xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

4a92f8d12f8097d1369ed2baa7d451f1b1b3b351

13,501

py

Python

evology/bin/mc.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

null

evology/bin/mc.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

2

2022-01-10T02:10:56.000Z

2022-01-14T03:41:42.000Z

evology/bin/mc.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

null

print( "Looking at different choices to represent the trading functions and how they impact the price, when we initialise at p=100" ) initial_price = 100 wealth = 50_000_000 + 500_000 * initial_price assets = 500_000 print("For ValNT = 100, reference") def func1(asset_key, price): # VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func2(asset_key, price): # NT return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func3(asset_key, price): # TF return (wealth / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) initial_price = 100 wealth = 50_000_000 + 500_000 * initial_price assets = 500_000 print("For ValNT = 100, reference WITH LEVERAGE ") def func1(asset_key, price): # VI return (8 * wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func2(asset_key, price): # NT return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func3(asset_key, price): # TF return (wealth / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print("For ValNT = 110, higher price as expected") def func1(asset_key, price): # VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func2(asset_key, price): # NT return (wealth / price) * np.tanh(np.log2(110) - np.log2(price)) - assets def func3(asset_key, price): # TF return (wealth / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print("For ValNT = 90, lower price as expected") def func1(asset_key, price): # VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func2(asset_key, price): # NT return (wealth / price) * np.tanh(np.log2(90) - np.log2(price)) - assets def func3(asset_key, price): # TF return (wealth / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print("With 0,5 inside tanh, price is higher") def func1(asset_key, price): # VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price) + 0.5) - assets def func2(asset_key, price): # NT return (wealth / price) * np.tanh(np.log2(90) - np.log2(price) + 0.5) - assets def func3(asset_key, price): # TF return (wealth / price) * np.tanh(0.5 + 0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print("With 0,5 outside tanh, price is even higher") def func1(asset_key, price): # VI return (wealth / price) * (np.tanh(np.log2(100) - np.log2(price)) + 0.5) - assets def func2(asset_key, price): # NT return (wealth / price) * (np.tanh(np.log2(90) - np.log2(price)) + 0.5) - assets def func3(asset_key, price): # TF return (wealth / price) * (np.tanh(0.5) + 0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print( "Question: MC is deterministic, which is good. Because now, does the 0,.5 choice gives unintended power to some strategies?" ) """ print('----') print('Lets study the resulting 10 day series') print('VI 90, no 0.5') new_price = 100 cash = 50_000_000 asset = 500_000 for i in range(10): wealth = cash + asset * new_price def func1(asset_key, price): #VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price)) - assets def func2(asset_key, price): #NT return (wealth / price) * np.tanh(np.log2(90) - np.log2(price)) - assets def func3(asset_key, price): #TF return (wealth / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = float(solve(functions, initial_price)[0]) print(new_price) print('With 0,5 inside tanh') new_price = 100 cash = 50_000_000 asset = 500_000 for i in range(10): wealth = cash + asset * new_price def func1(asset_key, price): #VI return (wealth / price) * np.tanh(np.log2(100) - np.log2(price) + 0.5) - assets def func2(asset_key, price): #NT return (wealth / price) * np.tanh(np.log2(90) - np.log2(price) + 0.5) - assets def func3(asset_key, price): #TF return (wealth / price) * np.tanh(0.5 + 0.5) - assets functions = [func1, func2, func3] new_price = float(solve(functions, initial_price)[0]) print(new_price) print('With 0,5 outside tanh') new_price = 100 cash = 50_000_000 asset = 500_000 for i in range(10): wealth = cash + asset * new_price def func1(asset_key, price): #VI return (wealth / price) * (np.tanh(np.log2(100) - np.log2(price)) + 0.5) - assets def func2(asset_key, price): #NT return (wealth / price) * (np.tanh(np.log2(90) - np.log2(price)) + 0.5) - assets def func3(asset_key, price): #TF return (wealth / price) * (np.tanh(0.5) + 0.5) - assets functions = [func1, func2, func3] new_price = float(solve(functions, initial_price)[0]) print(new_price) """ """ print('With 0,5 outside tanh, and VI/NT depending on previous price') print('Then we get oscillations around two attractors') print('Unless we adapt TF and then nothing happens') new_price = 100 previous_price = 90 cash = 50_000_000 asset = 500_000 for i in range(10): wealth = cash + asset * new_price LogPrev = np.log2(new_price) def func1(asset_key, price): #VI return (wealth / price) * (np.tanh(np.log2(100) - LogPrev) + 0.5) - assets def func2(asset_key, price): #NT return (wealth / price) * (np.tanh(np.log2(90) - LogPrev) + 0.5) - assets def func3(asset_key, price): #TF return (wealth / price) * (np.tanh(np.log2(price) - LogPrev) + 0.5) - assets functions = [func1, func2, func3] new_price = float(solve(functions, initial_price)[0]) print(new_price) print('Without and VI/NT depending on previous price') print('Then we stabilise') new_price = 100 previous_price = 90 cash = 50_000_000 asset = 500_000 for i in range(10): wealth = cash + asset * new_price LogPrev = np.log2(new_price) def func1(asset_key, price): #VI return (wealth / price) * (np.tanh(np.log2(100) - LogPrev) + 0) - assets def func2(asset_key, price): #NT return (wealth / price) * (np.tanh(np.log2(90) - LogPrev) + 0) - assets def func3(asset_key, price): #TF return (wealth / price) * (np.tanh(np.log2(price) - LogPrev) + 0) - assets functions = [func1, func2, func3] new_price = float(solve(functions, initial_price)[0]) print(new_price) """ """ print('Y Y N with noise') def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(price) + 0.5)) - 500_000 ValNT = 100 + 10 print(ValNT) def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(ValNT)) - np.log2(price) + 0.5) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0) + 0.5) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print('Y Y N without noise') initial_price = 100 def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(price) + 0.5)) - 500_000 ValNT = 100 print(ValNT) def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(ValNT)) - np.log2(price) + 0.5) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0) + 0.5) - 500_000 print('Y Y N with noise without 05') initial_price = 100 def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(price))) - 500_000 ValNT = 100 + 10 print(ValNT) def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(ValNT)) - np.log2(price)) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0)) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print('Y Y N without noise without 0.5') initial_price = 100 def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(price))) - 500_000 ValNT = 100 print(ValNT) def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(ValNT)) - np.log2(price)) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0)) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print('N N N ') initial_price = 100 def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100 + random.normalvariate(0,1)) - np.log2(price)) + 0.5) - 500_000 def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(100 + random.normalvariate(0,1)) - np.log2(price)) + 0.5) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0) + 0.5) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) print('Y Y Y ') initial_price = 100 import random def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(price) + 0.5)) - 500_000 def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(100 + random.normalvariate(0,1)) - np.log2(price) + 0.5)) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0 + 0.5)) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) # print(func1(0, float(new_price[0]))) # print(func2(0, float(new_price[0]))) # print(func3(0, float(new_price[0]))) # for i in range(10): # new_price = solve(functions, float(new_price[0])) # print(new_price) print('------') print('VI and NT depending on last price') initial_price = 100 def func1(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(initial_price) + 0.5)) - 500_000 def func2(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(100 + random.normalvariate(0,1)) - np.log2(initial_price) + 0.5)) - 500_000 def func3(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0 + 0.5)) - 500_000 functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) # print(func1(0, float(new_price[0]))) # print(func2(0, float(new_price[0]))) # print(func3(0, float(new_price[0]))) # for i in range(10): # new_price = solve(functions, float(new_price[0])) # print(new_price) print('------') print('Removing 0.5') initial_price = 100 def func4(asset_key, price): #value investor return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(np.log2(100) - np.log2(initial_price))) - 500_000 def func5(asset_key, price): #noise trader return ((50_000_000 + 500_000 * float(initial_price)) / price) * (np.tanh(np.log2(100 + random.normalvariate(0,1)) - np.log2(initial_price))) - 500_000 def func6(asset_key, price): #trend follower return ((50_000_000 + 500_000 * float(initial_price)) / price ) * (np.tanh(0)) - 500_000 functions = [func4, func5, func6] new_price = solve(functions, initial_price) print(new_price) """ initial_price = 100 wealth = 50_000_000 + 500_000 * initial_price assets = 500_000 assets = 400_000 print("For ValNT = 100, reference") def func1(asset_key, price): # VI return ((60_000_000 + assets * initial_price) / price) * np.tanh( np.log2(100) - np.log2(price) ) - assets def func2(asset_key, price): # NT return ((60_000_000 + assets * initial_price) / price) * np.tanh( np.log2(100) - np.log2(price) ) - assets def func3(asset_key, price): # TF return ((60_000_000 + assets * initial_price) / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price) assets = 500_000 print("For ValNT = 100, reference") def func1(asset_key, price): # VI return ((50_000_000 + assets * initial_price) / price) * np.tanh( np.log2(100) - np.log2(price) ) - assets def func2(asset_key, price): # NT return ((50_000_000 + assets * initial_price) / price) * np.tanh( np.log2(100) - np.log2(price) ) - assets def func3(asset_key, price): # TF return ((50_000_000 + assets * initial_price) / price) * np.tanh(0.5) - assets functions = [func1, func2, func3] new_price = solve(functions, initial_price) print(new_price)

30.002222

160

0.676542

2,142

13,501

4.108777

0.056489

0.057266

0.093058

0.064993

0.940916

0.935462

0.929781

0.926713

0

0.110297

0.170654

13,501

449

161

30.069042

0.675717

0.005259

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0.8

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0.019048

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0.228571

false

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0.228571

0.457143

0.171429

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null

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1

0

1

0

null

0

1

0

1

0

9

4ab83179f1239007ebb0eb7bb3fe0a1ac8adece4

105

py

Python

highcliff/medication/__init__.py

sermelo/Highcliff-SDK

255dd12b3402361cba8b1ea7a28c506f32a11dae

[ "Apache-2.0" ]

null

highcliff/medication/__init__.py

sermelo/Highcliff-SDK

255dd12b3402361cba8b1ea7a28c506f32a11dae

[ "Apache-2.0" ]

null

highcliff/medication/__init__.py

sermelo/Highcliff-SDK

255dd12b3402361cba8b1ea7a28c506f32a11dae

[ "Apache-2.0" ]

null

from highcliff.medication.medication import MonitorMedication, RequestMedication, ConfirmMedicationGiven

52.5

104

0.904762

8

105

11.875

0.875

0

0.057143

105

1

105

0.959596

0

1

0

true

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1

0

1

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null

0

1

0

1

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1

0

7

4ac870da0ad0956154ddce8d4b0d192596a7e0ea

96

py

Python

src/nncomp_molecule/decoders/__init__.py

k-fujikawa/Kaggle-BMS-Molecular-Translation

5503572686ed6c4082e276d9e17078185249be9e

[ "MIT" ]

3

2021-08-29T21:07:37.000Z

2022-03-30T07:46:57.000Z

src/nncomp_molecule/decoders/__init__.py

k-fujikawa/Kaggle-BMS-Molecular-Translation-

5503572686ed6c4082e276d9e17078185249be9e

[ "MIT" ]

null

src/nncomp_molecule/decoders/__init__.py

k-fujikawa/Kaggle-BMS-Molecular-Translation-

5503572686ed6c4082e276d9e17078185249be9e

[ "MIT" ]

1

2022-03-30T10:20:25.000Z

from . import rnn # NOQA from . import transformer # NOQA from . import transformer_v2 # NOQA

32

36

0.729167

13

96

5.307692

0.461538

0.434783

0.405797

0.724638

0

0.013158

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96

3

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true

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null

0

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1

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0

8

4367d589e313150eb0589cafc94ab3b4b8d10e4e

40,079

py

Python

src/openprocurement/tender/competitivedialogue/tests/stage1/lot_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

3

2020-03-13T06:44:23.000Z

2020-11-05T18:25:29.000Z

src/openprocurement/tender/competitivedialogue/tests/stage1/lot_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

2

2021-03-25T23:29:58.000Z

2022-03-21T22:18:37.000Z

src/openprocurement/tender/competitivedialogue/tests/stage1/lot_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

3

2020-10-16T16:25:14.000Z

2021-05-22T12:26:20.000Z

# -*- coding: utf-8 -*- from copy import deepcopy from openprocurement.api.utils import get_now from openprocurement.api.constants import RELEASE_2020_04_19 from openprocurement.tender.core.tests.cancellation import activate_cancellation_with_complaints_after_2020_04_19 # CompetitiveDialogueEU(UA)LotBidderResourceTest from openprocurement.tender.belowthreshold.tests.base import test_cancellation def create_tender_bidder_invalid(self): request_path = "/tenders/{}/bids".format(self.tender_id) response = self.app.post_json( request_path, {"data": {"selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"]}}, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": [u"This field is required."], u"location": u"body", u"name": u"lotValues"}], ) response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}}], } }, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [ { u"description": [{u"relatedLot": [u"This field is required."]}], u"location": u"body", u"name": u"lotValues", } ], ) response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}, "relatedLot": "0" * 32}], } }, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [ { u"description": [{u"relatedLot": [u"relatedLot should be one of lots"]}], u"location": u"body", u"name": u"lotValues", } ], ) # Field 'value' doesn't exists on first stage response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 5000000}, "relatedLot": self.initial_lots[0]["id"]}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [ {"value": {"amount": 500, "valueAddedTaxIncluded": False}, "relatedLot": self.initial_lots[0]["id"]} ], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500, "currency": "USD"}, "relatedLot": self.initial_lots[0]["id"]}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "value": {"amount": 500}, "lotValues": [{"value": {"amount": 500}, "relatedLot": self.initial_lots[0]["id"]}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") def patch_tender_bidder(self): lot_id = self.initial_lots[0]["id"] response = self.app.post_json( "/tenders/{}/bids".format(self.tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") bidder = response.json["data"] bid_token = response.json["access"]["token"] lot = bidder["lotValues"][0] response = self.app.patch_json( "/tenders/{}/bids/{}?acc_token={}".format(self.tender_id, bidder["id"], bid_token), {"data": {"tenderers": [{"name": u"Державне управління управлінням справами"}]}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["lotValues"][0]["date"], lot["date"]) self.assertNotEqual(response.json["data"]["tenderers"][0]["name"], bidder["tenderers"][0]["name"]) response = self.app.patch_json( "/tenders/{}/bids/{}?acc_token={}".format(self.tender_id, bidder["id"], bid_token), { "data": { "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], "tenderers": self.test_bids_data[0]["tenderers"], } }, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["lotValues"][0]["date"], lot["date"]) self.assertEqual(response.json["data"]["tenderers"][0]["name"], bidder["tenderers"][0]["name"]) # If we don't change anything then return null response = self.app.patch_json( "/tenders/{}/bids/{}?acc_token={}".format(self.tender_id, bidder["id"], bid_token), {"data": {"lotValues": [{"value": {"amount": 400}, "relatedLot": lot_id}]}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/bids/{}?acc_token={}".format(self.tender_id, bidder["id"], bid_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertNotIn("lotValues", response.json["data"]) response = self.app.patch_json( "/tenders/{}/bids/{}?acc_token={}".format(self.tender_id, bidder["id"], bid_token), {"data": {"lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], "status": "active"}}, status=403, ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"][0]["description"], "Can't update bid in current (unsuccessful) tender status" ) # CompetitiveDialogueEULotFeatureBidderResourceTest def create_tender_with_features_bidder_invalid(self): request_path = "/tenders/{}/bids".format(self.tender_id) response = self.app.post_json( request_path, {"data": {"selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"]}}, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}}], } }, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [ { u"description": [{u"relatedLot": [u"This field is required."]}], u"location": u"body", u"name": u"lotValues", } ], ) response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}, "relatedLot": "0" * 32}], } }, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [ { u"description": [{u"relatedLot": [u"relatedLot should be one of lots"]}], u"location": u"body", u"name": u"lotValues", } ], ) # Field 'value' doesn't exists on first stage response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 5000000}, "relatedLot": self.lot_id}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500, "valueAddedTaxIncluded": False}, "relatedLot": self.lot_id}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.post_json( request_path, { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500, "currency": "USD"}, "relatedLot": self.lot_id}], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") # CompetitiveDialogueEULotProcessTest def one_lot_0bid(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lot_id = response.json["data"]["id"] # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": lot_id}]}} ) self.assertEqual(response.status, "200 OK") # switch to active.tendering response = self.set_status("active.tendering") self.assertNotIn("auctionPeriod", response.json["data"]["lots"][0]) # switch to unsuccessful response = self.set_status("active.stage2.pending", {"status": "active.tendering"}) self.app.authorization = ("Basic", ("chronograph", "")) response = self.app.patch_json("/tenders/{}".format(tender_id), {"data": {"id": tender_id}}) self.assertEqual(response.json["data"]["lots"][0]["status"], "unsuccessful") self.assertEqual(response.json["data"]["status"], "unsuccessful") response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]}, status=403 ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual( response.json["errors"], [{"location": "body", "name": "data", "description": "Can't add lot in current (unsuccessful) tender status"}], ) def one_lot_2bid_1unqualified(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lot_id = response.json["data"]["id"] # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": lot_id}]}} ) self.assertEqual(response.status, "200 OK") # create bid self.app.authorization = ("Basic", ("broker", "")) bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) bidder_data["identifier"]["id"] = u"00037256" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], } }, ) bidder_data["identifier"]["id"] = u"00037257" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], } }, ) bidder_data["identifier"]["id"] = u"00037258" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id}], } }, ) # switch to active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualifications[0]["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualifications[1]["id"], owner_token), {"data": {"status": "unsuccessful"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "unsuccessful") response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualifications[2]["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"status": "active.pre-qualification.stand-still"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active.pre-qualification.stand-still") def one_lot_2bid(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lot_id = response.json["data"]["id"] self.initial_lots = [response.json["data"]] # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": lot_id}]}} ) self.assertEqual(response.status, "200 OK") # create bid self.app.authorization = ("Basic", ("broker", "")) bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) bidder_data["identifier"]["id"] = u"00037256" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 450}, "relatedLot": lot_id}], } }, ) bid_id = response.json["data"]["id"] bid_token = response.json["access"]["token"] # create second bid self.app.authorization = ("Basic", ("broker", "")) bidder_data["identifier"]["id"] = u"00037257" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 475}, "relatedLot": lot_id}], } }, ) # create third bidder_data["identifier"]["id"] = u"00037258" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 470}, "relatedLot": lot_id}], } }, ) # switch to active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] for qualification in qualifications: response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualification["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.get("/tenders/{}?acc_token={}".format(tender_id, owner_token)) self.assertEqual(response.status, "200 OK") for bid in response.json["data"]["bids"]: self.assertEqual(bid["status"], "active") response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"status": "active.pre-qualification.stand-still"}}, ) self.assertEqual(response.status, "200 OK") self.check_chronograph() response = self.app.get("/tenders/{}?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") self.assertEqual(response.status, "200 OK") def two_lot_2bid_1lot_del(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] lots = [] for lot in 2 * self.test_lots_data: # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lots.append(response.json["data"]["id"]) self.initial_lots = lots # add item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [self.test_tender_data["items"][0] for i in lots]}}, ) response = self.set_status("active.tendering") # create bid bids = [] self.app.authorization = ("Basic", ("broker", "")) response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[0]["tenderers"], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) bids.append(response.json) # create second bid self.app.authorization = ("Basic", ("broker", "")) response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": self.test_bids_data[1]["tenderers"], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) bids.append(response.json) response = self.app.delete("/tenders/{}/lots/{}?acc_token={}".format(self.tender_id, lots[0], owner_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") def one_lot_3bid_1del(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lot_id = response.json["data"]["id"] self.initial_lots = [response.json["data"]] # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": lot_id}]}} ) self.assertEqual(response.status, "200 OK") # create bids self.app.authorization = ("Basic", ("broker", "")) bids = [] bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) for index, test_bid in enumerate(self.test_bids_data): bidder_data["identifier"]["id"] = "00037256" + str(index) response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 450}, "relatedLot": lot_id}], } }, ) bids.append({response.json["data"]["id"]: response.json["access"]["token"]}) response = self.app.delete( "/tenders/{}/bids/{}?acc_token={}".format(tender_id, bids[2].keys()[0], bids[2].values()[0]) ) self.assertEqual(response.status, "200 OK") # switch to active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() # check tender status response = self.app.get("/tenders/{}?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "unsuccessful") def one_lot_3bid_1un(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lot_id = response.json["data"]["id"] self.initial_lots = [response.json["data"]] # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": lot_id}]}} ) self.assertEqual(response.status, "200 OK") # create bid self.app.authorization = ("Basic", ("broker", "")) bids = [] bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) for i in range(3): bidder_data["identifier"]["id"] = "00037256" + str(i) response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 450}, "relatedLot": lot_id}], } }, ) bids.append({response.json["data"]["id"]: response.json["access"]["token"]}) # switch to active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] for qualification in qualifications: if qualification["bidID"] == bids[2].keys()[0]: response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualification["id"], owner_token), {"data": {"status": "unsuccessful"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "unsuccessful") else: response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualification["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"status": "active.pre-qualification.stand-still"}}, ) self.assertEqual(response.status, "200 OK") self.check_chronograph() response = self.app.get("/tenders/{}?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") self.assertEqual(response.status, "200 OK") response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] def two_lot_0bid(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] lots = [] for lot in 2 * self.test_lots_data: # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lots.append(response.json["data"]["id"]) # add item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [self.test_tender_data["items"][0] for i in lots]}}, ) # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": i} for i in lots]}}, ) self.assertEqual(response.status, "200 OK") self.time_shift("active.pre-qualification") self.check_chronograph() # switch to unsuccessful self.app.authorization = ("Basic", ("broker", "")) response = self.app.get("/tenders/{}?acc_token={}".format(tender_id, owner_token)) self.assertTrue(all([i["status"] == "unsuccessful" for i in response.json["data"]["lots"]])) self.assertEqual(response.json["data"]["status"], "unsuccessful") def two_lot_2can(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] lots = [] for lot in 2 * self.test_lots_data: # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lots.append(response.json["data"]["id"]) # add item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [self.test_tender_data["items"][0] for i in lots]}}, ) # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": i} for i in lots]}}, ) self.assertEqual(response.status, "200 OK") set_complaint_period_end = getattr(self, "set_complaint_period_end", None) if RELEASE_2020_04_19 < get_now() and set_complaint_period_end: set_complaint_period_end() # cancel every lot for lot_id in lots: cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": lot_id, }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(tender_id, owner_token), {"data": cancellation}, ) cancellation_id = response.json["data"]["id"] if RELEASE_2020_04_19 < get_now(): activate_cancellation_with_complaints_after_2020_04_19(self, cancellation_id, tender_id, owner_token) response = self.app.get("/tenders/{}".format(tender_id)) self.assertTrue(all([i["status"] == "cancelled" for i in response.json["data"]["lots"]])) self.assertEqual(response.json["data"]["status"], "cancelled") def two_lot_2bid_0com_1can(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] lots = [] for lot in 2 * self.test_lots_data: # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lots.append(response.json["data"]["id"]) # add item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [self.test_tender_data["items"][0] for i in lots]}}, ) # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": i} for i in lots]}}, ) self.assertEqual(response.status, "200 OK") # create bid self.app.authorization = ("Basic", ("broker", "")) bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) bidder_data["identifier"]["id"] = u"00037256" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) bidder_data["identifier"]["id"] = u"00037257" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 499}, "relatedLot": lot_id} for lot_id in lots], } }, ) bidder_data["identifier"]["id"] = u"00037258" response = self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 499}, "relatedLot": lot_id} for lot_id in lots], } }, ) set_complaint_period_end = getattr(self, "set_complaint_period_end", None) if RELEASE_2020_04_19 < get_now() and set_complaint_period_end: set_complaint_period_end() self.app.authorization = ("Basic", ("broker", "")) cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": lots[0], }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(tender_id, owner_token), {"data": cancellation}, ) cancellation_id = response.json["data"]["id"] if RELEASE_2020_04_19 < get_now(): activate_cancellation_with_complaints_after_2020_04_19(self, cancellation_id, tender_id, owner_token) response = self.app.get("/tenders/{}?acc_token={}".format(tender_id, owner_token)) self.assertEqual(response.status, "200 OK") # active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] self.assertEqual(len(qualifications), 3) for qualification in qualifications: response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualification["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"status": "active.pre-qualification.stand-still"}}, ) self.assertEqual(response.status, "200 OK") def two_lot_2bid_2com_2win(self): self.app.authorization = ("Basic", ("broker", "")) # create tender response = self.app.post_json("/tenders", {"data": self.test_tender_data}) tender_id = self.tender_id = response.json["data"]["id"] owner_token = response.json["access"]["token"] lots = [] for lot in 2 * self.test_lots_data: # add lot response = self.app.post_json( "/tenders/{}/lots?acc_token={}".format(tender_id, owner_token), {"data": self.test_lots_data[0]} ) self.assertEqual(response.status, "201 Created") lots.append(response.json["data"]["id"]) self.initial_lots = lots # add item self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [self.test_tender_data["items"][0] for i in lots]}}, ) # add relatedLot for item response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"items": [{"relatedLot": i} for i in lots]}}, ) self.assertEqual(response.status, "200 OK") # create bid bidder_data = deepcopy(self.test_bids_data[0]["tenderers"][0]) bidder_data["identifier"]["id"] = u"00037256" self.app.authorization = ("Basic", ("broker", "")) self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) # create second bid bidder_data["identifier"]["id"] = u"00037257" self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) # create third bid bidder_data["identifier"]["id"] = u"00037258" self.app.post_json( "/tenders/{}/bids".format(tender_id), { "data": { "selfEligible": True, "selfQualified": True, "tenderers": [bidder_data], "lotValues": [{"value": {"amount": 500}, "relatedLot": lot_id} for lot_id in lots], } }, ) # switch to active.pre-qualification self.time_shift("active.pre-qualification") self.check_chronograph() response = self.app.get("/tenders/{}/qualifications?acc_token={}".format(self.tender_id, owner_token)) self.assertEqual(response.content_type, "application/json") qualifications = response.json["data"] self.assertEqual(len(qualifications), 6) for qualification in qualifications: response = self.app.patch_json( "/tenders/{}/qualifications/{}?acc_token={}".format(self.tender_id, qualification["id"], owner_token), {"data": {"status": "active", "qualified": True, "eligible": True}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}?acc_token={}".format(tender_id, owner_token), {"data": {"status": "active.pre-qualification.stand-still"}}, ) self.assertEqual(response.status, "200 OK")

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439c458c0e0f69c4609fa712c3acde7f98eea5b5

3,236

py

Python

src/examples/VRGameFog-IFogSim-WL/placement_Cluster_Edge.py

MarkoRimac/YAFS

5ea354439e4acb4ca83714b01eb427b508718836

[ "MIT" ]

58

2018-09-19T12:00:01.000Z

2022-03-28T12:14:32.000Z

src/examples/VRGameFog-IFogSim-WL/placement_Cluster_Edge.py

MarkoRimac/YAFS

5ea354439e4acb4ca83714b01eb427b508718836

[ "MIT" ]

55

2018-03-18T09:58:27.000Z

2022-02-19T16:40:02.000Z

src/examples/VRGameFog-IFogSim-WL/placement_Cluster_Edge.py

MarkoRimac/YAFS

5ea354439e4acb4ca83714b01eb427b508718836

[ "MIT" ]

51

2018-05-30T11:33:10.000Z

2022-03-14T15:37:01.000Z

""" This type of algorithm have two obligatory functions: *initial_allocation*: invoked at the start of the simulation *run* invoked according to the assigned temporal distribution. """ from yafs.placement import Placement class CloudPlacement(Placement): """ This implementation locates the services of the application in the cheapest cloud regardless of where the sources or sinks are located. It only runs once, in the initialization. """ def initial_allocation(self, sim, app_name): #We find the ID-nodo/resource value = {"model": "Cluster"} id_cluster = sim.topology.find_IDs(value) #there is only ONE Cluster value = {"model": "m-"} id_mobiles = sim.topology.find_IDs(value) #Given an application we get its modules implemented app = sim.apps[app_name] services = app.services for module in services.keys(): if "Coordinator" == module: if "Coordinator" in self.scaleServices.keys(): # print self.scaleServices["Coordinator"] for rep in range(0,self.scaleServices["Coordinator"]): idDES = sim.deploy_module(app_name,module,services[module],id_cluster) #Deploy as many modules as elements in the array elif "Calculator" == module: if "Calculator" in self.scaleServices.keys(): for rep in range(0, self.scaleServices["Calculator"]): idDES = sim.deploy_module(app_name,module,services[module],id_cluster) elif "Client" == module: idDES = sim.deploy_module(app_name,module, services[module],id_mobiles) #end function class FogPlacement(Placement): """ This implementation locates the services of the application in the fog-device regardless of where the sources or sinks are located. It only runs once, in the initialization. """ def initial_allocation(self, sim, app_name): #We find the ID-nodo/resource value = {"model": "Cluster"} id_cluster = sim.topology.find_IDs(value) #there is only ONE Cluster value = {"model": "d-"} id_proxies = sim.topology.find_IDs(value) value = {"model": "m-"} id_mobiles = sim.topology.find_IDs(value) #Given an application we get its modules implemented app = sim.apps[app_name] services = app.services for module in services.keys(): if "Coordinator" == module: if "Coordinator" in self.scaleServices.keys(): for rep in range(0, self.scaleServices["Coordinator"]): idDES = sim.deploy_module(app_name, module, services[module],id_cluster) # Deploy as many modules as elements in the array elif "Calculator" == module: if "Calculator" in self.scaleServices.keys(): for rep in range(0, self.scaleServices["Calculator"]): idDES = sim.deploy_module(app_name, module, services[module], id_proxies) elif "Client" == module: idDES = sim.deploy_module(app_name,module, services[module],id_mobiles)

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7

43d66d12e65e710131e613838fd0a0e7f5555ff9

1,446

py

Python

registry/smart_contract/migrations/0024_auto_20180819_0841.py

RustamSultanov/Python-test-registry-

1d779a8135567a0b3aeca0151b2d7f0905014e88

[ "MIT" ]

1

2019-01-16T14:52:37.000Z

registry/smart_contract/migrations/0024_auto_20180819_0841.py

RustamSultanov/Python-test-registry-

1d779a8135567a0b3aeca0151b2d7f0905014e88

[ "MIT" ]

8

2019-10-21T16:18:33.000Z

2021-06-08T20:33:14.000Z

registry/smart_contract/migrations/0024_auto_20180819_0841.py

RustamSultanov/Python-test-registry-

1d779a8135567a0b3aeca0151b2d7f0905014e88

[ "MIT" ]

null

# Generated by Django 2.1 on 2018-08-19 08:41 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('smart_contract', '0023_comment_adition_user'), ] operations = [ migrations.AlterField( model_name='comment', name='accept', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='comment', name='customer_flag', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='comment', name='failure', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='comment', name='hide', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='comment', name='implementer_flag', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='useraccept', name='accept', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='useraccept', name='failure', field=models.BooleanField(blank=True, default=False), ), ]

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0

9

43db135916e1fff3e792c8a89088c94fad89e0b3

23,297

py

Python

lib/src/owlracer/grpcClient/core_pb2_grpc.py

MATHEMA-GmbH/Owl-Racer-AI-Client-Python

3a16a254710e4a2e868e8569e7d6a67050cbc180

[ "MIT" ]

null

lib/src/owlracer/grpcClient/core_pb2_grpc.py

MATHEMA-GmbH/Owl-Racer-AI-Client-Python

3a16a254710e4a2e868e8569e7d6a67050cbc180

[ "MIT" ]

null

lib/src/owlracer/grpcClient/core_pb2_grpc.py

MATHEMA-GmbH/Owl-Racer-AI-Client-Python

3a16a254710e4a2e868e8569e7d6a67050cbc180

[ "MIT" ]

null

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2 from matlabs.owlracer import core_pb2 as matlabs_dot_owlracer_dot_core__pb2 class GrpcCoreServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.GetCarIds = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/GetCarIds', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidListData.FromString, ) self.CreateSession = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/CreateSession', request_serializer=matlabs_dot_owlracer_dot_core__pb2.CreateSessionData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.SessionData.FromString, ) self.GetSession = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/GetSession', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.SessionData.FromString, ) self.GetSessionIds = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/GetSessionIds', request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidListData.FromString, ) self.CreateCar = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/CreateCar', request_serializer=matlabs_dot_owlracer_dot_core__pb2.CreateCarData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, ) self.DestroyCar = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/DestroyCar', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.DestroySession = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/DestroySession', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.GetCarData = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/GetCarData', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, ) self.Step = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/Step', request_serializer=matlabs_dot_owlracer_dot_core__pb2.StepData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, ) self.Reset = channel.unary_unary( '/matlabs.owlracer.core.GrpcCoreService/Reset', request_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) class GrpcCoreServiceServicer(object): """Missing associated documentation comment in .proto file.""" def GetCarIds(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CreateSession(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetSession(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetSessionIds(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CreateCar(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DestroyCar(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DestroySession(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetCarData(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Step(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Reset(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_GrpcCoreServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'GetCarIds': grpc.unary_unary_rpc_method_handler( servicer.GetCarIds, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidListData.SerializeToString, ), 'CreateSession': grpc.unary_unary_rpc_method_handler( servicer.CreateSession, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.CreateSessionData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.SessionData.SerializeToString, ), 'GetSession': grpc.unary_unary_rpc_method_handler( servicer.GetSession, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.SessionData.SerializeToString, ), 'GetSessionIds': grpc.unary_unary_rpc_method_handler( servicer.GetSessionIds, request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.GuidListData.SerializeToString, ), 'CreateCar': grpc.unary_unary_rpc_method_handler( servicer.CreateCar, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.CreateCarData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.SerializeToString, ), 'DestroyCar': grpc.unary_unary_rpc_method_handler( servicer.DestroyCar, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'DestroySession': grpc.unary_unary_rpc_method_handler( servicer.DestroySession, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'GetCarData': grpc.unary_unary_rpc_method_handler( servicer.GetCarData, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.SerializeToString, ), 'Step': grpc.unary_unary_rpc_method_handler( servicer.Step, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.StepData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.RaceCarData.SerializeToString, ), 'Reset': grpc.unary_unary_rpc_method_handler( servicer.Reset, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.GuidData.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'matlabs.owlracer.core.GrpcCoreService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class GrpcCoreService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def GetCarIds(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/GetCarIds', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.GuidListData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CreateSession(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/CreateSession', matlabs_dot_owlracer_dot_core__pb2.CreateSessionData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.SessionData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetSession(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/GetSession', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.SessionData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetSessionIds(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/GetSessionIds', google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.GuidListData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CreateCar(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/CreateCar', matlabs_dot_owlracer_dot_core__pb2.CreateCarData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DestroyCar(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/DestroyCar', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DestroySession(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/DestroySession', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetCarData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/GetCarData', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Step(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/Step', matlabs_dot_owlracer_dot_core__pb2.StepData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.RaceCarData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Reset(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcCoreService/Reset', matlabs_dot_owlracer_dot_core__pb2.GuidData.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) class GrpcResourceServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.GetBaseImages = channel.unary_unary( '/matlabs.owlracer.core.GrpcResourceService/GetBaseImages', request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.ResourceImagesDataResponse.FromString, ) self.GetTrackImage = channel.unary_unary( '/matlabs.owlracer.core.GrpcResourceService/GetTrackImage', request_serializer=matlabs_dot_owlracer_dot_core__pb2.TrackIdData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.TrackImageDataResponse.FromString, ) self.GetTrackData = channel.unary_unary( '/matlabs.owlracer.core.GrpcResourceService/GetTrackData', request_serializer=matlabs_dot_owlracer_dot_core__pb2.TrackIdData.SerializeToString, response_deserializer=matlabs_dot_owlracer_dot_core__pb2.TrackData.FromString, ) class GrpcResourceServiceServicer(object): """Missing associated documentation comment in .proto file.""" def GetBaseImages(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetTrackImage(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetTrackData(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_GrpcResourceServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'GetBaseImages': grpc.unary_unary_rpc_method_handler( servicer.GetBaseImages, request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.ResourceImagesDataResponse.SerializeToString, ), 'GetTrackImage': grpc.unary_unary_rpc_method_handler( servicer.GetTrackImage, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.TrackIdData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.TrackImageDataResponse.SerializeToString, ), 'GetTrackData': grpc.unary_unary_rpc_method_handler( servicer.GetTrackData, request_deserializer=matlabs_dot_owlracer_dot_core__pb2.TrackIdData.FromString, response_serializer=matlabs_dot_owlracer_dot_core__pb2.TrackData.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'matlabs.owlracer.core.GrpcResourceService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class GrpcResourceService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def GetBaseImages(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcResourceService/GetBaseImages', google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.ResourceImagesDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetTrackImage(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcResourceService/GetTrackImage', matlabs_dot_owlracer_dot_core__pb2.TrackIdData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.TrackImageDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetTrackData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/matlabs.owlracer.core.GrpcResourceService/GetTrackData', matlabs_dot_owlracer_dot_core__pb2.TrackIdData.SerializeToString, matlabs_dot_owlracer_dot_core__pb2.TrackData.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

47.351626

121

0.676997

2,182

23,297

6.870761

0.055454

0.03035

0.076841

0.089648

0.923959

0.90595

0.902215

0.8127

0.774013

0.766409

0

0.004699

0.250891

23,297

491

122

47.448065

0.854343

0.060308

0

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1

0

0.097519

0.063786

0

1

0.072639

false

0

0.007264

0.031477

0.125908

0

null

0

1

0

1

0

null

0

7

6064fcc42a14c6f4e39b299f72b675b7191e529f

167

py

Python

blog/admin.py

ChaoFanMa01/my_site

29c2598a835c10684669e9ae66af641cdaf22ec4

[ "MIT" ]

null

blog/admin.py

ChaoFanMa01/my_site

29c2598a835c10684669e9ae66af641cdaf22ec4

[ "MIT" ]

null

blog/admin.py

ChaoFanMa01/my_site

29c2598a835c10684669e9ae66af641cdaf22ec4

[ "MIT" ]

null

from django.contrib import admin from .models import Category, Tag, Article, Photo # Register your models here. admin.site.register([Category, Tag, Article, Photo])

23.857143

52

0.772455

23

167

5.608696

0.608696

0.170543

0.27907

0.356589

0

0.131737

167

6

53

27.833333

0.889655

0.155689

0

1

0

true

0

0.666667

0

0.666667

0

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null

0

1

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1

0

null

0

1

0

1

0

1

0

7

607e40bfe05ecd3bd9ea77d8fc0169f7d8fdd226

67

py

Python

bare_python/s09_imutable_hashable.py

AndreiHondrari/python_exploration

cb4ac0b92ddc48c322201ba31cd6e7c5ee6af06d

[ "MIT" ]

3

2019-05-04T12:19:09.000Z

2019-08-30T07:12:31.000Z

bare_python/s09_imutable_hashable.py

AndreiHondrari/python_exploration

cb4ac0b92ddc48c322201ba31cd6e7c5ee6af06d

[ "MIT" ]

null

bare_python/s09_imutable_hashable.py

AndreiHondrari/python_exploration

cb4ac0b92ddc48c322201ba31cd6e7c5ee6af06d

[ "MIT" ]

null

#!python3 d = {} d[(1, 1)] = 10 d[(1, 2)] = 22 print(d[(1, 1)])

7.444444

16

0.38806

14

67

1.857143

0.5

0.230769

0

0.22

0.253731

67

8

17

8.375

0.3

0.119403

0

1

0

false

0

0.25

1

0

1

null

1

0

1

0

1

0

1

0

null

0

7

6081369ec4615005de695e0b430b124d664fa420

459

py

Python

Exercicios Python/ex108/moeda.py

ClaudioSiqueira/Exercicios-Python

128387769b34b7d42aee5c1effda16de21216e10

[ "MIT" ]

null

Exercicios Python/ex108/moeda.py

ClaudioSiqueira/Exercicios-Python

128387769b34b7d42aee5c1effda16de21216e10

[ "MIT" ]

null

Exercicios Python/ex108/moeda.py

ClaudioSiqueira/Exercicios-Python

128387769b34b7d42aee5c1effda16de21216e10

[ "MIT" ]

null

def metade(preco): res = preco/2 return res def aumentar(preco, taxa): res = preco + (preco * taxa/100) return res def diminuir(preco, taxa): res = preco - (preco * taxa/100) return res def dobro(preco): res = preco * 2 return res def formatacao(preco = 0, moeda = 'R$'): return f'{moeda}{preco:.2f}'.replace('.', ',') '''def moeda(preco = 0, moeda = 'R$'): return f'{moeda}{preco:.2f}'.replace('.', ',')'''

16.392857

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459

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0.124031

0.186047

0.108527

0.813953

0.612403

0

0.034483

0.24183

459

27

54

17

0.706897

0

0.285714

0

0.059946

0

1

0.357143

false

0

0.071429

0.714286

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

6098fc5172555c9cd0c34d258d49b8b070454c4f

278

py

Python

PythonExercicios/ex016.py

VitorFRodrigues/Python-curso

af75ff4a7ca14bc7e67b4f3362af837d355b1746

[ "MIT" ]

null

PythonExercicios/ex016.py

VitorFRodrigues/Python-curso

af75ff4a7ca14bc7e67b4f3362af837d355b1746

[ "MIT" ]

null

PythonExercicios/ex016.py

VitorFRodrigues/Python-curso

af75ff4a7ca14bc7e67b4f3362af837d355b1746

[ "MIT" ]

null

from math import trunc num = float(input('Digite um número com casas decimais: ')) print('O número {} tem a parte inteira {}'.format(num, trunc(num))) num = float(input('Digite um número com casas decimais: ')) print('O número {} tem a parte inteira {}'.format(num, int(num)))

39.714286

67

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278

4.386364

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0.082902

0.134715

0.196891

0.829016

0

0.147482

278

6

68

46.333333

0.814346

0

0.4

0

0.510791

0

1

0

false

0

0.2

0

0.2

0.4

0

null

0

1

0

1

0

null

0

8

88127f0da0b70ec2910993f5aba2f5a8b14997a3

9,335

py

Python

models/ac_simple.py

praveeenbadimala/flow_unsupervised

07385fd45e9213c06acacfd891e116f07993575e

[ "MIT" ]

null

models/ac_simple.py

praveeenbadimala/flow_unsupervised

07385fd45e9213c06acacfd891e116f07993575e

[ "MIT" ]

null

models/ac_simple.py

praveeenbadimala/flow_unsupervised

07385fd45e9213c06acacfd891e116f07993575e

[ "MIT" ]

null

import torch import torch.nn as nn from torch.nn.init import kaiming_normal def conv(batchNorm, in_planes, out_planes, kernel_size=3, stride=1): if batchNorm: return nn.Sequential( nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=(kernel_size-1)//2, bias=False), nn.BatchNorm2d(out_planes), nn.LeakyReLU(0.1,inplace=True) ) else: return nn.Sequential( nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=(kernel_size-1)//2, bias=True), nn.LeakyReLU(0.1,inplace=True) ) def predict_flow(in_planes): return nn.Conv2d(in_planes,2,kernel_size=3,stride=1,padding=1,bias=False) def deconv(in_planes, out_planes): return nn.Sequential( nn.ConvTranspose2d(in_planes, out_planes, kernel_size=4, stride=2, padding=1, bias=False), nn.LeakyReLU(0.1,inplace=True) ) def crop_like(input, target): if input.size()[2:] == target.size()[2:]: return input else: return input[:, :, :target.size(2), :target.size(3)] class Actor(nn.Module): expansion = 1 def __init__(self,batchNorm=True): super(Actor,self).__init__() self.batchNorm = batchNorm self.conv1 = conv(self.batchNorm, 6, 64, kernel_size=7, stride=2) self.conv2 = conv(self.batchNorm, 64, 128, kernel_size=5, stride=2) self.conv3 = conv(self.batchNorm, 128, 256, kernel_size=5, stride=2) self.conv3_1 = conv(self.batchNorm, 256, 256) self.conv4 = conv(self.batchNorm, 256, 512, stride=2) self.conv4_1 = conv(self.batchNorm, 512, 512) self.conv5 = conv(self.batchNorm, 512, 512, stride=2) self.conv5_1 = conv(self.batchNorm, 512, 512) self.conv6 = conv(self.batchNorm, 512, 1024, stride=2) self.conv6_1 = conv(self.batchNorm,1024, 1024) self.deconv5 = deconv(1024,512) self.deconv4 = deconv(1026,256) self.deconv3 = deconv(770,128) self.deconv2 = deconv(386,64) self.predict_flow6 = predict_flow(1024) self.predict_flow5 = predict_flow(1026) self.predict_flow4 = predict_flow(770) self.predict_flow3 = predict_flow(386) self.predict_flow2 = predict_flow(194) self.upsampled_flow6_to_5 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow5_to_4 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow4_to_3 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow3_to_2 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): kaiming_normal(m.weight.data) if m.bias is not None: m.bias.data.zero_() elif isinstance(m, nn.BatchNorm2d): m.weight.data.fill_(1) m.bias.data.zero_() def forward(self, x): out_conv2 = self.conv2(self.conv1(x)) out_conv3 = self.conv3_1(self.conv3(out_conv2)) out_conv4 = self.conv4_1(self.conv4(out_conv3)) out_conv5 = self.conv5_1(self.conv5(out_conv4)) out_conv6 = self.conv6_1(self.conv6(out_conv5)) flow6 = self.predict_flow6(out_conv6) flow6_up = crop_like(self.upsampled_flow6_to_5(flow6), out_conv5) out_deconv5 = crop_like(self.deconv5(out_conv6), out_conv5) concat5 = torch.cat((out_conv5,out_deconv5,flow6_up),1) flow5 = self.predict_flow5(concat5) flow5_up = crop_like(self.upsampled_flow5_to_4(flow5), out_conv4) out_deconv4 = crop_like(self.deconv4(concat5), out_conv4) concat4 = torch.cat((out_conv4,out_deconv4,flow5_up),1) flow4 = self.predict_flow4(concat4) flow4_up = crop_like(self.upsampled_flow4_to_3(flow4), out_conv3) out_deconv3 = crop_like(self.deconv3(concat4), out_conv3) concat3 = torch.cat((out_conv3,out_deconv3,flow4_up),1) flow3 = self.predict_flow3(concat3) flow3_up = crop_like(self.upsampled_flow3_to_2(flow3), out_conv2) out_deconv2 = crop_like(self.deconv2(concat3), out_conv2) concat2 = torch.cat((out_conv2,out_deconv2,flow3_up),1) flow2 = self.predict_flow2(concat2) return flow2 def weight_parameters(self): return [param for name, param in self.named_parameters() if 'weight' in name] def bias_parameters(self): return [param for name, param in self.named_parameters() if 'bias' in name] class Critic(nn.Module): expansion = 1 def __init__(self,batchNorm=True): super(Critic,self).__init__() self.batchNorm = batchNorm self.conv1 = conv(self.batchNorm, 8, 64, kernel_size=7, stride=2) self.conv2 = conv(self.batchNorm, 64, 128, kernel_size=5, stride=2) self.conv3 = conv(self.batchNorm, 128, 256, kernel_size=5, stride=2) self.conv3_1 = conv(self.batchNorm, 256, 256) self.conv4 = conv(self.batchNorm, 256, 512, stride=2) self.conv4_1 = conv(self.batchNorm, 512, 512) self.conv5 = conv(self.batchNorm, 512, 512, stride=2) self.conv5_1 = conv(self.batchNorm, 512, 512) self.conv6 = conv(self.batchNorm, 512, 1024, stride=2) self.conv6_1 = conv(self.batchNorm,1024, 1024) self.deconv5 = deconv(1024,512) self.deconv4 = deconv(1026,256) self.deconv3 = deconv(770,128) self.deconv2 = deconv(386,64) self.predict_flow6 = predict_flow(1024) self.predict_flow5 = predict_flow(1026) self.predict_flow4 = predict_flow(770) self.predict_flow3 = predict_flow(386) self.predict_flow2 = predict_flow(194) self.upsampled_flow6_to_5 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow5_to_4 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow4_to_3 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) self.upsampled_flow3_to_2 = nn.ConvTranspose2d(2, 2, 4, 2, 1, bias=False) for m in self.modules(): if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d): kaiming_normal(m.weight.data) if m.bias is not None: m.bias.data.zero_() elif isinstance(m, nn.BatchNorm2d): m.weight.data.fill_(1) m.bias.data.zero_() def forward(self, x): out_conv2 = self.conv2(self.conv1(x)) out_conv3 = self.conv3_1(self.conv3(out_conv2)) out_conv4 = self.conv4_1(self.conv4(out_conv3)) out_conv5 = self.conv5_1(self.conv5(out_conv4)) out_conv6 = self.conv6_1(self.conv6(out_conv5)) flow6 = self.predict_flow6(out_conv6) flow6_up = crop_like(self.upsampled_flow6_to_5(flow6), out_conv5) out_deconv5 = crop_like(self.deconv5(out_conv6), out_conv5) concat5 = torch.cat((out_conv5,out_deconv5,flow6_up),1) flow5 = self.predict_flow5(concat5) flow5_up = crop_like(self.upsampled_flow5_to_4(flow5), out_conv4) out_deconv4 = crop_like(self.deconv4(concat5), out_conv4) concat4 = torch.cat((out_conv4,out_deconv4,flow5_up),1) flow4 = self.predict_flow4(concat4) flow4_up = crop_like(self.upsampled_flow4_to_3(flow4), out_conv3) out_deconv3 = crop_like(self.deconv3(concat4), out_conv3) concat3 = torch.cat((out_conv3,out_deconv3,flow4_up),1) flow3 = self.predict_flow3(concat3) flow3_up = crop_like(self.upsampled_flow3_to_2(flow3), out_conv2) out_deconv2 = crop_like(self.deconv2(concat3), out_conv2) concat2 = torch.cat((out_conv2,out_deconv2,flow3_up),1) flow2 = self.predict_flow2(concat2) expected_energy = flow2.sum(3).sum(2).sum(1) return expected_energy def weight_parameters(self): return [param for name, param in self.named_parameters() if 'weight' in name] def bias_parameters(self): return [param for name, param in self.named_parameters() if 'bias' in name] def ActorLoad(path=None): """FlowNetS model architecture from the "Learning Optical Flow with Convolutional Networks" paper (https://arxiv.org/abs/1504.06852) Args: path : where to load pretrained network of actor network. will create a new one if not set """ model = Actor(batchNorm=False) if path is not None: data = torch.load(path) if 'state_dict' in data.keys(): model.load_state_dict(data['state_dict']) else: model.load_state_dict(data) return model def CriticLoad(path=None): """FlowNetS model architecture from the "Learning Optical Flow with Convolutional Networks" paper (https://arxiv.org/abs/1504.06852) Args: path : where to load pretrained network of critic network. will create a new one if not set """ model = Critic(batchNorm=False) if path is not None: data = torch.load(path) if 'state_dict' in data.keys(): model.load_state_dict(data['state_dict']) else: model.load_state_dict(data) return model

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40.942982

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7156a86935cb4bb72cc786923e60807d77cb0eab

15,122

py

Python

Along_isopycnal_property_values.py

UBC-MOAD/analysis_saurav_wcvi

16a348a3a828b04f20cac019a3ef1f1476ae9c4e

[ "Apache-2.0" ]

null

Along_isopycnal_property_values.py

UBC-MOAD/analysis_saurav_wcvi

16a348a3a828b04f20cac019a3ef1f1476ae9c4e

[ "Apache-2.0" ]

null

Along_isopycnal_property_values.py

UBC-MOAD/analysis_saurav_wcvi

16a348a3a828b04f20cac019a3ef1f1476ae9c4e

[ "Apache-2.0" ]

null

import numpy as np import netCDF4 as nc from scipy.interpolate import interp1d NEP_aug = nc.Dataset('/home/ssahu/saurav/NEP36_T_S_Spice_aug.nc') sal_aug = NEP_aug.variables['vosaline'] temp_aug = NEP_aug.variables['votemper'] spic_aug = NEP_aug.variables['spiciness'] rho_aug = NEP_aug.variables['density'] zlevels = nc.Dataset('/data/mdunphy/NEP036-N30-OUT/CDF_COMB_COMPRESSED/NEP036-N30_IN_20140915_00001440_grid_T.nc').variables['deptht'] mesh_mask = nc.Dataset('/data/mdunphy/NEP036-N30-OUT/INV/mesh_mask.nc') mbathy = mesh_mask['mbathy'][0,...] NEP_jul = nc.Dataset('/home/ssahu/saurav/NEP36_T_S_Spice_july.nc') sal_jul = NEP_jul.variables['vosaline'] temp_jul = NEP_jul.variables['votemper'] spic_jul = NEP_jul.variables['spiciness'] rho_jul = NEP_jul.variables['density'] y_wcvi_slice = np.arange(230,350) x_wcvi_slice = np.arange(550,650) #znew = np.arange(0,150,0.1) #dens_cont = np.arange(25.,27.,0.25/8.) #tol = 0.001 #spic_iso = np.empty((rho_jul.shape[0],dens_cont.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) #rho_iso = np.empty((rho_jul.shape[0],dens_cont.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) #temp_iso = np.empty((rho_jul.shape[0],dens_cont.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) #sal_iso = np.empty((rho_jul.shape[0],dens_cont.shape[0],y_wcvi_slice.shape[0],y_wcvi_slice.shape[0])) #t =12 znew = np.arange(0,250,0.05) den = np.arange(23.,28.,0.1) tol = 0.01 #rho_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) #spic_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) #rho_0 = rho_jul[t,:,y_wcvi_slice,x_wcvi_slice] - 1000 #spic_0 = spic_jul[t,:,y_wcvi_slice,x_wcvi_slice] spic_time_iso = np.empty((spic_jul.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_time_iso = np.empty((spic_jul.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_time_iso = np.empty((spic_jul.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for t in np.arange(spic_time_iso.shape[0]): rho_0 = rho_jul[t,:,y_wcvi_slice,x_wcvi_slice] - 1000 spic_0 = spic_jul[t,:,y_wcvi_slice,x_wcvi_slice] tem_0 = temp_jul[t,:,y_wcvi_slice,x_wcvi_slice] sal_0 = sal_jul[t,:,y_wcvi_slice,x_wcvi_slice] spic_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for iso in np.arange(den.shape[0]): spic_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for j in np.arange(y_wcvi_slice.shape[0]): spic_iso = np.empty(x_wcvi_slice.shape[0]) sal_iso = np.empty(x_wcvi_slice.shape[0]) tem_iso = np.empty(x_wcvi_slice.shape[0]) rho_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) spic_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) tem_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) sal_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) for i in np.arange(rho_new.shape[1]): f = interp1d(zlevels[:],rho_0[:,j,i],fill_value='extrapolate') g = interp1d(zlevels[:],spic_0[:,j,i],fill_value='extrapolate') h = interp1d(zlevels[:],tem_0[:,j,i],fill_value='extrapolate') p = interp1d(zlevels[:],sal_0[:,j,i],fill_value='extrapolate') rho_new[:,i] = f(znew[:]) spic_new[:,i] = g(znew[:]) tem_new[:,i] = h(znew[:]) sal_new[:,i] = p(znew[:]) V = rho_new[:,i] ind = (V>den[iso]-tol)&(V<den[iso]+tol) spic_iso[i] = np.nanmean(spic_new[ind,i]) tem_iso[i] = np.nanmean(tem_new[ind,i]) sal_iso[i] = np.nanmean(sal_new[ind,i]) spic_den[j,i] = spic_iso[i] tem_den[j,i] = tem_iso[i] sal_den[j,i] = sal_iso[i] spic_spec_iso[iso,j,i] = spic_den[j,i] tem_spec_iso[iso,j,i] = tem_den[j,i] sal_spec_iso[iso,j,i] = sal_den[j,i] spic_time_iso[t,iso,j,i] = spic_spec_iso[iso,j,i] tem_time_iso[t,iso,j,i] = tem_spec_iso[iso,j,i] sal_time_iso[t,iso,j,i] = sal_spec_iso[iso,j,i] print("Calculating the depths of the isopycnals (in July) for 3D plots") depth_rho_0 = np.empty((sal_time_iso[...].shape[0],sal_time_iso.shape[1],rho_jul.shape[2],rho_jul.shape[3])) for t in np.arange(spic_time_iso.shape[0]): for iso in np.arange(den.shape[0]): for j in np.arange(230,350): for i in np.arange(550,650): if mbathy[j,i] > 0: depth_rho_0[t,iso,j, i] = np.interp(den[iso], rho_jul[t,:mbathy[j, i], j, i]-1000, zlevels[:mbathy[j, i]]) depth_rho = np.empty_like(sal_time_iso[...]) depth_rho = depth_rho_0[:,:,y_wcvi_slice,x_wcvi_slice] #for den in np.arange(dens_cont.shape[0]): # for t in np.arange(rho_jul.shape[0]): # for j in np.arange(y_wcvi_slice.shape[0]): # # for i in np.arange(y_wcvi_slice.shape[0]): # # print(i) #Choose the data slice in x-z # rho_0 = rho_jul[t,:,j,x_wcvi_slice] - 1000 # spic_0 = spic_jul[t,:,j,x_wcvi_slice] # temp_0 = temp_jul[t,:,j,x_wcvi_slice] # sal_0 = sal_jul[t,:,j,x_wcvi_slice] # # # initialise the shapes of the variables# # rho_new = np.empty((znew.shape[0],rho_0.shape[1])) # spic_new = np.empty((znew.shape[0],rho_0.shape[1])) # temp_new = np.empty((znew.shape[0],rho_0.shape[1])) # sal_new = np.empty((znew.shape[0],rho_0.shape[1])) # ind = np.empty((znew.shape[0],rho_0.shape[1])) # Interpolate over z to choose the exact values of z for the isopycnals # f = interp1d(zlevels[:],rho_0[:,i],fill_value='extrapolate') # g = interp1d(zlevels[:],spic_0[:,i],fill_value='extrapolate') # h = interp1d(zlevels[:],temp_0[:,i],fill_value='extrapolate') # wine = interp1d(zlevels[:],sal_0[:,i],fill_value='extrapolate') # # # find the values of the variables at the fine z resolutions # # # rho_new[:,i] = f(znew[:]) # spic_new[:,i] = g(znew[:]) # temp_new[:,i] = h(znew[:]) # sal_new[:,i] = wine(znew[:]) # # # find the indices which relate to those isopycnal values in x and z from a created boolean masked tuple ind # # V = rho_new # ind = np.where((V>dens_cont[den]-tol)&(V<dens_cont[den]+tol)) # # edit the intialised array with the values returned from the isopycnal indices # spic_iso[t,den,j,i] = spic_new[ind[0][:],ind[1][:]] # rho_iso[t,den,j,i] = rho_new[ind[0][:],ind[1][:]] # temp_iso[t,den,j,i] = temp_new[ind[0][:],ind[1][:]] # sal_iso[t,den,j,i] = sal_new[ind[0][:],ind[1][:]] print("Writing the isopycnal data for July") path_to_save = '/home/ssahu/saurav/' bdy_file = nc.Dataset(path_to_save + 'NEP36_jul_along_isopycnal.nc', 'w', zlib=True); bdy_file.createDimension('x', spic_time_iso.shape[3]); bdy_file.createDimension('y', spic_time_iso.shape[2]); bdy_file.createDimension('isot', spic_time_iso.shape[1]); bdy_file.createDimension('time_counter', None); x = bdy_file.createVariable('x', 'int32', ('x',), zlib=True); x.units = 'indices'; x.longname = 'x indices of NEP36'; y = bdy_file.createVariable('y', 'int32', ('y',), zlib=True); y.units = 'indices'; y.longname = 'y indices of NEP36'; isot = bdy_file.createVariable('isot', 'float32', ('isot',), zlib=True); isot.units = 'm'; isot.longname = 'Vertical isopycnal Levels'; time_counter = bdy_file.createVariable('time_counter', 'int32', ('time_counter',), zlib=True); time_counter.units = 's'; time_counter.longname = 'time'; spiciness = bdy_file.createVariable('spiciness', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) temperature = bdy_file.createVariable('temperature', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) salinity = bdy_file.createVariable('salinity', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) zdepth_of_isopycnal = bdy_file.createVariable('Depth of Isopycnal', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) #density = bdy_file.createVariable('density', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) spiciness[...] = spic_time_iso[...]; temperature[...] = tem_time_iso[...]; salinity[...] = sal_time_iso[...]; zdepth_of_isopycnal[...] = depth_rho[...] #density[...] = rho_iso[...]; isot[...] = den[:]; x[...] = x_wcvi_slice[:]; y[...] = y_wcvi_slice[:]; bdy_file.close() print("File for July Written: Thanks") print("Starting interpolation and data extraction for August") spic_time_iso = np.empty((spic_aug.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_time_iso = np.empty((spic_aug.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_time_iso = np.empty((spic_aug.shape[0],den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for t in np.arange(spic_time_iso.shape[0]): rho_0 = rho_aug[t,:,y_wcvi_slice,x_wcvi_slice] - 1000 spic_0 = spic_aug[t,:,y_wcvi_slice,x_wcvi_slice] tem_0 = temp_aug[t,:,y_wcvi_slice,x_wcvi_slice] sal_0 = sal_aug[t,:,y_wcvi_slice,x_wcvi_slice] spic_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_spec_iso = np.empty((den.shape[0],y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for iso in np.arange(den.shape[0]): spic_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) tem_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) sal_den = np.empty((y_wcvi_slice.shape[0],x_wcvi_slice.shape[0])) for j in np.arange(y_wcvi_slice.shape[0]): spic_iso = np.empty(x_wcvi_slice.shape[0]) sal_iso = np.empty(x_wcvi_slice.shape[0]) tem_iso = np.empty(x_wcvi_slice.shape[0]) rho_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) spic_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) tem_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) sal_new = np.empty((znew.shape[0],x_wcvi_slice.shape[0])) for i in np.arange(rho_new.shape[1]): f = interp1d(zlevels[:],rho_0[:,j,i],fill_value='extrapolate') g = interp1d(zlevels[:],spic_0[:,j,i],fill_value='extrapolate') h = interp1d(zlevels[:],tem_0[:,j,i],fill_value='extrapolate') p = interp1d(zlevels[:],sal_0[:,j,i],fill_value='extrapolate') rho_new[:,i] = f(znew[:]) spic_new[:,i] = g(znew[:]) tem_new[:,i] = h(znew[:]) sal_new[:,i] = p(znew[:]) V = rho_new[:,i] ind = (V>den[iso]-tol)&(V<den[iso]+tol) spic_iso[i] = np.nanmean(spic_new[ind,i]) tem_iso[i] = np.nanmean(tem_new[ind,i]) sal_iso[i] = np.nanmean(sal_new[ind,i]) spic_den[j,i] = spic_iso[i] tem_den[j,i] = tem_iso[i] sal_den[j,i] = sal_iso[i] spic_spec_iso[iso,j,i] = spic_den[j,i] tem_spec_iso[iso,j,i] = tem_den[j,i] sal_spec_iso[iso,j,i] = sal_den[j,i] spic_time_iso[t,iso,j,i] = spic_spec_iso[iso,j,i] tem_time_iso[t,iso,j,i] = tem_spec_iso[iso,j,i] sal_time_iso[t,iso,j,i] = sal_spec_iso[iso,j,i] print("Calculating the depths of the isopycnals (in August) for 3D plots") depth_rho_0 = np.empty((sal_time_iso[...].shape[0],sal_time_iso.shape[1],rho_jul.shape[2],rho_jul.shape[3])) for t in np.arange(spic_time_iso.shape[0]): for iso in np.arange(den.shape[0]): for j in np.arange(230,350): for i in np.arange(550,650): if mbathy[j,i] > 0: depth_rho_0[t,iso,j, i] = np.interp(den[iso], rho_aug[t,:mbathy[j, i], j, i]-1000, zlevels[:mbathy[j, i]]) depth_rho = np.empty_like(sal_time_iso[...]) depth_rho = depth_rho_0[:,:,y_wcvi_slice,x_wcvi_slice] print("Writing the isopycnal data for August") path_to_save = '/home/ssahu/saurav/' bdy_file = nc.Dataset(path_to_save + 'NEP36_aug_along_isopycnal.nc', 'w', zlib=True); bdy_file.createDimension('x', spic_time_iso.shape[3]); bdy_file.createDimension('y', spic_time_iso.shape[2]); bdy_file.createDimension('isot', spic_time_iso.shape[1]); bdy_file.createDimension('time_counter', None); x = bdy_file.createVariable('x', 'int32', ('x',), zlib=True); x.units = 'indices'; x.longname = 'x indices of NEP36'; y = bdy_file.createVariable('y', 'int32', ('y',), zlib=True); y.units = 'indices'; y.longname = 'y indices of NEP36'; isot = bdy_file.createVariable('isot', 'float32', ('isot',), zlib=True); isot.units = 'm'; isot.longname = 'Vertical isopycnal Levels'; time_counter = bdy_file.createVariable('time_counter', 'int32', ('time_counter',), zlib=True); time_counter.units = 's'; time_counter.longname = 'time'; spiciness = bdy_file.createVariable('spiciness', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) temperature = bdy_file.createVariable('temperature', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) salinity = bdy_file.createVariable('salinity', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) zdepth_of_isopycnal = bdy_file.createVariable('Depth of Isopycnal', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) #density = bdy_file.createVariable('density', 'float32', ('time_counter','isot', 'y', 'x'), zlib=True) spiciness[...] = spic_time_iso[...]; temperature[...] = temp_time_iso[...]; salinity[...] = sal_time_iso[...]; zdepth_of_isopycnal[...] = depth_rho[...] #density[...] = rho_iso[...]; isot[...] = den[:]; x[...] = x_wcvi_slice[:]; y[...] = y_wcvi_slice[:]; bdy_file.close() print("File for August Written: Thanks")

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71775be0edc49973a6327889d79d8fb5ee3b89fd

103

py

Python

Exercicios-mundo-2/desafio049.py

talitadeoa/CEV-Exercicios-Python

11e8ad6c6b758c5b5fdf5050a3e97f98c308ea7e

[ "MIT" ]

null

Exercicios-mundo-2/desafio049.py

talitadeoa/CEV-Exercicios-Python

11e8ad6c6b758c5b5fdf5050a3e97f98c308ea7e

[ "MIT" ]

null

Exercicios-mundo-2/desafio049.py

talitadeoa/CEV-Exercicios-Python

11e8ad6c6b758c5b5fdf5050a3e97f98c308ea7e

[ "MIT" ]

null

#Refaça a tabuada do desafio 009 utilizando o laço for #kkk fiz o desafio 009 já utilizando o laço for

34.333333

54

0.786408

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103

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71b089167474786396993988893b5eadd6dc0f1d

33,499

py

Python

sdk/python/pulumi_gcp/billing/budget.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

[ "ECL-2.0", "Apache-2.0" ]

121

2018-06-18T19:16:42.000Z

2022-03-31T06:06:48.000Z

sdk/python/pulumi_gcp/billing/budget.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

[ "ECL-2.0", "Apache-2.0" ]

492

2018-06-22T19:41:03.000Z

2022-03-31T15:33:53.000Z

sdk/python/pulumi_gcp/billing/budget.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

[ "ECL-2.0", "Apache-2.0" ]

43

2018-06-19T01:43:13.000Z

2022-03-23T22:43:37.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['BudgetArgs', 'Budget'] @pulumi.input_type class BudgetArgs: def __init__(__self__, *, amount: pulumi.Input['BudgetAmountArgs'], billing_account: pulumi.Input[str], threshold_rules: pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]], all_updates_rule: Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']] = None, budget_filter: Optional[pulumi.Input['BudgetBudgetFilterArgs']] = None, display_name: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a Budget resource. :param pulumi.Input['BudgetAmountArgs'] amount: The budgeted amount for each usage period. Structure is documented below. :param pulumi.Input[str] billing_account: ID of the billing account to set a budget on. :param pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]] threshold_rules: Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. :param pulumi.Input['BudgetAllUpdatesRuleArgs'] all_updates_rule: Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. :param pulumi.Input['BudgetBudgetFilterArgs'] budget_filter: Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. :param pulumi.Input[str] display_name: User data for display name in UI. Must be <= 60 chars. """ pulumi.set(__self__, "amount", amount) pulumi.set(__self__, "billing_account", billing_account) pulumi.set(__self__, "threshold_rules", threshold_rules) if all_updates_rule is not None: pulumi.set(__self__, "all_updates_rule", all_updates_rule) if budget_filter is not None: pulumi.set(__self__, "budget_filter", budget_filter) if display_name is not None: pulumi.set(__self__, "display_name", display_name) @property @pulumi.getter def amount(self) -> pulumi.Input['BudgetAmountArgs']: """ The budgeted amount for each usage period. Structure is documented below. """ return pulumi.get(self, "amount") @amount.setter def amount(self, value: pulumi.Input['BudgetAmountArgs']): pulumi.set(self, "amount", value) @property @pulumi.getter(name="billingAccount") def billing_account(self) -> pulumi.Input[str]: """ ID of the billing account to set a budget on. """ return pulumi.get(self, "billing_account") @billing_account.setter def billing_account(self, value: pulumi.Input[str]): pulumi.set(self, "billing_account", value) @property @pulumi.getter(name="thresholdRules") def threshold_rules(self) -> pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]]: """ Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ return pulumi.get(self, "threshold_rules") @threshold_rules.setter def threshold_rules(self, value: pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]]): pulumi.set(self, "threshold_rules", value) @property @pulumi.getter(name="allUpdatesRule") def all_updates_rule(self) -> Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']]: """ Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. """ return pulumi.get(self, "all_updates_rule") @all_updates_rule.setter def all_updates_rule(self, value: Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']]): pulumi.set(self, "all_updates_rule", value) @property @pulumi.getter(name="budgetFilter") def budget_filter(self) -> Optional[pulumi.Input['BudgetBudgetFilterArgs']]: """ Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. """ return pulumi.get(self, "budget_filter") @budget_filter.setter def budget_filter(self, value: Optional[pulumi.Input['BudgetBudgetFilterArgs']]): pulumi.set(self, "budget_filter", value) @property @pulumi.getter(name="displayName") def display_name(self) -> Optional[pulumi.Input[str]]: """ User data for display name in UI. Must be <= 60 chars. """ return pulumi.get(self, "display_name") @display_name.setter def display_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "display_name", value) @pulumi.input_type class _BudgetState: def __init__(__self__, *, all_updates_rule: Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']] = None, amount: Optional[pulumi.Input['BudgetAmountArgs']] = None, billing_account: Optional[pulumi.Input[str]] = None, budget_filter: Optional[pulumi.Input['BudgetBudgetFilterArgs']] = None, display_name: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, threshold_rules: Optional[pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]]] = None): """ Input properties used for looking up and filtering Budget resources. :param pulumi.Input['BudgetAllUpdatesRuleArgs'] all_updates_rule: Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. :param pulumi.Input['BudgetAmountArgs'] amount: The budgeted amount for each usage period. Structure is documented below. :param pulumi.Input[str] billing_account: ID of the billing account to set a budget on. :param pulumi.Input['BudgetBudgetFilterArgs'] budget_filter: Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. :param pulumi.Input[str] display_name: User data for display name in UI. Must be <= 60 chars. :param pulumi.Input[str] name: Resource name of the budget. The resource name implies the scope of a budget. Values are of the form billingAccounts/{billingAccountId}/budgets/{budgetId}. :param pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]] threshold_rules: Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ if all_updates_rule is not None: pulumi.set(__self__, "all_updates_rule", all_updates_rule) if amount is not None: pulumi.set(__self__, "amount", amount) if billing_account is not None: pulumi.set(__self__, "billing_account", billing_account) if budget_filter is not None: pulumi.set(__self__, "budget_filter", budget_filter) if display_name is not None: pulumi.set(__self__, "display_name", display_name) if name is not None: pulumi.set(__self__, "name", name) if threshold_rules is not None: pulumi.set(__self__, "threshold_rules", threshold_rules) @property @pulumi.getter(name="allUpdatesRule") def all_updates_rule(self) -> Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']]: """ Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. """ return pulumi.get(self, "all_updates_rule") @all_updates_rule.setter def all_updates_rule(self, value: Optional[pulumi.Input['BudgetAllUpdatesRuleArgs']]): pulumi.set(self, "all_updates_rule", value) @property @pulumi.getter def amount(self) -> Optional[pulumi.Input['BudgetAmountArgs']]: """ The budgeted amount for each usage period. Structure is documented below. """ return pulumi.get(self, "amount") @amount.setter def amount(self, value: Optional[pulumi.Input['BudgetAmountArgs']]): pulumi.set(self, "amount", value) @property @pulumi.getter(name="billingAccount") def billing_account(self) -> Optional[pulumi.Input[str]]: """ ID of the billing account to set a budget on. """ return pulumi.get(self, "billing_account") @billing_account.setter def billing_account(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "billing_account", value) @property @pulumi.getter(name="budgetFilter") def budget_filter(self) -> Optional[pulumi.Input['BudgetBudgetFilterArgs']]: """ Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. """ return pulumi.get(self, "budget_filter") @budget_filter.setter def budget_filter(self, value: Optional[pulumi.Input['BudgetBudgetFilterArgs']]): pulumi.set(self, "budget_filter", value) @property @pulumi.getter(name="displayName") def display_name(self) -> Optional[pulumi.Input[str]]: """ User data for display name in UI. Must be <= 60 chars. """ return pulumi.get(self, "display_name") @display_name.setter def display_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "display_name", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Resource name of the budget. The resource name implies the scope of a budget. Values are of the form billingAccounts/{billingAccountId}/budgets/{budgetId}. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="thresholdRules") def threshold_rules(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]]]: """ Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ return pulumi.get(self, "threshold_rules") @threshold_rules.setter def threshold_rules(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['BudgetThresholdRuleArgs']]]]): pulumi.set(self, "threshold_rules", value) class Budget(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, all_updates_rule: Optional[pulumi.Input[pulumi.InputType['BudgetAllUpdatesRuleArgs']]] = None, amount: Optional[pulumi.Input[pulumi.InputType['BudgetAmountArgs']]] = None, billing_account: Optional[pulumi.Input[str]] = None, budget_filter: Optional[pulumi.Input[pulumi.InputType['BudgetBudgetFilterArgs']]] = None, display_name: Optional[pulumi.Input[str]] = None, threshold_rules: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['BudgetThresholdRuleArgs']]]]] = None, __props__=None): """ Budget configuration for a billing account. To get more information about Budget, see: * [API documentation](https://cloud.google.com/billing/docs/reference/budget/rest/v1/billingAccounts.budgets) * How-to Guides * [Creating a budget](https://cloud.google.com/billing/docs/how-to/budgets) > **Warning:** If you are using User ADCs (Application Default Credentials) with this resource, you must specify a `billing_project` and set `user_project_override` to true in the provider configuration. Otherwise the Billing Budgets API will return a 403 error. Your account must have the `serviceusage.services.use` permission on the `billing_project` you defined. ## Example Usage ### Billing Budget Basic ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.5, )]) ``` ### Billing Budget Lastperiod ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], ), amount=gcp.billing.BudgetAmountArgs( last_period_amount=True, ), threshold_rules=[gcp.billing.BudgetThresholdRuleArgs( threshold_percent=10, )]) ``` ### Billing Budget Filter ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], credit_types_treatment="EXCLUDE_ALL_CREDITS", services=["services/24E6-581D-38E5"], ), amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[ gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.5, ), gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.9, spend_basis="FORECASTED_SPEND", ), ]) ``` ### Billing Budget Notify ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() notification_channel = gcp.monitoring.NotificationChannel("notificationChannel", display_name="Example Notification Channel", type="email", labels={ "email_address": "address@example.com", }) budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], ), amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[ gcp.billing.BudgetThresholdRuleArgs( threshold_percent=1, ), gcp.billing.BudgetThresholdRuleArgs( threshold_percent=1, spend_basis="FORECASTED_SPEND", ), ], all_updates_rule=gcp.billing.BudgetAllUpdatesRuleArgs( monitoring_notification_channels=[notification_channel.id], disable_default_iam_recipients=True, )) ``` ## Import Budget can be imported using any of these accepted formats ```sh $ pulumi import gcp:billing/budget:Budget default billingAccounts/{{billing_account}}/budgets/{{name}} ``` ```sh $ pulumi import gcp:billing/budget:Budget default {{billing_account}}/{{name}} ``` ```sh $ pulumi import gcp:billing/budget:Budget default {{name}} ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[pulumi.InputType['BudgetAllUpdatesRuleArgs']] all_updates_rule: Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. :param pulumi.Input[pulumi.InputType['BudgetAmountArgs']] amount: The budgeted amount for each usage period. Structure is documented below. :param pulumi.Input[str] billing_account: ID of the billing account to set a budget on. :param pulumi.Input[pulumi.InputType['BudgetBudgetFilterArgs']] budget_filter: Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. :param pulumi.Input[str] display_name: User data for display name in UI. Must be <= 60 chars. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['BudgetThresholdRuleArgs']]]] threshold_rules: Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ ... @overload def __init__(__self__, resource_name: str, args: BudgetArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Budget configuration for a billing account. To get more information about Budget, see: * [API documentation](https://cloud.google.com/billing/docs/reference/budget/rest/v1/billingAccounts.budgets) * How-to Guides * [Creating a budget](https://cloud.google.com/billing/docs/how-to/budgets) > **Warning:** If you are using User ADCs (Application Default Credentials) with this resource, you must specify a `billing_project` and set `user_project_override` to true in the provider configuration. Otherwise the Billing Budgets API will return a 403 error. Your account must have the `serviceusage.services.use` permission on the `billing_project` you defined. ## Example Usage ### Billing Budget Basic ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.5, )]) ``` ### Billing Budget Lastperiod ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], ), amount=gcp.billing.BudgetAmountArgs( last_period_amount=True, ), threshold_rules=[gcp.billing.BudgetThresholdRuleArgs( threshold_percent=10, )]) ``` ### Billing Budget Filter ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], credit_types_treatment="EXCLUDE_ALL_CREDITS", services=["services/24E6-581D-38E5"], ), amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[ gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.5, ), gcp.billing.BudgetThresholdRuleArgs( threshold_percent=0.9, spend_basis="FORECASTED_SPEND", ), ]) ``` ### Billing Budget Notify ```python import pulumi import pulumi_gcp as gcp account = gcp.organizations.get_billing_account(billing_account="000000-0000000-0000000-000000") project = gcp.organizations.get_project() notification_channel = gcp.monitoring.NotificationChannel("notificationChannel", display_name="Example Notification Channel", type="email", labels={ "email_address": "address@example.com", }) budget = gcp.billing.Budget("budget", billing_account=account.id, display_name="Example Billing Budget", budget_filter=gcp.billing.BudgetBudgetFilterArgs( projects=[f"projects/{project.number}"], ), amount=gcp.billing.BudgetAmountArgs( specified_amount=gcp.billing.BudgetAmountSpecifiedAmountArgs( currency_code="USD", units="100000", ), ), threshold_rules=[ gcp.billing.BudgetThresholdRuleArgs( threshold_percent=1, ), gcp.billing.BudgetThresholdRuleArgs( threshold_percent=1, spend_basis="FORECASTED_SPEND", ), ], all_updates_rule=gcp.billing.BudgetAllUpdatesRuleArgs( monitoring_notification_channels=[notification_channel.id], disable_default_iam_recipients=True, )) ``` ## Import Budget can be imported using any of these accepted formats ```sh $ pulumi import gcp:billing/budget:Budget default billingAccounts/{{billing_account}}/budgets/{{name}} ``` ```sh $ pulumi import gcp:billing/budget:Budget default {{billing_account}}/{{name}} ``` ```sh $ pulumi import gcp:billing/budget:Budget default {{name}} ``` :param str resource_name: The name of the resource. :param BudgetArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(BudgetArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, all_updates_rule: Optional[pulumi.Input[pulumi.InputType['BudgetAllUpdatesRuleArgs']]] = None, amount: Optional[pulumi.Input[pulumi.InputType['BudgetAmountArgs']]] = None, billing_account: Optional[pulumi.Input[str]] = None, budget_filter: Optional[pulumi.Input[pulumi.InputType['BudgetBudgetFilterArgs']]] = None, display_name: Optional[pulumi.Input[str]] = None, threshold_rules: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['BudgetThresholdRuleArgs']]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = BudgetArgs.__new__(BudgetArgs) __props__.__dict__["all_updates_rule"] = all_updates_rule if amount is None and not opts.urn: raise TypeError("Missing required property 'amount'") __props__.__dict__["amount"] = amount if billing_account is None and not opts.urn: raise TypeError("Missing required property 'billing_account'") __props__.__dict__["billing_account"] = billing_account __props__.__dict__["budget_filter"] = budget_filter __props__.__dict__["display_name"] = display_name if threshold_rules is None and not opts.urn: raise TypeError("Missing required property 'threshold_rules'") __props__.__dict__["threshold_rules"] = threshold_rules __props__.__dict__["name"] = None super(Budget, __self__).__init__( 'gcp:billing/budget:Budget', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, all_updates_rule: Optional[pulumi.Input[pulumi.InputType['BudgetAllUpdatesRuleArgs']]] = None, amount: Optional[pulumi.Input[pulumi.InputType['BudgetAmountArgs']]] = None, billing_account: Optional[pulumi.Input[str]] = None, budget_filter: Optional[pulumi.Input[pulumi.InputType['BudgetBudgetFilterArgs']]] = None, display_name: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, threshold_rules: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['BudgetThresholdRuleArgs']]]]] = None) -> 'Budget': """ Get an existing Budget resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[pulumi.InputType['BudgetAllUpdatesRuleArgs']] all_updates_rule: Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. :param pulumi.Input[pulumi.InputType['BudgetAmountArgs']] amount: The budgeted amount for each usage period. Structure is documented below. :param pulumi.Input[str] billing_account: ID of the billing account to set a budget on. :param pulumi.Input[pulumi.InputType['BudgetBudgetFilterArgs']] budget_filter: Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. :param pulumi.Input[str] display_name: User data for display name in UI. Must be <= 60 chars. :param pulumi.Input[str] name: Resource name of the budget. The resource name implies the scope of a budget. Values are of the form billingAccounts/{billingAccountId}/budgets/{budgetId}. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['BudgetThresholdRuleArgs']]]] threshold_rules: Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _BudgetState.__new__(_BudgetState) __props__.__dict__["all_updates_rule"] = all_updates_rule __props__.__dict__["amount"] = amount __props__.__dict__["billing_account"] = billing_account __props__.__dict__["budget_filter"] = budget_filter __props__.__dict__["display_name"] = display_name __props__.__dict__["name"] = name __props__.__dict__["threshold_rules"] = threshold_rules return Budget(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="allUpdatesRule") def all_updates_rule(self) -> pulumi.Output[Optional['outputs.BudgetAllUpdatesRule']]: """ Defines notifications that are sent on every update to the billing account's spend, regardless of the thresholds defined using threshold rules. Structure is documented below. """ return pulumi.get(self, "all_updates_rule") @property @pulumi.getter def amount(self) -> pulumi.Output['outputs.BudgetAmount']: """ The budgeted amount for each usage period. Structure is documented below. """ return pulumi.get(self, "amount") @property @pulumi.getter(name="billingAccount") def billing_account(self) -> pulumi.Output[str]: """ ID of the billing account to set a budget on. """ return pulumi.get(self, "billing_account") @property @pulumi.getter(name="budgetFilter") def budget_filter(self) -> pulumi.Output['outputs.BudgetBudgetFilter']: """ Filters that define which resources are used to compute the actual spend against the budget. Structure is documented below. """ return pulumi.get(self, "budget_filter") @property @pulumi.getter(name="displayName") def display_name(self) -> pulumi.Output[Optional[str]]: """ User data for display name in UI. Must be <= 60 chars. """ return pulumi.get(self, "display_name") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ Resource name of the budget. The resource name implies the scope of a budget. Values are of the form billingAccounts/{billingAccountId}/budgets/{budgetId}. """ return pulumi.get(self, "name") @property @pulumi.getter(name="thresholdRules") def threshold_rules(self) -> pulumi.Output[Sequence['outputs.BudgetThresholdRule']]: """ Rules that trigger alerts (notifications of thresholds being crossed) when spend exceeds the specified percentages of the budget. Structure is documented below. """ return pulumi.get(self, "threshold_rules")

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71c2a7eeb383ff66b2a35eddd0ae1a31ca4e7701

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Python

visualizations/ch5-results/gtex_barcharts.py

arnegebert/splicing

3e19ce83a9f6d98bc6c2d8b653660d22e453ca77

[ "MIT" ]

1

2021-05-13T15:30:39.000Z

visualizations/ch5-results/gtex_barcharts.py

arnegebert/splicing

3e19ce83a9f6d98bc6c2d8b653660d22e453ca77

[ "MIT" ]

null

visualizations/ch5-results/gtex_barcharts.py

arnegebert/splicing

3e19ce83a9f6d98bc6c2d8b653660d22e453ca77

[ "MIT" ]

null

import matplotlib.pyplot as plt from sklearn.metrics import roc_curve, auc import numpy as np def bar_charts_exons(): plt.style.use('seaborn') with_extra_random_guessing_plot = False # can be further fine-tuned; either 0.5 from start or I include baseline model labels = ['DSC', 'D2V', 'RASC'] brain_means = [0.664, 0.617, 0.645] cerebellum_means = [0.649, 0.610, 0.631] heart_means = [0.657, 0.604, 0.627] brain_stds = [0.011, 0.010, 0.022] cerebellum_stds = [0.008, 0.008, 0.029] heart_stds = [0.016, 0.009, 0.014] x = np.arange(len(brain_means)) # the label locations width = 0.2 # the width of the bars fig, ax = plt.subplots() rects1 = ax.bar(x - width, brain_means, width, yerr=brain_stds, label='Brain cortex') rects2 = ax.bar(x, cerebellum_means, width, yerr=cerebellum_stds, label='Cerebellum') rects3 = ax.bar(x + width, heart_means, width, yerr=heart_stds, label='Heart') # ax.set_title('AUC and inverse number of weights by model') ax.set_xticks(np.arange(len(labels))) ax.set_ylim(0.5, 1) ax.set_ylabel('AUC') ax.set_xticklabels(labels) ax.legend() def autolabel(rects, labels=None, stds=None): """Attach a text label above each bar in *rects*, displaying its height.""" for i, rect in enumerate(rects): label = labels[i] if labels else rect.get_height() height = rect.get_height() if label == '1/20,000': continue y_label = height + 0.02 if not stds else height + stds[i]*0.7 + 0.002 ax.annotate(f'{label}', xy=(rect.get_x() + rect.get_width() / 2, y_label), xytext=(0, 3), # 3 points vertical offset textcoords="offset points", ha='center', va='bottom') autolabel(rects1, stds=brain_stds) autolabel(rects2, stds=cerebellum_stds) autolabel(rects3, stds=heart_stds) if with_extra_random_guessing_plot: labels.append('Random guessing') ax.bar(x - width, 0.5, width, color='gray') ax.bar(x, 0.5, width, color='gray') ax.bar(x + width, 0.5, width, color='gray') baseline_x = max(x) + 1 width2 = 0.3 rect4 = ax.bar(baseline_x, 0.5, width2, color='grey') autolabel(rect4) ax.axhline(y=0.5, color='gray') fig.tight_layout() plt.savefig('gtex_exon_barcharts.png', dpi=300, bbox_inches='tight') plt.show() def bar_charts_juncs(): plt.style.use('seaborn') with_extra_random_guessing_plot = False # can be further fine-tuned; either 0.5 from start or I include baseline model labels = ['DSC', 'D2V', 'RASC'] brain_means = [0.699, 0.671, 0.810] cerebellum_means = [0.704, 0.673, 0.808] heart_means = [0.699, 0.677, 0.807] brain_stds = [0.006, 0.003, 0.012] cerebellum_stds = [0.006, 0.004, 0.008] heart_stds = [0.008, 0.005, 0.013] x = np.arange(len(brain_means)) # the label locations width = 0.2 # the width of the bars fig, ax = plt.subplots() rects1 = ax.bar(x - width, brain_means, width, yerr=brain_stds, label='Brain cortex') rects2 = ax.bar(x, cerebellum_means, width, yerr=cerebellum_stds, label='Cerebellum') rects3 = ax.bar(x + width, heart_means, width, yerr=heart_stds, label='Heart') # ax.set_title('AUC and inverse number of weights by model') ax.set_xticks(np.arange(len(labels))) ax.set_ylim(0.5, 1) ax.set_ylabel('AUC') ax.set_xticklabels(labels) ax.legend() def autolabel(rects, labels=None, stds=None): """Attach a text label above each bar in *rects*, displaying its height.""" for i, rect in enumerate(rects): label = labels[i] if labels else rect.get_height() height = rect.get_height() if label == '1/20,000': continue y_label = height + 0.02 if not stds else height + stds[i]*0.7 + 0.002 ax.annotate(f'{label}', xy=(rect.get_x() + rect.get_width() / 2, y_label), xytext=(0, 3), # 3 points vertical offset textcoords="offset points", ha='center', va='bottom') autolabel(rects1, stds=brain_stds) autolabel(rects2, stds=cerebellum_stds) autolabel(rects3, stds=heart_stds) if with_extra_random_guessing_plot: labels.append('Random guessing') ax.bar(x - width, 0.5, width, color='gray') ax.bar(x, 0.5, width, color='gray') ax.bar(x + width, 0.5, width, color='gray') baseline_x = max(x) + 1 width2 = 0.3 rect4 = ax.bar(baseline_x, 0.5, width2, color='grey') autolabel(rect4) ax.axhline(y=0.5, color='gray') fig.tight_layout() plt.savefig('gtex_junc_barcharts.png', dpi=300, bbox_inches='tight') plt.show() if __name__ == '__main__': bar_charts_exons() bar_charts_juncs()

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71ce2d71bdb625e6aa93c6ea9878613f3cb9972a

2,515

py

Python

ietf/group/migrations/0004_auto_20150430_0847.py

ekr/ietfdb

8d936836b0b9ff31cda415b0a423e3f5b33ab695

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

2

2021-11-20T03:40:40.000Z

2021-11-20T03:40:42.000Z

ietf/group/migrations/0004_auto_20150430_0847.py

ekr/ietfdb

8d936836b0b9ff31cda415b0a423e3f5b33ab695

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

null

ietf/group/migrations/0004_auto_20150430_0847.py

ekr/ietfdb

8d936836b0b9ff31cda415b0a423e3f5b33ab695

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('group', '0003_auto_20150304_0743'), ] operations = [ migrations.AlterField( model_name='group', name='unused_states', field=models.ManyToManyField(help_text=b'Document states that have been disabled for the group.', to='doc.State', blank=True), preserve_default=True, ), migrations.AlterField( model_name='group', name='unused_tags', field=models.ManyToManyField(help_text=b'Document tags that have been disabled for the group.', to='name.DocTagName', blank=True), preserve_default=True, ), migrations.AlterField( model_name='grouphistory', name='unused_states', field=models.ManyToManyField(help_text=b'Document states that have been disabled for the group.', to='doc.State', blank=True), preserve_default=True, ), migrations.AlterField( model_name='grouphistory', name='unused_tags', field=models.ManyToManyField(help_text=b'Document tags that have been disabled for the group.', to='name.DocTagName', blank=True), preserve_default=True, ), migrations.AlterField( model_name='groupmilestone', name='resolved', field=models.CharField(help_text=b'Explanation of why milestone is resolved (usually "Done"), or empty if still due.', max_length=50, blank=True), preserve_default=True, ), migrations.AlterField( model_name='groupmilestonehistory', name='resolved', field=models.CharField(help_text=b'Explanation of why milestone is resolved (usually "Done"), or empty if still due.', max_length=50, blank=True), preserve_default=True, ), migrations.AlterField( model_name='role', name='email', field=models.ForeignKey(help_text=b'Email address used by person for this role.', to='person.Email'), preserve_default=True, ), migrations.AlterField( model_name='rolehistory', name='email', field=models.ForeignKey(help_text=b'Email address used by person for this role.', to='person.Email'), preserve_default=True, ), ]

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0.132538

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0.864148

0.819085

0

0.011564

0.277932

2,515

62

159

40.564516

0.819383

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0

0.785714

0

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0.017657

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false

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0

null

0

1

0

1

0

null

0

7

461723455604d9ac8342f3d56333b77671c52bba

987,467

py

Python

cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_asic_errors_oper.py

bopopescu/ACI

dd717bc74739eeed4747b3ea9e36b239580df5e1

[ "ECL-2.0", "Apache-2.0" ]

null

cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_asic_errors_oper.py

bopopescu/ACI

dd717bc74739eeed4747b3ea9e36b239580df5e1

[ "ECL-2.0", "Apache-2.0" ]

null

cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_asic_errors_oper.py

bopopescu/ACI

dd717bc74739eeed4747b3ea9e36b239580df5e1

[ "ECL-2.0", "Apache-2.0" ]

1

2020-07-22T04:04:44.000Z

""" Cisco_IOS_XR_asic_errors_oper This module contains a collection of YANG definitions for Cisco IOS\-XR asic\-errors package operational data. This module contains definitions for the following management objects\: asic\-errors\: Error summary of all asics Copyright (c) 2013\-2017 by Cisco Systems, Inc. All rights reserved. """ from collections import OrderedDict from ydk.types import Entity, EntityPath, Identity, Enum, YType, YLeaf, YLeafList, YList, LeafDataList, Bits, Empty, Decimal64 from ydk.filters import YFilter from ydk.errors import YError, YModelError from ydk.errors.error_handler import handle_type_error as _handle_type_error class AsicErrors(Entity): """ Error summary of all asics .. attribute:: nodes Asic errors for each available nodes **type**\: :py:class:`Nodes <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors, self).__init__() self._top_entity = None self.yang_name = "asic-errors" self.yang_parent_name = "Cisco-IOS-XR-asic-errors-oper" self.is_top_level_class = True self.has_list_ancestor = False self.ylist_key_names = [] self._child_container_classes = OrderedDict([("nodes", ("nodes", AsicErrors.Nodes))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict() self.nodes = AsicErrors.Nodes() self.nodes.parent = self self._children_name_map["nodes"] = "nodes" self._children_yang_names.add("nodes") self._segment_path = lambda: "Cisco-IOS-XR-asic-errors-oper:asic-errors" class Nodes(Entity): """ Asic errors for each available nodes .. attribute:: node Asic error for a particular node **type**\: list of :py:class:`Node <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes, self).__init__() self.yang_name = "nodes" self.yang_parent_name = "asic-errors" self.is_top_level_class = False self.has_list_ancestor = False self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("node", ("node", AsicErrors.Nodes.Node))]) self._leafs = OrderedDict() self.node = YList(self) self._segment_path = lambda: "nodes" self._absolute_path = lambda: "Cisco-IOS-XR-asic-errors-oper:asic-errors/%s" % self._segment_path() def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes, [], name, value) class Node(Entity): """ Asic error for a particular node .. attribute:: node_name (key) Node ID **type**\: str **pattern:** ([a\-zA\-Z0\-9\_]\*\\d+/){1,2}([a\-zA\-Z0\-9\_]\*\\d+) .. attribute:: asic_information Asic on the node **type**\: list of :py:class:`AsicInformation <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node, self).__init__() self.yang_name = "node" self.yang_parent_name = "nodes" self.is_top_level_class = False self.has_list_ancestor = False self.ylist_key_names = ['node_name'] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("asic-information", ("asic_information", AsicErrors.Nodes.Node.AsicInformation))]) self._leafs = OrderedDict([ ('node_name', YLeaf(YType.str, 'node-name')), ]) self.node_name = None self.asic_information = YList(self) self._segment_path = lambda: "node" + "[node-name='" + str(self.node_name) + "']" self._absolute_path = lambda: "Cisco-IOS-XR-asic-errors-oper:asic-errors/nodes/%s" % self._segment_path() def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node, ['node_name'], name, value) class AsicInformation(Entity): """ Asic on the node .. attribute:: asic (key) Asic string **type**\: str **pattern:** [\\w\\\-\\.\:,\_@#%$\\+=\\\|;]+ .. attribute:: all_instances All asic instance on the node **type**\: :py:class:`AllInstances <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.AllInstances>` .. attribute:: instances All asic errors on the node **type**\: :py:class:`Instances <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation, self).__init__() self.yang_name = "asic-information" self.yang_parent_name = "node" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = ['asic'] self._child_container_classes = OrderedDict([("all-instances", ("all_instances", AsicErrors.Nodes.Node.AsicInformation.AllInstances)), ("instances", ("instances", AsicErrors.Nodes.Node.AsicInformation.Instances))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('asic', YLeaf(YType.str, 'asic')), ]) self.asic = None self.all_instances = AsicErrors.Nodes.Node.AsicInformation.AllInstances() self.all_instances.parent = self self._children_name_map["all_instances"] = "all-instances" self._children_yang_names.add("all-instances") self.instances = AsicErrors.Nodes.Node.AsicInformation.Instances() self.instances.parent = self self._children_name_map["instances"] = "instances" self._children_yang_names.add("instances") self._segment_path = lambda: "asic-information" + "[asic='" + str(self.asic) + "']" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation, ['asic'], name, value) class AllInstances(Entity): """ All asic instance on the node .. attribute:: all_error_path Error path of all instances **type**\: :py:class:`AllErrorPath <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.AllInstances, self).__init__() self.yang_name = "all-instances" self.yang_parent_name = "asic-information" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([("all-error-path", ("all_error_path", AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict() self.all_error_path = AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath() self.all_error_path.parent = self self._children_name_map["all_error_path"] = "all-error-path" self._children_yang_names.add("all-error-path") self._segment_path = lambda: "all-instances" class AllErrorPath(Entity): """ Error path of all instances .. attribute:: summary Summary of all instances errors **type**\: :py:class:`Summary <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath, self).__init__() self.yang_name = "all-error-path" self.yang_parent_name = "all-instances" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([("summary", ("summary", AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict() self.summary = AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary() self.summary.parent = self self._children_name_map["summary"] = "summary" self._children_yang_names.add("summary") self._segment_path = lambda: "all-error-path" class Summary(Entity): """ Summary of all instances errors .. attribute:: legacy_client legacy client **type**\: bool .. attribute:: cih_client cih client **type**\: bool .. attribute:: sum_data sum data **type**\: list of :py:class:`SumData <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary.SumData>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary, self).__init__() self.yang_name = "summary" self.yang_parent_name = "all-error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("sum-data", ("sum_data", AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary.SumData))]) self._leafs = OrderedDict([ ('legacy_client', YLeaf(YType.boolean, 'legacy-client')), ('cih_client', YLeaf(YType.boolean, 'cih-client')), ]) self.legacy_client = None self.cih_client = None self.sum_data = YList(self) self._segment_path = lambda: "summary" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary, ['legacy_client', 'cih_client'], name, value) class SumData(Entity): """ sum data .. attribute:: num_nodes num nodes **type**\: int **range:** 0..4294967295 .. attribute:: crc_err_count crc err count **type**\: int **range:** 0..4294967295 .. attribute:: sbe_err_count sbe err count **type**\: int **range:** 0..4294967295 .. attribute:: mbe_err_count mbe err count **type**\: int **range:** 0..4294967295 .. attribute:: par_err_count par err count **type**\: int **range:** 0..4294967295 .. attribute:: gen_err_count gen err count **type**\: int **range:** 0..4294967295 .. attribute:: reset_err_count reset err count **type**\: int **range:** 0..4294967295 .. attribute:: err_count err count **type**\: list of int **range:** 0..4294967295 .. attribute:: pcie_err_count pcie err count **type**\: list of int **range:** 0..4294967295 .. attribute:: node_key node key **type**\: list of int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary.SumData, self).__init__() self.yang_name = "sum-data" self.yang_parent_name = "summary" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('num_nodes', YLeaf(YType.uint32, 'num-nodes')), ('crc_err_count', YLeaf(YType.uint32, 'crc-err-count')), ('sbe_err_count', YLeaf(YType.uint32, 'sbe-err-count')), ('mbe_err_count', YLeaf(YType.uint32, 'mbe-err-count')), ('par_err_count', YLeaf(YType.uint32, 'par-err-count')), ('gen_err_count', YLeaf(YType.uint32, 'gen-err-count')), ('reset_err_count', YLeaf(YType.uint32, 'reset-err-count')), ('err_count', YLeafList(YType.uint32, 'err-count')), ('pcie_err_count', YLeafList(YType.uint32, 'pcie-err-count')), ('node_key', YLeafList(YType.uint32, 'node-key')), ]) self.num_nodes = None self.crc_err_count = None self.sbe_err_count = None self.mbe_err_count = None self.par_err_count = None self.gen_err_count = None self.reset_err_count = None self.err_count = [] self.pcie_err_count = [] self.node_key = [] self._segment_path = lambda: "sum-data" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.AllInstances.AllErrorPath.Summary.SumData, ['num_nodes', 'crc_err_count', 'sbe_err_count', 'mbe_err_count', 'par_err_count', 'gen_err_count', 'reset_err_count', 'err_count', 'pcie_err_count', 'node_key'], name, value) class Instances(Entity): """ All asic errors on the node .. attribute:: instance Particular asic instance on the node **type**\: list of :py:class:`Instance <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances, self).__init__() self.yang_name = "instances" self.yang_parent_name = "asic-information" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("instance", ("instance", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance))]) self._leafs = OrderedDict() self.instance = YList(self) self._segment_path = lambda: "instances" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances, [], name, value) class Instance(Entity): """ Particular asic instance on the node .. attribute:: asic_instance (key) asic instance **type**\: int **range:** \-2147483648..2147483647 .. attribute:: error_path Error path of the instances **type**\: :py:class:`ErrorPath <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance, self).__init__() self.yang_name = "instance" self.yang_parent_name = "instances" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = ['asic_instance'] self._child_container_classes = OrderedDict([("error-path", ("error_path", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('asic_instance', YLeaf(YType.int32, 'asic-instance')), ]) self.asic_instance = None self.error_path = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath() self.error_path.parent = self self._children_name_map["error_path"] = "error-path" self._children_yang_names.add("error-path") self._segment_path = lambda: "instance" + "[asic-instance='" + str(self.asic_instance) + "']" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance, ['asic_instance'], name, value) class ErrorPath(Entity): """ Error path of the instances .. attribute:: multiple_bit_soft_errors Multiple bit soft error information **type**\: :py:class:`MultipleBitSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors>` .. attribute:: asic_error_generic_soft Indirect hard error information **type**\: :py:class:`AsicErrorGenericSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft>` .. attribute:: crc_hard_errors CRC hard error information **type**\: :py:class:`CrcHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors>` .. attribute:: asic_error_sbe_soft Indirect hard error information **type**\: :py:class:`AsicErrorSbeSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft>` .. attribute:: hardware_soft_errors Hardware soft error information **type**\: :py:class:`HardwareSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors>` .. attribute:: asic_error_crc_soft Indirect hard error information **type**\: :py:class:`AsicErrorCrcSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft>` .. attribute:: asic_error_parity_soft Indirect hard error information **type**\: :py:class:`AsicErrorParitySoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft>` .. attribute:: io_soft_errors IO soft error information **type**\: :py:class:`IoSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors>` .. attribute:: reset_soft_errors Reset soft error information **type**\: :py:class:`ResetSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors>` .. attribute:: barrier_hard_errors Barrier hard error information **type**\: :py:class:`BarrierHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors>` .. attribute:: ucode_soft_errors Ucode soft error information **type**\: :py:class:`UcodeSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors>` .. attribute:: asic_error_reset_hard Indirect hard error information **type**\: :py:class:`AsicErrorResetHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard>` .. attribute:: single_bit_hard_errors Single bit hard error information **type**\: :py:class:`SingleBitHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors>` .. attribute:: indirect_hard_errors Indirect hard error information **type**\: :py:class:`IndirectHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors>` .. attribute:: outof_resource_soft OOR thresh information **type**\: :py:class:`OutofResourceSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft>` .. attribute:: crc_soft_errors CRC soft error information **type**\: :py:class:`CrcSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors>` .. attribute:: time_out_hard_errors Time out hard error information **type**\: :py:class:`TimeOutHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors>` .. attribute:: barrier_soft_errors Barrier soft error information **type**\: :py:class:`BarrierSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors>` .. attribute:: asic_error_mbe_soft Indirect hard error information **type**\: :py:class:`AsicErrorMbeSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft>` .. attribute:: back_pressure_hard_errors BP hard error information **type**\: :py:class:`BackPressureHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors>` .. attribute:: single_bit_soft_errors Single bit soft error information **type**\: :py:class:`SingleBitSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors>` .. attribute:: indirect_soft_errors Indirect soft error information **type**\: :py:class:`IndirectSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors>` .. attribute:: generic_hard_errors Generic hard error information **type**\: :py:class:`GenericHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors>` .. attribute:: link_hard_errors Link hard error information **type**\: :py:class:`LinkHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors>` .. attribute:: configuration_hard_errors Configuration hard error information **type**\: :py:class:`ConfigurationHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors>` .. attribute:: instance_summary Summary for a specific instance **type**\: :py:class:`InstanceSummary <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary>` .. attribute:: unexpected_hard_errors Unexpected hard error information **type**\: :py:class:`UnexpectedHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors>` .. attribute:: time_out_soft_errors Time out soft error information **type**\: :py:class:`TimeOutSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors>` .. attribute:: asic_error_generic_hard Indirect hard error information **type**\: :py:class:`AsicErrorGenericHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard>` .. attribute:: parity_hard_errors Parity hard error information **type**\: :py:class:`ParityHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors>` .. attribute:: descriptor_hard_errors Descriptor hard error information **type**\: :py:class:`DescriptorHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors>` .. attribute:: interface_hard_errors Interface hard error information **type**\: :py:class:`InterfaceHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors>` .. attribute:: asic_error_sbe_hard Indirect hard error information **type**\: :py:class:`AsicErrorSbeHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard>` .. attribute:: asic_error_crc_hard Indirect hard error information **type**\: :py:class:`AsicErrorCrcHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard>` .. attribute:: asic_error_parity_hard Indirect hard error information **type**\: :py:class:`AsicErrorParityHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard>` .. attribute:: asic_error_reset_soft Indirect hard error information **type**\: :py:class:`AsicErrorResetSoft <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft>` .. attribute:: back_pressure_soft_errors BP soft error information **type**\: :py:class:`BackPressureSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors>` .. attribute:: generic_soft_errors Generic soft error information **type**\: :py:class:`GenericSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors>` .. attribute:: link_soft_errors Link soft error information **type**\: :py:class:`LinkSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors>` .. attribute:: configuration_soft_errors Configuration soft error information **type**\: :py:class:`ConfigurationSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors>` .. attribute:: multiple_bit_hard_errors Multiple bit hard error information **type**\: :py:class:`MultipleBitHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors>` .. attribute:: unexpected_soft_errors Unexpected soft error information **type**\: :py:class:`UnexpectedSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors>` .. attribute:: outof_resource_hard OOR thresh information **type**\: :py:class:`OutofResourceHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard>` .. attribute:: hardware_hard_errors Hardware hard error information **type**\: :py:class:`HardwareHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors>` .. attribute:: parity_soft_errors Parity soft error information **type**\: :py:class:`ParitySoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors>` .. attribute:: descriptor_soft_errors Descriptor soft error information **type**\: :py:class:`DescriptorSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors>` .. attribute:: interface_soft_errors Interface soft error information **type**\: :py:class:`InterfaceSoftErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors>` .. attribute:: io_hard_errors IO hard error information **type**\: :py:class:`IoHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors>` .. attribute:: reset_hard_errors Reset hard error information **type**\: :py:class:`ResetHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors>` .. attribute:: ucode_hard_errors UCode hard error information **type**\: :py:class:`UcodeHardErrors <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors>` .. attribute:: asic_error_mbe_hard Indirect hard error information **type**\: :py:class:`AsicErrorMbeHard <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath, self).__init__() self.yang_name = "error-path" self.yang_parent_name = "instance" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([("multiple-bit-soft-errors", ("multiple_bit_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors)), ("asic-error-generic-soft", ("asic_error_generic_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft)), ("crc-hard-errors", ("crc_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors)), ("asic-error-sbe-soft", ("asic_error_sbe_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft)), ("hardware-soft-errors", ("hardware_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors)), ("asic-error-crc-soft", ("asic_error_crc_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft)), ("asic-error-parity-soft", ("asic_error_parity_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft)), ("io-soft-errors", ("io_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors)), ("reset-soft-errors", ("reset_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors)), ("barrier-hard-errors", ("barrier_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors)), ("ucode-soft-errors", ("ucode_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors)), ("asic-error-reset-hard", ("asic_error_reset_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard)), ("single-bit-hard-errors", ("single_bit_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors)), ("indirect-hard-errors", ("indirect_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors)), ("outof-resource-soft", ("outof_resource_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft)), ("crc-soft-errors", ("crc_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors)), ("time-out-hard-errors", ("time_out_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors)), ("barrier-soft-errors", ("barrier_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors)), ("asic-error-mbe-soft", ("asic_error_mbe_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft)), ("back-pressure-hard-errors", ("back_pressure_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors)), ("single-bit-soft-errors", ("single_bit_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors)), ("indirect-soft-errors", ("indirect_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors)), ("generic-hard-errors", ("generic_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors)), ("link-hard-errors", ("link_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors)), ("configuration-hard-errors", ("configuration_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors)), ("instance-summary", ("instance_summary", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary)), ("unexpected-hard-errors", ("unexpected_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors)), ("time-out-soft-errors", ("time_out_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors)), ("asic-error-generic-hard", ("asic_error_generic_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard)), ("parity-hard-errors", ("parity_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors)), ("descriptor-hard-errors", ("descriptor_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors)), ("interface-hard-errors", ("interface_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors)), ("asic-error-sbe-hard", ("asic_error_sbe_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard)), ("asic-error-crc-hard", ("asic_error_crc_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard)), ("asic-error-parity-hard", ("asic_error_parity_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard)), ("asic-error-reset-soft", ("asic_error_reset_soft", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft)), ("back-pressure-soft-errors", ("back_pressure_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors)), ("generic-soft-errors", ("generic_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors)), ("link-soft-errors", ("link_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors)), ("configuration-soft-errors", ("configuration_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors)), ("multiple-bit-hard-errors", ("multiple_bit_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors)), ("unexpected-soft-errors", ("unexpected_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors)), ("outof-resource-hard", ("outof_resource_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard)), ("hardware-hard-errors", ("hardware_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors)), ("parity-soft-errors", ("parity_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors)), ("descriptor-soft-errors", ("descriptor_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors)), ("interface-soft-errors", ("interface_soft_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors)), ("io-hard-errors", ("io_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors)), ("reset-hard-errors", ("reset_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors)), ("ucode-hard-errors", ("ucode_hard_errors", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors)), ("asic-error-mbe-hard", ("asic_error_mbe_hard", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard))]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict() self.multiple_bit_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors() self.multiple_bit_soft_errors.parent = self self._children_name_map["multiple_bit_soft_errors"] = "multiple-bit-soft-errors" self._children_yang_names.add("multiple-bit-soft-errors") self.asic_error_generic_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft() self.asic_error_generic_soft.parent = self self._children_name_map["asic_error_generic_soft"] = "asic-error-generic-soft" self._children_yang_names.add("asic-error-generic-soft") self.crc_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors() self.crc_hard_errors.parent = self self._children_name_map["crc_hard_errors"] = "crc-hard-errors" self._children_yang_names.add("crc-hard-errors") self.asic_error_sbe_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft() self.asic_error_sbe_soft.parent = self self._children_name_map["asic_error_sbe_soft"] = "asic-error-sbe-soft" self._children_yang_names.add("asic-error-sbe-soft") self.hardware_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors() self.hardware_soft_errors.parent = self self._children_name_map["hardware_soft_errors"] = "hardware-soft-errors" self._children_yang_names.add("hardware-soft-errors") self.asic_error_crc_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft() self.asic_error_crc_soft.parent = self self._children_name_map["asic_error_crc_soft"] = "asic-error-crc-soft" self._children_yang_names.add("asic-error-crc-soft") self.asic_error_parity_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft() self.asic_error_parity_soft.parent = self self._children_name_map["asic_error_parity_soft"] = "asic-error-parity-soft" self._children_yang_names.add("asic-error-parity-soft") self.io_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors() self.io_soft_errors.parent = self self._children_name_map["io_soft_errors"] = "io-soft-errors" self._children_yang_names.add("io-soft-errors") self.reset_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors() self.reset_soft_errors.parent = self self._children_name_map["reset_soft_errors"] = "reset-soft-errors" self._children_yang_names.add("reset-soft-errors") self.barrier_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors() self.barrier_hard_errors.parent = self self._children_name_map["barrier_hard_errors"] = "barrier-hard-errors" self._children_yang_names.add("barrier-hard-errors") self.ucode_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors() self.ucode_soft_errors.parent = self self._children_name_map["ucode_soft_errors"] = "ucode-soft-errors" self._children_yang_names.add("ucode-soft-errors") self.asic_error_reset_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard() self.asic_error_reset_hard.parent = self self._children_name_map["asic_error_reset_hard"] = "asic-error-reset-hard" self._children_yang_names.add("asic-error-reset-hard") self.single_bit_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors() self.single_bit_hard_errors.parent = self self._children_name_map["single_bit_hard_errors"] = "single-bit-hard-errors" self._children_yang_names.add("single-bit-hard-errors") self.indirect_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors() self.indirect_hard_errors.parent = self self._children_name_map["indirect_hard_errors"] = "indirect-hard-errors" self._children_yang_names.add("indirect-hard-errors") self.outof_resource_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft() self.outof_resource_soft.parent = self self._children_name_map["outof_resource_soft"] = "outof-resource-soft" self._children_yang_names.add("outof-resource-soft") self.crc_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors() self.crc_soft_errors.parent = self self._children_name_map["crc_soft_errors"] = "crc-soft-errors" self._children_yang_names.add("crc-soft-errors") self.time_out_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors() self.time_out_hard_errors.parent = self self._children_name_map["time_out_hard_errors"] = "time-out-hard-errors" self._children_yang_names.add("time-out-hard-errors") self.barrier_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors() self.barrier_soft_errors.parent = self self._children_name_map["barrier_soft_errors"] = "barrier-soft-errors" self._children_yang_names.add("barrier-soft-errors") self.asic_error_mbe_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft() self.asic_error_mbe_soft.parent = self self._children_name_map["asic_error_mbe_soft"] = "asic-error-mbe-soft" self._children_yang_names.add("asic-error-mbe-soft") self.back_pressure_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors() self.back_pressure_hard_errors.parent = self self._children_name_map["back_pressure_hard_errors"] = "back-pressure-hard-errors" self._children_yang_names.add("back-pressure-hard-errors") self.single_bit_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors() self.single_bit_soft_errors.parent = self self._children_name_map["single_bit_soft_errors"] = "single-bit-soft-errors" self._children_yang_names.add("single-bit-soft-errors") self.indirect_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors() self.indirect_soft_errors.parent = self self._children_name_map["indirect_soft_errors"] = "indirect-soft-errors" self._children_yang_names.add("indirect-soft-errors") self.generic_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors() self.generic_hard_errors.parent = self self._children_name_map["generic_hard_errors"] = "generic-hard-errors" self._children_yang_names.add("generic-hard-errors") self.link_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors() self.link_hard_errors.parent = self self._children_name_map["link_hard_errors"] = "link-hard-errors" self._children_yang_names.add("link-hard-errors") self.configuration_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors() self.configuration_hard_errors.parent = self self._children_name_map["configuration_hard_errors"] = "configuration-hard-errors" self._children_yang_names.add("configuration-hard-errors") self.instance_summary = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary() self.instance_summary.parent = self self._children_name_map["instance_summary"] = "instance-summary" self._children_yang_names.add("instance-summary") self.unexpected_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors() self.unexpected_hard_errors.parent = self self._children_name_map["unexpected_hard_errors"] = "unexpected-hard-errors" self._children_yang_names.add("unexpected-hard-errors") self.time_out_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors() self.time_out_soft_errors.parent = self self._children_name_map["time_out_soft_errors"] = "time-out-soft-errors" self._children_yang_names.add("time-out-soft-errors") self.asic_error_generic_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard() self.asic_error_generic_hard.parent = self self._children_name_map["asic_error_generic_hard"] = "asic-error-generic-hard" self._children_yang_names.add("asic-error-generic-hard") self.parity_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors() self.parity_hard_errors.parent = self self._children_name_map["parity_hard_errors"] = "parity-hard-errors" self._children_yang_names.add("parity-hard-errors") self.descriptor_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors() self.descriptor_hard_errors.parent = self self._children_name_map["descriptor_hard_errors"] = "descriptor-hard-errors" self._children_yang_names.add("descriptor-hard-errors") self.interface_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors() self.interface_hard_errors.parent = self self._children_name_map["interface_hard_errors"] = "interface-hard-errors" self._children_yang_names.add("interface-hard-errors") self.asic_error_sbe_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard() self.asic_error_sbe_hard.parent = self self._children_name_map["asic_error_sbe_hard"] = "asic-error-sbe-hard" self._children_yang_names.add("asic-error-sbe-hard") self.asic_error_crc_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard() self.asic_error_crc_hard.parent = self self._children_name_map["asic_error_crc_hard"] = "asic-error-crc-hard" self._children_yang_names.add("asic-error-crc-hard") self.asic_error_parity_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard() self.asic_error_parity_hard.parent = self self._children_name_map["asic_error_parity_hard"] = "asic-error-parity-hard" self._children_yang_names.add("asic-error-parity-hard") self.asic_error_reset_soft = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft() self.asic_error_reset_soft.parent = self self._children_name_map["asic_error_reset_soft"] = "asic-error-reset-soft" self._children_yang_names.add("asic-error-reset-soft") self.back_pressure_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors() self.back_pressure_soft_errors.parent = self self._children_name_map["back_pressure_soft_errors"] = "back-pressure-soft-errors" self._children_yang_names.add("back-pressure-soft-errors") self.generic_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors() self.generic_soft_errors.parent = self self._children_name_map["generic_soft_errors"] = "generic-soft-errors" self._children_yang_names.add("generic-soft-errors") self.link_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors() self.link_soft_errors.parent = self self._children_name_map["link_soft_errors"] = "link-soft-errors" self._children_yang_names.add("link-soft-errors") self.configuration_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors() self.configuration_soft_errors.parent = self self._children_name_map["configuration_soft_errors"] = "configuration-soft-errors" self._children_yang_names.add("configuration-soft-errors") self.multiple_bit_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors() self.multiple_bit_hard_errors.parent = self self._children_name_map["multiple_bit_hard_errors"] = "multiple-bit-hard-errors" self._children_yang_names.add("multiple-bit-hard-errors") self.unexpected_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors() self.unexpected_soft_errors.parent = self self._children_name_map["unexpected_soft_errors"] = "unexpected-soft-errors" self._children_yang_names.add("unexpected-soft-errors") self.outof_resource_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard() self.outof_resource_hard.parent = self self._children_name_map["outof_resource_hard"] = "outof-resource-hard" self._children_yang_names.add("outof-resource-hard") self.hardware_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors() self.hardware_hard_errors.parent = self self._children_name_map["hardware_hard_errors"] = "hardware-hard-errors" self._children_yang_names.add("hardware-hard-errors") self.parity_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors() self.parity_soft_errors.parent = self self._children_name_map["parity_soft_errors"] = "parity-soft-errors" self._children_yang_names.add("parity-soft-errors") self.descriptor_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors() self.descriptor_soft_errors.parent = self self._children_name_map["descriptor_soft_errors"] = "descriptor-soft-errors" self._children_yang_names.add("descriptor-soft-errors") self.interface_soft_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors() self.interface_soft_errors.parent = self self._children_name_map["interface_soft_errors"] = "interface-soft-errors" self._children_yang_names.add("interface-soft-errors") self.io_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors() self.io_hard_errors.parent = self self._children_name_map["io_hard_errors"] = "io-hard-errors" self._children_yang_names.add("io-hard-errors") self.reset_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors() self.reset_hard_errors.parent = self self._children_name_map["reset_hard_errors"] = "reset-hard-errors" self._children_yang_names.add("reset-hard-errors") self.ucode_hard_errors = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors() self.ucode_hard_errors.parent = self self._children_name_map["ucode_hard_errors"] = "ucode-hard-errors" self._children_yang_names.add("ucode-hard-errors") self.asic_error_mbe_hard = AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard() self.asic_error_mbe_hard.parent = self self._children_name_map["asic_error_mbe_hard"] = "asic-error-mbe-hard" self._children_yang_names.add("asic-error-mbe-hard") self._segment_path = lambda: "error-path" class MultipleBitSoftErrors(Entity): """ Multiple bit soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors, self).__init__() self.yang_name = "multiple-bit-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "multiple-bit-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "multiple-bit-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorGenericSoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft, self).__init__() self.yang_name = "asic-error-generic-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-generic-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-generic-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class CrcHardErrors(Entity): """ CRC hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors, self).__init__() self.yang_name = "crc-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "crc-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "crc-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorSbeSoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft, self).__init__() self.yang_name = "asic-error-sbe-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-sbe-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-sbe-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class HardwareSoftErrors(Entity): """ Hardware soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors, self).__init__() self.yang_name = "hardware-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "hardware-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "hardware-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorCrcSoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft, self).__init__() self.yang_name = "asic-error-crc-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-crc-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-crc-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorParitySoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft, self).__init__() self.yang_name = "asic-error-parity-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-parity-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-parity-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParitySoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class IoSoftErrors(Entity): """ IO soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors, self).__init__() self.yang_name = "io-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "io-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "io-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ResetSoftErrors(Entity): """ Reset soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors, self).__init__() self.yang_name = "reset-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "reset-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "reset-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class BarrierHardErrors(Entity): """ Barrier hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors, self).__init__() self.yang_name = "barrier-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "barrier-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "barrier-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class UcodeSoftErrors(Entity): """ Ucode soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors, self).__init__() self.yang_name = "ucode-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "ucode-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "ucode-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorResetHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard, self).__init__() self.yang_name = "asic-error-reset-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-reset-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-reset-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class SingleBitHardErrors(Entity): """ Single bit hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors, self).__init__() self.yang_name = "single-bit-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "single-bit-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "single-bit-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class IndirectHardErrors(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors, self).__init__() self.yang_name = "indirect-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "indirect-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "indirect-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class OutofResourceSoft(Entity): """ OOR thresh information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft, self).__init__() self.yang_name = "outof-resource-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "outof-resource-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "outof-resource-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class CrcSoftErrors(Entity): """ CRC soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors, self).__init__() self.yang_name = "crc-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "crc-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "crc-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.CrcSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class TimeOutHardErrors(Entity): """ Time out hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors, self).__init__() self.yang_name = "time-out-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "time-out-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "time-out-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class BarrierSoftErrors(Entity): """ Barrier soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors, self).__init__() self.yang_name = "barrier-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "barrier-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "barrier-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BarrierSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorMbeSoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft, self).__init__() self.yang_name = "asic-error-mbe-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-mbe-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-mbe-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class BackPressureHardErrors(Entity): """ BP hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors, self).__init__() self.yang_name = "back-pressure-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "back-pressure-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "back-pressure-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class SingleBitSoftErrors(Entity): """ Single bit soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors, self).__init__() self.yang_name = "single-bit-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "single-bit-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "single-bit-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.SingleBitSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class IndirectSoftErrors(Entity): """ Indirect soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors, self).__init__() self.yang_name = "indirect-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "indirect-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "indirect-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IndirectSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class GenericHardErrors(Entity): """ Generic hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors, self).__init__() self.yang_name = "generic-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "generic-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "generic-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class LinkHardErrors(Entity): """ Link hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors, self).__init__() self.yang_name = "link-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "link-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "link-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ConfigurationHardErrors(Entity): """ Configuration hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors, self).__init__() self.yang_name = "configuration-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "configuration-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "configuration-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class InstanceSummary(Entity): """ Summary for a specific instance .. attribute:: legacy_client legacy client **type**\: bool .. attribute:: cih_client cih client **type**\: bool .. attribute:: sum_data sum data **type**\: list of :py:class:`SumData <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary.SumData>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary, self).__init__() self.yang_name = "instance-summary" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("sum-data", ("sum_data", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary.SumData))]) self._leafs = OrderedDict([ ('legacy_client', YLeaf(YType.boolean, 'legacy-client')), ('cih_client', YLeaf(YType.boolean, 'cih-client')), ]) self.legacy_client = None self.cih_client = None self.sum_data = YList(self) self._segment_path = lambda: "instance-summary" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary, ['legacy_client', 'cih_client'], name, value) class SumData(Entity): """ sum data .. attribute:: num_nodes num nodes **type**\: int **range:** 0..4294967295 .. attribute:: crc_err_count crc err count **type**\: int **range:** 0..4294967295 .. attribute:: sbe_err_count sbe err count **type**\: int **range:** 0..4294967295 .. attribute:: mbe_err_count mbe err count **type**\: int **range:** 0..4294967295 .. attribute:: par_err_count par err count **type**\: int **range:** 0..4294967295 .. attribute:: gen_err_count gen err count **type**\: int **range:** 0..4294967295 .. attribute:: reset_err_count reset err count **type**\: int **range:** 0..4294967295 .. attribute:: err_count err count **type**\: list of int **range:** 0..4294967295 .. attribute:: pcie_err_count pcie err count **type**\: list of int **range:** 0..4294967295 .. attribute:: node_key node key **type**\: list of int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary.SumData, self).__init__() self.yang_name = "sum-data" self.yang_parent_name = "instance-summary" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('num_nodes', YLeaf(YType.uint32, 'num-nodes')), ('crc_err_count', YLeaf(YType.uint32, 'crc-err-count')), ('sbe_err_count', YLeaf(YType.uint32, 'sbe-err-count')), ('mbe_err_count', YLeaf(YType.uint32, 'mbe-err-count')), ('par_err_count', YLeaf(YType.uint32, 'par-err-count')), ('gen_err_count', YLeaf(YType.uint32, 'gen-err-count')), ('reset_err_count', YLeaf(YType.uint32, 'reset-err-count')), ('err_count', YLeafList(YType.uint32, 'err-count')), ('pcie_err_count', YLeafList(YType.uint32, 'pcie-err-count')), ('node_key', YLeafList(YType.uint32, 'node-key')), ]) self.num_nodes = None self.crc_err_count = None self.sbe_err_count = None self.mbe_err_count = None self.par_err_count = None self.gen_err_count = None self.reset_err_count = None self.err_count = [] self.pcie_err_count = [] self.node_key = [] self._segment_path = lambda: "sum-data" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InstanceSummary.SumData, ['num_nodes', 'crc_err_count', 'sbe_err_count', 'mbe_err_count', 'par_err_count', 'gen_err_count', 'reset_err_count', 'err_count', 'pcie_err_count', 'node_key'], name, value) class UnexpectedHardErrors(Entity): """ Unexpected hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors, self).__init__() self.yang_name = "unexpected-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "unexpected-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "unexpected-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class TimeOutSoftErrors(Entity): """ Time out soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors, self).__init__() self.yang_name = "time-out-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "time-out-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "time-out-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.TimeOutSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorGenericHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard, self).__init__() self.yang_name = "asic-error-generic-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-generic-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-generic-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorGenericHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ParityHardErrors(Entity): """ Parity hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors, self).__init__() self.yang_name = "parity-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "parity-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "parity-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParityHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class DescriptorHardErrors(Entity): """ Descriptor hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors, self).__init__() self.yang_name = "descriptor-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "descriptor-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "descriptor-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class InterfaceHardErrors(Entity): """ Interface hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors, self).__init__() self.yang_name = "interface-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "interface-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "interface-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorSbeHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard, self).__init__() self.yang_name = "asic-error-sbe-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-sbe-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-sbe-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorSbeHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorCrcHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard, self).__init__() self.yang_name = "asic-error-crc-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-crc-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-crc-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorCrcHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorParityHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard, self).__init__() self.yang_name = "asic-error-parity-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-parity-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-parity-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorParityHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorResetSoft(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft, self).__init__() self.yang_name = "asic-error-reset-soft" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-reset-soft" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-reset-soft" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorResetSoft.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class BackPressureSoftErrors(Entity): """ BP soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors, self).__init__() self.yang_name = "back-pressure-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "back-pressure-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "back-pressure-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.BackPressureSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class GenericSoftErrors(Entity): """ Generic soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors, self).__init__() self.yang_name = "generic-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "generic-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "generic-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.GenericSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class LinkSoftErrors(Entity): """ Link soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors, self).__init__() self.yang_name = "link-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "link-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "link-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.LinkSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ConfigurationSoftErrors(Entity): """ Configuration soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors, self).__init__() self.yang_name = "configuration-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "configuration-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "configuration-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ConfigurationSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class MultipleBitHardErrors(Entity): """ Multiple bit hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors, self).__init__() self.yang_name = "multiple-bit-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "multiple-bit-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "multiple-bit-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.MultipleBitHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class UnexpectedSoftErrors(Entity): """ Unexpected soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors, self).__init__() self.yang_name = "unexpected-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "unexpected-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "unexpected-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UnexpectedSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class OutofResourceHard(Entity): """ OOR thresh information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard, self).__init__() self.yang_name = "outof-resource-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "outof-resource-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "outof-resource-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.OutofResourceHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class HardwareHardErrors(Entity): """ Hardware hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors, self).__init__() self.yang_name = "hardware-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "hardware-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "hardware-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.HardwareHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ParitySoftErrors(Entity): """ Parity soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors, self).__init__() self.yang_name = "parity-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "parity-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "parity-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ParitySoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class DescriptorSoftErrors(Entity): """ Descriptor soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors, self).__init__() self.yang_name = "descriptor-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "descriptor-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "descriptor-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.DescriptorSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class InterfaceSoftErrors(Entity): """ Interface soft error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors, self).__init__() self.yang_name = "interface-soft-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "interface-soft-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "interface-soft-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.InterfaceSoftErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class IoHardErrors(Entity): """ IO hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors, self).__init__() self.yang_name = "io-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "io-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "io-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.IoHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class ResetHardErrors(Entity): """ Reset hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors, self).__init__() self.yang_name = "reset-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "reset-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "reset-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.ResetHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class UcodeHardErrors(Entity): """ UCode hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors, self).__init__() self.yang_name = "ucode-hard-errors" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "ucode-hard-errors" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "ucode-hard-errors" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.UcodeHardErrors.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) class AsicErrorMbeHard(Entity): """ Indirect hard error information .. attribute:: error Collection of errors **type**\: list of :py:class:`Error <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard, self).__init__() self.yang_name = "asic-error-mbe-hard" self.yang_parent_name = "error-path" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("error", ("error", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error))]) self._leafs = OrderedDict() self.error = YList(self) self._segment_path = lambda: "asic-error-mbe-hard" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard, [], name, value) class Error(Entity): """ Collection of errors .. attribute:: name Name assigned to mem **type**\: str .. attribute:: asic_info Name of rack/board/asic **type**\: str .. attribute:: node_key 32 bit key **type**\: int **range:** 0..4294967295 .. attribute:: alarm_on High threshold crossed **type**\: bool .. attribute:: thresh_hi High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_hi High period value **type**\: int **range:** 0..4294967295 .. attribute:: thresh_lo High threshold value **type**\: int **range:** 0..4294967295 .. attribute:: period_lo High period value **type**\: int **range:** 0..4294967295 .. attribute:: count Accumulated count **type**\: int **range:** 0..4294967295 .. attribute:: intr_type Type of error **type**\: int **range:** 0..4294967295 .. attribute:: leaf_id Leaf ID defined in user data **type**\: int **range:** 0..4294967295 .. attribute:: last_cleared Time cleared **type**\: int **range:** 0..18446744073709551615 .. attribute:: csrs_info List of csrs\_info **type**\: list of :py:class:`CsrsInfo <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.CsrsInfo>` .. attribute:: last_err Last Printable error information **type**\: list of :py:class:`LastErr <ydk.models.cisco_ios_xr.Cisco_IOS_XR_asic_errors_oper.AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.LastErr>` """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error, self).__init__() self.yang_name = "error" self.yang_parent_name = "asic-error-mbe-hard" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([("csrs-info", ("csrs_info", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.CsrsInfo)), ("last-err", ("last_err", AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.LastErr))]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('asic_info', YLeaf(YType.str, 'asic-info')), ('node_key', YLeaf(YType.uint32, 'node-key')), ('alarm_on', YLeaf(YType.boolean, 'alarm-on')), ('thresh_hi', YLeaf(YType.uint32, 'thresh-hi')), ('period_hi', YLeaf(YType.uint32, 'period-hi')), ('thresh_lo', YLeaf(YType.uint32, 'thresh-lo')), ('period_lo', YLeaf(YType.uint32, 'period-lo')), ('count', YLeaf(YType.uint32, 'count')), ('intr_type', YLeaf(YType.uint32, 'intr-type')), ('leaf_id', YLeaf(YType.uint32, 'leaf-id')), ('last_cleared', YLeaf(YType.uint64, 'last-cleared')), ]) self.name = None self.asic_info = None self.node_key = None self.alarm_on = None self.thresh_hi = None self.period_hi = None self.thresh_lo = None self.period_lo = None self.count = None self.intr_type = None self.leaf_id = None self.last_cleared = None self.csrs_info = YList(self) self.last_err = YList(self) self._segment_path = lambda: "error" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error, ['name', 'asic_info', 'node_key', 'alarm_on', 'thresh_hi', 'period_hi', 'thresh_lo', 'period_lo', 'count', 'intr_type', 'leaf_id', 'last_cleared'], name, value) class CsrsInfo(Entity): """ List of csrs\_info .. attribute:: name name **type**\: str .. attribute:: address address **type**\: int **range:** 0..18446744073709551615 .. attribute:: width width **type**\: int **range:** 0..4294967295 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.CsrsInfo, self).__init__() self.yang_name = "csrs-info" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('name', YLeaf(YType.str, 'name')), ('address', YLeaf(YType.uint64, 'address')), ('width', YLeaf(YType.uint32, 'width')), ]) self.name = None self.address = None self.width = None self._segment_path = lambda: "csrs-info" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.CsrsInfo, ['name', 'address', 'width'], name, value) class LastErr(Entity): """ Last Printable error information .. attribute:: at_time at time **type**\: int **range:** 0..18446744073709551615 .. attribute:: at_time_nsec at time nsec **type**\: int **range:** 0..18446744073709551615 .. attribute:: counter_val counter val **type**\: int **range:** 0..4294967295 .. attribute:: error_desc error desc **type**\: str .. attribute:: error_regval error regval **type**\: list of int **range:** 0..255 """ _prefix = 'asic-errors-oper' _revision = '2015-11-09' def __init__(self): super(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.LastErr, self).__init__() self.yang_name = "last-err" self.yang_parent_name = "error" self.is_top_level_class = False self.has_list_ancestor = True self.ylist_key_names = [] self._child_container_classes = OrderedDict([]) self._child_list_classes = OrderedDict([]) self._leafs = OrderedDict([ ('at_time', YLeaf(YType.uint64, 'at-time')), ('at_time_nsec', YLeaf(YType.uint64, 'at-time-nsec')), ('counter_val', YLeaf(YType.uint32, 'counter-val')), ('error_desc', YLeaf(YType.str, 'error-desc')), ('error_regval', YLeafList(YType.uint8, 'error-regval')), ]) self.at_time = None self.at_time_nsec = None self.counter_val = None self.error_desc = None self.error_regval = [] self._segment_path = lambda: "last-err" def __setattr__(self, name, value): self._perform_setattr(AsicErrors.Nodes.Node.AsicInformation.Instances.Instance.ErrorPath.AsicErrorMbeHard.Error.LastErr, ['at_time', 'at_time_nsec', 'counter_val', 'error_desc', 'error_regval'], name, value) def clone_ptr(self): self._top_entity = AsicErrors() return self._top_entity

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987,467

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0.02579

0.056524

0.100698

0.981951

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0.963544

0.95583

0.942643

0.936524

0

0.035101

0.6119

987,467

16,477

7,124

59.930024

0.751662

0.159991

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0

0.086653

0.007181

0

1

0.070441

false

0

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0.107244

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1

0

1

0

null

0

9

1cd6786da7098d7f8ba5c5a50595664a820df91a

2,138

py

Python

address_validator.py

ZackDowning/VLANInventory2

6740a605be6bd39dfa5ba80dc5694c63bbb365af

[ "MIT" ]

null

address_validator.py

ZackDowning/VLANInventory2

6740a605be6bd39dfa5ba80dc5694c63bbb365af

[ "MIT" ]

null

address_validator.py

ZackDowning/VLANInventory2

6740a605be6bd39dfa5ba80dc5694c63bbb365af

[ "MIT" ]

null

import re def ipv4(address): if re.fullmatch( r'(([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])\.){3}' r'([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])' r'', address): return True else: return False def ipv6(address): if re.fullmatch( r'(([0-9aA-fF]{1,4}:){7}[0-9aA-fF]{1,4}|' r'([0-9aA-fF]{1,4}:){7}:|' r'([0-9aA-fF]{1,4}:){1,6}:[0-9aA-fF]{1,4}|' r'([0-9aA-fF]{1,4}:){1,5}(:[0-9aA-fF]{1,4}){1,2}|' r'([0-9aA-fF]{1,4}:){1,4}(:[0-9aA-fF]{1,4}){1,3}|' r'([0-9aA-fF]{1,4}:){1,3}(:[0-9aA-fF]{1,4}){1,4}|' r'([0-9aA-fF]{1,4}:){1,2}(:[0-9aA-fF]{1,4}){1,5}|' r'[0-9aA-fF]{1,4}:((:[0-9aA-fF]{1,4}){1,6})|' r':((:[0-9aA-fF]{1,4}){1,7}|:)|' r'fe80:(:[0-9aA-fF]{0,4}){0,4}%[0-9aA-zZ]+|::(ffff(:0{1,4})?:))' r'', address): return True else: return False def macaddress(address): if '.' in address: if re.fullmatch( r'((' r'([0-9aA-fF]){4}|' r'([0-9aA-fF]){3}([aA-fF0-9])|' r'(([aA-fF0-9])([aA-fF0-9]){3})|' r'((([0-9][aA-fF])|([aA-fF0-9])){2})|' r'(([aA-fF0-9])([aA-fF0-9]){2}([aA-fF0-9])))\.){2}' r'(([0-9aA-fF]){4})|' r'(([0-9aA-fF]){3}([aA-fF0-9]))|' r'(([aA-fF0-9])([aA-fF0-9]){3})|' r'((([0-9][aA-fF])|([aA-fF][0-9])){2})|' r'(([aA-fF0-9])([aA-fF0-9]){2}([aA-fF0-9]))' r'', address): return True else: return False else: if re.fullmatch( r'(((([0-9aA-fF]){2}-){5}|' r'(([0-9][aA-fF]|[aA-fF][0-9])-){5})' r'(([0-9aA-fF]){2}|([0-9][aA-fF]|[aA-fF][0-9]){2}))|' r'(((([0-9aA-fF]){2}:){5}|' r'(([0-9][aA-fF]|[aA-Ff][0-9]):){5})' r'(([0-9aA-fF]){2}|([0-9][aA-fF]|[aA-fF][0-9]){2}))' r'', address): return True else: return False

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null

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9

1ce14f9173c35c99da45e508da0c265da1ea9c31

196

py

Python

openwisp_utils/admin_theme/site.py

TPath123/openwisp-utils

2cae02b42dfc3234e2ceaca918e68405218dfac0

[ "BSD-3-Clause" ]

null

openwisp_utils/admin_theme/site.py

TPath123/openwisp-utils

2cae02b42dfc3234e2ceaca918e68405218dfac0

[ "BSD-3-Clause" ]

null

openwisp_utils/admin_theme/site.py

TPath123/openwisp-utils

2cae02b42dfc3234e2ceaca918e68405218dfac0

[ "BSD-3-Clause" ]

null

from django.utils.module_loading import import_string from .settings import OPENWISP_ADMIN_SITE_CLASS admin_site_class = import_string(OPENWISP_ADMIN_SITE_CLASS) admin_site = admin_site_class()

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e82cff630a7bae2efc0e696c0570a5c0adc5d8d6

88,097

py

Python

siren/siren.py

MrTornado24/FENeRF

9d90acda243b7c7d7f2c688a3bb333da2e7f8894

[ "MIT" ]

22

2022-03-18T16:29:04.000Z

2022-03-31T12:17:55.000Z

siren/siren.py

MrTornado24/FENeRF

9d90acda243b7c7d7f2c688a3bb333da2e7f8894

[ "MIT" ]

2

2022-03-28T09:21:27.000Z

2022-03-28T09:30:16.000Z

siren/siren.py

MrTornado24/FENeRF

9d90acda243b7c7d7f2c688a3bb333da2e7f8894

[ "MIT" ]

1

2022-03-20T14:15:11.000Z

import sys from numpy.lib.type_check import imag from torch._C import device from torch.functional import align_tensors sys.path.append('/apdcephfs/share_1330077/starksun/projects/pi-GAN') from fid_evaluation import output_images import numpy as np import torch.nn as nn import torch import math import torch.nn.functional as F from .latent_grid import StyleGenerator2D from .layers import * class Sine(nn.Module): """Sine Activation Function.""" def __init__(self): super().__init__() def forward(self, x): return torch.sin(30. * x) def sine_init(m): with torch.no_grad(): if isinstance(m, nn.Linear): num_input = m.weight.size(-1) m.weight.uniform_(-np.sqrt(6 / num_input) / 30, np.sqrt(6 / num_input) / 30) def first_layer_sine_init(m): with torch.no_grad(): if isinstance(m, nn.Linear): num_input = m.weight.size(-1) m.weight.uniform_(-1 / num_input, 1 / num_input) def film_sine_init(m): with torch.no_grad(): if isinstance(m, nn.Linear): num_input = m.weight.size(-1) m.weight.uniform_(-np.sqrt(6 / num_input) / 30, np.sqrt(6 / num_input) / 30) def first_layer_film_sine_init(m): with torch.no_grad(): if isinstance(m, nn.Linear): num_input = m.weight.size(-1) m.weight.uniform_(-1 / num_input, 1 / num_input) def kaiming_leaky_init(m): classname = m.__class__.__name__ if classname.find('Linear') != -1: torch.nn.init.kaiming_normal_(m.weight, a=0.2, mode='fan_in', nonlinearity='leaky_relu') # class CustomMappingNetwork(nn.Module): # def __init__(self, z_dim, map_hidden_dim, map_output_dim): # super().__init__() # self.network = nn.Sequential(nn.Linear(z_dim, map_hidden_dim), # nn.LeakyReLU(0.2, inplace=True), # nn.Linear(map_hidden_dim, map_hidden_dim), # nn.LeakyReLU(0.2, inplace=True), # nn.Linear(map_hidden_dim, map_hidden_dim), # nn.LeakyReLU(0.2, inplace=True), # nn.Linear(map_hidden_dim, map_output_dim)) # self.network.apply(kaiming_leaky_init) # with torch.no_grad(): # self.network[-1].weight *= 0.25 # def forward(self, z): # frequencies_offsets = self.network(z) # frequencies = frequencies_offsets[..., :frequencies_offsets.shape[-1]//2] # phase_shifts = frequencies_offsets[..., frequencies_offsets.shape[-1]//2:] # return frequencies, phase_shifts class CustomMappingNetwork(nn.Module): def __init__(self, z_dim, map_hidden_dim, map_output_dim, n_blocks=3): super().__init__() self.network = [nn.Linear(z_dim, map_hidden_dim), nn.LeakyReLU(0.2, inplace=True)] for _ in range(n_blocks): self.network.append(nn.Linear(map_hidden_dim, map_hidden_dim)) self.network.append(nn.LeakyReLU(0.2, inplace=True)) self.network.append(nn.Linear(map_hidden_dim, map_output_dim)) self.network = nn.Sequential(*self.network) self.network.apply(kaiming_leaky_init) with torch.no_grad(): self.network[-1].weight *= 0.25 def forward(self, z): frequencies_offsets = self.network(z) # z: (n_batch * n_point, n_channel) frequencies = frequencies_offsets[..., :frequencies_offsets.shape[-1]//2] phase_shifts = frequencies_offsets[..., frequencies_offsets.shape[-1]//2:] return frequencies, phase_shifts def frequency_init(freq): def init(m): with torch.no_grad(): if isinstance(m, nn.Linear): num_input = m.weight.size(-1) m.weight.uniform_(-np.sqrt(6 / num_input) / freq, np.sqrt(6 / num_input) / freq) return init class FiLMLayer(nn.Module): def __init__(self, input_dim, hidden_dim): super().__init__() self.layer = nn.Linear(input_dim, hidden_dim) def forward(self, x, freq, phase_shift): x = self.layer(x) if x.shape[1] != freq.shape[1]: freq = freq.unsqueeze(1).expand_as(x) #TODO: all x conditioned on a single freq and phase_shift --> every x conditioned on a specific freq and phase_shift phase_shift = phase_shift.unsqueeze(1).expand_as(x) return torch.sin(freq * x + phase_shift) class TALLSIREN(nn.Module): """Primary SIREN architecture used in pi-GAN generators.""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(input_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3), nn.Sigmoid()) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 1)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) rbg = self.color_layer_linear(rbg) return torch.cat([rbg, sigma], dim=-1) class UniformBoxWarp(nn.Module): def __init__(self, sidelength): super().__init__() self.scale_factor = 2/sidelength def forward(self, coordinates): return coordinates * self.scale_factor class SPATIALSIRENBASELINE(nn.Module): """Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 1)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class SPATIALSIRENBASELINEHD(nn.Module): """Same architecture as SPATIALSIRENBASELINE but use neural renderer""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 64)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 1)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) # rbg = torch.sigmoid(self.color_layer_linear(rbg)) rbg = self.color_layer_linear(rbg) return torch.cat([rbg, sigma], dim=-1) class UniformBoxWarp(nn.Module): def __init__(self, sidelength): super().__init__() self.scale_factor = 2/sidelength def forward(self, coordinates): return coordinates * self.scale_factor def sample_from_3dgrid(coordinates, grid): """ Expects coordinates in shape (batch_size, num_points_per_batch, 3) Expects grid in shape (1, channels, H, W, D) (Also works if grid has batch size) Returns sampled features of shape (batch_size, num_points_per_batch, feature_channels) """ coordinates = coordinates.float() grid = grid.float() batch_size, n_coords, n_dims = coordinates.shape sampled_features = torch.nn.functional.grid_sample(grid.expand(batch_size, -1, -1, -1, -1), coordinates.reshape(batch_size, 1, 1, -1, n_dims), mode='bilinear', padding_mode='zeros', align_corners=True) N, C, H, W, D = sampled_features.shape sampled_features = sampled_features.permute(0, 4, 3, 2, 1).reshape(N, H*W*D, C) return sampled_features def modified_first_sine_init(m): with torch.no_grad(): # if hasattr(m, 'weight'): if isinstance(m, nn.Linear): num_input = 3 m.weight.uniform_(-1 / num_input, 1 / num_input) class EmbeddingPiGAN128(nn.Module): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details.""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(32 + 3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) print(self.network) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 1)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) x = torch.cat([shared_features, input], -1) for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class EmbeddingPiGAN256(EmbeddingPiGAN128): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs, hidden_dim=256) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 64, 64, 64)*0.1) class SPATIALSIRENGRID(nn.Module): """Same architecture as SPATIALSIRENBASELINE but use local latent sampled from grid""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.local_coordinates = True self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(32, 256, (len(self.network) + 1)*hidden_dim*2, n_blocks=1) self.grid_latent_network = StyleGenerator2D(out_res=32, out_ch=32, z_dim=z_dim, ch_mul=1, ch_max=256, skip_conn=False) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): latent_grid = self.grid_latent_network(z) input_grid = self.gridwarper(input) # range: (-1.4, 1.4) sampled_latent = self.sample_local_latents(latent_grid, input_grid) frequencies, phase_shifts = self.mapping_network(sampled_latent) if self.local_coordinates: # map global coordinate space into local coordinate space (i.e. each grid cell has a [-1, 1] range) preserve_y = sampled_latent.ndim == 4 # if latents are 2D, then keep the y coordinate global input = self.get_local_coordinates( global_coords=input, local_grid_length=32, preserve_y=False ) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, box_warp=False, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 x = self.gridwarper(input) for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) def sample_local_latents(self, local_latents, xyz): B, local_z_dim, H, W = local_latents.shape # take only x and z coordinates, since our latent codes are in a 2D grid (no y dimension) # for the purposes of grid_sample we treat H*W as the H dimension and samples_per_ray as the W dimension xyz = xyz[:, :, [0, 2]].unsqueeze(1) # [B, H * W, samples_per_ray, 2] # all samples get the most detailed latent codes sampled_local_latents = nn.functional.grid_sample( input=local_latents, # (b, c, h, w) grid=xyz, # (b, 1, n_pixel, 2) mode='bilinear', # bilinear mode will use trilinear interpolation if input is 5D align_corners=False, padding_mode="zeros", ) # output is shape [B, local_z_dim, H * W, samples_per_ray] # put channel dimension at end: [B, H * W, samples_per_ray, local_z_dim] sampled_local_latents = sampled_local_latents.permute(0, 2, 3, 1) # merge everything else into batch dim: [B * H * W * samples_per_ray, local_z_dim] sampled_local_latents = sampled_local_latents.reshape(B, -1, local_z_dim) return sampled_local_latents def get_local_coordinates(self, global_coords, local_grid_length, preserve_y=True): local_coords = global_coords.clone() # it is assumed that the global coordinates are scaled to [-1, 1] # convert to [0, 1] scale local_coords = (local_coords + 1) / 2 # scale so that each grid cell in the local_latent grid is 1x1 in size local_coords = local_coords * local_grid_length # subtract integer from each coordinate so that they are all in range [0, 1] local_coords = local_coords - (local_coords - 0.5).round() # return to [-1, 1] scale local_coords = (local_coords * 2) - 1 if preserve_y: # preserve the y dimension in the global coordinate frame, since it doesn't have a local latent code coords = torch.cat([local_coords[..., 0:1], global_coords[..., 1:2], local_coords[..., 2:3]], dim=-1) else: coords = torch.cat([local_coords[..., 0:1], local_coords[..., 1:2], local_coords[..., 2:3]], dim=-1) return coords class SPATIALSIRENVOLUME(nn.Module): """Same architecture as SPATIALSIRENBASELINE but use local latent sampled from volume""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(32, 256, (len(self.network) + 1)*hidden_dim*2) # self.volume_latent_network = VolumeStyleGenerator( # mapping_fmaps=z_dim, # style_mixing_prob=0.9, # Probability of mixing styles during training. None = disable. # truncation_psi=0.7, # Style strength multiplier for the truncation trick. None = disable. # truncation_cutoff=8, # Number of layers for which to apply the truncation trick. None = disable. # resolution=32, # fmap_base=512, # fmap_max=256) self.volume_latent_network = VolumeStyleGenerator(input_nc=z_dim, output_nc=32, n_samples=3, norm='batch', activation='ReLU', padding_type='zero') self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): latent_grid = self.volume_latent_network(z) input_grid = self.gridwarper(input) # interpolate latent # samples = F.grid_sample(latent_grid, # input[..., [0, 2]].unsqueeze(2), # align_corners=True, # mode='bilinear', # padding_mode='zeros') samples = sample_from_3dgrid(input_grid, latent_grid) frequencies, phase_shifts = self.mapping_network(samples) return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, box_warp=False, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., -self.hidden_dim:], phase_shifts[..., -self.hidden_dim:]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class SPATIALSIRENSEMANTIC(nn.Module): """Same architecture as TALLSIREN but synthesis semantic map""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.label_layer_sine = FiLMLayer(hidden_dim, hidden_dim) self.label_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 19)) # 19 semantic labels self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 2)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.label_layer_sine.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) n_batch, n_pixel = input.shape[:2] # output = torch.zeros((n_batch, n_pixel, self.output_dim)).to(input) # for b in range(n_batch): # head = 0 # while head < n_pixel: # tail = head + self.max_batch_size # output[b:b+1, head:tail] = self.forward_with_frequencies_phase_shifts(input[b:b+1, head:tail], frequencies[b:b+1], phase_shifts[b:b+1], ray_directions[b:b+1, head:tail], **kwargs) # head += self.max_batch_size # return output return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) start += self.hidden_dim end += self.hidden_dim sigma = self.final_layer(x) labels = self.label_layer_sine(x, frequencies[..., start:end], phase_shifts[..., start:end]) # TODO: w. / w.o softmax activation on label labels = self.label_layer_linear(labels) start += self.hidden_dim end += self.hidden_dim rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., start:end], phase_shifts[..., start:end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class SPATIALSIRENBASELINESEMANTIC(nn.Module): """Same architecture as SPATIALSIRENSEMANTIC but doesn't condition on geometry code when regressing labels""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, 19)) # 19 semantic labels self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 1)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) n_batch, n_pixel = input.shape[:2] # output = torch.zeros((n_batch, n_pixel, self.output_dim)).to(input) # for b in range(n_batch): # head = 0 # while head < n_pixel: # tail = head + self.max_batch_size # output[b:b+1, head:tail] = self.forward_with_frequencies_phase_shifts(input[b:b+1, head:tail], frequencies[b:b+1], phase_shifts[b:b+1], ray_directions[b:b+1, head:tail], **kwargs) # head += self.max_batch_size # return output return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) sigma = self.final_layer(x) # labels = torch.sigmoid(self.label_layer_linear(x)) labels = self.label_layer_linear(x) start += self.hidden_dim end += self.hidden_dim rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., start:end], phase_shifts[..., start:end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class SPATIALSIRENDISENTANGLE(nn.Module): """Same architecture as TALLSIREN but use double latent codes""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 # TODO: 为什么做变换 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([ray_directions, x], dim=-1) sigma = self.final_layer(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class SPATIALSIRENDISENTANGLE_debug(nn.Module): """Same architecture as TALLSIREN but use double latent codes""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_pre = nn.Sequential(nn.Linear(hidden_dim, hidden_dim)) # self.color_layer_sine = FiLMLayer(hidden_dim + 32, hidden_dim) # ray_drection dim: 3 --> 32 self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.dir_mapping_network = nn.Sequential( nn.Linear(3, 256), nn.Linear(256, 32) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) # n_batch, n_pixel = input.shape[:2] # output = torch.zeros((n_batch, n_pixel, self.output_dim)).to(input) # for b in range(n_batch): # head = 0 # while head < n_pixel: # tail = head + self.max_batch_size # output[b:b+1, head:tail] = self.forward_with_frequencies_phase_shifts(input[b:b+1, head:tail], frequencies[b:b+1], phase_shifts[b:b+1], ray_directions[b:b+1, head:tail], **kwargs) # head += self.max_batch_size # return output return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 # TODO: 为什么做变换 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) sigma = self.final_layer(x) # ray_directions = self.dir_mapping_network(ray_directions) x = self.color_layer_pre(x) rbg = torch.cat([ray_directions, x], dim=-1) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class SPATIALSIRENAUGDISENTANGLE(nn.Module): """Same architecture as SPATIALSIRENDISENTANGLE but has augmented color branch and narrower density feature branch""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_pre = nn.Sequential( nn.Linear(hidden_dim, 3), ) # self.color_layer_sine = FiLMLayer(hidden_dim + 32, hidden_dim) # ray_drection dim: 3 --> 32 self.color_layer_sine = nn.ModuleList([ FiLMLayer(3 + 3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 # TODO: 为什么做变换 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) sigma = self.final_layer(x) x = self.color_layer_pre(x) rbg = torch.cat([ray_directions, x], dim=-1) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class RESSIRENDISENTANGLE(nn.Module): """ Same architecture as SIRENDISENTANGLE but use residual architecure code accroding to http://gvv.mpi-inf.mpg.de/projects/i3DMM/ """ def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.res_coord_layer = nn.Linear(hidden_dim, 3) self.density_layer_linear = nn.Sequential( nn.Linear(3, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, 1) ) self.color_layer_pre = nn.Sequential(nn.Linear(3, hidden_dim)) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) # self.dir_mapping_network = nn.Sequential( # nn.Linear(3, 256), # nn.Linear(256, 32) # ) self.network.apply(frequency_init(25)) self.density_layer_linear.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) # n_batch, n_pixel = input.shape[:2] # output = torch.zeros((n_batch, n_pixel, self.output_dim)).to(input) # for b in range(n_batch): # head = 0 # while head < n_pixel: # tail = head + self.max_batch_size # output[b:b+1, head:tail] = self.forward_with_frequencies_phase_shifts(input[b:b+1, head:tail], frequencies[b:b+1], phase_shifts[b:b+1], ray_directions[b:b+1, head:tail], **kwargs) # head += self.max_batch_size # return output return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 # TODO: 为什么做变换 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) coords_res = self.res_coord_layer(x) input = input + coords_res sigma = self.density_layer_linear(input) # ray_directions = self.dir_mapping_network(ray_directions) rbg = self.color_layer_pre(input) rbg = torch.cat([ray_directions, rbg], dim=-1) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([rbg, sigma], dim=-1) class SPATIALSIRENSEMANTICDISENTANGLE(nn.Module): """Same architecture as TALLSIREN but use double latent codes and render semantic maps""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim - 4)) # output_dim = seg_channel + rgb_channel + density_channel self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.color_layer_sine[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 # TODO: 为什么做变换 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) sigma = self.final_layer(x) start += self.hidden_dim end += self.hidden_dim labels = self.label_layer_linear(x) # rbg = torch.cat([ray_directions, input, labels], dim=-1) rbg = torch.cat([ray_directions, x], dim=-1) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class SIRENBASELINESEMANTICDISENTANGLE(nn.Module): """Same architecture as TALLSIREN baseline but use double latent codes and render semantic maps""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim - 4)) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([ray_directions, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class SIRENBASELINESEMANTICDISENTANGLE_debug(nn.Module): """Same architecture as SIRENBASELINESEMANTICDISENTANGLE_debug except adding sigmoid to label""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, 19)) # 19 semantic labels self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([ray_directions, x], dim=-1) sigma = self.final_layer(x) labels = torch.sigmoid(self.label_layer_linear(x)) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class SPATIALSIRENSEMANTICHD(nn.Module): """Same architecture as SPATIALSIRENSEMANTIC but on a high resolution""" def __init__(self, input_dim=2, z_dim=100, hidden_dim=256, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_dim = z_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.max_batch_size = 2500 self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) self.label_layer_sine = FiLMLayer(hidden_dim, hidden_dim) self.label_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 64)) # 19 semantic labels self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 64)) self.mapping_network = CustomMappingNetwork(z_dim, 256, (len(self.network) + 2)*hidden_dim*2) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.label_layer_sine.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.network[0].apply(first_layer_film_sine_init) self.activation = nn.Softmax(dim=-1) self.gridwarper = UniformBoxWarp(0.24) # Don't worry about this, it was added to ensure compatibility with another model. Shouldn't affect performance. def forward(self, input, z, ray_directions, **kwargs): frequencies, phase_shifts = self.mapping_network(z) n_batch, n_pixel = input.shape[:2] return self.forward_with_frequencies_phase_shifts(input, frequencies, phase_shifts, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies, phase_shifts, ray_directions, **kwargs): frequencies = frequencies*15 + 30 input = self.gridwarper(input) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies[..., start:end], phase_shifts[..., start:end]) start += self.hidden_dim end += self.hidden_dim sigma = self.final_layer(x) labels = self.label_layer_sine(x, frequencies[..., start:end], phase_shifts[..., start:end]) # TODO: w. / w.o softmax activation on label labels = self.label_layer_linear(labels) start += self.hidden_dim end += self.hidden_dim rbg = self.color_layer_sine(torch.cat([ray_directions, x], dim=-1), frequencies[..., start:end], phase_shifts[..., start:end]) rbg = self.color_layer_linear(rbg) # rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class EmbeddingPiGAN128SEMANTICDISENTANGLE(nn.Module): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details.""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(32 + 3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) # self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim-4) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) x = torch.cat([shared_features, input], -1) for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([ray_directions, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class TextureEmbeddingPiGAN128SEMANTICDISENTANGLE(nn.Module): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network""" def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) # self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+32+3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim-4) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) # x = torch.cat([shared_features, input], -1) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([ray_directions, shared_features, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class TextureEmbeddingPiGAN256SEMANTICDISENTANGLE(TextureEmbeddingPiGAN128SEMANTICDISENTANGLE): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network""" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs, hidden_dim=256) self.spatial_embeddings = nn.Parameter(torch.randn(1,32,64,64,64)*0.1) class TextureEmbeddingPiGAN256SEMANTICDISENTANGLE_DIM_96(TextureEmbeddingPiGAN128SEMANTICDISENTANGLE): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network""" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs, hidden_dim=256) self.spatial_embeddings = nn.Parameter(torch.randn(1,32,96,96,96)*0.1) class TextureEmbeddingPiGAN128SEMANTICDISENTANGLE_WO_DIR(nn.Module): """ 1. Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network; 2. remove view direction 3. add more color layers """ def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) # self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+32, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim-4) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) self.color_layer_sine[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) # x = torch.cat([shared_features, input], -1) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([shared_features, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class TextureEmbeddingPiGAN128SEMANTICDISENTANGLE_WO_DIR_debug(nn.Module): """ 1. Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network; 2. remove view direction 3. add more color layers """ def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) # self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+32, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim-4) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) self.color_layer_sine[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) # x = torch.cat([shared_features, input], -1) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([shared_features, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class TextureEmbeddingPiGAN128SEMANTICDISENTANGLE_WO_DIR_debug2(nn.Module): """ 1. Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network; 2. remove view direction 3. add more color layers """ def __init__(self, input_dim=2, z_geo_dim=100, z_app_dim=100, hidden_dim=128, output_dim=1, device=None): super().__init__() self.device = device self.input_dim = input_dim self.z_geo_dim = z_geo_dim self.z_app_dim = z_app_dim self.hidden_dim = hidden_dim self.output_dim = output_dim self.network = nn.ModuleList([ FiLMLayer(3, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.final_layer = nn.Linear(hidden_dim, 1) # self.color_layer_sine = FiLMLayer(hidden_dim + 3, hidden_dim) self.color_layer_sine = nn.ModuleList([ FiLMLayer(hidden_dim+32, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), FiLMLayer(hidden_dim, hidden_dim), ]) self.color_layer_linear = nn.Sequential(nn.Linear(hidden_dim, 3)) self.geo_mapping_network = CustomMappingNetwork(z_geo_dim, 256, len(self.network)*hidden_dim*2) self.app_mapping_network = CustomMappingNetwork(z_app_dim, 256, len(self.color_layer_sine)*hidden_dim*2) self.label_layer_linear = nn.Sequential( nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, hidden_dim), nn.Linear(hidden_dim, self.output_dim-4) ) self.network.apply(frequency_init(25)) self.final_layer.apply(frequency_init(25)) self.color_layer_sine.apply(frequency_init(25)) self.color_layer_linear.apply(frequency_init(25)) self.label_layer_linear.apply(frequency_init(25)) self.network[0].apply(modified_first_sine_init) # self.color_layer_sine[0].apply(modified_first_sine_init) self.spatial_embeddings = nn.Parameter(torch.randn(1, 32, 96, 96, 96)*0.01) # !! Important !! Set this value to the expected side-length of your scene. e.g. for for faces, heads usually fit in # a box of side-length 0.24, since the camera has such a narrow FOV. For other scenes, with higher FOV, probably needs to be bigger. self.gridwarper = UniformBoxWarp(0.24) def forward(self, input, z_geo, z_app, ray_directions, **kwargs): frequencies_geo, phase_shifts_geo = self.geo_mapping_network(z_geo) frequencies_app, phase_shifts_app = self.app_mapping_network(z_app) return self.forward_with_frequencies_phase_shifts(input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs) def forward_with_frequencies_phase_shifts(self, input, frequencies_geo, frequencies_app, phase_shifts_geo, phase_shifts_app, ray_directions, **kwargs): frequencies_geo = frequencies_geo*15 + 30 frequencies_app = frequencies_app*15 + 30 input = self.gridwarper(input) shared_features = sample_from_3dgrid(input, self.spatial_embeddings) # x = torch.cat([shared_features, input], -1) x = input for index, layer in enumerate(self.network): start = index * self.hidden_dim end = (index+1) * self.hidden_dim x = layer(x, frequencies_geo[..., start:end], phase_shifts_geo[..., start:end]) rbg = torch.cat([shared_features, x], dim=-1) sigma = self.final_layer(x) labels = self.label_layer_linear(x) for index, layer in enumerate(self.color_layer_sine): start, end = index * self.hidden_dim, (index+1) * self.hidden_dim rbg = layer(rbg, frequencies_app[..., start:end], phase_shifts_app[..., start: end]) rbg = torch.sigmoid(self.color_layer_linear(rbg)) return torch.cat([labels, rbg, sigma], dim=-1) class TextureEmbeddingPiGAN256SEMANTICDISENTANGLE_WO_DIR_DIM_96(TextureEmbeddingPiGAN128SEMANTICDISENTANGLE_WO_DIR): """Smaller architecture that has an additional cube of embeddings. Often gives better fine details. Embeddings are in color prediction branch instead of density network""" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs, hidden_dim=256) self.spatial_embeddings = nn.Parameter(torch.randn(1,32,96,96,96)*0.1) def main(): # model = SPATIALSIRENVOLUME(input_dim=3, z_dim=256, hidden_dim=256, output_dim=4, device=None) model = SPATIALSIRENSEMANTIC(input_dim=3, z_dim=256, hidden_dim=256, output_dim=4, device=None) input, z, ray_directions = torch.randn(2, 4000, 3), torch.rand(2, 256), torch.rand(2, 4000, 3) output = model(input, z, ray_directions) print(output.shape) if __name__ == "__main__": main()

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Python

rootfs/usr/lib/python3/dist-packages/numpy/distutils/compat.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

343

2015-01-07T05:58:44.000Z

2022-03-15T14:55:21.000Z

rootfs/usr/lib/python3/dist-packages/numpy/distutils/compat.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

61

2015-03-19T18:20:21.000Z

2019-10-23T12:58:23.000Z

rootfs/usr/lib/python3/dist-packages/numpy/distutils/compat.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

66

2015-01-20T15:35:05.000Z

2021-11-25T16:49:41.000Z

"""Small modules to cope with python 2 vs 3 incompatibilities inside numpy.distutils """ import sys def get_exception(): return sys.exc_info()[1]

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1

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7

1c56f3da5203656cfb5c5f767865ff64a9b22e0a

2,198

py

Python

final_submission/parser/json_dump.py

Groverkss/Breeding-Horses

8a8e3c5114ec7c26c87d7517bac7a0bb3f2b19a7

[ "MIT" ]

null

final_submission/parser/json_dump.py

Groverkss/Breeding-Horses

8a8e3c5114ec7c26c87d7517bac7a0bb3f2b19a7

[ "MIT" ]

null

final_submission/parser/json_dump.py

Groverkss/Breeding-Horses

8a8e3c5114ec7c26c87d7517bac7a0bb3f2b19a7

[ "MIT" ]

null

import json data = [ [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.74726809e-16, 0.0, 1.52226779e-05, -1.04623995e-06, -5.47552982e-09, 3.8344835e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.77e-16, 0.0, 1.52294786e-05, -1.03985242e-06, -5.4574558e-09, 3.78988721e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.74726809e-16, 0.0, 1.52226779e-05, -1.04623995e-06, -5.47552982e-09, 3.8344835e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.74726809e-16, 0.0, 1.51827267e-05, -1.04623995e-06, -5.47549689e-09, 3.83653816e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.77e-16, 0.0, 1.52294786e-05, -1.03985242e-06, -5.4574558e-09, 3.78988721e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.74726809e-16, 0.0, 1.52226779e-05, -1.04623995e-06, -5.47552982e-09, 3.8344835e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.77e-16, 0.0, 1.52294786e-05, -1.03985242e-06, -5.4574558e-09, 3.78988721e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.77e-16, 0.0, 1.52294786e-05, -1.03985242e-06, -5.38474558e-09, 3.78988721e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.74726809e-16, 0.0, 1.52226779e-05, -1.04623995e-06, -5.47552982e-09, 3.8344835e-10, ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -5.77e-16, 0.0, 1.52294786e-05, -1.03985242e-06, -5.4574558e-09, 3.78988721e-10, ], ] with open("output.json", "w") as outfile: json.dump(data, outfile)

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c743da3bb3ab3a0334c54507a96760529660fa1a

259

py

Python

nginx_access_tailer/__init__.py

swfrench/nginx-access-tailer

5e060396ca749935c622e8e9c50b659b39e3675b

[ "BSD-3-Clause" ]

null

nginx_access_tailer/__init__.py

swfrench/nginx-access-tailer

5e060396ca749935c622e8e9c50b659b39e3675b

[ "BSD-3-Clause" ]

null

nginx_access_tailer/__init__.py

swfrench/nginx-access-tailer

5e060396ca749935c622e8e9c50b659b39e3675b

[ "BSD-3-Clause" ]

null

"""Minimal top-level emports.""" from nginx_access_tailer.instance_metadata import InstanceMetadata from nginx_access_tailer.nginx_access_log_consumer import NginxAccessLogConsumer from nginx_access_tailer.nginx_access_log_tailer import NginxAccessLogTailer

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7

c74ae5f7d31d33d1e61caadd4f6839a8091cc959

5,933

py

Python

tests/parser/16-Incremental-Scheduling.asp.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/16-Incremental-Scheduling.asp.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/16-Incremental-Scheduling.asp.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

input = """ % % ******GRINGO 3.x REQUIRED****** % % time(0). time(T+1) :- time(T), T < MT, max_value(MT). %time(0..MT) :- max_value(MT). pen_value(T) :- time(T). td_value(T) :- time(T). instance_of(D,1) :- device(D). instance_of(D,I+1) :- device(D), instance_of(D,I), instances(D,N), I < N. % Pick a unique start time and instance for each job 1 <= { start(J,S) : time(S) } <= 1 :- job(J). 1 <= { on_instance(J,I) : instance_of(D,I) } <= 1 :- job(J), job_device(J,D). %---------------------- % - overlap %---------------------- :- on_instance(J1,I), on_instance(J2,I), J1 != J2, job_device(J1,D), job_device(J2,D), start(J1,S1), job_len(J1,L1), start(J2,S2), S1 <= S2, S2 < S1 + L1. %---------------------- % - order %---------------------- :- precedes(J1,J2), start(J1,S1), job_len(J1,L1), start(J2,S2), S2 < S1 + L1. %------------------------------------- % - completion -- total-tardiness %------------------------------------- td(J,S + L - D) :- job(J), start(J,S), job_len(J,L), deadline(J,D), S + L > D. td(J,0) :- job(J), start(J,S), job_len(J,L), deadline(J,D), S + L <= D. %------------------------------------- % - completion -- penalty %------------------------------------- penalty(J,TD * I) :- job(J), td(J,TD), importance(J,I). :- penalty(J,P), max_value(MV), P > MV. tot_penalty(TP) :- pen_value(TP), TP = #sum{ P,J : penalty(J,P) }. % % If the value of the total penalty would be greater than the % maximum allowed value of pen_value(_), the above rule % does not define tot_penalty(_). % In that case, the solution is not acceptable. % has_tot_penalty :- tot_penalty(TP). -has_tot_penalty :- not has_tot_penalty. :- -has_tot_penalty. :- pen_value(TP), tot_penalty(TP), max_total_penalty(K), TP > K. %---------------------- % - instance assignment %---------------------- :- on_instance(J1,I), on_instance(J2,I), job_device(J1,D), job_device(J2,D), instances(D,N), N > 1, J1 != J2, start(J1,S1), start(J2,S2), job_len(J1,L1), S1 <= S2, S2 < S1 + L1. :- on_instance(J,I), device(D), job(J), job_device(J,D), offline_instance(D,I), must_schedule(J). %---------------------- % - current schedule %---------------------- already_started(J) :- curr_job_start(J,S), curr_time(CT), CT > S. already_finished(J) :- curr_job_start(J,S), job_len(J,L), curr_time(CT), CT >= S + L. must_schedule(J) :- job(J), not must_not_schedule(J). must_not_schedule(J) :- already_started(J), not rescheduled(J). rescheduled(J) :- already_started(J), not already_finished(J), job_device(J,D), curr_on_instance(J,I), offline_instance(D,I). :- start(J,S), curr_time(CT), S < CT, device(D), job_device(J,D), time(S), must_schedule(J). :- start(J,S), curr_job_start(J,CS), S != CS, job_device(J,D), must_not_schedule(J). :- on_instance(J,I), curr_on_instance(J,CI), I != CI, must_not_schedule(J). """ output = """ % % ******GRINGO 3.x REQUIRED****** % % time(0). time(T+1) :- time(T), T < MT, max_value(MT). %time(0..MT) :- max_value(MT). pen_value(T) :- time(T). td_value(T) :- time(T). instance_of(D,1) :- device(D). instance_of(D,I+1) :- device(D), instance_of(D,I), instances(D,N), I < N. % Pick a unique start time and instance for each job 1 <= { start(J,S) : time(S) } <= 1 :- job(J). 1 <= { on_instance(J,I) : instance_of(D,I) } <= 1 :- job(J), job_device(J,D). %---------------------- % - overlap %---------------------- :- on_instance(J1,I), on_instance(J2,I), J1 != J2, job_device(J1,D), job_device(J2,D), start(J1,S1), job_len(J1,L1), start(J2,S2), S1 <= S2, S2 < S1 + L1. %---------------------- % - order %---------------------- :- precedes(J1,J2), start(J1,S1), job_len(J1,L1), start(J2,S2), S2 < S1 + L1. %------------------------------------- % - completion -- total-tardiness %------------------------------------- td(J,S + L - D) :- job(J), start(J,S), job_len(J,L), deadline(J,D), S + L > D. td(J,0) :- job(J), start(J,S), job_len(J,L), deadline(J,D), S + L <= D. %------------------------------------- % - completion -- penalty %------------------------------------- penalty(J,TD * I) :- job(J), td(J,TD), importance(J,I). :- penalty(J,P), max_value(MV), P > MV. tot_penalty(TP) :- pen_value(TP), TP = #sum{ P,J : penalty(J,P) }. % % If the value of the total penalty would be greater than the % maximum allowed value of pen_value(_), the above rule % does not define tot_penalty(_). % In that case, the solution is not acceptable. % has_tot_penalty :- tot_penalty(TP). -has_tot_penalty :- not has_tot_penalty. :- -has_tot_penalty. :- pen_value(TP), tot_penalty(TP), max_total_penalty(K), TP > K. %---------------------- % - instance assignment %---------------------- :- on_instance(J1,I), on_instance(J2,I), job_device(J1,D), job_device(J2,D), instances(D,N), N > 1, J1 != J2, start(J1,S1), start(J2,S2), job_len(J1,L1), S1 <= S2, S2 < S1 + L1. :- on_instance(J,I), device(D), job(J), job_device(J,D), offline_instance(D,I), must_schedule(J). %---------------------- % - current schedule %---------------------- already_started(J) :- curr_job_start(J,S), curr_time(CT), CT > S. already_finished(J) :- curr_job_start(J,S), job_len(J,L), curr_time(CT), CT >= S + L. must_schedule(J) :- job(J), not must_not_schedule(J). must_not_schedule(J) :- already_started(J), not rescheduled(J). rescheduled(J) :- already_started(J), not already_finished(J), job_device(J,D), curr_on_instance(J,I), offline_instance(D,I). :- start(J,S), curr_time(CT), S < CT, device(D), job_device(J,D), time(S), must_schedule(J). :- start(J,S), curr_job_start(J,CS), S != CS, job_device(J,D), must_not_schedule(J). :- on_instance(J,I), curr_on_instance(J,CI), I != CI, must_not_schedule(J). """

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8

c7c40a8980b0463e80cdc4ebc4a48759659fa0a3

115,654

py

Python

proyecto.py

pydae/pscig_doc

34964d1754acdae0e0a8f32da396ad1ce73e1280

[ "MIT" ]

null

proyecto.py

pydae/pscig_doc

34964d1754acdae0e0a8f32da396ad1ce73e1280

[ "MIT" ]

null

proyecto.py

pydae/pscig_doc

34964d1754acdae0e0a8f32da396ad1ce73e1280

[ "MIT" ]

null

import numpy as np import numba import scipy.optimize as sopt import json sin = np.sin cos = np.cos atan2 = np.arctan2 sqrt = np.sqrt class proyecto_class: def __init__(self): self.t_end = 10.000000 self.Dt = 0.0010000 self.decimation = 10.000000 self.itol = 1e-6 self.Dt_max = 0.001000 self.Dt_min = 0.001000 self.solvern = 5 self.imax = 100 self.N_x = 7 self.N_y = 20 self.N_z = 7 self.N_store = 10000 self.params_list = ['S_base', 'g_GRI_POI', 'b_GRI_POI', 'g_POI_PMV', 'b_POI_PMV', 'g_PMV_GR1', 'b_PMV_GR1', 'g_GR1_GR2', 'b_GR1_GR2', 'g_PMV_GR3', 'b_PMV_GR3', 'g_GR3_GR4', 'b_GR3_GR4', 'U_GRI_n', 'U_POI_n', 'U_PMV_n', 'U_GR1_n', 'U_GR2_n', 'U_GR3_n', 'U_GR4_n', 'S_n_GRI', 'X_d_GRI', 'X1d_GRI', 'T1d0_GRI', 'X_q_GRI', 'X1q_GRI', 'T1q0_GRI', 'R_a_GRI', 'X_l_GRI', 'H_GRI', 'D_GRI', 'Omega_b_GRI', 'omega_s_GRI', 'K_a_GRI', 'T_r_GRI', 'v_pss_GRI', 'Droop_GRI', 'T_m_GRI', 'K_sec_GRI', 'K_delta_GRI', 'v_ref_GRI'] self.params_values_list = [100000000.0, 1.4986238532110094, -4.995412844036698, 2.941176470588235, -11.76470588235294, 24.742268041237114, -10.996563573883162, 24.742268041237114, -10.996563573883162, 24.742268041237114, -10.996563573883162, 24.742268041237114, -10.996563573883162, 66000.0, 66000.0, 20000.0, 20000.0, 20000.0, 20000.0, 20000.0, 100000000.0, 1.81, 0.3, 8.0, 1.76, 0.65, 1.0, 0.003, 0.05, 6.0, 1.0, 314.1592653589793, 1.0, 100, 0.1, 0.0, 0.05, 5.0, 0.001, 0.01, 1.0] self.inputs_ini_list = ['P_GRI', 'Q_GRI', 'P_POI', 'Q_POI', 'P_PMV', 'Q_PMV', 'P_GR1', 'Q_GR1', 'P_GR2', 'Q_GR2', 'P_GR3', 'Q_GR3', 'P_GR4', 'Q_GR4'] self.inputs_ini_values_list = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0] self.inputs_run_list = ['P_GRI', 'Q_GRI', 'P_POI', 'Q_POI', 'P_PMV', 'Q_PMV', 'P_GR1', 'Q_GR1', 'P_GR2', 'Q_GR2', 'P_GR3', 'Q_GR3', 'P_GR4', 'Q_GR4'] self.inputs_run_values_list = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0, 1000000.0, 0.0] self.outputs_list = ['V_GRI', 'V_POI', 'V_PMV', 'V_GR1', 'V_GR2', 'V_GR3', 'V_GR4'] self.x_list = ['delta_GRI', 'omega_GRI', 'e1q_GRI', 'e1d_GRI', 'v_c_GRI', 'p_m_GRI', 'xi_m_GRI'] self.y_run_list = ['V_GRI', 'theta_GRI', 'V_POI', 'theta_POI', 'V_PMV', 'theta_PMV', 'V_GR1', 'theta_GR1', 'V_GR2', 'theta_GR2', 'V_GR3', 'theta_GR3', 'V_GR4', 'theta_GR4', 'i_d_GRI', 'i_q_GRI', 'P_GRI_1', 'Q_GRI_1', 'v_f_GRI', 'p_m_ref_GRI'] self.xy_list = self.x_list + self.y_run_list self.y_ini_list = ['V_GRI', 'theta_GRI', 'V_POI', 'theta_POI', 'V_PMV', 'theta_PMV', 'V_GR1', 'theta_GR1', 'V_GR2', 'theta_GR2', 'V_GR3', 'theta_GR3', 'V_GR4', 'theta_GR4', 'i_d_GRI', 'i_q_GRI', 'P_GRI_1', 'Q_GRI_1', 'v_f_GRI', 'p_m_ref_GRI'] self.xy_ini_list = self.x_list + self.y_ini_list self.t = 0.0 self.it = 0 self.it_store = 0 self.xy_prev = np.zeros((self.N_x+self.N_y,1)) self.initialization_tol = 1e-6 self.N_u = len(self.inputs_run_list) self.sopt_root_method='hybr' self.sopt_root_jac=True self.u_ini_list = self.inputs_ini_list self.u_ini_values_list = self.inputs_ini_values_list self.u_run_list = self.inputs_run_list self.u_run_values_list = self.inputs_run_values_list self.N_u = len(self.u_run_list) self.update() def update(self): self.N_steps = int(np.ceil(self.t_end/self.Dt)) dt = [ ('t_end', np.float64), ('Dt', np.float64), ('decimation', np.float64), ('itol', np.float64), ('Dt_max', np.float64), ('Dt_min', np.float64), ('solvern', np.int64), ('imax', np.int64), ('N_steps', np.int64), ('N_store', np.int64), ('N_x', np.int64), ('N_y', np.int64), ('N_z', np.int64), ('t', np.float64), ('it', np.int64), ('it_store', np.int64), ('idx', np.int64), ('idy', np.int64), ('f', np.float64, (self.N_x,1)), ('x', np.float64, (self.N_x,1)), ('x_0', np.float64, (self.N_x,1)), ('g', np.float64, (self.N_y,1)), ('y_run', np.float64, (self.N_y,1)), ('y_ini', np.float64, (self.N_y,1)), ('u_run', np.float64, (self.N_u,1)), ('y_0', np.float64, (self.N_y,1)), ('h', np.float64, (self.N_z,1)), ('Fx', np.float64, (self.N_x,self.N_x)), ('Fy', np.float64, (self.N_x,self.N_y)), ('Gx', np.float64, (self.N_y,self.N_x)), ('Gy', np.float64, (self.N_y,self.N_y)), ('Fu', np.float64, (self.N_x,self.N_u)), ('Gu', np.float64, (self.N_y,self.N_u)), ('Hx', np.float64, (self.N_z,self.N_x)), ('Hy', np.float64, (self.N_z,self.N_y)), ('Hu', np.float64, (self.N_z,self.N_u)), ('Fx_ini', np.float64, (self.N_x,self.N_x)), ('Fy_ini', np.float64, (self.N_x,self.N_y)), ('Gx_ini', np.float64, (self.N_y,self.N_x)), ('Gy_ini', np.float64, (self.N_y,self.N_y)), ('T', np.float64, (self.N_store+1,1)), ('X', np.float64, (self.N_store+1,self.N_x)), ('Y', np.float64, (self.N_store+1,self.N_y)), ('Z', np.float64, (self.N_store+1,self.N_z)), ('iters', np.float64, (self.N_store+1,1)), ('store', np.int64), ] values = [ self.t_end, self.Dt, self.decimation, self.itol, self.Dt_max, self.Dt_min, self.solvern, self.imax, self.N_steps, self.N_store, self.N_x, self.N_y, self.N_z, self.t, self.it, self.it_store, 0, # idx 0, # idy np.zeros((self.N_x,1)), # f np.zeros((self.N_x,1)), # x np.zeros((self.N_x,1)), # x_0 np.zeros((self.N_y,1)), # g np.zeros((self.N_y,1)), # y_run np.zeros((self.N_y,1)), # y_ini np.zeros((self.N_u,1)), # u_run np.zeros((self.N_y,1)), # y_0 np.zeros((self.N_z,1)), # h np.zeros((self.N_x,self.N_x)), # Fx np.zeros((self.N_x,self.N_y)), # Fy np.zeros((self.N_y,self.N_x)), # Gx np.zeros((self.N_y,self.N_y)), # Fy np.zeros((self.N_x,self.N_u)), # Fu np.zeros((self.N_y,self.N_u)), # Gu np.zeros((self.N_z,self.N_x)), # Hx np.zeros((self.N_z,self.N_y)), # Hy np.zeros((self.N_z,self.N_u)), # Hu np.zeros((self.N_x,self.N_x)), # Fx_ini np.zeros((self.N_x,self.N_y)), # Fy_ini np.zeros((self.N_y,self.N_x)), # Gx_ini np.zeros((self.N_y,self.N_y)), # Fy_ini np.zeros((self.N_store+1,1)), # T np.zeros((self.N_store+1,self.N_x)), # X np.zeros((self.N_store+1,self.N_y)), # Y np.zeros((self.N_store+1,self.N_z)), # Z np.zeros((self.N_store+1,1)), # iters 1, ] dt += [(item,np.float64) for item in self.params_list] values += [item for item in self.params_values_list] for item_id,item_val in zip(self.inputs_ini_list,self.inputs_ini_values_list): if item_id in self.inputs_run_list: continue dt += [(item_id,np.float64)] values += [item_val] dt += [(item,np.float64) for item in self.inputs_run_list] values += [item for item in self.inputs_run_values_list] self.struct = np.rec.array([tuple(values)], dtype=np.dtype(dt)) xy0 = np.zeros((self.N_x+self.N_y,)) self.ini_dae_jacobian_nn(xy0) self.run_dae_jacobian_nn(xy0) def load_params(self,data_input): if type(data_input) == str: json_file = data_input self.json_file = json_file self.json_data = open(json_file).read().replace("'",'"') data = json.loads(self.json_data) elif type(data_input) == dict: data = data_input self.data = data for item in self.data: self.struct[0][item] = self.data[item] self.params_values_list[self.params_list.index(item)] = self.data[item] def ini_problem(self,x): self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_ini[:,0] = x[self.N_x:(self.N_x+self.N_y)] ini(self.struct,2) ini(self.struct,3) fg = np.vstack((self.struct[0].f,self.struct[0].g))[:,0] return fg def run_problem(self,x): t = self.struct[0].t self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_run[:,0] = x[self.N_x:(self.N_x+self.N_y)] run(t,self.struct,2) run(t,self.struct,3) run(t,self.struct,10) run(t,self.struct,11) run(t,self.struct,12) run(t,self.struct,13) fg = np.vstack((self.struct[0].f,self.struct[0].g))[:,0] return fg def run_dae_jacobian(self,x): self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_run[:,0] = x[self.N_x:(self.N_x+self.N_y)] run(0.0,self.struct,10) run(0.0,self.struct,11) run(0.0,self.struct,12) run(0.0,self.struct,13) A_c = np.block([[self.struct[0].Fx,self.struct[0].Fy], [self.struct[0].Gx,self.struct[0].Gy]]) return A_c def run_dae_jacobian_nn(self,x): self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_run[:,0] = x[self.N_x:(self.N_x+self.N_y)] run_nn(0.0,self.struct,10) run_nn(0.0,self.struct,11) run_nn(0.0,self.struct,12) run_nn(0.0,self.struct,13) def eval_jacobians(self): run(0.0,self.struct,10) run(0.0,self.struct,11) run(0.0,self.struct,12) return 1 def ini_dae_jacobian(self,x): self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_ini[:,0] = x[self.N_x:(self.N_x+self.N_y)] ini(self.struct,10) ini(self.struct,11) A_c = np.block([[self.struct[0].Fx_ini,self.struct[0].Fy_ini], [self.struct[0].Gx_ini,self.struct[0].Gy_ini]]) return A_c def ini_dae_jacobian_nn(self,x): self.struct[0].x[:,0] = x[0:self.N_x] self.struct[0].y_ini[:,0] = x[self.N_x:(self.N_x+self.N_y)] ini_nn(self.struct,10) ini_nn(self.struct,11) def f_ode(self,x): self.struct[0].x[:,0] = x run(self.struct,1) return self.struct[0].f[:,0] def f_odeint(self,x,t): self.struct[0].x[:,0] = x run(self.struct,1) return self.struct[0].f[:,0] def f_ivp(self,t,x): self.struct[0].x[:,0] = x run(self.struct,1) return self.struct[0].f[:,0] def Fx_ode(self,x): self.struct[0].x[:,0] = x run(self.struct,10) return self.struct[0].Fx def eval_A(self): Fx = self.struct[0].Fx Fy = self.struct[0].Fy Gx = self.struct[0].Gx Gy = self.struct[0].Gy A = Fx - Fy @ np.linalg.solve(Gy,Gx) self.A = A return A def eval_A_ini(self): Fx = self.struct[0].Fx_ini Fy = self.struct[0].Fy_ini Gx = self.struct[0].Gx_ini Gy = self.struct[0].Gy_ini A = Fx - Fy @ np.linalg.solve(Gy,Gx) return A def reset(self): for param,param_value in zip(self.params_list,self.params_values_list): self.struct[0][param] = param_value for input_name,input_value in zip(self.inputs_ini_list,self.inputs_ini_values_list): self.struct[0][input_name] = input_value for input_name,input_value in zip(self.inputs_run_list,self.inputs_run_values_list): self.struct[0][input_name] = input_value def simulate(self,events,xy0=0): # initialize both the ini and the run system self.initialize(events,xy0=xy0) # simulation run for event in events: # make all the desired changes self.run([event]) # post process T,X,Y,Z = self.post() return T,X,Y,Z def run(self,events): # simulation run for event in events: # make all the desired changes for item in event: self.struct[0][item] = event[item] daesolver(self.struct) # run until next event return 1 def rtrun(self,events): # simulation run for event in events: # make all the desired changes for item in event: self.struct[0][item] = event[item] self.struct[0].it_store = self.struct[0].N_store-1 daesolver(self.struct) # run until next event return 1 def post(self): # post process result T = self.struct[0]['T'][:self.struct[0].it_store] X = self.struct[0]['X'][:self.struct[0].it_store,:] Y = self.struct[0]['Y'][:self.struct[0].it_store,:] Z = self.struct[0]['Z'][:self.struct[0].it_store,:] iters = self.struct[0]['iters'][:self.struct[0].it_store,:] self.T = T self.X = X self.Y = Y self.Z = Z self.iters = iters return T,X,Y,Z def save_0(self,file_name = 'xy_0.json'): xy_0_dict = {} for item in self.x_list: xy_0_dict.update({item:self.get_value(item)}) for item in self.y_ini_list: xy_0_dict.update({item:self.get_value(item)}) xy_0_str = json.dumps(xy_0_dict, indent=4) with open(file_name,'w') as fobj: fobj.write(xy_0_str) def load_0(self,file_name = 'xy_0.json'): with open(file_name) as fobj: xy_0_str = fobj.read() xy_0_dict = json.loads(xy_0_str) for item in xy_0_dict: if item in self.x_list: self.xy_prev[self.x_list.index(item)] = xy_0_dict[item] if item in self.y_ini_list: self.xy_prev[self.y_ini_list.index(item)+self.N_x] = xy_0_dict[item] def initialize(self,events=[{}],xy0=0): ''' Parameters ---------- events : dictionary Dictionary with at least 't_end' and all inputs and parameters that need to be changed. xy0 : float or string, optional 0 means all states should be zero as initial guess. If not zero all the states initial guess are the given input. If 'prev' it uses the last known initialization result as initial guess. Returns ------- T : TYPE DESCRIPTION. X : TYPE DESCRIPTION. Y : TYPE DESCRIPTION. Z : TYPE DESCRIPTION. ''' # simulation parameters self.struct[0].it = 0 # set time step to zero self.struct[0].it_store = 0 # set storage to zero self.struct[0].t = 0.0 # set time to zero # initialization it_event = 0 event = events[it_event] for item in event: self.struct[0][item] = event[item] ## compute initial conditions using x and y_ini if type(xy0) == str: if xy0 == 'prev': xy0 = self.xy_prev else: self.load_0(xy0) xy0 = self.xy_prev elif type(xy0) == dict: with open('xy_0.json','w') as fobj: fobj.write(json.dumps(xy0)) self.load_0('xy_0.json') xy0 = self.xy_prev else: if xy0 == 0: xy0 = np.zeros(self.N_x+self.N_y) elif xy0 == 1: xy0 = np.ones(self.N_x+self.N_y) else: xy0 = xy0*np.ones(self.N_x+self.N_y) #xy = sopt.fsolve(self.ini_problem,xy0, jac=self.ini_dae_jacobian ) if self.sopt_root_jac: sol = sopt.root(self.ini_problem, xy0, jac=self.ini_dae_jacobian, method=self.sopt_root_method, tol=self.initialization_tol) else: sol = sopt.root(self.ini_problem, xy0, method=self.sopt_root_method) self.initialization_ok = True if sol.success == False: print('initialization not found!') self.initialization_ok = False T = self.struct[0]['T'][:self.struct[0].it_store] X = self.struct[0]['X'][:self.struct[0].it_store,:] Y = self.struct[0]['Y'][:self.struct[0].it_store,:] Z = self.struct[0]['Z'][:self.struct[0].it_store,:] iters = self.struct[0]['iters'][:self.struct[0].it_store,:] if self.initialization_ok: xy = sol.x self.xy_prev = xy self.struct[0].x[:,0] = xy[0:self.N_x] self.struct[0].y_run[:,0] = xy[self.N_x:] ## y_ini to u_run for item in self.inputs_run_list: if item in self.y_ini_list: self.struct[0][item] = self.struct[0].y_ini[self.y_ini_list.index(item)] ## u_ini to y_run for item in self.inputs_ini_list: if item in self.y_run_list: self.struct[0].y_run[self.y_run_list.index(item)] = self.struct[0][item] #xy = sopt.fsolve(self.ini_problem,xy0, jac=self.ini_dae_jacobian ) if self.sopt_root_jac: sol = sopt.root(self.run_problem, xy0, jac=self.run_dae_jacobian, method=self.sopt_root_method, tol=self.initialization_tol) else: sol = sopt.root(self.run_problem, xy0, method=self.sopt_root_method) # evaluate f and g run(0.0,self.struct,2) run(0.0,self.struct,3) # evaluate run jacobians run(0.0,self.struct,10) run(0.0,self.struct,11) run(0.0,self.struct,12) run(0.0,self.struct,14) # post process result T = self.struct[0]['T'][:self.struct[0].it_store] X = self.struct[0]['X'][:self.struct[0].it_store,:] Y = self.struct[0]['Y'][:self.struct[0].it_store,:] Z = self.struct[0]['Z'][:self.struct[0].it_store,:] iters = self.struct[0]['iters'][:self.struct[0].it_store,:] self.T = T self.X = X self.Y = Y self.Z = Z self.iters = iters return self.initialization_ok def get_value(self,name): if name in self.inputs_run_list: value = self.struct[0][name] if name in self.x_list: idx = self.x_list.index(name) value = self.struct[0].x[idx,0] if name in self.y_run_list: idy = self.y_run_list.index(name) value = self.struct[0].y_run[idy,0] if name in self.params_list: value = self.struct[0][name] if name in self.outputs_list: value = self.struct[0].h[self.outputs_list.index(name),0] return value def get_values(self,name): if name in self.x_list: values = self.X[:,self.x_list.index(name)] if name in self.y_run_list: values = self.Y[:,self.y_run_list.index(name)] if name in self.outputs_list: values = self.Z[:,self.outputs_list.index(name)] return values def get_mvalue(self,names): ''' Parameters ---------- names : list list of variables names to return each value. Returns ------- mvalue : TYPE list of value of each variable. ''' mvalue = [] for name in names: mvalue += [self.get_value(name)] return mvalue def set_value(self,name,value): if name in self.inputs_run_list: self.struct[0][name] = value if name in self.params_list: self.struct[0][name] = value def report_x(self,value_format='5.2f'): for item in self.x_list: print(f'{item:5s} = {self.get_value(item):5.2f}') def report_y(self,value_format='5.2f'): for item in self.y_run_list: print(f'{item:5s} = {self.get_value(item):5.2f}') def report_u(self,value_format='5.2f'): for item in self.inputs_run_list: print(f'{item:5s} = {self.get_value(item):5.2f}') def report_z(self,value_format='5.2f'): for item in self.outputs_list: print(f'{item:5s} = {self.get_value(item):5.2f}') def report_params(self,value_format='5.2f'): for item in self.params_list: print(f'{item:5s} = {self.get_value(item):5.2f}') def get_x(self): return self.struct[0].x @numba.njit(cache=True) def ini(struct,mode): # Parameters: S_base = struct[0].S_base g_GRI_POI = struct[0].g_GRI_POI b_GRI_POI = struct[0].b_GRI_POI g_POI_PMV = struct[0].g_POI_PMV b_POI_PMV = struct[0].b_POI_PMV g_PMV_GR1 = struct[0].g_PMV_GR1 b_PMV_GR1 = struct[0].b_PMV_GR1 g_GR1_GR2 = struct[0].g_GR1_GR2 b_GR1_GR2 = struct[0].b_GR1_GR2 g_PMV_GR3 = struct[0].g_PMV_GR3 b_PMV_GR3 = struct[0].b_PMV_GR3 g_GR3_GR4 = struct[0].g_GR3_GR4 b_GR3_GR4 = struct[0].b_GR3_GR4 U_GRI_n = struct[0].U_GRI_n U_POI_n = struct[0].U_POI_n U_PMV_n = struct[0].U_PMV_n U_GR1_n = struct[0].U_GR1_n U_GR2_n = struct[0].U_GR2_n U_GR3_n = struct[0].U_GR3_n U_GR4_n = struct[0].U_GR4_n S_n_GRI = struct[0].S_n_GRI X_d_GRI = struct[0].X_d_GRI X1d_GRI = struct[0].X1d_GRI T1d0_GRI = struct[0].T1d0_GRI X_q_GRI = struct[0].X_q_GRI X1q_GRI = struct[0].X1q_GRI T1q0_GRI = struct[0].T1q0_GRI R_a_GRI = struct[0].R_a_GRI X_l_GRI = struct[0].X_l_GRI H_GRI = struct[0].H_GRI D_GRI = struct[0].D_GRI Omega_b_GRI = struct[0].Omega_b_GRI omega_s_GRI = struct[0].omega_s_GRI K_a_GRI = struct[0].K_a_GRI T_r_GRI = struct[0].T_r_GRI v_pss_GRI = struct[0].v_pss_GRI Droop_GRI = struct[0].Droop_GRI T_m_GRI = struct[0].T_m_GRI K_sec_GRI = struct[0].K_sec_GRI K_delta_GRI = struct[0].K_delta_GRI v_ref_GRI = struct[0].v_ref_GRI # Inputs: P_GRI = struct[0].P_GRI Q_GRI = struct[0].Q_GRI P_POI = struct[0].P_POI Q_POI = struct[0].Q_POI P_PMV = struct[0].P_PMV Q_PMV = struct[0].Q_PMV P_GR1 = struct[0].P_GR1 Q_GR1 = struct[0].Q_GR1 P_GR2 = struct[0].P_GR2 Q_GR2 = struct[0].Q_GR2 P_GR3 = struct[0].P_GR3 Q_GR3 = struct[0].Q_GR3 P_GR4 = struct[0].P_GR4 Q_GR4 = struct[0].Q_GR4 # Dynamical states: delta_GRI = struct[0].x[0,0] omega_GRI = struct[0].x[1,0] e1q_GRI = struct[0].x[2,0] e1d_GRI = struct[0].x[3,0] v_c_GRI = struct[0].x[4,0] p_m_GRI = struct[0].x[5,0] xi_m_GRI = struct[0].x[6,0] # Algebraic states: V_GRI = struct[0].y_ini[0,0] theta_GRI = struct[0].y_ini[1,0] V_POI = struct[0].y_ini[2,0] theta_POI = struct[0].y_ini[3,0] V_PMV = struct[0].y_ini[4,0] theta_PMV = struct[0].y_ini[5,0] V_GR1 = struct[0].y_ini[6,0] theta_GR1 = struct[0].y_ini[7,0] V_GR2 = struct[0].y_ini[8,0] theta_GR2 = struct[0].y_ini[9,0] V_GR3 = struct[0].y_ini[10,0] theta_GR3 = struct[0].y_ini[11,0] V_GR4 = struct[0].y_ini[12,0] theta_GR4 = struct[0].y_ini[13,0] i_d_GRI = struct[0].y_ini[14,0] i_q_GRI = struct[0].y_ini[15,0] P_GRI_1 = struct[0].y_ini[16,0] Q_GRI_1 = struct[0].y_ini[17,0] v_f_GRI = struct[0].y_ini[18,0] p_m_ref_GRI = struct[0].y_ini[19,0] # Differential equations: if mode == 2: struct[0].f[0,0] = -K_delta_GRI*delta_GRI + Omega_b_GRI*(omega_GRI - omega_s_GRI) struct[0].f[1,0] = (-D_GRI*(omega_GRI - omega_s_GRI) - i_d_GRI*(R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI)) - i_q_GRI*(R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI)) + p_m_GRI)/(2*H_GRI) struct[0].f[2,0] = (-e1q_GRI - i_d_GRI*(-X1d_GRI + X_d_GRI) + v_f_GRI)/T1d0_GRI struct[0].f[3,0] = (-e1d_GRI + i_q_GRI*(-X1q_GRI + X_q_GRI))/T1q0_GRI struct[0].f[4,0] = (V_GRI - v_c_GRI)/T_r_GRI struct[0].f[5,0] = (-p_m_GRI + p_m_ref_GRI)/T_m_GRI struct[0].f[6,0] = omega_GRI - 1 # Algebraic equations: if mode == 3: g_n = np.ascontiguousarray(struct[0].Gy_ini) @ np.ascontiguousarray(struct[0].y_ini) struct[0].g[0,0] = -P_GRI/S_base - P_GRI_1/S_base + V_GRI**2*g_GRI_POI + V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].g[1,0] = -Q_GRI/S_base - Q_GRI_1/S_base - V_GRI**2*b_GRI_POI + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].g[2,0] = -P_POI/S_base + V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + V_POI**2*(g_GRI_POI + g_POI_PMV) struct[0].g[3,0] = -Q_POI/S_base + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + V_POI**2*(-b_GRI_POI - b_POI_PMV) struct[0].g[4,0] = -P_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV**2*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].g[5,0] = -Q_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV**2*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].g[6,0] = -P_GR1/S_base + V_GR1**2*(g_GR1_GR2 + g_PMV_GR1) + V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].g[7,0] = -Q_GR1/S_base + V_GR1**2*(-b_GR1_GR2 - b_PMV_GR1) + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].g[8,0] = -P_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR2**2*g_GR1_GR2 struct[0].g[9,0] = -Q_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - V_GR2**2*b_GR1_GR2 struct[0].g[10,0] = -P_GR3/S_base + V_GR3**2*(g_GR3_GR4 + g_PMV_GR3) + V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].g[11,0] = -Q_GR3/S_base + V_GR3**2*(-b_GR3_GR4 - b_PMV_GR3) + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].g[12,0] = -P_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR4**2*g_GR3_GR4 struct[0].g[13,0] = -Q_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - V_GR4**2*b_GR3_GR4 struct[0].g[14,0] = R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI) + X1d_GRI*i_d_GRI - e1q_GRI struct[0].g[15,0] = R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI) - X1q_GRI*i_q_GRI - e1d_GRI struct[0].g[16,0] = -P_GRI_1/S_n_GRI + V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].g[17,0] = -Q_GRI_1/S_n_GRI + V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].g[18,0] = K_a_GRI*(-v_c_GRI + v_pss_GRI + v_ref_GRI) - v_f_GRI struct[0].g[19,0] = -K_sec_GRI*xi_m_GRI - p_m_ref_GRI - (omega_GRI - 1)/Droop_GRI # Outputs: if mode == 3: struct[0].h[0,0] = V_GRI struct[0].h[1,0] = V_POI struct[0].h[2,0] = V_PMV struct[0].h[3,0] = V_GR1 struct[0].h[4,0] = V_GR2 struct[0].h[5,0] = V_GR3 struct[0].h[6,0] = V_GR4 if mode == 10: struct[0].Fx_ini[0,0] = -K_delta_GRI struct[0].Fx_ini[0,1] = Omega_b_GRI struct[0].Fx_ini[1,0] = (-V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fx_ini[1,1] = -D_GRI/(2*H_GRI) struct[0].Fx_ini[1,5] = 1/(2*H_GRI) struct[0].Fx_ini[2,2] = -1/T1d0_GRI struct[0].Fx_ini[3,3] = -1/T1q0_GRI struct[0].Fx_ini[4,4] = -1/T_r_GRI struct[0].Fx_ini[5,5] = -1/T_m_GRI if mode == 11: struct[0].Fy_ini[1,0] = (-i_d_GRI*sin(delta_GRI - theta_GRI) - i_q_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,1] = (V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,14] = (-2*R_a_GRI*i_d_GRI - V_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,15] = (-2*R_a_GRI*i_q_GRI - V_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[2,14] = (X1d_GRI - X_d_GRI)/T1d0_GRI struct[0].Fy_ini[2,18] = 1/T1d0_GRI struct[0].Fy_ini[3,15] = (-X1q_GRI + X_q_GRI)/T1q0_GRI struct[0].Fy_ini[4,0] = 1/T_r_GRI struct[0].Fy_ini[5,19] = 1/T_m_GRI struct[0].Gx_ini[14,0] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gx_ini[14,2] = -1 struct[0].Gx_ini[15,0] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gx_ini[15,3] = -1 struct[0].Gx_ini[16,0] = V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gx_ini[17,0] = -V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gx_ini[18,4] = -K_a_GRI struct[0].Gx_ini[19,1] = -1/Droop_GRI struct[0].Gx_ini[19,6] = -K_sec_GRI struct[0].Gy_ini[0,0] = 2*V_GRI*g_GRI_POI + V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[0,1] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[0,2] = V_GRI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[0,3] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[0,16] = -1/S_base struct[0].Gy_ini[1,0] = -2*V_GRI*b_GRI_POI + V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[1,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[1,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[1,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[1,17] = -1/S_base struct[0].Gy_ini[2,0] = V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[2,1] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[2,2] = V_GRI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + 2*V_POI*(g_GRI_POI + g_POI_PMV) struct[0].Gy_ini[2,3] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[2,4] = V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[2,5] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[3,0] = V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[3,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[3,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + 2*V_POI*(-b_GRI_POI - b_POI_PMV) struct[0].Gy_ini[3,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[3,4] = V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[3,5] = V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,2] = V_PMV*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,3] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[4,4] = V_GR1*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + 2*V_PMV*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,5] = V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[4,6] = V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[4,7] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[4,10] = V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[4,11] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[5,2] = V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[5,3] = V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[5,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + 2*V_PMV*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[5,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[5,6] = V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[5,7] = V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[5,10] = V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[5,11] = V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[6,4] = V_GR1*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,5] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,6] = 2*V_GR1*(g_GR1_GR2 + g_PMV_GR1) + V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,7] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,8] = V_GR1*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[6,9] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[7,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,6] = 2*V_GR1*(-b_GR1_GR2 - b_PMV_GR1) + V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[7,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,6] = V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,7] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,8] = V_GR1*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + 2*V_GR2*g_GR1_GR2 struct[0].Gy_ini[8,9] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,6] = V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - 2*V_GR2*b_GR1_GR2 struct[0].Gy_ini[9,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[10,4] = V_GR3*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,5] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,10] = 2*V_GR3*(g_GR3_GR4 + g_PMV_GR3) + V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,11] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,12] = V_GR3*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[10,13] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[11,4] = V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,5] = V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,10] = 2*V_GR3*(-b_GR3_GR4 - b_PMV_GR3) + V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[11,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,10] = V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,11] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,12] = V_GR3*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + 2*V_GR4*g_GR3_GR4 struct[0].Gy_ini[12,13] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,10] = V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - 2*V_GR4*b_GR3_GR4 struct[0].Gy_ini[13,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[14,0] = cos(delta_GRI - theta_GRI) struct[0].Gy_ini[14,1] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[14,14] = X1d_GRI struct[0].Gy_ini[14,15] = R_a_GRI struct[0].Gy_ini[15,0] = sin(delta_GRI - theta_GRI) struct[0].Gy_ini[15,1] = -V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[15,14] = R_a_GRI struct[0].Gy_ini[15,15] = -X1q_GRI struct[0].Gy_ini[16,0] = i_d_GRI*sin(delta_GRI - theta_GRI) + i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[16,1] = -V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[16,14] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[16,15] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[16,16] = -1/S_n_GRI struct[0].Gy_ini[17,0] = i_d_GRI*cos(delta_GRI - theta_GRI) - i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[17,1] = V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[17,14] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[17,15] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[17,17] = -1/S_n_GRI @numba.njit(cache=True) def run(t,struct,mode): # Parameters: S_base = struct[0].S_base g_GRI_POI = struct[0].g_GRI_POI b_GRI_POI = struct[0].b_GRI_POI g_POI_PMV = struct[0].g_POI_PMV b_POI_PMV = struct[0].b_POI_PMV g_PMV_GR1 = struct[0].g_PMV_GR1 b_PMV_GR1 = struct[0].b_PMV_GR1 g_GR1_GR2 = struct[0].g_GR1_GR2 b_GR1_GR2 = struct[0].b_GR1_GR2 g_PMV_GR3 = struct[0].g_PMV_GR3 b_PMV_GR3 = struct[0].b_PMV_GR3 g_GR3_GR4 = struct[0].g_GR3_GR4 b_GR3_GR4 = struct[0].b_GR3_GR4 U_GRI_n = struct[0].U_GRI_n U_POI_n = struct[0].U_POI_n U_PMV_n = struct[0].U_PMV_n U_GR1_n = struct[0].U_GR1_n U_GR2_n = struct[0].U_GR2_n U_GR3_n = struct[0].U_GR3_n U_GR4_n = struct[0].U_GR4_n S_n_GRI = struct[0].S_n_GRI X_d_GRI = struct[0].X_d_GRI X1d_GRI = struct[0].X1d_GRI T1d0_GRI = struct[0].T1d0_GRI X_q_GRI = struct[0].X_q_GRI X1q_GRI = struct[0].X1q_GRI T1q0_GRI = struct[0].T1q0_GRI R_a_GRI = struct[0].R_a_GRI X_l_GRI = struct[0].X_l_GRI H_GRI = struct[0].H_GRI D_GRI = struct[0].D_GRI Omega_b_GRI = struct[0].Omega_b_GRI omega_s_GRI = struct[0].omega_s_GRI K_a_GRI = struct[0].K_a_GRI T_r_GRI = struct[0].T_r_GRI v_pss_GRI = struct[0].v_pss_GRI Droop_GRI = struct[0].Droop_GRI T_m_GRI = struct[0].T_m_GRI K_sec_GRI = struct[0].K_sec_GRI K_delta_GRI = struct[0].K_delta_GRI v_ref_GRI = struct[0].v_ref_GRI # Inputs: P_GRI = struct[0].P_GRI Q_GRI = struct[0].Q_GRI P_POI = struct[0].P_POI Q_POI = struct[0].Q_POI P_PMV = struct[0].P_PMV Q_PMV = struct[0].Q_PMV P_GR1 = struct[0].P_GR1 Q_GR1 = struct[0].Q_GR1 P_GR2 = struct[0].P_GR2 Q_GR2 = struct[0].Q_GR2 P_GR3 = struct[0].P_GR3 Q_GR3 = struct[0].Q_GR3 P_GR4 = struct[0].P_GR4 Q_GR4 = struct[0].Q_GR4 # Dynamical states: delta_GRI = struct[0].x[0,0] omega_GRI = struct[0].x[1,0] e1q_GRI = struct[0].x[2,0] e1d_GRI = struct[0].x[3,0] v_c_GRI = struct[0].x[4,0] p_m_GRI = struct[0].x[5,0] xi_m_GRI = struct[0].x[6,0] # Algebraic states: V_GRI = struct[0].y_run[0,0] theta_GRI = struct[0].y_run[1,0] V_POI = struct[0].y_run[2,0] theta_POI = struct[0].y_run[3,0] V_PMV = struct[0].y_run[4,0] theta_PMV = struct[0].y_run[5,0] V_GR1 = struct[0].y_run[6,0] theta_GR1 = struct[0].y_run[7,0] V_GR2 = struct[0].y_run[8,0] theta_GR2 = struct[0].y_run[9,0] V_GR3 = struct[0].y_run[10,0] theta_GR3 = struct[0].y_run[11,0] V_GR4 = struct[0].y_run[12,0] theta_GR4 = struct[0].y_run[13,0] i_d_GRI = struct[0].y_run[14,0] i_q_GRI = struct[0].y_run[15,0] P_GRI_1 = struct[0].y_run[16,0] Q_GRI_1 = struct[0].y_run[17,0] v_f_GRI = struct[0].y_run[18,0] p_m_ref_GRI = struct[0].y_run[19,0] struct[0].u_run[0,0] = P_GRI struct[0].u_run[1,0] = Q_GRI struct[0].u_run[2,0] = P_POI struct[0].u_run[3,0] = Q_POI struct[0].u_run[4,0] = P_PMV struct[0].u_run[5,0] = Q_PMV struct[0].u_run[6,0] = P_GR1 struct[0].u_run[7,0] = Q_GR1 struct[0].u_run[8,0] = P_GR2 struct[0].u_run[9,0] = Q_GR2 struct[0].u_run[10,0] = P_GR3 struct[0].u_run[11,0] = Q_GR3 struct[0].u_run[12,0] = P_GR4 struct[0].u_run[13,0] = Q_GR4 # Differential equations: if mode == 2: struct[0].f[0,0] = -K_delta_GRI*delta_GRI + Omega_b_GRI*(omega_GRI - omega_s_GRI) struct[0].f[1,0] = (-D_GRI*(omega_GRI - omega_s_GRI) - i_d_GRI*(R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI)) - i_q_GRI*(R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI)) + p_m_GRI)/(2*H_GRI) struct[0].f[2,0] = (-e1q_GRI - i_d_GRI*(-X1d_GRI + X_d_GRI) + v_f_GRI)/T1d0_GRI struct[0].f[3,0] = (-e1d_GRI + i_q_GRI*(-X1q_GRI + X_q_GRI))/T1q0_GRI struct[0].f[4,0] = (V_GRI - v_c_GRI)/T_r_GRI struct[0].f[5,0] = (-p_m_GRI + p_m_ref_GRI)/T_m_GRI struct[0].f[6,0] = omega_GRI - 1 # Algebraic equations: if mode == 3: g_n = np.ascontiguousarray(struct[0].Gy) @ np.ascontiguousarray(struct[0].y_run) + np.ascontiguousarray(struct[0].Gu) @ np.ascontiguousarray(struct[0].u_run) struct[0].g[0,0] = -P_GRI/S_base - P_GRI_1/S_base + V_GRI**2*g_GRI_POI + V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].g[1,0] = -Q_GRI/S_base - Q_GRI_1/S_base - V_GRI**2*b_GRI_POI + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].g[2,0] = -P_POI/S_base + V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + V_POI**2*(g_GRI_POI + g_POI_PMV) struct[0].g[3,0] = -Q_POI/S_base + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + V_POI**2*(-b_GRI_POI - b_POI_PMV) struct[0].g[4,0] = -P_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV**2*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].g[5,0] = -Q_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV**2*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].g[6,0] = -P_GR1/S_base + V_GR1**2*(g_GR1_GR2 + g_PMV_GR1) + V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].g[7,0] = -Q_GR1/S_base + V_GR1**2*(-b_GR1_GR2 - b_PMV_GR1) + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].g[8,0] = -P_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR2**2*g_GR1_GR2 struct[0].g[9,0] = -Q_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - V_GR2**2*b_GR1_GR2 struct[0].g[10,0] = -P_GR3/S_base + V_GR3**2*(g_GR3_GR4 + g_PMV_GR3) + V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].g[11,0] = -Q_GR3/S_base + V_GR3**2*(-b_GR3_GR4 - b_PMV_GR3) + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].g[12,0] = -P_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR4**2*g_GR3_GR4 struct[0].g[13,0] = -Q_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - V_GR4**2*b_GR3_GR4 struct[0].g[14,0] = R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI) + X1d_GRI*i_d_GRI - e1q_GRI struct[0].g[15,0] = R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI) - X1q_GRI*i_q_GRI - e1d_GRI struct[0].g[16,0] = -P_GRI_1/S_n_GRI + V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].g[17,0] = -Q_GRI_1/S_n_GRI + V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].g[18,0] = K_a_GRI*(-v_c_GRI + v_pss_GRI + v_ref_GRI) - v_f_GRI struct[0].g[19,0] = -K_sec_GRI*xi_m_GRI - p_m_ref_GRI - (omega_GRI - 1)/Droop_GRI # Outputs: if mode == 3: struct[0].h[0,0] = V_GRI struct[0].h[1,0] = V_POI struct[0].h[2,0] = V_PMV struct[0].h[3,0] = V_GR1 struct[0].h[4,0] = V_GR2 struct[0].h[5,0] = V_GR3 struct[0].h[6,0] = V_GR4 if mode == 10: struct[0].Fx[0,0] = -K_delta_GRI struct[0].Fx[0,1] = Omega_b_GRI struct[0].Fx[1,0] = (-V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fx[1,1] = -D_GRI/(2*H_GRI) struct[0].Fx[1,5] = 1/(2*H_GRI) struct[0].Fx[2,2] = -1/T1d0_GRI struct[0].Fx[3,3] = -1/T1q0_GRI struct[0].Fx[4,4] = -1/T_r_GRI struct[0].Fx[5,5] = -1/T_m_GRI if mode == 11: struct[0].Fy[1,0] = (-i_d_GRI*sin(delta_GRI - theta_GRI) - i_q_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,1] = (V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,14] = (-2*R_a_GRI*i_d_GRI - V_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,15] = (-2*R_a_GRI*i_q_GRI - V_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[2,14] = (X1d_GRI - X_d_GRI)/T1d0_GRI struct[0].Fy[2,18] = 1/T1d0_GRI struct[0].Fy[3,15] = (-X1q_GRI + X_q_GRI)/T1q0_GRI struct[0].Fy[4,0] = 1/T_r_GRI struct[0].Fy[5,19] = 1/T_m_GRI struct[0].Gx[14,0] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gx[14,2] = -1 struct[0].Gx[15,0] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gx[15,3] = -1 struct[0].Gx[16,0] = V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gx[17,0] = -V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gx[18,4] = -K_a_GRI struct[0].Gx[19,1] = -1/Droop_GRI struct[0].Gx[19,6] = -K_sec_GRI struct[0].Gy[0,0] = 2*V_GRI*g_GRI_POI + V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[0,1] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[0,2] = V_GRI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[0,3] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[0,16] = -1/S_base struct[0].Gy[1,0] = -2*V_GRI*b_GRI_POI + V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[1,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[1,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[1,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[1,17] = -1/S_base struct[0].Gy[2,0] = V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[2,1] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[2,2] = V_GRI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + 2*V_POI*(g_GRI_POI + g_POI_PMV) struct[0].Gy[2,3] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[2,4] = V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[2,5] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[3,0] = V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[3,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[3,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + 2*V_POI*(-b_GRI_POI - b_POI_PMV) struct[0].Gy[3,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[3,4] = V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[3,5] = V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,2] = V_PMV*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,3] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[4,4] = V_GR1*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + 2*V_PMV*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,5] = V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[4,6] = V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[4,7] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[4,10] = V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[4,11] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[5,2] = V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[5,3] = V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[5,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + 2*V_PMV*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[5,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[5,6] = V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[5,7] = V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[5,10] = V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[5,11] = V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[6,4] = V_GR1*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[6,5] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[6,6] = 2*V_GR1*(g_GR1_GR2 + g_PMV_GR1) + V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[6,7] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[6,8] = V_GR1*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[6,9] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[7,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[7,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[7,6] = 2*V_GR1*(-b_GR1_GR2 - b_PMV_GR1) + V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[7,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[7,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[7,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[8,6] = V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[8,7] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[8,8] = V_GR1*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + 2*V_GR2*g_GR1_GR2 struct[0].Gy[8,9] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[9,6] = V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[9,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[9,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - 2*V_GR2*b_GR1_GR2 struct[0].Gy[9,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[10,4] = V_GR3*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[10,5] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[10,10] = 2*V_GR3*(g_GR3_GR4 + g_PMV_GR3) + V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[10,11] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[10,12] = V_GR3*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[10,13] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[11,4] = V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[11,5] = V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[11,10] = 2*V_GR3*(-b_GR3_GR4 - b_PMV_GR3) + V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[11,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[11,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[11,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[12,10] = V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[12,11] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[12,12] = V_GR3*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + 2*V_GR4*g_GR3_GR4 struct[0].Gy[12,13] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[13,10] = V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[13,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[13,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - 2*V_GR4*b_GR3_GR4 struct[0].Gy[13,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[14,0] = cos(delta_GRI - theta_GRI) struct[0].Gy[14,1] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[14,14] = X1d_GRI struct[0].Gy[14,15] = R_a_GRI struct[0].Gy[15,0] = sin(delta_GRI - theta_GRI) struct[0].Gy[15,1] = -V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[15,14] = R_a_GRI struct[0].Gy[15,15] = -X1q_GRI struct[0].Gy[16,0] = i_d_GRI*sin(delta_GRI - theta_GRI) + i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[16,1] = -V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[16,14] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[16,15] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[16,16] = -1/S_n_GRI struct[0].Gy[17,0] = i_d_GRI*cos(delta_GRI - theta_GRI) - i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[17,1] = V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[17,14] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[17,15] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[17,17] = -1/S_n_GRI if mode > 12: struct[0].Gu[0,0] = -1/S_base struct[0].Gu[1,1] = -1/S_base struct[0].Gu[2,2] = -1/S_base struct[0].Gu[3,3] = -1/S_base struct[0].Gu[4,4] = -1/S_base struct[0].Gu[5,5] = -1/S_base struct[0].Gu[6,6] = -1/S_base struct[0].Gu[7,7] = -1/S_base struct[0].Gu[8,8] = -1/S_base struct[0].Gu[9,9] = -1/S_base struct[0].Gu[10,10] = -1/S_base struct[0].Gu[11,11] = -1/S_base struct[0].Gu[12,12] = -1/S_base struct[0].Gu[13,13] = -1/S_base struct[0].Hy[0,0] = 1 struct[0].Hy[1,2] = 1 struct[0].Hy[2,4] = 1 struct[0].Hy[3,6] = 1 struct[0].Hy[4,8] = 1 struct[0].Hy[5,10] = 1 struct[0].Hy[6,12] = 1 def ini_nn(struct,mode): # Parameters: S_base = struct[0].S_base g_GRI_POI = struct[0].g_GRI_POI b_GRI_POI = struct[0].b_GRI_POI g_POI_PMV = struct[0].g_POI_PMV b_POI_PMV = struct[0].b_POI_PMV g_PMV_GR1 = struct[0].g_PMV_GR1 b_PMV_GR1 = struct[0].b_PMV_GR1 g_GR1_GR2 = struct[0].g_GR1_GR2 b_GR1_GR2 = struct[0].b_GR1_GR2 g_PMV_GR3 = struct[0].g_PMV_GR3 b_PMV_GR3 = struct[0].b_PMV_GR3 g_GR3_GR4 = struct[0].g_GR3_GR4 b_GR3_GR4 = struct[0].b_GR3_GR4 U_GRI_n = struct[0].U_GRI_n U_POI_n = struct[0].U_POI_n U_PMV_n = struct[0].U_PMV_n U_GR1_n = struct[0].U_GR1_n U_GR2_n = struct[0].U_GR2_n U_GR3_n = struct[0].U_GR3_n U_GR4_n = struct[0].U_GR4_n S_n_GRI = struct[0].S_n_GRI X_d_GRI = struct[0].X_d_GRI X1d_GRI = struct[0].X1d_GRI T1d0_GRI = struct[0].T1d0_GRI X_q_GRI = struct[0].X_q_GRI X1q_GRI = struct[0].X1q_GRI T1q0_GRI = struct[0].T1q0_GRI R_a_GRI = struct[0].R_a_GRI X_l_GRI = struct[0].X_l_GRI H_GRI = struct[0].H_GRI D_GRI = struct[0].D_GRI Omega_b_GRI = struct[0].Omega_b_GRI omega_s_GRI = struct[0].omega_s_GRI K_a_GRI = struct[0].K_a_GRI T_r_GRI = struct[0].T_r_GRI v_pss_GRI = struct[0].v_pss_GRI Droop_GRI = struct[0].Droop_GRI T_m_GRI = struct[0].T_m_GRI K_sec_GRI = struct[0].K_sec_GRI K_delta_GRI = struct[0].K_delta_GRI v_ref_GRI = struct[0].v_ref_GRI # Inputs: P_GRI = struct[0].P_GRI Q_GRI = struct[0].Q_GRI P_POI = struct[0].P_POI Q_POI = struct[0].Q_POI P_PMV = struct[0].P_PMV Q_PMV = struct[0].Q_PMV P_GR1 = struct[0].P_GR1 Q_GR1 = struct[0].Q_GR1 P_GR2 = struct[0].P_GR2 Q_GR2 = struct[0].Q_GR2 P_GR3 = struct[0].P_GR3 Q_GR3 = struct[0].Q_GR3 P_GR4 = struct[0].P_GR4 Q_GR4 = struct[0].Q_GR4 # Dynamical states: delta_GRI = struct[0].x[0,0] omega_GRI = struct[0].x[1,0] e1q_GRI = struct[0].x[2,0] e1d_GRI = struct[0].x[3,0] v_c_GRI = struct[0].x[4,0] p_m_GRI = struct[0].x[5,0] xi_m_GRI = struct[0].x[6,0] # Algebraic states: V_GRI = struct[0].y_ini[0,0] theta_GRI = struct[0].y_ini[1,0] V_POI = struct[0].y_ini[2,0] theta_POI = struct[0].y_ini[3,0] V_PMV = struct[0].y_ini[4,0] theta_PMV = struct[0].y_ini[5,0] V_GR1 = struct[0].y_ini[6,0] theta_GR1 = struct[0].y_ini[7,0] V_GR2 = struct[0].y_ini[8,0] theta_GR2 = struct[0].y_ini[9,0] V_GR3 = struct[0].y_ini[10,0] theta_GR3 = struct[0].y_ini[11,0] V_GR4 = struct[0].y_ini[12,0] theta_GR4 = struct[0].y_ini[13,0] i_d_GRI = struct[0].y_ini[14,0] i_q_GRI = struct[0].y_ini[15,0] P_GRI_1 = struct[0].y_ini[16,0] Q_GRI_1 = struct[0].y_ini[17,0] v_f_GRI = struct[0].y_ini[18,0] p_m_ref_GRI = struct[0].y_ini[19,0] # Differential equations: if mode == 2: struct[0].f[0,0] = -K_delta_GRI*delta_GRI + Omega_b_GRI*(omega_GRI - omega_s_GRI) struct[0].f[1,0] = (-D_GRI*(omega_GRI - omega_s_GRI) - i_d_GRI*(R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI)) - i_q_GRI*(R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI)) + p_m_GRI)/(2*H_GRI) struct[0].f[2,0] = (-e1q_GRI - i_d_GRI*(-X1d_GRI + X_d_GRI) + v_f_GRI)/T1d0_GRI struct[0].f[3,0] = (-e1d_GRI + i_q_GRI*(-X1q_GRI + X_q_GRI))/T1q0_GRI struct[0].f[4,0] = (V_GRI - v_c_GRI)/T_r_GRI struct[0].f[5,0] = (-p_m_GRI + p_m_ref_GRI)/T_m_GRI struct[0].f[6,0] = omega_GRI - 1 # Algebraic equations: if mode == 3: struct[0].g[0,0] = -P_GRI/S_base - P_GRI_1/S_base + V_GRI**2*g_GRI_POI + V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].g[1,0] = -Q_GRI/S_base - Q_GRI_1/S_base - V_GRI**2*b_GRI_POI + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].g[2,0] = -P_POI/S_base + V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + V_POI**2*(g_GRI_POI + g_POI_PMV) struct[0].g[3,0] = -Q_POI/S_base + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + V_POI**2*(-b_GRI_POI - b_POI_PMV) struct[0].g[4,0] = -P_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV**2*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].g[5,0] = -Q_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV**2*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].g[6,0] = -P_GR1/S_base + V_GR1**2*(g_GR1_GR2 + g_PMV_GR1) + V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].g[7,0] = -Q_GR1/S_base + V_GR1**2*(-b_GR1_GR2 - b_PMV_GR1) + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].g[8,0] = -P_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR2**2*g_GR1_GR2 struct[0].g[9,0] = -Q_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - V_GR2**2*b_GR1_GR2 struct[0].g[10,0] = -P_GR3/S_base + V_GR3**2*(g_GR3_GR4 + g_PMV_GR3) + V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].g[11,0] = -Q_GR3/S_base + V_GR3**2*(-b_GR3_GR4 - b_PMV_GR3) + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].g[12,0] = -P_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR4**2*g_GR3_GR4 struct[0].g[13,0] = -Q_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - V_GR4**2*b_GR3_GR4 struct[0].g[14,0] = R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI) + X1d_GRI*i_d_GRI - e1q_GRI struct[0].g[15,0] = R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI) - X1q_GRI*i_q_GRI - e1d_GRI struct[0].g[16,0] = -P_GRI_1/S_n_GRI + V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].g[17,0] = -Q_GRI_1/S_n_GRI + V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].g[18,0] = K_a_GRI*(-v_c_GRI + v_pss_GRI + v_ref_GRI) - v_f_GRI struct[0].g[19,0] = -K_sec_GRI*xi_m_GRI - p_m_ref_GRI - (omega_GRI - 1)/Droop_GRI # Outputs: if mode == 3: struct[0].h[0,0] = V_GRI struct[0].h[1,0] = V_POI struct[0].h[2,0] = V_PMV struct[0].h[3,0] = V_GR1 struct[0].h[4,0] = V_GR2 struct[0].h[5,0] = V_GR3 struct[0].h[6,0] = V_GR4 if mode == 10: struct[0].Fx_ini[0,0] = -K_delta_GRI struct[0].Fx_ini[0,1] = Omega_b_GRI struct[0].Fx_ini[1,0] = (-V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fx_ini[1,1] = -D_GRI/(2*H_GRI) struct[0].Fx_ini[1,5] = 1/(2*H_GRI) struct[0].Fx_ini[2,2] = -1/T1d0_GRI struct[0].Fx_ini[3,3] = -1/T1q0_GRI struct[0].Fx_ini[4,4] = -1/T_r_GRI struct[0].Fx_ini[5,5] = -1/T_m_GRI struct[0].Fx_ini[6,1] = 1 if mode == 11: struct[0].Fy_ini[1,0] = (-i_d_GRI*sin(delta_GRI - theta_GRI) - i_q_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,1] = (V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,14] = (-2*R_a_GRI*i_d_GRI - V_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[1,15] = (-2*R_a_GRI*i_q_GRI - V_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy_ini[2,14] = (X1d_GRI - X_d_GRI)/T1d0_GRI struct[0].Fy_ini[2,18] = 1/T1d0_GRI struct[0].Fy_ini[3,15] = (-X1q_GRI + X_q_GRI)/T1q0_GRI struct[0].Fy_ini[4,0] = 1/T_r_GRI struct[0].Fy_ini[5,19] = 1/T_m_GRI struct[0].Gy_ini[0,0] = 2*V_GRI*g_GRI_POI + V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[0,1] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[0,2] = V_GRI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[0,3] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[0,16] = -1/S_base struct[0].Gy_ini[1,0] = -2*V_GRI*b_GRI_POI + V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[1,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[1,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[1,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[1,17] = -1/S_base struct[0].Gy_ini[2,0] = V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[2,1] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[2,2] = V_GRI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + 2*V_POI*(g_GRI_POI + g_POI_PMV) struct[0].Gy_ini[2,3] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[2,4] = V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[2,5] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[3,0] = V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy_ini[3,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy_ini[3,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + 2*V_POI*(-b_GRI_POI - b_POI_PMV) struct[0].Gy_ini[3,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[3,4] = V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[3,5] = V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,2] = V_PMV*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,3] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[4,4] = V_GR1*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + 2*V_PMV*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[4,5] = V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[4,6] = V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[4,7] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[4,10] = V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[4,11] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[5,2] = V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[5,3] = V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[5,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + 2*V_PMV*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy_ini[5,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy_ini[5,6] = V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[5,7] = V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[5,10] = V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[5,11] = V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[6,4] = V_GR1*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,5] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,6] = 2*V_GR1*(g_GR1_GR2 + g_PMV_GR1) + V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,7] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[6,8] = V_GR1*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[6,9] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[7,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,6] = 2*V_GR1*(-b_GR1_GR2 - b_PMV_GR1) + V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy_ini[7,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[7,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,6] = V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,7] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[8,8] = V_GR1*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + 2*V_GR2*g_GR1_GR2 struct[0].Gy_ini[8,9] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,6] = V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[9,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - 2*V_GR2*b_GR1_GR2 struct[0].Gy_ini[9,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy_ini[10,4] = V_GR3*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,5] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,10] = 2*V_GR3*(g_GR3_GR4 + g_PMV_GR3) + V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,11] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[10,12] = V_GR3*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[10,13] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[11,4] = V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,5] = V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,10] = 2*V_GR3*(-b_GR3_GR4 - b_PMV_GR3) + V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy_ini[11,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[11,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,10] = V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,11] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[12,12] = V_GR3*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + 2*V_GR4*g_GR3_GR4 struct[0].Gy_ini[12,13] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,10] = V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[13,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - 2*V_GR4*b_GR3_GR4 struct[0].Gy_ini[13,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy_ini[14,0] = cos(delta_GRI - theta_GRI) struct[0].Gy_ini[14,1] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[14,14] = X1d_GRI struct[0].Gy_ini[14,15] = R_a_GRI struct[0].Gy_ini[15,0] = sin(delta_GRI - theta_GRI) struct[0].Gy_ini[15,1] = -V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[15,14] = R_a_GRI struct[0].Gy_ini[15,15] = -X1q_GRI struct[0].Gy_ini[16,0] = i_d_GRI*sin(delta_GRI - theta_GRI) + i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[16,1] = -V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[16,14] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[16,15] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[16,16] = -1/S_n_GRI struct[0].Gy_ini[17,0] = i_d_GRI*cos(delta_GRI - theta_GRI) - i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[17,1] = V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[17,14] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy_ini[17,15] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy_ini[17,17] = -1/S_n_GRI struct[0].Gy_ini[18,18] = -1 struct[0].Gy_ini[19,19] = -1 def run_nn(t,struct,mode): # Parameters: S_base = struct[0].S_base g_GRI_POI = struct[0].g_GRI_POI b_GRI_POI = struct[0].b_GRI_POI g_POI_PMV = struct[0].g_POI_PMV b_POI_PMV = struct[0].b_POI_PMV g_PMV_GR1 = struct[0].g_PMV_GR1 b_PMV_GR1 = struct[0].b_PMV_GR1 g_GR1_GR2 = struct[0].g_GR1_GR2 b_GR1_GR2 = struct[0].b_GR1_GR2 g_PMV_GR3 = struct[0].g_PMV_GR3 b_PMV_GR3 = struct[0].b_PMV_GR3 g_GR3_GR4 = struct[0].g_GR3_GR4 b_GR3_GR4 = struct[0].b_GR3_GR4 U_GRI_n = struct[0].U_GRI_n U_POI_n = struct[0].U_POI_n U_PMV_n = struct[0].U_PMV_n U_GR1_n = struct[0].U_GR1_n U_GR2_n = struct[0].U_GR2_n U_GR3_n = struct[0].U_GR3_n U_GR4_n = struct[0].U_GR4_n S_n_GRI = struct[0].S_n_GRI X_d_GRI = struct[0].X_d_GRI X1d_GRI = struct[0].X1d_GRI T1d0_GRI = struct[0].T1d0_GRI X_q_GRI = struct[0].X_q_GRI X1q_GRI = struct[0].X1q_GRI T1q0_GRI = struct[0].T1q0_GRI R_a_GRI = struct[0].R_a_GRI X_l_GRI = struct[0].X_l_GRI H_GRI = struct[0].H_GRI D_GRI = struct[0].D_GRI Omega_b_GRI = struct[0].Omega_b_GRI omega_s_GRI = struct[0].omega_s_GRI K_a_GRI = struct[0].K_a_GRI T_r_GRI = struct[0].T_r_GRI v_pss_GRI = struct[0].v_pss_GRI Droop_GRI = struct[0].Droop_GRI T_m_GRI = struct[0].T_m_GRI K_sec_GRI = struct[0].K_sec_GRI K_delta_GRI = struct[0].K_delta_GRI v_ref_GRI = struct[0].v_ref_GRI # Inputs: P_GRI = struct[0].P_GRI Q_GRI = struct[0].Q_GRI P_POI = struct[0].P_POI Q_POI = struct[0].Q_POI P_PMV = struct[0].P_PMV Q_PMV = struct[0].Q_PMV P_GR1 = struct[0].P_GR1 Q_GR1 = struct[0].Q_GR1 P_GR2 = struct[0].P_GR2 Q_GR2 = struct[0].Q_GR2 P_GR3 = struct[0].P_GR3 Q_GR3 = struct[0].Q_GR3 P_GR4 = struct[0].P_GR4 Q_GR4 = struct[0].Q_GR4 # Dynamical states: delta_GRI = struct[0].x[0,0] omega_GRI = struct[0].x[1,0] e1q_GRI = struct[0].x[2,0] e1d_GRI = struct[0].x[3,0] v_c_GRI = struct[0].x[4,0] p_m_GRI = struct[0].x[5,0] xi_m_GRI = struct[0].x[6,0] # Algebraic states: V_GRI = struct[0].y_run[0,0] theta_GRI = struct[0].y_run[1,0] V_POI = struct[0].y_run[2,0] theta_POI = struct[0].y_run[3,0] V_PMV = struct[0].y_run[4,0] theta_PMV = struct[0].y_run[5,0] V_GR1 = struct[0].y_run[6,0] theta_GR1 = struct[0].y_run[7,0] V_GR2 = struct[0].y_run[8,0] theta_GR2 = struct[0].y_run[9,0] V_GR3 = struct[0].y_run[10,0] theta_GR3 = struct[0].y_run[11,0] V_GR4 = struct[0].y_run[12,0] theta_GR4 = struct[0].y_run[13,0] i_d_GRI = struct[0].y_run[14,0] i_q_GRI = struct[0].y_run[15,0] P_GRI_1 = struct[0].y_run[16,0] Q_GRI_1 = struct[0].y_run[17,0] v_f_GRI = struct[0].y_run[18,0] p_m_ref_GRI = struct[0].y_run[19,0] # Differential equations: if mode == 2: struct[0].f[0,0] = -K_delta_GRI*delta_GRI + Omega_b_GRI*(omega_GRI - omega_s_GRI) struct[0].f[1,0] = (-D_GRI*(omega_GRI - omega_s_GRI) - i_d_GRI*(R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI)) - i_q_GRI*(R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI)) + p_m_GRI)/(2*H_GRI) struct[0].f[2,0] = (-e1q_GRI - i_d_GRI*(-X1d_GRI + X_d_GRI) + v_f_GRI)/T1d0_GRI struct[0].f[3,0] = (-e1d_GRI + i_q_GRI*(-X1q_GRI + X_q_GRI))/T1q0_GRI struct[0].f[4,0] = (V_GRI - v_c_GRI)/T_r_GRI struct[0].f[5,0] = (-p_m_GRI + p_m_ref_GRI)/T_m_GRI struct[0].f[6,0] = omega_GRI - 1 # Algebraic equations: if mode == 3: struct[0].g[0,0] = -P_GRI/S_base - P_GRI_1/S_base + V_GRI**2*g_GRI_POI + V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].g[1,0] = -Q_GRI/S_base - Q_GRI_1/S_base - V_GRI**2*b_GRI_POI + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].g[2,0] = -P_POI/S_base + V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + V_POI**2*(g_GRI_POI + g_POI_PMV) struct[0].g[3,0] = -Q_POI/S_base + V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + V_POI**2*(-b_GRI_POI - b_POI_PMV) struct[0].g[4,0] = -P_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV**2*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].g[5,0] = -Q_PMV/S_base + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV**2*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].g[6,0] = -P_GR1/S_base + V_GR1**2*(g_GR1_GR2 + g_PMV_GR1) + V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].g[7,0] = -Q_GR1/S_base + V_GR1**2*(-b_GR1_GR2 - b_PMV_GR1) + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].g[8,0] = -P_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR2**2*g_GR1_GR2 struct[0].g[9,0] = -Q_GR2/S_base + V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - V_GR2**2*b_GR1_GR2 struct[0].g[10,0] = -P_GR3/S_base + V_GR3**2*(g_GR3_GR4 + g_PMV_GR3) + V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].g[11,0] = -Q_GR3/S_base + V_GR3**2*(-b_GR3_GR4 - b_PMV_GR3) + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].g[12,0] = -P_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR4**2*g_GR3_GR4 struct[0].g[13,0] = -Q_GR4/S_base + V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - V_GR4**2*b_GR3_GR4 struct[0].g[14,0] = R_a_GRI*i_q_GRI + V_GRI*cos(delta_GRI - theta_GRI) + X1d_GRI*i_d_GRI - e1q_GRI struct[0].g[15,0] = R_a_GRI*i_d_GRI + V_GRI*sin(delta_GRI - theta_GRI) - X1q_GRI*i_q_GRI - e1d_GRI struct[0].g[16,0] = -P_GRI_1/S_n_GRI + V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].g[17,0] = -Q_GRI_1/S_n_GRI + V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].g[18,0] = K_a_GRI*(-v_c_GRI + v_pss_GRI + v_ref_GRI) - v_f_GRI struct[0].g[19,0] = -K_sec_GRI*xi_m_GRI - p_m_ref_GRI - (omega_GRI - 1)/Droop_GRI # Outputs: if mode == 3: struct[0].h[0,0] = V_GRI struct[0].h[1,0] = V_POI struct[0].h[2,0] = V_PMV struct[0].h[3,0] = V_GR1 struct[0].h[4,0] = V_GR2 struct[0].h[5,0] = V_GR3 struct[0].h[6,0] = V_GR4 if mode == 10: struct[0].Fx[0,0] = -K_delta_GRI struct[0].Fx[0,1] = Omega_b_GRI struct[0].Fx[1,0] = (-V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fx[1,1] = -D_GRI/(2*H_GRI) struct[0].Fx[1,5] = 1/(2*H_GRI) struct[0].Fx[2,2] = -1/T1d0_GRI struct[0].Fx[3,3] = -1/T1q0_GRI struct[0].Fx[4,4] = -1/T_r_GRI struct[0].Fx[5,5] = -1/T_m_GRI struct[0].Fx[6,1] = 1 if mode == 11: struct[0].Fy[1,0] = (-i_d_GRI*sin(delta_GRI - theta_GRI) - i_q_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,1] = (V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) - V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,14] = (-2*R_a_GRI*i_d_GRI - V_GRI*sin(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[1,15] = (-2*R_a_GRI*i_q_GRI - V_GRI*cos(delta_GRI - theta_GRI))/(2*H_GRI) struct[0].Fy[2,14] = (X1d_GRI - X_d_GRI)/T1d0_GRI struct[0].Fy[2,18] = 1/T1d0_GRI struct[0].Fy[3,15] = (-X1q_GRI + X_q_GRI)/T1q0_GRI struct[0].Fy[4,0] = 1/T_r_GRI struct[0].Fy[5,19] = 1/T_m_GRI struct[0].Gy[0,0] = 2*V_GRI*g_GRI_POI + V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[0,1] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[0,2] = V_GRI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[0,3] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[0,16] = -1/S_base struct[0].Gy[1,0] = -2*V_GRI*b_GRI_POI + V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[1,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[1,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[1,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[1,17] = -1/S_base struct[0].Gy[2,0] = V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[2,1] = V_GRI*V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[2,2] = V_GRI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) + 2*V_POI*(g_GRI_POI + g_POI_PMV) struct[0].Gy[2,3] = V_GRI*V_POI*(-b_GRI_POI*cos(theta_GRI - theta_POI) - g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[2,4] = V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[2,5] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[3,0] = V_POI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) struct[0].Gy[3,1] = V_GRI*V_POI*(-b_GRI_POI*sin(theta_GRI - theta_POI) + g_GRI_POI*cos(theta_GRI - theta_POI)) struct[0].Gy[3,2] = V_GRI*(b_GRI_POI*cos(theta_GRI - theta_POI) + g_GRI_POI*sin(theta_GRI - theta_POI)) + V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) + 2*V_POI*(-b_GRI_POI - b_POI_PMV) struct[0].Gy[3,3] = V_GRI*V_POI*(b_GRI_POI*sin(theta_GRI - theta_POI) - g_GRI_POI*cos(theta_GRI - theta_POI)) + V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[3,4] = V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[3,5] = V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,2] = V_PMV*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,3] = V_PMV*V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[4,4] = V_GR1*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + 2*V_PMV*(g_PMV_GR1 + g_PMV_GR3 + g_POI_PMV) + V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[4,5] = V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*cos(theta_PMV - theta_POI) + g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[4,6] = V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[4,7] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[4,10] = V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[4,11] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[5,2] = V_PMV*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[5,3] = V_PMV*V_POI*(b_POI_PMV*sin(theta_PMV - theta_POI) + g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[5,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) + V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) + 2*V_PMV*(-b_PMV_GR1 - b_PMV_GR3 - b_POI_PMV) + V_POI*(b_POI_PMV*cos(theta_PMV - theta_POI) - g_POI_PMV*sin(theta_PMV - theta_POI)) struct[0].Gy[5,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) + V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) + V_PMV*V_POI*(-b_POI_PMV*sin(theta_PMV - theta_POI) - g_POI_PMV*cos(theta_PMV - theta_POI)) struct[0].Gy[5,6] = V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[5,7] = V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[5,10] = V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[5,11] = V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[6,4] = V_GR1*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[6,5] = V_GR1*V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[6,6] = 2*V_GR1*(g_GR1_GR2 + g_PMV_GR1) + V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[6,7] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*cos(theta_GR1 - theta_PMV) + g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[6,8] = V_GR1*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[6,9] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[7,4] = V_GR1*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[7,5] = V_GR1*V_PMV*(b_PMV_GR1*sin(theta_GR1 - theta_PMV) + g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[7,6] = 2*V_GR1*(-b_GR1_GR2 - b_PMV_GR1) + V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) + V_PMV*(b_PMV_GR1*cos(theta_GR1 - theta_PMV) - g_PMV_GR1*sin(theta_GR1 - theta_PMV)) struct[0].Gy[7,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + V_GR1*V_PMV*(-b_PMV_GR1*sin(theta_GR1 - theta_PMV) - g_PMV_GR1*cos(theta_GR1 - theta_PMV)) struct[0].Gy[7,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[7,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[8,6] = V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[8,7] = V_GR1*V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[8,8] = V_GR1*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) + 2*V_GR2*g_GR1_GR2 struct[0].Gy[8,9] = V_GR1*V_GR2*(-b_GR1_GR2*cos(theta_GR1 - theta_GR2) - g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[9,6] = V_GR2*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) struct[0].Gy[9,7] = V_GR1*V_GR2*(-b_GR1_GR2*sin(theta_GR1 - theta_GR2) + g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[9,8] = V_GR1*(b_GR1_GR2*cos(theta_GR1 - theta_GR2) + g_GR1_GR2*sin(theta_GR1 - theta_GR2)) - 2*V_GR2*b_GR1_GR2 struct[0].Gy[9,9] = V_GR1*V_GR2*(b_GR1_GR2*sin(theta_GR1 - theta_GR2) - g_GR1_GR2*cos(theta_GR1 - theta_GR2)) struct[0].Gy[10,4] = V_GR3*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[10,5] = V_GR3*V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[10,10] = 2*V_GR3*(g_GR3_GR4 + g_PMV_GR3) + V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[10,11] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*cos(theta_GR3 - theta_PMV) + g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[10,12] = V_GR3*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[10,13] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[11,4] = V_GR3*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[11,5] = V_GR3*V_PMV*(b_PMV_GR3*sin(theta_GR3 - theta_PMV) + g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[11,10] = 2*V_GR3*(-b_GR3_GR4 - b_PMV_GR3) + V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) + V_PMV*(b_PMV_GR3*cos(theta_GR3 - theta_PMV) - g_PMV_GR3*sin(theta_GR3 - theta_PMV)) struct[0].Gy[11,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + V_GR3*V_PMV*(-b_PMV_GR3*sin(theta_GR3 - theta_PMV) - g_PMV_GR3*cos(theta_GR3 - theta_PMV)) struct[0].Gy[11,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[11,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[12,10] = V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[12,11] = V_GR3*V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[12,12] = V_GR3*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) + 2*V_GR4*g_GR3_GR4 struct[0].Gy[12,13] = V_GR3*V_GR4*(-b_GR3_GR4*cos(theta_GR3 - theta_GR4) - g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[13,10] = V_GR4*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) struct[0].Gy[13,11] = V_GR3*V_GR4*(-b_GR3_GR4*sin(theta_GR3 - theta_GR4) + g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[13,12] = V_GR3*(b_GR3_GR4*cos(theta_GR3 - theta_GR4) + g_GR3_GR4*sin(theta_GR3 - theta_GR4)) - 2*V_GR4*b_GR3_GR4 struct[0].Gy[13,13] = V_GR3*V_GR4*(b_GR3_GR4*sin(theta_GR3 - theta_GR4) - g_GR3_GR4*cos(theta_GR3 - theta_GR4)) struct[0].Gy[14,0] = cos(delta_GRI - theta_GRI) struct[0].Gy[14,1] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[14,14] = X1d_GRI struct[0].Gy[14,15] = R_a_GRI struct[0].Gy[15,0] = sin(delta_GRI - theta_GRI) struct[0].Gy[15,1] = -V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[15,14] = R_a_GRI struct[0].Gy[15,15] = -X1q_GRI struct[0].Gy[16,0] = i_d_GRI*sin(delta_GRI - theta_GRI) + i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[16,1] = -V_GRI*i_d_GRI*cos(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[16,14] = V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[16,15] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[16,16] = -1/S_n_GRI struct[0].Gy[17,0] = i_d_GRI*cos(delta_GRI - theta_GRI) - i_q_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[17,1] = V_GRI*i_d_GRI*sin(delta_GRI - theta_GRI) + V_GRI*i_q_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[17,14] = V_GRI*cos(delta_GRI - theta_GRI) struct[0].Gy[17,15] = -V_GRI*sin(delta_GRI - theta_GRI) struct[0].Gy[17,17] = -1/S_n_GRI struct[0].Gy[18,18] = -1 struct[0].Gy[19,19] = -1 struct[0].Gu[0,0] = -1/S_base struct[0].Gu[1,1] = -1/S_base struct[0].Gu[2,2] = -1/S_base struct[0].Gu[3,3] = -1/S_base struct[0].Gu[4,4] = -1/S_base struct[0].Gu[5,5] = -1/S_base struct[0].Gu[6,6] = -1/S_base struct[0].Gu[7,7] = -1/S_base struct[0].Gu[8,8] = -1/S_base struct[0].Gu[9,9] = -1/S_base struct[0].Gu[10,10] = -1/S_base struct[0].Gu[11,11] = -1/S_base struct[0].Gu[12,12] = -1/S_base struct[0].Gu[13,13] = -1/S_base @numba.njit(cache=True) def Piecewise(arg): out = arg[0][1] N = len(arg) for it in range(N-1,-1,-1): if arg[it][1]: out = arg[it][0] return out @numba.njit(cache=True) def ITE(arg): out = arg[0][1] N = len(arg) for it in range(N-1,-1,-1): if arg[it][1]: out = arg[it][0] return out @numba.njit(cache=True) def Abs(x): return np.abs(x) @numba.njit(cache=True) def daesolver(struct): sin = np.sin cos = np.cos sqrt = np.sqrt i = 0 Dt = struct[i].Dt N_x = struct[i].N_x N_y = struct[i].N_y N_z = struct[i].N_z decimation = struct[i].decimation eye = np.eye(N_x) t = struct[i].t t_end = struct[i].t_end if struct[i].it == 0: run(t,struct, 1) struct[i].it_store = 0 struct[i]['T'][0] = t struct[i].X[0,:] = struct[i].x[:,0] struct[i].Y[0,:] = struct[i].y_run[:,0] struct[i].Z[0,:] = struct[i].h[:,0] solver = struct[i].solvern while t<t_end: struct[i].it += 1 struct[i].t += Dt t = struct[i].t if solver == 5: # Teapezoidal DAE as in Milano's book run(t,struct, 2) run(t,struct, 3) x = np.copy(struct[i].x[:]) y = np.copy(struct[i].y_run[:]) f = np.copy(struct[i].f[:]) g = np.copy(struct[i].g[:]) for iter in range(struct[i].imax): run(t,struct, 2) run(t,struct, 3) run(t,struct,10) run(t,struct,11) x_i = struct[i].x[:] y_i = struct[i].y_run[:] f_i = struct[i].f[:] g_i = struct[i].g[:] F_x_i = struct[i].Fx[:,:] F_y_i = struct[i].Fy[:,:] G_x_i = struct[i].Gx[:,:] G_y_i = struct[i].Gy[:,:] A_c_i = np.vstack((np.hstack((eye-0.5*Dt*F_x_i, -0.5*Dt*F_y_i)), np.hstack((G_x_i, G_y_i)))) f_n_i = x_i - x - 0.5*Dt*(f_i+f) # print(t,iter,g_i) Dxy_i = np.linalg.solve(-A_c_i,np.vstack((f_n_i,g_i))) x_i = x_i + Dxy_i[0:N_x] y_i = y_i + Dxy_i[N_x:(N_x+N_y)] struct[i].x[:] = x_i struct[i].y_run[:] = y_i # [f_i,g_i,F_x_i,F_y_i,G_x_i,G_y_i] = smib_transient(x_i,y_i,u); # A_c_i = [[eye(N_x)-0.5*Dt*F_x_i, -0.5*Dt*F_y_i], # [ G_x_i, G_y_i]]; # f_n_i = x_i - x - 0.5*Dt*(f_i+f); # Dxy_i = -A_c_i\[f_n_i.',g_i.'].'; # x_i = x_i + Dxy_i(1:N_x); # y_i = y_i + Dxy_i(N_x+1:N_x+N_y); xy = np.vstack((x_i,y_i)) max_relative = 0.0 for it_var in range(N_x+N_y): abs_value = np.abs(xy[it_var,0]) if abs_value < 0.001: abs_value = 0.001 relative_error = np.abs(Dxy_i[it_var,0])/abs_value if relative_error > max_relative: max_relative = relative_error if max_relative<struct[i].itol: break # if iter>struct[i].imax-2: # print('Convergence problem') struct[i].x[:] = x_i struct[i].y_run[:] = y_i # channels if struct[i].store == 1: it_store = struct[i].it_store if struct[i].it >= it_store*decimation: struct[i]['T'][it_store+1] = t struct[i].X[it_store+1,:] = struct[i].x[:,0] struct[i].Y[it_store+1,:] = struct[i].y_run[:,0] struct[i].Z[it_store+1,:] = struct[i].h[:,0] struct[i].iters[it_store+1,0] = iter struct[i].it_store += 1 struct[i].t = t return t

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400ab2f34a127823bbb296bbc2616dfd10727217

134

py

Python

allennlp_models/classification/__init__.py

matt-peters/allennlp-models

cdd505ed539fdc2b82e4cc0a23eae4bfd3368e7e

[ "Apache-2.0" ]

1

2022-02-10T22:19:55.000Z

allennlp_models/classification/__init__.py

matt-peters/allennlp-models

cdd505ed539fdc2b82e4cc0a23eae4bfd3368e7e

[ "Apache-2.0" ]

29

2020-10-29T20:28:47.000Z

2022-03-28T13:05:18.000Z

allennlp_models/classification/__init__.py

matt-peters/allennlp-models

cdd505ed539fdc2b82e4cc0a23eae4bfd3368e7e

[ "Apache-2.0" ]

null

# flake8: noqa: F403 from allennlp_models.classification.models import * from allennlp_models.classification.dataset_readers import *

33.5

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401c2e30c15e17596ce735d3d4aa0da8362ceda3

81,931

py

Python

anuga/shallow_water/tests/test_forcing.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

null

anuga/shallow_water/tests/test_forcing.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

null

anuga/shallow_water/tests/test_forcing.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

null

""" Test environmental forcing - rain, wind, etc. """ from __future__ import division from builtins import str from builtins import range from past.utils import old_div from future.utils import raise_ import unittest, os import anuga from anuga.shallow_water.shallow_water_domain import Domain from anuga.shallow_water.boundaries import Reflective_boundary from anuga.coordinate_transforms.geo_reference import Geo_reference from anuga.file_conversion.file_conversion import timefile2netcdf from anuga.abstract_2d_finite_volumes.mesh_factory import rectangular from anuga.abstract_2d_finite_volumes.util import file_function from anuga.config import netcdf_mode_r, netcdf_mode_w, netcdf_mode_a from anuga.shallow_water.forcing import * import numpy as num import warnings def scalar_func_list(t, x, y): """Function that returns a scalar. Used to test error message when numeric array is expected """ return [17.7] def speed(t, x, y): """ Variable windfield implemented using functions Large speeds halfway between center and edges Low speeds at center and edges """ from math import exp, cos, pi x = num.array(x) y = num.array(y) N = len(x) s = 0*x #New array for k in range(N): r = num.sqrt(x[k]**2 + y[k]**2) factor = exp(-(r-0.15)**2) s[k] = 4000 * factor * (cos(old_div(t*2*pi,150)) + 2) return s def angle(t, x, y): """Rotating field """ from math import atan, pi x = num.array(x) y = num.array(y) N = len(x) a = 0 * x # New array for k in range(N): r = num.sqrt(x[k]**2 + y[k]**2) angle = atan(old_div(y[k],x[k])) if x[k] < 0: angle += pi # Take normal direction angle -= old_div(pi,2) # Ensure positive radians if angle < 0: angle += 2*pi a[k] = old_div(angle,pi)*180 return a def time_varying_speed(t, x, y): """ Variable speed windfield """ from math import exp, cos, pi x = num.array(x,float) y = num.array(y,float) N = len(x) s = 0*x #New array #dx=x[-1]-x[0]; dy = y[-1]-y[0] S=100. for k in range(N): s[k]=S*(1.+t/100.) return s def time_varying_angle(t, x, y): """Rotating field """ from math import atan, pi x = num.array(x,float) y = num.array(y,float) N = len(x) a = 0 * x # New array phi=135. for k in range(N): a[k]=phi*(1.+t/100.) return a def time_varying_pressure(t, x, y): """Rotating field """ from math import atan, pi x = num.array(x,float) y = num.array(y,float) N = len(x) p = 0 * x # New array p0=1000. for k in range(N): p[k]=p0*(1.-t/100.) return p def spatial_linear_varying_speed(t, x, y): """ Variable speed windfield """ from math import exp, cos, pi x = num.array(x) y = num.array(y) N = len(x) s = 0*x #New array #dx=x[-1]-x[0]; dy = y[-1]-y[0] s0=250. ymin=num.min(y) xmin=num.min(x) a=0.000025; b=0.0000125; for k in range(N): s[k]=s0*(1+t/100.)+a*x[k]+b*y[k] return s def spatial_linear_varying_angle(t, x, y): """Rotating field """ from math import atan, pi x = num.array(x) y = num.array(y) N = len(x) a = 0 * x # New array phi=135. b1=0.000025; b2=0.00001125; for k in range(N): a[k]=phi*(1+t/100.)+b1*x[k]+b2*y[k] return a def spatial_linear_varying_pressure(t, x, y): p0=1000; a=0.000025; b=0.0000125; x = num.array(x) y = num.array(y) N = len(x) p = 0 * x # New array for k in range(N): p[k]=p0*(1.-t/100.)+a*x[k]+b*y[k] return p def grid_1d(x0,dx,nx): x = num.empty(nx,dtype=float) for i in range(nx): x[i]=x0+float(i)*dx return x def ndgrid(x,y): nx = len(x) ny = len(y) X = num.empty(nx*ny,dtype=float) Y = num.empty(nx*ny,dtype=float) k=0 for i in range(nx): for j in range(ny): X[k]=x[i] Y[k]=y[j] k+=1 return X,Y class Test_Forcing(unittest.TestCase): def setUp(self): pass def tearDown(self): for file in ['domain.sww']: try: os.remove(file) except: pass def write_wind_pressure_field_sts(self, field_sts_filename, nrows=10, ncols=10, cellsize=25, origin=(0.0,0.0), refzone=50, timestep=1, number_of_timesteps=10, angle=135.0, speed=100.0, pressure=1000.0): xllcorner=origin[0] yllcorner=origin[1] starttime = 0; endtime = number_of_timesteps*timestep; no_data = -9999 time = num.arange(starttime, endtime, timestep, dtype='i') x = grid_1d(xllcorner,cellsize,ncols) y = grid_1d(yllcorner,cellsize,nrows) [X,Y] = ndgrid(x,y) number_of_points = nrows*ncols wind_speed = num.empty((number_of_timesteps,nrows*ncols),dtype=float) wind_angle = num.empty((number_of_timesteps,nrows*ncols),dtype=float) barometric_pressure = num.empty((number_of_timesteps,nrows*ncols), dtype=float) if ( callable(speed) and callable(angle) and callable(pressure) ): x = num.ones(3, float) y = num.ones(3, float) try: s = speed(1.0, x=x, y=y) a = angle(1.0, x=x, y=y) p = pressure(1.0, x=x, y=y) use_function=True except Exception as e: msg = 'Function could not be executed.\n' raise_(Exception, msg) else: try : speed=float(speed) angle=float(angle) pressure=float(pressure) use_function=False except: msg = ('Force fields must be a scalar value coercible to float.') raise_(Exception, msg) for i,t in enumerate(time): if ( use_function ): wind_speed[i,:] = speed(t,X,Y) wind_angle[i,:] = angle(t,X,Y) barometric_pressure[i,:] = pressure(t,X,Y) else: wind_speed[i,:] = speed wind_angle[i,:] = angle barometric_pressure[i,:] = pressure # "Creating the field STS NetCDF file" fid = NetCDFFile(field_sts_filename+'.sts', 'w') fid.institution = 'Geoscience Australia' fid.description = "description" fid.starttime = 0.0 fid.ncols = ncols fid.nrows = nrows fid.cellsize = cellsize fid.no_data = no_data fid.createDimension('number_of_points', number_of_points) fid.createDimension('number_of_timesteps', number_of_timesteps) fid.createDimension('numbers_in_range', 2) fid.createVariable('x', 'd', ('number_of_points',)) fid.createVariable('y', 'd', ('number_of_points',)) fid.createVariable('time', 'i', ('number_of_timesteps',)) fid.createVariable('wind_speed', 'd', ('number_of_timesteps', 'number_of_points')) fid.createVariable('wind_speed_range', 'd', ('numbers_in_range', )) fid.createVariable('wind_angle', 'd', ('number_of_timesteps', 'number_of_points')) fid.createVariable('wind_angle_range', 'd', ('numbers_in_range',)) fid.createVariable('barometric_pressure', 'd', ('number_of_timesteps', 'number_of_points')) fid.createVariable('barometric_pressure_range', 'd', ('numbers_in_range',)) fid.variables['wind_speed_range'][:] = num.array([1e+036, -1e+036]) fid.variables['wind_angle_range'][:] = num.array([1e+036, -1e+036]) fid.variables['barometric_pressure_range'][:] = num.array([1e+036, -1e+036]) fid.variables['time'][:] = time ws = fid.variables['wind_speed'] wa = fid.variables['wind_angle'] pr = fid.variables['barometric_pressure'] for i in range(number_of_timesteps): ws[i] = wind_speed[i,:] wa[i] = wind_angle[i,:] pr[i] = barometric_pressure[i,:] origin = anuga.coordinate_transforms.geo_reference.Geo_reference(refzone, xllcorner, yllcorner) geo_ref = anuga.coordinate_transforms.geo_reference.write_NetCDF_georeference(origin, fid) fid.variables['x'][:]=X-geo_ref.get_xllcorner() fid.variables['y'][:]=Y-geo_ref.get_yllcorner() fid.close() def test_constant_wind_stress(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) #Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) #Setup only one forcing term, constant wind stress s = 100 phi = 135 domain.forcing_terms = [] domain.forcing_terms.append(Wind_stress(s, phi)) domain.compute_forcing_terms() const = old_div(eta_w*rho_a, rho_w) #Convert to radians phi = old_div(phi*pi, 180) #Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) #Compute wind stress S = const * num.sqrt(u**2 + v**2) assert num.allclose(domain.quantities['stage'].explicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].explicit_update, S*u) assert num.allclose(domain.quantities['ymomentum'].explicit_update, S*v) def test_variable_wind_stress(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) #Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) domain.set_time(5.54) # Take a random time (not zero) #Setup only one forcing term, constant wind stress s = 100 phi = 135 domain.forcing_terms = [] domain.forcing_terms.append(Wind_stress(s=speed, phi=angle)) domain.compute_forcing_terms() #Compute reference solution const = eta_w*rho_a/rho_w N = len(domain) # number_of_triangles xc = domain.get_centroid_coordinates() t = domain.get_time() x = xc[:,0] y = xc[:,1] s_vec = speed(t,x,y) phi_vec = angle(t,x,y) for k in range(N): # Convert to radians phi = old_div(phi_vec[k]*pi, 180) s = s_vec[k] # Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) # Compute wind stress S = const * num.sqrt(u**2 + v**2) assert num.allclose(domain.quantities['stage'].explicit_update[k], 0) assert num.allclose(domain.quantities['xmomentum'].\ explicit_update[k], S*u) assert num.allclose(domain.quantities['ymomentum'].\ explicit_update[k], S*v) def test_windfield_from_file(self): import time from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.abstract_2d_finite_volumes.util import file_function a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) domain.set_time(7) # Take a time that is represented in file (not zero) # Write wind stress file (ensure that domaim time is covered) # Take x=1 and y=0 filename = 'test_windstress_from_file' start = time.mktime(time.strptime('2000', '%Y')) fid = open(filename + '.txt', 'w') dt = 1 # One second interval t = 0.0 while t <= 10.0: t_string = time.strftime(time_format, time.gmtime(t+start)) fid.write('%s, %f %f\n' % (t_string, speed(t,[1],[0])[0], angle(t,[1],[0])[0])) t += dt fid.close() timefile2netcdf(filename + '.txt') os.remove(filename + '.txt') # Setup wind stress F = file_function(filename + '.tms', quantities=['Attribute0', 'Attribute1']) os.remove(filename + '.tms') W = Wind_stress(F) domain.forcing_terms = [] domain.forcing_terms.append(W) domain.compute_forcing_terms() # Compute reference solution const = old_div(eta_w*rho_a, rho_w) N = len(domain) # number_of_triangles t = domain.get_time() s = speed(t, [1], [0])[0] phi = angle(t, [1], [0])[0] # Convert to radians phi = old_div(phi*pi, 180) # Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) # Compute wind stress S = const * num.sqrt(u**2 + v**2) for k in range(N): assert num.allclose(domain.quantities['stage'].explicit_update[k], 0) assert num.allclose(domain.quantities['xmomentum'].\ explicit_update[k], S*u) assert num.allclose(domain.quantities['ymomentum'].\ explicit_update[k], S*v) def test_windfield_from_file_seconds(self): import time from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.abstract_2d_finite_volumes.util import file_function a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) domain.set_time(7) # Take a time that is represented in file (not zero) # Write wind stress file (ensure that domain time is covered) # Take x=1 and y=0 filename = 'test_windstress_from_file' start = time.mktime(time.strptime('2000', '%Y')) fid = open(filename + '.txt', 'w') dt = 0.5 # Half second interval t = 0.0 while t <= 10.0: fid.write('%s, %f %f\n' % (str(t), speed(t, [1], [0])[0], angle(t, [1], [0])[0])) t += dt fid.close() timefile2netcdf(filename + '.txt', time_as_seconds=True) os.remove(filename + '.txt') # Setup wind stress F = file_function(filename + '.tms', quantities=['Attribute0', 'Attribute1']) os.remove(filename + '.tms') W = Wind_stress(F) domain.forcing_terms = [] domain.forcing_terms.append(W) domain.compute_forcing_terms() # Compute reference solution const = old_div(eta_w*rho_a, rho_w) N = len(domain) # number_of_triangles t = domain.get_time() s = speed(t, [1], [0])[0] phi = angle(t, [1], [0])[0] # Convert to radians phi = old_div(phi*pi, 180) # Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) # Compute wind stress S = const * num.sqrt(u**2 + v**2) for k in range(N): assert num.allclose(domain.quantities['stage'].explicit_update[k], 0) assert num.allclose(domain.quantities['xmomentum'].\ explicit_update[k], S*u) assert num.allclose(domain.quantities['ymomentum'].\ explicit_update[k], S*v) def test_wind_stress_error_condition(self): """Test that windstress reacts properly when forcing functions are wrong - e.g. returns a scalar """ from math import pi, cos, sin from anuga.config import rho_a, rho_w, eta_w a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) domain.set_time(5.54) # Take a random time (not zero) # Setup only one forcing term, bad func domain.forcing_terms = [] try: domain.forcing_terms.append(Wind_stress(s=scalar_func_list, phi=angle)) except AssertionError: pass else: msg = 'Should have raised exception' raise_(Exception, msg) try: domain.forcing_terms.append(Wind_stress(s=speed, phi=scalar_func)) except Exception: pass else: msg = 'Should have raised exception' raise_(Exception, msg) try: domain.forcing_terms.append(Wind_stress(s=speed, phi='xx')) except: pass else: msg = 'Should have raised exception' raise_(Exception, msg) def test_rainfall(self): from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, constant rainfall domain.forcing_terms = [] domain.forcing_terms.append(Rainfall(domain, rate=2.0)) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update, 2.0/1000) def test_rainfall_restricted_by_polygon(self): from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, constant rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=2.0, polygon=[[1,1], [2,1], [2,2], [1,2]]) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], 2.0/1000) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_time_dependent_rainfall_restricted_by_polygon(self): a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=lambda t: 3*t + 7, polygon = [[1,1], [2,1], [2,2], [1,2]]) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) domain.set_time(10.0) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], (3*domain.get_time() + 7)/1000) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_time_dependent_rainfall_using_starttime(self): rainfall_poly = ensure_numeric([[1,1], [2,1], [2,2], [1,2]], float) a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=lambda t: 3*t + 7, polygon=rainfall_poly) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) # This will test that time is set to starttime in set_starttime domain.set_starttime(5.0) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], old_div((3*domain.get_time() + 7),1000)) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_absolute_time_dependent_rainfall_using_starttime(self): rainfall_poly = ensure_numeric([[1,1], [2,1], [2,2], [1,2]], float) a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=lambda t: 3*t + 7, polygon=rainfall_poly) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) # This will test that time is set to starttime in set_starttime domain.set_starttime(5.0) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], old_div((3*domain.get_starttime() + 7),1000)) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_time_dependent_rainfall_using_georef(self): """test_time_dependent_rainfall_using_georef This will also test the General forcing term using georef """ # Mesh in zone 56 (absolute coords) x0 = 314036.58727982 y0 = 6224951.2960092 rainfall_poly = ensure_numeric([[1,1], [2,1], [2,2], [1,2]], float) rainfall_poly += [x0, y0] a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices, geo_reference=Geo_reference(56, x0, y0)) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=lambda t: 3*t + 7, polygon=rainfall_poly) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) # This will test that time is set to starttime in set_starttime domain.set_starttime(5.0) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], old_div((3*domain.get_time() + 7),1000)) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_absolute_time_dependent_rainfall_using_georef(self): """test_time_dependent_rainfall_using_georef This will also test the General forcing term using georef """ # Mesh in zone 56 (absolute coords) x0 = 314036.58727982 y0 = 6224951.2960092 rainfall_poly = ensure_numeric([[1,1], [2,1], [2,2], [1,2]], float) rainfall_poly += [x0, y0] a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices, geo_reference=Geo_reference(56, x0, y0)) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # restricted to a polygon enclosing triangle #1 (bce) domain.forcing_terms = [] R = Rainfall(domain, rate=lambda t: 3*t + 7, polygon=rainfall_poly) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) # This will test that time is set to starttime in set_starttime domain.set_starttime(5.0) domain.set_time(5.0) domain.compute_forcing_terms() # print(domain.quantities['stage'].explicit_update[1]) # print((3*domain.get_time() + 7)/1000.0) # print(domain.relative_time) # print(domain.get_time()) assert num.allclose(domain.quantities['stage'].explicit_update[1], (3*domain.get_time() + 7)/1000.0) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_absolute_time_dependent_rainfall_restricted_by_polygon_with_default(self): """ Test that default rainfall can be used when given rate runs out of data. """ import warnings warnings.simplefilter('ignore', UserWarning) a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # that expires at t==20 from anuga.fit_interpolate.interpolate import Modeltime_too_late def main_rate(t): if t > 20: msg = 'Model time exceeded.' raise_(Modeltime_too_late, msg) else: return 3*t + 7 domain.forcing_terms = [] R = Rainfall(domain, rate=main_rate, polygon = [[1,1], [2,1], [2,2], [1,2]], default_rate=5.0) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) domain.set_time(10.) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], (3*domain.get_time()+7)/1000) assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) domain.set_time(100.) domain.quantities['stage'].explicit_update[:] = 0.0 # Reset domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update[1], 5.0/1000) # Default value assert num.allclose(domain.quantities['stage'].explicit_update[0], 0) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_rainfall_forcing_with_evolve(self): """test_rainfall_forcing_with_evolve Test how forcing terms are called within evolve """ # FIXME(Ole): This test is just to experiment import warnings warnings.simplefilter('ignore', UserWarning) a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # that expires at t==20 from anuga.fit_interpolate.interpolate import Modeltime_too_late def main_rate(t): if t > 20: msg = 'Model time exceeded.' raise_(Modeltime_too_late, msg) else: return 3*t + 7 domain.forcing_terms = [] R = Rainfall(domain, rate=main_rate, polygon=[[1,1], [2,1], [2,2], [1,2]], default_rate=5.0) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) for t in domain.evolve(yieldstep=1, finaltime=25): pass #FIXME(Ole): A test here is hard because explicit_update also # receives updates from the flux calculation. def test_rainfall_forcing_with_evolve_1(self): """test_rainfall_forcing_with_evolve_exception Test how forcing terms are called within evolve. This test checks that proper exception is thrown when no default_rate is set """ import warnings warnings.simplefilter('ignore', UserWarning) a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent rainfall # that expires at t==20 from anuga.fit_interpolate.interpolate import Modeltime_too_late def main_rate(t): if t > 20: msg = 'Model time exceeded.' raise_(Modeltime_too_late, msg) else: return 3*t + 7 domain.forcing_terms = [] R = Rainfall(domain, rate=main_rate, polygon=[[1,1], [2,1], [2,2], [1,2]]) assert num.allclose(R.exchange_area, 2) domain.forcing_terms.append(R) #for t in domain.evolve(yieldstep=1, finaltime=25): # pass try: for t in domain.evolve(yieldstep=1, finaltime=25): pass except Modeltime_too_late as e: # Test that error message is as expected assert 'can specify keyword argument default_rate in the forcing function' in str(e) else: raise Exception('Should have raised exception') def test_constant_wind_stress_from_file(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 nrows=5; ncols = 6; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 6 timestep=12*60 eps=2e-16 points, vertices, boundary =rectangular(nrows-2,ncols-2, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress s = 100 phi = 135 pressure=1000 domain.forcing_terms = [] field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=10, speed=s, angle=phi, pressure=pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['wind_speed', 'wind_angle'], interpolation_points = midpoints) W = Wind_stress(F,use_coordinates=False) domain.forcing_terms.append(W) domain.compute_forcing_terms() const = old_div(eta_w*rho_a, rho_w) # Convert to radians phi = old_div(phi*pi, 180) # Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) # Compute wind stress S = const * num.sqrt(u**2 + v**2) assert num.allclose(domain.quantities['stage'].explicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].explicit_update, S*u) assert num.allclose(domain.quantities['ymomentum'].explicit_update, S*v) def test_variable_windfield_from_file(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 #nrows=25; ncols = 25; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 10 timestep=1 eps=2.e-16 spatial_thinning=1 points, vertices, boundary =rectangular(nrows-2,ncols-2, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) time=num.arange(0,10,1,float) eval_time=time[7]; domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() vertexpoints = domain.get_nodes() """ x=grid_1d(xllcorner,cellsize,ncols) y=grid_1d(yllcorner,cellsize,nrows) X,Y=num.meshgrid(x,y) interpolation_points=num.empty((X.shape[0]*X.shape[1],2),float) k=0 for i in range(X.shape[0]): for j in range(X.shape[1]): interpolation_points[k,0]=X[i,j] interpolation_points[k,1]=Y[i,j] k+=1 z=spatial_linear_varying_speed(eval_time,interpolation_points[:,0], interpolation_points[:,1]) k=0 Z=num.empty((X.shape[0],X.shape[1]),float) for i in range(X.shape[0]): for j in range(X.shape[1]): Z[i,j]=z[k] k+=1 Q=num.empty((time.shape[0],points.shape[0]),float) for i, t in enumerate(time): Q[i,:]=spatial_linear_varying_speed(t,points[:,0],points[:,1]) from interpolate import Interpolation_function I = Interpolation_function(time,Q, vertex_coordinates = points, triangles = domain.triangles, #interpolation_points = midpoints, interpolation_points=interpolation_points, verbose=False) V=num.empty((X.shape[0],X.shape[1]),float) for k in range(len(interpolation_points)): assert num.allclose(I(eval_time,k),z[k]) V[k/X.shape[1],k%X.shape[1]]=I(eval_time,k) import mpl_toolkits.mplot3d.axes3d as p3 fig=P.figure() ax = p3.Axes3D(fig) ax.plot_surface(X,Y,V) ax.plot_surface(X,Y,Z) P.show() """ # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) domain.set_time(7*timestep) # Take a time that is represented in file (not zero) # Write wind stress file (ensure that domain time is covered) field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=10, speed=spatial_linear_varying_speed, angle=spatial_linear_varying_angle, pressure=spatial_linear_varying_pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=spatial_thinning, verbose=False) # Setup wind stress FW = file_function(field_sts_filename+'.sww', domain, quantities=['wind_speed', 'wind_angle'], interpolation_points = midpoints) W = Wind_stress(FW,use_coordinates=False) domain.forcing_terms = [] domain.forcing_terms.append(W) domain.compute_forcing_terms() # Compute reference solution const = old_div(eta_w*rho_a, rho_w) N = len(domain) # number_of_triangles xc = domain.get_centroid_coordinates() t = domain.get_time() x = xc[:,0] y = xc[:,1] s_vec = spatial_linear_varying_speed(t,x,y) phi_vec = spatial_linear_varying_angle(t,x,y) for k in range(N): # Convert to radians phi = old_div(phi_vec[k]*pi, 180) s = s_vec[k] # Compute velocity vector (u, v) u = s*cos(phi) v = s*sin(phi) # Compute wind stress S = const * num.sqrt(u**2 + v**2) assert num.allclose(domain.quantities['stage'].explicit_update[k],0) assert num.allclose(domain.quantities['xmomentum'].\ explicit_update[k],S*u,eps) assert num.allclose(domain.quantities['ymomentum'].\ explicit_update[k],S*v,eps) os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_variable_pressurefield_from_file(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 #nrows=25; ncols = 25; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 10 timestep=1 eps=2.e-16 spatial_thinning=1 points, vertices, boundary =rectangular(nrows-2,ncols-2, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) time=num.arange(0,10,1,float) eval_time=time[7]; domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() vertexpoints = domain.get_nodes() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) domain.set_time(7*timestep) # Take a time that is represented in file (not zero) # Write wind stress file (ensure that domain time is covered) field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=10, speed=spatial_linear_varying_speed, angle=spatial_linear_varying_angle, pressure=spatial_linear_varying_pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=spatial_thinning, verbose=False) # Setup barometric pressure FP = file_function(field_sts_filename+'.sww', domain, quantities=['barometric_pressure'], interpolation_points = vertexpoints) P = Barometric_pressure(FP,use_coordinates=False) domain.forcing_terms = [] domain.forcing_terms.append(P) domain.compute_forcing_terms() N = len(domain) # number_of_triangles xc = domain.get_centroid_coordinates() t = domain.get_time() x = xc[:,0] y = xc[:,1] p_vec = spatial_linear_varying_pressure(t,x,y) h=1 #depth px=0.000025 #pressure gradient in x-direction py=0.0000125 #pressure gradient in y-direction for k in range(N): # Convert to radians p = p_vec[k] assert num.allclose(domain.quantities['stage'].explicit_update[k],0) assert num.allclose(domain.quantities['xmomentum'].\ explicit_update[k],old_div(h*px,rho_w)) assert num.allclose(domain.quantities['ymomentum'].\ explicit_update[k],old_div(h*py,rho_w)) os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_constant_wind_stress_from_file_evolve(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 nrows=5; ncols = 6; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 27 timestep=1 eps=2e-16 points, vertices, boundary =rectangular(nrows-2,ncols-2, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress s = 100 phi = 135 field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=number_of_timesteps, speed=s, angle=phi) sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['wind_speed', 'wind_angle'], interpolation_points = midpoints) W = Wind_stress(F,use_coordinates=False) domain.forcing_terms.append(W) valuesUsingFunction=num.empty((3,number_of_timesteps+1,midpoints.shape[0]), float) i=0 for t in domain.evolve(yieldstep=1, finaltime=number_of_timesteps*timestep): valuesUsingFunction[0,i]=domain.quantities['stage'].explicit_update valuesUsingFunction[1,i]=domain.quantities['xmomentum'].explicit_update valuesUsingFunction[2,i]=domain.quantities['ymomentum'].explicit_update i+=1 domain_II = Domain(points, vertices, boundary) # Flat surface with 1m of water domain_II.set_quantity('elevation', 0) domain_II.set_quantity('stage', 1.0) domain_II.set_quantity('friction', 0) Br = Reflective_boundary(domain_II) domain_II.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) s = 100 phi = 135 domain_II.forcing_terms = [] domain_II.forcing_terms.append(Wind_stress(s, phi)) i=0; for t in domain_II.evolve(yieldstep=1, finaltime=number_of_timesteps*timestep): assert num.allclose(valuesUsingFunction[0,i],domain_II.quantities['stage'].explicit_update), max(valuesUsingFunction[0,i]-domain_II.quantities['stage'].explicit_update) assert num.allclose(valuesUsingFunction[1,i],domain_II.quantities['xmomentum'].explicit_update) assert num.allclose(valuesUsingFunction[2,i],domain_II.quantities['ymomentum'].explicit_update) i+=1 os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_temporally_varying_wind_stress_from_file_evolve(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 #nrows=20; ncols = 20; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 28 timestep=1. eps=2e-16 #points, vertices, boundary =rectangular(10,10, points, vertices, boundary =rectangular(5,5, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=number_of_timesteps, speed=time_varying_speed, angle=time_varying_angle, pressure=time_varying_pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['wind_speed', 'wind_angle'], interpolation_points = midpoints) #W = Wind_stress(F,use_coordinates=False) W = Wind_stress_fast(F,filename=field_sts_filename+'.sww', domain=domain) domain.forcing_terms.append(W) valuesUsingFunction=num.empty((3,2*number_of_timesteps,midpoints.shape[0]), float) i=0 for t in domain.evolve(yieldstep=timestep/2., finaltime=(number_of_timesteps-1)*timestep): valuesUsingFunction[0,i]=domain.quantities['stage'].explicit_update valuesUsingFunction[1,i]=domain.quantities['xmomentum'].explicit_update valuesUsingFunction[2,i]=domain.quantities['ymomentum'].explicit_update i+=1 domain_II = Domain(points, vertices, boundary) # Flat surface with 1m of water domain_II.set_quantity('elevation', 0) domain_II.set_quantity('stage', 1.0) domain_II.set_quantity('friction', 0) Br = Reflective_boundary(domain_II) domain_II.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) domain_II.forcing_terms.append(Wind_stress(s=time_varying_speed, phi=time_varying_angle)) i=0; for t in domain_II.evolve(yieldstep=timestep/2., finaltime=(number_of_timesteps-1)*timestep): assert num.allclose(valuesUsingFunction[0,i], domain_II.quantities['stage'].explicit_update, eps) #print i,valuesUsingFunction[1,i] assert num.allclose(valuesUsingFunction[1,i], domain_II.quantities['xmomentum'].explicit_update, eps),(valuesUsingFunction[1,i]- domain_II.quantities['xmomentum'].explicit_update) assert num.allclose(valuesUsingFunction[2,i], domain_II.quantities['ymomentum'].explicit_update, eps) #if i==1: assert-1==1 i+=1 os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_spatially_varying_wind_stress_from_file_evolve(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 nrows=20; ncols = 20; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 28 timestep=1. eps=2e-16 #points, vertices, boundary =rectangular(10,10, points, vertices, boundary =rectangular(5,5, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) midpoints = domain.get_centroid_coordinates() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=number_of_timesteps, speed=spatial_linear_varying_speed, angle=spatial_linear_varying_angle, pressure=spatial_linear_varying_pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['wind_speed', 'wind_angle'], interpolation_points = midpoints) W = Wind_stress(F,use_coordinates=False) domain.forcing_terms.append(W) valuesUsingFunction=num.empty((3,number_of_timesteps,midpoints.shape[0]), float) i=0 for t in domain.evolve(yieldstep=timestep, finaltime=(number_of_timesteps-1)*timestep): valuesUsingFunction[0,i]=domain.quantities['stage'].explicit_update valuesUsingFunction[1,i]=domain.quantities['xmomentum'].explicit_update valuesUsingFunction[2,i]=domain.quantities['ymomentum'].explicit_update i+=1 domain_II = Domain(points, vertices, boundary) # Flat surface with 1m of water domain_II.set_quantity('elevation', 0) domain_II.set_quantity('stage', 1.0) domain_II.set_quantity('friction', 0) Br = Reflective_boundary(domain_II) domain_II.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) domain_II.forcing_terms.append(Wind_stress(s=spatial_linear_varying_speed, phi=spatial_linear_varying_angle)) i=0; for t in domain_II.evolve(yieldstep=timestep, finaltime=(number_of_timesteps-1)*timestep): #print valuesUsingFunction[1,i],domain_II.quantities['xmomentum'].explicit_update assert num.allclose(valuesUsingFunction[0,i], domain_II.quantities['stage'].explicit_update, eps) assert num.allclose(valuesUsingFunction[1,i], domain_II.quantities['xmomentum'].explicit_update, eps) assert num.allclose(valuesUsingFunction[2,i], domain_II.quantities['ymomentum'].explicit_update, eps) i+=1 os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_temporally_varying_pressure_stress_from_file_evolve(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 #nrows=20; ncols = 20; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 28 timestep=10. eps=2e-16 #print "Building mesh" #points, vertices, boundary =rectangular(10,10, points, vertices, boundary =rectangular(5,5, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) vertexpoints = domain.get_nodes() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress field_sts_filename = 'wind_field' #print 'Writing pressure field sts file' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=number_of_timesteps, speed=time_varying_speed, angle=time_varying_angle, pressure=time_varying_pressure) #print "converting sts to sww" sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) #print 'initialising file_function' # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['barometric_pressure'], interpolation_points = vertexpoints) #P = Barometric_pressure(F,use_coordinates=False) #print 'initialising pressure forcing term' P = Barometric_pressure_fast(p=F,filename=field_sts_filename+'.sww',domain=domain) domain.forcing_terms.append(P) valuesUsingFunction=num.empty((3,2*number_of_timesteps,len(domain)), float) i=0 import time as timer t0=timer.time() for t in domain.evolve(yieldstep=timestep/2., finaltime=(number_of_timesteps-1)*timestep): valuesUsingFunction[0,i]=domain.quantities['stage'].explicit_update valuesUsingFunction[1,i]=domain.quantities['xmomentum'].explicit_update valuesUsingFunction[2,i]=domain.quantities['ymomentum'].explicit_update i+=1 #domain.write_time() t1=timer.time() #print "That took %fs seconds" %(t1-t0) domain_II = Domain(points, vertices, boundary) # Flat surface with 1m of water domain_II.set_quantity('elevation', 0) domain_II.set_quantity('stage', 1.0) domain_II.set_quantity('friction', 0) Br = Reflective_boundary(domain_II) domain_II.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) domain_II.forcing_terms.append(Barometric_pressure(p=time_varying_pressure)) i=0; for t in domain_II.evolve(yieldstep=timestep/2., finaltime=(number_of_timesteps-1)*timestep): assert num.allclose(valuesUsingFunction[0,i], domain_II.quantities['stage'].explicit_update, eps) assert num.allclose(valuesUsingFunction[1,i], domain_II.quantities['xmomentum'].explicit_update, eps) assert num.allclose(valuesUsingFunction[2,i], domain_II.quantities['ymomentum'].explicit_update, eps) i+=1 os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_spatially_varying_pressure_stress_from_file_evolve(self): from anuga.config import rho_a, rho_w, eta_w from math import pi, cos, sin from anuga.config import time_format from anuga.file_conversion.sts2sww_mesh import sts2sww_mesh cellsize = 25 #nrows=20; ncols = 20; nrows=10; ncols = 10; refzone=50 xllcorner=366000;yllcorner=6369500; number_of_timesteps = 28 timestep=1. eps=2e-16 #points, vertices, boundary =rectangular(10,10, points, vertices, boundary =rectangular(5,5, len1=cellsize*(ncols-1), len2=cellsize*(nrows-1), origin=(xllcorner,yllcorner)) domain = Domain(points, vertices, boundary) vertexpoints = domain.get_nodes() # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) # Setup only one forcing term, constant wind stress field_sts_filename = 'wind_field' self.write_wind_pressure_field_sts(field_sts_filename, nrows=nrows, ncols=ncols, cellsize=cellsize, origin=(xllcorner,yllcorner), refzone=50, timestep=timestep, number_of_timesteps=number_of_timesteps, speed=spatial_linear_varying_speed, angle=spatial_linear_varying_angle, pressure=spatial_linear_varying_pressure) sts2sww_mesh(field_sts_filename,spatial_thinning=1, verbose=False) # Setup wind stress F = file_function(field_sts_filename+'.sww', domain, quantities=['barometric_pressure'], interpolation_points = vertexpoints) P = Barometric_pressure(F,use_coordinates=False) domain.forcing_terms.append(P) valuesUsingFunction=num.empty((3,number_of_timesteps,len(domain)), float) i=0 for t in domain.evolve(yieldstep=timestep, finaltime=(number_of_timesteps-1)*timestep): valuesUsingFunction[0,i]=domain.quantities['stage'].explicit_update valuesUsingFunction[1,i]=domain.quantities['xmomentum'].explicit_update valuesUsingFunction[2,i]=domain.quantities['ymomentum'].explicit_update i+=1 domain_II = Domain(points, vertices, boundary) # Flat surface with 1m of water domain_II.set_quantity('elevation', 0) domain_II.set_quantity('stage', 1.0) domain_II.set_quantity('friction', 0) Br = Reflective_boundary(domain_II) domain_II.set_boundary({'top': Br, 'bottom' :Br, 'left': Br, 'right': Br}) domain_II.forcing_terms.append(Barometric_pressure(p=spatial_linear_varying_pressure)) i=0; for t in domain_II.evolve(yieldstep=timestep, finaltime=(number_of_timesteps-1)*timestep): assert num.allclose(valuesUsingFunction[0,i], domain_II.quantities['stage'].explicit_update, eps) assert num.allclose(valuesUsingFunction[1,i], domain_II.quantities['xmomentum'].explicit_update, eps) assert num.allclose(valuesUsingFunction[2,i], domain_II.quantities['ymomentum'].explicit_update, eps) i+=1 os.remove(field_sts_filename+'.sts') os.remove(field_sts_filename+'.sww') def test_flux_gravity(self): #Assuming no friction from anuga.config import g a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) domain.set_flow_algorithm('1_5') B = Reflective_boundary(domain) domain.set_boundary( {'exterior': B}) #Set up for a gradient of (3,0) at mid triangle (bce) def slope(x, y): return 3*x h = 0.1 def stage(x, y): return slope(x, y) + h domain.set_quantity('elevation', slope) domain.set_quantity('stage', stage) for name in domain.conserved_quantities: assert num.allclose(domain.quantities[name].explicit_update, 0) assert num.allclose(domain.quantities[name].semi_implicit_update, 0) # fluxes and gravity term are now combined. To ensure zero flux on boundary # need to set reflective boundaries domain.update_boundary() domain.compute_fluxes() assert num.allclose(domain.quantities['stage'].explicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].explicit_update, -g*h*3) assert num.allclose(domain.quantities['ymomentum'].explicit_update, 0) def test_manning_friction_old(self): from anuga.config import g a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Use the old function which doesn't take into account the extra # wetted area due to slope of bed domain.set_sloped_mannings_function(False) B = Reflective_boundary(domain) domain.set_boundary( {'exterior': B}) #Set up for a gradient of (3,0) at mid triangle (bce) def slope(x, y): return 3*x h = 0.1 def stage(x, y): return slope(x, y) + h eta = 0.07 domain.set_quantity('elevation', slope) domain.set_quantity('stage', stage) domain.set_quantity('friction', eta) for name in domain.conserved_quantities: assert num.allclose(domain.quantities[name].explicit_update, 0) assert num.allclose(domain.quantities[name].semi_implicit_update, 0) # Only manning friction in the forcing terms (gravity now combined with flux calc) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].explicit_update, 0) assert num.allclose(domain.quantities['ymomentum'].explicit_update, 0) assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update, 0) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update, 0) #Create some momentum for friction to work with domain.set_quantity('xmomentum', 1) S = old_div(-g*eta**2, h**(7.0/3)) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update, S) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update, 0) #A more complex example domain.quantities['stage'].semi_implicit_update[:] = 0.0 domain.quantities['xmomentum'].semi_implicit_update[:] = 0.0 domain.quantities['ymomentum'].semi_implicit_update[:] = 0.0 domain.set_quantity('xmomentum', 3) domain.set_quantity('ymomentum', 4) # sqrt(3^2 +4^2) = 5 S = old_div(-g*eta**2, h**(7.0/3)) * 5 domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update,3*S) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update,4*S) def test_manning_friction_new(self): from anuga.config import g import math a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) B = Reflective_boundary(domain) domain.set_boundary( {'exterior': B}) # Use the new function which takes into account the extra # wetted area due to slope of bed domain.set_sloped_mannings_function(True) #Set up for a gradient of (3,0) at mid triangle (bce) def slope(x, y): return 3*x h = 0.1 def stage(x, y): return slope(x, y) + h eta = 0.07 domain.set_quantity('elevation', slope) domain.set_quantity('stage', stage) domain.set_quantity('friction', eta) for name in domain.conserved_quantities: assert num.allclose(domain.quantities[name].explicit_update, 0) assert num.allclose(domain.quantities[name].semi_implicit_update, 0) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].explicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].explicit_update, 0) assert num.allclose(domain.quantities['ymomentum'].explicit_update, 0) assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update, 0) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update, 0) #Create some momentum for friction to work with domain.set_quantity('xmomentum', 1) S = old_div(-g*eta**2, h**(7.0/3)) * math.sqrt(10) domain.compute_forcing_terms() assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update, S) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update, 0) #A more complex example domain.quantities['stage'].semi_implicit_update[:] = 0.0 domain.quantities['xmomentum'].semi_implicit_update[:] = 0.0 domain.quantities['ymomentum'].semi_implicit_update[:] = 0.0 domain.set_quantity('xmomentum', 3) domain.set_quantity('ymomentum', 4) S = old_div(-g*eta**2 *5, h**(7.0/3)) * math.sqrt(10.0) domain.compute_forcing_terms() #print 'S', S #print domain.quantities['xmomentum'].semi_implicit_update #print domain.quantities['ymomentum'].semi_implicit_update assert num.allclose(domain.quantities['stage'].semi_implicit_update, 0) assert num.allclose(domain.quantities['xmomentum'].semi_implicit_update,3*S) assert num.allclose(domain.quantities['ymomentum'].semi_implicit_update,4*S) def test_inflow_using_circle(self): from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, constant inflow of 2 m^3/s # on a circle affecting triangles #0 and #1 (bac and bce) domain.forcing_terms = [] I = Inflow(domain, rate=2.0, center=(1,1), radius=1) domain.forcing_terms.append(I) domain.compute_forcing_terms() A = I.exchange_area assert num.allclose(A, 4) # Two triangles assert num.allclose(domain.quantities['stage'].explicit_update[1], 2.0/A) assert num.allclose(domain.quantities['stage'].explicit_update[0], 2.0/A) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_inflow_using_circle_function(self): from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, time dependent inflow of 2 m^3/s # on a circle affecting triangles #0 and #1 (bac and bce) domain.forcing_terms = [] I = Inflow(domain, rate=lambda t: 2., center=(1,1), radius=1) domain.forcing_terms.append(I) domain.compute_forcing_terms() A = I.exchange_area assert num.allclose(A, 4) # Two triangles assert num.allclose(domain.quantities['stage'].explicit_update[1], 2.0/A) assert num.allclose(domain.quantities['stage'].explicit_update[0], 2.0/A) assert num.allclose(domain.quantities['stage'].explicit_update[2:], 0) def test_inflow_catch_too_few_triangles(self): """ Test that exception is thrown if no triangles are covered by the inflow area """ from math import pi, cos, sin a = [0.0, 0.0] b = [0.0, 2.0] c = [2.0, 0.0] d = [0.0, 4.0] e = [2.0, 2.0] f = [4.0, 0.0] points = [a, b, c, d, e, f] # bac, bce, ecf, dbe vertices = [[1,0,2], [1,2,4], [4,2,5], [3,1,4]] domain = Domain(points, vertices) # Flat surface with 1m of water domain.set_quantity('elevation', 0) domain.set_quantity('stage', 1.0) domain.set_quantity('friction', 0) Br = Reflective_boundary(domain) domain.set_boundary({'exterior': Br}) # Setup only one forcing term, constant inflow of 2 m^3/s # on a circle affecting triangles #0 and #1 (bac and bce) try: Inflow(domain, rate=2.0, center=(1,1.1), radius=0.01) except: pass else: msg = 'Should have raised exception' raise_(Exception, msg) if __name__ == "__main__": suite = unittest.makeSuite(Test_Forcing, 'test') runner = unittest.TextTestRunner(verbosity=1) runner.run(suite)

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4029a4ce4aabb36c265b2c6f21702ec5d875e1d2

31,062

py

Python

inkscape/.config/inkscape/extensions/circuitSymbols/drawSources.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

inkscape/.config/inkscape/extensions/circuitSymbols/drawSources.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

inkscape/.config/inkscape/extensions/circuitSymbols/drawSources.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

#!/usr/bin/python import inkscapeMadeEasy.inkscapeMadeEasy_Base as inkBase import inkscapeMadeEasy.inkscapeMadeEasy_Draw as inkDraw class source(inkBase.inkscapeMadeEasy): def add(self, vector, delta): # nector does not need to be numpy array. delta will be converted to numpy array. Numpy can then deal with np.array + list return vector + np.array(delta) def drawSigns(self, group, positionPos=None, positionNeg=None): # draw + and - signs # positive Sign lineStyleSign = inkDraw.lineStyle.setSimpleBlack(lineWidth=0.6) if positionPos is not None: inkDraw.line.relCoords(group, [[2, 0]], self.add(positionPos, [-1, 0]), lineStyle=lineStyleSign) inkDraw.line.relCoords(group, [[0, 2]], self.add(positionPos, [0, -1]), lineStyle=lineStyleSign) # negative Sign if positionNeg is not None: inkDraw.line.relCoords(group, [[0, 2]], self.add(positionNeg, [0, -1]), lineStyle=lineStyleSign) # --------------------------------------------- def drawSourceV(self, parent, position=[0, 0], value='v(t)', sourceType='general', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, currName='i', invertArrows=False, mirror=False, convention='active', wireExtraSize=0,standard='IEEE',flagVariable=False): """ draws a independend voltage source parent: parent object position: position [x,y] value: string with value. sourceType: type of source. Values: 'general' (default), 'sinusoidal' label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) flagCurr: indicates whether the current arrow must be drawn (default: true) currName: current drop name (default: i) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) standard: types: 'IEEE' (american), 'IEC' (european) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) lineStyleSign = inkDraw.lineStyle.setSimpleBlack(lineWidth=0.6) inkDraw.line.relCoords(elem, [[-(18 + wireExtraSize), 0]], self.add(position, [-7, 0])) inkDraw.line.relCoords(elem, [[18 + wireExtraSize, 0]], self.add(position, [7, 0])) inkDraw.circle.centerRadius(elem, [0, 0], 7.0, offset=position, label='circle') if sourceType == 'general': if standard == 'IEEE': # signs if mirror: self.drawSigns(elem, positionPos=self.add(position, [-4, 0]), positionNeg=self.add(position, [4, 0])) else: self.drawSigns(elem, positionPos=self.add(position, [4, 0]), positionNeg=self.add(position, [-4, 0])) if standard == 'IEC': inkDraw.line.relCoords(elem, [[14, 0]], self.add(position, [-7, 0]),lineStyle=lineStyleSign) if sourceType == 'sinusoidal': sine = self.createGroup(elem) inkDraw.arc.startEndRadius(sine, self.add(position, [-5, 0]), position, 2.6, [0, 0], lineStyle=lineStyleSign, flagRightOf=True, largeArc=False) inkDraw.arc.startEndRadius(sine, self.add(position, [5, 0]), position, 2.6, [0, 0], lineStyle=lineStyleSign, flagRightOf=True, largeArc=False) self.rotateElement(sine, position, -angleDeg) if mirror: self.drawSigns(elem, positionPos=self.add(position, [-10, -4]), positionNeg=self.add(position, [10, -4])) else: self.drawSigns(elem, positionPos=self.add(position, [10, -4]), positionNeg=self.add(position, [-10, -4])) if flagVariable: # build arrow marker colorBlack = inkDraw.color.defined('black') L_arrow = 2.5 markerPath = 'M 0,0 l -%f,%f l 0,-%f z' % (L_arrow * 1.2, L_arrow / 2.0, L_arrow) markerArrow = inkDraw.marker.createMarker(self, 'arrow', markerPath, RenameMode=0, strokeColor=colorBlack, fillColor=colorBlack, lineWidth=0.6, markerTransform='translate (1,0)') lineStyleArrow = inkDraw.lineStyle.set(lineWidth=1, lineColor=colorBlack, markerEnd=markerArrow) inkDraw.line.relCoords(elem, [[17, -15]], self.add(position, [-8, 7]), lineStyle=lineStyleArrow) pos_text = self.add(position, [0, -8 - self.textOffset]) if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) inv_volt = (invertArrows == mirror) if flagVolt: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawVoltArrow(group, self.add(position, [0, 8]), name=value, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_volt) if flagCurr: if convention == 'active': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_volt) if convention == 'passive': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=not inv_volt) return group # --------------------------------------------- def drawSourceVDC(self, parent, position=[0, 0], value='V', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, currName='i', invertArrows=False, mirror=False, convention='active', wireExtraSize=0,flagVariable=False): """ draws a DC voltage source parent: parent object position: position [x,y] value: string with value. label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) flagCurr: indicates whether the current arrow must be drawn (default: true) currName: current drop name (default: i) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) inkDraw.line.relCoords(elem, [[-(24 + wireExtraSize), 0]], self.add(position, [-1, 0])) inkDraw.line.relCoords(elem, [[23 + wireExtraSize, 0]], self.add(position, [2, 0])) # draw source if mirror: self.drawSigns(elem, positionPos=self.add(position, [-4, -6]), positionNeg=self.add(position, [5, -6])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [2, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [-1, 7])) else: self.drawSigns(elem, positionPos=self.add(position, [5, -6]), positionNeg=self.add(position, [-4, -6])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [-1, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [2, 7])) if flagVariable: # build arrow marker colorBlack = inkDraw.color.defined('black') L_arrow = 2.5 markerPath = 'M 0,0 l -%f,%f l 0,-%f z' % (L_arrow * 1.2, L_arrow / 2.0, L_arrow) markerArrow = inkDraw.marker.createMarker(self, 'arrow', markerPath, RenameMode=0, strokeColor=colorBlack, fillColor=colorBlack, lineWidth=0.6, markerTransform='translate (1,0)') lineStyleArrow = inkDraw.lineStyle.set(lineWidth=1, lineColor=colorBlack, markerEnd=markerArrow) inkDraw.line.relCoords(elem, [[16, -10]], self.add(position, [-8, 5]), lineStyle=lineStyleArrow) pos_text = self.add(position, [0, -8 - self.textOffset]) if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) inv_volt = (invertArrows == mirror) if flagVolt: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawVoltArrow(group, self.add(position, [0, 8]), name=value, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_volt) if flagCurr: if convention == 'active': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_volt) if convention == 'passive': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=not inv_volt) return group # --------------------------------------------- def drawSourceVDCbattery(self, parent, position=[0, 0], value='V', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, currName='i', invertArrows=False, mirror=False, convention='active', wireExtraSize=0,flagVariable=False): """ draws a DC battery source parent: parent object position: position [x,y] value: string with value. label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) flagCurr: indicates whether the current arrow must be drawn (default: true) currName: current drop name (default: i) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) inkDraw.line.relCoords(elem, [[-(18 + wireExtraSize), 0]], self.add(position, [-7, 0])) inkDraw.line.relCoords(elem, [[17 + wireExtraSize, 0]], self.add(position, [8, 0])) # draw source if mirror: self.drawSigns(elem, positionPos=self.add(position, [-10, -4]), positionNeg=self.add(position, [11, -4])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [-4, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [-7, 7])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [2, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [-1, 7])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [8, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [5, 7])) else: self.drawSigns(elem, positionPos=self.add(position, [11, -4]), positionNeg=self.add(position, [-10, -4])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [-4, 7])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [-7, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [2, 7])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [-1, 3])) inkDraw.line.relCoords(elem, [[0, -14]], self.add(position, [8, 7])) inkDraw.line.relCoords(elem, [[0, -6]], self.add(position, [5, 3])) if flagVariable: # build arrow marker colorBlack = inkDraw.color.defined('black') L_arrow = 2.5 markerPath = 'M 0,0 l -%f,%f l 0,-%f z' % (L_arrow * 1.2, L_arrow / 2.0, L_arrow) markerArrow = inkDraw.marker.createMarker(self, 'arrow', markerPath, RenameMode=0, strokeColor=colorBlack, fillColor=colorBlack, lineWidth=0.6, markerTransform='translate (1,0)') lineStyleArrow = inkDraw.lineStyle.set(lineWidth=1, lineColor=colorBlack, markerEnd=markerArrow) inkDraw.line.relCoords(elem, [[19, -18]], self.add(position, [-9, 8]), lineStyle=lineStyleArrow) pos_text = self.add(position, [0, -9 - self.textOffset]) if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) inv_volt = (invertArrows == mirror) if flagVolt: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawVoltArrow(group, self.add(position, [0, 9]), name=value, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_volt) if flagCurr: if convention == 'active': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_volt) if convention == 'passive': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=not inv_volt) return group # --------------------------------------------- def drawSourceI(self, parent, position=[0, 0], value='i(t)', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, voltName='v', invertArrows=False, mirror=False, convention='active', wireExtraSize=0,standard='IEEE',flagVariable=False): """ draws a independend general current source parent: parent object position: position [x,y] value: string with value. label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) voltName: voltage drop name (default: v) flagCurr: indicates whether the current arrow must be drawn (default: true) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) standard: types: 'IEEE' (american), 'IEC' (european), 'OLD' (two circles - DIN) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) # terminals and circle(s) if standard.upper() == 'OLD': inkDraw.line.relCoords(elem, [[-(14 + wireExtraSize), 0]], self.add(position, [-11, 0])) inkDraw.line.relCoords(elem, [[14 + wireExtraSize, 0]], self.add(position, [11, 0])) inkDraw.circle.centerRadius(elem, [4, 0], 7.0, offset=position, label='circle') inkDraw.circle.centerRadius(elem, [-4, 0], 7.0, offset=position, label='circle') else: inkDraw.line.relCoords(elem, [[-(18 + wireExtraSize), 0]], self.add(position, [-7, 0])) inkDraw.line.relCoords(elem, [[18 + wireExtraSize, 0]], self.add(position, [7, 0])) inkDraw.circle.centerRadius(elem, [0, 0], 7.0, offset=position, label='circle') # arrow if standard.upper() == 'IEEE': lineStyleSign = inkDraw.lineStyle.set(lineWidth=0.7, lineColor=inkDraw.color.defined('black'), fillColor=inkDraw.color.defined('black')) if mirror: inkDraw.line.relCoords(elem, [[-5, 0], [0, 1.2], [-3, -1.2], [3, -1.2], [0, 1.2]], self.add(position, [4, 0]), lineStyle=lineStyleSign) else: inkDraw.line.relCoords(elem, [[5, 0], [0, 1.2], [3, -1.2], [-3, -1.2], [0, 1.2]], self.add(position, [-4, 0]), lineStyle=lineStyleSign) if standard.upper() == 'IEC': lineStyleSign = inkDraw.lineStyle.setSimpleBlack(lineWidth=0.6) inkDraw.line.relCoords(elem, [[0,14]], self.add(position, [0,-7]),lineStyle=lineStyleSign) #if standard.upper() == 'OLD': # lineStyleSign = inkDraw.lineStyle.set(lineWidth=0.7, lineColor=inkDraw.color.defined('black'), fillColor=inkDraw.color.defined('black')) # if mirror: # inkDraw.line.relCoords(elem, [[-13, 0], [0, 1.2], [-3, -1.2], [3, -1.2], [0, 1.2]], self.add(position, [8, 0]), lineStyle=lineStyleSign) # else: # inkDraw.line.relCoords(elem, [[13, 0], [0, 1.2], [3, -1.2], [-3, -1.2], [0, 1.2]], self.add(position, [-8, 0]), lineStyle=lineStyleSign) if flagVariable: # build arrow marker colorBlack = inkDraw.color.defined('black') L_arrow = 2.5 markerPath = 'M 0,0 l -%f,%f l 0,-%f z' % (L_arrow * 1.2, L_arrow / 2.0, L_arrow) markerArrow = inkDraw.marker.createMarker(self, 'arrow', markerPath, RenameMode=0, strokeColor=colorBlack, fillColor=colorBlack, lineWidth=0.6, markerTransform='translate (1,0)') lineStyleArrow = inkDraw.lineStyle.set(lineWidth=1, lineColor=colorBlack, markerEnd=markerArrow) if standard.upper() == 'OLD': inkDraw.line.relCoords(elem, [[20, -15]], self.add(position, [-10, 7]), lineStyle=lineStyleArrow) else: inkDraw.line.relCoords(elem, [[17, -15]], self.add(position, [-8, 7]), lineStyle=lineStyleArrow) pos_text = self.add(position, [0, -8 - self.textOffset]) if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) inv_curr = (invertArrows == mirror) if flagVolt: if convention == 'active': self.drawVoltArrow(group, self.add(position, [0, 9]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_curr) if convention == 'passive': self.drawVoltArrow(group, self.add(position, [0, 9]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=not inv_curr) if flagCurr: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=value, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_curr) return group # --------------------------------------------- def drawControledSourceV(self, parent, position=[0, 0], controlType='volt', gain='k', controlName='v_c', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, currName='i', invertArrows=False, mirror=False, convention='active', drawControl=False, wireExtraSize=0,standard='IEEE'): """ draws a controlled general voltage source parent: parent object position: position [x,y] controlType: 'volt' or 'curr' gain: controlled source gain value controlName: name of the controlling signal label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) currName: current name (default: i) flagCurr: indicates whether the current arrow must be drawn (default: true) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) drawControl: draws control annotation arrow (default:false) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) standard: types: 'IEEE' (american), 'IEC' (european) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) lineStyleSign = inkDraw.lineStyle.setSimpleBlack(lineWidth=0.6) inkDraw.line.relCoords(elem, [[-(17 + wireExtraSize), 0]], self.add(position, [-8, 0])) inkDraw.line.relCoords(elem, [[17 + wireExtraSize, 0]], self.add(position, [8, 0])) inkDraw.line.relCoords(elem, [[8, 8], [8, -8], [-8, -8], [-8, 8]], self.add(position, [-8, 0])) if standard == 'IEEE': # signs if mirror: self.drawSigns(elem, positionPos=self.add(position, [-4, 0]), positionNeg=self.add(position, [4, 0])) else: self.drawSigns(elem, positionPos=self.add(position, [4, 0]), positionNeg=self.add(position, [-4, 0])) if standard == 'IEC': inkDraw.line.relCoords(elem, [[14, 0]], self.add(position, [-7, 0]),lineStyle=lineStyleSign) # text pos_text = self.add(position, [0, -8 - self.textOffset]) value = gain + '.' + controlName if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) # arrows inv_volt = (invertArrows == mirror) if flagVolt: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawVoltArrow(group, self.add(position, [0, 8]), name=value, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_volt) if flagCurr: if convention == 'active': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_volt) if convention == 'passive': self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=not inv_volt) # control signal if drawControl: for theta in range(0, 360, 90): pos1 = self.add(position, [-20, 25 + theta / 4]) pos2 = self.add(position, [0, 25 + theta / 4]) if controlType == 'volt': temp1 = self.drawVoltArrow(parent, pos1, name=controlName, color=self.voltageColor, angleDeg=theta, invertArrows=False) temp2 = self.drawVoltArrow(parent, pos2, name=controlName, color=self.voltageColor, angleDeg=theta, invertArrows=True) if controlType == 'curr': temp1 = self.drawCurrArrow(parent, pos1, name=controlName, color=self.currentColor, angleDeg=theta, invertArrows=False) temp2 = self.drawCurrArrow(parent, pos2, name=controlName, color=self.currentColor, angleDeg=theta, invertArrows=True) self.rotateElement(temp1, pos1, theta) self.rotateElement(temp2, pos2, theta) return group # --------------------------------------------- def drawControledSourceI(self, parent, position=[0, 0], controlType='volt', gain='k', controlName='v_c', label='Source', angleDeg=0, flagVolt=True, flagCurr=True, voltName='v', invertArrows=False, mirror=False, convention='active', drawControl=False, wireExtraSize=0,standard='IEEE'): """ draws a controlled general current source parent: parent object position: position [x,y] controlType: 'volt' or 'curr' gain: controlled source gain value controlName: name of the controlling signal label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) flagVolt: indicates whether the voltage arrow must be drawn (default: true) voltName: voltage name (default: v) flagCurr: indicates whether the current arrow must be drawn (default: true) mirror: mirror source drawing (default: False) convention: passive/active sign convention. available types: 'passive', 'active' (default) wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) drawControl: draws control annotation arrow (default:false) standard: types: 'IEEE' (american), 'IEC' (european) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) inkDraw.line.relCoords(elem, [[-(17 + wireExtraSize), 0]], self.add(position, [-8, 0])) inkDraw.line.relCoords(elem, [[17 + wireExtraSize, 0]], self.add(position, [8, 0])) inkDraw.line.relCoords(elem, [[8, 8], [8, -8], [-8, -8], [-8, 8]], self.add(position, [-8, 0])) if standard == 'IEEE': # arrow lineStyleSign = inkDraw.lineStyle.set(lineWidth=0.7, lineColor=inkDraw.color.defined('black'), fillColor=inkDraw.color.defined('black')) if mirror: inkDraw.line.relCoords(elem, [[-5, 0], [0, 1.2], [-3, -1.2], [3, -1.2], [0, 1.2]], self.add(position, [4, 0]), lineStyle=lineStyleSign) else: inkDraw.line.relCoords(elem, [[5, 0], [0, 1.2], [3, -1.2], [-3, -1.2], [0, 1.2]], self.add(position, [-4, 0]), lineStyle=lineStyleSign) if standard == 'IEC': lineStyleSign = inkDraw.lineStyle.setSimpleBlack(lineWidth=0.6) inkDraw.line.relCoords(elem, [[0,14]], self.add(position, [0,-7]),lineStyle=lineStyleSign) # text pos_text = self.add(position, [0, -8 - self.textOffset]) value = gain + '.' + controlName if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bc', preambleFile=self.preambleFile) if angleDeg != 0: self.rotateElement(group, position, angleDeg) # arrows inv_curr = (invertArrows == mirror) if flagVolt: if convention == 'active': self.drawVoltArrow(group, self.add(position, [0, 8]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=inv_curr) if convention == 'passive': self.drawVoltArrow(group, self.add(position, [0, 8]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=not inv_curr) if flagCurr: if invertArrows: if inkDraw.useLatex: if value[1] == '-': value = value[0] + value[2:] else: value = value[0] + '-' + value[1:] else: if value[0] == '-': value = value[1:] else: value = '-' + value self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=value, color=self.currentColor, angleDeg=angleDeg, invertArrows=inv_curr) # control signal if drawControl: for theta in range(0, 360, 90): pos1 = self.add(position, [-20, 25 + theta / 4]) pos2 = self.add(position, [0, 25 + theta / 4]) if controlType == 'volt': temp1 = self.drawVoltArrow(parent, pos1, name=controlName, color=self.voltageColor, angleDeg=theta, invertArrows=False) temp2 = self.drawVoltArrow(parent, pos2, name=controlName, color=self.voltageColor, angleDeg=theta, invertArrows=True) if controlType == 'curr': temp1 = self.drawCurrArrow(parent, pos1, name=controlName, color=self.currentColor, angleDeg=theta, invertArrows=False) temp2 = self.drawCurrArrow(parent, pos2, name=controlName, color=self.currentColor, angleDeg=theta, invertArrows=True) self.rotateElement(temp1, pos1, theta) self.rotateElement(temp2, pos2, theta) return group

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4030505b9603d1865f92c966ab67b2f10ca9b440

13,191

py

Python

tests/test_metrics.py

HeqingZhang/mmsegmentation

90d8038e909be9f2154b49d15f95a648ceb75120

[ "Apache-2.0" ]

367

2022-01-14T03:32:25.000Z

2022-03-31T04:48:20.000Z

tests/test_metrics.py

Junjun2016/LiteHRNet

e2b13de52e970215be566067cab7bd880010f062

[ "Apache-2.0" ]

27

2022-01-27T07:12:49.000Z

2022-03-31T04:31:13.000Z

tests/test_metrics.py

Junjun2016/LiteHRNet

e2b13de52e970215be566067cab7bd880010f062

[ "Apache-2.0" ]

53

2022-01-18T11:21:43.000Z

2022-03-31T06:42:41.000Z

import numpy as np from mmseg.core.evaluation import (eval_metrics, mean_dice, mean_fscore, mean_iou) from mmseg.core.evaluation.metrics import f_score def get_confusion_matrix(pred_label, label, num_classes, ignore_index): """Intersection over Union Args: pred_label (np.ndarray): 2D predict map label (np.ndarray): label 2D label map num_classes (int): number of categories ignore_index (int): index ignore in evaluation """ mask = (label != ignore_index) pred_label = pred_label[mask] label = label[mask] n = num_classes inds = n * label + pred_label mat = np.bincount(inds, minlength=n**2).reshape(n, n) return mat # This func is deprecated since it's not memory efficient def legacy_mean_iou(results, gt_seg_maps, num_classes, ignore_index): num_imgs = len(results) assert len(gt_seg_maps) == num_imgs total_mat = np.zeros((num_classes, num_classes), dtype=np.float) for i in range(num_imgs): mat = get_confusion_matrix( results[i], gt_seg_maps[i], num_classes, ignore_index=ignore_index) total_mat += mat all_acc = np.diag(total_mat).sum() / total_mat.sum() acc = np.diag(total_mat) / total_mat.sum(axis=1) iou = np.diag(total_mat) / ( total_mat.sum(axis=1) + total_mat.sum(axis=0) - np.diag(total_mat)) return all_acc, acc, iou # This func is deprecated since it's not memory efficient def legacy_mean_dice(results, gt_seg_maps, num_classes, ignore_index): num_imgs = len(results) assert len(gt_seg_maps) == num_imgs total_mat = np.zeros((num_classes, num_classes), dtype=np.float) for i in range(num_imgs): mat = get_confusion_matrix( results[i], gt_seg_maps[i], num_classes, ignore_index=ignore_index) total_mat += mat all_acc = np.diag(total_mat).sum() / total_mat.sum() acc = np.diag(total_mat) / total_mat.sum(axis=1) dice = 2 * np.diag(total_mat) / ( total_mat.sum(axis=1) + total_mat.sum(axis=0)) return all_acc, acc, dice # This func is deprecated since it's not memory efficient def legacy_mean_fscore(results, gt_seg_maps, num_classes, ignore_index, beta=1): num_imgs = len(results) assert len(gt_seg_maps) == num_imgs total_mat = np.zeros((num_classes, num_classes), dtype=np.float) for i in range(num_imgs): mat = get_confusion_matrix( results[i], gt_seg_maps[i], num_classes, ignore_index=ignore_index) total_mat += mat all_acc = np.diag(total_mat).sum() / total_mat.sum() recall = np.diag(total_mat) / total_mat.sum(axis=1) precision = np.diag(total_mat) / total_mat.sum(axis=0) fv = np.vectorize(f_score) fscore = fv(precision, recall, beta=beta) return all_acc, recall, precision, fscore def test_metrics(): pred_size = (10, 30, 30) num_classes = 19 ignore_index = 255 results = np.random.randint(0, num_classes, size=pred_size) label = np.random.randint(0, num_classes, size=pred_size) # Test the availability of arg: ignore_index. label[:, 2, 5:10] = ignore_index # Test the correctness of the implementation of mIoU calculation. ret_metrics = eval_metrics( results, label, num_classes, ignore_index, metrics='mIoU') all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'IoU'] all_acc_l, acc_l, iou_l = legacy_mean_iou(results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(iou, iou_l) # Test the correctness of the implementation of mDice calculation. ret_metrics = eval_metrics( results, label, num_classes, ignore_index, metrics='mDice') all_acc, acc, dice = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'Dice'] all_acc_l, acc_l, dice_l = legacy_mean_dice(results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(dice, dice_l) # Test the correctness of the implementation of mDice calculation. ret_metrics = eval_metrics( results, label, num_classes, ignore_index, metrics='mFscore') all_acc, recall, precision, fscore = ret_metrics['aAcc'], ret_metrics[ 'Recall'], ret_metrics['Precision'], ret_metrics['Fscore'] all_acc_l, recall_l, precision_l, fscore_l = legacy_mean_fscore( results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(recall, recall_l) assert np.allclose(precision, precision_l) assert np.allclose(fscore, fscore_l) # Test the correctness of the implementation of joint calculation. ret_metrics = eval_metrics( results, label, num_classes, ignore_index, metrics=['mIoU', 'mDice', 'mFscore']) all_acc, acc, iou, dice, precision, recall, fscore = ret_metrics[ 'aAcc'], ret_metrics['Acc'], ret_metrics['IoU'], ret_metrics[ 'Dice'], ret_metrics['Precision'], ret_metrics[ 'Recall'], ret_metrics['Fscore'] assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(iou, iou_l) assert np.allclose(dice, dice_l) assert np.allclose(precision, precision_l) assert np.allclose(recall, recall_l) assert np.allclose(fscore, fscore_l) # Test the correctness of calculation when arg: num_classes is larger # than the maximum value of input maps. results = np.random.randint(0, 5, size=pred_size) label = np.random.randint(0, 4, size=pred_size) ret_metrics = eval_metrics( results, label, num_classes, ignore_index=255, metrics='mIoU', nan_to_num=-1) all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'IoU'] assert acc[-1] == -1 assert iou[-1] == -1 ret_metrics = eval_metrics( results, label, num_classes, ignore_index=255, metrics='mDice', nan_to_num=-1) all_acc, acc, dice = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'Dice'] assert acc[-1] == -1 assert dice[-1] == -1 ret_metrics = eval_metrics( results, label, num_classes, ignore_index=255, metrics='mFscore', nan_to_num=-1) all_acc, precision, recall, fscore = ret_metrics['aAcc'], ret_metrics[ 'Precision'], ret_metrics['Recall'], ret_metrics['Fscore'] assert precision[-1] == -1 assert recall[-1] == -1 assert fscore[-1] == -1 ret_metrics = eval_metrics( results, label, num_classes, ignore_index=255, metrics=['mDice', 'mIoU', 'mFscore'], nan_to_num=-1) all_acc, acc, iou, dice, precision, recall, fscore = ret_metrics[ 'aAcc'], ret_metrics['Acc'], ret_metrics['IoU'], ret_metrics[ 'Dice'], ret_metrics['Precision'], ret_metrics[ 'Recall'], ret_metrics['Fscore'] assert acc[-1] == -1 assert dice[-1] == -1 assert iou[-1] == -1 assert precision[-1] == -1 assert recall[-1] == -1 assert fscore[-1] == -1 # Test the bug which is caused by torch.histc. # torch.histc: https://pytorch.org/docs/stable/generated/torch.histc.html # When the arg:bins is set to be same as arg:max, # some channels of mIoU may be nan. results = np.array([np.repeat(31, 59)]) label = np.array([np.arange(59)]) num_classes = 59 ret_metrics = eval_metrics( results, label, num_classes, ignore_index=255, metrics='mIoU') all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'IoU'] assert not np.any(np.isnan(iou)) def test_mean_iou(): pred_size = (10, 30, 30) num_classes = 19 ignore_index = 255 results = np.random.randint(0, num_classes, size=pred_size) label = np.random.randint(0, num_classes, size=pred_size) label[:, 2, 5:10] = ignore_index ret_metrics = mean_iou(results, label, num_classes, ignore_index) all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'IoU'] all_acc_l, acc_l, iou_l = legacy_mean_iou(results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(iou, iou_l) results = np.random.randint(0, 5, size=pred_size) label = np.random.randint(0, 4, size=pred_size) ret_metrics = mean_iou( results, label, num_classes, ignore_index=255, nan_to_num=-1) all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'IoU'] assert acc[-1] == -1 assert acc[-1] == -1 def test_mean_dice(): pred_size = (10, 30, 30) num_classes = 19 ignore_index = 255 results = np.random.randint(0, num_classes, size=pred_size) label = np.random.randint(0, num_classes, size=pred_size) label[:, 2, 5:10] = ignore_index ret_metrics = mean_dice(results, label, num_classes, ignore_index) all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'Dice'] all_acc_l, acc_l, dice_l = legacy_mean_dice(results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(iou, dice_l) results = np.random.randint(0, 5, size=pred_size) label = np.random.randint(0, 4, size=pred_size) ret_metrics = mean_dice( results, label, num_classes, ignore_index=255, nan_to_num=-1) all_acc, acc, dice = ret_metrics['aAcc'], ret_metrics['Acc'], ret_metrics[ 'Dice'] assert acc[-1] == -1 assert dice[-1] == -1 def test_mean_fscore(): pred_size = (10, 30, 30) num_classes = 19 ignore_index = 255 results = np.random.randint(0, num_classes, size=pred_size) label = np.random.randint(0, num_classes, size=pred_size) label[:, 2, 5:10] = ignore_index ret_metrics = mean_fscore(results, label, num_classes, ignore_index) all_acc, recall, precision, fscore = ret_metrics['aAcc'], ret_metrics[ 'Recall'], ret_metrics['Precision'], ret_metrics['Fscore'] all_acc_l, recall_l, precision_l, fscore_l = legacy_mean_fscore( results, label, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(recall, recall_l) assert np.allclose(precision, precision_l) assert np.allclose(fscore, fscore_l) ret_metrics = mean_fscore( results, label, num_classes, ignore_index, beta=2) all_acc, recall, precision, fscore = ret_metrics['aAcc'], ret_metrics[ 'Recall'], ret_metrics['Precision'], ret_metrics['Fscore'] all_acc_l, recall_l, precision_l, fscore_l = legacy_mean_fscore( results, label, num_classes, ignore_index, beta=2) assert all_acc == all_acc_l assert np.allclose(recall, recall_l) assert np.allclose(precision, precision_l) assert np.allclose(fscore, fscore_l) results = np.random.randint(0, 5, size=pred_size) label = np.random.randint(0, 4, size=pred_size) ret_metrics = mean_fscore( results, label, num_classes, ignore_index=255, nan_to_num=-1) all_acc, recall, precision, fscore = ret_metrics['aAcc'], ret_metrics[ 'Recall'], ret_metrics['Precision'], ret_metrics['Fscore'] assert recall[-1] == -1 assert precision[-1] == -1 assert fscore[-1] == -1 def test_filename_inputs(): import cv2 import tempfile def save_arr(input_arrays: list, title: str, is_image: bool, dir: str): filenames = [] SUFFIX = '.png' if is_image else '.npy' for idx, arr in enumerate(input_arrays): filename = '{}/{}-{}{}'.format(dir, title, idx, SUFFIX) if is_image: cv2.imwrite(filename, arr) else: np.save(filename, arr) filenames.append(filename) return filenames pred_size = (10, 30, 30) num_classes = 19 ignore_index = 255 results = np.random.randint(0, num_classes, size=pred_size) labels = np.random.randint(0, num_classes, size=pred_size) labels[:, 2, 5:10] = ignore_index with tempfile.TemporaryDirectory() as temp_dir: result_files = save_arr(results, 'pred', False, temp_dir) label_files = save_arr(labels, 'label', True, temp_dir) ret_metrics = eval_metrics( result_files, label_files, num_classes, ignore_index, metrics='mIoU') all_acc, acc, iou = ret_metrics['aAcc'], ret_metrics[ 'Acc'], ret_metrics['IoU'] all_acc_l, acc_l, iou_l = legacy_mean_iou(results, labels, num_classes, ignore_index) assert all_acc == all_acc_l assert np.allclose(acc, acc_l) assert np.allclose(iou, iou_l)

37.688571

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4098cb75097ef32fb06fbb9da21062dfcdd26410

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py

Python

harness/determined/_swagger/client/api/internal_api.py

wbwatkinson/determined

f9e099e06746a79a2eaf51a89acc264fc5c301e1

[ "Apache-2.0" ]

null

harness/determined/_swagger/client/api/internal_api.py

wbwatkinson/determined

f9e099e06746a79a2eaf51a89acc264fc5c301e1

[ "Apache-2.0" ]

null

harness/determined/_swagger/client/api/internal_api.py

wbwatkinson/determined

f9e099e06746a79a2eaf51a89acc264fc5c301e1

[ "Apache-2.0" ]

null

# coding: utf-8 """ Determined API (Beta) Determined helps deep learning teams train models more quickly, easily share GPU resources, and effectively collaborate. Determined allows deep learning engineers to focus on building and training models at scale, without needing to worry about DevOps or writing custom code for common tasks like fault tolerance or experiment tracking. You can think of Determined as a platform that bridges the gap between tools like TensorFlow and PyTorch --- which work great for a single researcher with a single GPU --- to the challenges that arise when doing deep learning at scale, as teams, clusters, and data sets all increase in size. # noqa: E501 OpenAPI spec version: 0.1 Contact: community@determined.ai Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from determined._swagger.client.api_client import ApiClient class InternalApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def determined_complete_trial_searcher_validation(self, trial_id, body, **kwargs): # noqa: E501 """Reports to the searcher that the trial has completed the given searcher operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_complete_trial_searcher_validation(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param V1CompleteValidateAfterOperation body: The completed operation. (required) :return: V1CompleteTrialSearcherValidationResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_complete_trial_searcher_validation_with_http_info(trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_complete_trial_searcher_validation_with_http_info(trial_id, body, **kwargs) # noqa: E501 return data def determined_complete_trial_searcher_validation_with_http_info(self, trial_id, body, **kwargs): # noqa: E501 """Reports to the searcher that the trial has completed the given searcher operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_complete_trial_searcher_validation_with_http_info(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param V1CompleteValidateAfterOperation body: The completed operation. (required) :return: V1CompleteTrialSearcherValidationResponse If the method is called asynchronously, returns the request thread. """ all_params = ['trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_complete_trial_searcher_validation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'trial_id' is set if ('trial_id' not in params or params['trial_id'] is None): raise ValueError("Missing the required parameter `trial_id` when calling `determined_complete_trial_searcher_validation`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_complete_trial_searcher_validation`") # noqa: E501 collection_formats = {} path_params = {} if 'trial_id' in params: path_params['trialId'] = params['trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trialId}/searcher/completed_operation', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1CompleteTrialSearcherValidationResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_compute_hp_importance(self, experiment_id, **kwargs): # noqa: E501 """Trigger the computation of hyperparameter importance on-demand for a specific metric on a specific experiment. The status and results can be retrieved with GetHPImportance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_compute_hp_importance(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :return: V1ComputeHPImportanceResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_compute_hp_importance_with_http_info(experiment_id, **kwargs) # noqa: E501 else: (data) = self.determined_compute_hp_importance_with_http_info(experiment_id, **kwargs) # noqa: E501 return data def determined_compute_hp_importance_with_http_info(self, experiment_id, **kwargs): # noqa: E501 """Trigger the computation of hyperparameter importance on-demand for a specific metric on a specific experiment. The status and results can be retrieved with GetHPImportance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_compute_hp_importance_with_http_info(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :return: V1ComputeHPImportanceResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_compute_hp_importance" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_compute_hp_importance`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/hyperparameter-importance', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ComputeHPImportanceResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_create_experiment(self, body, **kwargs): # noqa: E501 """Create an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_create_experiment(body, async_req=True) >>> result = thread.get() :param async_req bool :param V1CreateExperimentRequest body: (required) :return: V1CreateExperimentResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_create_experiment_with_http_info(body, **kwargs) # noqa: E501 else: (data) = self.determined_create_experiment_with_http_info(body, **kwargs) # noqa: E501 return data def determined_create_experiment_with_http_info(self, body, **kwargs): # noqa: E501 """Create an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_create_experiment_with_http_info(body, async_req=True) >>> result = thread.get() :param async_req bool :param V1CreateExperimentRequest body: (required) :return: V1CreateExperimentResponse If the method is called asynchronously, returns the request thread. """ all_params = ['body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_create_experiment" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_create_experiment`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1CreateExperimentResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_get_current_trial_searcher_operation(self, trial_id, **kwargs): # noqa: E501 """Get the current searcher operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_current_trial_searcher_operation(trial_id, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :return: V1GetCurrentTrialSearcherOperationResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_get_current_trial_searcher_operation_with_http_info(trial_id, **kwargs) # noqa: E501 else: (data) = self.determined_get_current_trial_searcher_operation_with_http_info(trial_id, **kwargs) # noqa: E501 return data def determined_get_current_trial_searcher_operation_with_http_info(self, trial_id, **kwargs): # noqa: E501 """Get the current searcher operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_current_trial_searcher_operation_with_http_info(trial_id, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :return: V1GetCurrentTrialSearcherOperationResponse If the method is called asynchronously, returns the request thread. """ all_params = ['trial_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_get_current_trial_searcher_operation" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'trial_id' is set if ('trial_id' not in params or params['trial_id'] is None): raise ValueError("Missing the required parameter `trial_id` when calling `determined_get_current_trial_searcher_operation`") # noqa: E501 collection_formats = {} path_params = {} if 'trial_id' in params: path_params['trialId'] = params['trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trialId}/searcher/operation', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1GetCurrentTrialSearcherOperationResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_get_hp_importance(self, experiment_id, **kwargs): # noqa: E501 """Retrieve the latest computation of hyperparameter importance. Currently this is triggered for training loss (if emitted) and the searcher metric after 10% increments in an experiment's progress, but no more than every 10 minutes. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_hp_importance(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1GetHPImportanceResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_get_hp_importance_with_http_info(experiment_id, **kwargs) # noqa: E501 else: (data) = self.determined_get_hp_importance_with_http_info(experiment_id, **kwargs) # noqa: E501 return data def determined_get_hp_importance_with_http_info(self, experiment_id, **kwargs): # noqa: E501 """Retrieve the latest computation of hyperparameter importance. Currently this is triggered for training loss (if emitted) and the searcher metric after 10% increments in an experiment's progress, but no more than every 10 minutes. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_hp_importance_with_http_info(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1GetHPImportanceResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id', 'period_seconds'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_get_hp_importance" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_get_hp_importance`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] if 'period_seconds' in params: query_params.append(('periodSeconds', params['period_seconds'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/hyperparameter-importance', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1GetHPImportanceResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_get_resource_pools(self, **kwargs): # noqa: E501 """Get a list of all resource pools from the cluster. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_resource_pools(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Skip the number of resource pools before returning results. Negative values denote number of resource pools to skip from the end before returning results. :param int limit: Limit the number of resource pools. A value of 0 denotes no limit. :return: V1GetResourcePoolsResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_get_resource_pools_with_http_info(**kwargs) # noqa: E501 else: (data) = self.determined_get_resource_pools_with_http_info(**kwargs) # noqa: E501 return data def determined_get_resource_pools_with_http_info(self, **kwargs): # noqa: E501 """Get a list of all resource pools from the cluster. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_resource_pools_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Skip the number of resource pools before returning results. Negative values denote number of resource pools to skip from the end before returning results. :param int limit: Limit the number of resource pools. A value of 0 denotes no limit. :return: V1GetResourcePoolsResponse If the method is called asynchronously, returns the request thread. """ all_params = ['offset', 'limit'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_get_resource_pools" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/resource-pools', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1GetResourcePoolsResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_get_telemetry(self, **kwargs): # noqa: E501 """Get telemetry information. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_telemetry(async_req=True) >>> result = thread.get() :param async_req bool :return: V1GetTelemetryResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_get_telemetry_with_http_info(**kwargs) # noqa: E501 else: (data) = self.determined_get_telemetry_with_http_info(**kwargs) # noqa: E501 return data def determined_get_telemetry_with_http_info(self, **kwargs): # noqa: E501 """Get telemetry information. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_get_telemetry_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :return: V1GetTelemetryResponse If the method is called asynchronously, returns the request thread. """ all_params = [] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_get_telemetry" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/api/v1/master/telemetry', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1GetTelemetryResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_metric_batches(self, experiment_id, metric_name, metric_type, **kwargs): # noqa: E501 """Get the milestones (in batches processed) at which a metric is recorded by an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_metric_batches(experiment_id, metric_name, metric_type, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1MetricBatchesResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_metric_batches_with_http_info(experiment_id, metric_name, metric_type, **kwargs) # noqa: E501 else: (data) = self.determined_metric_batches_with_http_info(experiment_id, metric_name, metric_type, **kwargs) # noqa: E501 return data def determined_metric_batches_with_http_info(self, experiment_id, metric_name, metric_type, **kwargs): # noqa: E501 """Get the milestones (in batches processed) at which a metric is recorded by an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_metric_batches_with_http_info(experiment_id, metric_name, metric_type, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1MetricBatchesResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id', 'metric_name', 'metric_type', 'period_seconds'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_metric_batches" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_metric_batches`") # noqa: E501 # verify the required parameter 'metric_name' is set if ('metric_name' not in params or params['metric_name'] is None): raise ValueError("Missing the required parameter `metric_name` when calling `determined_metric_batches`") # noqa: E501 # verify the required parameter 'metric_type' is set if ('metric_type' not in params or params['metric_type'] is None): raise ValueError("Missing the required parameter `metric_type` when calling `determined_metric_batches`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] if 'metric_name' in params: query_params.append(('metricName', params['metric_name'])) # noqa: E501 if 'metric_type' in params: query_params.append(('metricType', params['metric_type'])) # noqa: E501 if 'period_seconds' in params: query_params.append(('periodSeconds', params['period_seconds'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/metrics-stream/batches', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1MetricBatchesResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_metric_names(self, experiment_id, **kwargs): # noqa: E501 """Get the set of metric names recorded for an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_metric_names(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1MetricNamesResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_metric_names_with_http_info(experiment_id, **kwargs) # noqa: E501 else: (data) = self.determined_metric_names_with_http_info(experiment_id, **kwargs) # noqa: E501 return data def determined_metric_names_with_http_info(self, experiment_id, **kwargs): # noqa: E501 """Get the set of metric names recorded for an experiment. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_metric_names_with_http_info(experiment_id, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1MetricNamesResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id', 'period_seconds'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_metric_names" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_metric_names`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] if 'period_seconds' in params: query_params.append(('periodSeconds', params['period_seconds'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/metrics-stream/metric-names', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1MetricNamesResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_report_trial_checkpoint_metadata(self, checkpoint_metadata_trial_id, body, **kwargs): # noqa: E501 """Record a checkpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_checkpoint_metadata(checkpoint_metadata_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int checkpoint_metadata_trial_id: The ID of the trial associated with the checkpoint. (required) :param V1CheckpointMetadata body: The training metrics to persist. (required) :return: V1ReportTrialCheckpointMetadataResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_report_trial_checkpoint_metadata_with_http_info(checkpoint_metadata_trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_report_trial_checkpoint_metadata_with_http_info(checkpoint_metadata_trial_id, body, **kwargs) # noqa: E501 return data def determined_report_trial_checkpoint_metadata_with_http_info(self, checkpoint_metadata_trial_id, body, **kwargs): # noqa: E501 """Record a checkpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_checkpoint_metadata_with_http_info(checkpoint_metadata_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int checkpoint_metadata_trial_id: The ID of the trial associated with the checkpoint. (required) :param V1CheckpointMetadata body: The training metrics to persist. (required) :return: V1ReportTrialCheckpointMetadataResponse If the method is called asynchronously, returns the request thread. """ all_params = ['checkpoint_metadata_trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_report_trial_checkpoint_metadata" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'checkpoint_metadata_trial_id' is set if ('checkpoint_metadata_trial_id' not in params or params['checkpoint_metadata_trial_id'] is None): raise ValueError("Missing the required parameter `checkpoint_metadata_trial_id` when calling `determined_report_trial_checkpoint_metadata`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_report_trial_checkpoint_metadata`") # noqa: E501 collection_formats = {} path_params = {} if 'checkpoint_metadata_trial_id' in params: path_params['checkpointMetadata.trialId'] = params['checkpoint_metadata_trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{checkpointMetadata.trialId}/checkpoint_metadata', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ReportTrialCheckpointMetadataResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_report_trial_progress(self, trial_id, body, **kwargs): # noqa: E501 """For bookkeeping, updates the progress towards to current requested searcher training length. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_progress(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param float body: Total units completed by the trial, in terms of the unit used to configure the searcher. (required) :return: V1ReportTrialProgressResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_report_trial_progress_with_http_info(trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_report_trial_progress_with_http_info(trial_id, body, **kwargs) # noqa: E501 return data def determined_report_trial_progress_with_http_info(self, trial_id, body, **kwargs): # noqa: E501 """For bookkeeping, updates the progress towards to current requested searcher training length. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_progress_with_http_info(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param float body: Total units completed by the trial, in terms of the unit used to configure the searcher. (required) :return: V1ReportTrialProgressResponse If the method is called asynchronously, returns the request thread. """ all_params = ['trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_report_trial_progress" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'trial_id' is set if ('trial_id' not in params or params['trial_id'] is None): raise ValueError("Missing the required parameter `trial_id` when calling `determined_report_trial_progress`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_report_trial_progress`") # noqa: E501 collection_formats = {} path_params = {} if 'trial_id' in params: path_params['trialId'] = params['trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trialId}/progress', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ReportTrialProgressResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_report_trial_searcher_early_exit(self, trial_id, body, **kwargs): # noqa: E501 """Reports to the searcher that the trial has completed the current requested amount of training with the given searcher validation metric. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_searcher_early_exit(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param V1TrialEarlyExit body: The exit reason. (required) :return: V1ReportTrialSearcherEarlyExitResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_report_trial_searcher_early_exit_with_http_info(trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_report_trial_searcher_early_exit_with_http_info(trial_id, body, **kwargs) # noqa: E501 return data def determined_report_trial_searcher_early_exit_with_http_info(self, trial_id, body, **kwargs): # noqa: E501 """Reports to the searcher that the trial has completed the current requested amount of training with the given searcher validation metric. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_searcher_early_exit_with_http_info(trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The id of the trial. (required) :param V1TrialEarlyExit body: The exit reason. (required) :return: V1ReportTrialSearcherEarlyExitResponse If the method is called asynchronously, returns the request thread. """ all_params = ['trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_report_trial_searcher_early_exit" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'trial_id' is set if ('trial_id' not in params or params['trial_id'] is None): raise ValueError("Missing the required parameter `trial_id` when calling `determined_report_trial_searcher_early_exit`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_report_trial_searcher_early_exit`") # noqa: E501 collection_formats = {} path_params = {} if 'trial_id' in params: path_params['trialId'] = params['trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trialId}/early_exit', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ReportTrialSearcherEarlyExitResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_report_trial_training_metrics(self, training_metrics_trial_id, body, **kwargs): # noqa: E501 """Record training metrics for specified training. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_training_metrics(training_metrics_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int training_metrics_trial_id: The trial associated with these metrics. (required) :param V1TrainingMetrics body: The training metrics to persist. (required) :return: V1ReportTrialTrainingMetricsResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_report_trial_training_metrics_with_http_info(training_metrics_trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_report_trial_training_metrics_with_http_info(training_metrics_trial_id, body, **kwargs) # noqa: E501 return data def determined_report_trial_training_metrics_with_http_info(self, training_metrics_trial_id, body, **kwargs): # noqa: E501 """Record training metrics for specified training. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_training_metrics_with_http_info(training_metrics_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int training_metrics_trial_id: The trial associated with these metrics. (required) :param V1TrainingMetrics body: The training metrics to persist. (required) :return: V1ReportTrialTrainingMetricsResponse If the method is called asynchronously, returns the request thread. """ all_params = ['training_metrics_trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_report_trial_training_metrics" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'training_metrics_trial_id' is set if ('training_metrics_trial_id' not in params or params['training_metrics_trial_id'] is None): raise ValueError("Missing the required parameter `training_metrics_trial_id` when calling `determined_report_trial_training_metrics`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_report_trial_training_metrics`") # noqa: E501 collection_formats = {} path_params = {} if 'training_metrics_trial_id' in params: path_params['trainingMetrics.trialId'] = params['training_metrics_trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trainingMetrics.trialId}/training_metrics', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ReportTrialTrainingMetricsResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_report_trial_validation_metrics(self, validation_metrics_trial_id, body, **kwargs): # noqa: E501 """Record validation metrics. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_validation_metrics(validation_metrics_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int validation_metrics_trial_id: The trial associated with these metrics. (required) :param V1ValidationMetrics body: The training metrics to persist. (required) :return: V1ReportTrialValidationMetricsResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_report_trial_validation_metrics_with_http_info(validation_metrics_trial_id, body, **kwargs) # noqa: E501 else: (data) = self.determined_report_trial_validation_metrics_with_http_info(validation_metrics_trial_id, body, **kwargs) # noqa: E501 return data def determined_report_trial_validation_metrics_with_http_info(self, validation_metrics_trial_id, body, **kwargs): # noqa: E501 """Record validation metrics. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_report_trial_validation_metrics_with_http_info(validation_metrics_trial_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int validation_metrics_trial_id: The trial associated with these metrics. (required) :param V1ValidationMetrics body: The training metrics to persist. (required) :return: V1ReportTrialValidationMetricsResponse If the method is called asynchronously, returns the request thread. """ all_params = ['validation_metrics_trial_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_report_trial_validation_metrics" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'validation_metrics_trial_id' is set if ('validation_metrics_trial_id' not in params or params['validation_metrics_trial_id'] is None): raise ValueError("Missing the required parameter `validation_metrics_trial_id` when calling `determined_report_trial_validation_metrics`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `determined_report_trial_validation_metrics`") # noqa: E501 collection_formats = {} path_params = {} if 'validation_metrics_trial_id' in params: path_params['validationMetrics.trialId'] = params['validation_metrics_trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{validationMetrics.trialId}/validation_metrics', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='V1ReportTrialValidationMetricsResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_trial_preemption_signal(self, trial_id, **kwargs): # noqa: E501 """Stream preemption signals for the given trial. Upon connection a signal is sent immediately, for synchronization purposes. If it is to preempt, that will be the only signal and the trial should preempt. Otherwise, the trial should continue to listen. The only signal ever sent after this will be to preempt. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trial_preemption_signal(trial_id, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The requested trial's id. (required) :return: StreamResultOfV1TrialPreemptionSignalResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_trial_preemption_signal_with_http_info(trial_id, **kwargs) # noqa: E501 else: (data) = self.determined_trial_preemption_signal_with_http_info(trial_id, **kwargs) # noqa: E501 return data def determined_trial_preemption_signal_with_http_info(self, trial_id, **kwargs): # noqa: E501 """Stream preemption signals for the given trial. Upon connection a signal is sent immediately, for synchronization purposes. If it is to preempt, that will be the only signal and the trial should preempt. Otherwise, the trial should continue to listen. The only signal ever sent after this will be to preempt. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trial_preemption_signal_with_http_info(trial_id, async_req=True) >>> result = thread.get() :param async_req bool :param int trial_id: The requested trial's id. (required) :return: StreamResultOfV1TrialPreemptionSignalResponse If the method is called asynchronously, returns the request thread. """ all_params = ['trial_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_trial_preemption_signal" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'trial_id' is set if ('trial_id' not in params or params['trial_id'] is None): raise ValueError("Missing the required parameter `trial_id` when calling `determined_trial_preemption_signal`") # noqa: E501 collection_formats = {} path_params = {} if 'trial_id' in params: path_params['trialId'] = params['trial_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/trials/{trialId}/signals/preemption', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1TrialPreemptionSignalResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_trials_sample(self, experiment_id, metric_name, metric_type, **kwargs): # noqa: E501 """Get a sample of the metrics over time for a sample of the trials. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trials_sample(experiment_id, metric_name, metric_type, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int max_trials: Maximum number of trials to fetch data for. :param int max_datapoints: Maximum number of initial / historical data points. :param int start_batches: Beginning of window (inclusive) to fetch data for. :param int end_batches: Ending of window (inclusive) to fetch data for. :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1TrialsSampleResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_trials_sample_with_http_info(experiment_id, metric_name, metric_type, **kwargs) # noqa: E501 else: (data) = self.determined_trials_sample_with_http_info(experiment_id, metric_name, metric_type, **kwargs) # noqa: E501 return data def determined_trials_sample_with_http_info(self, experiment_id, metric_name, metric_type, **kwargs): # noqa: E501 """Get a sample of the metrics over time for a sample of the trials. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trials_sample_with_http_info(experiment_id, metric_name, metric_type, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int max_trials: Maximum number of trials to fetch data for. :param int max_datapoints: Maximum number of initial / historical data points. :param int start_batches: Beginning of window (inclusive) to fetch data for. :param int end_batches: Ending of window (inclusive) to fetch data for. :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1TrialsSampleResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id', 'metric_name', 'metric_type', 'max_trials', 'max_datapoints', 'start_batches', 'end_batches', 'period_seconds'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_trials_sample" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_trials_sample`") # noqa: E501 # verify the required parameter 'metric_name' is set if ('metric_name' not in params or params['metric_name'] is None): raise ValueError("Missing the required parameter `metric_name` when calling `determined_trials_sample`") # noqa: E501 # verify the required parameter 'metric_type' is set if ('metric_type' not in params or params['metric_type'] is None): raise ValueError("Missing the required parameter `metric_type` when calling `determined_trials_sample`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] if 'metric_name' in params: query_params.append(('metricName', params['metric_name'])) # noqa: E501 if 'metric_type' in params: query_params.append(('metricType', params['metric_type'])) # noqa: E501 if 'max_trials' in params: query_params.append(('maxTrials', params['max_trials'])) # noqa: E501 if 'max_datapoints' in params: query_params.append(('maxDatapoints', params['max_datapoints'])) # noqa: E501 if 'start_batches' in params: query_params.append(('startBatches', params['start_batches'])) # noqa: E501 if 'end_batches' in params: query_params.append(('endBatches', params['end_batches'])) # noqa: E501 if 'period_seconds' in params: query_params.append(('periodSeconds', params['period_seconds'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/metrics-stream/trials-sample', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1TrialsSampleResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def determined_trials_snapshot(self, experiment_id, metric_name, metric_type, batches_processed, **kwargs): # noqa: E501 """Get a snapshot of a metric across all trials at a certain point of progress. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trials_snapshot(experiment_id, metric_name, metric_type, batches_processed, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int batches_processed: The point of progress at which to query metrics. (required) :param int batches_margin: A range either side of batches_processed to include near-misses. :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1TrialsSnapshotResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.determined_trials_snapshot_with_http_info(experiment_id, metric_name, metric_type, batches_processed, **kwargs) # noqa: E501 else: (data) = self.determined_trials_snapshot_with_http_info(experiment_id, metric_name, metric_type, batches_processed, **kwargs) # noqa: E501 return data def determined_trials_snapshot_with_http_info(self, experiment_id, metric_name, metric_type, batches_processed, **kwargs): # noqa: E501 """Get a snapshot of a metric across all trials at a certain point of progress. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.determined_trials_snapshot_with_http_info(experiment_id, metric_name, metric_type, batches_processed, async_req=True) >>> result = thread.get() :param async_req bool :param int experiment_id: The id of the experiment. (required) :param str metric_name: A metric name. (required) :param str metric_type: The type of metric. - METRIC_TYPE_UNSPECIFIED: Zero-value (not allowed). - METRIC_TYPE_TRAINING: For metrics emitted during training. - METRIC_TYPE_VALIDATION: For metrics emitted during validation. (required) :param int batches_processed: The point of progress at which to query metrics. (required) :param int batches_margin: A range either side of batches_processed to include near-misses. :param int period_seconds: Seconds to wait when polling for updates. :return: StreamResultOfV1TrialsSnapshotResponse If the method is called asynchronously, returns the request thread. """ all_params = ['experiment_id', 'metric_name', 'metric_type', 'batches_processed', 'batches_margin', 'period_seconds'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method determined_trials_snapshot" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'experiment_id' is set if ('experiment_id' not in params or params['experiment_id'] is None): raise ValueError("Missing the required parameter `experiment_id` when calling `determined_trials_snapshot`") # noqa: E501 # verify the required parameter 'metric_name' is set if ('metric_name' not in params or params['metric_name'] is None): raise ValueError("Missing the required parameter `metric_name` when calling `determined_trials_snapshot`") # noqa: E501 # verify the required parameter 'metric_type' is set if ('metric_type' not in params or params['metric_type'] is None): raise ValueError("Missing the required parameter `metric_type` when calling `determined_trials_snapshot`") # noqa: E501 # verify the required parameter 'batches_processed' is set if ('batches_processed' not in params or params['batches_processed'] is None): raise ValueError("Missing the required parameter `batches_processed` when calling `determined_trials_snapshot`") # noqa: E501 collection_formats = {} path_params = {} if 'experiment_id' in params: path_params['experimentId'] = params['experiment_id'] # noqa: E501 query_params = [] if 'metric_name' in params: query_params.append(('metricName', params['metric_name'])) # noqa: E501 if 'metric_type' in params: query_params.append(('metricType', params['metric_type'])) # noqa: E501 if 'batches_processed' in params: query_params.append(('batchesProcessed', params['batches_processed'])) # noqa: E501 if 'batches_margin' in params: query_params.append(('batchesMargin', params['batches_margin'])) # noqa: E501 if 'period_seconds' in params: query_params.append(('periodSeconds', params['period_seconds'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['BearerToken'] # noqa: E501 return self.api_client.call_api( '/api/v1/experiments/{experimentId}/metrics-stream/trials-snapshot', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='StreamResultOfV1TrialsSnapshotResponse', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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647

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0

7

40adef50bf33c68c32dc83c5f3b0e125d90da5aa

10,491

py

Python

src/utils/read_datasets.py

canbakiskan/neuro-inspired-defense

3c323aa3fa797ac6ea69db2731995370ede26f2f

[ "Apache-2.0" ]

null

src/utils/read_datasets.py

canbakiskan/neuro-inspired-defense

3c323aa3fa797ac6ea69db2731995370ede26f2f

[ "Apache-2.0" ]

null

src/utils/read_datasets.py

canbakiskan/neuro-inspired-defense

3c323aa3fa797ac6ea69db2731995370ede26f2f

[ "Apache-2.0" ]

1

2021-01-06T09:38:23.000Z

import torch import torch.nn as nn from torchvision import datasets, transforms import numpy as np from os import path from .namers import attack_file_namer def tiny_imagenet(args): data_dir = args.directory + "data/" train_dir = path.join(data_dir, "original_dataset", "tiny-imagenet-200", "train") test_dir = path.join(data_dir, "original_dataset", "tiny-imagenet-200", "val") use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 4, "pin_memory": True} if use_cuda else {} transform_train = transforms.Compose( [ transforms.RandomCrop(64, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), ] ) transform_test = transforms.Compose([transforms.ToTensor(), ]) trainset = datasets.ImageFolder(train_dir, transform=transform_train) train_loader = torch.utils.data.DataLoader( trainset, batch_size=args.train_batch_size, shuffle=True, num_workers=2 ) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) return train_loader, test_loader def tiny_imagenet_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read if args.attack_box_type == "other" and args.attack_otherbox_type == "transfer": filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_transfer_file elif args.attack_box_type == "white": filepath = attack_file_namer(args) else: raise AssertionError test_images = np.load(filepath) data_dir = args.directory + "data/" test_dir = path.join(data_dir, "original_dataset", "tiny-imagenet-200", "val") transform_test = transforms.Compose([transforms.ToTensor(), ]) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(test_loader.dataset.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader def tiny_imagenet_initialization_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_initialization_file test_images = np.load(filepath) data_dir = args.directory + "data/" test_dir = path.join(data_dir, "original_dataset", "tiny-imagenet-200", "val") transform_test = transforms.Compose([transforms.ToTensor(), ]) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(test_loader.dataset.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader def imagenette(args): data_dir = args.directory + "data/" train_dir = path.join(data_dir, "original_dataset", "imagenette2-160", "train") test_dir = path.join(data_dir, "original_dataset", "imagenette2-160", "val") use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 4, "pin_memory": True} if use_cuda else {} transform_train = transforms.Compose( [ transforms.RandomCrop((160), padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), ] ) transform_test = transforms.Compose( [ transforms.CenterCrop(160), transforms.ToTensor(), ] ) trainset = datasets.ImageFolder(train_dir, transform=transform_train) train_loader = torch.utils.data.DataLoader( trainset, batch_size=args.train_batch_size, shuffle=True, num_workers=2 ) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) return train_loader, test_loader def imagenette_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read if args.attack_box_type == "other" and args.attack_otherbox_type == "transfer": filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_transfer_file elif args.attack_box_type == "white": filepath = attack_file_namer(args) else: raise AssertionError test_images = np.load(filepath) data_dir = args.directory + "data/" test_dir = path.join(data_dir, "original_dataset", "imagenette2-160", "val") transform_test = transforms.Compose([transforms.ToTensor(), ]) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(test_loader.dataset.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader def imagenette_initialization_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_initialization_file test_images = np.load(filepath) data_dir = args.directory + "data/" test_dir = path.join(data_dir, "original_dataset", "imagenette2-160", "val") transform_test = transforms.Compose([transforms.ToTensor(), ]) testset = datasets.ImageFolder(test_dir, transform=transform_test) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(test_loader.dataset.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader def cifar10(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 4, "pin_memory": True} if use_cuda else {} transform_train = transforms.Compose( [ transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), ] ) transform_test = transforms.Compose([transforms.ToTensor(), ]) trainset = datasets.CIFAR10( root=args.directory + "data/original_dataset", train=True, download=True, transform=transform_train, ) train_loader = torch.utils.data.DataLoader( trainset, batch_size=args.train_batch_size, shuffle=True, num_workers=2 ) testset = datasets.CIFAR10( root=args.directory + "data/original_dataset", train=False, download=True, transform=transform_test, ) test_loader = torch.utils.data.DataLoader( testset, batch_size=args.test_batch_size, shuffle=False, num_workers=2 ) return train_loader, test_loader def cifar10_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read if args.attack_box_type == "other" and args.attack_otherbox_type == "transfer": filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_transfer_file elif args.attack_box_type == "white": filepath = attack_file_namer(args) else: raise AssertionError test_images = np.load(filepath) cifar10 = datasets.CIFAR10( path.join(args.directory, "data/original_dataset"), train=False, transform=None, target_transform=None, download=False, ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(cifar10.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader def cifar10_initialization_from_file(args): use_cuda = not args.no_cuda and torch.cuda.is_available() kwargs = {"num_workers": 1, "pin_memory": True} if use_cuda else {} # Read filepath = args.directory + "data/attacked_dataset/" + \ args.dataset + "/" + args.attack_initialization_file test_images = np.load(filepath) cifar10 = datasets.CIFAR10( path.join(args.directory, "data/original_dataset"), train=False, transform=None, target_transform=None, download=False, ) tensor_x = torch.Tensor(test_images / np.max(test_images)) tensor_y = torch.Tensor(cifar10.targets).long() tensor_data = torch.utils.data.TensorDataset(tensor_x, tensor_y) attack_loader = torch.utils.data.DataLoader( tensor_data, batch_size=args.test_batch_size, shuffle=False, **kwargs ) return attack_loader

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null

0

1

0

1

0

null

0

7

40b9c3cf7c42e6ec447b4657187518057e673df2

9,687

py

Python

config/yolo_config.py

felixchenfy/ros_yolo_as_template_matching

0d5c0a52ba5540d2a644e0b426f9041a2a5e7858

[ "MIT" ]

29

2019-12-02T01:54:18.000Z

2022-02-15T09:23:27.000Z

config/yolo_config.py

felixchenfy/ros_yolo_as_template_matching

0d5c0a52ba5540d2a644e0b426f9041a2a5e7858

[ "MIT" ]

8

2019-12-24T13:13:44.000Z

2022-02-10T00:16:31.000Z

config/yolo_config.py

felixchenfy/ros_yolo_as_template_matching

0d5c0a52ba5540d2a644e0b426f9041a2a5e7858

[ "MIT" ]

5

2020-01-31T00:31:37.000Z

2022-03-28T06:14:09.000Z

# -*- coding: future_fstrings -*- from __future__ import division ''' Provide a class to write yolo configs to file ''' class YoloConfig(object): def __init__(self, num_classes, num_layers): if num_layers not in [1, 2, 3]: raise ValueError("Yolo layer number should be 1 or 2 or 3") self.str_yolo_config = set_yolo_config(num_classes, num_layers) def get(self): return self.str_yolo_config def write_to_file(self, filename): with open(filename, 'w') as f: f.write(self.str_yolo_config) print("Write yolo config to: ", filename) def set_yolo_config(num_classes, num_layers): num_filters = (num_classes + 5) * 3 yolo_basic = f'''[net] # Testing #batch=1 #subdivisions=1 # Training batch=16 subdivisions=1 width=416 height=416 channels=3 momentum=0.9 decay=0.0005 angle=0 saturation = 1.5 exposure = 1.5 hue=.1 learning_rate=0.001 burn_in=1000 max_batches = 500200 policy=steps steps=400000,450000 scales=.1,.1 [convolutional] batch_normalize=1 filters=32 size=3 stride=1 pad=1 activation=leaky # Downsample [convolutional] batch_normalize=1 filters=64 size=3 stride=2 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=32 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear # Downsample [convolutional] batch_normalize=1 filters=128 size=3 stride=2 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear # Downsample [convolutional] batch_normalize=1 filters=256 size=3 stride=2 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear # Downsample [convolutional] batch_normalize=1 filters=512 size=3 stride=2 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear # Downsample [convolutional] batch_normalize=1 filters=1024 size=3 stride=2 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=1024 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=1024 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=1024 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=1024 size=3 stride=1 pad=1 activation=leaky [shortcut] from=-3 activation=linear ###################### [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] size=1 stride=1 pad=1 filters={num_filters} activation=linear ''' yolo_layer1 = f'''[yolo] mask = 6,7,8 anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 classes={num_classes} num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 random=1 [route] layers = -4 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [upsample] stride=2 [route] layers = -1, 61 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] size=1 stride=1 pad=1 filters={num_filters} activation=linear ''' yolo_layer2 = f'''[yolo] mask = 3,4,5 anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 classes={num_classes} num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 random=1 [route] layers = -4 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [upsample] stride=2 [route] layers = -1, 36 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] size=1 stride=1 pad=1 filters={num_filters} activation=linear ''' yolo_layer3 = f'''[yolo] mask = 0,1,2 anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 classes={num_classes} num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 random=1 ''' if num_layers == 1: return yolo_basic + yolo_layer1 elif num_layers == 2: return yolo_basic + yolo_layer1 + yolo_layer2 elif num_layers == 3: return yolo_basic + yolo_layer1 + yolo_layer2 + yolo_layer3 if __name__ == "__main__": def test_yolo_config(): print("Testing: yolo_config.py") filename = "tmp.cfg" yolo_config = YoloConfig(num_classes=2) yolo_config.write_to_file(filename) test_yolo_config()

11.573477

85

0.76804

1,530

9,687

4.764052

0.090196

0.082316

0.266703

0.276581

0.884758

0.881328

0.879956

0.856222

0.851969

0.845109

0

0.091016

0.124394

9,687

836

86

11.587321

0.768333

0.0032

0

0.91582

0

0.004354

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false

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1

0

1

0

1

0

null

0

10

dc03da85aee0c2a33fc102a7e4eac30e4c481b81

2,911

py

Python

src/problem008.py

wreckoner/PyEuler

96f2f3317e868337891d1ccb288bb485951e41ea

[ "MIT" ]

null

src/problem008.py

wreckoner/PyEuler

96f2f3317e868337891d1ccb288bb485951e41ea

[ "MIT" ]

null

src/problem008.py

wreckoner/PyEuler

96f2f3317e868337891d1ccb288bb485951e41ea

[ "MIT" ]

null

#-*- coding:utf-8 -*- """ Problem 8: Largest product in a series The four adjacent digits in the 1000-digit number that have the greatest product are 9 × 9 × 8 × 9 = 5832. 73167176531330624919225119674426574742355349194934 96983520312774506326239578318016984801869478851843 85861560789112949495459501737958331952853208805511 12540698747158523863050715693290963295227443043557 66896648950445244523161731856403098711121722383113 62229893423380308135336276614282806444486645238749 30358907296290491560440772390713810515859307960866 70172427121883998797908792274921901699720888093776 65727333001053367881220235421809751254540594752243 52584907711670556013604839586446706324415722155397 53697817977846174064955149290862569321978468622482 83972241375657056057490261407972968652414535100474 82166370484403199890008895243450658541227588666881 16427171479924442928230863465674813919123162824586 17866458359124566529476545682848912883142607690042 24219022671055626321111109370544217506941658960408 07198403850962455444362981230987879927244284909188 84580156166097919133875499200524063689912560717606 05886116467109405077541002256983155200055935729725 71636269561882670428252483600823257530420752963450 Find the thirteen adjacent digits in the 1000-digit number that have the greatest product. What is the value of this product? Answer: 23514624000 """ SERIES = "73167176531330624919225119674426574742355349194934\ 96983520312774506326239578318016984801869478851843\ 85861560789112949495459501737958331952853208805511\ 12540698747158523863050715693290963295227443043557\ 66896648950445244523161731856403098711121722383113\ 62229893423380308135336276614282806444486645238749\ 30358907296290491560440772390713810515859307960866\ 70172427121883998797908792274921901699720888093776\ 65727333001053367881220235421809751254540594752243\ 52584907711670556013604839586446706324415722155397\ 53697817977846174064955149290862569321978468622482\ 83972241375657056057490261407972968652414535100474\ 82166370484403199890008895243450658541227588666881\ 16427171479924442928230863465674813919123162824586\ 17866458359124566529476545682848912883142607690042\ 24219022671055626321111109370544217506941658960408\ 07198403850962455444362981230987879927244284909188\ 84580156166097919133875499200524063689912560717606\ 05886116467109405077541002256983155200055935729725\ 71636269561882670428252483600823257530420752963450" def largest_product_in_a_series(number_string): """ Create a window of 13 characters that traverses the entire number and finds product for each window. Linear time complexity. """ left, right = 0, 13 largest_product = 0 while right < len(number_string): window = number_string[left:right] product = eval('*'.join(window)) if product > largest_product: largest_product = product left += 1 right += 1 return largest_product if __name__ == '__main__': print largest_product_in_a_series(SERIES)

41.585714

125

0.902439

171

2,911

15.245614

0.467836

0.037591

0.018412

0.019563

0.839662

0.813195

0

0.748622

0.06527

2,911

70

126

41.585714

0.208379

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0

0.006276

0

1

0

null

0

null

0.030303

0

1

null

0

1

0

1

0

1

0

null

1

0

1

0

11

90e526c1b76792ded6f314cc006e44184a08c343

28,930

py

Python

heat/tests/neutron/test_neutron_security_group.py

maestro-hybrid-cloud/heat

91a4bb3170bd81b1c67a896706851e55709c9b5a

[ "Apache-2.0" ]

null

heat/tests/neutron/test_neutron_security_group.py

maestro-hybrid-cloud/heat

91a4bb3170bd81b1c67a896706851e55709c9b5a

[ "Apache-2.0" ]

null

heat/tests/neutron/test_neutron_security_group.py

maestro-hybrid-cloud/heat

91a4bb3170bd81b1c67a896706851e55709c9b5a

[ "Apache-2.0" ]

null

# # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from neutronclient.common import exceptions as neutron_exc from neutronclient.v2_0 import client as neutronclient from novaclient.v2 import security_group_rules as nova_sgr from novaclient.v2 import security_groups as nova_sg from heat.common import exception from heat.common import template_format from heat.engine import scheduler from heat.engine import stack as parser from heat.engine import template from heat.tests import common from heat.tests.nova import fakes as fakes_nova from heat.tests import utils class SecurityGroupTest(common.HeatTestCase): test_template = ''' heat_template_version: 2015-04-30 resources: the_sg: type: OS::Neutron::SecurityGroup properties: description: HTTP and SSH access rules: - port_range_min: 22 port_range_max: 22 remote_ip_prefix: 0.0.0.0/0 protocol: tcp - port_range_min: 80 port_range_max: 80 protocol: tcp remote_ip_prefix: 0.0.0.0/0 - remote_mode: remote_group_id remote_group_id: wwww protocol: tcp - direction: egress port_range_min: 22 port_range_max: 22 protocol: tcp remote_ip_prefix: 10.0.1.0/24 - direction: egress remote_mode: remote_group_id remote_group_id: xxxx - direction: egress remote_mode: remote_group_id ''' test_template_update = ''' heat_template_version: 2015-04-30 resources: the_sg: type: OS::Neutron::SecurityGroup properties: description: SSH access for private network name: myrules rules: - port_range_min: 22 port_range_max: 22 remote_ip_prefix: 10.0.0.10/24 protocol: tcp ''' test_template_validate = ''' heat_template_version: 2015-04-30 resources: the_sg: type: OS::Neutron::SecurityGroup properties: name: default ''' def setUp(self): super(SecurityGroupTest, self).setUp() self.fc = fakes_nova.FakeClient() self.m.StubOutWithMock(nova_sgr.SecurityGroupRuleManager, 'create') self.m.StubOutWithMock(nova_sgr.SecurityGroupRuleManager, 'delete') self.m.StubOutWithMock(nova_sg.SecurityGroupManager, 'create') self.m.StubOutWithMock(nova_sg.SecurityGroupManager, 'delete') self.m.StubOutWithMock(nova_sg.SecurityGroupManager, 'get') self.m.StubOutWithMock(nova_sg.SecurityGroupManager, 'list') self.m.StubOutWithMock(neutronclient.Client, 'create_security_group') self.m.StubOutWithMock( neutronclient.Client, 'create_security_group_rule') self.m.StubOutWithMock(neutronclient.Client, 'show_security_group') self.m.StubOutWithMock( neutronclient.Client, 'delete_security_group_rule') self.m.StubOutWithMock(neutronclient.Client, 'delete_security_group') self.m.StubOutWithMock(neutronclient.Client, 'update_security_group') def create_stack(self, templ): t = template_format.parse(templ) self.stack = self.parse_stack(t) self.assertIsNone(self.stack.create()) return self.stack def parse_stack(self, t): stack_name = 'test_stack' tmpl = template.Template(t) stack = parser.Stack(utils.dummy_context(), stack_name, tmpl) stack.store() return stack def assertResourceState(self, rsrc, ref_id, metadata=None): metadata = metadata or {} self.assertIsNone(rsrc.validate()) self.assertEqual((rsrc.CREATE, rsrc.COMPLETE), rsrc.state) self.assertEqual(ref_id, rsrc.FnGetRefId()) self.assertEqual(metadata, dict(rsrc.metadata_get())) def test_security_group(self): show_created = {'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': 'sc1', 'description': '', 'security_group_rules': [{ 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': '22', 'id': 'bbbb', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '22' }, { 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': '80', 'id': 'cccc', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '80' }, { 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': None, 'id': 'dddd', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': 'wwww', 'remote_ip_prefix': None, 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }, { 'direction': 'egress', 'protocol': 'tcp', 'port_range_max': '22', 'id': 'eeee', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '10.0.1.0/24', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '22' }, { 'direction': 'egress', 'protocol': None, 'port_range_max': None, 'id': 'ffff', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': 'xxxx', 'remote_ip_prefix': None, 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }, { 'direction': 'egress', 'protocol': None, 'port_range_max': None, 'id': 'gggg', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': 'aaaa', 'remote_ip_prefix': None, 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }], 'id': 'aaaa'} } # create script sg_name = utils.PhysName('test_stack', 'the_sg') neutronclient.Client.create_security_group({ 'security_group': { 'name': sg_name, 'description': 'HTTP and SSH access' } }).AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': sg_name, 'description': 'HTTP and SSH access', 'security_group_rules': [{ "direction": "egress", "ethertype": "IPv4", "id": "aaaa-1", "port_range_max": None, "port_range_min": None, "protocol": None, "remote_group_id": None, "remote_ip_prefix": None, "security_group_id": "aaaa", "tenant_id": "f18ca530cc05425e8bac0a5ff92f7e88" }, { "direction": "egress", "ethertype": "IPv6", "id": "aaaa-2", "port_range_max": None, "port_range_min": None, "protocol": None, "remote_group_id": None, "remote_ip_prefix": None, "security_group_id": "aaaa", "tenant_id": "f18ca530cc05425e8bac0a5ff92f7e88" }], 'id': 'aaaa' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa', 'id': 'bbbb' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '80', 'ethertype': 'IPv4', 'port_range_max': '80', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '80', 'ethertype': 'IPv4', 'port_range_max': '80', 'protocol': 'tcp', 'security_group_id': 'aaaa', 'id': 'cccc' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': 'wwww', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': 'wwww', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': 'tcp', 'security_group_id': 'aaaa', 'id': 'dddd' } }) neutronclient.Client.show_security_group('aaaa').AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': sg_name, 'description': 'HTTP and SSH access', 'security_group_rules': [{ "direction": "egress", "ethertype": "IPv4", "id": "aaaa-1", "port_range_max": None, "port_range_min": None, "protocol": None, "remote_group_id": None, "remote_ip_prefix": None, "security_group_id": "aaaa", "tenant_id": "f18ca530cc05425e8bac0a5ff92f7e88" }, { "direction": "egress", "ethertype": "IPv6", "id": "aaaa-2", "port_range_max": None, "port_range_min": None, "protocol": None, "remote_group_id": None, "remote_ip_prefix": None, "security_group_id": "aaaa", "tenant_id": "f18ca530cc05425e8bac0a5ff92f7e88" }], 'id': 'aaaa' } }) neutronclient.Client.delete_security_group_rule('aaaa-1').AndReturn( None) neutronclient.Client.delete_security_group_rule('aaaa-2').AndReturn( None) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': None, 'remote_ip_prefix': '10.0.1.0/24', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': None, 'remote_ip_prefix': '10.0.1.0/24', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa', 'id': 'eeee' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'xxxx', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'xxxx', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa', 'id': 'ffff' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'aaaa', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'aaaa', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa', 'id': 'gggg' } }) # update script neutronclient.Client.update_security_group( 'aaaa', {'security_group': { 'description': 'SSH access for private network', 'name': 'myrules'}} ).AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': 'myrules', 'description': 'SSH access for private network', 'security_group_rules': [], 'id': 'aaaa' } }) neutronclient.Client.show_security_group('aaaa').AndReturn( show_created) neutronclient.Client.delete_security_group_rule('bbbb').AndReturn(None) neutronclient.Client.delete_security_group_rule('cccc').AndReturn(None) neutronclient.Client.delete_security_group_rule('dddd').AndReturn(None) neutronclient.Client.delete_security_group_rule('eeee').AndReturn(None) neutronclient.Client.delete_security_group_rule('ffff').AndReturn(None) neutronclient.Client.delete_security_group_rule('gggg').AndReturn(None) neutronclient.Client.show_security_group('aaaa').AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': 'sc1', 'description': '', 'security_group_rules': [], 'id': 'aaaa' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', } }).AndReturn({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': None, 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa', 'id': 'hhhh' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'ethertype': 'IPv6', 'security_group_id': 'aaaa', } }).AndReturn({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': None, 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv6', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa', 'id': 'iiii' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '10.0.0.10/24', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndReturn({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '10.0.0.10/24', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa', 'id': 'jjjj' } }) # delete script neutronclient.Client.show_security_group('aaaa').AndReturn( show_created) neutronclient.Client.delete_security_group_rule('bbbb').AndReturn(None) neutronclient.Client.delete_security_group_rule('cccc').AndReturn(None) neutronclient.Client.delete_security_group_rule('dddd').AndReturn(None) neutronclient.Client.delete_security_group_rule('eeee').AndReturn(None) neutronclient.Client.delete_security_group_rule('ffff').AndReturn(None) neutronclient.Client.delete_security_group_rule('gggg').AndReturn(None) neutronclient.Client.delete_security_group('aaaa').AndReturn(None) self.m.ReplayAll() stack = self.create_stack(self.test_template) sg = stack['the_sg'] self.assertResourceState(sg, 'aaaa') updated_tmpl = template_format.parse(self.test_template_update) updated_stack = utils.parse_stack(updated_tmpl) stack.update(updated_stack) stack.delete() self.m.VerifyAll() def test_security_group_exception(self): # create script sg_name = utils.PhysName('test_stack', 'the_sg') neutronclient.Client.create_security_group({ 'security_group': { 'name': sg_name, 'description': 'HTTP and SSH access' } }).AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': sg_name, 'description': 'HTTP and SSH access', 'security_group_rules': [], 'id': 'aaaa' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'port_range_min': '80', 'ethertype': 'IPv4', 'port_range_max': '80', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'ingress', 'remote_group_id': 'wwww', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) neutronclient.Client.show_security_group('aaaa').AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': sg_name, 'description': 'HTTP and SSH access', 'security_group_rules': [], 'id': 'aaaa' } }) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': None, 'remote_ip_prefix': '10.0.1.0/24', 'port_range_min': '22', 'ethertype': 'IPv4', 'port_range_max': '22', 'protocol': 'tcp', 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'xxxx', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) neutronclient.Client.create_security_group_rule({ 'security_group_rule': { 'direction': 'egress', 'remote_group_id': 'aaaa', 'remote_ip_prefix': None, 'port_range_min': None, 'ethertype': 'IPv4', 'port_range_max': None, 'protocol': None, 'security_group_id': 'aaaa' } }).AndRaise( neutron_exc.Conflict()) # delete script neutronclient.Client.show_security_group('aaaa').AndReturn({ 'security_group': { 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'name': 'sc1', 'description': '', 'security_group_rules': [{ 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': '22', 'id': 'bbbb', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '22' }, { 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': '80', 'id': 'cccc', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '0.0.0.0/0', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '80' }, { 'direction': 'ingress', 'protocol': 'tcp', 'port_range_max': None, 'id': 'dddd', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': 'wwww', 'remote_ip_prefix': None, 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }, { 'direction': 'egress', 'protocol': 'tcp', 'port_range_max': '22', 'id': 'eeee', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': '10.0.1.0/24', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': '22' }, { 'direction': 'egress', 'protocol': None, 'port_range_max': None, 'id': 'ffff', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': 'xxxx', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }, { 'direction': 'egress', 'protocol': None, 'port_range_max': None, 'id': 'gggg', 'ethertype': 'IPv4', 'security_group_id': 'aaaa', 'remote_group_id': None, 'remote_ip_prefix': 'aaaa', 'tenant_id': 'f18ca530cc05425e8bac0a5ff92f7e88', 'port_range_min': None }], 'id': 'aaaa'}}) neutronclient.Client.delete_security_group_rule('bbbb').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group_rule('cccc').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group_rule('dddd').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group_rule('eeee').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group_rule('ffff').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group_rule('gggg').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.delete_security_group('aaaa').AndRaise( neutron_exc.NeutronClientException(status_code=404)) neutronclient.Client.show_security_group('aaaa').AndRaise( neutron_exc.NeutronClientException(status_code=404)) self.m.ReplayAll() stack = self.create_stack(self.test_template) sg = stack['the_sg'] self.assertResourceState(sg, 'aaaa') scheduler.TaskRunner(sg.delete)() sg.state_set(sg.CREATE, sg.COMPLETE, 'to delete again') sg.resource_id = 'aaaa' stack.delete() self.m.VerifyAll() def test_security_group_validate(self): stack = self.create_stack(self.test_template_validate) sg = stack['the_sg'] ex = self.assertRaises(exception.StackValidationFailed, sg.validate) self.assertEqual( 'Security groups cannot be assigned the name "default".', ex.message)

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py

Python

mtorch/core/logger/__init__.py

NullConvergence/torch_temp

29a0d7190f0be6124f51bd85b8320cd8b3cef29a

[ "MIT" ]

3

2019-08-08T13:23:50.000Z

2019-08-15T15:29:36.000Z

mtorch/core/logger/__init__.py

NullConvergence/torch-template

29a0d7190f0be6124f51bd85b8320cd8b3cef29a

[ "MIT" ]

10

2019-09-20T21:25:22.000Z

2019-10-16T10:52:04.000Z

mtorch/core/logger/__init__.py

NullConvergence/mtorch

29a0d7190f0be6124f51bd85b8320cd8b3cef29a

[ "MIT" ]

2

2019-08-08T13:23:52.000Z

2019-08-08T19:46:55.000Z

from .logger import * from .tensorboard_writer import * from .tb_logger import * from .sacred_logger import * from .wandb_logger import * from .neptune_logger import *

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Python

Scripts/SetIfEmpty/SetIfEmpty_test.py

lh34s8/content

6b1d72035be3a58641239e8cc9e7cd94139e55ba

[ "MIT" ]

null

Scripts/SetIfEmpty/SetIfEmpty_test.py

lh34s8/content

6b1d72035be3a58641239e8cc9e7cd94139e55ba

[ "MIT" ]

9

2021-02-08T20:51:18.000Z

2021-09-23T23:27:38.000Z

Scripts/SetIfEmpty/SetIfEmpty_test.py

lh34s8/content

6b1d72035be3a58641239e8cc9e7cd94139e55ba

[ "MIT" ]

null

from SetIfEmpty import get_value_to_set def test_when_value_is_a_valid_string_should_return_value(): validString = "validString" expectedOutput = validString result = get_value_to_set({'value': validString, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_a_number_should_return_value(): number = 0 expectedOutput = number result = get_value_to_set({'value': number, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_a_dictionary_should_return_value(): dictionary = {'name': "John", 'lastName': 'Doe'} expectedOutput = dictionary result = get_value_to_set({'value': dictionary, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_empty_string_should_return_value(): expectedOutput = "defaultValue" result = get_value_to_set({'value': '', 'defaultValue': 'defaultValue', 'applyIfEmpty': 'True'}) assert expectedOutput == result def test_when_value_is_empty_dictionary_should_return_default_value(): expectedOutput = "defaultValue" result = get_value_to_set({'value': {}, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_none_should_return_default_value(): expectedOutput = "defaultValue" result = get_value_to_set({'value': None, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_empty_string_and_apply_if_empty_is_false_should_return_empty_string(): expectedOutput = "" result = get_value_to_set({'value': '', 'defaultValue': 'defaultValue', 'applyIfEmpty': 'False'}) assert expectedOutput == result def test_when_value_is_empty_dictionary_and_apply_if_empty_is_false_should_return_empty_dictionary(): expectedOutput = {} result = get_value_to_set({'value': {}, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'false'}) assert expectedOutput == result def test_when_value_is_none_and_apply_if_empty_is_false_should_return_default_value(): expectedOutput = "defaultValue" result = get_value_to_set({'value': None, 'defaultValue': 'defaultValue', 'applyIfEmpty': 'false'}) assert expectedOutput == result def test_when_value_is_empty_array_and_apply_if_empty_is_true_should_return_default_value(): expectedOutput = "defaultValue" result = get_value_to_set({'value': [""], 'defaultValue': 'defaultValue', 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_empty_dict(): value = {} expectedOutput = "defaultValue" result = get_value_to_set({'value': value, 'defaultValue': expectedOutput, 'applyIfEmpty': 'true'}) assert expectedOutput == result def test_when_value_is_dict(): value = {1: 2} result = get_value_to_set({'value': value, 'defaultValue': "defaultValue", 'applyIfEmpty': 'true'}) assert result == value

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4668f091b477cf69ef6743ecf7e389511d57bdea

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Python

autoscale_cloudroast/test_repo/autoscale/functional/scaling_group/test_scaling_group_negative.py

alex/otter

e46316634ae4c211f7436aa4d41321ac1edba0af

[ "Apache-2.0" ]

1

2015-11-08T12:58:44.000Z

autoscale_cloudroast/test_repo/autoscale/functional/scaling_group/test_scaling_group_negative.py

alex/otter

e46316634ae4c211f7436aa4d41321ac1edba0af

[ "Apache-2.0" ]

null

autoscale_cloudroast/test_repo/autoscale/functional/scaling_group/test_scaling_group_negative.py

alex/otter

e46316634ae4c211f7436aa4d41321ac1edba0af

[ "Apache-2.0" ]

null

""" Test negative scenarios for a scaling group. """ from test_repo.autoscale.fixtures import AutoscaleFixture from autoscale.status_codes import HttpStatusCodes class ScalingGroupNegative(AutoscaleFixture): """ Verify negative scenarios for scaling group. """ # @unittest.skip('invalid when tests are running in parallel and on a tenant that has groups') # def test_list_scaling_group_when_none_exist(self): # """ # Negative test: List scaling groups when none exists on the account. # (also helps validate that teardowns within the testsuite ) # """ # list_groups_resp = self.autoscale_client.list_scaling_groups() # list_groups = list_groups_resp.entity # self.assertEquals(list_groups_resp.status_code, 200, # msg='The list group call when no groups exists failed with {0}' # .format(list_groups_resp.status_code) # self.validate_headers(list_groups_resp.headers) # self.assertEquals(list_groups, [], # msg='Some scaling groups exist on the account') # def test_scaling_group_name_blank(self): # """ # Negative Test: Scaling group should not get created with an empty # group configuration name # """ # expected_status_code = HttpStatusCodes.BAD_REQUEST # error_create_resp = self.autoscale_behaviors.create_scaling_group_given( # gc_name='') # create_error = error_create_resp.entity # self.assertEquals(error_create_resp.status_code, expected_status_code, # msg='Create scaling group succeeded with invalid request: {0}' # .format(error_create_resp.status_code)) # self.assertTrue(create_error is None, # msg='Create scaling group with invalid request returned: {0}' # .format(create_error)) def test_scaling_group_name_whitespace(self): """ Negative Test: Scaling group should not get created with group configuration name as only whitespace """ expected_status_code = HttpStatusCodes.BAD_REQUEST error_create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_name=' ') create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create scaling group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create scaling group with invalid request returned: {0}' .format(create_error)) def test_scaling_group_minentities_lessthan_zero(self): """ Negative Test: Scaling group should not get created when min entities are less than Zero """ expected_status_code = HttpStatusCodes.BAD_REQUEST error_create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_min_entities='-100') create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create scaling group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create scaling group with invalid request returned: {0}' .format(create_error)) def test_scaling_group_maxentities_lessthan_zero(self): """ Negative Test: Scaling group should not get created when max entities are less than Zero """ expected_status_code = HttpStatusCodes.BAD_REQUEST error_create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_max_entities='-0.01') create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create scaling group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create scaling group with invalid request returned: {0}' .format(create_error)) def test_scaling_group_maxentities_over_max(self): """ Negative Test: Scaling group should not get created when max entities are over 25 """ expected_status_code = HttpStatusCodes.BAD_REQUEST error_create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_max_entities=self.max_maxentities + 1) create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create scaling group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create scaling group with invalid request returned: {0}' .format(create_error)) def test_scaling_group_cooldown_lessthan_zero(self): """ Negative Test: Scaling group should not get created when cooldown is less than Zero """ expected_status_code = HttpStatusCodes.BAD_REQUEST error_create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_cooldown='-0.08') create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create scaling group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create scaling group with invalid request returned: {0}' .format(create_error)) def test_scaling_group_minentities_max(self): """ Negative Test: Scaling group should not get created when min entities are over allowed maxentities """ expected_status_code = HttpStatusCodes.BAD_REQUEST gc_min_entities = self.max_maxentities + 1 create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_min_entities=gc_min_entities) self.assertEquals(create_resp.status_code, expected_status_code, msg='Create scaling group passed with max minentities. Response: {0}' .format(create_resp.status_code)) def test_create_scaling_group_minentities_over_maxentities(self): """ Negative Test: Scaling group should not get created when min entities are over maxentities """ expected_status_code = HttpStatusCodes.BAD_REQUEST gc_min_entities = 22 gc_max_entities = 2 create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_min_entities=gc_min_entities, gc_max_entities=gc_max_entities) self.assertEquals(create_resp.status_code, expected_status_code, msg='Create scaling group passed with max < minentities. Response: {0}' .format(create_resp.status_code)) def test_scaling_group_maxentities_max(self): """ Negative Test: Scaling group should not get created when max entities is over 25 """ expected_status_code = HttpStatusCodes.BAD_REQUEST gc_max_entities = self.max_maxentities + 1 create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_max_entities=gc_max_entities) self.assertEquals(create_resp.status_code, expected_status_code, msg='Create group passed when maxntities is over 25 with response: {0}' .format(create_resp.status_code)) def test_scaling_group_with_max_cooldown(self): """ Negative Test: Scaling group should not get created when cooldown is over 86400 seconds (24 hrs) """ expected_status_code = HttpStatusCodes.BAD_REQUEST create_resp = self.autoscale_behaviors.create_scaling_group_given( gc_cooldown=self.max_cooldown + 1) self.assertEquals(create_resp.status_code, expected_status_code, msg='Create group passed when cooldown is over 24 hrs with response: {0}' .format(create_resp.status_code)) def test_get_invalid_group_id(self): """ Negative Test: Get group with invalid group id should fail with resource not found 404 """ group = 13344 expected_status_code = HttpStatusCodes.NOT_FOUND error_create_resp = self.autoscale_client.view_manifest_config_for_scaling_group( group_id=group) create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create group with invalid request returned: {0}' .format(create_error)) def test_update_invalid_group_id(self): """ Negative Test: Update group with invalid group id should fail with resource not found 404 """ group = gc_max_entities = 25 expected_status_code = HttpStatusCodes.NOT_FOUND error_create_resp = self.autoscale_client.update_group_config( group_id=group, name=self.gc_name, cooldown=self.gc_cooldown, min_entities=self.gc_min_entities, max_entities=gc_max_entities, metadata={}) create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create group with invalid request returned: {0}' .format(create_error)) def test_get_group_after_deletion(self): """ Negative Test: Get group when group is deleted should fail with 404 """ create_resp = self.autoscale_behaviors.create_scaling_group_min() group = create_resp.entity del_resp = self.autoscale_client.delete_scaling_group( group_id=group.id) self.assertEquals( create_resp.status_code, 201, msg='create group failed') self.assertEquals(del_resp.status_code, 204, msg='Delete group failed') expected_status_code = HttpStatusCodes.NOT_FOUND error_create_resp = self.autoscale_client.view_manifest_config_for_scaling_group( group_id=group.id) create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create group succeeded with invalid request: {0}' .format(error_create_resp.status_code)) self.assertTrue(create_error is None, msg='Create group with invalid request returned: {0}' .format(create_error)) def test_update_group_after_deletion(self): """ Negative Test: Trying to update group when group is deleted should fail with 404 """ create_resp = self.autoscale_behaviors.create_scaling_group_min() group = create_resp.entity del_resp = self.autoscale_client.delete_scaling_group( group_id=group.id) self.assertEquals( create_resp.status_code, 201, msg='create group failed') self.assertEquals(del_resp.status_code, 204, msg='Delete group failed') expected_status_code = HttpStatusCodes.NOT_FOUND error_create_resp = self.autoscale_client.update_group_config( group_id=group.id, name=self.gc_name, cooldown=90, min_entities=self.gc_min_entities, max_entities=group.groupConfiguration.maxEntities, metadata={}) create_error = error_create_resp.entity self.assertEquals(error_create_resp.status_code, expected_status_code, msg='Create group succeeded with invalid request: {0}, groupid: {1}' .format(error_create_resp.status_code, group.id)) self.assertTrue(create_error is None, msg='Create group with invalid request returned: {0}' .format(create_error))

49.208333

99

0.646832

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0.092016

0.077997

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1

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null

0

7

466b216a63e177b7fc7ec2eda41b69076a40c110

17,636

py

Python

snake_project/tests/test_gamemodes.py

GonnaFlyMethod/snake1976

567caccdbd027509dc15210e011ed7709132220d

[ "MIT" ]

4

2020-07-20T11:45:27.000Z

2020-07-22T08:36:38.000Z

snake_project/tests/test_gamemodes.py

GonnaFlyMethod/snake1976

567caccdbd027509dc15210e011ed7709132220d

[ "MIT" ]

null

snake_project/tests/test_gamemodes.py

GonnaFlyMethod/snake1976

567caccdbd027509dc15210e011ed7709132220d

[ "MIT" ]

1

2020-08-23T23:28:30.000Z

from extra.game_environment.menu_files.menu import Menu from extra.game_environment.score_files.score import Score from gamemodes.classic_mode import ClassicModeGameManager from gamemodes.survival_mode import SurvivalModeGameManager from gamemodes.battle_mode import BattleModeGameManager class TestClassicGamemodeClass: def setup(self): """Initialization of the game mode, player and installation of default settings. """ menu_inst = Menu() score_inst = Score('TestName') self.gamemode = ClassicModeGameManager(score_inst, menu_inst) self.gamemode.settings_storage['width'] = 40 self.gamemode.settings_storage['height'] = 20 walls = "can crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.settings_storage['speed'] = 0.08 self.gamemode.settings_storage['length'] = 3 self.gamemode.set_default_settings() self.gamemode.initialize_new_player() def test_initialize_new_player_method_classic_mode(self): """Testing the content of snake_segments' lists and the value of adding points. """ self.setup() assert len(self.gamemode.snake_segments_coord_x) != 0 assert len(self.gamemode.snake_segments_coord_y) != 0 assert self.gamemode.adding_points in [20, 30, 40] def test_snake_and_walls_logic_classic_mode(self): # Testing the ability to pass through one wall and exit the other. # Note: see self.gamemode.settings_storage['walls'] in setup method of # this class. self.gamemode.head_x_coord = 41 self.gamemode.process_hook_logic() assert self.gamemode.head_x_coord == 1 assert not self.gamemode.game_over self.gamemode.head_x_coord = 0 self.gamemode.process_hook_logic() assert self.gamemode.head_x_coord == self.gamemode.width - 1 assert not self.gamemode.game_over self.gamemode.head_y_coord = 22 self.gamemode.process_hook_logic() assert self.gamemode.head_y_coord == 0 assert not self.gamemode.game_over self.gamemode.head_y_coord = -1 self.gamemode.process_hook_logic() assert self.gamemode.head_y_coord == self.gamemode.height assert not self.gamemode.game_over # Testing logic when the ability to pass through the wall is disabled. walls = "can't crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.set_default_settings() self.gamemode.initialize_new_player() self.gamemode.head_x_coord = 40 self.gamemode.process_hook_logic() assert self.gamemode.game_over self.gamemode.game_over = False self.gamemode.head_x_coord = 0 self.gamemode.process_hook_logic() assert self.gamemode.game_over self.gamemode.game_over = False self.gamemode.head_y_coord = 21 self.gamemode.process_hook_logic() assert self.gamemode.game_over self.gamemode.game_over = False self.gamemode.head_y_coord = -1 self.gamemode.process_hook_logic() assert self.gamemode.game_over self.gamemode.game_over = False def test_snake_eats_fruit_logic_classic_mode(self): # Testing the logic of increasing the number of snake's segments when it # eats fruit. self.gamemode.head_x_coord = 20 self.gamemode.head_y_coord = 11 self.gamemode.x_coord_of_fruit = 20 self.gamemode.y_coord_of_fruit = 10 self.gamemode.process_hook_logic() assert self.gamemode.num_of_snake_segments == 4 def test_snake_eats_itself_logic_classic_mode(self): self.gamemode.head_x_coord = 20 self.gamemode.head_y_coord = 13 self.gamemode.process_hook_logic() assert self.gamemode.game_over class TestSurvivalGamemodeClass: def setup(self): """Initialization of the game mode, players and installation of default settings. """ menu_inst = Menu() score_inst = Score('TestName') self.gamemode = SurvivalModeGameManager(score_inst, menu_inst) self.gamemode.settings_storage['width'] = 40 self.gamemode.settings_storage['height'] = 20 walls = "can crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.settings_storage['speed'] = 0.08 self.gamemode.settings_storage['length'] = 3 self.gamemode.set_default_settings() self.gamemode.initialize_new_players() def test_initialize_new_players_method_survival_mode(self): """Testing the content of snake_segments_coord_x and snake_segments_coord_y for snake 1 and snake 2 and the value of adding points. """ self.setup() assert len(self.gamemode.snake_segments_coord_x_1) != 0 assert len(self.gamemode.snake_segments_coord_y_1) != 0 assert len(self.gamemode.snake_segments_coord_x_2) != 0 assert len(self.gamemode.snake_segments_coord_y_2) != 0 assert self.gamemode.adding_points in [20, 30, 40] def test_snakes_and_walls_logic_survival_mode(self): # Testing the ability to pass through one wall and exit the other for # snake 1. # Note: see self.gamemode.settings_storage['walls'] in setup method of # this class. self.gamemode.head_x_coord_1 = 41 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_x_coord_1 == 1 assert not self.gamemode.game_over_1 self.gamemode.head_x_coord_1 = 0 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_x_coord_1 == self.gamemode.width - 1 assert not self.gamemode.game_over_1 self.gamemode.head_y_coord_1 = 22 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_y_coord_1 == 0 assert not self.gamemode.game_over_1 self.gamemode.head_y_coord_1 = -1 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_y_coord_1 == self.gamemode.height assert not self.gamemode.game_over_1 # Testing the ability to pass through one wall and exit the other for # snake 2. self.gamemode.head_x_coord_2 = 41 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_x_coord_2 == 1 assert not self.gamemode.game_over_2 self.gamemode.head_x_coord_2 = 0 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_x_coord_2 == self.gamemode.width - 1 assert not self.gamemode.game_over_2 self.gamemode.head_y_coord_2 = 22 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_y_coord_2 == 0 assert not self.gamemode.game_over_2 self.gamemode.head_y_coord_2 = -1 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_y_coord_2 == self.gamemode.height assert not self.gamemode.game_over_2 # Testing logic when the ability to pass through the wall is disabled. walls = "can't crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.set_default_settings() self.gamemode.initialize_new_players() # Snake 1. self.gamemode.head_x_coord_1 = 40 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_x_coord_1 = 0 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_y_coord_1 = 21 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_y_coord_1 = -1 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False # Snake 2. self.gamemode.head_x_coord_2 = 40 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_x_coord_2 = 0 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_y_coord_2 = 21 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_y_coord_2 = -1 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False def test_snakes_eat_fruit_logic_survival_mode(self): # Testing the logic of increasing the number of snakes' segments when # they eat fruit. # Test for snake 1. self.gamemode.head_x_coord_1 = 20 self.gamemode.head_y_coord_1 = 11 self.gamemode.x_coord_of_fruit = 20 self.gamemode.y_coord_of_fruit = 10 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.num_of_snake_segments_1 == 4 # Test for snake 2. self.gamemode.head_x_coord_2 = 20 self.gamemode.head_y_coord_2 = 11 self.gamemode.x_coord_of_fruit = 20 self.gamemode.y_coord_of_fruit = 10 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.num_of_snake_segments_2 == 4 def test_snakes_eat_themselves_logic_survival_mode(self): # Snake 1. self.gamemode.head_x_coord_1 = 15 self.gamemode.head_y_coord_1 = 13 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False # Snake 2. self.gamemode.head_x_coord_2 = 25 self.gamemode.head_y_coord_2 = 13 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False def test_common_logic_of_2_snakes_survival_mode(self): # If two heads of snakes have the same coordinates, they lose. self.gamemode.head_x_coord_1 = 20 self.gamemode.head_y_coord_1 = 20 self.gamemode.head_x_coord_2 = 20 self.gamemode.head_y_coord_2 = 20 self.gamemode.process_common_logic_of_2_snakes() assert self.gamemode.game_over_1 assert self.gamemode.game_over_2 self.gamemode.game_over_1 = False self.gamemode.game_over_2 = False # If the coordinates of the first snake match the coordinates of the # elements of the tail of the 2nd snake, then the first snake loses and # vice versa. # Initial coords for the 2-nd snake's segments. self.gamemode.head_x_coord_1 = 25 self.gamemode.head_y_coord_1 = 13 self.gamemode.process_common_logic_of_2_snakes() assert self.gamemode.game_over_1 # Initial coords for the 1-st snake's segments. self.gamemode.head_x_coord_2 = 15 self.gamemode.head_y_coord_2 = 13 self.gamemode.process_common_logic_of_2_snakes() assert self.gamemode.game_over_2 class TestBattleGamemodeClass: def setup(self): """Initialization of the game mode, players and installation of default settings. """ menu_inst = Menu() score_inst = Score('TestName') self.gamemode = BattleModeGameManager(score_inst, menu_inst) walls = "can crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.settings_storage['speed'] = 0.08 self.gamemode.settings_storage['game_time'] = 1000 self.gamemode.settings_storage['length'] = 3 self.gamemode.set_default_settings() self.gamemode.initialize_new_players() def test_initialize_new_players_method_battle_mode(self): """Testing the content of snake_segments_coord_x and snake_segments_coord_y for snake 1 and snake 2 and the value of adding points. """ self.setup() assert len(self.gamemode.snake_segments_coord_x_1) != 0 assert len(self.gamemode.snake_segments_coord_y_1) != 0 assert len(self.gamemode.snake_segments_coord_x_2) != 0 assert len(self.gamemode.snake_segments_coord_y_2) != 0 assert self.gamemode.adding_points in [20, 30, 40] def test_snakes_and_walls_logic_battle_mode(self): # Testing the ability to pass through one wall and exit the other for # snake 1. # Note: see self.gamemode.settings_storage['walls'] in setup method of # this class. self.gamemode.head_x_coord_1 = 20 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_x_coord_1 == 1 assert not self.gamemode.game_over_1 self.gamemode.head_x_coord_1 = 0 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_x_coord_1 == 19 assert not self.gamemode.game_over_1 self.gamemode.head_y_coord_1 = 22 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_y_coord_1 == 0 assert not self.gamemode.game_over_1 self.gamemode.head_y_coord_1 = -1 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.head_y_coord_1 == 20 assert not self.gamemode.game_over_1 # Testing the ability to pass through one wall and exit the other for # snake 2. self.gamemode.head_x_coord_2 = 60 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_x_coord_2 == 41 assert not self.gamemode.game_over_2 self.gamemode.head_x_coord_2 = 40 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_x_coord_2 == 59 assert not self.gamemode.game_over_2 self.gamemode.head_y_coord_2 = 22 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_y_coord_2 == 0 assert not self.gamemode.game_over_2 self.gamemode.head_y_coord_2 = -1 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.head_y_coord_2 == 20 assert not self.gamemode.game_over_2 # Testing logic when the ability to pass through the wall is disabled. walls = "can't crawl through the walls" self.gamemode.settings_storage['walls'] = walls self.gamemode.set_default_settings() self.gamemode.initialize_new_players() # Snake 1. self.gamemode.head_x_coord_1 = 20 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_x_coord_1 = 0 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_y_coord_1 = 21 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False self.gamemode.head_y_coord_1 = -1 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 self.gamemode.game_over_1 = False # Snake 2. self.gamemode.head_x_coord_2 = 60 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_x_coord_2 = 40 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_y_coord_2 = 21 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False self.gamemode.head_y_coord_2 = -1 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2 self.gamemode.game_over_2 = False def test_snakes_eat_fruit_logic_battle_mode(self): # Testing the logic of increasing the number of segments of the 2-nd # snake when the first one eats fruit and vice versa. # Snake 1. self.gamemode.head_x_coord_1 = 10 self.gamemode.head_y_coord_1 = 11 self.gamemode.x_coord_of_fruit_1 = 10 self.gamemode.y_coord_of_fruit_1 = 10 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.num_of_snake_segments_2 == 4 # Snake 2. self.gamemode.head_x_coord_2 = 55 self.gamemode.head_y_coord_2 = 11 self.gamemode.x_coord_of_fruit_2 = 55 self.gamemode.y_coord_of_fruit_2 = 10 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.num_of_snake_segments_1 == 4 def test_snakes_eat_themselves_logic_battle_mode(self): # Snake 1. self.gamemode.head_x_coord_1 = 10 self.gamemode.head_y_coord_1 = 13 self.gamemode.process_hook_logic_for_player_1() assert self.gamemode.game_over_1 # Snake 2. self.gamemode.head_x_coord_2 = 50 self.gamemode.head_y_coord_2 = 13 self.gamemode.process_hook_logic_for_player_2() assert self.gamemode.game_over_2

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46a163ce1764a63c76e72ac1ad1e3282103d68e9

117

py

Python

api/tests/__init__.py

Skelmis/nextcord-stats

311268284166307b563826da0829b01c47df34d7

[ "MIT" ]

null

api/tests/__init__.py

Skelmis/nextcord-stats

311268284166307b563826da0829b01c47df34d7

[ "MIT" ]

1

2022-02-23T14:28:02.000Z

2022-02-27T10:30:35.000Z

api/tests/__init__.py

Skelmis/nextcord-stats

311268284166307b563826da0829b01c47df34d7

[ "MIT" ]

null

import datetime def get_aware_time() -> datetime.datetime: return datetime.datetime.now(datetime.timezone.utc)

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d3d85d3c232feddff3d1dfc2f1f20374625b2cd7

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py

Python

New_Atoll_Code_region_aggregating_visualization_short_aco.py

ale37911/AtollGeoMorph

77cc408010c0a8a257fe5fd40e694199cda1ea42

[ "MIT" ]

1

2022-01-25T18:31:14.000Z

New_Atoll_Code_region_aggregating_visualization_short_aco.py

ale37911/AtollGeoMorph

77cc408010c0a8a257fe5fd40e694199cda1ea42

[ "MIT" ]

null

New_Atoll_Code_region_aggregating_visualization_short_aco.py

ale37911/AtollGeoMorph

77cc408010c0a8a257fe5fd40e694199cda1ea42

[ "MIT" ]

null

#%%---------------------Import python libaries----------------------- #import gdal import matplotlib.pyplot as plt import numpy as np import os import pandas as pd import seaborn as sns import matplotlib.patches #%%------------------input data atollCompLoc = 'G:\Shared drives\Ortiz Atolls Database\CompositesWithCount\AllAtolls' #Location of all Atoll Composites (currently the ones made in 2019) atollComp = os.listdir(atollCompLoc) morphOutput = 'G:\Shared drives\Ortiz Atolls Database\MorphometricOutput' # Location that the output will be saved to countryName = 'AllAtollsNew' newAtollList = [] for i in range(len(atollComp)): fileName = atollComp[i] atollName = fileName[0:-20] full_path = morphOutput + '\\' + countryName + '\\' + atollName if os.path.exists(full_path): os.chdir(full_path) if os.path.isfile('df_motu.csv'): newAtollList.append(atollName) PF = [] for i in range(len(newAtollList)): if newAtollList[i][0:4] == 'P_PF': PF.append(newAtollList[i]) #%% Create large dataFrames i = 0 atollName = newAtollList[i] fileName = atollName + '50c50mCountClip2.tif' resolution = 30 morphOutput = 'G:\Shared drives\Ortiz Atolls Database\MorphometricOutput' # Location that the output will be saved to countryName = 'AllAtollsNew' full_path = morphOutput + '\\' + countryName + '\\' + atollName # create county and atoll directory if they do not exist os.chdir(full_path) # set working directory to the atoll directory # read in dataframes df3 = pd.read_csv('df_reef_flat.csv') df2 = pd.read_csv('df_motu.csv') dfatoll = pd.read_csv('df_atollOnly.csv') df2small = pd.read_csv('df_motu_small.csv') df3['ocean basin'] = atollName[0] df3['country code'] = atollName[2:4] df3['atoll name'] = atollName[5:] df2['ocean basin'] = atollName[0] df2['country code'] = atollName[2:4] df2['atoll name'] = atollName[5:] dfatoll['ocean basin'] = atollName[0] dfatoll['country code'] = atollName[2:4] dfatoll['atoll name'] = atollName[5:] df2small['ocean basin'] = atollName[0] df2small['country code'] = atollName[2:4] df2small['atoll name'] = atollName[5:] unwanted = df2.columns[df2.columns.str.startswith('Unnamed')] df2.drop(unwanted, axis=1, inplace=True) unwanted = df3.columns[df3.columns.str.startswith('Unnamed')] df3.drop(unwanted, axis=1, inplace=True) unwanted = dfatoll.columns[dfatoll.columns.str.startswith('Unnamed')] dfatoll.drop(unwanted, axis=1, inplace=True) unwanted = df2small.columns[df2small.columns.str.startswith('Unnamed')] df2small.drop(unwanted, axis=1, inplace=True) df2all = df2.copy(deep=True) df3all = df3.copy(deep=True) dfatollall = dfatoll.copy(deep=True) df2smallall = df2small.copy(deep=True) for i in range(1,155): atollName = newAtollList[i] fileName = atollName + '50c50mCountClip2.tif' resolution = 30 morphOutput = 'G:\Shared drives\Ortiz Atolls Database\MorphometricOutput' # Location that the output will be saved to countryName = 'AllAtollsNew' full_path = morphOutput + '\\' + countryName + '\\' + atollName # create county and atoll directory if they do not exist os.chdir(full_path) # set working directory to the atoll directory # read in dataframes df3 = pd.read_csv('df_reef_flat.csv') df2 = pd.read_csv('df_motu.csv') dfatoll = pd.read_csv('df_atollOnly.csv') df2small = pd.read_csv('df_motu_small.csv') df3['ocean basin'] = atollName[0] df3['country code'] = atollName[2:4] df3['atoll name'] = atollName[5:] df2['ocean basin'] = atollName[0] df2['country code'] = atollName[2:4] df2['atoll name'] = atollName[5:] dfatoll['ocean basin'] = atollName[0] dfatoll['country code'] = atollName[2:4] dfatoll['atoll name'] = atollName[5:] df2small['ocean basin'] = atollName[0] df2small['country code'] = atollName[2:4] df2small['atoll name'] = atollName[5:] unwanted = df2.columns[df2.columns.str.startswith('Unnamed')] df2.drop(unwanted, axis=1, inplace=True) unwanted = df3.columns[df3.columns.str.startswith('Unnamed')] df3.drop(unwanted, axis=1, inplace=True) unwanted = dfatoll.columns[dfatoll.columns.str.startswith('Unnamed')] dfatoll.drop(unwanted, axis=1, inplace=True) unwanted = df2small.columns[df2small.columns.str.startswith('Unnamed')] df2small.drop(unwanted, axis=1, inplace=True) frames2 = [df2all, df2] frames3 = [df3all, df3] frames4 = [dfatollall, dfatoll] framessmall = [df2smallall, df2small] df2all = pd.concat(frames2) df3all = pd.concat(frames3) dfatollall = pd.concat(frames4) df2smallall = pd.concat(framessmall) #%% save large dataframes morphOutput = 'G:\Shared drives\Ortiz Atolls Database\MorphometricOutput' # Location that the output will be saved to countryName = 'AllAtollsNew' full_path = morphOutput + '\\' + countryName + '\\Regional_Analysis' os.chdir(full_path) # set working directory to the atoll directory df2all.to_csv('df_motu_allACO.csv') df3all.to_csv('df_reef_flat_allACO.csv') dfatollall.to_csv('df_atollOnly_all.csv') df2smallall.to_csv('df_smallmotu_all.csv') #%% Alternatively if large dataframes exist, just read them in large dataframes morphOutput = 'G:\Shared drives\Ortiz Atolls Database\MorphometricOutput' # Location that the output will be saved to countryName = 'AllAtollsNew' full_path = morphOutput + '\\' + countryName + '\\Regional_Analysis' os.chdir(full_path) # set working directory to the atoll directory df3all = pd.read_csv('df_reef_flat_allACO.csv') df2all = pd.read_csv('df_motu_allACO.csv') dfatollall = pd.read_csv('df_atollOnly_all.csv') df2smallall = pd.read_csv('df_smallmotu_all.csv') df_binned2 = pd.read_csv('French Polynesia' + ' df_binned.csv') df3all['bins latitude'] = pd.cut(df3all['centroid_lat'], bins = [-25, -13, -3, 4, 15], labels = ['-25 to -13', '-13 to -3', '-3 to 4', '4 to 15'], ordered = False) df2all['bins latitude'] = pd.cut(df2all['centroid_lat'], bins = [-25, -13, -3, 4, 15], labels = ['-25 to -13', '-13 to -3', '-3 to 4', '4 to 15'], ordered = False) dfatollall['bins latitude'] = pd.cut(dfatollall['centroid_lat'], bins = [-25, -13, -3, 4, 15], labels = ['-25 to -13', '-13 to -3', '-3 to 4', '4 to 15'], ordered = False) #%% decide on grouping (regional or all or other) df3all['bins abs latitude'] = pd.cut(df3all['centroid_lat'].abs(), bins = [-1, 4.7, 14, 30], labels = ['low', 'mid', 'high'], ordered = False) df2all['bins abs latitude'] = pd.cut(df2all['centroid_lat'].abs(), bins = [-1, 4.7, 14, 30], labels = ['low', 'mid', 'high'], ordered = False) atoll_centroids = df3all.groupby(['atoll name']).mean()[['centroid_lat','centroid_long']] region_bin = df3all.groupby(['atoll name']).first()[['country code']] t2 = region_bin.groupby('country code').size() df3all_PF = df3all[df3all['country code'] == 'PF'] df2all_PF = df2all[df2all['country code'] == 'PF'] # depending on plotting interest/grouping # region_name = 'French Polynesia' # df_reef = df3all_PF # df_motu = df2all_PF region_name = 'All Atolls' df_reef = df3all df_motu = df2all #%% # create summary tables df_motu_summary = df_motu.groupby(['atoll name','motu index']).first()[['ocean basin','country code','bins abs latitude']] df_motu_summary[['motu label','reef flat label','centroid_lat']] = df_motu.groupby(['atoll name','motu index']).mean()[['motu label','reef flat label','centroid_lat']] df_motu_summary[['area (m^2)','perimeter (m)','mean motu to reef flat distance (m)','mean motu lagoon to reef flat lagoon (m)','mean motu width (m)','mean ocean reef width (m)', 'mean lagoon reef width (m)','motu length (m)','ocean side motu length (m)','lagoon side motu length (m)']] = df_motu.groupby(['atoll name','motu index']).mean()[['area m^2','perimeter m','motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width','motu length','ocean side motu length','lagoon side motu length']] df_motu_summary[['std motu to reef flat distance (m)','std motu lagoon to reef flat lagoon (m)','std motu width (m)','std ocean reef width (m)', 'std lagoon reef width (m)']] = df_motu.groupby(['atoll name','motu index']).std()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width']] df_reef_summary = df_reef.groupby(['atoll name','reef flat index']).mean()[['reef flat label','centroid_lat']] df_reef_summary[['area (m^2)','perimeter (m)','mean reef flat width (m)','mean effective reef flat width (m)','mean reef flat width motu (std)','ocean side reef flat length (m)']] = df_reef.groupby(['atoll name','reef flat index']).mean()[['area m^2','perimeter R','reef flat width','effective reef flat width','reef flat width motu','ocean side reef flat length']] df_reef_summary[['std reef flat width (m)','std effective reef flat width (m)','std reef flat width motu (m)']] = df_reef.groupby(['atoll name','reef flat index']).std()[['reef flat width','effective reef flat width','reef flat width motu']] #% totals def NumberObjects(m, s1): mt =m.copy() num = len(mt[s1].unique()) return num df_totals = df_motu.groupby('atoll name').first()[['ocean basin','country code','bins abs latitude']] df_totals[['atoll centroid_lat', 'atoll centroid_long']] = df_motu.groupby('atoll name').mean()[['centroid_lat', 'centroid_long']] df_totals['Number Motu'] = df_motu.groupby('atoll name').apply(NumberObjects,s1 = 'motu index') df_totals['Number Reef Flat'] = df_reef.groupby('atoll name').apply(NumberObjects,s1 = 'reef flat index') #% df_totals[['total motu area (m^2)','total motu perimeter (m)','total motu length (m)','total ocean side motu length (m)','total lagoon side motu length (m)']] = df_motu_summary.groupby('atoll name').sum()[['area (m^2)','perimeter (m)','motu length (m)','ocean side motu length (m)','lagoon side motu length (m)']] df_totals[['mean motu to reef flat distance (m)','mean motu lagoon to reef flat lagoon (m)','mean motu width (m)']] = df_motu.groupby('atoll name').mean()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width']] df_totals[['std motu to reef flat distance (m)','std motu lagoon to reef flat lagoon (m)','std motu width (m)']] = df_motu.groupby('atoll name').std()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width',]] df_totals[['total reef flat area (m^2)','total reef flat perimeter (m)','total ocean side reef flat length (m)']] = df_reef_summary.groupby('atoll name').sum()[['area (m^2)','perimeter (m)','ocean side reef flat length (m)']] df_totals[['mean reef flat width (m)','mean effective reef flat width (m)']] = df_reef.groupby('atoll name',).mean()[['reef flat width','effective reef flat width']] df_totals[['std reef flat width (m)','std effective reef flat width (m)']] = df_reef.groupby('atoll name').std()[['reef flat width','effective reef flat width']] df_totals['percent reef flat length covered by motu (%)'] = df_totals['total ocean side motu length (m)']/df_totals['total ocean side reef flat length (m)'] *100 df_totals['percent reef flat area covered by motu (%)'] = df_totals['total motu area (m^2)']/df_totals['total reef flat area (m^2)'] *100 df_totals['bins latitude'] = pd.cut(df_totals['atoll centroid_lat'], bins = [-25, -13, -3, 4, 15], labels = ['-25 to -13', '-13 to -3', '-3 to 4', '4 to 15'], ordered = False) df_totals.to_csv(region_name + ' df_totals_ACO.csv') #%% Create binned large dataFrames df_binned = df_reef.groupby(['atoll name','bins ac']).mean()[['centroid_lat', 'centroid_long','reef flat width','effective reef flat width','reef flat width motu','total binned reef flat length']] df_binned.columns = [['atoll centroid_lat', 'atoll centroid_long','mean reef flat width (m)','mean effective reef flat width (m)','mean reef flat width motu (m)','total binned reef flat length (m)']] df_binned[['bins abs latitude']] = df_reef.groupby(['atoll name','bins ac']).first()[['bins abs latitude']] df_binned[['std reef flat width (m)','std effective reef flat width (m)']] = df_reef.groupby(['atoll name','bins ac']).std()[['reef flat width','effective reef flat width']] df_binned[['mean motu to reef flat distance (m)','mean motu lagoon to reef flat lagoon (m)','mean motu width (m)','mean ocean reef width (m)', 'mean lagoon reef width (m)','total binned motu length (m)']] = df_motu.groupby(['atoll name','bins ac']).mean()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width','total binned motu length']] df_binned[['std motu to reef flat distance (m)','std motu lagoon to reef flat lagoon (m)','std motu width (m)','std ocean reef width (m)', 'std lagoon reef width (m)']] = df_motu.groupby(['atoll name','bins ac']).std()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width']] df_binned['percent reef flat length covered by motu (%)'] = df_binned['total binned motu length (m)'].squeeze().divide(df_binned['total binned reef flat length (m)'].squeeze(),fill_value = 0)*100 df_binned = df_binned.reset_index(drop = False) df_binned.to_csv(region_name + ' df_binnedACO.csv') #%% merge small and large motu df_motu_summary_large = df_motu_summary.reset_index(drop = False) df2all_small2 = df2smallall.reset_index(drop = False) maxMotu = df_motu_summary_large[['atoll name','motu index']].groupby('atoll name').max() df2all_small2['motu index'] = df2all_small2['small motu index'] + maxMotu.loc[df2all_small2['atoll name']].reset_index(drop = 'atoll name').squeeze() frames = [df2all_small2, df_motu_summary_large] df_motu_summary_all = pd.concat(frames) #%% create total motu summary df_totals_all = df_motu.groupby('atoll name').first()[['ocean basin','country code','bins abs latitude']] df_totals_all['Number Motu'] = df_motu_summary_all.groupby('atoll name').apply(NumberObjects,s1 = 'motu index') df_totals_all[['total motu area (km^2)']] = df_motu_summary_all.groupby('atoll name').sum()[['area (m^2)']]/1000000 df_totals_all[['total motu perimeter (km)']] = df_motu_summary_all.groupby('atoll name').sum()[['perimeter (m)']]/1000 df_totals_all['Number Motu small'] = df2all_small2.groupby('atoll name').apply(NumberObjects,s1 = 'motu index') df_totals_all[['motu area small (km^2)']] = df2all_small2.groupby('atoll name').sum()[['area (m^2)']]/1000000 df_totals_all[['motu perimeter small (km)']] = df2all_small2.groupby('atoll name').sum()[['perimeter (m)']]/1000 df_totals_all['Number Motu large'] = df_motu_summary_large.groupby('atoll name').apply(NumberObjects,s1 = 'motu index') df_totals_all[['motu area large (km^2)']] = df_motu_summary_large.groupby('atoll name').sum()[['area (m^2)']]/1000000 df_totals_all[['motu perimeter large (km)']] = df_motu_summary_large.groupby('atoll name').sum()[['perimeter (m)']]/1000 df_totals_all.to_csv('AllMotuSummarySmallLargeMotu.csv') #%%Motu summary data df_reef['exposure bin'] = pd.cut(df_reef['exposure angle'], bins = [-1, 45, 135, 225, 315, 360], labels = ['North', 'East', 'South', 'West', 'North'], ordered = False) df_motu['exposure bin'] = pd.cut(df_motu['exposure angle'], bins = [-1, 45, 135, 225, 315, 360], labels = ['North', 'East', 'South', 'West', 'North'], ordered = False) df_motu_summary = df_motu.groupby(['atoll name','motu index']).first()[['ocean basin','country code','bins abs latitude','motu excentricity']] df_motu_summary[['motu label','reef flat label','centroid_lat']] = df_motu.groupby(['atoll name','motu index']).mean()[['motu label','reef flat label','centroid_lat']] df_motu_summary[['area (m^2)','perimeter (m)','mean motu to reef flat distance (m)','mean motu lagoon to reef flat lagoon (m)','mean motu width (m)','mean ocean reef width (m)', 'mean lagoon reef width (m)','motu length (m)','ocean side motu length (m)','lagoon side motu length (m)']] = df_motu.groupby(['atoll name','motu index']).mean()[['area m^2','perimeter m','motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width','motu length','ocean side motu length','lagoon side motu length']] df_motu_summary[['std motu to reef flat distance (m)','std motu lagoon to reef flat lagoon (m)','std motu width (m)','std ocean reef width (m)', 'std lagoon reef width (m)']] = df_motu.groupby(['atoll name','motu index']).std()[['motu to reef flat distance','motu lagoon to reef flat lagoon','motu width','ocean reef width', 'lagoon reef width']] df_motu_summary[['directional bin']] = df_motu[df_motu['o/l label']=='ocean'].groupby(['atoll name','motu index'])['bins ac'].agg(pd.Series.mode).to_frame() df_motu_summary[['exposure bin']] = df_motu[df_motu['o/l label']=='ocean'].groupby(['atoll name','motu index'])['exposure bin'].agg(pd.Series.mode).to_frame() df_motu_summary['exposure bin'][df_motu_summary['exposure bin'].str.len() < 3.0] = np.nan m = df_motu_summary[df_motu_summary['directional bin'] != df_motu_summary['exposure bin']] #%% Exposure Angle & Position Angle from scipy.stats import circmean def circMean(m, s1): mt =m.copy() mt[[s1]] r = circmean(mt[[s1]], high = 360, low = 0) return r df_motu_summary['mean exposure angle'] = df_motu[df_motu['o/l label']=='ocean'].groupby(['atoll name','motu index']).apply(circMean, s1 = 'exposure angle') df_motu_summary['mean exposure bin'] = pd.cut(df_motu_summary['mean exposure angle'], bins = [-1, 45, 135, 225, 315, 360], labels = ['North', 'East', 'South', 'West', 'North'], ordered = False) df_motu_summary['mean position angle'] = df_motu[df_motu['o/l label']=='ocean'].groupby(['atoll name','motu index']).apply(circMean, s1 = 'binning angle ac') df_motu_summary['mean position bin'] = pd.cut(df_motu_summary['mean position angle'], bins = [-1, 45, 135, 225, 315, 360], labels = ['North', 'East', 'South', 'West', 'North'], ordered = False) df_merged = df_motu_summary.merge(df_reef_summary, on=['atoll name','reef flat label']) #%% valuble column names s1 = 'mean lagoon reef width (m)' s2 = 'mean motu width (m)' s3 = 'mean ocean reef width (m)' s4 = 'motu total reef width (m)' s5 = 'motu-reef-flat-dist / reef-flat width' s6 = 'motu length / reef-flat length' df_merged['motu total reef width (m)'] = df_merged[s1] + df_merged[s2] + df_merged[s3] #x = motu length / atoll perimeter; y-axis = motu-reef-flat-dist / reef-flat width df_merged['motu-reef-flat-dist / reef-flat width'] = df_merged['mean ocean reef width (m)']/df_merged['motu total reef width (m)'] df_merged['motu length / reef-flat length'] = df_merged['motu length (m)']/df_merged['ocean side reef flat length (m)'] df_mergedm = df_merged[df_merged['mean position bin'] != df_merged['mean exposure bin']] colors = {'low':'blue', 'mid':'orange', 'high':'green'} p1 = s5 p2 = s6 #%% Plot critical reef flat width vs motu length FP p1 = s3 p2 = 'motu length (m)' cmp = plt.get_cmap('gist_earth',6) ax1 = df_merged[(df_merged['mean position bin'] == 'North') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(1), xlim = (0,70000), ylim = (0,3000), label = 'North',s=25) df_merged[(df_merged['mean position bin'] == 'East') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(2), xlim = (0,70000), ylim = (0,3000),ax=ax1, label = 'East',s=25) df_merged[(df_merged['mean position bin'] == 'South') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(3), xlim = (0,70000), ylim = (0,3000),ax=ax1, label = 'South',s=10) df_merged[(df_merged['mean position bin'] == 'West') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(4), xlim = (0,6000), ylim = (0,1500),ax=ax1, label = 'West',s=10) plt.legend(framealpha=0.0) plt.yticks(np.arange(0,1500,step=250),fontsize=12) plt.xticks(np.arange(0,60000,step=15000),np.arange(0,60,step=15),fontsize=12) plt.xlabel('Motu Length (km)') plt.ylabel('Ocean Reef Width (m)') ax1.tick_params(axis='both',which='major',width=2,length=7,direction='in') #plt.savefig('MotuLengthOceanReefWidthFP.png',dpi=600) #%% Plot critical reef flat width vs motu length normalized #p1 = s3 #p2 = 'motu length (m)' p1 = s5 p2 = s6 cmp = plt.get_cmap('gist_earth',6) ax1 = df_merged[(df_merged['mean position bin'] == 'North') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(1), xlim = (0,70000), ylim = (0,3000), label = 'North',s=25) df_merged[(df_merged['mean position bin'] == 'East') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(2), xlim = (0,70000), ylim = (0,3000),ax=ax1, label = 'East',s=25) df_merged[(df_merged['mean position bin'] == 'South') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(3), xlim = (0,70000), ylim = (0,3000),ax=ax1, label = 'South',s=10) df_merged[(df_merged['mean position bin'] == 'West') & (df_merged['country code']== 'PF')].plot.scatter(y=p1, x=p2, c= cmp(4), xlim = (0,1), ylim = (0,1),ax=ax1, label = 'West',s=10) plt.legend(framealpha=0.0) plt.yticks(np.arange(0,1.1,step=.25)) plt.xticks(np.arange(0,1.1,step=.25)) plt.xlabel('Motu Length/Reef-flat Length') plt.ylabel('Ocean Reef Width/Total Reef-flat Width') ax1.tick_params(axis='both',which='major',width=2,length=7,direction='in') #plt.savefig('MotuLengthOceanReefWidthFPNormalized.png',dpi=600) #%%strings df_merged = df_motu_summary.merge(df_reef_summary, on=['atoll name','reef flat label']) s1 = 'mean lagoon reef width (m)' s2 = 'mean motu width (m)' s3 = 'mean ocean reef width (m)' s4 = 'motu total reef width (m)' s5 = 'motu-reef-flat-dist / reef-flat width' s6 = 'motu length / reef-flat length' df_merged['bins abs latitude'] = pd.cut(df_merged['centroid_lat_x'].abs(), bins = [-1, 4.7, 14, 30], labels = ['low', 'mid', 'high'], ordered = False) df_merged['bins abs latitude'] = pd.cut(df_merged['centroid_lat_x'].abs(), bins = [-1, 4.7, 14, 30], labels = ['low', 'mid', 'high'], ordered = False) #%%Motu length v reef width (m) binned by direction df_merged['motu total reef width (m)'] = df_merged[s1] + df_merged[s2] + df_merged[s3] df_merged['motu-reef-flat-dist / reef-flat width'] = df_merged['mean ocean reef width (m)']/df_merged['motu total reef width (m)'] df_merged['motu length / reef-flat length'] = df_merged['motu length (m)']/df_merged['ocean side reef flat length (m)'] p1 = s3 p2 = 'motu length (m)' blues = plt.get_cmap('Blues',5) purples = plt.get_cmap('Purples',5) reds = plt.get_cmap('Reds',5) oranges = plt.get_cmap('Oranges',6) greens = plt.get_cmap('Greens',5) df_merged['bins abs lat'] = df_merged['bins abs latitude'].map({'high': 'high tropical', 'mid': 'mid tropical', 'low':'equatorial'}) ax1 = df_merged[df_merged['bins abs latitude'] == 'low'].plot.scatter(y=p1, x=p2, color=blues(3), label = 'equatorial') df_merged[df_merged['bins abs latitude'] == 'mid'].plot.scatter(y=p1, x=p2, color=oranges(3), ax=ax1, label = 'mid tropical') df_merged[df_merged['bins abs latitude'] == 'high'].plot.scatter(y=p1, x=p2, color=greens(3), xlim = (0,70000), ylim = (0,3000),ax=ax1, label = 'high tropical') plt.legend(framealpha=0.0) plt.yticks(np.arange(0,3000,step=500)) plt.xticks(np.arange(0,70000,step=15000),np.arange(0,70,step=15)) # legend = plt.legend() # legend.get_frame().set_facecolor('none') plt.xlabel('Motu Length (km)') plt.ylabel('Ocean Reef Width (m)') ax1.tick_params(axis='both',which='major',width=2,length=7,direction='in') #plt.savefig('MotuLengthOceanReefWidthAll.png',dpi=600) #%% normalized All data critical reef width vs length p1 = s5 p2 = s6 blues = plt.get_cmap('Blues',5) purples = plt.get_cmap('Purples',5) reds = plt.get_cmap('Reds',5) oranges = plt.get_cmap('Oranges',6) greens = plt.get_cmap('Greens',5) df_merged['bins abs lat'] = df_merged['bins abs latitude'].map({'high': 'high tropical', 'mid': 'mid tropical', 'low':'equatorial'}) ax1 = df_merged[df_merged['bins abs latitude'] == 'low'].plot.scatter(y=p1, x=p2, color=blues(3), label = 'equatorial') df_merged[df_merged['bins abs latitude'] == 'mid'].plot.scatter(y=p1, x=p2, color=oranges(3), ax=ax1, label = 'mid tropical') df_merged[df_merged['bins abs latitude'] == 'high'].plot.scatter(y=p1, x=p2, color=greens(3), xlim = (0,1), ylim = (0,1),ax=ax1, label = 'high tropical') plt.legend(framealpha=0.0) #plt.yticks(np.arange(0,1500,step=250),fontsize=12) plt.yticks(np.arange(0,1.1,step=.25)) plt.xticks(np.arange(0,1.1,step=.25)) plt.xlabel('Motu Length/Reef-flat Length') plt.ylabel('Ocean Reef Width/Total Reef-flat Width') ax1.tick_params(axis='both',which='major',width=2,length=7,direction='in') #plt.savefig('MotuLengthOceanReefWidthAllNorm.png',dpi=600) #%% 2 d histigrams # libraries df_merged4 = df_merged.reset_index(drop = False) df_merged4[['log 10 motu length (m)']] = np.log10(df_merged4[['motu length (m)']]) df_merged4[['log 10 motu width (m)']] = np.log10(df_merged4[['mean motu width (m)']]) df_merged5 = df_merged4[df_merged4['bins abs latitude'] == 'high'] #change to mid, low #sns.displot(df_merged5, x='log 10 motu length (m)', y='log 10 motu width (m)', bins = [10,10]) #sns.displot(df_merged4, x='log 10 motu length (m)', y='log 10 motu width (m)', hue='bins abs latitude', kind="kde") plt.xlim([0, 5]) plt.ylim([0, 5]) #sns.displot(df_merged4, x='motu length (m)', y='mean motu width (m)', hue='bins abs latitude', kind="kde") sns.displot(df_merged5, x='log 10 motu length (m)', y='log 10 motu width (m)', hue='bins abs latitude', kind="kde",fill = True, levels = (0.05,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1)) #%% all widths in one with the colors for FP df_binned2['label bin'] = df_binned2['bins ac'].map({'North': 'a', 'East': 'b','South': 'c', 'West': 'd'}) df_binned2[['a) motu width','d) ocean reef width', 'c) lagoon reef width','b) reef flat width','e) effective reef flat width']] = df_binned2[['mean motu width (m)','mean ocean reef width (m)', 'mean lagoon reef width (m)','mean reef flat width (m)','mean effective reef flat width (m)']] axs = df_binned2[['label bin','a) motu width','d) ocean reef width', 'c) lagoon reef width','b) reef flat width','e) effective reef flat width']].boxplot(by = 'label bin',figsize = (12,6),layout=(1, 5),patch_artist = True, grid=False, color = {'whiskers' : 'black', 'caps' : 'black', 'medians' : 'black', 'boxes' : 'black'}) cmp = plt.get_cmap('gist_earth',6) for i in range(0,5): axs[i].findobj(matplotlib.patches.Patch)[0].set_facecolor(cmp(1)) axs[i].findobj(matplotlib.patches.Patch)[1].set_facecolor(cmp(2)) axs[i].findobj(matplotlib.patches.Patch)[2].set_facecolor(cmp(3)) axs[i].findobj(matplotlib.patches.Patch)[3].set_facecolor(cmp(4)) axs[0].set_xticklabels(('North', 'East', 'South', 'West','North', 'East', 'South', 'West','North', 'East', 'South', 'West','North', 'East', 'South', 'West','North', 'East', 'South', 'West')) axs[0].set(xlabel="", ylabel='mean width (m)') axs[1].set(xlabel="") axs[2].set(xlabel="") axs[3].set(xlabel="") axs[4].set(xlabel="") plt.show() #plt.savefig('WidthsFP_Boxplots.png') #%% df_merged['atoll name 2'] = df_merged.index df_mergedbin = df_merged[['motu length (m)']] df_mergedbin[['bins ac']] = df_merged[['mean position bin']] df_mergedbin.reset_index(level=0, inplace=True) df_binnedlength= df_mergedbin.groupby(['atoll name','bins ac']).mean()[['motu length (m)']] df_binnedlength[['motu length (km)']] = df_binnedlength[['motu length (m)']]/1000 df_binnedlength.reset_index(level=1, inplace=True) df_binnedlength['label bin'] = df_binnedlength['bins ac'].map({'North': 'a', 'East': 'b','South': 'c', 'West': 'd'}) #%% plot percent length blocked by motu binned box plot df_binned2['label bin'] = df_binned2['bins ac'].map({'North': 'a', 'East': 'b','South': 'c', 'West': 'd'}) fig, ax = plt.subplots(1, 2, figsize=(8, 5)) df_binned2.boxplot('percent reef flat length covered by motu (%)','label bin', ax=ax[1],patch_artist = True, grid=False, color = {'whiskers' : 'black', 'caps' : 'black', 'medians' : 'black', 'boxes' : 'black'}) df_binnedlength.boxplot('motu length (km)','label bin', ax=ax[0],patch_artist = True, grid=False, color = {'whiskers' : 'black', 'caps' : 'black', 'medians' : 'black', 'boxes' : 'black'}) ax[0].set_xticklabels(('North', 'East', 'South', 'West')) ax[1].set_xticklabels(('North', 'East', 'South', 'West')) ax[1].set(xlabel="", ylabel='reef flat length blocked by motu (%)', title='percent reef flat blocked by motu') ax[0].set(xlabel="", ylabel='mean motu length (km)', title='motu length') cmp = plt.get_cmap('gist_earth',6) for i in range(0,2): ax[i].findobj(matplotlib.patches.Patch)[0].set_facecolor(cmp(1)) ax[i].findobj(matplotlib.patches.Patch)[1].set_facecolor(cmp(2)) ax[i].findobj(matplotlib.patches.Patch)[2].set_facecolor(cmp(3)) ax[i].findobj(matplotlib.patches.Patch)[3].set_facecolor(cmp(4)) ax[1].set_ylim((-1,120)) ax[0].set_ylim((-.4,44)) #plt.savefig('%BlockedFP_Boxplots.png') #%% df_motu_summary.to_csv(region_name + ' df_motu_summaryACO.csv') df_reef_summary.to_csv(region_name + ' df_reef_summaryACO.csv') #%% total perimeter/area by lattitude df_reef['bins latitude 3'] = pd.cut(df_reef['centroid_lat'], bins = [-25,-23,-21,-19,-17,-15,-13,-11,-9,-7,-5,-3,-1,1,3,5,7,9,11,13,15], labels = [-24, -22, -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14], ordered = False) df_motu['bins latitude 3'] = pd.cut(df_motu['centroid_lat'], bins = [-25,-23,-21,-19,-17,-15,-13,-11,-9,-7,-5,-3,-1,1,3,5,7,9,11,13,15], labels = [-24, -22, -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14], ordered = False) df_reef['bins latitude 4'] = pd.cut(df_reef['centroid_lat'], bins = [-25.5,-22.5,-19.5,-16.5,-13.5,-10.5,-7.5,-4.5,-1.5,1.5,4.5,7.5,10.5,13.5,16.5], labels = [-24, -21, -18, -15, -12, -9, -6, -3, 0, 3, 6, 9, 12, 15], ordered = False) df_motu['bins latitude 4'] = pd.cut(df_motu['centroid_lat'], bins = [-25.5,-22.5,-19.5,-16.5,-13.5,-10.5,-7.5,-4.5,-1.5,1.5,4.5,7.5,10.5,13.5,16.5], labels = [-24, -21, -18, -15, -12, -9, -6, -3, 0, 3, 6, 9, 12, 15], ordered = False) s1 = 'bins latitude 4' df_motu_summary[s1] = df_motu.groupby(['atoll name','motu index']).first()[[s1]] df_reef_summary[s1] = df_reef.groupby(['atoll name','reef flat index']).first()[[s1]] df_motu_summary = df_motu_summary.reset_index(drop=False) df_lat_totals = df_motu_summary.groupby([s1]).sum()[['area (m^2)','perimeter (m)']] df_lat_totals['number atolls'] = df_motu_summary.groupby([s1]).nunique()[['atoll name']] df_lat_totals['number motu'] = df_motu_summary.groupby([s1]).count()[['area (m^2)']] df_lat_totals['total motu area (km^2)'] = df_lat_totals['area (m^2)']/1000000 df_lat_totals['total motu perimeter (km)'] = df_lat_totals['perimeter (m)']/1000 df_lat_totals[['total reef flat area (m^2)','total reef flat perimeter (m)']] = df_reef_summary.groupby([s1]).sum()[['area (m^2)','perimeter (m)']] df_lat_totals['number reef flat'] = df_reef_summary.groupby([s1]).count()[['area (m^2)']] df_lat_totals['total reef flat area (km^2)'] = df_lat_totals['total reef flat area (m^2)']/1000000 df_lat_totals['total reef flat perimeter (km)'] = df_lat_totals['total reef flat perimeter (m)']/1000 df_lat_totals = df_lat_totals.drop(['area (m^2)','perimeter (m)','total reef flat area (m^2)','total reef flat perimeter (m)'], axis=1) #%% df_lat_totals2 = df_lat_totals.reset_index(drop = False) df_lat_totals2 = df_lat_totals2.append({'bins latitude 4':-27,'number motu':0, 'total motu area (km^2)':0, 'total motu perimeter (km)':0, 'number reef flat':0, 'total reef flat area (km^2)':0,'total reef flat perimeter (km)':0},ignore_index=True) df_lat_totals2 = df_lat_totals2.append({'bins latitude 4':15,'number motu':0, 'total motu area (km^2)':0, 'total motu perimeter (km)':0, 'number reef flat':0, 'total reef flat area (km^2)':0,'total reef flat perimeter (km)':0},ignore_index=True) df_lat_totals2 = df_lat_totals2.sort_values([s1]) df_lat_totals2 = df_lat_totals2.reset_index(drop=True) #%% df2=df2all_PF df3=df3all_PF blues = plt.get_cmap('Blues',6) purples = plt.get_cmap('Purples',6) reds = plt.get_cmap('Reds',6) oranges = plt.get_cmap('Oranges',6) greens = plt.get_cmap('Greens',6) fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) lineW = 2 # Draw the density plot sns.distplot(df2['motu width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'motu width', color = reds(4)) sns.distplot(df3['reef flat width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'reef flat width', color = blues(4)) sns.distplot(df2['lagoon reef width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'lagoon reef width', color = oranges(4)) sns.distplot(df2['ocean reef width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'ocean reef width', color = purples(4)) sns.distplot(df3['effective reef flat width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'effective reef flat width', color = greens(4)) # Plot formatting plt.legend(prop={'size': 12}, title = 'Widths') plt.title('a) French Polynesia Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.tight_layout() #plt.savefig('DensityFP_AllWidths.png',dpi=600) #%% density functions for the width measurements - motu width df = df2.copy() s2 = 'bins ac' s1 = 'motu width' #Draw the density plot linecolor = reds fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) sns.distplot(df[df[s2] == 'North'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(5), label = 'North') sns.distplot(df[df[s2] == 'East'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(4), label = 'East') sns.distplot(df[df[s2] == 'South'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(3), label = 'South') sns.distplot(df[df[s2] == 'West'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(2), label = 'West') # Plot formatting plt.title('b) Motu Width') plt.xlabel('Width (m)') plt.ylabel('Density') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() #plt.savefig('DensityFP_motuwidth.png',dpi=600) #%% density functions for the width measurements - reef flat width df = df3.copy() s2 = 'bins ac' s1 = 'reef flat width' #Draw the density plot linecolor = blues fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) sns.distplot(df[df[s2] == 'North'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(5), label = 'North') sns.distplot(df[df[s2] == 'East'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(4), label = 'East') sns.distplot(df[df[s2] == 'South'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(3), label = 'South') sns.distplot(df[df[s2] == 'West'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(2), label = 'West') # Plot formatting plt.title('c) Reef Flat Width') plt.xlabel('Width (m)') plt.ylabel('Density') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() #plt.savefig('DensityFP_rfwidth.png',dpi=600) #%% density functions for the width measurements - lagoon reef width df = df2.copy() s2 = 'bins ac' s1 = 'lagoon reef width' #Draw the density plot linecolor = oranges fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) sns.distplot(df[df[s2] == 'North'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(5), label = 'North') sns.distplot(df[df[s2] == 'East'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(4), label = 'East') sns.distplot(df[df[s2] == 'South'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(3), label = 'South') sns.distplot(df[df[s2] == 'West'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(2), label = 'West') # Plot formatting plt.title('d) Motu Width') plt.xlabel('Width (m)') plt.ylabel('Density') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() #plt.savefig('DensityFP_motulagoonwidth.png',dpi=600) #%% density functions for the width measurements - ocean reef width df = df2.copy() s2 = 'bins ac' s1 = 'ocean reef width' #Draw the density plot linecolor = purples fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) sns.distplot(df[df[s2] == 'North'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(5), label = 'North') sns.distplot(df[df[s2] == 'East'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(4), label = 'East') sns.distplot(df[df[s2] == 'South'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(3), label = 'South') sns.distplot(df[df[s2] == 'West'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(2), label = 'West') # Plot formatting plt.title('e) Ocean Reef Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() #plt.savefig('DensityFP_motuoceanwidth.png',dpi=600) #%% density functions for the width measurements - effective reef width df = df3.copy() s1 = 'reef flat width' s2 = 'bins ac' s1 = 'effective reef flat width' #df = df_motu[df_motu['motu length'] > 1000].copy() # df = df2.copy() # s1 = 'ocean reef width' # s1 = 'lagoon reef width' # s1 = 'motu width' #Draw the density plot linecolor = greens fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) sns.distplot(df[df[s2] == 'North'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(5), label = 'North') sns.distplot(df[df[s2] == 'East'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(4), label = 'East') sns.distplot(df[df[s2] == 'South'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(3), label = 'South') sns.distplot(df[df[s2] == 'West'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, color = linecolor(2), label = 'West') # Plot formatting #plt.legend(prop={'size': 12}, title = s1) plt.title('f) Effective Reef Flat Width') plt.xlabel('Width (m)') plt.ylabel('Density') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.xlim([0, 2000]) plt.ylim([0,.013]) plt.yticks(np.arange(0,.015,step=.003)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() #plt.savefig('DensityFP_effectiverw.png',dpi=600) #%% density functions for the width measurements - all atolls - df2=df2all.copy() df3=df3all.copy() blues = plt.get_cmap('Blues',6) purples = plt.get_cmap('Purples',6) reds = plt.get_cmap('Reds',6) oranges = plt.get_cmap('Oranges',6) greens = plt.get_cmap('Greens',6) fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) lineW = 2 # Draw the density plot sns.distplot(df2['motu width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'motu width', color = reds(4)) sns.distplot(df3['reef flat width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'reef flat width', color = blues(4)) sns.distplot(df2['lagoon reef width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'lagoon reef width', color = oranges(4)) sns.distplot(df2['ocean reef width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'ocean reef width', color = purples(4)) sns.distplot(df3['effective reef flat width'], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'effective reef flat width', color = greens(4)) # Plot formatting plt.legend(prop={'size': 12}, title = 'Widths') plt.title('a) All Atolls Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') leg = plt.legend() leg.get_frame().set_linewidth(0.0) plt.tight_layout() #plt.savefig('DensityAll_AllWidths.png',dpi=600) #%% density functions for the width measurements - all atolls - motu width df = df2.copy() s1 = 'motu width' s2 = 'bins abs latitude' linecolor = reds fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) # Draw the density plot sns.distplot(df[df[s2] == 'low'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW},bins=int(2000), label = 'equatorial',color = linecolor(5)) sns.distplot(df[df[s2] == 'mid'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'mid tropical',color = linecolor(4)) sns.distplot(df[df[s2] == 'high'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'high tropical',color = linecolor(3)) # Plot formatting plt.legend(prop={'size': 12}, title = s1) plt.title('b) Motu Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() leg = plt.legend() leg.get_frame().set_linewidth(0.0) #plt.savefig('DensityAll_MotuWidths.png',dpi=600) #%% density functions for the width measurements - all atolls - reef total width df = df3.copy() s1 = 'reef flat width' s2 = 'bins abs latitude' linecolor = blues fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) # Draw the density plot sns.distplot(df[df[s2] == 'low'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW},bins=int(2000), label = 'equatorial',color = linecolor(5)) sns.distplot(df[df[s2] == 'mid'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'mid tropical',color = linecolor(4)) sns.distplot(df[df[s2] == 'high'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'high tropical',color = linecolor(3)) # Plot formatting plt.legend(prop={'size': 12}, title = s1) plt.title('c) Reef Flat Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() leg = plt.legend() leg.get_frame().set_linewidth(0.0) #plt.savefig('DensityAll_AllReefTotalWidths.png',dpi=600) #%% density functions for the width measurements - all atolls - lagoon reef width df = df2.copy() s1 = 'lagoon reef width' s2 = 'bins abs latitude' linecolor = oranges fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) # Draw the density plot sns.distplot(df[df[s2] == 'low'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW},bins=int(2000), label = 'equatorial',color = linecolor(5)) sns.distplot(df[df[s2] == 'mid'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'mid tropical',color = linecolor(4)) sns.distplot(df[df[s2] == 'high'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'high tropical',color = linecolor(3)) # Plot formatting plt.legend(prop={'size': 12}, title = s1) plt.title('d) Lagoon Reef Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() leg = plt.legend() leg.get_frame().set_linewidth(0.0) #plt.savefig('DensityAll_LagoonReefWidths.png',dpi=600) #%% density functions for the width measurements - all atolls - ocean reef width df = df2.copy() s1 = 'ocean reef width' s2 = 'bins abs latitude' linecolor = purples fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) # Draw the density plot sns.distplot(df[df[s2] == 'low'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW},bins=int(2000), label = 'equatorial',color = linecolor(5)) sns.distplot(df[df[s2] == 'mid'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'mid tropical',color = linecolor(4)) sns.distplot(df[df[s2] == 'high'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'high tropical',color = linecolor(3)) # Plot formatting plt.legend(prop={'size': 12}, title = s1) plt.title('e) Ocean Reef Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() leg = plt.legend() leg.get_frame().set_linewidth(0.0) #plt.savefig('DensityAll_OceanReefWidths.png',dpi=600) #%% density functions for the width measurements - all atolls - effective width df = df3.copy() s1 = 'effective reef flat width' s2 = 'bins abs latitude' linecolor = greens fig_dims = (4.5, 4) fig, ax = plt.subplots(figsize=fig_dims) # Draw the density plot sns.distplot(df[df[s2] == 'low'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW},bins=int(2000), label = 'equatorial',color = linecolor(5)) sns.distplot(df[df[s2] == 'mid'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'mid tropical',color = linecolor(4)) sns.distplot(df[df[s2] == 'high'][s1], hist = False, kde = True, kde_kws = {'linewidth': lineW}, label = 'high tropical',color = linecolor(3)) # Plot formatting plt.legend(prop={'size': 12}, title = s1) plt.title('f) Effective Reef Flat Width') plt.xlabel('Width (m)') plt.ylabel('Density') plt.xlim([0, 2000]) plt.ylim([0,.008]) plt.yticks(np.arange(0,.008,step=.0025)) plt.xticks(np.arange(0,2000,step=500)) plt.tick_params(axis='both',which='major',width=2,length=7,direction='in') plt.tight_layout() leg = plt.legend() leg.get_frame().set_linewidth(0.0) #plt.savefig('DensityAll_EffectivereefWidths.png',dpi=600) #%% calc. critical reef-flat widths for diff groups def calcCritWidth(df,s1,s2,l,s3,border): '''takes a dataframe, the two strings to iterate over, and the length to calc above, plus the bin order returns a dataframe with rows for each bin then each column: mean, std, number/count, %count, total''' aa = df[df[s1]>l][s2].agg(['mean','std','count']) aa['total count'] = df.count().max() aa['percent count'] = aa['count']/aa['total count'] * 100 df2 = pd.DataFrame([aa],index=['all']) for i in df[s3].dropna().unique(): aa2 = df[(df[s3]==i) & (df[s1]>l)][s2].agg(['mean','std','count']) aa2['total count'] = df[df[s3]==i].count().max() #find total motu in given bin aa2['percent count'] = aa2['count']/aa2['total count'] * 100 aa2.name=i df2 = df2.append([aa2]) df2['length'] = l df2 = df2.reindex(border) return df2 dfnewlong = calcCritWidth(df_merged,'motu length (m)','mean ocean reef width (m)',10000,'bins abs latitude',['low','mid','high','all']) dfnew = calcCritWidth(df_merged,'motu length (m)','mean ocean reef width (m)',1000,'bins abs latitude',['low','mid','high','all']) dfNew = dfnew.append(dfnewlong) #now calc. for normalized values dfnew = calcCritWidth(df_merged,'motu length / reef-flat length','motu-reef-flat-dist / reef-flat width',.1,'bins abs latitude',['low','mid','high','all']) dfnewl = calcCritWidth(df_merged,'motu length / reef-flat length','motu-reef-flat-dist / reef-flat width',.25,'bins abs latitude',['low','mid','high','all']) dfNewNorm = dfnew.append(dfnewl) #%% #df_mergedFP = df_merged #if you've reset way back in the beginning #%% # dfpnew = calcCritWidth(df_mergedFP,'motu length (m)','mean ocean reef width (m)',0,'directional bin',['North','East','South','West','all']) # dfpnewl = calcCritWidth(df_mergedFP,'motu length (m)','mean ocean reef width (m)',10000,'directional bin',['North','East','South','West','all']) # dfNewfp = dfpnew.append(dfpnewl) # #now calc. for normalized values # dfnew = calcCritWidth(df_mergedFP,'motu length / reef-flat length','motu-reef-flat-dist / reef-flat width',.1,'directional bin',['North','East','South','West','all']) # dfnewl = calcCritWidth(df_mergedFP,'motu length / reef-flat length','motu-reef-flat-dist / reef-flat width',.25,'directional bin',['North','East','South','West','all']) # dfNewNormFP = dfnew.append(dfnewl) # #export these tables to excel # # Create some Pandas dataframes from some data. # with pd.ExcelWriter('SummaryCriticalReefFlatWidth.xlsx') as writer: # workbook=writer.book # worksheet=workbook.add_worksheet('All Motu') # writer.sheets['All Motu'] = worksheet # worksheet.write_string(0, 0, 'Totals critical reef flat width (m)') # dfNew.to_excel(writer, sheet_name='All Motu', startrow = 1) # worksheet.write_string(13,0,'Normalized') # dfNewNorm.to_excel(writer, sheet_name='All Motu', startrow = 14) # worksheet=workbook.add_worksheet('FP Motu') # writer.sheets['FP Motu'] = worksheet # worksheet.write_string(0, 0, 'Totals critical reef flat width (m)') # dfNewfp.to_excel(writer, sheet_name='FP Motu', startrow = 1) # worksheet.write_string(13,0,'Normalized') # dfNewNormFP.to_excel(writer, sheet_name='FP Motu', startrow = 14)

46.773568

549

0.644948

7,979

53,088

4.200276

0.061787

0.041057

0.026765

0.021484

0.840127

0.809841

0.775497

0.746255

0.714418

0.691144

0

0.04357

0.168192

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1,134

550

46.814815

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null

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1

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null

0

7

d3da69d90442b17ea4483257426d455f8cbc0b5a

9,465

py

Python

tests/providers/hashicorp/secrets/test_vault.py

mebelousov/airflow

d99833c9b5be9eafc0c7851343ee86b6c20aed40

[ "Apache-2.0" ]

2

2021-07-30T17:35:51.000Z

2021-08-03T13:50:57.000Z

tests/providers/hashicorp/secrets/test_vault.py

mebelousov/airflow

d99833c9b5be9eafc0c7851343ee86b6c20aed40

[ "Apache-2.0" ]

9

2021-02-08T20:50:21.000Z

2022-03-29T22:29:28.000Z

tests/providers/hashicorp/secrets/test_vault.py

mebelousov/airflow

d99833c9b5be9eafc0c7851343ee86b6c20aed40

[ "Apache-2.0" ]

1

2020-04-25T00:31:39.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from unittest import TestCase, mock from hvac.exceptions import InvalidPath, VaultError from airflow.providers.hashicorp.secrets.vault import VaultBackend class TestVaultSecrets(TestCase): @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_conn_uri(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client mock_client.secrets.kv.v2.read_secret_version.return_value = { 'request_id': '94011e25-f8dc-ec29-221b-1f9c1d9ad2ae', 'lease_id': '', 'renewable': False, 'lease_duration': 0, 'data': { 'data': {'conn_uri': 'postgresql://airflow:airflow@host:5432/airflow'}, 'metadata': {'created_time': '2020-03-16T21:01:43.331126Z', 'deletion_time': '', 'destroyed': False, 'version': 1}}, 'wrap_info': None, 'warnings': None, 'auth': None } kwargs = { "connections_path": "connections", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS" } test_client = VaultBackend(**kwargs) returned_uri = test_client.get_conn_uri(conn_id="test_postgres") self.assertEqual('postgresql://airflow:airflow@host:5432/airflow', returned_uri) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_conn_uri_engine_version_1(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client mock_client.secrets.kv.v1.read_secret.return_value = { 'request_id': '182d0673-618c-9889-4cba-4e1f4cfe4b4b', 'lease_id': '', 'renewable': False, 'lease_duration': 2764800, 'data': {'conn_uri': 'postgresql://airflow:airflow@host:5432/airflow'}, 'wrap_info': None, 'warnings': None, 'auth': None} kwargs = { "connections_path": "connections", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS", "kv_engine_version": 1 } test_client = VaultBackend(**kwargs) returned_uri = test_client.get_conn_uri(conn_id="test_postgres") mock_client.secrets.kv.v1.read_secret.assert_called_once_with( mount_point='airflow', path='connections/test_postgres') self.assertEqual('postgresql://airflow:airflow@host:5432/airflow', returned_uri) @mock.patch.dict('os.environ', { 'AIRFLOW_CONN_TEST_MYSQL': 'mysql://airflow:airflow@host:5432/airflow', }) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_conn_uri_non_existent_key(self, mock_hvac): """ Test that if the key with connection ID is not present in Vault, VaultClient.get_connections should return None """ mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client # Response does not contain the requested key mock_client.secrets.kv.v2.read_secret_version.side_effect = InvalidPath() kwargs = { "connections_path": "connections", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS" } test_client = VaultBackend(**kwargs) self.assertIsNone(test_client.get_conn_uri(conn_id="test_mysql")) mock_client.secrets.kv.v2.read_secret_version.assert_called_once_with( mount_point='airflow', path='connections/test_mysql') self.assertEqual([], test_client.get_connections(conn_id="test_mysql")) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_variable_value(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client mock_client.secrets.kv.v2.read_secret_version.return_value = { 'request_id': '2d48a2ad-6bcb-e5b6-429d-da35fdf31f56', 'lease_id': '', 'renewable': False, 'lease_duration': 0, 'data': {'data': {'value': 'world'}, 'metadata': {'created_time': '2020-03-28T02:10:54.301784Z', 'deletion_time': '', 'destroyed': False, 'version': 1}}, 'wrap_info': None, 'warnings': None, 'auth': None } kwargs = { "variables_path": "variables", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS" } test_client = VaultBackend(**kwargs) returned_uri = test_client.get_variable("hello") self.assertEqual('world', returned_uri) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_variable_value_engine_version_1(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client mock_client.secrets.kv.v1.read_secret.return_value = { 'request_id': '182d0673-618c-9889-4cba-4e1f4cfe4b4b', 'lease_id': '', 'renewable': False, 'lease_duration': 2764800, 'data': {'value': 'world'}, 'wrap_info': None, 'warnings': None, 'auth': None} kwargs = { "variables_path": "variables", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS", "kv_engine_version": 1 } test_client = VaultBackend(**kwargs) returned_uri = test_client.get_variable("hello") mock_client.secrets.kv.v1.read_secret.assert_called_once_with( mount_point='airflow', path='variables/hello') self.assertEqual('world', returned_uri) @mock.patch.dict('os.environ', { 'AIRFLOW_VAR_HELLO': 'world', }) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_get_variable_value_non_existent_key(self, mock_hvac): """ Test that if the key with connection ID is not present in Vault, VaultClient.get_connections should return None """ mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client # Response does not contain the requested key mock_client.secrets.kv.v2.read_secret_version.side_effect = InvalidPath() kwargs = { "variables_path": "variables", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "s.7AU0I51yv1Q1lxOIg1F3ZRAS" } test_client = VaultBackend(**kwargs) self.assertIsNone(test_client.get_variable("hello")) mock_client.secrets.kv.v2.read_secret_version.assert_called_once_with( mount_point='airflow', path='variables/hello') self.assertIsNone(test_client.get_variable("hello")) @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_auth_failure_raises_error(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client mock_client.is_authenticated.return_value = False kwargs = { "connections_path": "connections", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", "token": "test_wrong_token" } with self.assertRaisesRegex(VaultError, "Vault Authentication Error!"): VaultBackend(**kwargs).get_connections(conn_id='test') @mock.patch("airflow.providers.hashicorp.secrets.vault.hvac") def test_empty_token_raises_error(self, mock_hvac): mock_client = mock.MagicMock() mock_hvac.Client.return_value = mock_client kwargs = { "connections_path": "connections", "mount_point": "airflow", "auth_type": "token", "url": "http://127.0.0.1:8200", } with self.assertRaisesRegex(VaultError, "token cannot be None for auth_type='token'"): VaultBackend(**kwargs).get_connections(conn_id='test')

40.276596

100

0.612995

1,051

9,465

5.295909

0.196004

0.048509

0.032699

0.034136

0.801833

0.774883

0.759792

0.732663

0.698347

0

0.042816

0.264659

9,465

234

101

40.448718

0.756897

0.11252

0

0.782123

0

0.290024

0.122236

0

0.078212

1

0.044693

false

0

0.01676

0

0.067039

0

null

0

1

0

1

0

null

0

7

310aea93d0d69f387e4434778f4e7d8617e60503

3,834

py

Python

scipy/linalg/benchmarks/bench_basic.py

lesserwhirls/scipy-cwt

ee673656d879d9356892621e23ed0ced3d358621

[ "BSD-3-Clause" ]

8

2015-10-07T00:37:32.000Z

2022-01-21T17:02:33.000Z

scipy/linalg/benchmarks/bench_basic.py

lesserwhirls/scipy-cwt

ee673656d879d9356892621e23ed0ced3d358621

[ "BSD-3-Clause" ]

null

scipy/linalg/benchmarks/bench_basic.py

lesserwhirls/scipy-cwt

ee673656d879d9356892621e23ed0ced3d358621

[ "BSD-3-Clause" ]

8

2015-05-09T14:23:57.000Z

2018-11-15T05:56:00.000Z

import sys from numpy.testing import * import numpy.linalg as linalg def random(size): return rand(*size) class TestSolve(TestCase): def bench_random(self): basic_solve = linalg.solve print print ' Solving system of linear equations' print ' ==================================' print ' | contiguous | non-contiguous ' print '----------------------------------------------' print ' size | scipy | basic | scipy | basic ' for size,repeat in [(20,1000),(100,150),(500,2),(1000,1)][:-1]: repeat *= 2 print '%5s' % size, sys.stdout.flush() a = random([size,size]) # larger diagonal ensures non-singularity: for i in range(size): a[i,i] = 10*(.1+a[i,i]) b = random([size]) print '| %6.2f ' % measure('solve(a,b)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_solve(a,b)',repeat), sys.stdout.flush() a = a[-1::-1,-1::-1] # turn into a non-contiguous array assert not a.flags['CONTIGUOUS'] print '| %6.2f ' % measure('solve(a,b)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_solve(a,b)',repeat), sys.stdout.flush() print ' (secs for %s calls)' % (repeat) class TestInv(TestCase): def bench_random(self): basic_inv = linalg.inv print print ' Finding matrix inverse' print ' ==================================' print ' | contiguous | non-contiguous ' print '----------------------------------------------' print ' size | scipy | basic | scipy | basic' for size,repeat in [(20,1000),(100,150),(500,2),(1000,1)][:-1]: repeat *= 2 print '%5s' % size, sys.stdout.flush() a = random([size,size]) # large diagonal ensures non-singularity: for i in range(size): a[i,i] = 10*(.1+a[i,i]) print '| %6.2f ' % measure('inv(a)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_inv(a)',repeat), sys.stdout.flush() a = a[-1::-1,-1::-1] # turn into a non-contiguous array assert not a.flags['CONTIGUOUS'] print '| %6.2f ' % measure('inv(a)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_inv(a)',repeat), sys.stdout.flush() print ' (secs for %s calls)' % (repeat) class TestDet(TestCase): def bench_random(self): basic_det = linalg.det print print ' Finding matrix determinant' print ' ==================================' print ' | contiguous | non-contiguous ' print '----------------------------------------------' print ' size | scipy | basic | scipy | basic ' for size,repeat in [(20,1000),(100,150),(500,2),(1000,1)][:-1]: repeat *= 2 print '%5s' % size, sys.stdout.flush() a = random([size,size]) print '| %6.2f ' % measure('det(a)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_det(a)',repeat), sys.stdout.flush() a = a[-1::-1,-1::-1] # turn into a non-contiguous array assert not a.flags['CONTIGUOUS'] print '| %6.2f ' % measure('det(a)',repeat), sys.stdout.flush() print '| %6.2f ' % measure('basic_det(a)',repeat), sys.stdout.flush() print ' (secs for %s calls)' % (repeat) if __name__ == "__main__": run_module_suite()

31.170732

71

0.454095

422

3,834

4.07346

0.182464

0.078534

0.122164

0.104712

0.827225

0.824898

0.770797

0

0.044988

0.339071

3,834

122

72

31.42623

0.633386

0.046688

0

0.8

0

0.265004

0.065771

0

0.035294

0

null

0

0.035294

null

0.423529

0

null

0

1

0

1

0

null

0

1

0

1

0

9

312f8746cafddc61eb8242db8c665e19e51638cf

8,949

py

Python

teaser/data/input/lca_data_input.py

linuscuy/TEASER

5bba638a6df0dd9c41de9036d42490c24497e04b

[ "MIT" ]

null

teaser/data/input/lca_data_input.py

linuscuy/TEASER

5bba638a6df0dd9c41de9036d42490c24497e04b

[ "MIT" ]

null

teaser/data/input/lca_data_input.py

linuscuy/TEASER

5bba638a6df0dd9c41de9036d42490c24497e04b

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Wed Oct 13 17:25:24 2021 @author: Linus """ from teaser.logic.buildingobjects.buildingphysics.en15804indicatorvalue import En15804IndicatorValue def load_en15804_lca_data_id(lca_data, lca_id, data_class): """LCA-data loader with id as identification. Loads LCA-data specified in the JSON by given LCA-ID. Parameters ---------- lca_data : En15804MainLcaData() instance of TEASERS En15804nLcaData class lca_id : str id of LCA-data from JSON data_class : DataClass() DataClass containing the bindings for En15804MainLcaData, TypeBuildingElement and Material (typically this is the data class stored in prj.data, but the user can individually change that. """ binding = data_class.lca_data_bind for id, data in binding.items(): if id != "version": if id == lca_id: lca_data.lca_data_id = id lca_data.name = data["name"] lca_data.ref_flow_value = data["ref_flow"]["value"] lca_data.ref_flow_unit = data["ref_flow"]["unit"] pere = En15804IndicatorValue() pert = En15804IndicatorValue() penre = En15804IndicatorValue() penrm = En15804IndicatorValue() penrt = En15804IndicatorValue() sm = En15804IndicatorValue() rsf = En15804IndicatorValue() nrsf = En15804IndicatorValue() fw = En15804IndicatorValue() hwd = En15804IndicatorValue() nhwd = En15804IndicatorValue() rwd = En15804IndicatorValue() cru = En15804IndicatorValue() mfr = En15804IndicatorValue() mer = En15804IndicatorValue() eee = En15804IndicatorValue() eet = En15804IndicatorValue() gwp = En15804IndicatorValue() odp = En15804IndicatorValue() pocp = En15804IndicatorValue() ap = En15804IndicatorValue() ep = En15804IndicatorValue() adpe = En15804IndicatorValue() adpf = En15804IndicatorValue() pere.set_values(**data["pere"]) pert.set_values(**data["pert"]) penre.set_values(**data["penre"]) penrm.set_values(**data["penrm"]) penrt.set_values(**data["penrt"]) sm.set_values(**data["sm"]) rsf.set_values(**data["rsf"]) nrsf.set_values(**data["nrsf"]) fw.set_values(**data["fw"]) hwd.set_values(**data["hwd"]) nhwd.set_values(**data["nhwd"]) rwd.set_values(**data["rwd"]) cru.set_values(**data["cru"]) mfr.set_values(**data["mfr"]) mer.set_values(**data["mer"]) eee.set_values(**data["eee"]) eet.set_values(**data["eet"]) gwp.set_values(**data["gwp"]) odp.set_values(**data["odp"]) pocp.set_values(**data["pocp"]) ap.set_values(**data["ap"]) ep.set_values(**data["ep"]) adpe.set_values(**data["adpe"]) adpf.set_values(**data["adpf"]) lca_data.pere = pere lca_data.pert = pert lca_data.penre = penre lca_data.penrm = penrm lca_data.penrt = penrt lca_data.sm = sm lca_data.rsf = rsf lca_data.nrsf = nrsf lca_data.fw = fw lca_data.hwd = hwd lca_data.nhwd = nhwd lca_data.rwd = rwd lca_data.cru = cru lca_data.mfr = mfr lca_data.mer = mer lca_data.eee = eee lca_data.eet = eet lca_data.gwp = gwp lca_data.odp = odp lca_data.pocp = pocp lca_data.ap = ap lca_data.ep = ep lca_data.adpe = adpe lca_data.adpf = adpf if data["fallback"]: lca_data.load_fallbacks(data["fallback"], data_class) lca_data.add_fallbacks() else: lca_data.fallback = [] def load_en15804_lca_data_fallback_id(lca_data, lca_id, data_class): """LCA-data-fallback loader with id as identification. Loads LCA-data-fallbacks specified in the JSON by given LCA-ID. LCA-fallbacks are specified in an seperated JSON-file to clarify they are just partial defined. Parameters ---------- lca_data : En15804MainLcaData() instance of TEASERS En15804nLcaData class lca_id : str id of LCA-data from JSON data_class : DataClass() DataClass containing the bindings for En15804MainLcaData, TypeBuildingElement and Material (typically this is the data class stored in prj.data, but the user can individually change that. """ binding = data_class.lca_data_fallback_bind for id, data in binding.items(): if id != "version": if id == lca_id: lca_data.lca_data_id = id lca_data.name = data["name"] lca_data.ref_flow_value = data["ref_flow"]["value"] lca_data.ref_flow_unit = data["ref_flow"]["unit"] pere = En15804IndicatorValue() pert = En15804IndicatorValue() penre = En15804IndicatorValue() penrm = En15804IndicatorValue() penrt = En15804IndicatorValue() sm = En15804IndicatorValue() rsf = En15804IndicatorValue() nrsf = En15804IndicatorValue() fw = En15804IndicatorValue() hwd = En15804IndicatorValue() nhwd = En15804IndicatorValue() rwd = En15804IndicatorValue() cru = En15804IndicatorValue() mfr = En15804IndicatorValue() mer = En15804IndicatorValue() eee = En15804IndicatorValue() eet = En15804IndicatorValue() gwp = En15804IndicatorValue() odp = En15804IndicatorValue() pocp = En15804IndicatorValue() ap = En15804IndicatorValue() ep = En15804IndicatorValue() adpe = En15804IndicatorValue() adpf = En15804IndicatorValue() pere.set_values(**data["pere"]) pert.set_values(**data["pert"]) penre.set_values(**data["penre"]) penrm.set_values(**data["penrm"]) penrt.set_values(**data["penrt"]) sm.set_values(**data["sm"]) rsf.set_values(**data["rsf"]) nrsf.set_values(**data["nrsf"]) fw.set_values(**data["fw"]) hwd.set_values(**data["hwd"]) nhwd.set_values(**data["nhwd"]) rwd.set_values(**data["rwd"]) cru.set_values(**data["cru"]) mfr.set_values(**data["mfr"]) mer.set_values(**data["mer"]) eee.set_values(**data["eee"]) eet.set_values(**data["eet"]) gwp.set_values(**data["gwp"]) odp.set_values(**data["odp"]) pocp.set_values(**data["pocp"]) ap.set_values(**data["ap"]) ep.set_values(**data["ep"]) adpe.set_values(**data["adpe"]) adpf.set_values(**data["adpf"]) lca_data.pere = pere lca_data.pert = pert lca_data.penre = penre lca_data.penrm = penrm lca_data.penrt = penrt lca_data.sm = sm lca_data.rsf = rsf lca_data.nrsf = nrsf lca_data.fw = fw lca_data.hwd = hwd lca_data.nhwd = nhwd lca_data.rwd = rwd lca_data.cru = cru lca_data.mfr = mfr lca_data.mer = mer lca_data.eee = eee lca_data.eet = eet lca_data.gwp = gwp lca_data.odp = odp lca_data.pocp = pocp lca_data.ap = ap lca_data.ep = ep lca_data.adpe = adpe lca_data.adpf = adpf lca_data.fallback = None

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100

0.496368

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5.083037

0.136418

0.124154

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null

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1

0

null

0

7

730fc86cfbe27424ed8ec8a7561ebe7a5fd4738d

583

py

Python

scripts/vault/bypass_constructor.py

yogeshprabhu/Ansible-inventory-file-examples

4bf6547f02b54c9d5ffedae7efdc407f08174dad

[ "MIT" ]

25

2017-10-17T07:09:11.000Z

2021-06-18T20:39:18.000Z

scripts/vault/bypass_constructor.py

yogeshprabhu/Ansible-inventory-file-examples

4bf6547f02b54c9d5ffedae7efdc407f08174dad

[ "MIT" ]

1

2019-10-25T14:50:33.000Z

2019-10-25T14:50:40.000Z

scripts/vault/bypass_constructor.py

yogeshprabhu/Ansible-inventory-file-examples

4bf6547f02b54c9d5ffedae7efdc407f08174dad

[ "MIT" ]

20

2017-11-03T15:02:38.000Z

2022-03-08T22:18:48.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- print """_meta: hostvars: foobar: should_be_artemis_here: !vault | $ANSIBLE_VAULT;1.2;AES256;alan 30386264646430643536336230313232653130643332356531633437363837323430663031356364 3836313935643038306263613631396136663634613066650a303838613532313236663966343433 37636234366130393131616631663831383237653761373533363666303361333662373664336261 6136313463383061330a633835643434616562633238383530356632336664316366376139306135 3534 ungrouped: hosts: - foobar"""

32.388889

90

0.763293

30

583

14.666667

0.933333

0

0.68476

0.178388

583

17

91

34.294118

0.23382

0.072041

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0.96846

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0

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null

0.076923

0

1

null

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0

1

0

1

null

1

0

1

0

7

733427acf231433358d1b236f98a5d2fc968c65f

8,214

py

Python

numba_stream/grid_test.py

jackd/numba-stream

79a12616a4a5b3107d8e9c17dc98cdeb79b2430a

[ "Apache-2.0" ]

null

numba_stream/grid_test.py

jackd/numba-stream

79a12616a4a5b3107d8e9c17dc98cdeb79b2430a

[ "Apache-2.0" ]

null

numba_stream/grid_test.py

jackd/numba-stream

79a12616a4a5b3107d8e9c17dc98cdeb79b2430a

[ "Apache-2.0" ]

null

import unittest import numpy as np import numba_stream.grid as grid class GridTest(unittest.TestCase): # def test_neighbor_offsets(self): # actual = grid.neighbor_offsets(np.array((3,))) # expected = [[-1], [0], [1]] # np.testing.assert_equal(actual, expected) # actual = grid.neighbor_offsets(np.array((2, 3))) # expected = np.stack(np.meshgrid(np.arange(2), # np.arange(3) - 1, # indexing='ij'), # axis=-1).reshape((6, 2)) # np.testing.assert_equal(actual, expected) # actual = grid.neighbor_offsets(np.array((2, 2))) # np.testing.assert_equal(actual, [[0, 0], [0, 1], [1, 0], [1, 1]]) # actual = grid.neighbor_offsets(np.array((3, 3))) # np.testing.assert_equal(actual, [ # [-1, -1], # [-1, 0], # [-1, 1], # [0, -1], # [0, 0], # [0, 1], # [1, -1], # [1, 0], # [1, 1], # ]) def test_ravel_multi_index(self): dims = (5, 6, 7) size = 100 indices = tuple(np.random.randint(0, d, size=size) for d in dims) actual = grid.ravel_multi_index(indices, dims) expected = np.ravel_multi_index(indices, dims) np.testing.assert_equal(actual, expected) def test_ravel_multi_index_transpose(self): dims = (5, 6, 7) size = 100 indices = tuple(np.random.randint(0, d, size=size) for d in dims) actual = grid.ravel_multi_index_transpose(np.stack(indices, axis=-1), dims) expected = np.ravel_multi_index(indices, dims) np.testing.assert_equal(actual, expected) def test_unravel_index(self): dims = (5, 6, 7) size = 100 indices = tuple(np.random.randint(0, d, size=size) for d in dims) ravelled = np.ravel_multi_index(indices, dims) # dims = (2, 3) # ravelled = np.array([1, 3, 5, 2]) actual = grid.unravel_index(ravelled, dims) expected = np.stack(np.unravel_index(ravelled, dims), axis=0) np.testing.assert_equal(actual, expected) def test_unravel_index_transpose(self): dims = (5, 6, 7) size = 100 indices = tuple(np.random.randint(0, d, size=size) for d in dims) ravelled = np.ravel_multi_index(indices, dims) # dims = (2, 3) # ravelled = np.array([1, 3, 5, 2]) actual = grid.unravel_index_transpose(ravelled, dims) expected = np.stack(np.unravel_index(ravelled, dims), axis=-1) np.testing.assert_equal(actual, expected) def test_base_grid_coords(self): np.testing.assert_equal( grid.base_grid_coords(np.array((3, 4))), [ [0, 0], [0, 1], [0, 2], [0, 3], [1, 0], [1, 1], [1, 2], [1, 3], [2, 0], [2, 1], [2, 2], [2, 3], ], ) def test_grid_coords(self): coords, shape = grid.grid_coords( in_shape=np.array([5]), kernel_shape=np.array([3]), strides=np.array([1]), padding=np.array([0]), ) np.testing.assert_equal(shape, (3,)) np.testing.assert_equal(coords, np.expand_dims([0, 1, 2], axis=-1)) def test_strided_grid_coords(self): coords, shape = grid.grid_coords( in_shape=np.array([5]), kernel_shape=np.array([3]), strides=np.array([2]), padding=np.array([0]), ) np.testing.assert_equal(shape, (2,)) np.testing.assert_equal(coords, np.expand_dims([0, 2], axis=-1)) def test_padded_grid_coords(self): coords, shape = grid.grid_coords( in_shape=np.array([5]), kernel_shape=np.array([3]), strides=np.array([1]), padding=np.array([1]), ) np.testing.assert_equal(shape, (5,)) np.testing.assert_equal(coords, np.expand_dims([-1, 0, 1, 2, 3], axis=-1)) def test_padded_strided_grid_coords(self): coords, shape = grid.grid_coords( in_shape=np.array([5]), kernel_shape=np.array([3]), strides=np.array([2]), padding=np.array([1]), ) np.testing.assert_equal(shape, (3,)) np.testing.assert_equal(coords, np.expand_dims([-1, 1, 3], axis=-1)) def test_even_grid_coords(self): coords, shape = grid.grid_coords( in_shape=np.array([4]), kernel_shape=np.array([3]), strides=np.array([2]), padding=np.array([1]), ) np.testing.assert_equal(shape, (2,)) np.testing.assert_equal(coords, np.expand_dims([-1, 1], axis=-1)) def test_sparse_neighborhood_1d(self): in_shape = np.array((7,)) kernel_shape = np.array((3,)) strides = np.array((2,)) padding = np.array((0,)) p, indices, splits, out_shape = grid.sparse_neighborhood( in_shape, kernel_shape, strides, padding=padding ) np.testing.assert_equal(out_shape, (3,)) np.testing.assert_equal(p, tuple(range(3)) * 3) np.testing.assert_equal(indices, [0, 1, 2, 2, 3, 4, 4, 5, 6]) np.testing.assert_equal(splits, [0, 3, 6, 9]) in_shape = np.array((7,)) kernel_shape = np.array((2,)) strides = np.array((2,)) padding = np.array((0,)) p, indices, splits, out_shape = grid.sparse_neighborhood( in_shape, kernel_shape, strides, padding=padding ) np.testing.assert_equal(out_shape, (3,)) np.testing.assert_equal(p, tuple(range(2)) * 3) np.testing.assert_equal(indices, [0, 1, 2, 3, 4, 5]) np.testing.assert_equal(splits, [0, 2, 4, 6]) def test_sparse_neighborhood(self): in_shape = np.array((4, 5), dtype=np.int64) kernel_shape = np.array((3, 3), dtype=np.int64) strides = np.array((2, 2), dtype=np.int64) padding = np.array((0, 0), dtype=np.int64) p, indices, splits, out_shape = grid.sparse_neighborhood( in_shape, kernel_shape, strides, padding=padding ) np.testing.assert_equal(out_shape, (1, 2)) np.testing.assert_equal(p, tuple(range(9)) * 2) np.testing.assert_equal( indices, [0, 1, 2, 5, 6, 7, 10, 11, 12, 2, 3, 4, 7, 8, 9, 12, 13, 14] ) np.testing.assert_equal(splits, [0, 9, 18]) def test_sparse_neighborhood_padded(self): in_shape = np.array((4, 5), dtype=np.int64) kernel_shape = np.array((3, 3), dtype=np.int64) strides = np.array((2, 2), dtype=np.int64) padding = np.array((1, 1), dtype=np.int64) p, indices, splits, out_shape = grid.sparse_neighborhood( in_shape, kernel_shape, strides, padding=padding ) np.testing.assert_equal(out_shape, (2, 3)) np.testing.assert_equal( p, (4, 5, 7, 8, 3, 4, 5, 6, 7, 8, 3, 4, 6, 7, 1, 2, 4, 5, 7, 8) + tuple(range(9)) + (0, 1, 3, 4, 6, 7), ) np.testing.assert_equal( indices, [ 0, 1, 5, 6, 1, 2, 3, 6, 7, 8, 3, 4, 8, 9, 5, 6, 10, 11, 15, 16, 6, 7, 8, 11, 12, 13, 16, 17, 18, 8, 9, 13, 14, 18, 19, ], ) np.testing.assert_equal(splits, [0, 4, 10, 14, 20, 29, 35]) if __name__ == "__main__": unittest.main() # GridTest().test_grid_coords()

33.255061

83

0.492695

1,036

8,214

3.753861

0.086873

0.077398

0.134996

0.179995

0.847776

0.812291

0.762407

0.729493

0.711237

0.665467

0

0.066412

0.362065

8,214

246

84

33.390244

0.675763

0.117117

0

0.53125

0

0.001108

0

0.161458

1

0.067708

false

0

0.015625

0

0.088542

0

null

0

1

0

null

0

7

734695cdfe43ddd8825c655221c557e8df2e81b0

33,684

py

Python

src/openprocurement/tender/limited/tests/cancellation_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

3

2020-03-13T06:44:23.000Z

2020-11-05T18:25:29.000Z

src/openprocurement/tender/limited/tests/cancellation_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

2

2021-03-25T23:29:58.000Z

2022-03-21T22:18:37.000Z

src/openprocurement/tender/limited/tests/cancellation_blanks.py

pontostroy/api

5afdd3a62a8e562cf77e2d963d88f1a26613d16a

[ "Apache-2.0" ]

3

2020-10-16T16:25:14.000Z

2021-05-22T12:26:20.000Z

# -*- coding: utf-8 -*- from mock import patch from datetime import timedelta from openprocurement.tender.core.utils import get_now from openprocurement.api.constants import RELEASE_2020_04_19 from openprocurement.tender.core.tests.cancellation import ( activate_cancellation_after_2020_04_19, ) from openprocurement.tender.belowthreshold.tests.base import test_organization, test_cancellation # TenderCancellationResourceTest def create_tender_cancellation_invalid(self): response = self.app.post_json( "/tenders/some_id/cancellations", {"data": test_cancellation}, status=404 ) self.assertEqual(response.status, "404 Not Found") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": u"Not Found", u"location": u"url", u"name": u"tender_id"}] ) request_path = "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token) response = self.app.post(request_path, "data", status=415) self.assertEqual(response.status, "415 Unsupported Media Type") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [ { u"description": u"Content-Type header should be one of ['application/json']", u"location": u"header", u"name": u"Content-Type", } ], ) response = self.app.post(request_path, "data", content_type="application/json", status=422) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": u"No JSON object could be decoded", u"location": u"body", u"name": u"data"}], ) response = self.app.post_json(request_path, "data", status=422) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": u"Data not available", u"location": u"body", u"name": u"data"}] ) response = self.app.post_json(request_path, {"not_data": {}}, status=422) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": u"Data not available", u"location": u"body", u"name": u"data"}] ) response = self.app.post_json(request_path, {"data": {}}, status=422) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": [u"This field is required."], u"location": u"body", u"name": u"reason"}], ) response = self.app.post_json(request_path, {"data": {"invalid_field": "invalid_value"}}, status=422) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["status"], "error") self.assertEqual( response.json["errors"], [{u"description": u"Rogue field", u"location": u"body", u"name": u"invalid_field"}] ) def create_tender_cancellation(self): response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": test_cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "active") response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": test_cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") first_cancellation = response.json["data"] self.assertEqual(first_cancellation["reason"], "cancellation reason") response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": test_cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") second_cancellation = response.json["data"] self.assertEqual(second_cancellation["reason"], "cancellation reason") if get_now() < RELEASE_2020_04_19: response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format( self.tender_id, second_cancellation["id"], self.tender_token ), {"data": {"status": "active"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "active") else: activate_cancellation_after_2020_04_19(self, second_cancellation["id"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "cancelled") response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": test_cancellation}, status=403, ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"][0]["description"], "Can't update tender in current (cancelled) status" ) def create_tender_cancellation_with_post(self): response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": test_cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "active") cancellation = dict(**test_cancellation) cancellation.update({ "status": "active" }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") if get_now() < RELEASE_2020_04_19: self.assertEqual(cancellation["status"], "active") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) else: self.assertEqual(cancellation["status"], "draft") activate_cancellation_after_2020_04_19(self, cancellation["id"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "cancelled") def create_cancellation_on_lot(self): """ Try create cancellation with cancellationOf = lot while tender hasn't lots """ cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", "relatedLot": "1" * 32 }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [ {u"location": u"body", u"name": u"relatedLot", u"description": [u"relatedLot should be one of lots"]}, { u"location": u"body", u"name": u"cancellationOf", u"description": [ u'Lot cancellation can not be submitted, since "multiple lots" option is not available for this type of tender.' ], }, ], ) # TenderNegotiationCancellationResourceTest def negotiation_create_cancellation_on_lot(self): """ Try create cancellation with cancellationOf = lot while tender hasn't lots """ cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", "relatedLot": "1" * 32 }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{u"description": [u"relatedLot should be one of lots"], u"location": u"body", u"name": u"relatedLot"}], ) # TenderNegotiationLotsCancellationResourceTest def create_tender_lots_cancellation(self): lot_id = self.initial_lots[0]["id"] cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", "relatedLot": lot_id }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["lots"][0]["status"], "active") self.assertEqual(response.json["data"]["status"], "active") cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", "relatedLot": lot_id, "status": "active" }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) if RELEASE_2020_04_19 > get_now(): self.assertEqual(cancellation["status"], "active") else: activate_cancellation_after_2020_04_19(self, cancellation["id"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["lots"][0]["status"], "cancelled") self.assertNotEqual(response.json["data"]["status"], "cancelled") cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", "relatedLot": lot_id, "status": "active" }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=403, ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["errors"][0]["description"], "Can perform cancellation only in active lot status") cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": self.initial_lots[1]["id"], }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) if RELEASE_2020_04_19 > get_now(): self.assertEqual(cancellation["status"], "active") else: activate_cancellation_after_2020_04_19(self, cancellation["id"]) response = self.app.get("/tenders/{}".format(self.tender_id)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["lots"][0]["status"], "cancelled") self.assertEqual(response.json["data"]["lots"][1]["status"], "cancelled") self.assertEqual(response.json["data"]["status"], "cancelled") def cancelled_lot_without_relatedLot(self): cancellation = dict(**test_cancellation) cancellation.update({ "cancellationOf": "lot", }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=422, ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{"location": "body", "name": "relatedLot", "description": ["This field is required."]}], ) def delete_first_lot_second_cancel(self): """ One lot we delete another cancel and check tender status """ self.app.patch_json( "/tenders/{}?acc_token={}".format(self.tender_id, self.tender_token), {"data": {"items": [{"relatedLot": self.initial_lots[1]["id"]}]}}, ) response = self.app.delete( "/tenders/{}/lots/{}?acc_token={}".format(self.tender_id, self.initial_lots[0]["id"], self.tender_token) ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") response = self.app.get("/tenders/{}/lots?acc_token={}".format(self.tender_id, self.tender_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(len(response.json["data"]), 1) cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": self.initial_lots[1]["id"], }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) if RELEASE_2020_04_19 > get_now(): self.assertEqual(cancellation["status"], "active") else: activate_cancellation_after_2020_04_19(self, cancellation["id"]) response = self.app.get("/tenders/{}?acc_token={}".format(self.tender_id, self.tender_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "cancelled") def cancel_tender(self): cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "tender", }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["reason"], "cancellation reason") if get_now() < RELEASE_2020_04_19: self.assertEqual(cancellation["status"], "active") self.assertIn("id", cancellation) self.assertIn(cancellation["id"], response.headers["Location"]) else: activate_cancellation_after_2020_04_19(self, cancellation["id"]) # Check tender response = self.app.get("/tenders/{}?acc_token={}".format(self.tender_id, self.tender_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "cancelled") # Check lots response = self.app.get("/tenders/{}/lots?acc_token={}".format(self.tender_id, self.tender_token)) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"][0]["status"], "active") self.assertEqual(response.json["data"][1]["status"], "active") def create_cancellation_on_tender_with_one_complete_lot(self): lot = self.initial_lots[0] # Create award response = self.app.post_json( "/tenders/{}/awards?acc_token={}".format(self.tender_id, self.tender_token), { "data": { "suppliers": [test_organization], "status": "pending", "qualified": True, "value": {"amount": 469, "currency": "UAH", "valueAddedTaxIncluded": True}, "lotID": lot["id"], } }, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.json["data"]["status"], "pending") # Activate award award = response.json["data"] response = self.app.patch_json( "/tenders/{}/awards/{}?acc_token={}".format(self.tender_id, award["id"], self.tender_token), {"data": {"status": "active"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") # time travel tender = self.db.get(self.tender_id) for i in tender.get("awards", []): if i.get("complaintPeriod", {}): # reporting procedure does not have complaintPeriod i["complaintPeriod"]["endDate"] = i["complaintPeriod"]["startDate"] self.db.save(tender) # Sign contract response = self.app.get("/tenders/{}/contracts".format(self.tender_id)) response = self.app.patch_json( "/tenders/{}/contracts/{}?acc_token={}".format( self.tender_id, response.json["data"][0]["id"], self.tender_token ), {"data": {"status": "active", "value": {"valueAddedTaxIncluded": False}}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.json["data"]["status"], "active") # Try to create cancellation on tender cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "tender", }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=403, ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"][0]["description"], "Can't perform cancellation, if there is at least one complete lot" ) def cancellation_on_not_active_lot(self): lot = self.initial_lots[0] # Create cancellation on lot with status cancelled cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": lot["id"], }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation_id = response.json["data"]["id"] if RELEASE_2020_04_19 < get_now(): activate_cancellation_after_2020_04_19(self, cancellation_id) # check lot status response = self.app.get("/tenders/{}/lots/{}".format(self.tender_id, lot["id"])) self.assertEqual(response.json["data"]["status"], "cancelled") # Try to create cancellation on lot with status cancelled cancellation = dict(**test_cancellation) cancellation.update({ "status": "active", "cancellationOf": "lot", "relatedLot": lot["id"], }) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation}, status=403, ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["errors"][0]["description"], "Can perform cancellation only in active lot status") @patch("openprocurement.tender.core.models.RELEASE_2020_04_19", get_now() - timedelta(days=1)) @patch("openprocurement.tender.core.views.cancellation.RELEASE_2020_04_19", get_now() - timedelta(days=1)) def create_tender_cancellation_2020_04_19(self): reasonType_choices = self.valid_reasonType_choices request_path = "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token) cancellation = dict(**test_cancellation) cancellation.update({"reasonType": reasonType_choices[0]}) response = self.app.post_json( request_path, {"data": cancellation} ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] cancellation_id = cancellation["id"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn("date", cancellation) self.assertEqual(cancellation["reasonType"], reasonType_choices[0]) self.assertEqual(cancellation["status"], "draft") self.assertIn(cancellation_id, response.headers["Location"]) cancellation = dict(**test_cancellation) cancellation.update({"reasonType": reasonType_choices[1]}) response = self.app.post_json( request_path, {"data": cancellation} ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] cancellation_id = cancellation["id"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn("date", cancellation) self.assertEqual(cancellation["reasonType"], reasonType_choices[1]) self.assertEqual(cancellation["status"], "draft") self.assertIn(cancellation_id, response.headers["Location"]) response = self.app.post( "/tenders/{}/cancellations/{}/documents?acc_token={}".format( self.tender_id, cancellation_id, self.tender_token ), upload_files=[("file", "name.doc", "content")], ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") request_path = "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token) response = self.app.patch_json( request_path, {"data": {"status": "pending"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["status"], "pending") @patch("openprocurement.tender.core.models.RELEASE_2020_04_19", get_now() - timedelta(days=1)) @patch("openprocurement.tender.core.validation.RELEASE_2020_04_19", get_now() - timedelta(days=1)) @patch("openprocurement.tender.core.views.cancellation.RELEASE_2020_04_19", get_now() - timedelta(days=1)) def patch_tender_cancellation_2020_04_19(self): reasonType_choices = self.valid_reasonType_choices cancellation = dict(**test_cancellation) cancellation.update({"reasonType": reasonType_choices[0]}) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation} ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] cancellation_id = cancellation["id"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn("date", cancellation) self.assertEqual(cancellation["reasonType"], reasonType_choices[0]) self.assertEqual(cancellation["status"], "draft") self.assertIn(cancellation_id, response.headers["Location"]) response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "pending"}}, status=422 ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Fields reason, cancellationOf and documents must be filled for switch cancellation to pending status", u"location": u"body", u"name": u"data", }] ) response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "active"}}, status=422 ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Cancellation can't be updated from draft to active status", u"location": u"body", u"name": u"data", }] ) response = self.app.post( "/tenders/{}/cancellations/{}/documents?acc_token={}".format( self.tender_id, cancellation_id, self.tender_token ), upload_files=[("file", "name.doc", "content")], ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") request_path = "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token) response = self.app.patch_json( request_path, {"data": {"status": "pending"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["status"], "pending") response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "draft"}}, status=422 ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Cancellation can't be updated from pending to draft status", u"location": u"body", u"name": u"data", }] ) response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "active"}}, status=422 ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Cancellation can't be updated from pending to active status", u"location": u"body", u"name": u"data", }] ) response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "unsuccessful"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "unsuccessful") response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": None}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") # self.assertEqual(response.json["data"]["status"], "unsuccessful") response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "pending"}}, status=422 ) self.assertEqual(response.status, "422 Unprocessable Entity") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Cancellation can't be updated from unsuccessful to pending status", u"location": u"body", u"name": u"data", }] ) cancellation = dict(**test_cancellation) cancellation.update({"reasonType": reasonType_choices[1]}) response = self.app.post_json( "/tenders/{}/cancellations?acc_token={}".format(self.tender_id, self.tender_token), {"data": cancellation} ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] cancellation_id = cancellation["id"] self.assertEqual(cancellation["reason"], "cancellation reason") self.assertIn("id", cancellation) self.assertIn("date", cancellation) self.assertEqual(cancellation["reasonType"], reasonType_choices[1]) self.assertEqual(cancellation["status"], "draft") self.assertIn(cancellation_id, response.headers["Location"]) response = self.app.post( "/tenders/{}/cancellations/{}/documents?acc_token={}".format( self.tender_id, cancellation_id, self.tender_token ), upload_files=[("file", "name.doc", "content")], ) self.assertEqual(response.status, "201 Created") self.assertEqual(response.content_type, "application/json") response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "pending"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") cancellation = response.json["data"] self.assertEqual(cancellation["status"], "pending") with patch( "openprocurement.tender.core.validation.get_now", return_value=get_now() + timedelta(days=20)) as mock_date: response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "active"}}, ) self.assertEqual(response.status, "200 OK") self.assertEqual(response.content_type, "application/json") self.assertEqual(response.json["data"]["status"], "active") response = self.app.patch_json( "/tenders/{}/cancellations/{}?acc_token={}".format(self.tender_id, cancellation_id, self.tender_token), {"data": {"status": "pending"}}, status=403 ) self.assertEqual(response.status, "403 Forbidden") self.assertEqual(response.content_type, "application/json") self.assertEqual( response.json["errors"], [{ u"description": u"Can't update tender in current (cancelled) status", u"location": u"body", u"name": u"data", }] )

41.482759

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41.482759

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false

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null

0

1

0

1

0

null

0

7

7dfe3186f8a8101fe611a6926b38ca1df625f579

1,911

py

Python

pytamil/tamil19.py

Ezhil-Language-Foundation/pytamil

6fe67a618ec699447fb71f3106c263a944572b73

[ "MIT" ]

1

2020-04-25T09:25:40.000Z

pytamil/tamil19.py

kumaranvram/pytamil

cd999fac9a63a055accefe18f18b0a154d152569

[ "MIT" ]

null

pytamil/tamil19.py

kumaranvram/pytamil

cd999fac9a63a055accefe18f18b0a154d152569

[ "MIT" ]

null

# -*- coding: utf-8 -*- import sys #FIXME: use PYTHONPATH with module directory sys.path.append('../pytamil') from pytamil import தமிழ் from தமிழ் import இலக்கணம் as இல from தமிழ் import புணர்ச்சி from தமிழ் import எழுத்து from தமிழ் import மாத்திரை # print( எழுத்து.எழுத்துக்கள்['மெல்லினம்']) # print( எழுத்து.எழுத்துக்கள்['குறில்'] ) # print (தமிழ்.வட்டெழுத்து('வணக்கம்')) # print ( எழுத்து.தொடர்மொழி_ஆக்கு('விருந்து', 'ஓம்பல்' )) # print( இல.தொடர்மொழி_ஆக்கு('விருந்து', 'ஓம்பல்')) # print( இல.தொடர்மொழி_ஆக்கு('மெய்', 'எழுத்து')) # print( இல.தொடர்மொழி_ஆக்கு('மெய்', 'பழுத்து')) # print( இல.தொடர்மொழி_ஆக்கு('முள்', 'இலை')) # print( இல.தொடர்மொழி_ஆக்கு('உயிர்', 'எழுத்து')) # print( இல.தொடர்மொழி_ஆக்கு('வேல்', 'எறிந்தான்')) # விதிகள் =[] # விதிகள் = getவிதிகள்(entries,விதிகள்) # சான்றுகள் = [] # சான்றுகள் = getசான்றுகள்(entries, சான்றுகள்) # print(விதிகள்) # print(சான்றுகள்) # result = புணர்ச்சி.check("(...)(இ,ஈ,ஐ)" ,"மணிதன்") # print (result) # result = புணர்ச்சி.check("(...)(உயிர்)" , "மணி") # print (result) # result = புணர்ச்சி.check("(உயிர்)(...)" , "அடி") # print (result) # print(புணர்ச்சி.தொடர்மொழி_ஆக்கு( 'உயிர்' , 'எழுத்து')) # புணர்ச்சி.புணர்ச்சிசெய்('''சே|உடம்படுமெய்(ய்)|சும்மா + சும்மா|திரிதல்(வ்)|அடி , # சே|உடம்படுமெய்(வ்) + திரிதல்(வ்)|அடி, # சே|உடம்படுமெய்(வ்) + திரிதல்(வ்)|அடி ''') # புணர்ச்சி.புணர்ச்சிசெய்('''சே|உடம்படுமெய்(ய்)|சும்மா + சும்மா|திரிதல்(வ்)|அடி , # சே|உடம்படுமெய்(வ்) + திரிதல்(வ்)|அடி''') # புணர்ச்சி.புணர்ச்சிசெய்('சேய் +இயல்பு+ அவ்') # புணர்ச்சி.தொடர்மொழி_ஆக்கு('சே', 'அடி' ) # புணர்ச்சி.தொடர்மொழி_ஆக்கு('கண்', 'மங்கியது') # print(மாத்திரை.மாத்திரை_கொடு('புணர்ச்சிசெய்')) # print(மாத்திரை.மொத்தமாத்திரை('புணர்ச்சிசெய்')) # print(புணர்ச்சி.தொடர்மொழி_ஆக்கு( 'மணி' , 'அடித்தான்')) # print(புணர்ச்சி.தொடர்மொழி_ஆக்கு( 'மெய்', 'எழுத்து')) print(புணர்ச்சி.தொடர்மொழி_ஆக்கு( 'நிலா', 'ஒளி'))

30.333333

82

0.462062

887

1,911

1.440812

0.087937

0.067293

0.056338

0.070423

0.792645

0.777778

0.716745

0.693271

0.649452

0.64867

0

0.000606

0.137101

1,911

62

83

30.822581

0.52638

0.831502

0

0.059859

0

0.016129

0

1

0

true

0

0.75

0

0.75

0.125

0

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null

0

1

0

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9

b469b67600381a5066664e4560057c4f9af04a57

35,825

py

Python

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

"""DHCPv6 Prefix Delegation""" # pylint: disable=invalid-name,line-too-long import pytest import srv_msg import srv_control import misc import references @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_onlyPD_request(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_IA_and_PD_request(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::1') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') srv_msg.response_check_suboption_content('Response', '5', '3', None, 'addr', '3000::1') misc.test_procedure() srv_msg.client_copy_option('IA_NA') srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') srv_msg.response_check_suboption_content('Response', '5', '3', None, 'addr', '3000::1') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_onlyPD_request_release(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('server-id') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '0') # tests MUST NOT include 'NoBinding'... references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_onlyPD_multiple_request_release(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('server-id') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '0') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # if it fails, it means that release process fails. references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_IA_and_PD_request_release(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') misc.test_procedure() srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_copy_option('server-id') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_include_option('Response', None, '3') # tests MUST NOT include 'NoBinding'... references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_IA_and_PD_multiple_request_release(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') misc.test_procedure() srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_copy_option('server-id') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '13') # tests MUST NOT include 'NoBinding'... misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.generate_new('IA') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.generate_new('IA') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_noprefixavail_release(): # assign 2 prefixes, try third, fail, release one, assign one more time with success. misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # success misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # both prefixes assigned. misc.test_procedure() srv_msg.client_save_option('IA_PD') srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '6') misc.test_procedure() srv_msg.client_add_saved_option('DONT ') srv_msg.client_copy_option('server-id') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '0') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_noprefixavail(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') # pool of two prefixes srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # both prefixes assigned. misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '6') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_release_nobinding(): misc.test_setup() srv_control.config_srv_subnet('3000::/32', '3000::1-3000::2') srv_control.config_srv_prefix('2001:db8:1::', '0', '32', '33') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '3') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_release_dual_nobinding(): misc.test_setup() srv_control.config_srv_subnet('3000::/32', '3000::1-3000::2') srv_control.config_srv_prefix('2001:db8:1::', '0', '32', '33') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_copy_option('IA_NA') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '3') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '3', None, 'statuscode', '3') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_release_nobinding2(): misc.test_setup() srv_control.config_srv_subnet('3000::/32', '3000::1-3000::2') srv_control.config_srv_prefix('2001:db8:1::', '0', '32', '33') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_save_option('IA_PD') srv_msg.client_add_saved_option('DONT ') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') # must not contain status code == 3. misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_add_saved_option('DONT ') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RELEASE') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '3') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_onlyPD_relay(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') srv_msg.client_does_include('RelayAgent', None, 'interface-id') srv_msg.create_relay_forward() misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'RELAYREPLY') srv_msg.response_check_include_option('Response', None, '18') srv_msg.response_check_include_option('Response', None, '9') srv_msg.response_check_include_option('Response', None, '9') # add test after Scapy fix references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_assign_saved_iapd(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') # two prefixes - 3000::/91; 3000::20:0:0/91; srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '91') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') # 1st prefix srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_save_option('IA_PD') srv_msg.client_add_saved_option('DONT ') # 2nd prefix srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # both prefixes assigned. misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '80', '95') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_add_saved_option(None) srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_suboption_content('Response', '26', '25', None, 'prefix', '2001:db8:1::20:0:0') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 @pytest.mark.disabled def test_prefix_delegation_compare_prefixes_after_client_reboot(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::300') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '96') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # save prefix value prefix1 = srv_msg.get_suboption('IA_PD', 'IA-Prefix')[0] misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') # client reboot srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # compare assigned prefix with the saved one prefix2 = srv_msg.get_suboption('IA_PD', 'IA-Prefix')[0] assert prefix1.prefix == prefix2.prefix references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD def test_prefix_delegation_just_PD_configured_PD_requested(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '$(EMPTY)') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '96') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', 'NOT ', '3') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', 'NOT ', '3') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD def test_prefix_delegation_just_PD_configured_PD_and_IA_requested(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '$(EMPTY)') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '96') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '3', None, 'statuscode', '2') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '3', None, 'statuscode', '2')

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1

0

null

0

1

0

8

c32e3a904ed33d8486773fc9aa670d076acbc954

45,215

py

Python

Detectron/detectron/roi_data/minibatch_ok.py

yiningzeng/docker-detectron

100072486b770b19918a344ec5b4e9a529232697

[ "Apache-2.0" ]

null

Detectron/detectron/roi_data/minibatch_ok.py

yiningzeng/docker-detectron

100072486b770b19918a344ec5b4e9a529232697

[ "Apache-2.0" ]

null

Detectron/detectron/roi_data/minibatch_ok.py

yiningzeng/docker-detectron

100072486b770b19918a344ec5b4e9a529232697

[ "Apache-2.0" ]

null

# Copyright (c) 2017-present, Facebook, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ############################################################################## # # Based on: # -------------------------------------------------------- # Fast R-CNN # Copyright (c) 2015 Microsoft # Licensed under The MIT License [see LICENSE for details] # Written by Ross Girshick # -------------------------------------------------------- """Construct minibatches for Detectron networks.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import cv2 import logging import numpy as np import scipy.sparse from detectron.core.config import cfg import detectron.roi_data.fast_rcnn as fast_rcnn_roi_data import detectron.roi_data.retinanet as retinanet_roi_data import detectron.utils.boxes as box_utils import detectron.roi_data.rpn as rpn_roi_data import detectron.utils.blob as blob_utils import random WIDTH = 1280 HEIGHT = 960 REAL_CLASS = 4 logger = logging.getLogger(__name__) BRIGHTNESS_CONTRAST = 0 def get_minibatch_blob_names(is_training=True): """Return blob names in the order in which they are read by the data loader. """ # data blob: holds a batch of N images, each with 3 channels blob_names = ['data'] if cfg.RPN.RPN_ON: # RPN-only or end-to-end Faster R-CNN blob_names += rpn_roi_data.get_rpn_blob_names(is_training=is_training) elif cfg.RETINANET.RETINANET_ON: blob_names += retinanet_roi_data.get_retinanet_blob_names( is_training=is_training ) else: # Fast R-CNN like models trained on precomputed proposals blob_names += fast_rcnn_roi_data.get_fast_rcnn_blob_names( is_training=is_training ) return blob_names def get_minibatch(roidb): """Given a roidb, construct a minibatch sampled from it.""" # We collect blobs from each image onto a list and then concat them into a # single tensor, hence we initialize each blob to an empty list blobs = {k: [] for k in get_minibatch_blob_names()} # Get the input image blob, formatted for caffe2 im_blob, im_scales = _get_image_blob(roidb) blobs['data'] = im_blob if cfg.RPN.RPN_ON: # RPN-only or end-to-end Faster/Mask R-CNN valid = rpn_roi_data.add_rpn_blobs(blobs, im_scales, roidb) elif cfg.RETINANET.RETINANET_ON: im_width, im_height = im_blob.shape[3], im_blob.shape[2] # im_width, im_height corresponds to the network input: padded image # (if needed) width and height. We pass it as input and slice the data # accordingly so that we don't need to use SampleAsOp valid = retinanet_roi_data.add_retinanet_blobs( blobs, im_scales, roidb, im_width, im_height ) else: # Fast R-CNN like models trained on precomputed proposals valid = fast_rcnn_roi_data.add_fast_rcnn_blobs(blobs, im_scales, roidb) return blobs, valid def get_minibatch_s6(roidb,roidb_noclass): """Given a roidb, construct a minibatch sampled from it.""" # We collect blobs from each image onto a list and then concat them into a # single tensor, hence we initialize each blob to an empty list if 0: random_bbox = dict() random_bbox['kernel_size'] = 224 random_bbox['tl_x'] = random.randint(0, 800) random_bbox['tl_y'] = random.randint(0, 800) blobs = {k: [] for k in get_minibatch_blob_names()} # Get the input image blob, formatted for caffe2 im_blob, im_scales,error_flag = _get_image_blob_s6(roidb,roidb_noclass) blobs['data'] = im_blob if cfg.RPN.RPN_ON: # RPN-only or end-to-end Faster/Mask R-CNN valid = rpn_roi_data.add_rpn_blobs(blobs, im_scales, roidb) elif cfg.RETINANET.RETINANET_ON: im_width, im_height = im_blob.shape[3], im_blob.shape[2] # im_width, im_height corresponds to the network input: padded image # (if needed) width and height. We pass it as input and slice the data # accordingly so that we don't need to use SampleAsOp valid = retinanet_roi_data.add_retinanet_blobs( blobs, im_scales, roidb, im_width, im_height ) else: # Fast R-CNN like models trained on precomputed proposals valid = fast_rcnn_roi_data.add_fast_rcnn_blobs(blobs, im_scales, roidb) return blobs, valid def contrast_brightness_image(src1, a=1.2, g=10): h, w, ch = src1.shape src2 = np.zeros([h, w, ch], src1.dtype) dst = cv2.addWeighted(src1, a, src2, 1 - a, g) cv2.imshow("con-bri-demo", dst) cv2.waitKey(0) cv2.destroyAllWindows() return dst def _get_image_blob(roidb): """Builds an input blob from the images in the roidb at the specified scales. """ num_images = len(roidb) # Sample random scales to use for each image in this batch scale_inds = np.random.randint( 0, high=len(cfg.TRAIN.SCALES), size=num_images ) processed_ims = [] im_scales = [] for i in range(num_images): im = cv2.imread(roidb[i]['image']) if 0: im_tmp = cv2.imread(roidb[i]['image']) random_flag = random.randint(0, 1) if BRIGHTNESS_CONTRAST and random_flag : im = contrast_brightness_image(im_tmp) else: im = im_tmp.copy() assert im is not None, \ 'Failed to read image \'{}\''.format(roidb[i]['image']) if roidb[i]['flipped']: im = im[:, ::-1, :] target_size = cfg.TRAIN.SCALES[scale_inds[i]] im, im_scale = blob_utils.prep_im_for_blob( im, cfg.PIXEL_MEANS, target_size, cfg.TRAIN.MAX_SIZE ) im_scales.append(im_scale) processed_ims.append(im) # Create a blob to hold the input images blob = blob_utils.im_list_to_blob(processed_ims) return blob, im_scales def mat_inter(box1,box2): # box=(xA,yA,xB,yB) x01, y01, x02, y02 = box1 x11, y11, x12, y12 = box2 lx = abs((x01 + x02) / 2 - (x11 + x12) / 2) ly = abs((y01 + y02) / 2 - (y11 + y12) / 2) sax = abs(x01 - x02) sbx = abs(x11 - x12) say = abs(y01 - y02) sby = abs(y11 - y12) if lx <= (sax + sbx) / 2 and ly <= (say + sby) / 2: return True else: return False def solve_coincide(box1,box2): # box=(xA,yA,xB,yB) if mat_inter(box1,box2)==True: x01, y01, x02, y02 = box1 x11, y11, x12, y12 = box2 col=min(x02,x12)-max(x01,x11) row=min(y02,y12)-max(y01,y11) intersection=col*row area1=(x02-x01)*(y02-y01) area2=(x12-x11)*(y12-y11) coincide=intersection/area2#(area1+area2-intersection) return coincide else: return False def compute_bbox_regression_targets(entry): """Compute bounding-box regression targets for an image.""" # Indices of ground-truth ROIs rois = entry['boxes'] overlaps = entry['max_overlaps'] labels = entry['max_classes'] gt_inds = np.where((entry['gt_classes'] > 0) & (entry['is_crowd'] == 0))[0] # Targets has format (class, tx, ty, tw, th) targets = np.zeros((rois.shape[0], 5), dtype=np.float32) if len(gt_inds) == 0: # Bail if the image has no ground-truth ROIs return targets # Indices of examples for which we try to make predictions ex_inds = np.where(overlaps >= cfg.TRAIN.BBOX_THRESH)[0] # Get IoU overlap between each ex ROI and gt ROI ex_gt_overlaps = box_utils.bbox_overlaps( rois[ex_inds, :].astype(dtype=np.float32, copy=False), rois[gt_inds, :].astype(dtype=np.float32, copy=False)) # Find which gt ROI each ex ROI has max overlap with: # this will be the ex ROI's gt target gt_assignment = ex_gt_overlaps.argmax(axis=1) gt_rois = rois[gt_inds[gt_assignment], :] ex_rois = rois[ex_inds, :] # Use class "1" for all boxes if using class_agnostic_bbox_reg targets[ex_inds, 0] = ( 1 if cfg.MODEL.CLS_AGNOSTIC_BBOX_REG else labels[ex_inds]) targets[ex_inds, 1:] = box_utils.bbox_transform_inv( ex_rois, gt_rois, cfg.MODEL.BBOX_REG_WEIGHTS) return targets def _get_image_blob_s6_0(roidb,roidb_noclass1): """Builds an input blob from the images in the roidb at the specified scales. """ num_images = len(roidb) # Sample random scales to use for each image in this batch scale_inds = np.random.randint( 0, high=len(cfg.TRAIN.SCALES), size=num_images ) processed_ims = [] im_scales = [] error_flag = [0,0] for i in range(num_images): roidb_noclass = roidb_noclass1.copy() if roidb[i][u'image'].split('/')[-1]==u'test.jpg': random_bbox = dict() random_bbox['kernel_size'] = 224 random_bbox['tl_x'] = 0 random_bbox['tl_y'] = 0 x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size'] im = cv2.imread(roidb[i]['image'])[y0:y1, x0:x1] im = cv2.resize(im,(WIDTH,HEIGHT)) #cv2.imwrite('/home/icubic/aa.png',im) error_flag[i] = 0 roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: if 1: real_class = []#roidb[i]['gt_classes'][0] num_real_class = len(roidb[i]['gt_classes']) random_bbox = dict() random_bbox['kernel_size'] = 224 random_bbox['tl_x'] = random.randint(0, 800) random_bbox['tl_y'] = random.randint(0, 800) x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size'] im = cv2.imread(roidb[i]['image'])[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) sum_inside_overlaps = 0 boxes_inside_overlaps = [] for i_roidb,sub_boxes in enumerate(roidb[i][u'boxes']): crop_x0 = int(sub_boxes[0]) crop_y0 = int(sub_boxes[1]) crop_x1 = int(sub_boxes[2]) crop_y1 = int(sub_boxes[3]) #real_x0 = float(crop_x0 - x0)*1024/224 # float(crop_x0) / 1024 * 224 #real_y0 = float(crop_y0 - y0)*1024/224 # float(crop_y0) / 1024 * 224 #real_x1 = float(crop_x1 - x0)*1024/224 # float(crop_x1) / 1024 * 224 #real_y1 = float(crop_y1 - y0)*1024/224 overlaps_rate = solve_coincide((x0, y0, x1, y1), (crop_x0, crop_y0, crop_x1, crop_y1)) if overlaps_rate>0.9: sum_inside_overlaps = sum_inside_overlaps + 1 #real_x0 = crop_x0 - x0 # float(crop_x0) / 1024 * 224 #real_y0 = crop_y0 - y0 # float(crop_y0) / 1024 * 224 #real_x1 = crop_x1 - x0 # float(crop_x1) / 1024 * 224 #real_y1 = crop_y1 - y0 real_x0 = float(crop_x0 - x0)*WIDTH/224 # float(crop_x0) / 1024 * 224 real_y0 = float(crop_y0 - y0)*HEIGHT/224 # float(crop_y0) / 1024 * 224 real_x1 = float(crop_x1 - x0)*WIDTH/224 # float(crop_x1) / 1024 * 224 real_y1 = float(crop_y1 - y0)*HEIGHT/224 if real_x0<0: real_x0 = 0 if real_x0>WIDTH: real_x0 = WIDTH if real_x1<0: real_x1 = 0 if real_x1>WIDTH: real_x1 = WIDTH if real_y0<0: real_y0 = 0 if real_y0>HEIGHT: real_y0 = HEIGHT if real_y1<0: real_y1 = 0 if real_y1>HEIGHT: real_y1 = HEIGHT boxes_inside_overlaps.append([real_x0, real_y0, real_x1, real_y1]) real_class.append(roidb[i]['gt_classes'][i_roidb]) #cv2.rectangle(im, (int(real_x0), int(real_y0)), #(int(real_x1), int(real_y1)), (255, 0, 255)) #cv2.imwrite('/home/icubic/daily_work/code/circruit/new/result/uu.png', im) #a = roidb[i]['gt_overlaps'].toarray() if sum_inside_overlaps>0: num_valid_objs = sum_inside_overlaps*1 boxes = np.zeros((num_valid_objs, 4), dtype=np.float32) gt_classes = np.zeros((num_valid_objs), dtype=np.int32) gt_overlaps = np.zeros((num_valid_objs, 3), dtype=np.float32) box_to_gt_ind_map = np.zeros((num_valid_objs), dtype=np.int32) is_crowd = np.zeros((num_valid_objs), dtype=np.bool) for ix in range(num_valid_objs): gt_classes[ix] = real_class[ix]#real_class*1 try: gt_overlaps[ix, real_class] = 1.0 except: print('error') is_crowd[ix] = False box_to_gt_ind_map[ix] = ix for i_index in range(4): boxes[ix,i_index] = boxes_inside_overlaps[ix][i_index] #for ix in range(num_valid_objs): #box_to_gt_ind_map[ix] = ix #cls = real_class*1 roidb_noclass['boxes'] = np.append(roidb_noclass['boxes'], boxes, axis=0) roidb_noclass['gt_classes'] = np.append(roidb_noclass['gt_classes'], gt_classes) #mm = np.append( # roidb_noclass['gt_overlaps'].toarray(), gt_overlaps,axis=0) roidb_noclass['gt_overlaps'] = np.append( roidb_noclass['gt_overlaps'].toarray(), gt_overlaps) roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(roidb_noclass['gt_overlaps']) #mm = np.append(mm, gt_overlaps, axis=0) #roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(mm) roidb_noclass['is_crowd'] = np.append(roidb_noclass['is_crowd'], is_crowd) roidb_noclass['box_to_gt_ind_map'] = np.append(roidb_noclass['box_to_gt_ind_map'], box_to_gt_ind_map) gt_overlaps = roidb_noclass['gt_overlaps'].toarray() # max overlap with gt over classes (columns) max_overlaps = gt_overlaps.max(axis=1) # gt class that had the max overlap max_classes = gt_overlaps.argmax(axis=1) roidb_noclass['max_classes'] = max_classes roidb_noclass['max_overlaps'] = max_overlaps # sanity checks # if max overlap is 0, the class must be background (class 0) zero_inds = np.where(max_overlaps == 0)[0] assert all(max_classes[zero_inds] == 0) # if max overlap > 0, the class must be a fg class (not class 0) nonzero_inds = np.where(max_overlaps > 0)[0] assert all(max_classes[nonzero_inds] != 0) roidb_noclass['bbox_targets'] = compute_bbox_regression_targets(roidb_noclass) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH if 0: if sum_inside_overlaps==0: roidb[i] = roidb_noclass['0'].copy() roidb[i][u'height'] = 1024 roidb[i][u'width'] = 1024 if sum_inside_overlaps==1: num_valid_objs = 1 roidb[i] = roidb_noclass['1'].copy() a = roidb[i]['gt_overlaps'].toarray() #for i_inside in enumerate(sum_inside_overlaps) if sum_inside_overlaps==2: num_valid_objs = 2 roidb[i] = roidb_noclass['2'].copy() a = roidb[i]['gt_overlaps'].toarray() if sum_inside_overlaps==3: num_valid_objs = 3 roidb[i] = roidb_noclass['3'].copy() a = roidb[i]['gt_overlaps'].toarray() if 0: crop_x0 = int(roidb[i][u'boxes'][0][0]) crop_y0 = int(roidb[i][u'boxes'][0][1]) crop_x1 = int(roidb[i][u'boxes'][0][2]) crop_y1 = int(roidb[i][u'boxes'][0][3]) crop_w = crop_x1 - crop_x0 crop_h = crop_y1 - crop_y0 random_bbox = dict() random_bbox['kernel_size'] = 224 random_bbox['tl_x'] = random.randint(0, 800) random_bbox['tl_y'] = random.randint(0, 800) x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size'] #real_x0 = crop_x0-x0#float(crop_x0) / 1024 * 224 #real_y0 = crop_y0-y0#float(crop_y0) / 1024 * 224 #real_x1 = 1024#float(crop_x1) / 1024 * 224 #real_y1 = 1024#float(crop_y1) / 1024 * 224 overlaps_rate = solve_coincide((x0,y0,x1,y1),(crop_x0,crop_y0,crop_x1,crop_y1)) im = cv2.imread(roidb[i]['image'])[y0:y1, x0:x1] #im = cv2.resize(im, (1024, 1024)) if overlaps_rate>0.9: real_x0 = crop_x0 - x0 # float(crop_x0) / 1024 * 224 real_y0 = crop_y0 - y0 # float(crop_y0) / 1024 * 224 real_x1 = crop_x1 - x0 # float(crop_x1) / 1024 * 224 real_y1 = crop_y1 - y0 roidb[i][u'boxes'][0][0] = real_x0 roidb[i][u'boxes'][0][1] = real_y0 roidb[i][u'boxes'][0][2] = real_x1 roidb[i][u'boxes'][0][3] = real_y1 roidb[i][u'height'] = 224 roidb[i][u'width'] = 224 error_flag[i] = 1 #cv2.imwrite('/home/icubic/daily_work/code/Detectron/detectron/datasets/data/s6_test/aa.png',im) else: roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = 224 roidb[i][u'width'] = 224 error_flag[i] = 0 #print('aa') assert im is not None, \ 'Failed to read image \'{}\''.format(roidb[i]['image']) if roidb[i]['flipped']: im = im[:, ::-1, :] target_size = cfg.TRAIN.SCALES[scale_inds[i]] im, im_scale = blob_utils.prep_im_for_blob( im, cfg.PIXEL_MEANS, target_size, cfg.TRAIN.MAX_SIZE ) im_scales.append(im_scale) processed_ims.append(im) # Create a blob to hold the input images blob = blob_utils.im_list_to_blob(processed_ims) return blob, im_scales,error_flag def _get_image_blob_s6(roidb,roidb_noclass1): """Builds an input blob from the images in the roidb at the specified scales. """ num_images = len(roidb) # Sample random scales to use for each image in this batch scale_inds = np.random.randint( 0, high=len(cfg.TRAIN.SCALES), size=num_images ) processed_ims = [] im_scales = [] error_flag = [0,0] for i in range(num_images): roidb_noclass = roidb_noclass1.copy() if roidb[i][u'image'].split('/')[-1]==u'test.png': #test.jpg random_bbox = dict() random_bbox['kernel_size_x'] = int(WIDTH / 5) random_bbox['kernel_size_y'] = int(HEIGHT / 5) random_bbox['tl_x'] = 0 random_bbox['tl_y'] = 0 x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] im = cv2.imread(roidb[i]['image'])[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) # cv2.imwrite('/home/icubic/aa.png',im) error_flag[i] = 0 roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: if 1: if len(roidb[i][u'boxes']) == 0: random_bbox = dict() random_flag = random.randint(0, 1) real_yuanlai_width = roidb[i][u'width'] * 1 real_yuanlai_height = roidb[i][u'height'] * 1 width_ratio = float(real_yuanlai_width) / 1024 height_after_ratio = int(float(real_yuanlai_height) / width_ratio) width_after_ratio = 1024 if 1: if random_flag == 0: #print(random_flag) random_bbox['kernel_size_x'] = int(WIDTH / 5) random_bbox['kernel_size_y'] = int(HEIGHT / 5) random_X = width_after_ratio - random_bbox['kernel_size_x'] random_Y = height_after_ratio - random_bbox['kernel_size_y'] try: random_bbox['tl_x'] = random.randint(0, random_X) random_bbox['tl_y'] = random.randint(0, random_Y) except: print('aa') x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] im = cv2.imread(roidb[i][u'image']) im = cv2.resize(im, (width_after_ratio, height_after_ratio))[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: #print(random_flag) random_bbox['kernel_size_x'] = int(float(width_after_ratio) / 1.2) random_bbox['kernel_size_y'] = int(float(height_after_ratio) / 1.2) random_X = width_after_ratio - random_bbox['kernel_size_x'] random_Y = height_after_ratio - random_bbox['kernel_size_y'] random_bbox['tl_x'] = random.randint(0, random_X) random_bbox['tl_y'] = random.randint(0, random_Y) x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] im = cv2.imread(roidb[i][u'image']) im = cv2.resize(im, (width_after_ratio, height_after_ratio))[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: im = cv2.imread(roidb[i][u'image']) im = cv2.resize(im, (WIDTH, HEIGHT)) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH # cv2.imwrite('/home/icubic/daily_work/circruit_model/tmp_images/aa.png',im) assert im is not None, \ 'Failed to read image \'{}\''.format(roidb[i]['image']) if roidb[i]['flipped']:#for image flip background training im = im[:, ::-1, :] target_size = cfg.TRAIN.SCALES[scale_inds[i]] im, im_scale = blob_utils.prep_im_for_blob( im, cfg.PIXEL_MEANS, target_size, cfg.TRAIN.MAX_SIZE ) im_scales.append(im_scale) processed_ims.append(im) continue real_yuanlai_width = roidb[i][u'width'] * 1 real_yuanlai_height = roidb[i][u'height'] * 1 width_ratio = float(real_yuanlai_width) / 1024 height_after_ratio = int(float(real_yuanlai_height) / width_ratio) width_after_ratio = 1024 real_class = []#roidb[i]['gt_classes'][0] num_real_class = len(roidb[i]['gt_classes']) random_bbox = dict() random_bbox['kernel_size_x'] = int(WIDTH / 5) random_bbox['kernel_size_y'] = int(HEIGHT / 5) if 1: w_tongji = 0 h_tongji = 0 for i_tongji, sub_boxes_tongji in enumerate(roidb[i][u'boxes']): crop_x0_tongji = int(sub_boxes_tongji[0] / real_yuanlai_width * width_after_ratio) crop_y0_tongji = int(sub_boxes_tongji[1] / real_yuanlai_height * height_after_ratio) crop_x1_tongji = int(sub_boxes_tongji[2] / real_yuanlai_width * width_after_ratio) crop_y1_tongji = int(sub_boxes_tongji[3] / real_yuanlai_height * height_after_ratio) w_tongji = crop_x1_tongji - crop_x0_tongji h_tongji = crop_y1_tongji - crop_y0_tongji if w_tongji>int(WIDTH / 5) or h_tongji>int(HEIGHT / 5): random_bbox['kernel_size_x'] = int(float(width_after_ratio) / 1.2) random_bbox['kernel_size_y'] = int(float(height_after_ratio) / 1.2) random_X = width_after_ratio - random_bbox['kernel_size_x'] random_Y = height_after_ratio - random_bbox['kernel_size_y'] random_bbox['tl_x'] = random.randint(0, random_X) random_bbox['tl_y'] = random.randint(0, random_Y) x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] try: im = cv2.imread(roidb[i][u'image']) except: im = cv2.imread(roidb[i][u'image']) im = cv2.resize(im, (width_after_ratio, height_after_ratio))[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) sum_inside_overlaps = 0 boxes_inside_overlaps = [] for i_roidb,sub_boxes in enumerate(roidb[i][u'boxes']): crop_x0 = int(sub_boxes[0]/real_yuanlai_width*width_after_ratio) crop_y0 = int(sub_boxes[1]/real_yuanlai_height*height_after_ratio) crop_x1 = int(sub_boxes[2]/real_yuanlai_width*width_after_ratio) crop_y1 = int(sub_boxes[3]/real_yuanlai_height*height_after_ratio) #real_x0 = float(crop_x0 - x0)*1024/224 # float(crop_x0) / 1024 * 224 #real_y0 = float(crop_y0 - y0)*1024/224 # float(crop_y0) / 1024 * 224 #real_x1 = float(crop_x1 - x0)*1024/224 # float(crop_x1) / 1024 * 224 #real_y1 = float(crop_y1 - y0)*1024/224 overlaps_rate = solve_coincide((x0, y0, x1, y1), (crop_x0, crop_y0, crop_x1, crop_y1)) if overlaps_rate>0.9: sum_inside_overlaps = sum_inside_overlaps + 1 #real_x0 = crop_x0 - x0 # float(crop_x0) / 1024 * 224 #real_y0 = crop_y0 - y0 # float(crop_y0) / 1024 * 224 #real_x1 = crop_x1 - x0 # float(crop_x1) / 1024 * 224 #real_y1 = crop_y1 - y0 real_x0 = float(crop_x0 - x0)*WIDTH/(random_bbox['kernel_size_x']) # float(crop_x0) / 1024 * 224 real_y0 = float(crop_y0 - y0)*HEIGHT/(random_bbox['kernel_size_y']) # float(crop_y0) / 1024 * 224 real_x1 = float(crop_x1 - x0)*WIDTH/(random_bbox['kernel_size_x']) # float(crop_x1) / 1024 * 224 real_y1 = float(crop_y1 - y0)*HEIGHT/(random_bbox['kernel_size_y']) if real_x0<0: real_x0 = 0 if real_x0>WIDTH: real_x0 = WIDTH if real_x1<0: real_x1 = 0 if real_x1>WIDTH: real_x1 = WIDTH if real_y0<0: real_y0 = 0 if real_y0>HEIGHT: real_y0 = HEIGHT if real_y1<0: real_y1 = 0 if real_y1>HEIGHT: real_y1 = HEIGHT #cv2.rectangle(im, (int(real_x0), int(real_y0)), (int(real_x1), int(real_y1)), (0, 255, 255), 3) #cv2.imwrite('/home/icubic/daily_work/code/Detectron/detectron/datasets/data/shanghai/aa.png',im) boxes_inside_overlaps.append([real_x0, real_y0, real_x1, real_y1]) real_class.append(roidb[i]['gt_classes'][i_roidb]) #cv2.rectangle(im, (int(real_x0), int(real_y0)), #(int(real_x1), int(real_y1)), (255, 0, 255)) #cv2.imwrite('/home/icubic/daily_work/code/circruit/new/result/uu.png', im) #a = roidb[i]['gt_overlaps'].toarray() if sum_inside_overlaps>0 : num_valid_objs = sum_inside_overlaps*1 boxes = np.zeros((num_valid_objs, 4), dtype=np.float32) gt_classes = np.zeros((num_valid_objs), dtype=np.int32) gt_overlaps = np.zeros((num_valid_objs, REAL_CLASS), dtype=np.float32) box_to_gt_ind_map = np.zeros((num_valid_objs), dtype=np.int32) is_crowd = np.zeros((num_valid_objs), dtype=np.bool) for ix in range(num_valid_objs): gt_classes[ix] = real_class[ix]#real_class*1 try: gt_overlaps[ix, real_class] = 1.0 except: print('error') is_crowd[ix] = False box_to_gt_ind_map[ix] = ix for i_index in range(4): boxes[ix,i_index] = boxes_inside_overlaps[ix][i_index] #for ix in range(num_valid_objs): #box_to_gt_ind_map[ix] = ix #cls = real_class*1 roidb_noclass['boxes'] = np.append(roidb_noclass['boxes'], boxes, axis=0) roidb_noclass['gt_classes'] = np.append(roidb_noclass['gt_classes'], gt_classes) #mm = np.append( # roidb_noclass['gt_overlaps'].toarray(), gt_overlaps,axis=0) roidb_noclass['gt_overlaps'] = np.append( roidb_noclass['gt_overlaps'].toarray(), gt_overlaps) roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(roidb_noclass['gt_overlaps']) #mm = np.append(mm, gt_overlaps, axis=0) #roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(mm) roidb_noclass['is_crowd'] = np.append(roidb_noclass['is_crowd'], is_crowd) roidb_noclass['box_to_gt_ind_map'] = np.append(roidb_noclass['box_to_gt_ind_map'], box_to_gt_ind_map) gt_overlaps = roidb_noclass['gt_overlaps'].toarray() # max overlap with gt over classes (columns) max_overlaps = gt_overlaps.max(axis=1) # gt class that had the max overlap max_classes = gt_overlaps.argmax(axis=1) roidb_noclass['max_classes'] = max_classes roidb_noclass['max_overlaps'] = max_overlaps # sanity checks # if max overlap is 0, the class must be background (class 0) zero_inds = np.where(max_overlaps == 0)[0] assert all(max_classes[zero_inds] == 0) # if max overlap > 0, the class must be a fg class (not class 0) nonzero_inds = np.where(max_overlaps > 0)[0] assert all(max_classes[nonzero_inds] != 0) roidb_noclass['bbox_targets'] = compute_bbox_regression_targets(roidb_noclass) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH #print('aa') assert im is not None, \ 'Failed to read image \'{}\''.format(roidb[i]['image']) if roidb[i]['flipped']: im = im[:, ::-1, :] target_size = cfg.TRAIN.SCALES[scale_inds[i]] im, im_scale = blob_utils.prep_im_for_blob( im, cfg.PIXEL_MEANS, target_size, cfg.TRAIN.MAX_SIZE ) im_scales.append(im_scale) processed_ims.append(im) # Create a blob to hold the input images blob = blob_utils.im_list_to_blob(processed_ims) return blob, im_scales,error_flag def _get_image_blob_s6_ok(roidb,roidb_noclass1): """Builds an input blob from the images in the roidb at the specified scales. """ num_images = len(roidb) # Sample random scales to use for each image in this batch scale_inds = np.random.randint( 0, high=len(cfg.TRAIN.SCALES), size=num_images ) processed_ims = [] im_scales = [] error_flag = [0,0] for i in range(num_images): roidb_noclass = roidb_noclass1.copy() if roidb[i][u'image'].split('/')[-1]==u'test.jpg': random_bbox = dict() random_bbox['kernel_size_x'] = int(WIDTH / 5) random_bbox['kernel_size_y'] = int(HEIGHT / 5) random_bbox['tl_x'] = 0 random_bbox['tl_y'] = 0 x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] im = cv2.imread(roidb[i]['image'])[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) # cv2.imwrite('/home/icubic/aa.png',im) error_flag[i] = 0 roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: if 1: real_yuanlai_width = roidb[i][u'width'] * 1 real_yuanlai_height = roidb[i][u'height'] * 1 width_ratio = float(real_yuanlai_width) / 1024 height_after_ratio = int(float(real_yuanlai_height) / width_ratio) width_after_ratio = 1024 real_class = []#roidb[i]['gt_classes'][0] num_real_class = len(roidb[i]['gt_classes']) random_bbox = dict() random_bbox['kernel_size_x'] = int(WIDTH / 5) random_bbox['kernel_size_y'] = int(HEIGHT / 5) random_X = width_after_ratio - random_bbox['kernel_size_x'] random_Y = height_after_ratio - random_bbox['kernel_size_y'] random_bbox['tl_x'] = random.randint(0, random_X) random_bbox['tl_y'] = random.randint(0, random_Y) x0 = random_bbox['tl_x'] x1 = random_bbox['tl_x'] + random_bbox['kernel_size_x'] y0 = random_bbox['tl_y'] y1 = random_bbox['tl_y'] + random_bbox['kernel_size_y'] im = cv2.imread(roidb[i]['image']) im = cv2.resize(im, (width_after_ratio, height_after_ratio))[y0:y1, x0:x1] im = cv2.resize(im, (WIDTH, HEIGHT)) sum_inside_overlaps = 0 boxes_inside_overlaps = [] for i_roidb,sub_boxes in enumerate(roidb[i][u'boxes']): crop_x0 = int(sub_boxes[0]/real_yuanlai_width*width_after_ratio) crop_y0 = int(sub_boxes[1]/real_yuanlai_height*height_after_ratio) crop_x1 = int(sub_boxes[2]/real_yuanlai_width*width_after_ratio) crop_y1 = int(sub_boxes[3]/real_yuanlai_height*height_after_ratio) #real_x0 = float(crop_x0 - x0)*1024/224 # float(crop_x0) / 1024 * 224 #real_y0 = float(crop_y0 - y0)*1024/224 # float(crop_y0) / 1024 * 224 #real_x1 = float(crop_x1 - x0)*1024/224 # float(crop_x1) / 1024 * 224 #real_y1 = float(crop_y1 - y0)*1024/224 overlaps_rate = solve_coincide((x0, y0, x1, y1), (crop_x0, crop_y0, crop_x1, crop_y1)) if overlaps_rate>0.9: sum_inside_overlaps = sum_inside_overlaps + 1 #real_x0 = crop_x0 - x0 # float(crop_x0) / 1024 * 224 #real_y0 = crop_y0 - y0 # float(crop_y0) / 1024 * 224 #real_x1 = crop_x1 - x0 # float(crop_x1) / 1024 * 224 #real_y1 = crop_y1 - y0 real_x0 = float(crop_x0 - x0)*WIDTH/(random_bbox['kernel_size_x']) # float(crop_x0) / 1024 * 224 real_y0 = float(crop_y0 - y0)*HEIGHT/(random_bbox['kernel_size_y']) # float(crop_y0) / 1024 * 224 real_x1 = float(crop_x1 - x0)*WIDTH/(random_bbox['kernel_size_x']) # float(crop_x1) / 1024 * 224 real_y1 = float(crop_y1 - y0)*HEIGHT/(random_bbox['kernel_size_y']) if real_x0<0: real_x0 = 0 if real_x0>WIDTH: real_x0 = WIDTH if real_x1<0: real_x1 = 0 if real_x1>WIDTH: real_x1 = WIDTH if real_y0<0: real_y0 = 0 if real_y0>HEIGHT: real_y0 = HEIGHT if real_y1<0: real_y1 = 0 if real_y1>HEIGHT: real_y1 = HEIGHT #cv2.rectangle(im, (int(real_x0), int(real_y0)), (int(real_x1), int(real_y1)), (0, 255, 255), 3) #cv2.imwrite('/home/icubic/daily_work/code/Detectron/detectron/datasets/data/shanghai/aa.png',im) boxes_inside_overlaps.append([real_x0, real_y0, real_x1, real_y1]) real_class.append(roidb[i]['gt_classes'][i_roidb]) #cv2.rectangle(im, (int(real_x0), int(real_y0)), #(int(real_x1), int(real_y1)), (255, 0, 255)) #cv2.imwrite('/home/icubic/daily_work/code/circruit/new/result/uu.png', im) #a = roidb[i]['gt_overlaps'].toarray() if sum_inside_overlaps>0: num_valid_objs = sum_inside_overlaps*1 boxes = np.zeros((num_valid_objs, 4), dtype=np.float32) gt_classes = np.zeros((num_valid_objs), dtype=np.int32) gt_overlaps = np.zeros((num_valid_objs, REAL_CLASS), dtype=np.float32) box_to_gt_ind_map = np.zeros((num_valid_objs), dtype=np.int32) is_crowd = np.zeros((num_valid_objs), dtype=np.bool) for ix in range(num_valid_objs): gt_classes[ix] = real_class[ix]#real_class*1 try: gt_overlaps[ix, real_class] = 1.0 except: print('error') is_crowd[ix] = False box_to_gt_ind_map[ix] = ix for i_index in range(4): boxes[ix,i_index] = boxes_inside_overlaps[ix][i_index] #for ix in range(num_valid_objs): #box_to_gt_ind_map[ix] = ix #cls = real_class*1 roidb_noclass['boxes'] = np.append(roidb_noclass['boxes'], boxes, axis=0) roidb_noclass['gt_classes'] = np.append(roidb_noclass['gt_classes'], gt_classes) #mm = np.append( # roidb_noclass['gt_overlaps'].toarray(), gt_overlaps,axis=0) roidb_noclass['gt_overlaps'] = np.append( roidb_noclass['gt_overlaps'].toarray(), gt_overlaps) roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(roidb_noclass['gt_overlaps']) #mm = np.append(mm, gt_overlaps, axis=0) #roidb_noclass['gt_overlaps'] = scipy.sparse.csr_matrix(mm) roidb_noclass['is_crowd'] = np.append(roidb_noclass['is_crowd'], is_crowd) roidb_noclass['box_to_gt_ind_map'] = np.append(roidb_noclass['box_to_gt_ind_map'], box_to_gt_ind_map) gt_overlaps = roidb_noclass['gt_overlaps'].toarray() # max overlap with gt over classes (columns) max_overlaps = gt_overlaps.max(axis=1) # gt class that had the max overlap max_classes = gt_overlaps.argmax(axis=1) roidb_noclass['max_classes'] = max_classes roidb_noclass['max_overlaps'] = max_overlaps # sanity checks # if max overlap is 0, the class must be background (class 0) zero_inds = np.where(max_overlaps == 0)[0] assert all(max_classes[zero_inds] == 0) # if max overlap > 0, the class must be a fg class (not class 0) nonzero_inds = np.where(max_overlaps > 0)[0] assert all(max_classes[nonzero_inds] != 0) roidb_noclass['bbox_targets'] = compute_bbox_regression_targets(roidb_noclass) roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH else: roidb[i] = roidb_noclass.copy() roidb[i][u'height'] = HEIGHT roidb[i][u'width'] = WIDTH #print('aa') assert im is not None, \ 'Failed to read image \'{}\''.format(roidb[i]['image']) if roidb[i]['flipped']: im = im[:, ::-1, :] target_size = cfg.TRAIN.SCALES[scale_inds[i]] im, im_scale = blob_utils.prep_im_for_blob( im, cfg.PIXEL_MEANS, target_size, cfg.TRAIN.MAX_SIZE ) im_scales.append(im_scale) processed_ims.append(im) # Create a blob to hold the input images blob = blob_utils.im_list_to_blob(processed_ims) return blob, im_scales,error_flag

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Python

morepath/tests/test_path_directive.py

timgates42/morepath

09972904229f807da75c75d8825af1495057acdc

[ "BSD-3-Clause" ]

314

2015-01-01T01:42:52.000Z

2022-01-07T21:46:15.000Z

morepath/tests/test_path_directive.py

timgates42/morepath

09972904229f807da75c75d8825af1495057acdc

[ "BSD-3-Clause" ]

369

2015-01-02T19:10:40.000Z

2021-07-03T04:37:27.000Z

morepath/tests/test_path_directive.py

timgates42/morepath

09972904229f807da75c75d8825af1495057acdc

[ "BSD-3-Clause" ]

37

2015-01-11T09:22:02.000Z

2021-07-02T20:48:20.000Z

import dectate import morepath from morepath.converter import Converter from morepath.error import ( DirectiveReportError, ConfigError, LinkError, TrajectError, ) from webtest import TestApp as Client import pytest def test_simple_path_one_step(): class app(morepath.App): pass class Model: def __init__(self): pass @app.path(model=Model, path="simple") def get_model(): return Model() @app.view(model=Model) def default(self, request): return "View" @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/simple") assert response.body == b"View" response = c.get("/simple/link") assert response.body == b"http://localhost/simple" def test_simple_path_two_steps(): class app(morepath.App): pass class Model: def __init__(self): pass @app.path(model=Model, path="one/two") def get_model(): return Model() @app.view(model=Model) def default(self, request): return "View" @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/one/two") assert response.body == b"View" response = c.get("/one/two/link") assert response.body == b"http://localhost/one/two" def test_variable_path_one_step(): class app(morepath.App): pass class Model: def __init__(self, name): self.name = name @app.path(model=Model, path="{name}") def get_model(name): return Model(name) @app.view(model=Model) def default(self, request): return "View: %s" % self.name @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/foo") assert response.body == b"View: foo" response = c.get("/foo/link") assert response.body == b"http://localhost/foo" def test_variable_path_two_steps(): class app(morepath.App): pass class Model: def __init__(self, name): self.name = name @app.path(model=Model, path="document/{name}") def get_model(name): return Model(name) @app.view(model=Model) def default(self, request): return "View: %s" % self.name @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/document/foo") assert response.body == b"View: foo" response = c.get("/document/foo/link") assert response.body == b"http://localhost/document/foo" def test_variable_path_two_variables(): class app(morepath.App): pass class Model: def __init__(self, name, version): self.name = name self.version = version @app.path(model=Model, path="{name}-{version}") def get_model(name, version): return Model(name, version) @app.view(model=Model) def default(self, request): return f"View: {self.name} {self.version}" @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/foo-one") assert response.body == b"View: foo one" response = c.get("/foo-one/link") assert response.body == b"http://localhost/foo-one" def test_variable_path_explicit_converter(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="{id}", converters=dict(id=Converter(int))) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/1/link") assert response.body == b"http://localhost/1" response = c.get("/broken", status=404) def test_variable_path_implicit_converter(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="{id}") def get_model(id=0): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/1/link") assert response.body == b"http://localhost/1" response = c.get("/broken", status=404) def test_variable_path_explicit_trumps_implicit(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="{id}", converters=dict(id=Converter(int))) def get_model(id="foo"): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/1/link") assert response.body == b"http://localhost/1" response = c.get("/broken", status=404) def test_url_parameter_explicit_converter(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="/", converters=dict(id=Converter(int))) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/link?id=1") assert response.body == b"http://localhost/?id=1" response = c.get("/?id=broken", status=400) response = c.get("/") assert response.body in ( b"View: None (<type 'NoneType'>)", b"View: None (<class 'NoneType'>)", ) def test_url_parameter_explicit_converter_get_converters(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id def get_converters(): return dict(id=Converter(int)) @app.path(model=Model, path="/", get_converters=get_converters) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/link?id=1") assert response.body == b"http://localhost/?id=1" response = c.get("/?id=broken", status=400) response = c.get("/") assert response.body in ( b"View: None (<type 'NoneType'>)", b"View: None (<class 'NoneType'>)", ) def test_url_parameter_get_converters_overrides_converters(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id def get_converters(): return dict(id=Converter(int)) @app.path( model=Model, path="/", converters={id: type("")}, get_converters=get_converters, ) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/link?id=1") assert response.body == b"http://localhost/?id=1" response = c.get("/?id=broken", status=400) response = c.get("/") assert response.body in ( b"View: None (<type 'NoneType'>)", b"View: None (<class 'NoneType'>)", ) def test_url_parameter_implicit_converter(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="/") def get_model(id=0): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/link?id=1") assert response.body == b"http://localhost/?id=1" response = c.get("/?id=broken", status=400) response = c.get("/") assert response.body in ( b"View: 0 (<type 'int'>)", b"View: 0 (<class 'int'>)", ) def test_multiple_url_parameters_stable_order(): class App(morepath.App): pass class Model: def __init__(self, a, b): self.a = a self.b = b @App.path(model=Model, path="/") def get_model(a, b): return Model(a, b) @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/link?a=A&b=B") assert response.body == b"http://localhost/?a=A&b=B" def test_url_parameter_explicit_trumps_implicit(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="/", converters=dict(id=Converter(int))) def get_model(id="foo"): return Model(id) @app.view(model=Model) def default(self, request): return "View: {} ({})".format(self.id, type(self.id)) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=1") assert response.body in ( b"View: 1 (<type 'int'>)", b"View: 1 (<class 'int'>)", ) response = c.get("/link?id=1") assert response.body == b"http://localhost/?id=1" response = c.get("/?id=broken", status=400) response = c.get("/") assert response.body in ( b"View: foo (<type 'str'>)", b"View: foo (<class 'str'>)", ) def test_decode_encode(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id def my_decode(s): return s + "ADD" def my_encode(s): return s[: -len("ADD")] @app.path( model=Model, path="/", converters=dict(id=Converter(my_decode, my_encode)), ) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: %s" % self.id @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=foo") assert response.body == b"View: fooADD" response = c.get("/link?id=foo") assert response.body == b"http://localhost/?id=foo" def test_unknown_converter(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d class Unknown: pass @app.path(model=Model, path="/") def get_model(d=Unknown()): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) with pytest.raises(DirectiveReportError): app.commit() def test_not_all_path_variables_arguments_of_model_factory(): class App(morepath.App): pass class Model: def __init__(self, foo): self.foo = foo class Unknown: pass @App.path(model=Model, path="/{foo}/{bar}") def get_model(foo): return Model(foo) with pytest.raises(DirectiveReportError) as e: App.commit() assert str(e.value).startswith( "Variable in path not found in function " "signature: bar" ) def test_unknown_explicit_converter(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d class Unknown: pass @app.path(model=Model, path="/", converters={"d": Unknown}) def get_model(d): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) with pytest.raises(DirectiveReportError): app.commit() def test_default_date_converter(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d from datetime import date @app.path(model=Model, path="/") def get_model(d=date(2011, 1, 1)): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?d=20121110") assert response.body == b"View: 2012-11-10" response = c.get("/") assert response.body == b"View: 2011-01-01" response = c.get("/link?d=20121110") assert response.body == b"http://localhost/?d=20121110" response = c.get("/link") assert response.body == b"http://localhost/?d=20110101" response = c.get("/?d=broken", status=400) def test_default_datetime_converter(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d from datetime import datetime @app.path(model=Model, path="/") def get_model(d=datetime(2011, 1, 1, 10, 30)): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?d=20121110T144530") assert response.body == b"View: 2012-11-10 14:45:30" response = c.get("/") assert response.body == b"View: 2011-01-01 10:30:00" response = c.get("/link?d=20121110T144500") assert response.body == b"http://localhost/?d=20121110T144500" response = c.get("/link") assert response.body == b"http://localhost/?d=20110101T103000" c.get("/?d=broken", status=400) def test_custom_date_converter(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d from datetime import date from time import strptime, mktime def date_decode(s): return date.fromtimestamp(mktime(strptime(s, "%d-%m-%Y"))) def date_encode(d): return d.strftime("%d-%m-%Y") @app.converter(type=date) def date_converter(): return Converter(date_decode, date_encode) @app.path(model=Model, path="/") def get_model(d=date(2011, 1, 1)): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?d=10-11-2012") assert response.body == b"View: 2012-11-10" response = c.get("/") assert response.body == b"View: 2011-01-01" response = c.get("/link?d=10-11-2012") assert response.body == b"http://localhost/?d=10-11-2012" response = c.get("/link") assert response.body == b"http://localhost/?d=01-01-2011" response = c.get("/?d=broken", status=400) def test_variable_path_parameter_required_no_default(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="", required=["id"]) def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: %s" % self.id @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=a") assert response.body == b"View: a" response = c.get("/", status=400) def test_variable_path_parameter_required_with_default(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="", required=["id"]) def get_model(id="b"): return Model(id) @app.view(model=Model) def default(self, request): return "View: %s" % self.id @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?id=a") assert response.body == b"View: a" response = c.get("/", status=400) def test_type_hints_and_converters(): class app(morepath.App): pass class Model: def __init__(self, d): self.d = d from datetime import date @app.path(model=Model, path="", converters=dict(d=date)) def get_model(d): return Model(d) @app.view(model=Model) def default(self, request): return "View: %s" % self.d @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?d=20140120") assert response.body == b"View: 2014-01-20" response = c.get("/link?d=20140120") assert response.body == b"http://localhost/?d=20140120" def test_link_for_none_means_no_parameter(): class app(morepath.App): pass class Model: def __init__(self, id): self.id = id @app.path(model=Model, path="") def get_model(id): return Model(id) @app.view(model=Model) def default(self, request): return "View: %s" % self.id @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/") assert response.body == b"View: None" response = c.get("/link") assert response.body == b"http://localhost/" def test_path_and_url_parameter_converter(): class app(morepath.App): pass class Model: def __init__(self, id, param): self.id = id self.param = param from datetime import date @app.path(model=Model, path="/{id}", converters=dict(param=date)) def get_model(id=0, param=None): return Model(id, param) @app.view(model=Model) def default(self, request): return f"View: {self.id} {self.param}" @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/1/link") assert response.body == b"http://localhost/1" def test_path_converter_fallback_on_view(): class app(morepath.App): pass class Root: pass class Model: def __init__(self, id): self.id = id @app.path(model=Root, path="") def get_root(): return Root() @app.path(model=Model, path="/{id}") def get_model(id=0): return Model(id) @app.view(model=Model) def default(self, request): return "Default view for %s" % self.id @app.view(model=Root, name="named") def named(self, request): return "Named view on root" c = Client(app()) response = c.get("/1") assert response.body == b"Default view for 1" response = c.get("/named") assert response.body == b"Named view on root" def test_root_named_link(): class app(morepath.App): pass @app.path(path="") class Root: pass @app.view(model=Root) def default(self, request): return request.link(self, "foo") c = Client(app()) response = c.get("/") assert response.body == b"http://localhost/foo" def test_path_class_and_model_argument(): class app(morepath.App): pass class Foo: pass @app.path(path="", model=Foo) class Root: pass with pytest.raises(ConfigError): app.commit() def test_path_no_class_and_no_model_argument(): class app(morepath.App): pass @app.path(path="") def get_foo(): return None with pytest.raises(ConfigError): app.commit() def test_url_parameter_list(): class app(morepath.App): pass class Model: def __init__(self, item): self.item = item @app.path(model=Model, path="/", converters={"item": [int]}) def get_model(item): return Model(item) @app.view(model=Model) def default(self, request): return repr(self.item) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?item=1&item=2") assert response.body == b"[1, 2]" response = c.get("/link?item=1&item=2") assert response.body == b"http://localhost/?item=1&item=2" response = c.get("/link") assert response.body == b"http://localhost/" response = c.get("/?item=broken&item=1", status=400) response = c.get("/") assert response.body == b"[]" def test_url_parameter_list_empty(): class app(morepath.App): pass class Model: def __init__(self, item): self.item = item @app.path(model=Model, path="/", converters={"item": []}) def get_model(item): return Model(item) @app.view(model=Model) def default(self, request): return repr(self.item) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?item=a&item=b") assert response.body in (b"[u'a', u'b']", b"['a', 'b']") response = c.get("/link?item=a&item=b") assert response.body == b"http://localhost/?item=a&item=b" response = c.get("/link") assert response.body == b"http://localhost/" response = c.get("/") assert response.body == b"[]" def test_url_parameter_list_explicit_converter(): class app(morepath.App): pass class Model: def __init__(self, item): self.item = item @app.path(model=Model, path="/", converters={"item": [Converter(int)]}) def get_model(item): return Model(item) @app.view(model=Model) def default(self, request): return repr(self.item) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?item=1&item=2") assert response.body == b"[1, 2]" response = c.get("/link?item=1&item=2") assert response.body == b"http://localhost/?item=1&item=2" response = c.get("/link") assert response.body == b"http://localhost/" response = c.get("/?item=broken&item=1", status=400) response = c.get("/") assert response.body == b"[]" def test_url_parameter_list_unknown_explicit_converter(): class app(morepath.App): pass class Model: def __init__(self, item): self.item = item class Unknown: pass @app.path(model=Model, path="/", converters={"item": [Unknown]}) def get_model(item): return Model(item) with pytest.raises(DirectiveReportError): app.commit() def test_url_parameter_list_but_only_one_allowed(): class app(morepath.App): pass class Model: def __init__(self, item): self.item = item @app.path(model=Model, path="/", converters={"item": int}) def get_model(item): return Model(item) @app.view(model=Model) def default(self, request): return repr(self.item) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) c.get("/?item=1&item=2", status=400) c.get("/link?item=1&item=2", status=400) def test_extra_parameters(): class app(morepath.App): pass class Model: def __init__(self, extra_parameters): self.extra_parameters = extra_parameters @app.path(model=Model, path="/") def get_model(extra_parameters): return Model(extra_parameters) @app.view(model=Model) def default(self, request): return repr(sorted(self.extra_parameters.items())) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?a=A&b=B") assert response.body in ( b"[(u'a', u'A'), (u'b', u'B')]", b"[('a', 'A'), ('b', 'B')]", ) response = c.get("/link?a=A&b=B") assert sorted(response.body[len("http://localhost/?") :].split(b"&")) == [ b"a=A", b"b=B", ] def test_extra_parameters_with_get_converters(): class app(morepath.App): pass class Model: def __init__(self, extra_parameters): self.extra_parameters = extra_parameters def get_converters(): return { "a": int, "b": type(""), } @app.path(model=Model, path="/", get_converters=get_converters) def get_model(extra_parameters): return Model(extra_parameters) @app.view(model=Model) def default(self, request): return repr(sorted(self.extra_parameters.items())) @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get("/?a=1&b=B") assert response.body in ( b"[(u'a', 1), (u'b', u'B')]", b"[('a', 1), ('b', 'B')]", ) response = c.get("/link?a=1&b=B") assert sorted(response.body[len("http://localhost/?") :].split(b"&")) == [ b"a=1", b"b=B", ] c.get("/?a=broken&b=B", status=400) def test_script_name(): class app(morepath.App): pass class Model: def __init__(self): pass @app.path(model=Model, path="simple") def get_model(): return Model() @app.view(model=Model) def default(self, request): return "View" @app.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(app()) response = c.get( "/prefix/simple", extra_environ=dict(SCRIPT_NAME="/prefix") ) assert response.body == b"View" response = c.get( "/prefix/simple/link", extra_environ=dict(SCRIPT_NAME="/prefix") ) assert response.body == b"http://localhost/prefix/simple" def test_sub_path_different_variable(): # See discussion in https://github.com/morepath/morepath/issues/155 class App(morepath.App): pass class Foo: def __init__(self, id): self.id = id class Bar: def __init__(self, id, foo): self.id = id self.foo = foo @App.path(model=Foo, path="{id}") def get_foo(id): return Foo(id) @App.path(model=Bar, path="{foo_id}/{bar_id}") def get_client(foo_id, bar_id): return Bar(bar_id, Foo(foo_id)) @App.view(model=Foo) def default_sbar(self, request): return "M: %s" % self.id @App.view(model=Bar) def default_bar(self, request): return f"S: {self.id} {self.foo.id}" c = Client(App()) with pytest.raises(TrajectError) as ex: response = c.get("/a") assert response.body == b"M: a" response = c.get("/a/b") assert response.body == b"S: b a" assert str(ex.value) == "step {id} and {foo_id} are in conflict" def test_absorb_path(): class app(morepath.App): pass class Root: pass class Model: def __init__(self, absorb): self.absorb = absorb @app.path(model=Root, path="") def get_root(): return Root() @app.path(model=Model, path="foo", absorb=True) def get_model(absorb): return Model(absorb) @app.view(model=Model) def default(self, request): return "%s" % self.absorb @app.view(model=Root) def default_root(self, request): return request.link(Model("a/b")) c = Client(app()) response = c.get("/foo/a") assert response.body == b"a" response = c.get("/foo") assert response.body == b"" response = c.get("/foo/a/b") assert response.body == b"a/b" # link to a/b absorb response = c.get("/") assert response.body == b"http://localhost/foo/a/b" def test_absorb_path_with_variables(): class app(morepath.App): pass class Root: pass class Model: def __init__(self, id, absorb): self.id = id self.absorb = absorb @app.path(model=Root, path="") def get_root(): return Root() @app.path(model=Model, path="{id}", absorb=True) def get_model(id, absorb): return Model(id, absorb) @app.view(model=Model) def default(self, request): return f"I:{self.id} A:{self.absorb}" @app.view(model=Root) def default_root(self, request): return request.link(Model("foo", "a/b")) c = Client(app()) response = c.get("/foo/a") assert response.body == b"I:foo A:a" response = c.get("/foo") assert response.body == b"I:foo A:" response = c.get("/foo/a/b") assert response.body == b"I:foo A:a/b" # link to a/b absorb response = c.get("/") assert response.body == b"http://localhost/foo/a/b" def test_absorb_path_explicit_subpath_ignored(): class app(morepath.App): pass class Root: pass class Model: def __init__(self, absorb): self.absorb = absorb class Another: pass @app.path(model=Root, path="") def get_root(): return Root() @app.path(model=Model, path="foo", absorb=True) def get_model(absorb): return Model(absorb) @app.path(model=Another, path="foo/another") def get_another(): return Another() @app.view(model=Model) def default(self, request): return "%s" % self.absorb @app.view(model=Another) def default_another(self, request): return "Another" @app.view(model=Root) def default_root(self, request): return request.link(Another()) c = Client(app()) response = c.get("/foo/a") assert response.body == b"a" response = c.get("/foo/another") assert response.body == b"another" # link to another still works XXX is this wrong? response = c.get("/") assert response.body == b"http://localhost/foo/another" def test_absorb_path_root(): class app(morepath.App): pass class Model: def __init__(self, absorb): self.absorb = absorb @app.path(model=Model, path="", absorb=True) def get_model(absorb): return Model(absorb) @app.view(model=Model) def default(self, request): return "A:{} L:{}".format(self.absorb, request.link(self)) c = Client(app()) response = c.get("/a") assert response.body == b"A:a L:http://localhost/a" response = c.get("/") assert response.body == b"A: L:http://localhost/" response = c.get("/a/b") assert response.body == b"A:a/b L:http://localhost/a/b" def test_path_explicit_variables(): class App(morepath.App): pass class Model: def __init__(self, id): self.store_id = id @App.path( model=Model, path="models/{id}", variables=lambda m: {"id": m.store_id} ) def get_model(id): return Model(id) @App.view(model=Model) def default(self, request): return request.link(self) c = Client(App()) response = c.get("/models/1") assert response.body == b"http://localhost/models/1" def test_path_explicit_variables_app_arg(): class App(morepath.App): pass class Model: def __init__(self, id): self.store_id = id def my_variables(app, m): assert isinstance(app, App) return {"id": m.store_id} @App.path(model=Model, path="models/{id}", variables=my_variables) def get_model(id): return Model(id) @App.view(model=Model) def default(self, request): return request.link(self) c = Client(App()) response = c.get("/models/1") assert response.body == b"http://localhost/models/1" def test_error_when_path_variable_is_none(): class App(morepath.App): pass class Model: def __init__(self, id): self.store_id = id @App.path(model=Model, path="models/{id}", variables=lambda m: {"id": None}) def get_model(id): return Model(id) @App.view(model=Model) def default(self, request): return request.link(self) c = Client(App()) with pytest.raises(LinkError): c.get("/models/1") def test_error_when_path_variable_is_missing(): class App(morepath.App): pass class Model: def __init__(self, id): self.store_id = id @App.path(model=Model, path="models/{id}", variables=lambda m: {}) def get_model(id): return Model(id) @App.view(model=Model) def default(self, request): return request.link(self) c = Client(App()) with pytest.raises(KeyError): c.get("/models/1") def test_error_when_path_variables_isnt_dict(): class App(morepath.App): pass class Model: def __init__(self, id): self.store_id = id @App.path(model=Model, path="models/{id}", variables=lambda m: "nondict") def get_model(id): return Model(id) @App.view(model=Model) def default(self, request): return request.link(self) c = Client(App()) with pytest.raises(LinkError): c.get("/models/1") def test_resolve_path_method_on_request_same_app(): class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="simple") def get_model(): return Model() @App.view(model=Model) def default(self, request): return str(isinstance(request.resolve_path("simple"), Model)) @App.view(model=Model, name="extra") def extra(self, request): return str(request.resolve_path("nonexistent") is None) @App.view(model=Model, name="appnone") def appnone(self, request): return request.resolve_path("simple", app=None) c = Client(App()) response = c.get("/simple") assert response.body == b"True" response = c.get("/simple/extra") assert response.body == b"True" with pytest.raises(LinkError): c.get("/simple/appnone") def test_resolve_path_method_on_request_different_app(): class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="simple") def get_model(): return Model() @App.view(model=Model) def default(self, request): obj = request.resolve_path("p", app=request.app.child("sub")) return str(isinstance(obj, SubModel)) class Sub(morepath.App): pass class SubModel: pass @Sub.path(model=SubModel, path="p") def get_sub_model(): return SubModel() @App.mount(path="sub", app=Sub) def mount_sub(): return Sub() c = Client(App()) response = c.get("/simple") assert response.body == b"True" def test_resolve_path_with_dots_in_url(): class app(morepath.App): pass class Root: def __init__(self, absorb): self.absorb = absorb @app.path(model=Root, path="root", absorb=True) def get_root(absorb): return Root(absorb) @app.view(model=Root) def default(self, request): return "%s" % self.absorb c = Client(app()) response = c.get("/root/x/../child") assert response.body == b"child" response = c.get("/root/x/%2E%2E/child") assert response.body == b"child" response = c.get("/root/%2E%2E/%2E%2E/root") assert response.body == b"" response = c.get("/root/%2E%2E/%2E%2E/root") assert response.body == b"" response = c.get("/root/%2E%2E/%2E%2E/test", expect_errors=True) assert response.status_code == 404 def test_quoting_link_generation(): class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="sim?ple") def get_model(): return Model() @App.view(model=Model) def default(self, request): return "View" @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/sim%3Fple") assert response.body == b"View" response = c.get("/sim%3Fple/link") assert response.body == b"http://localhost/sim%3Fple" def test_quoting_link_generation_umlaut(): class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="simëple") def get_model(): return Model() @App.view(model=Model) def default(self, request): return "View" @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/sim%C3%ABple") assert response.body == b"View" response = c.get("/sim%C3%ABple/link") assert response.body == b"http://localhost/sim%C3%ABple" def test_quoting_link_generation_tilde(): # tilde is an unreserved character according to # https://www.ietf.org/rfc/rfc3986.txt but urllib.quote # quotes it anyway. We test whether our workaround using # the safe parameter works class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="sim~ple") def get_model(): return Model() @App.view(model=Model) def default(self, request): return "View" @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/sim~ple") assert response.body == b"View" response = c.get("/sim~ple/link") assert response.body == b"http://localhost/sim~ple" def test_parameter_quoting(): class App(morepath.App): pass class Model: def __init__(self, s): self.s = s @App.path(model=Model, path="") def get_model(s): return Model(s) @App.view(model=Model) def default(self, request): return "View: %s" % self.s @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/?s=sim%C3%ABple") assert response.body == "View: simëple".encode() response = c.get("/link?s=sim%C3%ABple") assert response.body == b"http://localhost/?s=sim%C3%ABple" def test_parameter_quoting_tilde(): class App(morepath.App): pass class Model: def __init__(self, s): self.s = s @App.path(model=Model, path="") def get_model(s): return Model(s) @App.view(model=Model) def default(self, request): return "View: %s" % self.s @App.view(model=Model, name="link") def link(self, request): return request.link(self) c = Client(App()) response = c.get("/?s=sim~ple") assert response.body == b"View: sim~ple" response = c.get("/link?s=sim~ple") assert response.body == b"http://localhost/?s=sim~ple" def test_class_link_without_variables(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo") def get_model(): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model) c = Client(App()) response = c.get("/foo") assert response.body == b"http://localhost/foo" def test_class_link_no_app(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo") def get_model(): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model, app=None) c = Client(App()) with pytest.raises(LinkError): c.get("/foo") def test_class_link_with_variables(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo/{x}") def get_model(x): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model, variables={"x": "X"}) c = Client(App()) response = c.get("/foo/3") assert response.body == b"http://localhost/foo/X" def test_class_link_with_missing_variables(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo/{x}") def get_model(x): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model, variables={}) c = Client(App()) with pytest.raises(KeyError): c.get("/foo/3") def test_class_link_with_extra_variable(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo/{x}") def get_model(x): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model, variables={"x": "X", "y": "Y"}) c = Client(App()) response = c.get("/foo/3") assert response.body == b"http://localhost/foo/X" def test_class_link_with_url_parameter_variable(): class App(morepath.App): pass class Model: pass @App.path(model=Model, path="/foo/{x}") def get_model(x, y): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Model, variables={"x": "X", "y": "Y"}) c = Client(App()) response = c.get("/foo/3") assert response.body == b"http://localhost/foo/X?y=Y" def test_class_link_with_subclass(): class App(morepath.App): pass class Model: pass class Sub(Model): pass @App.path(model=Model, path="/foo/{x}") def get_model(x): return Model() @App.view(model=Model) def link(self, request): return request.class_link(Sub, variables={"x": "X"}) c = Client(App()) response = c.get("/foo/3") assert response.body == b"http://localhost/foo/X" def test_absorb_class_path(): class App(morepath.App): pass class Root: pass class Model: def __init__(self, absorb): self.absorb = absorb @App.path(model=Root, path="") def get_root(): return Root() @App.path(model=Model, path="foo", absorb=True) def get_model(absorb): return Model(absorb) @App.view(model=Model) def default(self, request): return "%s" % self.absorb @App.view(model=Root) def default_root(self, request): return request.class_link(Model, variables={"absorb": "a/b"}) c = Client(App()) # link to a/b absorb response = c.get("/") assert response.body == b"http://localhost/foo/a/b" def test_absorb_class_path_with_variables(): class App(morepath.App): pass class Root: pass class Model: def __init__(self, id, absorb): self.id = id self.absorb = absorb @App.path(model=Root, path="") def get_root(): return Root() @App.path(model=Model, path="{id}", absorb=True) def get_model(id, absorb): return Model(id, absorb) @App.view(model=Model) def default(self, request): return f"I:{self.id} A:{self.absorb}" @App.view(model=Root) def default_root(self, request): return request.class_link(Model, variables=dict(id="foo", absorb="a/b")) c = Client(App()) # link to a/b absorb response = c.get("/") assert response.body == b"http://localhost/foo/a/b" def test_class_link_extra_parameters(): class App(morepath.App): pass class Model: def __init__(self, extra_parameters): self.extra_parameters = extra_parameters @App.path(model=Model, path="/") def get_model(extra_parameters): return Model(extra_parameters) @App.view(model=Model) def default(self, request): return repr(sorted(self.extra_parameters.items())) @App.view(model=Model, name="link") def link(self, request): return request.class_link( Model, variables={"extra_parameters": {"a": "A", "b": "B"}} ) c = Client(App()) response = c.get("/link?a=A&b=B") assert sorted(response.body[len("http://localhost/?") :].split(b"&")) == [ b"a=A", b"b=B", ] def test_path_on_model_class(): class App(morepath.App): pass @App.path("/") class Model: def __init__(self): pass @App.path("/login") class Login: pass @App.view(model=Model) def model_view(self, request): return "Model" @App.view(model=Login) def login_view(self, request): return "Login" c = Client(App()) response = c.get("/") assert response.body == b"Model" response = c.get("/login") assert response.body == b"Login" def test_path_without_model(): class App(morepath.App): pass @App.path("/") def get_path(): pass with pytest.raises(dectate.DirectiveReportError): App.commit() def test_two_path_on_same_model_should_conflict(): class App(morepath.App): pass @App.path("/login") @App.path("/") class Login: pass with pytest.raises(dectate.ConflictError): App.commit() def test_path_on_same_model_explicit_and_class_should_conflict(): class App(morepath.App): pass @App.path("/") class Login: pass @App.path("/login", model=Login) def get_path(): return Login() with pytest.raises(dectate.ConflictError): App.commit() def test_nonexisting_path_too_long_unconsumed(): class App(morepath.App): pass class Model: def __init__(self): pass @App.path(model=Model, path="simple") def get_model(): return Model() @App.view(model=Model) def default(self, request): return "View" c = Client(App()) c.get("/foo/bar/baz", status=404) def test_collection_and_item(): class App(morepath.App): pass class Collection: def __init__(self): self.items = {} class Item: def __init__(self, id): self.id = id collection = Collection() collection.items["a"] = Item("a") collection.items["b"] = Item("b") @App.path(model=Collection, path="/") def get_collection(): return collection @App.path(model=Item, path="/{id}") def get_item(id): return collection.items.get(id) @App.view(model=Collection) def default_collection(self, request): return "Collection" @App.view(model=Item) def default(self, request): return "View: %s" % self.id c = Client(App()) r = c.get("/c", status=404) assert r.body != "Collection" r = c.get("/a") assert r.body == b"View: a" def test_view_for_missing(): class App(morepath.App): pass class Item: def __init__(self, id): self.id = id @App.path(model=Item, path="/{id}") def get_item(id): if id == "found": return Item(id) return None @App.view(model=Item, name="edit") def default(self, request): return "View: %s" % self.id c = Client(App()) c.get("/notfound/+edit", status=404) c.get("/notfound/edit", status=404) def test_absorb_error(): class App(morepath.App): pass @App.path("/") class Root: pass @App.view(model=Root) def view_root(self, request): return "root" class File: def __init__(self, absorb): self.absorb = absorb @App.path("/files", model=File, absorb=True) def get_file(absorb): if absorb == "foo": return File("foo") return None @App.view(model=File) def view_file(self, request): return request.path App.commit() client = Client(App()) assert client.get("/").text == "root" assert client.get("/files/foo").text == "/files/foo" client.get("/files/bar", status=404) def test_named_view_on_root(): class App(morepath.App): pass @App.path(path="/") class Root: pass @App.view(model=Root, name="named") def named(self, request): return "Named view on root" @App.view(model=Root) def default(self, request): return "Default view on root" c = Client(App()) response = c.get("/named") assert response.body == b"Named view on root" response = c.get("/+named") assert response.body == b"Named view on root" response = c.get("/") assert response.body == b"Default view on root"

22.280756

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0.585475

6,766

50,711

4.276973

0.03828

0.055982

0.056811

0.066971

0.850266

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0.741067

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0

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50,711

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22.290549

0.759172

0.007257

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0.745891

0

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0.001887

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0.082174

1

0.219343

false

0.072693

0.007585

0.128951

0.465234

0

null

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0

null

0

1

0

1

0

1

0

10

5ed94d394ca28614c2131c6c94838c1d9d1edccf

79

py

Python

py-bindings/ompl/morse/__init__.py

ericpairet/ompl

25c76431cef25f0100ed74d09dd88944ecca5ee1

[ "BSD-3-Clause" ]

837

2015-01-07T12:01:20.000Z

2022-03-31T08:42:42.000Z

py-bindings/ompl/morse/__init__.py

ericpairet/ompl

25c76431cef25f0100ed74d09dd88944ecca5ee1

[ "BSD-3-Clause" ]

271

2015-01-12T22:05:06.000Z

2022-03-30T22:16:01.000Z

py-bindings/ompl/morse/__init__.py

ericpairet/ompl

25c76431cef25f0100ed74d09dd88944ecca5ee1

[ "BSD-3-Clause" ]

452

2015-02-10T08:48:21.000Z

2022-03-23T06:53:33.000Z

from ompl import control from ompl import util from ompl.morse._morse import *

19.75

31

0.810127

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null

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1

0

1

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7

5efc9596aa75a5600fc62a1e2dd1eed0cd965fb7

2,258

py

Python

pandora/evaluation.py

mikekestemont/pandora

ecae769c8dac5cce563da114be923d22eec6656d

[ "MIT" ]

2

2016-02-19T10:23:17.000Z

2016-09-28T16:14:41.000Z

pandora/evaluation.py

mikekestemont/pandora

ecae769c8dac5cce563da114be923d22eec6656d

[ "MIT" ]

6

2016-06-22T12:40:57.000Z

2018-04-16T08:39:52.000Z

pandora/evaluation.py

mikekestemont/pandora

ecae769c8dac5cce563da114be923d22eec6656d

[ "MIT" ]

3

2016-01-10T10:24:53.000Z

2017-02-06T13:47:20.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import print_function from collections import Counter from operator import itemgetter import numpy as np def single_label_accuracies(gold, silver, test_tokens, known_tokens, print_scores=True): """ Calculate accuracies for all, known and unknown tokens. Uses index of items seen during training. """ kno_corr, unk_corr = 0.0, 0.0 nb_kno, nb_unk = 0.0, 0.0 for gold_pred, silver_pred, tok in zip(gold, silver, test_tokens): if tok in known_tokens: nb_kno += 1 if gold_pred == silver_pred: kno_corr += 1 else: nb_unk += 1 if gold_pred == silver_pred: unk_corr += 1 all_acc = (kno_corr + unk_corr) / (nb_kno + nb_unk) kno_acc = kno_corr / nb_kno # account for situation with no unknowns: unk_acc = 0.0 if nb_unk > 0: unk_acc = unk_corr / nb_unk if print_scores: print('+\tall acc:', all_acc) print('+\tkno acc:', kno_acc) print('+\tunk acc:', unk_acc) return all_acc, kno_acc, unk_acc def multilabel_accuracies(gold, silver, test_tokens, known_tokens, print_scores=True): """ Calculate accuracies for all, known and unknown tokens. Uses index of items seen during training. """ kno_corr, unk_corr = 0.0, 0.0 nb_kno, nb_unk = 0.0, 0.0 for gold_pred, silver_pred, tok in zip(gold, silver, test_tokens): gold_pred = set(gold_pred.split('|')) silver_pred = set(silver_pred.split('|')) if tok in known_tokens: nb_kno += 1 if gold_pred == silver_pred: kno_corr += 1 else: nb_unk += 1 if gold_pred == silver_pred: unk_corr += 1 all_acc = (kno_corr + unk_corr) / (nb_kno + nb_unk) kno_acc = kno_corr / nb_kno # account for situation with no unknowns: unk_acc = 0.0 if nb_unk > 0: unk_acc = unk_corr / nb_unk if print_scores: print('+\tall acc:', all_acc) print('+\tkno acc:', kno_acc) print('+\tunk acc:', unk_acc) return all_acc, kno_acc, unk_acc

27.536585

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null

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null

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5eff49ab774b5be893f7416e32ca525bbae6a16e

487

py

Python

PythonAPI/carissma_project/lib/python3.5/site-packages/pandas/tests/util/conftest.py

AbdulHoffmann/carla_carissma

8d382769ffa02a6c61a22c57160285505f5ff0a4

[ "MIT" ]

6,989

2017-07-18T06:23:18.000Z

2022-03-31T15:58:36.000Z

pandas/tests/util/conftest.py

ivan-vasilev/pandas

4071dde86e33434e1bee8304fa62074949f813cc

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1,978

2017-07-18T09:17:58.000Z

2022-03-31T14:28:43.000Z

pandas/tests/util/conftest.py

ivan-vasilev/pandas

4071dde86e33434e1bee8304fa62074949f813cc

[ "BSD-3-Clause" ]

1,228

2017-07-18T09:03:13.000Z

2022-03-29T05:57:40.000Z

import pytest @pytest.fixture(params=[True, False]) def check_dtype(request): return request.param @pytest.fixture(params=[True, False]) def check_exact(request): return request.param @pytest.fixture(params=[True, False]) def check_index_type(request): return request.param @pytest.fixture(params=[True, False]) def check_less_precise(request): return request.param @pytest.fixture(params=[True, False]) def check_categorical(request): return request.param

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6f00cb70eb55f632b4ba112286e58fc480249411

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py

Python

files/python_by_examples/loops/comprehensions/p01_list_comprehensions.py

Sher-Chowdhury/CentOS7-Python

2282aa2b8396891a060a132a3b340cc810bbf746

[ "Apache-2.0" ]

null

files/python_by_examples/loops/comprehensions/p01_list_comprehensions.py

Sher-Chowdhury/CentOS7-Python

2282aa2b8396891a060a132a3b340cc810bbf746

[ "Apache-2.0" ]

null

files/python_by_examples/loops/comprehensions/p01_list_comprehensions.py

Sher-Chowdhury/CentOS7-Python

2282aa2b8396891a060a132a3b340cc810bbf746

[ "Apache-2.0" ]

null

a = [1, 3, 5, 7, 9, 11] [print(x) for x in a]

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py

Python

scripts/slave/recipe_modules/skia/fake_specs.py

bopopescu/build

4e95fd33456e552bfaf7d94f7d04b19273d1c534

[ "BSD-3-Clause" ]

null

scripts/slave/recipe_modules/skia/fake_specs.py

bopopescu/build

4e95fd33456e552bfaf7d94f7d04b19273d1c534

[ "BSD-3-Clause" ]

null

scripts/slave/recipe_modules/skia/fake_specs.py

bopopescu/build

4e95fd33456e552bfaf7d94f7d04b19273d1c534

[ "BSD-3-Clause" ]

1

2020-07-23T10:57:32.000Z

# This file is generated by the scripts/slave/skia/gen_buildbot_specs.py script. 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'/usr/bin/clang', 'CXX': '/usr/bin/clang++', 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_clang_build=1 skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Mac10.8-Clang-Arm7-Debug-Android': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'Clang', 'configuration': 'Debug', 'extra_config': 'Android', 'is_trybot': False, 'os': 'Mac10.8', 'role': 'Build', 'target_arch': 'Arm7', }, 'configuration': 'Debug', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'CC': '/usr/bin/clang', 'CXX': '/usr/bin/clang++', 'GYP_DEFINES': 'skia_arch_type=arm skia_clang_build=1 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Mac10.9-Clang-Arm7-Debug-iOS': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'Clang', 'configuration': 'Debug', 'extra_config': 'iOS', 'is_trybot': False, 'os': 'Mac10.9', 'role': 'Build', 'target_arch': 'Arm7', }, 'configuration': 'Debug', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'CC': '/usr/bin/clang', 'CXX': '/usr/bin/clang++', 'GYP_DEFINES': ('skia_arch_type=arm skia_clang_build=1 skia_os=ios skia_warnings_a' 's_errors=1'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-Arm7-Debug-Android': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Debug', 'extra_config': 'Android', 'is_trybot': False, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'Arm7', }, 'configuration': 'Debug', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=arm skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-Arm7-Debug-Android-Trybot': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Debug', 'extra_config': 'Android', 'is_trybot': True, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'Arm7', }, 'configuration': 'Debug', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=arm skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-Arm7-Release-Android': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Release', 'extra_config': 'Android', 'is_trybot': False, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'Arm7', }, 'configuration': 'Release', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=arm skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-x86_64-Debug-Swarming': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Debug', 'extra_config': 'Swarming', 'is_trybot': False, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'x86_64', }, 'configuration': 'Debug', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-x86_64-Release-CMake': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Release', 'extra_config': 'CMake', 'is_trybot': False, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'x86_64', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-x86_64-Release-Swarming-Trybot': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Release', 'extra_config': 'Swarming', 'is_trybot': True, 'os': 'Ubuntu', 'role': 'Build', 'target_arch': 'x86_64', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_warnings_as_errors=1', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Build-Ubuntu-GCC-x86_64-Release-SwarmingValgrind': { 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'GCC', 'configuration': 'Release', 'extra_config': 'SwarmingValgrind', 'is_trybot': False, 'os': 'Ubuntu', 'role': 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{ 'build_targets': [ 'most', ], 'builder_cfg': { 'compiler': 'MSVC', 'configuration': 'Release', 'extra_config': 'Swarming', 'is_trybot': False, 'os': 'Win8', 'role': 'Build', 'target_arch': 'x86_64', }, 'configuration': 'Release_x64', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': ('qt_sdk=C:/Qt/Qt5.1.0/5.1.0/msvc2012_64/ skia_arch_type=x86_64 ski' 'a_warnings_as_errors=1 skia_win_debuggers_path=c:/DbgHelp skia_wi' 'n_ltcg=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Housekeeper-PerCommit': { 'build_targets': [ 'most', ], 'builder_cfg': { 'frequency': 'PerCommit', 'is_trybot': False, 'role': 'Housekeeper', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_shared_lib=1 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Housekeeper-PerCommit-Trybot': { 'build_targets': [ 'most', ], 'builder_cfg': { 'frequency': 'PerCommit', 'is_trybot': True, 'role': 'Housekeeper', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_shared_lib=1 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Perf-Android-GCC-Nexus5-CPU-NEON-Arm7-Release-Appurify': { 'build_targets': [ 'VisualBenchTest_APK', ], 'builder_cfg': { 'arch': 'Arm7', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'CPU', 'cpu_or_gpu_value': 'NEON', 'extra_config': 'Appurify', 'is_trybot': False, 'model': 'Nexus5', 'os': 'Android', 'role': 'Perf', }, 'configuration': 'Release', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=arm skia_gpu=0 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'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'Tegra3', 'is_trybot': False, 'model': 'Nexus7', 'os': 'Android', 'role': 'Perf', }, 'configuration': 'Release', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=arm skia_dump_stats=1 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'product.board': 'grouper', 'upload_dm_results': True, 'upload_perf_results': True, }, 'Perf-Ubuntu-GCC-GCE-CPU-AVX2-x86_64-Release-Swarming-Trybot': { 'build_targets': [ 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'CPU', 'cpu_or_gpu_value': 'AVX2', 'extra_config': 'Swarming', 'is_trybot': True, 'model': 'GCE', 'os': 'Ubuntu', 'role': 'Perf', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': False, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_gpu=0 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': True, }, 'Perf-Ubuntu-GCC-ShuttleA-GPU-GTX550Ti-x86_64-Release-VisualBench': { 'build_targets': [ 'visualbench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'GTX550Ti', 'extra_config': 'VisualBench', 'is_trybot': False, 'model': 'ShuttleA', 'os': 'Ubuntu', 'role': 'Perf', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': False, 'env': { 'GYP_DEFINES': ('skia_arch_type=x86_64 skia_dump_stats=1 skia_use_sdl=1 skia_warni' 'ngs_as_errors=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': True, }, 'Perf-Win8-MSVC-ShuttleB-GPU-HD4600-x86_64-Release-Trybot': { 'build_targets': [ 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'MSVC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'HD4600', 'is_trybot': True, 'model': 'ShuttleB', 'os': 'Win8', 'role': 'Perf', }, 'configuration': 'Release_x64', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': False, 'env': { 'GYP_DEFINES': ('qt_sdk=C:/Qt/Qt5.1.0/5.1.0/msvc2012_64/ skia_arch_type=x86_64 ski' 'a_dump_stats=1 skia_warnings_as_errors=0 skia_win_debuggers_path=' 'c:/DbgHelp'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': True, }, 'Test-Android-GCC-Nexus6-GPU-Adreno420-Arm7-Release': { 'build_targets': [ 'dm', ], 'builder_cfg': { 'arch': 'Arm7', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'Adreno420', 'is_trybot': False, 'model': 'Nexus6', 'os': 'Android', 'role': 'Test', }, 'configuration': 'Release', 'device_cfg': 'arm_v7_neon', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'GYP_DEFINES': 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'cpu_or_gpu_value': 'AVX2', 'is_trybot': True, 'model': 'GCE', 'os': 'Ubuntu', 'role': 'Test', }, 'configuration': 'Coverage', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'CC': '/usr/bin/clang-3.6', 'CXX': '/usr/bin/clang++-3.6', 'GYP_DEFINES': ('skia_arch_type=x86_64 skia_clang_build=1 skia_gpu=0 skia_warnings' '_as_errors=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': False, 'upload_perf_results': False, }, 'Test-Ubuntu-GCC-GCE-CPU-AVX2-x86_64-Debug': { 'build_targets': [ 'dm', 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Debug', 'cpu_or_gpu': 'CPU', 'cpu_or_gpu_value': 'AVX2', 'is_trybot': False, 'model': 'GCE', 'os': 'Ubuntu', 'role': 'Test', }, 'configuration': 'Debug', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': True, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_gpu=0 skia_warnings_as_errors=0', }, 'nanobench_flags': [ 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'Test', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_gpu=0 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': False, 'upload_perf_results': False, }, 'Test-Ubuntu-GCC-ShuttleA-GPU-GTX550Ti-x86_64-Debug-ZeroGPUCache': { 'build_targets': [ 'dm', 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Debug', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'GTX550Ti', 'extra_config': 'ZeroGPUCache', 'is_trybot': False, 'model': 'ShuttleA', 'os': 'Ubuntu', 'role': 'Test', }, 'configuration': 'Debug', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': True, 'env': { 'GYP_DEFINES': 'skia_arch_type=x86_64 skia_warnings_as_errors=0', }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Test-Ubuntu-GCC-ShuttleA-GPU-GTX550Ti-x86_64-Release-SwarmingValgrind': { 'build_targets': [ 'dm', 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'GTX550Ti', 'extra_config': 'SwarmingValgrind', 'is_trybot': False, 'model': 'ShuttleA', 'os': 'Ubuntu', 'role': 'Test', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': True, 'env': { 'GYP_DEFINES': ('skia_arch_type=x86_64 skia_release_optimization_level=1 skia_warn' 'ings_as_errors=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': False, 'upload_perf_results': False, }, 'Test-Ubuntu-GCC-ShuttleA-GPU-GTX550Ti-x86_64-Release-Valgrind': { 'build_targets': [ 'dm', 'nanobench', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'GCC', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'GTX550Ti', 'extra_config': 'Valgrind', 'is_trybot': False, 'model': 'ShuttleA', 'os': 'Ubuntu', 'role': 'Test', }, 'configuration': 'Release', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': True, 'env': { 'GYP_DEFINES': ('skia_arch_type=x86_64 skia_release_optimization_level=1 skia_warn' 'ings_as_errors=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': False, 'upload_perf_results': False, }, 'Test-Win8-MSVC-ShuttleB-CPU-AVX2-x86_64-Release-Swarming': { 'build_targets': [ 'dm', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'MSVC', 'configuration': 'Release', 'cpu_or_gpu': 'CPU', 'cpu_or_gpu_value': 'AVX2', 'extra_config': 'Swarming', 'is_trybot': False, 'model': 'ShuttleB', 'os': 'Win8', 'role': 'Test', }, 'configuration': 'Release_x64', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'GYP_DEFINES': ('qt_sdk=C:/Qt/Qt5.1.0/5.1.0/msvc2012_64/ skia_arch_type=x86_64 ski' 'a_gpu=0 skia_warnings_as_errors=0 skia_win_debuggers_path=c:/DbgH' 'elp'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Test-Win8-MSVC-ShuttleB-CPU-AVX2-x86_64-Release-Trybot': { 'build_targets': [ 'dm', ], 'builder_cfg': { 'arch': 'x86_64', 'compiler': 'MSVC', 'configuration': 'Release', 'cpu_or_gpu': 'CPU', 'cpu_or_gpu_value': 'AVX2', 'is_trybot': True, 'model': 'ShuttleB', 'os': 'Win8', 'role': 'Test', }, 'configuration': 'Release_x64', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'GYP_DEFINES': ('qt_sdk=C:/Qt/Qt5.1.0/5.1.0/msvc2012_64/ skia_arch_type=x86_64 ski' 'a_gpu=0 skia_warnings_as_errors=0 skia_win_debuggers_path=c:/DbgH' 'elp'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Test-iOS-Clang-iPad4-GPU-SGX554-Arm7-Debug': { 'build_targets': [ 'iOSShell', ], 'builder_cfg': { 'arch': 'Arm7', 'compiler': 'Clang', 'configuration': 'Debug', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'SGX554', 'is_trybot': False, 'model': 'iPad4', 'os': 'iOS', 'role': 'Test', }, 'configuration': 'Debug', 'device_cfg': 'iPad4,1', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': True, 'do_test_steps': True, 'env': { 'CC': '/usr/bin/clang', 'CXX': '/usr/bin/clang++', 'GYP_DEFINES': ('skia_arch_type=arm skia_clang_build=1 skia_os=ios skia_warnings_a' 's_errors=0'), }, 'nanobench_flags': [ '--dummy-flags', ], 'upload_dm_results': True, 'upload_perf_results': False, }, 'Test-iOS-Clang-iPad4-GPU-SGX554-Arm7-Release-Swarming': { 'build_targets': [ 'iOSShell', ], 'builder_cfg': { 'arch': 'Arm7', 'compiler': 'Clang', 'configuration': 'Release', 'cpu_or_gpu': 'GPU', 'cpu_or_gpu_value': 'SGX554', 'extra_config': 'Swarming', 'is_trybot': False, 'model': 'iPad4', 'os': 'iOS', 'role': 'Test', }, 'configuration': 'Release', 'device_cfg': 'iPad4,1', 'dm_flags': [ '--dummy-flags', ], 'do_perf_steps': False, 'do_test_steps': True, 'env': { 'CC': '/usr/bin/clang', 'CXX': '/usr/bin/clang++', 'GYP_DEFINES': 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Python

eod/plugins/yolov5/utils/__init__.py

Helicopt/EOD

b5db36f4ce267bf64d093b8174bde2c4097b4718

[ "Apache-2.0" ]

196

2021-10-30T05:15:36.000Z

2022-03-30T18:43:40.000Z

eod/tasks/det/plugins/yolov5/utils/__init__.py

YZW-explorer/EOD

f10e64de86c0f356ebf5c7e923f4042eec4207b1

[ "Apache-2.0" ]

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2021-10-30T11:33:28.000Z

2022-03-31T14:22:58.000Z

eod/tasks/det/plugins/yolov5/utils/__init__.py

YZW-explorer/EOD

f10e64de86c0f356ebf5c7e923f4042eec4207b1

[ "Apache-2.0" ]

23

2021-11-01T07:26:17.000Z

2022-03-27T05:55:37.000Z

from .optimizer_helper import * # noqa from .lr_helper import * # noqa

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Python

pymotor/plots.py

yoonghm/pymotor

8d9c36b4b1409103634d5a106fd44284b0a70be8

[ "MIT" ]

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2019-11-17T20:05:58.000Z

2021-07-23T12:40:09.000Z

pymotor/plots.py

yoonghm/pymotor

8d9c36b4b1409103634d5a106fd44284b0a70be8

[ "MIT" ]

1

2020-02-10T17:32:42.000Z

2020-03-24T02:29:17.000Z

pymotor/plots.py

yoonghm/pymotor

8d9c36b4b1409103634d5a106fd44284b0a70be8

[ "MIT" ]

2

2020-03-24T02:12:14.000Z

2020-10-27T09:07:37.000Z

import matplotlib.pyplot as plt DEFAULT_PLOT_WIDTH_INCHES = 6.5 DEFAULT_PLOT_HEIGHT_INCHES = 9.0 def _plot_df(df, plot_title='pandas.DataFrame', filename=None, width=DEFAULT_PLOT_WIDTH_INCHES, height=DEFAULT_PLOT_HEIGHT_INCHES, ): if filename is None: plt.switch_backend('TKAgg') else: plt.switch_backend('Agg') labels = list(df.columns.values) num_plots = df.shape[1] - 1 plt.figure(figsize=(width, height), clear=True) for i in range(num_plots): plt.subplot(num_plots, 1, i + 1) plt.plot(df.iloc[:, 0].get_values(), df.iloc[:, i + 1].get_values(), linestyle='solid', linewidth=1, color=(0.0, 0.0, 0.0)) plt.grid(linestyle=':', linewidth=1, color=(0.75, 0.75, 0.75)) plt.ylabel(labels[i + 1]) if i == 0: plt.title(plot_title) if i == num_plots - 1: plt.xlabel(labels[0]) plt.tight_layout() if filename is None: plt.show() else: plt.savefig(filename) def _plot_df_dual(df, series, plot_title='pandas.DataFrame', filename=None, width=DEFAULT_PLOT_WIDTH_INCHES, height=DEFAULT_PLOT_HEIGHT_INCHES, ): if filename is None: plt.switch_backend('TKAgg') else: plt.switch_backend('Agg') labels = list(df.columns.values) num_plots = df.shape[1] - 1 plt.figure(figsize=(width, height), clear=True) for i in range(num_plots): plt.subplot(num_plots, 1, i + 1) plt.plot(df.iloc[:, 0].get_values(), df.iloc[:, i + 1].get_values(), linestyle='solid', linewidth=1, color=(0.0, 0.0, 0.0)) if i == 0: plt.plot(df.iloc[:, 0].get_values(), series.get_values(), linestyle='--', linewidth=1, color=(1.0, 0.0, 0.0)) plt.grid(linestyle=':', linewidth=1, color=(0.75, 0.75, 0.75)) plt.ylabel(labels[i + 1]) if i == 0: plt.title(plot_title) if i == num_plots - 1: plt.xlabel(labels[0]) plt.tight_layout() if filename is None: plt.show() else: plt.savefig(filename)

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Python

experiment/random/tanhTest.py

predoodl/predoo

3a0ba0515373744364a0dd9daf4251867b39650c

[ "MIT" ]

14

2021-03-27T06:19:39.000Z

2022-03-07T01:29:42.000Z

experiment/random/tanhTest.py

predoodl/predoo

3a0ba0515373744364a0dd9daf4251867b39650c

[ "MIT" ]

null

experiment/random/tanhTest.py

predoodl/predoo

3a0ba0515373744364a0dd9daf4251867b39650c

[ "MIT" ]

null

import numpy as np import torch import torch.nn.functional as F import MNN import tensorflow as tf from tensorflow import keras from tensorflow.keras import layers import csv import time import math F_mnn = MNN.expr np.random.seed(0) def input_withDiffDype(x, dtype): return tf.convert_to_tensor(x, dtype=dtype) def tf_TanhWithDiffDype(dtype): return tf.keras.layers.Activation( 'tanh', dtype=dtype ) def torch_input_withDiffDype(x, dtype): return torch.tensor(x,dtype=dtype) def torch_tanhWithDiffType(dtype): torch_tanh = torch.nn.Tanh() # torch_tanh.half() torch_tanh.type(dtype) return torch_tanh def getdataforTorch(f): out = open(file=f, mode="a", newline='') csv_writer = csv.writer(out) for j in range(1000): print('j= ', j) print('------------------------------------------') x = np.random.randn(2, 2) csv_writer.writerow([x]) csv_writer.writerow(["No.", "32_16", "32_64", "64_16", "64_32"]) for i in range(100): print(i) res = [] res.append(i) # x_16 = torch_input_withDiffDype(x, torch.float16) x_32 = torch_input_withDiffDype(x, torch.float32) x_64 = torch_input_withDiffDype(x, torch.float64) torch_tanh_16 = torch_tanhWithDiffType(torch.float16) torch_tanh_32 = torch_tanhWithDiffType(torch.float32) torch_tanh_64 = torch_tanhWithDiffType(torch.float64) out_32_32_1 = torch_tanh_32(x_32).detach().numpy() out_32_16 = torch_tanh_16(x_32).detach().numpy() out_32_64 = torch_tanh_64(x_32).detach().numpy() diff3 = np.mean(out_32_16 - out_32_32_1) # 高精度到低精度 diff4 = np.mean(out_32_64 - out_32_32_1) # 低精度到高精度 res.append(diff3) res.append(diff4) out_64_16 = torch_tanh_16(x_64).detach().numpy() out_64_32 = torch_tanh_32(x_64).detach().numpy() out_64_64 = torch_tanh_64(x_64).detach().numpy() diff5 = np.mean(out_64_16 - out_64_64) # 高精度到低精度 diff6 = np.mean(out_64_32 - out_64_64) # 低精度到高精度 res.append(diff5) res.append(diff6) csv_writer.writerow(res) out.close() def torch_disturb(f): out = open(file=f, mode="a", newline='') csv_writer = csv.writer(out) for j in range(1000): print('j= ', j) print('------------------------------------------') x = np.random.randn(2, 2) a1 = 0.000001 * np.ones((2, 2), np.float64) a2 = 0.00000001 * np.ones((2, 2), np.float64) a3 = 0.0000000001 * np.ones((2, 2), np.float64) csv_writer.writerow([x]) csv_writer.writerow(["No.", "32_16", "32_64", "64_16", "64_32"]) getTorchData(x, csv_writer) csv_writer.writerow(["+10^-6", "32_16", "32_64", "64_16", "64_32"]) getTorchData(x + a1, csv_writer) csv_writer.writerow(["+10^-8", "32_16", "32_64", "64_16", "64_32"]) getTorchData(x + a2, csv_writer) csv_writer.writerow(["+10^-10", "32_16", "32_64", "64_16", "64_32"]) getTorchData(x + a3, csv_writer) out.close() def getTorchData(x,csv_writer): for i in range(20): res = [] res.append(i) # x_16 = torch_input_withDiffDype(x, torch.float16) x_32 = torch_input_withDiffDype(x, torch.float32) x_64 = torch_input_withDiffDype(x, torch.float64) torch_tanh_16 = torch_tanhWithDiffType(torch.float16) torch_tanh_32 = torch_tanhWithDiffType(torch.float32) torch_tanh_64 = torch_tanhWithDiffType(torch.float64) out_32_32_1 = torch_tanh_32(x_32).detach().numpy() out_32_16 = torch_tanh_16(x_32).detach().numpy() out_32_64 = torch_tanh_64(x_32).detach().numpy() diff3 = np.mean(out_32_16 - out_32_32_1) # 高精度到低精度 diff4 = np.mean(out_32_64 - out_32_32_1) # 低精度到高精度 res.append(diff3) res.append(diff4) out_64_16 = torch_tanh_16(x_64).detach().numpy() out_64_32 = torch_tanh_32(x_64).detach().numpy() out_64_64 = torch_tanh_64(x_64).detach().numpy() diff5 = np.mean(out_64_16 - out_64_64) # 高精度到低精度 diff6 = np.mean(out_64_32 - out_64_64) # 低精度到高精度 res.append(diff5) res.append(diff6) csv_writer.writerow(res) def getdataforTensorflow(f): out = open(file=f, mode="a", newline='') csv_writer = csv.writer(out) for j in range(1000): print('j= ', j) print('------------------------------------------') x = np.random.randn(2, 2) csv_writer.writerow([x]) csv_writer.writerow(["No.", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32"]) for i in range(100): print(i) res = [] res.append(i) # TF Pooling x_32 = input_withDiffDype(x, tf.float32) x_16 = input_withDiffDype(x, tf.float16) x_64 = input_withDiffDype(x, tf.float64) tf_Tanh_16 = tf_TanhWithDiffDype('float16') tf_Tanh_32 = tf_TanhWithDiffDype('float32') tf_Tanh_64 = tf_TanhWithDiffDype('float64') out_16_16_1 = tf_Tanh_16(x_16).numpy().astype(np.float32) out_16_16_2 = tf_Tanh_16(x_16).numpy().astype(np.float64) out_16_32 = tf_Tanh_32(x_16) out_16_64 = tf_Tanh_64(x_16) diff1 = np.mean(out_16_32 - out_16_16_1) # 低精度到高精度 diff2 = np.mean(out_16_64 - out_16_16_2) # 低精度到高精度 res.append(diff1) res.append(diff2) out_32_32_1 = tf_Tanh_32(x_32) out_32_32_2 = tf_Tanh_32(x_32).numpy().astype(np.float64) out_32_16 = tf_Tanh_16(x_32).numpy().astype(np.float32) out_32_64 = tf_Tanh_64(x_32) diff3 = np.mean(out_32_16 - out_32_32_1) # 高精度到低精度 diff4 = np.mean(out_32_64 - out_32_32_2) # 低精度到高精度 res.append(diff3) res.append(diff4) out_64_16 = tf_Tanh_16(x_64).numpy().astype(np.float64) out_64_32 = tf_Tanh_32(x_64).numpy().astype(np.float64) out_64_64 = tf_Tanh_64(x_64) diff5 = np.mean(out_64_16 - out_64_64) # 高精度到低精度 diff6 = np.mean(out_64_32 - out_64_64) # 低精度到高精度 res.append(diff5) res.append(diff6) csv_writer.writerow(res) out.close() def getDataforTfWihthG(f,g): out = open(file=f, mode="a", newline='') out1 = open(file=g, mode="a", newline='') csv_writer = csv.writer(out) csv_writer1 = csv.writer(out1) csv_writer.writerow(["No.", "16_32(16)", "16_64(16)", "32_16(32)", "32_64(32)", "64_16(64)", "64_32(64)", "time1", "32_16(16)", "64_16(16)", "16_32(32)", "64_32(32)", "16_64(64)", "32_64(64)", "time2", "isNaN"]) csv_writer1.writerow( ["No.", "当前最大误差(同输入)", "全局最大误差(同输入)", "引起最大误差的输入编号1", "当前最大误差(同算子)", "全局最大误差(同算子)", "引起最大误差的输入编号2"]) h_error1 = 0 h_error2 = 0 for i in range(20): tmp1 = 0 tmp2 = 0 index1 = 0 index2 = 0 info = [] info.append(i) for j in range(1000): print('j= ', j) x = np.random.randn(2, 2) res = [] res.append(j) # TF Pooling x_32 = input_withDiffDype(x, tf.float32) x_16 = input_withDiffDype(x, tf.float16) x_64 = input_withDiffDype(x, tf.float64) s=time.time() tf_Tanh_16 = tf_TanhWithDiffDype('float16') tf_Tanh_32 = tf_TanhWithDiffDype('float32') tf_Tanh_64 = tf_TanhWithDiffDype('float64') out_16_16_1 = tf_Tanh_16(x_16).numpy().astype(np.float32) out_16_16_2 = tf_Tanh_16(x_16).numpy().astype(np.float64) out_16_32 = tf_Tanh_32(x_16) out_16_64 = tf_Tanh_64(x_16) diff1 = np.mean(np.abs(out_16_32 - out_16_16_1)) # 低精度到高精度 diff2 = np.mean(np.abs(out_16_64 - out_16_16_2)) # 低精度到高精度 out_32_32_1 = tf_Tanh_32(x_32) out_32_32_2 = tf_Tanh_32(x_32).numpy().astype(np.float64) out_32_16 = tf_Tanh_16(x_32).numpy().astype(np.float32) out_32_64 = tf_Tanh_64(x_32) diff3 = np.mean(np.abs(out_32_16 - out_32_32_1) ) # 高精度到低精度 diff4 = np.mean(np.abs(out_32_64 - out_32_32_2)) # 低精度到高精度 out_64_16 = tf_Tanh_16(x_64).numpy().astype(np.float64) out_64_32 = tf_Tanh_32(x_64).numpy().astype(np.float64) out_64_64 = tf_Tanh_64(x_64) diff5 = np.mean(np.abs(out_64_16 - out_64_64)) # 高精度到低精度 diff6 = np.mean(np.abs(out_64_32 - out_64_64)) # 低精度到高精度 e=time.time() res.append(diff1) res.append(diff2) res.append(diff3) res.append(diff4) res.append(diff5) res.append(diff6) res.append(e-s) s = time.time() out_16_16 = tf_Tanh_16(x_16) diff7 = np.mean(np.abs(tf_Tanh_16(x_32) - out_16_16)) diff8 = np.mean(np.abs(tf_Tanh_16(x_64) - out_16_16)) diff9 = np.mean(np.abs(tf_Tanh_32(x_16) - out_32_32_1)) diff10 = np.mean(np.abs(tf_Tanh_32(x_64) - out_32_32_1)) diff11 = np.mean(np.abs(tf_Tanh_64(x_16) - out_64_64)) diff12 = np.mean(np.abs(tf_Tanh_64(x_32) - out_64_64)) e = time.time() res.append(diff7) res.append(diff8) res.append(diff9) res.append(diff10) res.append(diff11) res.append(diff12) res.append(e - s) for n in out_32_32_1.numpy().ravel(): if math.isnan(n): res.append("NAN") break csv_writer.writerow(res) if max(res[1:7]) > tmp1: index1 = j tmp1 = max(max(res[1:7]), tmp1) if max(res[8:14]) > tmp2: index2 = j tmp2 = max(max(res[8:14]), tmp2) h_error1 = max(h_error1, tmp1) h_error2 = max(h_error2, tmp2) info.append(tmp1) info.append(h_error1) info.append(index1) info.append(tmp2) info.append(h_error2) info.append(index2) csv_writer1.writerow(info) out.close() out1.close() def tf_disturb(f): out = open(file=f, mode="a", newline='') csv_writer = csv.writer(out) for j in range(1000): print('j= ', j) print('------------------------------------------') x = np.random.randn(2, 2) a1 = 0.000001 * np.ones((2, 2), np.float64) a2 = 0.00000001 * np.ones((2, 2), np.float64) a3 = 0.0000000001 * np.ones((2, 2), np.float64) csv_writer.writerow([x]) csv_writer.writerow(["No.", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32"]) getdata(x, csv_writer) csv_writer.writerow(["+10^-6", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32"]) getdata(x + a1, csv_writer) csv_writer.writerow(["+10^-8", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32"]) getdata(x + a2, csv_writer) csv_writer.writerow(["+10^-10", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32"]) getdata(x + a3, csv_writer) out.close() def getdata(x,csv_writer): for i in range(20): res = [] res.append(i) # TF Pooling x_32 = input_withDiffDype(x, tf.float32) x_16 = input_withDiffDype(x, tf.float16) x_64 = input_withDiffDype(x, tf.float64) tf_Tanh_16 = tf_TanhWithDiffDype('float16') tf_Tanh_32 = tf_TanhWithDiffDype('float32') tf_Tanh_64 = tf_TanhWithDiffDype('float64') out_16_16_1 = tf_Tanh_16(x_16).numpy().astype(np.float32) out_16_16_2 = tf_Tanh_16(x_16).numpy().astype(np.float64) out_16_32 = tf_Tanh_32(x_16) out_16_64 = tf_Tanh_64(x_16) diff1 = np.mean(out_16_32 - out_16_16_1) # 低精度到高精度 diff2 = np.mean(out_16_64 - out_16_16_2) # 低精度到高精度 res.append(diff1) res.append(diff2) out_32_32_1 = tf_Tanh_32(x_32) out_32_32_2 = tf_Tanh_32(x_32).numpy().astype(np.float64) out_32_16 = tf_Tanh_16(x_32).numpy().astype(np.float32) out_32_64 = tf_Tanh_64(x_32) diff3 = np.mean(out_32_16 - out_32_32_1) # 高精度到低精度 diff4 = np.mean(out_32_64 - out_32_32_2) # 低精度到高精度 res.append(diff3) res.append(diff4) out_64_16 = tf_Tanh_16(x_64).numpy().astype(np.float64) out_64_32 = tf_Tanh_32(x_64).numpy().astype(np.float64) out_64_64 = tf_Tanh_64(x_64) diff5 = np.mean(out_64_16 - out_64_64) # 高精度到低精度 diff6 = np.mean(out_64_32 - out_64_64) # 低精度到高精度 res.append(diff5) res.append(diff6) csv_writer.writerow(res) def tf_disturb_timeflow(f,g): out = open(file=f, mode="a", newline='') out1 = open(file=g, mode="a", newline='') csv_writer = csv.writer(out) csv_writer1 = csv.writer(out1) csv_writer.writerow(["No.", "16_32", "16_64", "32_16", "32_64", "64_16", "64_32","time","disturb"]) csv_writer1.writerow(["No.", "当前最大误差", "全局最大误差", "引起最大误差的输入编号"]) h_error = 0 a1 = 0.000001 * np.ones((2, 2), np.float64) a2 = 0.00000001 * np.ones((2, 2), np.float64) a3 = 0.0000000001 * np.ones((2, 2), np.float64) for i in range(20): tmp=0 index=0 info=[] info.append(i) for j in range(1000): err=[] print('j= ', j) print('------------------------------------------') x = np.random.randn(2, 2) getdatafortimeflow(x,csv_writer,j,"0",err) getdatafortimeflow(x+a1,csv_writer,j,"e-6",err) getdatafortimeflow(x+a2,csv_writer,j,"e-8",err) getdatafortimeflow(x+a3,csv_writer,j,"e-10",err) if max(err)>tmp: tmp=max(err) index=j h_error=max(h_error,tmp) info.append(tmp) info.append(h_error) info.append(index) csv_writer1.writerow(info) out.close() out1.close() def getdatafortimeflow(x,csv_writer,j,disturb,err): res = [] res.append(j) x_32 = input_withDiffDype(x, tf.float32) x_16 = input_withDiffDype(x, tf.float16) x_64 = input_withDiffDype(x, tf.float64) s = time.time() tf_Tanh_16 = tf_TanhWithDiffDype('float16') tf_Tanh_32 = tf_TanhWithDiffDype('float32') tf_Tanh_64 = tf_TanhWithDiffDype('float64') out_16_16_1 = tf_Tanh_16(x_16).numpy().astype(np.float32) out_16_16_2 = tf_Tanh_16(x_16).numpy().astype(np.float64) out_16_32 = tf_Tanh_32(x_16) out_16_64 = tf_Tanh_64(x_16) diff1 = np.mean(out_16_32 - out_16_16_1) # 低精度到高精度 diff2 = np.mean(out_16_64 - out_16_16_2) # 低精度到高精度 out_32_32_1 = tf_Tanh_32(x_32) out_32_32_2 = tf_Tanh_32(x_32).numpy().astype(np.float64) out_32_16 = tf_Tanh_16(x_32).numpy().astype(np.float32) out_32_64 = tf_Tanh_64(x_32) diff3 = np.mean(out_32_16 - out_32_32_1) # 高精度到低精度 diff4 = np.mean(out_32_64 - out_32_32_2) # 低精度到高精度 out_64_16 = tf_Tanh_16(x_64).numpy().astype(np.float64) out_64_32 = tf_Tanh_32(x_64).numpy().astype(np.float64) out_64_64 = tf_Tanh_64(x_64) diff5 = np.mean(out_64_16 - out_64_64) # 高精度到低精度 diff6 = np.mean(out_64_32 - out_64_64) # 低精度到高精度 e = time.time() res.append(diff1) res.append(diff2) res.append(diff3) res.append(diff4) res.append(diff5) res.append(diff6) res.append(e - s) res.append(disturb) err.append(max(res[1:7])) csv_writer.writerow(res) def tf_random(f, g): out = open(file=f, mode="a", newline='') out1 = open(file=g, mode="a", newline='') csv_writer = csv.writer(out) csv_writer1 = csv.writer(out1) csv_writer.writerow(["No.", "16_64", "32_64", "time", "isNaN"]) csv_writer1.writerow( ["No.", "当前最大误差", "全局最大误差", "引起最大误差的输入编号"]) h_error1 = 0 for i in range(20): tmp1 = 0 index1 = 0 info = [] info.append(i) for j in range(1000): print('j= ', j) x = np.random.randn(2, 2) res = [] res.append(j) x_32 = input_withDiffDype(x, tf.float32) x_16 = input_withDiffDype(x, tf.float16) x_64 = input_withDiffDype(x, tf.float64) # TF Conv2D s = time.time() tf_Tanh_16 = tf_TanhWithDiffDype('float16') tf_Tanh_32 = tf_TanhWithDiffDype('float32') tf_Tanh_64 = tf_TanhWithDiffDype('float64') out_16_16_2 = tf_Tanh_16(x_16).numpy().astype(np.float64) out_32_32_2 = tf_Tanh_32(x_32).numpy().astype(np.float64) out_64_64 = tf_Tanh_64(x_64) diff1 = np.mean(np.abs(out_16_16_2 - out_64_64)) # 低精度到高精度 diff2 = np.mean(np.abs(out_32_32_2 - out_64_64)) # 低精度到高精度 e = time.time() res.append(diff1) res.append(diff2) res.append(e - s) for n in out_64_64.numpy().ravel(): if math.isnan(n): res.append("NAN") break csv_writer.writerow(res) if max(res[1:3]) > tmp1: index1 = j tmp1 = max(res[1:3]) h_error1 = max(h_error1, tmp1) info.append(tmp1) info.append(h_error1) info.append(index1) csv_writer1.writerow(info) out.close() out1.close() if __name__ == '__main__': getDataforTfWihthG("/home/ise/opTest/data/timeflow2/tf_gpu_2.3.1/tanh.csv", "/home/ise/opTest/data/timeflow2/tf_gpu_2.3.1/tanh_count.csv")

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305

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Python

src/swimport/pools/derived_types/__init__.py

talos-gis/swimport

e8f0fcf02b0c9751b199f750f1f8bc57c8ff54b3

[ "MIT" ]

1

2019-03-07T20:43:42.000Z

src/swimport/pools/derived_types/__init__.py

talos-gis/swimport

e8f0fcf02b0c9751b199f750f1f8bc57c8ff54b3

[ "MIT" ]

null

src/swimport/pools/derived_types/__init__.py

talos-gis/swimport

e8f0fcf02b0c9751b199f750f1f8bc57c8ff54b3

[ "MIT" ]

null

import swimport.pools.derived_types.callable_ import swimport.pools.derived_types.iter_ import swimport.pools.derived_types.map_ import swimport.pools.derived_types.py_iterable import swimport.pools.derived_types.slice_ import swimport.pools.derived_types.tuple_ import swimport.pools.derived_types.array

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Python

nautobot/dcim/migrations/0002_initial_part_2.py

steffann/nautobot

f5cf4a294861e69fa10ac445f7fc89f432d5b3df

[ "Apache-2.0" ]

1

2021-03-16T15:14:55.000Z

nautobot/dcim/migrations/0002_initial_part_2.py

steffann/nautobot

f5cf4a294861e69fa10ac445f7fc89f432d5b3df

[ "Apache-2.0" ]

null

nautobot/dcim/migrations/0002_initial_part_2.py

steffann/nautobot

f5cf4a294861e69fa10ac445f7fc89f432d5b3df

[ "Apache-2.0" ]

1

2021-10-14T01:54:24.000Z

# Generated by Django 3.1.3 on 2021-02-20 08:07 from django.conf import settings from django.db import migrations, models import django.db.models.deletion import mptt.fields import nautobot.extras.models.statuses import taggit.managers class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("tenancy", "0001_initial"), ("dcim", "0001_initial_part_1"), ("extras", "0001_initial_part_1"), ("contenttypes", "0002_remove_content_type_name"), ] operations = [ migrations.AddField( model_name="virtualchassis", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="site", name="region", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="sites", to="dcim.region", ), ), migrations.AddField( model_name="site", name="status", field=nautobot.extras.models.statuses.StatusField( null=True, on_delete=django.db.models.deletion.PROTECT, related_name="dcim_site_related", to="extras.status", ), ), migrations.AddField( model_name="site", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="site", name="tenant", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="sites", to="tenancy.tenant", ), ), migrations.AddField( model_name="region", name="parent", field=mptt.fields.TreeForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name="children", to="dcim.region", ), ), migrations.AddField( model_name="rearporttemplate", name="device_type", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="rearporttemplates", to="dcim.devicetype", ), ), migrations.AddField( model_name="rearport", name="_cable_peer_type", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="contenttypes.contenttype", ), ), migrations.AddField( model_name="rearport", name="cable", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="dcim.cable", ), ), migrations.AddField( model_name="rearport", name="device", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="rearports", to="dcim.device", ), ), migrations.AddField( model_name="rearport", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="rackreservation", name="rack", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="reservations", to="dcim.rack", ), ), migrations.AddField( model_name="rackreservation", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="rackreservation", name="tenant", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="rackreservations", to="tenancy.tenant", ), ), migrations.AddField( model_name="rackreservation", name="user", field=models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name="rackgroup", name="parent", field=mptt.fields.TreeForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name="children", to="dcim.rackgroup", ), ), migrations.AddField( model_name="rackgroup", name="site", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="rack_groups", to="dcim.site", ), ), migrations.AddField( model_name="rack", name="group", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="racks", to="dcim.rackgroup", ), ), migrations.AddField( model_name="rack", name="role", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="racks", to="dcim.rackrole", ), ), migrations.AddField( model_name="rack", name="site", field=models.ForeignKey( on_delete=django.db.models.deletion.PROTECT, related_name="racks", to="dcim.site", ), ), migrations.AddField( model_name="rack", name="status", field=nautobot.extras.models.statuses.StatusField( null=True, on_delete=django.db.models.deletion.PROTECT, related_name="dcim_rack_related", to="extras.status", ), ), migrations.AddField( model_name="rack", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="rack", name="tenant", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="racks", to="tenancy.tenant", ), ), migrations.AddField( model_name="powerporttemplate", name="device_type", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="powerporttemplates", to="dcim.devicetype", ), ), migrations.AddField( model_name="powerport", name="_cable_peer_type", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="contenttypes.contenttype", ), ), migrations.AddField( model_name="powerport", name="_path", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to="dcim.cablepath", ), ), migrations.AddField( model_name="powerport", name="cable", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="dcim.cable", ), ), migrations.AddField( model_name="powerport", name="device", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="powerports", to="dcim.device", ), ), migrations.AddField( model_name="powerport", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="powerpanel", name="rack_group", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to="dcim.rackgroup", ), ), migrations.AddField( model_name="powerpanel", name="site", field=models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to="dcim.site"), ), migrations.AddField( model_name="powerpanel", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="poweroutlettemplate", name="device_type", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="poweroutlettemplates", to="dcim.devicetype", ), ), migrations.AddField( model_name="poweroutlettemplate", name="power_port", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="poweroutlet_templates", to="dcim.powerporttemplate", ), ), migrations.AddField( model_name="poweroutlet", name="_cable_peer_type", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="contenttypes.contenttype", ), ), migrations.AddField( model_name="poweroutlet", name="_path", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to="dcim.cablepath", ), ), migrations.AddField( model_name="poweroutlet", name="cable", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="dcim.cable", ), ), migrations.AddField( model_name="poweroutlet", name="device", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="poweroutlets", to="dcim.device", ), ), migrations.AddField( model_name="poweroutlet", name="power_port", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="poweroutlets", to="dcim.powerport", ), ), migrations.AddField( model_name="poweroutlet", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="powerfeed", name="_cable_peer_type", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="contenttypes.contenttype", ), ), migrations.AddField( model_name="powerfeed", name="_path", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to="dcim.cablepath", ), ), migrations.AddField( model_name="powerfeed", name="cable", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="dcim.cable", ), ), migrations.AddField( model_name="powerfeed", name="power_panel", field=models.ForeignKey( on_delete=django.db.models.deletion.PROTECT, related_name="powerfeeds", to="dcim.powerpanel", ), ), migrations.AddField( model_name="powerfeed", name="rack", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to="dcim.rack", ), ), migrations.AddField( model_name="powerfeed", name="status", field=nautobot.extras.models.statuses.StatusField( null=True, on_delete=django.db.models.deletion.PROTECT, related_name="dcim_powerfeed_related", to="extras.status", ), ), migrations.AddField( model_name="powerfeed", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="platform", name="manufacturer", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="platforms", to="dcim.manufacturer", ), ), migrations.AddField( model_name="inventoryitem", name="device", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="inventoryitems", to="dcim.device", ), ), migrations.AddField( model_name="inventoryitem", name="manufacturer", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name="inventory_items", to="dcim.manufacturer", ), ), migrations.AddField( model_name="inventoryitem", name="parent", field=mptt.fields.TreeForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name="child_items", to="dcim.inventoryitem", ), ), migrations.AddField( model_name="inventoryitem", name="tags", field=taggit.managers.TaggableManager(through="extras.TaggedItem", to="extras.Tag"), ), migrations.AddField( model_name="interfacetemplate", name="device_type", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="interfacetemplates", to="dcim.devicetype", ), ), migrations.AddField( model_name="interface", name="_cable_peer_type", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="contenttypes.contenttype", ), ), migrations.AddField( model_name="interface", name="_path", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to="dcim.cablepath", ), ), migrations.AddField( model_name="interface", name="cable", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="+", to="dcim.cable", ), ), migrations.AddField( model_name="interface", name="device", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="interfaces", to="dcim.device", ), ), migrations.AddField( model_name="interface", name="lag", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="member_interfaces", to="dcim.interface", ), ), ]

32.92446

110

0.490495

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5.836109

0.081945

0.119178

0.152283

0.178767

0.895662

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0

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null

0

1

0

1

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null

0

9

96089c8cedc2b6028ae8096529c080fa4f9ba5ba

13,841

py

Python

FCNmotif.py

suifengwangshi/MotifC

34117a6bfb7dacd5a84da3abd5b8a339ae73cc76

[ "Apache-2.0" ]

null

FCNmotif.py

suifengwangshi/MotifC

34117a6bfb7dacd5a84da3abd5b8a339ae73cc76

[ "Apache-2.0" ]

null

FCNmotif.py

suifengwangshi/MotifC

34117a6bfb7dacd5a84da3abd5b8a339ae73cc76

[ "Apache-2.0" ]

null

# -*- coding: utf8 -*- import torch import torch.nn as nn import torch.nn.functional as F #from torchsummary import summary import numpy as np import sys # threelayers c_in=256 """ class FCN(nn.Module): # FPN for semantic segmentation def __init__(self, motiflen=15): super(FCN, self).__init__() # 初始化 # encode process self.conv1 = nn.Conv1d(in_channels=4, out_channels=64, kernel_size=motiflen) # 注意这里是一维卷积层，图像处理任务时才是二维卷积层 self.pool1 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv2 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool2 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv3 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=3) self.pool3 = nn.MaxPool1d(kernel_size=2, stride=2) self.conv4 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool4 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv5 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool5 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv6 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=3) self.pool6 = nn.MaxPool1d(kernel_size=2, stride=2) # classifier head c_in = 256 self.linear1 = nn.Linear(c_in, 64) self.drop = nn.Dropout(p=0.5) self.linear2 = nn.Linear(64, 1) # general functions self.sigmoid = nn.Sigmoid() self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(p=0.2) self._init_weights() def _init_weights(self): # Initialize the new built layers for layer in self.modules(): if isinstance(layer, (nn.Conv1d, nn.Linear)): # nn.init.kaiming_uniform_(layer.weight, mode='fan_in', nonlinearity='relu') nn.init.xavier_uniform_(layer.weight) if layer.bias is not None: nn.init.constant_(layer.bias, 0) elif isinstance(layer, nn.BatchNorm1d): nn.init.constant_(layer.weight, 1) nn.init.constant_(layer.bias, 0) def forward(self, data1, data2): # Construct a new computation graph at each froward b, _, _ = data1.size() # encode process out1 = self.conv1(data1) out1 = self.relu(out1) out1 = self.pool1(out1) out1 = self.dropout(out1) out1 = self.conv2(out1) out1 = self.relu(out1) out1 = self.pool2(out1) out1 = self.dropout(out1) out1 = self.conv3(out1) out1 = self.relu(out1) out1 = self.pool3(out1) out1 = self.dropout(out1) skip1 = out1 out2 = self.conv4(data2) out2 = self.relu(out2) out2 = self.pool4(out2) out2 = self.dropout(out2) out2 = self.conv5(out2) out2 = self.relu(out2) out2 = self.pool5(out2) out2 = self.dropout(out2) out2 = self.conv6(out2) out2 = self.relu(out2) out2 = self.pool6(out2) out2 = self.dropout(out2) skip2 = out2 # classifier skip4 = skip1 + skip2 # classifier out3 = skip4.view(b, -1) out3 = self.linear1(out3) out3 = self.relu(out3) out3 = self.drop(out3) out3 = self.linear2(out3) out_class = self.sigmoid(out3) return out_class """ # twolayers c_in=640 101 class FCN(nn.Module): # FPN for semantic segmentation def __init__(self, motiflen=15): super(FCN, self).__init__() # 初始化 # encode process self.conv1 = nn.Conv1d(in_channels=4, out_channels=64, kernel_size=motiflen) # 注意这里是一维卷积层，图像处理任务时才是二维卷积层 self.pool1 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv2 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool2 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv4 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool4 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv5 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool5 = nn.MaxPool1d(kernel_size=4, stride=4) # classifier head c_in = 256 self.linear1 = nn.Linear(c_in, 64) self.drop = nn.Dropout(p=0.5) self.linear2 = nn.Linear(64, 1) # general functions self.sigmoid = nn.Sigmoid() self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(p=0.2) self._init_weights() def _init_weights(self): # Initialize the new built layers for layer in self.modules(): if isinstance(layer, (nn.Conv1d, nn.Linear)): # nn.init.kaiming_uniform_(layer.weight, mode='fan_in', nonlinearity='relu') nn.init.xavier_uniform_(layer.weight) if layer.bias is not None: nn.init.constant_(layer.bias, 0) elif isinstance(layer, nn.BatchNorm1d): nn.init.constant_(layer.weight, 1) nn.init.constant_(layer.bias, 0) def forward(self, data1, data2): # Construct a new computation graph at each froward b, _, _ = data1.size() # encode process out1 = self.conv1(data1) out1 = self.relu(out1) out1 = self.pool1(out1) out1 = self.dropout(out1) out1 = self.conv2(out1) out1 = self.relu(out1) out1 = self.pool2(out1) out1 = self.dropout(out1) skip1 = out1 out2 = self.conv4(data2) out2 = self.relu(out2) out2 = self.pool4(out2) out2 = self.dropout(out2) out2 = self.conv5(out2) out2 = self.relu(out2) out2 = self.pool5(out2) out2 = self.dropout(out2) skip2 = out2 # classifier skip4 = skip1 + skip2 # add # skip4 = torch.cat((skip1, skip2), 1) # classifier out3 = skip4.view(b, -1) out3 = self.linear1(out3) out3 = self.relu(out3) out3 = self.drop(out3) out3 = self.linear2(out3) out_class = self.sigmoid(out3) return out_class # twolayers class FCN1(nn.Module): # FPN for semantic segmentation def __init__(self, motiflen=15): super(FCN1, self).__init__() # 初始化 # encode process self.conv1 = nn.Conv1d(in_channels=4, out_channels=64, kernel_size=motiflen) # 注意这里是一维卷积层，图像处理任务时才是二维卷积层 self.pool1 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv2 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool2 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv4 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool4 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv5 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool5 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv7 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool7 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv8 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool8 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv10 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool10 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv11 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool11 = nn.MaxPool1d(kernel_size=4, stride=4) # classifier head c_in = 256 self.linear1 = nn.Linear(c_in, 64) self.drop = nn.Dropout(p=0.5) self.linear2 = nn.Linear(64, 1) # general functions self.sigmoid = nn.Sigmoid() self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(p=0.2) self._init_weights() def _init_weights(self): # Initialize the new built layers for layer in self.modules(): if isinstance(layer, (nn.Conv1d, nn.Linear)): # nn.init.kaiming_uniform_(layer.weight, mode='fan_in', nonlinearity='relu') nn.init.xavier_uniform_(layer.weight) if layer.bias is not None: nn.init.constant_(layer.bias, 0) elif isinstance(layer, nn.BatchNorm1d): nn.init.constant_(layer.weight, 1) nn.init.constant_(layer.bias, 0) def forward(self, data1, data2, data3, data4): # Construct a new computation graph at each froward b, _, _ = data1.size() # encode process out1 = self.conv1(data1) out1 = self.relu(out1) out1 = self.pool1(out1) out1 = self.dropout(out1) out1 = self.conv2(out1) out1 = self.relu(out1) out1 = self.pool2(out1) out1 = self.dropout(out1) skip1 = out1 out2 = self.conv4(data2) out2 = self.relu(out2) out2 = self.pool4(out2) out2 = self.dropout(out2) out2 = self.conv5(out2) out2 = self.relu(out2) out2 = self.pool5(out2) out2 = self.dropout(out2) skip2 = out2 out3 = self.conv7(data3) out3 = self.relu(out3) out3 = self.pool7(out3) out3 = self.dropout(out3) out3 = self.conv8(out3) out3 = self.relu(out3) out3 = self.pool8(out3) out3 = self.dropout(out3) skip3 = out3 out4 = self.conv10(data4) out4 = self.relu(out4) out4 = self.pool10(out4) out4 = self.dropout(out4) out4 = self.conv11(out4) out4 = self.relu(out4) out4 = self.pool11(out4) out4 = self.dropout(out4) skip4 = out4 # classifier skip = skip1 + skip2 + skip3 + skip4 # add # skip = torch.cat((skip1, skip2, skip3, skip4), 1) # classifier out = skip.view(b, -1) out = self.linear1(out) out = self.relu(out) out = self.drop(out) out = self.linear2(out) out_class = self.sigmoid(out) return out_class class FCN2(nn.Module): # FPN for semantic segmentation def __init__(self, motiflen=15): super(FCN2, self).__init__() # 初始化 # encode process self.conv1 = nn.Conv1d(in_channels=4, out_channels=64, kernel_size=motiflen) # 注意这里是一维卷积层，图像处理任务时才是二维卷积层 self.pool1 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv2 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool2 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv4 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool4 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv5 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool5 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv7 = nn.Conv1d(in_channels=1, out_channels=64, kernel_size=motiflen) # 4、5、6用于处理进化信息 self.pool7 = nn.MaxPool1d(kernel_size=4, stride=4) self.conv8 = nn.Conv1d(in_channels=64, out_channels=64, kernel_size=5) self.pool8 = nn.MaxPool1d(kernel_size=4, stride=4) # classifier head c_in = 256 self.linear1 = nn.Linear(c_in, 64) self.drop = nn.Dropout(p=0.5) self.linear2 = nn.Linear(64, 1) # general functions self.sigmoid = nn.Sigmoid() self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(p=0.2) self._init_weights() def _init_weights(self): # Initialize the new built layers for layer in self.modules(): if isinstance(layer, (nn.Conv1d, nn.Linear)): # nn.init.kaiming_uniform_(layer.weight, mode='fan_in', nonlinearity='relu') nn.init.xavier_uniform_(layer.weight) if layer.bias is not None: nn.init.constant_(layer.bias, 0) elif isinstance(layer, nn.BatchNorm1d): nn.init.constant_(layer.weight, 1) nn.init.constant_(layer.bias, 0) def forward(self, data1, data2, data3): # Construct a new computation graph at each froward b, _, _ = data1.size() # encode process out1 = self.conv1(data1) out1 = self.relu(out1) out1 = self.pool1(out1) out1 = self.dropout(out1) out1 = self.conv2(out1) out1 = self.relu(out1) out1 = self.pool2(out1) out1 = self.dropout(out1) skip1 = out1 out2 = self.conv4(data2) out2 = self.relu(out2) out2 = self.pool4(out2) out2 = self.dropout(out2) out2 = self.conv5(out2) out2 = self.relu(out2) out2 = self.pool5(out2) out2 = self.dropout(out2) skip2 = out2 out3 = self.conv7(data3) out3 = self.relu(out3) out3 = self.pool7(out3) out3 = self.dropout(out3) out3 = self.conv8(out3) out3 = self.relu(out3) out3 = self.pool8(out3) out3 = self.dropout(out3) skip3 = out3 # classifier skip = skip1 + skip2 + skip3 # add # skip = torch.cat((skip1, skip2, skip3), 1) # classifier out = skip.view(b, -1) out = self.linear1(out) out = self.relu(out) out = self.drop(out) out = self.linear2(out) out_class = self.sigmoid(out) return out_class

38.770308

114

0.57886

1,772

13,841

4.407449

0.079007

0.06146

0.043022

0.055314

0.957362

0.944046

0.9379

0.913572

0.908835

0

0.073618

0.307131

13,841

356

115

38.879213

0.740772

0.089661

0

0.853774

0

1

0.042453

false

0

0.023585

0

0.09434

0

null

0

1

0

1

0

null

0

7

825da7e2b2cdd060ea44daf563c6d2172104419f

110

py

Python

reaver/models/sc2/__init__.py

HatsuneMiku4/reaver

059320ce109498ec4100fcc2cee32177c427f1ea

[ "MIT" ]

239

2019-01-18T08:47:24.000Z

2022-03-21T08:29:50.000Z

reaver/models/sc2/__init__.py

HatsuneMiku4/reaver

059320ce109498ec4100fcc2cee32177c427f1ea

[ "MIT" ]

19

2019-01-27T10:10:12.000Z

2021-12-29T20:02:05.000Z

reaver/models/sc2/__init__.py

HatsuneMiku4/reaver

059320ce109498ec4100fcc2cee32177c427f1ea

[ "MIT" ]

44

2019-01-18T02:12:46.000Z

2021-07-28T14:54:10.000Z

from reaver.models.sc2.policy import SC2MultiPolicy from reaver.models.sc2.fully_conv import build_fully_conv

36.666667

57

0.872727

17

110

5.470588

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0

1

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1

0

8

8264ef4ad371deb30edcb8f8c92351fa55fe839a

33

py

Python

tests/test_stub.py

chalupaul/twitch_dungeon

97af4a73c8e99d2e5f1f1880e67e3253e0e06582

[ "MIT" ]

null

tests/test_stub.py

chalupaul/twitch_dungeon

97af4a73c8e99d2e5f1f1880e67e3253e0e06582

[ "MIT" ]

null

tests/test_stub.py

chalupaul/twitch_dungeon

97af4a73c8e99d2e5f1f1880e67e3253e0e06582

[ "MIT" ]

null

def test_stub(): return True

11

16

0.666667

5

33

4.2

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33

2

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0

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0

1

0

7

82d5f3b8843787b9a66927cab9f00c3a176b4546

3,617

py

Python

lnbits/extensions/lnticket/migrations.py

supertestnet/lnbits

0ea661babbf1b4251599380321b23fd7c8920fa6

[ "MIT" ]

null

lnbits/extensions/lnticket/migrations.py

supertestnet/lnbits

0ea661babbf1b4251599380321b23fd7c8920fa6

[ "MIT" ]

null

lnbits/extensions/lnticket/migrations.py

supertestnet/lnbits

0ea661babbf1b4251599380321b23fd7c8920fa6

[ "MIT" ]

1

2021-07-19T07:01:36.000Z

async def m001_initial(db): await db.execute( """ CREATE TABLE lnticket.forms ( id TEXT PRIMARY KEY, wallet TEXT NOT NULL, name TEXT NOT NULL, description TEXT NOT NULL, costpword INTEGER NOT NULL, amountmade INTEGER NOT NULL, time TIMESTAMP NOT NULL DEFAULT """ + db.timestamp_now + """ ); """ ) await db.execute( """ CREATE TABLE lnticket.tickets ( id TEXT PRIMARY KEY, form TEXT NOT NULL, email TEXT NOT NULL, ltext TEXT NOT NULL, name TEXT NOT NULL, wallet TEXT NOT NULL, sats INTEGER NOT NULL, time TIMESTAMP NOT NULL DEFAULT """ + db.timestamp_now + """ ); """ ) async def m002_changed(db): await db.execute( """ CREATE TABLE lnticket.ticket ( id TEXT PRIMARY KEY, form TEXT NOT NULL, email TEXT NOT NULL, ltext TEXT NOT NULL, name TEXT NOT NULL, wallet TEXT NOT NULL, sats INTEGER NOT NULL, paid BOOLEAN NOT NULL, time TIMESTAMP NOT NULL DEFAULT """ + db.timestamp_now + """ ); """ ) for row in [ list(row) for row in await db.fetchall("SELECT * FROM lnticket.tickets") ]: usescsv = "" for i in range(row[5]): if row[7]: usescsv += "," + str(i + 1) else: usescsv += "," + str(1) usescsv = usescsv[1:] await db.execute( """ INSERT INTO lnticket.ticket ( id, form, email, ltext, name, wallet, sats, paid ) VALUES (?, ?, ?, ?, ?, ?, ?, ?) """, ( row[0], row[1], row[2], row[3], row[4], row[5], row[6], True, ), ) await db.execute("DROP TABLE lnticket.tickets") async def m003_changed(db): await db.execute( """ CREATE TABLE lnticket.form ( id TEXT PRIMARY KEY, wallet TEXT NOT NULL, name TEXT NOT NULL, webhook TEXT, description TEXT NOT NULL, costpword INTEGER NOT NULL, amountmade INTEGER NOT NULL, time TIMESTAMP NOT NULL DEFAULT """ + db.timestamp_now + """ ); """ ) for row in [list(row) for row in await db.fetchall("SELECT * FROM lnticket.forms")]: usescsv = "" for i in range(row[5]): if row[7]: usescsv += "," + str(i + 1) else: usescsv += "," + str(1) usescsv = usescsv[1:] await db.execute( """ INSERT INTO lnticket.form ( id, wallet, name, webhook, description, costpword, amountmade ) VALUES (?, ?, ?, ?, ?, ?, ?) """, ( row[0], row[1], row[2], row[3], row[4], row[5], row[6], ), ) await db.execute("DROP TABLE lnticket.forms")

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3,617

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0.706333

0

0.018425

0.504838

3,617

147

89

24.605442

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0

0.722222

0

0.103972

0

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null

0

1

0

1

0

1

0

null

0

8

7d5e6f7224a8399574abd4213d59cc916117a0c6

12,285

py

Python

tests/test_order.py

masakichi/otcbtc-client

28f8ee57b4321e901463c913c5fd892ecb0cee7b

[ "MIT" ]

6

2018-05-20T13:51:41.000Z

2019-08-01T10:44:22.000Z

tests/test_order.py

masakichi/otcbtc-client

28f8ee57b4321e901463c913c5fd892ecb0cee7b

[ "MIT" ]

null

tests/test_order.py

masakichi/otcbtc-client

28f8ee57b4321e901463c913c5fd892ecb0cee7b

[ "MIT" ]

2

2018-12-03T01:12:17.000Z

2019-02-20T04:52:20.000Z

# coding: utf-8 import responses from otcbtc_client.client import OTCBTCClient from tests.helper import concat_url_and_params, body_str_to_dict class TestOrder(object): @property def order(self): return OTCBTCClient(api_key='xxx', api_secret='yyy').order @responses.activate def test_list_order(self): order = self.order params = { 'id': 1, 'access_key': 'xxx', 'signature': 'c242b60f1830337f7618afab08d378b7cb2e9501fe226e76e0cab0ee93ac1933' } responses.add( responses.GET, concat_url_and_params(order.build_url(order.ORDER_URI), params), json={ 'id': 1, # Unique order id. 'side': 'buy', # Either 'sell' or 'buy'. 'ord_type': 'limit', # Type of order, now only 'limit'. 'price': '0.002', # Price for each unit. e.g. If you sell/buy 1 OTB at 0.002 ETH, the price is '0.002' 'avg_price': '0.0', # Average execution price, average of price in trades. 'state': 'wait', # One of 'wait', 'done', or 'cancel'. An order in 'wait' is an active order, waiting fullfillment; a 'done' order is an order fullfilled; 'cancel' means the order has been cancelled. 'market': 'otbeth', # The market in which the order is placed, e.g. 'otbeth'. All available markets can be found at /api/v2/markets. 'created_at': '2017-02-01T00:00:00+08:00', # Order create time in iso8601 format. 'volume': '100.0', # The amount user want to sell/buy. An order could be partially executed, e.g. an order sell 100 otb can be matched with a buy 60 otb order, left 40 otb to be sold; in this case the order's volume would be '100.0', its remaining_volume would be '40.0', its executed volume is '60.0'. 'remaining_volume': '100.0', # The remaining volume 'executed_volume': '0.0', # The executed volume 'trades_count': 1 # Number of trades under this order }) resp = order.list_order(id=1) assert resp['id'] == 1 @responses.activate def test_list_orders(self): order = self.order market = 'otbeth' params = { 'market': market, 'access_key': 'xxx', 'signature': 'be0694b7c33e92da3ec6ee534f7391fb7d0332fc1d867681c5085c5194ed69c8' } responses.add( responses.GET, concat_url_and_params(order.build_url(order.ORDERS_URI), params), json=[ { 'id': 1, # Unique order id. 'side': 'buy', # Either 'sell' or 'buy'. 'ord_type': 'limit', # Type of order, now only 'limit'. 'price': '0.002', # Price for each unit. e.g. If you sell/buy 1 OTB at 0.002 ETH, the price is '0.002' 'avg_price': '0.0', # Average execution price, average of price in trades. 'state': 'wait', # One of 'wait', 'done', or 'cancel'. An order in 'wait' is an active order, waiting fullfillment; a 'done' order is an order fullfilled; 'cancel' means the order has been cancelled. 'market': 'otbeth', # The market in which the order is placed, e.g. 'otbeth'. All available markets can be found at /api/v2/markets. 'created_at': '2017-02-01T00:00:00+08:00', # Order create time in iso8601 format. 'volume': '100.0', # The amount user want to sell/buy. An order could be partially executed, e.g. an order sell 100 otb can be matched with a buy 60 otb order, left 40 otb to be sold; in this case the order's volume would be '100.0', its remaining_volume would be '40.0', its executed volume is '60.0'. 'remaining_volume': '100.0', # The remaining volume 'executed_volume': '0.0', # The executed volume 'trades_count': 1 # Counts of trades under this order }, { 'id': 3, 'side': 'sell', 'ord_type': 'limit', 'price': '0.003', 'avg_price': '0.0', 'state': 'wait', 'market': 'otbeth', 'created_at': '2017-02-01T00:00:00+08:00', 'volume': '100.0', 'remaining_volume': '100.0', 'executed_volume': '0.0', 'trades_count': 0 } ], match_querystring=True) resp = order.list_orders(market=market) assert isinstance(resp, list) @responses.activate def test_create_order(self): order = self.order market = 'otbeth' data = { 'market': market, 'price': '0.002', 'side': 'sell', 'volume': '100', 'access_key': 'xxx', 'signature': 'efcc83119fe25b18f0a02302aaee7765b62d7bf64dc6c5d4f2266f5a5fda4327' } responses.add( responses.POST, order.build_url(order.ORDERS_URI), json={ 'id': 1, # Unique order id. 'side': 'sell', # Either 'sell' or 'buy'. 'ord_type': 'limit', # Type of order, now only 'limit'. 'price': '0.002', # Price for each unit. e.g. If you sell/buy 100 OTB at 0.002 ETH, the price is '0.002'. 'avg_price': '0.0', # Average execution price, average of price in trades. 'state': 'wait', # One of 'wait', 'done', or 'cancel'. An order in 'wait' is an active order, waiting fullfillment; a 'done' order is an order fullfilled; 'cancel' means the order has been cancelled. 'market': 'otbeth', # The market in which the order is placed, e.g. 'otbeth'. All available markets can be found at /api/v2/markets. 'created_at': '2017-02-01T00:00:00+08:00', # Trade create time in iso8601 format. 'volume': '100.0', # The amount user want to sell/buy. An order could be partially executed, e.g. an order sell 100 otb can be matched with a buy 60 otb order, left 40 otb to be sold; in this case the order's volume would be '100.0', its remaining_volume would be '40.0', its executed volume is '60.0'. 'remaining_volume': '100.0', # The remaining volume 'executed_volume': '0.0', # The executed volume 'trades_count': 0 # Number of trades under this order }, match_querystring=True) order.create_order( market=market, side='sell', price='0.002', volume='100') # XXX(Gimo): due to responses library don't have a parameter like match_request_body. assert body_str_to_dict(responses.calls[0].request.body) == data @responses.activate def test_cancel_order(self): order = self.order data = { 'id': '1', 'access_key': 'xxx', 'signature': '47ba4a04e8f5471a05078f8dd13976b7caa80665c5f8152d654486de327c395c' } responses.add( responses.POST, order.build_url(order.DELETE_ORDER_URI), json={ 'id': 1, # Unique order id. 'side': 'buy', # Either 'sell' or 'buy'. 'ord_type': 'limit', # Type of order, now only 'limit'. 'price': '0.002', # Price for each unit. e.g. If you sell/buy 100 OTB at 0.002 ETH, the price is '0.002'. 'avg_price': '0.0', # Average execution price, average of price in trades. 'state': 'wait', # One of 'wait', 'done', or 'cancel'. An order in 'wait' is an active order, waiting fullfillment; a 'done' order is an order fullfilled; 'cancel' means the order has been cancelled. 'market': 'otbeth', # The market in which the order is placed, e.g. 'otbeth'. All available markets can be found at /api/v2/markets. 'created_at': '2017-02-01T00:00:00+08:00', # Trade create time in iso8601 format. 'volume': '100.0', # The amount user want to sell/buy. An order could be partially executed, e.g. an order sell 100 otb can be matched with a buy 60 otb order, left 40 otb to be sold; in this case the order's volume would be '100.0', its remaining_volume would be '40.0', its executed volume is '60.0'. 'remaining_volume': '100.0', # The remaining volume 'executed_volume': '0.0', # The executed volume 'trades_count': 0 # Number of trades under this order }, match_querystring=True) order.cancel_order(id='1') # XXX(Gimo): due to responses library don't have a parameter like match_request_body. assert body_str_to_dict(responses.calls[0].request.body) == data @responses.activate def test_cancel_orders(self): order = self.order data = { 'access_key': 'xxx', 'signature': 'f2ab1d061ad07a2de9fe7658b7203ce28ed6b6511287502b2a7a869172039bcf' } responses.add( responses.POST, order.build_url(order.CLEAR_ORDERS_URI), json=[ { 'id': 2, # Unique order id. 'side': 'buy', # Either 'sell' or 'buy'. 'ord_type': 'limit', # Type of order, now only 'limit'. 'price': '0.0015', # Price for each unit. e.g. If you sell/buy 100 OTB at 0.0015 ETH, the price is '0.0015'. 'avg_price': '0.0', # Average execution price, average of price in trades. 'state': 'wait', # One of 'wait', 'done', or 'cancel'. An order in 'wait' is an active order, waiting fullfillment; a 'done' order is an order fullfilled; 'cancel' means the order has been cancelled. 'market': 'otbeth', # The market in which the order is placed, e.g. 'otbeth'. All available markets can be found at /api/v2/markets. 'created_at': '2017-02-01T00:00:00+08:00', # Trade create time in iso8601 format. 'volume': '100.0', # The amount user want to sell/buy. An order could be partially executed, e.g. an order sell 100 otb can be matched with a buy 60 otb order, left 40 otb to be sold; in this case the order's volume would be '100.0', its remaining_volume would be '40.0', its executed volume is '60.0'. 'remaining_volume': '60.0', # The remaining volume 'executed_volume': '40.0', # The executed volume 'trades_count': 1 # Number of trades under this order }, { 'id': 1, 'side': 'sell', 'ord_type': 'limit', 'price': '0.0012', 'avg_price': '0.0', 'state': 'wait', 'market': 'otbeth', 'created_at': '2017-02-01T00:00:00+08:00', 'volume': '100.0', 'remaining_volume': '100.0', 'executed_volume': '0.0', 'trades_count': 0 } ], match_querystring=True) order.cancel_orders() # XXX(Gimo): due to responses library don't have a parameter like match_request_body. assert body_str_to_dict(responses.calls[0].request.body) == data

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12,285

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0

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0

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0

0.021739

1

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false

0

0.013043

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0.047826

0

null

0

1

0

1

0

null

0

7

7d630493628484a2618ca923afa00275e5c3c18f

213

py

Python

termination_handler/handlers/__init__.py

dgzlopes/termination-handler

526977887cfd9835075de71069fadb095933a654

[ "MIT" ]

7

2019-08-17T13:58:07.000Z

2021-12-15T20:14:58.000Z

termination_handler/handlers/__init__.py

dgzlopes/termination-handler

526977887cfd9835075de71069fadb095933a654

[ "MIT" ]

2

2020-07-16T07:55:49.000Z

2020-07-20T20:03:27.000Z

termination_handler/handlers/__init__.py

dgzlopes/termination-handler

526977887cfd9835075de71069fadb095933a654

[ "MIT" ]

3

2020-07-16T07:07:49.000Z

2021-02-12T06:10:23.000Z

from .handler import AbstractHandler # noqa: F401 from .k8s_handler import K8sHandler # noqa: F401 from .nomad_handler import NomadHandler # noqa: F401 from .slack_handler import SlackHandler # noqa: F401

42.6

54

0.774648

27

213

6

0.444444

0.320988

0.222222

0

0.079096

0.169014

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4

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0

true

0

1

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1

0

1

0

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1

0

1

0

null

0

1

0

1

0

1

0

7

81639ca88f234a4f52162465b40b32d3eddde71e

20,720

py

Python

python/sdk/client/api/alert_api.py

ashwinath/merlin

087a7fa6fb21e4c771d64418bd58873175226ca1

[ "Apache-2.0" ]

null

python/sdk/client/api/alert_api.py

ashwinath/merlin

087a7fa6fb21e4c771d64418bd58873175226ca1

[ "Apache-2.0" ]

null

python/sdk/client/api/alert_api.py

ashwinath/merlin

087a7fa6fb21e4c771d64418bd58873175226ca1

[ "Apache-2.0" ]

null

# coding: utf-8 """ Merlin API Guide for accessing Merlin's model management, deployment, and serving functionalities # noqa: E501 OpenAPI spec version: 0.7.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from client.api_client import ApiClient class AlertApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def alerts_teams_get(self, **kwargs): # noqa: E501 """Lists teams for alert notification channel. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alerts_teams_get(async_req=True) >>> result = thread.get() :param async_req bool :return: list[str] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alerts_teams_get_with_http_info(**kwargs) # noqa: E501 else: (data) = self.alerts_teams_get_with_http_info(**kwargs) # noqa: E501 return data def alerts_teams_get_with_http_info(self, **kwargs): # noqa: E501 """Lists teams for alert notification channel. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alerts_teams_get_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :return: list[str] If the method is called asynchronously, returns the request thread. """ all_params = [] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alerts_teams_get" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/alerts/teams', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[str]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def models_model_id_alerts_get(self, model_id, **kwargs): # noqa: E501 """Lists alerts for given model. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_alerts_get(model_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :return: list[ModelEndpointAlert] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.models_model_id_alerts_get_with_http_info(model_id, **kwargs) # noqa: E501 else: (data) = self.models_model_id_alerts_get_with_http_info(model_id, **kwargs) # noqa: E501 return data def models_model_id_alerts_get_with_http_info(self, model_id, **kwargs): # noqa: E501 """Lists alerts for given model. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_alerts_get_with_http_info(model_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :return: list[ModelEndpointAlert] If the method is called asynchronously, returns the request thread. """ all_params = ['model_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method models_model_id_alerts_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'model_id' is set if ('model_id' not in params or params['model_id'] is None): raise ValueError("Missing the required parameter `model_id` when calling `models_model_id_alerts_get`") # noqa: E501 collection_formats = {} path_params = {} if 'model_id' in params: path_params['model_id'] = params['model_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/models/{model_id}/alerts', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[ModelEndpointAlert]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def models_model_id_endpoints_model_endpoint_id_alert_get(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Gets alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_get(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :return: ModelEndpointAlert If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.models_model_id_endpoints_model_endpoint_id_alert_get_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 else: (data) = self.models_model_id_endpoints_model_endpoint_id_alert_get_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 return data def models_model_id_endpoints_model_endpoint_id_alert_get_with_http_info(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Gets alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_get_with_http_info(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :return: ModelEndpointAlert If the method is called asynchronously, returns the request thread. """ all_params = ['model_id', 'model_endpoint_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method models_model_id_endpoints_model_endpoint_id_alert_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'model_id' is set if ('model_id' not in params or params['model_id'] is None): raise ValueError("Missing the required parameter `model_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_get`") # noqa: E501 # verify the required parameter 'model_endpoint_id' is set if ('model_endpoint_id' not in params or params['model_endpoint_id'] is None): raise ValueError("Missing the required parameter `model_endpoint_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_get`") # noqa: E501 collection_formats = {} path_params = {} if 'model_id' in params: path_params['model_id'] = params['model_id'] # noqa: E501 if 'model_endpoint_id' in params: path_params['model_endpoint_id'] = params['model_endpoint_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/models/{model_id}/endpoints/{model_endpoint_id}/alert', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ModelEndpointAlert', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def models_model_id_endpoints_model_endpoint_id_alert_post(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Creates alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_post(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :param ModelEndpointAlert body: :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.models_model_id_endpoints_model_endpoint_id_alert_post_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 else: (data) = self.models_model_id_endpoints_model_endpoint_id_alert_post_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 return data def models_model_id_endpoints_model_endpoint_id_alert_post_with_http_info(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Creates alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_post_with_http_info(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :param ModelEndpointAlert body: :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['model_id', 'model_endpoint_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method models_model_id_endpoints_model_endpoint_id_alert_post" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'model_id' is set if ('model_id' not in params or params['model_id'] is None): raise ValueError("Missing the required parameter `model_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_post`") # noqa: E501 # verify the required parameter 'model_endpoint_id' is set if ('model_endpoint_id' not in params or params['model_endpoint_id'] is None): raise ValueError("Missing the required parameter `model_endpoint_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_post`") # noqa: E501 collection_formats = {} path_params = {} if 'model_id' in params: path_params['model_id'] = params['model_id'] # noqa: E501 if 'model_endpoint_id' in params: path_params['model_endpoint_id'] = params['model_endpoint_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/models/{model_id}/endpoints/{model_endpoint_id}/alert', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def models_model_id_endpoints_model_endpoint_id_alert_put(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Creates alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_put(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :param ModelEndpointAlert body: :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.models_model_id_endpoints_model_endpoint_id_alert_put_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 else: (data) = self.models_model_id_endpoints_model_endpoint_id_alert_put_with_http_info(model_id, model_endpoint_id, **kwargs) # noqa: E501 return data def models_model_id_endpoints_model_endpoint_id_alert_put_with_http_info(self, model_id, model_endpoint_id, **kwargs): # noqa: E501 """Creates alert for given model endpoint. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.models_model_id_endpoints_model_endpoint_id_alert_put_with_http_info(model_id, model_endpoint_id, async_req=True) >>> result = thread.get() :param async_req bool :param int model_id: (required) :param str model_endpoint_id: (required) :param ModelEndpointAlert body: :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['model_id', 'model_endpoint_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method models_model_id_endpoints_model_endpoint_id_alert_put" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'model_id' is set if ('model_id' not in params or params['model_id'] is None): raise ValueError("Missing the required parameter `model_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_put`") # noqa: E501 # verify the required parameter 'model_endpoint_id' is set if ('model_endpoint_id' not in params or params['model_endpoint_id'] is None): raise ValueError("Missing the required parameter `model_endpoint_id` when calling `models_model_id_endpoints_model_endpoint_id_alert_put`") # noqa: E501 collection_formats = {} path_params = {} if 'model_id' in params: path_params['model_id'] = params['model_id'] # noqa: E501 if 'model_endpoint_id' in params: path_params['model_endpoint_id'] = params['model_endpoint_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/models/{model_id}/endpoints/{model_endpoint_id}/alert', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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null

0

1

0

1

0

null

0

8

81869f4f250c69f3e7530e77316afe0db0f88a12

1,362

py

Python

example/ex_tprint.py

zoumingzhe/PyTools

7202268fca71db5e5b35fccc4031002e6ebbc023

[ "MIT" ]

3

2019-05-02T07:08:15.000Z

2021-03-10T04:55:03.000Z

example/ex_tprint.py

zoumingzhe/PyTools

7202268fca71db5e5b35fccc4031002e6ebbc023

[ "MIT" ]

null

example/ex_tprint.py

zoumingzhe/PyTools

7202268fca71db5e5b35fccc4031002e6ebbc023

[ "MIT" ]

1

2019-05-13T07:26:33.000Z

from ztools import tprint from ztools import AnsiStyle as style from ztools import AnsiFore as fore from ztools import AnsiBack as back tp = tprint() print("-----") tp.color("123", style.underline, fore.red, back.white) tp.flush() tp.color("123", style.underline, fore.red) tp.flush() tp.color("123", style.underline, back.white) tp.flush() tp.color("123", style.underline) tp.flush() tp.color("123") tp.flush() print("-----") tp.color("123", fore.red, back.white) tp.flush() tp.color("123", fore.red) tp.flush() tp.color("123", back.white) tp.flush() tp.color("123") tp.flush() print("-----") tp.color(123, fore.red, back.white) tp.flush() tp.color(123, fore.red) tp.flush() tp.color(123, back.white) tp.flush() tp.color(123) tp.flush() print("-----") tp.color((1,2,3), fore.red, back.white) tp.flush() tp.color((1,2,3), fore.red) tp.flush() tp.color((1,2,3), back.white) tp.flush() tp.color((1,2,3)) tp.flush() print("-----") tp.color([1,2,3], fore.red, back.white) tp.flush() tp.color([1,2,3], fore.red) tp.flush() tp.color([1,2,3], back.white) tp.flush() tp.color([1,2,3]) tp.flush() print("-----") tp.color({'k1':1, 'k2':2, 'k3':3}, fore.red, back.white) tp.flush() tp.color({'k1':1, 'k2':2, 'k3':3}, fore.red) tp.flush() tp.color({'k1':1, 'k2':2, 'k3':3}, back.white) tp.flush() tp.color({'k1':1, 'k2':2, 'k3':3}) tp.flush() input("按回车（Enter）继续")

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251

1,362

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0.30787

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0.655093

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1,362

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0

null

1

0

null

0

9

81b23b4f8a9c6a227c716b85514902591e4e2e6c

231

py

Python

tests/test_module.py

ABitMoreDepth/persistent_structures

98a61bfd9bb560ae952ee04d8ebda7297ca74b51

[ "MIT" ]

null

tests/test_module.py

ABitMoreDepth/persistent_structures

98a61bfd9bb560ae952ee04d8ebda7297ca74b51

[ "MIT" ]

4

2019-10-13T20:37:21.000Z

2019-10-13T20:38:42.000Z

tests/test_module.py

ABitMoreDepth/persistent_structures

98a61bfd9bb560ae952ee04d8ebda7297ca74b51

[ "MIT" ]

null

"""Test that the persistent_structures imports as expected.""" import persistent_structures def test_module() -> None: """Test that the module behaves as expected.""" assert persistent_structures.__version__ is not None

25.666667

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0.359281

0.131737

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0.155844

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63

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0.85641

0.424242

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0.333333

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0.333333

true

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0.333333

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1

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null

1

0

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0

null

0

1

0

1

0

1

0

7

81d36a0f1e180fccb998d541812439c33b87629e

5,651

py

Python

old/old_bin/cru_ts323_update_launcher.py

ua-snap/downscale

3fe8ea1774cf82149d19561ce5f19b25e6cba6fb

[ "MIT" ]

5

2020-06-24T21:55:12.000Z

2022-03-23T16:32:54.000Z

old/old_bin/cru_ts323_update_launcher.py

ua-snap/downscale

3fe8ea1774cf82149d19561ce5f19b25e6cba6fb

[ "MIT" ]

17

2016-01-04T23:37:47.000Z

2017-04-17T20:57:02.000Z

snap_scripts/old_scripts/tem_iem_older_scripts_april2018/tem_inputs_iem/old_code/cru_ts323_update_launcher.py

ua-snap/downscale

3fe8ea1774cf82149d19561ce5f19b25e6cba6fb

[ "MIT" ]

3

2020-09-16T04:48:57.000Z

2021-05-25T03:46:00.000Z

# SCRIPT TO RUN THE CRU TS3.1 BUILT SCRIPT OVER THE CRU TS3.2.3 UPDATE (SEPT.2015) # WHICH EXTENDS THE SERIES TO 12/2014. # THIS IS CURRENTLY WORKING FOR CLD, TMP, VAP, AND MORE TO COME! # # # # # # Author: Michael Lindgren (malindgren@alaska.edu) # # # # # # CURRENTLY SETUP TO RUN ON EOS. # CLD import os os.chdir( '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/CODE/tem_ar5_inputs/downscale_cmip5/bin' ) ncores = '14' base_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323' cru_ts31 = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323/cru_ts3.23.1901.2014.cld.dat.nc' cl20_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_october_final/cru_cl20/cld/akcan' template_raster_fn = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/templates/tas_mean_C_AR5_GFDL-CM3_historical_01_1860.tif' anomalies_calc_type = 'relative' downscaling_operation = 'mult' climatology_begin = '1961' climatology_end = '1990' year_begin = '1901' year_end = '2014' variable = 'cld' metric = 'pct' args_tuples = [ ('hi', cru_ts31), ('ci', cl20_path), ('tr', template_raster_fn), ('base', base_path), ('bt', year_begin), ('et', year_end), ('cbt', climatology_begin), ('cet', climatology_end), ('nc', ncores), ('at', anomalies_calc_type), ('m', metric), ('dso', downscaling_operation), ('v', variable) ] args = ''.join([ ' -'+flag+' '+value for flag, value in args_tuples ]) os.system( 'ipython2.7 -- tas_cld_cru_ts31_to_cl20_downscaling.py ' + args ) # TAS import os os.chdir( '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/CODE/tem_ar5_inputs/downscale_cmip5/bin' ) ncores = '14' base_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323' cru_ts31 = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323/cru_ts3.23.1901.2014.tmp.dat.nc' cl20_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_october_final/cru_cl20/cld/akcan' template_raster_fn = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/templates/tas_mean_C_AR5_GFDL-CM3_historical_01_1860.tif' anomalies_calc_type = 'absolute' downscaling_operation = 'add' climatology_begin = '1961' climatology_end = '1990' year_begin = '1901' year_end = '2014' variable = 'tas' metric = 'C' args_tuples = [ ('hi', cru_ts31), ('ci', cl20_path), ('tr', template_raster_fn), ('base', base_path), ('bt', year_begin), ('et', year_end), ('cbt', climatology_begin), ('cet', climatology_end), ('nc', ncores), ('at', anomalies_calc_type), ('m', metric), ('dso', downscaling_operation), ('v', variable) ] args = ''.join([ ' -'+flag+' '+value for flag, value in args_tuples ]) os.system( 'ipython2.7 -- tas_cld_cru_ts31_to_cl20_downscaling.py ' + args ) # VAP (HUR) import os os.chdir( '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/CODE/tem_ar5_inputs/downscale_cmip5/bin' ) ncores = '14' base_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323' cru_ts31_vap = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323/cru_ts3.23.1901.2014.vap.dat.nc' cru_ts31_tas = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323/cru_ts3.23.1901.2014.tmp.dat.nc' cl20_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_october_final/cru_cl20/hur/akcan' # hur template_raster_fn = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/templates/tas_mean_C_AR5_GFDL-CM3_historical_01_1860.tif' anomalies_calc_type = 'relative' downscaling_operation = 'mult' climatology_begin = '1961' climatology_end = '1990' year_begin = '1901' year_end = '2014' variable = 'hur' metric = 'pct' args_tuples = [ ('hhi', cru_ts31_vap), ('thi', cru_ts31_tas), ('ci', cl20_path), ('tr', template_raster_fn), ('base', base_path), ('bt', year_begin), ('et', year_end), ('cbt', climatology_begin), ('cet', climatology_end), ('nc', ncores), ('at', anomalies_calc_type), ('m', metric), ('dso', downscaling_operation), ('v', variable) ] args = ''.join([ ' -'+flag+' '+value for flag, value in args_tuples ]) os.system( 'ipython2.7 -i -- hur_cru_ts31_to_cl20_downscaling.py ' + args ) # PRECIP import os os.chdir( '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/CODE/tem_ar5_inputs/downscale_cmip5/bin' ) ncores = '14' base_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323' cru_ts31 = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_ts323/cru_ts3.23.1901.2014.pre.dat.nc' cl20_path = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/cru_october_final/cru_cl20/pre/akcan' template_raster_fn = '/workspace/Shared/Tech_Projects/ALFRESCO_Inputs/project_data/TEM_Data/templates/tas_mean_C_AR5_GFDL-CM3_historical_01_1860.tif' anomalies_calc_type = 'relative' downscaling_operation = 'mult' climatology_begin = '1961' climatology_end = '1990' year_begin = '1901' year_end = '2014' variable = 'pre' metric = 'mm' args_tuples = [ ('hi', cru_ts31), ('ci', cl20_path), ('tr', template_raster_fn), ('base', base_path), ('bt', year_begin), ('et', year_end), ('cbt', climatology_begin), ('cet', climatology_end), ('nc', ncores), ('at', anomalies_calc_type), ('m', metric), ('dso', downscaling_operation), ('v', variable) ] args = ''.join([ ' -'+flag+' '+value for flag, value in args_tuples ]) os.system( 'ipython2.7 -- tas_cld_cru_ts31_to_cl20_downscaling.py ' + args )

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0

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0

1

0

1

0

1

null

0

8

c49ad91e2ed5fe2988a43b2bdcde263133ddd00d

12,426

py

Python

tests/test_siemens.py

clintonjwang/dicom2nifti

6f7533cccb587d63423c6f77824a60776c8d5b5d

[ "MIT" ]

null

tests/test_siemens.py

clintonjwang/dicom2nifti

6f7533cccb587d63423c6f77824a60776c8d5b5d

[ "MIT" ]

null

tests/test_siemens.py

clintonjwang/dicom2nifti

6f7533cccb587d63423c6f77824a60776c8d5b5d

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ dicom2nifti @author: abrys """ import os import shutil import tempfile import unittest import nibabel import numpy import dicom2nifti.compressed_dicom as compressed_dicom import pydicom import tests.test_data as test_data import dicom2nifti.convert_siemens as convert_siemens from dicom2nifti.common import read_dicom_directory from tests.test_tools import assert_compare_nifti, assert_compare_bval, assert_compare_bvec, ground_thruth_filenames class TestConversionSiemens(unittest.TestCase): def test_diffusion_imaging(self): tmp_output_dir = tempfile.mkdtemp() try: results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_DTI), None) self.assertTrue(results.get('NII_FILE') is None) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) self.assertTrue(results.get('BVAL_FILE') is None) self.assertTrue(isinstance(results['BVAL'], numpy.ndarray)) self.assertTrue(results.get('BVEC_FILE') is None) self.assertTrue(isinstance(results['BVEC'], numpy.ndarray)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_DTI), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) assert_compare_bval(results['BVAL_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI)[2]) self.assertTrue(isinstance(results['BVAL'], numpy.ndarray)) assert_compare_bval(results['BVEC_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI)[3]) self.assertTrue(isinstance(results['BVEC'], numpy.ndarray)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_DTI_IMPLICIT), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI_IMPLICIT)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) assert_compare_bval(results['BVAL_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI_IMPLICIT)[2]) self.assertTrue(isinstance(results['BVAL'], numpy.ndarray)) assert_compare_bval(results['BVEC_FILE'], ground_thruth_filenames(test_data.SIEMENS_DTI_IMPLICIT)[3]) self.assertTrue(isinstance(results['BVEC'], numpy.ndarray)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) assert_compare_bval(results['BVAL_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI)[2]) self.assertTrue(isinstance(results['BVAL'], numpy.ndarray)) assert_compare_bval(results['BVEC_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI)[3]) self.assertTrue(isinstance(results['BVEC'], numpy.ndarray)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI_IMPLICIT), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI_IMPLICIT)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) assert_compare_bval(results['BVAL_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI_IMPLICIT)[2]) self.assertTrue(isinstance(results['BVAL'], numpy.ndarray)) assert_compare_bval(results['BVEC_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_DTI_IMPLICIT)[3]) self.assertTrue(isinstance(results['BVEC'], numpy.ndarray)) finally: shutil.rmtree(tmp_output_dir) def test_4d(self): tmp_output_dir = tempfile.mkdtemp() try: results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_FMRI), None) self.assertTrue(results.get('NII_FILE') is None) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_FMRI), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_FMRI)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_FMRI_IMPLICIT), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_FMRI_IMPLICIT)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_FMRI)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI_IMPLICIT), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_CLASSIC_FMRI_IMPLICIT)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) finally: shutil.rmtree(tmp_output_dir) def test_anatomical(self): tmp_output_dir = tempfile.mkdtemp() try: results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_ANATOMICAL), None) self.assertTrue(results.get('NII_FILE') is None) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_ANATOMICAL), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_ANATOMICAL)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) results = convert_siemens.dicom_to_nifti(read_dicom_directory(test_data.SIEMENS_ANATOMICAL_IMPLICIT), os.path.join(tmp_output_dir, 'test.nii.gz')) assert_compare_nifti(results['NII_FILE'], ground_thruth_filenames(test_data.SIEMENS_ANATOMICAL_IMPLICIT)[0]) self.assertTrue(isinstance(results['NII'], nibabel.nifti1.Nifti1Image)) finally: shutil.rmtree(tmp_output_dir) def test_is_mosaic(self): # test wit directory assert convert_siemens._is_mosaic(read_dicom_directory(test_data.SIEMENS_DTI)) assert convert_siemens._is_mosaic(read_dicom_directory(test_data.SIEMENS_FMRI)) assert not convert_siemens._is_mosaic(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI)) assert not convert_siemens._is_mosaic(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI)) assert not convert_siemens._is_mosaic(read_dicom_directory(test_data.SIEMENS_ANATOMICAL)) # test with grouped dicoms assert convert_siemens._is_mosaic( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_DTI))) assert convert_siemens._is_mosaic( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_FMRI))) assert not convert_siemens._is_mosaic( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI))) assert not convert_siemens._is_mosaic( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI))) assert not convert_siemens._is_mosaic( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_ANATOMICAL))) def test_is_4d(self): assert convert_siemens._is_4d(read_dicom_directory(test_data.SIEMENS_DTI)) assert convert_siemens._is_4d(read_dicom_directory(test_data.SIEMENS_FMRI)) assert not convert_siemens._is_4d(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI)) assert not convert_siemens._is_4d(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI)) assert not convert_siemens._is_4d(read_dicom_directory(test_data.SIEMENS_ANATOMICAL)) def test_is_diffusion_imaging(self): assert convert_siemens._is_diffusion_imaging(read_dicom_directory(test_data.SIEMENS_DTI)[0]) assert not convert_siemens._is_diffusion_imaging(read_dicom_directory(test_data.SIEMENS_FMRI)[0]) assert convert_siemens._is_diffusion_imaging(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI)[0]) assert not convert_siemens._is_diffusion_imaging(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI)[0]) assert not convert_siemens._is_diffusion_imaging(read_dicom_directory(test_data.SIEMENS_ANATOMICAL)[0]) def test_is_classic_4d(self): assert not convert_siemens._is_classic_4d( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_DTI))) assert not convert_siemens._is_classic_4d( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_FMRI))) assert convert_siemens._is_classic_4d( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_CLASSIC_DTI))) assert convert_siemens._is_classic_4d( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_CLASSIC_FMRI))) assert not convert_siemens._is_classic_4d( convert_siemens._classic_get_grouped_dicoms(read_dicom_directory(test_data.SIEMENS_ANATOMICAL))) def test_is_siemens(self): assert not convert_siemens.is_siemens(read_dicom_directory(test_data.PHILIPS_ANATOMICAL)) assert convert_siemens.is_siemens(read_dicom_directory(test_data.SIEMENS_ANATOMICAL)) assert not convert_siemens.is_siemens(read_dicom_directory(test_data.GE_ANATOMICAL)) assert not convert_siemens.is_siemens(read_dicom_directory(test_data.GENERIC_ANATOMICAL)) assert not convert_siemens.is_siemens(read_dicom_directory(test_data.HITACHI_ANATOMICAL)) def test_get_asconv_headers(self): mosaic = compressed_dicom.read_file(os.path.join(test_data.SIEMENS_FMRI, 'IM-0001-0001.dcm')) asconv_headers = convert_siemens._get_asconv_headers(mosaic) assert len(asconv_headers) == 64022 if __name__ == '__main__': unittest.main()

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12,426

205

117

60.614634

0.814432

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7

c4c4523ad6f7ab81e2098496ddaef99ba8c7f217

106,985

py

Python

uptrends/api/alert_definition_api.py

hpcc-systems/uptrends-python

2e05ba851a4e65bde3c40514f499c475465bef90

[ "BSD-3-Clause" ]

null

uptrends/api/alert_definition_api.py

hpcc-systems/uptrends-python

2e05ba851a4e65bde3c40514f499c475465bef90

[ "BSD-3-Clause" ]

null

uptrends/api/alert_definition_api.py

hpcc-systems/uptrends-python

2e05ba851a4e65bde3c40514f499c475465bef90

[ "BSD-3-Clause" ]

null

# coding: utf-8 """ Uptrends API v4 This document describes Uptrends API version 4. This Swagger environment also lets you execute API methods directly. Please note that this is not a sandbox environment: these API methods operate directly on your actual Uptrends account. For more information, please visit https://www.uptrends.com/api. # noqa: E501 OpenAPI spec version: 1.0.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from uptrends.api_client import ApiClient class AlertDefinitionApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def alert_definition_add_monitor_group_to_alert_definition(self, alert_definition_guid, monitor_group_guid, **kwargs): # noqa: E501 """Adds a monitor group to the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_monitor_group_to_alert_definition(alert_definition_guid, monitor_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_group_guid: The Guid of the monitor group to add. (required) :return: AlertDefinitionMonitorGroup If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_add_monitor_group_to_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_add_monitor_group_to_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, **kwargs) # noqa: E501 return data def alert_definition_add_monitor_group_to_alert_definition_with_http_info(self, alert_definition_guid, monitor_group_guid, **kwargs): # noqa: E501 """Adds a monitor group to the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_monitor_group_to_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_group_guid: The Guid of the monitor group to add. (required) :return: AlertDefinitionMonitorGroup If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'monitor_group_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_add_monitor_group_to_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_add_monitor_group_to_alert_definition`") # noqa: E501 # verify the required parameter 'monitor_group_guid' is set if ('monitor_group_guid' not in params or params['monitor_group_guid'] is None): raise ValueError("Missing the required parameter `monitor_group_guid` when calling `alert_definition_add_monitor_group_to_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'monitor_group_guid' in params: path_params['monitorGroupGuid'] = params['monitor_group_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/Members/MonitorGroup/{monitorGroupGuid}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinitionMonitorGroup', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_add_monitor_to_alert_definition(self, alert_definition_guid, monitor_guid, **kwargs): # noqa: E501 """Adds a monitor to the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_monitor_to_alert_definition(alert_definition_guid, monitor_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_guid: The Guid of the monitor to add. (required) :return: AlertDefinitionMonitor If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_add_monitor_to_alert_definition_with_http_info(alert_definition_guid, monitor_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_add_monitor_to_alert_definition_with_http_info(alert_definition_guid, monitor_guid, **kwargs) # noqa: E501 return data def alert_definition_add_monitor_to_alert_definition_with_http_info(self, alert_definition_guid, monitor_guid, **kwargs): # noqa: E501 """Adds a monitor to the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_monitor_to_alert_definition_with_http_info(alert_definition_guid, monitor_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_guid: The Guid of the monitor to add. (required) :return: AlertDefinitionMonitor If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'monitor_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_add_monitor_to_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_add_monitor_to_alert_definition`") # noqa: E501 # verify the required parameter 'monitor_guid' is set if ('monitor_guid' not in params or params['monitor_guid'] is None): raise ValueError("Missing the required parameter `monitor_guid` when calling `alert_definition_add_monitor_to_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'monitor_guid' in params: path_params['monitorGuid'] = params['monitor_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/Members/Monitor/{monitorGuid}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinitionMonitor', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_add_operator_group_to_escalation_level(self, alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs): # noqa: E501 """Adds an operator group to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_operator_group_to_escalation_level(alert_definition_guid, escalation_level_id, operator_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_group_guid: The Guid of the operator group to add. (required) :return: AlertDefinitionOperatorGroup If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_add_operator_group_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_add_operator_group_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs) # noqa: E501 return data def alert_definition_add_operator_group_to_escalation_level_with_http_info(self, alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs): # noqa: E501 """Adds an operator group to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_operator_group_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_group_guid: The Guid of the operator group to add. (required) :return: AlertDefinitionOperatorGroup If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id', 'operator_group_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_add_operator_group_to_escalation_level" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_add_operator_group_to_escalation_level`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_add_operator_group_to_escalation_level`") # noqa: E501 # verify the required parameter 'operator_group_guid' is set if ('operator_group_guid' not in params or params['operator_group_guid'] is None): raise ValueError("Missing the required parameter `operator_group_guid` when calling `alert_definition_add_operator_group_to_escalation_level`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'operator_group_guid' in params: path_params['operatorGroupGuid'] = params['operator_group_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Members/OperatorGroup/{operatorGroupGuid}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinitionOperatorGroup', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_add_operator_to_escalation_level(self, alert_definition_guid, escalation_level_id, operator_guid, **kwargs): # noqa: E501 """Adds an operator to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_operator_to_escalation_level(alert_definition_guid, escalation_level_id, operator_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_guid: The Guid of the operator to add. (required) :return: AlertDefinitionOperator If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_add_operator_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_add_operator_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, **kwargs) # noqa: E501 return data def alert_definition_add_operator_to_escalation_level_with_http_info(self, alert_definition_guid, escalation_level_id, operator_guid, **kwargs): # noqa: E501 """Adds an operator to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_add_operator_to_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_guid: The Guid of the operator to add. (required) :return: AlertDefinitionOperator If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id', 'operator_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_add_operator_to_escalation_level" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_add_operator_to_escalation_level`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_add_operator_to_escalation_level`") # noqa: E501 # verify the required parameter 'operator_guid' is set if ('operator_guid' not in params or params['operator_guid'] is None): raise ValueError("Missing the required parameter `operator_guid` when calling `alert_definition_add_operator_to_escalation_level`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'operator_guid' in params: path_params['operatorGuid'] = params['operator_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Members/Operator/{operatorGuid}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinitionOperator', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_create_alert_definition(self, alert_definition, **kwargs): # noqa: E501 """Creates a new alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_create_alert_definition(alert_definition, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The details of the alert definition to create. (required) :return: AlertDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_create_alert_definition_with_http_info(alert_definition, **kwargs) # noqa: E501 else: (data) = self.alert_definition_create_alert_definition_with_http_info(alert_definition, **kwargs) # noqa: E501 return data def alert_definition_create_alert_definition_with_http_info(self, alert_definition, **kwargs): # noqa: E501 """Creates a new alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_create_alert_definition_with_http_info(alert_definition, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The details of the alert definition to create. (required) :return: AlertDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_create_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition' is set if ('alert_definition' not in params or params['alert_definition'] is None): raise ValueError("Missing the required parameter `alert_definition` when calling `alert_definition_create_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'alert_definition' in params: body_params = params['alert_definition'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinition', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_delete_alert_definition(self, alert_definition_guid, **kwargs): # noqa: E501 """Deletes an existing alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_delete_alert_definition(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_delete_alert_definition_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_delete_alert_definition_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 return data def alert_definition_delete_alert_definition_with_http_info(self, alert_definition_guid, **kwargs): # noqa: E501 """Deletes an existing alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_delete_alert_definition_with_http_info(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_delete_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_delete_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_all_alert_definitions(self, **kwargs): # noqa: E501 """Gets a list of all alert definitions. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_all_alert_definitions(async_req=True) >>> result = thread.get() :param async_req bool :return: list[AlertDefinition] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_all_alert_definitions_with_http_info(**kwargs) # noqa: E501 else: (data) = self.alert_definition_get_all_alert_definitions_with_http_info(**kwargs) # noqa: E501 return data def alert_definition_get_all_alert_definitions_with_http_info(self, **kwargs): # noqa: E501 """Gets a list of all alert definitions. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_all_alert_definitions_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :return: list[AlertDefinition] If the method is called asynchronously, returns the request thread. """ all_params = [] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_all_alert_definitions" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[AlertDefinition]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_all_members(self, alert_definition_guid, **kwargs): # noqa: E501 """Gets a list of all monitor and monitor group guids of the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_all_members(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition for which to return the members. (required) :return: list[AlertDefinitionMember] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_all_members_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_get_all_members_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 return data def alert_definition_get_all_members_with_http_info(self, alert_definition_guid, **kwargs): # noqa: E501 """Gets a list of all monitor and monitor group guids of the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_all_members_with_http_info(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition for which to return the members. (required) :return: list[AlertDefinitionMember] If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_all_members" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_get_all_members`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/Members', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[AlertDefinitionMember]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_escalation_level(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the escalation level information of the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[EscalationLevel] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 else: (data) = self.alert_definition_get_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 return data def alert_definition_get_escalation_level_with_http_info(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the escalation level information of the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[EscalationLevel] If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_escalation_level" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_get_escalation_level`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_get_escalation_level`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='EscalationLevel', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_escalation_level_integration(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the integrations for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level_integration(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[Integration] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_escalation_level_integration_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 else: (data) = self.alert_definition_get_escalation_level_integration_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 return data def alert_definition_get_escalation_level_integration_with_http_info(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the integrations for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level_integration_with_http_info(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[Integration] If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_escalation_level_integration" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_get_escalation_level_integration`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_get_escalation_level_integration`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Integration', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Integration]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_escalation_level_operator(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the operator and operator group guids for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level_operator(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[AlertEscalationLevelMember] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_escalation_level_operator_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 else: (data) = self.alert_definition_get_escalation_level_operator_with_http_info(alert_definition_guid, escalation_level_id, **kwargs) # noqa: E501 return data def alert_definition_get_escalation_level_operator_with_http_info(self, alert_definition_guid, escalation_level_id, **kwargs): # noqa: E501 """Gets the operator and operator group guids for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_escalation_level_operator_with_http_info(alert_definition_guid, escalation_level_id, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :return: list[AlertEscalationLevelMember] If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_escalation_level_operator" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_get_escalation_level_operator`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_get_escalation_level_operator`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Members', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[AlertEscalationLevelMember]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_get_specified_alert_definitions(self, alert_definition_guid, **kwargs): # noqa: E501 """Gets the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_specified_alert_definitions(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :return: AlertDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_get_specified_alert_definitions_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_get_specified_alert_definitions_with_http_info(alert_definition_guid, **kwargs) # noqa: E501 return data def alert_definition_get_specified_alert_definitions_with_http_info(self, alert_definition_guid, **kwargs): # noqa: E501 """Gets the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_get_specified_alert_definitions_with_http_info(alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :return: AlertDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_get_specified_alert_definitions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_get_specified_alert_definitions`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AlertDefinition', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_patch_alert_definition(self, alert_definition, alert_definition_guid, **kwargs): # noqa: E501 """Partially updates the definition of the specified alert definition. # noqa: E501 This methods accepts parts of an alert definition. Fields that do not require changes can be omitted. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_patch_alert_definition(alert_definition, alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The partial definition for the alert definition that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition that should be updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_patch_alert_definition_with_http_info(alert_definition, alert_definition_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_patch_alert_definition_with_http_info(alert_definition, alert_definition_guid, **kwargs) # noqa: E501 return data def alert_definition_patch_alert_definition_with_http_info(self, alert_definition, alert_definition_guid, **kwargs): # noqa: E501 """Partially updates the definition of the specified alert definition. # noqa: E501 This methods accepts parts of an alert definition. Fields that do not require changes can be omitted. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_patch_alert_definition_with_http_info(alert_definition, alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The partial definition for the alert definition that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition that should be updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition', 'alert_definition_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_patch_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition' is set if ('alert_definition' not in params or params['alert_definition'] is None): raise ValueError("Missing the required parameter `alert_definition` when calling `alert_definition_patch_alert_definition`") # noqa: E501 # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_patch_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'alert_definition' in params: body_params = params['alert_definition'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_put_alert_definition(self, alert_definition, alert_definition_guid, **kwargs): # noqa: E501 """Updates the definition of the specified alert definition. # noqa: E501 This methods only accepts a complete alert definition where all fields are specified. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_put_alert_definition(alert_definition, alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The partial definition for the alert definition that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition that should be updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_put_alert_definition_with_http_info(alert_definition, alert_definition_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_put_alert_definition_with_http_info(alert_definition, alert_definition_guid, **kwargs) # noqa: E501 return data def alert_definition_put_alert_definition_with_http_info(self, alert_definition, alert_definition_guid, **kwargs): # noqa: E501 """Updates the definition of the specified alert definition. # noqa: E501 This methods only accepts a complete alert definition where all fields are specified. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_put_alert_definition_with_http_info(alert_definition, alert_definition_guid, async_req=True) >>> result = thread.get() :param async_req bool :param AlertDefinition alert_definition: The partial definition for the alert definition that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition that should be updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition', 'alert_definition_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_put_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition' is set if ('alert_definition' not in params or params['alert_definition'] is None): raise ValueError("Missing the required parameter `alert_definition` when calling `alert_definition_put_alert_definition`") # noqa: E501 # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_put_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'alert_definition' in params: body_params = params['alert_definition'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_remove_monitor_from_alert_definition(self, alert_definition_guid, monitor_guid, **kwargs): # noqa: E501 """Removes a monitor for the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_monitor_from_alert_definition(alert_definition_guid, monitor_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_guid: The Guid of the monitor to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_remove_monitor_from_alert_definition_with_http_info(alert_definition_guid, monitor_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_remove_monitor_from_alert_definition_with_http_info(alert_definition_guid, monitor_guid, **kwargs) # noqa: E501 return data def alert_definition_remove_monitor_from_alert_definition_with_http_info(self, alert_definition_guid, monitor_guid, **kwargs): # noqa: E501 """Removes a monitor for the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_monitor_from_alert_definition_with_http_info(alert_definition_guid, monitor_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_guid: The Guid of the monitor to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'monitor_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_remove_monitor_from_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_remove_monitor_from_alert_definition`") # noqa: E501 # verify the required parameter 'monitor_guid' is set if ('monitor_guid' not in params or params['monitor_guid'] is None): raise ValueError("Missing the required parameter `monitor_guid` when calling `alert_definition_remove_monitor_from_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'monitor_guid' in params: path_params['monitorGuid'] = params['monitor_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/Members/Monitor/{monitorGuid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_remove_monitor_group_from_alert_definition(self, alert_definition_guid, monitor_group_guid, **kwargs): # noqa: E501 """Removes a monitor group for the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_monitor_group_from_alert_definition(alert_definition_guid, monitor_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_group_guid: The Guid of the monitor group to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_remove_monitor_group_from_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_remove_monitor_group_from_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, **kwargs) # noqa: E501 return data def alert_definition_remove_monitor_group_from_alert_definition_with_http_info(self, alert_definition_guid, monitor_group_guid, **kwargs): # noqa: E501 """Removes a monitor group for the specified alert definition. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_monitor_group_from_alert_definition_with_http_info(alert_definition_guid, monitor_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition to modify. (required) :param str monitor_group_guid: The Guid of the monitor group to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'monitor_group_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_remove_monitor_group_from_alert_definition" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_remove_monitor_group_from_alert_definition`") # noqa: E501 # verify the required parameter 'monitor_group_guid' is set if ('monitor_group_guid' not in params or params['monitor_group_guid'] is None): raise ValueError("Missing the required parameter `monitor_group_guid` when calling `alert_definition_remove_monitor_group_from_alert_definition`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'monitor_group_guid' in params: path_params['monitorGroupGuid'] = params['monitor_group_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/Members/MonitorGroup/{monitorGroupGuid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_remove_operator_from_escalation_level(self, alert_definition_guid, escalation_level_id, operator_guid, **kwargs): # noqa: E501 """Removes an operator for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_operator_from_escalation_level(alert_definition_guid, escalation_level_id, operator_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_guid: The Guid of the operator to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_remove_operator_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_remove_operator_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, **kwargs) # noqa: E501 return data def alert_definition_remove_operator_from_escalation_level_with_http_info(self, alert_definition_guid, escalation_level_id, operator_guid, **kwargs): # noqa: E501 """Removes an operator for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_operator_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_guid: The Guid of the operator to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id', 'operator_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_remove_operator_from_escalation_level" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_remove_operator_from_escalation_level`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_remove_operator_from_escalation_level`") # noqa: E501 # verify the required parameter 'operator_guid' is set if ('operator_guid' not in params or params['operator_guid'] is None): raise ValueError("Missing the required parameter `operator_guid` when calling `alert_definition_remove_operator_from_escalation_level`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'operator_guid' in params: path_params['operatorGuid'] = params['operator_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Members/Operator/{operatorGuid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_remove_operator_group_from_escalation_level(self, alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs): # noqa: E501 """Removes an operator group for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_operator_group_from_escalation_level(alert_definition_guid, escalation_level_id, operator_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_group_guid: The Guid of the operator group to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_remove_operator_group_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_remove_operator_group_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs) # noqa: E501 return data def alert_definition_remove_operator_group_from_escalation_level_with_http_info(self, alert_definition_guid, escalation_level_id, operator_group_guid, **kwargs): # noqa: E501 """Removes an operator group for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_remove_operator_group_from_escalation_level_with_http_info(alert_definition_guid, escalation_level_id, operator_group_guid, async_req=True) >>> result = thread.get() :param async_req bool :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str operator_group_guid: The Guid of the operator group to remove. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['alert_definition_guid', 'escalation_level_id', 'operator_group_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_remove_operator_group_from_escalation_level" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_remove_operator_group_from_escalation_level`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_remove_operator_group_from_escalation_level`") # noqa: E501 # verify the required parameter 'operator_group_guid' is set if ('operator_group_guid' not in params or params['operator_group_guid'] is None): raise ValueError("Missing the required parameter `operator_group_guid` when calling `alert_definition_remove_operator_group_from_escalation_level`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'operator_group_guid' in params: path_params['operatorGroupGuid'] = params['operator_group_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Members/OperatorGroup/{operatorGroupGuid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_update_integration_for_escalation_with_patch(self, escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs): # noqa: E501 """Partially updates an integration to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_update_integration_for_escalation_with_patch(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, async_req=True) >>> result = thread.get() :param async_req bool :param EscalationLevelIntegration escalation_level_integration: The partial definition for the integration that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str integration_guid: The Guid of the integration to update. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_update_integration_for_escalation_with_patch_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_update_integration_for_escalation_with_patch_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs) # noqa: E501 return data def alert_definition_update_integration_for_escalation_with_patch_with_http_info(self, escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs): # noqa: E501 """Partially updates an integration to the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_update_integration_for_escalation_with_patch_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, async_req=True) >>> result = thread.get() :param async_req bool :param EscalationLevelIntegration escalation_level_integration: The partial definition for the integration that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str integration_guid: The Guid of the integration to update. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['escalation_level_integration', 'alert_definition_guid', 'escalation_level_id', 'integration_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_update_integration_for_escalation_with_patch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'escalation_level_integration' is set if ('escalation_level_integration' not in params or params['escalation_level_integration'] is None): raise ValueError("Missing the required parameter `escalation_level_integration` when calling `alert_definition_update_integration_for_escalation_with_patch`") # noqa: E501 # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_update_integration_for_escalation_with_patch`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_update_integration_for_escalation_with_patch`") # noqa: E501 # verify the required parameter 'integration_guid' is set if ('integration_guid' not in params or params['integration_guid'] is None): raise ValueError("Missing the required parameter `integration_guid` when calling `alert_definition_update_integration_for_escalation_with_patch`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'integration_guid' in params: path_params['integrationGuid'] = params['integration_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'escalation_level_integration' in params: body_params = params['escalation_level_integration'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Integration/{integrationGuid}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def alert_definition_update_integration_for_escalation_with_put(self, escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs): # noqa: E501 """Updates an integration for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_update_integration_for_escalation_with_put(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, async_req=True) >>> result = thread.get() :param async_req bool :param EscalationLevelIntegration escalation_level_integration: The definition for the integration that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str integration_guid: The Guid of the integration to update. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.alert_definition_update_integration_for_escalation_with_put_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs) # noqa: E501 else: (data) = self.alert_definition_update_integration_for_escalation_with_put_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs) # noqa: E501 return data def alert_definition_update_integration_for_escalation_with_put_with_http_info(self, escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, **kwargs): # noqa: E501 """Updates an integration for the specified escalation level. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.alert_definition_update_integration_for_escalation_with_put_with_http_info(escalation_level_integration, alert_definition_guid, escalation_level_id, integration_guid, async_req=True) >>> result = thread.get() :param async_req bool :param EscalationLevelIntegration escalation_level_integration: The definition for the integration that should be updated. (required) :param str alert_definition_guid: The Guid of the alert definition. (required) :param int escalation_level_id: The escalation level id. (required) :param str integration_guid: The Guid of the integration to update. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['escalation_level_integration', 'alert_definition_guid', 'escalation_level_id', 'integration_guid'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method alert_definition_update_integration_for_escalation_with_put" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'escalation_level_integration' is set if ('escalation_level_integration' not in params or params['escalation_level_integration'] is None): raise ValueError("Missing the required parameter `escalation_level_integration` when calling `alert_definition_update_integration_for_escalation_with_put`") # noqa: E501 # verify the required parameter 'alert_definition_guid' is set if ('alert_definition_guid' not in params or params['alert_definition_guid'] is None): raise ValueError("Missing the required parameter `alert_definition_guid` when calling `alert_definition_update_integration_for_escalation_with_put`") # noqa: E501 # verify the required parameter 'escalation_level_id' is set if ('escalation_level_id' not in params or params['escalation_level_id'] is None): raise ValueError("Missing the required parameter `escalation_level_id` when calling `alert_definition_update_integration_for_escalation_with_put`") # noqa: E501 # verify the required parameter 'integration_guid' is set if ('integration_guid' not in params or params['integration_guid'] is None): raise ValueError("Missing the required parameter `integration_guid` when calling `alert_definition_update_integration_for_escalation_with_put`") # noqa: E501 collection_formats = {} path_params = {} if 'alert_definition_guid' in params: path_params['alertDefinitionGuid'] = params['alert_definition_guid'] # noqa: E501 if 'escalation_level_id' in params: path_params['escalationLevelId'] = params['escalation_level_id'] # noqa: E501 if 'integration_guid' in params: path_params['integrationGuid'] = params['integration_guid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'escalation_level_integration' in params: body_params = params['escalation_level_integration'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/xml']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'application/xml']) # noqa: E501 # Authentication setting auth_settings = ['basicauth'] # noqa: E501 return self.api_client.call_api( '/AlertDefinition/{alertDefinitionGuid}/EscalationLevel/{escalationLevelId}/Integration/{integrationGuid}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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c4ff62e06552a2fb5ed82e376b924f37bb949faa

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py

Python

TP1/src/alineaC.py

LuisPereira23/PL-2021

951190835d8989e3afda1fd0f8f9ef08f5d85e07

[ "MIT" ]

null

TP1/src/alineaC.py

LuisPereira23/PL-2021

951190835d8989e3afda1fd0f8f9ef08f5d85e07

[ "MIT" ]

null

TP1/src/alineaC.py

LuisPereira23/PL-2021

951190835d8989e3afda1fd0f8f9ef08f5d85e07

[ "MIT" ]

null

import re def bibtex2json(docBib): docBib = "[" + docBib docBib = re.sub( r',\n', r',', docBib ) docBib = re.sub( r'["}],', r',\n', docBib ) docBib = re.sub( r'@', r'\n@', docBib ) docBib = re.sub( r'%(.)*', r'', docBib ) docBib = re.sub( r'>.*\n+', r'', docBib ) docBib = re.sub( r'@([a-zA-z]+){([À-ÿa-zA-Z0-9 :,\\{}/\.\-]+),', r'{\n\t"categoria":"\1",\n\t"label":"\2",', docBib ) docBib = re.sub( r'(?i) +author *= *{([À-ÿa-zA-Z0-9 ,\\{}:/\.\'\~]+)\n? *([À-ÿa-zA-Z0-9 ,\\{}:/\.]*)}', r'\t"author":"\1 \2"', docBib ) docBib = re.sub( r'(?i) +author *= *\"([À-ÿa-zA-Z0-9 ,\\{}:/\.]+)\n? *([À-ÿa-zA-Z0-9 ,\\{}:/\.]*)\"', r'\t"author":"\1 \2"', docBib ) docBib = re.sub( r'(?i) +title *= *{([À-ÿa-zA-Z0-9 ,\{\}\+\=\!:\/\.\?\_\$\-\&\'\{\}\#\\]+)\n?( *[À-ÿa-zA-Z0-9 ,\{\}:\/\.\-*]*)\n?( *[À-ÿa-zA-Z0-9 ,\{\}:\/\.]*)}', r'\t"title":"\1\2\3"', docBib ) docBib = re.sub( r'(?i) +title *= *{([^"]+)\n?("(.*)")( *[À-ÿa-zA-Z0-9 ,\\{}:\/\.\-*]*)\n?( *[À-ÿa-zA-Z0-9 ,\\{}:\/\.]*)}', r'\t"title":"\1\3\4"', docBib ) docBib = re.sub( r' +title *= *\"([À-ÿa-zA-Z0-9 \=\,\{\}\!:\/\.\?\\]+)\n?( *[À-ÿa-zA-Z0-9 \,\{\}:\/\.\-\*]*)\n?( *[À-ÿa-zA-Z0-9 \,\{\}\:\/\.]*)\"', r'\t"title":"\1\2\3"', docBib ) docBib = re.sub( r' +note *= *\"([À-ÿa-zA-Z0-9 ,\\{}:/\.]+)\n? *([À-ÿa-zA-Z0-9 ,\\{}:/\.]*)\"', r'\t"note":"\1\2"', docBib ) docBib = re.sub( r' +note *= *{([^}]*) *}', r'\t"note":"\1"', docBib ) docBib = re.sub( r'(?i) +booktitle *= *{([\$\º\'\ª\-À-ÿa-zA-Z0-9 ,\\{}:/\.]+)\n? *([À-ÿa-zA-Z0-9 ,\\{}:/\.]*)}', r'\t"booktitle":"\1 \2"', docBib ) docBib = re.sub( r'(?i) +booktitle *= *\"([\'\-À-ÿa-zA-Z0-9 ,\\{}:/\.]+)\n? *([À-ÿa-zA-Z0-9 ,\\{}:/\.]*)\"', r'\t"booktitle":"\1 \2"', docBib ) docBib = re.sub( r' +address *= *\"([^\"]+)\"', r'\t"adress":"\1"', docBib ) docBib = re.sub( r' +address *= *{(.*) *}', r'\t"address":"\1"', docBib ) docBib = re.sub( r'(?i) +year *= *([0-9]+)', r'\t"year":"\1"', docBib ) docBib = re.sub( r'(?i) +year *= *\"([0-9]+)\"', r'\t"year":"\1"', docBib ) docBib = re.sub( r'(?i) +year *= *{([0-9]*)}', r'\t"year":"\1"', docBib ) docBib = re.sub( r' +institution *= *\"(.*) *\"', r'\t"institution":"\1"', docBib ) docBib = re.sub( r' +type *= *\"(.*) *\"', r'\t"type":"\1"', docBib ) docBib = re.sub( r' +keyword *= *\"(.*) *\"', r'\t"keyword":"\1"', docBib ) docBib = re.sub( r' +keyword *= *{(.*) *}', r'\t"keyword":"\1"', docBib ) docBib = re.sub( r' +editor *=\t* *{(.*) *}', r'\t"editor":"\1"', docBib ) docBib = re.sub( r' +url *= *\"(.*) *\"', r'\t"url":"\1"', docBib ) docBib = re.sub( r' *url *=\n? *{(.*) *}', r'\t"url":"\1"', docBib ) docBib = re.sub( r' +month *= *\"(.*) *\"', r'\t"month":"\1"', docBib ) docBib = re.sub( r' +month *= *{(.*) *}', r'\t"month":"\1"', docBib ) # # docBib = re.sub( # r' +abstract *= *{([0-9]*)}', # r'\t"abstract":"\1"', # docBib # ) # # docBib = re.sub( # r' +abstract *= *\"([0-9]*)\"', # r'\t"abstract":"\1"', # docBib # ) docBib = re.sub( r' +editor *= *\"(.+) *\"', r'\t"editor":"\1"', docBib ) docBib = re.sub( r' +pages *= *\"(.*) *\"', r'\t"pages":"\1"', docBib ) docBib = re.sub( r' +pages *=\t* *{(.*) *}', r'\t"pages":"\1"', docBib ) docBib = re.sub( r' +number *= *[\"{](.*) *[\"}]', r'\t"number":"\1"', docBib ) docBib = re.sub( r' +number *= *\"?([0-9]*)\"?', r'\t"number":"\1"', docBib ) docBib = re.sub( r' +note *= *\"(.+) *\"', r'\t"note":"\1"', docBib ) docBib = re.sub( r' +publisher *= *\"(.*) *\"', r'\t"publisher":"\1"', docBib ) docBib = re.sub( r' +publisher *= *{(.*) *}', r'\t"publisher":"\1"', docBib ) docBib = re.sub( r' +docpage *= *\"(.+) *\"', r'\t"docpage":"\1"', docBib ) docBib = re.sub( r' +series *= *\"(.+) *\"', r'\t"series":"\1"', docBib ) docBib = re.sub( r' +series *=\t* *{(.+) *}', r'\t"series":"\1"', docBib ) docBib = re.sub( r'(?i) +volume *= *\"([0-9]*)\"', r'\t"volume":"\1"', docBib ) docBib = re.sub( r'(?i) +volume *=\t* *{?([0-9A-Z ]*)}?', r'\t"volume":"\1"', docBib ) docBib = re.sub( r' +journal *= *{(.+) *}', r'\t"journal":"\1"', docBib ) docBib = re.sub( r' +journal *= *\"(.+) *\"', r'\t"journal":"\1"', docBib ) docBib = re.sub( r' +isbn *= *\"(.*) *\"', r'\t"isbn":"\1"', docBib ) docBib = re.sub( r' +(isbn|ISBN)(13)? *= *{(.*) *}', r'\t"\1\2":"\3"', docBib ) docBib = re.sub( r' +lang *= *\"(.*) *\"', r'\t"lang":"\1"', docBib ) docBib = re.sub( r' +lang *= *{(.*) *}', r'\t"lang":"\1"', docBib ) docBib = re.sub( r' +school *= *{(.+) *}', r'\t"school":"\1"', docBib ) docBib = re.sub( r' +superviser *= *\"(.*) *\"', r'\t"superviser":"\1"', docBib ) docBib = re.sub( r' +location *= *\"(.*) *\"', r'\t"location":"\1"', docBib ) docBib = re.sub( r' +Note *= *\"(.*) *\"', r'\t"note":"\1"', docBib ) docBib = re.sub( r' +shortin *= *{(.*) *}', r'\t"shortin":"\1"', docBib ) docBib = re.sub( r' +edition *=\t* *{(.*) *}', r'\t"edition":"\1"', docBib ) docBib = re.sub( r' +annote *=\t* *{(.*) *}', r'\t"annote":"\1"', docBib ) docBib = re.sub( r'\\', r'\\\\', docBib ) docBib = re.sub( r'}\n', r'},\n', docBib ) docBib = re.sub( r',\n}', r'\n}', docBib ) docBib = docBib + "]" return docBib with open("exemplo-utf8.bib", encoding="utf8") as f: out = open ("out.json","w") conteudo = f.read() out.write(bibtex2json(conteudo))

18.716146

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null

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1

0

null

0

9

48009df1ff99e9a6f744b8e81b4555fa1822c2b6

21,675

py

Python

smaframework/common/address_keywords_extension_map.py

diegopso/smaframework

a49ccd1f035ab257acf734e07f88b4ed17d6cbc3

[ "MIT" ]

1

2020-12-25T07:10:27.000Z

smaframework/common/address_keywords_extension_map.py

diegopso/smaframework

a49ccd1f035ab257acf734e07f88b4ed17d6cbc3

[ "MIT" ]

null

smaframework/common/address_keywords_extension_map.py

diegopso/smaframework

a49ccd1f035ab257acf734e07f88b4ed17d6cbc3

[ "MIT" ]

null

import re ''' * Parses an address string to collect the relevant keywords. * * @param address - The address string. * @param mode - `extend` (to add abbreviations) or `clean` (to remove commom words). ''' def parse_str(address, mode='clean'): address_str = re.sub('[^a-zA-Z0-9\-]+', ' ', address).lower() address_keywords = address_str.split() if mode == 'extend': extensions = list(map(lambda k: next((tp for tp in address_keywords_extensions if k in tp), []), address_keywords)) for e in extensions: if len(e): address_keywords.extend(e) elif mode == 'clean': address_keywords = [item for item in address_keywords if item not in address_stop_words] return address_keywords address_stop_words = ["alley","allee","aly","ally","anex","anx","annex","annx","arcade","arc","avenue","av","ave","aven","avenu","avn","avnue","bayou","bayoo","byu","beach","bch","bend","bnd","bluff","blf","bluf","bluffs","blfs","bottom","bot","btm","bottm","boulevard","blvd","boul","boulv","branch","br","brnch","bridge","brdge","brg","brook","brk","brooks","brks","burg","bg","burgs","bgs","bypass","byp","bypa","bypas","byps","camp","cp","cmp","canyon","canyn","cyn","cnyn","cape","cpe","causeway","cswy","causwa","center","cen","ctr","cent","centr","centre","cnter","cntr","centers","ctrs","circle","cir","circ","circl","crcl","crcle","circles","cirs","cliff","clf","cliffs","clfs","club","clb","common","cmn","commons","cmns","corner","cor","corners","cors","course","crse","court","ct","courts","cts","cove","cv","coves","cvs","creek","crk","crescent","cres","crsent","crsnt","crest","crst","crossing","xing","crssng","crossroad","xrd","crossroads","xrds","curve","curv","dale","dl","dam","dm","divide","div","dv","dvd","drive","dr","driv","drv","drives","drs","estate","est","estates","ests","expressway","exp","expy","expr","express","expw","extension","ext","extn","extnsn","extensions","exts","fall","falls","fls","ferry","fry","frry","field","fld","fields","flds","flat","flt","flats","flts","ford","frd","fords","frds","forest","frst","forests","forge","forg","frg","forges","frgs","fork","frk","forks","frks","fort","ft","frt","freeway","fwy","freewy","frway","frwy","garden","gdn","gardn","grden","grdn","gardens","gdns","grdns","gateway","gtwy","gatewy","gatway","gtway","glen","gln","glens","glns","green","grn","greens","grns","grove","grov","grv","groves","grvs","harbor","harb","hbr","harbr","hrbor","harbors","hbrs","haven","hvn","heights","ht","hts","highway","hwy","highwy","hiway","hiwy","hway","hill","hl","hills","hls","hollow","hllw","holw","hollows","holws","inlet","inlt","island","is","islnd","islands","iss","islnds","isle","isles","junction","jct","jction","jctn","junctn","juncton","junctions","jctns","jcts","key","ky","keys","kys","knoll","knl","knol","knolls","knls","lake","lk","lakes","lks","land","landing","lndg","lndng","lane","ln","light","lgt","lights","lgts","loaf","lf","lock","lck","locks","lcks","lodge","ldg","ldge","lodg","loop","loops","mall","manor","mnr","manors","mnrs","meadow","mdw","meadows","mdw","mdws","medows","mews","mill","ml","mills","mls","mission","missn","msn","mssn","motorway","mtwy","mount","mnt","mt","mountain","mntain","mtn","mntn","mountin","mtin","mountains","mntns","mtns","neck","nck","orchard","orch","orchrd","oval","ovl","overpass","opas","park","prk","parks","park","parkway","pkwy","parkwy","pkway","pky","parkways","pkwy","pkwys","pass","passage","psge","path","paths","pike","pikes","pine","pne","pines","pnes","place","pl","plain","pln","plains","plns","plaza","plz","plza","point","pt","points","pts","port","prt","ports","prts","prairie","pr","prr","radial","rad","radl","radiel","ramp","ranch","rnch","ranches","rnchs","rapid","rpd","rapids","rpds","rest","rst","ridge","rdg","rdge","ridges","rdgs","river","riv","rvr","rivr","road","rd","roads","rds","route","rte","row","rue","run","shoal","shl","shoals","shls","shore","shoar","shr","shores","shoars","shrs","skyway","skwy","spring","spg","spng","sprng","springs","spgs","spngs","sprngs","spur","spurs","spur","square","sq","sqr","sqre","squ","squares","sqrs","sqs","station","sta","statn","stn","stravenue","stra","strav","straven","stravn","strvn","strvnue","stream","strm","streme","street","st","strt","str","streets","sts","summit","smt","sumit","sumitt","terrace","ter","terr","throughway","trwy","trace","trce","traces","track","trak","tracks","trk","trks","trafficway","trfy","trail","trl","trails","trls","trailer","trlr","trlrs","tunnel","tunel","tunl","tunls","tunnels","tunnl","turnpike","trnpk","tpke","turnpk","underpass","upas","union","un","unions","uns","valley","vly","vally","vlly","valleys","vlys","viaduct","vdct","via","viadct","view","vw","views","vws","village","vill","vlg","villag","villg","villiage","villages","vlgs","ville","vl","vista","vis","vist","vst","vsta","walk","walks","walk","wall","way","wy","ways","well","wl","wells","wls"] ''' * Map to extend addresses keywords, extracted from USPS.com Postal Explorer: C1 Street Suffix Abbreviations * * @param key - The key to retrieve extension options ''' address_keywords_extensions = [ [ "alley", "allee", "aly", "ally" ], [ "anex", "anx", "annex", "annx" ], [ "arcade", "arc" ], [ "avenue", "av", "ave", "aven", "avenu", "avn", "avnue" ], [ "bayou", "bayoo", "byu" ], [ "beach", "bch" ], [ "bend", "bnd" ], [ "bluff", "blf", "bluf" ], [ "bluffs", "blfs" ], [ "bottom", "bot", "btm", "bottm" ], [ "boulevard", "blvd", "boul", "boulv" ], [ "branch", "br", "brnch" ], [ "bridge", "brdge", "brg" ], [ "brook", "brk" ], [ "brooks", "brks" ], [ "burg", "bg" ], [ "burgs", "bgs" ], [ "bypass", "byp", "bypa", "bypas", "byps" ], [ "camp", "cp", "cmp" ], [ "canyon", "canyn", "cyn", "cnyn" ], [ "cape", "cpe" ], [ "causeway", "cswy", "causwa" ], [ "center", "cen", "ctr", "cent", "centr", "centre", "cnter", "cntr" ], [ "centers", "ctrs" ], [ "circle", "cir", "circ", "circl", "crcl", "crcle" ], [ "circles", "cirs" ], [ "cliff", "clf" ], [ "cliffs", "clfs" ], [ "club", "clb" ], [ "common", "cmn" ], [ "commons", "cmns" ], [ "corner", "cor" ], [ "corners", "cors" ], [ "course", "crse" ], [ "court", "ct" ], [ "courts", "cts" ], [ "cove", "cv" ], [ "coves", "cvs" ], [ "creek", "crk" ], [ "crescent", "cres", "crsent", "crsnt" ], [ "crest", "crst" ], [ "crossing", "xing", "crssng" ], [ "crossroad", "xrd" ], [ "crossroads", "xrds" ], [ "curve", "curv" ], [ "dale", "dl" ], [ "dam", "dm" ], [ "divide", "div", "dv", "dvd" ], [ "drive", "dr", "driv", "drv" ], [ "drives", "drs" ], [ "estate", "est" ], [ "estates", "ests" ], [ "expressway", "exp", "expy", "expr", "express", "expw" ], [ "extension", "ext", "extn", "extnsn" ], [ "extensions", "exts" ], [ "fall" ], [ "falls", "fls" ], [ "ferry", "fry", "frry" ], [ "field", "fld" ], [ "fields", "flds" ], [ "flat", "flt" ], [ "flats", "flts" ], [ "ford", "frd" ], [ "fords", "frds" ], [ "forest", "frst", "forests" ], [ "forge", "forg", "frg" ], [ "forges", "frgs" ], [ "fork", "frk" ], [ "forks", "frks" ], [ "fort", "ft", "frt" ], [ "freeway", "fwy", "freewy", "frway", "frwy" ], [ "garden", "gdn", "gardn", "grden", "grdn" ], [ "gardens", "gdns", "grdns" ], [ "gateway", "gtwy", "gatewy", "gatway", "gtway" ], [ "glen", "gln" ], [ "glens", "glns" ], [ "green", "grn" ], [ "greens", "grns" ], [ "grove", "grov", "grv" ], [ "groves", "grvs" ], [ "harbor", "harb", "hbr", "harbr", "hrbor" ], [ "harbors", "hbrs" ], [ "haven", "hvn" ], [ "heights", "ht", "hts" ], [ "highway", "hwy", "highwy", "hiway", "hiwy", "hway" ], [ "hill", "hl" ], [ "hills", "hls" ], [ "hollow", "hllw", "holw", "hollows", "holws" ], [ "inlet", "inlt" ], [ "island", "is", "islnd" ], [ "islands", "iss", "islnds" ], [ "isle", "isles" ], [ "junction", "jct", "jction", "jctn", "junctn", "juncton" ], [ "junctions", "jctns", "jcts" ], [ "key", "ky" ], [ "keys", "kys" ], [ "knoll", "knl", "knol" ], [ "knolls", "knls" ], [ "lake", "lk" ], [ "lakes", "lks" ], [ "land" ], [ "landing", "lndg", "lndng" ], [ "lane", "ln" ], [ "light", "lgt" ], [ "lights", "lgts" ], [ "loaf", "lf" ], [ "lock", "lck" ], [ "locks", "lcks" ], [ "lodge", "ldg", "ldge", "lodg" ], [ "loop", "loops" ], [ "mall" ], [ "manor", "mnr" ], [ "manors", "mnrs" ], [ "meadow", "mdw" ], [ "meadows", "mdw", "mdws", "medows" ], [ "mews" ], [ "mill", "ml" ], [ "mills", "mls" ], [ "mission", "missn", "msn", "mssn" ], [ "motorway", "mtwy" ], [ "mount", "mnt", "mt" ], [ "mountain", "mntain", "mtn", "mntn", "mountin", "mtin" ], [ "mountains", "mntns", "mtns" ], [ "neck", "nck" ], [ "orchard", "orch", "orchrd" ], [ "oval", "ovl" ], [ "overpass", "opas" ], [ "park", "prk" ], [ "parks", "park" ], [ "parkway", "pkwy", "parkwy", "pkway", "pky" ], [ "parkways", "pkwy", "pkwys" ], [ "pass" ], [ "passage", "psge" ], [ "path", "paths" ], [ "pike", "pikes" ], [ "pine", "pne" ], [ "pines", "pnes" ], [ "place", "pl" ], [ "plain", "pln" ], [ "plains", "plns" ], [ "plaza", "plz", "plza" ], [ "point", "pt" ], [ "points", "pts" ], [ "port", "prt" ], [ "ports", "prts" ], [ "prairie", "pr", "prr" ], [ "radial", "rad", "radl", "radiel" ], [ "ramp" ], [ "ranch", "rnch", "ranches", "rnchs" ], [ "rapid", "rpd" ], [ "rapids", "rpds" ], [ "rest", "rst" ], [ "ridge", "rdg", "rdge" ], [ "ridges", "rdgs" ], [ "river", "riv", "rvr", "rivr" ], [ "road", "rd" ], [ "roads", "rds" ], [ "route", "rte" ], [ "row" ], [ "rue" ], [ "run" ], [ "shoal", "shl" ], [ "shoals", "shls" ], [ "shore", "shoar", "shr" ], [ "shores", "shoars", "shrs" ], [ "skyway", "skwy" ], [ "spring", "spg", "spng", "sprng" ], [ "springs", "spgs", "spngs", "sprngs" ], [ "spur" ], [ "spurs", "spur" ], [ "square", "sq", "sqr", "sqre", "squ" ], [ "squares", "sqrs", "sqs" ], [ "station", "sta", "statn", "stn" ], [ "stravenue", "stra", "strav", "straven", "stravn", "strvn", "strvnue" ], [ "stream", "strm", "streme" ], [ "street", "st", "strt", "str" ], [ "streets", "sts" ], [ "summit", "smt", "sumit", "sumitt" ], [ "terrace", "ter", "terr" ], [ "throughway", "trwy" ], [ "trace", "trce", "traces" ], [ "track", "trak", "tracks", "trk", "trks" ], [ "trafficway", "trfy" ], [ "trail", "trl", "trails", "trls" ], [ "trailer", "trlr", "trlrs" ], [ "tunnel", "tunel", "tunl", "tunls", "tunnels", "tunnl" ], [ "turnpike", "trnpk", "tpke", "turnpk" ], [ "underpass", "upas" ], [ "union", "un" ], [ "unions", "uns" ], [ "valley", "vly", "vally", "vlly" ], [ "valleys", "vlys" ], [ "viaduct", "vdct", "via", "viadct" ], [ "view", "vw" ], [ "views", "vws" ], [ "village", "vill", "vlg", "villag", "villg", "villiage" ], [ "villages", "vlgs" ], [ "ville", "vl" ], [ "vista", "vis", "vist", "vst", "vsta" ], [ "walk" ], [ "walks", "walk" ], [ "wall" ], [ "way", "wy" ], [ "ways" ], [ "well", "wl" ], [ "wells", "wls" ] ]

21.762048

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1

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1

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1

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null

0

8

482b5b51d86f4d9258cbec2cc7552b05f86dab36

185,847

py

Python

smartrecruiters_python_client/apis/configuration_api.py

roksela/smartrecruiters-python-client

6d0849d173a3d6718b5f0769098f4c76857f637d

[ "MIT" ]

5

2018-03-27T08:20:13.000Z

2022-03-30T06:23:38.000Z

smartrecruiters_python_client/apis/configuration_api.py

roksela/smartrecruiters-python-client

6d0849d173a3d6718b5f0769098f4c76857f637d

[ "MIT" ]

null

smartrecruiters_python_client/apis/configuration_api.py

roksela/smartrecruiters-python-client

6d0849d173a3d6718b5f0769098f4c76857f637d

[ "MIT" ]

2

2018-12-05T04:48:37.000Z

2020-12-17T12:12:12.000Z

# coding: utf-8 """ Unofficial python library for the SmartRecruiters API The SmartRecruiters API provides a platform to integrate services or applications, build apps and create fully customizable career sites. It exposes SmartRecruiters functionality and allows to connect and build software enhancing it. OpenAPI spec version: 1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class ConfigurationApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def configuration_candidate_properties_all(self, **kwargs): """ Get a list of available candidate properties Get all candidate properties and their configuration for a company This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: CandidatePropertyDefinitionList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_all_with_http_info(**kwargs) else: (data) = self.configuration_candidate_properties_all_with_http_info(**kwargs) return data def configuration_candidate_properties_all_with_http_info(self, **kwargs): """ Get a list of available candidate properties Get all candidate properties and their configuration for a company This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: CandidatePropertyDefinitionList If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/candidate-properties'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyDefinitionList', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_candidate_properties_get(self, id, **kwargs): """ Get candidate property by id Get candidate property details and its configuration by id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_get(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :return: CandidatePropertyDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_get_with_http_info(id, **kwargs) else: (data) = self.configuration_candidate_properties_get_with_http_info(id, **kwargs) return data def configuration_candidate_properties_get_with_http_info(self, id, **kwargs): """ Get candidate property by id Get candidate property details and its configuration by id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_get_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :return: CandidatePropertyDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_candidate_properties_get`") collection_formats = {} resource_path = '/configuration/candidate-properties/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_candidate_properties_values_all(self, id, **kwargs): """ Get Candidate Property values Lists all available values for given candidate property id. This endpoint is available only for SINGLE_SELECT candidate property type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_all(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :return: CandidatePropertyValueList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_values_all_with_http_info(id, **kwargs) else: (data) = self.configuration_candidate_properties_values_all_with_http_info(id, **kwargs) return data def configuration_candidate_properties_values_all_with_http_info(self, id, **kwargs): """ Get Candidate Property values Lists all available values for given candidate property id. This endpoint is available only for SINGLE_SELECT candidate property type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_all_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :return: CandidatePropertyValueList If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_values_all" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_candidate_properties_values_all`") collection_formats = {} resource_path = '/configuration/candidate-properties/{id}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyValueList', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_candidate_properties_values_create(self, id, candidate_property_value, **kwargs): """ Create candidate property value Create SINGLE_SELECT candidate property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_create(id, candidate_property_value, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param CandidatePropertyValue candidate_property_value: Candidate property value. (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_values_create_with_http_info(id, candidate_property_value, **kwargs) else: (data) = self.configuration_candidate_properties_values_create_with_http_info(id, candidate_property_value, **kwargs) return data def configuration_candidate_properties_values_create_with_http_info(self, id, candidate_property_value, **kwargs): """ Create candidate property value Create SINGLE_SELECT candidate property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_create_with_http_info(id, candidate_property_value, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param CandidatePropertyValue candidate_property_value: Candidate property value. (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'candidate_property_value'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_values_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_candidate_properties_values_create`") # verify the required parameter 'candidate_property_value' is set if ('candidate_property_value' not in params) or (params['candidate_property_value'] is None): raise ValueError("Missing the required parameter `candidate_property_value` when calling `configuration_candidate_properties_values_create`") collection_formats = {} resource_path = '/configuration/candidate-properties/{id}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'candidate_property_value' in params: body_params = params['candidate_property_value'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyValue', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_candidate_properties_values_get(self, id, value_id, **kwargs): """ Get Candidate Property value by id Get Candidate Property value by its id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_get(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param str value_id: Identifier of candidate property value (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_values_get_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_candidate_properties_values_get_with_http_info(id, value_id, **kwargs) return data def configuration_candidate_properties_values_get_with_http_info(self, id, value_id, **kwargs): """ Get Candidate Property value by id Get Candidate Property value by its id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_get_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param str value_id: Identifier of candidate property value (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_values_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_candidate_properties_values_get`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_candidate_properties_values_get`") collection_formats = {} resource_path = '/configuration/candidate-properties/{id}/values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyValue', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_candidate_properties_values_update(self, id, value_id, candidate_property_value_label, **kwargs): """ Update candidate property value label Update candidate property value label This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_update(id, value_id, candidate_property_value_label, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param str value_id: Identifier of candidate property value (required) :param CandidatePropertyValueLabel candidate_property_value_label: Candidate property value label. (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_candidate_properties_values_update_with_http_info(id, value_id, candidate_property_value_label, **kwargs) else: (data) = self.configuration_candidate_properties_values_update_with_http_info(id, value_id, candidate_property_value_label, **kwargs) return data def configuration_candidate_properties_values_update_with_http_info(self, id, value_id, candidate_property_value_label, **kwargs): """ Update candidate property value label Update candidate property value label This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_candidate_properties_values_update_with_http_info(id, value_id, candidate_property_value_label, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of candidate property (required) :param str value_id: Identifier of candidate property value (required) :param CandidatePropertyValueLabel candidate_property_value_label: Candidate property value label. (required) :return: CandidatePropertyValue If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id', 'candidate_property_value_label'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_candidate_properties_values_update" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_candidate_properties_values_update`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_candidate_properties_values_update`") # verify the required parameter 'candidate_property_value_label' is set if ('candidate_property_value_label' not in params) or (params['candidate_property_value_label'] is None): raise ValueError("Missing the required parameter `candidate_property_value_label` when calling `configuration_candidate_properties_values_update`") collection_formats = {} resource_path = '/configuration/candidate-properties/{id}/values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'candidate_property_value_label' in params: body_params = params['candidate_property_value_label'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CandidatePropertyValue', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_company_my(self, **kwargs): """ Get company information Get all information about your company. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_company_my(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: CompanyConfiguration If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_company_my_with_http_info(**kwargs) else: (data) = self.configuration_company_my_with_http_info(**kwargs) return data def configuration_company_my_with_http_info(self, **kwargs): """ Get company information Get all information about your company. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_company_my_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: CompanyConfiguration If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_company_my" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/company'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='CompanyConfiguration', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_department_all(self, **kwargs): """ Get departments This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Departments If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_department_all_with_http_info(**kwargs) else: (data) = self.configuration_department_all_with_http_info(**kwargs) return data def configuration_department_all_with_http_info(self, **kwargs): """ Get departments This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Departments If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_department_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/departments'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Departments', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_department_create(self, department, **kwargs): """ Creates department This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_create(department, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param Department department: department to be created (required) :return: Department If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_department_create_with_http_info(department, **kwargs) else: (data) = self.configuration_department_create_with_http_info(department, **kwargs) return data def configuration_department_create_with_http_info(self, department, **kwargs): """ Creates department This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_create_with_http_info(department, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param Department department: department to be created (required) :return: Department If the method is called asynchronously, returns the request thread. """ all_params = ['department'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_department_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'department' is set if ('department' not in params) or (params['department'] is None): raise ValueError("Missing the required parameter `department` when calling `configuration_department_create`") collection_formats = {} resource_path = '/configuration/departments'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'department' in params: body_params = params['department'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Department', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_department_get(self, id, **kwargs): """ Get department This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_get(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a department (required) :return: Department If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_department_get_with_http_info(id, **kwargs) else: (data) = self.configuration_department_get_with_http_info(id, **kwargs) return data def configuration_department_get_with_http_info(self, id, **kwargs): """ Get department This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_department_get_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a department (required) :return: Department If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_department_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_department_get`") collection_formats = {} resource_path = '/configuration/departments/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Department', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_hiring_process_all(self, **kwargs): """ Get list of hiring process This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_hiring_process_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: HiringProcesses If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_hiring_process_all_with_http_info(**kwargs) else: (data) = self.configuration_hiring_process_all_with_http_info(**kwargs) return data def configuration_hiring_process_all_with_http_info(self, **kwargs): """ Get list of hiring process This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_hiring_process_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: HiringProcesses If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_hiring_process_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/hiring-processes'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HiringProcesses', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_hiring_process_get(self, id, **kwargs): """ Get hiring process This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_hiring_process_get(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a hiring process (required) :return: HiringProcess If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_hiring_process_get_with_http_info(id, **kwargs) else: (data) = self.configuration_hiring_process_get_with_http_info(id, **kwargs) return data def configuration_hiring_process_get_with_http_info(self, id, **kwargs): """ Get hiring process This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_hiring_process_get_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a hiring process (required) :return: HiringProcess If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_hiring_process_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_hiring_process_get`") collection_formats = {} resource_path = '/configuration/hiring-processes/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='HiringProcess', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_activate(self, id, **kwargs): """ Activate a job property Activates a job property with given id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_activate(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_activate_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_activate_with_http_info(id, **kwargs) return data def configuration_job_properties_activate_with_http_info(self, id, **kwargs): """ Activate a job property Activates a job property with given id. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_activate_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_activate" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_activate`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/activation'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_all(self, **kwargs): """ Get a list of available job properties Get a list of available job properties. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: JobPropertyDefinitionList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_all_with_http_info(**kwargs) else: (data) = self.configuration_job_properties_all_with_http_info(**kwargs) return data def configuration_job_properties_all_with_http_info(self, **kwargs): """ Get a list of available job properties Get a list of available job properties. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: JobPropertyDefinitionList If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/job-properties'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyDefinitionList', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_create(self, **kwargs): """ Create a job property Creates a job property This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_create(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param JobPropertyDefinition job_property_definition: job property to be created :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_create_with_http_info(**kwargs) else: (data) = self.configuration_job_properties_create_with_http_info(**kwargs) return data def configuration_job_properties_create_with_http_info(self, **kwargs): """ Create a job property Creates a job property This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_create_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param JobPropertyDefinition job_property_definition: job property to be created :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['job_property_definition'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_create" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/job-properties'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'job_property_definition' in params: body_params = params['job_property_definition'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_deactivate(self, id, **kwargs): """ Deactivate a job property Deactivates a job property. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_deactivate(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_deactivate_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_deactivate_with_http_info(id, **kwargs) return data def configuration_job_properties_deactivate_with_http_info(self, id, **kwargs): """ Deactivate a job property Deactivates a job property. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_deactivate_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_deactivate" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_deactivate`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/activation'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_all(self, id, **kwargs): """ Get job property's dependents Get list of job property's dependents This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_all(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: DependentJobProperties If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_all_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_dependents_all_with_http_info(id, **kwargs) return data def configuration_job_properties_dependents_all_with_http_info(self, id, **kwargs): """ Get job property's dependents Get list of job property's dependents This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_all_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: DependentJobProperties If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_all" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_all`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/dependents'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DependentJobProperties', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_create(self, id, dependent_job_properties_ids, **kwargs): """ Create job property dependents Create dependencies between job properties This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_create(id, dependent_job_properties_ids, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param DependentJobPropertiesIds dependent_job_properties_ids: Job properties' id (required) :return: DependentJobProperties If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_create_with_http_info(id, dependent_job_properties_ids, **kwargs) else: (data) = self.configuration_job_properties_dependents_create_with_http_info(id, dependent_job_properties_ids, **kwargs) return data def configuration_job_properties_dependents_create_with_http_info(self, id, dependent_job_properties_ids, **kwargs): """ Create job property dependents Create dependencies between job properties This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_create_with_http_info(id, dependent_job_properties_ids, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param DependentJobPropertiesIds dependent_job_properties_ids: Job properties' id (required) :return: DependentJobProperties If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'dependent_job_properties_ids'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_create`") # verify the required parameter 'dependent_job_properties_ids' is set if ('dependent_job_properties_ids' not in params) or (params['dependent_job_properties_ids'] is None): raise ValueError("Missing the required parameter `dependent_job_properties_ids` when calling `configuration_job_properties_dependents_create`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/dependents'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'dependent_job_properties_ids' in params: body_params = params['dependent_job_properties_ids'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DependentJobProperties', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_remove(self, id, dependent_id, **kwargs): """ Remove job property's dependent Remove dependency between job properties This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_remove(id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str dependent_id: Identifier of a job property's dependent (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_remove_with_http_info(id, dependent_id, **kwargs) else: (data) = self.configuration_job_properties_dependents_remove_with_http_info(id, dependent_id, **kwargs) return data def configuration_job_properties_dependents_remove_with_http_info(self, id, dependent_id, **kwargs): """ Remove job property's dependent Remove dependency between job properties This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_remove_with_http_info(id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str dependent_id: Identifier of a job property's dependent (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'dependent_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_remove" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_remove`") # verify the required parameter 'dependent_id' is set if ('dependent_id' not in params) or (params['dependent_id'] is None): raise ValueError("Missing the required parameter `dependent_id` when calling `configuration_job_properties_dependents_remove`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/dependents/{dependentId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'dependent_id' in params: path_params['dependentId'] = params['dependent_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_values_add(self, id, value_id, dependent_id, dependent_job_property_value_id, **kwargs): """ Add job property's dependent value Add job property's dependent value for specific job property's value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_add(id, value_id, dependent_id, dependent_job_property_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :param Identifiable dependent_job_property_value_id: Identifier of job property's dependent value (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_values_add_with_http_info(id, value_id, dependent_id, dependent_job_property_value_id, **kwargs) else: (data) = self.configuration_job_properties_dependents_values_add_with_http_info(id, value_id, dependent_id, dependent_job_property_value_id, **kwargs) return data def configuration_job_properties_dependents_values_add_with_http_info(self, id, value_id, dependent_id, dependent_job_property_value_id, **kwargs): """ Add job property's dependent value Add job property's dependent value for specific job property's value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_add_with_http_info(id, value_id, dependent_id, dependent_job_property_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :param Identifiable dependent_job_property_value_id: Identifier of job property's dependent value (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id', 'dependent_id', 'dependent_job_property_value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_values_add" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_values_add`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_dependents_values_add`") # verify the required parameter 'dependent_id' is set if ('dependent_id' not in params) or (params['dependent_id'] is None): raise ValueError("Missing the required parameter `dependent_id` when calling `configuration_job_properties_dependents_values_add`") # verify the required parameter 'dependent_job_property_value_id' is set if ('dependent_job_property_value_id' not in params) or (params['dependent_job_property_value_id'] is None): raise ValueError("Missing the required parameter `dependent_job_property_value_id` when calling `configuration_job_properties_dependents_values_add`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}/dependents/{dependentId}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] if 'dependent_id' in params: path_params['dependentId'] = params['dependent_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'dependent_job_property_value_id' in params: body_params = params['dependent_job_property_value_id'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_values_all(self, id, dependent_id, **kwargs): """ Get dependent job property's values Get dependent job property's values with corelation to the parent field. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_all(id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str dependent_id: Identifier of dependent job property (required) :return: DependentJobPropertyValuesRelations If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_values_all_with_http_info(id, dependent_id, **kwargs) else: (data) = self.configuration_job_properties_dependents_values_all_with_http_info(id, dependent_id, **kwargs) return data def configuration_job_properties_dependents_values_all_with_http_info(self, id, dependent_id, **kwargs): """ Get dependent job property's values Get dependent job property's values with corelation to the parent field. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_all_with_http_info(id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str dependent_id: Identifier of dependent job property (required) :return: DependentJobPropertyValuesRelations If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'dependent_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_values_all" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_values_all`") # verify the required parameter 'dependent_id' is set if ('dependent_id' not in params) or (params['dependent_id'] is None): raise ValueError("Missing the required parameter `dependent_id` when calling `configuration_job_properties_dependents_values_all`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/dependents/{dependentId}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'dependent_id' in params: path_params['dependentId'] = params['dependent_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DependentJobPropertyValuesRelations', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_values_get(self, id, value_id, dependent_id, **kwargs): """ Get job property's dependent values Get list of job property's dependent values for specific job property's value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_get(id, value_id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :return: DependentJobPropertyValues If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_values_get_with_http_info(id, value_id, dependent_id, **kwargs) else: (data) = self.configuration_job_properties_dependents_values_get_with_http_info(id, value_id, dependent_id, **kwargs) return data def configuration_job_properties_dependents_values_get_with_http_info(self, id, value_id, dependent_id, **kwargs): """ Get job property's dependent values Get list of job property's dependent values for specific job property's value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_get_with_http_info(id, value_id, dependent_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :return: DependentJobPropertyValues If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id', 'dependent_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_values_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_values_get`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_dependents_values_get`") # verify the required parameter 'dependent_id' is set if ('dependent_id' not in params) or (params['dependent_id'] is None): raise ValueError("Missing the required parameter `dependent_id` when calling `configuration_job_properties_dependents_values_get`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}/dependents/{dependentId}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] if 'dependent_id' in params: path_params['dependentId'] = params['dependent_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DependentJobPropertyValues', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_dependents_values_remove(self, id, value_id, dependent_id, dependent_value_id, **kwargs): """ Remove job property's dependent values relationship Remove relationship between dependent job properties values This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_remove(id, value_id, dependent_id, dependent_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :param str dependent_value_id: Identifier of job property's dependent value (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_dependents_values_remove_with_http_info(id, value_id, dependent_id, dependent_value_id, **kwargs) else: (data) = self.configuration_job_properties_dependents_values_remove_with_http_info(id, value_id, dependent_id, dependent_value_id, **kwargs) return data def configuration_job_properties_dependents_values_remove_with_http_info(self, id, value_id, dependent_id, dependent_value_id, **kwargs): """ Remove job property's dependent values relationship Remove relationship between dependent job properties values This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_dependents_values_remove_with_http_info(id, value_id, dependent_id, dependent_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value (required) :param str dependent_id: Identifier of job property's dependent (required) :param str dependent_value_id: Identifier of job property's dependent value (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id', 'dependent_id', 'dependent_value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_dependents_values_remove" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_dependents_values_remove`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_dependents_values_remove`") # verify the required parameter 'dependent_id' is set if ('dependent_id' not in params) or (params['dependent_id'] is None): raise ValueError("Missing the required parameter `dependent_id` when calling `configuration_job_properties_dependents_values_remove`") # verify the required parameter 'dependent_value_id' is set if ('dependent_value_id' not in params) or (params['dependent_value_id'] is None): raise ValueError("Missing the required parameter `dependent_value_id` when calling `configuration_job_properties_dependents_values_remove`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}/dependents/{dependentId}/values/{dependentValueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] if 'dependent_id' in params: path_params['dependentId'] = params['dependent_id'] if 'dependent_value_id' in params: path_params['dependentValueId'] = params['dependent_value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_get(self, id, **kwargs): """ Get job property by id Get job property by id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_get(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_get_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_get_with_http_info(id, **kwargs) return data def configuration_job_properties_get_with_http_info(self, id, **kwargs): """ Get job property by id Get job property by id This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_get_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_get`") collection_formats = {} resource_path = '/configuration/job-properties/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_update(self, id, **kwargs): """ Update a job property Updates a job property. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_update(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param JSONPatch json_patch: patch request :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_update_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_update_with_http_info(id, **kwargs) return data def configuration_job_properties_update_with_http_info(self, id, **kwargs): """ Update a job property Updates a job property. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_update_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param JSONPatch json_patch: patch request :return: JobPropertyDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'json_patch'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_update" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_update`") collection_formats = {} resource_path = '/configuration/job-properties/{id}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'json_patch' in params: body_params = params['json_patch'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json-patch+json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_archive(self, id, value_id, **kwargs): """ Archive a job property value Archive a job property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_archive(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be archived (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_archive_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_job_properties_values_archive_with_http_info(id, value_id, **kwargs) return data def configuration_job_properties_values_archive_with_http_info(self, id, value_id, **kwargs): """ Archive a job property value Archive a job property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_archive_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be archived (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_archive" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_archive`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_values_archive`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/archive-values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_create(self, id, **kwargs): """ Create a job property value Creates a job property value. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_create(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param JobPropertyValueDefinition job_property_value_definition: job property object to be created :return: JobPropertyValueDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_create_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_values_create_with_http_info(id, **kwargs) return data def configuration_job_properties_values_create_with_http_info(self, id, **kwargs): """ Create a job property value Creates a job property value. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_create_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param JobPropertyValueDefinition job_property_value_definition: job property object to be created :return: JobPropertyValueDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'job_property_value_definition'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_create`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'job_property_value_definition' in params: body_params = params['job_property_value_definition'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyValueDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_deprecated_archive(self, id, value_id, **kwargs): """ Archive a job property value Archive a job property value. Please use `PUT /configuration/job-properties/{id}/archive-values/{valueId}` instead. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_deprecated_archive(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be archived (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_deprecated_archive_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_job_properties_values_deprecated_archive_with_http_info(id, value_id, **kwargs) return data def configuration_job_properties_values_deprecated_archive_with_http_info(self, id, value_id, **kwargs): """ Archive a job property value Archive a job property value. Please use `PUT /configuration/job-properties/{id}/archive-values/{valueId}` instead. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_deprecated_archive_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be archived (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_deprecated_archive" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_deprecated_archive`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_values_deprecated_archive`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_deprecated_unarchive(self, id, value_id, **kwargs): """ Unarchive a job property value Unarchive a job property value. `DELETE /configuration/job-properties/{id}/archive-values/{valueId}` instead. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_deprecated_unarchive(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be unarchived (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_deprecated_unarchive_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_job_properties_values_deprecated_unarchive_with_http_info(id, value_id, **kwargs) return data def configuration_job_properties_values_deprecated_unarchive_with_http_info(self, id, value_id, **kwargs): """ Unarchive a job property value Unarchive a job property value. `DELETE /configuration/job-properties/{id}/archive-values/{valueId}` instead. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_deprecated_unarchive_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be unarchived (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_deprecated_unarchive" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_deprecated_unarchive`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_values_deprecated_unarchive`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_get(self, id, **kwargs): """ Get available job property values Get available job property values. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_get(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: JobPropertyValueDefinitionList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_get_with_http_info(id, **kwargs) else: (data) = self.configuration_job_properties_values_get_with_http_info(id, **kwargs) return data def configuration_job_properties_values_get_with_http_info(self, id, **kwargs): """ Get available job property values Get available job property values. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_get_with_http_info(id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :return: JobPropertyValueDefinitionList If the method is called asynchronously, returns the request thread. """ all_params = ['id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_get`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyValueDefinitionList', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_unarchive(self, id, value_id, **kwargs): """ Unarchive a job property value Unarchive a job property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_unarchive(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be unarchived (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_unarchive_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_job_properties_values_unarchive_with_http_info(id, value_id, **kwargs) return data def configuration_job_properties_values_unarchive_with_http_info(self, id, value_id, **kwargs): """ Unarchive a job property value Unarchive a job property value This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_unarchive_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be unarchived (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_unarchive" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_unarchive`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_values_unarchive`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/archive-values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_job_properties_values_update(self, id, value_id, **kwargs): """ Update a job property value Update a job property value. Returns an updated job property value object. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_update(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be updated (required) :param JSONPatch json_patch: patch request :return: JobPropertyValueDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_job_properties_values_update_with_http_info(id, value_id, **kwargs) else: (data) = self.configuration_job_properties_values_update_with_http_info(id, value_id, **kwargs) return data def configuration_job_properties_values_update_with_http_info(self, id, value_id, **kwargs): """ Update a job property value Update a job property value. Returns an updated job property value object. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_job_properties_values_update_with_http_info(id, value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str id: Identifier of a job property (required) :param str value_id: Identifier of a job property value to be updated (required) :param JSONPatch json_patch: patch request :return: JobPropertyValueDefinition If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'value_id', 'json_patch'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_job_properties_values_update" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `configuration_job_properties_values_update`") # verify the required parameter 'value_id' is set if ('value_id' not in params) or (params['value_id'] is None): raise ValueError("Missing the required parameter `value_id` when calling `configuration_job_properties_values_update`") collection_formats = {} resource_path = '/configuration/job-properties/{id}/values/{valueId}'.replace('{format}', 'json') path_params = {} if 'id' in params: path_params['id'] = params['id'] if 'value_id' in params: path_params['valueId'] = params['value_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'json_patch' in params: body_params = params['json_patch'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json-patch+json']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='JobPropertyValueDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_offer_properties_all(self, **kwargs): """ Get a list of available offer properties Get a list of available offer properties. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_offer_properties_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: OfferPropertiesDefinition If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_offer_properties_all_with_http_info(**kwargs) else: (data) = self.configuration_offer_properties_all_with_http_info(**kwargs) return data def configuration_offer_properties_all_with_http_info(self, **kwargs): """ Get a list of available offer properties Get a list of available offer properties. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_offer_properties_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: OfferPropertiesDefinition If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_offer_properties_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/offer-properties'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='OfferPropertiesDefinition', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_reasons_rejection_all(self, **kwargs): """ Get rejection reasons Get rejection reasons This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_reasons_rejection_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Properties If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_reasons_rejection_all_with_http_info(**kwargs) else: (data) = self.configuration_reasons_rejection_all_with_http_info(**kwargs) return data def configuration_reasons_rejection_all_with_http_info(self, **kwargs): """ Get rejection reasons Get rejection reasons This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_reasons_rejection_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Properties If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_reasons_rejection_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/rejection-reasons'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Properties', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_reasons_withdrawal_all(self, **kwargs): """ Get withdrawal reasons Get withdrawal reasons This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_reasons_withdrawal_all(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Properties If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_reasons_withdrawal_all_with_http_info(**kwargs) else: (data) = self.configuration_reasons_withdrawal_all_with_http_info(**kwargs) return data def configuration_reasons_withdrawal_all_with_http_info(self, **kwargs): """ Get withdrawal reasons Get withdrawal reasons This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_reasons_withdrawal_all_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Properties If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_reasons_withdrawal_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/withdrawal-reasons'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Properties', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_source_types(self, **kwargs): """ List candidate source types with subtypes Get a list of all available candidate source type with subtypes This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_types(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: SourceTypes If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_source_types_with_http_info(**kwargs) else: (data) = self.configuration_source_types_with_http_info(**kwargs) return data def configuration_source_types_with_http_info(self, **kwargs): """ List candidate source types with subtypes Get a list of all available candidate source type with subtypes This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_types_with_http_info(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: SourceTypes If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_source_types" % key ) params[key] = val del params['kwargs'] collection_formats = {} resource_path = '/configuration/sources'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='SourceTypes', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_source_values_all(self, source_type, **kwargs): """ List candidate sources Get a list of all available candidate sources by type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_values_all(source_type, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str source_type: Source type from /configuration/sources (required) :param str source_sub_type: Source SubType :param int limit: number of elements to return. max value is 100 :param int offset: number of elements to skip while processing result :return: Sources If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_source_values_all_with_http_info(source_type, **kwargs) else: (data) = self.configuration_source_values_all_with_http_info(source_type, **kwargs) return data def configuration_source_values_all_with_http_info(self, source_type, **kwargs): """ List candidate sources Get a list of all available candidate sources by type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_values_all_with_http_info(source_type, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str source_type: Source type from /configuration/sources (required) :param str source_sub_type: Source SubType :param int limit: number of elements to return. max value is 100 :param int offset: number of elements to skip while processing result :return: Sources If the method is called asynchronously, returns the request thread. """ all_params = ['source_type', 'source_sub_type', 'limit', 'offset'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_source_values_all" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'source_type' is set if ('source_type' not in params) or (params['source_type'] is None): raise ValueError("Missing the required parameter `source_type` when calling `configuration_source_values_all`") if 'limit' in params and params['limit'] > 100: raise ValueError("Invalid value for parameter `limit` when calling `configuration_source_values_all`, must be a value less than or equal to `100`") if 'limit' in params and params['limit'] < 1: raise ValueError("Invalid value for parameter `limit` when calling `configuration_source_values_all`, must be a value greater than or equal to `1`") if 'offset' in params and params['offset'] < 0: raise ValueError("Invalid value for parameter `offset` when calling `configuration_source_values_all`, must be a value greater than or equal to `0`") collection_formats = {} resource_path = '/configuration/sources/{sourceType}/values'.replace('{format}', 'json') path_params = {} if 'source_type' in params: path_params['sourceType'] = params['source_type'] query_params = {} if 'source_sub_type' in params: query_params['sourceSubType'] = params['source_sub_type'] if 'limit' in params: query_params['limit'] = params['limit'] if 'offset' in params: query_params['offset'] = params['offset'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Sources', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def configuration_source_values_single(self, source_type, source_value_id, **kwargs): """ Get a candidate source Get a single candidate sources for a given type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_values_single(source_type, source_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str source_type: Source type from /configuration/sources (required) :param str source_value_id: Source id (required) :param str source_sub_type: Source SubType from /configuration/sources :return: Source If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.configuration_source_values_single_with_http_info(source_type, source_value_id, **kwargs) else: (data) = self.configuration_source_values_single_with_http_info(source_type, source_value_id, **kwargs) return data def configuration_source_values_single_with_http_info(self, source_type, source_value_id, **kwargs): """ Get a candidate source Get a single candidate sources for a given type. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.configuration_source_values_single_with_http_info(source_type, source_value_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str source_type: Source type from /configuration/sources (required) :param str source_value_id: Source id (required) :param str source_sub_type: Source SubType from /configuration/sources :return: Source If the method is called asynchronously, returns the request thread. """ all_params = ['source_type', 'source_value_id', 'source_sub_type'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method configuration_source_values_single" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'source_type' is set if ('source_type' not in params) or (params['source_type'] is None): raise ValueError("Missing the required parameter `source_type` when calling `configuration_source_values_single`") # verify the required parameter 'source_value_id' is set if ('source_value_id' not in params) or (params['source_value_id'] is None): raise ValueError("Missing the required parameter `source_value_id` when calling `configuration_source_values_single`") collection_formats = {} resource_path = '/configuration/sources/{sourceType}/values/{sourceValueId}'.replace('{format}', 'json') path_params = {} if 'source_type' in params: path_params['sourceType'] = params['source_type'] if 'source_value_id' in params: path_params['sourceValueId'] = params['source_value_id'] query_params = {} if 'source_sub_type' in params: query_params['sourceSubType'] = params['source_sub_type'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json; charset=utf-8']) # Authentication setting auth_settings = ['key'] return self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Source', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

45.461595

237

0.590044

18,743

185,847

5.591634

0.015099

0.058013

0.04912

0.026106

0.984543

0.98148

0.975936

0.966385

0.956004

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0.000469

0.333931

185,847

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45.472718

0.846179

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0

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0.037782

false

0

0.003435

0

0.097645

0

null

0

1

0

1

0

null

0

7

482bb5fb145e90ab82f2f0d0b2c9351a436b85f9

509

py

Python

holobot/extensions/moderation/managers/ipermission_manager.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

1

2021-05-24T00:17:46.000Z

holobot/extensions/moderation/managers/ipermission_manager.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

41

2021-03-24T22:50:09.000Z

2021-12-17T12:15:13.000Z

holobot/extensions/moderation/managers/ipermission_manager.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

null

from ..enums import ModeratorPermission class IPermissionManager: async def add_permissions(self, server_id: str, user_id: str, permissions: ModeratorPermission) -> None: raise NotImplementedError async def remove_permissions(self, server_id: str, user_id: str, permissions: ModeratorPermission) -> None: raise NotImplementedError async def has_permissions(self, server_id: str, user_id: str, permissions: ModeratorPermission) -> bool: raise NotImplementedError

42.416667

111

0.748527

54

509

6.888889

0.388889

0.080645

0.169355

0.185484

0.717742

0

0.180747

509

11

112

46.272727

0.892086

0

0.375

0

1

0

true

0

0.125

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0.25

0

null

0

1

0

1

0

null

0

1

0

7

482d5e841578f224f7ffca17d87d07c108f64015

10,446

py

Python

catboost/spark/catboost4j-spark/core/src/test/generate_canonical_results/feature_importance_test.py

jochenater/catboost

de2786fbc633b0d6ea6a23b3862496c6151b95c2

[ "Apache-2.0" ]

6,989

2017-07-18T06:23:18.000Z

2022-03-31T15:58:36.000Z

catboost/spark/catboost4j-spark/core/src/test/generate_canonical_results/feature_importance_test.py

jochenater/catboost

de2786fbc633b0d6ea6a23b3862496c6151b95c2

[ "Apache-2.0" ]

1,978

2017-07-18T09:17:58.000Z

2022-03-31T14:28:43.000Z

catboost/spark/catboost4j-spark/core/src/test/generate_canonical_results/feature_importance_test.py

jochenater/catboost

de2786fbc633b0d6ea6a23b3862496c6151b95c2

[ "Apache-2.0" ]

1,228

2017-07-18T09:03:13.000Z

2022-03-29T05:57:40.000Z

import json import os import catboost as cb import utils from config import CATBOOST_TEST_DATA_DIR, OUTPUT_DIR def prediction_values_change(): dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'higgs') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train.cd") model = utils.run_dist_train( ['--iterations', '20', '--loss-function', 'RMSE', '--learn-set', learn_set_path, '--cd', cd_path ], model_class=cb.CatBoostRegressor ) result = {} for calc_type in ['Regular', 'Approximate', 'Exact']: result['calc_type_' + calc_type] = model.get_feature_importance( type=cb.EFstrType.PredictionValuesChange, shap_calc_type=calc_type ).tolist() prettified_result = model.get_feature_importance( type=cb.EFstrType.PredictionValuesChange, prettified=True, shap_calc_type=calc_type ) result['calc_type_' + calc_type + '_prettified'] = [ { "featureName": prettified_result['Feature Id'][i], "importance": prettified_result['Importances'][i] } for i in range(len(prettified_result.index)) ] json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_prediction_values_change.json'), 'w'), allow_nan=True, indent=2 ) def loss_function_change(): dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'querywise') learn_set_path = os.path.join(dataset_dir, "train") cd_path = os.path.join(dataset_dir, "train.cd") model = utils.run_dist_train( ['--iterations', '20', '--loss-function', 'QueryRMSE', '--learn-set', learn_set_path, '--cd', cd_path ], model_class=cb.CatBoostRegressor ) train_pool = cb.Pool( learn_set_path, column_description=cd_path ) result = {} for calc_type in ['Regular', 'Approximate', 'Exact']: result['calc_type_' + calc_type] = model.get_feature_importance( type=cb.EFstrType.LossFunctionChange, data=train_pool, shap_calc_type=calc_type ).tolist() prettified_result = model.get_feature_importance( type=cb.EFstrType.LossFunctionChange, data=train_pool, prettified=True, shap_calc_type=calc_type ) result['calc_type_' + calc_type + '_prettified'] = [ { "featureName": prettified_result['Feature Id'][i], "importance": prettified_result['Importances'][i] } for i in range(len(prettified_result.index)) ] json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_loss_function_change.json'), 'w'), allow_nan=True, indent=2 ) def interaction(): dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'querywise') learn_set_path = os.path.join(dataset_dir, "train") cd_path = os.path.join(dataset_dir, "train.cd") model = utils.run_dist_train( ['--iterations', '20', '--loss-function', 'QueryRMSE', '--learn-set', learn_set_path, '--cd', cd_path ], model_class=cb.CatBoostRegressor ) result = [] for firstFeatureIndex, secondFeatureIndex, score in model.get_feature_importance(type=cb.EFstrType.Interaction): result.append( { "firstFeatureIndex": int(firstFeatureIndex), "secondFeatureIndex": int(secondFeatureIndex), "score": score } ) json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_interaction.json'), 'w'), allow_nan=True, indent=2 ) def shap_values(): result = {} for problem_type in ['Regression', 'BinClass', 'MultiClass']: if problem_type == 'Regression': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'querywise') learn_set_path = os.path.join(dataset_dir, "train") cd_path = os.path.join(dataset_dir, "train.cd") loss_function = 'QueryRMSE' additional_train_params = [] model_class = cb.CatBoostRegressor elif problem_type == 'BinClass': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'higgs') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train.cd") loss_function = 'Logloss' additional_train_params = [] model_class = cb.CatBoostClassifier elif problem_type == 'MultiClass': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'cloudness_small') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train_float.cd") loss_function = 'MultiClass' additional_train_params = [] model_class = cb.CatBoostClassifier model = utils.run_dist_train( ['--iterations', '20', '--loss-function', loss_function, '--learn-set', learn_set_path, '--cd', cd_path ] + additional_train_params, model_class=model_class ) model.save_model(os.path.join(OUTPUT_DIR, "feature_importance_shap_values.problem_type=" + problem_type + ".cbm")) train_pool = cb.Pool( learn_set_path, column_description=cd_path ) for shap_mode in ['Auto', 'UsePreCalc', 'NoPreCalc']: for shap_calc_type in ['Regular', 'Approximate', 'Exact']: result_name = ( 'problem_type=' + problem_type + ',shap_mode=' + shap_mode + ',shap_calc_type=' + shap_calc_type ) result[result_name] = model.get_feature_importance( type=cb.EFstrType.ShapValues, data=train_pool, shap_mode=shap_mode, shap_calc_type=shap_calc_type ).tolist() json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_shap_values.json'), 'w'), allow_nan=True, indent=2 ) def prediction_diff(): dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'higgs') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train.cd") model = utils.run_dist_train( ['--iterations', '20', '--loss-function', 'RMSE', '--learn-set', learn_set_path, '--cd', cd_path ], model_class=cb.CatBoostRegressor ) train_pool = cb.Pool( learn_set_path, column_description=cd_path ) result = {} result['simple'] = model.get_feature_importance( type=cb.EFstrType.PredictionDiff, data=train_pool.get_features()[:2] ).tolist() prettified_result = model.get_feature_importance( type=cb.EFstrType.PredictionDiff, data=train_pool.get_features()[:2], prettified=True ) result['prettified'] = [ { "featureName": prettified_result['Feature Id'][i], "importance": prettified_result['Importances'][i] } for i in range(len(prettified_result.index)) ] json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_prediction_diff.json'), 'w'), allow_nan=True, indent=2 ) def shap_interaction_values(): result = {} for problem_type in ['Regression', 'BinClass', 'MultiClass']: if problem_type == 'Regression': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'higgs') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train.cd") loss_function = 'RMSE' additional_train_params = [] model_class = cb.CatBoostRegressor elif problem_type == 'BinClass': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'higgs') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train.cd") loss_function = 'Logloss' additional_train_params = [] model_class = cb.CatBoostClassifier elif problem_type == 'MultiClass': dataset_dir = os.path.join(CATBOOST_TEST_DATA_DIR, 'cloudness_small') learn_set_path = os.path.join(dataset_dir, "train_small") cd_path = os.path.join(dataset_dir, "train_float.cd") loss_function = 'MultiClass' additional_train_params = [] model_class = cb.CatBoostClassifier model = utils.run_dist_train( ['--iterations', '20', '--loss-function', loss_function, '--learn-set', learn_set_path, '--cd', cd_path ] + additional_train_params, model_class=model_class ) model.save_model(os.path.join(OUTPUT_DIR, "feature_importance_shap_interaction_values.problem_type=" + problem_type + ".cbm")) pool_for_feature_importance = cb.Pool( learn_set_path, column_description=cd_path ).slice([0,1,2,3,4]) for shap_mode in ['Auto', 'UsePreCalc', 'NoPreCalc']: for shap_calc_type in ['Regular']: result_name = ( 'problem_type=' + problem_type + ',shap_mode=' + shap_mode + ',shap_calc_type=' + shap_calc_type ) result[result_name] = model.get_feature_importance( type=cb.EFstrType.ShapInteractionValues, data=pool_for_feature_importance, shap_mode=shap_mode, shap_calc_type=shap_calc_type ).tolist() json.dump( result, fp=open(os.path.join(OUTPUT_DIR, 'feature_importance_shap_interaction_values.json'), 'w'), allow_nan=True, indent=2 ) def main(): prediction_values_change() loss_function_change() interaction() shap_values() prediction_diff() shap_interaction_values()

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0

7

4841ff660e8ab615dd34c486ce1e924b713d962d

16,746

py

Python

src/utils/utils_experiment.py

cchallu/dghl

1cafd3e1390f1069fb8ce3aab2e3d3bc8271a079

[ "Apache-2.0" ]

2

2022-02-17T03:06:36.000Z

2022-03-30T16:42:26.000Z

src/utils/utils_experiment.py

cchallu/dghl

1cafd3e1390f1069fb8ce3aab2e3d3bc8271a079

[ "Apache-2.0" ]

null

src/utils/utils_experiment.py

cchallu/dghl

1cafd3e1390f1069fb8ce3aab2e3d3bc8271a079

[ "Apache-2.0" ]

1

2022-03-07T08:16:43.000Z

""" Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import os import pickle import numpy as np import pandas as pd import torch from models.DGHL import DGHL from models.DGHL_encoder import DGHL_encoder from utils.utils import de_unfold from utils.utils_visualization import plot_reconstruction_ts, plot_anomaly_scores def train_DGHL(mc, train_data, test_data, test_labels, train_mask, test_mask, entities, make_plots, root_dir): """ train_data: List of tensors with training data, each shape (n_time, 1, n_features) test_data: List of tensor with training data, each shape (n_time, 1, n_features) test_labels: List of arrays with test lables, each (ntime) train_mask: List of tensors with training mask, each shape (n_time, 1, n_features) test_mask: List of tensors with test mask, each shape (n_time, 1, n_features) entities: List of names with entities """ print(pd.Series(mc)) # --------------------------------------- Random seed -------------------------------------- np.random.seed(mc['random_seed']) # --------------------------------------- Parse paramaters -------------------------------------- window_size = mc['window_size'] window_hierarchy = mc['window_hierarchy'] window_step = mc['window_step'] n_features = mc['n_features'] total_window_size = window_size*window_hierarchy # --------------------------------------- Data Processing -------------------------------------- n_entities = len(entities) train_data_list = [] test_data_list = [] train_mask_list = [] test_mask_list = [] # Loop to pre-process each entity for entity in range(n_entities): #print(10*'-','entity ', entity, ': ', entities[entity], 10*'-') train_data_entity = train_data[entity].copy() test_data_entity = test_data[entity].copy() train_mask_entity = train_mask[entity].copy() test_mask_entity = test_mask[entity].copy() assert train_data_entity.shape == train_mask_entity.shape, 'Train data and Train mask should have equal dimensions' assert test_data_entity.shape == test_mask_entity.shape, 'Test data and Test mask should have equal dimensions' assert train_data_entity.shape[2] == mc['n_features'], 'Train data should match n_features' assert test_data_entity.shape[2] == mc['n_features'], 'Test data should match n_features' # --------------------------------------- Data Processing --------------------------------------- # Complete first window for test, padding from training data padding = total_window_size - (len(test_data_entity) - total_window_size*(len(test_data_entity)//total_window_size)) test_data_entity = np.vstack([train_data_entity[-padding:], test_data_entity]) test_mask_entity = np.vstack([train_mask_entity[-padding:], test_mask_entity]) # Create rolling windows train_data_entity = torch.Tensor(train_data_entity).float() train_data_entity = train_data_entity.permute(0,2,1) train_data_entity = train_data_entity.unfold(dimension=0, size=total_window_size, step=window_step) test_data_entity = torch.Tensor(test_data_entity).float() test_data_entity = test_data_entity.permute(0,2,1) test_data_entity = test_data_entity.unfold(dimension=0, size=total_window_size, step=window_step) train_mask_entity = torch.Tensor(train_mask_entity).float() train_mask_entity = train_mask_entity.permute(0,2,1) train_mask_entity = train_mask_entity.unfold(dimension=0, size=total_window_size, step=window_step) test_mask_entity = torch.Tensor(test_mask_entity).float() test_mask_entity = test_mask_entity.permute(0,2,1) test_mask_entity = test_mask_entity.unfold(dimension=0, size=total_window_size, step=window_step) train_data_list.append(train_data_entity) test_data_list.append(test_data_entity) train_mask_list.append(train_mask_entity) test_mask_list.append(test_mask_entity) # Append all windows for complete windows data train_windows_data = torch.vstack(train_data_list) train_windows_mask = torch.vstack(train_mask_list) # -------------------------------------------- Instantiate and train Model -------------------------------------------- print('Training model...') model = DGHL(window_size=window_size, window_step=mc['window_step'], window_hierarchy=window_hierarchy, hidden_multiplier=mc['hidden_multiplier'], max_filters=mc['max_filters'], kernel_multiplier=mc['kernel_multiplier'], n_channels=n_features, z_size=mc['z_size'], z_size_up=mc['z_size_up'], z_iters=mc['z_iters'], z_sigma=mc['z_sigma'], z_step_size=mc['z_step_size'], z_with_noise=mc['z_with_noise'], z_persistent=mc['z_persistent'], batch_size=mc['batch_size'], learning_rate=mc['learning_rate'], noise_std=mc['noise_std'], normalize_windows=mc['normalize_windows'], random_seed=mc['random_seed'], device=mc['device']) model.fit(X=train_windows_data, mask=train_windows_mask, n_iterations=mc['n_iterations']) # -------------------------------------------- Inference on each entity -------------------------------------------- for entity in range(n_entities): rootdir_entity = f'{root_dir}/{entities[entity]}' os.makedirs(name=rootdir_entity, exist_ok=True) # Plots of reconstruction in train print('Reconstructing train...') x_train_true, x_train_hat, _, mask_windows = model.predict(X=train_data_list[entity], mask=train_mask_list[entity], z_iters=mc['z_iters_inference']) x_train_true, _ = de_unfold(x_windows=x_train_true, mask_windows=mask_windows, window_step=window_step) x_train_hat, _ = de_unfold(x_windows=x_train_hat, mask_windows=mask_windows, window_step=window_step) x_train_true = np.swapaxes(x_train_true,0,1) x_train_hat = np.swapaxes(x_train_hat,0,1) if make_plots: filename = f'{rootdir_entity}/reconstruction_train.png' plot_reconstruction_ts(x=x_train_true, x_hat=x_train_hat, n_features=n_features, filename=filename) # --------------------------------------- Inference on test and anomaly scores --------------------------------------- print('Computing scores on test...') score_windows, ts_score, x_windows, x_hat_windows, _, mask_windows = model.anomaly_score(X=test_data_list[entity], mask=test_mask_list[entity], z_iters=mc['z_iters_inference']) # Post-processing # Fold windows score_windows = score_windows[:,None,None,:] score_mask = np.ones(score_windows.shape) score, _ = de_unfold(x_windows=score_windows, mask_windows=score_mask, window_step=window_step) x_test_true, _ = de_unfold(x_windows=x_windows, mask_windows=mask_windows, window_step=window_step) x_test_hat, _ = de_unfold(x_windows=x_hat_windows, mask_windows=mask_windows, window_step=window_step) x_test_true = np.swapaxes(x_test_true,0,1) x_test_hat = np.swapaxes(x_test_hat,0,1) score = score.flatten() score = score[-len(test_labels[entity]):] if make_plots: filename = f'{rootdir_entity}/reconstruction_test.png' plot_reconstruction_ts(x=x_test_true, x_hat=x_test_hat, n_features=n_features, filename=filename) # Plot scores if make_plots: filename = f'{rootdir_entity}/anomaly_scores.png' plot_anomaly_scores(score=score, labels=test_labels[entity], filename=filename) results = {'score': score, 'ts_score':ts_score, 'x_test_true':x_test_true, 'x_test_hat':x_test_hat, 'labels':test_labels, 'x_train_true':x_train_true, 'x_train_hat':x_train_hat, 'train_mask': train_mask, 'mc':mc} with open(f'{rootdir_entity}/results.p','wb') as f: pickle.dump(results, f) def train_DGHL_encoder(mc, train_data, test_data, test_labels, train_mask, test_mask, entities, make_plots, root_dir): """ train_data: List of tensors with training data, each shape (n_time, 1, n_features) test_data: List of tensor with training data, each shape (n_time, 1, n_features) test_labels: List of arrays with test lables, each (ntime) train_mask: List of tensors with training mask, each shape (n_time, 1, n_features) test_mask: List of tensors with test mask, each shape (n_time, 1, n_features) entities: List of names with entities """ print(pd.Series(mc)) # --------------------------------------- Random seed -------------------------------------- np.random.seed(mc['random_seed']) # --------------------------------------- Parse paramaters -------------------------------------- window_size = mc['window_size'] window_hierarchy = mc['window_hierarchy'] window_step = mc['window_step'] n_features = mc['n_features'] total_window_size = window_size*window_hierarchy # --------------------------------------- Data Processing -------------------------------------- n_entities = len(entities) train_data_list = [] test_data_list = [] train_mask_list = [] test_mask_list = [] # Loop to pre-process each entity for entity in range(n_entities): #print(10*'-','entity ', entity, ': ', entities[entity], 10*'-') train_data_entity = train_data[entity].copy() test_data_entity = test_data[entity].copy() train_mask_entity = train_mask[entity].copy() test_mask_entity = test_mask[entity].copy() assert train_data_entity.shape == train_mask_entity.shape, 'Train data and Train mask should have equal dimensions' assert test_data_entity.shape == test_mask_entity.shape, 'Test data and Test mask should have equal dimensions' assert train_data_entity.shape[2] == mc['n_features'], 'Train data should match n_features' assert test_data_entity.shape[2] == mc['n_features'], 'Test data should match n_features' # --------------------------------------- Data Processing --------------------------------------- # Complete first window for test, padding from training data padding = total_window_size - (len(test_data_entity) - total_window_size*(len(test_data_entity)//total_window_size)) test_data_entity = np.vstack([train_data_entity[-padding:], test_data_entity]) test_mask_entity = np.vstack([train_mask_entity[-padding:], test_mask_entity]) # Create rolling windows train_data_entity = torch.Tensor(train_data_entity).float() train_data_entity = train_data_entity.permute(0,2,1) train_data_entity = train_data_entity.unfold(dimension=0, size=total_window_size, step=window_step) test_data_entity = torch.Tensor(test_data_entity).float() test_data_entity = test_data_entity.permute(0,2,1) test_data_entity = test_data_entity.unfold(dimension=0, size=total_window_size, step=window_step) train_mask_entity = torch.Tensor(train_mask_entity).float() train_mask_entity = train_mask_entity.permute(0,2,1) train_mask_entity = train_mask_entity.unfold(dimension=0, size=total_window_size, step=window_step) test_mask_entity = torch.Tensor(test_mask_entity).float() test_mask_entity = test_mask_entity.permute(0,2,1) test_mask_entity = test_mask_entity.unfold(dimension=0, size=total_window_size, step=window_step) train_data_list.append(train_data_entity) test_data_list.append(test_data_entity) train_mask_list.append(train_mask_entity) test_mask_list.append(test_mask_entity) # Append all windows for complete windows data train_windows_data = torch.vstack(train_data_list) train_windows_mask = torch.vstack(train_mask_list) # -------------------------------------------- Instantiate and train Model -------------------------------------------- print('Training model...') model = DGHL_encoder(window_size=window_size, window_step=mc['window_step'], window_hierarchy=window_hierarchy, hidden_multiplier=mc['hidden_multiplier'], max_filters=mc['max_filters'], kernel_multiplier=mc['kernel_multiplier'], n_channels=n_features, z_size=mc['z_size'], z_size_up=mc['z_size_up'], batch_size=mc['batch_size'], learning_rate=mc['learning_rate'], noise_std=mc['noise_std'], normalize_windows=mc['normalize_windows'], random_seed=mc['random_seed'], device=mc['device']) model.fit(X=train_windows_data, mask=train_windows_mask, n_iterations=mc['n_iterations']) # -------------------------------------------- Inference on each entity -------------------------------------------- for entity in range(n_entities): rootdir_entity = f'{root_dir}/{entities[entity]}' os.makedirs(name=rootdir_entity, exist_ok=True) # Plots of reconstruction in train print('Reconstructing train...') x_train_true, x_train_hat, _, mask_windows = model.predict(X=train_data_list[entity], mask=train_mask_list[entity]) x_train_true, _ = de_unfold(x_windows=x_train_true, mask_windows=mask_windows, window_step=window_step) x_train_hat, _ = de_unfold(x_windows=x_train_hat, mask_windows=mask_windows, window_step=window_step) x_train_true = np.swapaxes(x_train_true,0,1) x_train_hat = np.swapaxes(x_train_hat,0,1) if make_plots: filename = f'{rootdir_entity}/reconstruction_train.png' plot_reconstruction_ts(x=x_train_true, x_hat=x_train_hat, n_features=n_features, filename=filename) # --------------------------------------- Inference on test and anomaly scores --------------------------------------- print('Computing scores on test...') score_windows, ts_score, x_windows, x_hat_windows, _, mask_windows = model.anomaly_score(X=test_data_list[entity], mask=test_mask_list[entity]) # Post-processing # Fold windows score_windows = score_windows[:,None,None,:] score_mask = np.ones(score_windows.shape) score, _ = de_unfold(x_windows=score_windows, mask_windows=score_mask, window_step=window_step) x_test_true, _ = de_unfold(x_windows=x_windows, mask_windows=mask_windows, window_step=window_step) x_test_hat, _ = de_unfold(x_windows=x_hat_windows, mask_windows=mask_windows, window_step=window_step) x_test_true = np.swapaxes(x_test_true,0,1) x_test_hat = np.swapaxes(x_test_hat,0,1) score = score.flatten() score = score[-len(test_labels[entity]):] if make_plots: filename = f'{rootdir_entity}/reconstruction_test.png' plot_reconstruction_ts(x=x_test_true, x_hat=x_test_hat, n_features=n_features, filename=filename) # Plot scores if make_plots: filename = f'{rootdir_entity}/anomaly_scores.png' plot_anomaly_scores(score=score, labels=test_labels[entity], filename=filename) results = {'score': score, 'ts_score':ts_score, 'labels':test_labels, 'mc':mc} # results = {'score': score, 'ts_score':ts_score, 'x_test_true':x_test_true, 'x_test_hat':x_test_hat, 'labels':test_labels, # 'x_train_true':x_train_true, 'x_train_hat':x_train_hat, 'train_mask': train_mask, 'mc':mc} with open(f'{rootdir_entity}/results.p','wb') as f: pickle.dump(results, f)

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null

0

1

0

1

0

null

0

7

486b401f106af6df709d8d8f38b1b0631741bcd9

2,908

py

Python

usersec/migrations/0002_hpcgroup_adjustments.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

null

usersec/migrations/0002_hpcgroup_adjustments.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

27

2022-02-11T15:51:24.000Z

2022-03-31T12:11:20.000Z

usersec/migrations/0002_hpcgroup_adjustments.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

null

# Generated by Django 4.0.2 on 2022-03-02 12:20 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ("usersec", "0001_initial"), ] operations = [ migrations.AlterField( model_name="hpcgroup", name="owner", field=models.ForeignKey( help_text="User registered as owner of the group", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s_owner", to="usersec.hpcuser", ), ), migrations.AlterField( model_name="hpcgroup", name="status", field=models.CharField( choices=[ ("INITIAL", "INITIAL"), ("ACTIVE", "ACTIVE"), ("DELETED", "DELETED"), ("EXPIRED", "EXPIRED"), ], help_text="Status of the group object", max_length=16, ), ), migrations.AlterField( model_name="hpcgroupversion", name="owner", field=models.ForeignKey( help_text="User registered as owner of the group", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s_owner", to="usersec.hpcuser", ), ), migrations.AlterField( model_name="hpcgroupversion", name="status", field=models.CharField( choices=[ ("INITIAL", "INITIAL"), ("ACTIVE", "ACTIVE"), ("DELETED", "DELETED"), ("EXPIRED", "EXPIRED"), ], help_text="Status of the group object", max_length=16, ), ), migrations.AlterField( model_name="hpcuser", name="status", field=models.CharField( choices=[ ("INITIAL", "INITIAL"), ("ACTIVE", "ACTIVE"), ("DELETED", "DELETED"), ("EXPIRED", "EXPIRED"), ], help_text="Status of the user object", max_length=16, ), ), migrations.AlterField( model_name="hpcuserversion", name="status", field=models.CharField( choices=[ ("INITIAL", "INITIAL"), ("ACTIVE", "ACTIVE"), ("DELETED", "DELETED"), ("EXPIRED", "EXPIRED"), ], help_text="Status of the user object", max_length=16, ), ), ]

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0

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0

null

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8

d20422a2e661c658065e92cba23e21e0e355980c

180

py

Python

Road_safety/hackathon/forms.py

mukul54/xyz-bosch

92a3f2d1e8c8308547b2e9de5d5b20ebdd6d925a

[ "Apache-2.0" ]

3

2019-07-05T16:52:34.000Z

2021-07-09T09:01:03.000Z

Road_safety/hackathon/forms.py

mukul54/xyz-bosch

92a3f2d1e8c8308547b2e9de5d5b20ebdd6d925a

[ "Apache-2.0" ]

5

2020-08-18T21:45:56.000Z

2021-04-13T14:36:47.000Z

Road_safety/hackathon/forms.py

mukul54/xyz-bosch

92a3f2d1e8c8308547b2e9de5d5b20ebdd6d925a

[ "Apache-2.0" ]

2

2019-07-02T21:36:40.000Z

2019-08-23T16:17:11.000Z

from django import forms class LoginForm(forms.Form): username = forms.CharField(max_length=60) password = forms.CharField(max_length=60, widget=forms.PasswordInput())

36

75

0.755556

23

180

5.826087

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0.253731

0.343284

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75

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1

0

1

0

null

0

1

0

1

0

7

d21fbe2cb2a6286d6a2a99fbfeb7b8955af0ffb5

173

py

Python

python/src/collatz/__init__.py

Skenvy/Collatz

9b1738221fc421d153eabd37c837239b189c6bed

[ "Apache-2.0" ]

null

python/src/collatz/__init__.py

Skenvy/Collatz

9b1738221fc421d153eabd37c837239b189c6bed

[ "Apache-2.0" ]

null

python/src/collatz/__init__.py

Skenvy/Collatz

9b1738221fc421d153eabd37c837239b189c6bed

[ "Apache-2.0" ]

null

from .__version__ import __version__ from .parameterised import * from .parameterised import _ErrMsg from .parameterised import _CC from .parameterised import _KNOWN_CYCLES

28.833333

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0.849711

20

173

6.75

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0

0.115607

173

5

41

34.6

0.882353

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1

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true

0

1

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1

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1

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null

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null

0

1

0

1

0

1

0

7

d266e7e5f351b8bc0c6594fe1e92ff8f319cb5f0

189

py

Python

devel/lib/python2.7/dist-packages/motoman_msgs/msg/__init__.py

Pontiky/yaskawa-hc10-moveit

2a6031f9404d285aa662636ccc941485b339e7fd

[ "BSD-2-Clause" ]

1

2021-05-19T04:09:29.000Z

devel/lib/python2.7/dist-packages/motoman_msgs/msg/__init__.py

Pontiky/yaskawa-hc10-moveit

2a6031f9404d285aa662636ccc941485b339e7fd

[ "BSD-2-Clause" ]

null

devel/lib/python2.7/dist-packages/motoman_msgs/msg/__init__.py

Pontiky/yaskawa-hc10-moveit

2a6031f9404d285aa662636ccc941485b339e7fd

[ "BSD-2-Clause" ]

null

from ._DynamicJointPoint import * from ._DynamicJointState import * from ._DynamicJointTrajectory import * from ._DynamicJointTrajectoryFeedback import * from ._DynamicJointsGroup import *

31.5

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189

5

47

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1

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true

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null

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1

0

1

0

1

0

7

962c258ab7295ef7118b4f750bde90492ee5234a

5,499

py

Python

scripts/twitPersonality/embeddings.py

IllinoisSocialMediaMacroscope/smm-bae

9fea6fa61369db16c2bd95bc409be82c1f7a5c50

[ "Apache-2.0" ]

1

2018-12-11T18:57:15.000Z

scripts/twitPersonality/embeddings.py

IllinoisSocialMediaMacroscope/smm-bae

9fea6fa61369db16c2bd95bc409be82c1f7a5c50

[ "Apache-2.0" ]

1

2022-01-22T03:08:48.000Z

scripts/twitPersonality/embeddings.py

IllinoisSocialMediaMacroscope/smm-bae

9fea6fa61369db16c2bd95bc409be82c1f7a5c50

[ "Apache-2.0" ]

1

2021-11-04T01:10:18.000Z

from sklearn.feature_extraction.text import CountVectorizer import numpy as np #the function expects documents to be a list of documents. To use just one document, pass [[document]] def transformTextForTraining(embed_dictionary, length_threshold, documents, y_O, y_C, y_E, y_A, y_N, operation, FastText, friends=None): vectorizer = CountVectorizer(stop_words="english", analyzer="word") analyzer = vectorizer.build_analyzer() tokenizer = vectorizer.build_tokenizer() string = False deleted = 0 if type(documents) is str: #single post string = True documents = [documents] text_embeddings = [] i = 0 for document in documents: words = analyzer(document) #words = tokenizer(document) if len(words) < length_threshold and not string: deleted += 1 y_O = np.delete(y_O, i) y_C = np.delete(y_C, i) y_E = np.delete(y_E, i) y_A = np.delete(y_A, i) y_N = np.delete(y_N, i) if friends is not None: friends = np.delete(friends, i) continue doc_embeddings = [] for word in words: try: word_embedding = embed_dictionary[word] if FastText: word_embedding = np.array(list(float(value) for value in word_embedding[:-1].split(" "))) doc_embeddings.append(word_embedding) except KeyError: continue if len(doc_embeddings) == 0 and not string: deleted += 1 y_O = np.delete(y_O, i) y_C = np.delete(y_C, i) y_E = np.delete(y_E, i) y_A = np.delete(y_A, i) y_N = np.delete(y_N, i) if friends is not None: friends = np.delete(friends, i) continue if len(doc_embeddings) == 0: return False if friends is not None: if operation=="sum": text_embeddings.append( np.append(np.sum(np.array(doc_embeddings),axis=0),friends[i]) ) elif operation == "max": text_embeddings.append(np.append(np.amax(np.array(doc_embeddings),axis=0),friends[i]) ) elif operation == "min": text_embeddings.append(np.append(np.amin(np.array(doc_embeddings),axis=0),friends[i]) ) elif operation == "avg": text_embeddings.append(np.append(np.mean(np.array(doc_embeddings),axis=0),friends[i]) ) elif operation == "conc": npmax = np.amax(np.array(doc_embeddings),axis=0) npmin = np.amin(np.array(doc_embeddings),axis=0) npavg = np.mean(np.array(doc_embeddings),axis=0) text_embeddings.append( np.append(np.concatenate((npmax, npmin, npavg)),friends[i]) ) else: if operation=="sum": text_embeddings.append(np.sum(np.array(doc_embeddings),axis=0)) elif operation == "max": text_embeddings.append(np.amax(np.array(doc_embeddings),axis=0)) elif operation == "min": text_embeddings.append(np.amin(np.array(doc_embeddings),axis=0)) elif operation == "avg": text_embeddings.append(np.mean(np.array(doc_embeddings),axis=0)) elif operation == "conc": npmax = np.amax(np.array(doc_embeddings),axis=0) npmin = np.amin(np.array(doc_embeddings),axis=0) npavg = np.mean(np.array(doc_embeddings),axis=0) text_embeddings.append(np.concatenate((npmax, npmin, npavg))) i += 1 if friends is not None: return [np.array(text_embeddings), y_O, y_C, y_E, y_A, y_N, friends] else: return [np.array(text_embeddings), y_O, y_C, y_E, y_A, y_N] def transformTextForTesting(embed_dictionary, length_threshold, documents, operation): vectorizer = CountVectorizer(stop_words="english", analyzer="word") analyzer = vectorizer.build_analyzer() text_embeddings = [] i = 0 for document in documents: words = analyzer(document) if len(words) < length_threshold: #move to the next document continue doc_embeddings = [] for word in words: try: word_embedding_string = embed_dictionary[word] word_embedding = np.array(list(float(value) for value in word_embedding_string[:-1].split(" "))) doc_embeddings.append(word_embedding) except KeyError: continue if len(doc_embeddings) == 0: continue i += 1 if operation=="sum": text_embeddings.append(np.sum(np.array(doc_embeddings),axis=0)) elif operation == "max": text_embeddings.append(np.amax(np.array(doc_embeddings),axis=0)) elif operation == "min": text_embeddings.append(np.amin(np.array(doc_embeddings),axis=0)) elif operation == "avg": text_embeddings.append(np.mean(np.array(doc_embeddings),axis=0)) elif operation == "conc": npmax = np.amax(np.array(doc_embeddings),axis=0) npmin = np.amin(np.array(doc_embeddings),axis=0) npavg = np.mean(np.array(doc_embeddings),axis=0) text_embeddings.append(np.concatenate((npmax, npmin, npavg))) if len(text_embeddings) == 0: raise ValueError return np.array(text_embeddings)

41.977099

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692

5,499

4.524566

0.143064

0.116257

0.067071

0.134142

0.832961

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0.752475

0.717023

0.702012

0

0.008799

0.297327

5,499

131

137

41.977099

0.801501

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0

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0

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1

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false

0

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0.069565

0

null

0

1

0

1

0

null

0

7

962c300fc4d3ebe068fc610f0dcfc42c741b9318

2,202

py

Python

S4/S4 Library/simulation/conditional_layers/conditional_layer_commands.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

1

2021-05-20T19:33:37.000Z

S4/S4 Library/simulation/conditional_layers/conditional_layer_commands.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

S4/S4 Library/simulation/conditional_layers/conditional_layer_commands.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

from conditional_layers.conditional_layer_service import ConditionalLayerRequestSpeedType from server_commands.argument_helpers import TunableInstanceParam import services import sims4.commands @sims4.commands.Command('layers.load_layer') def load_conditional_layer(conditional_layer:TunableInstanceParam(sims4.resources.Types.CONDITIONAL_LAYER), immediate:bool=True, timer_interval:int=1, timer_object_count:int=5): if conditional_layer is None: sims4.commands.output('Unable to find the conditional_layer instance specified.') return conditional_layer_service = services.conditional_layer_service() speed = ConditionalLayerRequestSpeedType.IMMEDIATELY if immediate else ConditionalLayerRequestSpeedType.GRADUALLY conditional_layer_service.load_conditional_layer(conditional_layer, speed=speed, timer_interval=timer_interval, timer_object_count=timer_object_count) @sims4.commands.Command('layers.destroy_layer') def destroy_conditional_layer(conditional_layer:TunableInstanceParam(sims4.resources.Types.CONDITIONAL_LAYER), immediate:bool=True, timer_interval:int=1, timer_object_count:int=5): conditional_layer_service = services.conditional_layer_service() speed = ConditionalLayerRequestSpeedType.IMMEDIATELY if immediate else ConditionalLayerRequestSpeedType.GRADUALLY conditional_layer_service.destroy_conditional_layer(conditional_layer, speed=speed, timer_interval=timer_interval, timer_object_count=timer_object_count) @sims4.commands.Command('layers.reload_layer') def reload_conditional_layer(conditional_layer:TunableInstanceParam(sims4.resources.Types.CONDITIONAL_LAYER), immediate:bool=True, timer_interval:int=1, timer_object_count:int=5): conditional_layer_service = services.conditional_layer_service() speed = ConditionalLayerRequestSpeedType.IMMEDIATELY if immediate else ConditionalLayerRequestSpeedType.GRADUALLY conditional_layer_service.destroy_conditional_layer(conditional_layer, speed=speed, timer_interval=timer_interval, timer_object_count=timer_object_count) conditional_layer_service.load_conditional_layer(conditional_layer, speed=speed, timer_interval=timer_interval, timer_object_count=timer_object_count)

81.555556

180

0.865123

252

2,202

7.214286

0.18254

0.264026

0.139164

0.123212

0.810781

0.80473

0

0.006826

0.068574

2,202

26

181

84.692308

0.879571

0

0.434783

0

0.050863

0

1

0.130435

false

0

0.173913

0

0.347826

0

null

1

0

1

0

null

0

7

965d697abe9050e33f821acb378c2c5b1f222c88

763

py

Python

examples/v1.0.0/example.py

catsital/pycasso

eb54cd82e66d06b3677c2c068716ceb818c19f97

[ "MIT" ]

4

2021-11-08T08:35:10.000Z

2022-02-23T21:22:11.000Z

examples/v1.0.0/example.py

catsital/pycasso

eb54cd82e66d06b3677c2c068716ceb818c19f97

[ "MIT" ]

null

examples/v1.0.0/example.py

catsital/pycasso

eb54cd82e66d06b3677c2c068716ceb818c19f97

[ "MIT" ]

null

from pycasso import Canvas img = '../examples/en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2.png' slice_size = 30 seed = 'Pycasso' pyc = Canvas(img, slice_size, seed) pyc.export(mode='scramble', path='en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2_v1.0.0-prng.png') # Canvas(img, slice_size, seed).export('scramble', 'en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2_v1.0.0-prng.png') img = 'en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2_v1.0.0-prng.png' slice_size = 30 seed = 'Pycasso' pyc = Canvas(img, slice_size, seed) pyc.export(mode='unscramble', path='en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2_v1.0.0-prng-unscramble.png') # Canvas(img, slice_size, seed).export('unscramble', 'en_Pepper-and-Carrot_by-David-Revoy_E05P01_p2_v1.0.0-prng-unscramble.png')

42.388889

128

0.775885

135

763

4.125926

0.214815

0.086176

0.118492

0.183124

0.868941

0.768402

0.701975

0

0.068724

0.065531

763

17

129

44.882353

0.712482

0.314548

0

0.545455

0

0.551923

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0

1

0

false

0

0.090909

0

0.090909

0

null

0

1

0

1

null

0

8

967702d091c15203c5625e7ed8b2fa2b54732d3d

86

py

Python

Dynamics/Discrete/test.py

lambertdw/CalculiX-Examples

1c003ff3a9dd8872c6c44b4cfaf3698997346465

[ "MIT" ]

null

Dynamics/Discrete/test.py

lambertdw/CalculiX-Examples

1c003ff3a9dd8872c6c44b4cfaf3698997346465

[ "MIT" ]

null

Dynamics/Discrete/test.py

lambertdw/CalculiX-Examples

1c003ff3a9dd8872c6c44b4cfaf3698997346465

[ "MIT" ]

null

#!/usr/bin/python import os os.system("cgx -b run.fbd") os.system("cgx -b runM.fbd")

14.333333

28

0.662791

17

86

3.352941

0.647059

0.280702

0.385965

0.421053

0

0.116279

86

5

29

17.2

0.75

0.186047

0

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0

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true

0

0.333333

0

0.333333

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1

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null

1

0

1

0

null

0

1

0

1

0

7

96783813764d7f62c9c368cb8c5d05bd708b3231

13,299

py

Python

tests/testowyl.py

lullabee/owyl

db0458bce9ff378bce1ffb7e7b93c86a1a0e5743

[ "BSD-3-Clause" ]

null

tests/testowyl.py

lullabee/owyl

db0458bce9ff378bce1ffb7e7b93c86a1a0e5743

[ "BSD-3-Clause" ]

null

tests/testowyl.py

lullabee/owyl

db0458bce9ff378bce1ffb7e7b93c86a1a0e5743

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """testowyl -- some tests for owyl. Copyright 2008 David Eyk. All rights reserved. $Author$\n $Rev$\n $Date$ """ __author__ = "$Author$"[9:-2] __revision__ = "$Rev$"[6:-2] __date__ = "$Date$"[7:-2] import unittest import owyl from owyl import blackboard class OwylTests(unittest.TestCase): """Tests for Owyl. Note: tests should run the tree twice to make sure that the constructed tree is re-usable. """ def testSucceed(self): """Can we succeed? """ s = owyl.succeed() t = s() self.assertEqual(next(t), True) self.assertRaises(StopIteration, next(t)) t = s() self.assertEqual(next(t), True) self.assertRaises(StopIteration, next(t)) def testFail(self): """Can we fail? """ s = owyl.fail() t = s() self.assertEqual(next(t), False) self.assertRaises(StopIteration, next(t)) t = s() self.assertEqual(next(t), False) self.assertRaises(StopIteration, next(t)) def testVisitSequenceSuccess(self): """Can we visit a successful sequence? """ tree = owyl.sequence(owyl.succeed(), owyl.succeed(), owyl.succeed()) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True, True, True, True]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True, True, True, True]) def testVisitSequenceFailure(self): """Can we visit a failing sequence? """ tree = owyl.sequence(owyl.succeed(), owyl.succeed(), owyl.fail(), owyl.succeed()) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True, True, False, False]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True, True, False, False]) def testVisitSelectorSuccess(self): """Can we visit a successful selector? """ tree = owyl.selector(owyl.fail(), owyl.fail(), owyl.succeed(), owyl.fail()) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False, False, True, True]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False, False, True, True]) def testVisitSelectorFailure(self): """Can we visit a failing selector? """ tree = owyl.selector(owyl.fail(), owyl.fail(), owyl.fail()) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False, False, False, False]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False, False, False, False]) def testParallel_AllSucceed_Success(self): """Can we visit a suceeding parallel (all succeed)? """ tree = owyl.parallel(owyl.sequence(owyl.succeed(), owyl.succeed()), owyl.sequence(owyl.succeed(), owyl.succeed()), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ALL) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True]) def testParallel_OneSucceeds_Success(self): """Can we visit a suceeding parallel (one succeeds)? """ tree = owyl.parallel(owyl.sequence(owyl.succeed(), owyl.succeed()), owyl.sequence(owyl.succeed(), owyl.fail()), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ONE) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [True]) def testParallel_AllSucceed_Failure(self): """Can we visit a failing parallel (all succeed)? """ tree = owyl.parallel(owyl.sequence(owyl.succeed(), owyl.fail()), owyl.sequence(owyl.succeed(), owyl.succeed()), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ALL) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False]) def testParallel_OneSucceeds_Failure(self): """Can we visit a failing parallel (one succeeds)? """ tree = owyl.parallel(owyl.sequence(owyl.fail(), owyl.fail()), owyl.sequence(owyl.fail(), owyl.fail()), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ONE) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False]) v = owyl.visit(tree) results = [x for x in v if x is not None] self.assertEqual(results, [False]) def testThrow(self): """Can we throw an exception within the tree? """ tree = owyl.sequence(owyl.succeed(), owyl.succeed(), owyl.throw(throws=ValueError, throws_message="AUGH!!"), ) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertRaises(ValueError, next(v)) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertRaises(ValueError, next(v)) def testCatch(self): """Can we catch an exception thrown within the tree? """ tree = owyl.sequence(owyl.succeed(), owyl.succeed(), owyl.catch(owyl.throw(throws=ValueError, throws_message="AUGH!!"), caught=ValueError, branch=owyl.succeed()) ) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertEqual(next(v), True) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertEqual(next(v), True) def testCatchIgnoresOthers(self): """Does catch ignore other exceptions thrown within the tree? """ tree = owyl.sequence(owyl.succeed(), owyl.succeed(), owyl.catch(owyl.throw(throws=ValueError, throws_message="AUGH!!"), caught=IndexError, branch=owyl.succeed()) ) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertRaises(ValueError, next(v)) v = owyl.visit(tree) self.assertEqual(next(v), True) self.assertEqual(next(v), True) self.assertRaises(ValueError, next(v)) def testIdentity(self): """Does identity pass on return values unchanged? """ # Succeed after 5 iterations. after = 5 tree = owyl.identity(owyl.succeedAfter(after=after)) v = owyl.visit(tree) for x in range(after): self.assertEqual(next(v), None) self.assertEqual(next(v), True) v = owyl.visit(tree) for x in range(after): self.assertEqual(next(v), None) self.assertEqual(next(v), True) tree = owyl.identity(owyl.failAfter(after=after)) v = owyl.visit(tree) for x in range(after): self.assertEqual(next(v), None) self.assertEqual(next(v), False) v = owyl.visit(tree) for x in range(after): self.assertEqual(next(v), None) self.assertEqual(next(v), False) def testCheckBB(self): """Can we check a value on a blackboard? """ value = "foo" checker = lambda x: x == value bb = blackboard.Blackboard('test', value=value) tree = blackboard.checkBB(key='value', check=checker) # Note that we can pass in the blackboard at run-time. v = owyl.visit(tree, blackboard=bb) # Check should succeed. self.assertEqual(next(v), True) v = owyl.visit(tree, blackboard=bb) self.assertEqual(next(v), True) bb['value'] = 'bar' # Check should now fail. v = owyl.visit(tree, blackboard=bb) self.assertEqual(next(v), False) v = owyl.visit(tree, blackboard=bb) self.assertEqual(next(v), False) def testSetBB(self): """Can we set a value on a blackboard? """ value = 'foo' checker = lambda x: x == value bb = blackboard.Blackboard('test', value='bar') tree = owyl.sequence(blackboard.setBB(key="value", value=value), blackboard.checkBB(key='value', check=checker) ) # Note that we can pass in the blackboard at run-time. v = owyl.visit(tree, blackboard=bb) # Sequence will succeed if the check succeeds. result = [x for x in v][-1] self.assertEqual(result, True) v = owyl.visit(tree, blackboard=bb) result = [x for x in v][-1] self.assertEqual(result, True) def testRepeatUntilSucceed(self): """Can we repeat a behavior until it succeeds? """ bb = blackboard.Blackboard('test', ) # 'value' defaults to None. checker = lambda x: x is not None parallel = owyl.parallel repeat = owyl.repeatUntilSucceed checkBB = blackboard.checkBB setBB = blackboard.setBB tree = parallel(repeat(checkBB(key='value', check=checker), final_value=True), # That should fail until this sets the value: owyl.selector(owyl.fail(), owyl.fail(), setBB(key='value', value='foo')), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ALL) v = owyl.visit(tree, blackboard=bb) results = [x for x in v] result = results[-1] self.assertEqual(result, True) # Need to reset the blackboard to get the same results. bb = blackboard.Blackboard('test', ) # 'value' defaults to None. v = owyl.visit(tree, blackboard=bb) results = [x for x in v] result = results[-1] self.assertEqual(result, True) def testRepeatUntilFail(self): """Can we repeat a behavior until it fails? """ bb = blackboard.Blackboard('test', value="foo") checker = lambda x: x and True or False # must eval to True parallel = owyl.parallel repeat = owyl.repeatUntilFail checkBB = blackboard.checkBB setBB = blackboard.setBB tree = parallel(repeat(checkBB(key='value', check=checker), final_value=True), # That should succeed until this sets the value: owyl.selector(owyl.fail(), owyl.fail(), setBB(key='value', value=None)), policy=owyl.PARALLEL_SUCCESS.REQUIRE_ALL) v = owyl.visit(tree, blackboard=bb) results = [x for x in v] result = results[-1] self.assertEqual(result, True) # Need to reset the blackboard to get the same results. bb = blackboard.Blackboard('test', value="foo") v = owyl.visit(tree, blackboard=bb) results = [x for x in v] result = results[-1] self.assertEqual(result, True) if __name__ == "__main__": runner = unittest try: import testoob runner = testoob except ImportError: pass runner.main()

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null

0

1

0

1

0

null

0

7

738362558d730c020c556528e1034c8cb4754c79

2,217

py

Python

tests/deconflict_test.py

NACHC-CAD/linkage-agent-tools

324299e534bc55bd652eb670feb195ce5646f13e

[ "Apache-2.0" ]

null

tests/deconflict_test.py

NACHC-CAD/linkage-agent-tools

324299e534bc55bd652eb670feb195ce5646f13e

[ "Apache-2.0" ]

1

2021-10-01T15:13:15.000Z

tests/deconflict_test.py

NACHC-CAD/linkage-agent-tools

324299e534bc55bd652eb670feb195ce5646f13e

[ "Apache-2.0" ]

null

from dcctools.deconflict import deconflict, link_count example_result = { "a": [142], "b": [142, 280], "run_results": [ {"a": 142, "b": 142, "project": "name-sex-dob-zip"}, {"a": 142, "b": 280, "project": "name-sex-dob-zip"}, {"a": 142, "b": 142, "project": "name-sex-dob-phone"}, {"a": 142, "b": 280, "project": "name-sex-dob-phone"}, {"a": 142, "b": 142, "project": "name-sex-dob-addr"}, {"a": 142, "b": 280, "project": "name-sex-dob-addr"}, {"a": 142, "b": 142, "project": "name-sex-dob-parents"}, {"a": 142, "b": 280, "project": "name-sex-dob-parents"}, {"a": 142, "c": 142, "project": "name-sex-dob-zip"}, {"a": 142, "c": 142, "project": "name-sex-dob-phone"}, {"a": 142, "c": 142, "project": "name-sex-dob-addr"}, {"b": 142, "c": 142, "project": "name-sex-dob-zip"}, {"b": 142, "c": 142, "project": "name-sex-dob-phone"}, {"b": 142, "c": 142, "project": "name-sex-dob-addr"}, {"b": 142, "c": 142, "project": "name-sex-dob-parents"}, ], "c": [142], } example_result_no_c = { "a": [142], "b": [142, 280], "run_results": [ {"a": 142, "b": 142, "project": "name-sex-dob-zip"}, {"a": 142, "b": 280, "project": "name-sex-dob-zip"}, {"a": 142, "b": 142, "project": "name-sex-dob-phone"}, {"a": 142, "b": 280, "project": "name-sex-dob-phone"}, {"a": 142, "b": 142, "project": "name-sex-dob-addr"}, {"a": 142, "b": 280, "project": "name-sex-dob-addr"}, {"a": 142, "b": 142, "project": "name-sex-dob-parents"}, {"a": 142, "b": 280, "project": "name-sex-dob-parents"}, ], } def test_link_count(): count = link_count(example_result, "b", 142) assert count == 8 def test_deconflict(): deconflicted_record = deconflict(example_result, ["a", "b", "c"]) assert deconflicted_record["a"] == 142 assert deconflicted_record["b"] == 142 assert deconflicted_record["c"] == 142 def test_deconflict_with_missing_system(): deconflicted_record = deconflict(example_result_no_c, ["a", "b", "c"]) assert deconflicted_record["a"] == 142 assert deconflicted_record["b"] == 142

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1

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null

0

7

738e54d588ad0a67d06a9f242314f67878f2bba6

101

py

Python

pybase24/__init__.py

mildmelon/python-base24

f730eddc34668d17b09d99495c63b096ad22c748

[ "MIT" ]

1

2020-03-09T04:35:00.000Z

pybase24/__init__.py

mildmelon/python-base24

f730eddc34668d17b09d99495c63b096ad22c748

[ "MIT" ]

null

pybase24/__init__.py

mildmelon/python-base24

f730eddc34668d17b09d99495c63b096ad22c748

[ "MIT" ]

null

from pybase24.base24 import ALPHABET, ALPHABET_LENGTH from pybase24.base24 import encode24, decode24

33.666667

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null

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0

1

0

8

73affc7b86cf58700e0444c9daaa12b6a841ead2

2,641

py

Python

saleor/core/tests/test_middleware.py

fairhopeweb/saleor

9ac6c22652d46ba65a5b894da5f1ba5bec48c019

[ "CC-BY-4.0" ]

15,337

2015-01-12T02:11:52.000Z

2021-10-05T19:19:29.000Z

saleor/core/tests/test_middleware.py

fairhopeweb/saleor

9ac6c22652d46ba65a5b894da5f1ba5bec48c019

[ "CC-BY-4.0" ]

7,486

2015-02-11T10:52:13.000Z

2021-10-06T09:37:15.000Z

saleor/core/tests/test_middleware.py

fairhopeweb/saleor

9ac6c22652d46ba65a5b894da5f1ba5bec48c019

[ "CC-BY-4.0" ]

5,864

2015-01-16T14:52:54.000Z

2021-10-05T23:01:15.000Z

from django.core.handlers.base import BaseHandler from freezegun import freeze_time from ..jwt import ( JWT_REFRESH_TOKEN_COOKIE_NAME, JWT_REFRESH_TYPE, create_refresh_token, jwt_encode, jwt_user_payload, ) @freeze_time("2020-03-18 12:00:00") def test_jwt_refresh_token_middleware(rf, customer_user, settings): refresh_token = create_refresh_token(customer_user) settings.MIDDLEWARE = [ "saleor.core.middleware.jwt_refresh_token_middleware", ] request = rf.request() request.refresh_token = refresh_token handler = BaseHandler() handler.load_middleware() response = handler.get_response(request) cookie = response.cookies.get(JWT_REFRESH_TOKEN_COOKIE_NAME) assert cookie.value == refresh_token @freeze_time("2020-03-18 12:00:00") def test_jwt_refresh_token_middleware_token_without_expire(rf, customer_user, settings): settings.JWT_EXPIRE = True payload = jwt_user_payload( customer_user, JWT_REFRESH_TYPE, settings.JWT_TTL_REFRESH, ) del payload["exp"] refresh_token = jwt_encode(payload) settings.MIDDLEWARE = [ "saleor.core.middleware.jwt_refresh_token_middleware", ] request = rf.request() request.refresh_token = refresh_token handler = BaseHandler() handler.load_middleware() response = handler.get_response(request) cookie = response.cookies.get(JWT_REFRESH_TOKEN_COOKIE_NAME) assert cookie.value == refresh_token @freeze_time("2020-03-18 12:00:00") def test_jwt_refresh_token_middleware_samesite_debug_mode(rf, customer_user, settings): refresh_token = create_refresh_token(customer_user) settings.MIDDLEWARE = [ "saleor.core.middleware.jwt_refresh_token_middleware", ] settings.DEBUG = True request = rf.request() request.refresh_token = refresh_token handler = BaseHandler() handler.load_middleware() response = handler.get_response(request) cookie = response.cookies.get(JWT_REFRESH_TOKEN_COOKIE_NAME) assert cookie["samesite"] == "Lax" @freeze_time("2020-03-18 12:00:00") def test_jwt_refresh_token_middleware_samesite_none(rf, customer_user, settings): refresh_token = create_refresh_token(customer_user) settings.MIDDLEWARE = [ "saleor.core.middleware.jwt_refresh_token_middleware", ] settings.DEBUG = False request = rf.request() request.refresh_token = refresh_token handler = BaseHandler() handler.load_middleware() response = handler.get_response(request) cookie = response.cookies.get(JWT_REFRESH_TOKEN_COOKIE_NAME) assert cookie["samesite"] == "None"

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0

null

1

0

1

0

null

0

7

73eb1bceac18001f8491ab9f5c52a91da1e2874a

38,132

py

Python

msgraph-cli-extensions/beta/financials_beta/azext_financials_beta/generated/action.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/beta/financials_beta/azext_financials_beta/generated/action.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/beta/financials_beta/azext_financials_beta/generated/action.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- # pylint: disable=protected-access import argparse from collections import defaultdict from knack.util import CLIError class AddAccounts(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddAccounts, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'blocked': d['blocked'] = v[0] elif kl == 'category': d['category'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'number': d['number'] = v[0] elif kl == 'sub-category': d['sub_category'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter accounts. All possible keys are: blocked, ' 'category, display-name, last-modified-date-time, number, sub-category, id'.format(k)) return d class AddAgedAccountsPayable(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddAgedAccountsPayable, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'aged-as-of-date': d['aged_as_of_date'] = v[0] elif kl == 'balance-due': d['balance_due'] = v[0] elif kl == 'currency-code': d['currency_code'] = v[0] elif kl == 'current-amount': d['current_amount'] = v[0] elif kl == 'name': d['name'] = v[0] elif kl == 'period1-amount': d['period1_amount'] = v[0] elif kl == 'period2-amount': d['period2_amount'] = v[0] elif kl == 'period3-amount': d['period3_amount'] = v[0] elif kl == 'period-length-filter': d['period_length_filter'] = v[0] elif kl == 'vendor-number': d['vendor_number'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter aged_accounts_payable. All possible keys ' 'are: aged-as-of-date, balance-due, currency-code, current-amount, name, ' 'period1-amount, period2-amount, period3-amount, period-length-filter, vendor-number, ' 'id'.format(k)) return d class AddAgedAccountsReceivable(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddAgedAccountsReceivable, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'aged-as-of-date': d['aged_as_of_date'] = v[0] elif kl == 'balance-due': d['balance_due'] = v[0] elif kl == 'currency-code': d['currency_code'] = v[0] elif kl == 'current-amount': d['current_amount'] = v[0] elif kl == 'customer-number': d['customer_number'] = v[0] elif kl == 'name': d['name'] = v[0] elif kl == 'period1-amount': d['period1_amount'] = v[0] elif kl == 'period2-amount': d['period2_amount'] = v[0] elif kl == 'period3-amount': d['period3_amount'] = v[0] elif kl == 'period-length-filter': d['period_length_filter'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter aged_accounts_receivable. All possible ' 'keys are: aged-as-of-date, balance-due, currency-code, current-amount, ' 'customer-number, name, period1-amount, period2-amount, period3-amount, ' 'period-length-filter, id'.format(k)) return d class AddCountriesRegions(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddCountriesRegions, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'address-format': d['address_format'] = v[0] elif kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter countries_regions. All possible keys are: ' 'address-format, code, display-name, last-modified-date-time, id'.format(k)) return d class AddCurrencies(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddCurrencies, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'amount-decimal-places': d['amount_decimal_places'] = v[0] elif kl == 'amount-rounding-precision': d['amount_rounding_precision'] = v[0] elif kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'symbol': d['symbol'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter currencies. All possible keys are: ' 'amount-decimal-places, amount-rounding-precision, code, display-name, ' 'last-modified-date-time, symbol, id'.format(k)) return d class AddFinancialsDimensionValues(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsDimensionValues, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter dimension_values. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddItemCategories(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddItemCategories, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter item_categories. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddPaymentMethods(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddPaymentMethods, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter payment_methods. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddPaymentTerms(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddPaymentTerms, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'calculate-discount-on-credit-memos': d['calculate_discount_on_credit_memos'] = v[0] elif kl == 'code': d['code'] = v[0] elif kl == 'discount-date-calculation': d['discount_date_calculation'] = v[0] elif kl == 'discount-percent': d['discount_percent'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'due-date-calculation': d['due_date_calculation'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter payment_terms. All possible keys are: ' 'calculate-discount-on-credit-memos, code, discount-date-calculation, discount-percent, ' 'display-name, due-date-calculation, last-modified-date-time, id'.format(k)) return d class AddFinancialsPicture(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsPicture, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'content': d['content'] = v[0] elif kl == 'content-type': d['content_type'] = v[0] elif kl == 'height': d['height'] = v[0] elif kl == 'width': d['width'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter picture. All possible keys are: content, ' 'content-type, height, width, id'.format(k)) return d class AddShipmentMethods(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddShipmentMethods, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter shipment_methods. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddTaxAreas(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddTaxAreas, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'tax-type': d['tax_type'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter tax_areas. All possible keys are: code, ' 'display-name, last-modified-date-time, tax-type, id'.format(k)) return d class AddTaxGroups(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddTaxGroups, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'tax-type': d['tax_type'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter tax_groups. All possible keys are: code, ' 'display-name, last-modified-date-time, tax-type, id'.format(k)) return d class AddUnitsOfMeasure(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddUnitsOfMeasure, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'international-standard-code': d['international_standard_code'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter units_of_measure. All possible keys are: ' 'code, display-name, international-standard-code, last-modified-date-time, id'.format(k)) return d class AddAccount(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.body = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] return d class AddAddress(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.address = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'city': d['city'] = v[0] elif kl == 'country-letter-code': d['country_letter_code'] = v[0] elif kl == 'postal-code': d['postal_code'] = v[0] elif kl == 'state': d['state'] = v[0] elif kl == 'street': d['street'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter address. All possible keys are: city, ' 'country-letter-code, postal-code, state, street'.format(k)) return d class AddCurrency(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.body = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] return d class AddPaymentMethod(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.payment_method = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter payment_method. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddPaymentTerm(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.payment_term = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'calculate-discount-on-credit-memos': d['calculate_discount_on_credit_memos'] = v[0] elif kl == 'code': d['code'] = v[0] elif kl == 'discount-date-calculation': d['discount_date_calculation'] = v[0] elif kl == 'discount-percent': d['discount_percent'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'due-date-calculation': d['due_date_calculation'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter payment_term. All possible keys are: ' 'calculate-discount-on-credit-memos, code, discount-date-calculation, discount-percent, ' 'display-name, due-date-calculation, last-modified-date-time, id'.format(k)) return d class AddFinancialsCompaniesPicture(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsCompaniesPicture, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'content': d['content'] = v[0] elif kl == 'content-type': d['content_type'] = v[0] elif kl == 'height': d['height'] = v[0] elif kl == 'width': d['width'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter picture. All possible keys are: content, ' 'content-type, height, width, id'.format(k)) return d class AddShipmentMethod(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.shipment_method = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter shipment_method. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddFinancialsCompaniesDimensionValues(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsCompaniesDimensionValues, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter dimension_values. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddFinancialsFinancialCompanyCreateEmployeePicture(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsFinancialCompanyCreateEmployeePicture, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'content': d['content'] = v[0] elif kl == 'content-type': d['content_type'] = v[0] elif kl == 'height': d['height'] = v[0] elif kl == 'width': d['width'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter picture. All possible keys are: content, ' 'content-type, height, width, id'.format(k)) return d class AddItemCategory(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) namespace.item_category = action def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'code': d['code'] = v[0] elif kl == 'display-name': d['display_name'] = v[0] elif kl == 'last-modified-date-time': d['last_modified_date_time'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter item_category. All possible keys are: ' 'code, display-name, last-modified-date-time, id'.format(k)) return d class AddFinancialsFinancialCompanyCreateSaleCreditMemoLinePicture(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsFinancialCompanyCreateSaleCreditMemoLinePicture, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'content': d['content'] = v[0] elif kl == 'content-type': d['content_type'] = v[0] elif kl == 'height': d['height'] = v[0] elif kl == 'width': d['width'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter picture. All possible keys are: content, ' 'content-type, height, width, id'.format(k)) return d class AddFinancialsFinancialCompanyCreatePurchaseInvoicePicture(argparse._AppendAction): def __call__(self, parser, namespace, values, option_string=None): action = self.get_action(values, option_string) super(AddFinancialsFinancialCompanyCreatePurchaseInvoicePicture, self).__call__(parser, namespace, action, option_string) def get_action(self, values, option_string): # pylint: disable=no-self-use try: properties = defaultdict(list) for (k, v) in (x.split('=', 1) for x in values): properties[k].append(v) properties = dict(properties) except ValueError: raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) d = {} for k in properties: kl = k.lower() v = properties[k] if kl == 'content': d['content'] = v[0] elif kl == 'content-type': d['content_type'] = v[0] elif kl == 'height': d['height'] = v[0] elif kl == 'width': d['width'] = v[0] elif kl == 'id': d['id'] = v[0] else: raise CLIError('Unsupported Key {} is provided for parameter picture. All possible keys are: content, ' 'content-type, height, width, id'.format(k)) return d

43.23356

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0.521163

4,130

38,132

4.685714

0.047458

0.013849

0.034105

0.045473

0.888177

0.883578

0.877635

0.874122

0

0.007228

0.354164

38,132

881

134

43.282633

0.778576

0.03147

0

0.856061

0

0.008838

0.205781

0.050841

0

1

0.065657

false

0

0.003788

0

0.135101

0

null

0

1

0

1

0

null

0

7

73eba2a0057ee47e18b3a87462eecacf636329a2

8,364

py

Python

sawyer/mujoco/tasks/toy_tasks.py

rlagywjd802/gym-sawyer

385bbeafcccb61afb9099554f6a99b16f1f1a7c5

[ "MIT" ]

null

sawyer/mujoco/tasks/toy_tasks.py

rlagywjd802/gym-sawyer

385bbeafcccb61afb9099554f6a99b16f1f1a7c5

[ "MIT" ]

null

sawyer/mujoco/tasks/toy_tasks.py

rlagywjd802/gym-sawyer

385bbeafcccb61afb9099554f6a99b16f1f1a7c5

[ "MIT" ]

null

import numpy as np from sawyer.mujoco.tasks.base import ComposableTask class InsertTask(ComposableTask): """ Task to insert a key object into an upward facing lock. The task assumes the key is already grasped and the gripper is close to the lock hole. Reward function is based on the following heuristics: - Positive reward for a smaller z coordinate of the key - Negative reward for releasing object """ def __init__(self, key_object, lock_object, never_done=False, success_thresh=0.01, target_z_pos=0.20, completion_bonus=0, c_dist=0.1, c_grasp=0.9): self._key_object = key_object self._lock_object = lock_object self._never_done = never_done self._success_thresh = success_thresh self._target_z_pos = target_z_pos self._completion_bonus = completion_bonus self._c_dist = c_dist self._c_grasp = c_grasp def compute_reward(self, obs, info): key_pos = info['world_obs']['{}_position'.format(self._key_object)] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] target_pos = np.array([lock_site[0], lock_site[1], self._target_z_pos]) r_dist = -np.linalg.norm(target_pos - key_pos) r_grasp = grasped * self._c_grasp return r_dist + r_grasp def is_success(self, obs, info): if self._never_done: return False key_pos = info['world_obs']['{}_position'.format(self._key_object)] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] target_pos = np.array([lock_site[0], lock_site[1], self._target_z_pos]) r_dist = np.linalg.norm(target_pos - key_pos) return (grasped and np.linalg.norm(target_pos - key_pos) < self._success_thresh) @property def completion_bonus(self): return self._completion_bonus class RemoveTask(ComposableTask): """ Task to remove a key object from an upward facing lock. The task assumes the key is already grasped and the gripper is close to the lock hole. Reward function is based on the following heuristics: - Positive reward for a larger z coordinate of the key - Negative reward for releasing object """ def __init__(self, key_object, lock_object, never_done=False, success_thresh=0.01, target_z_pos=0.35, completion_bonus=0, c_dist=0.1, c_grasp=0.9): self._key_object = key_object self._lock_object = lock_object self._never_done = never_done self._success_thresh = success_thresh self._target_z_pos = target_z_pos self._completion_bonus = completion_bonus self._c_dist = c_dist self._c_grasp = c_grasp def compute_reward(self, obs, info): key_pos = info['world_obs']['{}_position'.format(self._key_object)] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] target_pos = np.array([lock_site[0], lock_site[1], self._target_z_pos]) r_dist = -np.linalg.norm(target_pos - key_pos) r_grasp = grasped * self._c_grasp return r_dist + r_grasp def is_success(self, obs, info): if self._never_done: return False key_pos = info['world_obs']['{}_position'.format(self._key_object)] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] target_pos = np.array([lock_site[0], lock_site[1], self._target_z_pos]) r_dist = np.linalg.norm(target_pos - key_pos) return (grasped and np.linalg.norm(target_pos - key_pos) < self._success_thresh) @property def completion_bonus(self): return self._completion_bonus class OpenTask(ComposableTask): """ Task to open a toy box lid on a lateral sliding joint with an inserted peg. The task assumes there is already a key object inserted into the lid hole. Reward function is based on the following heuristics: - Positive reward for increased lateral distance between box and lid - Negative reward for releasing key object """ def __init__(self, lid_object, key_object, never_done=False, success_thresh=0.01, target_lid_jpos=-0.05, completion_bonus=0, c_jdist=0.2, c_xydist=0.8): self._lid_object = lid_object self._key_object = key_object self._never_done = never_done self._success_thresh = success_thresh self._target_lid_jpos = target_lid_jpos self._completion_bonus = completion_bonus self._c_jdist = c_jdist self._c_xydist = c_xydist def compute_reward(self, obs, info): key_pos = info['world_obs']['{}_position'.format(self._key_object)] lid_joint_state = info['lid_joint_state'] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] dxy_peg2hole = key_pos[:2] - lock_site[:2] r_jdist = (1 - np.tanh(10. * np.abs(lid_joint_state - self._target_lid_jpos))) * 0.2 r_peg2hole = (1 - np.tanh(np.linalg.norm(dxy_peg2hole))) * self._c_xydist return int(grasped) * (r_jdist + r_peg2hole) def is_success(self, obs, info): if self._never_done: return False key_pos = info['world_obs']['{}_position'.format(self._key_object)] lid_joint_state = info['lid_joint_state'] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] dxy_peg2hole = key_pos[:2] - lock_site[:2] return (grasped and np.linalg.norm(dxy_peg2hole) < self._success_thresh and lid_joint_state <= self._target_lid_jpos) @property def completion_bonus(self): return self._completion_bonus class CloseTask(ComposableTask): """ Task to close a toy box lid with an inserted peg. The task assumes there is already a key object inserted into the lid hole. Reward function is based on the following heuristics: - Positive reward for decreased lateral distance between box and lid - Negative reward for releasing key object """ def __init__(self, lid_object, key_object, never_done=False, success_thresh=0.01, target_lid_jpos=-0.05, completion_bonus=0, c_jdist=0.2, c_xydist=0.8): self._lid_object = lid_object self._key_object = key_object self._never_done = never_done self._success_thresh = success_thresh self._target_lid_jpos = target_lid_jpos self._completion_bonus = completion_bonus self._c_jdist = c_jdist self._c_xydist = c_xydist def compute_reward(self, obs, info): key_pos = info['world_obs']['{}_position'.format(self._key_object)] lid_joint_state = info['lid_joint_state'] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] dxy_peg2hole = key_pos[:2] - lock_site[:2] r_jdist = (1 - np.tanh(10. * np.abs(lid_joint_state - self._target_lid_jpos))) * self._c_jdist r_peg2hole = (1 - np.tanh(np.linalg.norm(dxy_peg2hole))) * self._c_xydist return int(grasped) * (r_jdist + r_peg2hole) def is_success(self, obs, info): if self._never_done: return False key_pos = info['world_obs']['{}_position'.format(self._key_object)] lid_joint_state = info['lid_joint_state'] lock_site = info['hole_site'] grasped = info['grasped_{}'.format(self._key_object)] dxy_peg2hole = key_pos[:2] - lock_site[:2] return (grasped and np.linalg.norm(dxy_peg2hole) < self._success_thresh and lid_joint_state >= self._target_lid_jpos) @property def completion_bonus(self): return self._completion_bonus

35.142857

102

0.626853

1,113

8,364

4.362084

0.102426

0.063028

0.058908

0.062616

0.934089

0

0.01363

0.280727

8,364

237

103

35.291139

0.793384

0.143233

0

0.925926

0

0.052894

0

1

0.098765

false

0

0.012346

0.024691

0.234568

0

null

0

1

0

1

0

null

0

7

fb754a1c96b025de654642b4bbba2d4902f62fe6

43,030

py

Python

test/test_distributed_metrics.py

intel/lp-opt-tool

130eefa3586b38df6c0ff78cc8807ae273f6a63f

[ "Apache-2.0" ]

52

2020-08-04T04:31:48.000Z

2020-11-29T02:34:32.000Z

test/test_distributed_metrics.py

intel/lp-opt-tool

130eefa3586b38df6c0ff78cc8807ae273f6a63f

[ "Apache-2.0" ]

null

test/test_distributed_metrics.py

intel/lp-opt-tool

130eefa3586b38df6c0ff78cc8807ae273f6a63f

[ "Apache-2.0" ]

7

2020-08-21T01:08:55.000Z

2020-11-29T03:36:55.000Z

"""Tests for the distributed metrics.""" import os import signal import shutil import subprocess import unittest import re import tensorflow def build_fake_ut(): fake_ut = """ import numpy as np import unittest from neural_compressor.metric import METRICS from neural_compressor.experimental.metric.f1 import evaluate from neural_compressor.experimental.metric.evaluate_squad import evaluate as evaluate_squad from neural_compressor.experimental.metric import bleu import horovod.tensorflow as hvd import os import json import tensorflow as tf tf.compat.v1.enable_eager_execution() class TestMetrics(unittest.TestCase): @classmethod def setUpClass(cls): hvd.init() if hvd.rank() == 0: if os.path.exists('anno_0.yaml'): os.remove('anno_0.yaml') if os.path.exists('anno_1.yaml'): os.remove('anno_1.yaml') if os.path.exists('anno_2.yaml'): os.remove('anno_2.yaml') while hvd.rank() == 1: if not os.path.exists('anno_0.yaml') \\ and not os.path.exists('anno_1.yaml') \\ and not os.path.exists('anno_2.yaml'): break @classmethod def tearDownClass(cls): if hvd.rank() == 1: if os.path.exists('anno_0.yaml'): os.remove('anno_0.yaml') if os.path.exists('anno_1.yaml'): os.remove('anno_1.yaml') if os.path.exists('anno_2.yaml'): os.remove('anno_2.yaml') def test_mIOU(self): metrics = METRICS('tensorflow') miou = metrics['mIOU']() miou.hvd = hvd if hvd.rank() == 0: preds = np.array([0]) labels = np.array([0]) else: preds = np.array([0, 1, 1]) labels = np.array([1, 0, 1]) miou.update(preds, labels) self.assertAlmostEqual(miou.result(), 0.33333334) miou.reset() if hvd.rank() == 0: preds = np.array([0, 0]) labels = np.array([0, 1]) else: preds = np.array([1, 1]) labels = np.array([1, 1]) miou.update(preds, labels) self.assertAlmostEqual(miou.result(), 0.58333333) def test_onnxrt_GLUE(self): metrics = METRICS('onnxrt_qlinearops') glue = metrics['GLUE']('mrpc') glue.hvd = hvd hvd.init() preds = [np.array( [[-3.2443411, 3.0909934], [2.0500996, -2.3100944], [1.870293 , -2.0741048], [-2.8377204, 2.617834], [2.008347 , -2.0215416], [-2.9693947, 2.7782154], [-2.9949608, 2.7887983], [-3.0623112, 2.8748074]]) ] labels = [np.array([1, 0, 0, 1, 0, 1, 0, 1])] self.assertRaises(NotImplementedError, glue.update, preds, labels) preds_2 = [np.array( [[-3.1296735, 2.8356276], [-3.172515 , 2.9173899], [-3.220131 , 3.0916846], [2.1452675, -1.9398905], [1.5475761, -1.9101546], [-2.9797182, 2.721741], [-3.2052834, 2.9934788], [-2.7451005, 2.622343]]) ] labels_2 = [np.array([1, 1, 1, 0, 0, 1, 1, 1])] self.assertRaises(NotImplementedError, glue.update, preds_2, labels_2) glue.reset() self.assertRaises(NotImplementedError, glue.update, preds, labels) def test_tensorflow_F1(self): metrics = METRICS('tensorflow') F1 = metrics['F1']() F1.hvd = hvd hvd.init() if hvd.rank() == 0: preds = [1, 1, 1, 1] labels = [0, 1, 1, 1] else: preds = [1, 1, 1, 1, 1, 1] labels = [1, 1, 1, 1, 1, 1] F1.update(preds, labels) self.assertEqual(F1.result(), 0.9) def test_squad_evaluate(self): evaluate.hvd = hvd hvd.init() label = [{'paragraphs':\\ [{'qas':[{'answers': [{'answer_start': 177, 'text': 'Denver Broncos'}, \\ {'answer_start': 177, 'text': 'Denver Broncos'}, \\ {'answer_start': 177, 'text': 'Denver Broncos'}], \\ 'question': 'Which NFL team represented the AFC at Super Bowl 50?', \\ 'id': '56be4db0acb8001400a502ec'}]}]}] preds = {'56be4db0acb8001400a502ec': 'Denver Broncos'} f1 = evaluate(preds, label) self.assertEqual(f1, 100.) dataset = [{'paragraphs':\\ [{'qas':[{'answers': [{'answer_start': 177, 'text': 'Denver Broncos'}, \\ {'answer_start': 177, 'text': 'Denver Broncos'}, \\ {'answer_start': 177, 'text': 'Denver Broncos'}], \\ 'question': 'Which NFL team represented the AFC at Super Bowl 50?', \\ 'id': '56be4db0acb8001400a502ec'}]}]}] predictions = {'56be4db0acb8001400a502ec': 'Denver Broncos'} f1_squad = evaluate_squad(dataset,predictions) self.assertEqual(f1_squad['f1'], 100.) self.assertEqual(f1_squad['exact_match'], 100.) def test_pytorch_F1(self): metrics = METRICS('pytorch') F1 = metrics['F1']() import horovod.torch as hvd F1.hvd = hvd hvd.init() F1.reset() if hvd.rank() == 0: preds = [1] labels = [2] else: preds = [1] labels = [1, 1] F1.update(preds, labels) self.assertEqual(F1.result(), 0.8) def test_tensorflow_topk(self): metrics = METRICS('tensorflow') top1 = metrics['topk']() top1.reset() self.assertEqual(top1.result(), 0) top2 = metrics['topk'](k=2) top3 = metrics['topk'](k=3) top1.hvd = hvd top2.hvd = hvd top3.hvd = hvd hvd.init() if hvd.rank() == 0: predicts = [[0, 0.2, 0.9, 0.3]] labels = [[0, 1, 0, 0]] single_predict = [0, 0.2, 0.9, 0.3] sparse_labels = [2] single_label = 2 else: predicts = [[0, 0.9, 0.8, 0]] labels = [[0, 0, 1, 0]] single_predict = [0, 0.2, 0.9, 0.3] sparse_labels = [2] single_label = 2 # test functionality of one-hot label top1.update(predicts, labels) top2.update(predicts, labels) top3.update(predicts, labels) self.assertEqual(top1.result(), 0.0) self.assertEqual(top2.result(), 0.5) self.assertEqual(top3.result(), 1) # test functionality of sparse label top1.reset() top2.reset() top3.reset() top1.update(predicts, sparse_labels) top2.update(predicts, sparse_labels) top3.update(predicts, sparse_labels) self.assertEqual(top1.result(), 0.5) self.assertEqual(top2.result(), 1) self.assertEqual(top3.result(), 1) # test functionality of single label top1.reset() top2.reset() top3.reset() top1.update(single_predict, single_label) top2.update(single_predict, single_label) top3.update(single_predict, single_label) self.assertEqual(top1.result(), 1) self.assertEqual(top2.result(), 1) self.assertEqual(top3.result(), 1) def test_tensorflow_mAP(self): metrics = METRICS('tensorflow') fake_dict = 'dog: 1' if hvd.rank() == 0: with open('anno_0.yaml', 'w', encoding = "utf-8") as f: f.write(fake_dict) while True: if os.path.exists('anno_0.yaml'): break mAP = metrics['mAP']('anno_0.yaml') mAP.hvd = hvd self.assertEqual(mAP.category_map_reverse['dog'], 1) detection = [ np.array([[5]]), np.array([[5]]), np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([['a', 'b']]), np.array([[]]), np.array([b'000000397133.jpg']) ] self.assertRaises(NotImplementedError, mAP.update, detection, ground_truth) detection = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787]]), np.array([[ 1., 1.]]) ] ground_truth = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[b'dog', b'dog']]), np.array([[]]), np.array([b'000000397133.jpg']) ] self.assertRaises(NotImplementedError, mAP.update, detection, ground_truth) mAP.result() self.assertEqual(format(mAP.result(), '.5f'), '0.00000') detection = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] detection_2 = [ np.array([[8]]), np.array([[[0.82776225, 0.5865939 , 0.8927653 , 0.6302338 ], [0.8375764 , 0.6424138 , 0.9055594 , 0.6921875 ], [0.57902956, 0.39394334, 0.8342961 , 0.5577197 ], [0.7949219 , 0.6513021 , 0.8472295 , 0.68427753], [0.809729 , 0.5947042 , 0.8539927 , 0.62916476], [0.7258591 , 0.08907133, 1. , 0.86224866], [0.43100086, 0.37782395, 0.8384069 , 0.5616918 ], [0.32005906, 0.84334356, 1. , 1. ]]]), np.array([[0.86698544, 0.7562499 , 0.66414887, 0.64498234,\\ 0.63083494,0.46618757, 0.3914739 , 0.3094324 ]]), np.array([[55., 55., 79., 55., 55., 67., 79., 82.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.56262296, 0.0015625 , 1. , 0.5431719 ], [0.16374707, 0.60728127, 0.813911 , 0.77823436], [0.5841452 , 0.21182813, 0.65156907, 0.24670312], [0.8056206 , 0.048875 , 0.90124124, 0.1553125 ], [0.6729742 , 0.09317187, 0.7696956 , 0.21203125], [0.3848478 , 0.002125 , 0.61522245, 0.303 ], [0.61548007, 0. , 0.7015925 , 0.097125 ], [0.6381967 , 0.1865625 , 0.7184075 , 0.22534375], [0.6274239 , 0.22104688, 0.71140516, 0.27134374], [0.39566743, 0.24370313, 0.43578455, 0.284375 ], [0.2673302 , 0.245625 , 0.3043794 , 0.27353126], [0.7137705 , 0.15429688, 0.726815 , 0.17114063], [0.6003747 , 0.25942189, 0.6438876 , 0.27320313], [0.68845433, 0.13501562, 0.714637 , 0.17245312], [0.69358313, 0.10959375, 0.7043091 , 0.12409375], [0.493911 , 0. , 0.72571427, 0.299 ], [0.69576114, 0.15107812, 0.70714283, 0.16332813], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([[]]), np.array([[44, 67, 1, 49, 51, 51, 79, 1, 47, 47, 51, 51,\\ 56, 50, 56, 56, 79, 57, 81]]), np.array([b'000000397133.jpg']) ] ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.9358696 , 0.07528409, 0.99891305, 0.25 ], [0.8242174 , 0.3309659 , 0.93508697, 0.47301137], [0.77413046, 0.22599432, 0.9858696 , 0.8179261 ], [0.32582608, 0.8575 , 0.98426086, 0.9984659 ], [0.77795655, 0.6268466 , 0.89930433, 0.73434657], [0.5396087 , 0.39053977, 0.8483913 , 0.5615057 ], [0.58473915, 0.75661933, 0.5998261 , 0.83579546], [0.80391306, 0.6129829 , 0.8733478 , 0.66201705], [0.8737391 , 0.6579546 , 0.943 , 0.7053693 ], [0.775 , 0.6549716 , 0.8227391 , 0.6882955 ], [0.8130869 , 0.58292615, 0.90526086, 0.62551135], [0.7844348 , 0.68735796, 0.98182607, 0.83329546], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62, 62, 67, 82, 52, 79, 81, 55, 55, 55, 55, 62, 55]]), np.array([b'000000037777.jpg']) ] mAP = metrics['mAP']() self.assertEqual(mAP.result(), 0) mAP.update(detection, ground_truth) mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.18182') mAP.update(detection_2, ground_truth_2) self.assertEqual(format(mAP.result(), '.5f'), '0.20347') mAP.reset() mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.18182') ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[[64, 62]]]), np.array([b'000000037777.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64]]), np.array([b'000000037700.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_2) detection_1 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000011.jpg']) ] self.assertRaises(ValueError, mAP.update, detection_1, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000012.jpg']) ] detection_2 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787]]), np.array([[ 1., 67., 51., 79., 47.]]) ] self.assertRaises(ValueError, mAP.update, detection_2, ground_truth_2) def test_tensorflow_VOCmAP(self): metrics = METRICS('tensorflow') fake_dict = 'dog: 1' if hvd.rank() == 0: with open('anno_1.yaml', 'w', encoding = "utf-8") as f: f.write(fake_dict) while True: if os.path.exists('anno_1.yaml'): break mAP = metrics['VOCmAP']('anno_1.yaml') mAP.hvd = hvd self.assertEqual(mAP.iou_thrs, 0.5) self.assertEqual(mAP.map_points, 0) self.assertEqual(mAP.category_map_reverse['dog'], 1) detection = [ np.array([[5]]), np.array([[5]]), np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([['a', 'b']]), np.array([[]]), np.array([b'000000397133.jpg']) ] self.assertRaises(NotImplementedError, mAP.update, detection, ground_truth) mAP = metrics['VOCmAP']() detection = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] detection_2 = [ np.array([[8]]), np.array([[[0.82776225, 0.5865939 , 0.8927653 , 0.6302338 ], [0.8375764 , 0.6424138 , 0.9055594 , 0.6921875 ], [0.57902956, 0.39394334, 0.8342961 , 0.5577197 ], [0.7949219 , 0.6513021 , 0.8472295 , 0.68427753], [0.809729 , 0.5947042 , 0.8539927 , 0.62916476], [0.7258591 , 0.08907133, 1. , 0.86224866], [0.43100086, 0.37782395, 0.8384069 , 0.5616918 ], [0.32005906, 0.84334356, 1. , 1. ]]]), np.array([[0.86698544, 0.7562499 , 0.66414887, 0.64498234,\\ 0.63083494,0.46618757, 0.3914739 , 0.3094324 ]]), np.array([[55., 55., 79., 55., 55., 67., 79., 82.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.56262296, 0.0015625 , 1. , 0.5431719 ], [0.16374707, 0.60728127, 0.813911 , 0.77823436], [0.5841452 , 0.21182813, 0.65156907, 0.24670312], [0.8056206 , 0.048875 , 0.90124124, 0.1553125 ], [0.6729742 , 0.09317187, 0.7696956 , 0.21203125], [0.3848478 , 0.002125 , 0.61522245, 0.303 ], [0.61548007, 0. , 0.7015925 , 0.097125 ], [0.6381967 , 0.1865625 , 0.7184075 , 0.22534375], [0.6274239 , 0.22104688, 0.71140516, 0.27134374], [0.39566743, 0.24370313, 0.43578455, 0.284375 ], [0.2673302 , 0.245625 , 0.3043794 , 0.27353126], [0.7137705 , 0.15429688, 0.726815 , 0.17114063], [0.6003747 , 0.25942189, 0.6438876 , 0.27320313], [0.68845433, 0.13501562, 0.714637 , 0.17245312], [0.69358313, 0.10959375, 0.7043091 , 0.12409375], [0.493911 , 0. , 0.72571427, 0.299 ], [0.69576114, 0.15107812, 0.70714283, 0.16332813], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([[]]), np.array([[44, 67, 1, 49, 51, 51, 79, 1, 47, 47, 51, 51,\\ 56, 50, 56, 56, 79, 57, 81]]), np.array([b'000000397133.jpg']) ] ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.9358696 , 0.07528409, 0.99891305, 0.25 ], [0.8242174 , 0.3309659 , 0.93508697, 0.47301137], [0.77413046, 0.22599432, 0.9858696 , 0.8179261 ], [0.32582608, 0.8575 , 0.98426086, 0.9984659 ], [0.77795655, 0.6268466 , 0.89930433, 0.73434657], [0.5396087 , 0.39053977, 0.8483913 , 0.5615057 ], [0.58473915, 0.75661933, 0.5998261 , 0.83579546], [0.80391306, 0.6129829 , 0.8733478 , 0.66201705], [0.8737391 , 0.6579546 , 0.943 , 0.7053693 ], [0.775 , 0.6549716 , 0.8227391 , 0.6882955 ], [0.8130869 , 0.58292615, 0.90526086, 0.62551135], [0.7844348 , 0.68735796, 0.98182607, 0.83329546], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62, 62, 67, 82, 52, 79, 81, 55, 55, 55, 55, 62, 55]]), np.array([b'000000037777.jpg']) ] self.assertEqual(mAP.result(), 0) mAP.update(detection, ground_truth) mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.18182') mAP.update(detection_2, ground_truth_2) self.assertEqual(format(mAP.result(), '.5f'), '0.20347') mAP.reset() mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.18182') ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[[64, 62]]]), np.array([b'000000037777.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64]]), np.array([b'000000037700.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_2) detection_1 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000011.jpg']) ] self.assertRaises(ValueError, mAP.update, detection_1, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000012.jpg']) ] detection_2 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787]]), np.array([[ 1., 67., 51., 79., 47.]]) ] self.assertRaises(ValueError, mAP.update, detection_2, ground_truth_2) def test_tensorflow_COCOmAP(self): metrics = METRICS('tensorflow') fake_dict = 'dog: 1' if hvd.rank() == 0: with open('anno_2.yaml', 'w', encoding = "utf-8") as f: f.write(fake_dict) while True: if os.path.exists('anno_2.yaml'): break mAP = metrics['COCOmAP']('anno_2.yaml') mAP.hvd = hvd self.assertEqual(mAP.category_map_reverse['dog'], 1) detection = [ np.array([[5]]), np.array([[5]]), np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([['a', 'b']]), np.array([[]]), np.array([b'000000397133.jpg']) ] self.assertRaises(NotImplementedError, mAP.update, detection, ground_truth) mAP = metrics['COCOmAP']() detection = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ], [0.62706745, 0.35748824, 0.6892729 , 0.41513762], [0.40032804, 0.01218696, 0.6924763 , 0.30341768], [0.62706745, 0.35748824, 0.6892729 , 0.41513762]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] detection_2 = [ np.array([[8]]), np.array([[[0.82776225, 0.5865939 , 0.8927653 , 0.6302338 ], [0.8375764 , 0.6424138 , 0.9055594 , 0.6921875 ], [0.57902956, 0.39394334, 0.8342961 , 0.5577197 ], [0.7949219 , 0.6513021 , 0.8472295 , 0.68427753], [0.809729 , 0.5947042 , 0.8539927 , 0.62916476], [0.7258591 , 0.08907133, 1. , 0.86224866], [0.43100086, 0.37782395, 0.8384069 , 0.5616918 ], [0.32005906, 0.84334356, 1. , 1. ]]]), np.array([[0.86698544, 0.7562499 , 0.66414887, 0.64498234,\\ 0.63083494,0.46618757, 0.3914739 , 0.3094324 ]]), np.array([[55., 55., 79., 55., 55., 67., 79., 82.]]) ] ground_truth = [ np.array([[[0.5633255 , 0.34003124, 0.69857144, 0.4009531 ], [0.56262296, 0.0015625 , 1. , 0.5431719 ], [0.16374707, 0.60728127, 0.813911 , 0.77823436], [0.5841452 , 0.21182813, 0.65156907, 0.24670312], [0.8056206 , 0.048875 , 0.90124124, 0.1553125 ], [0.6729742 , 0.09317187, 0.7696956 , 0.21203125], [0.3848478 , 0.002125 , 0.61522245, 0.303 ], [0.61548007, 0. , 0.7015925 , 0.097125 ], [0.6381967 , 0.1865625 , 0.7184075 , 0.22534375], [0.6274239 , 0.22104688, 0.71140516, 0.27134374], [0.39566743, 0.24370313, 0.43578455, 0.284375 ], [0.2673302 , 0.245625 , 0.3043794 , 0.27353126], [0.7137705 , 0.15429688, 0.726815 , 0.17114063], [0.6003747 , 0.25942189, 0.6438876 , 0.27320313], [0.68845433, 0.13501562, 0.714637 , 0.17245312], [0.69358313, 0.10959375, 0.7043091 , 0.12409375], [0.493911 , 0. , 0.72571427, 0.299 ], [0.69576114, 0.15107812, 0.70714283, 0.16332813], [0.4763466 , 0.7769531 , 0.54334897, 0.9675937 ]]]), np.array([[]]), np.array([[44, 67, 1, 49, 51, 51, 79, 1, 47, 47, 51, 51,\\ 56, 50, 56, 56, 79, 57, 81]]), np.array([b'000000397133.jpg']) ] ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.9358696 , 0.07528409, 0.99891305, 0.25 ], [0.8242174 , 0.3309659 , 0.93508697, 0.47301137], [0.77413046, 0.22599432, 0.9858696 , 0.8179261 ], [0.32582608, 0.8575 , 0.98426086, 0.9984659 ], [0.77795655, 0.6268466 , 0.89930433, 0.73434657], [0.5396087 , 0.39053977, 0.8483913 , 0.5615057 ], [0.58473915, 0.75661933, 0.5998261 , 0.83579546], [0.80391306, 0.6129829 , 0.8733478 , 0.66201705], [0.8737391 , 0.6579546 , 0.943 , 0.7053693 ], [0.775 , 0.6549716 , 0.8227391 , 0.6882955 ], [0.8130869 , 0.58292615, 0.90526086, 0.62551135], [0.7844348 , 0.68735796, 0.98182607, 0.83329546], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62, 62, 67, 82, 52, 79, 81, 55, 55, 55, 55, 62, 55]]), np.array([b'000000037777.jpg']) ] self.assertEqual(mAP.result(), 0) mAP.update(detection, ground_truth) mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.14149') mAP.update(detection_2, ground_truth_2) self.assertEqual(format(mAP.result(), '.5f'), '0.13366') mAP.reset() mAP.update(detection, ground_truth) self.assertEqual(format(mAP.result(), '.5f'), '0.14149') ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[[64, 62]]]), np.array([b'000000037777.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64]]), np.array([b'000000037700.jpg']) ] self.assertRaises(ValueError, mAP.update, detection, ground_truth_2) detection_1 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787 , 0.60418576, 0.35155892, 0.31158054]]), np.array([[ 1., 67., 51., 79., 47.]]) ] ground_truth_1 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000011.jpg']) ] self.assertRaises(ValueError, mAP.update, detection_1, ground_truth_1) ground_truth_2 = [ np.array([[[0.51508695, 0.2911648 , 0.5903478 , 0.31360796], [0.872 , 0.6190057 , 0.9306522 , 0.6591761 ]]]), np.array([[]]), np.array([[64, 62]]), np.array([b'000000012.jpg']) ] detection_2 = [ np.array([[[0.16117382, 0.59801614, 0.81511605, 0.7858219 ], [0.5589304 , 0. , 0.98301625, 0.520178 ]]]), np.array([[0.9267181 , 0.8510787]]), np.array([[ 1., 67., 51., 79., 47.]]) ] self.assertRaises(ValueError, mAP.update, detection_2, ground_truth_2) def test__accuracy(self): if hvd.rank() == 0: predicts1 = [1] labels1 = [0] predicts2 = [[0, 0]] labels2 = [[0, 1]] predicts3 = [[[0, 1], [0, 0], [0, 1]]] labels3 = [[[0, 1], [0, 1], [1, 0]]] predicts4 = [[0.2, 0.8]] labels4 = [0] else: predicts1 = [0, 1, 1] labels1 = [1, 1, 1] predicts2 = [[0, 0]] labels2 = [[1, 1]] predicts3 = [[[0, 1], [0, 1], [0, 1]]] labels3 = [[[1, 0], [1, 0], [1, 0]]] predicts4 = [[0.1, 0.9], [0.3, 0.7], [0.4, 0.6]] labels4 = [1, 0, 0] import horovod.tensorflow as hvd_tf metrics = METRICS('tensorflow') acc = metrics['Accuracy']() acc.hvd = hvd_tf acc.update(predicts1, labels1) acc_result = acc.result() self.assertEqual(acc_result, 0.5) acc.reset() acc.update(predicts2, labels2) self.assertEqual(acc.result(), 0.25) acc.reset() acc.update(predicts3, labels3) self.assertEqual(acc.result(), 0.25) acc.reset() acc.update(predicts4, labels4) self.assertEqual(acc.result(), 0.25) acc.reset() acc.update(1, 1) self.assertEqual(acc.result(), 1.0) wrong_predictions = [1, 0, 0] wrong_labels = [[0, 1, 1]] self.assertRaises(ValueError, acc.update, wrong_predictions, wrong_labels) import horovod.torch as hvd_torch hvd_torch.init() metrics = METRICS('pytorch') acc = metrics['Accuracy']() acc.hvd = hvd_torch acc.update(predicts1, labels1) acc_result = acc.result() self.assertEqual(acc_result, 0.5) acc.reset() acc.update(predicts2, labels2) self.assertEqual(acc.result(), 0.25) acc.reset() acc.update(predicts3, labels3) self.assertEqual(acc.result(), 0.25) acc.reset() acc.update(predicts4, labels4) self.assertEqual(acc.result(), 0.25) def test_mse(self): if hvd.rank() == 0: predicts1 = [1] labels1 = [0] predicts2 = [1, 1] labels2 = [0, 1] else: predicts1 = [0, 0, 1] labels1 = [1, 0, 0] predicts2 = [1, 1] labels2 = [1, 0] import horovod.tensorflow as hvd_tf metrics = METRICS('tensorflow') mse = metrics['MSE'](compare_label=False) mse.hvd = hvd_tf mse.update(predicts1, labels1) mse_result = mse.result() self.assertEqual(mse_result, 0.75) mse.update(predicts2, labels2) mse_result = mse.result() self.assertEqual(mse_result, 0.625) import horovod.torch as hvd_torch hvd_torch.init() metrics = METRICS('pytorch') mse = metrics['MSE']() mse.hvd = hvd_torch mse.update(predicts1, labels1) mse_result = mse.result() self.assertEqual(mse_result, 0.75) mse.update(predicts2, labels2) mse_result = mse.result() self.assertEqual(mse_result, 0.625) def test_mae(self): if hvd.rank() == 0: predicts1 = [1] labels1 = [0] predicts2 = [1, 1] labels2 = [1, 1] else: predicts1 = [0, 0, 1] labels1 = [1, 0, 0] predicts2 = [1, 1] labels2 = [1, 0] import horovod.tensorflow as hvd_tf metrics = METRICS('tensorflow') mae = metrics['MAE']() mae.hvd = hvd_tf mae.update(predicts1, labels1) mae_result = mae.result() self.assertEqual(mae_result, 0.75) if hvd.rank() == 1: mae.update(0, 1) mae_result = mae.result() self.assertEqual(mae_result, 0.8) mae.reset() mae.update(predicts2, labels2) mae_result = mae.result() self.assertEqual(mae_result, 0.25) import horovod.torch as hvd_torch hvd_torch.init() metrics = METRICS('pytorch') mae = metrics['MAE']() mae.hvd = hvd_torch mae.update(predicts1, labels1) mae_result = mae.result() self.assertEqual(mae_result, 0.75) mae.update(predicts2, labels2) mae_result = mae.result() self.assertEqual(mae_result, 0.5) self.assertRaises(AssertionError, mae.update, [1], [1, 2]) self.assertRaises(AssertionError, mae.update, 1, [1,2]) self.assertRaises(AssertionError, mae.update, [1, 2], [1]) self.assertRaises(AssertionError, mae.update, 1, np.array([1,2])) def test_rmse(self): if hvd.rank() == 0: predicts1 = [1] labels1 = [1] predicts2 = [1, 1] labels2 = [1, 0] else: predicts1 = [0, 0, 1] labels1 = [0, 0, 0] predicts2 = [1, 1] labels2 = [0, 0] import horovod.tensorflow as hvd_tf metrics = METRICS('tensorflow') rmse = metrics['RMSE']() rmse.hvd = hvd_tf rmse.update(predicts1, labels1) rmse_result = rmse.result() self.assertEqual(rmse_result, 0.5) rmse.reset() rmse.update(predicts2, labels2) rmse_result = rmse.result() self.assertAlmostEqual(rmse_result, np.sqrt(0.75)) import horovod.torch as hvd_torch hvd_torch.init() metrics = METRICS('pytorch') rmse = metrics['RMSE']() rmse.hvd = hvd_torch rmse.update(predicts1, labels1) rmse_result = rmse.result() self.assertEqual(rmse_result, 0.5) rmse.update(predicts2, labels2) rmse_result = rmse.result() self.assertAlmostEqual(rmse_result, np.sqrt(0.5)) def test_loss(self): if hvd.rank() == 0: predicts1 = [1] labels1 = [0] predicts2 = [1, 0, 1] labels2 = [1, 0, 0] predicts3 = [1, 0] labels3 = [0, 1] else: predicts1 = [0, 0, 1] labels1 = [1, 0, 0] predicts2 = [1] labels2 = [0] predicts3 = [0, 1] labels3 = [0, 0] import horovod.tensorflow as hvd_tf metrics = METRICS('tensorflow') loss = metrics['Loss']() loss.hvd = hvd_tf loss.update(predicts1, labels1) loss_result = loss.result() self.assertEqual(loss_result, 0.5) loss.update(predicts2, labels2) loss_result = loss.result() self.assertEqual(loss_result, 0.625) loss.reset() loss.update(predicts3, labels3) self.assertEqual(loss.result(), 0.5) import horovod.torch as hvd_torch hvd_torch.init() metrics = METRICS('pytorch') loss = metrics['Loss']() loss.hvd = hvd_torch loss.update(predicts1, labels1) loss_result = loss.result() self.assertEqual(loss_result, 0.5) loss.update(predicts2, labels2) loss_result = loss.result() self.assertEqual(loss_result, 0.625) loss.reset() loss.update(predicts3, labels3) self.assertEqual(loss.result(), 0.5) if __name__ == "__main__": unittest.main() """ with open('fake_ut.py', 'w', encoding="utf-8") as f: f.write(fake_ut) class TestDistributed(unittest.TestCase): @classmethod def setUpClass(cls): build_fake_ut() @classmethod def tearDownClass(cls): os.remove('fake_ut.py') shutil.rmtree('./saved', ignore_errors = True) shutil.rmtree('runs', ignore_errors = True) @unittest.skipIf(tensorflow.version.VERSION >= '2.8.0', "Only supports tf 2.7.0 or below") def test_distributed(self): distributed_cmd = 'horovodrun -np 2 python fake_ut.py' p = subprocess.Popen(distributed_cmd, preexec_fn = os.setsid, stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True) # nosec try: out, error = p.communicate() matches = re.findall(r'FAILED', error.decode('utf-8')) self.assertEqual(matches, []) matches = re.findall(r'OK', error.decode('utf-8')) self.assertTrue(len(matches) > 0) except KeyboardInterrupt: os.killpg(os.getpgid(p.pid), signal.SIGKILL) assert 0 if __name__ == "__main__": unittest.main()

43.729675

96

0.473112

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43,030

4.223368

0.098105

0.055132

0.023528

0.015353

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0.824535

0.796022

0.78022

0.770899

0.762873

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0.324909

0.377434

43,030

983

97

43.774161

0.423943

0.000953

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0.725191

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0.019629

0.971952

0.16719

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0.098146

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false

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0.030534

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0.035987

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1

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null

0

10

fb88ed3aa9e5a1c09af74d57352a68aea9d75307

4,943

py

Python

Diagnostics/plotting.py

bongiovimatthew/jigsaw-rl

e9589a78b62a7645fe9bc054f0411230eb249acf

[ "MIT" ]

1

2018-09-11T23:50:38.000Z

Diagnostics/plotting.py

bongiovimatthew/jigsaw-rl

e9589a78b62a7645fe9bc054f0411230eb249acf

[ "MIT" ]

6

2018-09-11T23:46:57.000Z

2018-09-15T00:33:45.000Z

Diagnostics/plotting.py

bongiovimatthew/jigsaw-rl

e9589a78b62a7645fe9bc054f0411230eb249acf

[ "MIT" ]

null

import numpy as np import pandas as pd from collections import namedtuple from matplotlib import pyplot as plt EpisodeStats = namedtuple( "Stats", ["episode_lengths", "episode_rewards", "episode_running_variance"]) TimestepStats = namedtuple("Stats", ["cumulative_rewards", "regrets"]) def plot_episode_stats(stats, smoothing_window=10, hideplot=False): # Plot the episode length over time fig1 = plt.figure(figsize=(10, 5)) plt.plot(stats.episode_lengths) plt.xlabel("Episode") plt.ylabel("Episode Length") plt.title("Episode Length over Time") if hideplot: plt.close(fig1) else: plt.show(fig1) # Plot the episode reward over time fig2 = plt.figure(figsize=(10, 5)) rewards_smoothed = pd.Series(stats.episode_rewards).rolling( smoothing_window, min_periods=smoothing_window).mean() plt.plot(rewards_smoothed) plt.xlabel("Episode") plt.ylabel("Episode Reward (Smoothed)") plt.title("Episode Reward over Time (Smoothed over window size {})".format(smoothing_window)) if hideplot: plt.close(fig2) else: plt.show(fig2) return fig1, fig2 def plot_pgresults(stats, smoothing_window=20, hideplot=False): # Plot the episode length over time fig1 = plt.figure(figsize=(10, 5)) plt.plot(stats.episode_lengths) plt.xlabel("Episode") plt.ylabel("Episode Length") plt.title("Episode Length over Time") if hideplot: plt.close(fig1) else: plt.show(fig1) # Plot the episode reward over time fig2 = plt.figure(figsize=(10, 5)) rewards_smoothed = pd.Series(stats.episode_rewards).rolling( smoothing_window, min_periods=smoothing_window).mean() plt.plot(rewards_smoothed) plt.xlabel("Episode") plt.ylabel("Episode Reward (Smoothed)") plt.title("Episode Reward over Time (Smoothed over window size {})".format(smoothing_window)) if hideplot: plt.close(fig2) else: plt.show(fig2) # Plot time steps and episode number fig3 = plt.figure(figsize=(10, 5)) plt.plot(stats.episode_running_variance) plt.xlabel("Episode") plt.ylabel("Running Variance") plt.title("Running Variance over Time") if hideplot: plt.close(fig3) else: plt.show(fig3) # Plot time steps and episode number fig4 = plt.figure(figsize=(10, 5)) plt.plot(np.arange(len(stats.episode_lengths)), np.cumsum(stats.episode_lengths)) plt.xlabel("Episode") plt.ylabel("Cumulative Episode Length") plt.title("Cumulative Episode Length over Time") if hideplot: plt.close(fig4) else: plt.show(fig4) return fig1, fig2, fig3, fig4 def plot_dqnresults(stats, smoothing_window=20, hideplot=False): # Plot the episode length over time fig1 = plt.figure(figsize=(10, 5)) plt.plot(stats.episode_lengths) plt.xlabel("Episode") plt.ylabel("Episode Length") plt.title("Episode Length over Time") if hideplot: plt.close(fig1) else: plt.show(fig1) # Plot the episode reward over time fig2 = plt.figure(figsize=(10, 5)) rewards_smoothed = pd.Series(stats.episode_rewards).rolling( smoothing_window, min_periods=smoothing_window).mean() plt.plot(rewards_smoothed) plt.xlabel("Episode") plt.ylabel("Episode Reward (Smoothed)") plt.title("Episode Reward over Time (Smoothed over window size {})".format(smoothing_window)) if hideplot: plt.close(fig2) else: plt.show(fig2) # Plot time steps and episode number fig4 = plt.figure(figsize=(10, 5)) plt.plot(np.arange(len(stats.episode_lengths)), np.cumsum(stats.episode_lengths)) plt.xlabel("Episode") plt.ylabel("Cumulative Episode Length") plt.title("Cumulative Episode Length over Time") if hideplot: plt.close(fig4) else: plt.show(fig4) return fig1, fig2, fig3, fig4 def plot_reward_regret(stats, smoothing_window=1, hideplot=False): # Plot the cumulative reward over time fig1 = plt.figure(figsize=(10, 5)) plt.plot(stats.cumulative_rewards) plt.xlabel("Timestep") plt.ylabel("Cumulative Reward") plt.title("Cumulative Reward over Timestep") if hideplot: plt.close(fig1) else: plt.show(fig1) # Plot the regret over time fig2 = plt.figure(figsize=(10, 5)) plt.plot(stats.regrets) plt.xlabel("Timestep") plt.ylabel("Regret") plt.title("Regret over Timestep") if hideplot: plt.close(fig2) else: plt.show(fig2) return fig1, fig2 def plot_arm_rewards(y, hideplot=False): N = len(y) x = range(N) width = 1/1.5 fig1 = plt.figure(figsize=(10, 5)) plt.bar(x, y, width) plt.xlabel("Arm") plt.ylabel("Probability") plt.title("Arm's Reward Distribution") if hideplot: plt.close(fig1) else: plt.show(fig1) return fig1

28.572254

97

0.664374

651

4,943

4.970814

0.121352

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4,943

172

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null

0

1

0

1

0

null

0

7

fbb0c7886ab94aaa1e00208dd268bcd5ede401b5

127

py

Python

gsfpy/gsfSBSensorSpecific.py

irewolepeter/gsfpy_USM_Implementation

c4614ac3f7d833eb86ea38c7708108b130f96612

[ "MIT" ]

7

2020-07-01T07:12:19.000Z

2022-01-20T20:39:57.000Z

gsfpy/gsfSBSensorSpecific.py

irewolepeter/gsfpy_USM_Implementation

c4614ac3f7d833eb86ea38c7708108b130f96612

[ "MIT" ]

36

2020-06-23T09:10:15.000Z

2022-03-22T10:27:58.000Z

gsfpy/gsfSBSensorSpecific.py

irewolepeter/gsfpy_USM_Implementation

c4614ac3f7d833eb86ea38c7708108b130f96612

[ "MIT" ]

2

2021-02-07T13:21:52.000Z

2021-06-24T19:16:16.000Z

from gsfpy import mirror_default_gsf_version_submodule mirror_default_gsf_version_submodule(globals(), "gsfSBSensorSpecific")

31.75

70

0.889764

15

127

7

0.666667

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0.304762

0.438095

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127

3

71

42.333333

0.875

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null

0

1

0

1

0

7

837707f5f63be25a4ebf9fc9fa14b42c0c9e9b84

22

py

Python

test.py

CCPPSS/python

575659af9257038aa7d1343a19787c1569a66803

[ "MulanPSL-1.0" ]

null

test.py

CCPPSS/python

575659af9257038aa7d1343a19787c1569a66803

[ "MulanPSL-1.0" ]

null

test.py

CCPPSS/python

575659af9257038aa7d1343a19787c1569a66803

[ "MulanPSL-1.0" ]

null

print('c') print('c')

7.333333

10

0.545455

4

22

3

0.5

1

0

0.090909

22

2

11

0.6

0

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0.090909

0

1

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true

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null

1

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1

0

1

0

null

0

1

0

1

0

7

839c31c6f8aba804e3537751511a0b9123504f15

2,250

py

Python

exam/SandClock.py

yani-valeva/Programming-Basics-Python

c553d331ffd210d362df0098bedf28e125a65dbf

[ "MIT" ]

null

exam/SandClock.py

yani-valeva/Programming-Basics-Python

c553d331ffd210d362df0098bedf28e125a65dbf

[ "MIT" ]

null

exam/SandClock.py

yani-valeva/Programming-Basics-Python

c553d331ffd210d362df0098bedf28e125a65dbf

[ "MIT" ]

null

size = int(input()) hours = int(input()) question = 1 current_size = size current_hour = hours if hours == 0: print('*' + ' *' * (current_size - 1)) else: print('-' + ' -' * (current_size - 1)) for i in range(1, current_hour): current_size = current_size - 1 if i % 2 == 1: print('?' * question + '- ' * (current_size - 1) + '-' + '?' * question) else: print(' ' * question + '- ' * (current_size - 1) + '-' + ' ' * question) question = question + 1 current_size = current_size - 1 is_even = True if hours % 2 == 0: is_even = False if hours == 0: is_even = True sec_size = size - (hours + 1) for i in range(1, sec_size + 1): if is_even == True: print('?' * question + '* ' * (current_size - 1) + '*' + '?' * question) is_even = False else: print(' ' * question + '* ' * (current_size - 1) + '*' + ' ' * question) is_even = True if hours == 0 and i == sec_size - 1: current_size = current_size - 1 question = question + 1 break current_size = current_size - 1 question = question + 1 if is_even == True: print('?' * question + 'o' + '?' * question) is_even = False else: print(' ' * question + 'o' + ' ' * question) is_even = True current_size = current_size + 1 question = question - 1 for i in range(1, sec_size + 1): if is_even == True: print('?' * question + '- ' * (current_size - 1) + '-' + '?' * question) is_even = False else: print(' ' * question + '- ' * (current_size - 1) + '-' + ' ' * question) is_even = True if hours == 0 and i == sec_size - 1: current_size = current_size + 1 question = question - 1 break current_size = current_size + 1 question = question - 1 for i in range(1, current_hour): if is_even == True: print('?' * question + '* ' * (current_size - 1) + '*' + '?' * question) is_even = False else: print(' ' * question + '* ' * (current_size - 1) + '*' + ' ' * question) is_even = True current_size = current_size + 1 question = question - 1 if hours == 0: print('-' + ' -' * (current_size - 1)) else: print('*' + ' *' * (current_size - 1))

28.125

81

0.523556

273

2,250

4.124542

0.091575

0.283304

0.213144

0.248668

0.888988

0.846359

0.793961

0.708703

0.678508

0.676732

0

0.029544

0.308

2,250

80

82

28.125

0.693642

0

0.857143

0

0.025766

0

1

0

false

0

0.2

0

null

1

0

1

0

1

0

null

0

9

790214d60cffa2a494c5dcf9a8ff558464d131ab

149

py

Python

src/aijack/defense/ckks/__init__.py

luoshenseeker/AIJack

4e871a5b3beb4b7c976d38060d6956efcebf880d

[ "MIT" ]

24

2021-11-17T02:16:47.000Z

2022-03-27T01:04:08.000Z

src/aijack/defense/ckks/__init__.py

luoshenseeker/AIJack

4e871a5b3beb4b7c976d38060d6956efcebf880d

[ "MIT" ]

9

2021-12-03T06:09:27.000Z

2022-03-29T06:33:53.000Z

src/aijack/defense/ckks/__init__.py

luoshenseeker/AIJack

4e871a5b3beb4b7c976d38060d6956efcebf880d

[ "MIT" ]

5

2022-01-12T09:58:04.000Z

2022-03-17T09:29:04.000Z

from .encoder import CKKSEncoder # noqa: F401 from .encrypter import CKKSEncrypter # noqa: F401 from .plaintext import CKKSPlaintext # noqa: F401

37.25

50

0.778523

18

149

6.444444

0.555556

0.206897

0

0.072

0.161074

149

3

51

49.666667

0.856

0.214765

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

791a8c2f507bf3ec800896c79cb0eb3eda872906

61

py

Python

nodes/IGGrid/__init__.py

bertrandboudaud/imagegraph

7c95b645edeb1a68d56c6c3b19f1ff6fde413afc

[ "MIT" ]

null

nodes/IGGrid/__init__.py

bertrandboudaud/imagegraph

7c95b645edeb1a68d56c6c3b19f1ff6fde413afc

[ "MIT" ]

null

nodes/IGGrid/__init__.py

bertrandboudaud/imagegraph

7c95b645edeb1a68d56c6c3b19f1ff6fde413afc

[ "MIT" ]

null

from . import IGGrid def get(): return IGGrid.IGGrid()

10.166667

26

0.655738

8

61

5

0.75

0

0.229508

61

5

27

12.2

0.851064

0

1

0.333333

true

0

0.333333

1

0

1

0

null

0

1

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null

0

1

0

1

0

7