031652', u'ENSMUSG00000022545', u'ENSMUSG00000032477', u'ENSMUSG00000005102', u'ENSMUSG00000057789', u'ENSMUSG00000023353', u'ENSMUSG00000028086', u'ENSMUSG00000027342', u'ENSMUSG00000002342', u'ENSMUSG00000021116']), pop_n=13836, p_sm_bonferroni=0.01523268580132401, is_obsolete=False, GO='GO:0034644', name='cellular response to UV', pop_count=40, alt_ids=[], level=6, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028211', u'ENSMUSG00000030641', u'ENSMUSG00000003873', u'ENSMUSG00000022033', u'ENSMUSG00000020897', u'ENSMUSG00000027342', u'ENSMUSG00000059552', u'ENSMUSG00000038644', u'ENSMUSG00000057789', u'ENSMUSG00000032409', u'ENSMUSG00000032477']), symbols=u'Atr Aurkb Bak1 Bax Cdc25a Ddias Pbk Pcna Pold1 Trp53 Trp53inp1', symbol_set=set(['Ddias', u'Pcna', u'Trp53', u'Cdc25a', u'Bax', u'Bak1', u'Pold1', u'Trp53inp1', u'Atr', u'Aurkb', u'Pbk']), geneids='ENSMUSG00000028211 ENSMUSG00000030641 ENSMUSG00000003873 ENSMUSG00000057789 ENSMUSG00000059552 ENSMUSG00000027342 ENSMUSG00000020897 ENSMUSG00000038644 ENSMUSG00000022033 ENSMUSG00000032409 ENSMUSG00000032477', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=7, D1='BF', GO_name='cellular response to UV'), Nt(p_uncorrected=3.4475572661038637e-11, study_count=86, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000034349', u'ENSMUSG00000027469', u'ENSMUSG00000042029', u'ENSMUSG00000045328', u'ENSMUSG00000024974', u'ENSMUSG00000025358', u'ENSMUSG00000022177', u'ENSMUSG00000022070', u'ENSMUSG00000027379', u'ENSMUSG00000020897', u'ENSMUSG00000019773', u'ENSMUSG00000062510', u'ENSMUSG00000029521', u'ENSMUSG00000051378', u'ENSMUSG00000037313', u'ENSMUSG00000001855', u'ENSMUSG00000027715', u'ENSMUSG00000032254', u'ENSMUSG00000006398', u'ENSMUSG00000072082', u'ENSMUSG00000027496', u'ENSMUSG00000024660', u'ENSMUSG00000026622', u'ENSMUSG00000078762', u'ENSMUSG00000028873', u'ENSMUSG00000027306', u'ENSMUSG00000024056', u'ENSMUSG00000048922', u'ENSMUSG00000034906', u'ENSMUSG00000032397', u'ENSMUSG00000021965', u'ENSMUSG00000031478', u'ENSMUSG00000030867', u'ENSMUSG00000047534', u'ENSMUSG00000032400', u'ENSMUSG00000028312', u'ENSMUSG00000021115', u'ENSMUSG00000043065', u'ENSMUSG00000032477', u'ENSMUSG00000026683', u'ENSMUSG00000027326', u'ENSMUSG00000027635', u'ENSMUSG00000040034', u'ENSMUSG00000012443', u'ENSMUSG00000029414', u'ENSMUSG00000028066', u'ENSMUSG00000001403', u'ENSMUSG00000002055', u'ENSMUSG00000051220', u'ENSMUSG00000033364', u'ENSMUSG00000041431', u'ENSMUSG00000041238', u'ENSMUSG00000039994', u'ENSMUSG00000027331', u'ENSMUSG00000020492', u'ENSMUSG00000041133', u'ENSMUSG00000024989', u'ENSMUSG00000028896', u'ENSMUSG00000045273', u'ENSMUSG00000058290', u'ENSMUSG00000033952', u'ENSMUSG00000038252', u'ENSMUSG00000025001', u'ENSMUSG00000040599', u'ENSMUSG00000032218', u'ENSMUSG00000029472', u'ENSMUSG00000024795', u'ENSMUSG00000031756', u'ENSMUSG00000023940', u'ENSMUSG00000023505', u'ENSMUSG00000028678', u'ENSMUSG00000026779', u'ENSMUSG00000020326', u'ENSMUSG00000069910', u'ENSMUSG00000074476', u'ENSMUSG00000021374', u'ENSMUSG00000073705', u'ENSMUSG00000068744', u'ENSMUSG00000019942', u'ENSMUSG00000017499', u'ENSMUSG00000020808', u'ENSMUSG00000017716', u'ENSMUSG00000029910', u'ENSMUSG00000035024', u'ENSMUSG00000005233']), NS='BP', pop_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000019942', u'ENSMUSG00000026491', u'ENSMUSG00000024073', u'ENSMUSG00000029516', u'ENSMUSG00000026965', u'ENSMUSG00000027330', 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u'ENSMUSG00000019794', u'ENSMUSG00000062380', u'ENSMUSG00000053333', u'ENSMUSG00000029472', u'ENSMUSG00000017716', u'ENSMUSG00000029910', u'ENSMUSG00000031201', u'ENSMUSG00000021365', u'ENSMUSG00000031756', u'ENSMUSG00000048170', u'ENSMUSG00000023940', u'ENSMUSG00000025077', u'ENSMUSG00000014355', u'ENSMUSG00000026276', u'ENSMUSG00000027285', u'ENSMUSG00000033900', u'ENSMUSG00000021374', u'ENSMUSG00000024660', u'ENSMUSG00000023505', u'ENSMUSG00000029253', u'ENSMUSG00000028447', u'ENSMUSG00000027937', u'ENSMUSG00000018651', u'ENSMUSG00000029003', u'ENSMUSG00000040102', u'ENSMUSG00000022750', u'ENSMUSG00000038619', u'ENSMUSG00000001833', u'ENSMUSG00000029684', u'ENSMUSG00000020326', u'ENSMUSG00000069910', u'ENSMUSG00000028059', u'ENSMUSG00000029501', u'ENSMUSG00000040549', u'ENSMUSG00000025862', u'ENSMUSG00000074476', u'ENSMUSG00000034154', u'ENSMUSG00000028678', u'ENSMUSG00000064302', u'ENSMUSG00000041840', u'ENSMUSG00000073705', u'ENSMUSG00000068744', u'ENSMUSG00000030105', u'ENSMUSG00000073700', u'ENSMUSG00000042364', u'ENSMUSG00000040250', u'ENSMUSG00000030744', u'ENSMUSG00000052087', u'ENSMUSG00000017499', u'ENSMUSG00000049327', u'ENSMUSG00000053046', u'ENSMUSG00000031478', u'ENSMUSG00000043987', u'ENSMUSG00000020808', u'ENSMUSG00000032435', u'ENSMUSG00000031529', u'ENSMUSG00000040667', u'ENSMUSG00000030428', u'ENSMUSG00000052139', u'ENSMUSG00000028851', u'ENSMUSG00000032534', u'ENSMUSG00000035024', u'ENSMUSG00000027479', u'ENSMUSG00000019873', u'ENSMUSG00000031371', u'ENSMUSG00000007656', u'ENSMUSG00000015971', u'ENSMUSG00000032733', u'ENSMUSG00000079614', u'ENSMUSG00000031858']), pop_n=13836, p_sm_bonferroni=5.223394013873964e-07, is_obsolete=False, GO='GO:0007067', name='mitotic nuclear division', pop_count=249, alt_ids=[], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000029414', u'ENSMUSG00000040084', u'ENSMUSG00000031478', u'ENSMUSG00000028066', u'ENSMUSG00000001403', u'ENSMUSG00000033952', u'ENSMUSG00000027469', u'ENSMUSG00000037313', u'ENSMUSG00000045328', u'ENSMUSG00000024974', u'ENSMUSG00000025358', u'ENSMUSG00000051220', u'ENSMUSG00000033364', u'ENSMUSG00000041431', u'ENSMUSG00000041238', u'ENSMUSG00000039994', u'ENSMUSG00000022177', u'ENSMUSG00000027331', u'ENSMUSG00000022070', u'ENSMUSG00000027379', u'ENSMUSG00000024056', u'ENSMUSG00000020897', u'ENSMUSG00000020492', u'ENSMUSG00000041133', u'ENSMUSG00000024989', u'ENSMUSG00000019773', u'ENSMUSG00000062510', u'ENSMUSG00000029521', u'ENSMUSG00000028896', u'ENSMUSG00000045273', u'ENSMUSG00000058290', u'ENSMUSG00000024660', u'ENSMUSG00000038252', u'ENSMUSG00000051378', u'ENSMUSG00000042029', u'ENSMUSG00000025001', u'ENSMUSG00000040599', u'ENSMUSG00000001855', u'ENSMUSG00000002055', u'ENSMUSG00000027715', u'ENSMUSG00000032254', u'ENSMUSG00000006398', u'ENSMUSG00000072082', u'ENSMUSG00000027496', u'ENSMUSG00000026622', u'ENSMUSG00000078762', u'ENSMUSG00000028873', u'ENSMUSG00000027306', u'ENSMUSG00000029472', u'ENSMUSG00000048922', u'ENSMUSG00000024795', u'ENSMUSG00000034906', u'ENSMUSG00000031756', u'ENSMUSG00000032218', u'ENSMUSG00000023940', u'ENSMUSG00000032397', u'ENSMUSG00000021374', u'ENSMUSG00000023505', u'ENSMUSG00000021965', u'ENSMUSG00000034349', u'ENSMUSG00000030867', u'ENSMUSG00000047534', u'ENSMUSG00000026779', u'ENSMUSG00000032400', u'ENSMUSG00000020326', u'ENSMUSG00000069910', u'ENSMUSG00000028312', u'ENSMUSG00000074476', u'ENSMUSG00000028678', u'ENSMUSG00000021115', u'ENSMUSG00000073705', u'ENSMUSG00000068744', u'ENSMUSG00000019942', u'ENSMUSG00000017499', u'ENSMUSG00000043065', u'ENSMUSG00000032477', u'ENSMUSG00000026683', u'ENSMUSG00000020808', u'ENSMUSG00000027326', u'ENSMUSG00000027635', u'ENSMUSG00000017716', u'ENSMUSG00000029910', u'ENSMUSG00000040034', u'ENSMUSG00000035024', u'ENSMUSG00000005233', u'ENSMUSG00000012443']), symbols=u'Anapc5 Apitd1 Aspm Aurka Aurkb Birc5 Bora Bub1 Bub1b Ccna2 Ccnb1 Ccnb2 Ccnf Ccng1 Cdc20 Cdc25a Cdc6 Cdca2 Cdca3 Cdca8 Cdk1 Cdk2 Cenpe Cenph Cenpn Cep55 Chek2 Dsn1 Ercc6l Espl1 Fam64a Fbxo5 Haus4 Haus5 Hells Incenp Kif11 Kif18b Kif20b Kif23 Kif2c Knl1 Knstrn Kntc1 Mad2l1 Mastl Mis12 Mis18bp1 Ncapd2 Ncapd3 Ncapg2 Ncaph Ndc80 Nek2 Nek3 Nsl1 Nuf2 Nup153 Nup214 Nup43 Nusap1 Plk1 Pmf1 Psrc1 Rbbp8 Rcc1 Sgol1 Ska2 Ska3 Smc1a Smc2 Smc3 Smc4 Spag5 Spc24 Spc25 Spdl1 Spice1 Tacc3 Timeless Tipin Tpx2 Ube2c Usp37 Vrk1 Zwilch', symbol_set=set([u'Rbbp8', 'Spdl1', u'Cep55', u'Ccnf', u'Ncapg2', u'Mis12', u'Chek2', u'Ccng1', 'Ska3', 'Ska2', u'Fam64a', u'Cenpn', u'Ccna2', u'Cenph', u'Cenpe', u'Tacc3', u'Dsn1', u'Ncapd2', u'Ncapd3', u'Kif11', u'Smc1a', u'Rcc1', u'Cdc25a', u'Ccnb2', u'Ccnb1', u'Aspm', u'Ndc80', u'Cdc6', u'Tpx2', u'Mad2l1', u'Pmf1', u'Bub1b', u'Anapc5', u'Ercc6l', u'Aurka', u'Aurkb', u'Spc25', u'Spc24', u'Hells', u'Kntc1', u'Timeless', u'Incenp', u'Spag5', u'Cdk1', u'Cdk2', u'Ncaph', u'Nup214', 'Bora', u'Nuf2', u'Haus4', u'Haus5', u'Spice1', u'Nek2', u'Nek3', u'Sgol1', u'Kif18b', u'Nsl1', u'Nusap1', u'Tipin', u'Cdc20', u'Fbxo5', u'Zwilch', 'Knstrn', u'Psrc1', u'Mis18bp1', u'Ube2c', u'Cdca2', u'Cdca3', u'Espl1', u'Bub1', u'Cdca8', u'Kif20b', u'Smc3', u'Smc2', u'Mastl', u'Smc4', u'Kif23', u'Apitd1', u'Nup153', 'Knl1', u'Vrk1', u'Plk1', u'Usp37', u'Birc5', u'Nup43', u'Kif2c']), geneids='ENSMUSG00000040084 ENSMUSG00000019942 ENSMUSG00000027469 ENSMUSG00000037313 ENSMUSG00000045328 ENSMUSG00000024974 ENSMUSG00000025358 ENSMUSG00000022177 ENSMUSG00000022070 ENSMUSG00000027379 ENSMUSG00000033952 ENSMUSG00000019773 ENSMUSG00000062510 ENSMUSG00000029521 ENSMUSG00000051378 ENSMUSG00000042029 ENSMUSG00000001855 ENSMUSG00000027715 ENSMUSG00000032254 ENSMUSG00000027306 ENSMUSG00000072082 ENSMUSG00000027496 ENSMUSG00000024660 ENSMUSG00000026622 ENSMUSG00000078762 ENSMUSG00000028873 ENSMUSG00000024056 ENSMUSG00000048922 ENSMUSG00000034906 ENSMUSG00000032397 ENSMUSG00000021965 ENSMUSG00000034349 ENSMUSG00000030867 ENSMUSG00000047534 ENSMUSG00000032400 ENSMUSG00000028312 ENSMUSG00000021115 ENSMUSG00000043065 ENSMUSG00000032477 ENSMUSG00000026683 ENSMUSG00000027326 ENSMUSG00000027635 ENSMUSG00000040034 ENSMUSG00000012443 ENSMUSG00000029414 ENSMUSG00000028066 ENSMUSG00000001403 ENSMUSG00000002055 ENSMUSG00000051220 ENSMUSG00000033364 ENSMUSG00000006398 ENSMUSG00000041431 ENSMUSG00000041238 ENSMUSG00000039994 ENSMUSG00000027331 ENSMUSG00000020492 ENSMUSG00000041133 ENSMUSG00000024989 ENSMUSG00000028896 ENSMUSG00000045273 ENSMUSG00000058290 ENSMUSG00000020897 ENSMUSG00000038252 ENSMUSG00000025001 ENSMUSG00000040599 ENSMUSG00000032218 ENSMUSG00000029472 ENSMUSG00000024795 ENSMUSG00000031756 ENSMUSG00000023940 ENSMUSG00000023505 ENSMUSG00000028678 ENSMUSG00000026779 ENSMUSG00000020326 ENSMUSG00000069910 ENSMUSG00000074476 ENSMUSG00000021374 ENSMUSG00000073705 ENSMUSG00000068744 ENSMUSG00000017499 ENSMUSG00000031478 ENSMUSG00000020808 ENSMUSG00000017716 ENSMUSG00000029910 ENSMUSG00000035024 ENSMUSG00000005233', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=1, D1='BH', GO_name='mitotic nuclear division'), Nt(p_uncorrected=0.000430543497990217, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.03019983582430453, study_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000030867', u'ENSMUSG00000045328', u'ENSMUSG00000001403']), NS='BP', pop_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000026749', u'ENSMUSG00000024370', u'ENSMUSG00000029176', u'ENSMUSG00000001403', u'ENSMUSG00000066149', u'ENSMUSG00000045328', u'ENSMUSG00000030867', u'ENSMUSG00000036977']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0030071', name='regulation of mitotic metaphase/anaphase transition', pop_count=9, alt_ids=[], level=7, depth=10, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000017499', u'ENSMUSG00000030867', u'ENSMUSG00000045328', u'ENSMUSG00000001403']), symbols=u'Cdc6 Cenpe Plk1 Ube2c', symbol_set=set([u'Plk1', u'Cenpe', u'Ube2c', u'Cdc6']), geneids='ENSMUSG00000017499 ENSMUSG00000030867 ENSMUSG00000045328 ENSMUSG00000001403', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=11, D1='A', GO_name='regulation of mitotic metaphase/anaphase transition'), Nt(p_uncorrected=2.327303960478811e-06, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=0.0003326507764642874, study_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000018983', u'ENSMUSG00000024521', u'ENSMUSG00000027490', u'ENSMUSG00000036986', u'ENSMUSG00000034457', u'ENSMUSG00000059552']), NS='BP', pop_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000018983', u'ENSMUSG00000030793', u'ENSMUSG00000020267', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000026510', u'ENSMUSG00000027663', u'ENSMUSG00000000552', u'ENSMUSG00000052676', u'ENSMUSG00000030888', u'ENSMUSG00000020719', u'ENSMUSG00000021285', u'ENSMUSG00000037492', u'ENSMUSG00000021690', u'ENSMUSG00000003068', u'ENSMUSG00000004637', u'ENSMUSG00000026278', u'ENSMUSG00000027016', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000034457', u'ENSMUSG00000021481', u'ENSMUSG00000027490', u'ENSMUSG00000040463', u'ENSMUSG00000024521', u'ENSMUSG00000019851', u'ENSMUSG00000038967']), pop_n=13836, p_sm_bonferroni=0.03526098230521446, is_obsolete=False, GO='GO:0072332', name='intrinsic apoptotic signaling pathway by p53 class mediator', pop_count=28, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000003873', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000018983', u'ENSMUSG00000024521', u'ENSMUSG00000027490', u'ENSMUSG00000036986', u'ENSMUSG00000034457', u'ENSMUSG00000059552']), symbols=u'Bax Bbc3 E2f1 E2f2 Eda2r Pmaip1 Pml Shisa5 Trp53', symbol_set=set([u'Eda2r', u'Pmaip1', u'E2f2', u'E2f1', u'Trp53', u'Bax', u'Shisa5', u'Pml', u'Bbc3']), geneids='ENSMUSG00000003873 ENSMUSG00000025647 ENSMUSG00000002083 ENSMUSG00000018983 ENSMUSG00000024521 ENSMUSG00000027490 ENSMUSG00000036986 ENSMUSG00000034457 ENSMUSG00000059552', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='AB', GO_name='intrinsic apoptotic signaling pathway by p53 class mediator'), Nt(p_uncorrected=9.131151172475021e-05, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.008090413532992342, study_items=set([u'ENSMUSG00000020897', u'ENSMUSG00000069910', u'ENSMUSG00000017716']), NS='BP', pop_items=set([u'ENSMUSG00000020897', u'ENSMUSG00000069910', u'ENSMUSG00000017716']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0031577', name='spindle checkpoint', pop_count=3, alt_ids=[], level=3, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000020897', u'ENSMUSG00000069910', u'ENSMUSG00000017716']), symbols=u'Aurkb Birc5 Spdl1', symbol_set=set([u'Birc5', u'Aurkb', 'Spdl1']), geneids='ENSMUSG00000020897 ENSMUSG00000069910 ENSMUSG00000017716', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=8, D1='AB', GO_name='spindle checkpoint'), Nt(p_uncorrected=0.000161263723064093, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.012996312064596133, study_items=set([u'ENSMUSG00000052833', u'ENSMUSG00000017716', u'ENSMUSG00000020380', u'ENSMUSG00000023067', u'ENSMUSG00000030867', u'ENSMUSG00000062248', u'ENSMUSG00000037214', u'ENSMUSG00000019773']), NS='BP', pop_items=set([u'ENSMUSG00000028249', u'ENSMUSG00000023067', u'ENSMUSG00000018697', u'ENSMUSG00000029635', u'ENSMUSG00000025083', u'ENSMUSG00000029026', u'ENSMUSG00000022346', u'ENSMUSG00000020380', u'ENSMUSG00000030867', u'ENSMUSG00000039128', u'ENSMUSG00000020950', u'ENSMUSG00000025224', u'ENSMUSG00000020063', u'ENSMUSG00000075334', u'ENSMUSG00000038481', u'ENSMUSG00000019773', u'ENSMUSG00000020052', u'ENSMUSG00000021466', u'ENSMUSG00000033862', u'ENSMUSG00000031176', u'ENSMUSG00000024042', u'ENSMUSG00000040250', u'ENSMUSG00000052833', u'ENSMUSG00000031155', u'ENSMUSG00000034974', u'ENSMUSG00000018669', u'ENSMUSG00000035828', u'ENSMUSG00000036712', u'ENSMUSG00000037664', u'ENSMUSG00000017716', u'ENSMUSG00000012483', u'ENSMUSG00000033209', u'ENSMUSG00000062248', u'ENSMUSG00000024454', u'ENSMUSG00000022105', u'ENSMUSG00000037214']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0007346', name='regulation of mitotic cell cycle', pop_count=36, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000052833', u'ENSMUSG00000023067', u'ENSMUSG00000020380', u'ENSMUSG00000017716', u'ENSMUSG00000030867', u'ENSMUSG00000062248', u'ENSMUSG00000037214', u'ENSMUSG00000019773']), symbols=u'Birc5 Cdkn1a Cks2 Fbxo5 Plk1 Rad50 Sae1 Thap1', symbol_set=set([u'Thap1', u'Plk1', u'Cks2', u'Birc5', u'Sae1', u'Fbxo5', u'Rad50', u'Cdkn1a']), geneids='ENSMUSG00000052833 ENSMUSG00000017716 ENSMUSG00000020380 ENSMUSG00000023067 ENSMUSG00000030867 ENSMUSG00000062248 ENSMUSG00000037214 ENSMUSG00000019773', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=175, D1='A', GO_name='regulation of mitotic cell cycle'), Nt(p_uncorrected=0.00018502014117979695, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.014524560409404683, study_items=set([u'ENSMUSG00000041238', u'ENSMUSG00000037474', u'ENSMUSG00000032113', u'ENSMUSG00000030867', u'ENSMUSG00000017146', u'ENSMUSG00000042489']), NS='BP', pop_items=set([u'ENSMUSG00000059981', u'ENSMUSG00000026749', u'ENSMUSG00000017291', u'ENSMUSG00000041238', u'ENSMUSG00000020235', u'ENSMUSG00000037474', u'ENSMUSG00000032113', u'ENSMUSG00000031820', u'ENSMUSG00000025878', u'ENSMUSG00000052139', u'ENSMUSG00000030867', u'ENSMUSG00000031201', u'ENSMUSG00000035486', u'ENSMUSG00000042489', u'ENSMUSG00000016528', u'ENSMUSG00000035390', u'ENSMUSG00000035032', u'ENSMUSG00000033102', u'ENSMUSG00000035234', u'ENSMUSG00000017146']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0031572', name='G2 DNA damage 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hdr1usr01='*', dcnt=9858, D1='C', GO_name='single-organism process'), Nt(p_uncorrected=0.00012860653072037162, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000036086', u'ENSMUSG00000030528', u'ENSMUSG00000005370', u'ENSMUSG00000030254']), NS='BP', pop_items=set([u'ENSMUSG00000036086', u'ENSMUSG00000014850', u'ENSMUSG00000020697', u'ENSMUSG00000005370', u'ENSMUSG00000030254', u'ENSMUSG00000030528', u'ENSMUSG00000024151']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0045910', name='negative regulation of DNA recombination', pop_count=7, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036086', u'ENSMUSG00000030528', u'ENSMUSG00000005370', u'ENSMUSG00000030254']), symbols=u'Blm Msh6 Rad18 Zranb3', symbol_set=set([u'Blm', u'Rad18', u'Msh6', u'Zranb3']), geneids='ENSMUSG00000036086 ENSMUSG00000030528 ENSMUSG00000005370 ENSMUSG00000030254', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=18, D1='A', GO_name='negative regulation of DNA recombination'), Nt(p_uncorrected=2.000325641521453e-09, study_count=24, study_n=624, namespace='biological_process', p_fdr_bh=7.215936617783699e-07, study_items=set([u'ENSMUSG00000009035', u'ENSMUSG00000037321', u'ENSMUSG00000033033', u'ENSMUSG00000041879', u'ENSMUSG00000025134', u'ENSMUSG00000003779', u'ENSMUSG00000022142', u'ENSMUSG00000023015', u'ENSMUSG00000006930', u'ENSMUSG00000018167', u'ENSMUSG00000027115', u'ENSMUSG00000027699', u'ENSMUSG00000028693', u'ENSMUSG00000021371', u'ENSMUSG00000036992', u'ENSMUSG00000052798', u'ENSMUSG00000026088', u'ENSMUSG00000020290', u'ENSMUSG00000001855', u'ENSMUSG00000024097', u'ENSMUSG00000024737', u'ENSMUSG00000036678', u'ENSMUSG00000019874', u'ENSMUSG00000040034']), NS='BP', pop_items=set([u'ENSMUSG00000020198', u'ENSMUSG00000002015', u'ENSMUSG00000006005', u'ENSMUSG00000018379', u'ENSMUSG00000046027', 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u'ENSMUSG00000041482', u'ENSMUSG00000049265', u'ENSMUSG00000042529', u'ENSMUSG00000008892', u'ENSMUSG00000069806', u'ENSMUSG00000030525', u'ENSMUSG00000045053', u'ENSMUSG00000027748', u'ENSMUSG00000053395', u'ENSMUSG00000023030', u'ENSMUSG00000023032', u'ENSMUSG00000023033', u'ENSMUSG00000022132', u'ENSMUSG00000017740', u'ENSMUSG00000019734', u'ENSMUSG00000026519', u'ENSMUSG00000027950', u'ENSMUSG00000022295', u'ENSMUSG00000053897', u'ENSMUSG00000021313', u'ENSMUSG00000051331', u'ENSMUSG00000002908', u'ENSMUSG00000054720', u'ENSMUSG00000029088', u'ENSMUSG00000071424', u'ENSMUSG00000026463', u'ENSMUSG00000057914', u'ENSMUSG00000032511', u'ENSMUSG00000029016', u'ENSMUSG00000031129', u'ENSMUSG00000026904', u'ENSMUSG00000028420', u'ENSMUSG00000017412', u'ENSMUSG00000019558', u'ENSMUSG00000022342', u'ENSMUSG00000022956', u'ENSMUSG00000037610', u'ENSMUSG00000062785', u'ENSMUSG00000066189', u'ENSMUSG00000029468', u'ENSMUSG00000029467', u'ENSMUSG00000039156', u'ENSMUSG00000047976', u'ENSMUSG00000033007', u'ENSMUSG00000023959', u'ENSMUSG00000031532', u'ENSMUSG00000042682', u'ENSMUSG00000022462', u'ENSMUSG00000025986', u'ENSMUSG00000030987', u'ENSMUSG00000030737', u'ENSMUSG00000027163', u'ENSMUSG00000051726', u'ENSMUSG00000020882', u'ENSMUSG00000027365', u'ENSMUSG00000040373']), pop_n=13836, p_sm_bonferroni=0.32580768111281294, is_obsolete=False, GO='GO:0006811', name='ion transport', pop_count=395, alt_ids=[], level=4, depth=4, enrichment='p', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000033033', u'ENSMUSG00000023015', u'ENSMUSG00000021371']), symbols=u'Calhm2 Mcur1 Racgap1', symbol_set=set([u'Racgap1', 'Mcur1', u'Calhm2']), geneids='ENSMUSG00000033033 ENSMUSG00000023015 ENSMUSG00000021371', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=657, D1='G', GO_name='ion transport'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0050790', name='', pop_count='', alt_ids='', level=3, depth=3, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=639, D1='A', GO_name='regulation of catalytic activity'), Nt(p_uncorrected=2.2796759490055655e-05, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.0024670978788130945, study_items=set([u'ENSMUSG00000027699', u'ENSMUSG00000002083', u'ENSMUSG00000030346', u'ENSMUSG00000023067', u'ENSMUSG00000027323', u'ENSMUSG00000035455', u'ENSMUSG00000059552', u'ENSMUSG00000030528']), NS='BP', pop_items=set([u'ENSMUSG00000036390', u'ENSMUSG00000055762', u'ENSMUSG00000020413', u'ENSMUSG00000044627', u'ENSMUSG00000059552', u'ENSMUSG00000041974', u'ENSMUSG00000030528', u'ENSMUSG00000038569', u'ENSMUSG00000029238', u'ENSMUSG00000048668', u'ENSMUSG00000053914', u'ENSMUSG00000037461', u'ENSMUSG00000022248', u'ENSMUSG00000020063', u'ENSMUSG00000059923', u'ENSMUSG00000027699', u'ENSMUSG00000030346', u'ENSMUSG00000034154', u'ENSMUSG00000021215', u'ENSMUSG00000024824', u'ENSMUSG00000022184', u'ENSMUSG00000002083', u'ENSMUSG00000023067', u'ENSMUSG00000054364', u'ENSMUSG00000027323', u'ENSMUSG00000035455', u'ENSMUSG00000053436', u'ENSMUSG00000064289']), pop_n=13836, p_sm_bonferroni=0.3453937030338332, is_obsolete=False, GO='GO:0071479', name='cellular response to ionizing radiation', pop_count=28, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027699', u'ENSMUSG00000002083', u'ENSMUSG00000030346', u'ENSMUSG00000023067', u'ENSMUSG00000027323', u'ENSMUSG00000035455', u'ENSMUSG00000059552', u'ENSMUSG00000030528']), symbols=u'Bbc3 Blm Cdkn1a Ect2 Fignl1 Rad51 Rad51ap1 Trp53', symbol_set=set([u'Ect2', u'Trp53', u'Cdkn1a', u'Fignl1', u'Blm', u'Rad51ap1', u'Rad51', u'Bbc3']), geneids='ENSMUSG00000027699 ENSMUSG00000002083 ENSMUSG00000030346 ENSMUSG00000023067 ENSMUSG00000027323 ENSMUSG00000035455 ENSMUSG00000059552 ENSMUSG00000030528', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='BF', GO_name='cellular response to ionizing radiation'), Nt(p_uncorrected=0.00046048838074520853, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.0321514260676067, study_items=set([u'ENSMUSG00000068606', u'ENSMUSG00000046879', u'ENSMUSG00000037321', u'ENSMUSG00000078853', u'ENSMUSG00000078921', u'ENSMUSG00000034855', u'ENSMUSG00000024308']), NS='BP', pop_items=set([u'ENSMUSG00000029417', u'ENSMUSG00000058163', u'ENSMUSG00000026656', u'ENSMUSG00000035279', u'ENSMUSG00000037321', u'ENSMUSG00000078920', u'ENSMUSG00000078921', u'ENSMUSG00000031639', u'ENSMUSG00000073555', u'ENSMUSG00000024927', u'ENSMUSG00000015396', u'ENSMUSG00000022556', u'ENSMUSG00000061353', u'ENSMUSG00000002603', u'ENSMUSG00000023078', u'ENSMUSG00000027447', u'ENSMUSG00000068606', u'ENSMUSG00000069874', u'ENSMUSG00000046879', u'ENSMUSG00000030120', u'ENSMUSG00000030341', u'ENSMUSG00000078853', u'ENSMUSG00000034855', u'ENSMUSG00000029371', u'ENSMUSG00000069893', u'ENSMUSG00000024610', u'ENSMUSG00000044827', u'ENSMUSG00000090942', u'ENSMUSG00000018819', u'ENSMUSG00000038058', u'ENSMUSG00000079227', u'ENSMUSG00000024308']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0006952', name='defense response', pop_count=32, alt_ids=['GO:0002217', 'GO:0042829'], level=3, depth=3, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000037321', u'ENSMUSG00000078853', u'ENSMUSG00000078921', u'ENSMUSG00000068606', u'ENSMUSG00000034855', u'ENSMUSG00000046879', u'ENSMUSG00000024308']), symbols=u'Cxcl10 Gm4841 Igtp Irgm1 Tap1 Tapbp Tgtp2', symbol_set=set([u'Tap1', u'Gm4841', u'Tgtp2', u'Tapbp', u'Igtp', u'Cxcl10', u'Irgm1']), geneids='ENSMUSG00000068606 ENSMUSG00000046879 ENSMUSG00000037321 ENSMUSG00000078853 ENSMUSG00000078921 ENSMUSG00000034855 ENSMUSG00000024308', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=93, D1='F', GO_name='defense response'), Nt(p_uncorrected=1.7206633078450607e-06, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.000255585978207456, study_items=set([u'ENSMUSG00000027496', u'ENSMUSG00000002055', u'ENSMUSG00000021572', u'ENSMUSG00000020897', u'ENSMUSG00000027331', u'ENSMUSG00000033952', u'ENSMUSG00000012443']), NS='BP', pop_items=set([u'ENSMUSG00000018474', u'ENSMUSG00000027496', u'ENSMUSG00000002055', u'ENSMUSG00000001151', u'ENSMUSG00000021572', u'ENSMUSG00000020897', u'ENSMUSG00000027331', u'ENSMUSG00000040549', u'ENSMUSG00000033952', u'ENSMUSG00000005732', u'ENSMUSG00000012443', u'ENSMUSG00000074749', u'ENSMUSG00000026857', u'ENSMUSG00000035354', u'ENSMUSG00000052087']), pop_n=13836, p_sm_bonferroni=0.026069769777160516, is_obsolete=False, GO='GO:0007051', name='spindle organization', pop_count=15, alt_ids=['GO:0043146'], level=3, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000020897', u'ENSMUSG00000027331', u'ENSMUSG00000033952', u'ENSMUSG00000027496', u'ENSMUSG00000012443', u'ENSMUSG00000002055', u'ENSMUSG00000021572']), symbols=u'Aspm Aurka Aurkb Cep72 Kif11 Knstrn Spag5', symbol_set=set(['Knstrn', u'Cep72', u'Aspm', u'Spag5', u'Aurka', u'Aurkb', u'Kif11']), geneids='ENSMUSG00000027496 ENSMUSG00000002055 ENSMUSG00000021572 ENSMUSG00000033952 ENSMUSG00000027331 ENSMUSG00000020897 ENSMUSG00000012443', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=24, D1='BCH', GO_name='spindle organization'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0006950', name='', pop_count='', alt_ids='', level=2, depth=2, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=491, D1='F', GO_name='response to stress'), Nt(p_uncorrected=0.00014991499902937172, study_count=13, study_n=624, namespace='biological_process', p_fdr_bh=0.012146321659326262, study_items=set([u'ENSMUSG00000041827', u'ENSMUSG00000034394', u'ENSMUSG00000032661', u'ENSMUSG00000032508', u'ENSMUSG00000027399', u'ENSMUSG00000022074', u'ENSMUSG00000029561', u'ENSMUSG00000016496', u'ENSMUSG00000034855', u'ENSMUSG00000035352', u'ENSMUSG00000018930', u'ENSMUSG00000029605', u'ENSMUSG00000002699']), NS='BP', pop_items=set([u'ENSMUSG00000045322', u'ENSMUSG00000026656', u'ENSMUSG00000032661', u'ENSMUSG00000059327', u'ENSMUSG00000060586', u'ENSMUSG00000031778', u'ENSMUSG00000002015', u'ENSMUSG00000061353', u'ENSMUSG00000029371', u'ENSMUSG00000023078', u'ENSMUSG00000021796', u'ENSMUSG00000022074', u'ENSMUSG00000036103', u'ENSMUSG00000079362', u'ENSMUSG00000006014', u'ENSMUSG00000027399', u'ENSMUSG00000029605', u'ENSMUSG00000000982', u'ENSMUSG00000037649', u'ENSMUSG00000045827', u'ENSMUSG00000032251', u'ENSMUSG00000029287', u'ENSMUSG00000020941', u'ENSMUSG00000024778', u'ENSMUSG00000031165', u'ENSMUSG00000022425', u'ENSMUSG00000061132', u'ENSMUSG00000032402', u'ENSMUSG00000036867', u'ENSMUSG00000035352', u'ENSMUSG00000061232', u'ENSMUSG00000034116', u'ENSMUSG00000039217', u'ENSMUSG00000044583', u'ENSMUSG00000034855', u'ENSMUSG00000022637', u'ENSMUSG00000031706', u'ENSMUSG00000037370', u'ENSMUSG00000032369', u'ENSMUSG00000001016', u'ENSMUSG00000017344', u'ENSMUSG00000024610', u'ENSMUSG00000026321', u'ENSMUSG00000034987', u'ENSMUSG00000021508', u'ENSMUSG00000022148', u'ENSMUSG00000079227', u'ENSMUSG00000052384', u'ENSMUSG00000029417', u'ENSMUSG00000056216', u'ENSMUSG00000019122', u'ENSMUSG00000002699', u'ENSMUSG00000073421', u'ENSMUSG00000032508', u'ENSMUSG00000018927', u'ENSMUSG00000079547', u'ENSMUSG00000008318', u'ENSMUSG00000029561', u'ENSMUSG00000056749', u'ENSMUSG00000036469', u'ENSMUSG00000033510', u'ENSMUSG00000028776', u'ENSMUSG00000060802', u'ENSMUSG00000026117', u'ENSMUSG00000032690', u'ENSMUSG00000022468', u'ENSMUSG00000039304', u'ENSMUSG00000018930', u'ENSMUSG00000030339', u'ENSMUSG00000006342', u'ENSMUSG00000028362', u'ENSMUSG00000024793', u'ENSMUSG00000005533', u'ENSMUSG00000041827', u'ENSMUSG00000021846', u'ENSMUSG00000038642', u'ENSMUSG00000039004', u'ENSMUSG00000034394', u'ENSMUSG00000030341', u'ENSMUSG00000016496', u'ENSMUSG00000073411', u'ENSMUSG00000035385', u'ENSMUSG00000027995', u'ENSMUSG00000044827', u'ENSMUSG00000036594', u'ENSMUSG00000027164', u'ENSMUSG00000041515', u'ENSMUSG00000028599']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0006955', name='immune response', pop_count=88, alt_ids=[], level=2, depth=2, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000041827', u'ENSMUSG00000034394', u'ENSMUSG00000032661', u'ENSMUSG00000035352', u'ENSMUSG00000032508', u'ENSMUSG00000034855', u'ENSMUSG00000029561', u'ENSMUSG00000016496', u'ENSMUSG00000022074', u'ENSMUSG00000027399', u'ENSMUSG00000018930', u'ENSMUSG00000029605', u'ENSMUSG00000002699']), symbols=u'Ccl12 Ccl4 Cd274 Cxcl10 Il1a Lcp2 Lif Myd88 Oas1b Oas3 Oasl1 Oasl2 Tnfrsf10b', symbol_set=set([u'Lif', u'Oas1b', u'Ccl4', u'Cd274', u'Oasl2', u'Ccl12', u'Oasl1', u'Lcp2', u'Tnfrsf10b', u'Oas3', u'Il1a', u'Cxcl10', u'Myd88']), geneids='ENSMUSG00000041827 ENSMUSG00000034394 ENSMUSG00000032661 ENSMUSG00000035352 ENSMUSG00000032508 ENSMUSG00000029561 ENSMUSG00000034855 ENSMUSG00000027399 ENSMUSG00000016496 ENSMUSG00000022074 ENSMUSG00000002699 ENSMUSG00000018930 ENSMUSG00000029605', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=107, D1='FL', GO_name='immune response'), Nt(p_uncorrected=8.529826491330587e-05, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=0.007977493899391959, study_items=set([u'ENSMUSG00000046591', u'ENSMUSG00000032555', u'ENSMUSG00000003873', u'ENSMUSG00000030609', u'ENSMUSG00000028702', u'ENSMUSG00000027323', u'ENSMUSG00000017146', u'ENSMUSG00000034218', u'ENSMUSG00000078773']), NS='BP', pop_items=set([u'ENSMUSG00000025932', u'ENSMUSG00000046591', u'ENSMUSG00000003873', u'ENSMUSG00000018841', u'ENSMUSG00000027933', u'ENSMUSG00000031201', u'ENSMUSG00000025374', u'ENSMUSG00000027323', u'ENSMUSG00000038544', u'ENSMUSG00000024926', u'ENSMUSG00000030994', u'ENSMUSG00000031644', u'ENSMUSG00000022471', u'ENSMUSG00000020381', u'ENSMUSG00000031820', u'ENSMUSG00000028886', u'ENSMUSG00000026510', u'ENSMUSG00000026107', u'ENSMUSG00000017146', u'ENSMUSG00000021144', u'ENSMUSG00000000148', u'ENSMUSG00000090083', u'ENSMUSG00000021287', u'ENSMUSG00000007646', u'ENSMUSG00000078773', u'ENSMUSG00000035234', u'ENSMUSG00000026648', u'ENSMUSG00000068917', u'ENSMUSG00000033596', u'ENSMUSG00000014074', u'ENSMUSG00000032267', u'ENSMUSG00000022672', u'ENSMUSG00000025878', u'ENSMUSG00000040782', u'ENSMUSG00000032555', u'ENSMUSG00000049717', u'ENSMUSG00000028702', u'ENSMUSG00000030609', u'ENSMUSG00000052139', u'ENSMUSG00000021615', u'ENSMUSG00000034218', u'ENSMUSG00000003068']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0010212', name='response to ionizing radiation', pop_count=42, alt_ids=[], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000046591', u'ENSMUSG00000032555', u'ENSMUSG00000003873', u'ENSMUSG00000030609', u'ENSMUSG00000028702', u'ENSMUSG00000027323', u'ENSMUSG00000017146', u'ENSMUSG00000034218', u'ENSMUSG00000078773']), symbols=u'Aen Atm Bax Brca1 Rad51 Rad54b Rad54l Ticrr Topbp1', symbol_set=set([u'Brca1', 'Ticrr', u'Topbp1', u'Rad54l', u'Atm', u'Bax', u'Rad54b', u'Rad51', u'Aen']), geneids='ENSMUSG00000046591 ENSMUSG00000032555 ENSMUSG00000003873 ENSMUSG00000030609 ENSMUSG00000028702 ENSMUSG00000027323 ENSMUSG00000017146 ENSMUSG00000034218 ENSMUSG00000078773', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=5, D1='F', GO_name='response to ionizing radiation'), Nt(p_uncorrected=1.0613331792342115e-06, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.00016408427549568916, study_items=set([u'ENSMUSG00000034218', u'ENSMUSG00000020380', u'ENSMUSG00000002068', u'ENSMUSG00000028212', u'ENSMUSG00000027323']), NS='BP', pop_items=set([u'ENSMUSG00000028212', u'ENSMUSG00000031229', u'ENSMUSG00000020380', u'ENSMUSG00000002068', u'ENSMUSG00000027323', u'ENSMUSG00000034218']), pop_n=13836, p_sm_bonferroni=0.016080258998577537, is_obsolete=False, GO='GO:0070192', name='chromosome organization involved in meiotic cell cycle', pop_count=6, alt_ids=[], level=3, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034218', u'ENSMUSG00000020380', u'ENSMUSG00000028212', u'ENSMUSG00000002068', u'ENSMUSG00000027323']), symbols=u'Atm Ccne1 Ccne2 Rad50 Rad51', symbol_set=set([u'Ccne2', u'Ccne1', u'Atm', u'Rad51', u'Rad50']), geneids='ENSMUSG00000034218 ENSMUSG00000020380 ENSMUSG00000028212 ENSMUSG00000002068 ENSMUSG00000027323', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=17, D1='BHK', GO_name='chromosome organization involved in meiotic cell cycle'), Nt(p_uncorrected=0.0003012446800247431, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.022049073174178178, study_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000057789', u'ENSMUSG00000019979']), NS='BP', pop_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000024392', u'ENSMUSG00000036986', u'ENSMUSG00000056501', u'ENSMUSG00000059552', u'ENSMUSG00000026883', u'ENSMUSG00000029203', u'ENSMUSG00000020715', u'ENSMUSG00000028914', u'ENSMUSG00000027006', u'ENSMUSG00000027313', u'ENSMUSG00000023010', u'ENSMUSG00000071369', u'ENSMUSG00000025408', u'ENSMUSG00000057789', u'ENSMUSG00000022812', u'ENSMUSG00000036932', u'ENSMUSG00000030102', u'ENSMUSG00000033538', u'ENSMUSG00000031668', u'ENSMUSG00000031628', u'ENSMUSG00000042682', u'ENSMUSG00000042406', u'ENSMUSG00000053046', u'ENSMUSG00000019979', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000020484', u'ENSMUSG00000021831', u'ENSMUSG00000057329']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0070059', name='intrinsic apoptotic signaling pathway in response to endoplasmic reticulum stress', pop_count=30, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036986', u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000059552', u'ENSMUSG00000024521', u'ENSMUSG00000057789', u'ENSMUSG00000019979']), symbols=u'Apaf1 Bak1 Bax Bbc3 Pmaip1 Pml Trp53', symbol_set=set([u'Pmaip1', u'Trp53', u'Bax', u'Bak1', u'Pml', u'Bbc3', u'Apaf1']), geneids='ENSMUSG00000019979 ENSMUSG00000002083 ENSMUSG00000024521 ENSMUSG00000036986 ENSMUSG00000059552 ENSMUSG00000057789 ENSMUSG00000003873', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='ABF', GO_name='intrinsic apoptotic signaling pathway in response to endoplasmic reticulum stress'), Nt(p_uncorrected=0.00012860653072037162, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000035842', u'ENSMUSG00000039994', u'ENSMUSG00000001517', u'ENSMUSG00000036097']), NS='BP', pop_items=set([u'ENSMUSG00000032565', u'ENSMUSG00000001517', u'ENSMUSG00000021597', u'ENSMUSG00000036097', u'ENSMUSG00000039994', u'ENSMUSG00000035842', u'ENSMUSG00000041974']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:2000781', name='positive regulation of double-strand break repair', pop_count=7, alt_ids=[], level=7, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000035842', u'ENSMUSG00000039994', u'ENSMUSG00000001517', u'ENSMUSG00000036097']), symbols=u'Ddx11 Fam178a Foxm1 Timeless', symbol_set=set([u'Foxm1', u'Timeless', u'Fam178a', u'Ddx11']), geneids='ENSMUSG00000035842 ENSMUSG00000039994 ENSMUSG00000001517 ENSMUSG00000036097', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='A', GO_name='positive regulation of double-strand break repair'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0050896', name='', pop_count='', alt_ids='', level=1, depth=1, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=2241, D1='F', GO_name='response to stimulus'), Nt(p_uncorrected=8.945577520622059e-06, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.001075670198531308, study_items=set([u'ENSMUSG00000028718', u'ENSMUSG00000028896', u'ENSMUSG00000027883', u'ENSMUSG00000041431', u'ENSMUSG00000027496', u'ENSMUSG00000024056', u'ENSMUSG00000005233', u'ENSMUSG00000020897']), NS='BP', pop_items=set([u'ENSMUSG00000035198', u'ENSMUSG00000024056', u'ENSMUSG00000027883', u'ENSMUSG00000025337', u'ENSMUSG00000037020', u'ENSMUSG00000028718', u'ENSMUSG00000040729', u'ENSMUSG00000041431', u'ENSMUSG00000024096', u'ENSMUSG00000031516', u'ENSMUSG00000023345', u'ENSMUSG00000001151', u'ENSMUSG00000021701', u'ENSMUSG00000020897', u'ENSMUSG00000058070', u'ENSMUSG00000021693', u'ENSMUSG00000040250', u'ENSMUSG00000064302', u'ENSMUSG00000033392', u'ENSMUSG00000028896', u'ENSMUSG00000027496', u'ENSMUSG00000032479', u'ENSMUSG00000005233', u'ENSMUSG00000028832', u'ENSMUSG00000025410']), pop_n=13836, p_sm_bonferroni=0.1355344450149448, is_obsolete=False, GO='GO:0007052', name='mitotic spindle organization', pop_count=25, alt_ids=['GO:0043148'], level=4, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028718', u'ENSMUSG00000028896', u'ENSMUSG00000027883', u'ENSMUSG00000041431', u'ENSMUSG00000027496', u'ENSMUSG00000024056', u'ENSMUSG00000005233', u'ENSMUSG00000020897']), symbols=u'Aurka Aurkb Ccnb1 Gpsm2 Ndc80 Rcc1 Spc25 Stil', symbol_set=set([u'Rcc1', u'Stil', u'Ndc80', u'Ccnb1', u'Aurka', u'Aurkb', u'Gpsm2', u'Spc25']), geneids='ENSMUSG00000028718 ENSMUSG00000028896 ENSMUSG00000027883 ENSMUSG00000041431 ENSMUSG00000027496 ENSMUSG00000024056 ENSMUSG00000005233 ENSMUSG00000020897', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=5, D1='BCH', GO_name='mitotic spindle organization'), Nt(p_uncorrected=0.000352948400217597, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.025224156658947224, study_items=set([u'ENSMUSG00000017550', u'ENSMUSG00000022960', u'ENSMUSG00000004642']), NS='BP', pop_items=set([u'ENSMUSG00000017550', u'ENSMUSG00000022960', u'ENSMUSG00000046010', u'ENSMUSG00000004642']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0033260', name='nuclear DNA replication', pop_count=4, alt_ids=[], level=4, depth=10, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000017550', u'ENSMUSG00000022960', u'ENSMUSG00000004642']), symbols=u'Atad5 Donson Slbp', symbol_set=set([u'Atad5', u'Slbp', u'Donson']), geneids='ENSMUSG00000017550 ENSMUSG00000022960 ENSMUSG00000004642', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='BD', GO_name='nuclear DNA replication'), Nt(p_uncorrected=0.000352948400217597, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.025224156658947224, study_items=set([u'ENSMUSG00000027342', u'ENSMUSG00000029730', u'ENSMUSG00000027490']), NS='BP', pop_items=set([u'ENSMUSG00000022105', u'ENSMUSG00000027342', u'ENSMUSG00000029730', u'ENSMUSG00000027490']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0071466', name='cellular response to xenobiotic stimulus', pop_count=4, alt_ids=[], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027342', u'ENSMUSG00000029730', u'ENSMUSG00000027490']), symbols=u'E2f1 Mcm7 Pcna', symbol_set=set([u'Pcna', u'Mcm7', u'E2f1']), geneids='ENSMUSG00000027342 ENSMUSG00000029730 ENSMUSG00000027490', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BF', GO_name='cellular response to xenobiotic stimulus'), Nt(p_uncorrected=5.716066791862708e-05, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.005735372712815357, study_items=set([u'ENSMUSG00000023940', u'ENSMUSG00000034906', u'ENSMUSG00000034349', u'ENSMUSG00000028312']), NS='BP', pop_items=set([u'ENSMUSG00000032498', u'ENSMUSG00000028312', u'ENSMUSG00000041408', u'ENSMUSG00000034349', u'ENSMUSG00000034906', u'ENSMUSG00000023940']), pop_n=13836, p_sm_bonferroni=0.8660412796351189, is_obsolete=False, GO='GO:0045132', name='meiotic chromosome segregation', pop_count=6, alt_ids=[], level=3, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000023940', u'ENSMUSG00000034906', u'ENSMUSG00000034349', u'ENSMUSG00000028312']), symbols=u'Ncaph Sgol1 Smc2 Smc4', symbol_set=set([u'Smc4', u'Smc2', u'Sgol1', u'Ncaph']), geneids='ENSMUSG00000023940 ENSMUSG00000034906 ENSMUSG00000034349 ENSMUSG00000028312', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=7, D1='BCK', GO_name='meiotic chromosome segregation'), Nt(p_uncorrected=2.452210095801524e-05, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.0026349954015240347, study_items=set([u'ENSMUSG00000030641', u'ENSMUSG00000029521', u'ENSMUSG00000023067', u'ENSMUSG00000059552', u'ENSMUSG00000034218', u'ENSMUSG00000049932', u'ENSMUSG00000032409']), NS='BP', pop_items=set([u'ENSMUSG00000032409', u'ENSMUSG00000030641', u'ENSMUSG00000029110', u'ENSMUSG00000022471', u'ENSMUSG00000034345', u'ENSMUSG00000026187', u'ENSMUSG00000009406', u'ENSMUSG00000023067', u'ENSMUSG00000029521', u'ENSMUSG00000053110', u'ENSMUSG00000020694', u'ENSMUSG00000036940', u'ENSMUSG00000031583', u'ENSMUSG00000032060', u'ENSMUSG00000007659', u'ENSMUSG00000034218', u'ENSMUSG00000049932', u'ENSMUSG00000038984', u'ENSMUSG00000059552', u'ENSMUSG00000038418', u'ENSMUSG00000034659']), pop_n=13836, p_sm_bonferroni=0.3715343516148889, is_obsolete=False, GO='GO:0071480', name='cellular response to gamma radiation', pop_count=21, alt_ids=[], level=6, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034218', u'ENSMUSG00000030641', u'ENSMUSG00000029521', u'ENSMUSG00000059552', u'ENSMUSG00000049932', u'ENSMUSG00000023067', u'ENSMUSG00000032409']), symbols=u'Atm Atr Cdkn1a Chek2 Ddias H2afx Trp53', symbol_set=set(['Ddias', u'Trp53', u'Cdkn1a', u'Atm', u'H2afx', u'Atr', u'Chek2']), geneids='ENSMUSG00000030641 ENSMUSG00000029521 ENSMUSG00000023067 ENSMUSG00000059552 ENSMUSG00000034218 ENSMUSG00000049932 ENSMUSG00000032409', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BF', GO_name='cellular response to gamma radiation'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0030154', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=513, D1='BCE', GO_name='cell differentiation'), Nt(p_uncorrected=3.58209532492208e-08, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=8.349588656599144e-06, study_items=set([u'ENSMUSG00000041827', u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000035692', u'ENSMUSG00000024079', u'ENSMUSG00000023341', u'ENSMUSG00000046718', u'ENSMUSG00000024691', u'ENSMUSG00000020641', u'ENSMUSG00000029605']), NS='BP', pop_items=set([u'ENSMUSG00000032661', u'ENSMUSG00000023341', u'ENSMUSG00000062604', u'ENSMUSG00000027951', u'ENSMUSG00000024079', u'ENSMUSG00000063268', u'ENSMUSG00000066800', u'ENSMUSG00000024691', u'ENSMUSG00000009585', u'ENSMUSG00000041827', u'ENSMUSG00000010175', u'ENSMUSG00000029826', u'ENSMUSG00000037523', u'ENSMUSG00000032178', u'ENSMUSG00000039236', u'ENSMUSG00000046718', u'ENSMUSG00000060591', u'ENSMUSG00000038884', u'ENSMUSG00000029605', u'ENSMUSG00000025492', u'ENSMUSG00000032369', u'ENSMUSG00000035692', u'ENSMUSG00000004865', u'ENSMUSG00000020641']), pop_n=13836, p_sm_bonferroni=0.0005427232626789443, is_obsolete=False, GO='GO:0045071', name='negative regulation of viral genome replication', pop_count=24, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000041827', u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000035692', u'ENSMUSG00000046718', u'ENSMUSG00000023341', u'ENSMUSG00000024079', u'ENSMUSG00000024691', u'ENSMUSG00000020641', u'ENSMUSG00000029605']), symbols=u'Bst2 Eif2ak2 Fam111a Isg15 Isg20 Mx2 Oas1b Oas3 Oasl1 Rsad2', symbol_set=set([u'Eif2ak2', u'Mx2', u'Oasl1', u'Oas3', u'Isg15', u'Bst2', u'Isg20', u'Oas1b', u'Rsad2', u'Fam111a']), geneids='ENSMUSG00000041827 ENSMUSG00000032661 ENSMUSG00000039236 ENSMUSG00000035692 ENSMUSG00000046718 ENSMUSG00000023341 ENSMUSG00000024079 ENSMUSG00000024691 ENSMUSG00000020641 ENSMUSG00000029605', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='A', GO_name='negative regulation of viral genome replication'), Nt(p_uncorrected=6.805064957364015e-10, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=2.6436804915133895e-07, study_items=set([u'ENSMUSG00000019942', u'ENSMUSG00000028312', u'ENSMUSG00000038252', u'ENSMUSG00000034349', u'ENSMUSG00000020914', u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000042029']), NS='BP', pop_items=set([u'ENSMUSG00000047777', u'ENSMUSG00000008690', u'ENSMUSG00000028312', u'ENSMUSG00000038252', u'ENSMUSG00000019942', u'ENSMUSG00000020914', u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000034349', u'ENSMUSG00000042029']), pop_n=13836, p_sm_bonferroni=1.031035391690222e-05, is_obsolete=False, GO='GO:0030261', name='chromosome condensation', pop_count=10, alt_ids=['GO:0000068'], level=7, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034349', u'ENSMUSG00000028312', u'ENSMUSG00000038252', u'ENSMUSG00000019942', u'ENSMUSG00000020914', u'ENSMUSG00000034906', u'ENSMUSG00000035024', u'ENSMUSG00000042029']), symbols=u'Cdk1 Ncapd2 Ncapd3 Ncapg2 Ncaph Smc2 Smc4 Top2a', symbol_set=set([u'Ncapg2', u'Smc2', u'Smc4', u'Ncapd2', u'Ncapd3', u'Cdk1', u'Ncaph', u'Top2a']), geneids='ENSMUSG00000034349 ENSMUSG00000028312 ENSMUSG00000038252 ENSMUSG00000019942 ENSMUSG00000020914 ENSMUSG00000034906 ENSMUSG00000035024 ENSMUSG00000042029', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=5, D1='BH', GO_name='chromosome condensation'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0034641', name='', pop_count='', alt_ids='', level=3, depth=3, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=2095, D1='BD', GO_name='cellular nitrogen compound metabolic process'), Nt(p_uncorrected=2.8290260638386237e-06, study_count=11, study_n=624, namespace='biological_process', p_fdr_bh=0.0003947433489227972, study_items=set([u'ENSMUSG00000032397', u'ENSMUSG00000036086', u'ENSMUSG00000037474', u'ENSMUSG00000024521', u'ENSMUSG00000023067', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000005370', u'ENSMUSG00000030254', u'ENSMUSG00000040204', u'ENSMUSG00000028560']), NS='BP', pop_items=set([u'ENSMUSG00000018199', u'ENSMUSG00000020413', u'ENSMUSG00000059552', u'ENSMUSG00000018449', u'ENSMUSG00000030254', u'ENSMUSG00000050697', u'ENSMUSG00000025076', u'ENSMUSG00000030400', u'ENSMUSG00000032397', u'ENSMUSG00000036086', u'ENSMUSG00000030994', u'ENSMUSG00000037355', u'ENSMUSG00000028914', u'ENSMUSG00000045193', u'ENSMUSG00000035390', u'ENSMUSG00000028329', u'ENSMUSG00000051675', u'ENSMUSG00000040204', u'ENSMUSG00000054051', u'ENSMUSG00000034485', u'ENSMUSG00000026048', u'ENSMUSG00000033712', u'ENSMUSG00000026641', u'ENSMUSG00000002109', u'ENSMUSG00000024382', u'ENSMUSG00000021694', u'ENSMUSG00000026082', u'ENSMUSG00000024947', u'ENSMUSG00000002948', u'ENSMUSG00000031628', u'ENSMUSG00000028560', u'ENSMUSG00000031986', u'ENSMUSG00000024242', u'ENSMUSG00000036986', u'ENSMUSG00000022545', u'ENSMUSG00000020390', u'ENSMUSG00000037474', u'ENSMUSG00000024521', u'ENSMUSG00000023067', u'ENSMUSG00000005370', u'ENSMUSG00000028960', u'ENSMUSG00000021936', u'ENSMUSG00000038225', u'ENSMUSG00000016308']), pop_n=13836, p_sm_bonferroni=0.042862573893218986, is_obsolete=False, GO='GO:0009411', name='response to UV', pop_count=44, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032397', u'ENSMUSG00000036086', 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ENSMUSG00000038943 ENSMUSG00000026088 ENSMUSG00000012443 ENSMUSG00000058729 ENSMUSG00000017499 ENSMUSG00000001228 ENSMUSG00000031478 ENSMUSG00000043065 ENSMUSG00000020808 ENSMUSG00000017716 ENSMUSG00000029910 ENSMUSG00000036202 ENSMUSG00000035024 ENSMUSG00000005233 ENSMUSG00000044783 ENSMUSG00000022945', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=12, D1='BC', GO_name='cell cycle'), Nt(p_uncorrected=3.913269289633273e-08, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=8.849245224960258e-06, study_items=set([u'ENSMUSG00000069910', u'ENSMUSG00000040084', u'ENSMUSG00000038379', u'ENSMUSG00000027326', u'ENSMUSG00000019942', u'ENSMUSG00000020897', u'ENSMUSG00000040599']), NS='BP', pop_items=set([u'ENSMUSG00000069910', u'ENSMUSG00000022369', u'ENSMUSG00000047710', u'ENSMUSG00000038379', u'ENSMUSG00000027326', u'ENSMUSG00000019942', u'ENSMUSG00000040084', u'ENSMUSG00000032264', u'ENSMUSG00000020897', u'ENSMUSG00000040599']), pop_n=13836, p_sm_bonferroni=0.0005928994300723373, is_obsolete=False, GO='GO:0034501', name='protein localization to kinetochore', pop_count=10, alt_ids=[], level=8, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000069910', u'ENSMUSG00000040084', u'ENSMUSG00000038379', u'ENSMUSG00000020897', u'ENSMUSG00000027326', u'ENSMUSG00000019942', u'ENSMUSG00000040599']), symbols=u'Aurkb Bub1b Cdk1 Knl1 Mis12 Spdl1 Ttk', symbol_set=set([u'Aurkb', u'Bub1b', 'Spdl1', u'Ttk', u'Cdk1', 'Knl1', u'Mis12']), geneids='ENSMUSG00000069910 ENSMUSG00000040084 ENSMUSG00000038379 ENSMUSG00000027326 ENSMUSG00000019942 ENSMUSG00000020897 ENSMUSG00000040599', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='G', GO_name='protein localization to kinetochore'), Nt(p_uncorrected=2.839880208077678e-06, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=0.0003947433489227972, study_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000028212', u'ENSMUSG00000028884', u'ENSMUSG00000020380', u'ENSMUSG00000002068', u'ENSMUSG00000020898', u'ENSMUSG00000034218', u'ENSMUSG00000038685', u'ENSMUSG00000036875', u'ENSMUSG00000030528']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000026496', u'ENSMUSG00000042694', u'ENSMUSG00000018841', u'ENSMUSG00000030528', u'ENSMUSG00000031583', u'ENSMUSG00000035960', u'ENSMUSG00000030655', u'ENSMUSG00000038685', u'ENSMUSG00000058301', u'ENSMUSG00000027845', u'ENSMUSG00000028884', u'ENSMUSG00000022471', u'ENSMUSG00000031921', u'ENSMUSG00000020380', u'ENSMUSG00000038000', u'ENSMUSG00000020898', u'ENSMUSG00000023249', u'ENSMUSG00000000751', u'ENSMUSG00000024811', u'ENSMUSG00000026648', u'ENSMUSG00000028212', u'ENSMUSG00000033430', u'ENSMUSG00000002068', u'ENSMUSG00000022672', u'ENSMUSG00000038290', u'ENSMUSG00000026187', u'ENSMUSG00000091971', u'ENSMUSG00000022545', u'ENSMUSG00000022184', u'ENSMUSG00000000568', u'ENSMUSG00000029676', u'ENSMUSG00000032410', u'ENSMUSG00000036875', u'ENSMUSG00000034218', u'ENSMUSG00000025925']), pop_n=13836, p_sm_bonferroni=0.0430270250325849, is_obsolete=False, GO='GO:0000723', name='telomere maintenance', pop_count=36, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028224', u'ENSMUSG00000028212', u'ENSMUSG00000028884', u'ENSMUSG00000020380', u'ENSMUSG00000002068', u'ENSMUSG00000020898', u'ENSMUSG00000034218', u'ENSMUSG00000038685', u'ENSMUSG00000036875', u'ENSMUSG00000030528']), symbols=u'Atm Blm Ccne1 Ccne2 Ctc1 Dna2 Nbn Rad50 Rpa2 Rtel1', symbol_set=set([u'Atm', u'Ccne2', 'Ctc1', u'Ccne1', u'Rpa2', u'Blm', u'Dna2', u'Nbn', u'Rad50', u'Rtel1']), geneids='ENSMUSG00000028224 ENSMUSG00000028212 ENSMUSG00000028884 ENSMUSG00000020380 ENSMUSG00000002068 ENSMUSG00000020898 ENSMUSG00000034218 ENSMUSG00000030528 ENSMUSG00000036875 ENSMUSG00000038685', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=15, D1='ABDH', GO_name='telomere maintenance'), Nt(p_uncorrected=9.548068345280445e-07, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.00015389657819079151, study_items=set([u'ENSMUSG00000028884', u'ENSMUSG00000030346', u'ENSMUSG00000032113', u'ENSMUSG00000027323', u'ENSMUSG00000035455', u'ENSMUSG00000038685', u'ENSMUSG00000009628']), NS='BP', pop_items=set([u'ENSMUSG00000028884', u'ENSMUSG00000030346', u'ENSMUSG00000032113', u'ENSMUSG00000052144', u'ENSMUSG00000033430', u'ENSMUSG00000027323', u'ENSMUSG00000035455', u'ENSMUSG00000036940', u'ENSMUSG00000030697', u'ENSMUSG00000041974', u'ENSMUSG00000038685', u'ENSMUSG00000009628', u'ENSMUSG00000034748', u'ENSMUSG00000075324']), pop_n=13836, p_sm_bonferroni=0.014466278349934403, is_obsolete=False, GO='GO:0010569', name='regulation of double-strand break repair via homologous recombination', pop_count=14, alt_ids=[], level=7, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000035455', u'ENSMUSG00000028884', u'ENSMUSG00000030346', u'ENSMUSG00000032113', u'ENSMUSG00000038685', u'ENSMUSG00000009628', u'ENSMUSG00000027323']), symbols=u'Chek1 Fignl1 Rad51 Rad51ap1 Rpa2 Rtel1 Tex15', symbol_set=set([u'Fignl1', u'Tex15', u'Rpa2', u'Rad51ap1', u'Rad51', u'Rtel1', u'Chek1']), geneids='ENSMUSG00000028884 ENSMUSG00000030346 ENSMUSG00000032113 ENSMUSG00000027323 ENSMUSG00000035455 ENSMUSG00000038685 ENSMUSG00000009628', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=4, D1='A', GO_name='regulation of double-strand break repair via homologous recombination'), Nt(p_uncorrected=2.9401082193258835e-06, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.00040495981482733146, study_items=set([u'ENSMUSG00000031004', u'ENSMUSG00000027496', u'ENSMUSG00000025474', u'ENSMUSG00000027323', u'ENSMUSG00000024974', u'ENSMUSG00000000759', u'ENSMUSG00000041133']), NS='BP', pop_items=set([u'ENSMUSG00000032498', u'ENSMUSG00000051786', u'ENSMUSG00000027263', u'ENSMUSG00000031004', u'ENSMUSG00000027496', u'ENSMUSG00000025474', u'ENSMUSG00000027323', u'ENSMUSG00000032410', u'ENSMUSG00000005493', u'ENSMUSG00000000759', u'ENSMUSG00000024974', u'ENSMUSG00000068117', u'ENSMUSG00000041133', u'ENSMUSG00000000751', u'ENSMUSG00000033790', u'ENSMUSG00000079109']), pop_n=13836, p_sm_bonferroni=0.044545579631006464, is_obsolete=False, GO='GO:0007126', name='meiotic nuclear division', pop_count=16, alt_ids=[], level=3, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000024974', u'ENSMUSG00000000759', u'ENSMUSG00000031004', u'ENSMUSG00000027496', u'ENSMUSG00000041133', u'ENSMUSG00000025474', u'ENSMUSG00000027323']), symbols=u'Aurka Mki67 Rad51 Smc1a Smc3 Tubgcp2 Tubgcp3', symbol_set=set([u'Smc1a', u'Mki67', u'Smc3', u'Aurka', u'Rad51', u'Tubgcp2', u'Tubgcp3']), geneids='ENSMUSG00000031004 ENSMUSG00000027496 ENSMUSG00000025474 ENSMUSG00000027323 ENSMUSG00000024974 ENSMUSG00000000759 ENSMUSG00000041133', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=9, D1='BHK', GO_name='meiotic nuclear division'), Nt(p_uncorrected=7.750347293209027e-11, study_count=16, study_n=624, namespace='biological_process', p_fdr_bh=4.697020473576398e-08, study_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000021569', u'ENSMUSG00000041238', u'ENSMUSG00000039748', u'ENSMUSG00000036928', u'ENSMUSG00000020380', u'ENSMUSG00000041133', u'ENSMUSG00000003824', u'ENSMUSG00000024974', u'ENSMUSG00000027496', u'ENSMUSG00000025358', u'ENSMUSG00000026622', u'ENSMUSG00000026039', u'ENSMUSG00000049932', u'ENSMUSG00000019303', u'ENSMUSG00000009628']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000060657', u'ENSMUSG00000020349', u'ENSMUSG00000021569', u'ENSMUSG00000036928', u'ENSMUSG00000024974', u'ENSMUSG00000005493', u'ENSMUSG00000025358', u'ENSMUSG00000049932', u'ENSMUSG00000031928', u'ENSMUSG00000036196', u'ENSMUSG00000041238', u'ENSMUSG00000032221', u'ENSMUSG00000020380', u'ENSMUSG00000002190', u'ENSMUSG00000009628', u'ENSMUSG00000015149', u'ENSMUSG00000026039', u'ENSMUSG00000024033', u'ENSMUSG00000020152', u'ENSMUSG00000039748', u'ENSMUSG00000025862', u'ENSMUSG00000066979', u'ENSMUSG00000033392', u'ENSMUSG00000043410', u'ENSMUSG00000068117', u'ENSMUSG00000019303', u'ENSMUSG00000029279', u'ENSMUSG00000027496', u'ENSMUSG00000042396', u'ENSMUSG00000041133', u'ENSMUSG00000026341', u'ENSMUSG00000003824', u'ENSMUSG00000063576', u'ENSMUSG00000026622', u'ENSMUSG00000015597', u'ENSMUSG00000041775', u'ENSMUSG00000005893', u'ENSMUSG00000021395', u'ENSMUSG00000079470']), pop_n=13836, p_sm_bonferroni=1.1742551183940996e-06, is_obsolete=False, GO='GO:0051321', name='meiotic cell cycle', pop_count=40, alt_ids=[], level=3, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028224', u'ENSMUSG00000021569', u'ENSMUSG00000039748', u'ENSMUSG00000036928', u'ENSMUSG00000024974', u'ENSMUSG00000025358', u'ENSMUSG00000049932', u'ENSMUSG00000019303', u'ENSMUSG00000026039', u'ENSMUSG00000041238', u'ENSMUSG00000027496', u'ENSMUSG00000020380', u'ENSMUSG00000009628', u'ENSMUSG00000026622', u'ENSMUSG00000041133', u'ENSMUSG00000003824']), symbols=u'Aurka Cdk2 Exo1 H2afx Nbn Nek2 Psmc3ip Rad50 Rbbp8 Sgol2a Smc1a Smc3 Stag3 Syce2 Tex15 Trip13', symbol_set=set([u'Smc1a', u'Rbbp8', u'Nek2', 'Sgol2a', u'Tex15', u'Stag3', u'Smc3', u'Exo1', u'H2afx', u'Psmc3ip', u'Cdk2', u'Syce2', u'Nbn', u'Rad50', u'Trip13', u'Aurka']), geneids='ENSMUSG00000028224 ENSMUSG00000021569 ENSMUSG00000041238 ENSMUSG00000039748 ENSMUSG00000027496 ENSMUSG00000020380 ENSMUSG00000041133 ENSMUSG00000009628 ENSMUSG00000024974 ENSMUSG00000036928 ENSMUSG00000025358 ENSMUSG00000026622 ENSMUSG00000026039 ENSMUSG00000049932 ENSMUSG00000019303 ENSMUSG00000003824', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='BCK', GO_name='meiotic cell cycle'), Nt(p_uncorrected=9.97694118363845e-11, study_count=20, study_n=624, namespace='biological_process', p_fdr_bh=5.3985941383323624e-08, study_items=set([u'ENSMUSG00000035266', u'ENSMUSG00000028224', u'ENSMUSG00000049932', u'ENSMUSG00000028884', u'ENSMUSG00000027353', u'ENSMUSG00000041238', u'ENSMUSG00000030346', u'ENSMUSG00000059323', u'ENSMUSG00000020380', u'ENSMUSG00000028702', u'ENSMUSG00000041147', u'ENSMUSG00000034218', u'ENSMUSG00000017146', u'ENSMUSG00000020608', u'ENSMUSG00000045751', u'ENSMUSG00000030528', u'ENSMUSG00000027323', u'ENSMUSG00000078773', u'ENSMUSG00000051235', u'ENSMUSG00000044702']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000026914', u'ENSMUSG00000018841', u'ENSMUSG00000059323', u'ENSMUSG00000074781', u'ENSMUSG00000020413', u'ENSMUSG00000045751', u'ENSMUSG00000025374', u'ENSMUSG00000021264', u'ENSMUSG00000041974', u'ENSMUSG00000030528', u'ENSMUSG00000049932', u'ENSMUSG00000044702', u'ENSMUSG00000028884', u'ENSMUSG00000041238', u'ENSMUSG00000028933', u'ENSMUSG00000020380', u'ENSMUSG00000053914', u'ENSMUSG00000066440', u'ENSMUSG00000026434', u'ENSMUSG00000026107', u'ENSMUSG00000017146', u'ENSMUSG00000020752', u'ENSMUSG00000024317', u'ENSMUSG00000044627', u'ENSMUSG00000032705', u'ENSMUSG00000021287', u'ENSMUSG00000000751', u'ENSMUSG00000078773', u'ENSMUSG00000035266', u'ENSMUSG00000033458', u'ENSMUSG00000030750', u'ENSMUSG00000027353', u'ENSMUSG00000058298', u'ENSMUSG00000030346', u'ENSMUSG00000039623', u'ENSMUSG00000014243', u'ENSMUSG00000034154', u'ENSMUSG00000022545', u'ENSMUSG00000041147', u'ENSMUSG00000024943', u'ENSMUSG00000051238', u'ENSMUSG00000030243', u'ENSMUSG00000031072', u'ENSMUSG00000062270', u'ENSMUSG00000068264', u'ENSMUSG00000020608', u'ENSMUSG00000025066', u'ENSMUSG00000051235', u'ENSMUSG00000042541', u'ENSMUSG00000039738', u'ENSMUSG00000025218', u'ENSMUSG00000007646', u'ENSMUSG00000059586', u'ENSMUSG00000028702', u'ENSMUSG00000012483', u'ENSMUSG00000032512', u'ENSMUSG00000030166', u'ENSMUSG00000034218', u'ENSMUSG00000028820', u'ENSMUSG00000027323']), pop_n=13836, p_sm_bonferroni=1.5116063587330615e-06, is_obsolete=False, GO='GO:0000724', name='double-strand break repair via homologous recombination', pop_count=61, alt_ids=['GO:0016924'], level=7, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000035266', u'ENSMUSG00000028224', u'ENSMUSG00000020608', u'ENSMUSG00000030346', u'ENSMUSG00000059323', u'ENSMUSG00000041147', u'ENSMUSG00000045751', u'ENSMUSG00000030528', u'ENSMUSG00000049932', u'ENSMUSG00000051235', u'ENSMUSG00000044702', u'ENSMUSG00000028884', u'ENSMUSG00000041238', u'ENSMUSG00000020380', u'ENSMUSG00000028702', u'ENSMUSG00000027323', u'ENSMUSG00000017146', u'ENSMUSG00000027353', u'ENSMUSG00000034218', u'ENSMUSG00000078773']), symbols=u'Atm Blm Brca1 Brca2 Gen1 H2afx Helq Mcm8 Mms22l Nbn Palb2 Rad50 Rad51 Rad51ap1 Rad54b Rad54l Rbbp8 Rpa2 Smc6 Tonsl', symbol_set=set([u'Brca1', u'Brca2', u'Helq', u'Rad54b', u'Rad54l', u'Palb2', u'Tonsl', u'H2afx', u'Mms22l', u'Atm', u'Smc6', u'Blm', u'Rad51ap1', u'Rbbp8', u'Nbn', u'Rad51', u'Rad50', u'Gen1', u'Rpa2', u'Mcm8']), geneids='ENSMUSG00000028224 ENSMUSG00000035266 ENSMUSG00000049932 ENSMUSG00000028884 ENSMUSG00000020608 ENSMUSG00000041238 ENSMUSG00000030346 ENSMUSG00000059323 ENSMUSG00000020380 ENSMUSG00000028702 ENSMUSG00000027323 ENSMUSG00000045751 ENSMUSG00000017146 ENSMUSG00000027353 ENSMUSG00000034218 ENSMUSG00000030528 ENSMUSG00000041147 ENSMUSG00000078773 ENSMUSG00000051235 ENSMUSG00000044702', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='BDF', GO_name='double-strand break repair via homologous recombination'), Nt(p_uncorrected=6.079901029339501e-07, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=0.00010118906047752281, study_items=set([u'ENSMUSG00000071516', u'ENSMUSG00000049932', u'ENSMUSG00000068855', u'ENSMUSG00000061991', u'ENSMUSG00000069272', u'ENSMUSG00000069302', u'ENSMUSG00000069301', u'ENSMUSG00000025001', u'ENSMUSG00000061615', u'ENSMUSG00000063021']), NS='BP', pop_items=set([u'ENSMUSG00000002052', u'ENSMUSG00000049932', u'ENSMUSG00000071516', u'ENSMUSG00000040007', u'ENSMUSG00000031358', u'ENSMUSG00000069270', u'ENSMUSG00000069272', u'ENSMUSG00000020086', u'ENSMUSG00000069301', u'ENSMUSG00000069302', u'ENSMUSG00000039477', u'ENSMUSG00000047669', u'ENSMUSG00000031393', u'ENSMUSG00000039231', u'ENSMUSG00000039741', u'ENSMUSG00000068855', u'ENSMUSG00000060032', u'ENSMUSG00000023977', u'ENSMUSG00000078851', u'ENSMUSG00000063689', u'ENSMUSG00000062270', u'ENSMUSG00000025001', u'ENSMUSG00000061615', u'ENSMUSG00000031422', u'ENSMUSG00000015937', u'ENSMUSG00000061991', u'ENSMUSG00000037894', u'ENSMUSG00000048154', u'ENSMUSG00000063021', u'ENSMUSG00000025578', u'ENSMUSG00000041126']), pop_n=13836, p_sm_bonferroni=0.009211658049552278, is_obsolete=False, GO='GO:0006342', name='chromatin silencing', pop_count=31, alt_ids=['GO:0016440'], level=4, depth=11, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000071516', u'ENSMUSG00000061615', u'ENSMUSG00000068855', u'ENSMUSG00000061991', u'ENSMUSG00000069272', u'ENSMUSG00000063021', u'ENSMUSG00000069301', u'ENSMUSG00000069302', u'ENSMUSG00000049932', u'ENSMUSG00000025001']), symbols=u'H2afx Hells Hist1h2ab Hist1h2ae Hist1h2af Hist1h2ag Hist1h2ah Hist1h2ai Hist1h2ak Hist2h2ac', symbol_set=set([u'Hells', u'H2afx', u'Hist1h2ai', u'Hist1h2ah', u'Hist1h2ak', u'Hist1h2ae', u'Hist1h2ag', u'Hist1h2af', u'Hist2h2ac', u'Hist1h2ab']), geneids='ENSMUSG00000071516 ENSMUSG00000061615 ENSMUSG00000068855 ENSMUSG00000061991 ENSMUSG00000069272 ENSMUSG00000069302 ENSMUSG00000069301 ENSMUSG00000025001 ENSMUSG00000049932 ENSMUSG00000063021', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=9, D1='ABCH', GO_name='chromatin silencing'), Nt(p_uncorrected=3.126181591424736e-06, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.000426709705330416, study_items=set([u'ENSMUSG00000028212', u'ENSMUSG00000036928', u'ENSMUSG00000034023', u'ENSMUSG00000002068', u'ENSMUSG00000034329', u'ENSMUSG00000009628']), NS='BP', pop_items=set([u'ENSMUSG00000032498', u'ENSMUSG00000031928', u'ENSMUSG00000028212', u'ENSMUSG00000036817', u'ENSMUSG00000036928', u'ENSMUSG00000034023', u'ENSMUSG00000002068', u'ENSMUSG00000005493', u'ENSMUSG00000028614', u'ENSMUSG00000034329', u'ENSMUSG00000009628']), pop_n=13836, p_sm_bonferroni=0.04736477729167617, is_obsolete=False, GO='GO:0007129', name='synapsis', pop_count=11, alt_ids=[], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028212', u'ENSMUSG00000036928', u'ENSMUSG00000034329', u'ENSMUSG00000034023', u'ENSMUSG00000009628', u'ENSMUSG00000002068']), symbols=u'Brip1 Ccne1 Ccne2 Fancd2 Stag3 Tex15', symbol_set=set([u'Ccne2', u'Stag3', u'Ccne1', u'Tex15', u'Fancd2', u'Brip1']), geneids='ENSMUSG00000028212 ENSMUSG00000036928 ENSMUSG00000034023 ENSMUSG00000002068 ENSMUSG00000034329 ENSMUSG00000009628', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BHK', GO_name='synapsis'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0051179', name='', pop_count='', alt_ids='', level=1, depth=1, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=2176, D1='G', GO_name='localization'), Nt(p_uncorrected=0.00012860653072037162, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000062727', u'ENSMUSG00000058385', u'ENSMUSG00000047246', u'ENSMUSG00000069268']), NS='BP', pop_items=set([u'ENSMUSG00000058385', u'ENSMUSG00000047246', u'ENSMUSG00000068854', u'ENSMUSG00000079641', u'ENSMUSG00000018102', u'ENSMUSG00000062727', u'ENSMUSG00000069268']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0002227', name='innate immune response in 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u'ENSMUSG00000034674', u'ENSMUSG00000024317', u'ENSMUSG00000000751', u'ENSMUSG00000036822', u'ENSMUSG00000026648', u'ENSMUSG00000024943', u'ENSMUSG00000035958', u'ENSMUSG00000024947', u'ENSMUSG00000058317', u'ENSMUSG00000025066', u'ENSMUSG00000023953', u'ENSMUSG00000030744', u'ENSMUSG00000037032', u'ENSMUSG00000030983', u'ENSMUSG00000020390', u'ENSMUSG00000028886', u'ENSMUSG00000027164', u'ENSMUSG00000052139', u'ENSMUSG00000016308']), pop_n=13836, p_sm_bonferroni=7.768725664767739e-07, is_obsolete=False, GO='GO:0006974', name='cellular response to DNA damage stimulus', pop_count=400, alt_ids=['GO:0034984'], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028224', u'ENSMUSG00000046591', u'ENSMUSG00000003873', u'ENSMUSG00000046295', u'ENSMUSG00000021668', u'ENSMUSG00000024974', u'ENSMUSG00000026196', u'ENSMUSG00000025358', u'ENSMUSG00000030254', u'ENSMUSG00000059552', u'ENSMUSG00000030528', u'ENSMUSG00000007080', u'ENSMUSG00000036086', u'ENSMUSG00000041238', u'ENSMUSG00000034206', u'ENSMUSG00000039994', u'ENSMUSG00000020380', u'ENSMUSG00000039187', u'ENSMUSG00000020914', u'ENSMUSG00000027067', u'ENSMUSG00000025507', u'ENSMUSG00000017146', u'ENSMUSG00000020898', u'ENSMUSG00000040204', u'ENSMUSG00000034329', u'ENSMUSG00000041133', u'ENSMUSG00000024742', u'ENSMUSG00000039748', u'ENSMUSG00000029521', u'ENSMUSG00000035365', u'ENSMUSG00000001228', u'ENSMUSG00000020185', u'ENSMUSG00000041147', u'ENSMUSG00000005481', u'ENSMUSG00000028560', u'ENSMUSG00000009628', u'ENSMUSG00000051235', u'ENSMUSG00000032555', u'ENSMUSG00000024521', u'ENSMUSG00000002083', u'ENSMUSG00000023067', u'ENSMUSG00000028702', u'ENSMUSG00000002221', u'ENSMUSG00000035764', u'ENSMUSG00000027342', u'ENSMUSG00000036875', u'ENSMUSG00000002835', u'ENSMUSG00000036822', u'ENSMUSG00000032815', u'ENSMUSG00000034023', u'ENSMUSG00000029730', u'ENSMUSG00000045102', u'ENSMUSG00000020471', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000049932', u'ENSMUSG00000056394', u'ENSMUSG00000044702', u'ENSMUSG00000032397', u'ENSMUSG00000030641', u'ENSMUSG00000028884', u'ENSMUSG00000030609', u'ENSMUSG00000032113', u'ENSMUSG00000030726', u'ENSMUSG00000027353', u'ENSMUSG00000002748', u'ENSMUSG00000061607', u'ENSMUSG00000078773', u'ENSMUSG00000032409', u'ENSMUSG00000038644', u'ENSMUSG00000022906', u'ENSMUSG00000001517', u'ENSMUSG00000030346', u'ENSMUSG00000073705', u'ENSMUSG00000035958', u'ENSMUSG00000036202', u'ENSMUSG00000045751', u'ENSMUSG00000031311', u'ENSMUSG00000023953', u'ENSMUSG00000017550', u'ENSMUSG00000051768', u'ENSMUSG00000026669', u'ENSMUSG00000036097', u'ENSMUSG00000037474', u'ENSMUSG00000027323', u'ENSMUSG00000049502', u'ENSMUSG00000005370', u'ENSMUSG00000042489', u'ENSMUSG00000020608', u'ENSMUSG00000034218', u'ENSMUSG00000027242', u'ENSMUSG00000022945', u'ENSMUSG00000038774']), symbols=u'Aen Ankle1 Apitd1 Ascc3 Atad5 Atm Atr Bard1 Bax Baz1b Bbc3 Blm Brca1 Brca2 Brip1 Cdk2 Cdkn1a Chaf1a Chaf1b Chek1 Chek2 Clspn Ctc1 Ddias Ddx11 Ddx39 Dna2 Dtl Dtx3l E2f7 Exo1 Fam178a Fanca Fancd2 Fanci Fbxo45 Fen1 Foxm1 Gen1 H2afx Lig1 Mcm10 Mcm7 Mcm8 Mdc1 Mms22l Msh6 Nbn Nono Palb2 Parp9 Parpbp Paxip1 Pclaf Pcna Pidd1 Pmaip1 Pold1 Pold2 Pold3 Pole Polh Polk Poln Polq Rad18 Rad50 Rad51 Rad51ap1 Rad54b Rad54l Rbbp8 Rif1 Rpa2 Rtel1 Smc1a Smc3 Smc6 Ssrp1 Tdp2 Tex15 Ticrr Timeless Tipin Top2a Topbp1 Topors Trp53 Uhrf1 Usp1 Wdr76 Xrcc1 Zranb3', symbol_set=set([u'Rbbp8', u'Rif1', 'Ticrr', u'Usp1', u'Msh6', u'Paxip1', u'Smc6', u'Chek2', u'Tdp2', u'Top2a', u'Mms22l', u'Rad51ap1', u'Brip1', u'Topors', u'Smc1a', u'Atad5', 'Ctc1', u'Rad18', u'Bax', 'Pidd1', u'Fam178a', u'Dtx3l', u'Polq', u'Ddx11', u'Pole', u'Poln', u'Rtel1', u'Polk', u'Polh', 'Parpbp', u'Palb2', u'Mdc1', u'Blm', u'Fbxo45', u'Brca2', u'Rpa2', u'Rad54l', u'Baz1b', u'Lig1', u'Xrcc1', 'Pclaf', u'Chek1', u'Wdr76', u'Rad54b', u'Nono', u'Cdkn1a', u'Timeless', u'Bbc3', u'Dna2', u'Parp9', u'Ssrp1', u'Exo1', u'Cdk2', u'Fen1', u'Uhrf1', u'Mcm10', u'Clspn', u'Gen1', u'Pold1', u'Pold2', u'Pold3', u'Bard1', u'Foxm1', 'Ddias', u'Pmaip1', u'Dtl', u'Tex15', u'Fancd2', u'Aen', u'Tipin', u'Nbn', u'E2f7', u'Brca1', u'H2afx', u'Mcm7', u'Chaf1a', u'Chaf1b', u'Ascc3', u'Mcm8', u'Topbp1', u'Smc3', u'Apitd1', u'Rad51', u'Rad50', u'Ankle1', u'Zranb3', u'Trp53', u'Atm', u'Atr', u'Ddx39', u'Pcna', u'Fanca', u'Fanci']), geneids='ENSMUSG00000028224 ENSMUSG00000046591 ENSMUSG00000003873 ENSMUSG00000046295 ENSMUSG00000021668 ENSMUSG00000024974 ENSMUSG00000025358 ENSMUSG00000059552 ENSMUSG00000007080 ENSMUSG00000020380 ENSMUSG00000027067 ENSMUSG00000025507 ENSMUSG00000017146 ENSMUSG00000020898 ENSMUSG00000034329 ENSMUSG00000039748 ENSMUSG00000029521 ENSMUSG00000020185 ENSMUSG00000041147 ENSMUSG00000009628 ENSMUSG00000032555 ENSMUSG00000023067 ENSMUSG00000036875 ENSMUSG00000038644 ENSMUSG00000032815 ENSMUSG00000034023 ENSMUSG00000029730 ENSMUSG00000045102 ENSMUSG00000035842 ENSMUSG00000038685 ENSMUSG00000049932 ENSMUSG00000056394 ENSMUSG00000032397 ENSMUSG00000028884 ENSMUSG00000030609 ENSMUSG00000078773 ENSMUSG00000032409 ENSMUSG00000022906 ENSMUSG00000045751 ENSMUSG00000031311 ENSMUSG00000051768 ENSMUSG00000036097 ENSMUSG00000037474 ENSMUSG00000027323 ENSMUSG00000005370 ENSMUSG00000042489 ENSMUSG00000034218 ENSMUSG00000027242 ENSMUSG00000038774 ENSMUSG00000026196 ENSMUSG00000030254 ENSMUSG00000030528 ENSMUSG00000036086 ENSMUSG00000041238 ENSMUSG00000039994 ENSMUSG00000039187 ENSMUSG00000020914 ENSMUSG00000034206 ENSMUSG00000040204 ENSMUSG00000041133 ENSMUSG00000024742 ENSMUSG00000035365 ENSMUSG00000026669 ENSMUSG00000005481 ENSMUSG00000028560 ENSMUSG00000051235 ENSMUSG00000024521 ENSMUSG00000028702 ENSMUSG00000002221 ENSMUSG00000035764 ENSMUSG00000027342 ENSMUSG00000020471 ENSMUSG00000002835 ENSMUSG00000044702 ENSMUSG00000030641 ENSMUSG00000032113 ENSMUSG00000030726 ENSMUSG00000027353 ENSMUSG00000002748 ENSMUSG00000061607 ENSMUSG00000036822 ENSMUSG00000001517 ENSMUSG00000030346 ENSMUSG00000073705 ENSMUSG00000035958 ENSMUSG00000023953 ENSMUSG00000017550 ENSMUSG00000001228 ENSMUSG00000002083 ENSMUSG00000036202 ENSMUSG00000049502 ENSMUSG00000020608 ENSMUSG00000022945', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=80, D1='BF', GO_name='cellular response to DNA damage stimulus'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0045595', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=864, D1='A', GO_name='regulation of cell differentiation'), Nt(p_uncorrected=9.181792629849965e-06, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.0010783979855415258, study_items=set([u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000023067', u'ENSMUSG00000020184', u'ENSMUSG00000025507']), NS='BP', pop_items=set([u'ENSMUSG00000036986', u'ENSMUSG00000029863', u'ENSMUSG00000076431', u'ENSMUSG00000023067', u'ENSMUSG00000020184', u'ENSMUSG00000045867', u'ENSMUSG00000025507', u'ENSMUSG00000059552']), pop_n=13836, p_sm_bonferroni=0.13911334013485682, is_obsolete=False, GO='GO:0006977', name='DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest', pop_count=8, alt_ids=[], level=6, depth=11, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000023067', u'ENSMUSG00000020184', u'ENSMUSG00000025507']), symbols=u'Cdkn1a Mdm2 Pidd1 Pml Trp53', symbol_set=set([u'Pml', u'Cdkn1a', 'Pidd1', u'Mdm2', u'Trp53']), geneids='ENSMUSG00000036986 ENSMUSG00000025507 ENSMUSG00000023067 ENSMUSG00000020184 ENSMUSG00000059552', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='ABF', GO_name='DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0098542', name='', pop_count='', alt_ids='', level=4, depth=5, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=37, D1='F', GO_name='defense response to other organism'), Nt(p_uncorrected=5.337213979495868e-08, study_count=11, study_n=624, namespace='biological_process', p_fdr_bh=1.1552018429048844e-05, study_items=set([u'ENSMUSG00000037725', u'ENSMUSG00000029177', u'ENSMUSG00000034311', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000027306', u'ENSMUSG00000030867', u'ENSMUSG00000002307', u'ENSMUSG00000003779', u'ENSMUSG00000026088', u'ENSMUSG00000024989']), NS='BP', pop_items=set([u'ENSMUSG00000029516', u'ENSMUSG00000027306', u'ENSMUSG00000038467', u'ENSMUSG00000036777', u'ENSMUSG00000042364', u'ENSMUSG00000038545', u'ENSMUSG00000001833', u'ENSMUSG00000037725', u'ENSMUSG00000003779', u'ENSMUSG00000023015', u'ENSMUSG00000030867', u'ENSMUSG00000024989', u'ENSMUSG00000069601', u'ENSMUSG00000037855', u'ENSMUSG00000056201', u'ENSMUSG00000028832', u'ENSMUSG00000005871', u'ENSMUSG00000024068', u'ENSMUSG00000022961', u'ENSMUSG00000029177', u'ENSMUSG00000026088', u'ENSMUSG00000002365', u'ENSMUSG00000025235', u'ENSMUSG00000032254', u'ENSMUSG00000034311', u'ENSMUSG00000006906', u'ENSMUSG00000002307', u'ENSMUSG00000020900', u'ENSMUSG00000020315', u'ENSMUSG00000032733', u'ENSMUSG00000027363']), pop_n=13836, p_sm_bonferroni=0.000808641290033419, is_obsolete=False, GO='GO:0000281', name='mitotic cytokinesis', pop_count=31, alt_ids=[], level=4, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000030867', u'ENSMUSG00000029177', u'ENSMUSG00000027306', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000034311', u'ENSMUSG00000037725', u'ENSMUSG00000002307', u'ENSMUSG00000003779', u'ENSMUSG00000026088', u'ENSMUSG00000024989']), symbols=u'Cenpa Cep55 Ckap2 Daxx Kif20a Kif23 Kif4 Mitd1 Nusap1 Plk1 Racgap1', symbol_set=set([u'Daxx', u'Nusap1', u'Plk1', u'Kif4', u'Cep55', u'Kif23', u'Racgap1', u'Cenpa', u'Ckap2', u'Mitd1', u'Kif20a']), geneids='ENSMUSG00000030867 ENSMUSG00000003779 ENSMUSG00000034311 ENSMUSG00000032254 ENSMUSG00000023015 ENSMUSG00000027306 ENSMUSG00000002307 ENSMUSG00000037725 ENSMUSG00000029177 ENSMUSG00000026088 ENSMUSG00000024989', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='B', GO_name='mitotic cytokinesis'), Nt(p_uncorrected=1.4774031261817023e-06, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.00022162509668097993, study_items=set([u'ENSMUSG00000024056', u'ENSMUSG00000028678', u'ENSMUSG00000043065', u'ENSMUSG00000045328', u'ENSMUSG00000026605', u'ENSMUSG00000030677']), NS='BP', pop_items=set([u'ENSMUSG00000027654', u'ENSMUSG00000028214', u'ENSMUSG00000020628', u'ENSMUSG00000024056', u'ENSMUSG00000028678', u'ENSMUSG00000043065', u'ENSMUSG00000045328', u'ENSMUSG00000026605', u'ENSMUSG00000023919', u'ENSMUSG00000030677']), pop_n=13836, p_sm_bonferroni=0.022384134764778973, is_obsolete=False, GO='GO:0051310', name='metaphase plate congression', pop_count=10, alt_ids=[], level=5, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000026605', u'ENSMUSG00000024056', u'ENSMUSG00000028678', u'ENSMUSG00000043065', u'ENSMUSG00000030677', u'ENSMUSG00000045328']), symbols=u'Cenpe Cenpf Kif22 Kif2c Ndc80 Spice1', symbol_set=set([u'Cenpf', u'Cenpe', u'Kif22', u'Spice1', u'Ndc80', u'Kif2c']), geneids='ENSMUSG00000024056 ENSMUSG00000028678 ENSMUSG00000043065 ENSMUSG00000045328 ENSMUSG00000026605 ENSMUSG00000030677', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=4, D1='G', GO_name='metaphase plate congression'), Nt(p_uncorrected=1.976111142578265e-05, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.002185405833664474, study_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000045328', u'ENSMUSG00000030254', u'ENSMUSG00000020608']), NS='BP', pop_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000030254', u'ENSMUSG00000024943', u'ENSMUSG00000045328', u'ENSMUSG00000020608']), pop_n=13836, p_sm_bonferroni=0.29940059921203294, is_obsolete=False, GO='GO:0051984', name='positive regulation of chromosome segregation', pop_count=5, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000017499', u'ENSMUSG00000030254', u'ENSMUSG00000045328', u'ENSMUSG00000020608']), symbols=u'Cdc6 Cenpe Rad18 Smc6', symbol_set=set([u'Cenpe', u'Rad18', u'Cdc6', u'Smc6']), geneids='ENSMUSG00000017499 ENSMUSG00000045328 ENSMUSG00000030254 ENSMUSG00000020608', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=26, D1='A', GO_name='positive regulation of chromosome segregation'), Nt(p_uncorrected=2.89924240239775e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.0030717777369740074, study_items=set([u'ENSMUSG00000021569', u'ENSMUSG00000032555', u'ENSMUSG00000020380', u'ENSMUSG00000027323', u'ENSMUSG00000019214', u'ENSMUSG00000005370']), NS='BP', pop_items=set([u'ENSMUSG00000032498', u'ENSMUSG00000021569', u'ENSMUSG00000007646', u'ENSMUSG00000032555', u'ENSMUSG00000018841', u'ENSMUSG00000005493', u'ENSMUSG00000020380', u'ENSMUSG00000014850', u'ENSMUSG00000027323', u'ENSMUSG00000019214', u'ENSMUSG00000005370', u'ENSMUSG00000028933', u'ENSMUSG00000021287', u'ENSMUSG00000024151', u'ENSMUSG00000032534']), pop_n=13836, p_sm_bonferroni=0.4392642163872831, is_obsolete=False, GO='GO:0007131', name='reciprocal meiotic recombination', pop_count=15, alt_ids=['GO:0000021', 'GO:0007145'], level=3, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000021569', u'ENSMUSG00000005370', u'ENSMUSG00000032555', u'ENSMUSG00000019214', u'ENSMUSG00000020380', u'ENSMUSG00000027323']), symbols=u'Chtf18 Msh6 Rad50 Rad51 Topbp1 Trip13', symbol_set=set([u'Chtf18', u'Topbp1', u'Msh6', u'Rad51', u'Rad50', u'Trip13']), geneids='ENSMUSG00000021569 ENSMUSG00000032555 ENSMUSG00000020380 ENSMUSG00000027323 ENSMUSG00000019214 ENSMUSG00000005370', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BDK', GO_name='reciprocal meiotic recombination'), Nt(p_uncorrected=3.830456154235559e-05, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.004030225082834927, study_items=set([u'ENSMUSG00000059552', u'ENSMUSG00000023067', u'ENSMUSG00000001517', u'ENSMUSG00000029521', u'ENSMUSG00000041147']), NS='BP', pop_items=set([u'ENSMUSG00000061436', u'ENSMUSG00000024926', u'ENSMUSG00000029026', u'ENSMUSG00000001517', u'ENSMUSG00000029521', u'ENSMUSG00000030330', u'ENSMUSG00000023067', u'ENSMUSG00000025665', u'ENSMUSG00000041147', u'ENSMUSG00000059552']), pop_n=13836, p_sm_bonferroni=0.5803524119282295, is_obsolete=False, GO='GO:0006978', name='DNA damage response, signal transduction by p53 class mediator resulting in transcription of p21 class mediator', pop_count=10, alt_ids=[], level=6, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000059552', u'ENSMUSG00000001517', u'ENSMUSG00000023067', u'ENSMUSG00000029521', u'ENSMUSG00000041147']), symbols=u'Brca2 Cdkn1a Chek2 Foxm1 Trp53', symbol_set=set([u'Chek2', u'Cdkn1a', u'Brca2', u'Foxm1', u'Trp53']), geneids='ENSMUSG00000059552 ENSMUSG00000023067 ENSMUSG00000001517 ENSMUSG00000029521 ENSMUSG00000041147', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='ABF', GO_name='DNA damage response, signal transduction by p53 class mediator resulting in transcription of p21 class mediator'), Nt(p_uncorrected=0.0002694261654455126, study_count=1, study_n=624, namespace='biological_process', p_fdr_bh=0.020108747944162373, study_items=set([u'ENSMUSG00000037321']), NS='BP', pop_items=set([u'ENSMUSG00000033720', u'ENSMUSG00000032839', u'ENSMUSG00000024096', u'ENSMUSG00000037321', u'ENSMUSG00000045246', u'ENSMUSG00000022404', u'ENSMUSG00000020865', u'ENSMUSG00000018507', u'ENSMUSG00000050556', u'ENSMUSG00000009731', u'ENSMUSG00000057378', u'ENSMUSG00000034402', u'ENSMUSG00000040164', u'ENSMUSG00000002984', u'ENSMUSG00000024270', u'ENSMUSG00000050144', u'ENSMUSG00000026791', u'ENSMUSG00000034320', u'ENSMUSG00000030592', u'ENSMUSG00000042604', u'ENSMUSG00000029924', u'ENSMUSG00000015968', u'ENSMUSG00000004110', u'ENSMUSG00000054640', u'ENSMUSG00000063873', u'ENSMUSG00000016319', u'ENSMUSG00000025759', u'ENSMUSG00000020620', u'ENSMUSG00000037490', u'ENSMUSG00000071253', u'ENSMUSG00000040584', u'ENSMUSG00000026819', u'ENSMUSG00000092083', u'ENSMUSG00000028033', u'ENSMUSG00000030102', u'ENSMUSG00000021432', u'ENSMUSG00000020873', u'ENSMUSG00000039838', u'ENSMUSG00000048833', u'ENSMUSG00000033147', u'ENSMUSG00000022094', u'ENSMUSG00000018459', u'ENSMUSG00000055782', u'ENSMUSG00000027010', u'ENSMUSG00000036949', u'ENSMUSG00000048677', u'ENSMUSG00000025212', u'ENSMUSG00000036636', u'ENSMUSG00000027716', u'ENSMUSG00000033486', u'ENSMUSG00000020805', u'ENSMUSG00000037089', u'ENSMUSG00000031974', u'ENSMUSG00000020102', u'ENSMUSG00000022003', u'ENSMUSG00000039463', u'ENSMUSG00000040569', u'ENSMUSG00000041771', u'ENSMUSG00000020744', u'ENSMUSG00000018999', u'ENSMUSG00000021474', u'ENSMUSG00000024112', u'ENSMUSG00000021265', u'ENSMUSG00000027895', u'ENSMUSG00000024818', u'ENSMUSG00000040896', u'ENSMUSG00000022822', u'ENSMUSG00000009292', u'ENSMUSG00000002346', u'ENSMUSG00000045100', u'ENSMUSG00000030376', u'ENSMUSG00000025036', u'ENSMUSG00000029016', u'ENSMUSG00000005802', u'ENSMUSG00000056258', u'ENSMUSG00000005674', u'ENSMUSG00000028645', u'ENSMUSG00000031378', u'ENSMUSG00000035681', u'ENSMUSG00000030287', u'ENSMUSG00000041945', u'ENSMUSG00000022843', u'ENSMUSG00000019080', u'ENSMUSG00000000197', u'ENSMUSG00000000792', u'ENSMUSG00000037455', u'ENSMUSG00000028631', u'ENSMUSG00000018900', u'ENSMUSG00000026220', u'ENSMUSG00000021771', u'ENSMUSG00000014158', u'ENSMUSG00000032313', u'ENSMUSG00000024597', u'ENSMUSG00000064329', u'ENSMUSG00000031333', u'ENSMUSG00000033965', u'ENSMUSG00000038077', u'ENSMUSG00000055296', u'ENSMUSG00000023088', u'ENSMUSG00000020402', u'ENSMUSG00000041920', u'ENSMUSG00000066595', u'ENSMUSG00000000605', u'ENSMUSG00000019838', u'ENSMUSG00000020331', u'ENSMUSG00000028127', u'ENSMUSG00000023259', u'ENSMUSG00000029221', u'ENSMUSG00000004319', u'ENSMUSG00000041710', u'ENSMUSG00000016346', u'ENSMUSG00000037579', u'ENSMUSG00000017756', u'ENSMUSG00000020334', u'ENSMUSG00000041654', u'ENSMUSG00000019935', u'ENSMUSG00000008892', u'ENSMUSG00000026614', u'ENSMUSG00000032741', u'ENSMUSG00000037434', u'ENSMUSG00000040322', u'ENSMUSG00000009378', u'ENSMUSG00000031633', u'ENSMUSG00000039908', u'ENSMUSG00000020829', u'ENSMUSG00000029151', u'ENSMUSG00000027896', u'ENSMUSG00000026198', u'ENSMUSG00000019082', u'ENSMUSG00000038319', u'ENSMUSG00000045053', u'ENSMUSG00000024339', u'ENSMUSG00000017740', u'ENSMUSG00000027748', u'ENSMUSG00000051111', u'ENSMUSG00000013275', u'ENSMUSG00000042644', u'ENSMUSG00000040724', u'ENSMUSG00000020651', u'ENSMUSG00000089774', u'ENSMUSG00000021629', u'ENSMUSG00000023033', u'ENSMUSG00000029802', u'ENSMUSG00000028976', u'ENSMUSG00000075316', u'ENSMUSG00000001082', u'ENSMUSG00000038212', u'ENSMUSG00000050822', u'ENSMUSG00000002105', u'ENSMUSG00000063354', u'ENSMUSG00000029408', u'ENSMUSG00000047959', u'ENSMUSG00000004902', u'ENSMUSG00000070570', u'ENSMUSG00000030089', u'ENSMUSG00000059742', u'ENSMUSG00000053897', u'ENSMUSG00000032754', u'ENSMUSG00000046329', u'ENSMUSG00000021313', u'ENSMUSG00000046822', u'ENSMUSG00000032988', u'ENSMUSG00000051331', u'ENSMUSG00000030249', u'ENSMUSG00000064267', u'ENSMUSG00000063698', u'ENSMUSG00000004113', u'ENSMUSG00000029650', u'ENSMUSG00000058248', u'ENSMUSG00000024327', u'ENSMUSG00000037762', u'ENSMUSG00000032511', u'ENSMUSG00000052310', u'ENSMUSG00000031934', u'ENSMUSG00000028970', u'ENSMUSG00000015112', u'ENSMUSG00000040447', u'ENSMUSG00000050953', u'ENSMUSG00000006641', u'ENSMUSG00000053025', u'ENSMUSG00000027340', u'ENSMUSG00000004317', u'ENSMUSG00000038497', u'ENSMUSG00000024036', u'ENSMUSG00000060882', u'ENSMUSG00000043673', u'ENSMUSG00000032902', u'ENSMUSG00000040441', u'ENSMUSG00000021730', u'ENSMUSG00000031129', u'ENSMUSG00000021240', u'ENSMUSG00000063796', u'ENSMUSG00000036298', u'ENSMUSG00000018566', u'ENSMUSG00000031997', u'ENSMUSG00000030500', u'ENSMUSG00000027775', u'ENSMUSG00000010122', u'ENSMUSG00000042078', u'ENSMUSG00000059149', u'ENSMUSG00000036196', u'ENSMUSG00000003153', u'ENSMUSG00000003528', u'ENSMUSG00000025161', u'ENSMUSG00000032449', u'ENSMUSG00000022342', u'ENSMUSG00000027827', u'ENSMUSG00000044367', u'ENSMUSG00000022199', u'ENSMUSG00000042476', u'ENSMUSG00000032114', u'ENSMUSG00000038178', u'ENSMUSG00000050963', u'ENSMUSG00000062785', u'ENSMUSG00000027074', u'ENSMUSG00000017765', u'ENSMUSG00000038486', u'ENSMUSG00000026065', u'ENSMUSG00000038267', u'ENSMUSG00000038260', u'ENSMUSG00000058975', u'ENSMUSG00000021541', u'ENSMUSG00000028973', u'ENSMUSG00000028051', u'ENSMUSG00000024069', u'ENSMUSG00000074575', u'ENSMUSG00000047976', u'ENSMUSG00000030450', u'ENSMUSG00000032842', u'ENSMUSG00000079055', u'ENSMUSG00000030741', u'ENSMUSG00000054099', u'ENSMUSG00000058441', u'ENSMUSG00000037344', u'ENSMUSG00000025986', u'ENSMUSG00000049624', u'ENSMUSG00000037341', u'ENSMUSG00000034656', u'ENSMUSG00000034258', u'ENSMUSG00000032122', u'ENSMUSG00000089911', u'ENSMUSG00000051726', u'ENSMUSG00000054414', u'ENSMUSG00000024650', u'ENSMUSG00000028854', u'ENSMUSG00000027365', u'ENSMUSG00000040938', u'ENSMUSG00000063142']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0055085', name='transmembrane transport', pop_count=248, alt_ids=[], level=4, depth=4, enrichment='p', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000037321']), symbols=u'Tap1', symbol_set=set([u'Tap1']), geneids='ENSMUSG00000037321', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=338, D1='G', GO_name='transmembrane transport'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0051983', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=113, D1='A', GO_name='regulation of chromosome segregation'), Nt(p_uncorrected=2.0487717169098736e-08, study_count=12, study_n=624, namespace='biological_process', p_fdr_bh=5.351886255672671e-06, study_items=set([u'ENSMUSG00000034349', u'ENSMUSG00000028312', u'ENSMUSG00000028873', u'ENSMUSG00000020380', u'ENSMUSG00000028702', u'ENSMUSG00000041147', u'ENSMUSG00000024974', u'ENSMUSG00000020898', u'ENSMUSG00000059552', u'ENSMUSG00000041133', u'ENSMUSG00000030528', u'ENSMUSG00000032409']), NS='BP', pop_items=set([u'ENSMUSG00000034349', u'ENSMUSG00000018841', u'ENSMUSG00000024054', u'ENSMUSG00000024974', u'ENSMUSG00000049878', u'ENSMUSG00000020415', u'ENSMUSG00000021264', u'ENSMUSG00000059552', u'ENSMUSG00000030528', u'ENSMUSG00000031928', u'ENSMUSG00000003549', u'ENSMUSG00000049717', u'ENSMUSG00000022346', u'ENSMUSG00000020380', u'ENSMUSG00000028820', u'ENSMUSG00000020898', u'ENSMUSG00000024174', u'ENSMUSG00000041133', u'ENSMUSG00000000751', u'ENSMUSG00000075266', u'ENSMUSG00000032409', u'ENSMUSG00000026648', u'ENSMUSG00000028214', u'ENSMUSG00000028312', u'ENSMUSG00000032565', u'ENSMUSG00000005871', u'ENSMUSG00000041147', u'ENSMUSG00000074797', u'ENSMUSG00000046010', u'ENSMUSG00000042275', u'ENSMUSG00000008690', u'ENSMUSG00000028873', u'ENSMUSG00000028702', u'ENSMUSG00000029676', u'ENSMUSG00000036672']), pop_n=13836, p_sm_bonferroni=0.000310409402829015, is_obsolete=False, GO='GO:0051276', name='chromosome organization', pop_count=35, alt_ids=['GO:0007001', 'GO:0051277'], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000020380', u'ENSMUSG00000028312', u'ENSMUSG00000028873', u'ENSMUSG00000034349', u'ENSMUSG00000028702', u'ENSMUSG00000041147', u'ENSMUSG00000024974', u'ENSMUSG00000020898', u'ENSMUSG00000059552', u'ENSMUSG00000041133', u'ENSMUSG00000030528', u'ENSMUSG00000032409']), symbols=u'Atr Blm Brca2 Cdca8 Ctc1 Rad50 Rad54l Smc1a Smc2 Smc3 Smc4 Trp53', symbol_set=set([u'Smc1a', u'Brca2', u'Trp53', u'Rad54l', 'Ctc1', u'Smc3', u'Smc2', u'Smc4', u'Blm', u'Atr', u'Rad50', u'Cdca8']), geneids='ENSMUSG00000034349 ENSMUSG00000028312 ENSMUSG00000028873 ENSMUSG00000020380 ENSMUSG00000028702 ENSMUSG00000041147 ENSMUSG00000024974 ENSMUSG00000020898 ENSMUSG00000059552 ENSMUSG00000030528 ENSMUSG00000041133 ENSMUSG00000032409', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=111, D1='BH', GO_name='chromosome organization'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0008637', name='', pop_count='', alt_ids='', level=5, depth=5, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=7, D1='BH', GO_name='apoptotic mitochondrial changes'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0007568', name='', pop_count='', alt_ids='', level=3, depth=3, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=18, D1='CE', GO_name='aging'), Nt(p_uncorrected=4.022772597795271e-08, study_count=13, study_n=624, namespace='biological_process', p_fdr_bh=8.963092298411199e-06, study_items=set([u'ENSMUSG00000029521', u'ENSMUSG00000003873', u'ENSMUSG00000005413', u'ENSMUSG00000024521', u'ENSMUSG00000027490', u'ENSMUSG00000041147', u'ENSMUSG00000036986', u'ENSMUSG00000005370', u'ENSMUSG00000017146', u'ENSMUSG00000034218', u'ENSMUSG00000057789', u'ENSMUSG00000006445', u'ENSMUSG00000036822']), NS='BP', pop_items=set([u'ENSMUSG00000021871', u'ENSMUSG00000006360', u'ENSMUSG00000028329', u'ENSMUSG00000036986', u'ENSMUSG00000062762', u'ENSMUSG00000027381', u'ENSMUSG00000024959', u'ENSMUSG00000003873', u'ENSMUSG00000031536', u'ENSMUSG00000041417', u'ENSMUSG00000028914', u'ENSMUSG00000022346', u'ENSMUSG00000043099', u'ENSMUSG00000003541', u'ENSMUSG00000068329', u'ENSMUSG00000042349', u'ENSMUSG00000006818', u'ENSMUSG00000061175', u'ENSMUSG00000017146', u'ENSMUSG00000020063', u'ENSMUSG00000024151', u'ENSMUSG00000034485', u'ENSMUSG00000036822', u'ENSMUSG00000032498', u'ENSMUSG00000057329', u'ENSMUSG00000038612', u'ENSMUSG00000029521', u'ENSMUSG00000030322', u'ENSMUSG00000030341', u'ENSMUSG00000022672', u'ENSMUSG00000054051', u'ENSMUSG00000041147', u'ENSMUSG00000006445', u'ENSMUSG00000026278', u'ENSMUSG00000005413', u'ENSMUSG00000024521', u'ENSMUSG00000030990', u'ENSMUSG00000027490', u'ENSMUSG00000005370', u'ENSMUSG00000007659', u'ENSMUSG00000034218', u'ENSMUSG00000089682', u'ENSMUSG00000057789', u'ENSMUSG00000028599']), pop_n=13836, p_sm_bonferroni=0.0006094902762919615, is_obsolete=False, GO='GO:0008630', name='intrinsic apoptotic signaling pathway in response to DNA damage', pop_count=44, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000029521', u'ENSMUSG00000005413', u'ENSMUSG00000024521', u'ENSMUSG00000027490', u'ENSMUSG00000041147', u'ENSMUSG00000036986', u'ENSMUSG00000005370', u'ENSMUSG00000017146', u'ENSMUSG00000034218', u'ENSMUSG00000036822', u'ENSMUSG00000057789', u'ENSMUSG00000006445', u'ENSMUSG00000003873']), symbols=u'Atm Bak1 Bax Brca1 Brca2 Chek2 E2f1 Epha2 Hmox1 Msh6 Pmaip1 Pml Topors', symbol_set=set([u'Brca1', u'Brca2', u'Pmaip1', u'E2f1', u'Atm', u'Hmox1', u'Epha2', u'Msh6', u'Bak1', u'Bax', u'Pml', u'Chek2', u'Topors']), geneids='ENSMUSG00000003873 ENSMUSG00000005413 ENSMUSG00000024521 ENSMUSG00000027490 ENSMUSG00000041147 ENSMUSG00000036986 ENSMUSG00000005370 ENSMUSG00000017146 ENSMUSG00000034218 ENSMUSG00000036822 ENSMUSG00000057789 ENSMUSG00000006445 ENSMUSG00000029521', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='ABF', GO_name='intrinsic apoptotic signaling pathway in response to DNA damage'), Nt(p_uncorrected=0.000430543497990217, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.03019983582430453, study_items=set([u'ENSMUSG00000039748', u'ENSMUSG00000020380', u'ENSMUSG00000024742', u'ENSMUSG00000036875']), NS='BP', pop_items=set([u'ENSMUSG00000039748', u'ENSMUSG00000020380', u'ENSMUSG00000032026', u'ENSMUSG00000040482', u'ENSMUSG00000024824', u'ENSMUSG00000036875', u'ENSMUSG00000032705', u'ENSMUSG00000024742', u'ENSMUSG00000038569']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0090305', name='nucleic acid phosphodiester bond hydrolysis', pop_count=9, alt_ids=[], level=5, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000039748', u'ENSMUSG00000020380', u'ENSMUSG00000024742', u'ENSMUSG00000036875']), symbols=u'Dna2 Exo1 Fen1 Rad50', symbol_set=set([u'Exo1', u'Fen1', u'Dna2', u'Rad50']), geneids='ENSMUSG00000039748 ENSMUSG00000020380 ENSMUSG00000024742 ENSMUSG00000036875', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=58, D1='BD', GO_name='nucleic acid phosphodiester bond hydrolysis'), Nt(p_uncorrected=2.1385239695277385e-07, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=3.857235316942234e-05, study_items=set([u'ENSMUSG00000067455', u'ENSMUSG00000027018', u'ENSMUSG00000028693', u'ENSMUSG00000069266', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000005470']), NS='BP', pop_items=set([u'ENSMUSG00000067455', u'ENSMUSG00000060678', u'ENSMUSG00000060639', u'ENSMUSG00000020196', u'ENSMUSG00000019857', u'ENSMUSG00000031229', u'ENSMUSG00000069274', u'ENSMUSG00000091405', u'ENSMUSG00000039473', u'ENSMUSG00000002319', u'ENSMUSG00000069305', u'ENSMUSG00000069306', u'ENSMUSG00000060981', u'ENSMUSG00000057236', u'ENSMUSG00000028693', u'ENSMUSG00000060093', u'ENSMUSG00000027018', u'ENSMUSG00000022702', u'ENSMUSG00000069266', u'ENSMUSG00000061482', u'ENSMUSG00000005470', u'ENSMUSG00000064288']), pop_n=13836, p_sm_bonferroni=0.0032400776662314767, is_obsolete=False, GO='GO:0006336', name='DNA replication-independent nucleosome assembly', pop_count=22, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000067455', u'ENSMUSG00000027018', u'ENSMUSG00000028693', u'ENSMUSG00000069266', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000005470']), symbols=u'Asf1b Hat1 Hist1h4a Hist1h4b Hist1h4d Hist1h4f Hist1h4j Hist1h4k Nasp', symbol_set=set([u'Hist1h4b', u'Nasp', u'Hist1h4f', u'Hist1h4d', u'Hat1', u'Hist1h4j', u'Hist1h4a', u'Hist1h4k', u'Asf1b']), geneids='ENSMUSG00000067455 ENSMUSG00000069266 ENSMUSG00000027018 ENSMUSG00000028693 ENSMUSG00000060093 ENSMUSG00000069274 ENSMUSG00000061482 ENSMUSG00000005470 ENSMUSG00000064288', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='BH', GO_name='DNA replication-independent nucleosome assembly'), Nt(p_uncorrected=2.1385239695277385e-07, study_count=9, study_n=624, namespace='biological_process', p_fdr_bh=3.857235316942234e-05, study_items=set([u'ENSMUSG00000036086', u'ENSMUSG00000059323', u'ENSMUSG00000027323', u'ENSMUSG00000035842', u'ENSMUSG00000073705', u'ENSMUSG00000027342', u'ENSMUSG00000045751', u'ENSMUSG00000038685', u'ENSMUSG00000030528']), NS='BP', pop_items=set([u'ENSMUSG00000031229', u'ENSMUSG00000059323', u'ENSMUSG00000031583', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000030528', u'ENSMUSG00000073436', u'ENSMUSG00000036086', u'ENSMUSG00000026434', u'ENSMUSG00000058594', u'ENSMUSG00000039354', u'ENSMUSG00000024287', u'ENSMUSG00000061755', u'ENSMUSG00000009555', u'ENSMUSG00000045751', u'ENSMUSG00000025144', u'ENSMUSG00000024906', u'ENSMUSG00000055884', u'ENSMUSG00000073705', u'ENSMUSG00000027323', u'ENSMUSG00000027342', u'ENSMUSG00000038225']), pop_n=13836, p_sm_bonferroni=0.0032400776662314767, is_obsolete=False, GO='GO:0031297', name='replication fork processing', pop_count=22, alt_ids=[], level=6, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036086', u'ENSMUSG00000059323', u'ENSMUSG00000027323', u'ENSMUSG00000045751', u'ENSMUSG00000073705', u'ENSMUSG00000027342', u'ENSMUSG00000035842', u'ENSMUSG00000038685', u'ENSMUSG00000030528']), symbols=u'Apitd1 Blm Ddx11 Mms22l Pcna Rad51 Rtel1 Tonsl Zranb3', symbol_set=set([u'Pcna', u'Zranb3', u'Ddx11', u'Tonsl', u'Mms22l', u'Apitd1', u'Blm', u'Rad51', u'Rtel1']), geneids='ENSMUSG00000036086 ENSMUSG00000059323 ENSMUSG00000027323 ENSMUSG00000045751 ENSMUSG00000073705 ENSMUSG00000027342 ENSMUSG00000035842 ENSMUSG00000030528 ENSMUSG00000038685', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=3, D1='BD', GO_name='replication fork processing'), Nt(p_uncorrected=4.084711977912572e-11, study_count=30, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000058385', u'ENSMUSG00000067455', u'ENSMUSG00000058773', u'ENSMUSG00000002835', u'ENSMUSG00000074403', u'ENSMUSG00000062727', u'ENSMUSG00000002870', u'ENSMUSG00000064168', u'ENSMUSG00000002307', u'ENSMUSG00000049539', u'ENSMUSG00000069308', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000069300', u'ENSMUSG00000069310', u'ENSMUSG00000075031', u'ENSMUSG00000028693', u'ENSMUSG00000060093', u'ENSMUSG00000029177', u'ENSMUSG00000047246', u'ENSMUSG00000052565', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000061482', u'ENSMUSG00000005470', u'ENSMUSG00000064288', u'ENSMUSG00000056895', u'ENSMUSG00000022945', u'ENSMUSG00000069268']), NS='BP', pop_items=set([u'ENSMUSG00000054766', u'ENSMUSG00000058385', u'ENSMUSG00000028333', u'ENSMUSG00000067455', u'ENSMUSG00000031229', u'ENSMUSG00000058773', u'ENSMUSG00000059119', u'ENSMUSG00000058799', u'ENSMUSG00000002835', u'ENSMUSG00000032187', u'ENSMUSG00000074403', u'ENSMUSG00000062727', u'ENSMUSG00000031715', u'ENSMUSG00000002870', u'ENSMUSG00000055733', u'ENSMUSG00000064168', u'ENSMUSG00000002307', u'ENSMUSG00000049539', u'ENSMUSG00000024921', u'ENSMUSG00000041096', u'ENSMUSG00000047514', u'ENSMUSG00000024335', u'ENSMUSG00000051627', u'ENSMUSG00000069308', u'ENSMUSG00000049516', u'ENSMUSG00000015749', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000035623', u'ENSMUSG00000020086', u'ENSMUSG00000069300', u'ENSMUSG00000038984', u'ENSMUSG00000060639', u'ENSMUSG00000069306', u'ENSMUSG00000091405', u'ENSMUSG00000082229', u'ENSMUSG00000075031', u'ENSMUSG00000018974', u'ENSMUSG00000060981', u'ENSMUSG00000005982', u'ENSMUSG00000005470', u'ENSMUSG00000057113', u'ENSMUSG00000052565', u'ENSMUSG00000068854', u'ENSMUSG00000060743', u'ENSMUSG00000055430', u'ENSMUSG00000028693', u'ENSMUSG00000019857', u'ENSMUSG00000016559', u'ENSMUSG00000039485', u'ENSMUSG00000028759', u'ENSMUSG00000015937', u'ENSMUSG00000018102', u'ENSMUSG00000055067', u'ENSMUSG00000031540', u'ENSMUSG00000056895', u'ENSMUSG00000036181', u'ENSMUSG00000060678', u'ENSMUSG00000029177', u'ENSMUSG00000000567', u'ENSMUSG00000047246', u'ENSMUSG00000090112', u'ENSMUSG00000069305', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000061482', u'ENSMUSG00000060093', u'ENSMUSG00000064288', u'ENSMUSG00000069268', u'ENSMUSG00000021767', u'ENSMUSG00000022945', u'ENSMUSG00000069310']), pop_n=13836, p_sm_bonferroni=6.188747117735338e-07, is_obsolete=False, GO='GO:0006334', name='nucleosome assembly', pop_count=73, alt_ids=[], level=6, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000069267', u'ENSMUSG00000058385', u'ENSMUSG00000075031', u'ENSMUSG00000067455', u'ENSMUSG00000005470', u'ENSMUSG00000058773', u'ENSMUSG00000028693', u'ENSMUSG00000060093', u'ENSMUSG00000002835', u'ENSMUSG00000074403', u'ENSMUSG00000062727', u'ENSMUSG00000029177', u'ENSMUSG00000069268', u'ENSMUSG00000002870', u'ENSMUSG00000064168', u'ENSMUSG00000069308', u'ENSMUSG00000049539', u'ENSMUSG00000047246', u'ENSMUSG00000052565', u'ENSMUSG00000002307', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000069300', u'ENSMUSG00000064288', u'ENSMUSG00000056895', u'ENSMUSG00000022945', u'ENSMUSG00000069310']), symbols=u'Asf1b Cenpa Chaf1a Chaf1b Daxx Hist1h1a Hist1h1b Hist1h1d Hist1h2bb Hist1h2be Hist1h2bf Hist1h2bg Hist1h2bh Hist1h2bj Hist1h2bk Hist1h2bp Hist1h3a Hist1h3b Hist1h3c Hist1h3e Hist1h4a Hist1h4b Hist1h4d Hist1h4f Hist1h4j Hist1h4k Hist2h3b Hist3h2ba Mcm2 Nasp', symbol_set=set([u'Daxx', u'Hist1h2bp', u'Hist1h2be', u'Hist1h2bf', u'Hist1h2bg', u'Chaf1a', u'Mcm2', u'Hist1h2bb', u'Chaf1b', u'Hist1h2bh', u'Asf1b', u'Hist1h2bk', u'Hist1h4b', u'Hist1h4a', u'Hist1h4f', u'Hist1h4d', u'Hist1h4k', u'Hist1h4j', u'Hist1h2bj', u'Nasp', u'Cenpa', u'Hist3h2ba', u'Hist1h3b', u'Hist1h3c', u'Hist1h3a', u'Hist2h3b', u'Hist1h3e', u'Hist1h1d', u'Hist1h1a', u'Hist1h1b']), geneids='ENSMUSG00000058385 ENSMUSG00000067455 ENSMUSG00000058773 ENSMUSG00000002835 ENSMUSG00000074403 ENSMUSG00000062727 ENSMUSG00000002870 ENSMUSG00000064168 ENSMUSG00000002307 ENSMUSG00000049539 ENSMUSG00000069308 ENSMUSG00000069273 ENSMUSG00000069274 ENSMUSG00000069300 ENSMUSG00000069310 ENSMUSG00000075031 ENSMUSG00000028693 ENSMUSG00000005470 ENSMUSG00000029177 ENSMUSG00000047246 ENSMUSG00000052565 ENSMUSG00000069267 ENSMUSG00000069266 ENSMUSG00000069265 ENSMUSG00000061482 ENSMUSG00000060093 ENSMUSG00000064288 ENSMUSG00000069268 ENSMUSG00000022945 ENSMUSG00000056895', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=3, D1='BH', GO_name='nucleosome assembly'), Nt(p_uncorrected=4.4593414733267585e-12, study_count=15, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000067455', u'ENSMUSG00000027018', u'ENSMUSG00000028693', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000074403', u'ENSMUSG00000060093', u'ENSMUSG00000002835', u'ENSMUSG00000064288', u'ENSMUSG00000005470', u'ENSMUSG00000022945']), NS='BP', pop_items=set([u'ENSMUSG00000067455', u'ENSMUSG00000060678', u'ENSMUSG00000060639', u'ENSMUSG00000002835', u'ENSMUSG00000074403', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000091405', u'ENSMUSG00000002319', u'ENSMUSG00000060093', u'ENSMUSG00000069306', u'ENSMUSG00000060981', u'ENSMUSG00000057236', u'ENSMUSG00000028693', u'ENSMUSG00000005470', u'ENSMUSG00000027018', u'ENSMUSG00000069305', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000061482', u'ENSMUSG00000019857', u'ENSMUSG00000064288', u'ENSMUSG00000022945']), pop_n=13836, p_sm_bonferroni=6.756348266237371e-08, is_obsolete=False, GO='GO:0006335', name='DNA replication-dependent nucleosome assembly', pop_count=24, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000067455', u'ENSMUSG00000027018', u'ENSMUSG00000028693', u'ENSMUSG00000069267', u'ENSMUSG00000069266', u'ENSMUSG00000069265', u'ENSMUSG00000069273', u'ENSMUSG00000069274', u'ENSMUSG00000061482', u'ENSMUSG00000074403', u'ENSMUSG00000060093', u'ENSMUSG00000002835', u'ENSMUSG00000064288', u'ENSMUSG00000005470', u'ENSMUSG00000022945']), symbols=u'Asf1b Chaf1a Chaf1b Hat1 Hist1h3a Hist1h3b Hist1h3e Hist1h4a Hist1h4b Hist1h4d Hist1h4f Hist1h4j Hist1h4k Hist2h3b Nasp', symbol_set=set([u'Hist1h4b', u'Nasp', u'Hist1h4f', u'Hist1h4d', u'Hat1', u'Hist1h4j', u'Chaf1b', u'Hist1h4a', u'Hist1h3b', u'Hist1h4k', u'Hist1h3a', u'Chaf1a', u'Hist2h3b', u'Hist1h3e', u'Asf1b']), geneids='ENSMUSG00000067455 ENSMUSG00000069266 ENSMUSG00000027018 ENSMUSG00000028693 ENSMUSG00000069267 ENSMUSG00000060093 ENSMUSG00000069265 ENSMUSG00000069273 ENSMUSG00000002835 ENSMUSG00000061482 ENSMUSG00000074403 ENSMUSG00000005470 ENSMUSG00000069274 ENSMUSG00000064288 ENSMUSG00000022945', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BH', GO_name='DNA replication-dependent nucleosome assembly'), Nt(p_uncorrected=5.716066791862708e-05, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.005735372712815357, study_items=set([u'ENSMUSG00000020897', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000034311']), NS='BP', pop_items=set([u'ENSMUSG00000050930', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000034311', u'ENSMUSG00000020897', u'ENSMUSG00000033502']), pop_n=13836, p_sm_bonferroni=0.8660412796351189, is_obsolete=False, GO='GO:0051256', name='mitotic spindle midzone assembly', pop_count=6, alt_ids=[], level=4, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000020897', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000034311']), symbols=u'Aurkb Kif23 Kif4 Racgap1', symbol_set=set([u'Racgap1', u'Kif4', u'Kif23', u'Aurkb']), geneids='ENSMUSG00000020897 ENSMUSG00000032254 ENSMUSG00000023015 ENSMUSG00000034311', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCH', GO_name='mitotic spindle midzone assembly'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0080134', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=960, D1='A', GO_name='regulation of response to stress'), Nt(p_uncorrected=4.804111827681834e-06, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.0005917650268390852, study_items=set([u'ENSMUSG00000038644', u'ENSMUSG00000021668', u'ENSMUSG00000025574', u'ENSMUSG00000007080', u'ENSMUSG00000023953', u'ENSMUSG00000056394', u'ENSMUSG00000058729']), NS='BP', pop_items=set([u'ENSMUSG00000031536', u'ENSMUSG00000026082', u'ENSMUSG00000025218', u'ENSMUSG00000049717', u'ENSMUSG00000007080', u'ENSMUSG00000035824', u'ENSMUSG00000014301', u'ENSMUSG00000021668', u'ENSMUSG00000038845', u'ENSMUSG00000020697', u'ENSMUSG00000025574', u'ENSMUSG00000019997', u'ENSMUSG00000038425', u'ENSMUSG00000038644', u'ENSMUSG00000023953', u'ENSMUSG00000056394', u'ENSMUSG00000058729']), pop_n=13836, p_sm_bonferroni=0.07278709830120746, is_obsolete=False, GO='GO:0071897', name='DNA biosynthetic process', pop_count=17, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000058729', u'ENSMUSG00000025574', u'ENSMUSG00000007080', u'ENSMUSG00000021668', u'ENSMUSG00000023953', u'ENSMUSG00000056394', u'ENSMUSG00000038644']), symbols=u'Lig1 Lin9 Pold1 Pole Polh Polk Tk1', symbol_set=set([u'Lin9', u'Pold1', u'Pole', u'Lig1', u'Tk1', u'Polk', u'Polh']), geneids='ENSMUSG00000021668 ENSMUSG00000058729 ENSMUSG00000025574 ENSMUSG00000007080 ENSMUSG00000023953 ENSMUSG00000056394 ENSMUSG00000038644', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=19, D1='BD', GO_name='DNA biosynthetic process'), Nt(p_uncorrected=0.0002616703282067204, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.01962657001316842, study_items=set([u'ENSMUSG00000032113', u'ENSMUSG00000041147', u'ENSMUSG00000044702', u'ENSMUSG00000027454', u'ENSMUSG00000042029']), NS='BP', pop_items=set([u'ENSMUSG00000018736', u'ENSMUSG00000031546', u'ENSMUSG00000029547', u'ENSMUSG00000032113', u'ENSMUSG00000024735', u'ENSMUSG00000015697', u'ENSMUSG00000044702', u'ENSMUSG00000023980', u'ENSMUSG00000027454', u'ENSMUSG00000042029', u'ENSMUSG00000025337', u'ENSMUSG00000041147', u'ENSMUSG00000032078', u'ENSMUSG00000024002']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0001833', name='inner cell mass cell proliferation', pop_count=14, alt_ids=[], level=3, depth=3, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032113', u'ENSMUSG00000044702', u'ENSMUSG00000042029', u'ENSMUSG00000027454', u'ENSMUSG00000041147']), symbols=u'Brca2 Chek1 Gins1 Ncapg2 Palb2', symbol_set=set([u'Gins1', u'Palb2', u'Ncapg2', u'Brca2', u'Chek1']), geneids='ENSMUSG00000032113 ENSMUSG00000042029 ENSMUSG00000044702 ENSMUSG00000027454 ENSMUSG00000041147', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='C', GO_name='inner cell mass cell proliferation'), Nt(p_uncorrected=9.131151172475021e-05, study_count=3, study_n=624, namespace='biological_process', p_fdr_bh=0.008090413532992342, study_items=set([u'ENSMUSG00000034349', u'ENSMUSG00000045273', u'ENSMUSG00000028312']), NS='BP', pop_items=set([u'ENSMUSG00000034349', u'ENSMUSG00000045273', u'ENSMUSG00000028312']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0051383', name='kinetochore organization', pop_count=3, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034349', u'ENSMUSG00000045273', u'ENSMUSG00000028312']), symbols=u'Cenph Smc2 Smc4', symbol_set=set([u'Smc2', u'Smc4', u'Cenph']), geneids='ENSMUSG00000034349 ENSMUSG00000045273 ENSMUSG00000028312', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='BH', GO_name='kinetochore organization'), Nt(p_uncorrected=0.000430543497990217, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.03019983582430453, study_items=set([u'ENSMUSG00000073705', u'ENSMUSG00000029177', u'ENSMUSG00000040599', u'ENSMUSG00000045273']), NS='BP', pop_items=set([u'ENSMUSG00000038902', u'ENSMUSG00000029177', u'ENSMUSG00000045273', u'ENSMUSG00000029253', u'ENSMUSG00000073705', u'ENSMUSG00000025144', u'ENSMUSG00000075266', u'ENSMUSG00000040599', u'ENSMUSG00000036672']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0051382', name='kinetochore assembly', pop_count=9, alt_ids=['GO:0000069'], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000073705', u'ENSMUSG00000029177', u'ENSMUSG00000040599', u'ENSMUSG00000045273']), symbols=u'Apitd1 Cenpa Cenph Mis12', symbol_set=set([u'Mis12', u'Cenph', u'Cenpa', u'Apitd1']), geneids='ENSMUSG00000073705 ENSMUSG00000029177 ENSMUSG00000040599 ENSMUSG00000045273', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BH', GO_name='kinetochore assembly'), Nt(p_uncorrected=4.099215555456427e-06, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.000521909368745549, study_items=set([u'ENSMUSG00000036928', u'ENSMUSG00000007589', u'ENSMUSG00000009628', u'ENSMUSG00000038379']), NS='BP', pop_items=set([u'ENSMUSG00000036928', u'ENSMUSG00000007589', u'ENSMUSG00000009628', u'ENSMUSG00000038379']), pop_n=13836, p_sm_bonferroni=0.06210721488072033, is_obsolete=False, GO='GO:0034502', name='protein localization to chromosome', pop_count=4, alt_ids=[], level=6, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036928', u'ENSMUSG00000007589', u'ENSMUSG00000009628', u'ENSMUSG00000038379']), symbols=u'Stag3 Tex15 Tinf2 Ttk', symbol_set=set([u'Tinf2', u'Stag3', u'Ttk', u'Tex15']), geneids='ENSMUSG00000036928 ENSMUSG00000007589 ENSMUSG00000009628 ENSMUSG00000038379', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=22, D1='G', GO_name='protein localization to chromosome'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0097190', name='', pop_count='', alt_ids='', level=3, depth=5, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=22, D1='AB', GO_name='apoptotic signaling pathway'), Nt(p_uncorrected=9.181792629849965e-06, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.0010783979855415258, study_items=set([u'ENSMUSG00000023940', u'ENSMUSG00000024056', u'ENSMUSG00000027326', u'ENSMUSG00000045328', u'ENSMUSG00000026683']), NS='BP', pop_items=set([u'ENSMUSG00000026683', u'ENSMUSG00000024056', u'ENSMUSG00000027326', u'ENSMUSG00000066979', u'ENSMUSG00000045328', u'ENSMUSG00000030965', u'ENSMUSG00000017421', u'ENSMUSG00000023940']), pop_n=13836, p_sm_bonferroni=0.13911334013485682, is_obsolete=False, GO='GO:0008608', name='attachment of spindle microtubules to kinetochore', pop_count=8, alt_ids=['GO:0051313'], level=3, depth=3, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000023940', u'ENSMUSG00000024056', u'ENSMUSG00000027326', u'ENSMUSG00000045328', u'ENSMUSG00000026683']), symbols=u'Cenpe Knl1 Ndc80 Nuf2 Sgol1', symbol_set=set([u'Cenpe', u'Ndc80', u'Sgol1', 'Knl1', u'Nuf2']), geneids='ENSMUSG00000023940 ENSMUSG00000024056 ENSMUSG00000027326 ENSMUSG00000045328 ENSMUSG00000026683', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=8, D1='B', GO_name='attachment of spindle microtubules to kinetochore'), Nt(p_uncorrected=6.079901029339501e-07, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=0.00010118906047752281, study_items=set([u'ENSMUSG00000068606', u'ENSMUSG00000018899', u'ENSMUSG00000034459', u'ENSMUSG00000039997', u'ENSMUSG00000046879', u'ENSMUSG00000078853', u'ENSMUSG00000078921', u'ENSMUSG00000054072', u'ENSMUSG00000026104', u'ENSMUSG00000074896']), NS='BP', pop_items=set([u'ENSMUSG00000040264', u'ENSMUSG00000020307', u'ENSMUSG00000058163', u'ENSMUSG00000009293', u'ENSMUSG00000078922', u'ENSMUSG00000078920', u'ENSMUSG00000078921', u'ENSMUSG00000036199', u'ENSMUSG00000028268', u'ENSMUSG00000029203', u'ENSMUSG00000073555', u'ENSMUSG00000021494', u'ENSMUSG00000043263', u'ENSMUSG00000039997', u'ENSMUSG00000068329', u'ENSMUSG00000054072', u'ENSMUSG00000026104', u'ENSMUSG00000037860', u'ENSMUSG00000068606', u'ENSMUSG00000018899', u'ENSMUSG00000069874', u'ENSMUSG00000046879', u'ENSMUSG00000073489', u'ENSMUSG00000078853', u'ENSMUSG00000020464', u'ENSMUSG00000028270', u'ENSMUSG00000069893', u'ENSMUSG00000024349', u'ENSMUSG00000034459', u'ENSMUSG00000090942', u'ENSMUSG00000074896']), pop_n=13836, p_sm_bonferroni=0.009211658049552278, is_obsolete=False, GO='GO:0035458', name='cellular response to interferon-beta', pop_count=31, alt_ids=[], level=6, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000068606', u'ENSMUSG00000018899', u'ENSMUSG00000034459', u'ENSMUSG00000039997', u'ENSMUSG00000046879', u'ENSMUSG00000078853', u'ENSMUSG00000078921', u'ENSMUSG00000054072', u'ENSMUSG00000026104', u'ENSMUSG00000074896']), symbols=u'Gm4841 Ifi203 Ifit1 Ifit3 Igtp Iigp1 Irf1 Irgm1 Stat1 Tgtp2', symbol_set=set([u'Irf1', u'Stat1', u'Gm4841', u'Tgtp2', u'Ifi203', u'Igtp', u'Ifit3', u'Iigp1', u'Ifit1', u'Irgm1']), geneids='ENSMUSG00000068606 ENSMUSG00000018899 ENSMUSG00000034459 ENSMUSG00000039997 ENSMUSG00000046879 ENSMUSG00000078853 ENSMUSG00000078921 ENSMUSG00000054072 ENSMUSG00000026104 ENSMUSG00000074896', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BF', GO_name='cellular response to interferon-beta'), Nt(p_uncorrected=2.0341930676437693e-07, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=3.8049455762803394e-05, study_items=set([u'ENSMUSG00000006398', u'ENSMUSG00000029521', u'ENSMUSG00000043065', u'ENSMUSG00000027469', u'ENSMUSG00000017716', u'ENSMUSG00000025474', u'ENSMUSG00000000759', u'ENSMUSG00000017861', u'ENSMUSG00000026622', u'ENSMUSG00000012443']), NS='BP', pop_items=set([u'ENSMUSG00000002546', u'ENSMUSG00000043065', u'ENSMUSG00000027469', u'ENSMUSG00000029521', u'ENSMUSG00000006398', u'ENSMUSG00000047126', u'ENSMUSG00000029029', u'ENSMUSG00000033186', u'ENSMUSG00000017861', u'ENSMUSG00000001440', u'ENSMUSG00000071176', u'ENSMUSG00000000759', u'ENSMUSG00000033900', u'ENSMUSG00000021693', u'ENSMUSG00000017421', u'ENSMUSG00000004771', u'ENSMUSG00000033790', u'ENSMUSG00000051786', u'ENSMUSG00000022064', u'ENSMUSG00000031328', u'ENSMUSG00000017716', u'ENSMUSG00000025474', u'ENSMUSG00000030965', u'ENSMUSG00000027263', u'ENSMUSG00000026622', u'ENSMUSG00000027475', u'ENSMUSG00000012443', u'ENSMUSG00000007815']), pop_n=13836, p_sm_bonferroni=0.0030820059167870747, is_obsolete=False, GO='GO:0090307', name='mitotic spindle assembly', pop_count=28, alt_ids=[], level=5, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000029521', u'ENSMUSG00000043065', u'ENSMUSG00000027469', u'ENSMUSG00000006398', u'ENSMUSG00000017716', u'ENSMUSG00000025474', u'ENSMUSG00000000759', u'ENSMUSG00000017861', u'ENSMUSG00000026622', u'ENSMUSG00000012443']), symbols=u'Birc5 Cdc20 Chek2 Kif11 Mybl2 Nek2 Spice1 Tpx2 Tubgcp2 Tubgcp3', symbol_set=set([u'Tpx2', u'Mybl2', u'Nek2', u'Birc5', u'Cdc20', u'Kif11', u'Spice1', u'Tubgcp2', u'Tubgcp3', u'Chek2']), geneids='ENSMUSG00000043065 ENSMUSG00000029521 ENSMUSG00000006398 ENSMUSG00000027469 ENSMUSG00000017716 ENSMUSG00000025474 ENSMUSG00000000759 ENSMUSG00000017861 ENSMUSG00000026622 ENSMUSG00000012443', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCH', GO_name='mitotic spindle assembly'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0022402', name='', pop_count='', alt_ids='', level=2, depth=2, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=478, D1='B', GO_name='cell cycle process'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0008219', name='', pop_count='', alt_ids='', level=3, depth=3, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=107, D1='BC', GO_name='cell death'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0010941', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=335, D1='A', GO_name='regulation of cell death'), Nt(p_uncorrected=2.89924240239775e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.0030717777369740074, study_items=set([u'ENSMUSG00000032815', u'ENSMUSG00000009628', u'ENSMUSG00000019214', u'ENSMUSG00000034218', u'ENSMUSG00000027115', u'ENSMUSG00000026039']), NS='BP', pop_items=set([u'ENSMUSG00000032498', u'ENSMUSG00000032815', u'ENSMUSG00000019214', u'ENSMUSG00000059970', u'ENSMUSG00000021245', u'ENSMUSG00000042500', u'ENSMUSG00000026646', u'ENSMUSG00000009628', u'ENSMUSG00000028871', u'ENSMUSG00000063415', u'ENSMUSG00000026039', u'ENSMUSG00000034218', u'ENSMUSG00000041912', u'ENSMUSG00000027115', u'ENSMUSG00000029279']), pop_n=13836, p_sm_bonferroni=0.4392642163872831, is_obsolete=False, GO='GO:0007140', name='male meiosis', pop_count=15, alt_ids=[], level=4, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032815', u'ENSMUSG00000019214', u'ENSMUSG00000034218', u'ENSMUSG00000026039', u'ENSMUSG00000027115', u'ENSMUSG00000009628']), symbols=u'Atm Chtf18 Fanca Kif18a Sgol2a Tex15', symbol_set=set([u'Fanca', 'Sgol2a', u'Tex15', u'Atm', u'Kif18a', u'Chtf18']), geneids='ENSMUSG00000032815 ENSMUSG00000027115 ENSMUSG00000019214 ENSMUSG00000034218 ENSMUSG00000026039 ENSMUSG00000009628', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BHK', GO_name='male meiosis'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0006325', name='', pop_count='', alt_ids='', level=4, depth=4, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=185, D1='BH', GO_name='chromatin organization'), Nt(p_uncorrected=6.48431637746412e-05, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.006338314673223154, study_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000034023', u'ENSMUSG00000041147', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000057789', u'ENSMUSG00000029521']), NS='BP', pop_items=set([u'ENSMUSG00000021871', u'ENSMUSG00000003873', u'ENSMUSG00000034023', u'ENSMUSG00000036986', u'ENSMUSG00000050697', u'ENSMUSG00000059552', u'ENSMUSG00000029026', u'ENSMUSG00000048787', u'ENSMUSG00000028933', u'ENSMUSG00000006818', u'ENSMUSG00000063856', u'ENSMUSG00000038028', u'ENSMUSG00000054051', u'ENSMUSG00000040613', u'ENSMUSG00000026395', u'ENSMUSG00000029521', u'ENSMUSG00000041147', u'ENSMUSG00000022672', u'ENSMUSG00000024947', u'ENSMUSG00000049717', u'ENSMUSG00000057789', u'ENSMUSG00000057329', u'ENSMUSG00000022346', u'ENSMUSG00000021615']), pop_n=13836, p_sm_bonferroni=0.9824387743495889, is_obsolete=False, GO='GO:0010332', name='response to gamma radiation', pop_count=24, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036986', u'ENSMUSG00000003873', u'ENSMUSG00000059552', u'ENSMUSG00000057789', u'ENSMUSG00000034023', u'ENSMUSG00000029521', u'ENSMUSG00000041147']), symbols=u'Bak1 Bax Brca2 Chek2 Fancd2 Pml Trp53', symbol_set=set([u'Brca2', u'Trp53', u'Bax', u'Bak1', u'Fancd2', u'Pml', u'Chek2']), geneids='ENSMUSG00000003873 ENSMUSG00000034023 ENSMUSG00000041147 ENSMUSG00000036986 ENSMUSG00000059552 ENSMUSG00000057789 ENSMUSG00000029521', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='F', GO_name='response to gamma radiation'), Nt(p_uncorrected=0.00011390587371645838, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.009750214082926898, study_items=set([u'ENSMUSG00000028896', u'ENSMUSG00000027469', u'ENSMUSG00000022177', u'ENSMUSG00000024542', u'ENSMUSG00000078762', u'ENSMUSG00000012443', u'ENSMUSG00000019773']), NS='BP', pop_items=set([u'ENSMUSG00000027469', u'ENSMUSG00000033705', u'ENSMUSG00000024790', u'ENSMUSG00000027285', u'ENSMUSG00000018501', u'ENSMUSG00000025162', u'ENSMUSG00000041415', u'ENSMUSG00000031371', u'ENSMUSG00000022177', u'ENSMUSG00000063870', u'ENSMUSG00000038047', u'ENSMUSG00000019773', u'ENSMUSG00000001525', u'ENSMUSG00000033900', u'ENSMUSG00000034154', u'ENSMUSG00000041840', u'ENSMUSG00000078762', u'ENSMUSG00000030744', u'ENSMUSG00000028896', u'ENSMUSG00000035439', u'ENSMUSG00000002546', u'ENSMUSG00000031529', u'ENSMUSG00000024542', u'ENSMUSG00000024454', u'ENSMUSG00000012443', u'ENSMUSG00000079555']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0051225', name='spindle assembly', pop_count=26, alt_ids=['GO:0051226', 'GO:0051227'], level=4, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000019773', u'ENSMUSG00000028896', u'ENSMUSG00000078762', u'ENSMUSG00000012443', u'ENSMUSG00000027469', u'ENSMUSG00000022177', u'ENSMUSG00000024542']), symbols=u'Cep192 Fbxo5 Haus4 Haus5 Kif11 Rcc1 Tpx2', symbol_set=set([u'Rcc1', u'Tpx2', u'Haus4', u'Haus5', u'Cep192', u'Fbxo5', u'Kif11']), geneids='ENSMUSG00000028896 ENSMUSG00000027469 ENSMUSG00000022177 ENSMUSG00000024542 ENSMUSG00000078762 ENSMUSG00000012443 ENSMUSG00000019773', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=12, D1='BCH', GO_name='spindle assembly'), Nt(p_uncorrected=6.987878234184759e-11, study_count=94, study_n=624, namespace='biological_process', p_fdr_bh=4.603188831571012e-08, study_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000023015', u'ENSMUSG00000027469', u'ENSMUSG00000042029', u'ENSMUSG00000045328', u'ENSMUSG00000024974', u'ENSMUSG00000025358', u'ENSMUSG00000032782', u'ENSMUSG00000022177', u'ENSMUSG00000022070', u'ENSMUSG00000027379', u'ENSMUSG00000020897', u'ENSMUSG00000019773', u'ENSMUSG00000062510', u'ENSMUSG00000029521', u'ENSMUSG00000002068', u'ENSMUSG00000051378', u'ENSMUSG00000037313', u'ENSMUSG00000027715', u'ENSMUSG00000032254', u'ENSMUSG00000006398', u'ENSMUSG00000072082', u'ENSMUSG00000027496', u'ENSMUSG00000029283', u'ENSMUSG00000024660', u'ENSMUSG00000026622', u'ENSMUSG00000078762', u'ENSMUSG00000032218', u'ENSMUSG00000027306', u'ENSMUSG00000024056', u'ENSMUSG00000048922', u'ENSMUSG00000034906', u'ENSMUSG00000056394', u'ENSMUSG00000032397', u'ENSMUSG00000021965', u'ENSMUSG00000034349', u'ENSMUSG00000030867', u'ENSMUSG00000041498', u'ENSMUSG00000047534', u'ENSMUSG00000032400', u'ENSMUSG00000028312', u'ENSMUSG00000021115', u'ENSMUSG00000028896', u'ENSMUSG00000032477', u'ENSMUSG00000026683', u'ENSMUSG00000027326', u'ENSMUSG00000027635', u'ENSMUSG00000003824', u'ENSMUSG00000040034', u'ENSMUSG00000026039', u'ENSMUSG00000029414', u'ENSMUSG00000028066', u'ENSMUSG00000001403', u'ENSMUSG00000002055', u'ENSMUSG00000051220', u'ENSMUSG00000033364', u'ENSMUSG00000041431', u'ENSMUSG00000041238', u'ENSMUSG00000039994', u'ENSMUSG00000027331', u'ENSMUSG00000020492', u'ENSMUSG00000041133', u'ENSMUSG00000024989', u'ENSMUSG00000027699', u'ENSMUSG00000033952', u'ENSMUSG00000038252', u'ENSMUSG00000025001', u'ENSMUSG00000040599', u'ENSMUSG00000028873', u'ENSMUSG00000028678', u'ENSMUSG00000029472', u'ENSMUSG00000024795', u'ENSMUSG00000023940', u'ENSMUSG00000023505', u'ENSMUSG00000019942', u'ENSMUSG00000026779', u'ENSMUSG00000035024', u'ENSMUSG00000020326', u'ENSMUSG00000069910', u'ENSMUSG00000028212', u'ENSMUSG00000074476', u'ENSMUSG00000073705', u'ENSMUSG00000068744', u'ENSMUSG00000038943', u'ENSMUSG00000026088', u'ENSMUSG00000012443', u'ENSMUSG00000017499', u'ENSMUSG00000031478', u'ENSMUSG00000043065', u'ENSMUSG00000020808', u'ENSMUSG00000017716', u'ENSMUSG00000029910', u'ENSMUSG00000062248', u'ENSMUSG00000005233']), NS='BP', pop_items=set([u'ENSMUSG00000066842', u'ENSMUSG00000029414', u'ENSMUSG00000040084', u'ENSMUSG00000000001', u'ENSMUSG00000026491', u'ENSMUSG00000051378', u'ENSMUSG00000024073', u'ENSMUSG00000029516', u'ENSMUSG00000026965', u'ENSMUSG00000027330', u'ENSMUSG00000027469', u'ENSMUSG00000042029', u'ENSMUSG00000045328', u'ENSMUSG00000006005', u'ENSMUSG00000024974', u'ENSMUSG00000020697', u'ENSMUSG00000025358', u'ENSMUSG00000017639', u'ENSMUSG00000022089', u'ENSMUSG00000027937', u'ENSMUSG00000025001', u'ENSMUSG00000059248', u'ENSMUSG00000030649', u'ENSMUSG00000024370', u'ENSMUSG00000022456', u'ENSMUSG00000033088', u'ENSMUSG00000001403', u'ENSMUSG00000032782', u'ENSMUSG00000039128', u'ENSMUSG00000025616', u'ENSMUSG00000040250', u'ENSMUSG00000024277', u'ENSMUSG00000022177', u'ENSMUSG00000011589', u'ENSMUSG00000041769', u'ENSMUSG00000070348', u'ENSMUSG00000022070', u'ENSMUSG00000020752', u'ENSMUSG00000020897', u'ENSMUSG00000053119', 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u'ENSMUSG00000035024', u'ENSMUSG00000005233', u'ENSMUSG00000026039']), symbols=u'Anapc5 Apitd1 Aspm Aurka Aurkb Birc5 Bora Bub1 Bub1b Ccna2 Ccnb1 Ccnb2 Ccne1 Ccne2 Ccnf Ccng1 Cdc20 Cdc25a Cdc6 Cdc7 Cdca2 Cdca3 Cdca8 Cdk1 Cdk2 Cenpe Cep55 Chek2 Cks2 Cntrob Dsn1 Ect2 Ercc6l Fam64a Fbxo5 Haus4 Haus5 Hells Incenp Kif11 Kif14 Kif18b Kif20b Kif23 Kif2c Knl1 Knstrn Kntc1 Lig1 Mad2l1 Mastl Mis12 Mis18bp1 Mitd1 Ncapd2 Ncapd3 Ncapg2 Ncaph Ndc80 Nek2 Nek3 Nsl1 Nuf2 Nup43 Nusap1 Plk1 Pmf1 Prc1 Psrc1 Racgap1 Rbbp8 Rcc1 Sgol1 Sgol2a Ska2 Ska3 Smc1a Smc2 Smc3 Smc4 Spag5 Spc24 Spc25 Spdl1 Spice1 Syce2 Tacc3 Timeless Tipin Tpx2 Ube2c Usp37 Vrk1 Zwilch', symbol_set=set([u'Ncapg2', 'Spdl1', u'Cep55', u'Mitd1', u'Ccnf', u'Rbbp8', u'Mis12', u'Chek2', 'Sgol2a', u'Ccng1', 'Ska3', 'Ska2', u'Fam64a', u'Lig1', u'Ccna2', u'Cenpe', u'Tacc3', u'Dsn1', u'Ncapd2', u'Ncapd3', u'Kif14', u'Syce2', u'Kif11', u'Prc1', u'Smc1a', u'Rcc1', u'Cdc25a', u'Ccnb2', u'Ccnb1', u'Racgap1', u'Aspm', u'Ndc80', u'Cdc6', u'Cdc7', u'Tpx2', u'Mad2l1', u'Pmf1', u'Bub1b', u'Anapc5', u'Ercc6l', u'Aurka', u'Aurkb', u'Spc25', u'Spc24', u'Hells', u'Kntc1', u'Timeless', u'Incenp', u'Spag5', u'Cdk1', u'Cdk2', u'Ncaph', 'Bora', u'Nuf2', u'Haus4', u'Haus5', u'Spice1', u'Nek2', u'Nek3', u'Ect2', u'Sgol1', u'Kif18b', u'Cks2', u'Nsl1', u'Ccne2', u'Ccne1', u'Nusap1', u'Tipin', u'Cdc20', u'Fbxo5', u'Zwilch', 'Knstrn', u'Psrc1', u'Mis18bp1', u'Ube2c', u'Cdca2', u'Cdca3', u'Bub1', u'Cdca8', u'Kif20b', u'Smc3', u'Smc2', u'Mastl', u'Smc4', u'Kif23', u'Apitd1', 'Knl1', u'Vrk1', u'Plk1', u'Cntrob', u'Usp37', u'Birc5', u'Nup43', u'Kif2c']), geneids='ENSMUSG00000040084 ENSMUSG00000034349 ENSMUSG00000027469 ENSMUSG00000037313 ENSMUSG00000045328 ENSMUSG00000024974 ENSMUSG00000025358 ENSMUSG00000032782 ENSMUSG00000022177 ENSMUSG00000022070 ENSMUSG00000027379 ENSMUSG00000033952 ENSMUSG00000019773 ENSMUSG00000062510 ENSMUSG00000029521 ENSMUSG00000002068 ENSMUSG00000051378 ENSMUSG00000042029 ENSMUSG00000027715 ENSMUSG00000032254 ENSMUSG00000027306 ENSMUSG00000072082 ENSMUSG00000027496 ENSMUSG00000029283 ENSMUSG00000024660 ENSMUSG00000026622 ENSMUSG00000078762 ENSMUSG00000028873 ENSMUSG00000006398 ENSMUSG00000048922 ENSMUSG00000034906 ENSMUSG00000056394 ENSMUSG00000032397 ENSMUSG00000021965 ENSMUSG00000023015 ENSMUSG00000030867 ENSMUSG00000041498 ENSMUSG00000047534 ENSMUSG00000032400 ENSMUSG00000028312 ENSMUSG00000021115 ENSMUSG00000043065 ENSMUSG00000032477 ENSMUSG00000026683 ENSMUSG00000027326 ENSMUSG00000027635 ENSMUSG00000003824 ENSMUSG00000040034 ENSMUSG00000026039 ENSMUSG00000029414 ENSMUSG00000028066 ENSMUSG00000001403 ENSMUSG00000002055 ENSMUSG00000051220 ENSMUSG00000033364 ENSMUSG00000041431 ENSMUSG00000041238 ENSMUSG00000039994 ENSMUSG00000027331 ENSMUSG00000024056 ENSMUSG00000020492 ENSMUSG00000041133 ENSMUSG00000024989 ENSMUSG00000027699 ENSMUSG00000028896 ENSMUSG00000020897 ENSMUSG00000038252 ENSMUSG00000025001 ENSMUSG00000040599 ENSMUSG00000032218 ENSMUSG00000028678 ENSMUSG00000029472 ENSMUSG00000024795 ENSMUSG00000023940 ENSMUSG00000023505 ENSMUSG00000019942 ENSMUSG00000026779 ENSMUSG00000062248 ENSMUSG00000020326 ENSMUSG00000069910 ENSMUSG00000028212 ENSMUSG00000074476 ENSMUSG00000073705 ENSMUSG00000068744 ENSMUSG00000038943 ENSMUSG00000026088 ENSMUSG00000012443 ENSMUSG00000017499 ENSMUSG00000031478 ENSMUSG00000020808 ENSMUSG00000017716 ENSMUSG00000029910 ENSMUSG00000035024 ENSMUSG00000005233', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=54, D1='BC', GO_name='cell division'), Nt(p_uncorrected=6.48431637746412e-05, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.006338314673223154, study_items=set([u'ENSMUSG00000017499', u'ENSMUSG00000027699', u'ENSMUSG00000032254', u'ENSMUSG00000023015', u'ENSMUSG00000024795', u'ENSMUSG00000041498', u'ENSMUSG00000020897']), NS='BP', pop_items=set([u'ENSMUSG00000029516', u'ENSMUSG00000024795', u'ENSMUSG00000018509', u'ENSMUSG00000005533', u'ENSMUSG00000023015', u'ENSMUSG00000004591', u'ENSMUSG00000004364', u'ENSMUSG00000041498', u'ENSMUSG00000027330', u'ENSMUSG00000020897', u'ENSMUSG00000053119', u'ENSMUSG00000019433', u'ENSMUSG00000060735', u'ENSMUSG00000027699', u'ENSMUSG00000050930', u'ENSMUSG00000024068', u'ENSMUSG00000045038', u'ENSMUSG00000026991', u'ENSMUSG00000056763', u'ENSMUSG00000017499', u'ENSMUSG00000032259', u'ENSMUSG00000032254', u'ENSMUSG00000027475', u'ENSMUSG00000007815']), pop_n=13836, p_sm_bonferroni=0.9824387743495889, is_obsolete=False, GO='GO:0032467', name='positive regulation of cytokinesis', pop_count=24, alt_ids=['GO:0071777'], level=6, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000017499', u'ENSMUSG00000027699', u'ENSMUSG00000041498', u'ENSMUSG00000024795', u'ENSMUSG00000020897', u'ENSMUSG00000032254', u'ENSMUSG00000023015']), symbols=u'Aurkb Cdc6 Ect2 Kif14 Kif20b Kif23 Racgap1', symbol_set=set([u'Ect2', u'Racgap1', u'Kif23', u'Kif14', u'Aurkb', u'Kif20b', u'Cdc6']), geneids='ENSMUSG00000017499 ENSMUSG00000027699 ENSMUSG00000032254 ENSMUSG00000023015 ENSMUSG00000024795 ENSMUSG00000041498 ENSMUSG00000020897', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=18, D1='A', GO_name='positive regulation of cytokinesis'), Nt(p_uncorrected=0.00012842189570401926, study_count=10, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000036986', u'ENSMUSG00000004446', u'ENSMUSG00000026104', u'ENSMUSG00000028282', u'ENSMUSG00000019979', u'ENSMUSG00000057789', u'ENSMUSG00000025507']), NS='BP', pop_items=set([u'ENSMUSG00000003955', u'ENSMUSG00000024012', u'ENSMUSG00000003873', u'ENSMUSG00000029433', u'ENSMUSG00000021576', u'ENSMUSG00000039168', u'ENSMUSG00000030793', u'ENSMUSG00000036986', u'ENSMUSG00000028282', u'ENSMUSG00000003031', u'ENSMUSG00000030110', u'ENSMUSG00000004446', u'ENSMUSG00000024959', u'ENSMUSG00000026029', u'ENSMUSG00000028914', u'ENSMUSG00000022346', u'ENSMUSG00000039959', u'ENSMUSG00000004069', u'ENSMUSG00000023030', u'ENSMUSG00000025507', u'ENSMUSG00000048376', u'ENSMUSG00000032402', u'ENSMUSG00000038007', u'ENSMUSG00000026104', u'ENSMUSG00000019979', u'ENSMUSG00000057789', u'ENSMUSG00000079465', u'ENSMUSG00000024066', u'ENSMUSG00000000915', u'ENSMUSG00000028191', u'ENSMUSG00000020372', u'ENSMUSG00000036932', u'ENSMUSG00000033075', u'ENSMUSG00000025889', u'ENSMUSG00000024789', u'ENSMUSG00000022883', u'ENSMUSG00000031668', u'ENSMUSG00000051234', u'ENSMUSG00000026278', u'ENSMUSG00000025980', u'ENSMUSG00000028452', u'ENSMUSG00000031523', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000028128', u'ENSMUSG00000070390', u'ENSMUSG00000032691', u'ENSMUSG00000045867', u'ENSMUSG00000027381', u'ENSMUSG00000032532', u'ENSMUSG00000038058', u'ENSMUSG00000014771', u'ENSMUSG00000041241', u'ENSMUSG00000032965']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0006919', name='activation of cysteine-type endopeptidase activity involved in apoptotic process', pop_count=54, alt_ids=[], level=9, depth=13, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000036986', u'ENSMUSG00000028282', u'ENSMUSG00000026104', u'ENSMUSG00000004446', u'ENSMUSG00000057789', u'ENSMUSG00000025507', u'ENSMUSG00000019979']), symbols=u'Apaf1 Bak1 Bax Bbc3 Bid Casp8ap2 Pidd1 Pmaip1 Pml Stat1', symbol_set=set([u'Pmaip1', u'Stat1', u'Casp8ap2', u'Bax', u'Bak1', u'Pml', u'Bbc3', 'Pidd1', u'Bid', u'Apaf1']), geneids='ENSMUSG00000019979 ENSMUSG00000002083 ENSMUSG00000024521 ENSMUSG00000036986 ENSMUSG00000025507 ENSMUSG00000028282 ENSMUSG00000026104 ENSMUSG00000004446 ENSMUSG00000057789 ENSMUSG00000003873', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=1, D1='A', GO_name='activation of cysteine-type endopeptidase activity involved in apoptotic process'), Nt(p_uncorrected=4.7830996364588304e-08, study_count=29, study_n=624, namespace='biological_process', p_fdr_bh=1.0502716317679384e-05, study_items=set([u'ENSMUSG00000032661', u'ENSMUSG00000070034', u'ENSMUSG00000046718', u'ENSMUSG00000074151', u'ENSMUSG00000036986', u'ENSMUSG00000074896', u'ENSMUSG00000041827', u'ENSMUSG00000032508', u'ENSMUSG00000023341', u'ENSMUSG00000054072', u'ENSMUSG00000021624', u'ENSMUSG00000039236', u'ENSMUSG00000054717', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000024079', u'ENSMUSG00000046879', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000005566', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000034459', u'ENSMUSG00000025498', u'ENSMUSG00000040296', u'ENSMUSG00000032344', u'ENSMUSG00000020641', u'ENSMUSG00000045932', u'ENSMUSG00000000386']), NS='BP', pop_items=set([u'ENSMUSG00000028099', u'ENSMUSG00000035834', u'ENSMUSG00000045322', u'ENSMUSG00000028874', u'ENSMUSG00000031103', u'ENSMUSG00000021703', u'ENSMUSG00000024079', u'ENSMUSG00000074151', u'ENSMUSG00000016481', u'ENSMUSG00000055172', u'ENSMUSG00000036887', u'ENSMUSG00000009585', u'ENSMUSG00000020455', u'ENSMUSG00000047123', u'ENSMUSG00000022476', u'ENSMUSG00000024371', u'ENSMUSG00000042228', u'ENSMUSG00000000266', u'ENSMUSG00000017707', u'ENSMUSG00000071369', u'ENSMUSG00000026399', u'ENSMUSG00000037523', u'ENSMUSG00000038628', u'ENSMUSG00000020115', u'ENSMUSG00000076617', u'ENSMUSG00000000776', u'ENSMUSG00000019843', u'ENSMUSG00000035235', u'ENSMUSG00000015217', u'ENSMUSG00000028530', u'ENSMUSG00000039236', u'ENSMUSG00000036908', u'ENSMUSG00000024164', u'ENSMUSG00000026842', u'ENSMUSG00000020275', u'ENSMUSG00000024045', u'ENSMUSG00000015340', u'ENSMUSG00000075705', u'ENSMUSG00000025280', u'ENSMUSG00000022791', u'ENSMUSG00000005566', u'ENSMUSG00000026596', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000025199', u'ENSMUSG00000014599', u'ENSMUSG00000022607', u'ENSMUSG00000030966', u'ENSMUSG00000032312', u'ENSMUSG00000051439', u'ENSMUSG00000038058', u'ENSMUSG00000025512', u'ENSMUSG00000050199', u'ENSMUSG00000026154', u'ENSMUSG00000001366', u'ENSMUSG00000000275', u'ENSMUSG00000027951', u'ENSMUSG00000021326', u'ENSMUSG00000070390', u'ENSMUSG00000036986', u'ENSMUSG00000025139', u'ENSMUSG00000004707', u'ENSMUSG00000025034', u'ENSMUSG00000026883', u'ENSMUSG00000058715', u'ENSMUSG00000032691', u'ENSMUSG00000018446', u'ENSMUSG00000006519', u'ENSMUSG00000027995', u'ENSMUSG00000028885', u'ENSMUSG00000029826', u'ENSMUSG00000027646', u'ENSMUSG00000003184', u'ENSMUSG00000031805', u'ENSMUSG00000016024', u'ENSMUSG00000054072', u'ENSMUSG00000051675', u'ENSMUSG00000037860', u'ENSMUSG00000036905', u'ENSMUSG00000004933', u'ENSMUSG00000031392', u'ENSMUSG00000060591', u'ENSMUSG00000055204', u'ENSMUSG00000041000', u'ENSMUSG00000045932', u'ENSMUSG00000072115', u'ENSMUSG00000033777', u'ENSMUSG00000059883', u'ENSMUSG00000027598', u'ENSMUSG00000003283', u'ENSMUSG00000033124', u'ENSMUSG00000044583', u'ENSMUSG00000002688', u'ENSMUSG00000039853', u'ENSMUSG00000078942', u'ENSMUSG00000078945', u'ENSMUSG00000027639', u'ENSMUSG00000033307', u'ENSMUSG00000034889', u'ENSMUSG00000000787', u'ENSMUSG00000034453', u'ENSMUSG00000020641', u'ENSMUSG00000024457', u'ENSMUSG00000023992', u'ENSMUSG00000025532', u'ENSMUSG00000000386', u'ENSMUSG00000052384', u'ENSMUSG00000070034', u'ENSMUSG00000027427', u'ENSMUSG00000026928', u'ENSMUSG00000035279', u'ENSMUSG00000030793', u'ENSMUSG00000021457', u'ENSMUSG00000074896', u'ENSMUSG00000024948', u'ENSMUSG00000031639', u'ENSMUSG00000020823', u'ENSMUSG00000028041', u'ENSMUSG00000025498', u'ENSMUSG00000032508', u'ENSMUSG00000002602', u'ENSMUSG00000053647', u'ENSMUSG00000053158', u'ENSMUSG00000024621', u'ENSMUSG00000066232', u'ENSMUSG00000036896', u'ENSMUSG00000025225', u'ENSMUSG00000071203', u'ENSMUSG00000030880', u'ENSMUSG00000032175', u'ENSMUSG00000041135', u'ENSMUSG00000014932', u'ENSMUSG00000021624', u'ENSMUSG00000020707', u'ENSMUSG00000017830', u'ENSMUSG00000046879', u'ENSMUSG00000024349', u'ENSMUSG00000033454', u'ENSMUSG00000022514', u'ENSMUSG00000022887', u'ENSMUSG00000023973', u'ENSMUSG00000043496', u'ENSMUSG00000057982', u'ENSMUSG00000036712', u'ENSMUSG00000025492', u'ENSMUSG00000032109', u'ENSMUSG00000060802', u'ENSMUSG00000029798', u'ENSMUSG00000032344', u'ENSMUSG00000059456', u'ENSMUSG00000026117', u'ENSMUSG00000040296', u'ENSMUSG00000032690', u'ENSMUSG00000056851', u'ENSMUSG00000038160', u'ENSMUSG00000022043', u'ENSMUSG00000034317', u'ENSMUSG00000001128', u'ENSMUSG00000029771', u'ENSMUSG00000013707', u'ENSMUSG00000032661', u'ENSMUSG00000038521', u'ENSMUSG00000020399', u'ENSMUSG00000031750', u'ENSMUSG00000046718', u'ENSMUSG00000024927', u'ENSMUSG00000031537', u'ENSMUSG00000024483', u'ENSMUSG00000050335', u'ENSMUSG00000032688', u'ENSMUSG00000026471', u'ENSMUSG00000032905', u'ENSMUSG00000038517', u'ENSMUSG00000023341', u'ENSMUSG00000000127', u'ENSMUSG00000023224', u'ENSMUSG00000015947', u'ENSMUSG00000027514', u'ENSMUSG00000002983', u'ENSMUSG00000039005', u'ENSMUSG00000041827', u'ENSMUSG00000028059', u'ENSMUSG00000054717', u'ENSMUSG00000018899', u'ENSMUSG00000021277', u'ENSMUSG00000024789', u'ENSMUSG00000033538', u'ENSMUSG00000028291', u'ENSMUSG00000029217', u'ENSMUSG00000022575', u'ENSMUSG00000066839', u'ENSMUSG00000029561', u'ENSMUSG00000029915', u'ENSMUSG00000056612', u'ENSMUSG00000044827', u'ENSMUSG00000028163', u'ENSMUSG00000043279', u'ENSMUSG00000026365', u'ENSMUSG00000032322', u'ENSMUSG00000034459', u'ENSMUSG00000039936', u'ENSMUSG00000021423', u'ENSMUSG00000038147', u'ENSMUSG00000050132', u'ENSMUSG00000032041', u'ENSMUSG00000046034']), pop_n=13836, p_sm_bonferroni=0.0007246874259198774, is_obsolete=False, GO='GO:0045087', name='innate immune response', pop_count=206, alt_ids=['GO:0002226'], level=3, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032344', u'ENSMUSG00000032661', u'ENSMUSG00000039236', u'ENSMUSG00000070034', u'ENSMUSG00000018899', u'ENSMUSG00000027514', u'ENSMUSG00000024079', u'ENSMUSG00000046718', u'ENSMUSG00000074151', u'ENSMUSG00000036986', u'ENSMUSG00000029561', u'ENSMUSG00000017830', u'ENSMUSG00000074896', u'ENSMUSG00000054717', u'ENSMUSG00000029605', u'ENSMUSG00000026896', u'ENSMUSG00000041827', u'ENSMUSG00000032508', u'ENSMUSG00000034459', u'ENSMUSG00000046879', u'ENSMUSG00000023341', u'ENSMUSG00000040296', u'ENSMUSG00000025498', u'ENSMUSG00000020641', u'ENSMUSG00000054072', u'ENSMUSG00000045932', u'ENSMUSG00000005566', u'ENSMUSG00000000386', u'ENSMUSG00000021624']), symbols=u'Bst2 Cd180 Ddx58 Dhx58 Eif2ak2 Hmgb2 Ifih1 Ifit1 Ifit2 Ifit3 Iigp1 Irf1 Irf7 Irgm1 Isg20 Mb21d1 Mx1 Mx2 Myd88 Nlrc5 Oas1b Oas3 Oasl1 Oasl2 Pml Rsad2 Sp110 Trim28 Zbp1', symbol_set=set(['Mb21d1', u'Sp110', u'Mx1', u'Iigp1', u'Irf1', u'Irf7', u'Zbp1', u'Eif2ak2', u'Oas3', u'Isg20', u'Nlrc5', u'Cd180', u'Oasl2', u'Ifih1', u'Oasl1', u'Irgm1', u'Ddx58', u'Oas1b', u'Trim28', u'Dhx58', u'Hmgb2', u'Mx2', u'Ifit2', u'Bst2', u'Pml', u'Myd88', u'Ifit3', u'Rsad2', u'Ifit1']), geneids='ENSMUSG00000032661 ENSMUSG00000023341 ENSMUSG00000070034 ENSMUSG00000024079 ENSMUSG00000074151 ENSMUSG00000036986 ENSMUSG00000074896 ENSMUSG00000041827 ENSMUSG00000032508 ENSMUSG00000017830 ENSMUSG00000054072 ENSMUSG00000021624 ENSMUSG00000039236 ENSMUSG00000054717 ENSMUSG00000018899 ENSMUSG00000027514 ENSMUSG00000046718 ENSMUSG00000046879 ENSMUSG00000029561 ENSMUSG00000005566 ENSMUSG00000029605 ENSMUSG00000026896 ENSMUSG00000034459 ENSMUSG00000032344 ENSMUSG00000040296 ENSMUSG00000025498 ENSMUSG00000020641 ENSMUSG00000045932 ENSMUSG00000000386', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=26, D1='FL', GO_name='innate immune response'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0006461', name='', pop_count='', alt_ids='', level=5, depth=5, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=170, D1='BH', GO_name='protein complex assembly'), Nt(p_uncorrected=0.00012860653072037162, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.010589769276871469, study_items=set([u'ENSMUSG00000027469', u'ENSMUSG00000022070', u'ENSMUSG00000068744', u'ENSMUSG00000037313']), NS='BP', pop_items=set([u'ENSMUSG00000027469', u'ENSMUSG00000022070', u'ENSMUSG00000032855', u'ENSMUSG00000037313', u'ENSMUSG00000023249', u'ENSMUSG00000047126', u'ENSMUSG00000068744']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0060236', name='regulation of mitotic spindle organization', pop_count=7, alt_ids=[], level=7, depth=9, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027469', u'ENSMUSG00000022070', u'ENSMUSG00000068744', u'ENSMUSG00000037313']), symbols=u'Bora Psrc1 Tacc3 Tpx2', symbol_set=set([u'Tpx2', u'Tacc3', u'Psrc1', 'Bora']), geneids='ENSMUSG00000027469 ENSMUSG00000022070 ENSMUSG00000068744 ENSMUSG00000037313', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=6, D1='A', GO_name='regulation of mitotic spindle organization'), Nt(p_uncorrected=4.79364473285348e-07, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=8.348104752581963e-05, study_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000038379', u'ENSMUSG00000045328', u'ENSMUSG00000029910', u'ENSMUSG00000024542', u'ENSMUSG00000030867', u'ENSMUSG00000027379', u'ENSMUSG00000034218']), NS='BP', pop_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000024537', u'ENSMUSG00000022750', u'ENSMUSG00000038379', u'ENSMUSG00000029910', u'ENSMUSG00000029554', u'ENSMUSG00000066979', u'ENSMUSG00000045328', u'ENSMUSG00000006005', u'ENSMUSG00000005871', u'ENSMUSG00000030867', u'ENSMUSG00000034509', u'ENSMUSG00000032264', u'ENSMUSG00000017421', u'ENSMUSG00000027379', u'ENSMUSG00000034218', u'ENSMUSG00000025925', u'ENSMUSG00000024542']), pop_n=13836, p_sm_bonferroni=0.007262851134746308, is_obsolete=False, GO='GO:0007094', name='mitotic spindle assembly checkpoint', pop_count=18, alt_ids=[], level=5, depth=13, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000040084', u'ENSMUSG00000038379', u'ENSMUSG00000045328', u'ENSMUSG00000029910', u'ENSMUSG00000024542', u'ENSMUSG00000030867', u'ENSMUSG00000027379', u'ENSMUSG00000034218']), symbols=u'Atm Bub1 Bub1b Cenpe Cep192 Mad2l1 Plk1 Ttk', symbol_set=set([u'Mad2l1', u'Bub1', u'Bub1b', u'Plk1', u'Cenpe', u'Atm', u'Cep192', u'Ttk']), geneids='ENSMUSG00000040084 ENSMUSG00000038379 ENSMUSG00000045328 ENSMUSG00000029910 ENSMUSG00000024542 ENSMUSG00000030867 ENSMUSG00000027379 ENSMUSG00000034218', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='AB', GO_name='mitotic spindle assembly checkpoint'), Nt(p_uncorrected=9.573736428560848e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.008384490209776035, study_items=set([u'ENSMUSG00000002083', u'ENSMUSG00000028702', u'ENSMUSG00000059552', u'ENSMUSG00000005370', u'ENSMUSG00000034218', u'ENSMUSG00000078773']), NS='BP', pop_items=set([u'ENSMUSG00000029104', u'ENSMUSG00000021268', u'ENSMUSG00000036273', u'ENSMUSG00000026288', u'ENSMUSG00000002083', u'ENSMUSG00000004263', u'ENSMUSG00000056999', u'ENSMUSG00000028702', u'ENSMUSG00000039428', u'ENSMUSG00000005370', u'ENSMUSG00000026048', u'ENSMUSG00000057637', u'ENSMUSG00000059552', u'ENSMUSG00000026380', u'ENSMUSG00000024151', u'ENSMUSG00000078773', u'ENSMUSG00000034218', u'ENSMUSG00000030652']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0008340', name='determination of adult lifespan', pop_count=18, alt_ids=[], level=3, depth=3, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000034218', u'ENSMUSG00000005370', u'ENSMUSG00000002083', u'ENSMUSG00000059552', u'ENSMUSG00000078773', u'ENSMUSG00000028702']), symbols=u'Atm Bbc3 Msh6 Rad54b Rad54l Trp53', symbol_set=set([u'Rad54b', u'Trp53', u'Rad54l', u'Atm', u'Msh6', u'Bbc3']), geneids='ENSMUSG00000002083 ENSMUSG00000028702 ENSMUSG00000059552 ENSMUSG00000005370 ENSMUSG00000034218 ENSMUSG00000078773', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='CJ', GO_name='determination of adult lifespan'), Nt(p_uncorrected=0.00017467511089396258, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.013790477588226161, study_items=set([u'ENSMUSG00000027715', u'ENSMUSG00000026605', u'ENSMUSG00000041498', u'ENSMUSG00000025358', u'ENSMUSG00000020898']), NS='BP', pop_items=set([u'ENSMUSG00000040274', u'ENSMUSG00000034402', u'ENSMUSG00000027499', u'ENSMUSG00000027715', u'ENSMUSG00000053819', u'ENSMUSG00000025358', u'ENSMUSG00000041498', u'ENSMUSG00000063275', u'ENSMUSG00000026778', u'ENSMUSG00000006728', u'ENSMUSG00000020898', u'ENSMUSG00000026605', u'ENSMUSG00000021932']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0010389', name='regulation of G2/M transition of mitotic cell cycle', pop_count=13, alt_ids=[], level=7, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027715', u'ENSMUSG00000026605', u'ENSMUSG00000041498', u'ENSMUSG00000025358', u'ENSMUSG00000020898']), symbols=u'Ccna2 Cdk2 Cenpf Ctc1 Kif14', symbol_set=set([u'Kif14', u'Cenpf', u'Cdk2', u'Ccna2', 'Ctc1']), geneids='ENSMUSG00000027715 ENSMUSG00000026605 ENSMUSG00000041498 ENSMUSG00000025358 ENSMUSG00000020898', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=14, D1='A', GO_name='regulation of G2/M transition of mitotic cell cycle'), Nt(p_uncorrected=0.0006920361223044611, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.0468082111117629, study_items=set([u'ENSMUSG00000004446', u'ENSMUSG00000028224', u'ENSMUSG00000041133', u'ENSMUSG00000029521']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000059923', u'ENSMUSG00000036390', u'ENSMUSG00000029521', u'ENSMUSG00000028914', u'ENSMUSG00000030990', u'ENSMUSG00000026842', u'ENSMUSG00000053436', u'ENSMUSG00000004446', u'ENSMUSG00000041133']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0042770', name='signal transduction in response to DNA damage', pop_count=10, alt_ids=[], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000004446', u'ENSMUSG00000028224', u'ENSMUSG00000041133', u'ENSMUSG00000029521']), symbols=u'Bid Chek2 Nbn Smc1a', symbol_set=set([u'Smc1a', u'Bid', u'Chek2', u'Nbn']), geneids='ENSMUSG00000004446 ENSMUSG00000028224 ENSMUSG00000041133 ENSMUSG00000029521', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=11, D1='ABF', GO_name='signal transduction in response to DNA damage'), Nt(p_uncorrected=2.6139984942594557e-09, study_count=12, study_n=624, namespace='biological_process', p_fdr_bh=9.088283859667372e-07, study_items=set([u'ENSMUSG00000029521', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000023067', u'ENSMUSG00000030609', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000020108', u'ENSMUSG00000041147', u'ENSMUSG00000041801', u'ENSMUSG00000036822']), NS='BP', pop_items=set([u'ENSMUSG00000061436', u'ENSMUSG00000024392', u'ENSMUSG00000030793', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000029026', u'ENSMUSG00000030609', u'ENSMUSG00000030990', u'ENSMUSG00000028630', u'ENSMUSG00000032267', u'ENSMUSG00000034659', u'ENSMUSG00000004071', u'ENSMUSG00000020063', u'ENSMUSG00000024151', u'ENSMUSG00000036822', u'ENSMUSG00000029521', u'ENSMUSG00000073489', u'ENSMUSG00000041147', u'ENSMUSG00000055024', u'ENSMUSG00000036781', u'ENSMUSG00000041801', u'ENSMUSG00000008730', u'ENSMUSG00000030717', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000053175', u'ENSMUSG00000023067', u'ENSMUSG00000021039', u'ENSMUSG00000020108']), pop_n=13836, p_sm_bonferroni=3.9604691186525016e-05, is_obsolete=False, GO='GO:0042771', name='intrinsic apoptotic signaling pathway in response to DNA damage by p53 class mediator', pop_count=30, alt_ids=[], level=6, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000029521', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000023067', u'ENSMUSG00000030609', u'ENSMUSG00000036986', u'ENSMUSG00000059552', u'ENSMUSG00000020108', u'ENSMUSG00000041147', u'ENSMUSG00000041801', u'ENSMUSG00000036822']), symbols=u'Aen Bbc3 Brca2 Cdkn1a Chek2 Ddit4 Phlda3 Pmaip1 Pml Shisa5 Topors Trp53', symbol_set=set([u'Brca2', u'Pmaip1', u'Trp53', u'Cdkn1a', u'Shisa5', u'Pml', u'Ddit4', u'Bbc3', u'Topors', u'Chek2', u'Phlda3', u'Aen']), geneids='ENSMUSG00000029521 ENSMUSG00000025647 ENSMUSG00000002083 ENSMUSG00000024521 ENSMUSG00000023067 ENSMUSG00000030609 ENSMUSG00000036986 ENSMUSG00000059552 ENSMUSG00000020108 ENSMUSG00000041147 ENSMUSG00000041801 ENSMUSG00000036822', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='ABF', GO_name='intrinsic apoptotic signaling pathway in response to DNA damage by p53 class mediator'), Nt(p_uncorrected=1.5039379199994453e-10, study_count=19, study_n=624, namespace='biological_process', p_fdr_bh=7.350375298681159e-08, study_items=set([u'ENSMUSG00000031311', u'ENSMUSG00000039748', u'ENSMUSG00000020380', u'ENSMUSG00000054717', u'ENSMUSG00000030346', u'ENSMUSG00000027433', u'ENSMUSG00000033762', u'ENSMUSG00000056394', u'ENSMUSG00000002221', u'ENSMUSG00000049932', u'ENSMUSG00000017146', u'ENSMUSG00000020608', u'ENSMUSG00000041147', u'ENSMUSG00000028884', u'ENSMUSG00000038685', u'ENSMUSG00000027323', u'ENSMUSG00000019303', u'ENSMUSG00000030528', u'ENSMUSG00000044702']), NS='BP', pop_items=set([u'ENSMUSG00000059772', u'ENSMUSG00000024906', u'ENSMUSG00000018841', u'ENSMUSG00000033762', u'ENSMUSG00000039738', u'ENSMUSG00000020474', u'ENSMUSG00000018449', u'ENSMUSG00000047989', u'ENSMUSG00000031583', u'ENSMUSG00000012483', u'ENSMUSG00000021264', u'ENSMUSG00000030034', u'ENSMUSG00000030750', u'ENSMUSG00000030528', u'ENSMUSG00000049932', u'ENSMUSG00000038685', u'ENSMUSG00000073436', u'ENSMUSG00000003549', u'ENSMUSG00000028884', u'ENSMUSG00000022471', u'ENSMUSG00000028933', u'ENSMUSG00000019303', u'ENSMUSG00000020380', u'ENSMUSG00000025612', u'ENSMUSG00000070520', u'ENSMUSG00000056394', u'ENSMUSG00000041974', u'ENSMUSG00000017146', u'ENSMUSG00000020752', u'ENSMUSG00000062270', u'ENSMUSG00000021287', u'ENSMUSG00000044702', u'ENSMUSG00000026648', u'ENSMUSG00000039748', u'ENSMUSG00000018189', u'ENSMUSG00000054717', u'ENSMUSG00000025269', u'ENSMUSG00000030346', u'ENSMUSG00000020608', u'ENSMUSG00000014243', u'ENSMUSG00000027433', u'ENSMUSG00000003868', u'ENSMUSG00000041147', u'ENSMUSG00000024943', u'ENSMUSG00000027671', u'ENSMUSG00000030243', u'ENSMUSG00000015971', u'ENSMUSG00000040865', u'ENSMUSG00000031311', u'ENSMUSG00000026187', u'ENSMUSG00000043535', u'ENSMUSG00000035960', u'ENSMUSG00000030079', u'ENSMUSG00000037262', u'ENSMUSG00000000751', u'ENSMUSG00000037570', u'ENSMUSG00000049717', u'ENSMUSG00000037761', u'ENSMUSG00000059586', u'ENSMUSG00000020697', u'ENSMUSG00000034154', u'ENSMUSG00000027323', u'ENSMUSG00000020079', u'ENSMUSG00000002221', u'ENSMUSG00000051238', u'ENSMUSG00000007646', u'ENSMUSG00000030166', u'ENSMUSG00000021615', u'ENSMUSG00000042185', u'ENSMUSG00000006335']), pop_n=13836, p_sm_bonferroni=2.2786163425911594e-06, is_obsolete=False, GO='GO:0006310', name='DNA recombination', pop_count=70, alt_ids=[], level=5, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000039748', u'ENSMUSG00000054717', u'ENSMUSG00000030346', u'ENSMUSG00000030528', u'ENSMUSG00000027433', u'ENSMUSG00000033762', u'ENSMUSG00000038685', u'ENSMUSG00000031311', u'ENSMUSG00000019303', u'ENSMUSG00000056394', u'ENSMUSG00000044702', u'ENSMUSG00000049932', u'ENSMUSG00000028884', u'ENSMUSG00000020380', u'ENSMUSG00000027323', u'ENSMUSG00000002221', u'ENSMUSG00000017146', u'ENSMUSG00000020608', u'ENSMUSG00000041147']), symbols=u'Blm Brca1 Brca2 Exo1 H2afx Hmgb2 Lig1 Nono Palb2 Paxip1 Psmc3ip Rad50 Rad51 Rad51ap1 Recql4 Rpa2 Rtel1 Smc6 Xrn2', symbol_set=set([u'Brca1', u'Recql4', u'Smc6', u'Rad51', u'Nono', u'Hmgb2', u'Palb2', u'Exo1', u'H2afx', u'Psmc3ip', u'Rpa2', u'Blm', u'Rad51ap1', u'Brca2', u'Lig1', u'Xrn2', u'Rad50', u'Paxip1', u'Rtel1']), geneids='ENSMUSG00000039748 ENSMUSG00000027433 ENSMUSG00000028884 ENSMUSG00000056394 ENSMUSG00000030346 ENSMUSG00000020380 ENSMUSG00000027323 ENSMUSG00000033762 ENSMUSG00000002221 ENSMUSG00000049932 ENSMUSG00000017146 ENSMUSG00000020608 ENSMUSG00000041147 ENSMUSG00000054717 ENSMUSG00000030528 ENSMUSG00000031311 ENSMUSG00000019303 ENSMUSG00000038685 ENSMUSG00000044702', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=52, D1='BD', GO_name='DNA recombination'), Nt(p_uncorrected=5.467793990178798e-11, study_count=14, study_n=624, namespace='biological_process', p_fdr_bh=3.774646010782965e-08, study_items=set([u'ENSMUSG00000062510', u'ENSMUSG00000029177', u'ENSMUSG00000024056', u'ENSMUSG00000028873', u'ENSMUSG00000027635', u'ENSMUSG00000027306', u'ENSMUSG00000029910', u'ENSMUSG00000058290', u'ENSMUSG00000040599', u'ENSMUSG00000030867', u'ENSMUSG00000027331', u'ENSMUSG00000051378', u'ENSMUSG00000026622', u'ENSMUSG00000002055']), NS='BP', pop_items=set([u'ENSMUSG00000029516', u'ENSMUSG00000024056', u'ENSMUSG00000002055', u'ENSMUSG00000031922', u'ENSMUSG00000030867', u'ENSMUSG00000027331', u'ENSMUSG00000032264', u'ENSMUSG00000022750', u'ENSMUSG00000019923', u'ENSMUSG00000062510', u'ENSMUSG00000034154', u'ENSMUSG00000066979', u'ENSMUSG00000058290', u'ENSMUSG00000017421', u'ENSMUSG00000051378', u'ENSMUSG00000040599', u'ENSMUSG00000029177', u'ENSMUSG00000028873', u'ENSMUSG00000027635', u'ENSMUSG00000027306', u'ENSMUSG00000029910', u'ENSMUSG00000019813', u'ENSMUSG00000026622']), pop_n=13836, p_sm_bonferroni=8.284254674519896e-07, is_obsolete=False, GO='GO:0000070', name='mitotic sister chromatid segregation', pop_count=23, alt_ids=['GO:0016359'], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000062510', u'ENSMUSG00000029177', u'ENSMUSG00000024056', u'ENSMUSG00000028873', u'ENSMUSG00000027635', u'ENSMUSG00000027306', u'ENSMUSG00000029910', u'ENSMUSG00000058290', u'ENSMUSG00000030867', u'ENSMUSG00000027331', u'ENSMUSG00000051378', u'ENSMUSG00000026622', u'ENSMUSG00000002055', u'ENSMUSG00000040599']), symbols=u'Cdca8 Cenpa Dsn1 Espl1 Kif18b Knstrn Mad2l1 Mis12 Ndc80 Nek2 Nsl1 Nusap1 Plk1 Spag5', symbol_set=set([u'Nsl1', 'Knstrn', u'Mad2l1', u'Nusap1', u'Plk1', u'Spag5', u'Dsn1', u'Cenpa', u'Kif18b', u'Espl1', u'Mis12', u'Nek2', u'Cdca8', u'Ndc80']), geneids='ENSMUSG00000062510 ENSMUSG00000029177 ENSMUSG00000024056 ENSMUSG00000002055 ENSMUSG00000027635 ENSMUSG00000027306 ENSMUSG00000029910 ENSMUSG00000058290 ENSMUSG00000040599 ENSMUSG00000030867 ENSMUSG00000027331 ENSMUSG00000051378 ENSMUSG00000026622 ENSMUSG00000028873', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCH', GO_name='mitotic sister chromatid segregation'), Nt(p_uncorrected=8.945577520622059e-06, study_count=8, study_n=624, namespace='biological_process', p_fdr_bh=0.001075670198531308, study_items=set([u'ENSMUSG00000032397', u'ENSMUSG00000028224', u'ENSMUSG00000029521', u'ENSMUSG00000032113', u'ENSMUSG00000027490', u'ENSMUSG00000042489', u'ENSMUSG00000034218', u'ENSMUSG00000032409']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000020413', u'ENSMUSG00000004085', u'ENSMUSG00000038569', u'ENSMUSG00000032119', u'ENSMUSG00000029238', u'ENSMUSG00000032113', u'ENSMUSG00000037461', u'ENSMUSG00000032267', u'ENSMUSG00000022248', u'ENSMUSG00000032409', u'ENSMUSG00000053436', u'ENSMUSG00000032397', u'ENSMUSG00000029521', u'ENSMUSG00000024824', u'ENSMUSG00000040843', u'ENSMUSG00000043733', u'ENSMUSG00000013698', u'ENSMUSG00000061589', u'ENSMUSG00000027490', u'ENSMUSG00000021635', u'ENSMUSG00000042489', u'ENSMUSG00000043909', u'ENSMUSG00000034218', u'ENSMUSG00000048668']), pop_n=13836, p_sm_bonferroni=0.1355344450149448, is_obsolete=False, GO='GO:0000077', name='DNA damage checkpoint', pop_count=25, alt_ids=[], level=4, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032397', u'ENSMUSG00000028224', u'ENSMUSG00000029521', u'ENSMUSG00000032113', u'ENSMUSG00000027490', u'ENSMUSG00000042489', u'ENSMUSG00000034218', u'ENSMUSG00000032409']), symbols=u'Atm Atr Chek1 Chek2 Clspn E2f1 Nbn Tipin', symbol_set=set([u'Atm', u'E2f1', u'Clspn', u'Tipin', u'Atr', u'Nbn', u'Chek2', u'Chek1']), geneids='ENSMUSG00000028224 ENSMUSG00000032397 ENSMUSG00000029521 ENSMUSG00000032113 ENSMUSG00000027490 ENSMUSG00000042489 ENSMUSG00000034218 ENSMUSG00000032409', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=6, D1='ABF', GO_name='DNA damage checkpoint'), Nt(p_uncorrected=5.716066791862708e-05, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.005735372712815357, study_items=set([u'ENSMUSG00000032397', u'ENSMUSG00000006585', u'ENSMUSG00000042489', u'ENSMUSG00000036875']), NS='BP', pop_items=set([u'ENSMUSG00000032397', u'ENSMUSG00000042489', u'ENSMUSG00000024824', u'ENSMUSG00000036875', u'ENSMUSG00000006585', u'ENSMUSG00000038569']), pop_n=13836, p_sm_bonferroni=0.8660412796351189, is_obsolete=False, GO='GO:0000076', name='DNA replication checkpoint', pop_count=6, alt_ids=[], level=4, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000032397', u'ENSMUSG00000006585', u'ENSMUSG00000042489', u'ENSMUSG00000036875']), symbols=u'Cdt1 Clspn Dna2 Tipin', symbol_set=set([u'Clspn', u'Cdt1', u'Dna2', u'Tipin']), geneids='ENSMUSG00000006585 ENSMUSG00000032397 ENSMUSG00000042489 ENSMUSG00000036875', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=2, D1='AB', GO_name='DNA replication checkpoint'), Nt(p_uncorrected=1.5588440593918757e-09, study_count=21, study_n=624, namespace='biological_process', p_fdr_bh=5.904511585961577e-07, study_items=set([u'ENSMUSG00000052684', u'ENSMUSG00000028212', u'ENSMUSG00000003873', u'ENSMUSG00000059552', u'ENSMUSG00000018983', u'ENSMUSG00000027641', u'ENSMUSG00000037313', u'ENSMUSG00000054115', u'ENSMUSG00000072082', u'ENSMUSG00000002068', u'ENSMUSG00000035455', u'ENSMUSG00000023067', u'ENSMUSG00000001855', u'ENSMUSG00000026779', u'ENSMUSG00000027490', u'ENSMUSG00000037474', u'ENSMUSG00000040204', u'ENSMUSG00000020326', u'ENSMUSG00000057789', u'ENSMUSG00000034218', u'ENSMUSG00000020493']), NS='BP', pop_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000020262', u'ENSMUSG00000023572', u'ENSMUSG00000059552', u'ENSMUSG00000048661', u'ENSMUSG00000018841', u'ENSMUSG00000052837', u'ENSMUSG00000025616', u'ENSMUSG00000070348', u'ENSMUSG00000028580', u'ENSMUSG00000028820', u'ENSMUSG00000025917', u'ENSMUSG00000026395', u'ENSMUSG00000026812', u'ENSMUSG00000020372', u'ENSMUSG00000027552', u'ENSMUSG00000002068', u'ENSMUSG00000037313', u'ENSMUSG00000002496', u'ENSMUSG00000001855', u'ENSMUSG00000057367', u'ENSMUSG00000023067', u'ENSMUSG00000072082', u'ENSMUSG00000027490', u'ENSMUSG00000033949', u'ENSMUSG00000015656', u'ENSMUSG00000039474', u'ENSMUSG00000036390', u'ENSMUSG00000071076', u'ENSMUSG00000018983', u'ENSMUSG00000025217', u'ENSMUSG00000055116', u'ENSMUSG00000040957', u'ENSMUSG00000052684', u'ENSMUSG00000014859', u'ENSMUSG00000022557', u'ENSMUSG00000027641', u'ENSMUSG00000027646', u'ENSMUSG00000015149', u'ENSMUSG00000057789', u'ENSMUSG00000022018', u'ENSMUSG00000051177', u'ENSMUSG00000038344', u'ENSMUSG00000009681', u'ENSMUSG00000032968', u'ENSMUSG00000037373', u'ENSMUSG00000037474', u'ENSMUSG00000035455', u'ENSMUSG00000034218', u'ENSMUSG00000034165', u'ENSMUSG00000020349', u'ENSMUSG00000021453', u'ENSMUSG00000026842', u'ENSMUSG00000013663', u'ENSMUSG00000024537', u'ENSMUSG00000054115', u'ENSMUSG00000030061', u'ENSMUSG00000034201', u'ENSMUSG00000020430', u'ENSMUSG00000020493', u'ENSMUSG00000066043', u'ENSMUSG00000021514', u'ENSMUSG00000015312', u'ENSMUSG00000020950', u'ENSMUSG00000057113', u'ENSMUSG00000025809', u'ENSMUSG00000021901', u'ENSMUSG00000046707', u'ENSMUSG00000040204', u'ENSMUSG00000040687', u'ENSMUSG00000007872', u'ENSMUSG00000057329', u'ENSMUSG00000022961', u'ENSMUSG00000006728', u'ENSMUSG00000029385', u'ENSMUSG00000038990', u'ENSMUSG00000027684', u'ENSMUSG00000033862', u'ENSMUSG00000000282', u'ENSMUSG00000041459', u'ENSMUSG00000085795', u'ENSMUSG00000026779', u'ENSMUSG00000063015', u'ENSMUSG00000056917', u'ENSMUSG00000003228', u'ENSMUSG00000020326', u'ENSMUSG00000055866', u'ENSMUSG00000028212', u'ENSMUSG00000056596', u'ENSMUSG00000005871', u'ENSMUSG00000031666', u'ENSMUSG00000000184', u'ENSMUSG00000027852', u'ENSMUSG00000004040', u'ENSMUSG00000041415', u'ENSMUSG00000019970', u'ENSMUSG00000022105']), pop_n=13836, p_sm_bonferroni=2.361804634384631e-05, is_obsolete=False, GO='GO:0051726', name='regulation of cell cycle', pop_count=97, alt_ids=['GO:0000074'], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028212', u'ENSMUSG00000003873', u'ENSMUSG00000018983', u'ENSMUSG00000002068', u'ENSMUSG00000034218', u'ENSMUSG00000037313', u'ENSMUSG00000059552', u'ENSMUSG00000052684', u'ENSMUSG00000020493', u'ENSMUSG00000001855', u'ENSMUSG00000037474', u'ENSMUSG00000027641', u'ENSMUSG00000054115', u'ENSMUSG00000072082', u'ENSMUSG00000027490', u'ENSMUSG00000035455', u'ENSMUSG00000023067', u'ENSMUSG00000026779', u'ENSMUSG00000040204', u'ENSMUSG00000057789', u'ENSMUSG00000020326']), symbols=u'Atm Bak1 Bax Ccne1 Ccne2 Ccnf Ccng1 Cdkn1a Dtl E2f1 E2f2 Fignl1 Jun Mastl Nup214 Pclaf Prr11 Rbl1 Skp2 Tacc3 Trp53', symbol_set=set([u'Dtl', u'Ccne1', u'Skp2', u'E2f2', u'E2f1', u'Trp53', u'Ccne2', u'Mastl', u'Cdkn1a', u'Tacc3', u'Jun', u'Bax', u'Fignl1', u'Ccng1', u'Ccnf', u'Prr11', u'Nup214', 'Pclaf', u'Atm', u'Bak1', u'Rbl1']), geneids='ENSMUSG00000040204 ENSMUSG00000001855 ENSMUSG00000003873 ENSMUSG00000059552 ENSMUSG00000054115 ENSMUSG00000018983 ENSMUSG00000027641 ENSMUSG00000037474 ENSMUSG00000023067 ENSMUSG00000027490 ENSMUSG00000002068 ENSMUSG00000072082 ENSMUSG00000035455 ENSMUSG00000034218 ENSMUSG00000028212 ENSMUSG00000026779 ENSMUSG00000037313 ENSMUSG00000020493 ENSMUSG00000052684 ENSMUSG00000057789 ENSMUSG00000020326', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=412, D1='A', GO_name='regulation of cell cycle'), Nt(p_uncorrected='', study_count='', study_n='', namespace='', p_fdr_bh='', study_items='', NS='BP', pop_items='', pop_n='', p_sm_bonferroni='', is_obsolete='', GO='GO:0032204', name='', pop_count='', alt_ids='', level=4, depth=7, enrichment='', Cluster='', geneid_set='', symbols='', symbol_set='', geneids='', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=False, hdr1usr01='*', dcnt=32, D1='A', GO_name='regulation of telomere maintenance'), Nt(p_uncorrected=4.099215555456427e-06, study_count=4, study_n=624, namespace='biological_process', p_fdr_bh=0.000521909368745549, study_items=set([u'ENSMUSG00000059552', u'ENSMUSG00000034218', u'ENSMUSG00000032409', u'ENSMUSG00000020898']), NS='BP', pop_items=set([u'ENSMUSG00000034218', u'ENSMUSG00000059552', u'ENSMUSG00000032409', u'ENSMUSG00000020898']), pop_n=13836, p_sm_bonferroni=0.06210721488072033, is_obsolete=False, GO='GO:0090399', name='replicative senescence', pop_count=4, alt_ids=[], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000059552', u'ENSMUSG00000034218', u'ENSMUSG00000032409', u'ENSMUSG00000020898']), symbols=u'Atm Atr Ctc1 Trp53', symbol_set=set(['Ctc1', u'Atm', u'Atr', u'Trp53']), geneids='ENSMUSG00000034218 ENSMUSG00000059552 ENSMUSG00000032409 ENSMUSG00000020898', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCE', GO_name='replicative senescence'), Nt(p_uncorrected=6.761987816954612e-05, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.006525533593291677, study_items=set([u'ENSMUSG00000036986', u'ENSMUSG00000028224', u'ENSMUSG00000038685', u'ENSMUSG00000020380', u'ENSMUSG00000007589']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000031928', u'ENSMUSG00000020380', u'ENSMUSG00000042354', u'ENSMUSG00000031229', u'ENSMUSG00000031921', u'ENSMUSG00000007589', u'ENSMUSG00000036986', u'ENSMUSG00000038685', u'ENSMUSG00000034748', u'ENSMUSG00000027770']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0032206', name='positive regulation of telomere maintenance', pop_count=11, alt_ids=[], level=5, depth=8, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000036986', u'ENSMUSG00000028224', u'ENSMUSG00000038685', u'ENSMUSG00000020380', u'ENSMUSG00000007589']), symbols=u'Nbn Pml Rad50 Rtel1 Tinf2', symbol_set=set([u'Pml', u'Tinf2', u'Rtel1', u'Nbn', u'Rad50']), geneids='ENSMUSG00000028224 ENSMUSG00000020380 ENSMUSG00000036986 ENSMUSG00000007589 ENSMUSG00000038685', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=10, D1='A', GO_name='positive regulation of telomere maintenance'), Nt(p_uncorrected=1.2481129335863986e-07, study_count=14, study_n=624, namespace='biological_process', p_fdr_bh=2.5904327475024004e-05, study_items=set([u'ENSMUSG00000012443', u'ENSMUSG00000003779', u'ENSMUSG00000024301', u'ENSMUSG00000005237', u'ENSMUSG00000034311', u'ENSMUSG00000032254', u'ENSMUSG00000028678', u'ENSMUSG00000045328', u'ENSMUSG00000024795', u'ENSMUSG00000041498', u'ENSMUSG00000051378', u'ENSMUSG00000036768', u'ENSMUSG00000027115', u'ENSMUSG00000030677']), NS='BP', pop_items=set([u'ENSMUSG00000026494', u'ENSMUSG00000018707', u'ENSMUSG00000032489', u'ENSMUSG00000063077', u'ENSMUSG00000029757', u'ENSMUSG00000033705', u'ENSMUSG00000010021', u'ENSMUSG00000024795', u'ENSMUSG00000018395', u'ENSMUSG00000022629', u'ENSMUSG00000028438', u'ENSMUSG00000030677', u'ENSMUSG00000020821', u'ENSMUSG00000021843', u'ENSMUSG00000003779', u'ENSMUSG00000028678', u'ENSMUSG00000022262', u'ENSMUSG00000047459', u'ENSMUSG00000035770', u'ENSMUSG00000038844', u'ENSMUSG00000041498', u'ENSMUSG00000014602', u'ENSMUSG00000021288', u'ENSMUSG00000037933', u'ENSMUSG00000027115', u'ENSMUSG00000031788', u'ENSMUSG00000004187', u'ENSMUSG00000026764', u'ENSMUSG00000021693', u'ENSMUSG00000060176', u'ENSMUSG00000045328', u'ENSMUSG00000021375', u'ENSMUSG00000060012', u'ENSMUSG00000028758', u'ENSMUSG00000051378', u'ENSMUSG00000036768', u'ENSMUSG00000024862', u'ENSMUSG00000027012', u'ENSMUSG00000052273', u'ENSMUSG00000021879', u'ENSMUSG00000020668', u'ENSMUSG00000032254', u'ENSMUSG00000032435', u'ENSMUSG00000034311', u'ENSMUSG00000047193', u'ENSMUSG00000041642', u'ENSMUSG00000005237', u'ENSMUSG00000023999', u'ENSMUSG00000074657', u'ENSMUSG00000021076', u'ENSMUSG00000024301', u'ENSMUSG00000027475', u'ENSMUSG00000012443', u'ENSMUSG00000006740', u'ENSMUSG00000033826', u'ENSMUSG00000050382']), pop_n=13836, p_sm_bonferroni=0.0018910159056767526, is_obsolete=False, GO='GO:0007018', name='microtubule-based movement', pop_count=56, alt_ids=[], level=4, depth=4, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000030677', u'ENSMUSG00000003779', u'ENSMUSG00000051378', u'ENSMUSG00000024795', u'ENSMUSG00000045328', u'ENSMUSG00000032254', u'ENSMUSG00000028678', u'ENSMUSG00000034311', u'ENSMUSG00000027115', u'ENSMUSG00000005237', u'ENSMUSG00000041498', u'ENSMUSG00000024301', u'ENSMUSG00000012443', u'ENSMUSG00000036768']), symbols=u'Cenpe Dnah2 Kif11 Kif14 Kif15 Kif18a Kif18b Kif20a Kif20b Kif22 Kif23 Kif2c Kif4 Kifc5b', symbol_set=set(['Dnah2', u'Kif11', u'Cenpe', u'Kif18a', u'Kif23', u'Kif18b', u'Kif14', u'Kif15', u'Kifc5b', u'Kif22', u'Kif20b', u'Kif4', u'Kif2c', u'Kif20a']), geneids='ENSMUSG00000003779 ENSMUSG00000051378 ENSMUSG00000024795 ENSMUSG00000045328 ENSMUSG00000032254 ENSMUSG00000028678 ENSMUSG00000034311 ENSMUSG00000030677 ENSMUSG00000005237 ENSMUSG00000041498 ENSMUSG00000024301 ENSMUSG00000036768 ENSMUSG00000012443 ENSMUSG00000027115', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=78, D1='BC', GO_name='microtubule-based movement'), Nt(p_uncorrected=1.7006735838089953e-05, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.0019520382930522794, study_items=set([u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000024521', u'ENSMUSG00000004446', u'ENSMUSG00000059552', u'ENSMUSG00000057789', u'ENSMUSG00000052684']), NS='BP', pop_items=set([u'ENSMUSG00000026278', u'ENSMUSG00000004446', u'ENSMUSG00000020366', u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000029026', u'ENSMUSG00000024521', u'ENSMUSG00000003438', u'ENSMUSG00000006818', u'ENSMUSG00000002797', u'ENSMUSG00000022789', u'ENSMUSG00000019054', u'ENSMUSG00000032532', u'ENSMUSG00000007659', u'ENSMUSG00000059552', u'ENSMUSG00000024959', u'ENSMUSG00000057789', u'ENSMUSG00000057329', u'ENSMUSG00000033792', u'ENSMUSG00000052684']), pop_n=13836, p_sm_bonferroni=0.25766905468290086, is_obsolete=False, GO='GO:0001836', name='release of cytochrome c from mitochondria', pop_count=20, alt_ids=[], level=6, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000059552', u'ENSMUSG00000003873', u'ENSMUSG00000002083', u'ENSMUSG00000004446', u'ENSMUSG00000024521', u'ENSMUSG00000057789', u'ENSMUSG00000052684']), symbols=u'Bak1 Bax Bbc3 Bid Jun Pmaip1 Trp53', symbol_set=set([u'Pmaip1', u'Trp53', u'Bid', u'Jun', u'Bax', u'Bak1', u'Bbc3']), geneids='ENSMUSG00000003873 ENSMUSG00000002083 ENSMUSG00000024521 ENSMUSG00000059552 ENSMUSG00000004446 ENSMUSG00000057789 ENSMUSG00000052684', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BH', GO_name='release of cytochrome c from mitochondria'), Nt(p_uncorrected=1.8083719736883525e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.002044674908459122, study_items=set([u'ENSMUSG00000027959', u'ENSMUSG00000032782', u'ENSMUSG00000021572', u'ENSMUSG00000025358', u'ENSMUSG00000068394', u'ENSMUSG00000025758']), NS='BP', pop_items=set([u'ENSMUSG00000033904', u'ENSMUSG00000027959', u'ENSMUSG00000064128', u'ENSMUSG00000032782', u'ENSMUSG00000020807', u'ENSMUSG00000031347', u'ENSMUSG00000021572', u'ENSMUSG00000025358', u'ENSMUSG00000032534', u'ENSMUSG00000068394', u'ENSMUSG00000036403', u'ENSMUSG00000025758', u'ENSMUSG00000037020', u'ENSMUSG00000039298']), pop_n=13836, p_sm_bonferroni=0.27398643773352227, is_obsolete=False, GO='GO:0007099', name='centriole replication', pop_count=14, alt_ids=['GO:0032054'], level=3, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000027959', u'ENSMUSG00000025358', u'ENSMUSG00000068394', u'ENSMUSG00000032782', u'ENSMUSG00000021572', u'ENSMUSG00000025758']), symbols=u'Cdk2 Cep152 Cep72 Cntrob Plk4 Sass6', symbol_set=set([u'Cep152', u'Plk4', u'Cntrob', u'Cdk2', u'Sass6', u'Cep72']), geneids='ENSMUSG00000027959 ENSMUSG00000032782 ENSMUSG00000021572 ENSMUSG00000025358 ENSMUSG00000068394 ENSMUSG00000025758', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='BCH', GO_name='centriole replication'), Nt(p_uncorrected=0.0002616703282067204, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.01962657001316842, study_items=set([u'ENSMUSG00000035266', u'ENSMUSG00000039748', u'ENSMUSG00000025574', u'ENSMUSG00000020914', u'ENSMUSG00000027323']), NS='BP', pop_items=set([u'ENSMUSG00000035266', u'ENSMUSG00000039748', u'ENSMUSG00000022545', u'ENSMUSG00000026496', u'ENSMUSG00000020914', u'ENSMUSG00000017485', u'ENSMUSG00000025159', u'ENSMUSG00000055884', u'ENSMUSG00000025574', u'ENSMUSG00000031583', u'ENSMUSG00000039354', u'ENSMUSG00000024906', u'ENSMUSG00000003812', u'ENSMUSG00000027323']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0006259', name='DNA metabolic process', pop_count=14, alt_ids=['GO:0055132'], level=4, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000035266', u'ENSMUSG00000039748', u'ENSMUSG00000027323', u'ENSMUSG00000020914', u'ENSMUSG00000025574']), symbols=u'Exo1 Helq Rad51 Tk1 Top2a', symbol_set=set([u'Exo1', u'Helq', u'Tk1', u'Rad51', u'Top2a']), geneids='ENSMUSG00000035266 ENSMUSG00000039748 ENSMUSG00000027323 ENSMUSG00000020914 ENSMUSG00000025574', format_txt=1, hdr_idx=1, is_hdrgo=True, is_usrgo=True, hdr1usr01='**', dcnt=302, D1='BD', GO_name='DNA metabolic process'), Nt(p_uncorrected=6.63436507852268e-05, study_count=6, study_n=624, namespace='biological_process', p_fdr_bh=0.0064434144426087905, study_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000032555', u'ENSMUSG00000019942', u'ENSMUSG00000039187', u'ENSMUSG00000030528', u'ENSMUSG00000020326']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000031928', u'ENSMUSG00000003541', u'ENSMUSG00000032555', u'ENSMUSG00000030322', u'ENSMUSG00000021597', u'ENSMUSG00000061288', u'ENSMUSG00000020381', u'ENSMUSG00000019942', u'ENSMUSG00000039187', u'ENSMUSG00000042903', u'ENSMUSG00000030994', u'ENSMUSG00000028821', u'ENSMUSG00000018669', u'ENSMUSG00000024906', u'ENSMUSG00000030528', u'ENSMUSG00000020326']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0007095', name='mitotic G2 DNA damage checkpoint', pop_count=17, alt_ids=[], level=5, depth=11, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000028224', u'ENSMUSG00000032555', u'ENSMUSG00000030528', u'ENSMUSG00000019942', u'ENSMUSG00000039187', u'ENSMUSG00000020326']), symbols=u'Blm Ccng1 Cdk1 Fanci Nbn Topbp1', symbol_set=set([u'Topbp1', u'Ccng1', u'Blm', u'Cdk1', u'Nbn', u'Fanci']), geneids='ENSMUSG00000028224 ENSMUSG00000032555 ENSMUSG00000019942 ENSMUSG00000039187 ENSMUSG00000030528 ENSMUSG00000020326', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=0, D1='ABF', GO_name='mitotic G2 DNA damage checkpoint'), Nt(p_uncorrected=8.658111398305377e-05, study_count=7, study_n=624, namespace='biological_process', p_fdr_bh=0.007998722304617364, study_items=set([u'ENSMUSG00000029414', u'ENSMUSG00000028224', u'ENSMUSG00000038379', u'ENSMUSG00000032113', u'ENSMUSG00000029910', u'ENSMUSG00000032400', u'ENSMUSG00000041133']), NS='BP', pop_items=set([u'ENSMUSG00000028224', u'ENSMUSG00000029414', u'ENSMUSG00000038379', u'ENSMUSG00000027933', u'ENSMUSG00000020413', u'ENSMUSG00000043991', u'ENSMUSG00000025374', u'ENSMUSG00000034509', u'ENSMUSG00000002603', u'ENSMUSG00000032113', u'ENSMUSG00000000126', u'ENSMUSG00000032264', u'ENSMUSG00000026107', u'ENSMUSG00000045482', u'ENSMUSG00000041133', u'ENSMUSG00000019923', u'ENSMUSG00000021701', u'ENSMUSG00000032400', u'ENSMUSG00000014668', u'ENSMUSG00000004895', u'ENSMUSG00000025499', u'ENSMUSG00000029910', u'ENSMUSG00000021635', u'ENSMUSG00000028495', u'ENSMUSG00000007659']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0007093', name='mitotic cell cycle checkpoint', pop_count=25, alt_ids=['GO:0031575', 'GO:0071780'], level=3, depth=7, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000029414', u'ENSMUSG00000028224', u'ENSMUSG00000038379', u'ENSMUSG00000032400', u'ENSMUSG00000032113', u'ENSMUSG00000041133', u'ENSMUSG00000029910']), symbols=u'Chek1 Kntc1 Mad2l1 Nbn Smc1a Ttk Zwilch', symbol_set=set([u'Smc1a', u'Mad2l1', u'Kntc1', u'Ttk', u'Nbn', u'Zwilch', u'Chek1']), geneids='ENSMUSG00000028224 ENSMUSG00000029414 ENSMUSG00000038379 ENSMUSG00000032113 ENSMUSG00000029910 ENSMUSG00000032400 ENSMUSG00000041133', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=18, D1='AB', GO_name='mitotic cell cycle checkpoint'), Nt(p_uncorrected=7.499341564904797e-05, study_count=40, study_n=624, namespace='biological_process', p_fdr_bh=0.00714607069496054, study_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000070034', u'ENSMUSG00000003873', u'ENSMUSG00000027469', u'ENSMUSG00000036986', u'ENSMUSG00000040483', u'ENSMUSG00000059552', u'ENSMUSG00000002870', u'ENSMUSG00000029521', u'ENSMUSG00000002307', u'ENSMUSG00000030641', u'ENSMUSG00000035683', u'ENSMUSG00000032508', u'ENSMUSG00000035293', u'ENSMUSG00000019942', u'ENSMUSG00000025507', u'ENSMUSG00000028282', u'ENSMUSG00000027379', u'ENSMUSG00000022074', u'ENSMUSG00000057789', u'ENSMUSG00000028211', u'ENSMUSG00000055612', u'ENSMUSG00000018899', u'ENSMUSG00000041801', u'ENSMUSG00000006445', u'ENSMUSG00000040734', u'ENSMUSG00000004446', u'ENSMUSG00000019979', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000005413', u'ENSMUSG00000024521', u'ENSMUSG00000017716', u'ENSMUSG00000027490', u'ENSMUSG00000030609', u'ENSMUSG00000037725', u'ENSMUSG00000000037', u'ENSMUSG00000045932', u'ENSMUSG00000020108', u'ENSMUSG00000046607']), NS='BP', pop_items=set([u'ENSMUSG00000040084', u'ENSMUSG00000003873', u'ENSMUSG00000002015', u'ENSMUSG00000028029', u'ENSMUSG00000020190', u'ENSMUSG00000027381', u'ENSMUSG00000027387', u'ENSMUSG00000050088', u'ENSMUSG00000037242', u'ENSMUSG00000004637', u'ENSMUSG00000020817', u'ENSMUSG00000027663', u'ENSMUSG00000030849', u'ENSMUSG00000068220', u'ENSMUSG00000030847', u'ENSMUSG00000030846', u'ENSMUSG00000034958', u'ENSMUSG00000020755', u'ENSMUSG00000021408', u'ENSMUSG00000024044', u'ENSMUSG00000030204', u'ENSMUSG00000031887', u'ENSMUSG00000045502', u'ENSMUSG00000006445', u'ENSMUSG00000042350', u'ENSMUSG00000027016', u'ENSMUSG00000080268', u'ENSMUSG00000041837', u'ENSMUSG00000078566', u'ENSMUSG00000002307', u'ENSMUSG00000038058', u'ENSMUSG00000020108', u'ENSMUSG00000054676', u'ENSMUSG00000022763', u'ENSMUSG00000019851', u'ENSMUSG00000019850', u'ENSMUSG00000024290', u'ENSMUSG00000036986', u'ENSMUSG00000026942', u'ENSMUSG00000018209', u'ENSMUSG00000002870', u'ENSMUSG00000021886', 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u'ENSMUSG00000092035', u'ENSMUSG00000020205', u'ENSMUSG00000059921', u'ENSMUSG00000059920', u'ENSMUSG00000029027', u'ENSMUSG00000067787', u'ENSMUSG00000024826', u'ENSMUSG00000025024', u'ENSMUSG00000023915', u'ENSMUSG00000028549', u'ENSMUSG00000030417', u'ENSMUSG00000041801', u'ENSMUSG00000027804', u'ENSMUSG00000044340', u'ENSMUSG00000024500', u'ENSMUSG00000057530', u'ENSMUSG00000030774', u'ENSMUSG00000041241', u'ENSMUSG00000020484', u'ENSMUSG00000030898', u'ENSMUSG00000035104', u'ENSMUSG00000020077', u'ENSMUSG00000019428', u'ENSMUSG00000048756', u'ENSMUSG00000035109', u'ENSMUSG00000032580', u'ENSMUSG00000027937', u'ENSMUSG00000021453', u'ENSMUSG00000047496', u'ENSMUSG00000062210', u'ENSMUSG00000030557', u'ENSMUSG00000026285', u'ENSMUSG00000026288', u'ENSMUSG00000021127', u'ENSMUSG00000070814', u'ENSMUSG00000032076', u'ENSMUSG00000020650', u'ENSMUSG00000020653', u'ENSMUSG00000023034', u'ENSMUSG00000040435', u'ENSMUSG00000078652', u'ENSMUSG00000041028', u'ENSMUSG00000032194', u'ENSMUSG00000004535', u'ENSMUSG00000033352', u'ENSMUSG00000031536', u'ENSMUSG00000059866', u'ENSMUSG00000032515', u'ENSMUSG00000022043', u'ENSMUSG00000030400', u'ENSMUSG00000021910', u'ENSMUSG00000010911', u'ENSMUSG00000002580', u'ENSMUSG00000041112', u'ENSMUSG00000017716', u'ENSMUSG00000043991', u'ENSMUSG00000022500', u'ENSMUSG00000058325', u'ENSMUSG00000029863', u'ENSMUSG00000010608', u'ENSMUSG00000002688', u'ENSMUSG00000037752', u'ENSMUSG00000053436', u'ENSMUSG00000026767', u'ENSMUSG00000078578', u'ENSMUSG00000025060', u'ENSMUSG00000030744', u'ENSMUSG00000037032', u'ENSMUSG00000054252', u'ENSMUSG00000052139', u'ENSMUSG00000042675', u'ENSMUSG00000018819']), pop_n=13836, p_sm_bonferroni=1.0, is_obsolete=False, GO='GO:0006915', name='apoptotic process', pop_count=458, alt_ids=['GO:0006917', 'GO:0008632'], level=5, depth=5, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000040084', u'ENSMUSG00000070034', u'ENSMUSG00000003873', u'ENSMUSG00000027469', u'ENSMUSG00000036986', u'ENSMUSG00000040483', u'ENSMUSG00000059552', u'ENSMUSG00000002870', u'ENSMUSG00000018899', u'ENSMUSG00000037725', u'ENSMUSG00000030641', u'ENSMUSG00000035683', u'ENSMUSG00000032508', u'ENSMUSG00000035293', u'ENSMUSG00000019942', u'ENSMUSG00000025507', u'ENSMUSG00000028282', u'ENSMUSG00000027379', u'ENSMUSG00000022074', u'ENSMUSG00000057789', u'ENSMUSG00000028211', u'ENSMUSG00000055612', u'ENSMUSG00000029521', u'ENSMUSG00000041801', u'ENSMUSG00000006445', u'ENSMUSG00000040734', u'ENSMUSG00000004446', u'ENSMUSG00000019979', u'ENSMUSG00000025647', u'ENSMUSG00000002083', u'ENSMUSG00000005413', u'ENSMUSG00000024521', u'ENSMUSG00000017716', u'ENSMUSG00000027490', u'ENSMUSG00000030609', u'ENSMUSG00000002307', u'ENSMUSG00000000037', u'ENSMUSG00000045932', u'ENSMUSG00000020108', u'ENSMUSG00000046607']), symbols=u'Aen Apaf1 Bak1 Bax Bbc3 Bid Birc5 Bub1 Bub1b Casp8ap2 Cdca7 Cdk1 Chek2 Ckap2 Daxx Ddias Ddit4 E2f1 Epha2 G2e3 Hmox1 Hrk Ifit2 Irf1 Mcm2 Melk Myd88 Phlda3 Pidd1 Pmaip1 Pml Ppp1r13l Scml2 Shisa5 Sp110 Tnfrsf10b Tpx2 Trp53 Trp53inp1 Xaf1', symbol_set=set([u'Daxx', u'Hmox1', u'Tnfrsf10b', u'Irf1', u'Mcm2', u'Hrk', u'Sp110', u'Pmaip1', u'Chek2', u'Phlda3', u'Tpx2', u'Bub1b', u'Bid', u'G2e3', u'Epha2', u'Bak1', u'Shisa5', u'Apaf1', 'Ddias', u'Bub1', u'E2f1', u'Trp53', u'Xaf1', u'Bax', 'Pidd1', u'Scml2', u'Ckap2', u'Bbc3', u'Aen', u'Ppp1r13l', u'Ddit4', u'Melk', u'Casp8ap2', u'Ifit2', u'Cdk1', u'Trp53inp1', u'Pml', u'Myd88', u'Birc5', u'Cdca7']), geneids='ENSMUSG00000040084 ENSMUSG00000070034 ENSMUSG00000003873 ENSMUSG00000027469 ENSMUSG00000036986 ENSMUSG00000004446 ENSMUSG00000028282 ENSMUSG00000059552 ENSMUSG00000002870 ENSMUSG00000029521 ENSMUSG00000037725 ENSMUSG00000030641 ENSMUSG00000032508 ENSMUSG00000030609 ENSMUSG00000035293 ENSMUSG00000019942 ENSMUSG00000025507 ENSMUSG00000040483 ENSMUSG00000027379 ENSMUSG00000022074 ENSMUSG00000057789 ENSMUSG00000028211 ENSMUSG00000055612 ENSMUSG00000018899 ENSMUSG00000035683 ENSMUSG00000041801 ENSMUSG00000006445 ENSMUSG00000040734 ENSMUSG00000019979 ENSMUSG00000025647 ENSMUSG00000002083 ENSMUSG00000005413 ENSMUSG00000024521 ENSMUSG00000017716 ENSMUSG00000027490 ENSMUSG00000002307 ENSMUSG00000000037 ENSMUSG00000045932 ENSMUSG00000020108 ENSMUSG00000046607', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=78, D1='BC', GO_name='apoptotic process'), Nt(p_uncorrected=1.0613331792342115e-06, study_count=5, study_n=624, namespace='biological_process', p_fdr_bh=0.00016408427549568916, study_items=set([u'ENSMUSG00000026622', u'ENSMUSG00000027699', u'ENSMUSG00000002055', u'ENSMUSG00000023015', u'ENSMUSG00000027331']), NS='BP', pop_items=set([u'ENSMUSG00000027699', u'ENSMUSG00000002055', u'ENSMUSG00000023015', u'ENSMUSG00000005871', u'ENSMUSG00000027331', u'ENSMUSG00000026622']), pop_n=13836, p_sm_bonferroni=0.016080258998577537, is_obsolete=False, GO='GO:0051988', name='regulation of attachment of spindle microtubules to kinetochore', pop_count=6, alt_ids=[], level=5, depth=6, enrichment='e', Cluster='Transient Increase', geneid_set=set([u'ENSMUSG00000026622', u'ENSMUSG00000027699', u'ENSMUSG00000002055', u'ENSMUSG00000023015', u'ENSMUSG00000027331']), symbols=u'Ect2 Knstrn Nek2 Racgap1 Spag5', symbol_set=set([u'Racgap1', 'Knstrn', u'Spag5', u'Nek2', u'Ect2']), geneids='ENSMUSG00000026622 ENSMUSG00000027699 ENSMUSG00000002055 ENSMUSG00000023015 ENSMUSG00000027331', format_txt=0, hdr_idx=0, is_hdrgo=False, is_usrgo=True, hdr1usr01='', dcnt=9, D1='A', GO_name='regulation of attachment of spindle microtubules to kinetochore'), ]

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6568595debe66e5c9b1fc61422da41e8ed04ccf7

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py

Python

cases/admin.py

johngriebel/APDIncidentReports

491b91bcc7eef9a32bda05ad3236b14748ba3b50

[ "MIT" ]

null

cases/admin.py

johngriebel/APDIncidentReports

491b91bcc7eef9a32bda05ad3236b14748ba3b50

[ "MIT" ]

16

2019-05-23T03:25:01.000Z

2022-02-10T08:54:24.000Z

cases/admin.py

johngriebel/APDIncidentReports

491b91bcc7eef9a32bda05ad3236b14748ba3b50

[ "MIT" ]

null

from django.contrib import admin from .models import Officer, Offense admin.site.register(Officer) admin.site.register(Offense)

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658c5b917bf76484e27afd2f1d60730aa95388f9

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py

Python

rosbots/src/bag_records/actionlib_records.py

aivian/robots

6827886916e36432ce1d806f0a78edef6c9270d9

[ "MIT" ]

null

rosbots/src/bag_records/actionlib_records.py

aivian/robots

6827886916e36432ce1d806f0a78edef6c9270d9

[ "MIT" ]

null

rosbots/src/bag_records/actionlib_records.py

aivian/robots

6827886916e36432ce1d806f0a78edef6c9270d9

[ "MIT" ]

1

2021-09-24T17:08:30.000Z

import pdb import numpy import geometry.quaternion import bag_records.records import bag_records.std_records import copy class GoalID(bag_records.records.RecordBase): """Record for actionlib_msgs/GoalID types """ def __init__(self, has_msg_time=False): """Constructor Arguments: has_msg_time: optional bool indicating if this record should have a message time. Typically false, but if this is part of a message, then it could have a message stamp Returns: class instance """ super(GoalID, self).__init__(has_msg_time) self._fields = { 'bag_time': [], 'msg_time': [], 'stamp': [], 'id': [], } class GoalStatus(bag_records.records.RecordBase): """Record for actionlib_msgs/GoalStatus types """ def __init__(self, has_msg_time=False): """Constructor Arguments: has_msg_time: optional bool indicating if this record should have a message time. Typically false, but if this is part of a message, then it could have a message stamp Returns: class instance """ super(GoalStatus, self).__init__(has_msg_time) self._fields = { 'bag_time': [], 'msg_time': [], 'goal_id': GoalID(has_msg_time=has_msg_time), 'status': [], 'text': [], } class GoalStatusArray(bag_records.records.RecordBase): """Record for actionlib_msgs/GoalStatus types """ def __init__(self, has_msg_time=True): """Constructor Arguments: has_msg_time: optional bool indicating if this record should have a message time. Typically false, but if this is part of a message, then it could have a message stamp Returns: class instance """ super(GoalStatusArray, self).__init__(has_msg_time) self._fields = { 'bag_time': [], 'msg_time': [], 'status_list': [], } self._array_types = { 'status_list': GoalStatus, }

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65a95659faa88634ba957a369f7dac7c6172942c

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py

Python

scripts/python/catalyst/updatedSCR/load_550C_SCR.py

coelectrolyzer/cats

21f8e6f5f176767ec403ad2738c80a5a71fba959

[ "MIT" ]

1

2022-02-17T16:37:12.000Z

scripts/python/catalyst/updatedSCR/load_550C_SCR.py

coelectrolyzer/cats

21f8e6f5f176767ec403ad2738c80a5a71fba959

[ "MIT" ]

5

2021-10-30T00:06:31.000Z

2022-03-09T13:34:07.000Z

scripts/python/catalyst/updatedSCR/load_550C_SCR.py

coelectrolyzer/cats

21f8e6f5f176767ec403ad2738c80a5a71fba959

[ "MIT" ]

3

2021-05-08T02:26:08.000Z

2022-03-01T22:27:40.000Z

#This file is used to rerun a simulation using newly found parameters. #The purpose is for additional refinement of kinetics. We will reuse this #script for additional optimization passes. import sys sys.path.append('../..') from catalyst.isothermal_monolith_catalysis import * # Create a simulator object and Load a full model from json run = "03" #update this number to reflect changes in runs readfile = 'output/550C_model02.json' #update this name to reflect which model to load writefile = "550C_model"+run+".json" #NOTE: Other output names can remain the same, most important thing is .json file sim = Isothermal_Monolith_Simulator() sim.load_model_full(readfile, reset_param_bounds=True) sim.unfix_all_reactions() sim.fix_reaction("r1") sim.fix_reaction("r2a") sim.fix_reaction("r2b") sim.fix_reaction("r3") sim.fix_reaction("r4a") sim.fix_reaction("r4b") # NOTE: This downward bias helps tremendously with the fits (try at higher temps as well) old_rxns = ["r5f","r5r","r6f","r6r","r13","r14","r15","r18","r19"] new_rxns = ["r16","r17","r20","r21","r22","r23","r24","r25","r26","r27","r28","r29","r30","r31","r32","r33"] oxd_rxns = ["r7","r8","r9"] new_oxd_rxns = ["r10","r11","r12"] cuo_rxns = ["r34","r35","r36"] n2o_rxns = ["r37","r38","r39"] upper = 1+1 lower = 1-0.2 for rxn in old_rxns: sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) #sim.fix_reaction(rxn) upper = 1+1 lower = 1-0.2 for rxn in new_rxns: sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) #sim.fix_reaction(rxn) upper = 1+2 lower = 1-0.2 for rxn in oxd_rxns: #sim.set_reaction_param_bounds(rxn, "A", bounds=(lower_val,upper_val)) sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) #sim.fix_reaction(rxn) upper_val = 1000 lower_val = 0 upper = 1+2 lower = 1-0.2 for rxn in new_oxd_rxns: #sim.set_reaction_param_bounds(rxn, "A", bounds=(lower_val,upper_val)) sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) upper_val = 10000 lower_val = 0 upper = 1+2 lower = 1-0.2 for rxn in cuo_rxns: #sim.set_reaction_param_bounds(rxn, "A", bounds=(lower_val,upper_val)) sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) upper_val = 1000 lower_val = 0 upper = 1+2 lower = 1-0.2 for rxn in n2o_rxns: #sim.set_reaction_param_bounds(rxn, "A", bounds=(lower_val,upper_val)) sim.set_reaction_param_bounds(rxn, "A", bounds=(sim.model.A[rxn].value*lower,sim.model.A[rxn].value*upper)) #Customize the weight factors sim.auto_select_all_weight_factors() #Select specific weight factor windows based on observed data sim.ignore_weight_factor("NH3","Unaged","550C",time_window=(64,120)) sim.ignore_weight_factor("NO","Unaged","550C",time_window=(64,120)) sim.ignore_weight_factor("NO2","Unaged","550C",time_window=(64,120)) sim.ignore_weight_factor("N2O","Unaged","550C",time_window=(64,120)) sim.ignore_weight_factor("NH3","2hr","550C",time_window=(57,81)) sim.ignore_weight_factor("NO","2hr","550C",time_window=(57,81)) sim.ignore_weight_factor("NO2","2hr","550C",time_window=(57,81)) sim.ignore_weight_factor("N2O","2hr","550C",time_window=(57,81)) sim.ignore_weight_factor("NH3","2hr","550C",time_window=(96,101)) sim.ignore_weight_factor("NO","2hr","550C",time_window=(96,101)) sim.ignore_weight_factor("NO2","2hr","550C",time_window=(96,101)) sim.ignore_weight_factor("N2O","2hr","550C",time_window=(96,101)) sim.ignore_weight_factor("NH3","4hr","550C",time_window=(54,87)) sim.ignore_weight_factor("NO","4hr","550C",time_window=(54,87)) sim.ignore_weight_factor("NO2","4hr","550C",time_window=(54,87)) sim.ignore_weight_factor("N2O","4hr","550C",time_window=(54,87)) sim.ignore_weight_factor("NH3","4hr","550C",time_window=(103,109)) sim.ignore_weight_factor("NO","4hr","550C",time_window=(103,109)) sim.ignore_weight_factor("NO2","4hr","550C",time_window=(103,109)) sim.ignore_weight_factor("N2O","4hr","550C",time_window=(103,109)) sim.ignore_weight_factor("NH3","8hr","550C",time_window=(55,82)) sim.ignore_weight_factor("NO","8hr","550C",time_window=(55,82)) sim.ignore_weight_factor("NO2","8hr","550C",time_window=(55,82)) sim.ignore_weight_factor("N2O","8hr","550C",time_window=(55,82)) sim.ignore_weight_factor("NH3","8hr","550C",time_window=(99,110)) sim.ignore_weight_factor("NO","8hr","550C",time_window=(99,110)) sim.ignore_weight_factor("NO2","8hr","550C",time_window=(99,110)) sim.ignore_weight_factor("N2O","8hr","550C",time_window=(99,110)) sim.ignore_weight_factor("NH3","16hr","550C",time_window=(44,64)) sim.ignore_weight_factor("NO","16hr","550C",time_window=(44,64)) sim.ignore_weight_factor("NO2","16hr","550C",time_window=(44,64)) sim.ignore_weight_factor("N2O","16hr","550C",time_window=(44,64)) sim.ignore_weight_factor("NH3","16hr","550C",time_window=(82,94)) sim.ignore_weight_factor("NO","16hr","550C",time_window=(82,94)) sim.ignore_weight_factor("NO2","16hr","550C",time_window=(82,94)) sim.ignore_weight_factor("N2O","16hr","550C",time_window=(82,94)) sim.ignore_weight_factor("NH3","16hr","550C",time_window=(103,120)) sim.ignore_weight_factor("NO","16hr","550C",time_window=(103,120)) sim.ignore_weight_factor("NO2","16hr","550C",time_window=(103,120)) sim.ignore_weight_factor("N2O","16hr","550C",time_window=(103,120)) sim.finalize_auto_scaling() sim.run_solver() sim.print_results_of_breakthrough(["NH3","NO","NO2","N2O","O2","N2","H2O"], "Unaged", "550C", file_name="Unaged_SCR_550C_breakthrough.txt") sim.print_results_of_location(["NH3","NO","NO2","N2O","O2","N2","H2O"], "Unaged", "550C", 0, file_name="Unaged_SCR_550C_bypass.txt") sim.print_results_of_integral_average(["Z1CuOH-NH3","Z2Cu-NH3","Z2Cu-(NH3)2","ZNH4", "Z1CuOH-NH4NO3", "Z2Cu-NH4NO3", "ZH-NH4NO3"], "Unaged", "550C", file_name="Unaged_SCR_550C_average_ads.txt") sim.print_results_of_breakthrough(["NH3","NO","NO2","N2O","O2","N2","H2O"], "2hr", "550C", file_name="2hr_SCR_550C_breakthrough.txt") sim.print_results_of_location(["NH3","NO","NO2","N2O","O2","N2","H2O"], "2hr", "550C", 0, file_name="2hr_SCR_550C_bypass.txt") sim.print_results_of_integral_average(["Z1CuOH-NH3","Z2Cu-NH3","Z2Cu-(NH3)2","ZNH4", "Z1CuOH-NH4NO3", "Z2Cu-NH4NO3", "ZH-NH4NO3"], "2hr", "550C", file_name="2hr_SCR_550C_average_ads.txt") sim.print_results_of_breakthrough(["NH3","NO","NO2","N2O","O2","N2","H2O"], "4hr", "550C", file_name="4hr_SCR_550C_breakthrough.txt") sim.print_results_of_location(["NH3","NO","NO2","N2O","O2","N2","H2O"], "4hr", "550C", 0, file_name="4hr_SCR_550C_bypass.txt") sim.print_results_of_integral_average(["Z1CuOH-NH3","Z2Cu-NH3","Z2Cu-(NH3)2","ZNH4", "Z1CuOH-NH4NO3", "Z2Cu-NH4NO3", "ZH-NH4NO3"], "4hr", "550C", file_name="4hr_SCR_550C_average_ads.txt") sim.print_results_of_breakthrough(["NH3","NO","NO2","N2O","O2","N2","H2O"], "8hr", "550C", file_name="8hr_SCR_550C_breakthrough.txt") sim.print_results_of_location(["NH3","NO","NO2","N2O","O2","N2","H2O"], "8hr", "550C", 0, file_name="8hr_SCR_550C_bypass.txt") sim.print_results_of_integral_average(["Z1CuOH-NH3","Z2Cu-NH3","Z2Cu-(NH3)2","ZNH4", "Z1CuOH-NH4NO3", "Z2Cu-NH4NO3", "ZH-NH4NO3"], "8hr", "550C", file_name="8hr_SCR_550C_average_ads.txt") sim.print_results_of_breakthrough(["NH3","NO","NO2","N2O","O2","N2","H2O"], "16hr", "550C", file_name="16hr_SCR_550C_breakthrough.txt") sim.print_results_of_location(["NH3","NO","NO2","N2O","O2","N2","H2O"], "16hr", "550C", 0, file_name="16hr_SCR_550C_bypass.txt") sim.print_results_of_integral_average(["Z1CuOH-NH3","Z2Cu-NH3","Z2Cu-(NH3)2","ZNH4", "Z1CuOH-NH4NO3", "Z2Cu-NH4NO3", "ZH-NH4NO3"], "16hr", "550C", file_name="16hr_SCR_550C_average_ads.txt") sim.print_kinetic_parameter_info(file_name="550C_opt_params"+run+".txt") sim.save_model_state(file_name=writefile)

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65b176ea89d77bf65618f67dce057538eb611bf1

3,114

py

Python

data_sources/virus_sample.py

DEIB-GECO/virusurf_downloader

b4151260b80ebecfbd62da29ec90af287bfa1737

[ "Apache-2.0" ]

3

2021-04-14T08:20:04.000Z

2021-07-07T19:44:38.000Z

data_sources/virus_sample.py

DEIB-GECO/virusurf_downloader

b4151260b80ebecfbd62da29ec90af287bfa1737

[ "Apache-2.0" ]

1

2021-08-23T20:51:08.000Z

data_sources/virus_sample.py

DEIB-GECO/virusurf_downloader

b4151260b80ebecfbd62da29ec90af287bfa1737

[ "Apache-2.0" ]

2

2021-03-25T17:50:34.000Z

2021-10-10T14:52:32.000Z

from typing import Tuple, Callable, Generator, Optional class VirusSample: def __init__(self): pass def internal_id(self): """ An id used internally by this program when needed to log some errors. Choose whatever form and type you like. This id is not going to be written in the output data and possibly it will be printed only on the console in order to trace errors. """ raise NotImplementedError def primary_accession_number(self): raise NotImplementedError def alternative_accession_number(self): raise NotImplementedError def strain(self): raise NotImplementedError def is_reference(self): raise NotImplementedError def is_complete(self): raise NotImplementedError def nucleotide_sequence(self): raise NotImplementedError def strand(self): raise NotImplementedError def length(self): raise NotImplementedError def gc_percent(self): raise NotImplementedError def n_percent(self): raise NotImplementedError def lineage(self): raise NotImplementedError def clade(self): raise NotImplementedError def sequencing_technology(self): raise NotImplementedError def assembly_method(self): raise NotImplementedError def coverage(self): raise NotImplementedError def collection_date(self): raise NotImplementedError def isolation_source(self): raise NotImplementedError def province__region__country__geo_group(self) -> Tuple[Optional[str], Optional[str], Optional[str], Optional[str]]: raise NotImplementedError def submission_date(self): raise NotImplementedError def originating_lab(self) -> Optional[str]: raise NotImplementedError def sequencing_lab(self) -> Optional[str]: raise NotImplementedError def host_taxon_name(self) -> Optional[str]: raise NotImplementedError def host_taxon_id(self) -> Optional[int]: raise NotImplementedError def gender(self) -> Optional[str]: raise NotImplementedError def age(self) -> Optional[int]: raise NotImplementedError def database_source(self) -> str: raise NotImplementedError def bioproject_id(self): raise NotImplementedError def nucleotide_variants_and_effects(self, aligner: Callable) -> Generator[Tuple, None, None]: raise NotImplementedError def annotations_and_amino_acid_variants(self, reference_virus_sample) -> Generator[Tuple, None, None]: raise NotImplementedError def on_before_multiprocessing(self): raise NotImplementedError def nucleotide_var_aligner(self): raise NotImplementedError # class DoNotImportSample(RollbackTransactionAndRaise): # def __init__(self, sample_name_or_accession_id): # self.internal_name_or_accession_id = sample_name_or_accession_id # super().__init__(f'Request to abort the import of sample with accession id {sample_name_or_accession_id}')

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65d4748ff0c4c06a2b00b2659499456efba84a78

38

py

Python

testing/tests/001-main/005-unittests/003-other/__init__.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

216

2015-01-05T12:48:10.000Z

2022-03-08T00:12:23.000Z

testing/tests/001-main/005-unittests/003-other/__init__.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

55

2015-02-28T12:10:26.000Z

2020-11-18T17:45:16.000Z

testing/tests/001-main/005-unittests/003-other/__init__.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

34

2015-05-02T15:15:10.000Z

2020-06-15T19:20:37.000Z

# @dependency 001-main/000-install.py

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02d8aa3e091d4479bee921bbc2565193c6a65785

44

py

Python

python/testData/codeInsight/mlcompletion/prev2calls/assignmentVisitorOnePrevCall.py

Sajaki/intellij-community

6748af2c40567839d11fd652ec77ba263c074aad

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/codeInsight/mlcompletion/prev2calls/assignmentVisitorOnePrevCall.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

2

2022-02-19T09:45:05.000Z

2022-02-27T20:32:55.000Z

python/testData/codeInsight/mlcompletion/prev2calls/assignmentVisitorOnePrevCall.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

1

2020-03-10T02:53:51.000Z

import numpy as np a = np.arange(42) <caret>

14.666667

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0

1

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1

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5

02e42aba7c5c8b3f434d13a4eebe91c0bebb3705

81

py

Python

src/exceptions.py

clausia/tetromiq

1d43e57066f78b12ac0d1f19bb16512243e091f3

[ "MIT" ]

1

2021-09-30T06:08:27.000Z

src/exceptions.py

clausia/tetromiq

1d43e57066f78b12ac0d1f19bb16512243e091f3

[ "MIT" ]

30

2021-09-25T21:28:51.000Z

2021-10-03T11:34:04.000Z

src/exceptions.py

clausia/tetromiq

1d43e57066f78b12ac0d1f19bb16512243e091f3

[ "MIT" ]

1

2022-02-27T09:38:27.000Z

class BottomReached(Exception): pass class TopReached(Exception): pass

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02f1f2ee4082952f20b4934f132996a916d25bae

227

py

Python

src/python/pants/backend/experimental/scala/debug_goals/register.py

yoav-orca/pants

995448e9add343975844c7a43d5d64618fc4e4d9

[ "Apache-2.0" ]

1,806

2015-01-05T07:31:00.000Z

2022-03-31T11:35:41.000Z

src/python/pants/backend/experimental/scala/debug_goals/register.py

yoav-orca/pants

995448e9add343975844c7a43d5d64618fc4e4d9

[ "Apache-2.0" ]

9,565

2015-01-02T19:01:59.000Z

2022-03-31T23:25:16.000Z

src/python/pants/backend/experimental/scala/debug_goals/register.py

ryanking/pants

e45b00d2eb467b599966bca262405a5d74d27bdd

[ "Apache-2.0" ]

443

2015-01-06T20:17:57.000Z

2022-03-31T05:28:17.000Z

# Copyright 2021 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from pants.backend.scala.goals import debug_goals def rules(): return debug_goals.rules()

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null

0

1

0

1

0

5

f308d3869bd0de3b8ca74a39048579c60f59bc52

545

py

Python

main/routes/pages.py

rahulworld/vap_tool

01fa3bf96fd4824eed35f7d8f135df3d38ae642b

[ "MIT" ]

null

main/routes/pages.py

rahulworld/vap_tool

01fa3bf96fd4824eed35f7d8f135df3d38ae642b

[ "MIT" ]

null

main/routes/pages.py

rahulworld/vap_tool

01fa3bf96fd4824eed35f7d8f135df3d38ae642b

[ "MIT" ]

null

from flask import render_template, Blueprint, request blueprint = Blueprint('pages', __name__) ################ #### routes #### ################ @blueprint.route('/') def home(): return render_template('pages/home.html') @blueprint.route('/analysis') def analysis(): return render_template('pages/analysis.html') @blueprint.route('/prediction') def prediction(): return render_template('pages/prediction.html') @blueprint.route('/visualisation') def visualisation(): return render_template('pages/visualisation.html')

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1

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1

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1

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5

f30cfba925cd4aa1cfea991f650ef749faaa46cc

74

py

Python

castjeeves/sqltables/metadata/__init__.py

dkauf42/bayota

104ba91746231be10419390a9d7ed8f2593a21bc

[ "BSD-3-Clause" ]

1

2021-07-23T18:09:55.000Z

castjeeves/sqltables/metadata/__init__.py

dkauf42/bayota

104ba91746231be10419390a9d7ed8f2593a21bc

[ "BSD-3-Clause" ]

null

castjeeves/sqltables/metadata/__init__.py

dkauf42/bayota

104ba91746231be10419390a9d7ed8f2593a21bc

[ "BSD-3-Clause" ]

null

"""Metadata tables from the CBPO model""" from .Metadata import Metadata

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null

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1

0

1

0

1

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5

f3228314189ffc1727089bbb28b36399f552df6b

80

py

Python

morpheus/analysis/tools/__init__.py

kajdreef/spidertools

78a5095582b0bc1fe05a81de5c742fe994de5aa4

[ "MIT" ]

null

morpheus/analysis/tools/__init__.py

kajdreef/spidertools

78a5095582b0bc1fe05a81de5c742fe994de5aa4

[ "MIT" ]

null

morpheus/analysis/tools/__init__.py

kajdreef/spidertools

78a5095582b0bc1fe05a81de5c742fe994de5aa4

[ "MIT" ]

null

from .methodsignature import MethodParserRunner from .tacoco import TacocoRunner

40

47

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8.875

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0

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null

0

1

0

1

0

1

0

5

b8413101343f7af0cc46932665d445defcad237b

2,015

py

Python

projects/urls.py

kasrasamareh454/beekeeper

8e8719a9a46f0e8aaae35a2027f69a252a5371f1

[ "BSD-3-Clause" ]

23

2017-07-31T14:29:46.000Z

2019-02-12T02:47:12.000Z

projects/urls.py

kasrasamareh454/beekeeper

8e8719a9a46f0e8aaae35a2027f69a252a5371f1

[ "BSD-3-Clause" ]

9

2017-08-09T05:49:11.000Z

2019-03-19T18:01:59.000Z

projects/urls.py

kasrasamareh454/beekeeper

8e8719a9a46f0e8aaae35a2027f69a252a5371f1

[ "BSD-3-Clause" ]

12

2017-08-08T01:31:22.000Z

2018-09-04T09:17:53.000Z

from django.conf import settings from django.conf.urls import url, include from django.contrib import admin from projects import views as projects urlpatterns = [ url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)$', projects.project, name='project'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/shield$', projects.project_shield, name='project-shield'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})$', projects.change, name='change'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/status$', projects.change_status, name='change-status'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/build/(?P<build_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})$', projects.build, name='build'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/build/(?P<build_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/status$', projects.build_status, name='build-status'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/build/(?P<build_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/code$', projects.build_code, name='build-code'), url(r'^(?P<owner>[-\w]+)/(?P<repo_name>[-\w]+)/change/(?P<change_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/build/(?P<build_pk>[-\da-fA-F]{8}-[-\da-fA-F]{4}-4[-\da-fA-F]{3}-[-\da-fA-F]{4}-[-\da-fA-F]{12})/task/', include('%s.task_urls' % settings.BEEKEEPER_BUILD_APP)) ]

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0

null

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1

0

1

0

1

null

0

5

b86bbbbc640bc68deefdda3dca244bd7ed764302

90

py

Python

src/selfpub/inp/__init__.py

groboclown/py-book-selfpub

42060d8bca7c7d281801fe6836f238f41df872e3

[ "Apache-2.0" ]

null

src/selfpub/inp/__init__.py

groboclown/py-book-selfpub

42060d8bca7c7d281801fe6836f238f41df872e3

[ "Apache-2.0" ]

null

src/selfpub/inp/__init__.py

groboclown/py-book-selfpub

42060d8bca7c7d281801fe6836f238f41df872e3

[ "Apache-2.0" ]

null

from .inpf import InputFile from .odt import ODTInputFile from .cleaner import Cleaner

12.857143

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12

90

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90

6

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1

0

null

0

1

0

1

0

1

0

5

b87e49c98d6a93f030af331eb627403f5162e161

43

py

Python

ainnovation_dcim/ticket/__init__.py

ltxwanzl/ainnovation_dcim

b065489e2aa69729c0fd5142cf75d8caa7788b31

[ "Apache-2.0" ]

null

ainnovation_dcim/ticket/__init__.py

ltxwanzl/ainnovation_dcim

b065489e2aa69729c0fd5142cf75d8caa7788b31

[ "Apache-2.0" ]

null

ainnovation_dcim/ticket/__init__.py

ltxwanzl/ainnovation_dcim

b065489e2aa69729c0fd5142cf75d8caa7788b31

[ "Apache-2.0" ]

null

# default_app_config = 'apps.TicketConfig'

21.5

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1

0

1

0

null

0

1

0

5

b215ef4ffec922ae245e59730cc2e2545bb651c5

194

py

Python

examples/testproject/testapp/sampledata.py

jpetto/django-eadred

5b3ffdfd8eccb55c53908198eda1598cb4461ba1

[ "BSD-3-Clause" ]

1

2015-07-07T12:37:07.000Z

examples/testproject/testapp/sampledata.py

jpetto/django-eadred

5b3ffdfd8eccb55c53908198eda1598cb4461ba1

[ "BSD-3-Clause" ]

2

2015-04-15T14:13:10.000Z

2015-11-12T01:22:43.000Z

examples/testproject/testapp/sampledata.py

jpetto/django-eadred

5b3ffdfd8eccb55c53908198eda1598cb4461ba1

[ "BSD-3-Clause" ]

2

2016-10-08T19:54:43.000Z

2018-11-22T02:49:11.000Z

DEFAULT = False called = DEFAULT def reset_app(): global called called = DEFAULT def generate_sampledata(options): global called assert called == DEFAULT called = True

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0

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false

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null

1

0

1

0

null

0

1

0

5

b23971bb07d7851b4c3c2ef6debdd18a33b3c372

51,771

py

Python

unittests/test_optimization.py

YangyangFu/MPCPy

c9980cbfe7b5ea21b003c2c0bab800099dccf3f1

[ "BSD-3-Clause-LBNL" ]

null

unittests/test_optimization.py

YangyangFu/MPCPy

c9980cbfe7b5ea21b003c2c0bab800099dccf3f1

[ "BSD-3-Clause-LBNL" ]

null

unittests/test_optimization.py

YangyangFu/MPCPy

c9980cbfe7b5ea21b003c2c0bab800099dccf3f1

[ "BSD-3-Clause-LBNL" ]

1

2021-11-20T03:23:13.000Z

# -*- coding: utf-8 -*- """ This module contains the classes for testing the optimization module of mpcpy. """ import unittest import os import pandas as pd from matplotlib import pyplot as plt from mpcpy import models from mpcpy import optimization from mpcpy import exodata from mpcpy import utility from mpcpy import variables from mpcpy import units import numpy as np from testing import TestCaseMPCPy #%% class OptimizeSimpleFromJModelica(TestCaseMPCPy): '''Test simple model optimization functions. ''' def setUp(self): self.start_time = '1/1/2017'; self.final_time = '1/2/2017'; # Set .mo path self.mopath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'Simple.mo'); # Gather inputs self.start_time_exo = '1/1/2017'; self.final_time_exo = '1/10/2017'; control_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'SimpleRC_Input.csv'); control_variable_map = {'q_flow_csv' : ('q_flow', units.W)}; self.controls = exodata.ControlFromCSV(control_csv_filepath, control_variable_map); self.controls.collect_data(self.start_time_exo, self.final_time_exo); # Set measurements self.measurements = {}; self.measurements['T_db'] = {'Sample' : variables.Static('T_db_sample', 1800, units.s)}; self.measurements['q_flow'] = {'Sample' : variables.Static('q_flow_sample', 1800, units.s)}; # Gather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'GTE', units.K), \ 'T_db_max' : ('T_db', 'LTE', units.K)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); def tearDown(self): del self.start_time del self.final_time del self.mopath del self.constraints del self.controls del self.measurements def test_optimize(self): '''Test the optimization of a model. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem with default res_control_step opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_measurements.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_control_default.csv'); # Simulate model with optimal control model.simulate(self.start_time, self.final_time) # Check references df_test = model.display_measurements('Simulated'); self.check_df(df_test, 'simulate_optimal_default.csv'); # Solve optimization problem with user-defined res_control_step opt_problem.optimize(self.start_time, self.final_time, res_control_step = 60.0); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_measurements.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_control_userdefined.csv'); # Simulate model with optimal control model.simulate(self.start_time, self.final_time) # Check references df_test = model.display_measurements('Simulated'); self.check_df(df_test, 'simulate_optimal_userdefined.csv'); # Get opt input object and create dataframe time = np.linspace(0,3600,3601); df_test = pd.DataFrame(); data = []; opt_input_traj = opt_problem.opt_input[1] names = opt_problem.opt_input[0] # Create data for t in time: data.append(opt_input_traj(t)) # Create index timedelta = pd.to_timedelta(time, 's'); index = pd.to_datetime(self.start_time) + timedelta; df_test = pd.DataFrame(data=data, index=index, columns=names) df_test.index.name = 'Time' # Check references self.check_df(df_test, 'optimize_opt_input.csv'); def test_set_problem_type(self): '''Test the dynamic setting of a problem type. ''' modelpath = 'Simple.RC'; # Instantiate model parameter_data = {}; parameter_data['heatCapacitor.C'] = {}; parameter_data['heatCapacitor.C']['Free'] = variables.Static('C_free', False, units.boolean); parameter_data['heatCapacitor.C']['Value'] = variables.Static('C_value', 3e6, units.boolean); model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data, \ parameter_data = parameter_data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energy.csv'); # Set new problem type opt_problem.set_problem_type(optimization.EnergyCostMin); # Gather prices price_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Prices.csv'); price_variable_map = {'energy[cents/kWh]' : ('pi_e', units.cents_kWh)}; price = exodata.PriceFromCSV(price_csv_filepath, price_variable_map); price.collect_data(self.start_time, self.final_time); # Check price data price_data = price.get_base_data() self.check_df(price_data, 'optimize_energycost_price_data.csv'); opt_problem.optimize(self.start_time, self.final_time, price_data = price.data) # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energycost.csv'); def test_slack_constraints(self): '''Test the slack constraints are created properly. ''' # Regather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints_Slack.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'sGTE', units.K, 1000), \ 'T_db_max' : ('T_db', 'sLTE', units.K, 500)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Check slack variables slack_vars_test = opt_problem.get_slack_variables() self.check_json(slack_vars_test, 'slack_variables.txt') def test_optimize_slack_constraints_energy(self): '''Test the energy optimization of a model with slack constraints. ''' # Regather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints_Slack.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'sGTE', units.K, 500000), \ 'T_db_max' : ('T_db', 'sLTE', units.K, 500000)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); modelpath = 'Simple.RC'; # Instantiate model parameter_data = {}; parameter_data['heatCapacitor.C'] = {}; parameter_data['heatCapacitor.C']['Free'] = variables.Static('C_free', False, units.boolean); parameter_data['heatCapacitor.C']['Value'] = variables.Static('C_value', 3e6, units.boolean); model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data, parameter_data = parameter_data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem with default res_control_step opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energy_slack_constraints.csv'); def test_optimize_slack_constraints_energycost(self): '''Test the energy cost optimization of a model with slack constraints. ''' # Regather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints_Slack.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'sGTE', units.K, 500000*500), \ 'T_db_max' : ('T_db', 'sLTE', units.K, 100*500)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); modelpath = 'Simple.RC'; # Gather prices price_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Prices.csv'); price_variable_map = {'energy[cents/kWh]' : ('pi_e', units.cents_kWh)}; price = exodata.PriceFromCSV(price_csv_filepath, price_variable_map); price.collect_data(self.start_time, self.final_time); # Instantiate model parameter_data = {}; parameter_data['heatCapacitor.C'] = {}; parameter_data['heatCapacitor.C']['Free'] = variables.Static('C_free', False, units.boolean); parameter_data['heatCapacitor.C']['Value'] = variables.Static('C_value', 3e6, units.boolean); model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data, parameter_data = parameter_data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyCostMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem with default res_control_step opt_problem.optimize(self.start_time, self.final_time, price_data = price.data) # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energycost_slack_constraints.csv'); def test_optimize_subpackage(self): '''Test the optimization of a model within a subpackage. ''' modelpath = 'Simple.SubPackage.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_subpackage.csv'); def test_get_options(self): '''Test the getting of optimization options. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Get options opt_options = opt_problem.get_optimization_options(); # Check references json_test = opt_options; self.check_json(json_test, 'initial_options.txt'); def test_set_options(self): '''Test the setting of optimization options. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Get initial options opt_options = opt_problem.get_optimization_options(); # Set new options opt_options['IPOPT_options']['max_iter'] = 2; opt_options['n_e'] = 2; opt_options['result_mode'] = 'mesh_points'; opt_problem.set_optimization_options(opt_options) # Get new options opt_options = opt_problem.get_optimization_options(); # Check references json_test = opt_options; self.check_json(json_test, 'new_options.txt'); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_new_options.csv'); def test_set_options_error(self): '''Test the setting of optimization options cannot occur with auto options. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); for key in ['external_data', 'init_traj', 'nominal_traj']: # Get initial options opt_options = opt_problem.get_optimization_options(); # Set new options and check KeyError raised with self.assertRaises(KeyError): opt_options[key] = 2; opt_problem.set_optimization_options(opt_options); def test_get_statistics(self): '''Test the getting of optimization result statistics. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Get statistics opt_statistics = opt_problem.get_optimization_statistics(); # Check references (except execution time) df_test = pd.DataFrame(columns=['message', 'iterations', 'objective'], index = [0]) df_test.loc[0] = opt_statistics[:-1] self.check_df(df_test, 'statistics.csv', timeseries=False); def test_set_parameters(self): '''Test the dynamic setting of parameters. ''' modelpath = 'Simple.RC'; # Instantiate model parameter_data = {'heatCapacitor.C' : {'Free' : variables.Static('C_free', False, units.boolean), \ 'Value' : variables.Static('C_new', 1e5, units.J_K)}, \ 'To' : {'Free' : variables.Static('To_free', False, units.boolean), \ 'Value' : variables.Static('To', 24, units.degC)}}; model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data, parameter_data = parameter_data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_set_parameters_1.csv'); # Set new parameters of model parameter_data['heatCapacitor.C']['Value'] = variables.Static('C_new', 1e7, units.J_K); parameter_data['To']['Value'] = variables.Static('To', 22, units.degC); opt_problem.Model.parameter_data = parameter_data; # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_set_parameters_2.csv'); def test_initial_constraint(self): '''Test the optimization of a model with an initial constraint. ''' modelpath = 'Simple.RC_nostart'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Add initial constraint self.constraints.data['T_db']['Initial'] = {'Value':variables.Static('T_db_initial', 21, units.degC), 'Weight':None}; # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_initial_constraint.csv'); opt_statistics = opt_problem.get_optimization_statistics(); # Check references (except execution time) df_test = pd.DataFrame(columns=['message', 'iterations', 'objective'], index = [0]) df_test.loc[0] = opt_statistics[:-1] self.check_df(df_test, 'statistics_initial_constraint.csv', timeseries=False); def test_continue_error(self): '''Test a ValueError is raised if try to use the "continue" keyword. ''' modelpath = 'Simple.RC_nostart'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Check ValueError raised with self.assertRaises(ValueError): opt_problem.optimize('continue', self.final_time); def test_optimize_long(self): '''Test update of control data with opt horizon longer than initial. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem opt_problem.optimize('1/10/2017 00:00:00', '1/11/2017 02:00:00'); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_long_measurements.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_long_control.csv'); def test_update_constraints(self): '''Test the updating of constraints in the optimization. ''' modelpath = 'Simple.RC'; # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem with default constraints opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_measurements.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_control_default.csv'); # Update constraints and control data self.constraints.collect_data('1/11/2017', '1/12/2017'); opt_problem.constraint_data = self.constraints.data; self.controls.collect_data('1/11/2017', '1/12/2017'); # Solve optimization problem with updated constraints opt_problem.optimize('1/11/2017', '1/12/2017'); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_measurements_updated_constraints.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_control_default_updated_constraints.csv'); # Check new constraint key raises error self.constraints.data['New_Constraint'] = opt_problem.constraint_data['q_flow'] opt_problem.constraint_data = self.constraints.data with self.assertRaises(ValueError): opt_problem.optimize('1/11/2017', '1/12/2017'); def test_extra_control_data(self): '''Test the optimization of a model where there is extra control data. ''' modelpath = 'Simple.RC'; # Gather inputs with extra data start_time_exo = '1/1/2017'; final_time_exo = '1/10/2017'; control_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'SimpleRC_Input.csv'); control_variable_map = {'q_flow_csv' : ('q_flow', units.W), 'extra_input' : ('not_input', units.W)}; self.controls = exodata.ControlFromCSV(control_csv_filepath, control_variable_map); self.controls.collect_data(start_time_exo, final_time_exo); # Instantiate model model = models.Modelica(models.JModelica, \ models.RMSE, \ self.measurements, \ moinfo = (self.mopath, modelpath, {}), \ control_data = self.controls.data); # Instantiate optimization problem opt_problem = optimization.Optimization(model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data); # Solve optimization problem with default res_control_step opt_problem.optimize(self.start_time, self.final_time); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_measurements.csv'); df_test = model.control_data['q_flow'].display_data().to_frame(); df_test.index.name = 'Time' self.check_df(df_test, 'optimize_control_default.csv'); class EnergyPlusDemand(TestCaseMPCPy): '''Test simple model optimization functions. ''' def setUp(self): self.start_time = '1/2/2017'; self.final_time = '1/3/2017'; # Set .mo path mopath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'Simple.mo'); # Gather inputs self.start_time_exo = '1/1/2017'; self.final_time_exo = '1/10/2017'; control_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'SimpleRC_Input.csv'); control_variable_map = {'q_flow_csv' : ('q_flow', units.W)}; controls = exodata.ControlFromCSV(control_csv_filepath, control_variable_map); controls.collect_data(self.start_time_exo, self.final_time_exo); # Set measurements measurements = {}; measurements['T_db'] = {'Sample' : variables.Static('T_db_sample', 1800, units.s)}; measurements['q_flow'] = {'Sample' : variables.Static('q_flow_sample', 1800, units.s)}; measurements['Tamb.y'] = {'Sample' : variables.Static('T_amb_sample', 1800, units.s)}; # Instantiate model modelpath = 'Simple.RC'; parameter_data = {}; parameter_data['heatCapacitor.C'] = {}; parameter_data['heatCapacitor.C']['Free'] = variables.Static('C_free', False, units.boolean); parameter_data['heatCapacitor.C']['Value'] = variables.Static('C_value', 1e6, units.boolean); self.model = models.Modelica(models.JModelica, \ models.RMSE, \ measurements, \ moinfo = (mopath, modelpath, {}), \ control_data = controls.data, \ parameter_data = parameter_data); def test_energyplusdemandcostmin(self): '''Test energy plus demand cost minimization problem. ''' plot = False # Gather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'GTE', units.K), \ 'T_db_max' : ('T_db', 'LTE', units.K)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); # Instantiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyPlusDemandCostMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data, demand_periods=4); # Gather prices price_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Prices.csv'); price_variable_map = {'energy' : ('pi_e', units.dol_J), 'demand' : ('pi_d', units.dol_W), 'peak_power' : ('P_est', units.W), 'demand_coincident' : ('pi_d_c', units.dol_W), 'peak_power_coincident' : ('P_est_c', units.W)}; price = exodata.PriceFromCSV(price_csv_filepath, price_variable_map); price.collect_data(self.start_time, self.final_time); opt_problem.optimize(self.start_time, self.final_time, price_data = price.data) # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energyplusdemandcost.csv'); # Plot if wanted if plot: fig,ax = plt.subplots(2,1,sharex=True) ax[0].plot(df_test['T_db']) ax[0].plot(df_test['Tamb.y']) ax[1].plot(df_test['q_flow']) ax[0].plot([df_test.index[0], df_test.index[-1]], [293, 293]) ax[0].plot([df_test.index[0], df_test.index[-1]], [298, 298]) plt.show() def test_energyplusdemandcostmin_excessdemandperiods(self): '''Test energy plus demand cost minimization problem with excess demand periods. ''' plot = False # Gather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'GTE', units.K), \ 'T_db_max' : ('T_db', 'LTE', units.K)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); # Instantiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyPlusDemandCostMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data, demand_periods=7); # Gather prices price_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Prices.csv'); price_variable_map = {'energy' : ('pi_e', units.dol_J), 'demand' : ('pi_d', units.dol_W), 'peak_power' : ('P_est', units.W), 'demand_coincident' : ('pi_d_c', units.dol_W), 'peak_power_coincident' : ('P_est_c', units.W)}; price = exodata.PriceFromCSV(price_csv_filepath, price_variable_map); price.collect_data(self.start_time, self.final_time); opt_problem.optimize(self.start_time, self.final_time, price_data = price.data) # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energyplusdemandcost_excessdemandperiods.csv'); # Plot if wanted if plot: fig,ax = plt.subplots(2,1,sharex=True) ax[0].plot(df_test['T_db']) ax[0].plot(df_test['Tamb.y']) ax[1].plot(df_test['q_flow']) ax[0].plot([df_test.index[0], df_test.index[-1]], [293, 293]) ax[0].plot([df_test.index[0], df_test.index[-1]], [298, 298]) plt.show() def test_energyplusdemandcostmin_slack(self): '''Test energy plus demand cost minimization problem with slack constraints. ''' plot = False # Gather constraints constraint_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Constraints.csv'); constraint_variable_map = {'q_flow_min' : ('q_flow', 'GTE', units.W), \ 'T_db_min' : ('T_db', 'sGTE', units.K, 10), \ 'T_db_max' : ('T_db', 'sLTE', units.K, 10)}; self.constraints = exodata.ConstraintFromCSV(constraint_csv_filepath, constraint_variable_map); self.constraints.collect_data(self.start_time_exo, self.final_time_exo); # Instantiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyPlusDemandCostMin, \ optimization.JModelica, \ 'q_flow', \ constraint_data = self.constraints.data, demand_periods=4); # Gather prices price_csv_filepath = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'SimpleRC_Prices.csv'); price_variable_map = {'energy' : ('pi_e', units.dol_J), 'demand' : ('pi_d', units.dol_W), 'peak_power' : ('P_est', units.W), 'demand_coincident' : ('pi_d_c', units.dol_W), 'peak_power_coincident' : ('P_est_c', units.W)}; price = exodata.PriceFromCSV(price_csv_filepath, price_variable_map); price.collect_data(self.start_time, self.final_time); opt_problem.optimize(self.start_time, self.final_time, price_data = price.data) # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'optimize_energyplusdemandcost_slack_constraints.csv'); # Plot if wanted if plot: fig,ax = plt.subplots(2,1,sharex=True) ax[0].plot(df_test['T_db']) ax[0].plot(df_test['Tamb.y']) ax[1].plot(df_test['q_flow']) ax[0].plot([df_test.index[0], df_test.index[-1]], [293, 293]) ax[0].plot([df_test.index[0], df_test.index[-1]], [298, 298]) plt.show() #%% Temperature tests class OptimizeAdvancedFromJModelica(TestCaseMPCPy): '''Tests for the optimization of a model using JModelica. ''' def setUp(self): ## Setup model mopath = os.path.join(self.get_unittest_path(), 'resources', 'model', 'LBNL71T_MPC.mo'); modelpath = 'LBNL71T_MPC.MPC'; libraries = os.environ.get('MODELICAPATH'); estimate_method = models.JModelica; validation_method = models.RMSE; zone_names = ['wes', 'hal', 'eas']; # Measurements measurements = {}; measurements['wesTdb'] = {'Sample' : variables.Static('wesTdb_sample', 1800, units.s)}; measurements['halTdb'] = {'Sample' : variables.Static('halTdb_sample', 1800, units.s)}; measurements['easTdb'] = {'Sample' : variables.Static('easTdb_sample', 1800, units.s)}; measurements['wesPhvac'] = {'Sample' : variables.Static('easTdb_sample', 1800, units.s)}; measurements['halPhvac'] = {'Sample' : variables.Static('easTdb_sample', 1800, units.s)}; measurements['easPhvac'] = {'Sample' : variables.Static('easTdb_sample', 1800, units.s)}; measurements['Ptot'] = {'Sample' : variables.Static('easTdb_sample', 1800, units.s)}; ## Exodata # Exogenous collection time start_time_exodata = '1/1/2015'; final_time_exodata = '1/30/2015'; # Optimization time self.start_time_optimization = '1/2/2015'; self.final_time_optimization = '1/3/2015'; # Weather weather_path = os.path.join(self.get_unittest_path(), 'resources', 'weather', 'USA_IL_Chicago-OHare.Intl.AP.725300_TMY3.epw'); weather = exodata.WeatherFromEPW(weather_path); weather.collect_data(start_time_exodata, final_time_exodata); # Internal internal_path = os.path.join(self.get_unittest_path(), 'resources', 'internal', 'sampleCSV.csv'); internal_variable_map = {'intRad_wes' : ('wes', 'intRad', units.W_m2), \ 'intCon_wes' : ('wes', 'intCon', units.W_m2), \ 'intLat_wes' : ('wes', 'intLat', units.W_m2), \ 'intRad_hal' : ('hal', 'intRad', units.W_m2), \ 'intCon_hal' : ('hal', 'intCon', units.W_m2), \ 'intLat_hal' : ('hal', 'intLat', units.W_m2), \ 'intRad_eas' : ('eas', 'intRad', units.W_m2), \ 'intCon_eas' : ('eas', 'intCon', units.W_m2), \ 'intLat_eas' : ('eas', 'intLat', units.W_m2)}; internal = exodata.InternalFromCSV(internal_path, internal_variable_map, tz_name = weather.tz_name); internal.collect_data(start_time_exodata, final_time_exodata); # Control (as initialization) control_path = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'ControlCSV.csv'); control_variable_map = {'conHeat_wes' : ('conHeat_wes', units.unit1), \ 'conHeat_hal' : ('conHeat_hal', units.unit1), \ 'conHeat_eas' : ('conHeat_eas', units.unit1)}; control = exodata.ControlFromCSV(control_path, control_variable_map, tz_name = weather.tz_name); control.collect_data(start_time_exodata, final_time_exodata); # Parameters parameters_path = os.path.join(self.get_unittest_path(), 'outputs', 'model_parameters.txt'); parameters = exodata.ParameterFromCSV(parameters_path); parameters.collect_data(); # Constraints constraints_path = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'sampleConstraintCSV_Constant.csv'); constraints_variable_map = {'wesTdb_min' : ('wesTdb', 'GTE', units.degC), \ 'wesTdb_max' : ('wesTdb', 'LTE', units.degC), \ 'easTdb_min' : ('easTdb', 'GTE', units.degC), \ 'easTdb_max' : ('easTdb', 'LTE', units.degC), \ 'halTdb_min' : ('halTdb', 'GTE', units.degC), \ 'halTdb_max' : ('halTdb', 'LTE', units.degC), \ 'der_wesTdb_min' : ('wesTdb', 'dGTE', units.K), \ 'der_wesTdb_max' : ('wesTdb', 'dLTE', units.K), \ 'der_easTdb_min' : ('easTdb', 'dGTE', units.K), \ 'der_easTdb_max' : ('easTdb', 'dLTE', units.K), \ 'der_halTdb_min' : ('halTdb', 'dGTE', units.K), \ 'der_halTdb_max' : ('halTdb', 'dLTE', units.K), \ 'conHeat_wes_min' : ('conHeat_wes', 'GTE', units.unit1), \ 'conHeat_wes_max' : ('conHeat_wes', 'LTE', units.unit1), \ 'conHeat_hal_min' : ('conHeat_hal', 'GTE', units.unit1), \ 'conHeat_hal_max' : ('conHeat_hal', 'LTE', units.unit1), \ 'conHeat_eas_min' : ('conHeat_eas', 'GTE', units.unit1), \ 'conHeat_eas_max' : ('conHeat_eas', 'LTE', units.unit1)}; self.constraints = exodata.ConstraintFromCSV(constraints_path, constraints_variable_map, tz_name = weather.tz_name); self.constraints.collect_data(start_time_exodata, final_time_exodata); self.constraints.data['wesTdb']['Cyclic'] = {'Value':variables.Static('wesTdb_cyclic', 1, units.boolean_integer), 'Weight':None}; self.constraints.data['easTdb']['Cyclic'] = {'Value':variables.Static('easTdb_cyclic', 1, units.boolean_integer), 'Weight':None}; self.constraints.data['halTdb']['Cyclic'] = {'Value':variables.Static('halTdb_cyclic', 1, units.boolean_integer), 'Weight':None}; # Prices prices_path = os.path.join(self.get_unittest_path(), 'resources', 'optimization', 'PriceCSV.csv'); price_variable_map = {'pi_e' : ('pi_e', units.dol_J)}; self.prices = exodata.PriceFromCSV(prices_path, price_variable_map, tz_name = weather.tz_name); self.prices.collect_data(start_time_exodata, final_time_exodata); ## Parameters parameters.data['lat'] = {}; parameters.data['lat']['Value'] = weather.lat; ## Instantiate model self.model = models.Modelica(estimate_method, \ validation_method, \ measurements, \ moinfo = (mopath, modelpath, libraries), \ zone_names = zone_names, \ weather_data = weather.data, \ internal_data = internal.data, \ control_data = control.data, \ parameter_data = parameters.data, \ tz_name = weather.tz_name); def tearDown(self): del self.model del self.constraints del self.prices def test_energymin(self): '''Test energy minimization of a model.''' plt.close('all'); # Instanatiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyMin, \ optimization.JModelica, \ 'Ptot', \ constraint_data = self.constraints.data) # Optimize opt_problem.optimize(self.start_time_optimization, self.final_time_optimization); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'energymin.csv'); def test_energycostmin(self): '''Test energy cost minimization of a model.''' plt.close('all'); # Instanatiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyCostMin, \ optimization.JModelica, \ 'Ptot', \ constraint_data = self.constraints.data) # Optimize opt_problem.optimize(self.start_time_optimization, self.final_time_optimization, price_data = self.prices.data); # Check references df_test = opt_problem.display_measurements('Simulated'); self.check_df(df_test, 'energycostmin.csv'); def test_energycostmin_save_parameter_input_data(self): '''Test energy cost minimization of a model.''' plt.close('all'); # Set save parameter input data in model self.model._save_parameter_input_data = True # Instanatiate optimization problem opt_problem = optimization.Optimization(self.model, \ optimization.EnergyCostMin, \ optimization.JModelica, \ 'Ptot', \ constraint_data = self.constraints.data) # Optimize opt_problem.optimize(self.start_time_optimization, self.final_time_optimization, price_data = self.prices.data); # Check references df_test = pd.read_csv('mpcpy_optimization_inputs.csv', index_col='Time'); df_test.index = pd.to_datetime(df_test.index).tz_localize('UTC') self.check_df(df_test, 'mpcpy_optimization_inputs.csv'); df_test = pd.read_csv('mpcpy_simulation_inputs_optimization_initial.csv', index_col='Time'); df_test.index = pd.to_datetime(df_test.index).tz_localize('UTC') self.check_df(df_test, 'mpcpy_simulation_inputs_optimization_initial.csv'); df_test = pd.read_csv('mpcpy_optimization_parameters.csv', index_col='parameter'); self.check_df(df_test, 'mpcpy_optimization_parameters.csv', timeseries=False); df_test = pd.read_csv('mpcpy_simulation_parameters_optimization_initial.csv', index_col='parameter'); self.check_df(df_test, 'mpcpy_simulation_parameters_optimization_initial.csv', timeseries=False); if __name__ == '__main__': unittest.main()

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relevanceai/operations_new/__init__.py

RelevanceAI/RelevanceAI

a0542f35153d9c842f3d2cd0955d6b07f6dfc07b

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2022-03-23T03:45:30.000Z

relevanceai/operations_new/__init__.py

RelevanceAI/RelevanceAI

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2022-03-30T08:11:49.000Z

relevanceai/operations_new/__init__.py

RelevanceAI/RelevanceAI

a0542f35153d9c842f3d2cd0955d6b07f6dfc07b

[ "Apache-2.0" ]

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2022-01-04T01:48:30.000Z

2022-02-11T03:19:32.000Z

from relevanceai.operations_new.ops import Operations

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epab/core/__init__.py

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epab/core/__init__.py

etcher-be/epab

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[ "MIT" ]

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2018-08-22T04:25:56.000Z

2019-10-17T05:10:21.000Z

epab/core/__init__.py

etcher-be/epab

5226d3a36580f8cc50cf5dcac426adb1350a2c9b

[ "MIT" ]

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2018-02-25T05:53:18.000Z

# coding=utf-8 """ Core functions of EPAB """ from epab.core.context import CTX

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src/interpreter/functions/time.py

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[ "MIT" ]

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src/interpreter/functions/time.py

BowlingPizzaBall/b-star

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[ "MIT" ]

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src/interpreter/functions/time.py

BowlingPizzaBall/b-star

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[ "MIT" ]

null

from typing import List def time(block: List, codebase): return None # return math.round(time.time() + (float(block[1]) * 3600), # int(block[2])) # miniDOCs: arg1 is hour offset, arg2 is decimals to round to

30.125

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null

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1

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1

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5

b28319af00599708ba60d200c326ffd037ef2614

13,044

py

Python

doajtest/unit/test_query_filters.py

gaybro8777/doaj

27d9d98ce4f496ae52acbaba6ee8e42c84cf1a58

[ "Apache-2.0" ]

47

2015-04-24T13:13:39.000Z

2022-03-06T03:22:42.000Z

doajtest/unit/test_query_filters.py

gaybro8777/doaj

27d9d98ce4f496ae52acbaba6ee8e42c84cf1a58

[ "Apache-2.0" ]

1,215

2015-01-02T14:29:38.000Z

2022-03-28T14:19:13.000Z

doajtest/unit/test_query_filters.py

gaybro8777/doaj

27d9d98ce4f496ae52acbaba6ee8e42c84cf1a58

[ "Apache-2.0" ]

14

2015-11-27T13:01:23.000Z

2021-05-21T07:57:23.000Z

from copy import deepcopy from doajtest.fixtures import AccountFixtureFactory, EditorGroupFixtureFactory, ApplicationFixtureFactory from doajtest.helpers import DoajTestCase from portality import models from portality import constants from portality.lib import query_filters from portality.bll.services.query import Query class TestQueryFilters(DoajTestCase): def setUp(self): self.q = Query() assert self.q.as_dict() == {"query": {"match_all": {}}}, self.q.as_dict() super(TestQueryFilters, self).setUp() def tearDown(self): super(TestQueryFilters, self).tearDown() def test_01_only_in_doaj(self): newq = query_filters.only_in_doaj(self.q) assert newq.as_dict() == {'query': {'filtered': {'filter': {'bool': {'must': [{'term': {'admin.in_doaj': True}}]}}}}}, newq.as_dict() def test_02_owner(self): acc = models.Account(**AccountFixtureFactory.make_publisher_source()) self._make_and_push_test_context(acc=acc) newq = query_filters.owner(self.q) assert newq.as_dict() == {'query': {'filtered': {'filter': {'bool': {'must': [{'term': {'admin.owner.exact': acc.id}}]}}}}}, newq.as_dict() def test_03_update_request(self): old_update_request_show_oldest = self.app_test.config.get('UPDATE_REQUEST_SHOW_OLDEST') self.app_test.config['UPDATE_REQUEST_SHOW_OLDEST'] = '2018-05-03' newq = query_filters.update_request(self.q) assert newq.as_dict() == {'query': {'filtered': {'filter': {'bool': {'must': [{"range" : {"created_date" : {"gte" : '2018-05-03'}}}, {"exists" : {"field" : "admin.current_journal"}}]}}}}}, newq.as_dict() self.app_test.config['UPDATE_REQUEST_SHOW_OLDEST'] = old_update_request_show_oldest def test_04_associate(self): acc = models.Account(**AccountFixtureFactory.make_assed1_source()) self._make_and_push_test_context(acc=acc) newq = query_filters.associate(self.q) assert newq.as_dict() == {'query': {'filtered': {'filter': {'bool': {'must': [{'term': {'admin.editor.exact': acc.id}}]}}}}}, newq.as_dict() def test_05_editor(self): eg = EditorGroupFixtureFactory.setup_editor_group_with_editors() self._make_and_push_test_context(acc=models.Account.pull('eddie')) newq = query_filters.editor(self.q) assert newq.as_dict() == {'query': {'filtered': {'filter': {'bool': {'must': [{'terms': {'admin.editor_group.exact': [eg.name]}}]}}}}}, newq.as_dict() def test_06_public_result_filter(self): res = { "hits": { "hits": [ { "_type": "article", "_source": { "admin": { "seal": False, "publisher_record_id" : "some_identifier", "upload_id" : "zyxwvutsrqpo_upload_id"}, "bibjson": {}}}, { "_type": "article", "_source": { "admin": { "seal": False, "publisher_record_id" : "some_identifier", "upload_id" : "zyxwvutsrqpo_upload_id"}, "bibjson": {}}}, { "_type": "article", "_source": { "admin": { "seal": False, "publisher_record_id" : "some_identifier", "upload_id" : "zyxwvutsrqpo_upload_id"}, "bibjson": {}}} ], "total": 3 } } newres = query_filters.public_result_filter(res) assert newres == { "hits": { "hits": [ { "_type": "article", "_source": { "admin": { "seal": False }, "bibjson": {}}}, { "_type": "article", "_source": { "admin": { "seal": False }, "bibjson": {}}}, { "_type": "article", "_source": { "admin": { "seal": False }, "bibjson": {}}} ], "total": 3 } }, newres def test_07_public_result_filter_unpacked(self): res = { "admin": { "seal": False, "publisher_record_id" : "some_identifier", "upload_id" : "zyxwvutsrqpo_upload_id"}, "bibjson": {}} newres = query_filters.public_result_filter(res, unpacked=True) assert newres == { "admin": { "seal": False }, "bibjson": {}}, newres def test_08_publisher_result_filter(self): apsrc_admin = ApplicationFixtureFactory.make_update_request_source()['admin'] # Not all of these properties are applicable to applications, but these test objects are not applications: # they are made-up admin sections designed solely to test whether the filter lets the right keys through. # We just use applications as a base to construct them. apsrc_admin['ticked'] = True apsrc_admin['in_doaj'] = True apsrc_admin['related_applications'] = [1,2,3] apsrc_admin['current_application'] = 'abcde' allowed = ["ticked", "seal", "in_doaj", "related_applications", "current_application", "current_journal", "application_status"] forbidden = ['notes', 'contact', 'editor_group', 'editor', 'related_journal'] res = { "hits": { "hits": [ { "_type": "article", "_source": { "admin": deepcopy(apsrc_admin), "bibjson": {}}}, { "_type": "article", "_source": { "admin": deepcopy(apsrc_admin), "bibjson": {}}}, { "_type": "article", "_source": { "admin": deepcopy(apsrc_admin), "bibjson": {}}} ], "total": 3 } } newres = query_filters.publisher_result_filter(res) for n, r in enumerate(newres['hits']['hits']): for allowed_k in allowed: assert allowed_k in r['_source']['admin'], \ '{} key not found in result {}, but it is allowed and should have been left intact by the filter'.format(allowed_k, n) for forbidden_k in forbidden: assert forbidden_k not in r['_source']['admin'], \ '{} key was found in result {}, but it is forbidden and should have been stripped out by the filter'.format(forbidden_k, n) def test_09_publisher_result_filter_unpacked(self): apsrc_admin = ApplicationFixtureFactory.make_update_request_source()['admin'] # Not all of these properties are applicable to applications, but these test objects are not applications: # they are made-up admin sections designed solely to test whether the filter lets the right keys through. # We just use applications as a base to construct them. apsrc_admin['ticked'] = True apsrc_admin['in_doaj'] = True apsrc_admin['related_applications'] = [1,2,3] apsrc_admin['current_application'] = 'abcde' allowed = ["ticked", "seal", "in_doaj", "related_applications", "current_application", "current_journal", "application_status"] forbidden = ['notes', 'contact', 'editor_group', 'editor', 'related_journal'] res = { "admin": deepcopy(apsrc_admin), "bibjson": {}} newres = query_filters.publisher_result_filter(res, unpacked=True) for allowed_k in allowed: assert allowed_k in newres['admin'], \ '{} key not found in result {}, but it is allowed and should have been left intact by the filter'.format(allowed_k, newres) for forbidden_k in forbidden: assert forbidden_k not in newres['admin'], \ '{} key was found in result {}, but it is forbidden and should have been stripped out by the filter'.format(forbidden_k, newres) def test_10_prune_author_emails(self): """Check we don't let publisher emails through the query endpoint""" res = { "hits": { "hits": [ {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author", 'email': 'janet@example.com'}]}}}, {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author", 'email': 'janet@example.com'}, {'name': "Jimmy Author", 'email': 'jimmy@example.com'}]}}}, {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}}}, ], "total": 3 } } newres = query_filters.prune_author_emails(res) assert newres == { "hits": { "hits": [ {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}]}}}, {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}}}, {"_type": "article", "_source": {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}}}, ], "total": 3 } }, newres def test_11_prune_author_emails_unpacked(self): """Check we don't let publisher emails through the query endpoint""" res1 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author", 'email': 'janet@example.com'}]}} res2 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author", 'email': 'janet@example.com'}, {'name': "Jimmy Author", 'email': 'jimmy@example.com'}]}} res3 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}} newres1 = query_filters.prune_author_emails(res1, unpacked=True) expres1 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}]}} assert newres1 == expres1, newres1 newres2 = query_filters.prune_author_emails(res2, unpacked=True) expres2 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}} assert newres2 == expres2, newres2 newres3 = query_filters.prune_author_emails(res3, unpacked=True) expres3 = {"admin": {"seal": False, "publisher_record_id": "some_identifier", "upload_id": "zyxwvutsrqpo_upload_id"}, "bibjson": {"author": [{'name': "Janet Author"}, {'name': "Jimmy Author"}]}} assert newres3 == expres3, newres3 def test_12_private_source(self): newq = query_filters.private_source(self.q) fields = ["admin.application_status", "admin.ticked", "admin.seal", "last_updated", "created_date", "id", "bibjson"] assert len(newq.as_dict()["_source"]["include"]) == len(fields), newq.as_dict() assert sorted(newq.as_dict()["_source"]["include"]) == sorted(fields), newq.as_dict() def test_13_public_source(self): newq = query_filters.public_source(self.q) fields = ["admin.ticked", "admin.seal", "last_updated", "created_date", "id", "bibjson"] assert len(newq.as_dict()["_source"]["include"]) == len(fields), newq.as_dict() assert sorted(newq.as_dict()["_source"]["include"]) == sorted(fields), newq.as_dict()

60.110599

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1

0

1

0

null

0

5

b284a2b3017da9fc0172a1b27fed69c812ba7b12

245

py

Python

hello/goodbye/views.py

AwelEshetu/docker_django

6cf53805b725bd8fae7f5c946cf802d4c7a77fbc

[ "MIT" ]

null

hello/goodbye/views.py

AwelEshetu/docker_django

6cf53805b725bd8fae7f5c946cf802d4c7a77fbc

[ "MIT" ]

null

hello/goodbye/views.py

AwelEshetu/docker_django

6cf53805b725bd8fae7f5c946cf802d4c7a77fbc

[ "MIT" ]

null

from django.shortcuts import render # Create your views here. def index(request): return render(request, "goodbye/index.html") def goodbye(request, name): return render(request, "goodbye/goodbye.html", {"name": name.capitalize()})

18.846154

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null

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1

0

1

0

5

b2a08b12940f7a390ea2493e569345f514f8c032

117

py

Python

app/v1/user_page_views/admin.py

FormatMemory/django_api_backend

690439ad612598c86c22a837bc0f2e5bea74f2d2

[ "MIT" ]

null

app/v1/user_page_views/admin.py

FormatMemory/django_api_backend

690439ad612598c86c22a837bc0f2e5bea74f2d2

[ "MIT" ]

8

2021-03-18T23:26:33.000Z

2022-03-11T23:44:22.000Z

app/v1/user_page_views/admin.py

FormatMemory/django_api_backend

690439ad612598c86c22a837bc0f2e5bea74f2d2

[ "MIT" ]

null

from django.contrib import admin from .models.user_page_view import UserPageView admin.site.register(UserPageView)

19.5

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0.846154

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0

1

0

1

0

5

b2ad89c4fe442620581b2dee9db9b5ea6ce553f5

3,915

py

Python

randomDailySample.py

fairscape/hctsa-analysis-replication-code

16148637cad2d360065ecb8815f4962e6848213b

[ "MIT" ]

null

randomDailySample.py

fairscape/hctsa-analysis-replication-code

16148637cad2d360065ecb8815f4962e6848213b

[ "MIT" ]

null

randomDailySample.py

fairscape/hctsa-analysis-replication-code

16148637cad2d360065ecb8815f4962e6848213b

[ "MIT" ]

1

2021-08-23T08:30:45.000Z

from minio import Minio import pickle from io import BytesIO minioClient = Minio('minio:9000', access_key='access_key', secret_key='secret_key', secure=False) with open("all_ids.pkl", "rb") as fp: both = pickle.load(fp) import pandas as pd import warnings warnings.filterwarnings("ignore") import numpy as np for patient in both[:1]: print(patient) try: file = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_HR.csv' file2 = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_HR3.csv' df = pd.read_csv(minioClient.get_object('prevent', file)) df3 = pd.read_csv(minioClient.get_object('prevent', file2)).drop(['time'],axis = 1) hr = pd.concat([df.reset_index(drop=True), df3], axis=1) hr = hr.add_prefix('HR_') hr = hr.rename(columns={'HR_time': 'time'}) except: print('Patient ' + str(patient) + ' failed to load HR') continue try: file = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_SPO2-%.csv' file2 = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_SPO2-%3.csv' df = pd.read_csv(minioClient.get_object('prevent', file)) df3 = pd.read_csv(minioClient.get_object('prevent', file2)).drop(['time'],axis = 1) sp = pd.concat([df.reset_index(drop=True), df3], axis=1) sp = sp.add_prefix('SP_') sp = sp.rename(columns={'SP_time': 'time'}) except: print('Patient ' + str(patient) + ' failed to load SP') continue full = pd.merge(hr, sp, on=['time']) full = full[(full['HR_Observations'] == 300) & (full['SP_Observations'] == 300)] full['day'] = np.ceil(full['time'] / 60 / 60 / 24) full = full.groupby('day').apply(lambda df: df.sample(1)) full['id'] = patient total = full.copy() import time for patient in both[1:]: start = time.time() if str(patient) == '7191': continue print(patient) try: file = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_HR.csv' file2 = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_HR3.csv' df = pd.read_csv(minioClient.get_object('prevent', file)) df3 = pd.read_csv(minioClient.get_object('prevent', file2)).drop(['time'],axis = 1) hr = pd.concat([df.reset_index(drop=True), df3], axis=1) hr = hr.add_prefix('HR_') hr = hr.rename(columns={'HR_time': 'time'}) except: print('Patient ' + str(patient) + ' failed to load HR') continue try: file = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_SPO2-%.csv' file2 = 'Non-PreVent-hctsa/UVA_' + str(patient) + '/UVA_' + str(patient) + '_SPO2-%3.csv' df = pd.read_csv(minioClient.get_object('prevent', file)) df3 = pd.read_csv(minioClient.get_object('prevent', file2)).drop(['time'],axis = 1) sp = pd.concat([df.reset_index(drop=True), df3], axis=1) sp = sp.add_prefix('SP_') sp = sp.rename(columns={'SP_time': 'time'}) except: print('Patient ' + str(patient) + ' failed to load SP') continue full = pd.merge(hr, sp, on=['time']) full = full[(full['HR_Observations'] == 300) & (full['SP_Observations'] == 300)] full['day'] = np.ceil(full['time'] / 60 / 60 / 24) full = full.groupby('day').apply(lambda df: df.sample(1)) full['id'] = patient total = pd.concat([total,full]) print('Took: ' + str(time.time() - start)) csv_bytes = total.to_csv(index = False).encode('utf-8') csv_buffer = BytesIO(csv_bytes) minioClient.put_object('breakfast', 'randomDailySample.csv', data=csv_buffer, length=len(csv_bytes), content_type='application/csv')

40.360825

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null

0

1

0

null

0

5

a24b06add70c9b4c6c3107d76744ec673da3b772

334

py

Python

01_class/base_model.py

wuyueCreator/python-test

6072ac9264a257c89925469238c14fff3bda5630

[ "MIT" ]

1

2019-03-25T03:44:54.000Z

01_class/base_model.py

wuyueCreator/python-test

6072ac9264a257c89925469238c14fff3bda5630

[ "MIT" ]

null

01_class/base_model.py

wuyueCreator/python-test

6072ac9264a257c89925469238c14fff3bda5630

[ "MIT" ]

null

from abc import abstractmethod class BaseModel: _subclass_basename = '' @property def name(self): return self._subclass_basename[:-3] @abstractmethod def init_subclass_basename(self): pass def __call__(self, *args, **kwargs): self.init_subclass_basename() return self.name

18.555556

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0

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1

0

null

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1

0

1

0

1

0

5

a263222de8e3be973a60e2a1618af38601698945

199

py

Python

terracommon/notifications/managers.py

Terralego/terra-back

32779117ee3613b9d2e476cf445f94dbdb0f114f

[ "MIT" ]

4

2019-05-07T12:34:35.000Z

2019-11-14T10:52:11.000Z

terracommon/notifications/managers.py

Terralego/terra-back

32779117ee3613b9d2e476cf445f94dbdb0f114f

[ "MIT" ]

16

2019-08-14T11:09:39.000Z

2022-02-10T07:55:31.000Z

terracommon/notifications/managers.py

Terralego/terra-back

32779117ee3613b9d2e476cf445f94dbdb0f114f

[ "MIT" ]

1

2019-04-17T09:03:02.000Z

from django.db import models class NotificationManager(models.Manager): def read_all(self): return self.update(read=True) def unread(self): return self.filter(read=False)

18.090909

42

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26

199

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null

0

1

0

1

0

5

a2787362db571a3152f0168d67039a63299675e0

80

py

Python

src/scripts/extract routes/extract_routes.py

oSoc17/rideaway-backend

f77a58c75d4ce69dbed620c2098654c17d7a37a7

[ "MIT" ]

null

src/scripts/extract routes/extract_routes.py

oSoc17/rideaway-backend

f77a58c75d4ce69dbed620c2098654c17d7a37a7

[ "MIT" ]

19

2017-07-04T14:36:26.000Z

2018-12-04T15:15:33.000Z

src/scripts/extract routes/extract_routes.py

oSoc17/rideaway-backend

f77a58c75d4ce69dbed620c2098654c17d7a37a7

[ "MIT" ]

null

import osm_processor if __name__ == "__main__": osm_processor.process_osm()

20

31

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10

80

5

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null

0

1

0

1

0

5

a2bca28428fabb83d7ed23f91d0aa383a2be8ebd

219

py

Python

synthetic_data/__init__.py

kasra-hosseini/synthetic_data_release

768fe15cae6a033a17390d8dc2152bb75a083ca2

[ "MIT", "BSD-3-Clause" ]

null

synthetic_data/__init__.py

kasra-hosseini/synthetic_data_release

768fe15cae6a033a17390d8dc2152bb75a083ca2

[ "MIT", "BSD-3-Clause" ]

null

synthetic_data/__init__.py

kasra-hosseini/synthetic_data_release

768fe15cae6a033a17390d8dc2152bb75a083ca2

[ "MIT", "BSD-3-Clause" ]

null

__author__ = "Theresa Stadler" __license__ = "BSD" __copyright__ = "2021, Theresa Stadler (EPFL SPRING Lab)" from . import feature_sets from . import generative_models from . import privacy_attacks from . import utils

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py

Python

post_processing/tmp.py

gwpark-git/dynamics_of_networks_and_colloids

0b0a3687533379ec75171ae6b906aeff5bedfbba

[ "MIT" ]

null

post_processing/tmp.py

gwpark-git/dynamics_of_networks_and_colloids

0b0a3687533379ec75171ae6b906aeff5bedfbba

[ "MIT" ]

null

post_processing/tmp.py

gwpark-git/dynamics_of_networks_and_colloids

0b0a3687533379ec75171ae6b906aeff5bedfbba

[ "MIT" ]

null

from numpy import * class test: """ test condition"""

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Python

software/python/simple_pendulum/controllers/sac/__init__.py

alopezrivera/torque_limited_simple_pendulum

2164a41d65c16743ba260a79a04a04cdd72c3903

[ "BSD-3-Clause" ]

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2021-10-16T04:50:34.000Z

2022-03-26T23:54:19.000Z

software/python/simple_pendulum/controllers/sac/__init__.py

alopezrivera/torque_limited_simple_pendulum

2164a41d65c16743ba260a79a04a04cdd72c3903

[ "BSD-3-Clause" ]

17

2021-11-30T22:17:28.000Z

2022-03-21T12:28:45.000Z

software/python/simple_pendulum/controllers/sac/__init__.py

alopezrivera/torque_limited_simple_pendulum

2164a41d65c16743ba260a79a04a04cdd72c3903

[ "BSD-3-Clause" ]

13

2021-10-18T07:45:29.000Z

2022-03-22T12:56:33.000Z

""" Soft Actor Critic (SAC) Control =============================== """

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py

Python

oasislmf/utils/fm.py

lucaspanayiotou/OasisLMF_SQL

619244f6c5b2e1b6483d50ada045fc24e081de42

[ "BSD-3-Clause" ]

null

oasislmf/utils/fm.py

lucaspanayiotou/OasisLMF_SQL

619244f6c5b2e1b6483d50ada045fc24e081de42

[ "BSD-3-Clause" ]

1

2021-03-31T19:01:15.000Z

oasislmf/utils/fm.py

OasisLMF/OasisLMF_SQL

4c0edef7b346cf2a0b3cd0813320d063fa3e8b40

[ "BSD-3-Clause" ]

2

2019-03-21T09:22:34.000Z

2020-01-16T15:09:58.000Z

# -*- coding: utf-8 -*- __all__ = [ 'get_coverage_level_fm_terms', 'get_fm_terms_by_level_as_list', 'get_layer_calcrule_id', 'get_layer_level_fm_terms', 'get_policytc_ids', 'get_sub_layer_calcrule_id', 'get_sub_layer_non_coverage_level_fm_terms', 'unified_canonical_fm_profile_by_level', 'unified_canonical_fm_profile_by_level_and_term_group' ] import io import itertools import json from future.utils import ( viewitems, viewvalues, ) import pandas as pd from .exceptions import OasisException from .metadata import ( OASIS_FM_LEVELS, OED_FM_LEVELS, ) def get_coverage_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed=True): lid = level_fm_items[0]['level_id'] cov_level = OASIS_FM_LEVELS['coverage']['id'] if not oed else OED_FM_LEVELS['site coverage']['id'] if lid != cov_level: raise OasisException('Invalid FM level ID {} for generating coverage level FM terms - expected to be {}'.format(lid, cov_level)) lfmap = level_fm_agg_profile agg_key = tuple(v['field'].lower() for v in viewvalues(lfmap['FMAggKey'])) li = sorted([it for it in viewvalues(level_fm_items)], key=lambda it: tuple(it[k] for k in agg_key)) can_df = pd.merge(canexp_df, canacc_df, left_on='accntnum', right_on='accntnum') def get_can_item(canexp_id, canacc_id, policy_num): return can_df[(can_df['row_id_x'] == canexp_id + 1) & (can_df['row_id_y'] == canacc_id + 1) & (can_df['policynum'] == policy_num)].iloc[0] for it, i in itertools.chain((it, i) for i, (key, group) in enumerate(itertools.groupby(li, key=lambda it: tuple(it[k] for k in agg_key))) for it in group): it['agg_id'] = i + 1 can_item = get_can_item(it['canexp_id'], it['canacc_id'], it['policy_num']) can_item_ded = can_item.get(it['ded_elm']) or 0.0 it['deductible'] = (can_item_ded if can_item_ded >= 1 else it['tiv'] * can_item_ded) or 0.0 can_item_ded_min = can_item.get(it['ded_min_elm']) or 0.0 it['deductible_min'] = (can_item_ded_min if can_item_ded_min >= 1 else it['tiv'] * can_item_ded_min) or 0.0 can_item_ded_max = can_item.get(it['ded_max_elm']) or 0.0 it['deductible_max'] = (can_item_ded_max if can_item_ded_max >= 1 else it['tiv'] * can_item_ded_max) or 0.0 can_item_lim = can_item.get(it['lim_elm']) or 0.0 it['limit'] = (can_item_lim if can_item_lim >= 1 else it['tiv'] * can_item_lim) or 0.0 it['share'] = can_item.get(it['shr_elm']) or 0.0 it['calcrule_id'] = get_sub_layer_calcrule_id(it['deductible'], it['deductible_min'], it['deductible_max'], it['limit']) yield it def get_layer_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed=True): lid = level_fm_items[0]['level_id'] layer_level = OASIS_FM_LEVELS['layer']['id'] if not oed else OED_FM_LEVELS['policy layer']['id'] if lid != layer_level: raise OasisException('Invalid FM level ID {} for generating coverage level FM terms - expected to be {}'.format(lid, layer_level)) lufcp = level_unified_canonical_profile lfmap = level_fm_agg_profile agg_key = tuple(v['field'].lower() for v in viewvalues(lfmap['FMAggKey'])) li = sorted([it for it in viewvalues(level_fm_items)], key=lambda it: tuple(it[k] for k in agg_key)) can_df = pd.merge(canexp_df, canacc_df, left_on='accntnum', right_on='accntnum') def get_can_item(canexp_id, canacc_id, policy_num): return can_df[(can_df['row_id_x'] == canexp_id + 1) & (can_df['row_id_y'] == canacc_id + 1) & (can_df['policynum'] == policy_num)].iloc[0] ded_fld = lufcp[1].get('deductible') or {} ded_elm = ded_fld['ProfileElementName'].lower() if ded_fld else None lim_fld = lufcp[1].get('limit') or {} lim_elm = lim_fld['ProfileElementName'].lower() if lim_fld else None shr_fld = lufcp[1].get('share') or {} shr_elm = shr_fld['ProfileElementName'].lower() if shr_fld else None for it, i in itertools.chain((it, i) for i, (key, group) in enumerate(itertools.groupby(li, key=lambda it: tuple(it[k] for k in agg_key))) for it in group): it['agg_id'] = i + 1 can_item = get_can_item(it['canexp_id'], it['canacc_id'], it['policy_num']) it['ded_elm'] = ded_elm it['deductible'] = can_item.get(ded_elm) or 0.0 it['attachment'] = it['deductible'] it['deductible_min'] = it['deductible_max'] = 0.0 it['lim_elm'] = lim_elm it['limit'] = can_item.get(lim_elm) or 9999999999 it['shr_elm'] = shr_elm it['share'] = can_item.get(shr_elm) or 1.0 it['calcrule_id'] = get_layer_calcrule_id(it['attachment'], it['limit'], it['share']) yield it def get_sub_layer_non_coverage_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed=True): lid = level_fm_items[0]['level_id'] sub_layer_non_coverage_levels = ( range(OASIS_FM_LEVELS['combined']['id'], OASIS_FM_LEVELS['layer']['id']) if not oed else (OED_FM_LEVELS[level]['id'] for level in ['site pd', 'site all', 'cond all', 'policy all']) ) if lid not in sub_layer_non_coverage_levels: raise OasisException('Invalid FM level ID {} for generating sub-layer non-coverage level FM terms - expected to be in the set {}'.format(lid, set(sub_layer_non_coverage_levels))) lufcp = level_unified_canonical_profile lfmap = level_fm_agg_profile agg_key = tuple(v['field'].lower() for v in viewvalues(lfmap['FMAggKey'])) li = sorted([it for it in viewvalues(level_fm_items)], key=lambda it: tuple(it[k] for k in agg_key)) can_df = pd.merge(canexp_df, canacc_df, left_on='accntnum', right_on='accntnum') def get_can_item(canexp_id, canacc_id, policy_num): return can_df[(can_df['row_id_x'] == canexp_id + 1) & (can_df['row_id_y'] == canacc_id + 1) & (can_df['policynum'] == policy_num)].iloc[0] ded_fld = lufcp[1].get('deductible') or {} ded_elm = ded_fld['ProfileElementName'].lower() if ded_fld else None ded_min_fld = lufcp[1].get('deductiblemin') or {} ded_min_elm = ded_min_fld['ProfileElementName'].lower() if ded_min_fld else None ded_max_fld = lufcp[1].get('deductiblemax') or {} ded_max_elm = ded_max_fld['ProfileElementName'].lower() if ded_max_fld else None lim_fld = lufcp[1].get('limit') or {} lim_elm = lim_fld['ProfileElementName'].lower() if lim_fld else None for it, i in itertools.chain((it, i) for i, (key, group) in enumerate(itertools.groupby(li, key=lambda it: tuple(it[k] for k in agg_key))) for it in group): it['agg_id'] = i + 1 can_item = get_can_item(it['canexp_id'], it['canacc_id'], it['policy_num']) it['ded_elm'] = ded_elm if (not ded_fld.get('CoverageTypeID') or it['coverage_type_id'] in (ded_fld['CoverageTypeID'] or [])) else None can_item_ded = can_item.get(it['ded_elm']) or 0.0 it['deductible'] = (can_item_ded if can_item_ded >= 1 else it['tiv'] * can_item_ded) or 0.0 it['ded_min_elm'] = ded_min_elm if (not ded_min_fld.get('CoverageTypeID') or it['coverage_type_id'] in (ded_min_fld['CoverageTypeID'] or [])) else None can_item_ded_min = can_item.get(it['ded_min_elm']) or 0.0 it['deductible_min'] = (can_item_ded_min if can_item_ded_min >= 1 else it['tiv'] * can_item_ded_min) or 0.0 it['ded_max_elm'] = ded_max_elm if (not ded_max_fld.get('CoverageTypeID') or it['coverage_type_id'] in (ded_max_fld['CoverageTypeID'] or [])) else None can_item_ded_max = can_item.get(it['ded_max_elm']) or 0.0 it['deductible_max'] = (can_item_ded_max if can_item_ded_max >= 1 else it['tiv'] * can_item_ded_max) or 0.0 it['lim_elm'] = lim_elm if (not lim_fld.get('CoverageTypeID') or it['coverage_type_id'] in (lim_fld['CoverageTypeID'] or [])) else None can_item_lim = can_item.get(it['lim_elm']) or 0.0 it['limit'] = (can_item_lim if can_item_lim >= 1 else it['tiv'] * can_item_lim) or 0.0 it['calcrule_id'] = get_sub_layer_calcrule_id(it['deductible'], it['deductible_min'], it['deductible_max'], it['limit']) yield it def get_fm_terms_by_level_as_list(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed=True): level_id = level_fm_items[0]['level_id'] cov_level = OASIS_FM_LEVELS['coverage']['id'] if not oed else OED_FM_LEVELS['site coverage']['id'] sub_layer_non_coverage_levels = ( range(OASIS_FM_LEVELS['combined']['id'], OASIS_FM_LEVELS['layer']['id']) if not oed else (OED_FM_LEVELS[level]['id'] for level in ['site pd', 'site all', 'cond all', 'policy all']) ) layer_level = OASIS_FM_LEVELS['layer']['id'] if not oed else OED_FM_LEVELS['policy layer']['id'] if level_id == cov_level: return [it for it in get_coverage_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed)] elif level_id in sub_layer_non_coverage_levels: return [it for it in get_sub_layer_non_coverage_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed)] elif level_id == layer_level: return [it for it in get_layer_level_fm_terms(level_unified_canonical_profile, level_fm_agg_profile, level_fm_items, canexp_df, canacc_df, oed)] def get_policytc_ids(fm_items_df): columns = [ col for col in fm_items_df.columns if col not in ('limit', 'deductible', 'deductible_min', 'deductible_max', 'attachment', 'share', 'calcrule_id',) ] policytc_df = fm_items_df.drop(columns, axis=1).drop_duplicates() for col in policytc_df.columns: policytc_df[col] = policytc_df[col].astype(float) if col != 'calcrule_id' else policytc_df[col].astype(int) policytc_df['index'] = range(1, len(policytc_df) + 1) policytc_ids = { i: { 'limit': policytc_df.iloc[i - 1]['limit'], 'deductible': policytc_df.iloc[i - 1]['deductible'], 'deductible_min': policytc_df.iloc[i - 1]['deductible_min'], 'deductible_max': policytc_df.iloc[i - 1]['deductible_max'], 'attachment': policytc_df.iloc[i - 1]['attachment'], 'share': policytc_df.iloc[i - 1]['share'], 'calcrule_id': int(policytc_df.iloc[i - 1]['calcrule_id']) } for i in policytc_df['index'] } return policytc_ids def get_layer_calcrule_id(att=0, lim=9999999999, shr=1): if att > 0 or lim > 0 or shr > 0: return 2 def get_sub_layer_calcrule_id(ded, ded_min, ded_max, lim, ded_code=0, lim_code=0): if (ded > 0 and ded_code == 0) and (ded_min == ded_max == 0) and (lim > 0 and lim_code == 0): return 1 elif (ded > 0 and ded_code == 2) and (ded_min == ded_max == 0) and (lim > 0 and lim_code == 0): return 4 elif (ded > 0 and ded_code == 1) and (ded_min == ded_max == 0) and (lim > 0 and lim_code == 1): return 5 elif (ded > 0 and ded_code == 2) and (ded_min == ded_max == 0) and (lim == lim_code == 0): return 6 elif (ded == ded_code == 0) and (ded_min == 0 and ded_max > 0) and (lim > 0 and lim_code == 0): return 7 elif (ded == ded_code == 0) and (ded_min > 0 and ded_max == 0) and (lim > 0 and lim_code == 0): return 8 elif (ded == ded_code == 0) and (ded_min == 0 and ded_max > 0) and (lim == lim_code == 0): return 10 elif (ded == ded_code == 0) and (ded_min > 0 and ded_max == 0) and (lim == lim_code == 0): return 11 elif (ded >= 0 and ded_code == 0) and (ded_min == ded_max == 0) and (lim == lim_code == 0): return 12 elif (ded == ded_code == 0) and (ded_min > 0 and ded_max > 0) and (lim == lim_code == 0): return 13 elif (ded == ded_code == 0) and (ded_min == ded_max == 0) and (lim > 0 and lim_code == 0): return 14 elif (ded == ded_code == 0) and (ded_min == ded_max == 0) and (lim > 0 and lim_code == 1): return 15 elif (ded > 0 and ded_code == 1) and (ded_min == ded_max == 0) and (lim == lim_code == 0): return 16 elif (ded > 0 and ded_code == 1) and (ded_min > 0 and ded_max > 0) and (lim == lim_code == 0): return 19 elif (ded > 0 and ded_code in [0, 2]) and (ded_min > 0 and ded_max > 0) and (lim == lim_code == 0): return 21 def unified_canonical_fm_profile_by_level(profiles=[], profile_paths=[]): if not (profiles or profile_paths): raise OasisException('A list of canonical profiles (loc. or acc.) or a list of canonical profiles paths must be provided') if not profiles: for pp in profile_paths: with io.open(pp, 'r', encoding='utf-8') as f: profiles.append(json.load(f)) comb_prof = {k: v for p in profiles for k, v in ((k, v) for k, v in viewitems(p) if 'FMLevel' in v)} return { int(k): {v['ProfileElementName']: v for v in g} for k, g in itertools.groupby(sorted(viewvalues(comb_prof), key=lambda v: v['FMLevel']), key=lambda v: v['FMLevel']) } def unified_canonical_fm_profile_by_level_and_term_group(profiles=[], profile_paths=[]): if not (profiles or profile_paths): raise OasisException('A list of canonical profiles (loc. or acc.) or a list of canonical profiles paths must be provided') comb_prof = unified_canonical_fm_profile_by_level(profiles=profiles, profile_paths=profile_paths) return { k: { _k: {v['FMTermType'].lower(): v for v in g} for _k, g in itertools.groupby(sorted(viewvalues(comb_prof[k]), key=lambda v: v['FMTermGroupID']), key=lambda v: v['FMTermGroupID']) } for k in comb_prof }

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py

Python

cs150/varscope1.py

icterguru/DrLutchClass

4ae75e047d00e36af7fd5019a7d751a44bc7daa8

[ "Apache-2.0" ]

null

cs150/varscope1.py

icterguru/DrLutchClass

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cs150/varscope1.py

icterguru/DrLutchClass

4ae75e047d00e36af7fd5019a7d751a44bc7daa8

[ "Apache-2.0" ]

1

2018-09-20T20:50:08.000Z

def square(a): return a * a print(square(4))

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py

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numpy/typing/tests/data/reveal/ctypeslib.py

AnirudhDagar/numpy

77bc3225e6f4badf83190ec300a0e10e56949644

[ "BSD-3-Clause" ]

5

2021-08-23T06:23:15.000Z

2022-02-05T07:27:30.000Z

numpy/typing/tests/data/reveal/ctypeslib.py

AnirudhDagar/numpy

77bc3225e6f4badf83190ec300a0e10e56949644

[ "BSD-3-Clause" ]

91

2021-05-18T03:32:13.000Z

2022-03-28T03:07:36.000Z

numpy/typing/tests/data/reveal/ctypeslib.py

AnirudhDagar/numpy

77bc3225e6f4badf83190ec300a0e10e56949644

[ "BSD-3-Clause" ]

1

2019-11-05T15:23:08.000Z

import numpy as np reveal_type(np.ctypeslib.c_intp()) # E: {c_intp}

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py

Python

apis/stock_data/config.py

m0thm4n/webapp_template

58e75f7a7c95fdde1772c0b0bc9364f08d71e1a3

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null

apis/stock_data/config.py

m0thm4n/webapp_template

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[ "MIT" ]

null

apis/stock_data/config.py

m0thm4n/webapp_template

58e75f7a7c95fdde1772c0b0bc9364f08d71e1a3

[ "MIT" ]

null

import os api_key = os.getenv("QUANDL_API_KEY")

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py

Python

tests/test_loan_search.py

equadon/invenio-circulation

5133e71119a4d989aaace36e34718b34f2d31fb2

[ "MIT" ]

null

tests/test_loan_search.py

equadon/invenio-circulation

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null

tests/test_loan_search.py

equadon/invenio-circulation

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[ "MIT" ]

null

# -*- coding: utf-8 -*- # # Copyright (C) 2018 CERN. # Copyright (C) 2018 RERO. # # Invenio-Circulation is free software; you can redistribute it and/or modify # it under the terms of the MIT License; see LICENSE file for more details. """Tests for loan search class.""" from invenio_circulation.api import Loan from invenio_circulation.search.api import search_by_patron_item_or_document, \ search_by_patron_pid, search_by_pid def test_search_loans_by_pid(indexed_loans): """Test retrieve loan list belonging to an item.""" loans = list(search_by_pid(item_pid="item_pending_1").scan()) assert len(loans) == 1 loan = Loan.get_record_by_pid(loans[0]["pid"]) assert loan.get("item_pid") == "item_pending_1" def test_search_loans_by_pid_filtering_states(indexed_loans): """Test retrieve loan list belonging to an item filtering states.""" search = search_by_pid(item_pid="item_multiple_pending_on_loan_7", filter_states=["PENDING", "ITEM_ON_LOAN"]) search_result = search.execute() assert search_result.hits.total == 3 def test_search_loans_by_pid_excluding_states(indexed_loans): """Test retrieve loan list belonging to an item excluding states.""" search_result = search_by_pid(item_pid="item_multiple_pending_on_loan_7", exclude_states=["ITEM_ON_LOAN"]).execute() assert search_result.hits.total == 2 def test_search_loans_by_patron_pid(indexed_loans): """Test retrieve loan list belonging to a patron.""" search_result = search_by_patron_pid("1").execute() assert search_result.hits.total == 8 search_result = search_by_patron_pid("2").execute() assert search_result.hits.total == 3 search_result = search_by_patron_pid("3").execute() assert search_result.hits.total == 1 def test_search_loans_by_patron_and_item_or_document(indexed_loans): """Test retrieve loan list by patron and items.""" search_result = search_by_patron_item_or_document( patron_pid="1", item_pid="item_returned_3").execute() assert search_result.hits.total == 1 search_result = search_by_patron_item_or_document( patron_pid="1", item_pid="not_existing").execute() assert search_result.hits.total == 0 search_result = search_by_patron_item_or_document( patron_pid="999999", item_pid="item_returned_3").execute() assert search_result.hits.total == 0 search_result = search_by_patron_item_or_document( patron_pid="1", document_pid="document_pid").execute() assert search_result.hits.total == 8 search_result = search_by_patron_item_or_document( patron_pid="1", document_pid="not_existing").execute() assert search_result.hits.total == 0 search_result = search_by_patron_item_or_document( patron_pid="999999", document_pid="document_returned_1").execute() assert search_result.hits.total == 0 def test_search_loans_by_patron_and_item_or_document_filtering_states( indexed_loans): """Test retrieve loan list by patron and items filtering states.""" search = search_by_patron_item_or_document(patron_pid="1", item_pid="item_returned_3", filter_states=['ITEM_RETURNED']) search_result = search.execute() assert search_result.hits.total == 1 search = search_by_patron_item_or_document(patron_pid="1", item_pid="item_returned_3", filter_states=['ITEM_AT_DESK']) search_result = search.execute() assert search_result.hits.total == 0 search = search_by_patron_item_or_document(patron_pid="1", document_pid="document_pid", filter_states=['ITEM_RETURNED']) search_result = search.execute() assert search_result.hits.total == 2 search = search_by_patron_item_or_document(patron_pid="2", document_pid="document_pid", filter_states=['ITEM_RETURNED']) search_result = search.execute() assert search_result.hits.total == 1 search = search_by_patron_item_or_document(patron_pid="1", document_pid="document_pid", filter_states=['ITEM_AT_DESK']) search_result = search.execute() assert search_result.hits.total == 1 search = search_by_patron_item_or_document(patron_pid="1", document_pid="document_pid", filter_states=['PENDING']) search_result = search.execute() assert search_result.hits.total == 3

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py

Python

recohut/None.py

sparsh-ai/recohut

4121f665761ffe38c9b6337eaa9293b26bee2376

[ "Apache-2.0" ]

null

recohut/None.py

sparsh-ai/recohut

4121f665761ffe38c9b6337eaa9293b26bee2376

[ "Apache-2.0" ]

1

2022-01-12T05:40:57.000Z

recohut/None.py

RecoHut-Projects/recohut

4121f665761ffe38c9b6337eaa9293b26bee2376

[ "Apache-2.0" ]

null

# Cell import time from functools import wraps from math import trunc

10.285714

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