xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

e2a3a5e193462cd9cfc3f8e77576ef311f0d6d70

1,050

py

Python

async_sched/client/request_schedules.py

justengel/async_sched

f980722d51d15025522b2265426b0188ff368418

[ "MIT" ]

1

2020-10-19T13:36:20.000Z

async_sched/client/request_schedules.py

justengel/async_sched

f980722d51d15025522b2265426b0188ff368418

[ "MIT" ]

null

async_sched/client/request_schedules.py

justengel/async_sched

f980722d51d15025522b2265426b0188ff368418

[ "MIT" ]

null

""" module to run with the -m flag python -m async_sched.client.request_schedules """ import argparse from async_sched.client.client import request_schedules from async_sched.utils import DEFAULT_HOST, DEFAULT_PORT __all__ = ['NAME', 'get_argparse', 'main'] NAME = 'request_schedules' def get_argparse(host: str = DEFAULT_HOST, port: int = DEFAULT_PORT, parent_parser=None): if parent_parser is None: p = argparse.ArgumentParser(description='Request and list the running schedules') else: p = parent_parser.add_parser(NAME, help='Request and list the running schedules') p.add_argument('--host', type=str, default=host) p.add_argument('--port', type=int, default=port) return p def main(host: str = DEFAULT_HOST, port: int = DEFAULT_PORT, **kwargs): request_schedules((host, port)) if __name__ == '__main__': P = get_argparse() ARGS = P.parse_args() KWARGS = {n: getattr(ARGS, n) for n in dir(ARGS) if not n.startswith('_') and getattr(ARGS, n, None) is not None} main(**KWARGS)

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null

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e2a4885ec926f3d640fc765abc70c06983834ccb

2,156

py

Python

sns/api/reddit/reddit.py

kylepw/panner

482ef8e8c1e8d9464d7dc8e4df5b5d9b58e83d35

[ "MIT" ]

2

2019-07-20T01:48:20.000Z

2019-11-15T06:50:54.000Z

sns/api/reddit/reddit.py

kylepw/panner

482ef8e8c1e8d9464d7dc8e4df5b5d9b58e83d35

[ "MIT" ]

5

2020-02-12T08:58:06.000Z

2021-09-22T17:56:42.000Z

sns/api/reddit/reddit.py

kylepw/panner

482ef8e8c1e8d9464d7dc8e4df5b5d9b58e83d35

[ "MIT" ]

null

from datetime import datetime import logging import os from praw import Reddit as PrawReddit from prawcore.exceptions import NotFound import pytz logger = logging.getLogger(__name__) class Reddit: def __init__(self, client_id=None, client_secret=None, user_agent=None): self.client_id = client_id or os.getenv('REDDIT_CLIENT_ID') self.client_secret = client_secret or os.getenv('REDDIT_CLIENT_SECRET') self.user_agent = user_agent or os.getenv('REDDIT_USER_AGENT') self.api = PrawReddit( client_id=self.client_id, client_secret=self.client_secret, user_agent=self.user_agent, read_only=True, ) def get_comments_submissions(self, username, num=5): """Return max `num` of comments and submissions by `username`.""" coms = [ dict( title=comment.link_title, text=comment.body_html, subreddit=comment.subreddit_name_prefixed, url=comment.link_url, created=datetime.fromtimestamp(comment.created_utc, pytz.utc), ) for comment in self.api.redditor(username).comments.new(limit=num) ] subs = [ dict( title=submission.title, text=submission.selftext_html, subreddit=submission.subreddit_name_prefixed, url=submission.url, created=datetime.fromtimestamp(submission.created_utc, pytz.utc), ) for submission in self.api.redditor(username).submissions.new(limit=num) ] return coms + subs if len(coms + subs) < num else (coms + subs)[:num] def profile_image_url(self, username): """Return URL of user's avatar image.""" try: return self.api.redditor(username).icon_img except NotFound: logger.exception('Failed to fetch Reddit profile image of %s', username) return None @staticmethod def profile_url(username): """Return URL of user's profile.""" return 'https://www.reddit.com/user/%s' % username

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null

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e2a8d2bec3d6270cbb856eb6bae1fa43dddb9949

1,736

py

Python

tests/test_lsp.py

WeixinYang/DatasetLoader

d6e800d6a9cca8809d7dab88a6a13a7916ef272d

[ "Apache-2.0" ]

1

2021-08-16T14:14:40.000Z

tests/test_lsp.py

WeixinYang/DatasetLoader

d6e800d6a9cca8809d7dab88a6a13a7916ef272d

[ "Apache-2.0" ]

1

2020-10-12T20:56:21.000Z

tests/test_lsp.py

WeixinYang/DatasetLoader

d6e800d6a9cca8809d7dab88a6a13a7916ef272d

[ "Apache-2.0" ]

1

2021-06-14T10:30:08.000Z

import os.path import pytest from datasetloader import LSP from datasetloader import LSPExtended from . import DS_PATH class TestLSP(): def test_LSP(self): # test loading both, full sized and small images folders = ("lsp", "lsp_small") for ds in folders: lsp = LSP(os.path.join(DS_PATH, ds)) # check dataset sizes and get_data accessors on different elements assert lsp.get_data("image-filenames").shape == (2000, ) assert lsp.get_data("keypoints", "train").shape == (1000, 14, 3) d = lsp.get_data(("image-filenames", "keypoints"), "test") assert d[0].shape == (1000, ) assert d[1].shape == (1000, 14, 3) # test iterator access it = lsp.get_iterator(("image-filenames", "keypoints"), "train") filename, keypoints = next(it) # check we got the correct first element assert isinstance(filename, str) assert keypoints.shape == (14, 3) def test_LSPExtended(self): lsp = LSPExtended(os.path.join(DS_PATH, "lsp_extended")) # check dataset sizes and get_data accessors on different elements assert lsp.get_data("image-filenames").shape == (10000, ) assert lsp.get_data("keypoints").shape == (10000, 14, 3) with pytest.raises(Exception): lsp.get_data("image-filenames", "train") lsp = LSPExtended(os.path.join(DS_PATH, "lsp_extended_improved"), improved=True) # check dataset sizes and get_data accessors on different elements assert lsp.get_data("image-filenames").shape == (9428, ) assert lsp.get_data("keypoints").shape == (9428, 14, 3)

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null

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null

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0

e2aefdb5d4c4918146034a0834daf3d3d9bd181b

1,173

py

Python

website/python/app.py

man-r/DimensionsLab

c94c3aec0d52326ad522a6fa41d43ec3bde87d74

[ "MIT" ]

null

website/python/app.py

man-r/DimensionsLab

c94c3aec0d52326ad522a6fa41d43ec3bde87d74

[ "MIT" ]

1

2022-03-24T06:13:52.000Z

website/python/app.py

man-r/DimensionsLab

c94c3aec0d52326ad522a6fa41d43ec3bde87d74

[ "MIT" ]

null

from flask import Flask from flask_restful import Api, Resource, reqparse app = Flask(__name__) api = Api(app) users = [ { "name": "Nicholas", "age": 42, "occupation": "Network Engineer" }, { "name": "Elvin", "age": 32, "occupation": "Doctor" }, { "name": "Jass", "age": 22, "occupation": "Web Developer" } ] class User(Resource): def get(self, name): for user in users: if (name == user["name"]): return user, 200 return "User not found", 404 def post(self, name): parser = reqparse.RequestParser() parser.add_argument("age") parser.add_argument("occupation") args = parser.parse_args() for user in users: if (name == user["name"]): return "User with the name {} already exist".format(name), 400 user = { "name": name, "age": args["age"], "occupation": args["occupation"] } users.append(user) return user, 201 def delete(self, name): global users users = [user for user in users if user["name"] != name] return "{} is deleted.".format(name), 200 api.add_resource(User, "/user/<string:name>") app.run(debug=True)

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null

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null

0

1

0

e2af09249eabdf6c6cfac1108013ff5630a16a85

371

py

Python

src/applications/reviews/urls.py

Alex-T13/sxw_data_conversion

ae70198960af1af004ad28b73d6e885c5afa74c2

[ "MIT" ]

null

src/applications/reviews/urls.py

Alex-T13/sxw_data_conversion

ae70198960af1af004ad28b73d6e885c5afa74c2

[ "MIT" ]

null

src/applications/reviews/urls.py

Alex-T13/sxw_data_conversion

ae70198960af1af004ad28b73d6e885c5afa74c2

[ "MIT" ]

null

from django.urls import path from applications.reviews import views urlpatterns = [ path('', views.AllPostView.as_view(), name='reviews'), path('add_post', views.AddPostView.as_view(), name='add_post'), path('post/<int:pk>', views.ShowPostView.as_view(), name='post'), path('update_post/<int:pk>', views.UpdatePostView.as_view(), name='update_post'), ]

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null

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null

0

1

0

e2af6e967078f9ead2d03be919925056b558ae89

13,207

py

Python

tests/tests_with_server_and_cached_results/test_planner/test_canvas.py

aquariumbio/trident

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

5

2019-01-21T11:12:05.000Z

2020-03-05T20:52:14.000Z

tests/tests_with_server_and_cached_results/test_planner/test_canvas.py

aquariumbio/pydent

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

28

2020-11-18T02:07:09.000Z

2021-06-08T15:49:41.000Z

tests/tests_with_server_and_cached_results/test_planner/test_canvas.py

aquariumbio/trident

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

2

2021-02-27T19:23:45.000Z

2021-09-14T10:29:07.000Z

import pytest from pydent.planner import Planner from pydent.planner import PlannerException from pydent.planner.utils import get_subgraphs def test_canvas_create(session): canvas = Planner(session) canvas.create() assert canvas.plan.id def test_raises_exception_wiring_with_no_afts(session): canvas = Planner(session) op1 = canvas.create_operation_by_name("Make PCR Fragment", category="Cloning") op2 = canvas.create_operation_by_name("Check Plate", category="Cloning") with pytest.raises(PlannerException): canvas._set_wire(op1.outputs[0], op2.inputs[0]) def test_add_wire(session): canvas = Planner(session) assert len(canvas.plan.wires) == 0 op1 = canvas.create_operation_by_name("Make PCR Fragment", category="Cloning") op2 = canvas.create_operation_by_name("Rehydrate Primer", category="Cloning") canvas.add_wire(op2.outputs[0], op1.input("Forward Primer")) assert len(canvas.plan.wires) == 1 wire = canvas.plan.wires[0] assert ( wire.source.allowable_field_type.sample_type_id == wire.destination.allowable_field_type.sample_type_id ) assert ( wire.source.allowable_field_type.object_type_id == wire.destination.allowable_field_type.object_type_id ) def test_add_wire_sets_sample_from_destination(session): """When adding a wire, the sample should be set from the destination to the source.""" session.set_verbose(True) canvas = Planner(session) assert len(canvas.plan.wires) == 0 p = session.Sample.one( query=dict(sample_type_id=session.SampleType.find_by_name("Primer").id) ) destination = canvas.create_operation_by_name( "Make PCR Fragment", category="Cloning" ) source = canvas.create_operation_by_name("Rehydrate Primer", category="Cloning") canvas.set_field_value(destination.input("Forward Primer"), sample=p) assert destination.input("Forward Primer").sample is p canvas.add_wire(source.outputs[0], destination.input("Forward Primer")) assert source.outputs[0].sample.id == p.id def test_add_wire_sets_sample_from_source(session): session.set_verbose(True) canvas = Planner(session) assert len(canvas.plan.wires) == 0 p = session.Sample.one( query=dict(sample_type_id=session.SampleType.find_by_name("Primer").id) ) destination = canvas.create_operation_by_name( "Make PCR Fragment", category="Cloning" ) source = canvas.create_operation_by_name("Rehydrate Primer", category="Cloning") canvas.set_field_value(source.outputs[0], sample=p) canvas.add_wire(source.outputs[0], destination.input("Forward Primer")) assert destination.input("Forward Primer").sample.id == p.id def test_collect_matching_afts(session): canvas = Planner(session) op1 = canvas.create_operation_by_name("Check Plate", category="Cloning") op2 = canvas.create_operation_by_name("E Coli Lysate", category="Cloning") afts = canvas._collect_matching_afts(op1, op2) print(afts) def test_raise_exception_if_wiring_two_inputs(session): canvas = Planner(session) assert len(canvas.plan.wires) == 0 op1 = canvas.create_operation_by_name("Check Plate", category="Cloning") op2 = canvas.create_operation_by_name("Check Plate", category="Cloning") with pytest.raises(PlannerException): canvas.add_wire(op1.inputs[0], op2.inputs[0]) def test_raise_exception_if_wiring_two_outputs(session): canvas = Planner(session) assert len(canvas.plan.wires) == 0 op1 = canvas.create_operation_by_name("Check Plate", category="Cloning") op2 = canvas.create_operation_by_name("Check Plate", category="Cloning") with pytest.raises(PlannerException): canvas.add_wire(op1.outputs[0], op2.outputs[0]) def test_canvas_add_op(session): canvas = Planner(session) canvas.create_operation_by_name("Yeast Transformation") canvas.create_operation_by_name("Yeast Antibiotic Plating") canvas.quick_wire_by_name("Yeast Transformation", "Yeast Antibiotic Plating") canvas.create() p = session.Plan.find(canvas.plan.id) pass def test_canvas_quick_create_chain(session): canvas = Planner(session) canvas.chain( "Yeast Transformation", "Check Yeast Plate", "Yeast Overnight Suspension" ) assert len(canvas.plan.operations) == 3 assert len(canvas.plan.wires) == 2, "There should be two operations" def test_chain_run_gel(session): canvas = Planner(session) canvas.chain("Make PCR Fragment", "Run Gel", category="Cloning") def test_quick_chain_to_existing_operation(session): canvas = Planner(session) op = canvas.create_operation_by_name("Yeast Transformation") canvas.chain(op, "Check Yeast Plate") assert len(canvas.plan.wires) == 1 def test_quick_chain_to_existing_operation_too_many_times(session): canvas = Planner(session) op = canvas.create_operation_by_name("Yeast Transformation") op1 = canvas.chain(op, "Check Yeast Plate")[-1] with pytest.raises(PlannerException): canvas.chain("Yeast Transformation", op1) assert len(canvas.plan.wires) == 1 def test_canvas_chaining(session): canvas = Planner(session) canvas.browser.log.set_verbose(True) ops = canvas.chain( "Assemble Plasmid", "Transform Cells", "Plate Transformed Cells", "Check Plate", category="Cloning", ) assert len(canvas.plan.wires) == 3 new_ops = [] for i in range(3): new_ops += canvas.chain( ops[-1], ("E Coli Lysate", "Cloning"), "E Coli Colony PCR" )[1:] assert len(canvas.plan.wires) == 2 * 3 + 3 def test_layout_edges_and_nodes(session): canvas = Planner(session) canvas.chain( "Yeast Transformation", "Check Yeast Plate", "Yeast Overnight Suspension" ) G = canvas.layout.nxgraph edges = list(G.edges) assert len(edges) == 2, "There should only be 2 edges/wires in the graph/plan" assert ( len(G.nodes) == 3 ), "There should only be 3 nodes/Operations in the graph/plan" assert edges[0][1] == edges[1][0], "Check Yeast Plate should be in both wires" def test_load_canvas(session): canvas = Planner(session.Plan.one()) assert canvas is not None assert canvas.plan is not None assert canvas.plan.operations is not None def test_proper_setting_of_object_types(session): canvas = Planner(session) yeast = session.Sample.where( {"sample_type_id": session.SampleType.find_by_name("Yeast Strain").id}, opts={"limit": 10}, )[-1] streak = canvas.create_operation_by_name("Streak Plate", category="Yeast") glycerol = canvas.create_operation_by_name("Yeast Glycerol Stock", category="Yeast") canvas.set_field_value(glycerol.inputs[0], sample=yeast) canvas.set_field_value(streak.inputs[0], sample=yeast) mating = canvas.create_operation_by_name("Yeast Mating") canvas.add_wire(streak.outputs[0], mating.inputs[0]) canvas.add_wire(glycerol.outputs[0], mating.inputs[1]) assert ( mating.inputs[0].allowable_field_type.object_type.name == "Divided Yeast Plate" ) assert ( mating.inputs[1].allowable_field_type.object_type.name == "Yeast Glycerol Stock" ) def test_annotate(session): canvas = Planner(session) a = canvas.annotate("This is my annotation", 10, 20, 110, 100) assert a["x"] == 10 assert a["y"] == 20 anchor = a["anchor"] assert anchor["x"] == 110 assert anchor["y"] == 100 def test_annotate_layout(session): canvas = Planner(session) ops = canvas.chain("Make PCR Fragment", "Run Gel", category="Cloning") canvas.layout.topo_sort() canvas.layout.move(100, 200) a = canvas.annotate_above_layout("This is an annotation", 100, 50) anchor = a["anchor"] xmidpoint = a["x"] + anchor["x"] / 2 ybottom = a["y"] + anchor["y"] assert xmidpoint == 100 + canvas.layout.BOX_WIDTH / 2 assert ybottom == 200 - canvas.layout.BOX_DELTA_Y / 2 canvas.plan.name = "annotation test" canvas.create() print(canvas.url) def test_routing_graph(session): canvas = Planner(session) ops = canvas.chain( "Rehydrate Primer", "Make PCR Fragment", "Run Gel", "Extract Gel Slice", "Purify Gel Slice", "Assemble Plasmid", category="Cloning", ) routing_graph = canvas._routing_graph() print(get_subgraphs(routing_graph)) def test_quick_wire_to_input_array(session): canvas = Planner(session) ops = canvas.chain("Purify Gel Slice", "Assemble Plasmid", category="Cloning") canvas.chain("Purify Gel Slice", ops[-1], category="Cloning") assert len(canvas.plan.operations) == 3 assert len(canvas.plan.wires) == 2 def test_quick_wire_to_input_array_and_then_set_sample(session): canvas = Planner(session) frags = session.Sample.where( {"sample_type_id": session.SampleType.find_by_name("Fragment").id}, opts={"limit": 10}, ) purify1 = canvas.create_operation_by_name("Purify Gel Slice", category="Cloning") purify2 = canvas.create_operation_by_name("Purify Gel Slice", category="Cloning") assemble = canvas.create_operation_by_name("Assemble Plasmid", category="Cloning") canvas.quick_wire(purify1, assemble) canvas.quick_wire(purify2, assemble) canvas.set_field_value_and_propogate(purify1.inputs[0], sample=frags[0]) input_array = assemble.input_array("Fragment") print("purify1: " + str(purify1.rid)) print("purify2: " + str(purify2.rid)) for i in input_array: print( i.operation.operation_type.name + " " + i.name + " " + str(i.sample) + " " + str(canvas.get_incoming_wires(i)[0].source.operation.rid) ) print("ljljklj") print(purify2.outputs[0].sample) assert ( assemble.input_array("Fragment")[0].sample == frags[0] ), "Setting a wire should propogate to a field value" assert assemble.input_array("Fragment")[1].sample is None, ( "Setting a wire should not propogate sample to other field" "values in the input array." ) def test_quick_wire_to_input_array_with_set_sample(session): canvas = Planner(session) frags = session.Sample.where( {"sample_type_id": session.SampleType.find_by_name("Fragment").id}, opts={"limit": 10}, ) purify1 = canvas.create_operation_by_name("Purify Gel Slice", category="Cloning") purify2 = canvas.create_operation_by_name("Purify Gel Slice", category="Cloning") canvas.set_field_value(purify1.inputs[0], sample=frags[0]) canvas.set_field_value(purify2.inputs[0], sample=frags[1]) assemble = canvas.create_operation_by_name("Assemble Plasmid", category="Cloning") canvas.quick_wire(purify1, assemble) canvas.quick_wire(purify2, assemble) canvas.chain("Purify Gel Slice", assemble, category="Cloning") input_array = assemble.input_array("Fragment") assert len(input_array) == 3, "There should be 3 field values" assert input_array[0].sample == frags[0] assert input_array[1].sample == frags[1] assert input_array[2].sample is None # TODO: this test is not finished.. def test_set_output_and_propogate(session): session.set_verbose(True) canvas = Planner(session) ops = canvas.chain( "Rehydrate Primer", "Make PCR Fragment", "Run Gel", "Extract Gel Slice", "Purify Gel Slice", "Assemble Plasmid", category="Cloning", ) example_fragment = session.Sample.find_by_name("SV40-dCas9-split") canvas.set_output_sample( ops[1].outputs[0], sample=example_fragment, setter=canvas.set_field_value_and_propogate, ) canvas.validate() def test_set_input_array(session): canvas = Planner(session) op = canvas.create_operation_by_name("Assemble Plasmid", category="Cloning") frags = session.Sample.where( {"sample_type_id": session.SampleType.find_by_name("Fragment").id}, opts={"limit": 10}, ) canvas.set_input_field_value_array(op, "Fragment", sample=frags[0]) canvas.set_input_field_value_array(op, "Fragment", sample=frags[1]) input_array = op.input_array("Fragment") assert ( len(op.input_array("Fragment")) == 2 ), "There should be exactly 2 field values in the input array" assert ( input_array[0] != input_array[1] ), "Input array field values should be different" assert len(op.input_array("Fragment")) == 2 assert ( op.input_array("Fragment")[0].sample == frags[0] ), "Input array 0 should have fragment 0" assert ( op.input_array("Fragment")[1].sample == frags[1] ), "Input array 1 should have fragment 1" def test_plan_validate_with_no_errors(session): """An easy to pass test. A plan that is complete should always pass the validation method. """ session.set_verbose(True) plan = session.Plan.one(query='status != "planning"') assert plan canvas = Planner(plan) canvas.validate()

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0

null

0

null

0

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0

e2b0056c08e76535e1062630476c66ecd0573a56

1,021

py

Python

icekit/plugins/image/migrations/0015_auto_20170310_2004.py

ic-labs/django-icekit

c507ea5b1864303732c53ad7c5800571fca5fa94

[ "MIT" ]

52

2016-09-13T03:50:58.000Z

2022-02-23T16:25:08.000Z

icekit/plugins/image/migrations/0015_auto_20170310_2004.py

ic-labs/django-icekit

c507ea5b1864303732c53ad7c5800571fca5fa94

[ "MIT" ]

304

2016-08-11T14:17:30.000Z

2020-07-22T13:35:18.000Z

icekit/plugins/image/migrations/0015_auto_20170310_2004.py

ic-labs/django-icekit

c507ea5b1864303732c53ad7c5800571fca5fa94

[ "MIT" ]

12

2016-09-21T18:46:35.000Z

2021-02-15T19:37:50.000Z

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('icekit_plugins_image', '0014_image_external_ref'), ] operations = [ migrations.RenameField( model_name='image', old_name='maximum_dimension', new_name='maximum_dimension_pixels', ), migrations.AlterField( model_name='image', name='maximum_dimension_pixels', field=models.PositiveIntegerField(blank=True, help_text='If this image is to be limited to a particular pixel size for distribution, note it here.', null=True), ), migrations.AlterField( model_name='image', name='alt_text', field=models.CharField(max_length=255, blank=True, help_text="A description of the image for users who don't see images visually. Leave blank if the image has no informational value."), ), ]

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null

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e2b14a40b24c80800d570e25ab804585deb5e038

3,531

py

Python

b3j0f/conf/parser/resolver/base.py

b3j0f/configuration

18dd6d5d6560f9b202793739e2330a2181163511

[ "MIT" ]

3

2016-02-18T18:58:24.000Z

2017-03-14T08:40:01.000Z

b3j0f/conf/parser/resolver/base.py

b3j0f/configuration

18dd6d5d6560f9b202793739e2330a2181163511

[ "MIT" ]

1

2016-02-18T15:27:35.000Z

2016-04-02T10:36:43.000Z

b3j0f/conf/parser/resolver/base.py

b3j0f/configuration

18dd6d5d6560f9b202793739e2330a2181163511

[ "MIT" ]

null

# -*- coding: utf-8 -*- # -------------------------------------------------------------------- # The MIT License (MIT) # # Copyright (c) 2015 Jonathan Labéjof <jonathan.labejof@gmail.com> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # -------------------------------------------------------------------- """Programming language expression resolver module. This module defines expression resolvers for dedicated programming languages. An expression resolver is a function which takes in parameters: - expr: string expression to resolve. - safe: boolean flag for a safe execution context. - tostr: boolean flag about format the expression into a string representation. - scope: dict of variables for execution context (contain variables). A resolver is registered with the function ``register``. And is loaded in three ways: - in setting the environment variable 'B3J0F_EXPRRES_PATH' (for example, `b3j0f.conf.parser.lang.js,custom.c` could load both modules `js` and `c` containing programming language parsers). - in using the function `loadresolvers`. - in simply importing a dedicated module with the import keyword. """ __all__ = ['ExprResolver'] from six import add_metaclass from .registry import register from .core import ( DEFAULT_BESTEFFORT, DEFAULT_SAFE, DEFAULT_TOSTR, DEFAULT_SCOPE ) class _MetaExprResolver(type): """Expression Resolver meta class. Register automatically ExprResolver classes.""" def __new__(cls, *args, **kwargs): result = super(_MetaExprResolver, cls).__new__(cls, *args, **kwargs) if result.__register__: register(exprresolver=result) return result @add_metaclass(_MetaExprResolver) class ExprResolver(object): """Expression resolver class. All sub classes are automatically registered.""" __register__ = False #: class registration flag. def __call__( self, expr, safe=DEFAULT_SAFE, tostr=DEFAULT_TOSTR, scope=DEFAULT_SCOPE, besteffort=DEFAULT_BESTEFFORT ): """Resolve input expression. :param str expr: configuration expression to resolve in this language. :param bool safe: safe run execution context (True by default). :param bool tostr: format the result. :param dict scope: execution scope (contains references to expression objects). :param bool besteffort: try to resolve unknown variable name from runtime context. """ raise NotImplementedError()

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3,531

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null

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null

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1

0

e2b187b27bc8c59eec3870b18d05e4350c4e270b

1,670

py

Python

statement_renamer/extractors/capitalone360.py

mkazin/StatementRenamer

ef03c71f0e627a15a4bba08e45bfa90ecacd28fc

[ "Apache-2.0" ]

null

statement_renamer/extractors/capitalone360.py

mkazin/StatementRenamer

ef03c71f0e627a15a4bba08e45bfa90ecacd28fc

[ "Apache-2.0" ]

15

2018-05-01T12:48:30.000Z

2021-05-14T02:52:48.000Z

statement_renamer/extractors/capitalone360.py

mkazin/StatementRenamer

ef03c71f0e627a15a4bba08e45bfa90ecacd28fc

[ "Apache-2.0" ]

1

2019-07-09T22:59:50.000Z

from datetime import datetime from .extractor import DateExtractor, ExtractedData, ExtractorException class CapitalOne360ExtractorException(ExtractorException): def __init__(self, *args, **kwargs): ExtractorException.__init__(self, *args, **kwargs) class CapitalOne360DateExtractor(DateExtractor): EXCEPTION = CapitalOne360ExtractorException DATE_FORMAT = '%m/%d/%Y' SEARCH_TEXT = "Opening Balance" END_TEXT = 'Closing Balance' FILE_FORMAT = '{:02}-{:02}-CapitalOne360.pdf' @staticmethod def match(text): return 'My Info section.capitalone360.comInteractive' in text def extract(self, text): start_date = None end_date = None start = 0 while True: start = text.find(self.__class__.SEARCH_TEXT, start + 1) self.__handle_search_failure__(start < 0) start += len(self.__class__.SEARCH_TEXT) try: int(text[start]) parts = text[start:].strip().split('$') start_date = datetime.strptime( parts[0], self.__class__.DATE_FORMAT) end = text.find(self.__class__.END_TEXT) end_text = text[end + len(self.__class__.END_TEXT):] int(end_text[0]) parts = end_text.replace(' ', '').split('$') end_date = datetime.strptime( parts[0], self.__class__.DATE_FORMAT) break except ValueError: print("ValueError at index: {} - [{}]".format(start, text[start:])) pass return ExtractedData(start_date, end_date)

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0.096463

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0.3

1,670

55

84

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false

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0.026316

0

null

0

null

0

1

0

e2b274a05a49e36d3f5f1623c359598acd291590

1,335

py

Python

setup.py

oeg-upm/ya2ro

799b59046c77a9277b92f2adfa1521d353dfe93d

[ "Apache-2.0" ]

1

2021-10-06T09:34:48.000Z

setup.py

oeg-upm/ya2ro

799b59046c77a9277b92f2adfa1521d353dfe93d

[ "Apache-2.0" ]

30

2021-11-17T18:35:31.000Z

2022-03-28T10:46:45.000Z

setup.py

PavelAntonia/EELISA-research-object

799b59046c77a9277b92f2adfa1521d353dfe93d

[ "Apache-2.0" ]

1

2021-11-22T17:15:53.000Z

from setuptools import find_packages, setup version = {} with open("src/ya2ro/ya2ro.py") as fp: exec(fp.read(), version) setup( name='ya2ro', author='Antonia Pavel', author_email='floriana.antonia.pavel@gmail.com', description='Tool to which you pass basic information of a project or a research article (such as the datasets, software, people who have been involved, bibliography...) and generates two files with structured information with the intention of easing the readability for machines and people. One file is a webpage with all the relevant information and the other one is a Research Object.', version=version['__version__'], url='https://github.com/oeg-upm/ya2ro', packages=find_packages(where="src",), package_dir={"": "src"}, package_data={'ya2ro': ['images/*', 'resources/*']}, license='Apache License 2.0', long_description=open('README.md').read(), long_description_content_type='text/markdown', entry_points={ 'console_scripts': [ 'ya2ro = ya2ro.ya2ro:main', ], }, install_requires=[ 'PyYAML>=5.0.0', 'bs4>=0.0.1', 'requests>=2.22.0', 'bibtexparser>=1.2.0', 'Pygments>=2.11.2', 'somef', 'soca @ git+https://github.com/oeg-upm/soca', 'metadata-parser' ] )

37.083333

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1,335

35

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false

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0

0.030303

0

null

0

null

0

1

0

e2b8e2b89a1d109f4bd53134df5660df9751af92

545

py

Python

actstream/tests/test_apps.py

kimbugp/django-activity-stream

4e53e62adf2b82cd01ab70a033839ab61b2d087b

[ "BSD-3-Clause" ]

1,489

2015-01-02T02:46:30.000Z

2022-03-30T07:32:45.000Z

actstream/tests/test_apps.py

kimbugp/django-activity-stream

4e53e62adf2b82cd01ab70a033839ab61b2d087b

[ "BSD-3-Clause" ]

277

2015-01-02T19:54:09.000Z

2022-03-28T12:07:20.000Z

actstream/tests/test_apps.py

kimbugp/django-activity-stream

4e53e62adf2b82cd01ab70a033839ab61b2d087b

[ "BSD-3-Clause" ]

345

2015-01-13T01:02:42.000Z

2022-03-21T09:39:26.000Z

from unittest import TestCase from django.apps.registry import apps class ActstreamConfigTestCase(TestCase): def test_data_field_is_added_to_action_class_only_once_even_if_app_is_loaded_again(self): actstream_config = apps.get_app_config('actstream') actstream_config.ready() actstream_config.ready() from actstream.models import Action data_fields = [field for field in Action._meta.fields if field.name == 'data'] self.assertEqual( len(data_fields), 1 )

28.684211

93

0.702752

68

545

5.294118

0.558824

0.125

0.111111

0

0.002381

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545

18

94

30.277778

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1

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false

0

0.230769

0

0.384615

0

null

0

null

0

1

0

2c3378c740ae8e44f9721f70acf8526419bc1dcc

26,445

py

Python

viz_platform/dynamic_datasets/model/classes.py

alexanderzimmerman/smart-vp-server

3aa57b5fa32e90a8406684d0d0a2860e224d7916

[ "Apache-2.0" ]

null

viz_platform/dynamic_datasets/model/classes.py

alexanderzimmerman/smart-vp-server

3aa57b5fa32e90a8406684d0d0a2860e224d7916

[ "Apache-2.0" ]

null

viz_platform/dynamic_datasets/model/classes.py

alexanderzimmerman/smart-vp-server

3aa57b5fa32e90a8406684d0d0a2860e224d7916

[ "Apache-2.0" ]

null

import numpy as np import scipy import scipy.special import scipy.interpolate import pickle import sklearn import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import MySQLdb import sqlalchemy from sqlalchemy.ext.declarative import declarative_base import sqlalchemy.ext.mutable from sqlalchemy import Table, Column, Integer, String, Binary, Float, Boolean, Enum, ForeignKey, PickleType, DateTime, LargeBinary from sqlalchemy import create_engine, inspect from sqlalchemy.orm import sessionmaker, relationship import sqlalchemy.types as types Base = declarative_base() scenario_x_ensemble = Table('scenario_x_ensemble', Base.metadata, Column('scenario_id', Integer, ForeignKey('scenario.id')), Column('ensemble_id', Integer, ForeignKey('ensemble.id'))) deployment_x_instrument = Table('deployment_x_instrument', Base.metadata, Column('deployment_id', Integer, ForeignKey('deployment.id')), Column('instrument_id', Integer, ForeignKey('instrument.id'))) deployment_x_platform = Table('deployment_x_platform', Base.metadata, Column('deployment_id', Integer, ForeignKey('deployment.id')), Column('platform_id', Integer, ForeignKey('platform.id'))) opt_x_optParamType = Table('opt_x_optParamType', Base.metadata, Column('optimization_id', Integer, ForeignKey('optimization.id')), Column('optParamType_id', Integer, ForeignKey('operationalParameterType.id'))) opt_x_decisionType = Table('opt_x_decisionType', Base.metadata, Column('optimization_id', Integer, ForeignKey('optimization.id')), Column('decisionType_id', Integer, ForeignKey('decisionType.id'))) opt_x_modelParamType = Table('opt_x_modelParamType', Base.metadata, Column('optimization_id', Integer, ForeignKey('optimization.id')), Column('modelParamType_id', Integer, ForeignKey('modelParameterType.id'))) opt_x_stateVarType = Table('opt_x_stateVarType', Base.metadata, Column('optimization_id', Integer, ForeignKey('optimization.id')), Column('stateVarType_id', Integer, ForeignKey('stateVarType.id'))) opt_x_instrumentType = Table('opt_x_instrumentType', Base.metadata, Column('optimization_id', Integer, ForeignKey('optimization.id')), Column('instrumentType_id', Integer, ForeignKey('instrumentType.id'))) class Decision(Base): __tablename__ = 'decision' id = Column(Integer, primary_key=True, autoincrement=True) id_type = Column(Integer, ForeignKey('decisionType.id'), primary_key=True ) id_schedule = Column(Integer, ForeignKey('schedule.id') ) time = Column(Float) value = Column(PickleType) decisionType = relationship( 'DecisionType', back_populates='decisions' ) class DecisionType(Base): __tablename__ = 'decisionType' id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String(128)) decisions = relationship( 'Decision', back_populates='decisionType' ) opts = relationship( 'Optimization', back_populates='decisionTypes', secondary=opt_x_decisionType ) class DecisionDependency(Base): __tablename__ = 'decisionDependency' id = Column(Integer, primary_key=True, autoincrement=True) id_subject = Column(Integer, ForeignKey('decisionType.id') ) id_object = Column(Integer, ForeignKey('decisionType.id') ) dec_subject = relationship( 'DecisionType', foreign_keys=[id_subject] ) dec_object = relationship( 'DecisionType', foreign_keys=[id_object] ) class Deployment(Base): __tablename__ = 'deployment' id = Column(Integer, primary_key=True, autoincrement=True) instruments = relationship( 'Instrument', back_populates='deployment', secondary=deployment_x_instrument ) platforms = relationship( 'Platform', back_populates='deployment', secondary=deployment_x_platform ) predictions = relationship( 'PredictedDataset', back_populates='deployment' ) observations = relationship( 'ObservedDataset', back_populates='deployment' ) class Ensemble(Base): __tablename__ = 'ensemble' id = Column(Integer, primary_key=True, autoincrement=True) scenarios = relationship( 'Scenario', back_populates='ensembles', secondary=scenario_x_ensemble ) class Instrument(Base): __tablename__ = 'instrument' id = Column(Integer, primary_key=True, autoincrement=True) id_type = Column(Integer, ForeignKey('instrumentType.id') ) name = Column(String(256)) type = relationship( 'InstrumentType' ) deployment = relationship( 'Deployment', back_populates='instruments', secondary=deployment_x_instrument ) objFuncs = relationship( 'ObjectiveFunction', back_populates='instrument' ) class InstrumentType(Base): __tablename__ = 'instrumentType' id = Column(Integer, primary_key=True, autoincrement=True) id_type = Column(Integer, ForeignKey('stateVarType.id') ) type = relationship( 'StateVariableType' ) opts = relationship( 'Optimization', back_populates='instrumentTypes', secondary=opt_x_instrumentType ) class ModelParameter(Base): __tablename__ = 'modelParameter' id = Column(Integer, primary_key=True, autoincrement=True) id_type = Column(Integer, ForeignKey('modelParameterType.id'), primary_key=True ) id_realization = Column(Integer, ForeignKey('realization.id') ) value = Column(Float) modelParamType = relationship( 'ModelParameterType', back_populates='modelParams' ) realization = relationship( 'Realization', back_populates='modelParams' ) class ModelParameterType(Base): __tablename__ = 'modelParameterType' id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String(64)) # pressure, aqueous CO2 content, total dissolved solids abvr = Column(String(64)) # pf, co2, tds unit = Column(String(64)) # kPa, %, kg/m3 modelParams = relationship( 'ModelParameter', back_populates='modelParamType' ) opts = relationship( 'Optimization', back_populates='modelParamTypes', secondary=opt_x_modelParamType ) class ObjectiveFunction(Base): __tablename__ = 'objFunction' id = Column(Integer, primary_key=True, autoincrement=True) id_instrument = Column(Integer, ForeignKey('instrument.id') ) instrument = relationship( 'Instrument', back_populates='objFuncs' ) objVals = relationship( 'ObjectiveValue', back_populates='objFunction' ) class ObjectiveValue(Base): __tablename__ = 'objValue' id = Column(Integer, primary_key=True, autoincrement=True) id_objectF = Column(Integer, ForeignKey('objFunction.id') ) id_simulation = Column(Integer, ForeignKey('simulation.id') ) value = Column(Float) objFunction = relationship( 'ObjectiveFunction', back_populates='objVals' ) simulation = relationship( 'Simulation', back_populates='objVals' ) def compute(self,time,end): observation = self.objFunction.instrument.deployment[0].observations[0] for prediction in self.objFunction.instrument.deployment[0].predictions: if prediction.simulation==self.simulation: f = scipy.interpolate.interp1d(time,prediction.data) err=0 for i in range(observation.data.shape[0]): if time[i]<end: err += (f(observation.data[i,0])-observation.data[i,1])**2 return err class ObservedDataset(Base): __tablename__ = 'observedDataset' id = Column(Integer, primary_key=True, autoincrement=True) id_deployment = Column(Integer, ForeignKey('deployment.id') ) id_stateVarType = Column(Integer, ForeignKey('stateVarType.id') ) deployment = relationship( 'Deployment', back_populates='observations' ) stateVarType = relationship( 'StateVariableType' ) data = Column(String(2**24)) class OperationalParameterType(Base): __tablename__ = 'operationalParameterType' id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String(64)) abvr = Column(String(64)) unit = Column(String(64)) schedules = relationship( 'Schedule', back_populates='optParamType' ) opts = relationship( 'Optimization', back_populates='optParamTypes', secondary=opt_x_optParamType ) class Optimization(Base): __tablename__ = 'optimization' id = Column(Integer, primary_key=True, autoincrement=True) X = Column(String(2**24)) Y = Column(String(2**24)) Z = Column(String(2**24)) t = Column(String(2**24)) end = Column(Float) optParamTypes = relationship( 'OperationalParameterType', back_populates='opts', secondary=opt_x_optParamType ) decisionTypes = relationship( 'DecisionType', back_populates='opts', secondary=opt_x_decisionType ) modelParamTypes = relationship( 'ModelParameterType', back_populates='opts', secondary=opt_x_modelParamType ) stateVarTypes = relationship( 'StateVariableType', back_populates='opts', secondary=opt_x_stateVarType ) instrumentTypes = relationship( 'InstrumentType', back_populates='opts', secondary=opt_x_instrumentType ) def generate_scenario(self,realization): scenario = Scenario(realization=realization) nInj = np.random.randint(1,3+1) nObs = np.random.randint(1,3+1) nInj = 2 nObs = 2 for iInj in range(nInj): pump_rates = np.random.uniform(400,1000) start_time = np.random.uniform(0.48*np.max(self.t),0.52*np.max(self.t)) if iInj==0: start_time=0 easting = np.random.uniform(np.min(self.X),np.max(self.X)) northing = np.random.uniform(np.min(self.Y),np.max(self.Y)) depth = np.random.uniform(np.min(self.Z),np.max(self.Z)) injWell = Well(easting=easting,northing=northing,depth=depth,time=start_time) schedule = Schedule(optParamType=self.optParamTypes[0],value=pump_rates,well=injWell) decisions = [Decision(decisionType=self.decisionTypes[0])] scenario.schedules += [schedule] simulation = Simulation(scenario=scenario) simulation.run(self.X,self.Y,self.Z,self.t,self.stateVarTypes[0]) for iObs in range(nObs): if iObs==0: drill_time = np.random.uniform(0.00*np.max(self.t),0.05*np.max(self.t)) elif iObs==1: drill_time = np.random.uniform(0.35*np.max(self.t),0.40*np.max(self.t)) else: drill_time = np.random.uniform(0.45*np.max(self.t),0.50*np.max(self.t)) easting = np.random.uniform(np.min(self.X),np.max(self.X)) northing = np.random.uniform(np.min(self.Y),np.max(self.Y)) depth = np.random.uniform(np.min(self.Z),np.max(self.Z)) obsWell = Well(easting=easting,northing=northing,depth=depth,time=drill_time) platform = Platform(wells=[obsWell]) sensor = Instrument(type=self.instrumentTypes[0]) deployment = Deployment(platforms=[platform],instruments=[sensor]) prediction = PredictedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],simulation=simulation) prediction.compute(self.X,self.Y,self.Z,self.t) observed = ObservedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],data=prediction.noisy_data(self.t,0.0005)) objectiveFunction = ObjectiveFunction(instrument=sensor) return scenario def add_to_scenario(self,scenario,easting,northing,depth,drill_time): obsWell = Well(easting=easting,northing=northing,depth=depth,time=drill_time) platform = Platform(wells=[obsWell]) sensor = Instrument(type=self.instrumentTypes[0]) deployment = Deployment(platforms=[platform],instruments=[sensor]) prediction = PredictedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],simulation=scenario.simulations[0]) prediction.compute(self.X,self.Y,self.Z,self.t) observed = ObservedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],data=prediction.noisy_data(self.t,0.0005)) objFunc = ObjectiveFunction(instrument=sensor) return scenario def monte_carlo(self,schedules,deployments,full=False): T = np.random.uniform(0.2e+4,2.6e+4) S = np.random.uniform(0.5e-5,0.5e-2) #print T,S modelParams = [] modelParams += [ModelParameter(value=T,modelParamType=self.modelParamTypes[0])] modelParams += [ModelParameter(value=S,modelParamType=self.modelParamTypes[1])] realization = Realization(modelParams=modelParams) scenario = Scenario(realization=realization) for true_schedule in schedules: pump_rates = true_schedule.value start_time = true_schedule.well.time easting = true_schedule.well.easting northing = true_schedule.well.northing depth = true_schedule.well.depth injWell = Well(easting=easting,northing=northing,depth=depth,time=start_time) schedule = Schedule(optParamType=self.optParamTypes[0],value=pump_rates,well=injWell) decisions = [Decision(decisionType=self.decisionTypes[0])] scenario.schedules += [schedule] simulation = Simulation(scenario=scenario) if full: simulation.run(self.X,self.Y,self.Z,self.t,self.stateVarTypes[0]) for true_deployment in deployments: obsWell = true_deployment.platforms[0].wells[0] platform = true_deployment.platforms[0] sensor = true_deployment.instruments[0] deployment = true_deployment prediction = PredictedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],simulation=simulation) prediction.compute(self.X,self.Y,self.Z,self.t) objFunc = sensor.objFuncs[0] objVal = ObjectiveValue(objFunction=objFunc,simulation=simulation) return scenario def mcmc(self,schedules,deployments,nn,full=False): scenarios = [self.monte_carlo(schedules,deployments)] nRej = 0 while len(scenarios)<nn: print(len(scenarios)) while True: step = 1-0.75/(1+np.exp(-2*(nRej-4))) T = scenarios[-1].realization.modelParams[0].value+np.random.normal(0,step*0.025e+4) S = scenarios[-1].realization.modelParams[1].value+np.random.normal(0,step*0.025e-3) if (0.2e+4<T<2.6e+4) and (0.5e-5<S<0.5e-2): break #print T,S modelParams = [] modelParams += [ModelParameter(value=T,modelParamType=self.modelParamTypes[0])] modelParams += [ModelParameter(value=S,modelParamType=self.modelParamTypes[1])] realization = Realization(modelParams=modelParams) scenario = Scenario(realization=realization) for true_schedule in schedules: pump_rates = true_schedule.value start_time = true_schedule.well.time easting = true_schedule.well.easting northing = true_schedule.well.northing depth = true_schedule.well.depth injWell = Well(easting=easting,northing=northing,depth=depth,time=start_time) schedule = Schedule(optParamType=self.optParamTypes[0],value=pump_rates,well=injWell) decisions = [Decision(decisionType=self.decisionTypes[0])] scenario.schedules += [schedule] simulation = Simulation(scenario=scenario) if full: simulation.run(self.X,self.Y,self.Z,self.t,self.stateVarTypes[0]) for true_deployment in deployments: obsWell = true_deployment.platforms[0].wells[0] platform = true_deployment.platforms[0] sensor = true_deployment.instruments[0] deployment = true_deployment prediction = PredictedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],simulation=simulation) prediction.compute(self.X,self.Y,self.Z,self.t) objFunc = sensor.objFuncs[0] objVal = ObjectiveValue(objFunction=objFunc,simulation=simulation) # new e1new = scenario.simulations[0].objVals[0].compute(self.t,self.end)**0.5 e2new = scenario.simulations[0].objVals[1].compute(self.t,self.end)**0.5 # old e1old = scenarios[-1].simulations[0].objVals[0].compute(self.t,self.end)**0.5 e2old = scenarios[-1].simulations[0].objVals[1].compute(self.t,self.end)**0.5 #print e1,e3, e2,e4 #print e1<=e3, e2<=e4 acc1 = e1new<e1old and e2new<e2old acc2 = e1new<e1old and e2new>e2old and np.random.uniform(0,1)<(0.1+0.9*(e2new-e2old)/e2old) acc3 = e2new<e2old and e1new>e1old and np.random.uniform(0,1)<(0.1+0.9*(e1new-e1old)/e1old) acc4 = e1new>e1old and e2new>e2old and np.random.uniform(0,1)<(0.1+0.9*((e1new-e1old)/e1old+(e2new-e2old)/e2old)) if acc1 or acc2 or acc3 or acc4: scenarios += [scenario] nRej = 0 else: nRej+=1 return scenarios def mcmc2(self,schedules,deployments,nn): scenarios = [self.monte_carlo(schedules,deployments)] nRej = 0 while len(scenarios)<nn: print(len(scenarios)) while True: step = 1-0.75/(1+np.exp(-2*(nRej-4))) T = scenarios[-1].realization.modelParams[0].value+np.random.normal(0,step*0.025e+4) S = scenarios[-1].realization.modelParams[1].value+np.random.normal(0,step*0.025e-3) if (0.2e+4<T<2.6e+4) and (0.5e-5<S<0.5e-2): break #print T,S modelParams = [] modelParams += [ModelParameter(value=T,modelParamType=self.modelParamTypes[0])] modelParams += [ModelParameter(value=S,modelParamType=self.modelParamTypes[1])] realization = Realization(modelParams=modelParams) scenario = Scenario(realization=realization) for true_schedule in schedules: pump_rates = true_schedule.value start_time = true_schedule.well.time easting = true_schedule.well.easting northing = true_schedule.well.northing depth = true_schedule.well.depth injWell = Well(easting=easting,northing=northing,depth=depth,time=start_time) schedule = Schedule(optParamType=self.optParamTypes[0],value=pump_rates,well=injWell) decisions = [Decision(decisionType=self.decisionTypes[0])] scenario.schedules += [schedule] simulation = Simulation(scenario=scenario) simulation.run(self.X,self.Y,self.Z,self.t,self.stateVarTypes[0]) for true_deployment in deployments: obsWell = true_deployment.platforms[0].wells[0] platform = true_deployment.platforms[0] sensor = true_deployment.instruments[0] deployment = true_deployment prediction = PredictedDataset(deployment=deployment,stateVarType=self.stateVarTypes[0],simulation=simulation) prediction.compute(self.X,self.Y,self.Z,self.t) objFunc = sensor.objFuncs[0] objVal = ObjectiveValue(objFunction=objFunc,simulation=simulation) e1 = scenario.simulations[0].objVals[0].compute(self.t,self.end)**0.5 e2 = scenario.simulations[0].objVals[1].compute(self.t,self.end)**0.5 e3 = scenario.simulations[0].objVals[2].compute(self.t,self.end)**0.5 e4 = scenarios[-1].simulations[0].objVals[0].compute(self.t,self.end)**0.5 e5 = scenarios[-1].simulations[0].objVals[1].compute(self.t,self.end)**0.5 e6 = scenarios[-1].simulations[0].objVals[2].compute(self.t,self.end)**0.5 #print e1<=e3, e2<=e4 if (e1<=e4 or e2<=e5 or e3<=e6): scenarios += [scenario] nRej = 0 else: nRej+=1 return scenarios class Platform(Base): __tablename__ = 'platform' id = Column(Integer, primary_key=True, autoincrement=True) deployment = relationship( 'Deployment', back_populates='platforms', secondary=deployment_x_platform ) wells = relationship( 'Well', back_populates='platform' ) class PredictedDataset(Base): __tablename__ = 'predictedDataset' id = Column(Integer, primary_key=True, autoincrement=True) id_deployment = Column(Integer, ForeignKey('deployment.id') ) id_stateVarType = Column(Integer, ForeignKey('stateVarType.id') ) id_simulation = Column(Integer, ForeignKey('simulation.id') ) deployment = relationship( 'Deployment', back_populates='predictions' ) stateVarType = relationship( 'StateVariableType' ) simulation = relationship( 'Simulation', back_populates='predictions' ) data = Column(String(2**24)) def stateVarField(self): for field in self.simulation.fields: if field.type==self.stateVarType: return field def compute(self,X,Y,Z,ts): #print type(self.stateVarField()) self.data = np.zeros(ts.shape,dtype='float') if type(self.stateVarField())==type(None): #print 'compute just the sensor response' for schedule in self.simulation.scenario.schedules: Q = schedule.value T = self.simulation.scenario.realization.modelParams[0].value S = self.simulation.scenario.realization.modelParams[1].value xw = schedule.well.easting yw = schedule.well.northing zw = schedule.well.depth t0 = schedule.well.time xo = self.deployment.platforms[0].wells[0].easting yo = self.deployment.platforms[0].wells[0].northing zo = self.deployment.platforms[0].wells[0].depth r = ( (xw-xo)**2+(yw-yo)**2+(zw-zo)**2 )**0.5 for it in range(len(ts)): self.data[it] += self.simulation.theis(Q,T,S,r,ts[it],t0) else: #print 'compute the full 4d response' data = pickle.loads(self.stateVarField().data) xw = self.deployment.platforms[0].wells[0].easting yw = self.deployment.platforms[0].wells[0].northing zw = self.deployment.platforms[0].wells[0].depth pts = np.array(list(zip(X.ravel(),Y.ravel(),Z.ravel())),dtype='float') for it in range(len(ts)): f = scipy.interpolate.LinearNDInterpolator(pts,data[:,:,:,it].ravel()) self.data[it] = f(xw,yw,zw) def noisy_data(self,time,level): ii = np.where(time>self.deployment.platforms[0].wells[0].time)[0] return np.concatenate([ time[ii].reshape([len(ii),1]), (self.data[ii]+np.cumsum(np.random.normal(0,level,self.data[ii].shape))).reshape([len(ii),1]) ], axis=1) class Realization(Base): __tablename__ = 'realization' id = Column(Integer, primary_key=True, autoincrement=True) modelParams = relationship( 'ModelParameter', back_populates='realization' ) scenarios = relationship( 'Scenario', back_populates='realization' ) class Scenario(Base): __tablename__ = 'scenario' id = Column(Integer, primary_key=True, autoincrement=True) id_realization = Column(Integer, ForeignKey('realization.id') ) realization = relationship( 'Realization', back_populates='scenarios' ) schedules = relationship( 'Schedule', back_populates='scenario' ) ensembles = relationship( 'Ensemble', back_populates='scenarios', secondary=scenario_x_ensemble ) simulations = relationship( 'Simulation', back_populates='scenario' ) class Schedule(Base): __tablename__ = 'schedule' id = Column(Integer, primary_key=True, autoincrement=True) id_optParamType = Column(Integer, ForeignKey('operationalParameterType.id') ) id_scenario = Column(Integer, ForeignKey('scenario.id') ) id_well = Column(Integer, ForeignKey('well.id') ) value = Column(PickleType) optParamType = relationship( 'OperationalParameterType', back_populates='schedules' ) scenario = relationship( 'Scenario', back_populates='schedules' ) well = relationship( 'Well', back_populates='schedules' ) class Simulation(Base): __tablename__ = 'simulation' id = Column(Integer, primary_key=True, autoincrement=True) id_scenario = Column(Integer, ForeignKey('scenario.id') ) scenario = relationship( 'Scenario', back_populates='simulations' ) fields = relationship( 'StateVariableField', back_populates='simulation' ) predictions = relationship( 'PredictedDataset', back_populates='simulation' ) objVals = relationship( 'ObjectiveValue', back_populates='simulation' ) def theis(self,Q,T,S,r,t,t0): if t>t0: u = (r**2*S)/(4*T*(t-t0)) W = -scipy.special.expi(-u) return Q / (4*np.pi*T) * W else: return 0.0 def run(self,X,Y,Z,time,stateVarType): T = self.scenario.realization.modelParams[0].value S = self.scenario.realization.modelParams[1].value s = np.zeros([X.shape[0],Y.shape[1],Z.shape[2],time.shape[0]],dtype='float') for schedule in self.scenario.schedules: Q = schedule.value x = schedule.well.easting y = schedule.well.northing z = schedule.well.depth t0 = schedule.well.time for i in range(X.shape[0]): for j in range(Y.shape[1]): for k in range(X.shape[2]): r = ((X[i,j,k]-x)**2+(Y[i,j,k]-y)**2+(Z[i,j,k]-z)**2)**0.5 for l in range(time.shape[0]): s[i,j,k,l] += self.theis(Q,T,S,r,time[l],t0) StateVariableField(type=stateVarType,simulation=self,data=pickle.dumps(s)) class StateVariableField(Base): __tablename__ = 'stateVarField' id = Column(Integer, primary_key=True, autoincrement=True) id_type = Column(Integer, ForeignKey('stateVarType.id') ) id_simulation = Column(Integer, ForeignKey('simulation.id') ) data = Column(String(2**26)) type = relationship( 'StateVariableType' ) simulation = relationship( 'Simulation', back_populates='fields' ) class StateVariableType(Base): __tablename__ = 'stateVarType' id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String(64)) abvr = Column(String(64)) unit = Column(String(64)) opts = relationship( 'Optimization', back_populates='stateVarTypes', secondary=opt_x_stateVarType ) class Well(Base): __tablename__ = 'well' id = Column(Integer, primary_key=True, autoincrement=True) id_platform = Column(Integer, ForeignKey('platform.id') ) easting = Column(Float) northing = Column(Float) depth = Column(Float) time = Column(Float) platform = relationship( 'Platform', back_populates='wells' ) schedules = relationship( 'Schedule', back_populates='well' ) class Forecast(Base): __tablename__ = 'forecast' id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String(64)) abvr = Column(String(64)) unit = Column(String(64)) # %% f = Forecast() print(f)

49.615385

163

0.690187

3,100

26,445

5.775484

0.09129

0.035579

0.020331

0.029491

0.618968

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49.615385

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null

0

null

0

1

0

2c3545b94818bca3c82a497be99bd356be44a3e7

7,592

py

Python

lokii/table.py

dorukerenaktas/lok

0fce198cfc3e5293a2666a66a5d1ee80b81fca48

[ "MIT" ]

1

2021-02-07T09:57:28.000Z

lokii/table.py

dorukerenaktas/lokii

0fce198cfc3e5293a2666a66a5d1ee80b81fca48

[ "MIT" ]

null

lokii/table.py

dorukerenaktas/lokii

0fce198cfc3e5293a2666a66a5d1ee80b81fca48

[ "MIT" ]

null

import random from typing import Dict, Callable, List, Any, Optional import pandas as pd class Table: def __init__(self, name: str, outfile: str, index_cache_size: int, random_cache_size: int, debug: bool): """ Database table like data structure definition that hold column and general configuration to adjust generated data. :param name: name of the table """ self.name = name self.outfile = outfile self.columns = None self.relations: List["Table"] = [] self.defaults: List[Dict] = [] # Determine if table is product of a multiplication self.is_product = False # Multiplicand table, for each row in this table multiplier length of rows will be generated self.multiplicand: Optional["Table"] = None # Multiplier of the pivot table self.multiplier: List[Any] = [1] self.gen_func = lambda x: x # The number of rows to be created self.target_count = 0 # Processed number of target rows self.row_count = 0 # Number of generated rows self.gen_row_count = 0 self._index_cache_size = index_cache_size self._random_cache_size = random_cache_size self._debug = debug self._row_cache = [] self._row_cache_start = -1 self._row_cache_end = -1 def cols(self, *cols: str) -> "Table": """ Adds columns to table. Generated output will be ordered by given columns order. :param cols: name of the columns """ if len(cols) <= 1: # In order to use row cache (Pandas to dict oriented as records) there must be two or more rows raise KeyError('Table {} must have 2 or more columns'.format(self.name)) dup = {x for x in cols if cols.count(x) > 1} if len(dup) > 0: raise KeyError('Columns {} are duplicated for table {}'.format(dup, self.name)) self.columns = cols return self def rels(self, *tables: "Table") -> "Table": """ Adds relations to the table. For every generated row, a random row will be selected from relation tables. :param tables: the relation tables """ dup = {x for x in tables if tables.count(x) > 1} if len(dup) > 0: raise KeyError('Relations {} are duplicated for table {}'.format(dup, self.name)) self.relations = tables return self def defs(self, defaults: List[Dict]) -> "Table": """ Adds default rows to the table. Every default row must have all required columns. :param defaults: default rows for the table """ for i, d in enumerate(defaults): if not all(k in self.columns for k in d): raise KeyError('Default row at index {} does have all required columns for table {}' .format(i, self.name)) self.defaults = defaults return self def simple(self, count: int, gen: Callable[[int, Dict], Dict]) -> "Table": self.target_count = count def generate_row(index: int, rel_dict: Dict) -> Dict: return gen(index, rel_dict) # self._write_async(100 if self._debug else count, generate_row) self.gen_func = generate_row return self def multiply(self, table: "Table", gen: Callable[[int, Any, Dict], Dict], multiplier: List) -> "Table": if len(multiplier) == 0: raise KeyError('Table {} has a multiplier with no items'.format(self.name)) self.is_product = True self.multiplicand = table self.multiplier = multiplier if multiplier else [1] def generate_row(index: int, rel_dict: Dict) -> Dict: return gen(index, multiplier[index % len(multiplier)], rel_dict) # self._write_async(count, generate_row) self.gen_func = generate_row return self def prepare(self): if self.is_product: self.target_count = self.multiplicand.gen_row_count * len(self.multiplier) def load_index_cache(self, start: int, end: int) -> None: """ Index cache is used for multiplying. Before starting batch jobs pivot table needs to cache all range of required indexes. :param start index of range :param end index of range """ if self._row_cache_start <= start and end <= self._row_cache_end: # Already have all required indexes, do nothing return if start + self._index_cache_size > self.gen_row_count: # Remaining range is smaller than cache size, cache all remaining self._row_cache_start = start self._row_cache_end = self.gen_row_count else: # Cache range from start to start + cache size self._row_cache_start = start self._row_cache_end = start + self._index_cache_size dfs = pd.read_csv(self.outfile, sep=',', header=0, names=self.columns, skiprows=self._row_cache_start, chunksize=self._row_cache_end - self._row_cache_start, squeeze=True) df = pd.concat(dfs) self._row_cache = df.to_dict(orient='records') def load_random_cache(self, process: float): """ Random cache is used for relations. Before starting batch jobs relation table needs to cache range of random indexes. :param process completion ratio of the process """ curr = int(self.gen_row_count * process) if self._row_cache_start <= curr <= self._row_cache_end: # Already have all required indexes, do nothing return if curr + self._random_cache_size > self.gen_row_count: # Remaining range is smaller than cache size, cache all remaining self._row_cache_start = curr self._row_cache_end = self.gen_row_count else: # Cache range from start to start + cache size self._row_cache_start = curr self._row_cache_end = curr + self._random_cache_size dfs = pd.read_csv(self.outfile, sep=',', header=0, names=self.columns, skiprows=self._row_cache_start, chunksize=self._row_cache_end - self._row_cache_start, squeeze=True) df = pd.concat(dfs) self._row_cache = df.to_dict(orient='records') random.shuffle(self._row_cache) def purge_cache(self): """ Purge cache after generation process end. """ self._row_cache = [] self._row_cache_start = -1 self._row_cache_end = -1 def get_row(self, index: int): if index >= self.gen_row_count: raise IndexError('Index {} is not valid for table {}'.format(index, self.name)) if self._row_cache_start > index or self._row_cache_end < index: raise IndexError('Index {} is not cached for table {}, cache range {}-{} of {}' .format(index, self.name, self._row_cache_start, self._row_cache_end, self.gen_row_count)) return self._row_cache[index - self._row_cache_start] def get_rand(self, seed: int): index = seed % self.gen_row_count \ if self._random_cache_size > self.gen_row_count \ else seed % self._random_cache_size return self._row_cache[index]

37.584158

107

0.601159

979

7,592

4.467824

0.180797

0.056013

0.093278

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0.386145

0.328304

0.318244

0.262003

0

0.00403

0.31362

7,592

201

108

37.771144

0.835348

0.221417

0

0.318966

0

0.066407

0

1

0.12069

false

0

0.025862

0.017241

0.25

0

null

0

null

0

1

0

2c36eb0bb22cd8a2ed48443d1c87d8de5ed364ca

13,428

py

Python

powerspectrum.py

ronniyjoseph/Beam-Perturbations

0122fed7e3018f2e188e12b62ad760e11f6eb158

[ "MIT" ]

null

powerspectrum.py

ronniyjoseph/Beam-Perturbations

0122fed7e3018f2e188e12b62ad760e11f6eb158

[ "MIT" ]

4

2019-06-25T02:02:56.000Z

2019-10-24T08:12:41.000Z

powerspectrum.py

ronniyjoseph/Beam-Perturbations

0122fed7e3018f2e188e12b62ad760e11f6eb158

[ "MIT" ]

null

import numpy import powerbox import matplotlib from matplotlib import pyplot import matplotlib.colors as colors from plottools import colorbar from generaltools import symlog_bounds from radiotelescope import beam_width """ This file is going to contain all relevant power spectrum functions, i.e data gridding, (frequency tapering), frequency fft, angular averaging, plotting """ class PowerSpectrumData: def __init__(self, visibility_data = None, u_coordinate = None, v_coordinate = None, frequency_coordinate = None): self.data_raw = visibility_data self.u_raw = u_coordinate self.v_raw = v_coordinate self.f_raw = frequency_coordinate self.data_regrid = None self.u_regrid = None self.v_regrid = None self.f_regrid = None self.eta = None return def append_frequency_slice(self, new_data, new_u, new_v, new_frequency): if self.data is None: self.data = new_data self.u = new_u self.v = new_v self.f = numpy.array([new_frequency]) else: current_data = self.data current_u = self.u current_v = self.v current_f = self.f self.data = numpy.vstack((current_data, new_data)) self.u = numpy.vstack((current_u, new_u)) self.v = numpy.vstack((current_v, new_v)) self.f = numpy.vstack((current_f, numpy.array([new_frequency]))) return def regrid_data(self, keep_raw = True): return def serialised_gridding(): return def parallelised_gridding(): return def regrid_visibilities(measured_visibilities, baseline_u, baseline_v, u_grid): u_shifts = numpy.diff(u_grid) / 2. u_bin_edges = numpy.concatenate((numpy.array([u_grid[0] - u_shifts[0]]), u_grid[1:] - u_shifts, numpy.array([u_grid[-1] + u_shifts[-1]]))) weights_regrid, u_bins, v__bins = numpy.histogram2d(baseline_u, baseline_v, bins=(u_bin_edges, u_bin_edges)) real_regrid, u_bins, v__bins = numpy.histogram2d(baseline_u, baseline_v, bins=(u_bin_edges, u_bin_edges), weights= numpy.real(measured_visibilities)) imag_regrid, u_bins, v__bins = numpy.histogram2d(baseline_u, baseline_v, bins=(u_bin_edges, u_bin_edges), weights= numpy.imag(measured_visibilities)) regridded_visibilities = real_regrid + 1j*imag_regrid normed_regridded_visibilities = numpy.nan_to_num(regridded_visibilities/weights_regrid) return normed_regridded_visibilities, weights_regrid def regrid_visibilities_gaussian(measured_visibilities, baseline_u, baseline_v, u_grid, frequency): u_shifts = numpy.diff(u_grid) / 2. u_bin_edges = numpy.concatenate((numpy.array([u_grid[0] - u_shifts[0]]), u_grid[1:] - u_shifts, numpy.array([u_grid[-1] + u_shifts[-1]]))) gridded_data = numpy.zeros((len(u_grid), len(u_grid)), dtype = complex) gridded_weights = numpy.zeros((len(u_grid), len(u_grid))) #calculate the kernel kernel_pixel_size = 51 if kernel_pixel_size % 2 == 0: dimension = kernel_pixel_size/2 else: dimension = (kernel_pixel_size + 1)/2 grid_midpoint = int(len(u_grid)/2) kernel_width = beam_width(frequency) print(kernel_width) kernel_grid = u_grid[int(grid_midpoint-dimension):int(grid_midpoint+dimension+1)] uu, vv = numpy.meshgrid(kernel_grid, kernel_grid) kernel = (numpy.exp(-kernel_width**2*(uu ** 2. + vv ** 2.)).flatten()) kernel_coordinates = numpy.arange(-dimension, dimension + 1, 1, dtype = int) kernel_mapx, kernel_mapy = numpy.meshgrid(kernel_coordinates, kernel_coordinates) for i in range(len(measured_visibilities)): u_index = numpy.digitize(numpy.array(baseline_u[i]), u_bin_edges) v_index = numpy.digitize(numpy.array(baseline_v[i]), u_bin_edges) kernel_x = kernel_mapx.flatten() + u_index kernel_y = kernel_mapy.flatten() + v_index #filter indices which are beyond array range indices = numpy.where((kernel_x > 0) & (kernel_x < len(u_grid)) & (kernel_y > 0) & (kernel_y < len(u_grid)))[0] print(indices) gridded_data[kernel_x[indices], kernel_y[indices]] += measured_visibilities[i]*kernel[indices] gridded_weights[kernel_x[indices], kernel_y[indices]] += kernel[indices] normed_gridded_data = numpy.nan_to_num(gridded_data/gridded_weights) return normed_gridded_data, gridded_weights def get_power_spectrum(frequency_range, radio_telescope, ideal_measured_visibilities, broken_measured_visibilities, faulty_tile, plot_file_name, gaussian_kernel = False, verbose = False): baseline_table = radio_telescope.baseline_table # Determine maximum resolution max_frequency = frequency_range[-1] max_u = numpy.max(numpy.abs(baseline_table.u(max_frequency))) max_v = numpy.max(numpy.abs(baseline_table.v(max_frequency))) max_b = max(max_u, max_v) re_gridding_resolution = 0.5 # lambda n_regridded_cells = int(numpy.ceil(2 * max_b / re_gridding_resolution)) #ensure gridding cells are always odd numbered if n_regridded_cells % 2 == 0: n_regridded_cells += 1 else: pass regridded_uv = numpy.linspace(-max_b, max_b, n_regridded_cells) if verbose: print("Gridding data for Power Spectrum Estimation") #Create empty_uvf_cubes: ideal_regridded_cube = numpy.zeros((n_regridded_cells,n_regridded_cells, len(frequency_range)), dtype = complex) broken_regridded_cube= ideal_regridded_cube.copy() ideal_regridded_weights = numpy.zeros((n_regridded_cells,n_regridded_cells, len(frequency_range))) broken_regridded_weights= ideal_regridded_weights.copy() for frequency_index in range(len(frequency_range)): if gaussian_kernel: ideal_regridded_cube[..., frequency_index], ideal_regridded_weights[ ..., frequency_index] = regrid_visibilities_gaussian( ideal_measured_visibilities[:, frequency_index], baseline_table.u(frequency_range[frequency_index]), baseline_table.v(frequency_range[frequency_index]), regridded_uv, frequency_range[frequency_index]) broken_regridded_cube[..., frequency_index], broken_regridded_weights[ ..., frequency_index] = regrid_visibilities_gaussian( broken_measured_visibilities[:, frequency_index], baseline_table.u(frequency_range[frequency_index]), baseline_table.v(frequency_range[frequency_index]), regridded_uv, frequency_range[frequency_index]) else: ideal_regridded_cube[..., frequency_index], ideal_regridded_weights[..., frequency_index] = regrid_visibilities( ideal_measured_visibilities[:, frequency_index], baseline_table.u(frequency_range[frequency_index]), baseline_table.v(frequency_range[frequency_index]), regridded_uv) broken_regridded_cube[..., frequency_index], broken_regridded_weights[..., frequency_index] = regrid_visibilities( broken_measured_visibilities[:, frequency_index], baseline_table.u(frequency_range[frequency_index]), baseline_table.v(frequency_range[frequency_index]), regridded_uv) pyplot.imshow(numpy.abs(ideal_regridded_weights[...,frequency_index])) pyplot.savefig("blaah1.pdf") # visibilities have now been re-gridded if verbose: print("Taking Fourier Transform over frequency and averaging") ideal_shifted = numpy.fft.ifftshift(ideal_regridded_cube, axes=2) broken_shifted = numpy.fft.ifftshift(broken_regridded_cube, axes=2) ideal_uvn, eta_coords = powerbox.dft.fft(ideal_shifted, L=numpy.max(frequency_range) - numpy.min(frequency_range), axes=(2,)) broken_uvn, eta_coords = powerbox.dft.fft(broken_shifted, L=numpy.max(frequency_range) - numpy.min(frequency_range), axes=(2,)) ideal_PS, uv_bins = powerbox.tools.angular_average_nd(numpy.abs(ideal_uvn) ** 2, coords=[regridded_uv, regridded_uv, eta_coords], bins=75, n=2, weights=numpy.sum(ideal_regridded_weights, axis=2)) broken_PS, uv_bins = powerbox.tools.angular_average_nd(numpy.abs(broken_uvn) ** 2, coords=[regridded_uv, regridded_uv, eta_coords], bins=75, n=2, weights=numpy.sum(broken_regridded_weights, axis=2)) diff_PS, uv_bins = powerbox.tools.angular_average_nd(numpy.abs(broken_uvn - ideal_uvn) ** 2, coords=[regridded_uv, regridded_uv, eta_coords], bins=75, n=2, weights=numpy.sum(broken_regridded_weights, axis=2)) #diff_PS = (broken_PS - ideal_PS)/ideal_PS selection = int(len(eta_coords[0]) / 2) + 1 if verbose: print("Making 2D PS Plots") power_spectrum_plot(uv_bins, eta_coords[0, selection:], ideal_PS[:, selection:], broken_PS[:, selection:], diff_PS[:, selection:],plot_file_name, faulty_tile) return def power_spectrum_plot(uv_bins, eta_coords, ideal_PS, broken_PS, diff_PS, plot_file_name, faulty_tile = -1, ): fontsize = 25 tickfontsize = 20 figure = pyplot.figure(figsize=(30, 10)) ideal_axes = figure.add_subplot(131) broken_axes = figure.add_subplot(132) difference_axes = figure.add_subplot(133) ideal_plot = ideal_axes.pcolor(uv_bins, eta_coords, numpy.real(ideal_PS.T), cmap='Spectral_r', norm=colors.LogNorm(vmin=numpy.nanmin(numpy.real(ideal_PS.T)), vmax=numpy.nanmax(numpy.real(ideal_PS.T)))) broken_plot = broken_axes.pcolor(uv_bins, eta_coords, numpy.real(broken_PS.T), cmap='Spectral_r', norm=colors.LogNorm(vmin=numpy.nanmin(numpy.real(broken_PS.T)), vmax=numpy.nanmax(numpy.real(broken_PS.T)))) symlog_min, symlog_max, symlog_threshold, symlog_scale = symlog_bounds(numpy.real(diff_PS)) diff_plot = difference_axes.pcolor(uv_bins, eta_coords, numpy.real(diff_PS.T), norm=colors.SymLogNorm(linthresh=10**-5, linscale=symlog_scale, vmin=symlog_min, vmax=symlog_max), cmap='coolwarm') ideal_axes.set_xscale("log") ideal_axes.set_yscale("log") broken_axes.set_xscale("log") broken_axes.set_yscale("log") difference_axes.set_xscale("log") difference_axes.set_yscale("log") x_labeling = r"$ k_{\perp} \, [\mathrm{h}\,\mathrm{Mpc}^{-1}]$" y_labeling = r"$k_{\parallel} $" x_labeling = r"$ |u |$" y_labeling = r"$ \eta $" ideal_axes.set_xlabel(x_labeling, fontsize=fontsize ) broken_axes.set_xlabel(x_labeling, fontsize=fontsize ) difference_axes.set_xlabel(x_labeling, fontsize=fontsize) ideal_axes.set_ylabel(y_labeling, fontsize=fontsize ) ideal_axes.tick_params(axis='both', which='major', labelsize=tickfontsize) broken_axes.tick_params(axis='both', which='major', labelsize=tickfontsize) difference_axes.tick_params(axis='both', which='major', labelsize=tickfontsize) figure.suptitle(f"Tile {faulty_tile}") ideal_axes.set_title("Ideal Array", fontsize = fontsize) broken_axes.set_title("Broken Array", fontsize = fontsize) difference_axes.set_title("(Ideal - Broken)/Ideal", fontsize = fontsize) # ideal_axes.set_xlim(10**-2.5, 10**-0.5) # broken_axes.set_xlim(10**-2.5, 10**-0.5) # difference_axes.set_xlim(10**-2.5, 10**-0.5) print(uv_bins) ideal_axes.set_xlim(numpy.nanmin(uv_bins), 2*1e2) broken_axes.set_xlim(numpy.nanmin(uv_bins), 2*1e2) difference_axes.set_xlim(numpy.nanmin(uv_bins), 2*1e2) ideal_cax = colorbar(ideal_plot) broken_cax = colorbar(broken_plot) diff_cax = colorbar(diff_plot) diff_cax.set_label(r"$[Jy^2]$", fontsize=fontsize) ideal_cax.ax.tick_params(axis='both', which='major', labelsize=tickfontsize) broken_cax.tick_params(axis='both', which='major', labelsize=tickfontsize) diff_cax.ax.tick_params(axis='both', which='major', labelsize=tickfontsize) print(plot_file_name) figure.savefig(plot_file_name) return

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0.033175

0

null

0

null

0

1

0

2c3a2df09b00838929b47a69b48dbd4d97a14392

3,089

py

Python

banditpylib/protocols/single_player.py

XiGYmax/banditpylib

07698a1c6b17720a8199dea76580546fe3dfb9be

[ "MIT" ]

null

banditpylib/protocols/single_player.py

XiGYmax/banditpylib

07698a1c6b17720a8199dea76580546fe3dfb9be

[ "MIT" ]

null

banditpylib/protocols/single_player.py

XiGYmax/banditpylib

07698a1c6b17720a8199dea76580546fe3dfb9be

[ "MIT" ]

null

from typing import List, Dict import numpy as np from absl import logging from banditpylib.bandits import Bandit from banditpylib.learners import Learner from .utils import Protocol class SinglePlayerProtocol(Protocol): """Single player protocol This protocol is used to simulate the ordinary single-player game. It runs in rounds. During each round, the protocol runs the following steps in sequence. * fetch the state of the environment and ask the learner for actions * send the actions to the enviroment for execution * update the learner with the feedback of the environment The simulation stops when actions returned by the learner is `None`. .. note:: The total number of rounds shows how adaptive the learner is and it is at most the total number of actions. """ def __init__(self, bandit: Bandit, learners: List[Learner], intermediate_regrets: List[int] = None): """ Args: bandit: bandit environment learner: learners to be compared with intermediate_regrets: a list of intermediate times to record intermediate regrets """ super().__init__(bandit=bandit, learners=learners) self.__intermediate_regrets = \ intermediate_regrets if intermediate_regrets is not None else [] @property def name(self) -> str: """default protocol name""" return 'single_player_protocol' def _one_trial(self, random_seed: int, debug: bool) -> List[Dict]: """One trial of the game This method defines how to run one trial of the game. Args: random_seed: random seed debug: whether to run the trial in debug mode Returns: result of one trial """ if debug: logging.set_verbosity(logging.DEBUG) np.random.seed(random_seed) # reset the bandit environment and the learner self.bandit.reset() self.current_learner.reset() one_trial_data = [] # number of rounds to communicate with the bandit environment adaptive_rounds = 0 # total actions executed by the bandit environment total_actions = 0 def record_data(): one_trial_data.append( dict({ 'bandit': self.bandit.name, 'learner': self.current_learner.name, 'rounds': adaptive_rounds, 'total_actions': total_actions, 'regret': self.bandit.regret(self.current_learner.goal) })) while True: context = self.bandit.context() actions = self.current_learner.actions(context) # stop the game if actions returned by the learner is None if actions is None: break # record intermediate regrets if adaptive_rounds in self.__intermediate_regrets: record_data() feedback = self.bandit.feed(actions) self.current_learner.update(feedback) if feedback: # information update for (_, times) in actions: total_actions += int(times) adaptive_rounds += 1 # record final regret record_data() return one_trial_data

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null

0

null

0

1

0

2c3ba3a7de0cd2d1f09de245212daad861a07972

2,873

py

Python

3pxnet-inference/scripts/runValidation.py

SRavit1/3pxnet

1f81a2bdcbb97c42163e914b01dba4e6c73ade60

[ "MIT" ]

7

2020-12-11T16:06:03.000Z

2022-02-13T20:56:06.000Z

3pxnet-inference/scripts/runValidation.py

SRavit1/3pxnet

1f81a2bdcbb97c42163e914b01dba4e6c73ade60

[ "MIT" ]

4

2021-07-13T10:50:49.000Z

2021-08-13T16:06:20.000Z

3pxnet-inference/scripts/runValidation.py

SRavit1/3pxnet

1f81a2bdcbb97c42163e914b01dba4e6c73ade60

[ "MIT" ]

1

2021-07-06T03:41:55.000Z

#!/usr/bin/env python ################################################################################ # MIT License # # Copyright (c) 2019 UCLA NanoCAD Laboratory # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. ################################################################################ """Tests XNOR/3PXnet implementation against reference Author: Wojciech Romaszkan Organization: NanoCAD Laboratory, University of California, Los Angeles License: MIT """ import subprocess __author__ = "Wojciech Romaszkan, NanoCAD Laboratory, UCLA" __license__ = "MIT" class runValidation(object): def __init__(self): self.f = open("logfile", "w") # Iterations self.iters = 100 # Layers to run self.layers = [" -f ", " -c ", " -c -d ", " -c -l 2 ", " -c -l 2 -d "] # batch norm self.bnorm = [" ", " -b "] # output binarization self.outbin = [" ", " -n "] # sparsity self.sparse = [" ", " -s 90 -p "] def run(self): # Failure counter fail = 0 for layer in self.layers: for bn in self.bnorm: for ob in self.outbin: for sp in self.sparse: cmdString = "./validation" + layer + ob + bn + sp + " -i " + str(self.iters) print("Running: " + cmdString) result = subprocess.call(cmdString, shell=True, stdout=self.f) if result: print("FAILED") fail = 1 else: print("PASSED") # Check if any of the tests failed if fail: print("Some tests failed") return True def main(): validator = runValidation() validator.run() if __name__ == '__main__': main()

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4.907186

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0.053691

0.015863

0

0.006803

0.283676

2,873

82

96

35.036585

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false

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0.181818

0.121212

0

null

0

null

0

1

0

2c3c00e8f94657bbf831d69554620cc2f14d7279

978

py

Python

setup.py

nous-consulting/basecamp-next

33851de091056a33663c9370f564cf3d41fe868f

[ "MIT" ]

2

2015-03-28T21:50:36.000Z

2015-09-10T22:29:17.000Z

setup.py

GetBlimp/basecamp-next

f7ebdd3da97ee13cd5ca18f440506fbbc84e7800

[ "MIT" ]

null

setup.py

GetBlimp/basecamp-next

f7ebdd3da97ee13cd5ca18f440506fbbc84e7800

[ "MIT" ]

4

2015-04-14T16:18:26.000Z

2021-03-28T19:00:21.000Z

import os try: from setuptools import setup except ImportError: from distutils.core import setup def read(fname): return open(os.path.join(os.path.dirname(__file__), fname)).read() required = ['requests>=1.0.0', 'requests-oauth2>=0.2.0'] setup( name='basecampx', version='0.1.8', author='Rimvydas Naktinis', author_email='naktinis@gmail.com', description=('Wrapper for Basecamp Next API.'), license="MIT", keywords="basecamp bcx api", url='https://github.com/nous-consulting/basecamp-next', packages=['basecampx'], install_requires=required, long_description=read('README.rst'), include_package_data=True, classifiers=[ 'Development Status :: 3 - Alpha', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Operating System :: OS Independent', 'Programming Language :: Python :: 2.7' ], )

27.166667

70

0.641104

112

978

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0.705357

0.035599

0

0.016905

0.213701

978

35

71

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0.786736

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0.408998

0.022495

0

1

0.032258

false

0

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0.032258

0.193548

0

null

0

null

0

1

0

2c3c2a730b5f9ebaec5a9cf2153e02f5e709d39e

2,602

py

Python

crop_align/crop_align_affectnet.py

AutoLV/NoisyFER

353ff60bad90dd346cd6a8fc54d7a6acd5897044

[ "MIT" ]

15

2020-11-09T16:35:08.000Z

2022-02-12T14:53:11.000Z

crop_align/crop_align_affectnet.py

AutoLV/NoisyFER

353ff60bad90dd346cd6a8fc54d7a6acd5897044

[ "MIT" ]

1

2021-07-21T03:33:46.000Z

2021-08-08T20:24:12.000Z

crop_align/crop_align_affectnet.py

AutoLV/NoisyFER

353ff60bad90dd346cd6a8fc54d7a6acd5897044

[ "MIT" ]

3

2021-03-30T10:21:52.000Z

2021-09-12T15:55:32.000Z

import sys rootPath = '/Users/siwei/Desktop/noisyFER' sys.path.append(rootPath) import os from tqdm import tqdm import cv2 import csv import numpy as np import argparse from crop_align.align import MyFaceAligner parser = argparse.ArgumentParser() parser.add_argument("--root", type=str, default='datasets/affectnet') args = parser.parse_args() def lms_to_np(lms): lms = lms.split(';') x_cor_list, y_cor_list = [], [] for i in range(len(lms)): if i % 2 == 0: x_cor_list.append(float(lms[i])) else: y_cor_list.append(float(lms[i])) lms = [x_cor_list, y_cor_list] lms = np.asarray(lms) # [2, 68] return lms # training.csv def crop_align_affectnet(csv_file, root): img_root = os.path.join(root, 'Manually_Annotated_Images') save_root = os.path.join(root, 'myaligned') if not os.path.exists(save_root): os.makedirs(save_root) my_fa = MyFaceAligner(desiredLeftEye=(0.3, 0.3), desiredFaceWidth=256) cnt = 0 with open(csv_file, 'r') as csvfile: reader = csv.DictReader(csvfile) for row in tqdm(reader): cur_sample = {} cur_sample['img_path'] = os.path.join(img_root, row['subDirectory_filePath'].split('/')[1]) lms = row['facial_landmarks'] cur_sample['lms'] = lms_to_np(lms) cur_sample['expression'] = int(row['expression'][0:]) # for Uncertain and No-face categories the value is -2) cur_sample['valence'] = float(row['valence']) cur_sample['arousal'] = float(row['arousal']) # affectnet emotion label: # 0: Neutral, 1: Happy, 2: Sad, 3: Surprise, 4: Fear, 5: Disgust, 6: Anger, 7: Contempt # 8: None, 9: Uncertain, 10: No-Face if cur_sample['valence'] != -2 and 0 <= cur_sample['expression'] <= 7: img = cv2.imread(cur_sample['img_path']) img_name = row['subDirectory_filePath'].split('/')[1] save_path = os.path.join(save_root, img_name) # use 68 lms provided by AffectNet result = my_fa.align(img, cur_sample['lms']) cv2.imwrite(save_path, result) cnt += 1 print('num of saved images:', cnt) if __name__ == '__main__': print('crop and align for affectnet training set...') crop_align_affectnet(csv_file=os.path.join(args.root, 'training.csv'), root=args.root) print('crop and align for affectnet validation set...') crop_align_affectnet(csv_file=os.path.join(args.root, 'validate.csv'), root=args.root)

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0.03886

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false

0

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0.203704

0.055556

0

null

0

null

0

1

0

2c3c89d30724c38d60dae13286e13556b05ebcb3

640

py

Python

bot/cli.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

bot/cli.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

bot/cli.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

#!/usr/bin/env python import argparse from Toggl.togglApi import getTogglReport if __name__ == '__main__': parser = argparse.ArgumentParser(description='Obtain report from Toggl.') parser.add_argument("--toggl-token", "-tt", help="Set Toggl token.") parser.add_argument("--toggl-workspace", "-w", help="Set Toggl workspace") parser.add_argument("--since", "-s", help="Start date for the report.") parser.add_argument("--until", "-u", help="End date for the report.") args = parser.parse_args() report = getTogglReport(args.toggl_token, int(args.toggl_workspace), args.since, args.until) print(report)

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0.698438

83

640

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0.46988

0.083333

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19

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0.181818

0.090909

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null

0

null

0

1

0

2c3e24b4b6d91fcd05c76dfb86067fae1b3b498e

3,746

py

Python

a_storage/codec/codec_agroup.py

praefrontalis/Anfisa-Annotations

b4127c68e3696b75b2972f6759437034cc56f8e3

[ "Apache-2.0" ]

null

a_storage/codec/codec_agroup.py

praefrontalis/Anfisa-Annotations

b4127c68e3696b75b2972f6759437034cc56f8e3

[ "Apache-2.0" ]

3

2022-03-28T13:44:24.000Z

2022-03-28T13:53:57.000Z

a_storage/codec/codec_agroup.py

praefrontalis/Anfisa-Annotations

b4127c68e3696b75b2972f6759437034cc56f8e3

[ "Apache-2.0" ]

3

2019-02-18T17:05:06.000Z

2022-03-22T19:42:38.000Z

from ._codec_data import _CodecData #=============================================== class CodecAGroup(_CodecData): def __init__(self, master, parent, schema_instr, default_name): self.mGroupName = "?" _CodecData.__init__(self, master, parent, schema_instr, default_name) self.mGroup = self._getProperty("group") self.mGroupName = self._getProperty("group-name") self.mItemCodecs = [ _CodecData.create(self.getMaster(), self, it_instr, "?") for it_instr in self._getProperty("items")] if not self.mGroupName.startswith('<'): self.mGroupName = "<%s>" % self.mGroupName self._updateProperty("group-name", self.mGroupName) self._updateProperty("items", [it.getSchemaDescr() for it in self.mItemCodecs]) used_names = set() for it in self.mItemCodecs: it._checkNameUsage(used_names) stat_info = self._getProperty("stat", dict()) self.mStatValCount = stat_info.get("val", 0) self.mStatGrpCount = stat_info.get("groups") if self.mStatGrpCount is None: self.mStatGrpCount = {name: 0 for name in self.mGroup} stat_info["groups"] = self.mStatGrpCount self._onDuty() def _checkNameUsage(self, used_names): for name in self.mGroup: assert name not in used_names, ( "Duplication name in group for codec %s" % self.getPath()) used_names.add(name) def getType(self): return "attr-group" def isAtomic(self): return False def isAggregate(self): return True def getPath(self): if self.mParent is None: return "/" + self.mGroupName return self.mParent.getPath() + "/" + self.mGroupName def encode(self, value, encode_env): self.mStatValCount += 1 ret_repr = [] for name_idx, name in enumerate(self.mGroup): it_dict = value.get(name) if it_dict is None: continue self.mStatGrpCount[name] += 1 items_repr = [str(name_idx)] for it in self.mItemCodecs: it_repr = "null" if it.isAggregate(): it_repr = it.encode(it_dict, encode_env) else: it_val = it_dict.get(it.getName()) if it_val is not None: it_repr = it.encode(it_val, encode_env) items_repr.append(it_repr) while len(items_repr) > 0 and items_repr[-1] == "null": del items_repr[-1] ret_repr.append('[' + ','.join(items_repr) + ']') return '[' + ','.join(ret_repr) + ']' def updateWStat(self): stat_info = self._getProperty("stat") stat_info["groups"] = self.mStatGrpCount stat_info["val"] = self.mStatValCount for it in self.mItemCodecs: it.updateWStat() def decode(self, group_obj, decode_env): ret = dict() for int_obj in group_obj: name = self.mGroup[int_obj[0]] grp_obj = dict() for idx, it in enumerate(self.mItemCodecs): it_obj = None if idx + 1 < len(int_obj): it_obj = int_obj[idx + 1] if it.isAggregate(): if it_obj is not None: grp_obj.update(it.decode(it_obj, decode_env)) else: if it_obj is not None: grp_obj[it.getName()] = it.decode(it_obj, decode_env) else: grp_obj[it.getName()] = None ret[name] = grp_obj return ret

38.618557

77

0.540577

422

3,746

4.592417

0.203791

0.057792

0.014448

0.022704

0.241486

0.134159

0.097007

0.070175

0.047472

0

0.00405

0.340897

3,746

96

78

39.020833

0.780883

0.012547

0

0.137931

0

0.037317

0

0.011494

1

0.103448

false

0

0.011494

0.034483

0.206897

0

null

0

null

0

1

0

2c3ea335989982f0ae8f5847cf419f798c2e40fa

3,528

py

Python

app/customer/models/bottle_message.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

[ "Apache-2.0" ]

2

2017-12-02T13:58:30.000Z

2018-08-02T17:07:59.000Z

app/customer/models/bottle_message.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

[ "Apache-2.0" ]

null

app/customer/models/bottle_message.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

[ "Apache-2.0" ]

null

# coding=utf-8 import random from mongoengine import * from base.settings import CHATPAMONGO import datetime connect(CHATPAMONGO.db, host=CHATPAMONGO.host, port=CHATPAMONGO.port, username=CHATPAMONGO.username, password=CHATPAMONGO.password) class BottleMessageText(Document): USER_TYPE = [ (0, "主播发送"), (1, "用户发送") ] GENDER = [ (0, "Both"), (1, "男用户"), (2, "女用户") ] DELETE_STATUS = [ (0, "已删除"), (2, "正在使用") ] label = IntField(verbose_name=u"标签", unique=True) message = StringField(verbose_name=u"消息") sender_type = IntField(verbose_name=u"发送者类型", choices=USER_TYPE) gender = IntField(verbose_name=u"性别") delete_status = IntField(verbose_name=u"是否删除", ) create_time = DateTimeField(verbose_name=u"创建时间") def normal_info(self): return { "lable": self.label, "message": self.message, "sender_type": self.sender_type, "gender": self.gender } @classmethod def create_message_text(cls, label, message, sender_type, to_gender): obj_ = cls() obj_.label = label obj_.message = message obj_.sender_type = sender_type obj_.gender = to_gender obj_.create_time = datetime.datetime.now() obj_.save() @classmethod def get_message_text(cls, sender_type, gender=0): return cls.objects.filter(sender_type=sender_type) @classmethod def get_one_mesasge_text(cls, sender_type): messages = cls.objects.filter(sender_type=sender_type) num = random.randint(0,messages.count()-1) return messages[num] @classmethod def get_two_message(cls): to_male_messages = cls.objects.filter(gender=2) # delete_status=2 to_female_messages = cls.objects.filter(gender=1) message_list = [] if to_male_messages: to_male_num = random.randint(0, to_male_messages.count()-1) message_list.append(to_male_messages[to_male_num]) if to_female_messages: to_female_num = random.randint(0, to_female_messages.count()-1) message_list.append(to_female_messages[to_female_num]) return message_list @classmethod def delete_message_text(cls): #todo 待开发 pass @classmethod def update_message_test(cls): #todo 待开发 pass class BottleRecord(Document): SEND_STATUS = [ (0, "开始发送"), (1, "发送成功"), (2, "发送失败") ] SENDER_TYPE = [ (0, "主播发送"), (1, "用户发送") ] user_id = IntField(verbose_name=u"发送者id") label = IntField(verbose_name=u"消息标签") messages = StringField(verbose_name=u"消息内容") sender_type = IntField(verbose_name=u"发送者类型", choices=SENDER_TYPE) send_time = DateTimeField(verbose_name=u"发送时间") count = IntField(verbose_name=u"发送人数") status = IntField(verbose_name=u"发送状态", choices=SEND_STATUS) @classmethod def create_bottle_record(cls, user_id, label, messages, sender_type, count): obj_ = cls() obj_.user_id = user_id obj_.label = label obj_.messages = messages obj_.sender_type = sender_type obj_.send_time = datetime.datetime.now() obj_.count = count # todo 暂时默认发送陈功 obj_.status = 1 obj_.save() @classmethod def update(cls, id, status): record = cls.objects.get(id=id) record.update(set__status=status)

23.837838

100

0.622166

426

3,528

4.894366

0.246479

0.086331

0.07482

0.086331

0.336691

0.177458

0.106475

0.040288

0

0.009277

0.266723

3,528

147

101

24

0.796676

0.016723

0

0.22

0

0.035673

0

0.006803

0

1

0.09

false

0.03

0.04

0.02

0.37

0

null

0

null

0

1

0

2c43035692fa6a7c9793606b200857a4997d78db

3,646

py

Python

names_generator/__init__.py

glentner/names_generator

c3526a90f3c0f8d2b388542dc3770baa4cc455fe

[ "Apache-2.0" ]

1

2020-12-03T08:52:58.000Z

names_generator/__init__.py

glentner/names_generator

c3526a90f3c0f8d2b388542dc3770baa4cc455fe

[ "Apache-2.0" ]

null

names_generator/__init__.py

glentner/names_generator

c3526a90f3c0f8d2b388542dc3770baa4cc455fe

[ "Apache-2.0" ]

2

2021-01-16T08:52:33.000Z

2022-02-24T13:53:58.000Z

# This program is free software: you can redistribute it and/or modify it under the # terms of the Apache License (v2.0) as published by the Apache Software Foundation. # # This program is distributed in the hope that it will be useful, but WITHOUT ANY # WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A # PARTICULAR PURPOSE. See the Apache License for more details. # # You should have received a copy of the Apache License along with this program. # If not, see <https://www.apache.org/licenses/LICENSE-2.0>. """API and entry-point for names_generator.""" # type annotations from typing import Tuple, List, Dict, Callable # standard libs import sys import random import logging # internal libs from .__meta__ import __version__, __description__, __authors__, __contact__ from . import names # external libs from cmdkit.app import Application from cmdkit.cli import Interface # In the interest of keeping with the original implementation :) restricted_names: List[Tuple[str, str]] = [ ('boring', 'wozniak') # Steve Wozniak is not boring. ] def random_names() -> Tuple[str, str]: """Select a random choice of names from `names.LEFT` and `names.RIGHT`.""" _names = random.choice(names.LEFT), random.choice(names.RIGHT) return _names if _names not in restricted_names else random_names() def _format_plain(pair: Tuple[str, str]) -> str: return f'{pair[0]} {pair[1]}' def _format_capital(pair: Tuple[str, str]) -> str: return f'{pair[0].capitalize()} {pair[1].capitalize()}' def _format_hyphen(pair: Tuple[str, str]) -> str: return f'{pair[0]}-{pair[1]}' def _format_underscore(pair: Tuple[str, str]) -> str: return f'{pair[0]}_{pair[1]}' _formatting_methods: Dict[str, Callable[[Tuple[str, str]], str]] = { 'plain': _format_plain, 'capital': _format_capital, 'hyphen': _format_hyphen, 'underscore': _format_underscore, } def format_names(pair: Tuple[str, str], style: str = 'underscore') -> str: """Format a pair of names in one of several styles.""" try: return _formatting_methods[style](pair) except KeyError as error: raise NotImplementedError(f'No style \'{style}\'') from error def generate_name(style: str = 'underscore', seed: int = None) -> str: """Generate a random name.""" if seed is not None: random.seed(seed) return format_names(random_names(), style=style) # Command-line interface implementation PROGRAM = 'generate_name' USAGE = f"""\ usage: {PROGRAM} [-h] [-v] [--style NAME] Generate random name pairing.\ """ EPILOG = f"""\ Documentation and issue tracking at: https://github.com/glentner/names_generator\ """ HELP = f"""\ {USAGE} options: -s, --style NAME Formatting (default: underscore). -h, --help Show this message and exit. -v, --version Show the version and exit. {EPILOG}\ """ class NamesGeneratorApp(Application): """Top-level application class for `generate_name` console application.""" interface = Interface(PROGRAM, USAGE, HELP) interface.add_argument('-v', '--version', action='version', version=__version__) style: str = 'underscore' interface.add_argument('-s', '--style', default=style, choices=list(_formatting_methods)) # run even without arguments (do not print usage) ALLOW_NOARGS = True def run(self) -> None: """Generate a random name and print it.""" print(generate_name(style=self.style)) def main() -> int: """Entry-point for `generate_name` console application.""" logging.basicConfig(format='%(msg)s') return NamesGeneratorApp.main(sys.argv[1:])

28.708661

93

0.694185

491

3,646

5.01833

0.356415

0.031656

0.035714

0.030438

0.08888

0.062094

0.049919

0

0.004326

0.175809

3,646

126

94

28.936508

0.815641

0.302523

0

0.046154

0

0.232035

0.017664

0

1

0.138462

false

0

0.123077

0.061538

0.446154

0.015385

0

null

0

null

0

1

0

2c431d85cef6b81fa14e9c6e9f5d7057ee4c9176

849

py

Python

cotd/plugins/motivationv2.py

5h4d0w4rt/cotd-telegram-bot

2185353047557aa0864d64d464597993d0b5eb02

[ "MIT" ]

1

2021-01-14T10:03:49.000Z

cotd/plugins/motivationv2.py

5h4d0w4rt/cotd-telegram-bot

2185353047557aa0864d64d464597993d0b5eb02

[ "MIT" ]

2

2020-09-13T00:47:54.000Z

2021-09-25T16:14:35.000Z

cotd/plugins/motivationv2.py

5h4d0w4rt/cotd-telegram-bot

2185353047557aa0864d64d464597993d0b5eb02

[ "MIT" ]

1

2020-09-12T22:34:04.000Z

import io import typing import uuid import ratelimit import telegram import telegram.ext from cotd.plugins.helpers import make_image from PIL import Image ONE_SECOND = 1 def motivation_inline( update: telegram.Update, context: telegram.ext.CallbackContext ) -> telegram.InlineQueryResultCachedPhoto: db = context.dispatcher._cotd_db query = update.inline_query.query if query == "": return motivation_image = make_image(Image.open("static/motivator.jpg"), query, "top") msg = context.bot.send_photo( chat_id=db, photo=motivation_image, ) photo_id = msg.photo[0].file_id context.bot.delete_message(chat_id=db, message_id=msg.message_id) return telegram.InlineQueryResultCachedPhoto( id=str(uuid.uuid4()), title="CachedPhoto", photo_file_id=photo_id, )

24.257143

83

0.714959

107

849

5.485981

0.448598

0.0477

0.027257

0

0.004373

0.191991

849

34

84

24.970588

0.851312

0

0.040047

0

1

0.035714

false

0

0.285714

0

0.392857

0

null

0

null

0

1

0

2c46ebea0fe0e050587aad5c5ac6a903aa168e9c

21,090

py

Python

renderSDK/Rayvision.py

wangshunhui/renderSDK

b512c43fd0111c114b6abc6398c4609b758436e4

[ "Apache-2.0" ]

2

2020-02-12T09:57:46.000Z

2020-04-03T07:40:07.000Z

renderSDK/Rayvision.py

wangshunhui/renderSDK

b512c43fd0111c114b6abc6398c4609b758436e4

[ "Apache-2.0" ]

null

renderSDK/Rayvision.py

wangshunhui/renderSDK

b512c43fd0111c114b6abc6398c4609b758436e4

[ "Apache-2.0" ]

1

2020-04-16T11:19:58.000Z

#!/usr/bin/env python # -*- coding:utf-8 -*- """ Main """ from .compat import * import os import sys import logging import codecs import time from .RayvisionUtil import get_os, hump2underline, cg_id_name_dict, decorator_use_in_class, format_time from .RayvisionAPI import RayvisionAPI from .RayvisionJob import RayvisionJob from .RayvisionTransfer import RayvisionTransfer from .RayvisionException import RayvisionError from .RayvisionManageJob import RayvisionManageJob from .analyse import RayvisionAnalyse CURRENT_DIR = os.path.dirname(os.path.realpath(__file__)) SDK_LOG = logging.getLogger('sdk_log') class Rayvision(object): def __init__(self, domain_name, platform, access_id, access_key, workspace=None, *args, **kwargs): """ :param str domain_name: domain name, such as: task.renderbus.com :param str platform: platform number, such as: 2 :param str access_id: Authorization id to identify the API caller :param str access_key: authorization key used to encrypt the signature string and the server-side verification signature string :param str workspace: working directory, used to store configuration files and logs generated in the analysis, etc. :param kwargs: """ domain_name = str(domain_name) platform = str(platform) access_id = str(access_id) access_key = str(access_key) if workspace is None: workspace = os.path.join(CURRENT_DIR, 'workspace') # default workspace else: workspace = str(workspace) # init log self.G_SDK_LOG = SDK_LOG sdk_log_filename = 'run_{0}.log'.format(format_time('%Y%m%d')) sdk_log_path = os.path.join(workspace, 'log', 'sdk', sdk_log_filename) self._init_log(self.G_SDK_LOG, sdk_log_path) self.G_SDK_LOG.info('='*50) self._user_info = { 'domain_name': domain_name, 'platform': platform, 'access_id': access_id, 'access_key': access_key, 'local_os': get_os(), 'workspace': workspace } self._api_obj = RayvisionAPI(domain_name, platform, access_id, access_key, log_obj=self.G_SDK_LOG) self._login() # update self._user_info self._manage_job_obj = RayvisionManageJob(self._api_obj) self._transfer_obj = RayvisionTransfer(self._user_info, self._api_obj, self._manage_job_obj, log_obj=self.G_SDK_LOG) @decorator_use_in_class(SDK_LOG) def set_render_env(self, cg_name, cg_version, plugin_config={}, edit_name=None, label_name=None): """ Set the job rendering environment, label (optional) :param str cg_name: Software name, such as 3ds Max, Maya, Houdini :param str cg_version: software version :param dict plugin_config: {"3dhippiesterocam":"2.0.13"} :param str edit_name: The unique identifier name of the rendering environment, temporarily unused :param str label_name: label name, is project name, optional """ cg_name = str(cg_name) cg_version = str(cg_version) if edit_name is not None: edit_name = str(edit_name) if label_name is not None: label_name = str(label_name) self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('cg_name:{0}'.format(cg_name)) self.G_SDK_LOG.info('cg_version:{0}'.format(cg_version)) self.G_SDK_LOG.info('plugin_config:{0}'.format(plugin_config)) self.G_SDK_LOG.info('edit_name:{0}'.format(edit_name)) self.G_SDK_LOG.info('label_name:{0}'.format(label_name)) self.G_SDK_LOG.info('='*20) # initialize the variables self.is_analyse = False # Whether to call the analysis method self.errors_number = 0 # number of errors in tips.json self.error_warn_info_list = [] # error, warning message # self.cg_name = str(cg_name) # Software name (3ds Max, Maya, Houdini) cg_id = cg_id_name_dict.get(cg_name, None) # Software id if cg_id is None: raise RayvisionError(1000000, r'Please input correct cg_name!') # Please enter the correct cg_name # Generate job ID job_id = str(self._api_obj.create_task().get(r'taskIdList', [''])[0]) if job_id == '': raise RayvisionError(1000000, r'Failed to create task number!') # task ID creating failed self.G_SDK_LOG.info('JOB ID:{0}'.format(job_id)) # Instantiate the RayvisionJob object self._job_info = RayvisionJob(self._user_info, job_id) self._job_info._task_info['task_info']['cg_id'] = cg_id # Set up label self.set_label(label_name) # Set the task rendering environment (that is, the software configuration of the task) software_config_dict = {} software_config_dict['cg_name'] = cg_name software_config_dict['cg_version'] = cg_version software_config_dict['plugins'] = plugin_config self._job_info._task_info['software_config'] = software_config_dict return job_id @decorator_use_in_class(SDK_LOG) def analyse(self, cg_file, project_dir=None, software_path=None): """ Analyse cg file. :param str cg_file: scene file path :param str project_dir: The project path of the scene. If set, all assets are searched from the project path when rendering. :param str software_path: Local rendering software path, read from the registry by default, user-definable :return: """ cg_file = str(cg_file) if project_dir is not None: project_dir = str(project_dir) self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('cg_file:{0}'.format(cg_file)) self.G_SDK_LOG.info('project_dir:{0}'.format(project_dir)) self.G_SDK_LOG.info('='*20) self.is_analyse = True # Pass self.job_info, directly modify job_info self._job_info._task_info['task_info']['input_cg_file'] = cg_file.replace('\\', '/') self._job_info._task_info['task_info']['scenefile'] = cg_file.replace('\\', '/') self._job_info._task_info['task_info']['cgfile'] = cg_file.replace('\\', '/') self._job_info._task_info['task_info']['original_cg_file'] = cg_file.replace('\\', '/') if project_dir is not None: self._job_info._task_info['task_info']['input_project_path'] = project_dir RayvisionAnalyse.execute(cg_file, self._job_info, exe_path=software_path) scene_info_data = self._job_info._task_info['scene_info'] # add frames to scene_info_render.<layer>.common.frames if self._job_info._task_info['task_info']['cg_id'] == '2000': # Maya for layer_name, layer_dict in scene_info_data.items(): start_frame = layer_dict['common']['start'] end_frame = layer_dict['common']['end'] by_frame = layer_dict['common']['by_frame'] frames = '{0}-{1}[{2}]'.format(start_frame, end_frame, by_frame) scene_info_data[layer_name]['common']['frames'] = frames self._job_info._task_info['scene_info_render'] = scene_info_data return_scene_info_render = self._job_info._task_info['scene_info_render'] return_task_info = self._job_info._task_info['task_info'] return return_scene_info_render, return_task_info @decorator_use_in_class(SDK_LOG) def check_error_warn_info(self, language='0'): """ Get the analyzed error and warning information :param str language: Return language 0: Chinese (default) 1: English """ if len(self._job_info._tips_info) > 0: for code, value in self._job_info._tips_info.items(): code_info_list = self._api_obj.query_error_detail(code, language=language) for code_info in code_info_list: code_info['details'] = value if str(code_info['type']) == '1': # 0:warning 1:error self.errors_number += 1 self.error_warn_info_list.append(code_info) self.G_SDK_LOG.info('error_warn_info_list:{0}'.format(self.error_warn_info_list)) return self.error_warn_info_list @decorator_use_in_class(SDK_LOG) def submit_job(self, scene_info_render=None, task_info=None, upload_info=None, max_speed=None): """ Submit job (1) Determine if there are any errors or warnings (2) Edit rendering parameters (3) Upload configuration files and assets (4) Submit the job ID :param dict scene_info_render: rendering parameters :param dict task_info: task parameters :param dict upload_info: upload files infomations :param int max_speed: Upload speed limit.The unit of 'max_speed' is KB/S, default value is 1048576 KB/S, means 1 GB/S """ self._is_scene_have_error() # check error self._edit_param(scene_info_render, task_info, upload_info) self._upload(max_speed) self._submit_job() @decorator_use_in_class(SDK_LOG) def download(self, job_id_list, local_dir, max_speed=None, print_log=True): """ Download :param list<int> job_id_list:Job ID :param str local_dir: Download the stored directory :param int max_speed: Download speed limit.The unit of 'max_speed' is KB/S, default value is 1048576 KB/S, means 1 GB/S :param bool print_log: Whether to display the download command line. True: display; False: not display """ self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('job_id_list:{0}'.format(job_id_list)) self.G_SDK_LOG.info('local_dir:{0}'.format(local_dir)) self.G_SDK_LOG.info('='*20) self._transfer_obj._download(job_id_list, local_dir, max_speed, print_log) return True @decorator_use_in_class(SDK_LOG) def auto_download(self, job_id_list, local_dir, max_speed=None, print_log=False, sleep_time=10): """ Auto download as long as any frame is complete. :param list<int> job_id_list:Job ID :param str local_dir: Download the stored directory :param int max_speed: Download speed limit.The unit of 'max_speed' is KB/S, default value is 1048576 KB/S, means 1 GB/S :param bool print_log: Whether to display the download command line. True: display; False: not display :param int/float sleep_time: Sleep time between download, unit is second """ self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('job_id_list:{0}'.format(job_id_list)) self.G_SDK_LOG.info('local_dir:{0}'.format(local_dir)) self.G_SDK_LOG.info('='*20) while True: if len(job_id_list) > 0: time.sleep(float(sleep_time)) for job_id in job_id_list: is_job_end = self._manage_job_obj.is_job_end(job_id) self._transfer_obj._download([job_id], local_dir, max_speed, print_log) if is_job_end is True: self.G_SDK_LOG.info('The job end: {0}'.format(job_id)) job_id_list.remove(job_id) else: break return True @decorator_use_in_class(SDK_LOG) def auto_download_after_job_completed(self, job_id_list, local_dir, max_speed=None, print_log=True, sleep_time=10): """ Auto download after the job render completed. :param list<int> job_id_list:Job ID :param str local_dir: Download the stored directory :param int max_speed: Download speed limit.The unit of 'max_speed' is KB/S, default value is 1048576 KB/S, means 1 GB/S :param bool print_log: Whether to display the download command line. True: display; False: not display :param int/float sleep_time: Sleep time between download, unit is second """ self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('job_id_list:{0}'.format(job_id_list)) self.G_SDK_LOG.info('local_dir:{0}'.format(local_dir)) self.G_SDK_LOG.info('='*20) while True: if len(job_id_list) > 0: time.sleep(float(sleep_time)) for job_id in job_id_list: is_job_end = self._manage_job_obj.is_job_end(job_id) if is_job_end is True: self.G_SDK_LOG.info('The job end: {0}'.format(job_id)) self._transfer_obj._download([job_id], local_dir, max_speed, print_log) job_id_list.remove(job_id) else: break return True def _init_log(self, log_obj, log_path, is_print_log=True): log_dir = os.path.dirname(log_path) # If the log_dir path is a file, add timestamp after the log folder name. if os.path.exists(log_dir): if not os.path.isdir(log_dir): log_dir = '{0}{1}'.format(log_dir, format_time()) if not os.path.exists(log_dir): os.makedirs(log_dir) # If the log_path path is a folder, add timestamp after the log file name. if os.path.isdir(log_path): log_dir = '{0}{1}'.format(log_path, format_time()) log_obj.setLevel(logging.DEBUG) # FileHandler file_handler = logging.FileHandler(log_path, encoding='utf-8') fm=logging.Formatter("%(asctime)s %(levelname)s - %(message)s","%Y-%m-%d %H:%M:%S") file_handler.setFormatter(fm) log_obj.addHandler(file_handler) # StreamHandler if is_print_log: stream_handler = logging.StreamHandler() stream_handler.setLevel(logging.INFO) log_obj.addHandler(stream_handler) def _login(self): """ Query user information and update to self._user_info 1. Get user details (query_user_profile) 2. Get user settings (query_user_setting) 3. Get user transfer BID (get_transfer_bid) :return: True """ self.G_SDK_LOG.info('[Rayvision.login.start.....]') data1 = self._api_obj.query_user_profile() data2 = self._api_obj.query_user_setting() data3 = self._api_obj.get_transfer_bid() data1.update(data2) data1.update(data3) # Update the above interface results to self._user_info and convert all the keys into underscores. for key, value in data1.items(): if isinstance(value, (int, long, float)): value = str(value) key_underline = hump2underline(key) # Variable name: hump to underline self._user_info[key_underline] = value self.G_SDK_LOG.info('USER INFO:{0}'.format(self._user_info)) self.G_SDK_LOG.info('[Rayvision.login.end.....]') return True def set_label(self, label_name): """ Customize the label to the job, find the task by label :param str label_name: label name """ if label_name is not None: is_label_exist = False label_id = '' for _ in range(3): # try by three time label_dict_list = self._api_obj.get_label_list().get('projectNameList', []) # Get the list of existing users for label_dict in label_dict_list: if label_dict['projectName'] == label_name: is_label_exist = True label_id = str(label_dict['projectId']) break if is_label_exist: if label_id == '': continue break else: # Add a label if the no label exists self._api_obj.add_label(label_name, '0') is_label_exist = True self._job_info._task_info['task_info']['project_name'] = label_name self._job_info._task_info['task_info']['project_id'] = str(label_id) def _edit_param(self, scene_info_render=None, task_info=None, upload_info=None): """ Modify rendering parameters, task parameters :param dict scene_info_render: rendering parameters :param dict task_info: task parameters :param dict upload_info: upload path informations :return: True """ self.G_SDK_LOG.info('INPUT:') self.G_SDK_LOG.info('='*20) self.G_SDK_LOG.info('scene_info_render:{0}'.format(scene_info_render)) self.G_SDK_LOG.info('task_info:{0}'.format(task_info)) self.G_SDK_LOG.info('='*20) if scene_info_render is not None: self._job_info._task_info['scene_info_render'] = scene_info_render if not self.is_analyse: self._job_info._task_info['scene_info'] = scene_info_render if task_info is not None: modifiable_param = [ 'input_cg_file', # The scene file path 'frames_per_task', # Quantity of frames that rendered on one machine 'test_frames', # The frames of test render 'job_stop_time', # Small task stopped due to timingout，unite is second。default is 8 hours 'task_stop_time', # Big task stopped due to timingout，unite is second。default is 24 hours 'time_out', # time-out period，turn into yellow color。unite is second。default is 12 hours 'stop_after_test', # Whether to pause the task after the priority rendering is completed, 1: Pause the task after the priority rendering is completed 2. Do not pause the task after the priority rendering is completed 'tiles_type', # "block(block-based),strip(strip-based)" 'tiles', # If the number of blocks is greater than 1, or stripe is equal to 1 , then it is a single machine. 'is_layer_rendering', # If maya has turned on the layers。"0":Turn off "1":Turn on 'is_distribute_render', # Whether to turn on the distributed rendering。"0":Turn off"1":Turn on 'distribute_render_node', # The quantities of distributed rendering machine 'input_project_path', # Project path 'render_layer_type', # Render layer mode selection。"0"：renderlayer mode；"1"：rendersetup mode 'os_name', # rendering os type。"0": Linux; "1": Windows 'ram' # rendering machine RAM。"64": 64G；"128": 128G ] # Modifiable parameters list for key, value in task_info.items(): if key in modifiable_param: if isinstance(value, (int, long, float)): value = str(value) self._job_info._task_info['task_info'][key] = value # write upload.json if upload_info is not None: self._job_info._upload_info = upload_info with codecs.open(self._job_info._upload_json_path, 'w', 'utf-8') as f_upload_json: json.dump(upload_info, f_upload_json, indent=4, ensure_ascii=False) # write task.json with codecs.open(self._job_info._task_json_path, 'w', 'utf-8') as f_task_json: json.dump(self._job_info._task_info, f_task_json, indent=4, ensure_ascii=False) # write tips.json if not os.path.exists(self._job_info._tips_json_path): with codecs.open(self._job_info._tips_json_path, 'w', 'utf-8') as f_tips_json: json.dump(self._job_info._tips_info, f_tips_json, indent=4, ensure_ascii=False) return True def _upload(self, max_speed=None): cfg_list = [] root = self._job_info._work_dir for file_name in os.listdir(self._job_info._work_dir): if file_name.endswith('.7z'): continue file_path = os.path.join(root, file_name) cfg_list.append(file_path) self._transfer_obj._upload(self._job_info._job_id, cfg_list, self._job_info._upload_info, max_speed) # upload assets and config files return True def _submit_job(self): self._api_obj.submit_task(int(self._job_info._job_id)) return True def _is_scene_have_error(self): if self.errors_number > 0: return_message = r'There are {0} errors. error_warn_info_list:{1}'.format(self.errors_number, self.error_warn_info_list) raise RayvisionError(1000000, return_message) # Analysis completed with errors

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2c4810e4fa88798c039566c38fcfb8acd43be82c

13,764

py

Python

scqubits/io_utils/fileio_backends.py

dmtvanzanten/scqubits

d4d8a0f71ac91077594a6173348279aa490ed048

[ "BSD-3-Clause" ]

null

scqubits/io_utils/fileio_backends.py

dmtvanzanten/scqubits

d4d8a0f71ac91077594a6173348279aa490ed048

[ "BSD-3-Clause" ]

null

scqubits/io_utils/fileio_backends.py

dmtvanzanten/scqubits

d4d8a0f71ac91077594a6173348279aa490ed048

[ "BSD-3-Clause" ]

null

# fileio_backends.py # # This file is part of scqubits. # # Copyright (c) 2019 and later, Jens Koch and Peter Groszkowski # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. ############################################################################ """ Helper routines for writing data to h5 files. """ import ast import csv import os import re from abc import ABC, abstractmethod from typing import Any, Dict, List, Tuple, Union import numpy as np from numpy import ndarray import scqubits.io_utils.fileio as io import scqubits.utils.misc as utils try: import h5py from h5py import AttributeManager, File, Group except ImportError: _HAS_H5PY = False else: _HAS_H5PY = True # from scqubits.core.discretization import Grid1d # from scqubits.io_utils.fileio import IOData class IOWriter(ABC): """ ABC for writing class instance data to file. Parameters ---------- filename: str file_handle: h5.Group, optional """ def __init__(self, filename: str, file_handle: Group = None) -> None: self.filename = filename self.io_data: io.IOData self.file_handle = file_handle @abstractmethod def to_file(self, io_data: io.IOData, **kwargs): pass @abstractmethod def write_attributes(self, *args, **kwargs): pass @abstractmethod def write_ndarrays(self, *args, **kwargs): pass @abstractmethod def write_objects(self, *args, **kwargs): pass class H5Writer(IOWriter): """Writes IOData to a custom-format h5 file""" def write_attributes(self, h5file_group: Union[Group, File]) -> None: # type: ignore """ Attribute data consists of 1. `__init__` parameters that are of type str or numerical. These are directly written into `h5py.Group.attrs` 2. lists are stored under `<h5py.Group>/__lists` 3. dicts are stored under `<h5py.Group>/__dicts` """ h5file_group.attrs.create( "__type", self.io_data.typename ) # Record the type of the current class instance attributes = self.io_data.attributes for attr_name, attr_value in attributes.items(): if isinstance( attr_value, dict ): # h5py does not serialize dicts automatically, so have to do it manually group_name = "__dicts/" + attr_name h5file_group.create_group(group_name) io.write( attr_value, self.filename, file_handle=h5file_group[group_name] ) elif isinstance(attr_value, (list, tuple)): group_name = "__lists/" + attr_name h5file_group.create_group(group_name) io.write( attr_value, self.filename, file_handle=h5file_group[group_name] ) else: h5file_group.attrs[attr_name] = attr_value def write_ndarrays(self, h5file_group: Union[Group, File]) -> None: # type: ignore """ Writes ndarray (float or complex) data contained in `self.iodata` to the provided `h5py.Group` as a `h5py.Dataset`, using gzip compression. """ data_group = h5file_group.file.require_group("__data") for name, array in self.io_data.ndarrays.items(): array_id = hash(array.tobytes()) h5file_group.create_dataset(name, data=[array_id], dtype="int64") if str(array_id) not in data_group: data_group.create_dataset( str(array_id), data=array, dtype=array.dtype, compression="gzip" ) def write_objects(self, h5file_group: Union[Group, File]) -> None: # type: ignore """ Writes data representing a Python object other than ndarray, list and dict, contained in `self.iodata` to the provided `h5py.Group` und `<h5py.Group>/__objects`. """ h5file_group = h5file_group.create_group("__objects") for obj_name in self.io_data.objects.keys(): new_h5group = h5file_group.create_group(obj_name) io.write( self.io_data.objects[obj_name], self.filename, file_handle=new_h5group ) @utils.Required(h5py=_HAS_H5PY) def to_file(self, io_data: io.IOData, file_handle: Group = None) -> None: """ Takes the serialized IOData and writes it either to a new h5 file with file name given by `self.filename` to to the given h5py.Group of an open h5 file. """ self.io_data = io_data if file_handle is None: h5file_group = h5py.File(self.filename, "w", rdcc_nbytes=1024 ** 2 * 200) _ = h5file_group.create_group("__data") close_when_done = True else: h5file_group = file_handle close_when_done = False self.write_attributes(h5file_group) self.write_ndarrays(h5file_group) self.write_objects(h5file_group) if close_when_done: h5file_group.close() class H5Reader: """ Enables reading h5 files generated with scqubits. """ def __init__(self, filename: str, file_handle: Group = None) -> None: self.filename = filename self.io_data = None self.file_handle = file_handle @staticmethod def h5_attrs_to_dict( h5_attrs: AttributeManager, ) -> Dict[str, Union[float, str, int]]: """ Converts h5 attribute data to a Python dictionary. Parameters ---------- h5_attrs: h5py.AttributeManager as obtained by accessing `<h5py.Group>.attrs` """ return {attr_name: attr_value for attr_name, attr_value in h5_attrs.items()} def read_attributes(self, h5file_group: Union[Group, File]) -> Dict[str, Any]: """ Read data from h5 file group that is stored directly as `<h5py.Group>.attrs`, or saved in subgroups titled `<h5py.Group>/__lists` and `<h5py.Group>/__dicts`. """ attributes = self.h5_attrs_to_dict(h5file_group.attrs) if "__dicts" in h5file_group: for dict_name in h5file_group["__dicts"]: attributes[dict_name] = io.read( self.filename, h5file_group["__dicts/" + dict_name] ) if "__lists" in h5file_group: for list_name in h5file_group["__lists"]: attributes[list_name] = io.read( self.filename, h5file_group["__lists/" + list_name] ) return attributes def read_ndarrays(self, h5file_group: Union[Group, File]) -> Dict[str, ndarray]: """ Read numpy array data from h5 file group. """ ndarrays = {} if "__data" in h5file_group.file: datagroup = h5file_group.file.require_group("__data") for name, id_dataset in h5file_group.items(): if isinstance(id_dataset, h5py.Dataset): id_int = id_dataset[:][0] data = datagroup[str(id_int)][:] ndarrays[name] = data return ndarrays # legacy support ndarrays = { name: array[:] for name, array in h5file_group.items() if isinstance(array, h5py.Dataset) } return ndarrays def read_objects(self, h5file_group: Union[Group, File]) -> Dict[str, io.IOData]: """ Read data from the given h5 file group that represents a Python object other than an ndarray, list, or dict. """ inner_objects = {} h5file_group = h5file_group["__objects"] for obj_name in h5file_group: inner_objects[obj_name] = io.read(self.filename, h5file_group[obj_name]) return inner_objects @utils.Required(h5py=_HAS_H5PY) def from_file(self, filename: str, file_handle: Group = None) -> io.IOData: """ Either opens a new h5 file for reading or accesses an already opened file via the given h5.Group handle. Reads all data from the three categories of attributes (incl. lists and dicts), ndarrays, and objects. """ if file_handle is None: h5file_group = h5py.File(filename, "r", rdcc_nbytes=1024 ** 2 * 200) else: h5file_group = file_handle attributes = self.read_attributes(h5file_group) typename = attributes["__type"] assert isinstance(typename, str) del attributes["__type"] ndarrays = self.read_ndarrays(h5file_group) inner_objects = self.read_objects(h5file_group) return io.IOData(typename, attributes, ndarrays, inner_objects) class CSVWriter(IOWriter): """ Given filename='somename.csv', write initdata into somename.csv Then, additional csv files are written for each dataset, with filenames: 'somename_' + dataname0 + '.csv' etc. """ def append_ndarray_info(self, attributes): """Add data set information to attributes, so that dataset names and dimensions are available in attributes CSV file.""" for index, dataname in enumerate(self.io_data.ndarrays.keys()): data = self.io_data.ndarrays[dataname] attributes["dataset" + str(index)] = dataname if data.ndim == 3: slice_count = len(data) else: slice_count = 1 attributes["dataset" + str(index) + ".slices"] = slice_count return attributes def write_attributes(self, filename: str): # type: ignore attributes = self.io_data.attributes attributes["__type"] = self.io_data.typename attributes = self.append_ndarray_info(attributes) with open(filename, mode="w", newline="") as meta_file: file_writer = csv.writer(meta_file, delimiter=",") file_writer.writerow(attributes.keys()) file_writer.writerow(attributes.values()) def write_ndarrays(self, filename: str): # type: ignore filename_stub, _ = os.path.splitext(filename) for dataname, dataset in self.io_data.ndarrays.items(): filename = filename_stub + "_" + dataname + ".csv" self.write_data(filename, dataset) def write_data(self, filename: str, dataset: ndarray): # type: ignore if dataset.ndim <= 2: np.savetxt(filename, dataset) elif dataset.ndim == 3: np_savetxt_3d(dataset, filename) else: raise Exception("Dataset has dimensions > 3. Cannot write to CSV file.") def write_objects(self, *args, **kwargs): # type: ignore raise NotImplementedError def to_file(self, io_data: io.IOData, **kwargs): self.io_data = io_data self.write_attributes(self.filename) self.write_ndarrays(self.filename) # no support for write_objects in CSV format class CSVReader: @staticmethod def read_attributes(filename): with open(filename, mode="r") as meta_file: file_reader = csv.reader(meta_file, delimiter=",") meta_keys = file_reader.__next__() meta_values = file_reader.__next__() return dict(zip(meta_keys, meta_values)) def process_metadict(self, meta_dict: Dict) -> Tuple[Dict, List[str], ndarray]: attributes = { attr_name: utils.to_expression_or_string(attr_value) for attr_name, attr_value in meta_dict.items() if not re.match(r"dataset\d+", attr_name) } data_names = [ dataname for datalabel, dataname in meta_dict.items() if re.match(r"dataset\d+$", datalabel) ] data_slices = [ ast.literal_eval(value) for key, value in meta_dict.items() if re.match(r"dataset\d+.slices", key) ] return attributes, data_names, data_slices @staticmethod def read_data(filename, slices): try: data_array = np.loadtxt(filename) except ValueError: data_array = np.loadtxt(filename, dtype=np.complex_) if slices > 1: nrows, ncols = data_array.shape return data_array.reshape((slices, nrows // slices, ncols)) return data_array def from_file(self, filename: str, **kwargs) -> io.IOData: """ Returns ------- class instance generated from file data """ ext_attributes = self.read_attributes(filename) typename = ext_attributes["__type"] del ext_attributes["__type"] attributes, data_names, data_slices = self.process_metadict(ext_attributes) filename_stub, _ = os.path.splitext(filename) ndarrays = {} for index, dataname in enumerate(data_names): data_filename = filename_stub + "_" + dataname + ".csv" slices = data_slices[index] ndarrays[dataname] = self.read_data(data_filename, slices) return io.IOData(typename, attributes, ndarrays, objects=None) def np_savetxt_3d(array3d: ndarray, filename: str): """ Helper function that splits a 3d numpy array into 2d slices for writing as csv data to a new file. Slices are separated by a comment row `# New slice`. Parameters ---------- array3d: ndarray with ndim = 3 """ with open(filename, mode="w", newline="") as datafile: datafile.write("# Array shape: {0}\n".format(array3d.shape)) for data_slice in array3d: np.savetxt(datafile, data_slice) datafile.write("# New slice\n")

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0.613266

1,653

13,764

4.900181

0.174834

0.059753

0.020988

0.008889

0.328395

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0.169506

0.12963

0.095926

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0.013732

0.285745

13,764

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35.937337

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false

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0

0.237288

0

null

0

null

0

1

0

2c4e1b3188875d9cc7ead2bb542721689bd51cbf

2,107

py

Python

util/trig.py

alemigliardi/talkbot

371f2c9e7240a4438cbb202865cf18dbefb0c352

[ "MIT" ]

2

2021-08-07T12:01:26.000Z

2022-01-31T13:48:25.000Z

util/trig.py

alemigliardi/talkbot

371f2c9e7240a4438cbb202865cf18dbefb0c352

[ "MIT" ]

null

util/trig.py

alemigliardi/talkbot

371f2c9e7240a4438cbb202865cf18dbefb0c352

[ "MIT" ]

1

2021-08-07T12:01:28.000Z

import os import re import asyncio from pyrogram.types import Message from util.message import send_media class Trigger: def __init__(self, regex:str, response:str = "", from_self:bool = False, from_others:bool = True, mention:bool = True, media_path:str = "", auto_vanish:int = -1, ): self.regex = re.compile(regex) self.response = response self.from_self = from_self self.from_others = from_others self.mention = mention self.path = media_path self.vanish = auto_vanish @staticmethod def unserialize(obj): return Trigger(obj["regex"], response=obj["response"], from_self=obj["from_self"], from_others=obj["from_others"], mention=obj["mention"], media_path=obj["path"], auto_vanish=obj["vanish"]) def check(self, message:Message) -> bool: if message.from_user.is_self: if not self.from_self: return False elif not self.from_others: return False if self.mention and message.chat.type != "private" and not message.mentioned: return False if self.regex.search(message.text): return True return False async def fire(self, client, message:Message): if self.path: msg = await send_media(client, message.chat.id, self.path, reply_to_message_id=message.message_id, caption=self.response) else: msg = await message.reply(self.response) if self.vanish >= 0: await asyncio.sleep(self.auto_vanish) await msg.delete() def serialize(self) -> dict: return { "regex": self.regex.pattern, "response": self.response, "from_self": self.from_self, "from_others": self.from_others, "mention": self.mention, "path": self.path, "vanish": self.vanish } class TriggerList: def __init__(self): if os.path.isfile("data/triggers.json"): with open("data/triggers.json") as f: self.data = json.load(f) else: self.data = [] with open("data/triggers.json", "w") as f: json.dump(self.data, f) def serialize(self): with open("data/triggers.json", "w") as f: json.dump(self.data, f) def __iter__(self): return self.data.__iter__() # TRIGGERS = TriggerList()

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2,107

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0.297297

0

null

0

null

0

1

0

2c4fccadd03cd528d853e80ad9d2e69c96250a99

3,185

py

Python

back-app/research/form_vision/template_matching.py

AntoineAwaida/ad-covia

1dd10a0361421149e6e318fee146ccf370a81074

[ "MIT" ]

1

2020-04-15T13:48:34.000Z

back-app/research/form_vision/template_matching.py

AntoineAwaida/ad-covia

1dd10a0361421149e6e318fee146ccf370a81074

[ "MIT" ]

1

2022-02-13T09:58:43.000Z

back-app/research/form_vision/template_matching.py

AntoineAwaida/ad-covia

1dd10a0361421149e6e318fee146ccf370a81074

[ "MIT" ]

null

import cv2 from typing import Tuple, Generator from research.form_vision.image import Image, NormalizedCoords import numpy as np class TemplateMatcher: width = 800 def __init__( self, template_image: Image, reference_region: Tuple[NormalizedCoords, NormalizedCoords] ): self._template = template_image.resize(self.width) self._reference_region = reference_region self._reference = self._template.select_subimage(*reference_region) self._ref_region_height = reference_region[1][0] - reference_region[0][0] self._ref_region_width = reference_region[1][1] - reference_region[0][1] def match(self, img: Image) -> Image: img = img.crop_to_aspect_ratio(self._template.aspect_ratio) img = img.resize(width=self.width) region_to_search_coords = self._around_reference_region() region_to_search = img.select_subimage(*region_to_search_coords) best_top_left, most_similar = None, 0.0 for (scaled_rotated_img, scale_factor, angle) in self._get_scaled_rotated_versions(img): top_left, similarity = self._match_template(scaled_rotated_img) found_match = self._extract_match(region_to_search, top_left) return found_match if similarity > most_similar: most_similar = similarity best_top_left = top_left top_left, sim = self._match_template(region_to_search) found_match = self._extract_match(region_to_search, top_left) print(sim) return found_match def _around_reference_region( self, coeff: float = 0.5 ) -> Tuple[NormalizedCoords, NormalizedCoords]: start_vert = max(0, self._reference_region[0][0] - self._ref_region_height * coeff / 2) start_horiz = max(0, self._reference_region[0][1] - self._ref_region_width * coeff / 2) end_vert = min(1, self._reference_region[1][0] + self._ref_region_height * coeff / 2) end_horiz = min(1, self._reference_region[1][1] + self._ref_region_width * coeff / 2) return ((start_vert, start_horiz), (end_vert, end_horiz)) def _extract_match(self, searched_region: Image, top_left: NormalizedCoords) -> Image: return searched_region[ top_left[0] : top_left[0] + int(self._ref_region_height * self._template.shape[0]), top_left[1] : top_left[1] + int(self._ref_region_width * self._template.shape[1]), ] def _get_scaled_rotated_versions( self, image: Image ) -> Generator[Tuple[Image, float, float], None, None]: for scaling_factor in np.arange(0.9, 1.1, 0.02): for angle in np.arange(-3, 3, 0.3): yield ( image.resize(int(scaling_factor * image.shape[1])).rotate(angle), scaling_factor, angle, ) def _match_template(self, image_to_search: Image) -> Tuple[NormalizedCoords, float]: res = cv2.matchTemplate( image_to_search.image_data, self._reference.image_data, cv2.TM_CCOEFF ) _, max_val, _, max_loc = cv2.minMaxLoc(res) return max_loc[::-1], max_val

44.236111

96

0.663736

412

3,185

4.759709

0.218447

0.107088

0.053034

0.038756

0.164202

0.123406

0.047935

0

0.022231

0.237363

3,185

71

97

44.859155

0.785097

0

0.066667

0

1

0.1

false

0

0.066667

0.016667

0.283333

0.016667

0

null

0

null

0

1

0

2c5166b8cabcb5a4f633be4f4e1a16e185d3520c

763

py

Python

src/run.py

ShaghayeghAmeri/test

968eea52ce0ea309f020add61ab597ca402feb14

[ "MIT" ]

null

src/run.py

ShaghayeghAmeri/test

968eea52ce0ea309f020add61ab597ca402feb14

[ "MIT" ]

null

src/run.py

ShaghayeghAmeri/test

968eea52ce0ea309f020add61ab597ca402feb14

[ "MIT" ]

null

import os import emoji import telebot from loguru import logger from src.utils.constant import keyboards from src.utils.io import write_json class But: """ telegram bot to randomly connect two strangers """ def __init__(self): self.bot = telebot.TeleBot(os.environ['BOT_TOKEN']) self.echo = self.bot.message_handler(func=lambda m: True)(self.echo_all) def run(self): logger.info('bot is running...') self.bot.infinity_polling() def echo_all(self, message): print(emoji.demojize(message.text)) self.bot.send_message(message.chat.id, message.text, reply_markup=keyboards.main) write_json(message.json, 'message.json') if __name__=='__main__': bot = But() bot.run()

23.84375

89

0.673657

104

763

4.740385

0.509615

0.056795

0.048682

0

0.209699

763

31

90

24.612903

0.817579

0.060288

0

0.065714

0

1

0.15

false

0

0.3

0

0.5

0.05

0

null

0

null

0

1

0

2c52b06ffe9aba58e5600ed9c53a392211b57c2c

713

py

Python

PythonFiles/MCQGame.py

IamVaibhavsar/Python_Files

283d73929a3e11955c71499407c4f8bff56e4273

[ "MIT" ]

null

PythonFiles/MCQGame.py

IamVaibhavsar/Python_Files

283d73929a3e11955c71499407c4f8bff56e4273

[ "MIT" ]

null

PythonFiles/MCQGame.py

IamVaibhavsar/Python_Files

283d73929a3e11955c71499407c4f8bff56e4273

[ "MIT" ]

1

2019-07-26T15:25:21.000Z

from MCQGame2 import Question MCQ=[ "What color of apples? \na)red\nb)blue\nc)green\nd)yellow", "Half adder has how many inputs?\na)1\nb)2\nc)3\nd)4", "which operator can be overloaded?\na).\nb).*\nc)::\nd)+" ] questions = [ Question(MCQ[0],"a"), #Objects of class Question Question(MCQ[1],"b"), Question(MCQ[2],"d"), ] def run_test(questions): #looping through objects score=0 for question in questions: answer=input(question.prompt) #invoke elements of array MCQ if answer==question.answer: score=score+1 print("You got " + str(score) + " out of " + str(len(questions)) +" correct") run_test(questions)

31

82

0.601683

100

713

4.27

0.61

0.103045

0.074941

0

0.018587

0.245442

713

23

83

31

0.775093

0.106592

0

0.105263

0.30832

0.153344

0

1

0.052632

false

0

0.052632

0

0.105263

0.052632

0

null

0

null

0

1

0

2c52e41b928f577557908dcb035f2bea35861221

5,286

py

Python

gada/main.py

gadalang/gada

2dd4f4dfd5b7390c06307040cad23203a015f7a4

[ "MIT" ]

null

gada/main.py

gadalang/gada

2dd4f4dfd5b7390c06307040cad23203a015f7a4

[ "MIT" ]

null

gada/main.py

gadalang/gada

2dd4f4dfd5b7390c06307040cad23203a015f7a4

[ "MIT" ]

1

2021-06-15T13:52:33.000Z

from __future__ import annotations __all__ = ["run", "main"] import os import sys import io import argparse from typing import Optional from gada import component, runners, datadir def split_unknown_args(argv: list[str]) -> tuple[list[str], list[str]]: """Separate known command-line arguments from unknown one. Unknown arguments are separated from known arguments by the special **--** argument. :param argv: command-line arguments :return: tuple (known_args, unknown_args) """ for i in range(len(argv)): if argv[i] == "--": return argv[:i], argv[i + 1 :] return argv, [] def run( node: str, argv: Optional[list[str]] = None, *, stdin=None, stdout=None, stderr=None, ): """Run a gada node: .. code-block:: python >>> import gada >>> >>> # Overwrite "gada/test/testnodes/config.yml" for this test >>> gada.test_utils.write_testnodes_config({ ... 'nodes': { ... 'echo': { ... 'runner': 'generic', ... 'bin': 'echo' ... } ... } ... }) >>> >>> # Need to create fake stdin and stdout for unittests >>> with gada.test_utils.PipeStream() as stdin: ... with gada.test_utils.PipeStream() as stdout: ... # Run node with CLI arguments ... gada.run( ... 'testnodes.echo', ... ['hello'], ... stdin=stdin.reader, ... stdout=stdout.writer, ... stderr=stdout.writer ... ) ... ... # Close writer end so we can read form it ... stdout.writer.close() ... ... # Read node output ... stdout.reader.read().decode().strip() 'hello' >>> The three parameters ``stdin``, ``stdout`` or ``stderr`` are provided as a convenience for writing unit tests when you can't use ``sys.stdin`` or ``sys.stdout``, or simply when you want to be able to read from the output. :param node: node to run :param argv: additional CLI arguments :param stdin: input stream :param stdout: output stream :param stderr: error stream """ # Load gada configuration gada_config = datadir.load_config() # Check command format node_argv = node.split(".") if len(node_argv) != 2: raise Exception(f"invalid command {node}") # Load component module comp = component.load(node_argv[0]) # Load node configuration node_config = component.get_node_config(component.load_config(comp), node_argv[1]) # Load correct runner runner = runners.load(node_config.get("runner", None)) # Run component runner.run( comp=comp, gada_config=gada_config, node_config=node_config, argv=argv, stdin=stdin, stdout=stdout, stderr=stderr, ) def main( argv: Optional[list[str]] = None, *, stdin=None, stdout=None, stderr=None, ): """Gada main: .. code-block:: python >>> import gada >>> >>> # Overwrite "gada/test/testnodes/config.yml" for this test >>> gada.test_utils.write_testnodes_config({ ... 'nodes': { ... 'echo': { ... 'runner': 'generic', ... 'bin': 'echo' ... } ... } ... }) >>> >>> # Need to create fake stdin and stdout for unittests >>> with gada.test_utils.PipeStream() as stdin: ... with gada.test_utils.PipeStream() as stdout: ... # Run node with CLI arguments ... gada.main( ... ['gada', 'testnodes.echo', 'hello'], ... stdin=stdin.reader, ... stdout=stdout.writer, ... stderr=stdout.writer ... ) ... ... # Close writer end so we can read form it ... stdout.writer.close() ... ... # Read node output ... stdout.reader.read().decode().strip() 'hello' >>> The three parameters ``stdin``, ``stdout`` or ``stderr`` are provided as a convenience for writing unit tests when you can't use ``sys.stdin`` or ``sys.stdout``, or simply when you want to be able to read from the output. :param argv: command line arguments :param stdin: input stream :param stdout: output stream :param stderr: error stream """ argv = sys.argv if argv is None else argv parser = argparse.ArgumentParser(prog="Service", description="Help") parser.add_argument("node", type=str, help="command name") parser.add_argument( "argv", type=str, nargs=argparse.REMAINDER, help="additional CLI arguments" ) parser.add_argument("-v", "--verbose", action="store_true", help="Verbosity level") args = parser.parse_args(args=argv[1:]) node_argv, gada_argv = split_unknown_args(args.argv) run(node=args.node, argv=node_argv, stdin=stdin, stdout=stdout, stderr=stderr) if __name__ == "__main__": main(sys.argv)

30.034091

90

0.541241

582

5,286

4.821306

0.252577

0.022808

0.027798

0.024234

0.560941

0.54526

0.518175

0

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0.323685

5,286

175

91

30.205714

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0

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0

1

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false

0

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0

0.214286

0

null

0

null

0

1

0

2c542dbe200f504a92d4395bd7676e95bb9c6b42

2,912

py

Python

Example_Cases/Gypsum_Model/Scripts/external_gyp1d.py

koverholt/bayes-fire

4333cdf7b93bf77d8e021f0c4a1931a77056534d

[ "BSD-3-Clause" ]

6

2016-06-19T12:44:22.000Z

2021-12-21T07:01:38.000Z

Example_Cases/Gypsum_Model/Scripts/external_gyp1d.py

koverholt/bayes-fire

4333cdf7b93bf77d8e021f0c4a1931a77056534d

[ "BSD-3-Clause" ]

null

Example_Cases/Gypsum_Model/Scripts/external_gyp1d.py

koverholt/bayes-fire

4333cdf7b93bf77d8e021f0c4a1931a77056534d

[ "BSD-3-Clause" ]

2

2017-10-15T02:37:25.000Z

2022-03-04T16:22:44.000Z

#!/usr/bin/env python """Module for gyp1d functions""" import numpy as np import platform import subprocess import os import data_expt as de # Detect operating system op_sys = platform.system() def gen_input( k1, k2, k3, k4, rho_0, c_p1, c_p2, c_p3, eps, Y1_0, A1, A2, E1, E2, dh1, dh2 ): """Generate gyp1d input file from template. Keyword arguments: matl = [ k1, k2, k3, k4, rho_0, c_p1, c_p2, c_p3, eps, Y1_0, A1, A2, E1, E2, dh1, dh2 ] """ template = """ &matl k_temps = 273.15, 448.15, 1088.15, 1473.15 k_vals = %(k1)s, %(k2)s, %(k3)s, %(k4)s rho_0 = %(rho_0)s c_p = %(c_p1)s, %(c_p2)s, %(c_p3)s eps = %(eps)s Y1_0 = %(Y1_0)s A = %(A1)s, %(A2)s E = %(E1)s, %(E2)s dh = %(dh1)s, %(dh2)s / &scen L = 0.0159 L_a = 0.092 t_end = 3601 H = 3.048 / &numr N = 30 N_t = 160000 N_sol = 100 / """ # ================================================== # = Generate gyp1d input file = # ================================================== outcase = template % {'k1':str(k1), 'k2':str(k2), 'k3':str(k3), 'k4':str(k4), 'rho_0':str(rho_0), 'c_p1':str(c_p1), 'c_p2':str(c_p2), 'c_p3':str(c_p3), 'eps':str(eps), 'Y1_0':str(Y1_0), 'A1':str(A1), 'A2':str(A2), 'E1':str(E1), 'E2':str(E2), 'dh1':str(dh1), 'dh2':str(dh2)} # ===================== # = Write gyp1d files = # ===================== casename = 'case' filename = '../' + casename + '.inp' # Opens a new file, writes the gyp1d input file, and closes the file f = open(filename, 'w') f.write(outcase) f.close() return casename def run_gyp1d(casename): """Run gyp1d on case file.""" os.chdir('../') # Run appropriate executable depending on operating system if op_sys == 'Linux': p = subprocess.Popen(['./gyp1d_intel_linux_64', casename + '.inp']) p.wait() if op_sys == 'Darwin': p = subprocess.Popen(['./gyp1d_gfortran_osx_64', casename + '.inp']) p.wait() os.chdir('./Scripts') def read_gyp1d(casename): """Read in gyp1d output.""" temp_file = '../temp_nom.out' temps = np.genfromtxt(temp_file) #mlrs = np.genfromtxt(mlr_file, delimiter=',', skip_header=2) time = temps[:,0] T_1b = temps[:,1] T_2b = temps[:,2] # interpolate to experimental times time_expt = de.time T_1b_interp = np.interp(time_expt, time, T_1b) os.remove('../temp_nom.out') return T_1b_interp

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null

0

null

0

1

0

2c54677ea98da9a5515de3a923f5ef0038257527

6,356

py

Python

datacollector/collector/maincollector.py

samharju/5GDrones-data-collector

331d8c433f5b46eaba62a55c39bbe12d365b2474

[ "Apache-2.0" ]

2

2021-04-26T07:08:26.000Z

2021-05-01T16:01:26.000Z

datacollector/collector/maincollector.py

samharju/5GDrones-data-collector

331d8c433f5b46eaba62a55c39bbe12d365b2474

[ "Apache-2.0" ]

null

datacollector/collector/maincollector.py

samharju/5GDrones-data-collector

331d8c433f5b46eaba62a55c39bbe12d365b2474

[ "Apache-2.0" ]

1

2021-05-01T15:04:46.000Z

# © 2021 Nokia # # Licensed under the Apache license, version 2.0 # SPDX-License-Identifier: Apache-2.0 """Class for handling collector threads.""" import logging import time from datetime import datetime from threading import Event, Thread from datacollector.collector.connection_config_parser import ConnectionConfig from datacollector.collector.memcpunodecollector import MemCpuNodeCollector from datacollector.collector.sshconnection import SshConnection class UnhandledException(Exception): """Raised when unable to collect properly.""" class NoNodesException(Exception): """Raised when no nodes are discovered.""" class MainCollector(Thread): """Maincollector class.""" def __init__(self, agent): """Initialize main collector.""" super().__init__(daemon=True) self.agent = agent self.stop = False self.name = "{addition}-{default}".format(addition=type(self).__name__, default=self.name) self._config = None self._reconnect_lock = False self._stop_event = Event() self._collect_interval = agent.collect_interval self._start_time = agent.collect_start_time self._collect_start_time = datetime.min self._node_collectors = [] @property def collect_interval(self): """Public access for collect_interval.""" return self._collect_interval @property def start_time(self): """Public access for start_time.""" return self._start_time @property def lock_status(self): """Public access for lock_status""" return self._reconnect_lock @property def config(self): """Public access for config.""" return self._config def lock_connections(self): """Set reconnect_lock to True.""" self._reconnect_lock = True def unlock_connections(self): """Set reconnect_lock to False.""" self._reconnect_lock = False def node_finished(self): """Interface for NodeCollector threads to report when they have finished. Last thread that finishes informs adapter that data has been collected. """ if self._all_nodes_finished(): elapsed_time = datetime.utcnow() - self._collect_start_time logging.info("Time elapsed during collection: %ss", elapsed_time) def run(self): """Check when we can stop. See _run method.""" logging.info("%s started.", self.name) while not self.stop: self._run() logging.info("%s finished.", self.name) def signal_stop(self): """Call after StopCollector message.""" logging.debug("%s Received stop signal", self.name) self.stop = True self._stop_event.set() def _read_config(self): self._config.read_config() def _all_nodes_finished(self): return all(not collector.collecting for collector in self._node_collectors) def _run(self): """Start collector threads and triggers first collection immediately. Then triggers collection between every collect interval. """ try: self._main_logic() except Exception as e: logging.error(self.name + " unhandled exception" + str(e)) self.stop = True def _main_logic(self): """Run main logic.""" try: logging.info("Running MainCollector _main_logic...") self._create_node_collectors() self._start_node_collectors() self.agent._reconnect_start_time = None self.agent._reconnect = False self._collect() # Trigger first collection immediately. while not self._stop_event.wait(timeout=self._collect_interval) and self._node_collectors != []: self._collect() self._collect() # Collect last time after stop event has been set. time.sleep(self._collect_interval) self._stop_node_collectors() except Exception as e: logging.warning("Collector ran into an issue. Shutting down...") self.stop = True def _create_node_collectors(self): logging.info("Creating NodeCollectors...") """Create NodeCollectors with implemented ConnectionConfig- and IConnection-objects.""" self._config = ConnectionConfig('device') self._node_collectors.append(MemCpuNodeCollector(self, SshConnection(self._config.hostname, self._config.port, self._config.username, self._config.password))) def _start_node_collectors(self): logging.info("Starting NodeCollectors...") if not self._node_collectors: raise NoNodesException for collector in self._node_collectors: collector.start() def _collect(self): """Distribute collect command to all NodeCollector threads. If last collection is still ongoing, skips the new incoming request. There is some delay between starting collectors, so that ssh connections get time to authenticate themselves. """ if not self._check_alive_collectors(): self.signal_stop() if not self._all_nodes_finished(): logging.warning( "New collect ordered before last one was finished, skipping.") return logging.info("Triggering new collection for all nodes.") self._collect_start_time = datetime.utcnow() for collector in self._node_collectors: collector.collect() def _stop_node_collectors(self): """Set stop flag for each NodeCollector thread and then waits for them to join.""" logging.info("%s stopping node collector threads.", self.name) for collector in self._node_collectors: collector.connection.close_session() collector.stop() for collector in self._node_collectors: collector.join() logging.info("%s all node collectors stopped.", self.name) def _check_alive_collectors(self): for collector in self._node_collectors: if not collector.isAlive(): return False return True

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6,356

5.620144

0.284892

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0.075269

0.041987

0

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6,356

178

119

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0.84552

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0

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0

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0

1

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false

0.008772

0.061404

0.008772

0.324561

0

null

0

null

0

1

0

2c55b9fde76dce6c7aa8c956dc28575c3c2afb98

5,959

py

Python

utils/memory.py

alanmackey/DRL-for-BG-Control

a7c5015b828c250205b9ecb1bf4bdb928e0d975f

[ "MIT" ]

null

utils/memory.py

alanmackey/DRL-for-BG-Control

a7c5015b828c250205b9ecb1bf4bdb928e0d975f

[ "MIT" ]

null

utils/memory.py

alanmackey/DRL-for-BG-Control

a7c5015b828c250205b9ecb1bf4bdb928e0d975f

[ "MIT" ]

null

import numpy as np import torch class ReplayBuffer(object): def __init__( self, state_dim, action_dim, hidden_size, max_size=int(5e3), recurrent=False ): self.max_size = int(max_size) self.ptr = 0 self.size = 0 self.recurrent = recurrent self.state = np.zeros((self.max_size, state_dim)) self.action = np.zeros((self.max_size, action_dim)) self.next_state = np.zeros((self.max_size, state_dim)) self.reward = np.zeros((self.max_size, 1)) self.not_done = np.zeros((self.max_size, 1)) if self.recurrent: self.h = np.zeros((self.max_size, hidden_size)) self.nh = np.zeros((self.max_size, hidden_size)) self.c = np.zeros((self.max_size, hidden_size)) self.nc = np.zeros((self.max_size, hidden_size)) self.device = torch.device( "cuda" if torch.cuda.is_available() else "cpu") def add( self, state, action, next_state, reward, done, hiddens, next_hiddens ): self.state[self.ptr] = state self.action[self.ptr] = action self.next_state[self.ptr] = next_state self.reward[self.ptr] = reward self.not_done[self.ptr] = 1. - done if self.recurrent: h, c = hiddens nh, nc = next_hiddens # Detach the hidden state so that BPTT only goes through 1 timestep self.h[self.ptr] = h.detach().cpu() self.c[self.ptr] = c.detach().cpu() self.nh[self.ptr] = nh.detach().cpu() self.nc[self.ptr] = nc.detach().cpu() self.ptr = (self.ptr + 1) % self.max_size self.size = min(self.size + 1, self.max_size) def sample(self, batch_size=100): # TODO: Clean this up. There's probably a cleaner way to seperate # on-policy and off-policy sampling. Clean up extra-dimension indexing # also ind = np.random.randint(0, self.size, size=int(batch_size)) # TODO: Clean up indexing. RNNs needs batch shape of # Batch size * Timesteps * Input size if not self.recurrent: return self._ff_sampling(ind) h = torch.tensor(self.h[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) c = torch.tensor(self.c[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) nh = torch.tensor(self.nh[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) nc = torch.tensor(self.nc[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) # TODO: Return hidden states or not, or only return the # first hidden state (although it's already been detached, # so returning nothing might be better) hidden = (h, c) next_hidden = (nh, nc) s = torch.FloatTensor( self.state[ind][:, None, :]).to(self.device) a = torch.FloatTensor( self.action[ind][:, None, :]).to(self.device) ns = torch.FloatTensor( self.next_state[ind][:, None, :]).to(self.device) r = torch.FloatTensor( self.reward[ind][:, None, :]).to(self.device) d = torch.FloatTensor( self.not_done[ind][:, None, :]).to(self.device) return s, a, ns, r, d, hidden, next_hidden def on_policy_sample(self): ind = np.arange(0, self.size) # TODO: Clean up indexing. RNNs needs batch shape of # Batch size * Timesteps * Input size if not self.recurrent: return self._ff_sampling(ind) h = torch.tensor(self.h[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) c = torch.tensor(self.c[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) nh = torch.tensor(self.nh[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) nc = torch.tensor(self.nc[ind][None, ...], requires_grad=True, dtype=torch.float).to(self.device) # TODO: Return hidden states or not, or only return the # first hidden state (although it's already been detached, # so returning nothing might be better) hidden = (h, c) next_hidden = (nh, nc) s = torch.FloatTensor( self.state[ind][:, None, :]).to(self.device) a = torch.FloatTensor( self.action[ind][:, None, :]).to(self.device) ns = torch.FloatTensor( self.next_state[ind][:, None, :]).to(self.device) # reward and dones don't need to be "batched" r = torch.FloatTensor( self.reward[ind]).to(self.device) d = torch.FloatTensor( self.not_done[ind]).to(self.device) return s, a, ns, r, d, hidden, next_hidden def _ff_sampling(self, ind): # FF only need Batch size * Input size, on_policy or not hidden = None next_hidden = None s = torch.FloatTensor(self.state[ind]).to(self.device) a = torch.FloatTensor(self.action[ind]).to(self.device) ns = \ torch.FloatTensor(self.next_state[ind]).to(self.device) r = torch.FloatTensor(self.reward[ind]).to(self.device) d = torch.FloatTensor(self.not_done[ind]).to(self.device) return s, a, ns, r, d, hidden, next_hidden def clear_memory(self): self.ptr = 0 self.size = 0

38.445161

80

0.538345

749

5,959

4.190921

0.158879

0.076457

0.087926

0.04014

0.670596

0.662313

0.630137

0.58936

0.540299

0

0.004302

0.336801

5,959

154

81

38.694805

0.78998

0.129888

0

0.531532

0

0.001396

0

0.006494

0

1

0.054054

false

0

0.018018

0

0.126126

0

null

0

null

0

1

0

2c566a2dcb7cec78c109c0686b33ccf0da89a5b9

1,043

py

Python

TilingDomains/main.py

ClathomasPrime/linear-prefs

e700589a82667ca0f307459816e4f5b211fbd7d2

[ "BSD-3-Clause" ]

null

TilingDomains/main.py

ClathomasPrime/linear-prefs

e700589a82667ca0f307459816e4f5b211fbd7d2

[ "BSD-3-Clause" ]

null

TilingDomains/main.py

ClathomasPrime/linear-prefs

e700589a82667ca0f307459816e4f5b211fbd7d2

[ "BSD-3-Clause" ]

null

from GraphDraw import * from Graph import * from Implicit import * from impExamples import * import os import errno flags = os.O_CREAT | os.O_EXCL | os.O_WRONLY # For trying stuff # Currently just displays the alternating domain on 9 outcomes n = 9 impG = impAlternatingDomain(n) G = impG.explicit() d = G.d G.computePoset() G.completeInversionOrder() size = G.sizeOfDomain() snakes = G.getTrackSnakes() try: file_handle = os.open("test-output/best/info"+str(d)+".txt", flags) except OSError as e: if e.errno == errno.EEXIST: # Failed as the file already exists. pass else: # Something unexpected went wrong so reraise the exception. raise else: # No exception, so the file must have been created successfully. with os.fdopen(file_handle, 'w') as F: F.write(str(G.getVRSystem())) F.write("Size of domain: " + str(size)) F.write("") F.write(str(snakes)) drawGraph(G, "best/graphs/bestgraph"+str(d)) drawPoset(G, "best/posets/bestposet"+str(d)) drawGraphAndPoset(G, "best/both/best"+str(d))

21.285714

71

0.700863

156

1,043

4.653846

0.557692

0.022039

0.024793

0

0.002315

0.17162

1,043

48

72

21.729167

0.837963

0.223394

0

0.064516

0

0.121891

0.078358

0

1

0

false

0.032258

0.193548

0

0.193548

0

null

0

null

0

1

0

2c583e62e222fa52ab726c248c5d0731a9185e71

3,647

py

Python

reinforcement-learning/deep-line-wars/game_1.py

cair/experiments

d19a9eda0e9e743e401f46eec358f0c815c64a7c

[ "MIT" ]

null

reinforcement-learning/deep-line-wars/game_1.py

cair/experiments

d19a9eda0e9e743e401f46eec358f0c815c64a7c

[ "MIT" ]

null

reinforcement-learning/deep-line-wars/game_1.py

cair/experiments

d19a9eda0e9e743e401f46eec358f0c815c64a7c

[ "MIT" ]

null

import random import numpy as np from PIL import Image from DeepLineWars.Game import Game import uuid # https://github.com/cair/DeepRTS # https://github.com/reinforceio/tensorforce class GameInstance: @staticmethod def start(data_queue): g = GameInstance(data_queue) g.loop() return True def get_stacked_state(self, swapaxes=False): if len(self.states) > self.stack: if swapaxes: return np.swapaxes(np.array(self.states[-1 * self.stack:]), 0, 2) else: return np.array(self.states[-1 * self.stack:]) return None def __init__(self, data_queue): self.id = uuid.uuid4() print("Game %s - Start" % self.id) self.data_queue = data_queue self.game = Game({ "game": { "width": 11, "height": 11, "tile_width": 32, "tile_height": 32 }, "mechanics": { "complexity": { "build_anywhere": False }, "start_health": 50, "start_gold": 100, "start_lumber": 0, "start_income": 20, "income_frequency": 10, "ticks_per_second": 20, "fps": 10, "ups": 10008000, "income_ratio": 0.20, "kill_gold_ratio": 0.10 }, "gui": { "enabled": True, "draw_friendly": True, "minimal": True } }) self.states = list() self.experience_replay = list() self.s0 = None self.player_1 = self.game.players[0] self.player_2 = self.game.players[1] self.episode = 1 self.representation = "image_grayscaled" self.running = False self.stack = 4 self.num_ticks = 10 self.tick_limit = 30000 def loop(self): self.running = True t = 0 while self.running: # Do action self.player_1.do_action(random.randint(0, 12)) self.player_2.do_action(random.randint(0, 12)) # Process game for i in range(self.num_ticks): self.game.update() t += 1 # Update image state self.game.render() # Retrieve state, add to list of states, s1 = self.game.get_state(representation=self.representation) self.states.append(s1) self.s0 = s1 # Terminal State, Reset Game if self.game.is_terminal() or t >= self.tick_limit: self.game.reset() print("Game %s - %s#%s" % (self.id, self.episode, t)) self.episode += 1 if t < self.tick_limit: self.data_queue.put(self.states) self.states.clear() t = 0 if __name__ == "__main__": import multiprocessing import threading n_proc = 10 processes = [] data_queue = multiprocessing.Queue() def on_data(): while True: data = data_queue.get(block=True) #print(data) t = threading.Thread(target=on_data, args=()) t.start() g = GameInstance(data_queue) g.loop() with multiprocessing.Pool(processes=n_proc): for n in range(n_proc): p = multiprocessing.Process(target=GameInstance.start, args=(data_queue, )) p.start() processes.append(p) for p in processes: p.join()

26.427536

87

0.502879

398

3,647

4.462312

0.344221

0.050676

0.016892

0.024775

0.108108

0.087838

0.030405

0

0.03278

0.389361

3,647

137

88

26.620438

0.764706

0.05292

0

0.058824

0

0.076722

0

1

0.04902

false

0

0.068627

0

0.166667

0.019608

0

null

0

null

0

1

0

2c59f1356149160db7e39588bbaf937c38c8c634

790

py

Python

src/back-django/scraper_api/tests/views/test_page_list_view.py

Arkko002/PyWalker

9e8a02b74a1217cfed385898654815a218297cce

[ "MIT" ]

null

src/back-django/scraper_api/tests/views/test_page_list_view.py

Arkko002/PyWalker

9e8a02b74a1217cfed385898654815a218297cce

[ "MIT" ]

null

src/back-django/scraper_api/tests/views/test_page_list_view.py

Arkko002/PyWalker

9e8a02b74a1217cfed385898654815a218297cce

[ "MIT" ]

null

import json import pytest from django.urls import reverse from scraper_api.models import ScrapedPage class TestPageListView: @pytest.mark.django_db def test_get(self, client, fill_db, url, html): url = reverse("pages/") response = client.get(url) pages = json.loads(response.body) assert pages.len() == fill_db @pytest.mark.django_db def test_post(self, client): url = reverse("pages/") data = {"url": "url1"} page1 = ScrapedPage(url="url1") page2 = ScrapedPage(url="url2") page1.save() page2.save() response = client.post(url, json.dumps(data)) res_pages = json.loads(response.body) assert (res_pages[0].url == "url1" and res_pages.len() == 1)

23.939394

53

0.605063

98

790

4.77551

0.418367

0.044872

0.068376

0.076923

0.24359

0

0.017331

0.26962

790

32

54

24.6875

0.793761

0

0.173913

0

0.039241

0

0.086957

1

0.086957

false

0

0.173913

0

0.304348

0

null

0

null

0

1

0

2c5bc0aa11bc0c3b60a29a13ecd16e57a11921fb

594

py

Python

skfasttext/sk_ft_example.py

tatacoa/hatespeech

fab054d86848c2242443ae3ddf532e94f404f529

[ "MIT" ]

2

2020-03-15T13:46:46.000Z

2020-05-26T06:56:52.000Z

skfasttext/sk_ft_example.py

tatacoa/hatespeech

fab054d86848c2242443ae3ddf532e94f404f529

[ "MIT" ]

1

2018-05-22T20:22:39.000Z

skfasttext/sk_ft_example.py

tatacoa/hatespeech

fab054d86848c2242443ae3ddf532e94f404f529

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed May 2 17:34:43 2018 @author: arndt """ # http://scikit-learn.org/stable/developers/contributing.html#rolling-your-own-estimator # https://github.com/vishnumani2009/sklearn-fasttext from os import chdir chdir("/home/arndt/git-reps/hatespeech/") from skfasttext import SimpleFastTextClassifier # files were previously created in the HateSpeech.py script train_file="data/train_data.txt" test_file="data/test_data.txt" clf=SimpleFastTextClassifier() model = clf.fit(train_file) predictions = clf.predict(test_file, k_best=2)

25.826087

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594

5.232558

0.755814

0.04

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0.033457

0.094276

594

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0.25

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null

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null

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1

0

2c5c4a72fd65572e3fc2aa97977ae16747547c5e

15,366

py

Python

src/niweb/apps/noclook/tests/schema/admin/test_schema.py

SUNET/ni

f652e230524346bf0801cdf8bbb6ee63f4985cc2

[ "BSD-2-Clause-FreeBSD" ]

null

src/niweb/apps/noclook/tests/schema/admin/test_schema.py

SUNET/ni

f652e230524346bf0801cdf8bbb6ee63f4985cc2

[ "BSD-2-Clause-FreeBSD" ]

2

2019-07-24T12:41:11.000Z

2020-03-31T10:10:04.000Z

src/niweb/apps/noclook/tests/schema/admin/test_schema.py

SUNET/ni

f652e230524346bf0801cdf8bbb6ee63f4985cc2

[ "BSD-2-Clause-FreeBSD" ]

1

2019-02-25T14:58:20.000Z

# -*- coding: utf-8 -*- __author__ = 'ffuentes' from apps.noclook.tests.schema.base import Neo4jGraphQLGenericTest from apps.noclook.models import NodeHandleContext from django.contrib.auth.models import User from niweb.schema import schema from pprint import pformat from . import BasicAdminTest import apps.noclook.vakt.utils as sriutils import graphene class GenericUserPermissionTest(BasicAdminTest): def test_contexts(self): if not hasattr(self, 'test_type'): return # add adittional contexts sriutils.set_nodehandle_context(self.network_ctxt, self.organization) sriutils.set_nodehandle_context(self.contracts_ctxt, self.host) sriutils.set_nodehandle_context(self.community_ctxt, self.address) # query context_t = "contexts: [{context_input}]" query_t = """ {{ ninodes(filter: {{ type_in: [{types_str}] with_context: {{ {context} exclude: {exclude} }} }}){{ edges{{ node{{ __typename name contexts }} }} }} }} """ types_str = ", ".join([ '"{}"'.format(x) for x in \ ["Organization", "Host", "Address", "Service", "Cable"] ]) context = context_t.format(context_input=', '.join( [ '"{}"'.format(v.name) for k, v in sriutils.get_all_contexts().items()] )) query = query_t.format(types_str=types_str, context=context, exclude='false') result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) if self.test_type == "admin" or self.test_type == "superadmin": # check the contexts are the expecteds expected = [{'node': {'__typename': 'Organization', 'contexts': ['Community', 'Network'], 'name': 'organization1'}}, {'node': {'__typename': 'Organization', 'contexts': ['Community', 'Network'], 'name': 'organization1'}}, {'node': {'__typename': 'Host', 'contexts': ['Network', 'Contracts'], 'name': 'host1'}}, {'node': {'__typename': 'Host', 'contexts': ['Network', 'Contracts'], 'name': 'host1'}}, {'node': {'__typename': 'Address', 'contexts': ['Contracts', 'Community'], 'name': 'address1'}}, {'node': {'__typename': 'Address', 'contexts': ['Contracts', 'Community'], 'name': 'address1'}}] self.assertEquals(result.data['ninodes']['edges'], expected) else: # test contexts attribute comes empty for node in result.data['ninodes']['edges']: self.assertEquals(node['node']['contexts'], None) def test_node_list(self): if not hasattr(self, 'test_type'): return context_t = "contexts: [{context_input}]" query_t = """ {{ ninodes(filter: {{ type_in: [{types_str}] with_context: {{ {context} exclude: {exclude} }} }} orderBy: name_ASC ){{ edges{{ node{{ __typename id name }} }} }} }} """ types_str = ", ".join([ '"{}"'.format(x) for x in \ ["Organization", "Host", "Address", "Service", "Cable"] ]) organization_id = graphene.relay.Node.to_global_id( str(self.organization.node_type), str(self.organization.handle_id)) host_id = graphene.relay.Node.to_global_id( str(self.host.node_type), str(self.host.handle_id)) address_id = graphene.relay.Node.to_global_id( str(self.address.node_type), str(self.address.handle_id)) service_id = graphene.relay.Node.to_global_id( str(self.service.node_type), str(self.service.handle_id)) cable_id = graphene.relay.Node.to_global_id( str(self.cable.node_type), str(self.cable.handle_id)) # test empty context (test empty parameter and invalid contexts): for context_input in [None, '"Invalid Ctx", "Module"', ""]: context_str = "" if context_input != None: context_str = context_t.format(context_input=context_input) # test exclude true: only contexted nodes exclude = str(True).lower() query = query_t.format( types_str=types_str, context=context_str, exclude=exclude, ) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = {'ninodes': {'edges': [ {'node': {'__typename': 'Organization', 'id': organization_id, 'name': 'organization1'}}, {'node': {'__typename': 'Host', 'id': host_id, 'name': 'host1'}}, {'node': {'__typename': 'Address', 'id': address_id, 'name': 'address1'}} ] } } self.assert_correct(result, expected) # test exclude false: uncontexted nodes (only for superadmin) exclude = str(False).lower() query = query_t.format( types_str=types_str, context=context_str, exclude=exclude, ) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = {'ninodes': {'edges': []}} if self.test_type == "superadmin": expected = {'ninodes': {'edges': [ {'node': {'__typename': 'Service', 'id': service_id, 'name': 'service1'}}, {'node': {'__typename': 'Cable', 'id': cable_id, 'name': 'cable1'}} ]}} self.assert_correct(result, expected) # test filled context: context_input = ", ".join([ '"{}"'.format(x) for x in ["Community", "Network"] ]) context_str = context_t.format(context_input=context_input) # test exclude true: show nodes out of those contexts exclude = str(True).lower() query = query_t.format( types_str=types_str, context=context_str, exclude=exclude, ) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = {'ninodes': {'edges': [ {'node': {'__typename': 'Address', 'id': address_id, 'name': 'address1'}} ] } } self.assert_correct(result, expected) # test exclude false: show nodes in of those contexts exclude = str(False).lower() query = query_t.format( types_str=types_str, context=context_str, exclude=exclude, ) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = {'ninodes': {'edges': [ {'node': {'__typename': 'Organization', 'id': organization_id, 'name': 'organization1'}}, {'node': {'__typename': 'Host', 'id': host_id, 'name': 'host1'}}, ] } } self.assert_correct(result, expected) def test_user_list(self): if not hasattr(self, 'test_type'): return query_t = """ {{ users( filter:{{ username_contains: "{name_contains}" }} ){{ edges{{ node{{ id username }} }} }} }} """ # get both users name_contains = "user" query = query_t.format(name_contains=name_contains) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = { 'users': { 'edges': [ {'node': { 'id': str(self.user.id), 'username': 'test user' }}, {'node': { 'id': str(self.another_user.id), 'username': 'another_user' }}, {'node': { 'id': str(self.other_user.id), 'username': 'other_user' }}, ] } } self.assert_correct(result, expected) # get only one name_contains = "test" query = query_t.format(name_contains=name_contains) result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = { 'users': { 'edges': [ {'node': { 'id': str(self.user.id), 'username': 'test user' }}, ] } } self.assert_correct(result, expected) def test_user_permissions(self): # create a simple group with another user test_user = self.user self.user = self.another_user self.group1 = self.create_node('group1', 'group', meta='Logical') NodeHandleContext( nodehandle=self.group1, context=self.community_ctxt).save() self.user = test_user query = """ { all_groups{ name modifier{ user_permissions{ community{ read list write } network{ read list write } contracts{ read list write } } } } } """ result = schema.execute(query, context=self.context) assert not result.errors, pformat(result.errors, indent=1) expected = None if hasattr(self, 'test_type'): if self.test_type == "user": expected = { 'all_groups': [{ 'name': 'group1', 'modifier': { 'user_permissions': None, } }] } elif self.test_type == "admin" or self.test_type == "superadmin": # check that an admin or superadmin can read permissions of # another user expected = { 'all_groups': [{ 'name': 'group1', 'modifier': { 'user_permissions': { 'community': { 'read': False, 'list': False, 'write': False, }, 'network': { 'read': False, 'list': False, 'write': False, }, 'contracts': { 'read': False, 'list': False, 'write': False, }, } } }] } self.assert_correct(result, expected) class PlainUserPermissionsTest(GenericUserPermissionTest): def setUp(self, group_dict=None): group_dict = { 'community': { 'admin': False, 'read': True, 'list': True, 'write': True, }, 'network': { 'admin': False, 'read': True, 'list': True, 'write': True, }, 'contracts': { 'admin': False, 'read': True, 'list': True, 'write': True, }, } self.test_type = "user" super().setUp(group_dict=group_dict) class AdminUserPermissionsTest(GenericUserPermissionTest): def setUp(self, group_dict=None): group_dict = { 'community': { 'admin': False, 'read': True, 'list': True, 'write': True, }, 'network': { 'admin': True, 'read': True, 'list': True, 'write': True, }, 'contracts': { 'admin': False, 'read': True, 'list': True, 'write': True, }, } self.test_type = "admin" super().setUp(group_dict=group_dict) class SuperAdminUserPermissionsTest(GenericUserPermissionTest): def setUp(self, group_dict=None): group_dict = { 'community': { 'admin': True, 'read': True, 'list': True, 'write': True, }, 'network': { 'admin': True, 'read': True, 'list': True, 'write': True, }, 'contracts': { 'admin': True, 'read': True, 'list': True, 'write': True, }, } self.test_type = "superadmin" super().setUp(group_dict=group_dict)

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0.002597

0

null

0

null

0

1

0

2c5e15ddaa18b77dfb245e91f9e636201f9744ac

1,542

py

Python

alphamind/tests/analysis/test_perfanalysis.py

rongliang-tech/alpha-mind

39f720974c637d17e185e445dc05c9fc4863a241

[ "MIT" ]

186

2017-11-27T01:26:44.000Z

2022-03-28T16:11:33.000Z

alphamind/tests/analysis/test_perfanalysis.py

atefar2/alpha-mind

66d839affb5d81d31d5cac7e5e224278e3f99a8b

[ "MIT" ]

2

2017-12-19T02:47:36.000Z

2021-01-09T05:25:18.000Z

alphamind/tests/analysis/test_perfanalysis.py

atefar2/alpha-mind

66d839affb5d81d31d5cac7e5e224278e3f99a8b

[ "MIT" ]

65

2017-11-27T01:26:47.000Z

2022-03-17T10:50:52.000Z

# -*- coding: utf-8 -*- """ Created on 2017-5-12 @author: cheng.li """ import unittest import numpy as np import pandas as pd from alphamind.analysis.perfanalysis import perf_attribution_by_pos class TestPerformanceAnalysis(unittest.TestCase): @classmethod def test_perf_attribution_by_pos(cls): n_samples = 36000 n_dates = 20 n_risk_factors = 35 dates = np.sort(np.random.randint(n_dates, size=n_samples)) weights_series = pd.Series(data=np.random.randn(n_samples), index=dates) bm_series = pd.Series(data=np.random.randn(n_samples), index=dates) next_bar_return_series = pd.Series(data=np.random.randn(n_samples), index=dates) risk_table = pd.DataFrame(data=np.random.randn(n_samples, n_risk_factors), columns=list(range(n_risk_factors)), index=dates) explained_table = perf_attribution_by_pos(weights_series - bm_series, next_bar_return_series, risk_table) to_explain = (weights_series - bm_series).multiply(next_bar_return_series, axis=0) aggregated_to_explain = pd.Series(to_explain).groupby(dates).sum() aggregated_explained = explained_table.sum(axis=1) np.testing.assert_array_almost_equal(aggregated_to_explain.values, aggregated_explained.values) if __name__ == '__main__': unittest.main()

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null

0

null

0

1

0

2c5f7612ff8eec29cef986e54718511e7172e74e

1,457

py

Python

appengine/src/greenday_api/tests/test_distinct_channels_api.py

meedan/montage

4da0116931edc9af91f226876330645837dc9bcc

[ "Apache-2.0" ]

6

2018-07-31T16:48:07.000Z

2020-02-01T03:17:51.000Z

appengine/src/greenday_api/tests/test_distinct_channels_api.py

meedan/montage

4da0116931edc9af91f226876330645837dc9bcc

[ "Apache-2.0" ]

41

2018-08-07T16:43:07.000Z

2020-06-05T18:54:50.000Z

appengine/src/greenday_api/tests/test_distinct_channels_api.py

meedan/montage

4da0116931edc9af91f226876330645837dc9bcc

[ "Apache-2.0" ]

1

2018-08-07T16:40:18.000Z

""" Tests for :mod:`greenday_api.misc.distinct_channels_api <greenday_api.misc.distinct_channels_api>` """ from protorpc import message_types from .base import ApiTestCase from ..misc.distinct_channels_api import DistinctChannelsAPI class DistinctChannelsAPITests(ApiTestCase): """ Test case for :func:`greenday_api.misc.distinct_channels_api <greenday_api.misc.distinct_channels_api>` """ api_type = DistinctChannelsAPI def setUp(self): """ Bootstrap test case """ super(DistinctChannelsAPITests, self).setUp() self.video_1 = self.create_video( channel_id="123", channel_name="foo") self.video_2 = self.create_video( channel_id="123", channel_name="fez") self.video_3 = self.create_video( channel_id="456", channel_name="bar") def test_get_distinct_channels(self): """ Gets all distinct channels across all videos in Montage """ self._sign_in(self.admin) request = message_types.VoidMessage() response = self.api.get_distinct_channels(request) self.assertEqual(2, len(response.items)) channel_123_resp = next(r for r in response.items if r.id == "123") self.assertEqual("fez", channel_123_resp.name) channel_456_resp = next(r for r in response.items if r.id == "456") self.assertEqual("bar", channel_456_resp.name)

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0

null

0

null

0

1

0

2c6349a307102d7f6afaff901e97fb40d85722ea

3,142

py

Python

pypipegraph/utils/log_listen.py

bopopescu/pypipegraph-2

3a3f9ba565789d8d73c8cd503703a957de2be9d8

[ "MIT" ]

4

2017-05-24T16:57:42.000Z

2017-09-21T19:55:27.000Z

pypipegraph/utils/log_listen.py

bopopescu/pypipegraph-2

3a3f9ba565789d8d73c8cd503703a957de2be9d8

[ "MIT" ]

2

2019-11-22T15:33:47.000Z

2020-07-27T11:59:44.000Z

pypipegraph/utils/log_listen.py

bopopescu/pypipegraph-2

3a3f9ba565789d8d73c8cd503703a957de2be9d8

[ "MIT" ]

4

2015-08-26T15:43:00.000Z

2020-07-20T03:36:40.000Z

""" The MIT License (MIT) Copyright (c) 2012, Florian Finkernagel <finkernagel@imt.uni-marburg.de> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from twisted.internet.protocol import Protocol, Factory, ClientFactory from twisted.internet.error import CannotListenError from twisted.internet import reactor import logging import cPickle import sys try: port = int(sys.argv[1]) except IndexError: port = 5005 of = open("log.txt", "wb") class Debug(Protocol): def dataReceived(self, data): global of try: if data == "please exit": print("End log because other logger requested access") of.write("End log because other logger requested access") reactor.stop() lr = logging.makeLogRecord(cPickle.loads(data[4:])) if lr.getMessage().find("New Pipegraph") != -1: of.close() of = open("log.txt", "wb") print("%s:%i: %s" % (lr.name, lr.lineno, lr.getMessage())) of.write("%s:%i: %s\n" % (lr.name, lr.lineno, lr.getMessage())) of.flush() except cPickle.UnpicklingError: print("a messages was missing") # self.transport.write(data, (host, port)) class Killer(Protocol): def connectionMade(self): print("sending please exit") self.transport.write("please exit") # no need for address self.transport.loseConnection() def connectionLost(self, reason): print("Other logger apperantly exited, now trying to listen again in 2 seconds") reactor.callLater(2, start_listening) class KillerFactory(ClientFactory): protocol = Killer def start_listening(): factory = Factory() factory.protocol = Debug def listening(): print("now listening") factory.startFactory = listening reactor.listenTCP(port, factory) try: start_listening() except CannotListenError: print("trying to send kill signal to already running instance") d = reactor.connectTCP("localhost", port, KillerFactory()) # print "Going to listen on port %i, logging to %s" % (port, of.name) reactor.run()

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null

0

null

0

1

0

2c68214d1193846a164314f13ae12a80f459ffd1

9,130

py

Python

ldapauthenticator/ldapauthenticator.py

jbmarcille/ldapauthenticator

f6037d72bd8c76317b8741d96de1c7b1dee26298

[ "BSD-3-Clause" ]

null

ldapauthenticator/ldapauthenticator.py

jbmarcille/ldapauthenticator

f6037d72bd8c76317b8741d96de1c7b1dee26298

[ "BSD-3-Clause" ]

null

ldapauthenticator/ldapauthenticator.py

jbmarcille/ldapauthenticator

f6037d72bd8c76317b8741d96de1c7b1dee26298

[ "BSD-3-Clause" ]

null

import ldap3 import re from jupyterhub.auth import Authenticator from tornado import gen from traitlets import Unicode, Int, Bool, List, Union class LDAPAuthenticator(Authenticator): server_address = Unicode( config=True, help=""" Address of the LDAP server to contact. Could be an IP address or hostname. """ ) server_port = Int( config=True, help=""" Port on which to contact the LDAP server. Defaults to `636` if `use_ssl` is set, `389` otherwise. """ ) def _server_port_default(self): if self.use_ssl: return 636 # default SSL port for LDAP else: return 389 # default plaintext port for LDAP use_ssl = Bool( True, config=True, help=""" Use SSL to communicate with the LDAP server. Highly recommended! Your LDAP server must be configured to support this, however. """ ) bind_dn_template = Union( [List(),Unicode()], config=True, help=""" Template from which to construct the full dn when authenticating to LDAP. {username} is replaced with the actual username used to log in. If your LDAP is set in such a way that the userdn can not be formed from a template, but must be looked up with an attribute (such as uid or sAMAccountName), please see `lookup_dn`. It might be particularly relevant for ActiveDirectory installs. Unicode Example: uid={username},ou=people,dc=wikimedia,dc=org List Example: [ uid={username},ou=people,dc=wikimedia,dc=org, uid={username},ou=Developers,dc=wikimedia,dc=org ] """ ) allowed_groups = List( config=True, allow_none=True, default=None, help=""" List of LDAP group DNs that users could be members of to be granted access. If a user is in any one of the listed groups, then that user is granted access. Membership is tested by fetching info about each group and looking for the User's dn to be a value of one of `member` or `uniqueMember`, *or* if the username being used to log in with is value of the `uid`. Set to an empty list or None to allow all users that have an LDAP account to log in, without performing any group membership checks. """ ) # FIXME: Use something other than this? THIS IS LAME, akin to websites restricting things you # can use in usernames / passwords to protect from SQL injection! valid_username_regex = Unicode( r'^[a-z][.a-z0-9_-]*$', config=True, help=""" Regex for validating usernames - those that do not match this regex will be rejected. This is primarily used as a measure against LDAP injection, which has fatal security considerations. The default works for most LDAP installations, but some users might need to modify it to fit their custom installs. If you are modifying it, be sure to understand the implications of allowing additional characters in usernames and what that means for LDAP injection issues. See https://www.owasp.org/index.php/LDAP_injection for an overview of LDAP injection. """ ) lookup_dn = Bool( False, config=True, help=""" Form user's DN by looking up an entry from directory By default, LDAPAuthenticator finds the user's DN by using `bind_dn_template`. However, in some installations, the user's DN does not contain the username, and hence needs to be looked up. You can set this to True and then use `user_search_base` and `user_attribute` to accomplish this. """ ) user_search_base = Unicode( config=True, default=None, allow_none=True, help=""" Base for looking up user accounts in the directory, if `lookup_dn` is set to True. LDAPAuthenticator will search all objects matching under this base where the `user_attribute` is set to the current username to form the userdn. For example, if all users objects existed under the base ou=people,dc=wikimedia,dc=org, and the username users use is set with the attribute `uid`, you can use the following config: ``` c.LDAPAuthenticator.lookup_dn = True c.LDAPAuthenticator.user_search_base = 'ou=people,dc=wikimedia,dc=org' c.LDAPAuthenticator.user_attribute = 'uid' ``` """ ) user_attribute = Unicode( config=True, default=None, allow_none=True, help=""" Attribute containing user's name, if `lookup_dn` is set to True. See `user_search_base` for info on how this attribute is used. For most LDAP servers, this is uid. For Active Directory, it is sAMAccountName. """ ) @gen.coroutine def authenticate(self, handler, data): username = data['username'] password = data['password'] # Get LDAP Connection def getConnection(userdn, username, password): server = ldap3.Server( self.server_address, port=self.server_port, use_ssl=self.use_ssl ) self.log.debug('Attempting to bind {username} with {userdn}'.format( username=username, userdn=userdn )) conn = ldap3.Connection(server, user=userdn, password=password) return conn # Protect against invalid usernames as well as LDAP injection attacks if not re.match(self.valid_username_regex, username): self.log.warn('username:%s Illegal characters in username, must match regex %s', username, self.valid_username_regex) return None # No empty passwords! if password is None or password.strip() == '': self.log.warn('username:%s Login denied for blank password', username) return None isBound = False self.log.debug("TYPE= '%s'",isinstance(self.bind_dn_template, list)) # In case, there are multiple binding templates if isinstance(self.bind_dn_template, list): for dn in self.bind_dn_template: userdn = dn.format(username=username) conn = getConnection(userdn, username, password) isBound = conn.bind() self.log.debug('Status of user bind {username} with {userdn} : {isBound}'.format( username=username, userdn=userdn, isBound=isBound )) if isBound: break else: userdn = self.bind_dn_template.format(username=username) conn = getConnection(userdn, username, password) isBound = conn.bind() if isBound: if self.allowed_groups: if self.lookup_dn: # In some cases, like AD, we don't bind with the DN, and need to discover it. conn.search( search_base=self.user_search_base, search_scope=ldap3.SUBTREE, search_filter='({userattr}={username})'.format( userattr=self.user_attribute, username=username ), attributes=[self.user_attribute] ) if len(conn.response) == 0: self.log.warn('username:%s No such user entry found when looking up with attribute %s', username, self.user_attribute) return None userdn = conn.response[0]['dn'] self.log.debug('username:%s Using dn %s', username, userdn) for group in self.allowed_groups: groupfilter = ( '(|' '(member={userdn})' '(uniqueMember={userdn})' '(memberUid={uid})' ')' ).format(userdn=userdn, uid=username) groupattributes = ['member', 'uniqueMember', 'memberUid'] if conn.search( group, search_scope=ldap3.BASE, search_filter=groupfilter, attributes=groupattributes ): return username # If we reach here, then none of the groups matched self.log.warn('username:%s User not in any of the allowed groups', username) return None else: return username else: self.log.warn('Invalid password for user {username}'.format( username=username, )) return None

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false

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0.139303

0

null

0

null

0

1

0

2c6b0c96f51c49cf2ddaf1214e424470ce2b7534

23,329

py

Python

PyText3.py

Shock9616/PyText3

f16214060390ae8b457fc8dfbdb0943c7c34720b

[ "MIT" ]

null

PyText3.py

Shock9616/PyText3

f16214060390ae8b457fc8dfbdb0943c7c34720b

[ "MIT" ]

null

PyText3.py

Shock9616/PyText3

f16214060390ae8b457fc8dfbdb0943c7c34720b

[ "MIT" ]

1

2021-11-06T13:45:11.000Z

#!/usr/bin/env python3 """ The main file for a basic code editor written entirely with the python standard library main.py PyText3 Text Editor Created by Kaleb Rosborough on 10/23/2018 Copyright © Shock9616 2018 All rights reserved """ #region Imports from tkinter import * import tkinter as tk from tkinter import filedialog, simpledialog, messagebox, END from tkinter import ttk import os import sys import prefs import themes try: # Try to import third party modules. import syntaxhighlighting except ImportError: pass #endregion #region Global Variables COL_BG = "grey" COL_FG = "white" CURRENT_FILE = "untitled" #endregion #region Custom Classes class TextLineNumbers(tk.Canvas): """ Custom canvas class for creating line numbers """ def __init__(self, *args, **kwargs): tk.Canvas.__init__(self, *args, **kwargs) self.textwidget = None def attach(self, text_widget): self.textwidget = text_widget def redraw(self, fillcolor): """ redraw line numbers """ self.delete("all") i = self.textwidget.index("@0,0") while True: dline = self.textwidget.dlineinfo(i) if dline is None: break y = dline[1] linenum = str(i).split(".")[0] self.create_text(2, y, anchor="nw", text=linenum, fill=fillcolor) i = self.textwidget.index("%s+1line" % i) class CustomText(tk.Text): """ A custom text field class that can have line numbers attatched to it """ def __init__(self, *args, **kwargs): tk.Text.__init__(self, *args, **kwargs) # create a proxy for the underlying widget self._orig = self._w + "_orig" self.tk.call("rename", self._w, self._orig) self.tk.createcommand(self._w, self._proxy) def _proxy(self, *args): # let the actual widget perform the requested action cmd = (self._orig,) + args try: result = self.tk.call(cmd) except Exception: return None # generate an event if something was added or deleted, # or the cursor position changed if (args[0] in ("insert", "replace", "delete") or args[0:3] == ("mark", "set", "insert") or args[0:2] == ("xview", "moveto") or args[0:2] == ("xview", "scroll") or args[0:2] == ("yview", "moveto") or args[0:2] == ("yview", "scroll") ): self.event_generate("<<Change>>", when="tail") # return what the actual widget returned return result ########################################## #endregion #region Command Definitions def onChange(event): fillColor = "#FFFFFF" linenumbers.redraw(fillcolor=fillColor) cursorPos = (textField.index(INSERT)).split(".") lineCount.config(text=("Line: " + cursorPos[0])) columnCount.config(text=("Column: " + str(int(cursorPos[1]) + 1))) # syntaxhighlighting.HighlightSyntax(textField, defaultTheme, language) def closeWindow(event=None): if messagebox.askyesno("Quit", "Are you sure you want to exit?", icon="question"): if messagebox.askyesno("Save", "Would you like to save the current file?", icon="question"): saveFile() root.destroy() quit(1) #region File Menu Commands def newFile(event=None): # if len(textField.get("1.0", END + "-1c")) > 0: # If there is something in the file if messagebox.askyesno("Save", "Would you like to save the current file?", icon="question"): saveFile() textField.delete("1.0", tk.END) else: textField.delete("1.0", tk.END) def openFile(event=None): file = filedialog.askopenfile(parent=root, mode="rb", title="Select a file to open") if messagebox.askyesno("Save", "Would you like to save the current file?", icon="question"): saveFile() if file is not None: contents = file.read() textField.delete("1.0", END) textField.insert("1.0", contents) CURRENT_FILE = file.name root.title(CURRENT_FILE) file.close() ####################################################### def saveFileAs(event=None): selectedLanguage = language.get() if selectedLanguage == prefs.LANGUAGES[0]: file = filedialog.asksaveasfile(mode="w", defaultextension=".cpp", filetypes=( ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Swift File", "*.swift"), ("Text File", "*.txt"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[1]: file = filedialog.asksaveasfile(mode="w", defaultextension=".html", filetypes=( ("HTML File", "*.html"), ("C++ File", "*.cpp"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Swift File", "*.swift"), ("Text File", "*.txt"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[2]: file = filedialog.asksaveasfile(mode="w", defaultextension=".java", filetypes=( ("Java File", "*.java"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Swift File", "*.swift"), ("Text File", "*.txt"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[3]: file = filedialog.asksaveasfile(mode="w", defaultextension=".js", filetypes=( ("JavaScript File", "*.js"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("Python File", "*.py"), ("Swift File", "*.swift"), ("Text File", "*.txt"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[4]: file = filedialog.asksaveasfile(mode="w", defaultextension=".txt", filetypes=( ("Text File", "*.txt"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Swift File", "*.swift"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[5]: file = filedialog.asksaveasfile(mode="w", defaultextension=".py", filetypes=( ("Python File", "*.py"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Swift File", "*.swift"), ("Text File", "*.txt"), ("All Files", "*.*") )) elif selectedLanguage == prefs.LANGUAGES[6]: file = filedialog.asksaveasfile(mode="w", defaultextension=".swift", filetypes=( ("Swift File", "*.swift"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Text File", "*.txt"), ("All Files", "*.*") )) else: file = filedialog.asksaveasfile(mode="w", defaultextension=".", filetypes=( ("All Files", "*.*"), ("Text File", "*.txt"), ("C++ File", "*.cpp"), ("HTML File", "*.html"), ("Java File", "*.java"), ("JavaScript File", "*.js"), ("Python File", "*.py"), ("Swift File", "*.swift") )) if file is None: return fileContent = textField.get(1.0, "end") file.write(fileContent) CURRENT_FILE = file.name root.title(CURRENT_FILE) file.close() def saveFile(event=None): print("Saving file...") exists = os.path.isfile(str(CURRENT_FILE)) if exists: with open(CURRENT_FILE, "w") as file: file.write(textField.get("1.0", "end")) else: saveFileAs() ####################################################### #endregion #region Edit Menu Commands def undo(event=None): textField.event_generate("<<Undo>>") def redo(event=None): textField.event_generate("<<Redo>>") ####################################################### def copySelected(event=None): selectedText = textField.selection_get() root.clipboard_clear() root.clipboard_append(selectedText) def cutSelected(event=None): textField.event_generate("<<Cut>>") def paste(event=None): textField.event_generate("<<Paste>>") return "break" def selectAll(event=None): textField.tag_add(SEL, "1.0", END) textField.mark_set(INSERT, "1.0") textField.see(INSERT) return "break" ####################################################### def find(event=None): textField.tag_remove("found", "1.0", END) searchedText = simpledialog.askstring("Find", "Enter the text you want to find:") if searchedText == "": done = messagebox.showerror("Find", "Error: You did not enter any text") if searchedText: idx = "1.0" while 1: idx = textField.search(searchedText, idx, nocase=1, stopindex=END) if not idx: break lastidx = "%s+%dc" % (idx, len(searchedText)) textField.tag_add("found", idx, lastidx) idx = lastidx done = messagebox.showinfo("Find", "Highlighting all instances of " + searchedText + ".") if done: textField.tag_remove("found", "1.0", END) def replace(event=None): searchedText = simpledialog.askstring("Replace", "Enter the text you want to replace:") if searchedText: idx = "1.0" while 1: idx = textField.search(searchedText, idx, nocase=1, stopindex=END) if not idx: break lastidx = "%s+%dc" % (idx, len(searchedText)) textField.tag_add("replace", idx, lastidx) idx = lastidx replaceText = simpledialog.askstring("Replace", "Enter the text you want to replace with:") if replaceText: idx = "1.0" while 1: idx = textField.search(searchedText, idx, nocase=1, stopindex=END) if not idx: break start = textField.index("replace.first") end = textField.index("replace.last") textField.insert(end, replaceText) textField.delete(start, end) #endregion #region Options Menu Commands def openPreferences(): def applySettings(): newFont = font.get() fontSaveFile = open("font.sav", "w+") fontSaveFile.write(newFont) fontSaveFile.close() if sys.platform.startswith("darwin"): textField.configure(font=(newFont, 12)) else: textField.configure(font=(newFont, 10)) newTheme = theme.get() themeSaveFile = open("theme.sav", "w+") themeSaveFile.write(newTheme) themeSaveFile.close() themes.setTheme(textField, linenumbers, newTheme) def applyAndCloseSettings(): applySettings() pw.destroy() def cancelSettings(): pw.destroy() pw = Toplevel() pw.minsize(width=250, height=226) pw.title("Preferences") if sys.platform.startswith("darwin"): pw.iconbitmap("images/settingsicon.icns") else: pw.iconbitmap("images/settingsicon.ico") pw.wm_attributes("-topmost", 1) labelColumn = 0 listColumn = 1 fontRow = 0 themeRow = 1 # ***** Font Settings ***** currentFont = open("font.sav", "r").readline() font = StringVar(pw) if currentFont in prefs.FONTS: font.set(currentFont) else: font.set(prefs.FONTS[2]) # Default font fontLabel = Label(pw, text="Font", padx=10) fontLabel.grid(row=0, column=0) fontList = OptionMenu(pw, font, *prefs.FONTS) fontList.config(width=15) fontList.grid(row=0, column=1) # ***** Theme Settings ***** currentTheme = open("theme.sav", "r").readline() theme = StringVar(pw) if currentTheme in prefs.THEMES: theme.set(currentTheme) # Default Theme else: theme.set(prefs.THEMES[26]) themeLabel = Label(pw, text="Theme", padx=10) themeLabel.grid(row=1, column=0) themeList = OptionMenu(pw, theme, *prefs.THEMES) themeList.config(width=15) themeList.grid(row=1, column=1) # ***** Preview ***** PREVEIW_TEXT = Text(pw, width=48, height=11) previewTextContent = prefs.PREVEIW_TEXT PREVEIW_TEXT.insert(END, previewTextContent) PREVEIW_TEXT.config(state="disabled") PREVEIW_TEXT.grid(row=0, column=3, rowspan=3, columnspan=15, padx=5, pady=5) # ***** Apply, Ok, and Cancel buttons ***** okButton = Button(pw, text="Ok", command=applyAndCloseSettings) okButton.grid(row=5, column=13, padx=5, pady=5) applyButton = Button(pw, text="Apply", command=applySettings) applyButton.grid(row=5, column=14, padx=5, pady=5) cancelButton = Button(pw, text="Cancel", command=cancelSettings) cancelButton.grid(row=5, column=15, padx=5, pady=5) pw.mainloop() #endregion #region Help Menu Commands def aboutPyText3(event=None): label = messagebox.showinfo("About PyText3", "Shock9616\nVersion: 1.0\n© 2018 Shock9616 All rights reserved", icon="info") def showCredits(event=None): cw = messagebox.showinfo("PyText3 Credits", prefs.CREDITS_TEXT, icon="info") #endregion #endregion #region UI Setup if __name__ == "__main__": print("Running PyText3 on " + sys.platform) root = tk.Tk() root.configure() root.minsize(width=650, height=450) root.title(CURRENT_FILE) if sys.platform.startswith("darwin"): root.iconbitmap("images/icon.icns") else: root.iconbitmap("images/icon.ico") root.protocol("WM_DELETE_WINDOW", closeWindow) textFont = open("font.sav", "r").readline() #region Set up basic UI elements defaultTheme = open("theme.sav", "r").readline() defaultFont = open("font.sav", "r").readline() toolBar = Frame(root, bd=1, relief="sunken") toolBar.pack(side="top", fill="x") textField = CustomText(root, wrap=NONE, undo=True, border=0) hsb = tk.Scrollbar(orient="horizontal", command=textField.xview) vsb = tk.Scrollbar(orient="vertical", command=textField.yview) textField.configure(yscrollcommand=vsb.set, xscrollcommand=hsb.set, font=(textFont, 10)) textField.tag_configure("bigfont", font=("Helvetica", "10", "bold")) textField.tag_configure("found", background="gray") textField.tag_configure("replace", background="gray") if sys.platform.startswith("darwin"): textField.configure(font=(defaultFont, 12)) else: textField.configure(font=(defaultFont, 10)) linenumbers = TextLineNumbers(width=30, highlightthickness=1) linenumbers.attach(textField) statusBar = Frame(root, bd=1, height=50, relief="sunken") statusBar.pack(side="bottom", fill="x") hsb.pack(side="bottom", fill="x") vsb.pack(side="right", fill="y") linenumbers.pack(side="left", fill="y") textField.pack(side="right", fill="both", expand=True) textField.bind("<<Change>>", onChange) textField.bind("<Configure>", onChange) linenumbers.configure(highlightthickness=0) themes.setTheme(textField, linenumbers, defaultTheme) cursorPos = str(textField.index(INSERT)).split(".") #endregion #region Set up menu bar menuBar = Menu(root) root.config(menu=menuBar) #region Create Menu Bar Sub-Menus fileMenu = Menu(menuBar, tearoff=False) menuBar.add_cascade(label="File", menu=fileMenu) editMenu = Menu(menuBar, tearoff=False) menuBar.add_cascade(label="Edit", menu=editMenu) optionsMenu = Menu(menuBar, tearoff=False) menuBar.add_cascade(label="Options", menu=optionsMenu) #endregion #region Fill Sub-Menus for Windows and Linux if sys.platform.startswith("win32") or sys.platform.startswith("linux"): # ***** File Menu ***** fileMenu.add_command(label="New File", command=newFile, accelerator="Ctrl+N") fileMenu.add_command(label="Open", command=openFile, accelerator="Ctrl+O") fileMenu.add_separator() fileMenu.add_command(label="Save", command=saveFile, accelerator="Ctrl+S") fileMenu.add_command(label="Save As", command=saveFileAs, accelerator="Ctrl+^+N") # ***** Edit Menu ***** editMenu.add_command(label="Undo", command=undo, accelerator="Ctrl+Z") editMenu.add_command(label="Redo", command=redo, accelerator="Ctrl+^+Z") editMenu.add_separator() editMenu.add_command(label="Cut", command=cutSelected, accelerator="Ctrl+X") editMenu.add_command(label="Copy", command=copySelected, accelerator="Ctrl+C") editMenu.add_command(label="Paste", command=paste, accelerator="Ctrl+V") editMenu.add_command(label="Select All", command=selectAll, accelerator="Ctrl+A") editMenu.add_separator() editMenu.add_command(label="Find", command=find, accelerator="Ctrl+F") editMenu.add_command(label="Replace", command=replace, accelerator="Ctrl+H") # ***** Options Menu ***** optionsMenu.add_command(label="Preferences", command=openPreferences) #endregion #region Fill Sub-Menus for Mac OS elif sys.platform.startswith("darwin"): # ***** File Menu ***** fileMenu.add_command(label="New File", command=newFile, accelerator="Cmd+N") fileMenu.add_command(label="Open", command=openFile, accelerator="Cmd+O") fileMenu.add_separator() fileMenu.add_command(label="Save", command=saveFile, accelerator="Cmd+S") fileMenu.add_command(label="Save As", command=saveFileAs, accelerator="Cm^+S") # ***** Edit Menu ***** editMenu.add_command(label="Undo", command=undo, accelerator="Cmd+Z") editMenu.add_command(label="Redo", command=redo, accelerator="Cmd+Shift+Z") editMenu.add_separator() editMenu.add_command(label="Cut", command=cutSelected, accelerator="Cmd+X") editMenu.add_command(label="Copy", command=copySelected, accelerator="Cmd+C") editMenu.add_command(label="Paste", command=paste, accelerator="Cmd+V") editMenu.add_command(label="Select All", command=selectAll, accelerator="CtCmd") editMenu.add_separator() editMenu.add_command(label="Find", command=find, accelerator="Cmd+F") editMenu.add_command(label="Replace", command=replace, accelerator="Cmd+H") # ***** Options Menu ***** optionsMenu.add_command(label="Preferences", command=openPreferences, accelerator="Cmd+,") #endregion #region Help Menu helpMenu = Menu(menuBar, tearoff=False) menuBar.add_cascade(menu=helpMenu, label="Help") helpMenu.add_command(label="About", command=aboutPyText3) helpMenu.add_command(label="Credits", command=showCredits) #endregion #region Status Bar lineCount = Label(statusBar, text=("Line " + cursorPos[0]), bd=1) lineCount.pack(side="left") columnCount = Label(statusBar, text=("Column " + cursorPos[1]), bd=1) columnCount.pack(side="left") language = StringVar(root) language.set(prefs.LANGUAGES[4]) languageSwitcher = OptionMenu(statusBar, language, *prefs.LANGUAGES) languageSwitcher.config(indicator=False, compound="none", relief="flat") languageSwitcher.pack(side="right", expand="no", fill="y") separator = ttk.Separator(statusBar, orient="vertical") separator.pack(side="right", fill="y") #endregion #endregion #region Set up key bindings #region Windows and Linux if sys.platform.startswith("win32") or sys.platform.startswith("linux"): textField.bind("<Control-n>", newFile) textField.bind("<Control-N>", newFile) textField.bind("<Control-o>", openFile) textField.bind("<Control-O>", openFile) textField.bind("<Control-s>", saveFile) textField.bind("<Control-S>", saveFile) textField.bind("<Control-Shift-s>", saveFileAs) textField.bind("<Control-Shift-S>", saveFileAs) textField.bind("<Control-n>", newFile) textField.bind("<Control-n>", newFile) textField.bind("<Control-q>", closeWindow) textField.bind("<Control-Q>", closeWindow) textField.bind("<Control-z>", undo) textField.bind("<Control-Z>", undo) textField.bind("<Control-Shift-z>", redo) textField.bind("<Control-Shift-Z>", redo) textField.bind("<Control-c>", copySelected) textField.bind("<Control-C>", copySelected) textField.bind("<Control-v>", paste) textField.bind("<Control-V>", paste) textField.bind("<Control-a>", selectAll) textField.bind("<Control-A>", selectAll) textField.bind("<Control-f>", find) textField.bind("<Control-F>", find) textField.bind("<Control-h>", replace) textField.bind("<Control-H>", replace) #endregion #region Mac OS elif sys.platform.startswith("darwin"): textField.bind("<Command-n>", newFile) textField.bind("<Command-N>", newFile) textField.bind("<Command-o>", openFile) textField.bind("<Command-O>", openFile) textField.bind("<Command-s>", saveFile) textField.bind("<Command-S>", saveFile) textField.bind("<Command-Shift-s>", saveFileAs) textField.bind("<Command-Shift-S>", saveFileAs) textField.bind("<Command-n>", newFile) textField.bind("<Command-n>", newFile) textField.bind("<Command-q>", closeWindow) textField.bind("<Command-Q>", closeWindow) textField.bind("<Command-z>", undo) textField.bind("<Command-Z>", undo) textField.bind("<Command-Shift-z>", redo) textField.bind("<Command-Shift-Z>", redo) textField.bind("<Command-x>", cutSelected) textField.bind("<Command-X>", cutSelected) textField.bind("<Command-c>", copySelected) textField.bind("<Command-C>", copySelected) textField.bind("<Command-v>", paste) textField.bind("<Command-V>", paste) textField.bind("<Command-a>", selectAll) textField.bind("<Command-A>", selectAll) textField.bind("<Command-f>", find) textField.bind("<Command-F>", find) textField.bind("<Command-h>", replace) textField.bind("<Command-H>", replace) #endregion #endregion root.mainloop() #endregion

37.207337

114

0.582365

2,506

23,329

5.378292

0.180367

0.054014

0.031162

0.027304

0.481451

0.433076

0.387298

0.374833

0.290473

0.225479

0

0.011048

0.251147

23,329

626

115

37.266773

0.760332

0.071885

0

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0

0.158422

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0

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false

0.002132

0.021322

0

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0.004264

0

null

0

null

0

1

0

2c6b575ef99f368943f9457f0e564df734ee7fbc

569

py

Python

array/0075_sort_colors/0075_sort_colors.py

zdyxry/LeetCode

33371285d0f3302158230f46e8b1b63b9f4639c4

[ "Xnet", "X11" ]

6

2019-09-16T01:50:44.000Z

2020-09-17T08:52:25.000Z

array/0075_sort_colors/0075_sort_colors.py

zdyxry/LeetCode

33371285d0f3302158230f46e8b1b63b9f4639c4

[ "Xnet", "X11" ]

null

array/0075_sort_colors/0075_sort_colors.py

zdyxry/LeetCode

33371285d0f3302158230f46e8b1b63b9f4639c4

[ "Xnet", "X11" ]

4

2020-02-07T12:43:16.000Z

2021-04-11T06:38:55.000Z

class Solution(object): def sortColors(self, nums): def triPartition(nums, target): i,j,n = 0, 0,len(nums) -1 while j <= n: if nums[j] < target: nums[i], nums[j] = nums[j], nums[i] i += 1 j += 1 elif nums[j] > target: nums[j], nums[n] = nums[n], nums[j] n -=1 else: j +=1 triPartition(nums, 1) nums = [2,0,2,1,1,0] Solution().sortColors(nums) print(nums)

27.095238

55

0.391916

70

569

3.185714

0.3

0.134529

0.121076

0.134529

0

0.046358

0.469244

569

21

56

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2c6b6b00c0e5fe6ce8b9350c4a38df05692a0c5c

2,545

py

Python

transforms/h52h5.py

srujanm/ibex

ed8167b8b1573830bee39c469db7733fdfcb41d1

[ "MIT" ]

3

2018-08-10T21:11:09.000Z

2019-07-26T13:47:24.000Z

transforms/h52h5.py

srujanm/ibex

ed8167b8b1573830bee39c469db7733fdfcb41d1

[ "MIT" ]

null

transforms/h52h5.py

srujanm/ibex

ed8167b8b1573830bee39c469db7733fdfcb41d1

[ "MIT" ]

6

2018-03-05T20:14:11.000Z

2020-07-23T18:39:16.000Z

# general functions for transforming h5 files from ibex.utilities.constants import * from numba import jit import numpy as np import math # downsample the data by (z, y, x) ratio @jit(nopython=True) def DownsampleData(data, ratio=(1, 2, 2)): # get the size of the current dataset (zres, yres, xres) = data.shape # create an empty array for downsampling (down_zres, down_yres, down_xres) = (int(zres / ratio[IB_Z]), int(yres / ratio[IB_Y]), int(xres / ratio[IB_X])) downsampled_data = np.zeros((down_zres, down_yres, down_xres), dtype=data.dtype) # fill in the entries of the array for iz in range(down_zres): for iy in range(down_yres): for ix in range(down_xres): downsampled_data[iz,iy,ix] = data[int(iz * ratio[IB_Z]), int(iy * ratio[IB_Y]), int(ix * ratio[IB_X])] return downsampled_data @jit(nopython=True) def MaskAndCropSegmentation(data, labels): # create a set of valid segments ids = set() for label in labels: ids.add(label) # get the shape of the data zres, yres, xres = data.shape zmin, ymin, xmin = data.shape zmax, ymax, xmax = (0, 0, 0) masked_data = np.zeros((zres, yres, xres), dtype=np.int64) # go through the entire data set for iz in range(zres): for iy in range(yres): for ix in range(xres): # skip masked out values if not data[iz,iy,ix] in ids: continue masked_data[iz,iy,ix] = data[iz,iy,ix] if iz < zmin: zmin = iz if iy < ymin: ymin = iy if ix < xmin: xmin = ix if iz > zmax: zmax = iz if iy > ymax: ymax = iy if ix > xmax: xmax = ix return masked_data[zmin:zmax,ymin:ymax,xmin:xmax] # split the data to create training and validation data @jit(nopython=True) def SplitData(data, axis, threshold=0.5): assert (0 <= axis and axis <= 2) # get the separation index separation = int(threshold * data.shape[axis]) # split the data into two components if (axis == 0): training_data = data[0:separation,:,:] validation_data = data[separation:,:,:] elif (axis == 1): training_data = data[:,0:separation,:] validation_data = data[:,separation:,:] else: training_data = data[:,:,0:separation] validation_data = data[:,:,separation:] # return the training and validation data return training_data, validation_data

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0

2c6ed73d803fe3c8ab6eab6f07fcada596456cd6

7,933

py

Python

src/lingcomp/farm/prediction_head.py

CharlottePouw/interpreting-complexity

b9a73c0aff18e4c6b4209a6511d00639494c70da

[ "Apache-2.0" ]

2

2020-12-18T12:26:22.000Z

2020-12-19T18:47:07.000Z

src/lingcomp/farm/prediction_head.py

CharlottePouw/interpreting-complexity

b9a73c0aff18e4c6b4209a6511d00639494c70da

[ "Apache-2.0" ]

null

src/lingcomp/farm/prediction_head.py

CharlottePouw/interpreting-complexity

b9a73c0aff18e4c6b4209a6511d00639494c70da

[ "Apache-2.0" ]

1

2021-05-19T13:39:45.000Z

import logging import os import torch from farm.modeling.prediction_head import FeedForwardBlock, PredictionHead from torch.nn import MSELoss from torch.nn.functional import pad from lingcomp.farm.utils import roll logger = logging.getLogger(__name__) # TokenRegressionHead class TokenRegressionHead(PredictionHead): def __init__(self, layer_dims=[768, 1], task_name="token_regression", spillover=0, mask_cls=True, **kwargs): """ :param layer_dims: The size of the layers in the feed forward component. The feed forward will have as many layers as there are ints in this list. :type layer_dims: list :param task_name: :param spillover: If > 0, token values are summed with a kernel of this size before being passed to the feedforward layer. :param mask_cls: If spillover is specified, defines if the initial token should be masked or not during averaging. :param kwargs: """ super(TokenRegressionHead, self).__init__() # num_labels could in most cases also be automatically retrieved from the data processor self.layer_dims = layer_dims # num_labels is being set to 2 since it is being hijacked to store the scaling factor and the mean self.num_labels = 2 if spillover > 0: logger.info(f"Spillover mode with size {spillover}, mask_cls: {mask_cls}") logger.info( f"Prediction head initialized with size [{self.layer_dims[0]} * {(spillover + 1)}, {self.layer_dims[1]}]" ) self.feed_forward = FeedForwardBlock([self.layer_dims[0] * (spillover + 1), self.layer_dims[1]]) else: logger.info(f"Prediction head initialized with size {self.layer_dims}") self.feed_forward = FeedForwardBlock(self.layer_dims) self.loss_fct = MSELoss(reduction="none") self.ph_output_type = "per_token" self.model_type = "token_regression" self.task_name = task_name self.spillover = spillover self.mask_cls = mask_cls self.generate_config() @classmethod def load(cls, pretrained_model_name_or_path): """ Load a prediction head from a saved FARM or transformers model. `pretrained_model_name_or_path` can be one of the following: a) Local path to a FARM prediction head config (e.g. my-bert/prediction_head_0_config.json) :param pretrained_model_name_or_path: local path of a saved model or name of a publicly available model. See https://huggingface.co/models for full list """ if ( os.path.exists(pretrained_model_name_or_path) and "config.json" in pretrained_model_name_or_path and "prediction_head" in pretrained_model_name_or_path ): # a) FARM style head = super(TokenRegressionHead, cls).load(pretrained_model_name_or_path) else: raise NotImplementedError("Load from Transformers not supported yet.") return head def forward(self, X): if self.spillover > 0: if self.mask_cls: # Create mask on [CLS] cls_mask = torch.ones(X.size()).bool() cls_mask[:, 0, :] = False # Apply mask # [batch, seq_len, hidden] => [batch, seq_len - 1, hidden] m = X[cls_mask].reshape(X.shape[0], X.shape[1] - 1, X.shape[2]) # Rolling concat of embeddings for spillover tokens # [batch, seq_len - 1, hidden] => [batch, seq_len - 1, hidden * (spillover + 1)] out = torch.cat([roll(m, shift, 1, 0) for shift in range(self.spillover, -1, -1)], dim=2) ret = torch.cat((pad(X[:, 0, :].unsqueeze(1), (0, out.shape[2] - X.shape[2], 0, 0)), out), dim=1) else: # Rolling sum of the unmasked sequence ret = torch.cat([roll(X, shift, 1, 0) for shift in range(self.spillover, -1, -1)], dim=2) logits = self.feed_forward(ret) else: logits = self.feed_forward(X) return logits def logits_to_loss(self, logits, initial_mask, padding_mask=None, **kwargs): label_ids = kwargs.get(self.label_tensor_name) label_ids = label_ids.float() # masking on padding and non-initial tokens active_loss = (padding_mask.view(-1) == 1) & (initial_mask.view(-1) == 1) active_logits = logits.view(-1)[active_loss] active_labels = label_ids.view(-1)[active_loss] loss = self.loss_fct(active_logits, active_labels) # loss is a 1 dimensional (active) token loss return loss def logits_to_preds(self, logits, initial_mask, **kwargs): preds_token = logits.detach().cpu().numpy() initial_mask = initial_mask.detach().cpu().numpy() preds_word_all = [] for preds_token_one_sample, initial_mask_one_sample in zip(preds_token, initial_mask): # Get labels and predictions for just the word initial tokens preds_word_id = self.initial_token_only(preds_token_one_sample, initial_mask=initial_mask_one_sample) # Rescaling predictions to actual label distributions preds_word = [x[0] * self.label_list[1] + self.label_list[0] for x in preds_word_id] preds_word_all.append(preds_word) return preds_word_all def prepare_labels(self, initial_mask, **kwargs): label_ids = kwargs.get(self.label_tensor_name) label_ids = label_ids.cpu().numpy() initial_mask = initial_mask.detach().cpu().numpy() labels_all = [] for label_ids_one_sample, initial_mask_one_sample in zip(label_ids, initial_mask): label_ids = self.initial_token_only(label_ids_one_sample, initial_mask=initial_mask_one_sample) labels = [x * self.label_list[1] + self.label_list[0] for x in label_ids] labels_all.append(labels) return labels_all @staticmethod def initial_token_only(seq, initial_mask): ret = [] for init, s in zip(initial_mask, seq): if init: ret.append(s) return ret def formatted_preds(self, logits, initial_mask, samples, **kwargs): preds = self.logits_to_preds(logits, initial_mask) # align back with original input by getting the original word spans spans = [] for sample, _ in zip(samples, preds): word_spans = [] span = None for token, offset, start_of_word in zip( sample.tokenized["tokens"], sample.tokenized["offsets"], sample.tokenized["start_of_word"], ): if start_of_word: # previous word has ended unless it's the very first word if span is not None: word_spans.append(span) span = {"start": offset, "end": offset + len(token)} else: # expand the span to include the subword-token span["end"] = offset + len(token.replace("##", "")) word_spans.append(span) spans.append(word_spans) assert len(preds) == len(spans) res = {"task": self.task_name, "predictions": []} for preds_seq, sample, spans_seq in zip(preds, samples, spans): seq_res = [] for score, span in zip(preds_seq, spans_seq): context = sample.clear_text["text"][span["start"] : span["end"]] seq_res.append( { "start": span["start"], "end": span["end"], "context": f"{context}", f"{self.task_name}_score": f"{score}", } ) res["predictions"].append(seq_res) return res

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null

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null

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0

2c7013fe7de804ea6c1f8cce79d5e2ec488e9041

381

py

Python

6.00.2x/week1/lecture1/more_on_plotting.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

6.00.2x/week1/lecture1/more_on_plotting.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

6.00.2x/week1/lecture1/more_on_plotting.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

import matplotlib.pyplot as pylab principal = 10000 interestRate = 0.05 years = 20 values = [] for i in range(years + 1): values.append(principal) principal += principal * interestRate pylab.plot(range(years + 1), values, linewidth=3) pylab.title('5% Growth, Compaunded Annually') pylab.xlabel('Years or Compounding') pylab.ylabel('Value of Principal ($)') pylab.show()

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null

0

null

0

1

0

2c7496e73af3dc1a12f6aa6a4517eb8851e79e00

972

py

Python

activitypub/lib.py

wakin-/simple_ap

f13013fdc79207cfb07f3944caeeef45fe31bbf7

[ "MIT" ]

10

2018-06-18T09:17:59.000Z

2020-04-22T11:46:12.000Z

activitypub/lib.py

wakin-/simple_ap

f13013fdc79207cfb07f3944caeeef45fe31bbf7

[ "MIT" ]

4

2020-06-05T18:24:12.000Z

2021-06-10T20:29:49.000Z

activitypub/lib.py

wakin-/simple_ap

f13013fdc79207cfb07f3944caeeef45fe31bbf7

[ "MIT" ]

null

import requests import json from urllib.parse import urlparse from httpsig import HeaderSigner from datetime import datetime def sign_headers(account, method, path): sign = HeaderSigner(account.ap_id(), account.private_key, algorithm='rsa-sha256', headers=['(request-target)', 'date']).sign({'Date': datetime.now().isoformat()}, method=method, path=path) auth = sign.pop('authorization') sign['Signature'] = auth[len('Signature '):] if auth.startswith('Signature ') else '' return sign def post_accept(account, target, activity): to = target.inbox jsn = { '@context': 'https://www.w3.org/ns/activitystreams', 'type': 'Accept', 'actor': account.ap_id(), 'object': activity, } headers = sign_headers(account, 'POST', urlparse(to).path) response = requests.post(to, json=jsn, headers=headers) if response.status_code >= 400 and response.status_code < 600: raise Exception('accept post error')

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null

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null

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0

2c74d6e02e3c3e03fa94c6d04730c15d838799a4

4,230

py

Python

account/views.py

josephdubon/boilerplate_image_share_app

e079715577ca112e4de234c8a35dde73639c3366

[ "Unlicense" ]

null

account/views.py

josephdubon/boilerplate_image_share_app

e079715577ca112e4de234c8a35dde73639c3366

[ "Unlicense" ]

3

2021-09-22T18:45:21.000Z

2022-03-12T00:58:12.000Z

account/views.py

josephdubon/boilerplate_image_share_app

e079715577ca112e4de234c8a35dde73639c3366

[ "Unlicense" ]

null

from django.http import HttpResponse from django.shortcuts import render from django.contrib import messages from django.contrib.auth import authenticate, login from django.contrib.auth.decorators import login_required from .forms import ( LoginForm, UserRegistrationForm, UserEditForm, ProfileEditForm ) from .models import Profile # Login view def user_login(request): if request.method == "POST": # Instantiate the form with the submitted data with form = LoginForm(request.POST). form = LoginForm(request.POST) # Check whether the form is valid with form.is_valid(). If it is not valid, you display # - the form errors in your template (for example, if the user didn't fill in one of the fields). if form.is_valid(): cd = form.cleaned_data # Authenticate the user against the database using the authenticate() method. user = authenticate(request, username=cd['username'], password=cd['password'] ) if user is not None: # If user is registered and active log user in if user.is_active: login(request, user) return HttpResponse('Authenticated successfully') else: # If user account is disabled return HttpResponse('Disabled account') else: # If there user account does not exist return HttpResponse('Invalid login') else: # Return clean form form = LoginForm() return render(request, 'account/login.html', { 'form': form }) # Dashboard view # Check if current user is authenticated @login_required def dashboard(request): return render(request, 'account/dashboard.html', { 'section': 'dashboard' }) # User registration view def register(request): if request.method == 'POST': user_form = UserRegistrationForm(request.POST) if user_form.is_valid(): # Create a new user obj but don't save yet new_user = user_form.save(commit=False) # Set the chosen password # For security reasons, instead of saving the raw password entered by the # - user, you use the set_password() method of the user model that handles hashing. new_user.set_password( user_form.cleaned_data['password']) # Save the user obj new_user.save() # Create the user an empty profile Profile.objects.create(user=new_user) return render(request, 'account/register_done.html', { 'new_user': new_user }) else: user_form = UserRegistrationForm() return render(request, 'account/register.html', { 'user_form': user_form }) # Edit user and profile view @login_required def edit(request): if request.method == 'POST': user_form = UserEditForm(instance=request.user, data=request.POST) profile_form = ProfileEditForm( instance=request.user.profile, data=request.POST, files=request.FILES) if user_form.is_valid() and profile_form.is_valid(): user_form.save() profile_form.save() # Send message to user on success messages.success(request, 'Profile updated successfully') else: # Send message to user on fail messages.error(request, 'Error updating your profile') else: user_form = UserEditForm(instance=request.user) profile_form = ProfileEditForm( instance=request.user.profile) return render(request, 'account/edit.html', {'user_form': user_form, 'profile_form': profile_form})

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0

null

0

null

0

1

0

2c7775424a57f17a890bdf4b7a7ff0cf9abb892f

932

py

Python

admin_tasks.py

draem0507/rietveld

70bda77edf3a642ef51ecc2d73c165345af5fdee

[ "Apache-2.0" ]

583

2015-03-28T23:49:34.000Z

2022-03-25T10:58:07.000Z

admin_tasks.py

draem0507/rietveld

70bda77edf3a642ef51ecc2d73c165345af5fdee

[ "Apache-2.0" ]

61

2015-04-02T01:08:34.000Z

2021-05-27T16:19:35.000Z

admin_tasks.py

draem0507/rietveld

70bda77edf3a642ef51ecc2d73c165345af5fdee

[ "Apache-2.0" ]

175

2015-03-29T13:06:36.000Z

2022-03-31T07:02:20.000Z

"""Collection of mapreduce jobs.""" import logging from mapreduce import operation as op from codereview.models import Account, Issue def delete_unused_accounts(account): """Delete accounts for uses that don't participate in any reviews.""" email = account.user.email() if Issue.query(Issue.owner_email == email).get(): return if Issue.query(Issue.cc == email).get(): return if Issue.query(Issue.reviewers == email).get(): return logging.warn('Deleting %s' % email) yield op.db.Delete(account) def update_account_schema(account): """Update schema for all Accounts by saving them back to the datastore.""" # Make sure we don't alter the modified time of any accounts. Because of how # mapreduce is designed, we just set this to False on every function # invocation (since there's no convenient once-per-instance place to do it). Account.modified.auto_now = False yield op.db.Put(account)

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null

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null

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2c778b23ac35cdce2fabe050d19757ad54f60c5c

3,426

py

Python

core/pwc_tiny.py

hologerry/RAFT

a80209c442ea2e2a8860af3c9ca96e62498533ca

[ "BSD-3-Clause" ]

null

core/pwc_tiny.py

hologerry/RAFT

a80209c442ea2e2a8860af3c9ca96e62498533ca

[ "BSD-3-Clause" ]

null

core/pwc_tiny.py

hologerry/RAFT

a80209c442ea2e2a8860af3c9ca96e62498533ca

[ "BSD-3-Clause" ]

null

import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from core.corr import AlternateCorrBlock, CorrBlock from core.extractor import BasicEncoder, SmallEncoder from core.mobilenetv3 import MobileNetV3 from core.pwc_decoder import Decoder from core.pwc_refiner import Refiner from core.update import BasicUpdateBlock, SmallUpdateBlock, TinyUpdateBlock from core.utils.utils import bilinear_sampler, coords_grid, upflow8, upflow4 try: autocast = torch.cuda.amp.autocast except: # dummy autocast for PyTorch < 1.6 class autocast: def __init__(self, enabled): pass def __enter__(self): pass def __exit__(self, *args): pass class PWCTiny(nn.Module): def __init__(self, args): super(PWCTiny, self).__init__() self.args = args self.extractor = MobileNetV3('mobilenet_v3_small', last_stage=5, norm_type='instance') self.decoder_2 = Decoder(level=2) self.decoder_3 = Decoder(level=3) self.decoder_4 = Decoder(level=4) self.decoder_5 = Decoder(level=5) self.refiner = Refiner() def is_training(self): return self.args.mode == 'train' def freeze_bn(self): for m in self.modules(): if isinstance(m, nn.BatchNorm2d): m.eval() def forward(self, image1, image2, iters=12, flow_init=None, upsample=True, test_mode=False): """ Estimate optical flow between pair of frames """ # image1, image2 = torch.chunk(x, 2, dim=1) image1 = 2 * (image1 / 255.0) - 1.0 image2 = 2 * (image2 / 255.0) - 1.0 image1 = image1.contiguous() image2 = image2.contiguous() # run the feature network feats1 = self.extractor(image1) feats2 = self.extractor(image2) estimate_out = self.decoder_5(feats1['C5'], feats2['C5'], None) flow_5 = estimate_out['flow'] estimate_out = self.decoder_4(feats1['C4'], feats2['C4'], estimate_out) flow_4 = estimate_out['flow'] estimate_out = self.decoder_3(feats1['C3'], feats2['C3'], estimate_out) flow_3 = estimate_out['flow'] estimate_out = self.decoder_2(feats1['C2'], feats2['C2'], estimate_out) flow_2 = estimate_out['flow'] + self.refiner(estimate_out['feat']) flow_out = upflow4(flow_2) if not test_mode: return flow_out, flow_2, flow_3, flow_4, flow_5 else: return flow_out * 20.0, flow_out * 20.0 if __name__ == '__main__': import argparse from ptflops import get_model_complexity_info parser = argparse.ArgumentParser() parser.add_argument('--name', default='pwc_tiny', help="name your experiment") parser.add_argument('--mode', default='train', help="") parser.add_argument('--small', action='store_true', help='use small model') parser.add_argument('--mixed_precision', action='store_true', help='use mixed precision') args = parser.parse_args() net = PWCTiny(args).cuda() with torch.cuda.device(0): macs, params = get_model_complexity_info(net, (6, 160, 96), as_strings=True, print_per_layer_stat=True, verbose=True) print('{:<30} {:<8}'.format('Computational complexity: ', macs)) print('{:<30} {:<8}'.format('Number of parameters: ', params)) data = torch.randn((2, 6, 224, 224)).cuda() out = net(data)

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false

0.041096

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0.041096

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null

0

null

0

1

0

2c784ec9ca5bd9cab47e3e48eed02b1261eb6710

1,631

py

Python

dependencies_analysis/src/utils.py

afdaniele/director

845ba027f9009803fcf77f44874f2ab9d7ab72e3

[ "BSD-3-Clause" ]

null

dependencies_analysis/src/utils.py

afdaniele/director

845ba027f9009803fcf77f44874f2ab9d7ab72e3

[ "BSD-3-Clause" ]

null

dependencies_analysis/src/utils.py

afdaniele/director

845ba027f9009803fcf77f44874f2ab9d7ab72e3

[ "BSD-3-Clause" ]

null

''' Created by: @author: Andrea F Daniele - TTIC - Toyota Technological Institute at Chicago Feb 6, 2019 - Mountain View, CA ''' import sys import numpy as np from os.path import isfile class ProgressBar(object): def __init__(self, maxVal=100, precision=5, doneMessage=True ): self.maxVal = float( max(1.0, maxVal) ) self.doneMessage = doneMessage self.precision = precision self.currentLength = -1 self.currentVal = 0.0 self.barParts = [ '[0%' ] for i in range(10,101,10): self.barParts.extend( ['.'] * self.precision + ['%d%%' % i] ) self.barParts[-1] += ']' if doneMessage: self.barParts[-1] += ' Done!' self.barLength = len(self.barParts) self.step = float(self.barLength-1) / self.maxVal def next(self): newLength = int(np.floor( (self.currentVal + 1.0) * self.step )) if newLength > self.currentLength and newLength <= self.barLength: for i in range(self.currentLength+1, newLength+1): sys.stdout.write(self.barParts[i]); sys.stdout.flush() if newLength == self.barLength-1: print self.currentLength = newLength self.currentVal += 1 def setMessage(self, message): self.barParts[-1] = '100%%] :: %s\n' % message class FileReader(object): def __init__(self, file_path): if not isfile(file_path): raise ValueError("The file '%s' does not exist" % file_path) self._file_path = file_path # open file self._lines = None def lines(self): # read lines if not self._lines: with open(self._file_path, "r") as fo: self._lines = fo.readlines() # return lines return self._lines

28.614035

92

0.650521

221

1,631

4.710407

0.402715

0.080692

0.037464

0.032661

0

0.027259

0.212753

1,631

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29.125

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false

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0.027027

0

null

0

null

0

1

0

2c78b387f4bdb0a5aec5ed308c83c4da0844e7b4

1,673

py

Python

attendees/persons/serializers/folk_serializer.py

xjlin0/-attendees30

48a2f2cbec11ec471d7a40d24903b48890feebf9

[ "MIT" ]

null

attendees/persons/serializers/folk_serializer.py

xjlin0/-attendees30

48a2f2cbec11ec471d7a40d24903b48890feebf9

[ "MIT" ]

null

attendees/persons/serializers/folk_serializer.py

xjlin0/-attendees30

48a2f2cbec11ec471d7a40d24903b48890feebf9

[ "MIT" ]

null

from attendees.persons.models import Folk, FolkAttendee, Relation, Utility, Attendee from attendees.whereabouts.serializers import PlaceSerializer from rest_framework import serializers class FolkSerializer(serializers.ModelSerializer): places = PlaceSerializer(many=True, read_only=True) class Meta: model = Folk fields = '__all__' def create(self, validated_data): """ Create or update `Family` instance, given the validated data. """ raw_data = self._kwargs.get('data', {}) family_id = raw_data.get('id') folk, folk_created = Folk.objects.update_or_create( id=family_id, defaults=validated_data, ) if folk_created: for attendee_id in raw_data.get('attendees', []): unspecified_role = Relation.objects.filter(title='unspecified').first attendee = Attendee.objects.get(pk=attendee_id) FolkAttendee.objects.update_or_create( attendee=attendee, folk=folk, defaults={ 'attendee': attendee, 'folk': folk, 'role': unspecified_role, 'start': Utility.now_with_timezone() }, ) return folk def update(self, instance, validated_data): """ Update and return an existing `Family` instance, given the validated data. """ obj, created = Folk.objects.update_or_create( id=instance.id, defaults=validated_data, ) return obj

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0.569038

160

1,673

5.7625

0.39375

0.084599

0.048807

0.06833

0.149675

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0

0.344889

1,673

54

86

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0.841241

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0

0.277778

0

null

0

null

0

1

0

2c7a53fa7046ae0ca4fe288507356e009d06bfd4

6,826

py

Python

V4 - HybridTTS/Utils/functions.py

riju-stone/chatbot

cfbd1a162f777440b138e2824d07f70cca8c4a48

[ "MIT" ]

null

V4 - HybridTTS/Utils/functions.py

riju-stone/chatbot

cfbd1a162f777440b138e2824d07f70cca8c4a48

[ "MIT" ]

1

2021-10-06T15:56:14.000Z

2021-10-07T04:54:15.000Z

V4 - HybridTTS/Utils/functions.py

riju-stone/chatbot

cfbd1a162f777440b138e2824d07f70cca8c4a48

[ "MIT" ]

null

import string import random from nltk.tokenize import TweetTokenizer import re import time import sys import numpy as np # source: https://gist.github.com/nealrs/96342d8231b75cf4bb82 cList = { "ain't": "am not", "aren't": "are not", "can't": "cannot", "can't've": "cannot have", "'cause": "because", "could've": "could have", "couldn't": "could not", "couldn't've": "could not have", "didn't": "did not", "doesn't": "does not", "don't": "do not", "hadn't": "had not", "hadn't've": "had not have", "hasn't": "has not", "haven't": "have not", "he'd": "he would", "he'd've": "he would have", "he'll": "he will", "he'll've": "he will have", "he's": "he is", "how'd": "how did", "how're": "how are", "how'd'y": "how do you", "how'll": "how will", "how's": "how is", "i'd": "I would", "i'd've": "I would have", "i'll": "I will", "i'll've": "I will have", "i'm": "I am", "i've": "i have", "isn't": "is not", "it'd": "it had", "it'd've": "it would have", "it'll": "it will", "it'll've": "it will have", "it's": "it is", "let's": "let us", "ma'am": "madam", "mayn't": "may not", "might've": "might have", "mightn't": "might not", "mightn't've": "might not have", "must've": "must have", "mustn't": "must not", "mustn't've": "must not have", "needn't": "need not", "needn't've": "need not have", "o'clock": "of the clock", "oughtn't": "ought not", "oughtn't've": "ought not have", "shan't": "shall not", "sha'n't": "shall not", "shan't've": "shall not have", "she'd": "she would", "she'd've": "she would have", "she'll": "she will", "she'll've": "she will have", "she's": "she is", "should've": "should have", "shouldn't": "should not", "shouldn't've": "should not have", "so've": "so have", "so's": "so is", "that'd": "that would", "that'd've": "that would have", "that's": "that is", "there'd": "there had", "there'd've": "there would have", "there's": "there is", "they'd": "they would", "they'd've": "they would have", "they'll": "they will", "they'll've": "they will have", "they're": "they are", "they've": "they have", "to've": "to have", "wasn't": "was not", "we'd": "we had", "we'd've": "we would have", "we'll": "we will", "we'll've": "we will have", "we're": "we are", "we've": "we have", "weren't": "were not", "what'll": "what will", "what'll've": "what will have", "what're": "what are", "what's": "what is", "what've": "what have", "when's": "when is", "when've": "when have", "where'd": "where did", "where's": "where is", "where've": "where have", "who'll": "who will", "who'll've": "who will have", "who's": "who is", "who've": "who have", "why's": "why is", "why've": "why have", "will've": "will have", "won't": "will not", "won't've": "will not have", "would've": "would have", "wouldn't": "would not", "wouldn't've": "would not have", "y'all": "you all", "y'alls": "you alls", "y'all'd": "you all would", "y'all'd've": "you all would have", "y'all're": "you all are", "y'all've": "you all have", "you'd": "you had", "you'd've": "you would have", "you'll": "you will", "you'll've": "you will have", "you're": "you are", "you've": "you have" } c_re = re.compile('(%s)' % '|'.join(cList.keys())) def expandContractions(text): global cList global c_re def replace(match): return cList[match.group(0)] return c_re.sub(replace, text) def replace(text, regex, replacement): def replace_fn(match): return replacement return regex.sub(replace_fn, text) def clean(text): filter_list_1 = ['’'] replacement_1 = "'" regex_1 = re.compile('(%s)' % '|'.join(filter_list_1)) text = replace(text, regex_1, replacement_1) filter_list_2 = ['\[wp\]', 'eli5\:', 'cmv\:', '\[d\]', '\[r\]', '\[n\]', '\&gt\;', '/r/', 'r/'] replacement_2 = '' regex_2 = re.compile('(%s)' % '|'.join(filter_list_2)) text = replace(text, regex_2, replacement_2) filter_list_3 = ['@[a-z0-9]+', '\/u\/[0-9a-z]+', '\[[0-9a-z]+\]$\/u\/[0-9a-z]+$'] replacement_3 = 'someone' regex_3 = re.compile('(%s)' % '|'.join(filter_list_3)) text = replace(text, regex_3, replacement_3) filter_list_4 = ['\[', '\]'] replacement_4 = ' ' regex_4 = re.compile('(%s)' % '|'.join(filter_list_4)) text = replace(text, regex_4, replacement_4) return text def simple_preprocess(text, return_tokenized=False, for_speech=False): tw = TweetTokenizer() text = text.lower() if not for_speech: text = clean(text) else: text = text.replace("*", "") text = expandContractions(text) # sometimes two iterations are needed for double contractions text = expandContractions(text) if for_speech: text = re.sub( r"[' '\(]*https\:[^ ]*|[' '\(]*http\:[^ ]*|[' ']*www\..[^ ]*", ' ', text) else: text = re.sub( r"[' '\(]*https\:[^ ]*|[' '\(]*http\:[^ ]*|[' ']*www\..[^ ]*", ' (url) ', text) if return_tokenized: tokenized_text = tw.tokenize(text) return tokenized_text else: return text # "but hey aren ’ t snobby . the wayne ’ s are well known for their philanthropy ." #print(simple_preprocess("[Zaflis000](/u/Zaflis000) @fodor000, > [can] http://plato.stanford.edu/entries/other-minds/ you're she'll do this for me? http://plato.stanford.edu/entries/other-minds/")) # Adapted from: https://stackoverflow.com/questions/9246076/how-to-print-one-character-at-a-time-on-one-line def delay_print(s, t=0.05): for c in s: sys.stdout.write(c) sys.stdout.flush() time.sleep(t) def cosine_similarity_nd(embd1, embd2): numerator = np.multiply(embd1, embd2) numerator = np.sum(numerator, axis=1) eucli_norm_1 = np.sqrt(np.sum(np.power(embd1, 2), axis=1)) eucli_norm_2 = np.sqrt(np.sum(np.power(embd2, 2), axis=1)) denominator = np.multiply(eucli_norm_1, eucli_norm_2) denominator = denominator + 1e-10 # remove zeros cosine_similarity = np.divide(numerator, denominator) return cosine_similarity.reshape((-1)) def normalize(values): # shift and normalize - create probability distribution minimum_val = np.amin(values) values = values - minimum_val norm_denom = np.sum(values) if norm_denom == 0: size = values.shape[-1] return np.asarray([1/size for _ in range(size)], np.float32) else: return values/norm_denom

28.206612

200

0.547612

1,005

6,826

3.654726

0.228856

0.008984

0.013613

0.019058

0.068064

0.032126

0

0.017456

0.236302

6,826

241

201

28.323651

0.687128

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0

0.049505

0

0.347534

0.004965

0

1

0.044554

false

0

0.034653

0.009901

0.128713

0.004951

0

null

0

null

0

1

0

2c7b3b7be42370503ba918b7f804028312f44fe9

896

py

Python

reverse_integer.py

alexhla/programming-problems-in-python

2db759f6196c026f43c6f2d6c9104d04a6850829

[ "MIT" ]

null

reverse_integer.py

alexhla/programming-problems-in-python

2db759f6196c026f43c6f2d6c9104d04a6850829

[ "MIT" ]

null

reverse_integer.py

alexhla/programming-problems-in-python

2db759f6196c026f43c6f2d6c9104d04a6850829

[ "MIT" ]

null

class Solution: def reverse(self, x): sign = -1 if x<0 else 1 x = abs(x) # floor division ALWAYS rounds down (-1//10 = -1) n = 0 # thus save sign and take absolute value while x != 0: n *= 10 # left shift digits one place n += x%10 # push least significant digit x //= 10 # pop processed digit if n > (2**31)-1: # check for overflow return 0 else: return sign * n # recombine with sign and return def reverse2(self, x): sign = -1 if x<0 else 1 s = str(abs(x)) # convert absolute value of int to string to avoid dash n = sign*int(s[::-1]) # reverse string and convert back to int adding sign last if (n > (2**31)-1) or (n < -2**31): # check for overflow return 0 else: return n obj = Solution() num = 123456789 print("Reversing {}" .format(num)) print("Answer-1: {}" .format(obj.reverse(num))) print("Answer-2: {}" .format(obj.reverse2(num)))

28.903226

81

0.626116

153

896

3.666667

0.431373

0.035651

0.02139

0.035651

0.210339

0.185383

0.067736

0

0.065407

0.232143

896

31

82

28.903226

0.75

0.382813

0

0.230769

0

0.066298

0

1

0.076923

false

0

0.269231

0.115385

0

null

0

null

0

1

0

2c827b375cd33ffc35313851f36e3892e6b7ddad

17,537

py

Python

revisiting_rainbow/Agents/quantile_agent_new.py

jiawei415/revisiting_rainbow

7cd2bc6f64d08ebc2233d93210063cc64d2598a7

[ "Apache-2.0" ]

72

2020-11-24T22:12:59.000Z

2022-03-21T21:18:21.000Z

revisiting_rainbow/Agents/quantile_agent_new.py

jiawei415/revisiting_rainbow

7cd2bc6f64d08ebc2233d93210063cc64d2598a7

[ "Apache-2.0" ]

2

2021-06-02T08:01:10.000Z

2021-07-03T03:11:54.000Z

revisiting_rainbow/Agents/quantile_agent_new.py

jiawei415/revisiting_rainbow

7cd2bc6f64d08ebc2233d93210063cc64d2598a7

[ "Apache-2.0" ]

6

2021-01-13T22:15:17.000Z

2021-11-04T04:00:05.000Z

"""An extension of Rainbow to perform quantile regression. This loss is computed as in "Distributional Reinforcement Learning with Quantile Regression" - Dabney et. al, 2017" Specifically, we implement the following components: * n-step updates * prioritized replay * double_dqn * noisy * dueling """ import copy import time import functools from dopamine.jax import networks from dopamine.jax.agents.dqn import dqn_agent from dopamine.replay_memory import prioritized_replay_buffer #check import gin import jax import jax.numpy as jnp import numpy as onp import tensorflow as tf @functools.partial(jax.vmap, in_axes=(None, None, 0, 0, 0, None)) def target_distributionDouble(model,target_network, next_states, rewards, terminals, cumulative_gamma): """Builds the Quantile target distribution as per Dabney et al. (2017). Args: target_network: Jax Module used for the target network. next_states: numpy array of batched next states. rewards: numpy array of batched rewards. terminals: numpy array of batched terminals. cumulative_gamma: float, cumulative gamma to use (static_argnum). Returns: The target distribution from the replay. """ is_terminal_multiplier = 1. - terminals.astype(jnp.float32) # Incorporate terminal state to discount factor. gamma_with_terminal = cumulative_gamma * is_terminal_multiplier next_state_target_outputs = model(next_states) q_values = jnp.squeeze(next_state_target_outputs.q_values) next_qt_argmax = jnp.argmax(q_values) next_dist = target_network(next_states) logits = jnp.squeeze(next_dist.logits) next_logits = logits[next_qt_argmax] return jax.lax.stop_gradient(rewards + gamma_with_terminal * next_logits) @functools.partial(jax.vmap, in_axes=(None, 0, 0, 0, None)) def target_distribution(target_network, next_states, rewards, terminals, cumulative_gamma): """Builds the Quantile target distribution as per Dabney et al. (2017). Args: target_network: Jax Module used for the target network. next_states: numpy array of batched next states. rewards: numpy array of batched rewards. terminals: numpy array of batched terminals. cumulative_gamma: float, cumulative gamma to use (static_argnum). Returns: The target distribution from the replay. """ is_terminal_multiplier = 1. - terminals.astype(jnp.float32) # Incorporate terminal state to discount factor. gamma_with_terminal = cumulative_gamma * is_terminal_multiplier next_state_target_outputs = target_network(next_states) q_values = jnp.squeeze(next_state_target_outputs.q_values) next_qt_argmax = jnp.argmax(q_values) logits = jnp.squeeze(next_state_target_outputs.logits) next_logits = logits[next_qt_argmax] return jax.lax.stop_gradient(rewards + gamma_with_terminal * next_logits) @functools.partial(jax.jit, static_argnums=(0, 9, 10, 11, 12)) def train(network_def, target_params, optimizer, states, actions, next_states, rewards, terminals, loss_weights, kappa, num_atoms, cumulative_gamma, double_dqn, rng): """Run a training step.""" online_params = optimizer.target def loss_fn(params,rng_input, target, loss_multipliers): def q_online(state): return network_def.apply(params, state, rng=rng_input) logits = jax.vmap(q_online)(states).logits logits = jnp.squeeze(logits) # Fetch the logits for its selected action. We use vmap to perform this # indexing across the batch. chosen_action_logits = jax.vmap(lambda x, y: x[y])(logits, actions) bellman_errors = (target[:, None, :] - chosen_action_logits[:, :, None]) # Input `u' of Eq. 9. # Eq. 9 of paper. huber_loss = ( (jnp.abs(bellman_errors) <= kappa).astype(jnp.float32) * 0.5 * bellman_errors ** 2 + (jnp.abs(bellman_errors) > kappa).astype(jnp.float32) * kappa * (jnp.abs(bellman_errors) - 0.5 * kappa)) tau_hat = ((jnp.arange(num_atoms, dtype=jnp.float32) + 0.5) / num_atoms) # Quantile midpoints. See Lemma 2 of paper. # Eq. 10 of paper. tau_bellman_diff = jnp.abs( tau_hat[None, :, None] - (bellman_errors < 0).astype(jnp.float32)) quantile_huber_loss = tau_bellman_diff * huber_loss # Sum over tau dimension, average over target value dimension. loss = jnp.sum(jnp.mean(quantile_huber_loss, 2), 1) mean_loss = jnp.mean(loss_multipliers * loss) return mean_loss, loss rng, rng2, rng3, rng4 = jax.random.split(rng, 4) def q_target(state): return network_def.apply(target_params, state, rng=rng2) def q_target_online(state): return network_def.apply(online_params, state, rng=rng4) if double_dqn: target = target_distributionDouble(q_target_online, q_target, next_states, rewards, terminals, cumulative_gamma) else: target = target_distribution(q_target, next_states, rewards, terminals, cumulative_gamma) grad_fn = jax.value_and_grad(loss_fn, has_aux=True) (mean_loss, loss), grad = grad_fn(online_params, rng3, target, loss_weights) optimizer = optimizer.apply_gradient(grad) return optimizer, loss, mean_loss @functools.partial(jax.jit, static_argnums=(0, 4, 5, 6, 7, 8, 10, 11)) def select_action(network_def, params, state, rng, num_actions, eval_mode, epsilon_eval, epsilon_train, epsilon_decay_period, training_steps, min_replay_history, epsilon_fn): epsilon = jnp.where(eval_mode, epsilon_eval, epsilon_fn(epsilon_decay_period, training_steps, min_replay_history, epsilon_train)) rng, rng1, rng2, rng3 = jax.random.split(rng, num=4) selected_action = jnp.argmax(network_def.apply(params, state, rng=rng3).q_values) p = jax.random.uniform(rng1) return rng, jnp.where(p <= epsilon, jax.random.randint(rng2, (), 0, num_actions), selected_action) @gin.configurable class JaxQuantileAgentNew(dqn_agent.JaxDQNAgent): """An implementation of Quantile regression DQN agent.""" def __init__(self, num_actions, kappa=1.0, num_atoms=200, noisy = False, dueling = False, initzer = 'variance_scaling', net_conf = None, env = "CartPole", normalize_obs = True, hidden_layer=2, neurons=512, double_dqn=False, replay_scheme='prioritized', optimizer='adam', network=networks.QuantileNetwork, epsilon_fn=dqn_agent.linearly_decaying_epsilon, seed=None): """Initializes the agent and constructs the Graph. Args: num_actions: Int, number of actions the agent can take at any state. observation_shape: tuple of ints or an int. If single int, the observation is assumed to be a 2D square. observation_dtype: DType, specifies the type of the observations. Note that if your inputs are continuous, you should set this to jnp.float32. stack_size: int, number of frames to use in state stack. network: tf.Keras.Model, expects 3 parameters: num_actions, num_atoms, network_type. A call to this object will return an instantiation of the network provided. The network returned can be run with different inputs to create different outputs. See dopamine.discrete_domains.jax.networks.QuantileNetwork as an example. kappa: Float, Huber loss cutoff. num_atoms: Int, the number of buckets for the value function distribution. gamma: Float, exponential decay factor as commonly used in the RL literature. update_horizon: Int, horizon at which updates are performed, the 'n' in n-step update. min_replay_history: Int, number of stored transitions for training to start. update_period: Int, period between DQN updates. target_update_period: Int, ppdate period for the target network. epsilon_fn: Function expecting 4 parameters: (decay_period, step, warmup_steps, epsilon), and which returns the epsilon value used for exploration during training. epsilon_train: Float, final epsilon for training. epsilon_eval: Float, epsilon during evaluation. epsilon_decay_period: Int, number of steps for epsilon to decay. replay_scheme: String, replay memory scheme to be used. Choices are: uniform - Standard (DQN) replay buffer (Mnih et al., 2015) prioritized - Prioritized replay buffer (Schaul et al., 2015) optimizer: str, name of optimizer to use. summary_writer: SummaryWriter object for outputting training statistics. Summary writing disabled if set to None. summary_writing_frequency: int, frequency with which summaries will be written. Lower values will result in slower training. allow_partial_reload: bool, whether we allow reloading a partial agent (for instance, only the network parameters). """ seed = int(time.time() * 1e6) if seed is None else seed self._num_atoms = num_atoms self._kappa = kappa self._replay_scheme = replay_scheme self._double_dqn = double_dqn self._net_conf = net_conf self._env = env self._normalize_obs = normalize_obs self._hidden_layer= hidden_layer self._neurons=neurons self._noisy = noisy self._dueling = dueling self._initzer = initzer self._rng = jax.random.PRNGKey(seed) super(JaxQuantileAgentNew, self).__init__( num_actions=num_actions, optimizer=optimizer, epsilon_fn = dqn_agent.identity_epsilon if self._noisy == True else epsilon_fn, network=functools.partial(network, num_atoms=self._num_atoms , net_conf=self._net_conf, env=self._env, normalize_obs=self._normalize_obs, hidden_layer=self._hidden_layer, neurons=self._neurons, noisy=self._noisy, dueling=self._dueling, initzer=self._initzer)) def _build_networks_and_optimizer(self): self._rng, rng = jax.random.split(self._rng) online_network_params = self.network_def.init(rng, x=self.state, rng=self._rng) optimizer_def = dqn_agent.create_optimizer(self._optimizer_name) self.optimizer = optimizer_def.create(online_network_params) self.target_network_params = copy.deepcopy(online_network_params) def _build_replay_buffer(self): """Creates the replay buffer used by the agent.""" if self._replay_scheme not in ['uniform', 'prioritized']: raise ValueError('Invalid replay scheme: {}'.format(self._replay_scheme)) # Both replay schemes use the same data structure, but the 'uniform' scheme # sets all priorities to the same value (which yields uniform sampling). return prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer( observation_shape=self.observation_shape, stack_size=self.stack_size, update_horizon=self.update_horizon, gamma=self.gamma, observation_dtype=self.observation_dtype) def begin_episode(self, observation): self._reset_state() self._record_observation(observation) if not self.eval_mode: self._train_step() self._rng, self.action = select_action(self.network_def, self.online_params, self.state, self._rng, self.num_actions, self.eval_mode, self.epsilon_eval, self.epsilon_train, self.epsilon_decay_period, self.training_steps, self.min_replay_history, self.epsilon_fn) self.action = onp.asarray(self.action) return self.action def step(self, reward, observation): self._last_observation = self._observation self._record_observation(observation) if not self.eval_mode: self._store_transition(self._last_observation, self.action, reward, False) self._train_step() self._rng, self.action = select_action(self.network_def, self.online_params, self.state, self._rng, self.num_actions, self.eval_mode, self.epsilon_eval, self.epsilon_train, self.epsilon_decay_period, self.training_steps, self.min_replay_history, self.epsilon_fn) self.action = onp.asarray(self.action) return self.action def _train_step(self): """Runs a single training step. Runs training if both: (1) A minimum number of frames have been added to the replay buffer. (2) `training_steps` is a multiple of `update_period`. Also, syncs weights from online_network to target_network if training steps is a multiple of target update period. """ if self._replay.add_count > self.min_replay_history: if self.training_steps % self.update_period == 0: self._sample_from_replay_buffer() if self._replay_scheme == 'prioritized': # The original prioritized experience replay uses a linear exponent # schedule 0.4 -> 1.0. Comparing the schedule to a fixed exponent of # 0.5 on 5 games (Asterix, Pong, Q*Bert, Seaquest, Space Invaders) # suggested a fixed exponent actually performs better, except on Pong. probs = self.replay_elements['sampling_probabilities'] loss_weights = 1.0 / jnp.sqrt(probs + 1e-10) loss_weights /= jnp.max(loss_weights) else: loss_weights = jnp.ones(self.replay_elements['state'].shape[0]) self.optimizer, loss, mean_loss = train( self.network_def, self.target_network_params, self.optimizer, self.replay_elements['state'], self.replay_elements['action'], self.replay_elements['next_state'], self.replay_elements['reward'], self.replay_elements['terminal'], loss_weights, self._kappa, self._num_atoms, self.cumulative_gamma, self._double_dqn, self._rng) if self._replay_scheme == 'prioritized': # Rainbow and prioritized replay are parametrized by an exponent # alpha, but in both cases it is set to 0.5 - for simplicity's sake we # leave it as is here, using the more direct sqrt(). Taking the square # root "makes sense", as we are dealing with a squared loss. Add a # small nonzero value to the loss to avoid 0 priority items. While # technically this may be okay, setting all items to 0 priority will # cause troubles, and also result in 1.0 / 0.0 = NaN correction terms. self._replay.set_priority(self.replay_elements['indices'], jnp.sqrt(loss + 1e-10)) if self.summary_writer is not None: summary = tf.compat.v1.Summary(value=[ tf.compat.v1.Summary.Value(tag='QuantileLoss', simple_value=mean_loss)]) self.summary_writer.add_summary(summary, self.training_steps) if self.training_steps % self.target_update_period == 0: self._sync_weights() self.training_steps += 1 def _store_transition(self, last_observation, action, reward, is_terminal, priority=None): """Stores a transition when in training mode. Stores the following tuple in the replay buffer (last_observation, action, reward, is_terminal, priority). Args: last_observation: Last observation, type determined via observation_type parameter in the replay_memory constructor. action: An integer, the action taken. reward: A float, the reward. is_terminal: Boolean indicating if the current state is a terminal state. priority: Float. Priority of sampling the transition. If None, the default priority will be used. If replay scheme is uniform, the default priority is 1. If the replay scheme is prioritized, the default priority is the maximum ever seen [Schaul et al., 2015]. """ if priority is None: if self._replay_scheme == 'uniform': priority = 1. else: priority = self._replay.sum_tree.max_recorded_priority if not self.eval_mode: self._replay.add(last_observation, action, reward, is_terminal, priority)

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0.216821

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0.011204

0.282374

17,537

405

118

43.301235

0.84855

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0.160338

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null

0

null

0

1

0

2c846fbf1fb31138dd5ef08bbb8178074cf8b762

4,395

py

Python

utils/visualize_utils.py

ljrprocc/Motif-Removal

8979ca91398212248a2be61345c99bdec53ae37e

[ "MIT" ]

null

utils/visualize_utils.py

ljrprocc/Motif-Removal

8979ca91398212248a2be61345c99bdec53ae37e

[ "MIT" ]

null

utils/visualize_utils.py

ljrprocc/Motif-Removal

8979ca91398212248a2be61345c99bdec53ae37e

[ "MIT" ]

null

import torch import os.path from utils.train_utils import load_globals, init_folders, init_nets from loaders.motif_dataset import MotifDS from PIL import Image import numpy as np # network names root_path = '..' train_tag = 'vm_demo_text_remover' load_tag = '' device = torch.device('cuda:0') net_path = '%s/checkpoints/%s' % (root_path, train_tag) resources_root = 'test images folder' target_root = '%s/data/tmp' % root_path def load_image(image_path, _device, include_tensor=False): numpy_image = None tensor_image = None if os.path.isfile(image_path): to_save = False row_image = Image.open(image_path) w, h = row_image.size if h > 512: to_save = True h = int((512. * h) / w) row_image = row_image.resize((512, h), Image.BICUBIC) w, h = row_image.size if w % 16 != 0 or h % 16 != 0: to_save = True row_image = row_image.crop((0, 0, (w // 16) * 16, (h // 16) * 16)) if to_save: row_image.save(image_path) numpy_image = np.array(row_image) if len(numpy_image.shape) != 3: numpy_image = np.repeat(np.expand_dims(numpy_image, 2), 3, axis=2) if numpy_image.shape[2] != 3: numpy_image = numpy_image[:, :, :3] if include_tensor: tensor_image = MotifDS.trans(MotifDS.flip(numpy_image)[0])[0] tensor_image = torch.unsqueeze(torch.from_numpy(tensor_image), 0).to(_device) numpy_image = np.expand_dims(numpy_image / 255, 0) return numpy_image, tensor_image def transform_to_numpy_image(tensor_image): image = tensor_image.cpu().detach().numpy() image = np.transpose(image, (0, 2, 3, 1)) if image.shape[3] != 3: image = np.repeat(image, 3, axis=3) else: image = (image / 2 + 0.5) return image def collect_synthesized(_source): paths = [] for root, _, files in os.walk(_source): for file in files: file_name, file_extension = os.path.splitext(file) if (file_extension == '.png' or file_extension == '.jpg' or file_extension == '.jpeg') and \ ('real' not in file_name and 'reconstructed' not in file_name and 'grid' not in file_name): paths.append(os.path.join(root, file)) return paths def save_numpy_image(images, suffix, _target_root, _resources_root, prefix='', start_count=0): images = (images * 255).astype(np.uint8) # unnormalize for image_index in range(images.shape[0]): if prefix == '': image_path = '%s/%d_%s.png' % (_resources_root, image_index + start_count, suffix) else: image_path = '%s/%s_%s.png' % (_target_root, prefix, suffix) image = Image.fromarray(images[image_index]) image.save(image_path) def run_net(opt, _device, _net_path, _source, _target, _train_tag, _tag=''): net = init_nets(opt, _net_path, _device, _tag).eval() synthesized_paths = collect_synthesized(_source) image_suffixes = ['reconstructed_image', 'reconstructed_motif'] for path in synthesized_paths: prefix, _ = os.path.splitext(os.path.split(path)[-1]) prefix = prefix.split('_')[0] sy_np, sy_ts = load_image(path, _device, True) results = list(net(sy_ts)) for idx, result in enumerate(results): results[idx] = transform_to_numpy_image(result) reconstructed_mask = results[1] reconstructed_motif = None if len(results) == 3: reconstructed_raw_motif = results[2] reconstructed_motif = (reconstructed_raw_motif - 1) * reconstructed_mask + 1 reconstructed_image = reconstructed_mask * results[0] + (1 - reconstructed_mask) * sy_np for idx, image in enumerate([reconstructed_image, reconstructed_motif]): if image is not None and idx < len(image_suffixes): save_numpy_image(image, '%s_%s' % (image_suffixes[idx], _train_tag), _target, _source, prefix=prefix) print('done') if __name__ == '__main__': _opt = load_globals(net_path, {}, override=False) init_folders(target_root) run_net(_opt, device, net_path, resources_root, target_root, train_tag, load_tag)

40.321101

111

0.61661

581

4,395

4.371773

0.2358

0.066929

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0.059843

0.029921

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0.020516

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4,395

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false

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0.01087

0

null

0

null

0

1

0

2c8726dfb28106d95bb06c1763a01f4331da1d8a

651

py

Python

python/Data Structures and Algorithms in Python Book/stacks/match_delimiter.py

gauravssnl/Data-Structures-and-Algorithms

1c335c72ce514d4f95090241bbd6edf01a1141a8

[ "MIT" ]

7

2020-05-10T09:57:23.000Z

2021-03-27T11:55:07.000Z

python/Data Structures and Algorithms in Python Book/stacks/match_delimiter.py

gauravssnl/Data-Structures-and-Algorithms

1c335c72ce514d4f95090241bbd6edf01a1141a8

[ "MIT" ]

null

python/Data Structures and Algorithms in Python Book/stacks/match_delimiter.py

gauravssnl/Data-Structures-and-Algorithms

1c335c72ce514d4f95090241bbd6edf01a1141a8

[ "MIT" ]

3

2021-03-27T03:42:57.000Z

2021-08-09T12:03:41.000Z

from arraystack import ArrayStack def is_matched(expr): """Return True if all delimiters properly match (or closed); False otherwise""" left_delimiters = "({[" right_delimiter = ")}]" S = ArrayStack() for c in expr: if c in left_delimiters: S.push(c) elif c in right_delimiter: if S.is_empty(): return False if right_delimiter.index(c) != left_delimiters.index(S.pop()): return False return S.is_empty() if __name__ == "__main__": expr = "[(5+x)-(y+z)]" print(is_matched(expr)) expr = "[(5+x)-y+z)]" print(is_matched(expr))

28.304348

84

0.572965

85

651

4.164706

0.435294

0.076271

0.110169

0.039548

0.146893

0

0.004338

0.291859

651

23

85

28.304348

0.763557

0.113671

0

0.210526

0

0.068182

0

1

0.052632

false

0

0.052632

0

0.263158

0.105263

0

null

0

null

0

1

0

2c889835bd8ac35d8cbc3f5d416195de17ced7a8

24,522

py

Python

cogs/werewolf.py

vluk/baymaxBot

fb7e7dd4b2d99a6987a8e8c09afc7e43af844ffc

[ "MIT" ]

null

cogs/werewolf.py

vluk/baymaxBot

fb7e7dd4b2d99a6987a8e8c09afc7e43af844ffc

[ "MIT" ]

4

2021-04-24T06:38:49.000Z

2021-04-24T06:44:21.000Z

cogs/werewolf.py

vluk/baymaxBot

fb7e7dd4b2d99a6987a8e8c09afc7e43af844ffc

[ "MIT" ]

1

2021-05-02T08:04:08.000Z

import discord from discord.ext import commands import random import asyncio cards = ["villager", "werewolf", "minion", "mason", "seer", "robber", "troublemaker", "drunk", "insomniac", "tanner", "hunter"] aesthetics = { "werewolf" : { "color" : 0x25d0ff, "thumbnail" : "https://cdn.discordapp.com/attachments/323535193073778689/716453639782137876/unknown.png" } } class Game: def __init__(self, host, join_message): self.state = "preparing" self.players = [1, 2, 3] self.host = host self.join_message = join_message self.initial_roles = [] self.current_roles = [] self.votes = {} def fetch_player(self, arg): try: for player in self.players: if not isinstance(player, int): if player.id == int(arg): return self.players.index(player) except ValueError: pass arg = str(arg) for player in self.players: if not isinstance(player, int): if player.name.lower() == arg.lower(): return self.players.index(player) for player in self.players: if not isinstance(player, int): if player.nick != None and player.nick.lower() == arg.lower(): return self.players.index(player) return -1 def get_refreshed_embed(self): embed = self.join_message.embeds[0] embed.clear_fields() players = ", ".join(self.get_player_list()) if len(self.players) > 3 else "None" embed.add_field(name="Players:", value = players) roles = ", ".join([cards[i] for i in self.initial_roles]) if len(self.initial_roles) > 0 else "None" embed.add_field(name="Roles:", value = roles) return embed def get_player_list(self): return [i.display_name for i in self.players if not isinstance(i, int)] def get_debrief(self): return [(self.players[i].display_name, cards[self.current_roles[i]]) for i in range(len(self.current_roles)) if not isinstance(self.players[i], int)] def simulate(self, instructions): for i in instructions: for j in i: swap = self.current_roles[j[0]] self.current_roles[j[0]] = self.current_roles[j[1]] self.current_roles[j[1]] = swap class Werewolf(commands.Cog): def __init__(self, bot): self.bot = bot self.games = {} async def do_villager(): pass async def do_werewolf(self, user, game): werewolves = [] for i in range(len(game.players)): if not isinstance(game.players[i], int) and game.initial_roles[i] == 1: werewolves.append(game.players[i]) if len(werewolves) == 1: embed = discord.Embed( title = "You are a werewolf!", description = " ".join([ "You are a werewolf, the very embodiment of evil itself.", "As a werewolf, your goal is to stay alive by deceiving the other players.", "If all of the werewolves manage to stay alive, then their team wins.", "Since it looks like you're the only werewolf, you get to look at a card from the center.", "Click on one of the reactions on this message to reveal a card." ]), color = aesthetics["werewolf"]["color"] ) embed.set_thumbnail(url=aesthetics["werewolf"]["thumbnail"]) embed.add_field( name="Werewolves", value = "Just you!" ) message = await user.send(embed=embed) key = {"1️⃣" : 1, "2️⃣" : 2, "3️⃣" : 3} for i in key: await message.add_reaction(i) def check(r, u): return u.id == user.id and r.message.id == message.id and str(r.emoji) in key reaction, user = await self.bot.wait_for("reaction_add", check=check) selection = key[str(reaction.emoji)] revealed = cards[game.initial_roles[game.players.index(selection)]].capitalize() embed.add_field( name="Revealed Card", value=revealed, ) await message.edit(embed=embed) elif len(werewolves) > 1: embed = discord.Embed( title = "You are a werewolf!", description = " ".join([ "As a werewolf, your goal is to stay alive by deceiving the other players.", "If all of the werewolves manage to stay alive, then their team wins." ]), color = aesthetics["werewolf"]["color"] ) embed.set_thumbnail(url=aesthetics["werewolf"]["thumbnail"]) embed.add_field( name="Werewolves:", value = ", ".join([werewolf.display_name for werewolf in werewolves]) ) await user.send(embed=embed) return [] async def do_minion(self, user, game): werewolves = [] for i in range(len(game.players)): if not isinstance(game.players[i], int) and game.initial_roles[i] == 1: werewolves.append(game.players[i]) if len(werewolves) == 0: embed = discord.Embed( title = "You are a minion!", description = " ".join([ "You are a dastardly minion, only barely tolerated by the werewolves.", "Try to draw the fire of the other players, or divert suspicion towards one of the villagers.", "If all of the werewolves manage to stay alive, then you win.", ]) ) embed.add_field( name="Werewolves:", value = "None" ) await user.send(embed=embed) else: embed = discord.Embed( title = "You are a minion!", description = " ".join([ "You are a minion, dashing but with a heart of coal.", "Try to draw the fire of the other players, or divert suspicion towards one of the villagers.", "If all of the werewolves manage to stay alive, then you win.", ]) ) embed.add_field( name="Werewolves:", value = ", ".join([werewolf.display_name for werewolf in werewolves]) ) await user.send(embed=embed) return [] async def do_mason(self, user, game): masons = [] for i in range(len(game.players)): if not isinstance(game.players[i], int) and game.initial_roles[i] == 3: masons.append(game.players[i]) embed = discord.Embed( title = "You are a mason!", description = " ".join([ "Your sublime bond with your partner is unbreakable.", "Leverage your maybe-platonic love to narrow down the suspects.", "If you manage to kill a werewolf, then you win.", ]) ) embed.add_field( name="Masons", value = ", ".join([mason.display_name for mason in masons]) ) message = await user.send(embed=embed) return [] async def do_seer(self, user, game): embed = discord.Embed( title = "You are a seer!", description = " ".join([ "You are one with the very fabric of reality itself.", "Use your eldritch knowledge to gain insights into the game.", "If you manage to kill a werewolf, then you win.", "You can either look at either another player's card or two cards in the center. " "React with either 🇵 or 🇨 to choose." ]) ) message = await user.send(embed=embed) key = {"🇵" : "player", "🇨" : "center"} for i in key: await message.add_reaction(i) def check(r, u): return u.id == user.id and r.message.id == message.id and str(r.emoji) in key reaction, user = await self.bot.wait_for("reaction_add", check=check) selection = key[str(reaction.emoji)] if selection == "player": await user.send("Choose which player, using either their full username or nickname.") def user_check(m): if m.author.id != self.bot.user.id: if m.channel.id == user.dm_channel.id: if game.fetch_player(m.content) != -1: self.bot.loop.create_task(m.add_reaction("✅")) return True else: self.bot.loop.create_task(m.add_reaction("❌")) return False player = game.fetch_player((await self.bot.wait_for("message", check=user_check)).content) await user.send(cards[game.initial_roles[player]]) elif selection == "center": await user.send("Choose which two using two numbers (1, 2, 3) seperated with a space.") def card_check(m): if m.channel.id != user.dm_channel.id: return False split = m.content.split() if len(split) != 2: self.bot.loop.create_task(m.add_reaction("❌")) return False try: valid = int(split[0]) in [1, 2, 3] and int(split[1]) in [1, 2, 3] and split[0] != split[1] if valid: self.bot.loop.create_task(m.add_reaction("✅")) return True self.bot.loop.create_task(m.add_reaction("❌")) return False except ValueError: self.bot.loop.create_task(m.add_reaction("❌")) return False centers = [int(i) for i in (await self.bot.wait_for("message", check=card_check)).content.split()] await user.send(cards[game.initial_roles[game.players.index(centers[0])]]) await user.send(cards[game.initial_roles[game.players.index(centers[1])]]) await user.send("You're good to go!") return [] async def do_robber(self, user, game): embed = discord.Embed( title = "You are a robber!", description = " ".join([ "Your morals are flexible, and so is your identity.", "Choose another player to swap your card with.", "Whoever ends up with your card will be on the villager team.", "(Send a message containing their full username or nickname.)" ]) ) message = await user.send(embed=embed) initial = game.fetch_player(user.id) def check(m): if m.channel.id == user.dm_channel.id: if (game.fetch_player(m.content) != -1 and game.fetch_player(m.content) != initial): self.bot.loop.create_task(m.add_reaction("✅")) return True else: self.bot.loop.create_task(m.add_reaction("❌")) return False target = game.fetch_player((await self.bot.wait_for("message", check=check)).content) await user.send("you are now the " + cards[game.initial_roles[target]]) await user.send("You're good to go!") return [(initial, target)] async def do_troublemaker(self, user, game): await user.send("choose two players to swap (seperate messages)") initial = game.fetch_player(user.id) first = None def check(m): if m.channel.id == user.dm_channel.id: if (game.fetch_player(m.content) != -1 and game.fetch_player(m.content) != first and game.fetch_player(m.content) != initial): self.bot.loop.create_task(m.add_reaction("✅")) return True else: self.bot.loop.create_task(m.add_reaction("❌")) return False first_message = await self.bot.wait_for("message", check=check) first = game.fetch_player(first_message.content) second_message = await self.bot.wait_for("message", check=check) second = game.fetch_player(second_message.content) await user.send("You're good to go!") return [(first, second)] async def do_drunk(self, user, game): embed = discord.Embed( title = "You are a drunk!", description = " ".join([ "You like the happy juice a biiiit more than is probably healthy.", "Choose a card in the center to swap with." ]) ) message = await user.send(embed=embed) key = {"1️⃣" : 1, "2️⃣" : 2, "3️⃣" : 3} for i in key: await message.add_reaction(i) def check(r, u): return u.id == user.id and r.message.id == message.id and str(r.emoji) in key reaction, user = await self.bot.wait_for("reaction_add", check=check) selection = key[str(reaction.emoji)] current = game.fetch_player(user.id) middle = game.players.index(key[str(reaction.emoji)]) await user.send("You're good to go!") return [(current, middle)] async def do_insomniac(self, user, game): current = game.fetch_player(user.id) await user.send(cards[game.current_roles[current]]) @commands.group(aliases=["ww"], invoke_without_command=True) async def werewolf(self, ctx): host = ctx.message.author embed = discord.Embed( title = "Werewolf", description = " ".join([ "A classic social deduction game where two sides face off against each other: the **Villagers** and **Werewolves**.", "Uncover who the werewolves are, or use deception to stay hidden until the end.", "But be careful: if you kill the Tanner, then both teams lose.", "\n\n**Instructions:**\n", "**React to this message with 🐺** to join the game, " "then **add cards** using `%ww add` followed by a list of the roles you want to add, seperated by spaces.", "For example, you might do something like this to add multiple roles:", "`%ww add werewolf minion seer tanner troublemaker mason mason`.", "Additionally, you can get the order of the roles using %ww roleOrder." ]), color = 0x7289da ) embed.set_footer(text=f"{host.display_name} is the host", icon_url=host.avatar_url) embed.add_field(name="Players", value="None") embed.add_field(name="Roles", value="None") if not ctx.channel.id in self.games: message = await ctx.send(embed=embed) await message.add_reaction("🐺") self.games[ctx.channel.id] = Game(ctx.message.author, message) else: await ctx.send("There's already a game running here!") @werewolf.command() async def join(self, ctx): game = None if not ctx.channel.id in self.games: self.games[ctx.channel.id] = Game() game = self.games[ctx.channel.id] if game.state == "preparing": if game.fetch_player(ctx.message.author.id) == -1: game.players.append(ctx.message.author) await ctx.send("yeah sure") else: await ctx.send("already in the game") else: await ctx.send("nah you cant join in the middle of a round") @werewolf.command(aliases=["addcard"]) async def add(self, ctx, *, names): if not ctx.channel.id in self.games: await ctx.send("theres no game here dummy") return game = self.games[ctx.channel.id] if game.host.id != ctx.message.author.id: await ctx.send("Only the host can add roles.") return if all([name.lower() in cards for name in names.split()]) and game.state == "preparing": for name in names.split(): game.initial_roles.append(cards.index(name.lower())) await game.join_message.edit(embed=game.get_refreshed_embed()) @werewolf.command() async def set(self, ctx, *, names): if not ctx.channel.id in self.games: await ctx.send("theres no game here dummy") return game = self.games[ctx.channel.id] if game.host.id != ctx.message.author.id: await ctx.send("Only the host can add roles.") return game.initial_roles = [] if all([name.lower() in cards for name in names.split()]) and game.state == "preparing": for name in names.split(): game.initial_roles.append(cards.index(name.lower())) await game.join_message.edit(embed=game.get_refreshed_embed()) @werewolf.command(aliase=["removecard"]) async def remove(self, ctx, name): if not ctx.channel.id in self.games: await ctx.send("theres no game here dummy") return game = self.games[ctx.channel.id] if game.host.id != ctx.message.author.id: await ctx.send("Only the host can add roles.") game = self.games[ctx.channel.id] if game.state == "preparing" and cards.index(name.lower()) in game.initial_roles: game.initial_roles.remove(cards.index(name.lower())) await game.join_message.edit(embed=game.get_refreshed_embed()) @werewolf.command() async def vote(self, ctx, *, accused : str): if not ctx.channel.id in self.games: await ctx.send("theres no game here dummy") return game = self.games[ctx.channel.id] if game.state != "voting": await ctx.send("cant vote yet") return author = ctx.message.author if game.fetch_player(author.id) != -1: if game.fetch_player(accused) != -1: game.votes[author.id] = game.players[game.fetch_player(accused)].id if len(game.votes) == len(game.players) - 3: tally = {} for i in game.votes: if not game.votes[i] in tally: tally[game.votes[i]] = 0 tally[game.votes[i]] += 1 top = sorted([(tally[i], i) for i in tally]) if len(top) > 1 and top[-1][0] == top[-2][0]: await ctx.send("no decisive winner") else: killed_id = top[-1][1] index = game.fetch_player(killed_id) killed = game.players[index] await ctx.send("killing " + killed.mention) if cards[game.current_roles[index]] == "hunter": def user_check(m): if m.channel.id == ctx.message.channel.id: if game.fetch_player(m.content) != -1: self.bot.loop.create_task(m.add_reaction("✅")) return True else: self.bot.loop.create_task(m.add_reaction("❌")) return False player = game.fetch_player((await self.bot.wait_for("message", check=user_check)).content) await ctx.send(killed.display_name + " was " + cards[game.current_roles[index]]) paired_roles = [" was ".join(i) for i in game.get_debrief()] await ctx.send(", ".join(paired_roles)) del self.games[ctx.channel.id] else: await ctx.send("vote registered") else: await ctx.send("cant find") else: await ctx.send("you're not playing") @werewolf.command() async def roleOrder(self, ctx): await ctx.send(", ".join(cards)) @werewolf.command() async def start(self, ctx): if not ctx.channel.id in self.games: await ctx.send("theres no game here dummy") return game = self.games[ctx.channel.id] if game.host.id != ctx.message.author.id: await ctx.send("Only the host can start the game.") return if len(game.players) > len(game.initial_roles): await ctx.send("You need more roles to play!") return if len(game.players) < len(game.initial_roles): await ctx.send("You need less roles to play!") return game.state = "running" game.initial_roles = sorted(game.initial_roles) random.shuffle(game.players) game.current_roles = [i for i in game.initial_roles] await ctx.send("game starting") for i in range(len(game.players)): if not isinstance(game.players[i], int): await game.players[i].send("you're the " + cards[game.initial_roles[i]]) tasks = [] for i in range(len(game.initial_roles)): if not isinstance(game.players[i], int): if game.initial_roles[i] == 1: tasks.append(self.do_werewolf(game.players[i], game)) if game.initial_roles[i] == 2: tasks.append(self.do_minion(game.players[i], game)) if game.initial_roles[i] == 3: tasks.append(self.do_mason(game.players[i], game)) if game.initial_roles[i] == 4: tasks.append(self.do_seer(game.players[i], game)) if game.initial_roles[i] == 5: tasks.append(self.do_robber(game.players[i], game)) if game.initial_roles[i] == 6: tasks.append(self.do_troublemaker(game.players[i], game)) if game.initial_roles[i] == 7: tasks.append(self.do_drunk(game.players[i], game)) instructions = await asyncio.gather(*tasks) game.simulate(instructions) for i in range(len(game.players)): if not isinstance(game.players[i], int): if game.initial_roles[i] == 8: await self.do_insomniac(game.players[i], game) await ctx.send("the night's now over, do ur stuff then do %ww vote") game.state = "voting" @commands.Cog.listener() async def on_reaction_add(self, reaction, user): if user.id == self.bot.user.id: return message = reaction.message if message.channel.id in self.games and self.games[message.channel.id].state == "preparing": game = self.games[message.channel.id] if game.join_message.id == message.id: if game.fetch_player(user.id) == -1: game.players.append(user) await message.edit(embed=game.get_refreshed_embed()) @commands.Cog.listener() async def on_reaction_remove(self, reaction, user): message = reaction.message if message.channel.id in self.games and self.games[message.channel.id].state == "preparing": game = self.games[message.channel.id] if game.join_message.id == message.id: if game.fetch_player(user.id) != -1: for player in range(len(game.players)): if not isinstance(game.players[player], int) and game.players[player].id == user.id: del game.players[player] await message.edit(embed=game.get_refreshed_embed()) @werewolf.command() async def cancel(self, ctx): if ctx.message.channel.id in self.games: game = self.games[ctx.channel.id] if game.host.id == ctx.message.author.id: del self.games[ctx.channel.id] await ctx.send("game cancelled") def setup(bot): bot.add_cog(Dictionary(bot))

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24,522

4.346973

0.119095

0.032831

0.034285

0.016071

0.594398

0.560496

0.522461

0.498584

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0.44356

0

0.007294

0.345853

24,522

636

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38.556604

0.805436

0

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0.128

0

null

0

null

0

1

0

2c8b5792d3174dff39013842e2317ce417ed4a8a

650

py

Python

main.py

KShah707/TweetDownloader

ff6770e2f86273919c279466337a4e5ab2cd63e0

[ "MIT" ]

null

main.py

KShah707/TweetDownloader

ff6770e2f86273919c279466337a4e5ab2cd63e0

[ "MIT" ]

null

main.py

KShah707/TweetDownloader

ff6770e2f86273919c279466337a4e5ab2cd63e0

[ "MIT" ]

null

################################################### # Uses the tweepy client to query a user's tweets # ################################################### import csv import tweepy # Load secrets from separate file from user_secrets import * # Set up API client auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET) auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET) api = tweepy.API(auth) # Fetch all tweets with open('downloaded_tweets.csv', 'w') as outfile: writer = csv.writer(outfile) my_tweets = [[tweet.full_text] for tweet in api.user_timeline(tweet_mode='extended')] print(my_tweets) writer.writerows(my_tweets)

30.952381

89

0.641538

83

650

4.843373

0.566265

0.08209

0.084577

0.109453

0

0.124615

650

21

90

30.952381

0.706503

0.176923

0

0.070093

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0

1

0

false

0

0.272727

0

0.272727

0.090909

0

null

0

null

0

1

0

2c8c64b7f637476a4c3e62cdc4f47747851211f2

1,664

py

Python

anime_downloader/sites/nyaa.py

Alsira/anime-downloader

d82b4cfd5c7c6c358d0d8ffd36ce2d5c4a285595

[ "Unlicense" ]

1,077

2020-10-17T15:43:17.000Z

2022-03-31T15:24:29.000Z

anime_downloader/sites/nyaa.py

Alsira/anime-downloader

d82b4cfd5c7c6c358d0d8ffd36ce2d5c4a285595

[ "Unlicense" ]

509

2018-06-01T13:07:56.000Z

2020-10-17T13:34:39.000Z

anime_downloader/sites/nyaa.py

Alsira/anime-downloader

d82b4cfd5c7c6c358d0d8ffd36ce2d5c4a285595

[ "Unlicense" ]

255

2018-05-27T03:52:11.000Z

2020-10-12T17:27:38.000Z

from anime_downloader.sites.anime import Anime, AnimeEpisode, SearchResult from anime_downloader.sites import helpers class Nyaa(Anime, sitename='nyaa'): """ Site: https://nyaa.si Config ~~~~~~ filter: Choose filter method in search. One of ['No filter', 'No remakes', 'Trusted Only'] category: Choose categories to search. One of ['Anime Music Video', 'English-translated', 'Non-English-translated'] """ sitename = 'nyaa' url = f'https://{sitename}.si' @classmethod def search(cls, query): filters = {"No filter": 0, "No remakes": 1, "Trusted only": 2} categories = {"Anime Music Video": "1_1", "English-translated": "1_2", "Non-English-translated": "1_3"} self = cls() parameters = {"f": filters[self.config["filter"]], "c": categories[self.config["category"]], "q": query, "s": "size", "o": "desc"} search_results = helpers.soupify(helpers.get(f"https://nyaa.si/", params=parameters)) search_results = [ SearchResult( title=i.select("a:not(.comments)")[1].get("title"), url=i.select_one('a[href*="magnet"]')['href'], meta={'peers': i.find_all('td', class_='text-center')[3].text + ' peers', 'size':i.find_all('td', class_='text-center')[1].text}) for i in search_results.select("tr.default, tr.success") ] return search_results def _scrape_episodes(self): # the magnet has all episodes making this redundant return [self.url] class NyaaEpisode(AnimeEpisode, sitename='nyaa'): def _get_sources(self): return [('no_extractor', self.url)]

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4.859223

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0.047952

0.04995

0

0.009224

0.218149

1,664

46

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0

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0

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false

0

0.08

0.48

0

null

0

null

0

1

0

2c8f674fb4bb528a31df28c9e6f31e31a0334ee4

810

py

Python

src/hgg_coffea/tools/xgb_loader.py

holzman/hgg-coffea

5aabdb127edaa15b0f22d54f0e3ccdc74c5c10de

[ "BSD-3-Clause" ]

3

2021-07-22T07:02:03.000Z

2021-09-22T07:01:59.000Z

src/hgg_coffea/tools/xgb_loader.py

holzman/hgg-coffea

5aabdb127edaa15b0f22d54f0e3ccdc74c5c10de

[ "BSD-3-Clause" ]

2

2021-08-16T16:08:09.000Z

2021-11-12T00:41:50.000Z

src/hgg_coffea/tools/xgb_loader.py

holzman/hgg-coffea

5aabdb127edaa15b0f22d54f0e3ccdc74c5c10de

[ "BSD-3-Clause" ]

8

2021-07-22T07:49:19.000Z

2022-01-26T22:58:03.000Z

import gzip import lzma import warnings from typing import Optional import xgboost def _get_gzip(fname: str) -> bytearray: return bytearray(gzip.open(fname, "rb").read()) def _get_lzma(fname: str) -> bytearray: return bytearray(lzma.open(fname, "rb").read()) _magics = { b"\x1f\x8b": _get_gzip, b"\xfd7": _get_lzma, } def load_bdt(fname: str) -> Optional[xgboost.Booster]: try: bdt = xgboost.Booster() with open(fname, "rb") as f: magic = f.read(2) opener = _magics.get(magic, lambda x: x) bdt.load_model(opener(fname)) except xgboost.core.XGBoostError as xgberr: warnings.warn(repr(xgberr)) bdt = None except FileNotFoundError as fnferr: warnings.warn(repr(fnferr)) bdt = None return bdt

21.891892

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810

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0.066

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0

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0.245679

810

36

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false

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0.407407

0

null

0

null

0

1

0

2c8faf8eecad5b6ac0b19aefead4deb655a3a6fb

16,629

py

Python

latent_rationale/snli/util.py

bastings/interpretable_neural_predictions

fef61833bd22205dc2d4f77e2c0ed3f40cbe8ea6

[ "MIT" ]

100

2019-05-21T21:26:19.000Z

2022-03-27T18:22:27.000Z

latent_rationale/snli/util.py

bastings/interpretable_neural_predictions

fef61833bd22205dc2d4f77e2c0ed3f40cbe8ea6

[ "MIT" ]

6

2019-07-30T03:08:44.000Z

2021-05-07T16:49:55.000Z

latent_rationale/snli/util.py

bastings/interpretable_neural_predictions

fef61833bd22205dc2d4f77e2c0ed3f40cbe8ea6

[ "MIT" ]

20

2019-06-19T18:36:41.000Z

2022-01-08T12:59:39.000Z

import os from argparse import ArgumentParser import torch from hashlib import md5 import numpy as np import glob import re from torch.nn import functional as F from latent_rationale.snli.constants import UNK_TOKEN, PAD_TOKEN, INIT_TOKEN from latent_rationale.snli.plotting import plot_heatmap from latent_rationale.snli.text import data BIN_REGEX = re.compile(r"$ | $") NON_BIN_REGEX = re.compile(r"$[A-Z.,:$]+|$") def masked_softmax(t, mask, dim=-1): t = torch.where(mask, t, t.new_full([1], float('-inf'))) return F.softmax(t, dim=dim) def get_data_fields(glove_words, lowercase=False, init_token=INIT_TOKEN): not_in_glove = set() def _tokens_from_binary_parse(s): tokens = re.sub(BIN_REGEX, "", s).split() tokens = unk_unknown_tokens( tokens, glove_words=glove_words, not_in_glove=not_in_glove) return tokens def _tokens_from_non_binary_parse(s): tokens = re.sub(NON_BIN_REGEX, "", s).split() tokens = unk_unknown_tokens( tokens, glove_words=glove_words, not_in_glove=not_in_glove) return tokens input_field = data.Field( lower=lowercase, tokenize=_tokens_from_binary_parse, batch_first=True, include_lengths=True, init_token=init_token, pad_token=PAD_TOKEN, unk_token=UNK_TOKEN) label_field = data.Field( sequential=False, batch_first=True, unk_token=None) return input_field, label_field, not_in_glove def unk_unknown_tokens(tokens, n=100, lowercase=False, glove_words=None, not_in_glove=None): """ Hash unknown words into N different UNK-classes :param tokens: :param n: hash tokens into this many classes :param lowercase: :param glove_words: a set with all valid glove words :param not_in_glove: an empty set where we store words that were not in glove :return: """ new_tokens = [] for token in tokens: if lowercase: token = token.lower() if token not in glove_words: not_in_glove.add(token) hash_idx = hash_token(token, n=n) token = "<unk_{:02d}>".format(hash_idx) new_tokens.append(token) return new_tokens def get_n_correct(batch, answer): """get number of correct predictions (float)""" return (torch.max(answer, 1)[1].view( batch.label.size()) == batch.label).float().sum().item() def find_ckpt_in_directory(path): for f in os.listdir(os.path.join(path, "")): if f.startswith('best_ckpt'): return os.path.join(path, f) def save_checkpoint(ckpt, save_path, iterations, prefix="ckpt", dev_acc=None, test_acc=None, delete_old=False): ckpt_prefix = os.path.join(save_path, prefix) ckpt_path = ckpt_prefix + "_iter_{:08d}".format(iterations) if dev_acc is not None: ckpt_path += "_devacc_{:4.2f}".format(dev_acc) if test_acc is not None: ckpt_path += "_testacc_{:4.2f}".format(test_acc) ckpt_path += ".pt" try: torch.save(ckpt, ckpt_path) except IOError: print("Error while saving checkpoint (iteration %d)" % iterations) if delete_old: try: for f in glob.glob(ckpt_prefix + '*'): if f != ckpt_path: os.remove(f) except IOError: print("Error while deleting old checkpoint") def load_glove_words(word_vectors): print("Loading Glove dictionary: {}".format(word_vectors)) words = set() path = os.path.join("data/snli", word_vectors + ".words.txt") with open(path, mode="r", encoding="utf-8") as f: for line in f: word = line.rstrip() words.add(word) print("Loaded:", len(words), "words") return words def get_z_counts(att, prem_mask, hypo_mask): """ Compute z counts (number of 0, continious, 1 elements). :param att: similarity matrix [B, prem, hypo] :param prem_mask: :param hypo_mask: :return: z0, zc, z1 """ # mask out all invalid positions with -1 att = torch.where(hypo_mask.unsqueeze(1), att, att.new_full([1], -1.)) att = torch.where(prem_mask.unsqueeze(2), att, att.new_full([1], -1.)) z0 = (att == 0.).sum().item() zc = ((0 < att) & (att < 1)).sum().item() z1 = (att == 1.).sum().item() assert (att > -1).sum().item() == z0 + zc + z1, "mismatch" return z0, zc, z1 def get_device(): if torch.cuda.is_available(): return torch.device('cuda') else: return torch.device('cpu') def print_config(config): for k, v in vars(config).items(): print("%22s : %16s" % (k, str(v))) print() def print_parameters(model): model_parameters = filter(lambda p: p.requires_grad, model.parameters()) n_params = sum([np.prod(p.size()) for p in model_parameters]) print("Total params: %d" % n_params) for name, p in model.named_parameters(): if p.requires_grad: print("%30s : %12s" % (name, list(p.size()))) else: print("%30s : %12s (no-grad)" % (name, list(p.size()))) print() def hash_token(token, n=100): return int(md5(token.encode()).hexdigest(), 16) % n def makedirs(name): """helper function for python 2 and 3 to call os.makedirs() avoiding an error if the directory to be created already exists""" import os, errno try: os.makedirs(name) except OSError as ex: if ex.errno == errno.EEXIST and os.path.isdir(name): # ignore existing directory pass else: # a different error happened raise def remove_padding(text, pad_token): try: cut = text.index(PAD_TOKEN) text = text[:cut] except ValueError: # no padding present pass return text def extract_attention(model, data_iter, input_vocab, answer_vocab): """ :param model: :param data_iter: :param input_vocab: :param answer_vocab: :return: """ if not hasattr(model, "prem2hypo_att"): return data_iter.init_epoch() model.eval() p2h_att = [] h2p_att = [] prems = [] hypos = [] predictions = [] targets = [] with torch.no_grad(): for i, batch in enumerate(data_iter, 1): result = model(batch) for j in range(batch.batch_size): prem = [input_vocab.itos[x] for x in batch.premise[0][j]] hypo = [input_vocab.itos[x] for x in batch.hypothesis[0][j]] prem = remove_padding(prem, PAD_TOKEN) hypo = remove_padding(hypo, PAD_TOKEN) label = answer_vocab.itos[batch.label[j]] answer = answer_vocab.itos[result.argmax(dim=-1)[j]] prem2hypo_att = model.prem2hypo_att[j].cpu().numpy() hypo2prem_att = model.hypo2prem_att[j].cpu().numpy() prem2hypo_att = prem2hypo_att[:len(prem), :len(hypo)] hypo2prem_att = hypo2prem_att[:len(hypo), :len(prem)] targets.append(label) predictions.append(answer) p2h_att.append(prem2hypo_att) h2p_att.append(hypo2prem_att) prems.append(prem) hypos.append(hypo) return p2h_att, h2p_att, prems, hypos, predictions, targets def print_examples(model, data_iter, input_vocab, answer_vocab, save_path, iterations, n=3, writer=None, skip_null=True): """ :param model: :param data_iter: :param input_vocab: :param answer_vocab: :param save_path: :param iterations: :param n: :param writer: Tensorboard writer to write attention images to Tensorboard :param skip_null: do not show NULL (first) symbol in plot :return: """ data_iter.init_epoch() model.eval() n_printed = 0 with torch.no_grad(): for i, batch in enumerate(data_iter, 1): result = model(batch) for j in range(batch.batch_size): prem = [input_vocab.itos[x] for x in batch.premise[0][j]] hypo = [input_vocab.itos[x] for x in batch.hypothesis[0][j]] try: cut = prem.index(PAD_TOKEN) prem = prem[:cut] except ValueError: pass try: cut = hypo.index(PAD_TOKEN) hypo = hypo[:cut] except ValueError: pass label = answer_vocab.itos[batch.label[j]] answer = answer_vocab.itos[result.argmax(dim=-1)[j]] # extract attention matrices if hasattr(model, "prem2hypo_att"): prem2hypo_att = model.prem2hypo_att[j].cpu().numpy() hypo2prem_att = model.hypo2prem_att[j].cpu().numpy() if skip_null: prem2hypo_att = prem2hypo_att[1:, 1:] hypo2prem_att = hypo2prem_att[1:, 1:] prem = prem[1:] hypo = hypo[1:] # attention is normalized by last dimension, so columns here name = "ex{:02d}_prem2hypo_att".format(n_printed) if writer is not None: writer.add_image("data/" + name, prem2hypo_att[None, :, :], iterations) path = os.path.join(save_path, name + ".pdf") plot_heatmap(prem2hypo_att, row_labels=prem, column_labels=hypo, output_path=path) # attention is normalized by last dimension, so columns here name = "ex{:02d}_hypo2prem_att".format(n_printed) if writer is not None: writer.add_image("data/" + name, hypo2prem_att[None, :, :], iterations) path = os.path.join(save_path, name + ".pdf") plot_heatmap(hypo2prem_att, row_labels=prem, column_labels=hypo, output_path=path) # extract multi-head self-attention matrices if hasattr(model, "prem_self_att_samples"): for k, a in enumerate(model.prem_self_att_samples): prem_self_att = a[j].cpu().numpy() prem_self_att = prem_self_att[:len(prem), :len(prem)] name = "ex{:02d}_prem_sa{}".format(n_printed, k) if writer is not None: writer.add_image("data/" + name, prem_self_att[None, :, :], iterations) name = name + ".pdf" plot_heatmap(prem_self_att, row_labels=prem, column_labels=prem, output_path=os.path.join(save_path, name)) if hasattr(model, "hypo_self_att_samples"): for k, a in enumerate(model.hypo_self_att_samples): hypo_self_att = a[j].cpu().numpy() hypo_self_att = hypo_self_att[:len(hypo), :len(hypo)] name = "ex{:02d}_hypo_sa{}".format(n_printed, k) if writer is not None: writer.add_image("data/" + name, hypo_self_att[None, :, :], iterations) name = name + ".pdf" plot_heatmap(hypo_self_att, row_labels=prem, column_labels=prem, output_path=os.path.join(save_path, name)) # extract self-attention matrices if hasattr(model, "prem_self_att") and \ model.prem_self_att is not None: prem_self_att = model.prem_self_att[j].cpu().numpy() hypo_self_att = model.hypo_self_att[j].cpu().numpy() plot_heatmap(prem_self_att, row_labels=prem, column_labels=prem, output_path=os.path.join( save_path, "ex%02d_prem_self_att.pdf" % n_printed)) plot_heatmap(hypo_self_att, row_labels=hypo, column_labels=hypo, output_path=os.path.join( save_path, "ex%02d_hypo_self_att.pdf" % n_printed)) print("Example {}".format(n_printed)) print("{:11} : {}".format("Premise:", " ".join(prem))) print("{:11} : {}".format("Hypothesis:", " ".join(hypo))) print("{:11} : {}".format("Label:", label)) print("{:11} : {}".format("Prediction:", answer)) print() n_printed += 1 if n_printed == n: return def get_predict_args(): parser = ArgumentParser(description='PyTorch/torchtext SNLI example') parser.add_argument('--ckpt', type=str, default="path_to_checkpoint") args = parser.parse_args() return args def get_args(): parser = ArgumentParser(description='SNLI') parser.add_argument('--save_path', type=str, default='results/snli/default') parser.add_argument('--resume_snapshot', type=str, default='') parser.add_argument('--epochs', type=int, default=200) parser.add_argument('--batch_size', type=int, default=64) parser.add_argument('--embed_size', type=int, default=300) parser.add_argument('--proj_size', type=int, default=200) parser.add_argument('--hidden_size', type=int, default=200) parser.add_argument('--n_layers', type=int, default=1) parser.add_argument('--print_every', type=int, default=100) parser.add_argument('--eval_every', type=int, default=1000) parser.add_argument('--save_every', type=int, default=1000) parser.add_argument('--dropout', type=float, default=0.2) parser.add_argument('--lr', type=float, default=0.0002) parser.add_argument('--min_lr', type=float, default=5e-5) parser.add_argument('--lr_decay', type=float, default=0.999) parser.add_argument('--weight_decay', type=float, default=1e-6) parser.add_argument('--patience', type=int, default=10000) parser.add_argument('--max_grad_norm', type=float, default=5.) parser.add_argument('--stop_lr_threshold', type=float, default=1e-5) parser.add_argument('--max_relative_distance', type=int, default=11) parser.add_argument('--model', choices=["recurrent", "decomposable"], default="decomposable") parser.add_argument('--dist', choices=["", "hardkuma"], default="") parser.add_argument('--self-attention', action='store_true', help="intra-sentence attention (Decomposable model)") parser.add_argument('--no-bidirectional', action='store_false', dest='birnn') # control Hard Kuma sparsity parser.add_argument('--selection', type=float, default=1.0) # lagrange settings parser.add_argument('--lagrange_lr', type=float, default=0.01, help="learning rate for lagrange") parser.add_argument('--lagrange_alpha', type=float, default=0.99, help="alpha for computing the running average") parser.add_argument('--lambda_init', type=float, default=1e-5, help="initial value for lambda") # misc parser.add_argument('--no-projection', action='store_false', dest='projection') parser.add_argument('--mask-diagonal', action='store_true') parser.add_argument('--overwrite', action='store_true', help="erase save_path if it exists") parser.add_argument('--no-emb-normalization', action='store_false', dest='normalize_embeddings') parser.add_argument('--train_embed', action='store_false', dest='fix_emb') parser.add_argument('--word_vectors', type=str, default='glove.840B.300d') args = parser.parse_args() return args

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null

0

1

0

2c9220dbfde66eef7cdc24410685f09d9949bf06

5,357

py

Python

lc_functions.py

mrawls/kepler-makelc

72a929b04d1c71bb5e854b96a9901544f681ed86

[ "MIT" ]

1

2018-09-10T01:35:08.000Z

lc_functions.py

mrawls/kepler-makelc

72a929b04d1c71bb5e854b96a9901544f681ed86

[ "MIT" ]

null

lc_functions.py

mrawls/kepler-makelc

72a929b04d1c71bb5e854b96a9901544f681ed86

[ "MIT" ]

null

import numpy as np from pyraf import iraf from pyraf.iraf import kepler ''' Useful functions for Kepler light curve processing Use this with the program 'makelc.py' Originally by Jean McKeever Edited and improved by Meredith Rawls ''' # calculate orbital phase # times must be a list of observation times in the same units as BJD0 # it returns 'phases': orbital phases from 0 to 1 # it also returns 'phasedoubles': twice as long as 'phases' and now from 0 to 2 def phasecalc(times, period=100, BJD0=2454833): phases = [] cycles = [] for i in range(0, len(times)): fracP = (times[i] - BJD0) / period if fracP < 0: phases.append(fracP % 1) cycles.append(int(fracP)) else: phases.append(fracP % 1) cycles.append(int(fracP) + 1) #print(fracP, phases[i]) return phases # remove long-term trends # uses a simple 3rd-order polynomial by default # operates on one array at a time (e.g., after all quarters have been combined) def long_detrend(t, flux, order=3): model = np.polyfit(t, flux, order) fit = np.zeros(len(t)) # apply the model coefficients to create the fit for i in range(0, order+1): fit += model[i]*np.power(t, (order-i)) #flux = flux/fit*1e6 - 1e6 # put it in ppm >:( flux = flux/fit*np.median(flux) # don't put it in ppm, because ppm is annoying return t, flux # Delete any observation that has one or more NaN values. # Assumes there are six parallel arrays... use dummy arrays if you don't have 6 # columns of interest to operate on (sorry). # Operates on one quarter at a time def nan_delete(time, flux, ferr, other1, other2, other3): a = [] a = [time, flux, ferr, other1, other2, other3] atrans = np.transpose(a) newatrans = [] newa = [] for row in atrans: # only save rows that DON'T contain a NaN value if np.isnan(row).any() != True: newatrans.append(row) newa = np.transpose(newatrans) newtime = newa[0] newflux = newa[1] newferr = newa[2] newother1 = newa[3] newother2 = newa[4] newother3 = newa[5] return newtime, newflux, newferr, newother1, newother2, newother3 # Put data from different quarters on the same AVERAGE level # operates on a list of arrays (multiple quarters) all at once # DON'T USE THIS ONE # def normalize_qtr_avg(flux): # sumflux = 0 # npts = 0 # for arr in flux: # sumflux += np.nansum(arr) # npts += len(arr[arr>0]) # avgflux = sumflux/npts # overall average for all quarters # for arr in flux: # avg_arr = np.mean(arr[arr>0]) # average for an individual quarter # arr += avgflux - avg_arr # return flux # Put data from different quarters on the same MEDIAN level # operates on a list of arrays (multiple quarters) all at once def normalize_qtr_med(flux): sumflux = 0 npts = 0 for arr in flux: sumflux += np.nansum(arr) npts += len(arr) avgflux = sumflux/npts # overall average for all quarters for arr in flux: med_arr = np.median(arr) # median for an individual quarter arr += avgflux - med_arr return flux # Line up the gaps within each quarter # operates on a list of arrays (multiple quarters) all at once def lineup_qtr_gaps(time, flux, maskstart, maskend): diffs = np.zeros(len(time) - 1) for i in range(0,len(time) - 1): # loop through quarters # calculate differences between flux points at quarter start/end start = 0 end = -1 for idx, mask in enumerate(maskstart): while (time[i][end] > maskstart[idx] and time[i][end] < maskend[idx]): #print('end', end, time[i][end], maskstart[idx], maskend[idx]) end -= 1 while (time[i+1][start] > maskstart[idx] and time[i+1][start] < maskend[idx]): #print('start', start, time[i+1][start], maskstart[idx], maskend[idx]) start += 1 diffs[i] = (flux[i][end] - flux[i+1][start]) # maxi will find the point with the largest change in flux maxi = lambda z: np.where(max(abs(z)) == abs(z))[0][0] cntr = 0 # counter max_val = max(abs(diffs)) while max_val > 100: #original value here was 100 # this is the index of the largest change in flux, so it needs adjusting ind = maxi(diffs) # this is the actual change in flux associated with that index diff = diffs[ind] # adjust the flux at this spot and its neighbor so they meet flux[ind] = flux[ind] - diff/2.0 flux[ind+1] = flux[ind+1] + diff/2.0 diffs = np.zeros(len(time) - 1) for i in range(0, len(time) - 1): # calculate differences between flux points at quarter start/end, again start = 0 end = -1 for idx, mask in enumerate(maskstart): while time[i][end] > maskstart[idx] and time[i][end] < maskend[idx]: #print('end', end, time[i][end], maskstart[idx], maskend[idx]) end -= 1 while time[i+1][start] > maskstart[idx] and time[i+1][start] < maskend[idx]: #print('start', start, time[i+1][start], maskstart[idx], maskend[idx]) start += 1 diffs[i] = (flux[i][end] - flux[i+1][start]) cntr += 1 # count how many times this while-loop happens max_val = max(abs(diffs)) # print(max_val, cntr) return time, flux # performs detrending with cotrending basis vectors (cbvs) # lcin and lcout must both be FITS filenames def kepcotrend(lcin, lcout, cbvfile, maskfile=''): iraf.kepcotrend(infile=lcin, outfile=lcout, cbvfile=cbvfile, vectors='1 2', method='simplex', fitpower=1, iterate='yes', sigmaclip=2.0, maskfile=maskfile, scinterp='None', plot='no', clobber='yes', verbose='no') return

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null

0

null

0

1

0

2c93c3807680923e216b02227b5a6105e6428b73

17,649

py

Python

src/beacon_api/utils/polyvalent_functions.py

jrambla/beacon-2.x

f6c8bbecd183471d62c01e040d6e0b3c9ef8f448

[ "Apache-2.0" ]

null

src/beacon_api/utils/polyvalent_functions.py

jrambla/beacon-2.x

f6c8bbecd183471d62c01e040d6e0b3c9ef8f448

[ "Apache-2.0" ]

null

src/beacon_api/utils/polyvalent_functions.py

jrambla/beacon-2.x

f6c8bbecd183471d62c01e040d6e0b3c9ef8f448

[ "Apache-2.0" ]

null

""" Functions used by different endopoints. - To do basic operations - To parse the filters request - To manage access resolution """ import ast import logging import yaml import requests from pathlib import Path from ..api.exceptions import BeaconBadRequest, BeaconServerError, BeaconForbidden, BeaconUnauthorised from .. import __apiVersion__ from ..conf.config import DB_SCHEMA LOG = logging.getLogger(__name__) # ---------------------------------------------------------------------------------------------------------------------- # BASIC FUNCTIONS # ---------------------------------------------------------------------------------------------------------------------- def create_prepstmt_variables(value): """Takes a value of how many prepared variables you want to pass a query and creates a string to put it in it""" dollars = [] for element in range(value): element += 1 variable = "$" + str(element) dollars.append(variable) return ", ".join(dollars) def filter_exists(include_dataset, datasets): """Return those datasets responses that the `includeDatasetResponses` parameter decides. Look at the exist parameter in each returned dataset to established HIT or MISS. """ if include_dataset == 'ALL': return datasets elif include_dataset == 'NONE': return [] elif include_dataset == 'HIT': return [d for d in datasets if d['exists'] is True] elif include_dataset == 'MISS': return [d for d in datasets if d['exists'] is False] def datasetHandover(dataset_name): """Return the datasetHandover with the correct name of the dataset.""" datasetHandover = [ { "handoverType" : { "id" : "CUSTOM", "label" : "Dataset info" }, "note" : "Dataset information and DAC contact details in EGA Website", "url" : f"https://ega-archive.org/datasets/{dataset_name}" } ] return datasetHandover # ---------------------------------------------------------------------------------------------------------------------- # YAML LOADER # ---------------------------------------------------------------------------------------------------------------------- def find_yml_and_load(input_file): """Try to load the access levels yaml and return it as a dict.""" file = Path(input_file) if not file.exists(): LOG.error(f"The file '{file}' does not exist", file=sys.stderr) return if file.suffix in ('.yaml', '.yml'): with open(file, 'r') as stream: file_dict = yaml.safe_load(stream) return file_dict # Otherwise, fail LOG.error(f"Unsupported format for {file}", file=sys.stderr) # ---------------------------------------------------------------------------------------------------------------------- # FILTERING TERMS MANAGEMENT # ---------------------------------------------------------------------------------------------------------------------- def parse_filters_request(filters_request_list): """Create a list of the filters passed in the query, where each filter is another list in the main list with the following elements: ontology, term, operator, value. """ list_filters = [] for unprocessed_filter in filters_request_list: filter_elements = unprocessed_filter.split(":") ontology = filter_elements[0] operator_switch = False for operator in [">=", "<=", "=", ">", "<"]: # TO DO: raise an error if "=<" or "=>" are given if operator in filter_elements[1]: operator = operator term = filter_elements[1].split(operator)[0] value = filter_elements[1].split(operator)[1] operator_switch = True break if operator_switch: final_elements = [ontology, term, operator, value] operator_switch = False else: final_elements = [ontology, filter_elements[1]] list_filters.append(final_elements) return list_filters async def prepare_filter_parameter(db_pool, filters_request): """Parse the filters parameters given in the query to create the string that needs to be passed to the SQL query. e.g. '(technology)::jsonb ?& array[''Illumina Genome Analyzer II'', ''Illumina HiSeq 2000''] AND (other)::jsonb ?& array[''example1'', ''example2''] """ # First we want to parse the filters request if isinstance(filters_request, list): list_filters = parse_filters_request(filters_request) else: list_filters = parse_filters_request(ast.literal_eval(filters_request)) combinations_list = "','".join([":".join([filter_elements[0],filter_elements[1]]) for filter_elements in list_filters]) combinations_list = "'" + combinations_list + "'" # Then we connect to the DB and retrieve the parameters that will be passed to the main query async with db_pool.acquire(timeout=180) as connection: try: query = f"""SELECT target_table, column_name, column_value FROM ontology_term_column_correspondance WHERE concat_ws(':', ontology, term) IN ({combinations_list})""" LOG.debug(f"QUERY filters info: {query}") statement = await connection.prepare(query) db_response = await statement.fetch() filter_dict = {} for record in list(db_response): if record["target_table"] not in filter_dict.keys(): filter_dict[record["target_table"]] = {} filter_dict[record["target_table"]][record["column_name"]] = [] filter_dict[record["target_table"]][record["column_name"]].append(record["column_value"]) elif record["column_name"] not in filter_dict[record["target_table"]].keys(): filter_dict[record["target_table"]][record["column_name"]] = [] filter_dict[record["target_table"]][record["column_name"]].append(record["column_value"]) else: filter_dict[record["target_table"]][record["column_name"]].append(record["column_value"]) # After we have retrieved the values in a dict with the target_table as keys and as value another dict with column_name as keys, we need to create the final string strings_list = [] final_string = "" for target_table, column_name_dict in filter_dict.items(): if target_table == "public.beacon_dataset_table": for column_name, values in column_name_dict.items(): string_values = ", ".join("'" + str(value) + "'" for value in values) string = f'({column_name})::jsonb ?& array[{string_values}]' strings_list.append(string) # Once we have the response, we parse it to create the final string needed as input if not strings_list: final_string = 'null' else: final_string = " AND ".join(strings_list) return str(final_string), filter_dict except Exception as e: raise BeaconServerError(f'Query filters DB error: {e}') # ---------------------------------------------------------------------------------------------------------------------- # ACCESS RELATED FUNCTIONS AND DICT # ---------------------------------------------------------------------------------------------------------------------- def access_resolution(request, token, host, public_data, registered_data, controlled_data): """Determine the access level for a user. Depends on user bona_fide_status, and by default it should be PUBLIC. """ permissions = [] # all should have access to PUBLIC datasets # unless the request is for specific datasets if public_data: permissions.append("PUBLIC") access = set(public_data) # empty if no datasets are given # for now we are expecting that the permissions are a list of datasets if registered_data and token["bona_fide_status"] is True: permissions.append("REGISTERED") access = access.union(set(registered_data)) # if user requests public datasets do not throw an error # if both registered and controlled datasets are request this will be shown first elif registered_data and not public_data: if token["authenticated"] is False: # token is not provided (user not authed) raise BeaconUnauthorised(request, host, "missing_token", 'Unauthorized access to dataset(s), missing token.') # token is present, but is missing perms (user authed but no access) raise BeaconForbidden(request, host, 'Access to dataset(s) is forbidden.') if controlled_data and 'permissions' in token and token['permissions']: # The idea is to return only accessible datasets # Default event, when user doesn't specify dataset ids # Contains only dataset ids from token that are present at beacon controlled_access = set(controlled_data).intersection(set(token['permissions'])) access = access.union(controlled_access) if controlled_access: permissions.append("CONTROLLED") # if user requests public datasets do not throw an error # By default permissions cannot be None, at worst empty set, thus this might never be reached elif controlled_data and not (public_data or registered_data): if token["authenticated"] is False: # token is not provided (user not authed) raise BeaconUnauthorised(request, host, "missing_token", 'Unauthorized access to dataset(s), missing token.') # token is present, but is missing perms (user authed but no access) raise BeaconForbidden(request, host, 'Access to dataset(s) is forbidden.') LOG.info(f"Accesible datasets are: {list(access)}.") return permissions, list(access) async def fetch_datasets_access(db_pool, datasets): """Retrieve 3 list of the available datasets depending on the access type""" LOG.info('Retrieving info about the available datasets (id and access type).') public = [] registered = [] controlled = [] async with db_pool.acquire(timeout=180) as connection: async with connection.transaction(): datasets_query = None if datasets == "null" or not datasets else ast.literal_eval(datasets) try: query = f"""SELECT access_type, id, stable_id FROM {DB_SCHEMA}.beacon_dataset WHERE coalesce(stable_id = any($1), true); """ LOG.debug(f"QUERY datasets access: {query}") statement = await connection.prepare(query) db_response = await statement.fetch(datasets_query) for record in list(db_response): if record['access_type'] == 'PUBLIC': public.append(record['id']) if record['access_type'] == 'REGISTERED': registered.append(record['id']) if record['access_type'] == 'CONTROLLED': controlled.append(record['id']) return public, registered, controlled except Exception as e: raise BeaconServerError(f'Query available datasets DB error: {e}') # ---------------------------------------------------------------------------------------------------------------------- # FILTER RESPONSE BASED ON ACCESS LEVELS # ---------------------------------------------------------------------------------------------------------------------- def filter_response(response, access_levels_dict, accessible_datasets, user_levels, field2access, parent_key=None): """ Recursive function that parses the response of the beacon to filter out those fields that are not accessible for the user (based on the access level). :response: beacon response :access_levels_dict: access levels dictionary created out of the yml file in /utils :accessible_datasets: list of datasets accessible by the user (taking into account its privileges) :user_levels: list of levels that the user has, i.e ['PUBLIC', 'REGISTERED'] :field2access: dictionary that maps the child_field name to its corresponding parent_field name in the access levels dict (i.e 'datasets' inside the parent 'beacon' maps to its parent name 'beaconDataset') :parent_key: used inside de recursion to store the parent key of the dict we are in """ final_dict = {} if isinstance(response, dict): for key, val in response.items(): translated_key = field2access[key] if key in field2access.keys() else key specific_access_levels_dict = access_levels_dict[parent_key] if parent_key else access_levels_dict if translated_key not in access_levels_dict.keys() and translated_key not in specific_access_levels_dict.keys(): final_dict[key] = val else: # if (isinstance(val, dict) or isinstance(val, list)) and key != "info": if (isinstance(val, dict) or isinstance(val, list)) and translated_key in access_levels_dict.keys(): parent_permission = True self_permission = True if access_levels_dict[translated_key]["accessLevelSummary"] in user_levels else False if parent_key: parent_permission = True if access_levels_dict[parent_key][key] in user_levels else False if self_permission and parent_permission: final_dict[key] = filter_response(val, access_levels_dict, accessible_datasets, user_levels, field2access, translated_key) else: valid_level = access_levels_dict[parent_key][translated_key] if parent_key else access_levels_dict[translated_key] if valid_level in user_levels: final_dict[key] = val elif isinstance(response, list): filtered = [] for element in response: if isinstance(element, dict): datasetId = element.get("internalId") if not datasetId or datasetId in accessible_datasets: # controlling specific access permission to show a dataset response filtered.append(filter_response(element, access_levels_dict, accessible_datasets, user_levels, field2access, parent_key)) return filtered return final_dict # ---------------------------------------------------------------------------------------------------------------------- # VARIANT HANDOVER and extra ANNOTATION # ---------------------------------------------------------------------------------------------------------------------- def snp_resultsHandover(variantId): """Create the resultsHanover dict by inserting the variantId into the template.""" resultsHandover = [ { "handoverType" : { "id" : "data:1106", "label" : "dbSNP ID" }, "note" : "Link to dbSNP database", "url" : f"https://www.ncbi.nlm.nih.gov/snp/?term={variantId}" }, { "handoverType" : { "id" : "data:1106", "label" : "dbSNP ID" }, "note" : "Link to dbSNP API", "url" : f"https://api.ncbi.nlm.nih.gov/variation/v0/beta/refsnp/{variantId[2:]}" } ] return resultsHandover async def fetch_variantAnnotations(variant_details): """ Create the a part of the variantsAnnotation response by fetching the cellBase API and the dbSNP API. The variant_id has to be in the following format: chrom:start:ref:alt. If in the variantDetails the alt is null, it has to be changed to a '-'. """ # cellBase chrom = variant_details.get("chromosome") if variant_details.get("chromosome") else variant_details.get("referenceName") start = variant_details.get("start") ref = variant_details.get("referenceBases") alt = variant_details.get("alternateBases") if variant_details.get("alternateBases") else '-' variant_id = ":".join([str(chrom), str(start + 1), ref, alt]) url = f"http://cellbase.clinbioinfosspa.es/cb/webservices/rest/v4/hsapiens/genomic/variant/{variant_id}/annotation" r = requests.get(url) cellBase_dict = r.json() if r else '' try: cellBase_rsID = cellBase_dict["response"][0]["result"][0]["id"] except: cellBase_rsID = None # dbSNP rsID = variant_details.get("variantId") if (variant_details.get("variantId") and variant_details.get("variantId") != ".") else cellBase_rsID if rsID: url = f"https://api.ncbi.nlm.nih.gov/variation/v0/beta/refsnp/{rsID[2:]}" r = requests.get(url) dnSNP_dict = r.json() if r else '' else: dnSNP_dict = '' return rsID, cellBase_dict, dnSNP_dict

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2c94bd3786b5a0a64f466b5fdfd28ee49d03d138

990

py

Python

02_Double/double_aws-samples_1_v1.py

Machine-Learning-Labs/DeepRacerRewardFunctionsCollection

f6addf4654de90f9d1669fd5de67331add93ab2f

[ "MIT" ]

17

2020-01-14T06:25:10.000Z

2022-01-25T18:02:37.000Z

02_Double/double_aws-samples_1_v1.py

Machine-Learning-Labs/DeepRacerRewardFunctionsCollection

f6addf4654de90f9d1669fd5de67331add93ab2f

[ "MIT" ]

null

02_Double/double_aws-samples_1_v1.py

Machine-Learning-Labs/DeepRacerRewardFunctionsCollection

f6addf4654de90f9d1669fd5de67331add93ab2f

[ "MIT" ]

5

2020-05-30T18:49:18.000Z

2021-09-03T19:38:39.000Z

''' @author: AWS Samples @Link: https://docs.aws.amazon.com/deepracer/latest/developerguide/what-is-deepracer.html @License: Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. ''' def reward_function(params): ''' Example of rewarding the agent to follow the track center line ''' # Read input parameters track_width = params['track_width'] distance_from_center = abs(params['distance_from_center']) # Calculate 3 marks that are farther and father away from the center line marker_1 = 0.1 * track_width marker_2 = 0.25 * track_width marker_3 = 0.5 * track_width # Give higher reward if the car is closer to center line and vice versa if distance_from_center <= marker_1: reward = 1 elif distance_from_center <= marker_2: reward = 0.5 elif distance_from_center <= marker_3: reward = 0.1 else: reward = 1e-3 # likely crashed/close to off-track return reward

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990

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null

0

null

0

1

0

2c95e40e7220fe3c7db4c0c8a471b2078f613932

14,498

py

Python

parsons/github/github.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

3

2019-09-05T16:57:15.000Z

2019-10-01T19:56:58.000Z

parsons/github/github.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

22

2019-09-03T13:23:37.000Z

2019-10-03T20:32:48.000Z

parsons/github/github.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

2

2019-09-01T18:30:10.000Z

2019-10-03T20:07:46.000Z

import logging from functools import partial, wraps import petl import requests from github import Github as PyGithub from github.GithubException import UnknownObjectException from parsons.etl.table import Table from parsons.utilities import check_env, files logger = logging.getLogger(__name__) def _wrap_method(decorator, method): def _wrapper(self, *args, **kwargs): bound_method = partial(method.__get__(self, type(self))) return decorator(bound_method)(*args, **kwargs) return _wrapper def decorate_methods(decorator): # Based on Django's django.utils.decorators.method_decorator def decorate(cls): for method in dir(cls): # Don't decorate dunder methods if method.startswith("__"): continue cls_method = getattr(cls, method) if callable(cls_method): setattr(cls, method, _wrap_method(decorator, cls_method)) return cls return decorate def wrap_github_404(func): @wraps(func) def _wrapped_func(*args, **kwargs): try: return (func)(*args, **kwargs) except UnknownObjectException: raise ParsonsGitHubError( "Couldn't find the object you referenced, maybe you need to log in?" ) return _wrapped_func class ParsonsGitHubError(Exception): pass @decorate_methods(wrap_github_404) class GitHub(object): """Creates a GitHub class for accessing the GitHub API. Uses ``parsons.utilities.check_env`` to load credentials from environment variables if not supplied. Supports either a username and password or an access token for authentication. The client also supports unauthenticated access. Args: username: Optional[str] Username of account to use for credentials. Can be set with ``GITHUB_USERNAME`` environment variable. password: Optional[str] Password of account to use for credentials. Can be set with ``GITHUB_PASSWORD`` environment variable. access_token: Optional[str] Access token to use for credentials. Can be set with ``GITHUB_ACCESS_TOKEN`` environment variable. """ def __init__(self, username=None, password=None, access_token=None): self.username = check_env.check('GITHUB_USERNAME', username, optional=True) self.password = check_env.check('GITHUB_PASSWORD', password, optional=True) self.access_token = check_env.check('GITHUB_ACCESS_TOKEN', access_token, optional=True) if self.username and self.password: self.client = PyGithub(self.username, self.password) elif self.access_token: self.client = PyGithub(self.access_token) else: self.client = PyGithub() def _as_table(self, paginated_list, page=None, page_size=100): """Converts a paginated list into a Parsons ``Table``. Uses the ``_rawData`` property of each item instead of calling ``raw_data`` to avoid making a separate request for each item in a page for types that PyGithub doesn't consider complete. Args: paginated_list: ``pygithub.PaginatedList.PaginatedList`` PyGithub paginated list page: Optional[int] Page number to load. Defaults to None. If not specified, all results are returned. page_size: int Page size. Defaults to 100. Ignored if ``page`` is not set. Returns: ``Table`` Table object created from the raw data of the list """ if page is not None: page_start = (page - 1) * page_size page_end = page_start + page_size list_pages = paginated_list[page_start:page_end] else: list_pages = paginated_list return Table([list_item._rawData for list_item in list_pages]) def get_user(self, username): """Loads a GitHub user by username Args: username: str Username of user to load Returns: dict User information """ return self.client.get_user(username).raw_data def get_organization(self, organization_name): """Loads a GitHub organization by name Args: organization_name: str Name of organization to load Returns: dict Organization information """ return self.client.get_organization(organization_name).raw_data def get_repo(self, repo_name): """Loads a GitHub repo by name Args: repo_name: str Full repo name (account/name) Returns: dict Repo information """ return self.client.get_repo(repo_name).raw_data def list_user_repos(self, username, page=None, page_size=100): """List user repos with pagination, returning a ``Table`` Args: username: str GitHub username page: Optional[int] Page number. All results are returned if not set. page_size: int Page size. Defaults to 100. Returns: ``Table`` Table with page of user repos """ logger.info(f'Listing page {page} of repos for user {username}') return self._as_table( self.client.get_user(username).get_repos(), page=page, page_size=page_size ) def list_organization_repos(self, organization_name, page=None, page_size=100): """List organization repos with pagination, returning a ``Table`` Args: organization_name: str GitHub organization name page: Optional[int] Page number. All results are returned if not set. page_size: int Page size. Defaults to 100. Returns: ``Table`` Table with page of organization repos """ logger.info(f'Listing page {page} of repos for organization {organization_name}') return self._as_table( self.client.get_organization(organization_name).get_repos(), page=page, page_size=page_size, ) def get_issue(self, repo_name, issue_number): """Loads a GitHub issue Args: repo_name: str Full repo name (account/name) issue_number: int Number of issue to load Returns: dict Issue information """ return self.client.get_repo(repo_name).get_issue(number=issue_number).raw_data def list_repo_issues(self, repo_name, state="open", assignee=None, creator=None, mentioned=None, labels=[], sort="created", direction="desc", since=None, page=None, page_size=100): """List issues for a given repo Args: repo_name: str Full repo name (account/name) state: str State of issues to return. One of "open", "closed", "all". Defaults to "open". assignee: Optional[str] Name of assigned user, "none", or "*". creator: Optional[str] Name of user that created the issue. mentioned: Optional[str] Name of user mentioned in the issue. labels: list[str] List of label names. Defaults to [] sort: str What to sort results by. One of "created", "updated", "comments". Defaults to "created". direction: str Direction to sort. One of "asc", "desc". Defaults to "desc". since: Optional[Union[datetime.datetime, datetime.date]] Timestamp to pull issues since. Defaults to None. page: Optional[int] Page number. All results are returned if not set. page_size: int Page size. Defaults to 100. Returns: ``Table`` Table with page of repo issues """ logger.info(f'Listing page {page} of issues for repo {repo_name}') kwargs_dict = {"state": state, "sort": sort, "direction": direction} if assignee: kwargs_dict["assignee"] = assignee if creator: kwargs_dict["creator"] = creator if mentioned: kwargs_dict["mentioned"] = mentioned if len(labels) > 0: kwargs_dict["labels"] = ",".join(labels) if since: kwargs_dict["since"] = f'{since.isoformat()[:19]}Z' return self._as_table( self.client.get_repo(repo_name).get_issues(**kwargs_dict), page=page, page_size=page_size, ) def get_pull_request(self, repo_name, pull_request_number): """Loads a GitHub pull request Args: repo_name: str Full repo name (account/name) pull_request_number: int Pull request number Returns: dict Pull request information """ return self.client.get_repo(repo_name).get_pull(pull_request_number).raw_data def list_repo_pull_requests(self, repo_name, state="open", base=None, sort="created", direction="desc", page=None, page_size=100): """Lists pull requests for a given repo Args: repo_name: str Full repo name (account/name) state: str One of "open, "closed", "all". Defaults to "open". base: Optional[str] Base branch to filter pull requests by. sort: str How to sort pull requests. One of "created", "updated", "popularity". Defaults to "created". direction: str Direction to sort by. Defaults to "desc". page: Optional[int] Page number. All results are returned if not set. page_size: int Page size. Defaults to 100. Returns: ``Table`` Table with page of repo pull requests """ logger.info(f'Listing page {page} of pull requests for repo {repo_name}') kwargs_dict = {"state": state, "sort": sort, "direction": direction} if base: kwargs_dict["base"] = base self._as_table( self.client.get_repo(repo_name).get_pulls(**kwargs_dict), page=page, page_size=page_size ) def list_repo_contributors(self, repo_name, page=None, page_size=100): """Lists contributors for a given repo Args: repo_name: str Full repo name (account/name) page: Optional[int] Page number. All results are returned if not set. page_size: int Page size. Defaults to 100. Returns: ``Table`` Table with page of repo contributors """ logger.info(f'Listing page {page} of contributors for repo {repo_name}') return self._as_table( self.client.get_repo(repo_name).get_contributors(), page=page, page_size=page_size ) def download_file(self, repo_name, path, branch=None, local_path=None): """Download a file from a repo by path and branch. Defaults to the repo's default branch if branch is not supplied. Uses the download_url directly rather than the API because the API only supports contents up to 1MB from a repo directly, and the process for downloading larger files through the API is much more involved. Because download_url does not go through the API, it does not support username / password authentication, and requires a token to authenticate. Args: repo_name: str Full repo name (account/name) path: str Path from the repo base directory branch: Optional[str] Branch to download file from. Defaults to repo default branch local_path: Optional[str] Local file path to download file to. Will create a temp file if not supplied. Returns: str File path of downloaded file """ if not local_path: local_path = files.create_temp_file_for_path(path) repo = self.client.get_repo(repo_name) if branch is None: branch = repo.default_branch logger.info(f'Downloading {path} from {repo_name}, branch {branch} to {local_path}') headers = None if self.access_token: headers = { 'Authorization': f'token {self.access_token}', } res = requests.get(f'https://raw.githubusercontent.com/{repo_name}/{branch}/{path}', headers=headers) if res.status_code == 404: raise UnknownObjectException(status=404, data=res.content) elif res.status_code != 200: raise ParsonsGitHubError( f'Error downloading {path} from repo {repo_name}: {res.content}') with open(local_path, 'wb') as f: f.write(res.content) logger.info(f'Downloaded {path} to {local_path}') return local_path def download_table(self, repo_name, path, branch=None, local_path=None, delimiter=','): """Download a CSV file from a repo by path and branch as a Parsons Table. Args: repo_name: str Full repo name (account/name) path: str Path from the repo base directory branch: Optional[str] Branch to download file from. Defaults to repo default branch local_path: Optional[str] Local file path to download file to. Will create a temp file if not supplied. delimiter: Optional[str] The CSV delimiter to use to parse the data. Defaults to ',' Returns: Parsons Table See :ref:`parsons-table` for output options. """ downloaded_file = self.download_file(repo_name, path, branch, local_path) return Table(petl.fromcsv(downloaded_file, delimiter=delimiter))

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0

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0

null

0

null

0

1

0

2c9cfa04dec4051e0276862ca37caf6daae18af1

3,716

py

Python

thirdparty/gd2c/gd2c/loader.py

ppiecuch/godot

ff2098b324b814a0d1bd9d5722aa871fc5214fab

[ "MIT", "Apache-2.0", "CC-BY-4.0", "Unlicense" ]

null

thirdparty/gd2c/gd2c/loader.py

ppiecuch/godot

ff2098b324b814a0d1bd9d5722aa871fc5214fab

[ "MIT", "Apache-2.0", "CC-BY-4.0", "Unlicense" ]

null

thirdparty/gd2c/gd2c/loader.py

ppiecuch/godot

ff2098b324b814a0d1bd9d5722aa871fc5214fab

[ "MIT", "Apache-2.0", "CC-BY-4.0", "Unlicense" ]

null

from __future__ import annotations from pathlib import Path from gd2c.gdscriptclass import GDScriptClass, GDScriptClassConstant, GDScriptFunctionConstant, GDScriptFunction, GDScriptGlobal, GDScriptMember, GDScriptFunctionParameter from gd2c.variant import VariantType from gd2c.bytecode import extract from typing import List, Iterable, TYPE_CHECKING import json def to_camel_case(snake_str: str, capitalize_first: bool = True): components = snake_str.split('_') # We capitalize the first letter of each component if capitalize_first: return ''.join(x.title() for x in components[0:]) else: return components[0] + ''.join(x.title() for x in components[1:]) if TYPE_CHECKING: from gd2c.project import Project class JsonGDScriptLoader: def __init__(self, project: Project): self._project = project def load_classes(self, physical_path: Path) -> Iterable[GDScriptClass]: with physical_path.open() as f: data = json.load(f) yield self._build_class(physical_path, data) def _build_class(self, physical_path: Path, data) -> GDScriptClass: cls = GDScriptClass( self._project.to_resource_path(str(physical_path)), data.get("name", None) or self._project.generate_unique_class_name(to_camel_case(physical_path.with_suffix('').stem)), self._project.generate_unique_class_type_id()) cls.base_resource_path = data["base_type"] cls.built_in_type = data["type"] for index, entry in enumerate(data["global_constants"]): glob = GDScriptGlobal(index, entry["name"], entry["original_name"], entry["type_code"], entry["kind_code"], entry["value"], entry["source"]) cls.globals[glob.index] = glob for signal in data["signals"]: cls.add_signal(signal) for entry in data["members"]: member = GDScriptMember(entry["name"], int(entry["index"]), entry["type"]) cls.add_member(member) for index, entry in enumerate(data["constants"]): cconst = GDScriptClassConstant(entry["name"], int(entry["type"]), bytes(list(entry["data"])), entry["declaration"]) cls.add_constant(cconst) for index, entry in enumerate(data["methods"]): func = GDScriptFunction(entry["name"], GDScriptFunction.TYPE_METHOD) func.stack_size = int(entry["stack_size"]) func.default_arguments_jump_table = list(map(lambda x: int(x), entry["default_arguments"])) func.return_vtype = VariantType.get(int(entry["return_type"]["type"])) func.global_names = entry["global_names"] num_parameters = len(entry["parameters"]) len_jump_table = len(func.default_arguments_jump_table) for pindex, pentry in enumerate(entry["parameters"]): param = GDScriptFunctionParameter( pentry["name"], VariantType.get(pentry["type"]), pindex) param.is_optional = pindex >= num_parameters - len_jump_table func.add_parameter(param) for centry in entry["constants"]: mconst = GDScriptFunctionConstant( int(centry["index"]), centry["type"], bytes(list(map(lambda x: int(x), centry["data"]))), centry["declaration"]) func.add_constant(mconst) ip = 0 while ip < len(entry["bytecode"]): op = extract(func, entry["bytecode"], ip) func.add_op(ip, op) ip += op.stride cls.add_function(func) return cls

43.209302

170

0.626749

417

3,716

5.390887

0.314149

0.032028

0.017349

0.020018

0.129004

0.076512

0.023132

0

0.002901

0.257804

3,716

85

171

43.717647

0.812183

0.012917

0

0.07665

0

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0.057971

false

0

0.115942

0

0.231884

0

null

0

null

0

1

0

2c9e2ce825149494c4555d540152aae13598ea62

1,301

py

Python

deepppl/tests/target_py/kmeans.py

sfantao/deepppl

3091c342814744d622eda6f7a185085d420a152b

[ "Apache-2.0" ]

18

2018-06-07T17:41:30.000Z

2021-03-19T23:31:14.000Z

deepppl/tests/target_py/kmeans.py

sfantao/deepppl

3091c342814744d622eda6f7a185085d420a152b

[ "Apache-2.0" ]

19

2018-06-11T17:42:03.000Z

2020-10-13T17:19:11.000Z

deepppl/tests/target_py/kmeans.py

sfantao/deepppl

3091c342814744d622eda6f7a185085d420a152b

[ "Apache-2.0" ]

7

2018-06-08T20:50:24.000Z

2020-10-12T22:00:09.000Z

import torch from torch import tensor, rand import pyro import torch.distributions.constraints as constraints import pyro.distributions as dist def transformed_data(D=None, K=None, N=None, y=None): neg_log_K = -log(K) return {'neg_log_K': neg_log_K} def model(D=None, K=None, N=None, y=None, transformed_data=None): neg_log_K = transformed_data['neg_log_K'] mu = sample('mu', ImproperUniform(shape=(K, D))) soft_z = zeros((N, K)) for n in range(1, N + 1): for k in range(1, K + 1): soft_z[n - 1, k - 1] = neg_log_K - 0.5 * dot_self(mu[k - 1] - y [n - 1]) for k in range(1, K + 1): sample('mu' + '__{}'.format(k - 1) + '__1', dist.Normal(zeros(D), 1 ), obs=mu[k - 1]) for n in range(1, N + 1): sample('expr' + '__{}'.format(n) + '__2', dist.Exponential(1.0), obs=-log_sum_exp(soft_z[n - 1])) def generated_quantities(D=None, K=None, N=None, y=None, transformed_data= None, parameters=None): neg_log_K = transformed_data['neg_log_K'] mu = parameters['mu'] soft_z = zeros((N, K)) for n in range(1, N + 1): for k in range(1, K + 1): soft_z[n - 1, k - 1] = neg_log_K - 0.5 * dot_self(mu[k - 1] - y [n - 1]) return {'soft_z': soft_z}

34.236842

75

0.571868

225

1,301

3.115556

0.213333

0.057061

0.089872

0.042796

0.479315

0.459344

0.430813

0.410842

0

0.033368

0.262875

1,301

38

76

34.236842

0.697602

0

0.4375

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0.043779

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0.09375

false

0

0.15625

0

0.3125

0

null

0

null

0

1

0

2c9ffef9867b37cc6ff8be2016f65cefeb7bd057

5,885

py

Python

Siberia/plug/plugin_adminka.py

spouk/Siberia

0b7dfe2271b285eb038a09ef954ed8c605cbd2d2

[ "MIT" ]

null

Siberia/plug/plugin_adminka.py

spouk/Siberia

0b7dfe2271b285eb038a09ef954ed8c605cbd2d2

[ "MIT" ]

null

Siberia/plug/plugin_adminka.py

spouk/Siberia

0b7dfe2271b285eb038a09ef954ed8c605cbd2d2

[ "MIT" ]

null

#!/usr/local/bin/python __author__ = 'spouk' __all__ = ('AdminkaPlugin',) __version__ = 0.1 __name__ = 'AdminkaPLugin for Siberia' __middleware__ = True #--------------------------------------------------------------------------- # global imports #--------------------------------------------------------------------------- from jinja2 import Environment, FileSystemLoader, TemplateError from ..plugins import SiberiaPlugin from ..data import ProxyStack from aiohttp import web, request from asyncio import coroutine from sqlalchemy import func import os #--------------------------------------------------------------------------- # implement jinja2 plugin for Siberia #--------------------------------------------------------------------------- class AdminkaPlugin(SiberiaPlugin): # stack assert messages assert_msg = ProxyStack( route = " не найден путь для добавления роутера для админки", middle = " не найден стак в основном приложении для middlewares", jinja2 = " не найден плагин Jinja2Plugin, установите его, он нужен для работы админки", ) # plugin definitions variables plugin_stack = ProxyStack( api = 0.1, name = "Adminka", version = 0.1, middleware = True, ) # config for session config = ProxyStack( adminroute = '/adminka', template_path = 'adminka/', static_path = 'static/', mark = '[ADMINKAPLUGIN] {}', ) def __init__(self, app, template_path=None, routeadminka=None): self.app = app self.routeadminka = routeadminka or self.config.adminroute self.template_adminka = os.path.join(os.path.dirname(os.path.realpath(__file__)), self.config.template_path) # adminka handlers containers self.hand = AdminkaHandlers(app=self.app, adminka=self) # result functions some self.online = None def assignrouteadmin(self): # assert self.routeadminka, (self.config.mark.format(self.config.assert_msg.get('route'))) # adding template self.app.fn.get(self.routeadminka, name="adminka", handler=self.hand.adminkalogin) # adding static paths self.staticpath = os.path.join(self.template_adminka, self.config.static_path) print("Adding static path: ", self.staticpath) self.app.router.add_static(prefix='/adminka/static/css', path=self.staticpath + '/css', name='css_admin') self.app.router.add_static(prefix='/adminka/static/font', path=self.staticpath + '/font', name='font_admin') self.app.router.add_static(prefix='/adminka/static/img', path=self.staticpath + '/img', name='img_admin') self.app.router.add_static(prefix='/adminka/static/js', path=self.staticpath + '/js', name='js_admin') print("Added static adminka path") # self.app.fn.maproute() def setup(self): # проверка нужных для плагина переменных и плагинов в основном приложении # для работы адимнки требуется jinja плагин, ибо все там адаптировано под испоьзование в качестве рендера `нинзю` assert hasattr(self.app, 'middlewares'), (self.config.mark.format(self.config.assert_msg.get('middle'))) assert 'jinja2' in self.app.plugins, (self.config.mark.format(self.config.assert_msg.get('jinja2'))) # проверки прошли успешно, добавляем в миддлы if hasattr(self.app, 'middlewares'): self.app.middlewares.append(self.adminka_middleware(app=self.app)) # устанавливаю директорию темплейтов для админки к лодеру jinja jinja2 = self.app.plugins.get('jinja2') jinja2.addtemplate(self.template_adminka) print("------NEW JINJA TEMPLATES: ", jinja2.config.template_path) # добавляю роутер print(self.config.mark.format(" добавляю роутер админки")) self.assignrouteadmin() print(self.config.mark.format(" добавляю роутер админки, добавил вроде")) def adminka_middleware(self, app): @coroutine def adminka(app, handler): @coroutine def middleware(request): if request.path == self.routeadminka: url = request.app.router['adminka'].url() print("ADMINKA PATH FOUND:", url) # return web.HTTPFound(url) # get users online r = yield from self.hand.users_online(request) self.online = r response = yield from handler(request) return response return middleware return adminka class AdminkaHandlers(ProxyStack): def __init__(self, app, adminka): self.adminka = adminka # self adminka self.app = app self.db = self.app.db self.render = self.app.render # /`adminkaroute` async def adminkalogin(self, request): # return web.Response(body='/usr/home/spouk/PycharmProjects/Siberia/plug/adminka/adminka.html'.encode()) return await self.app.render('adminindex.html', online=self.adminka.online) @coroutine def url_user_online(self, request): res = yield from self.app.render('usersonline.html', online=self.adminka.online) return res # users online @coroutine def users_online(self, request): with (yield from self.db) as conn: dbs = self.db.cook # q = dbs.select().where([func.count(dbs.c.status)]) q = dbs.select().where(dbs.c.status == 1) resp = yield from conn.execute(q) found = yield from resp.fetchall() return found

38.464052

121

0.584367

616

5,885

5.48539

0.310065

0.045576

0.020716

0.029595

0.149453

0.11749

0.07813

0

0.003935

0.26593

5,885

152

122

38.717105

0.778241

0.202209

0

0.061224

0

0.137887

0

0.030612

1

0.091837

false

0

0.071429

0

0.27551

0.061224

0

null

0

null

0

1

0

2ca1f66514af862a2395c2a72cc563dfe7628eb9

2,576

py

Python

services/jobs/tests/api/base.py

Open-EO/openeo-openshift-driver

822dbd3ccee25180cc48efd2f891504b6b5edc14

[ "Apache-2.0" ]

6

2018-10-02T15:04:11.000Z

2019-12-13T11:36:49.000Z

services/jobs/tests/api/base.py

Open-EO/openeo-openshift-driver

822dbd3ccee25180cc48efd2f891504b6b5edc14

[ "Apache-2.0" ]

54

2019-01-09T17:14:29.000Z

2020-10-02T11:39:38.000Z

services/jobs/tests/api/base.py

Open-EO/openeo-openshift-driver

822dbd3ccee25180cc48efd2f891504b6b5edc14

[ "Apache-2.0" ]

6

2018-07-03T15:58:05.000Z

2019-07-03T07:20:46.000Z

"""Provide base test class.""" from typing import Any, Callable from nameko_sqlalchemy.database_session import Session from jobs.dependencies.dag_handler import DagHandler from jobs.service import JobService from .exceptions import get_missing_resource_service_exception, get_not_authorized_service_exception from ..utils import add_job, get_configured_job_service, get_random_job_id, get_random_user class BaseCase: """Base test class to be inherited from by other test classes.""" dag_handler = DagHandler() def get_method(self, service: JobService, method: str) -> Callable: """Return service method corresponding to a given string.""" mapper = { "get": service.get, "modify": service.modify, "delete": service.delete, "process": service.process, "get_results": service.get_results, } if method not in mapper: raise NotImplementedError(f"The method {method} is currently not supported") return mapper[method] def test_not_existing_job(self, db_session: Session, method: str, **kwargs: Any) -> None: """Check trying to access a non existing job throws the expected error. Args: db_session: Database session. method: Which method to call with a non-existing job identifier. kwargs: Additional keyword arguments which need to be supplied to the given method. """ job_service = get_configured_job_service(db_session) user = get_random_user() job_id = get_random_job_id() result = self.get_method(job_service, method)(user=user, job_id=job_id, **kwargs) assert result == get_missing_resource_service_exception(user_id=user["id"], job_id=job_id) def test_not_authorized_for_job(self, db_session: Session, method: str, **kwargs: Any) -> None: """Check trying to access a job of another user throws the expected error. Args: db_session: Database session. method: Which method to call as not authorized user. kwargs: Additional keyword arguments which need to be supplied to the given method. """ job_service = get_configured_job_service(db_session) user = get_random_user() job_id = add_job(job_service, user=user) other_user = get_random_user() result = self.get_method(job_service, method)(user=other_user, job_id=job_id, **kwargs) assert result == get_not_authorized_service_exception(user_id=other_user["id"], job_id=job_id)

42.933333

102

0.689829

339

2,576

4.99705

0.268437

0.035419

0.024793

0.023613

0.50059

0.42621

0.40732

0.361275

0.319953

0

0.229037

2,576

59

103

43.661017

0.852971

0.257764

0

0.125

0

0.046009

0

0.0625

1

0.09375

false

0

0.1875

0

0.375

0

null

0

null

0

1

0

2ca3388b5b4f8f447dfd365008e2dd96e0c723ba

1,919

py

Python

egi/models.py

gtaylor/evennia-game-directory

f7a4d0731503de540026dc0fe6409a7c24ad676e

[ "BSD-3-Clause" ]

1

2019-02-06T10:58:11.000Z

egi/models.py

gtaylor/evennia-game-index

f7a4d0731503de540026dc0fe6409a7c24ad676e

[ "BSD-3-Clause" ]

4

2017-10-24T21:47:53.000Z

2019-09-22T13:12:57.000Z

egi/models.py

gtaylor/evennia-game-directory

f7a4d0731503de540026dc0fe6409a7c24ad676e

[ "BSD-3-Clause" ]

2

2017-02-09T16:25:27.000Z

2017-10-24T21:40:42.000Z

import datetime from google.appengine.ext import ndb class GameListing(ndb.Model): # Game listing stuff game_name = ndb.StringProperty(required=True) game_status = ndb.StringProperty(required=True) game_website = ndb.StringProperty() listing_contact = ndb.StringProperty(required=True) short_description = ndb.StringProperty() long_description = ndb.TextProperty() # How to play telnet_hostname = ndb.StringProperty() telnet_port = ndb.IntegerProperty() web_client_url = ndb.StringProperty() # Game stats connected_account_count = ndb.IntegerProperty() total_account_count = ndb.IntegerProperty() # System info evennia_version = ndb.StringProperty(required=True) python_version = ndb.StringProperty() django_version = ndb.StringProperty() server_platform = ndb.StringProperty() created_time = ndb.DateTimeProperty(auto_now_add=True) checkin_time = ndb.DateTimeProperty(auto_now=True) @classmethod def get_all_fresh_games_list(cls): games = cls.query() # Getting around a weird Google Cloud Datastore limitation crappily # until I can figure out a better way. filtered_games = [g for g in games if g.is_fresh()] # Saves us from having to create an index, which is apparently slightly # more expensive (monetarily). # we sort first so that games having a telnet/webclient link ends up on top, # then by number of connected players and finally alphabetically by game name return sorted(filtered_games, key=lambda game: ( (0 if ((game.telnet_hostname and game.telnet_port) or game.web_client_url) else 1), (-1 * (game.connected_account_count or 0)), game.game_name)) def is_fresh(self): cutoff_time = datetime.datetime.now() - datetime.timedelta(hours=2) return self.checkin_time > cutoff_time

37.627451

95

0.706097

241

1,919

5.452282

0.53112

0.142314

0.076104

0.08828

0.09589

0

0.003318

0.214695

1,919

50

96

38.38

0.868613

0.211569

0

1

0.064516

false

0

0.064516

0

0.774194

0

null

0

null

0

1

0

2ca4292d50c5517e99b0982bf8f944c2f58adef3

2,267

py

Python

stylelens/dataset/df/generate_category_classifier_dataset.py

williamcameron/bl-magi

a35809489c15df25efc9c322166afaee7df3e192

[ "Apache-2.0" ]

null

stylelens/dataset/df/generate_category_classifier_dataset.py

williamcameron/bl-magi

a35809489c15df25efc9c322166afaee7df3e192

[ "Apache-2.0" ]

null

stylelens/dataset/df/generate_category_classifier_dataset.py

williamcameron/bl-magi

a35809489c15df25efc9c322166afaee7df3e192

[ "Apache-2.0" ]

null

from __future__ import print_function from stylelens_dataset.categories import Categories from stylelens_dataset.objects import Objects from pprint import pprint import os import urllib.request as urllib # create an instance of the API class category_api = Categories() object_api = Objects() def download_image_from_url(url, filename): try: urllib.urlretrieve(url, filename) except urllib.HTTPError: pass def get_objects_with_category_name(category_name): try: offset = 0 limit = 100 i = 0 while True: res = object_api.get_objects_by_category_name(category_name, offset=offset, limit=limit) for object in res: download_image_from_url(object['url'], str(object['_id']) + '.jpg') i += 1 if limit > len(res): break else: offset = offset + limit pprint(category_name + ' : ' + str(i)) except Exception as e: print("Exception when calling get_objects_by_category_name: %s\n" % e) def get_category_classes(): try: offset = 0 limit = 10 categories = [] while True: res = category_api.get_categories(offset=offset, limit=limit) if limit > len(res): break else: offset = offset + limit for cate in res: categories.append(cate) return categories except Exception as e: print("Exception when calling add_category: %s\n" % e) return None def make_category_dataset(): dataset_path = '/Users/daesubkim/Desktop/Python/py-example' categories = get_category_classes() if categories: for category in categories: category_name = category["name"] os.chdir(dataset_path) try: os.mkdir(category_name) except FileExistsError: pass os.chdir(category_name) get_objects_with_category_name(category_name) def start(): try: make_category_dataset() except Exception as e: pprint(e) # log.error(str(e)) if __name__ == '__main__': try: start() except Exception as e: pprint(e)

25.47191

100

0.603

264

2,267

4.94697

0.314394

0.11026

0.061256

0.073507

0.258806

0.222052

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0.125574

0.059724

0

0.005818

0.3176

2,267

88

101

25.761364

0.838397

0.023379

0

0.371429

0

0.074627

0.032112

0

1

0.071429

false

0.028571

0.085714

0

0.185714

0.1

0

null

0

null

0

1

0

2ca44cd0b909b867cabf4f36b32c482801cc16f1

8,429

py

Python

keras/dtensor/lazy_variable.py

englert-m/keras

7007cd0fd548032f1bb2c23b1defa4812628baec

[ "Apache-2.0" ]

null

keras/dtensor/lazy_variable.py

englert-m/keras

7007cd0fd548032f1bb2c23b1defa4812628baec

[ "Apache-2.0" ]

null

keras/dtensor/lazy_variable.py

englert-m/keras

7007cd0fd548032f1bb2c23b1defa4812628baec

[ "Apache-2.0" ]

null

# Copyright 2022 The TensorFlow Authors. 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. # ============================================================================== """Lazily initialized variables, useful for creating a symbolic Keras model.""" # pylint: disable=g-direct-tensorflow-import from tensorflow.core.framework import attr_value_pb2 from tensorflow.python.eager import context from tensorflow.python.framework import ops from tensorflow.python.ops import gen_resource_variable_ops from tensorflow.python.ops import resource_variable_ops from tensorflow.python.ops import variable_scope from tensorflow.python.training.tracking import base as trackable from tensorflow.python.util import compat from tensorflow.python.util import tf_contextlib def _infer_shape_dtype_and_create_handle(initial_value, shape, dtype, name): """Infer shape and dtype from initial_value and create a variable handle.""" with ops.name_scope(name, "Variable", skip_on_eager=False) as name: handle_name = ops.name_from_scope_name(name) unique_id = "%s_%d" % (handle_name, ops.uid()) # Use attr_scope and device(None) to simulate the behavior of # colocate_with when the variable we want to colocate with doesn't # yet exist. device_context_manager = ops.NullContextmanager attr = attr_value_pb2.AttrValue( list=attr_value_pb2.AttrValue.ListValue( s=[compat.as_bytes("loc:@%s" % handle_name)])) with ops.get_default_graph()._attr_scope({"_class": attr}): # pylint: disable=protected-access with ops.name_scope("Initializer"), device_context_manager(None): if not callable(initial_value): if isinstance(initial_value, trackable.CheckpointInitialValue): raise NotImplementedError( "CheckpointInitialValue is not supported to be the initial " "value of a lazy variable.") initial_value = ops.convert_to_tensor( initial_value, name="initial_value", dtype=dtype) assert not callable(initial_value) assert initial_value.shape.is_compatible_with(shape) dtype = dtype or initial_value.dtype.base_dtype shape = shape or initial_value.shape assert dtype assert shape handle = resource_variable_ops._variable_handle_from_shape_and_dtype( # pylint: disable=protected-access shape=shape, dtype=dtype, shared_name=None, # Never shared name=name, graph_mode=False, initial_value=None) # initial_value=initial_value if not callable(initial_value) else None) return initial_value, shape, dtype, handle, handle_name, unique_id class LazyInitVariable(resource_variable_ops.BaseResourceVariable): """Lazily initialized variables. The major use case for this class is to serve as a memory efficient alternative for tf.Variable. The resource handle of this class is point to nothing, which mean it will raise error when its value is fetched in a eager context. Having said that, it will perform like a normal tf.Variable when using with graph tensor, like KerasTensor produced from tf.keras.Input. """ def __init__( self, initial_value=None, trainable=None, collections=None, validate_shape=True, # pylint: disable=unused-argument caching_device=None, name=None, dtype=None, variable_def=None, import_scope=None, constraint=None, distribute_strategy=None, synchronization=None, aggregation=None, shape=None, **kwargs): assert context.executing_eagerly() # To simplify the logic assert variable_def is None # Not supported yet. assert caching_device is None # Not supported yet if initial_value is None: raise ValueError("The `initial_value` arg to `tf.Variable` must " "be specified except when you are not providing a " "`variable_def`. You provided neither.") if isinstance(initial_value, ops.Tensor) and hasattr( initial_value, "graph") and initial_value.graph.building_function: raise ValueError(f"Argument `initial_value` ({initial_value}) could not " "be lifted out of a `tf.function`. " "(Tried to create variable with name='{name}'). " "To avoid this error, when constructing `tf.Variable`s " "inside of `tf.function` you can create the " "`initial_value` tensor in a " "`tf.init_scope` or pass a callable `initial_value` " "(e.g., `tf.Variable(lambda : " "tf.truncated_normal([10, 40]))`). " "Please file a feature request if this " "restriction inconveniences you.") if constraint is not None and not callable(constraint): raise ValueError(f"Argument `constraint` must be None or a callable. " f"a callable. Got a {type(constraint)}: {constraint}") self._name = name (initial_value, shape, dtype, handle, handle_name, unique_id) = _infer_shape_dtype_and_create_handle(initial_value, shape, dtype, name) super(LazyInitVariable, self).__init__( distribute_strategy=distribute_strategy, initial_value=initial_value, shape=shape, dtype=dtype, name=name, unique_id=unique_id, handle_name=handle_name, constraint=constraint, handle=handle, graph_element=None, trainable=trainable, synchronization=synchronization, aggregation=aggregation, in_graph_mode=False) # TODO(scottzhu): This method and create_and_initialize might be removed if # we decide to just use the tf.Variable to replace this class. def initialize(self): with ops.name_scope(self._name, "Variable", skip_on_eager=False) as name: with ops.colocate_with(self._handle), ops.name_scope("Initializer"): if callable(self._initial_value): initial_value = self._initial_value() else: initial_value = self._initial_value if not initial_value.shape.is_compatible_with(self._shape): raise ValueError( f"In this `tf.Variable` creation, the initial value's shape " f"({initial_value.shape}) is not compatible with " f"the explicitly supplied `shape` argument ({self._shape}).") assert self._dtype is initial_value.dtype.base_dtype gen_resource_variable_ops.assign_variable_op(self._handle, initial_value) def create_and_initialize(self): if callable(self._initial_value): initial_value = self._initial_value() with ops.device(initial_value.device): (initial_value, shape, dtype, handle, handle_name, unique_id) = _infer_shape_dtype_and_create_handle( initial_value, self._shape, self._dtype, self._name) self.initialize() super(LazyInitVariable, self).__init__( trainable=self._trainable, shape=shape, dtype=dtype, handle=handle, synchronization=self._synchronization, constraint=self._constraint, aggregation=self._aggregation, distribute_strategy=self._distribute_strategy, name=self._name, unique_id=unique_id, handle_name=handle_name, graph_element=None, initial_value=initial_value, initializer_op=None, is_initialized_op=None, cached_value=None, caching_device=None) def _lazy_init_variable_creator(next_creator, **kwargs): del next_creator return LazyInitVariable(**kwargs) @tf_contextlib.contextmanager def lazy_init_scope(): with variable_scope.variable_creator_scope(_lazy_init_variable_creator): yield

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null

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null

0

1

0

2ca5cbc4f5357898528acdf248026bc993f249fb

2,493

py

Python

txaws/tests/test_util.py

vargas/txaws

b75d00e042c6e7e1609c05e01ee54e1c72b1eaf6

[ "MIT" ]

1

2021-12-17T00:03:24.000Z

txaws/tests/test_util.py

vargas/txaws

b75d00e042c6e7e1609c05e01ee54e1c72b1eaf6

[ "MIT" ]

null

txaws/tests/test_util.py

vargas/txaws

b75d00e042c6e7e1609c05e01ee54e1c72b1eaf6

[ "MIT" ]

1

2021-12-17T00:06:41.000Z

from urllib.parse import urlparse import binascii from twisted.trial.unittest import TestCase from txaws.util import hmac_sha1, iso8601time, parse class MiscellaneousTestCase(TestCase): def test_hmac_sha1(self): cases = [ (binascii.unhexlify(b"0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b0b"), "Hi There", "thcxhlUFcmTii8C2+zeMjvFGvgA="), ("Jefe", "what do ya want for nothing?", "7/zfauXrL6LSdBbV8YTfnCWafHk="), (binascii.unhexlify(b"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"), "\xdd" * 50, "El1zQrmsEc2Ro5r0iqF7T2PxddM="), ] for key, data, expected in cases: self.assertEqual(hmac_sha1(key, data), expected) def test_iso8601time(self): self.assertEqual("2006-07-07T15:04:56Z", iso8601time((2006, 7, 7, 15, 4, 56, 0, 0, 0))) class ParseUrlTestCase(TestCase): """ Test URL parsing facility and defaults values. """ def test_parse(self): """ L{parse} correctly parses a URL into its various components. """ # The default port for HTTP is 80. self.assertEqual( parse("http://127.0.0.1/"), ("http", "127.0.0.1", 80, "/")) # The default port for HTTPS is 443. self.assertEqual( parse("https://127.0.0.1/"), ("https", "127.0.0.1", 443, "/")) # Specifying a port. self.assertEqual( parse("http://spam:12345/"), ("http", "spam", 12345, "/")) # Weird (but commonly accepted) structure uses default port. self.assertEqual( parse("http://spam:/"), ("http", "spam", 80, "/")) # Spaces in the hostname are trimmed, the default path is /. self.assertEqual( parse("http://foo "), ("http", "foo", 80, "/")) def test_externalUnicodeInterference(self): """ L{parse} should return C{str} for the scheme, host, and path elements of its return tuple, even when passed an URL which has previously been passed to L{urlparse} as a C{unicode} string. """ badInput = u"http://example1.com/path" goodInput = badInput.encode("ascii") urlparse(badInput) scheme, host, port, path = parse(goodInput) self.assertTrue(isinstance(scheme, str)) self.assertTrue(isinstance(host, str)) self.assertTrue(isinstance(path, str))

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null

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null

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0

2ca6030084049893d40df687b5267b7ac8dd9230

7,674

py

Python

vgame/theater.py

cilame/vgame

9b7076256500137fe5c95426798007734dd613a2

[ "MIT" ]

null

vgame/theater.py

cilame/vgame

9b7076256500137fe5c95426798007734dd613a2

[ "MIT" ]

null

vgame/theater.py

cilame/vgame

9b7076256500137fe5c95426798007734dd613a2

[ "MIT" ]

null

import pygame from pygame.locals import * from .actor import Actor from .actor import Player, Wall, Enemy, Bullet, NPC, Anime, Map from .actor import Menu, Background, Button from .actor import Delayer import vgame class Camera: ''' 主要负责处理镜头的处理，看看后续能够扩展出多少的功能。 ''' DEBUG = False def __init__(self, width, height): self.w = width self.h = height self.camera = pygame.Rect(0, 0, self.w, self.h) self.camera_xy = (0., 0.) self.theater = None self.follow = None # 单角色跟随 self.fspeed = 1 self.offsets = (0, 0) self.padding = pygame.Vector2(0, 0) self.debug_area = None # 多角色镜头缩放的处理目前几乎无解，这里的接口后续将很长时间内没有进展，毕竟通用游戏框架对于此处的需求并不强烈。 self.follows = None # 尚在开发中的接口，后续将解决多角色跟随问题 self.paddings = None # 尚在开发中的接口，后续将解决多角色跟随问题 # self.margin = pygame.Vector2(*((100, 100) if vgame.DEBUG else (0, 0))) # 调试时候使用，方便查看边界 self.margin = pygame.Vector2((0,0)) # 调试时候使用，方便查看边界 self.delayer = Delayer() def _get_fspeed(self): return self._fspeed def _set_fspeed(self, value): if value <= 0 or value > 1: raise ValueError('fspeed:{} limit in "0 < fspeed <= 1".'.format(value)) self._fspeed = value fspeed = property(_get_fspeed, _set_fspeed) def apply(self, entity): x, y = self.camera.topleft x += self.offsets[0] y += self.offsets[1] return entity.rect.move((x, y)) def update(self, ticks): if self.follow: _x, _y = self.follow.rect.center x = -_x + int(self.w/2) y = -_y + int(self.h/2) x = min(self.margin.x, x) # top y = min(self.margin.y, y) # left tx = max(x, -(self.theater.size[0] - self.w + self.margin.x)) # right ty = max(y, -(self.theater.size[1] - self.h + self.margin.y)) # bottom cx, cy = self.camera_xy if self.delayer.update(ticks): _tx = cx + (tx - cx) * self.fspeed _ty = cy + (ty - cy) * self.fspeed ox, oy = self.camera[:2] jx, jy = abs(self.w/2-(_x+ox)), abs(self.h/2-(_y+oy)) if jx < self.padding.x/2: _tx = ox if jy < self.padding.y/2: _ty = oy self.camera = pygame.Rect(_tx, _ty, self.w, self.h) self.camera_xy = _tx, _ty def debug_padding(self): if vgame.DEBUG and Camera.DEBUG: if not self.debug_area: showsize = (int(self.padding.x), int(self.padding.y)) showpoint = (self.w/2-self.padding.x/2, self.h/2-self.padding.y/2) self.debug_area = Actor((0,0,0,30), showsize=showsize, showpoint=showpoint) self.debug_area.imager._delay_bind_debug() self.theater.screen.blit(self.debug_area.image, self.debug_area.rect) # self.theater.screen.blit(self.debug_area.image, self.apply(self.debug_area)) class Theater: ''' 舞台对象，主要负责布景功能（地图信息主要就是放在这里）负责场景的资源加载（加载进全局，留下一个引用的结构）这样，已经加载的资源就不会再被加载进内存当中，并且调用资源仅仅需要通过自身的实例的绑定就能获取到 ''' Camera = Camera # 用于快速定位并修改某些配置参数： vgame.Theater.Camera.DEBUG _theater_numb = 0 _theater_format = 'theater:{}' def __init__(self, background = None, # 背景图片，可以传很多类型的数据，详细请看 Image 实例化时的参数 size = None, # 游戏背景大小，背景大小如未设定则使用屏幕大小 camera_size = None, # 镜头的尺寸，默认情况下镜头尺寸和游戏背景大小一样 ): game_screen = pygame.display.get_surface() # 游戏屏幕(镜头)显示的大小 if game_screen is None or not vgame.Artist.ARTIST: raise 'pls use vgame.Initer() to init game first.' self.artist = vgame.Artist.ARTIST self.screen = game_screen self.screen_size = self.screen.get_size() self.theater_name = self._mk_theater_name() self.size = size if size else self.screen_size self.showsize = self.size self.group_grid = pygame.sprite.Group() self.group = pygame.sprite.Group() self.background = None self.camera = self.regist_camera(Camera(*self.screen_size)) # 用这个初始化不同场景下的物理检测的 Actor 列表 Actor .RIGID_BODY[self.theater_name] = [] Actor .SHOW_BODY [self.theater_name] = [] Player.RIGID_BODY[self.theater_name] = [] Player.SHOW_BODY [self.theater_name] = [] Wall .RIGID_BODY[self.theater_name] = [] Wall .SHOW_BODY [self.theater_name] = [] Enemy .RIGID_BODY[self.theater_name] = [] Enemy .SHOW_BODY [self.theater_name] = [] Bullet.RIGID_BODY[self.theater_name] = [] Bullet.SHOW_BODY [self.theater_name] = [] NPC .RIGID_BODY[self.theater_name] = [] NPC .SHOW_BODY [self.theater_name] = [] Anime .RIGID_BODY[self.theater_name] = [] Anime .SHOW_BODY [self.theater_name] = [] Menu .RIGID_BODY[self.theater_name] = [] Menu .SHOW_BODY [self.theater_name] = [] Button.RIGID_BODY[self.theater_name] = [] Button.SHOW_BODY [self.theater_name] = [] # *暂未使用的参数，后续要考虑入场和出场的动画表演，否则切换场景会非常僵硬（至少要提供配置接口） # *后面可以考虑实现一些可配置的淡入淡出的效果 self.enter = None self.leave = None # 初始化时可以传一张图片作为背景，也可以为空，透明的区域，用于限定游戏的范围，增加更多的可配置的空间 # 主要用于限定镜头跟随的范围 self._add_background(background if background else (0,0,0,0)) self.artist.regist(self) def regist(self,*actors): for actor in actors: actor.theater = self actor._regist = self.regist if isinstance(actor, Actor) and not self.group.has(actor): self.group.add(actor) def regist_camera(self, camera): camera.theater = self return camera def regist_grid(self, grid): grid.theater = self grid._regist = self.regist_grid if isinstance(grid, Actor) and not self.group_grid.has(grid): self.group_grid.add(grid) return grid def _add_background(self, background): self.background = Background(background, showsize=self.size) self.background.theater = self if self.background.image: self.group.add(self.background) def _mk_theater_name(self): Theater._theater_numb += 1 return Theater._theater_format.format(Theater._theater_numb) @property def name(self): return self.theater_name def change_theater(self, name_or_class): self.artist.change_theater(name_or_class) def follow(self, actor, speed, offsets, padding): self.camera.follow = actor self.camera.fspeed = speed self.camera.offsets = offsets self.camera.padding[:2] = padding @property def Actor(self): return Actor.SHOW_BODY[self.name].copy() @property def Player(self): return Player.SHOW_BODY[self.name].copy() @property def Wall(self): return Wall.SHOW_BODY[self.name].copy() @property def Enemy(self): return Enemy.SHOW_BODY[self.name].copy() @property def Bullet(self): return Bullet.SHOW_BODY[self.name].copy() @property def NPC(self): return NPC.SHOW_BODY[self.name].copy() @property def Anime(self): return Anime.SHOW_BODY[self.name].copy() @property def Menu(self): return Menu.SHOW_BODY[self.name].copy() @property def Button(self): return Button.SHOW_BODY[self.name].copy() @property def rect(self): return self.background.rect @property def draw(self): return vgame.draw(self.background)

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0

null

0

null

0

1

0

2ca906d948f8bdc4ff1f5129d6cb152946ac17af

60,654

py

Python

third_party/chromite/lib/auto_updater.py

zipated/src

2b8388091c71e442910a21ada3d97ae8bc1845d3

[ "BSD-3-Clause" ]

2,151

2020-04-18T07:31:17.000Z

2022-03-31T08:39:18.000Z

third_party/chromite/lib/auto_updater.py

cangulcan/src

2b8388091c71e442910a21ada3d97ae8bc1845d3

[ "BSD-3-Clause" ]

395

2020-04-18T08:22:18.000Z

2021-12-08T13:04:49.000Z

third_party/chromite/lib/auto_updater.py

cangulcan/src

2b8388091c71e442910a21ada3d97ae8bc1845d3

[ "BSD-3-Clause" ]

338

2020-04-18T08:03:10.000Z

2022-03-29T12:33:22.000Z

# -*- coding: utf-8 -*- # Copyright 2016 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Library containing functions to execute auto-update on a remote device. TODO(xixuan): Make this lib support other update logics, including: auto-update CrOS images for DUT beaglebones for servo stage images to servo usb install custom CrOS images for chaos lab install firmware images with FAFT install android/brillo TODO(xixuan): crbugs.com/631837, re-consider the structure of this file, like merging check functions into one class. Currently, this lib supports ChromiumOSFlashUpdater and ChromiumOSUpdater. --------------- | BaseUpdater | : Updater --------------- | | ------------------------- | ChromiumOSFlashUpdater | : Chromium OS Updater by cros flash ------------------------- | | --------------------- | ChromiumOSUpdater | : Chromium OS Updater by cros flash --------------------- with more checks ChromiumOSFlashUpdater includes: ----Precheck--- * Pre-check payload's existence before auto-update. * Pre-check if the device can run its devserver. ----Tranfer---- * Transfer devserver package at first. * Transfer rootfs update files if rootfs update is required. * Transfer stateful update files if stateful update is required. ----Auto-Update--- * Do rootfs partition update if it's required. * Do stateful partition update if it's required. * Do reboot for device if it's required. ----Verify---- * Do verification if it's required. * Disable rootfs verification in device if it's required. ChromiumOSUpdater adds: ----Check----- * Check functions, including kernel/version/cgpt check. ----Precheck--- * Pre-check for stateful/rootfs update/whole update. ----Tranfer---- * Add @retry to all transfer functions. ----Verify---- * Post-check stateful/rootfs update/whole update. """ from __future__ import print_function import cStringIO import json import os import re import shutil import tempfile import time from chromite.cli import command from chromite.lib import auto_update_util from chromite.lib import constants from chromite.lib import cros_build_lib from chromite.lib import cros_logging as logging from chromite.lib import dev_server_wrapper as ds_wrapper from chromite.lib import operation from chromite.lib import osutils from chromite.lib import path_util from chromite.lib import remote_access from chromite.lib import retry_util from chromite.lib import timeout_util # Naming conventions for global variables: # File on remote host without slash: REMOTE_XXX_FILENAME # File on remote host with slash: REMOTE_XXX_FILE_PATH # Path on remote host with slash: REMOTE_XXX_PATH # File on local server without slash: LOCAL_XXX_FILENAME # File on local server with slash: LOCAL_XXX_FILE_PATH # Path on local server: LOCAL_XXX_PATH # Update Status for remote device. UPDATE_STATUS_IDLE = 'UPDATE_STATUS_IDLE' UPDATE_STATUS_DOWNLOADING = 'UPDATE_STATUS_DOWNLOADING' UPDATE_STATUS_FINALIZING = 'UPDATE_STATUS_FINALIZING' UPDATE_STATUS_UPDATED_NEED_REBOOT = 'UPDATE_STATUS_UPDATED_NEED_REBOOT' # Error msg in loading shared libraries when running python command. ERROR_MSG_IN_LOADING_LIB = 'python: error while loading shared libraries' # Max number of the times for retry: # 1. for transfer functions to be retried. # 2. for some retriable commands to be retried. MAX_RETRY = 5 # Number of times to retry update_engine_client --status. See crbug.com/744212. UPDATE_ENGINE_STATUS_RETRY = 30 # The delay between retriable tasks. DELAY_SEC_FOR_RETRY = 5 # Third-party package directory on devserver THIRD_PARTY_PKG_DIR = '/usr/lib/python2.7/dist-packages/' # Third-party package list THIRD_PARTY_PKG_LIST = ['cherrypy', 'google/protobuf'] # update_payload path from update_engine. UPDATE_PAYLOAD_DIR = os.path.join( constants.UPDATE_ENGINE_SCRIPTS_PATH, 'update_payload') # Number of seconds to wait for the post check version to settle. POST_CHECK_SETTLE_SECONDS = 15 # Number of seconds to delay between post check retries. POST_CHECK_RETRY_SECONDS = 5 class ChromiumOSUpdateError(Exception): """Thrown when there is a general ChromiumOS-specific update error.""" class PreSetupUpdateError(ChromiumOSUpdateError): """Raised for the rootfs/stateful update pre-setup failures.""" class RootfsUpdateError(ChromiumOSUpdateError): """Raised for the Rootfs partition update failures.""" class StatefulUpdateError(ChromiumOSUpdateError): """Raised for the stateful partition update failures.""" class AutoUpdateVerifyError(ChromiumOSUpdateError): """Raised for verification failures after auto-update.""" class DevserverCannotStartError(ChromiumOSUpdateError): """Raised when devserver cannot restart after stateful update.""" class RebootVerificationError(ChromiumOSUpdateError): """Raised for failing to reboot errors.""" class BaseUpdater(object): """The base updater class.""" def __init__(self, device, payload_dir): self.device = device self.payload_dir = payload_dir class ChromiumOSFlashUpdater(BaseUpdater): """Used to update DUT with image.""" # stateful update files LOCAL_STATEFUL_UPDATE_FILENAME = 'stateful_update' LOCAL_CHROOT_STATEFUL_UPDATE_PATH = '/usr/bin/stateful_update' REMOTE_STATEFUL_UPDATE_PATH = '/usr/local/bin/stateful_update' # devserver files LOCAL_DEVSERVER_LOG_FILENAME = 'target_devserver.log' REMOTE_DEVSERVER_FILENAME = 'devserver.py' # rootfs update files REMOTE_UPDATE_ENGINE_BIN_FILENAME = 'update_engine_client' REMOTE_UPDATE_ENGINE_LOGFILE_PATH = '/var/log/update_engine.log' REMOTE_PROVISION_FAILED_FILE_PATH = '/var/tmp/provision_failed' REMOTE_HOSTLOG_FILE_PATH = '/var/log/devserver_hostlog' REMOTE_QUICK_PROVISION_LOGFILE_PATH = '/var/log/quick-provision.log' UPDATE_CHECK_INTERVAL_PROGRESSBAR = 0.5 UPDATE_CHECK_INTERVAL_NORMAL = 10 # Update engine perf files REMOTE_UPDATE_ENGINE_PERF_SCRIPT_PATH = \ '/mnt/stateful_partition/unencrypted/preserve/' \ 'update_engine_performance_monitor.py' REMOTE_UPDATE_ENGINE_PERF_RESULTS_PATH = '/var/log/perf_data_results.json' # `mode` parameter when copying payload files to the DUT. PAYLOAD_MODE_PARALLEL = 'parallel' PAYLOAD_MODE_SCP = 'scp' # Related to crbug.com/276094: Restore to 5 mins once the 'host did not # return from reboot' bug is solved. REBOOT_TIMEOUT = 480 def __init__(self, device, payload_dir, dev_dir='', tempdir=None, original_payload_dir=None, do_rootfs_update=True, do_stateful_update=True, reboot=True, disable_verification=False, clobber_stateful=False, yes=False, payload_filename=None, send_payload_in_parallel=False): """Initialize a ChromiumOSFlashUpdater for auto-update a chromium OS device. Args: device: the ChromiumOSDevice to be updated. payload_dir: the directory of payload(s). dev_dir: the directory of the devserver that runs the CrOS auto-update. tempdir: the temp directory in caller, not in the device. For example, the tempdir for cros flash is /tmp/cros-flash****/, used to temporarily keep files when transferring devserver package, and reserve devserver and update engine logs. original_payload_dir: The directory containing payloads whose version is the same as current host's rootfs partition. If it's None, will first try installing the matched stateful.tgz with the host's rootfs Partition when restoring stateful. Otherwise, install the target stateful.tgz. do_rootfs_update: whether to do rootfs partition update. The default is True. do_stateful_update: whether to do stateful partition update. The default is True. reboot: whether to reboot device after update. The default is True. disable_verification: whether to disabling rootfs verification on the device. The default is False. clobber_stateful: whether to do a clean stateful update. The default is False. yes: Assume "yes" (True) for any prompt. The default is False. However, it should be set as True if we want to disable all the prompts for auto-update. payload_filename: Filename of exact payload file to use for update instead of the default: update.gz. Defaults to None. Use only if you staged a payload by filename (i.e not artifact) first. send_payload_in_parallel: whether to transfer payload in chunks in parallel. The default is False. """ super(ChromiumOSFlashUpdater, self).__init__(device, payload_dir) if tempdir is not None: self.tempdir = tempdir else: self.tempdir = tempfile.mkdtemp(prefix='cros-update') self.dev_dir = dev_dir self.original_payload_dir = original_payload_dir # Update setting self._cmd_kwargs = {} self._cmd_kwargs_omit_error = {'error_code_ok': True} self._do_stateful_update = do_stateful_update self._do_rootfs_update = do_rootfs_update self._disable_verification = disable_verification self._clobber_stateful = clobber_stateful self._reboot = reboot self._yes = yes # Device's directories self.device_dev_dir = os.path.join(self.device.work_dir, 'src') self.device_static_dir = os.path.join(self.device.work_dir, 'static') self.device_restore_dir = os.path.join(self.device.work_dir, 'old') self.stateful_update_bin = None # autoupdate_EndToEndTest uses exact payload filename for update self.payload_filename = payload_filename if send_payload_in_parallel: self.payload_mode = self.PAYLOAD_MODE_PARALLEL else: self.payload_mode = self.PAYLOAD_MODE_SCP self.perf_id = None @property def is_au_endtoendtest(self): return self.payload_filename is not None def CheckPayloads(self): """Verify that all required payloads are in |self.payload_dir|.""" logging.debug('Checking if payloads have been stored in directory %s...', self.payload_dir) filenames = [] payload_name = self._GetRootFsPayloadFileName() filenames += [payload_name] if self._do_rootfs_update else [] if self._do_stateful_update: filenames += [ds_wrapper.STATEFUL_FILENAME] for fname in filenames: payload = os.path.join(self.payload_dir, fname) if not os.path.exists(payload): raise ChromiumOSUpdateError('Payload %s does not exist!' % payload) def CheckRestoreStateful(self): """Check whether to restore stateful.""" logging.debug('Checking whether to restore stateful...') restore_stateful = False try: self._CheckDevserverCanRun() return restore_stateful except DevserverCannotStartError as e: if self._do_rootfs_update: msg = ('Cannot start devserver! The stateful partition may be ' 'corrupted: %s' % e) prompt = 'Attempt to restore the stateful partition?' restore_stateful = self._yes or cros_build_lib.BooleanPrompt( prompt=prompt, default=False, prolog=msg) if not restore_stateful: raise ChromiumOSUpdateError( 'Cannot continue to perform rootfs update!') logging.debug('Restore stateful partition is%s required.', ('' if restore_stateful else ' not')) return restore_stateful def _CheckDevserverCanRun(self): """We can run devserver on |device|. If the stateful partition is corrupted, Python or other packages (e.g. cherrypy) needed for rootfs update may be missing on |device|. This will also use `ldconfig` to update library paths on the target device if it looks like that's causing problems, which is necessary for base images. Raise DevserverCannotStartError if devserver cannot start. """ # Try to capture the output from the command so we can dump it in the case # of errors. Note that this will not work if we were requested to redirect # logs to a |log_file|. cmd_kwargs = dict(self._cmd_kwargs) cmd_kwargs['capture_output'] = True cmd_kwargs['combine_stdout_stderr'] = False logging.info('Checking if we can run devserver on the device...') devserver_bin = os.path.join(self.device_dev_dir, self.REMOTE_DEVSERVER_FILENAME) devserver_check_command = ['python', devserver_bin, '--help'] try: self.device.RunCommand(devserver_check_command, **cmd_kwargs) except cros_build_lib.RunCommandError as e: logging.warning('Cannot start devserver:') logging.warning(e.result.error) if ERROR_MSG_IN_LOADING_LIB in str(e): logging.info('Attempting to correct device library paths...') try: self.device.RunCommand(['ldconfig', '-r', '/'], **cmd_kwargs) self.device.RunCommand(devserver_check_command, **cmd_kwargs) logging.info('Library path correction successful.') return except cros_build_lib.RunCommandError as e2: logging.warning('Library path correction failed:') logging.warning(e2.result.error) error_msg = e.result.error.splitlines()[-1] raise DevserverCannotStartError(error_msg) # pylint: disable=unbalanced-tuple-unpacking @classmethod def GetUpdateStatus(cls, device, keys=None): """Returns the status of the update engine on the |device|. Retrieves the status from update engine and confirms all keys are in the status. Args: device: A ChromiumOSDevice object. keys: the keys to look for in the status result (defaults to ['CURRENT_OP']). Returns: A list of values in the order of |keys|. """ keys = keys or ['CURRENT_OP'] result = device.RunCommand([cls.REMOTE_UPDATE_ENGINE_BIN_FILENAME, '--status'], capture_output=True, log_output=True) if not result.output: raise Exception('Cannot get update status') try: status = cros_build_lib.LoadKeyValueFile( cStringIO.StringIO(result.output)) except ValueError: raise ValueError('Cannot parse update status') values = [] for key in keys: if key not in status: raise ValueError('Missing %s in the update engine status') values.append(status.get(key)) return values @classmethod def GetRootDev(cls, device): """Get the current root device on |device|. Args: device: a ChromiumOSDevice object, defines whose root device we want to fetch. """ rootdev = device.RunCommand( ['rootdev', '-s'], capture_output=True).output.strip() logging.debug('Current root device is %s', rootdev) return rootdev def _GetStatefulUpdateScript(self): """Returns the path to the stateful_update_bin on the target. Returns: <need_transfer, path>: need_transfer is True if stateful_update_bin is found in local path, False if we directly use stateful_update_bin on the host. path: If need_transfer is True, it represents the local path of stateful_update_bin, and is used for further transferring. Otherwise, it refers to the host path. """ # We attempt to load the local stateful update path in 2 different # ways. If this doesn't exist, we attempt to use the Chromium OS # Chroot path to the installed script. If all else fails, we use the # stateful update script on the host. stateful_update_path = path_util.FromChrootPath( self.LOCAL_CHROOT_STATEFUL_UPDATE_PATH) if not os.path.exists(stateful_update_path): logging.warning('Could not find chroot stateful_update script in %s, ' 'falling back to the client copy.', stateful_update_path) stateful_update_path = os.path.join(self.dev_dir, self.LOCAL_STATEFUL_UPDATE_FILENAME) if os.path.exists(stateful_update_path): logging.debug('Use stateful_update script in devserver path: %s', stateful_update_path) return True, stateful_update_path logging.debug('Cannot find stateful_update script, will use the script ' 'on the host') return False, self.REMOTE_STATEFUL_UPDATE_PATH else: return True, stateful_update_path def _StartUpdateEngineIfNotRunning(self, device): """Starts update-engine service if it is not running. Args: device: a ChromiumOSDevice object, defines the target root device. """ try: result = device.RunCommand(['start', 'update-engine'], capture_output=True, log_output=True).output if 'start/running' in result: logging.info('update engine was not running, so we started it.') except cros_build_lib.RunCommandError as e: if e.result.returncode != 1 or 'is already running' not in e.result.error: raise e def SetupRootfsUpdate(self): """Makes sure |device| is ready for rootfs update.""" logging.info('Checking if update engine is idle...') self._StartUpdateEngineIfNotRunning(self.device) status, = self.GetUpdateStatus(self.device) if status == UPDATE_STATUS_UPDATED_NEED_REBOOT: logging.info('Device needs to reboot before updating...') self._Reboot('setup of Rootfs Update') status, = self.GetUpdateStatus(self.device) if status != UPDATE_STATUS_IDLE: raise RootfsUpdateError('Update engine is not idle. Status: %s' % status) def _GetDevicePythonSysPath(self): """Get python sys.path of the given |device|.""" sys_path = self.device.RunCommand( ['python', '-c', '"import json, sys; json.dump(sys.path, sys.stdout)"'], capture_output=True, log_output=True).output return json.loads(sys_path) def _FindDevicePythonPackagesDir(self): """Find the python packages directory for the given |device|.""" third_party_host_dir = '' sys_path = self._GetDevicePythonSysPath() for p in sys_path: if p.endswith('site-packages') or p.endswith('dist-packages'): third_party_host_dir = p break if not third_party_host_dir: raise ChromiumOSUpdateError( 'Cannot find proper site-packages/dist-packages directory from ' 'sys.path for storing packages: %s' % sys_path) return third_party_host_dir def _CopyPythonFilesToTemp(self, source_python_dir, dest_temp_dir, extra_ignore_patterns=None): """Copy filtered python files to tempdir. Args; source_python_dir: The source python directory that is used to copy from. dest_temp_dir: The dest temp directory that is used to copy to. extra_ignore_patterns: A list of extra ignore patterns in addition to default patterns. """ logging.debug('Copy from %s to %s', source_python_dir, dest_temp_dir) default_ignore_patterns = ['*.pyc', 'tmp*', '.*', 'static', '*~'] if extra_ignore_patterns: default_ignore_patterns.extend(extra_ignore_patterns) shutil.copytree( source_python_dir, dest_temp_dir, ignore=shutil.ignore_patterns(*default_ignore_patterns), symlinks=True) def _TransferRequiredPackage(self): """Transfer third-party packages related to devserver package.""" logging.info('Copying third-party packages to device...') try: # Copy third-party packages to pythonX.X/site(dist)-packages third_party_host_dir = self._FindDevicePythonPackagesDir() package_dir = os.path.join(self.tempdir, 'third_party') osutils.RmDir(package_dir, ignore_missing=True) for package in THIRD_PARTY_PKG_LIST: # Filter python files from (binary) garbage. self._CopyPythonFilesToTemp( os.path.join(THIRD_PARTY_PKG_DIR, package), os.path.join(package_dir, package)) # Python packages are plain text files so we chose rsync --compress. self.device.CopyToDevice( os.path.join(package_dir, os.path.split(package)[0]), third_party_host_dir, mode='rsync', log_output=True, **self._cmd_kwargs) except cros_build_lib.RunCommandError as e: # There's a chance that the DUT doesn't have any basic lib before # provisioning, like python. These commands will fail first, but succeed # after stateful partition is restored. So we choose not to raise error # here. logging.debug( 'Cannot transfer third-party packages to host due to: %s', e) def _EnsureDeviceDirectory(self, directory): """Mkdir the directory no matther whether this directory exists on host. Args: directory: the directory to be made on the device. """ self.device.RunCommand(['mkdir', '-p', directory], **self._cmd_kwargs) def _GetRootFsPayloadFileName(self): """Get the correct RootFs payload filename. Returns: The payload filename. (update.gz or a custom payload filename). """ if self.is_au_endtoendtest: return self.payload_filename else: return ds_wrapper.ROOTFS_FILENAME def TransferDevServerPackage(self): """Transfer devserver package to work directory of the remote device.""" logging.info('Copying devserver package to device...') src_dir = os.path.join(self.tempdir, 'src') osutils.RmDir(src_dir, ignore_missing=True) # Filter python files from (binary) garbage. # Also filter out directories including symlink to chromite. self._CopyPythonFilesToTemp(ds_wrapper.DEVSERVER_PKG_DIR, src_dir, extra_ignore_patterns=['venv', 'gs_cache']) # Copy update_payload from update_engine repository. update_payload_dir = os.path.join(src_dir, 'update_payload') self._CopyPythonFilesToTemp(UPDATE_PAYLOAD_DIR, update_payload_dir) # Make sure the device.work_dir exist after any installation and reboot. self._EnsureDeviceDirectory(self.device.work_dir) # Python packages are plain text files so we chose rsync --compress. self.device.CopyToWorkDir(src_dir, mode='rsync', log_output=True, **self._cmd_kwargs) if self.original_payload_dir: self._TransferRequiredPackage() def TransferRootfsUpdate(self): """Transfer files for rootfs update. Copy the update payload to the remote device for rootfs update. """ device_payload_dir = os.path.join(self.device_static_dir, 'pregenerated') self._EnsureDeviceDirectory(device_payload_dir) logging.info('Copying rootfs payload to device...') payload_name = self._GetRootFsPayloadFileName() payload = os.path.join(self.payload_dir, payload_name) self.device.CopyToDevice(payload, device_payload_dir, mode=self.payload_mode, log_output=True, **self._cmd_kwargs) if self.is_au_endtoendtest: self.RenameRootfsPayloadForAUTest(device_payload_dir, payload_name) def RenameRootfsPayloadForAUTest(self, payload_dir, payload_name): """Rename the payload supplied by autoupdate_EndToEndTest on the DUT. The au test takes in a payload that we want to update to. In order not to break the devservers update handling we rename this payload to update.gz after we copy it to the DUT. """ expected_path = os.path.join(payload_dir, ds_wrapper.ROOTFS_FILENAME) # Strip any partial paths from the filename e.g payloads/payload.bin payload_name = payload_name.rpartition('/')[2] current_path = os.path.join(payload_dir, payload_name) # Rename the payload on the DUT so we don't break the current # devserver staging. Rename to update.gz so DUTs devserver can respond. self.device.RunCommand(['mv', current_path, expected_path]) def TransferStatefulUpdate(self): """Transfer files for stateful update. The stateful update bin and the corresponding payloads are copied to the target remote device for stateful update. """ logging.debug('Checking whether file stateful_update_bin needs to be ' 'transferred to device...') need_transfer, stateful_update_bin = self._GetStatefulUpdateScript() if need_transfer: logging.info('Copying stateful_update_bin to device...') # stateful_update is a tiny uncompressed text file, so use rsync. self.device.CopyToWorkDir(stateful_update_bin, mode='rsync', log_output=True, **self._cmd_kwargs) self.stateful_update_bin = os.path.join( self.device.work_dir, os.path.basename( self.LOCAL_CHROOT_STATEFUL_UPDATE_PATH)) else: self.stateful_update_bin = stateful_update_bin if self.original_payload_dir: logging.info('Copying original stateful payload to device...') original_payload = os.path.join( self.original_payload_dir, ds_wrapper.STATEFUL_FILENAME) self._EnsureDeviceDirectory(self.device_restore_dir) self.device.CopyToDevice(original_payload, self.device_restore_dir, mode=self.payload_mode, log_output=True, **self._cmd_kwargs) logging.info('Copying target stateful payload to device...') payload = os.path.join(self.payload_dir, ds_wrapper.STATEFUL_FILENAME) self.device.CopyToWorkDir(payload, mode=self.payload_mode, log_output=True, **self._cmd_kwargs) def RestoreStateful(self): """Restore stateful partition for device.""" logging.warning('Restoring the stateful partition') self.RunUpdateStateful() self._Reboot('stateful partition restoration') try: self._CheckDevserverCanRun() logging.info('Stateful partition restored.') except DevserverCannotStartError as e: raise ChromiumOSUpdateError( 'Unable to restore stateful partition: %s', e) def ResetStatefulPartition(self): """Clear any pending stateful update request.""" logging.debug('Resetting stateful partition...') try: self.device.RunCommand(['sh', self.stateful_update_bin, '--stateful_change=reset'], **self._cmd_kwargs) except cros_build_lib.RunCommandError as e: if self.is_au_endtoendtest and not self.device.HasRsync(): # If we have updated backwards from a build with ext4 crytpo to a # build without ext4 crypto the DUT gets powerwashed. So the stateful # bin, payloads, and devserver files are no longer accessible. # See crbug.com/689105. Rsync will no longer be available either so we # will need to use scp for the rest of the update. logging.warning('Exception while resetting stateful: %s', e) if self.CheckRestoreStateful(): logging.info('Stateful files and devserver code now back on ' 'the device. Trying to reset stateful again.') self.device.RunCommand(['sh', self.stateful_update_bin, '--stateful_change=reset'], **self._cmd_kwargs) else: raise def RevertBootPartition(self): """Revert the boot partition.""" part = self.GetRootDev(self.device) logging.warning('Reverting update; Boot partition will be %s', part) try: self.device.RunCommand(['/postinst', part], **self._cmd_kwargs) except cros_build_lib.RunCommandError as e: logging.warning('Reverting the boot partition failed: %s', e) def UpdateRootfs(self): """Update the rootfs partition of the device.""" logging.info('Updating rootfs partition') devserver_bin = os.path.join(self.device_dev_dir, self.REMOTE_DEVSERVER_FILENAME) ds = ds_wrapper.RemoteDevServerWrapper( self.device, devserver_bin, self.is_au_endtoendtest, static_dir=self.device_static_dir, log_dir=self.device.work_dir) try: ds.Start() logging.debug('Successfully started devserver on the device on port ' '%d.', ds.port) # Use the localhost IP address to ensure that update engine # client can connect to the devserver. omaha_url = ds.GetDevServerURL( ip='127.0.0.1', port=ds.port, sub_dir='update/pregenerated') cmd = [self.REMOTE_UPDATE_ENGINE_BIN_FILENAME, '-check_for_update', '-omaha_url=%s' % omaha_url] self._StartPerformanceMonitoringForAUTest() self.device.RunCommand(cmd, **self._cmd_kwargs) # If we are using a progress bar, update it every 0.5s instead of 10s. if command.UseProgressBar(): update_check_interval = self.UPDATE_CHECK_INTERVAL_PROGRESSBAR oper = operation.ProgressBarOperation() else: update_check_interval = self.UPDATE_CHECK_INTERVAL_NORMAL oper = None end_message_not_printed = True # Loop until update is complete. while True: #TODO(dhaddock): Remove retry when M61 is stable. See crbug.com/744212. op, progress = retry_util.RetryException(cros_build_lib.RunCommandError, UPDATE_ENGINE_STATUS_RETRY, self.GetUpdateStatus, self.device, ['CURRENT_OP', 'PROGRESS'], delay_sec=DELAY_SEC_FOR_RETRY) logging.info('Waiting for update...status: %s at progress %s', op, progress) if op == UPDATE_STATUS_UPDATED_NEED_REBOOT: logging.notice('Update completed.') break if op == UPDATE_STATUS_IDLE: raise RootfsUpdateError( 'Update failed with unexpected update status: %s' % op) if oper is not None: if op == UPDATE_STATUS_DOWNLOADING: oper.ProgressBar(float(progress)) elif end_message_not_printed and op == UPDATE_STATUS_FINALIZING: oper.Cleanup() logging.notice('Finalizing image.') end_message_not_printed = False time.sleep(update_check_interval) # Write the hostlog to a file before shutting off devserver. self._CollectDevServerHostLog(ds) ds.Stop() except Exception as e: logging.error('Rootfs update failed.') self.RevertBootPartition() logging.warning(ds.TailLog() or 'No devserver log is available.') error_msg = 'Failed to perform rootfs update: %r' raise RootfsUpdateError(error_msg % e) finally: if ds.is_alive(): self._CollectDevServerHostLog(ds) ds.Stop() self.device.CopyFromDevice( ds.log_file, os.path.join(self.tempdir, self.LOCAL_DEVSERVER_LOG_FILENAME), **self._cmd_kwargs_omit_error) self.device.CopyFromDevice( self.REMOTE_UPDATE_ENGINE_LOGFILE_PATH, os.path.join(self.tempdir, os.path.basename( self.REMOTE_UPDATE_ENGINE_LOGFILE_PATH)), follow_symlinks=True, **self._cmd_kwargs_omit_error) self.device.CopyFromDevice( self.REMOTE_QUICK_PROVISION_LOGFILE_PATH, os.path.join(self.tempdir, os.path.basename( self.REMOTE_QUICK_PROVISION_LOGFILE_PATH)), follow_symlinks=True, ignore_failures=True, **self._cmd_kwargs_omit_error) self._CopyHostLogFromDevice('rootfs') self._StopPerformanceMonitoringForAUTest() def UpdateStateful(self, use_original_build=False): """Update the stateful partition of the device. Args: use_original_build: True if we use stateful.tgz of original build for stateful update, otherwise, as default, False. """ msg = 'Updating stateful partition' if self.original_payload_dir and use_original_build: payload_dir = self.device_restore_dir else: payload_dir = self.device.work_dir cmd = ['sh', self.stateful_update_bin, os.path.join(payload_dir, ds_wrapper.STATEFUL_FILENAME)] if self._clobber_stateful: cmd.append('--stateful_change=clean') msg += ' with clobber enabled' logging.info('%s...', msg) try: self.device.RunCommand(cmd, **self._cmd_kwargs) except cros_build_lib.RunCommandError as e: logging.error('Stateful update failed.') self.ResetStatefulPartition() error_msg = 'Failed to perform stateful partition update: %s' raise StatefulUpdateError(error_msg % e) def RunUpdateRootfs(self): """Run all processes needed by updating rootfs. 1. Check device's status to make sure it can be updated. 2. Copy files to remote device needed for rootfs update. 3. Do root updating. TODO(ihf): Change this to: 2. Unpack rootfs here on server. 3. rsync from server rootfs to device rootfs to perform update (do not use --compress). """ self.SetupRootfsUpdate() # Copy payload for rootfs update. self.TransferRootfsUpdate() self.UpdateRootfs() def RunUpdateStateful(self): """Run all processes needed by updating stateful. 1. Copy files to remote device needed by stateful update. 2. Do stateful update. TODO(ihf): Change this to: 1. Unpack stateful here on server. 2. rsync from server stateful to device stateful to update (do not use --compress). """ self.TransferStatefulUpdate() self.UpdateStateful() def RebootAndVerify(self): """Reboot and verify the remote device. 1. Reboot the remote device. If _clobber_stateful (--clobber-stateful) is executed, the stateful partition is wiped, and the working directory on the remote device no longer exists. So, recreate the working directory for this remote device. 2. Verify the remote device, by checking that whether the root device changed after reboot. """ logging.notice('rebooting device...') # Record the current root device. This must be done after SetupRootfsUpdate # and before reboot, since SetupRootfsUpdate may reboot the device if there # is a pending update, which changes the root device, and reboot will # definitely change the root device if update successfully finishes. old_root_dev = self.GetRootDev(self.device) self.device.Reboot() if self._clobber_stateful: self.device.BaseRunCommand(['mkdir', '-p', self.device.work_dir]) if self._do_rootfs_update: logging.notice('Verifying that the device has been updated...') new_root_dev = self.GetRootDev(self.device) if old_root_dev is None: raise AutoUpdateVerifyError( 'Failed to locate root device before update.') if new_root_dev is None: raise AutoUpdateVerifyError( 'Failed to locate root device after update.') if new_root_dev == old_root_dev: raise AutoUpdateVerifyError( 'Failed to boot into the new version. Possibly there was a ' 'signing problem, or an automated rollback occurred because ' 'your new image failed to boot.') def RunUpdate(self): """Update the device with image of specific version.""" self.TransferDevServerPackage() restore_stateful = self.CheckRestoreStateful() if restore_stateful: self.RestoreStateful() # Perform device updates. if self._do_rootfs_update: self.RunUpdateRootfs() logging.info('Rootfs update completed.') if self._do_stateful_update and not restore_stateful: self.RunUpdateStateful() logging.info('Stateful update completed.') if self._reboot: self.RebootAndVerify() if self._disable_verification: logging.info('Disabling rootfs verification on the device...') self.device.DisableRootfsVerification() def _CollectDevServerHostLog(self, devserver): """Write the host_log events from the remote DUTs devserver to a file. The hostlog is needed for analysis by autoupdate_EndToEndTest only. We retry several times as some DUTs are slow immediately after starting up a devserver and return no hostlog on the first call(s). Args: devserver: The remote devserver wrapper for the running devserver. """ if not self.is_au_endtoendtest: return for _ in range(0, MAX_RETRY): try: host_log_url = devserver.GetDevServerHostLogURL(ip='127.0.0.1', port=devserver.port, host='127.0.0.1') # Save the hostlog. self.device.RunCommand(['curl', host_log_url, '-o', self.REMOTE_HOSTLOG_FILE_PATH], **self._cmd_kwargs) # Copy it back. tmphostlog = os.path.join(self.tempdir, 'hostlog') self.device.CopyFromDevice(self.REMOTE_HOSTLOG_FILE_PATH, tmphostlog, **self._cmd_kwargs_omit_error) # Check that it is not empty. with open(tmphostlog, 'r') as out_log: hostlog_data = json.loads(out_log.read()) if not hostlog_data: logging.info('Hostlog empty. Trying again...') time.sleep(DELAY_SEC_FOR_RETRY) else: break except cros_build_lib.RunCommandError as e: logging.debug('Exception raised while trying to write the hostlog: ' '%s', e) def _StartPerformanceMonitoringForAUTest(self): """Start update_engine performance monitoring script in rootfs update. This script is used by autoupdate_EndToEndTest. """ if self._clobber_stateful or not self.is_au_endtoendtest: return None cmd = ['python', self.REMOTE_UPDATE_ENGINE_PERF_SCRIPT_PATH, '--start-bg'] try: perf_id = self.device.RunCommand(cmd).output.strip() logging.info('update_engine_performance_monitors pid is %s.', perf_id) self.perf_id = perf_id except cros_build_lib.RunCommandError as e: logging.debug('Could not start performance monitoring script: %s', e) def _StopPerformanceMonitoringForAUTest(self): """Stop the performance monitoring script and save results to file.""" if self.perf_id is None: return cmd = ['python', self.REMOTE_UPDATE_ENGINE_PERF_SCRIPT_PATH, '--stop-bg', self.perf_id] try: perf_json_data = self.device.RunCommand(cmd).output.strip() self.device.RunCommand(['echo', json.dumps(perf_json_data), '>', self.REMOTE_UPDATE_ENGINE_PERF_RESULTS_PATH]) except cros_build_lib.RunCommandError as e: logging.debug('Could not stop performance monitoring process: %s', e) def _CopyHostLogFromDevice(self, partial_filename): """Copy the hostlog file generated by the devserver from the device.""" if self.is_au_endtoendtest: self.device.CopyFromDevice( self.REMOTE_HOSTLOG_FILE_PATH, os.path.join(self.tempdir, '_'.join([os.path.basename( self.REMOTE_HOSTLOG_FILE_PATH), partial_filename])), **self._cmd_kwargs_omit_error) def _Reboot(self, error_stage): try: self.device.Reboot(timeout_sec=self.REBOOT_TIMEOUT) except cros_build_lib.DieSystemExit: raise ChromiumOSUpdateError('%s cannot recover from reboot at %s' % ( self.device.hostname, error_stage)) except remote_access.SSHConnectionError: raise ChromiumOSUpdateError('Failed to connect to %s at %s' % ( self.device.hostname, error_stage)) class ChromiumOSUpdater(ChromiumOSFlashUpdater): """Used to auto-update Cros DUT with image. Different from ChromiumOSFlashUpdater, which only contains cros-flash related auto-update methods, ChromiumOSUpdater includes pre-setup and post-check methods for both rootfs and stateful update. It also contains various single check functions, like CheckVersion() and _ResetUpdateEngine(). Furthermore, this class adds retry to package transfer-related functions. """ REMOTE_STATEFUL_PATH_TO_CHECK = ['/var', '/home', '/mnt/stateful_partition'] REMOTE_STATEFUL_TEST_FILENAME = '.test_file_to_be_deleted' REMOTE_UPDATED_MARKERFILE_PATH = '/run/update_engine_autoupdate_completed' REMOTE_LAB_MACHINE_FILE_PATH = '/mnt/stateful_partition/.labmachine' KERNEL_A = {'name': 'KERN-A', 'kernel': 2, 'root': 3} KERNEL_B = {'name': 'KERN-B', 'kernel': 4, 'root': 5} KERNEL_UPDATE_TIMEOUT = 180 def __init__(self, device, build_name, payload_dir, dev_dir='', log_file=None, tempdir=None, original_payload_dir=None, clobber_stateful=True, local_devserver=False, yes=False, payload_filename=None): """Initialize a ChromiumOSUpdater for auto-update a chromium OS device. Args: device: the ChromiumOSDevice to be updated. build_name: the target update version for the device. payload_dir: the directory of payload(s). dev_dir: the directory of the devserver that runs the CrOS auto-update. log_file: The file to save running logs. tempdir: the temp directory in caller, not in the device. For example, the tempdir for cros flash is /tmp/cros-flash****/, used to temporarily keep files when transferring devserver package, and reserve devserver and update engine logs. original_payload_dir: The directory containing payloads whose version is the same as current host's rootfs partition. If it's None, will first try installing the matched stateful.tgz with the host's rootfs Partition when restoring stateful. Otherwise, install the target stateful.tgz. clobber_stateful: whether to do a clean stateful update. The default is True for CrOS update. local_devserver: Indicate whether users use their local devserver. Default: False. yes: Assume "yes" (True) for any prompt. The default is False. However, it should be set as True if we want to disable all the prompts for auto-update. payload_filename: Filename of exact payload file to use for update instead of the default: update.gz. """ super(ChromiumOSUpdater, self).__init__( device, payload_dir, dev_dir=dev_dir, tempdir=tempdir, original_payload_dir=original_payload_dir, clobber_stateful=clobber_stateful, yes=yes, payload_filename=payload_filename) if log_file: self._cmd_kwargs['log_stdout_to_file'] = log_file self._cmd_kwargs['append_to_file'] = True self._cmd_kwargs['combine_stdout_stderr'] = True self._cmd_kwargs_omit_error['log_stdout_to_file'] = log_file self._cmd_kwargs_omit_error['append_to_file'] = True self._cmd_kwargs_omit_error['combine_stdout_stderr'] = True self.inactive_kernel = None if local_devserver: self.update_version = None else: self.update_version = build_name def _cgpt(self, flag, kernel, dev='$(rootdev -s -d)'): """Return numeric cgpt value for the specified flag, kernel, device.""" cmd = ['cgpt', 'show', '-n', '-i', '%d' % kernel['kernel'], flag, dev] return int(self._RetryCommand( cmd, capture_output=True, log_output=True).output.strip()) def _GetKernelPriority(self, kernel): """Return numeric priority for the specified kernel. Args: kernel: information of the given kernel, KERNEL_A or KERNEL_B. """ return self._cgpt('-P', kernel) def _GetKernelSuccess(self, kernel): """Return boolean success flag for the specified kernel. Args: kernel: information of the given kernel, KERNEL_A or KERNEL_B. """ return self._cgpt('-S', kernel) != 0 def _GetKernelTries(self, kernel): """Return tries count for the specified kernel. Args: kernel: information of the given kernel, KERNEL_A or KERNEL_B. """ return self._cgpt('-T', kernel) def _GetKernelState(self): """Returns the (<active>, <inactive>) kernel state as a pair.""" active_root = int(re.findall(r'(\d+\Z)', self.GetRootDev(self.device))[0]) if active_root == self.KERNEL_A['root']: return self.KERNEL_A, self.KERNEL_B elif active_root == self.KERNEL_B['root']: return self.KERNEL_B, self.KERNEL_A else: raise ChromiumOSUpdateError('Encountered unknown root partition: %s' % active_root) def _GetReleaseVersion(self): """Get release version of the device.""" lsb_release_content = self._RetryCommand( ['cat', '/etc/lsb-release'], capture_output=True, log_output=True).output.strip() regex = r'^CHROMEOS_RELEASE_VERSION=(.+)$' return auto_update_util.GetChromeosBuildInfo( lsb_release_content=lsb_release_content, regex=regex) def _GetReleaseBuilderPath(self): """Get release version of the device.""" lsb_release_content = self._RetryCommand( ['cat', '/etc/lsb-release'], capture_output=True, log_output=True).output.strip() regex = r'^CHROMEOS_RELEASE_BUILDER_PATH=(.+)$' return auto_update_util.GetChromeosBuildInfo( lsb_release_content=lsb_release_content, regex=regex) def CheckVersion(self): """Check the image running in DUT has the expected version. Returns: True if the DUT's image version matches the version that the ChromiumOSUpdater tries to update to. """ if not self.update_version: return False # Use CHROMEOS_RELEASE_BUILDER_PATH to match the build version if it exists # in lsb-release, otherwise, continue using CHROMEOS_RELEASE_VERSION. release_builder_path = self._GetReleaseBuilderPath() if release_builder_path: return self.update_version == release_builder_path return self.update_version.endswith(self._GetReleaseVersion()) def _ResetUpdateEngine(self): """Resets the host to prepare for a clean update regardless of state.""" self._RetryCommand(['rm', '-f', self.REMOTE_UPDATED_MARKERFILE_PATH], **self._cmd_kwargs) self._RetryCommand(['stop', 'ui'], **self._cmd_kwargs_omit_error) self._RetryCommand(['stop', 'update-engine'], **self._cmd_kwargs_omit_error) self._RetryCommand(['start', 'update-engine'], **self._cmd_kwargs) status = retry_util.RetryException( Exception, MAX_RETRY, self.GetUpdateStatus, self.device, delay_sec=DELAY_SEC_FOR_RETRY) if status[0] != UPDATE_STATUS_IDLE: raise PreSetupUpdateError('%s is not in an installable state' % self.device.hostname) def _VerifyBootExpectations(self, expected_kernel_state, rollback_message): """Verify that we fully booted given expected kernel state. It verifies that we booted using the correct kernel state, and that the OS has marked the kernel as good. Args: expected_kernel_state: kernel state that we're verifying with i.e. I expect to be booted onto partition 4 etc. See output of _GetKernelState. rollback_message: string to raise as a RootfsUpdateError if we booted with the wrong partition. """ logging.debug('Start verifying boot expectations...') # Figure out the newly active kernel active_kernel_state = self._GetKernelState()[0] # Rollback if (expected_kernel_state and active_kernel_state != expected_kernel_state): logging.debug('Dumping partition table.') self.device.RunCommand(['cgpt', 'show', '$(rootdev -s -d)'], **self._cmd_kwargs) logging.debug('Dumping crossystem for firmware debugging.') self.device.RunCommand(['crossystem', '--all'], **self._cmd_kwargs) raise RootfsUpdateError(rollback_message) # Make sure chromeos-setgoodkernel runs try: timeout_util.WaitForReturnTrue( lambda: (self._GetKernelTries(active_kernel_state) == 0 and self._GetKernelSuccess(active_kernel_state)), self.KERNEL_UPDATE_TIMEOUT, period=5) except timeout_util.TimeoutError: services_status = self.device.RunCommand( ['status', 'system-services'], capture_output=True, log_output=True).output logging.debug('System services_status: %r' % services_status) if services_status != 'system-services start/running\n': event = ('Chrome failed to reach login screen') else: event = ('update-engine failed to call ' 'chromeos-setgoodkernel') raise RootfsUpdateError( 'After update and reboot, %s ' 'within %d seconds' % (event, self.KERNEL_UPDATE_TIMEOUT)) def _CheckVersionToConfirmInstall(self): # In the local_devserver case, we can't know the expected # build, so just pass. logging.debug('Checking whether the new build is successfully installed...') if not self.update_version: logging.debug('No update_version is provided if test is executed with' 'local devserver.') return True # Always try the default check_version method first, this prevents # any backward compatibility issue. if self.CheckVersion(): return True return auto_update_util.VersionMatch( self.update_version, self._GetReleaseVersion()) def _RetryCommand(self, cmd, **kwargs): """Retry commands if SSHConnectionError happens. Args: cmd: the command to be run by device. kwargs: the parameters for device to run the command. Returns: the output of running the command. """ return retry_util.RetryException( remote_access.SSHConnectionError, MAX_RETRY, self.device.RunCommand, cmd, delay_sec=DELAY_SEC_FOR_RETRY, **kwargs) def TransferDevServerPackage(self): """Transfer devserver package to work directory of the remote device.""" retry_util.RetryException( cros_build_lib.RunCommandError, MAX_RETRY, super(ChromiumOSUpdater, self).TransferDevServerPackage, delay_sec=DELAY_SEC_FOR_RETRY) def TransferRootfsUpdate(self): """Transfer files for rootfs update. The corresponding payload are copied to the remote device for rootfs update. """ retry_util.RetryException( cros_build_lib.RunCommandError, MAX_RETRY, super(ChromiumOSUpdater, self).TransferRootfsUpdate, delay_sec=DELAY_SEC_FOR_RETRY) def TransferStatefulUpdate(self): """Transfer files for stateful update. The stateful update bin and the corresponding payloads are copied to the target remote device for stateful update. """ retry_util.RetryException( cros_build_lib.RunCommandError, MAX_RETRY, super(ChromiumOSUpdater, self).TransferStatefulUpdate, delay_sec=DELAY_SEC_FOR_RETRY) def PreSetupCrOSUpdate(self): """Pre-setup for whole auto-update process for cros_host. It includes: 1. Create a file to indicate if provision fails for cros_host. The file will be removed by stateful update or full install. """ logging.debug('Start pre-setup for the whole CrOS update process...') if not self.is_au_endtoendtest: self._RetryCommand(['touch', self.REMOTE_PROVISION_FAILED_FILE_PATH], **self._cmd_kwargs) # Related to crbug.com/360944. release_pattern = r'^.*-release/R[0-9]+-[0-9]+\.[0-9]+\.0$' if not re.match(release_pattern, self.update_version): logging.debug('The update version is not matched to release pattern') return False if not self.CheckVersion(): logging.debug('The update version is not matched to the current version') return False return True def PreSetupStatefulUpdate(self): """Pre-setup for stateful update for CrOS host.""" logging.debug('Start pre-setup for stateful update...') self._RetryCommand(['sudo', 'stop', 'ap-update-manager'], **self._cmd_kwargs_omit_error) for folder in self.REMOTE_STATEFUL_PATH_TO_CHECK: touch_path = os.path.join(folder, self.REMOTE_STATEFUL_TEST_FILENAME) self._RetryCommand(['touch', touch_path], **self._cmd_kwargs) self._ResetUpdateEngine() self.ResetStatefulPartition() def PostCheckStatefulUpdate(self): """Post-check for stateful update for CrOS host.""" logging.debug('Start post check for stateful update...') self._Reboot('post check of stateful update') if self._clobber_stateful: for folder in self.REMOTE_STATEFUL_PATH_TO_CHECK: test_file_path = os.path.join(folder, self.REMOTE_STATEFUL_TEST_FILENAME) # If stateful update succeeds, these test files should not exist. if self.device.IfFileExists(test_file_path, **self._cmd_kwargs_omit_error): raise StatefulUpdateError('failed to post-check stateful update.') def PreSetupRootfsUpdate(self): """Pre-setup for rootfs update for CrOS host.""" logging.debug('Start pre-setup for rootfs update...') self._Reboot('pre-setup of rootfs update') self._RetryCommand(['sudo', 'stop', 'ap-update-manager'], **self._cmd_kwargs_omit_error) self._ResetUpdateEngine() def _IfDevserverPackageInstalled(self): """Check whether devserver package is well installed. There's a chance that devserver package is removed in the middle of auto-update process. This function double check it and transfer it if it's removed. """ logging.info('Checking whether devserver files are still on the device...') try: devserver_bin = os.path.join(self.device_dev_dir, self.REMOTE_DEVSERVER_FILENAME) if not self.device.IfFileExists( devserver_bin, **self._cmd_kwargs_omit_error): logging.info('Devserver files not found on device. Resending them...') self.TransferDevServerPackage() self.TransferStatefulUpdate() return True except cros_build_lib.RunCommandError as e: logging.warning('Failed to verify whether packages still exist: %s', e) return False def _CheckDevserverCanRun(self): """Check if devserver can successfully run for ChromiumOSUpdater.""" self._IfDevserverPackageInstalled() super(ChromiumOSUpdater, self)._CheckDevserverCanRun() def CheckDevserverRun(self): """Check whether devserver can start.""" self._CheckDevserverCanRun() logging.info('Devserver successfully start.') def RestoreStateful(self): """Restore stateful partition for device.""" logging.warning('Restoring the stateful partition') self.PreSetupStatefulUpdate() use_original_build = bool(self.original_payload_dir) self.UpdateStateful(use_original_build=use_original_build) self.PostCheckStatefulUpdate() self.CheckDevserverRun() def PostCheckRootfsUpdate(self): """Post-check for rootfs update for CrOS host.""" logging.debug('Start post check for rootfs update...') active_kernel, inactive_kernel = self._GetKernelState() logging.debug('active_kernel= %s, inactive_kernel=%s', active_kernel, inactive_kernel) if (self._GetKernelPriority(inactive_kernel) < self._GetKernelPriority(active_kernel)): raise RootfsUpdateError('Update failed. The priority of the inactive ' 'kernel partition is less than that of the ' 'active kernel partition.') self.inactive_kernel = inactive_kernel if not self.is_au_endtoendtest: # The issue is that certain AU tests leave the TPM in a bad state which # most commonly shows up in provisioning. Executing this 'crossystem' # command before rebooting clears the problem state during the reboot. # It's also worth mentioning that this isn't a complete fix: The bad # TPM state in theory might happen some time other than during # provisioning. Also, the bad TPM state isn't supposed to happen at # all; this change is just papering over the real bug. self._RetryCommand('crossystem clear_tpm_owner_request=1', **self._cmd_kwargs_omit_error) self._Reboot('post check of rootfs update') def PostCheckCrOSUpdate(self): """Post check for the whole auto-update process.""" logging.debug('Post check for the whole CrOS update...') start_time = time.time() # Not use 'sh' here since current device.RunCommand cannot recognize # the content of $FILE. autoreboot_cmd = ('FILE="%s" ; [ -f "$FILE" ] || ' '( touch "$FILE" ; start autoreboot )') self._RetryCommand(autoreboot_cmd % self.REMOTE_LAB_MACHINE_FILE_PATH, **self._cmd_kwargs) # Loop in case the initial check happens before the reboot. while True: try: start_verify_time = time.time() self._VerifyBootExpectations( self.inactive_kernel, rollback_message= 'Build %s failed to boot on %s; system rolled back to previous ' 'build' % (self.update_version, self.device.hostname)) # Check that we've got the build we meant to install. if not self._CheckVersionToConfirmInstall(): raise ChromiumOSUpdateError( 'Failed to update %s to build %s; found build ' '%s instead' % (self.device.hostname, self.update_version, self._GetReleaseVersion())) except RebootVerificationError as e: # If a minimum amount of time since starting the check has not # occurred, wait and retry. Use the start of the verification # time in case an SSH call takes a long time to return/fail. if start_verify_time - start_time < POST_CHECK_SETTLE_SECONDS: logging.warning('Delaying for re-check of %s to update to %s (%s)' % (self.device.hostname, self.update_version, e)) time.sleep(POST_CHECK_RETRY_SECONDS) continue raise break # For autoupdate_EndToEndTest only, we have one extra step to verify. if self.is_au_endtoendtest and not self._clobber_stateful: self.PostRebootUpdateCheckForAUTest() def PostRebootUpdateCheckForAUTest(self): """Do another update check after reboot to get the post update hostlog. This is only done with autoupdate_EndToEndTest. """ logging.debug('Doing one final update check to get post update hostlog.') devserver_bin = os.path.join(self.device_dev_dir, self.REMOTE_DEVSERVER_FILENAME) ds = ds_wrapper.RemoteDevServerWrapper( self.device, devserver_bin, self.is_au_endtoendtest, static_dir=self.device_static_dir, log_dir=self.device.work_dir) try: ds.Start() logging.debug('Successfully started devserver on the device on port ' '%d.', ds.port) omaha_url = ds.GetDevServerURL(ip='127.0.0.1', port=ds.port, sub_dir='update') cmd = [self.REMOTE_UPDATE_ENGINE_BIN_FILENAME, '-check_for_update', '-omaha_url=%s' % omaha_url] self.device.RunCommand(cmd, **self._cmd_kwargs) op = self.GetUpdateStatus(self.device) logging.info('Post update check status: %s' % op) self._CollectDevServerHostLog(ds) ds.Stop() except Exception: logging.error('Post reboot update check failed.') logging.warning(ds.TailLog() or 'No devserver log is available.') finally: if ds.is_alive(): self._CollectDevServerHostLog(ds) ds.Stop() self._CopyHostLogFromDevice('reboot') def AwaitReboot(self, old_boot_id): """Await a reboot, ensuring that it is no longer running old_boot_id. Args: old_boot_id: The boot_id that must be transitioned away from for success. Returns: True if the device has successfully rebooted. Raises: RebootVerificationError if a successful reboot has not occurred. """ logging.debug('Awaiting reboot from %s...', old_boot_id) if not self.device.AwaitReboot(old_boot_id): raise RebootVerificationError('Device has not rebooted from %s' % old_boot_id) return True

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0

null

0

null

0

1

0

2caaeb7931baabb2f2a4e505483d42162334c020

1,368

py

Python

d2lbook/common.py

dltech-xyz/d2l-book

5f5279708f029c9724f4b258a1a26b6db2317532

[ "Apache-2.0" ]

1

2021-01-02T03:34:04.000Z

d2lbook/common.py

szha/d2l-book

5f5279708f029c9724f4b258a1a26b6db2317532

[ "Apache-2.0" ]

null

d2lbook/common.py

szha/d2l-book

5f5279708f029c9724f4b258a1a26b6db2317532

[ "Apache-2.0" ]

1

2020-09-15T05:57:12.000Z

import re from typing import Optional, List, Any, Callable, Tuple # Our special mark in markdown, e.g. :label:`chapter_intro` md_mark_pattern = re.compile(':([-\/\\._\w\d]+):(`[\ \*-\/\\\._\w\d]+`)?') # Same for md_mark_pattern, but for rst files rst_mark_pattern = re.compile(':([-\/\\._\w\d]+):(``[\ \*-\/\\\._\w\d]+``)?') # The source code tab mark source_tab_pattern = re.compile('# *@tab +([\w\,\ ]+)') # Markdown code fence md_code_fence = re.compile('(```+) *(.*)') def group_list(list_obj: List[Any], status_fn: Callable[[Any, Any], Any] ) -> List[Tuple[Any, List[Any]]]: """Cut a list into multiple parts when fn returns True""" prev_status = None prev_pos = 0 ret = [] for i, item in enumerate(list_obj): cur_status = status_fn(item, prev_status) if prev_status is not None and cur_status != prev_status: ret.append((prev_status, list_obj[prev_pos:i])) prev_pos = i prev_status = cur_status ret.append((cur_status, list_obj[prev_pos:])) return ret def flatten(x): """flatten a list of lists into a list.""" return [item for sublist in x for item in sublist] def print_list(x): print(f'len: {len(x)}') for i, y in enumerate(x): print(f'{i}\t{y}') def print_dict(x): print(f'len: {len(x)}') for k in x: print(f'{k}\t{x[k]}')

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false

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0.206897

0

null

0

null

0

1

0

2cab7ae8cc2711116a7008627d7fc69c47ab979f

4,999

py

Python

emulator/demoEmulator.py

ojotoxy/Processor

8e6e4e8b33b2d3b51b05104089e801f187bb4617

[ "Apache-2.0" ]

1

2021-07-21T03:46:43.000Z

emulator/demoEmulator.py

ojotoxy/Processor

8e6e4e8b33b2d3b51b05104089e801f187bb4617

[ "Apache-2.0" ]

null

emulator/demoEmulator.py

ojotoxy/Processor

8e6e4e8b33b2d3b51b05104089e801f187bb4617

[ "Apache-2.0" ]

1

2021-01-22T07:46:38.000Z

#!/usr/bin/env python3 from enum import Enum # This computer will have these memory mapped registers: # 0 = PC # 1 = SP # but I didn't implement them. Only the program counter exists and its not memory mapped class Memory(object): def __init__(self): self.storage = {} def __setitem__(self, addr, value): self.storage[addr] = value def __getitem__(self, addr): return self.storage.get(addr, 0) Instruction = Enum('Instruction', 'mov literal add sub mul div mod inc dec jmp je jne jg jge print') # argument size in words: what the op does # 2: mov A -> B # 2: literal VAL -> A # 3: add A + B -> C # 3: sub A - B -> C # 3: mul A * B -> C # 3: div A / B -> C # 3: mod A % B -> C # 1: inc A + 1 -> A # 1: dec A - 1 -> A # 1: jmp POSITION # 3: je if A == B goto POSITION # 3: jne if A != B goto POSITION # 3: jg if A > B goto POSITION # 3: jge if A >= B goto POSITION # 1: print A # writepointer mov A -> memory[B] # readpointer memory[A] --> B # Need to ensure you dont overwrite the code memory with variables! # This is the task that assemblers do for you by createing code and data sections. VAR_COUNTER = 100 VAR_COUNTER_INNER = 101 VAR_MODULO_RESULT = 102 VAR_ZERO = 103 PROGRAM_COUNT_UPWARDS = [ Instruction.literal, 1, VAR_COUNTER, # 0 Instruction.inc, VAR_COUNTER, # 3 Instruction.print, VAR_COUNTER, # 5 Instruction.jmp, 3 # 7 ] PROGRAM_LIST_PRIME_NUMBERS = [ Instruction.literal, 1, VAR_COUNTER, # 0 Instruction.literal, 0, VAR_ZERO, # 3 Instruction.inc, VAR_COUNTER, # 6 Instruction.literal, 2, VAR_COUNTER_INNER, # 8 Instruction.mod, VAR_COUNTER, VAR_COUNTER_INNER, VAR_MODULO_RESULT, # 11 Instruction.je, VAR_MODULO_RESULT, VAR_ZERO, 6, # 15, jump to next candidate prime Instruction.inc, VAR_COUNTER_INNER, # 19, increment factor Instruction.jge, VAR_COUNTER_INNER, VAR_COUNTER, 27, # 21, This number is prime, go to print it Instruction.jmp, 11, # 25, jump to next modulo test. Instruction.print, VAR_COUNTER, # 27 Instruction.jmp, 3 # 29, jump to next candidate prime ] program = PROGRAM_LIST_PRIME_NUMBERS memory = Memory() # load the program into memory for i in range(len(program)): memory[i] = program[i] program_counter = 0 def readword(): global program_counter val = memory[program_counter] program_counter += 1 return val while True: instruction_code = readword() instruction = Instruction(instruction_code) # print('PC = {}, Got Instruction {}'.format(program_counter-1, instruction)) if instruction == Instruction.mov: A = readword() B = readword() memory[B] = memory[A] elif instruction == Instruction.literal: VAL = readword() A = readword() memory[A] = VAL elif instruction == Instruction.add: A = readword() B = readword() C = readword() memory[C] = memory[A] + memory[B] # TODO modulo elif instruction == Instruction.sub: A = readword() B = readword() C = readword() memory[C] = memory[A] - memory[B] # TODO modulo elif instruction == Instruction.mul: A = readword() B = readword() C = readword() memory[C] = memory[A] * memory[B] # TODO modulo elif instruction == Instruction.div: A = readword() B = readword() C = readword() memory[C] = int(memory[A] / memory[B]) elif instruction == Instruction.mod: A = readword() B = readword() C = readword() memory[C] = int(memory[A] % memory[B]) elif instruction == Instruction.inc: A = readword() memory[A] = memory[A] + 1 # TODO modulo elif instruction == Instruction.dec: A = readword() memory[A] = memory[A] - 1 # TODO modulo elif instruction == Instruction.jmp: POSITION = readword() program_counter = POSITION elif instruction == Instruction.je: A = readword() B = readword() POSITION = readword() A_val = memory[A] B_val = memory[B] if A_val == B_val: program_counter = POSITION elif instruction == Instruction.jne: A = readword() B = readword() POSITION = readword() A_val = memory[A] B_val = memory[B] if A_val != B_val: program_counter = POSITION elif instruction == Instruction.jg: A = readword() B = readword() POSITION = readword() A_val = memory[A] B_val = memory[B] if A_val > B_val: program_counter = POSITION elif instruction == Instruction.jge: A = readword() B = readword() POSITION = readword() A_val = memory[A] B_val = memory[B] if A_val >= B_val: program_counter = POSITION elif instruction == Instruction.print: A = readword() value = memory[A] print(value)

29.063953

100

0.605721

657

4,999

4.493151

0.2207

0.040312

0.123306

0.060976

0.41565

0.39397

0.360434

0.332656

0

0.019899

0.286257

4,999

171

101

29.233918

0.807455

0.215643

0

0.447154

0

0.019102

0

0.005848

0

1

0.03252

false

0

0.00813

0.065041

0.04065

0

null

0

null

0

1

0

2cace54cc66cc33d32eb380eadf379d0098d853a

8,842

py

Python

ggshield/config.py

boblefrag/gg-shield

8eef8e02596ca05b9250482d9ea5cafd4435cfa0

[ "MIT" ]

null

ggshield/config.py

boblefrag/gg-shield

8eef8e02596ca05b9250482d9ea5cafd4435cfa0

[ "MIT" ]

null

ggshield/config.py

boblefrag/gg-shield

8eef8e02596ca05b9250482d9ea5cafd4435cfa0

[ "MIT" ]

null

import copy import json import os from typing import Any, Dict, List, NamedTuple import click import yaml from dotenv import load_dotenv from pygitguardian.models import PolicyBreak from .git_shell import get_git_root, is_git_dir from .text_utils import display_error CONTEXT_SETTINGS = dict(help_option_names=["-h", "--help"]) # max file size to accept MAX_FILE_SIZE = 1048576 CPU_COUNT = os.cpu_count() or 1 class Attribute(NamedTuple): name: str default: Any def replace_in_keys(data: Dict, old_char: str, new_char: str) -> None: """ Replace old_char with new_char in data keys. """ for key in list(data): if old_char in key: new_key = key.replace(old_char, new_char) data[new_key] = data.pop(key) class Config: all_policies: bool api_url: str exit_zero: bool matches_ignore: set paths_ignore: set show_secrets: bool verbose: bool CONFIG_LOCAL = ["./.gitguardian", "./.gitguardian.yml", "./.gitguardian.yaml"] CONFIG_GLOBAL = [ os.path.join(os.path.expanduser("~"), ".gitguardian"), os.path.join(os.path.expanduser("~"), ".gitguardian.yml"), os.path.join(os.path.expanduser("~"), ".gitguardian.yaml"), ] DEFAULT_CONFIG_LOCAL = "./.gitguardian.yaml" attributes: List[Attribute] = [ Attribute("all_policies", False), Attribute("api_url", "https://api.gitguardian.com"), Attribute("exit_zero", False), Attribute("matches_ignore", set()), Attribute("paths_ignore", set()), Attribute("show_secrets", False), Attribute("verbose", False), ] def __init__(self) -> None: for attr in self.attributes: setattr(self, attr.name, attr.default) self.load_configs(self.CONFIG_GLOBAL) self.load_configs(self.CONFIG_LOCAL) def __getattr__(self, name: str) -> Any: # Required for dynamic types on mypy return object.__getattribute__(self, name) def get_attributes_keys(self) -> List: return list( list(zip(*self.attributes))[0] ) # get list of first elements in tuple def update_config(self, **kwargs: Any) -> None: for key, item in kwargs.items(): if key in self.get_attributes_keys(): if isinstance(item, list): getattr(self, key).update(item) else: setattr(self, key, item) else: click.echo("Unrecognized key in config: {}".format(key)) def load_config(self, filename: str) -> bool: if not os.path.isfile(filename): return False with open(filename, "r") as f: try: _config = yaml.safe_load(f) or {} replace_in_keys(_config, "-", "_") self.update_config(**_config) except Exception as e: raise click.ClickException( f"Parsing error while reading {filename}:\n{str(e)}" ) return True def load_configs(self, filenames: List[str]) -> None: """ Loads config files until one succeeds. """ for filename in filenames: try: if self.load_config(filename): return except Exception as exc: click.echo(str(exc)) def to_dict(self) -> Dict[str, Any]: _config = {key: getattr(self, key) for key in self.get_attributes_keys()} # Convert all sets into more human readable lists for key in self.get_attributes_keys(): value = _config[key] if type(value) is set: _config[key] = list(value) replace_in_keys(_config, "_", "-") return _config def save(self) -> bool: """ Save config in the first CONFIG_LOCAL file. If no local config file, creates a local .gitguardian.yaml """ config_file = self.DEFAULT_CONFIG_LOCAL for filename in self.CONFIG_LOCAL: if os.path.isfile(filename): config_file = filename break with open(config_file, "w") as f: try: stream = yaml.dump(self.to_dict(), default_flow_style=False) f.write(stream.replace("- ", " - ")) except Exception as e: raise click.ClickException( f"Error while saving config in {config_file}:\n{str(e)}" ) return True def add_ignored_match(self, secret_hash: str) -> None: """ Add secret to matches_ignore. """ current_ignored = self.matches_ignore current_ignored.add(secret_hash) def load_dot_env() -> None: """Loads .env file into sys.environ.""" dont_load_env = os.getenv("GITGUARDIAN_DONT_LOAD_ENV", False) dotenv_path = os.getenv("GITGUARDIAN_DOTENV_PATH", None) cwd_env = os.path.join(".", ".env") if not dont_load_env: if dotenv_path and os.path.isfile(dotenv_path): load_dotenv(dotenv_path, override=True) return elif dotenv_path: display_error( "GITGUARDIAN_DOTENV_LOCATION does not point to a valid .env file" ) if os.path.isfile(cwd_env): load_dotenv(cwd_env, override=True) return if is_git_dir() and os.path.isfile(os.path.join(get_git_root(), ".env")): load_dotenv(os.path.join(get_git_root(), ".env"), override=True) return class Cache: last_found_secrets: set CACHE_FILENAME = "./.cache_ggshield" attributes: List[Attribute] = [ Attribute("last_found_secrets", set()), ] def __init__(self) -> None: self.purge() self.load_cache() def __getattr__(self, name: str) -> Any: # Required for dynamic types on mypy return object.__getattribute__(self, name) def get_attributes_keys(self) -> List: return list( list(zip(*self.attributes))[0] ) # get list of first elements in tuple def create_empty_cache(self) -> None: # Creates a new file with open(self.CACHE_FILENAME, "w"): pass def load_cache(self) -> bool: if not os.path.isfile(self.CACHE_FILENAME): self.create_empty_cache() return True _cache: dict = {} if os.stat(self.CACHE_FILENAME).st_size != 0: with open(self.CACHE_FILENAME, "r") as f: try: _cache = json.load(f) # Convert back all sets that were serialized as lists for attr in self.attributes: if type(attr.default) is set and attr.name in _cache: _cache[attr.name] = set(_cache[attr.name]) or set() except Exception as e: raise click.ClickException( f"Parsing error while reading {self.CACHE_FILENAME}:\n{str(e)}" ) self.update_cache(**_cache) return True def update_cache(self, **kwargs: Any) -> None: for key, item in kwargs.items(): if key in self.get_attributes_keys(): if isinstance(item, list): getattr(self, key).update(item) else: setattr(self, key, item) else: click.echo("Unrecognized key in cache: {}".format(key)) def to_dict(self) -> Dict[str, Any]: _cache = {key: getattr(self, key) for key in self.get_attributes_keys()} # Convert all sets into list so they can be json serialized for key in self.get_attributes_keys(): value = _cache[key] if type(value) is set: _cache[key] = list(value) return _cache def save(self) -> bool: if not os.path.isfile(self.CACHE_FILENAME): return False with open(self.CACHE_FILENAME, "w") as f: try: json.dump(self.to_dict(), f) except Exception as e: raise click.ClickException( f"Error while saving cache in {self.CACHE_FILENAME}:\n{str(e)}" ) return True def purge(self) -> None: for attr in self.attributes: # Deep copy to avoid mutating the default value default = copy.copy(attr.default) setattr(self, attr.name, default) def add_found_secret(self, hash: str) -> None: self.last_found_secrets.add(hash) def add_found_policy_break(self, policy_break: PolicyBreak) -> None: if policy_break.policy.lower() == "secrets detection": for match in policy_break.matches: self.add_found_secret(match.match)

33.240602

87

0.577358

1,075

8,842

4.55907

0.194419

0.019588

0.027749

0.014691

0.37727

0.345032

0.312385

0.247705

0.23383

0

0.001821

0.316784

8,842

265

88

33.366038

0.809469

0.072721

0

0.321782

0

0.085802

0.022618

0

1

0.108911

false

0.004951

0.049505

0.019802

0.336634

0

null

0

null

0

1

0

2cad9f866ea7aa26c12ef287f5ee514f9321fee4

1,444

py

Python

pynetest/lib/pyne_test_blocks.py

Avvir/pyne

864885a8fb632b72c00af164f150b1daa38a346f

[ "MIT" ]

4

2018-08-10T20:05:10.000Z

2019-07-24T15:29:32.000Z

pynetest/lib/pyne_test_blocks.py

Avvir/pyne

864885a8fb632b72c00af164f150b1daa38a346f

[ "MIT" ]

6

2018-09-25T20:15:51.000Z

2021-12-22T17:09:52.000Z

pynetest/lib/pyne_test_blocks.py

Avvir/pyne

864885a8fb632b72c00af164f150b1daa38a346f

[ "MIT" ]

null

class BehaviorBlock: def __init__(self, parent, method, description): self.method = method self.parent = parent self.description = description class Context(object): def __init__(self, parent): if parent is not None: for attr in dir(parent.context): if not hasattr(self, attr): setattr(self, attr, getattr(parent.context, attr)) class DescribeBlock(BehaviorBlock): def __init__(self, parent, context_description, method, pending=False, focused=False, has_focused_descendants=False): super().__init__(parent, method, context_description) self.after_each_blocks = [] self.describe_blocks = [] self.before_each_blocks = [] self.it_blocks = [] self.context = Context(parent) self.pending = pending self.has_focused_descendants = has_focused_descendants self.focused = focused class ItBlock(BehaviorBlock): def __init__(self, parent, description, method, pending=False, focused=False): super().__init__(parent, method, description) self.pending = pending self.focused = focused class BeforeEachBlock(BehaviorBlock): def __init__(self, parent, method): super().__init__(parent, method, "@before_each") class AfterEachBlock(BehaviorBlock): def __init__(self, parent, method): super().__init__(parent, method, "@after_each")

32.088889

121

0.665512

154

1,444

5.876623

0.24026

0.077348

0.072928

0.112707

0.374586

0.256354

0.125967

0

0.234072

1,444

44

122

32.818182

0.818264

0

0.181818

0

0.015928

0

1

0.181818

false

0

0.363636

0

null

0

null

0

1

0

2cae6969a37d3bd9a688ae9ce4914b584b626699

1,166

py

Python

code/Metricsource.py

t1191578/moniteredit

48465d7cbee2452392720a26320d8753f8807bc9

[ "Apache-2.0" ]

null

code/Metricsource.py

t1191578/moniteredit

48465d7cbee2452392720a26320d8753f8807bc9

[ "Apache-2.0" ]

null

code/Metricsource.py

t1191578/moniteredit

48465d7cbee2452392720a26320d8753f8807bc9

[ "Apache-2.0" ]

null

import requests from multipledispatch import dispatch class Source: def __init__(self,url,query="query?query="): self.url = url self.query= query def url(self): #form url pass @dispatch(str) def inputoutput(self, metricreq): Aurl = self.url+self.query+metricreq print(Aurl) resp = requests.get(Aurl) if resp.status_code != 200: # This means something went wrong. raise ApiError('GET /tasks/ {}'.format(resp.status_code)) val= resp.json() cluster = val['data']['result'] print (cluster) return cluster @dispatch(str,str) def inputoutput(self, name, metricreq): Aurl = self.url + self.query + metricreq+'{job="'+name+'"}' resp = requests.get(Aurl) if resp.status_code != 200: # This means something went wrong. raise ApiError('GET /tasks/ {}'.format(resp.status_code)) val = resp.json() cluster = val['data']['result'] return cluster uri="http://35.154.106.147:9090/api/v1/" query= "query?query=" val=Source(uri) val.inputoutput( "go_info")

29.897436

69

0.587479

140

1,166

4.828571

0.378571

0.073965

0.08284

0.06213

0.517751

0.405325

0

0.026128

0.277873

1,166

39

70

29.897436

0.776722

0.063465

0

0.375

0

0.111009

0

1

0.125

false

0.03125

0.0625

0

0.28125

0.0625

0

null

0

null

0

1

0

2cb1bb53ea364d5eed2d8ae779c2ec9f50b57788

966

py

Python

mygrations/formats/mysql/file_reader/parsers/index_primary.py

cmancone/mygrations

30d1d568ca7d6c38dbc5211834dd2d04c0bcf078

[ "MIT" ]

10

2018-04-09T08:39:42.000Z

2022-03-14T15:36:05.000Z

mygrations/formats/mysql/file_reader/parsers/index_primary.py

cmancone/mygrations

30d1d568ca7d6c38dbc5211834dd2d04c0bcf078

[ "MIT" ]

14

2018-05-02T11:14:08.000Z

2022-01-15T18:48:54.000Z

mygrations/formats/mysql/file_reader/parsers/index_primary.py

cmancone/mygrations

30d1d568ca7d6c38dbc5211834dd2d04c0bcf078

[ "MIT" ]

5

2018-07-18T02:20:48.000Z

2022-02-19T09:32:07.000Z

from mygrations.core.parse.parser import parser from mygrations.formats.mysql.definitions.index import index class index_primary(parser, index): _index_type = 'primary' has_comma = False # PRIMARY KEY (`id`), rules = [{ 'type': 'literal', 'value': 'PRIMARY KEY' }, { 'type': 'literal', 'value': '(' }, { 'type': 'delimited', 'name': 'columns', 'separator': ',', 'quote': '`' }, { 'type': 'literal', 'value': ')' }, { 'type': 'literal', 'value': ',', 'optional': True, 'name': 'ending_comma' }] def __init__(self, rules=[]): super().__init__(rules) self._errors = [] self._warnings = [] self._columns = [] def process(self): self._name = '' self._columns = self._values['columns'] self.has_comma = True if 'ending_comma' in self._values else False

22.465116

74

0.509317

90

966

5.222222

0.444444

0.093617

0.13617

0.085106

0

0.321946

966

42

75

23

0.717557

0.019669

0

0.235294

0

0.177778

0

1

0.058824

false

0

0.058824

0

0.235294

0

null

0

null

0

1

0

2cb2f10583b45235d86386a62278891da1c81b82

445

py

Python

cryptolens/exchanges/poloniex.py

hkilian/cryptolens

22ad4257fb9316e57b2402a83dbbfd583493fb39

[ "MIT" ]

null

cryptolens/exchanges/poloniex.py

hkilian/cryptolens

22ad4257fb9316e57b2402a83dbbfd583493fb39

[ "MIT" ]

1

2021-06-01T21:50:08.000Z

cryptolens/exchanges/poloniex.py

hkilian/cryptolens

22ad4257fb9316e57b2402a83dbbfd583493fb39

[ "MIT" ]

1

2017-11-02T05:08:57.000Z

import json import requests from .exchange import Exchange class Poloniex(Exchange): def __init__(self): Exchange.__init__(self, "GDAX") def PullData(self): url = "https://poloniex.com/public?command=returnTicker&currencyPair=USDT_BTC" response = requests.get(url) ticker = response.json()['USDT_BTC'] data = {} data['price'] = ticker['last'] data['percentChange'] = 0 data['volume'] = ticker['baseVolume'] return data

21.190476

80

0.705618

54

445

5.62963

0.592593

0.052632

0

0.002632

0.146067

445

20

81

22.25

0.797368

0

0.269663

0

1

0.133333

false

0

0.2

0

0.466667

0

null

0

null

0

1

0

2cb370dba58960e4d34825e77ae18854da4dd923

354

py

Python

exercises/exc_04_02.py

rklymentiev/py-for-neuro

6bb163347483642c79eac429e5a9289edff7ce09

[ "MIT" ]

7

2021-04-28T13:12:16.000Z

2022-01-15T00:21:11.000Z

exercises/exc_04_02.py

rklymentiev/py-for-neuro

6bb163347483642c79eac429e5a9289edff7ce09

[ "MIT" ]

2

2021-04-02T18:42:55.000Z

2021-05-20T08:43:06.000Z

exercises/exc_04_02.py

rklymentiev/py-for-neuro

6bb163347483642c79eac429e5a9289edff7ce09

[ "MIT" ]

2

2021-07-04T22:57:29.000Z

2021-07-29T19:28:43.000Z

import pandas as ___ import seaborn as ___ import matplotlib.pyplot as ___ # read in the data ___ # select the columns with 'mean' in the name selected_columns = list(___) # find the correlations corr_matrix = ___ # make a plot plt.___(figsize=(8,7), facecolor='white') sns.___(data=___, cmap="YlGnBu") plt.___("Correlation Among Variables") ___.___()

20.823529

44

0.748588

47

354

4.829787

0.765957

0.070485

0

0.006601

0.144068

354

16

45

22.125

0.742574

0.262712

0

0.148438

0

1

0

false

0

0.3

0

0.3

0

null

0

null

0

1

0

2cb530e8e30ba2311d864307233f32b3ff43ff4d

3,178

py

Python

tests/lexer_test.py

tykazzz/pseudo

7414ab0f14142b9ed704d03af0223cf847bf8861

[ "MIT" ]

null

tests/lexer_test.py

tykazzz/pseudo

7414ab0f14142b9ed704d03af0223cf847bf8861

[ "MIT" ]

null

tests/lexer_test.py

tykazzz/pseudo

7414ab0f14142b9ed704d03af0223cf847bf8861

[ "MIT" ]

null

"""This module contains unit tests for lexer module.""" import pytest import pseudo from pseudo.pseudo_types import Operation, Operator, Int __author__ = "Patryk Niedźwiedziński" @pytest.fixture def lexer(): """Returns lexer object.""" lex = pseudo.lexer.Lexer("") return lex def test_is_keyword(lexer): """Check Lexer.is_keyword""" if not ( lexer.is_keyword("pisz") is True and lexer.is_keyword("oo") is False and lexer.is_keyword("koniec") is True ): raise AssertionError def test_is_alphabet(lexer): """Check Lexer.is_alphabet""" if not ( lexer.is_alphabet("a") is True and lexer.is_alphabet("A") is True and lexer.is_alphabet("1") is False and lexer.is_alphabet("*") is False and lexer.is_alphabet(1) is False ): raise AssertionError def test_is_digit(lexer): """Check Lexer.is_digit""" if not ( lexer.is_digit("1") is True and lexer.is_digit("a") is False and lexer.is_digit('"') is False ): raise AssertionError def test_is_operator(lexer): """Checks Lexer.is_operator""" if not ( lexer.is_operator("*") is True and lexer.is_operator("div") is True and lexer.is_operator(":=") is False and lexer.is_operator("pisz") is False ): raise AssertionError def test_is_not_keyword_end(lexer): """Checks Lexer.is_not_keyword_end""" if not ( lexer.is_not_keyword_end("a") is True and lexer.is_not_keyword_end("+") is False and lexer.is_not_keyword_end("!") is False ): raise AssertionError def test_update_args(lexer): """Checks Lexer.update_args""" if not ( lexer.update_args([Int(2), Operator("+"), Int(2)], 1) == [Operation(Operator("+"), Int(2), Int(2))] ): raise AssertionError def test_read_number(lexer): """Checks Lexer.read_number""" lexer.i = pseudo.stream.Stream("123") if 123 != lexer.read_number().value: raise AssertionError lexer.i = pseudo.stream.Stream("abc") if lexer.read_number() is not None: raise AssertionError def test_read_string(lexer): """Checks Lexer.read_string""" lexer.i = pseudo.stream.Stream('"abc"') if "abc" != lexer.read_string().value: raise AssertionError def test_keyword(lexer): """Checks Lexer.read_keyword""" lexer.i = pseudo.stream.Stream("pisz x") if "pisz" != lexer.read_keyword(): raise AssertionError def test_read_args(lexer): """Checks Lexer.read_args""" lexer.i = pseudo.stream.Stream(" 12") if 12 != lexer.read_args().value: raise AssertionError lexer.i = pseudo.stream.Stream("2+2*2") if 6 != lexer.read_args().eval(): raise AssertionError lexer.i = pseudo.stream.Stream("(2+2)*2") if 8 != lexer.read_args().eval(): raise AssertionError def test_read_expression(lexer): """Checks Lexer.read_expression""" if ( lexer.read_expression( [Int(2), Operator("+"), Int(2), Operator("*"), Int(2)] ).eval() != 6 ): raise AssertionError

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2cb5f4cd3fc9c93d71c637d25d6816c5fcb669d6

19,227

py

Python

app/helpers.py

zhuding/javatools

4b3a57b2ddfec36cae4af08ac5c3d71cfe879f63

[ "Apache-2.0" ]

null

app/helpers.py

zhuding/javatools

4b3a57b2ddfec36cae4af08ac5c3d71cfe879f63

[ "Apache-2.0" ]

null

app/helpers.py

zhuding/javatools

4b3a57b2ddfec36cae4af08ac5c3d71cfe879f63

[ "Apache-2.0" ]

null

# coding=utf8 from app import db def get_databases(): sql = "SHOW DATABASES" result = db.engine.execute(sql) dbs = [] for row in result: dbs.append(row['Database']) return dbs def get_tables(dbname): sql = "SELECT TABLE_NAME AS tableName FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA='" + dbname + "'" result = db.engine.execute(sql) tables = [] for row in result: tables.append(row['tableName']) return tables def get_table_field(tablename): sql = "SHOW FULL COLUMNS FROM " + tablename results = db.engine.execute(sql) fields = [] for result in results: fields.append({'field': result['Field'], 'type': result['Type'], \ 'isNull': result['Null'], 'key': result['Key'], \ 'defaultValue': result['Default'], 'extra': result['Extra'], 'comment': result['Comment']}) return fields def get_select_field(tableName, fields): sql = "SELECT " sqlField = "" for field in fields: attr = convertField(field['field']) if (sqlField == ''): sqlField += field['field'] else: sqlField += ',' + field['field'] sql += sqlField + ' FROM ' + tableName return sql def get_select_field_AS_Bean(tableName, fields): sql = "SELECT " sqlField = "" for field in fields: attr = convertField(field['field']) if (sqlField == ''): sqlField += field['field'] + ' AS ' + attr else: sqlField += ', ' + field['field'] + ' AS ' + attr sql += sqlField + ' FROM ' + tableName return sql def get_insert_sql(objectName, tableName, fields): sql = "INSERT INTO " + tableName + " " sqlField = '' sqlValue = '' for field in fields: if (field['extra'] != 'auto_increment'): if (sqlField == ''): sqlField += field['field'] else: sqlField += ',' + field['field'] sql += '(' + sqlField + ') VALUES ' for field in fields: if (field['extra'] != 'auto_increment'): attr = convertField(field['field']) if (sqlValue == ''): sqlValue = '#{' + attr + '}' else: sqlValue += ',#{' + attr + '}' sql += '(' + sqlValue + ') ' return sql def get_update_sql(objectName, tableName, fields): sql = "UPDATE " + tableName + " SET " sqlField = "" where = "" for field in fields: attr = convertField(field['field']) if (field['extra'] != 'auto_increment'): if (sqlField == ''): sqlField += field['field'] + '=#{' + attr + '}' else: sqlField += ', ' + field['field'] + '=#{' + attr + '}' if (field['extra'] == 'auto_increment'): where = ' WHERE ' + field['field'] + '=#{' + attr + '}' sql += sqlField + where return sql def get_update_sql_v2(tableName, fields): sql = "UPDATE " + tableName + " " sql += "\t\t<set> " for field in fields: attr = convertField(field['field']) if not (field['extra'] == 'auto_increment'): sql += "\t\t\t<if test=\"" + attr + "!=null\"> " + field['field'] + "=#{" + attr + "} " \ "</if> " sql += "\t\t</set> " sql += "\t\tWHERE id=#{id}" return sql def get_delete_sql(objectName, tableName, fields): sql = "DELETE FROM " + tableName where = "" for field in fields: attr = convertField(field['field']) if (field['extra'] == 'auto_increment'): where = ' WHERE ' + field['field'] + '=#{' + attr + '}' sql += where return sql def get_select_sql(tableName, fields): sql = "SELECT " sqlField = "" where = "" for field in fields: attr = convertField(field['field']) if (sqlField == ''): sqlField += field['field'] + ' AS ' + attr else: sqlField += ',' + field['field'] + ' AS ' + attr if (field['extra'] == 'auto_increment'): where = ' WHERE ' + field['field'] + '=#{' + attr + '}' sql += sqlField + ' FROM ' + tableName + where return sql def get_simple_select_sql(tableName, fields): sql = "SELECT " sqlField = "" where = "" for field in fields: attr = convertField(field['field']) if (sqlField == ''): sqlField += field['field'] else: sqlField += ',' + field['field'] if (field['extra'] == 'auto_increment'): where = ' WHERE ' + field['field'] + '=#{' + attr + '}' sql += sqlField + ' FROM ' + tableName + where return sql def get_java_code(objectName, fields): code = "public class " + titleFirst(objectName) + " { " for field in fields: attr = convertField(field['field']) code += "\t" + '// ' + field['comment'] + '' + " " codeType = field['type'] if codeType.find('int')==0: codeType = 'Integer' elif codeType.find('tinyint')==0: codeType = 'Integer' elif codeType.find('bigint')==0: codeType = 'Long' elif codeType.find('timestamp')==0: codeType = 'LocalDateTime' elif codeType.find('datetime')==0: codeType = 'LocalDateTime' elif codeType.find('date')==0: codeType = 'LocalDate' elif codeType.find('char')==0: codeType = 'String' elif codeType.find('varchar')==0: codeType = 'String' elif codeType.find('text')>=0: codeType = 'String' elif codeType.find('blob')>=0: codeType = 'String' else: codeType = 'String' code += "\t" + 'private ' + codeType + ' ' + attr + "; " code += '}' return code def get_mybatis_xml(objectName, tableName, fields): select_fileds = get_select_field(tableName, fields) simple_select_sql = get_simple_select_sql(tableName, fields) insert_sql = get_insert_sql(objectName, tableName, fields) update_sql = get_update_sql(objectName, tableName, fields) #update_sql_v2 = get_update_sql_v2(tableName, fields) className = titleFirst(objectName) code = "" code += "<?xml version=\"1.0\" encoding=\"UTF-8\" ?> " code += "<!DOCTYPE mapper PUBLIC \"-//mybatis.org//DTD Mapper 3.0//EN\" " \ "\"http://mybatis.org/dtd/mybatis-3-mapper.dtd\"> " code += "<mapper namespace=\"" + className + "Mapper\"> " code += "\t<resultMap id=\"" + objectName + "Map\" type=\"" + className + "\"> " for field in fields: attr = convertField(field['field']) code += "\t\t<id column=\"" + field['field'] + "\" property=\"" + attr + "\" /> " code += "\t</resultMap> " # Select fields code += "\t<sql id=\"selectFields\"> " code += "\t\t" + select_fileds + " " code += "\t</sql> " # Select by id SQL code += "\t<select id=\"get" + className + "ById\" resultMap=\"" + objectName + "Map\"> " code += "\t\t<include refid=\"selectFields\" /> " code += "\t\tWHERE id=#{id} " code += "\t</select> " # Select all SQL code += "\t<select id=\"get" + className + "List\" resultMap=\"" + objectName + "Map\"> " code += "\t\t<include refid=\"selectFields\" /> " code += "\t\tORDER BY id DESC " code += "\t</select> " # Create SQL code += "\t<insert id=\"create" + className + "\" useGeneratedKeys=\"true\" keyProperty=\"id\" " \ "parameterType=\"" + className + "\"> " code += "\t\t" + insert_sql + " " code += "\t</insert> " # Update SQL code += "\t<update id=\"update" + className + "\" parameterType=\"" + className + "\"> " code += "\t\t" + update_sql + " " code += "\t</update> " # Update SQL V2 #code += "\t<update id=\"update" + className + "\" parameterType=\"" + className + "\"> " #code += "\t\t" + update_sql_v2 + " " #code += "\t</update> " # Delete SQL code += "\t<delete id=\"delete" + className + "\" parameterType=\"int\"> " code += "\t\tDELETE FROM " + tableName + " WHERE id=#{id} " code += "\t</delete> " code += "</mapper> " return code def getJavaMapper(objectName, tableName, fields): className = titleFirst(objectName) select_fileds = get_select_field_AS_Bean(tableName, fields) simple_select_sql = get_simple_select_sql(tableName, fields) insert_sql = get_insert_sql(objectName, tableName, fields) update_sql = get_update_sql(objectName, tableName, fields) code = "public interface " + className + "Mapper { " code += "\t" + 'String selectFields = " ' + select_fileds + ' "; ' code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param ' + objectName + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t" + '@Options(useGeneratedKeys = true, keyProperty = "id")' + " " code += "\t" + '@Insert("' + insert_sql + '")' + " " code += "\t"+ 'int create' + className + '(' + className + ' '+objectName+');' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param ' + objectName + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t" + '@Update("' + update_sql + '")' + " " code += "\t"+ 'int update' + className + '(' + className + ' '+objectName+');' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param id' + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t" + '@Delete("DELETE FROM ' + tableName + ' WHERE id=#{id}")' + " " code += "\t"+ 'int delete' + className + '(@Param("id") int id);' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param id' + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t" + '@Select(selectFields + " WHERE id=#{id} ")' + " " code += "\t"+ '' + className + ' get' + className + 'ById(@Param("id") int id);' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t" + '@Select(selectFields + " ORDER BY id DESC ")' + " " code += "\t"+ 'List<' + className + '> get' + className + 'List();' + " " code += '}' return code def getJavaService(objectName): className = titleFirst(objectName) code = "public interface " + className + "Service { " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param ' + objectName + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t"+ 'int create' + className + '(' + className + ' '+objectName+');' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param ' + objectName + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t"+ 'int update' + className + '(' + className + ' '+objectName+');' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param '+objectName+'Id' + " " code += "\t" + ' * @return int' + " " code += "\t" + ' */' + " " code += "\t"+ 'int delete' + className + '(int '+objectName+'Id);' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @param '+objectName+'Id' + " " code += "\t" + ' * @return ' + className + " " code += "\t" + ' */' + " " code += "\t"+ '' + className + ' get' + className + 'ById(int '+objectName+'Id);' + " " code += " " code += "\t" + '/**' + " " code += "\t" + ' * <pre></pre>' + " " code += "\t" + ' *' + " " code += "\t" + ' * @return List<' + className + '>'+" " code += "\t" + ' */' + " " code += "\t"+ 'List<' + className + '> get' + className + 'List();' + " " code += '}' return code def get_test_case(objectName): className = titleFirst(objectName) code = "public class " + className + "ServiceTest { " code += "\t" + 'private static final Logger logger = LoggerFactory.getLogger(' + className + 'ServiceTest.class);' + " " code += "\t" + 'private static ' + className + ' ' + objectName + ';' + " " code += "\t" + 'private static ' + className + 'ServiceImpl ' + objectName + 'ServiceImpl;' + " " code += "\t" + 'private static ' + className + 'Mapper ' + objectName + 'Mapper;' + " " code += "\t" + '@SuppressWarnings("resource")' + " " code += "\t" + '@BeforeClass' + " " code += "\t" + 'public static void init() {' + " " code += "\t\t" + 'ApplicationContext context = new ClassPathXmlApplicationContext("classpath*:applicationContext-test.xml");' + " " code += "\t\t" + objectName + 'Mapper = (' + className + 'Mapper) context.getBean("' + objectName + 'Mapper");' + " " code += "\t\t" + objectName + 'ServiceImpl = (' + className + 'ServiceImpl) context.getBean("' + objectName + 'ServiceImpl");' + " " code += "\t\t" + 'ReflectionTestUtils.setField(' + objectName + 'ServiceImpl, "' + objectName + 'Mapper", ' + objectName + 'Mapper);' + " " code += "\t\t" + objectName + ' = new ' + className + '();' + " " code += "\t" + '}' + " " code += " " code += '}' return code def get_java_codeStr(objectName, fields): code = "@Data\r" code += "public class " + titleFirst(objectName) + " {\r" for field in fields: attr = convertField(field['field']) code += " " + '// ' + field['comment'] + '' + "\r" codeType = field['type'] if codeType.find('int')==0: codeType = 'Integer' elif codeType.find('tinyint')==0: codeType = 'Integer' elif codeType.find('bigint')==0: codeType = 'Long' elif codeType.find('timestamp')==0: codeType = 'LocalDateTime' elif codeType.find('datetime')==0: codeType = 'LocalDateTime' elif codeType.find('date')==0: codeType = 'LocalDate' elif codeType.find('char')==0: codeType = 'String' elif codeType.find('varchar')==0: codeType = 'String' elif codeType.find('text')>=0: codeType = 'String' elif codeType.find('blob')>=0: codeType = 'String' else: codeType = 'String' code += " " + 'private ' + codeType + ' ' + attr + ";\r" code += '}' return code def getJavaMapperStr(objectName, tableName, fields): className = titleFirst(objectName) select_fileds = get_select_field_AS_Bean(tableName, fields) simple_select_sql = get_simple_select_sql(tableName, fields) insert_sql = get_insert_sql(objectName, tableName, fields) update_sql = get_update_sql(objectName, tableName, fields) code = "public interface " + className + "Mapper {\r" code += " " + 'String selectFields = " ' + select_fileds + ' ";\r' code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param ' + objectName + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " " + '@Options(useGeneratedKeys = true, keyProperty = "id")' + "\r" code += " " + '@Insert("' + insert_sql + '")' + "\r" code += " " + 'int create' + className + '(' + className + ' ' + objectName + ');' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param ' + objectName + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " " + '@Update("' + update_sql + '")' + "\r" code += " " + 'int update' + className + '(' + className + ' ' + objectName + ');' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param id' + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " " + '@Delete("DELETE FROM ' + tableName + ' WHERE id=#{id}")' + "\r" code += " " + 'int delete' + className + '(@Param("id") int id);' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param id' + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " " + '@Select(selectFields + " WHERE id=#{id} ")' + "\r" code += " " + '' + className + ' get' + className + 'ById(@Param("id") int id);' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " " + '@Select(selectFields + " ORDER BY id DESC ")' + "\r" code += " " + 'List<' + className + '> get' + className + 'List();' + "\r" code += '}' return code def getJavaServiceStr(objectName): className = titleFirst(objectName) code = "public interface " + className + "Service {\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param ' + objectName + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " "+ 'int create' + className + '(' + className + ' '+objectName+');' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param ' + objectName + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " "+ 'int update' + className + '(' + className + ' '+objectName+');' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param '+objectName+'Id' + "\r" code += " " + ' * @return int' + "\r" code += " " + ' */' + "\r" code += " "+ 'int delete' + className + '(int '+objectName+'Id);' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @param '+objectName+'Id' + "\r" code += " " + ' * @return ' + className + "\r" code += " " + ' */' + "\r" code += " "+ '' + className + ' get' + className + 'ById(int '+objectName+'Id);' + "\r" code += "\r" code += " " + '/**' + "\r" code += " " + ' * <pre></pre>' + "\r" code += " " + ' *' + "\r" code += " " + ' * @return List<' + className + '>'+"\r" code += " " + ' */' + "\r" code += " "+ 'List<' + className + '> get' + className + 'List();' + "\r" code += '}' return code def convertField(field): fieldList = field.split("_") attr = '' for f in fieldList: if (attr == ''): attr = f else: attr += f.title() return attr def titleFirst(str): if len(str)<=0: return return str[0:1].title() + str[1:] def lowerFirst(str): if len(str)<=0: return return str[0:1].lower() + str[1:] def debug_print(msg): print("\n##########################################################################################################") print(msg) print("\n##########################################################################################################")

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null

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0

2cb6f59ec4572da89ea0442177be6d5a3a77df0f

1,931

py

Python

pythonforandroid/recipes/numpy/__init__.py

wo01/python-for-android

df0866d95c9c508299a6f948302454beb971e3ac

[ "MIT" ]

2

2019-01-07T12:13:25.000Z

2019-10-19T09:53:50.000Z

pythonforandroid/recipes/numpy/__init__.py

tangingw/python-for-android

7c125ad96f71a950ed272a116a9446c6f60e87a9

[ "MIT" ]

null

pythonforandroid/recipes/numpy/__init__.py

tangingw/python-for-android

7c125ad96f71a950ed272a116a9446c6f60e87a9

[ "MIT" ]

3

2018-12-13T09:57:33.000Z

2019-01-09T15:36:46.000Z

from pythonforandroid.recipe import CompiledComponentsPythonRecipe from pythonforandroid.toolchain import warning from os.path import join class NumpyRecipe(CompiledComponentsPythonRecipe): version = '1.15.1' url = 'https://pypi.python.org/packages/source/n/numpy/numpy-{version}.zip' site_packages_name = 'numpy' depends = [('python2', 'python3crystax')] patches = [ join('patches', 'fix-numpy.patch'), join('patches', 'prevent_libs_check.patch'), join('patches', 'ar.patch'), join('patches', 'lib.patch'), join('patches', 'python2-fixes.patch') ] def get_recipe_env(self, arch): env = super(NumpyRecipe, self).get_recipe_env(arch) flags = " -L{} --sysroot={}".format( join(self.ctx.ndk_platform, 'usr', 'lib'), self.ctx.ndk_platform ) if self.ctx.ndk == 'crystax': py_ver = self.ctx.python_recipe.version[0:3] src_dir = join(self.ctx.ndk_dir, 'sources') py_inc_dir = join(src_dir, 'python', py_ver, 'include', 'python') py_lib_dir = join(src_dir, 'python', py_ver, 'libs', arch.arch) cry_inc_dir = join(src_dir, 'crystax', 'include') cry_lib_dir = join(src_dir, 'crystax', 'libs', arch.arch) flags += ' -I{}'.format(py_inc_dir) flags += ' -L{} -lpython{}m'.format(py_lib_dir, py_ver) flags += " -I{}".format(cry_inc_dir) flags += " -L{}".format(cry_lib_dir) if flags not in env['CC']: env['CC'] += flags if flags not in env['LD']: env['LD'] += flags + ' -shared' return env def prebuild_arch(self, arch): super(NumpyRecipe, self).prebuild_arch(arch) warning('Numpy is built assuming the archiver name is ' 'arm-linux-androideabi-ar, which may not always be true!') recipe = NumpyRecipe()

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1,931

55

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0.025375

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1

0.047619

false

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0.071429

0

0.285714

0

null

0

null

0

1

0

2cba683ad98eb61e03c5f63735dc9df320aadbb6

6,136

py

Python

webdriverwrapper/exceptions.py

jayeshgupta91/python-webdriverwrapper

9b2c32bbf06ada669feb62ef17fd23365a14ad14

[ "MIT" ]

null

webdriverwrapper/exceptions.py

jayeshgupta91/python-webdriverwrapper

9b2c32bbf06ada669feb62ef17fd23365a14ad14

[ "MIT" ]

null

webdriverwrapper/exceptions.py

jayeshgupta91/python-webdriverwrapper

9b2c32bbf06ada669feb62ef17fd23365a14ad14

[ "MIT" ]

null

# pylint: disable=wildcard-import,unused-wildcard-import from selenium.common.exceptions import * try: from Levenshtein import distance as levenshteinDistance except ImportError: levenshteinDistance = None def _create_exception_msg( id_=None, class_name=None, name=None, tag_name=None, parent_id=None, parent_class_name=None, parent_name=None, parent_tag_name=None, text=None, xpath=None, css_selector=None, url=None, driver=None, ): elm_text = _create_exception_msg_tag( id_, class_name, name, tag_name, parent_id, parent_class_name, parent_name, parent_tag_name, text, xpath, css_selector, ) msg = 'No element {} found'.format(elm_text) if url: msg += ' at {}'.format(url) suggest = _get_suggestion(driver, id_, class_name, tag_name) if suggest: msg += ' {}'.format(suggest) return msg def _create_exception_msg_tag( id_=None, class_name=None, name=None, tag_name=None, parent_id=None, parent_class_name=None, parent_name=None, parent_tag_name=None, text=None, xpath=None, css_selector=None, ): elm_text = _create_exception_msg_tag_element(id_, class_name, name, tag_name, text, xpath, css_selector) parent_text = _create_exception_msg_tag_element(parent_id, parent_class_name, parent_name, parent_tag_name) if parent_text: return '{} in parent element {}'.format(elm_text, parent_text) return elm_text def _create_exception_msg_tag_element(id_=None, class_name=None, name=None, tag_name=None, text=None, xpath=None, css_selector=None): if text: return '"{}"'.format(text) if xpath: return xpath if css_selector: return css_selector if id_ or class_name or tag_name or name: msg = '<{}'.format(tag_name or '*') if id_: msg += ' id={}'.format(id_) if class_name: msg += ' class={}'.format(class_name) if name: msg += ' name={}'.format(name) msg += '>' return msg return '' def _get_suggestion(driver, id_=None, class_name=None, name=None): if not driver or not levenshteinDistance: return '' if id_: suggest_by = 'id' value = id_ elif class_name: suggest_by = 'class' value = class_name elif name: suggest_by = 'name' value = name else: return '' # Can't be used xpath because it can return only element and then # get attribute for every element is very slow. So by JS it's done # by only one Selenium call. items = driver.execute_script('return Array.prototype.map.call(document.querySelectorAll("[id]"), function(el) {return el.id})') if not items: return '' suggestion = _find_best_suggestion(value, set(items)) if not suggestion: return '' return 'did you mean {}={}?'.format(suggest_by, suggestion) def _find_best_suggestion(value, items): if not levenshteinDistance: return None best = None min_distance = len(value) + 10 # So it can find distance between btn and btn-default for example. for item in items: distance = levenshteinDistance(value, item) if 0 < distance < min_distance: min_distance = distance best = item return best class WebdriverWrapperException(Exception): """ Base exception of WebDriver Wrapper. """ def __init__(self, url, msg): super().__init__() self.url = url self.msg = msg def __str__(self): return '{} [at {}]'.format(self.msg, self.url) def __repr__(self): return self.__str__() class ErrorPageException(WebdriverWrapperException): """ Exception raised when there is some unexpected error page. Like page 404, 500 and so on. """ def __init__(self, url, error_page, expected_error_page, allowed_error_pages, traceback=None): if expected_error_page: msg = 'Expected error page "{}", but found "{}" instead.'.format(expected_error_page, error_page) else: msg = 'Unexpected error page "{}".'.format(error_page) if allowed_error_pages: msg += ' Allowed error pages: "{}"'.format(allowed_error_pages) if traceback: msg += '\n\nTraceback:\n{}'.format(traceback) super(ErrorPageException, self).__init__(url, msg) class ErrorMessagesException(WebdriverWrapperException): """ Exception raised when there is some unexpected error message. Like "some field is mandatory", "wrong e-mail" and so on. """ def __init__(self, url, error_messages, expected_error_messages, allowed_error_messages): if expected_error_messages: msg = 'Expected error messages "{}", but found "{}" instead.'.format(expected_error_messages, error_messages) else: msg = 'Unexpected error messages "{}".'.format(error_messages) if allowed_error_messages: msg += ' Allowed error messages: "{}"'.format(allowed_error_messages) super(ErrorMessagesException, self).__init__(url, msg) class JSErrorsException(WebdriverWrapperException): """ Exception raised when there is some JS error. See :py:meth:`get_js_errors <webdriverwrapper.errors.WebdriverWrapperErrorMixin.get_js_errors>` for more information. """ def __init__(self, url, js_errors): msg = 'Unexpected JavaScript errors "{}".'.format(js_errors) super(JSErrorsException, self).__init__(url, msg) class InfoMessagesException(WebdriverWrapperException): """ Exception raised when there is missing some expected info message. Like "sucessfully saved" and so on. """ def __init__(self, url, info_messages, expected_info_messages, allowed_info_messages): msg = 'Expected info messages "{}", but found "{}" instead.'.format(expected_info_messages, info_messages) if allowed_info_messages: msg += ' Allowed info messages: "{}"'.format(allowed_info_messages) super(InfoMessagesException, self).__init__(url, msg)

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133

0.661506

750

6,136

5.125333

0.198667

0.03538

0.028096

0.027315

0.306972

0.28512

0.203174

0.16077

0.147242

0.110822

0

0.001917

0.234681

6,136

184

134

33.347826

0.816652

0.128748

0

0.147541

0

0.008197

0.107701

0.011247

0

1

0.098361

false

0

0.02459

0.016393

0.303279

0

null

0

null

0

1

0

2cc08333be3174d0b142d7bc58887c3bfc8700a5

6,369

py

Python

app/routes.py

MBkkt/TaskManager

ed4a5cb5bbb93dc3b10d459cf2e37a82be5b8a5e

[ "MIT" ]

null

app/routes.py

MBkkt/TaskManager

ed4a5cb5bbb93dc3b10d459cf2e37a82be5b8a5e

[ "MIT" ]

1

2019-04-30T22:19:15.000Z

2019-04-30T22:20:06.000Z

app/routes.py

MBkkt/Task_Manager

ed4a5cb5bbb93dc3b10d459cf2e37a82be5b8a5e

[ "MIT" ]

null

from functools import wraps from flask import render_template, flash, redirect, url_for, request from flask_login import login_user, logout_user, current_user, login_required from app import app from app.models import User, Task from app.forms import ( LoginForm, RegistrationForm, AddTask, EditTaskForPerformer, EditTaskForOwner, ProfileForm ) def admin_required(func): @wraps(func) def func_new(*args, **kwargs): if current_user.type == 0: return redirect(url_for('index')) return func(*args, **kwargs) return func_new @app.route('/') @app.route('/index') @login_required def index(): stat = current_user.tasks_quantity() return render_template('index.html', title='Main', stat=stat) @app.route('/register', methods=('GET', 'POST')) def register(): if current_user.is_authenticated and current_user.type == 0: return redirect(url_for('index')) form = RegistrationForm() if form.validate_on_submit(): login_user(User.create(source={ 'login': form.login.data, 'email': form.email.data, 'first_name': form.first_name.data, 'last_name': form.last_name.data, 'type': form.type.data, 'password': form.password.data, }), remember=True) next_page = request.args.get('next') or url_for('index') return redirect(next_page) return render_template('register.html', title='Register', form=form) @app.route('/login', methods=('GET', 'POST')) def login(): if current_user.is_authenticated: return redirect(url_for('index')) form = LoginForm() if form.validate_on_submit(): user = User.query.filter_by(login=form.login.data).first() next_page = url_for('login') if user is None: flash('Account does not exist', 'danger') elif not user.check_password(form.password.data): flash('Wrong password', 'danger') else: login_user(user, remember=form.remember_me.data) next_page = request.args.get('next') or url_for('index') return redirect(next_page) return render_template('login.html', title='Log in', form=form) @app.route('/logout') @login_required def logout(): logout_user() return redirect(url_for('login')) @app.route('/tasks') @login_required def tasks(): temp = current_user.tasks tasks_len = temp.count() if temp else 0 return render_template( 'tasks.html', title='Tasks', current_user=current_user, tasks=temp, tasks_len=tasks_len ) @app.route('/assigned_tasks') @login_required @admin_required def assigned_tasks(): return render_template( 'tasks.html', title='Assigned tasks', current_user=current_user, tasks=current_user.assign_tasks.all(), tasks_len=len(current_user.assign_tasks.all()) ) @app.route('/profile/<int:user_id>', methods=('GET', 'POST')) @login_required def profile(user_id): if current_user.id != user_id: return redirect(request.args.get('next') or url_for('index')) user = User.query.filter_by(id=user_id).first() form = ProfileForm() if form.validate_on_submit(): User.edit(user, { 'delete': form.delete.data, 'login': form.login.data, 'email': form.email.data, 'first_name': form.first_name.data, 'last_name': form.last_name.data, 'type': form.type.data, }) if form.delete.data: flash('Profile is deleted', 'primary') else: flash('Profile is edited', 'primary') return redirect(url_for('login')) if request.method == 'GET': form.login.data = user.login form.email.data = user.email form.first_name.data = user.first_name form.last_name.data = user.last_name form.type.data = user.type return render_template( 'profile.html', title='Profile', form=form, current_user=current_user ) def task_for_owner(task_): form = EditTaskForOwner(request.form) form.users_id.choices = [ (user.id, user.login) for user in User.query.all() ] if form.validate_on_submit(): task_.edit(task_, { 'delete': form.delete.data, 'title': form.title.data, 'description': form.description.data, 'status': form.status.data, 'users_id': form.users_id.data, }) flash('Task is edited', 'primary') return redirect(url_for('assigned_tasks')) if request.method == 'GET': form.title.data = task_.title form.description.data = task_.description form.status.data = task_.status form.users_id.data = [user.id for user in task_.users] else: flash('Task does not correct', 'error') return render_template( 'add_task.html', title='Edit task', task=task_, current_user=current_user, form=form ) def task_for_performer(task_): form = EditTaskForPerformer(request.form) if request.method == 'POST' and form.validate_on_submit(): task_.edit_status(form.status.data) flash('Task status is edited', 'primary') return redirect(url_for('tasks')) return render_template( 'add_task.html', title='Edit task', task=task_, current_user=current_user, form=form ) @app.route('/task/<int:task_id>', methods=('GET', 'POST')) @login_required def task(task_id): task_ = Task.query.filter_by(id=task_id).first() if current_user.id == task_.author_id: return task_for_owner(task_) return task_for_performer(task_) @app.route('/add_task', methods=('GET', 'POST')) @login_required @admin_required def add_task(): form = AddTask() form.users_id.choices = [ (user.id, user.login) for user in User.query.all() ] task_ = {'author_id': current_user.id} if form.validate_on_submit(): task_ = Task.create({ 'title': form.title.data, 'description': form.description.data, 'author_id': current_user.id, 'users_id': form.users_id.data, }) flash('Task successfully assigned', 'primary') return render_template( 'add_task.html', title='Add task', form=form, task=task_, current_user=current_user )

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0.04644

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0.469298

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0.185759

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0

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6,369

202

78

31.529703

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0

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0

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0.003454

0

1

0.073864

false

0.017045

0.034091

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0.238636

0

null

0

null

0

1

0

2cc092fe85073efa8f38bdc1b3e3d9c07f22b3d8

4,136

py

Python

project.py

Peter-Sanders/IE-512-Decison-Analysis-Final-Project

868c6bb3843350d943027073cf4b4631d0188de0

[ "Unlicense" ]

1

2019-12-14T03:08:23.000Z

project.py

Peter-Sanders/IE-512-Decison-Analysis-Final-Project

868c6bb3843350d943027073cf4b4631d0188de0

[ "Unlicense" ]

null

project.py

Peter-Sanders/IE-512-Decison-Analysis-Final-Project

868c6bb3843350d943027073cf4b4631d0188de0

[ "Unlicense" ]

null

# coding: utf-8 # # Stock Choice Decision Analysis # Code written and commentated by Peter Sanders # ### Load Relevant Packages # In[1]: from pandas_datareader import data import matplotlib.pyplot as plt import pandas as pd import seaborn as sns from datetime import datetime import numpy as np import math from scipy.special import expit sns.set(style='whitegrid', context='talk') # ### Define the Softmax Funcction to be used later # In[2]: def softmax(x): """Compute softmax values for each sets of scores in x.""" e_x = np.exp(x - np.max(x)) return e_x / e_x.sum(axis=0) # only difference # ### Insert stock tickers # In[3]: tickers = ["IFNNY", "INTC", "MCHP","ON","STM","SWKS","^VIX"] # ### Set date range # In[4]: start_date = datetime(2008,12,5) end_date = datetime(2019,12,5) # ### Get the data # In[68]: df = data.DataReader(tickers, 'yahoo', start_date, end_date) dates =[] for x in range(len(df)): newdate = str(df.index[x]) newdate = newdate[0:10] dates.append(newdate) df['dates'] = dates # ### Get only closing price data # In[69]: close = df['Close'] all_weekdays = pd.date_range(start=start_date, end=end_date, freq='B') close = close.reindex(all_weekdays) close = close.fillna(method='ffill') close = close.rename(columns={"^VIX" : "VIX"}) # In[70]: for i in close: vars()[i] = close.loc[:,'%s' %i] # In[71]: close = close.drop(columns="VIX") # In[72]: close.describe() # ### Get Covariance Matrix # In[73]: cov =df['Close'].cov() cov =cov.drop(columns="^VIX", index = "^VIX") # In[74]: cov # ### Send Cov matrix to CSV # In[75]: cov.to_csv(r'\Users\Pete\OneDrive\School\Grad\IE 512\Project 2\Project\cov.csv') # # Moving Average Time # ### exponenetial weighted averages of closing prices # In[76]: ema_short = close.ewm(span=30, adjust=False).mean() ema_long = close.ewm(span=90, adjust=False).mean() ema_loong = close.ewm(span=300, adjust=False).mean() # ### Trading position # In[77]: trading_positions_raw = ema_short - ema_long trading_positions = trading_positions_raw.apply(np.sign) trading_positions_final = trading_positions.shift(1) # ### Build Epsilon # In[82]: q = abs(trading_positions_final.tail(30).mean()) r = abs(trading_positions_raw.tail(30).mean()) d = q*r epsilon = expit(d) print(epsilon) # ### Lambda # In[67]: Lambda = expit(np.log10(cov.sum()/10)) Lambda # ### Chi # In[83]: vix30=VIX.tail(30).mean() pg = math.exp(1-abs(vix30-12)/12) pb = math.exp(1-abs(vix30-30)/30) Chi = softmax([pg,pb]) Chi print(pb,pg) # ### Plot EMA vs Price # In[80]: for i in close: fig, ax = plt.subplots(figsize=(16,9)) ax.plot(close.loc[start_date:end_date, :].index, close.loc[start_date:end_date, i], label= 'Close') ax.plot(ema_short.loc[start_date:end_date, :].index, ema_short.loc[start_date:end_date, i], label = 'Span 30-days EMA') ax.plot(ema_long.loc[start_date:end_date, :].index, ema_long.loc[start_date:end_date, i], label = 'Span 90-days EMA') #ax.plot(ema_loong.loc[start_date:end_date, :].index, ema_loong.loc[start_date:end_date, i], label = 'Span 180-days EMA') ax.legend(loc='best') ax.set_ylabel('Price in $') ax.set_title(i) # ### Plot trading position vs PRice and EMA # In[81]: for i in close: fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(16,9)) ax1.set_title(i) ax1.plot(close.loc[start_date:end_date, :].index, close.loc[start_date:end_date, i], label= 'Close') ax1.plot(ema_short.loc[start_date:end_date, :].index, ema_short.loc[start_date:end_date, i], label = 'Span 30-days EMA') ax1.plot(ema_long.loc[start_date:end_date, :].index, ema_long.loc[start_date:end_date, i], label = 'Span 90-days EMA') #ax1.plot(ema_loong.loc[start_date:end_date, :].index, ema_loong.loc[start_date:end_date, i], label = 'Span 300-days EMA') ax1.legend(loc='best') ax1.set_ylabel('Price in $') ax2.set_title(i) ax2.plot(trading_positions_final.loc[start_date:end_date, :].index, trading_positions_final.loc[start_date:end_date, i], label='Trading position') ax2.set_ylabel('Trading position')

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0

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0.027027

0

null

0

null

0

1

0

2cc331db5c05974b7e5d6a6759775540b86d78ad

40,276

py

Python

slicem_gui.py

marcottelab/Slicem

2dbf9f8faf89a12c983595871809445663bc5a26

[ "MIT" ]

5

2019-10-05T03:04:57.000Z

2021-10-02T23:52:56.000Z

slicem_gui.py

marcottelab/Slicem

2dbf9f8faf89a12c983595871809445663bc5a26

[ "MIT" ]

2

2019-11-24T09:58:13.000Z

2020-11-09T23:57:28.000Z

slicem_gui.py

marcottelab/SLICEM

2dbf9f8faf89a12c983595871809445663bc5a26

[ "MIT" ]

null

import os import mrcfile import numpy as np import pandas as pd import networkx as nx from igraph import Graph from scipy import ndimage as ndi from skimage import transform, measure import tkinter as tk from tkinter import ttk import tkinter.filedialog import matplotlib from matplotlib import cm import matplotlib.pyplot as plt from matplotlib.figure import Figure import matplotlib.gridspec as gridspec from mpl_toolkits.axes_grid1 import ImageGrid from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk import warnings warnings.filterwarnings("ignore", category=UserWarning) matplotlib.use('TkAgg') class SLICEM_GUI(tk.Tk): def __init__(self, *args, **kwargs): tk.Tk.__init__(self, *args, **kwargs) tk.Tk.wm_title(self, "SLICEM_GUI") tabControl = ttk.Notebook(self) input_tab = ttk.Frame(tabControl) network_tab = ttk.Frame(tabControl) projection_tab = ttk.Frame(tabControl) output_tab = ttk.Frame(tabControl) tabControl.add(input_tab, text='Inputs') tabControl.add(network_tab, text='Network Plot') tabControl.add(projection_tab, text='Projection Plot') tabControl.add(output_tab, text='Outputs') tabControl.pack(expand=1, fill="both") self.cwd = os.getcwd() ######################### INPUT TAB ############################## mrc_label = ttk.Label(input_tab, text="path to 2D class averages (mrcs): ") mrc_label.grid(row=0, column=0, sticky=tk.E, pady=10) self.mrc_entry = ttk.Entry(input_tab, width=20) self.mrc_entry.grid(row=0, column=1, sticky=tk.W, pady=10) self.mrc_button = ttk.Button( input_tab, text="Browse", command=lambda: self.set_text( text=self.askfile(), entry=self.mrc_entry ) ) self.mrc_button.grid(row=0, column=2, sticky=tk.W, pady=2) scores_label = ttk.Label(input_tab, text="path to SLICEM scores: ") scores_label.grid(row=1, column=0, sticky=tk.E, pady=10) self.score_entry = ttk.Entry(input_tab, width=20) self.score_entry.grid(row=1, column=1, sticky=tk.W, pady=10) self.score_button = ttk.Button( input_tab, text="Browse", command=lambda: self.set_text( text=self.askfile(), entry=self.score_entry ) ) self.score_button.grid(row=1, column=2, sticky=tk.W, pady=2) scale_label = ttk.Label(input_tab, text="scale factor (if used): ") scale_label.grid(row=2, column=0, sticky=tk.E, pady=10) self.scale_entry = ttk.Entry(input_tab, width=5) self.scale_entry.grid(row=2, column=1, sticky=tk.W, pady=10) self.load_button = ttk.Button( input_tab, text='Load Inputs', command=lambda: self.load_inputs( self.mrc_entry.get(), self.score_entry.get(), self.scale_entry.get() ) ) self.load_button.grid(row=3, column=1, pady=20) ############################################################################ ######################### NETWORK TAB ############################## network_tab.grid_rowconfigure(0, weight=1) network_tab.grid_columnconfigure(0, weight=1) #TOP FRAME nettopFrame = tk.Frame(network_tab, bg='lightgrey', width=600, height=400) nettopFrame.grid(row=0, column=0, sticky='nsew') self.netcanvas = None self.nettoolbar = None #BOTTOM FRAME netbottomFrame = ttk.Frame(network_tab, width=600, height=100) netbottomFrame.grid(row=1, column=0, sticky='nsew') netbottomFrame.grid_propagate(0) self.detection = tk.StringVar(network_tab) self.detection.set('walktrap') comm_label = ttk.Label(netbottomFrame, text='community detection:') comm_label.grid(row=0, column=0, sticky=tk.E) self.community_wt = ttk.Radiobutton( netbottomFrame, text='walktrap', variable=self.detection, value='walktrap' ) self.community_wt.grid(row=0, column=1, padx=5, sticky=tk.W) n_clusters_label = ttk.Label(netbottomFrame, text='# of clusters (optional):') n_clusters_label.grid(row=0, column=2, sticky=tk.E) self.n_clust = ttk.Entry(netbottomFrame, width=6) self.n_clust.grid(row=0, column=3, padx=5, sticky=tk.W) self.wt_steps = ttk.Entry(netbottomFrame, width=6) self.wt_steps.insert(0, 4) # self.wt_steps.grid(row=0, column=2, padx=50, sticky=tk.W) #EV: Errors w/ betweenness iGraph version, temporarily remove #self.community_eb = ttk.Radiobutton( # netbottomFrame, # text='betweenness', # variable=self.detection, # value='betweenness' #) #self.community_eb.grid(row=0, column=2, padx=3, sticky=tk.W) self.network = tk.StringVar(network_tab) self.network.set('knn') net_label = ttk.Label(netbottomFrame, text='construct network from:') net_label.grid(row=1, column=0, sticky=tk.E) self.net1 = ttk.Radiobutton( netbottomFrame, text='nearest neighbors', variable=self.network, value='knn' ) self.net1.grid(row=1, column=1, padx=5, sticky=tk.W) self.net2 = ttk.Radiobutton( netbottomFrame, text='top n scores', variable=self.network, value='top_n' ) self.net2.grid(row=2, column=1, padx=5, sticky=tk.W) knn_label = ttk.Label(netbottomFrame, text='# of k:') knn_label.grid(row=1, column=2, sticky=tk.E) self.knn_entry = ttk.Entry(netbottomFrame, width=6) self.knn_entry.insert(0, 0) self.knn_entry.grid(row=1, column=3, padx=5, sticky=tk.W) topn_label = ttk.Label(netbottomFrame, text='# of n:') topn_label.grid(row=2, column=2, sticky=tk.E) self.topn_entry = ttk.Entry(netbottomFrame, width=6) self.topn_entry.insert(0, 0) self.topn_entry.grid(row=2, column=3, padx=5, sticky=tk.W) self.cluster = ttk.Button( netbottomFrame, width=12, text='cluster', command=lambda: self.slicem_cluster( self.detection.get(), self.network.get(), int(self.wt_steps.get()), self.n_clust.get(), int(self.knn_entry.get()), int(self.topn_entry.get()), self.drop_nodes.get() ) ) self.cluster.grid(row=0, column=4, sticky=tk.W, padx=5, pady=2) self.net_plot = ttk.Button( netbottomFrame, width=12, text='plot network', command=lambda: self.plot_slicem_network( self.network.get(), nettopFrame) ) self.net_plot.grid(row=1, column=4, sticky=tk.W, padx=5, pady=2) self.tiles = ttk.Button( netbottomFrame, width=12, text='plot 2D classes', command=lambda: self.plot_tiles() ) self.tiles.grid(row=2, column=4, sticky=tk.W, padx=5, pady=2) drop_label = ttk.Label(netbottomFrame, text='remove nodes') drop_label.grid(row=0, column=5) self.drop_nodes = ttk.Entry(netbottomFrame, width=15) self.drop_nodes.grid(row=1, column=5, sticky=tk.W, padx=10) ############################################################################ ######################### PROJECTION TAB ########################## projection_tab.grid_rowconfigure(0, weight=1) projection_tab.grid_columnconfigure(0, weight=1) #TOP FRAME projtopFrame = tk.Frame(projection_tab, bg='lightgrey', width=600, height=400) projtopFrame.grid(row=0, column=0, sticky='nsew') projtopFrame.grid_rowconfigure(0, weight=1) projtopFrame.grid_columnconfigure(0, weight=1) self.projcanvas = None self.projtoolbar = None #BOTTOM FRAME projbottomFrame = ttk.Frame(projection_tab, width=600, height=50) projbottomFrame.grid(row=1, column=0, sticky='nsew') projbottomFrame.grid_propagate(0) avg1_label = ttk.Label(projbottomFrame, text='class average 1: ') avg1_label.grid(row=0, column=0, sticky=tk.E, padx=2) self.avg1 = ttk.Entry(projbottomFrame, width=5) self.avg1.grid(row=0, column=1, padx=2) avg2_label = ttk.Label(projbottomFrame, text='class avereage 2: ') avg2_label.grid(row=0, column=2, sticky=tk.E, padx=2) self.avg2 = ttk.Entry(projbottomFrame, width=5) self.avg2.grid(row=0, column=3, padx=2) self.proj_button = ttk.Button( projbottomFrame, text='plot projections', command=lambda: self.plot_projections( int(self.avg1.get()), int(self.avg2.get()), projtopFrame ) ) self.proj_button.grid(row=0, column=4, padx=20) self.overlay_button = ttk.Button( projbottomFrame, text='plot overlap', command=lambda: self.overlay_lines( int(self.avg1.get()), int(self.avg2.get()), self.ft_check_var.get(), projtopFrame ) ) self.overlay_button.grid(row=0, column=5, padx=12) self.ft_check_var = tk.BooleanVar() self.ft_check_var.set(0) self.ft_check = ttk.Checkbutton(projbottomFrame, text='FT plot', variable=self.ft_check_var) self.ft_check.grid(row=0, column=6, padx=12) ################################################################################ ########################### OUTPUT TAB ################################# star_label = ttk.Label(output_tab, text='path to corresponding star file (star): ') star_label.grid(row=0, column=0, sticky=tk.E, pady=10) self.star_entry = ttk.Entry(output_tab, width=20) self.star_entry.grid(row=0, column=1, stick=tk.W, pady=10) self.star_button = ttk.Button( output_tab, text="Browse", command=lambda: self.set_text( text=self.askfile(), entry=self.star_entry ) ) self.star_button.grid(row=0, column=2, sticky=tk.W, pady=2) outdir_label = ttk.Label(output_tab, text='directory to save files in: ') outdir_label.grid(row=1, column=0, sticky=tk.E, pady=10) self.out_entry = ttk.Entry(output_tab, width=20) self.out_entry.grid(row=1, column=1, sticky=tk.W, pady=10) self.out_button = ttk.Button( output_tab, text="Browse", command=lambda: self.set_text( text=self.askpath(), entry=self.out_entry ) ) self.out_button.grid(row=1, column=2, sticky=tk.W, pady=2) self.write_button = ttk.Button( output_tab, text='Write Star Files', command=lambda: self.write_star_files( self.star_entry.get(), self.out_entry.get() ) ) self.write_button.grid(row=2, column=1, pady=20) self.write_edges = ttk.Button( output_tab, text='Write Edge List', command=lambda: self.write_edge_list( self.network.get(), self.out_entry.get() ) ) self.write_edges.grid(row=3, column=1, pady=10) ################################################################################ ############################### GUI METHODS ################################ def load_scores(self, score_file): complete_scores = {} with open(score_file, 'r') as f: next(f) for line in f: l = line.rstrip('\n').split('\t') complete_scores[(int(l[0]), int(l[2]))] = (int(l[1]), int(l[3]), float(l[4])) return complete_scores def load_class_avg(self, mrcs, factor): """read, scale and extract class averages""" global shape projection_2D = {} extract_2D = {} if len(factor) == 0: # Empty entry, set factor 1 factor = 1 with mrcfile.open(mrcs) as mrc: for i, data in enumerate(mrc.data): projection_2D[i] = data mrc.close() shape = transform.rotate(projection_2D[0].copy(), 45, resize=True).shape[0] for k, avg in projection_2D.items(): if factor == 1: extract_2D[k] = extract_class_avg(avg) else: scaled_img = transform.rescale( avg, scale=(1/float(factor)), anti_aliasing=True, multichannel=False, # Add to supress warning mode='constant' # Add to supress warning ) extract_2D[k] = extract_class_avg(scaled_img) return projection_2D, extract_2D def load_inputs(self, mrc_entry, score_entry, scale_entry): global projection_2D, extract_2D, num_class_avg, complete_scores projection_2D, extract_2D = self.load_class_avg(mrc_entry, scale_entry) num_class_avg = len(projection_2D) complete_scores = self.load_scores(score_entry) print('Inputs Loaded!') def askfile(self): file = tk.filedialog.askopenfilename(initialdir=self.cwd) return file def askpath(self): path = tk.filedialog.askdirectory(initialdir=self.cwd) return path def set_text(self, text, entry): entry.delete(0, tk.END) entry.insert(0, text) def show_dif_class_msg(self): tk.messagebox.showwarning(None, 'Select different class averages') def show_cluster_fail(self): tk.messagebox.showwarning(None, 'Clustering failed.\nTry adjusting # of clusters\n or # of edges') def show_drop_list_msg(self): tk.messagebox.showwarning(None, 'use comma separated list\nfor nodes to drop \ne.g. 1, 2, 3') def slicem_cluster(self, community_detection, network_from, wt_steps, n_clust, neighbors, top, drop_nodes): """construct graph and get colors for plotting""" #TODO: change to prevent cluster on exception global scores_update, drop, flat, clusters, G, colors if len(n_clust) == 0: n_clust = None # Cluster at optimum modularity else: n_clust = int(n_clust) if len(drop_nodes) > 0: try: drop = [int(n) for n in drop_nodes.split(',')] print('dropping nodes:', drop) scores_update = {} for pair, score in complete_scores.items(): if pair[0] in drop or pair[1] in drop: next else: scores_update[pair] = score except: self.show_drop_list_msg() else: drop = [] scores_update = complete_scores flat, clusters, G = self.create_network( community_detection=community_detection, wt_steps=wt_steps, n_clust=n_clust, network_from=network_from, neighbors=neighbors, top=top ) colors = get_plot_colors(clusters, G) print('clusters computed!') def create_network(self, community_detection, wt_steps, n_clust, network_from, neighbors, top): """get new clusters depending on input options""" if network_from == 'top_n': sort_by_scores = [] for pair, score in scores_update.items(): sort_by_scores.append([pair[0], pair[1], score[2]]) top_n = sorted(sort_by_scores, reverse=False, key=lambda x: x[2])[:top] # Convert from distance to similarity for edge for score in top_n: c = 1/(1 + score[2]) score[2] = c flat = [tuple(pair) for pair in top_n] elif network_from == 'knn': flat = [] projection_knn = nearest_neighbors(neighbors=neighbors) for projection, knn in projection_knn.items(): for n in knn: flat.append((projection, n[0], abs(n[3]))) # p1, p2, score clusters = {} g = Graph.TupleList(flat, weights=True) if community_detection == 'walktrap': try: wt = Graph.community_walktrap(g, weights='weight', steps=wt_steps) cluster_dendrogram = wt.as_clustering(n_clust) except: self.show_cluster_fail() elif community_detection == 'betweenness': try: ebs = Graph.community_edge_betweenness(g, weights='weight', directed=True) cluster_dendrogram = ebs.as_clustering(n_clust) except: self.show_cluster_fail() for community, projection in enumerate(cluster_dendrogram.subgraphs()): clusters[community] = projection.vs['name'] #convert node IDs back to ints for cluster, nodes in clusters.items(): clusters[cluster] = sorted([int(node) for node in nodes]) remove_outliers(clusters) clustered = [] for cluster, nodes in clusters.items(): for n in nodes: clustered.append(n) clusters['singles'] = [] # Add singles to clusters if not in top n scores clusters['removed'] = [] for node in projection_2D: if node not in clustered and node not in drop: clusters['singles'].append(node) elif node in drop: clusters['removed'].append(node) G = nx.Graph() for pair in flat: G.add_edge(int(pair[0]), int(pair[1]), weight=pair[2]) #if you want to see directionality in the networkx plot #G = nx.MultiDiGraph(G) #adds singles if not in top n scores for node_key in projection_2D: if node_key not in G.nodes: G.add_node(node_key) return flat, clusters, G def plot_slicem_network(self, network_from, frame): #TODO: adjust k, scale for clearer visualization G_subset = G.copy() color_dict = {i: color for i, color in enumerate(colors)} node_dict = {node: i for i, node in enumerate(G.nodes)} for d in drop: G_subset.remove_node(d) color_dict.pop(node_dict[d]) color_subset = [color for k, color in color_dict.items()] if network_from == 'knn': positions = nx.spring_layout(G_subset, weight='weight', k=0.3, scale=3.5) else: positions = nx.spring_layout(G_subset, weight='weight', k=0.18, scale=1.5) f = Figure(figsize=(8,5)) a = f.add_subplot(111) a.axis('off') nx.draw_networkx_nodes(G_subset, positions, ax=a, edgecolors='black', linewidths=2, node_size=300, alpha=0.65, node_color=color_subset) nx.draw_networkx_edges(G_subset, positions, ax=a, width=1, edge_color='grey') nx.draw_networkx_labels(G_subset, positions, ax=a, font_weight='bold', font_size=10) if self.netcanvas: self.netcanvas.get_tk_widget().destroy() self.nettoolbar.destroy() self.netcanvas = FigureCanvasTkAgg(f, frame) self.netcanvas.draw() self.netcanvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.netcanvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.nettoolbar = NavigationToolbar2Tk(self.netcanvas, frame) self.nettoolbar.update() def plot_tiles(self): """plot 2D class avgs sorted and colored by cluster""" #TODO: adjust plot, border and text_box sizes ordered_projections = [] flat_clusters = [] colors_2D = [] for cluster, nodes in clusters.items(): for n in nodes: ordered_projections.append(projection_2D[n]) for n in nodes: flat_clusters.append(n) for i, n in enumerate(G.nodes): if n in nodes: colors_2D.append(colors[i]) grid_cols = int(np.ceil(np.sqrt(len(ordered_projections)))) if len(ordered_projections) <= (grid_cols**2 - grid_cols): grid_rows = grid_cols - 1 else: grid_rows = grid_cols #assuming images are same size, get shape l, w = ordered_projections[0].shape #add blank images to pack in grid while len(ordered_projections) < grid_rows*grid_cols: ordered_projections.append(np.zeros((l, w))) colors_2D.append((0., 0., 0.)) flat_clusters.append('') f = Figure() grid = ImageGrid(f, 111, #similar to subplot(111) nrows_ncols=(grid_rows, grid_cols), #creates grid of axes axes_pad=0.05) #pad between axes in inch lw = 1.75 text_box_size = 5 props = dict(boxstyle='round', facecolor='white') for i, (ax, im) in enumerate(zip(grid, ordered_projections)): ax.imshow(im, cmap='gray') for side, spine in ax.spines.items(): spine.set_color(colors_2D[i]) spine.set_linewidth(lw) ax.get_yaxis().set_ticks([]) ax.get_xaxis().set_ticks([]) text = str(flat_clusters[i]) ax.text(1, 1, text, va='top', ha='left', bbox=props, size=text_box_size) newWindow = tk.Toplevel() newWindow.grid_rowconfigure(0, weight=1) newWindow.grid_columnconfigure(0, weight=1) #PLOT FRAME plotFrame = tk.Frame(newWindow, bg='lightgrey', width=600, height=400) plotFrame.grid(row=0, column=0, sticky='nsew') canvas = FigureCanvasTkAgg(f, plotFrame) canvas.draw() canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True) canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True) canvas.figure.tight_layout() #TOOLBAR FRAME toolbarFrame = ttk.Frame(newWindow, width=600, height=100) toolbarFrame.grid(row=1, column=0, sticky='nsew') toolbarFrame.grid_propagate(0) toolbar = NavigationToolbar2Tk(canvas, toolbarFrame) toolbar.update() def plot_projections(self, p1, p2, frame): if p1 == p2: self.show_dif_class_msg() else: projection1 = extract_2D[p1] projection2 = extract_2D[p2] angle1 = complete_scores[p1, p2][0] angle2 = complete_scores[p1, p2][1] ref = transform.rotate(projection1, angle1, resize=True) comp = transform.rotate(projection2, angle2, resize=True) ref_square, comp_square = make_equal_square_images(ref, comp) ref_intensity = ref_square.sum(axis=0) comp_intensity = comp_square.sum(axis=0) y_axis_max = max(np.amax(ref_intensity), np.amax(comp_intensity)) y_axis_min = min(np.amin(ref_intensity), np.amin(comp_intensity)) f = Figure(figsize=(4,4)) spec = gridspec.GridSpec(ncols=2, nrows=2, figure=f) tl = f.add_subplot(spec[0, 0]) tr = f.add_subplot(spec[0, 1]) bl = f.add_subplot(spec[1, 0]) br = f.add_subplot(spec[1, 1]) # PROJECTION_1 #2D projection image tl.imshow(ref_square, cmap=plt.get_cmap('gray'), aspect='equal') tl.axis('off') #1D line projection bl.plot(ref_intensity, color='black') bl.xaxis.set_visible(False) bl.yaxis.set_visible(False) bl.set_ylim([y_axis_min, (y_axis_max + 0.025*y_axis_max)]) bl.fill_between(range(len(ref_intensity)), ref_intensity, alpha=0.5, color='deepskyblue') # PROJECTION_2 #2D projection image tr.imshow(comp_square, cmap=plt.get_cmap('gray'), aspect='equal') tr.axis('off') #lD line projection br.plot(comp_intensity, color='black') br.xaxis.set_visible(False) br.yaxis.set_visible(False) br.set_ylim([y_axis_min, (y_axis_max + 0.025*y_axis_max)]) br.fill_between(range(len(comp_intensity)), comp_intensity, alpha=0.5, color='yellow') asp = np.diff(bl.get_xlim())[0] / np.diff(bl.get_ylim())[0] bl.set_aspect(asp) asp1 = np.diff(br.get_xlim())[0] / np.diff(br.get_ylim())[0] br.set_aspect(asp) f.tight_layout() if self.projcanvas: self.projcanvas.get_tk_widget().destroy() self.projtoolbar.destroy() self.projcanvas = FigureCanvasTkAgg(f, frame) self.projcanvas.draw() self.projcanvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.projcanvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.projtoolbar = NavigationToolbar2Tk(self.projcanvas, frame) self.projtoolbar.update() def overlay_lines(self, p1, p2, FT, frame): """overlays line projections at optimum angle between two class averages""" if p1 == p2: self.show_dif_class_msg() else: a1 = complete_scores[p1, p2][0] a2 = complete_scores[p1, p2][1] projection1 = make_1D(extract_2D[p1], a1) projection2 = make_1D(extract_2D[p2], a2) if FT: pad_p1 = np.pad(projection1.vector, pad_width=(0, shape-projection1.size())) pad_p2 = np.pad(projection2.vector, pad_width=(0, shape-projection2.size())) A = abs(np.fft.rfft(pad_p1)) B = abs(np.fft.rfft(pad_p2)) f = Figure(figsize=(8,4)) ax = f.add_subplot(111) ax.bar(range(len(A)), A, alpha=0.35, color='deepskyblue', ec='k', linewidth=1) ax.bar(range(len(B)), B, alpha=0.35, color='yellow', ec='k', linewidth=1) ax.get_xaxis().set_ticks([]) ax.set_xlabel('frequency component') ax.set_ylabel('Amplitude') else: a2_flip = complete_scores[p1, p2][1] + 180 projection2_flip = make_1D(extract_2D[p2], a2_flip) score_default, r, c = slide_score(projection1, projection2) # Score and location of optimum score_flip, r_flip, c_flip = slide_score(projection1, projection2_flip) # Score of phase flipped if score_default <= score_flip: ref_intensity, comp_intensity = r, c else: ref_intensity, comp_intensity = r_flip, c_flip f = Figure(figsize=(8,4)) ax = f.add_subplot(111) x_axis_max = len(ref_intensity) y_axis_max = max(np.amax(ref_intensity), np.amax(comp_intensity)) y_axis_min = min(np.amin(ref_intensity), np.amin(comp_intensity)) ax.plot(ref_intensity, color='black') ax.plot(comp_intensity, color='black') ax.fill_between(range(len(ref_intensity)), ref_intensity, alpha=0.35, color='deepskyblue') ax.fill_between(range(len(comp_intensity)), comp_intensity, alpha=0.35, color='yellow') ax.set_ylabel('Intensity') ax.set_ylim([y_axis_min, (y_axis_max + 0.025*y_axis_max)]) ax.xaxis.set_visible(False) f.tight_layout() if self.projcanvas: self.projcanvas.get_tk_widget().destroy() self.projtoolbar.destroy() self.projcanvas = FigureCanvasTkAgg(f, frame) self.projcanvas.draw() self.projcanvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.projcanvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True) self.projtoolbar = NavigationToolbar2Tk(self.projcanvas, frame) self.projtoolbar.update() def write_star_files(self, star_input, outpath): """split star file into new star files based on clusters""" with open(star_input, 'r') as f: table = parse_star(f) cluster_star = {} for cluster, nodes in clusters.items(): if nodes: #convert to str to match df #add 1 to match RELION indexing avgs = [str(node+1) for node in nodes] subset = table[table['ClassNumber'].isin(avgs)] cluster_star[cluster] = subset for cluster, table in cluster_star.items(): with open(outpath+'/slicem_cluster_{0}.star'.format(cluster), 'w') as f: #write the star file print('data_', file=f) print('loop_', file=f) for i, name in enumerate(table.columns): print('_rln' + name + ' #' + str(i+1), file=f) table.to_csv(f, sep='\t', index=False, header=False) with open(outpath+'/slicem_clusters.txt', 'w') as f: for cluster, averages in clusters.items(): f.write(str(cluster) + '\t' + str(averages) + '\n') print('star files written!') def write_edge_list(self, network, outpath): with open(outpath+'/slicem_edge_list.txt', 'w') as f: f.write('projection_1'+'\t'+'projection_2'+'\t'+'score'+'\n') for t in flat: f.write(str(t[0])+'\t'+str(t[1])+'\t'+str(t[2])+'\n') if network == 'top_n': if clusters['singles']: for single in clusters['singles']: f.write(str(single)+'\n') print('edge list written!') #Utility functions from main script to make GUI standalone def extract_class_avg(avg): """fit in minimal bounding box""" image = avg.copy() image[image < 0] = 0 struct = np.ones((2, 2), dtype=bool) dilate = ndi.binary_dilation(image, struct) labeled = measure.label(dilate, connectivity=2) rprops = measure.regionprops(labeled, image, cache=False) if len(rprops) == 1: select_region = 0 else: img_y, img_x = image.shape if labeled[int(img_y/2), int(img_x/2)] != 0: # Check for central region select_region = labeled[int(img_y/2), int(img_x/2)] - 1 # For index else: distances = [ (i, np.linalg.norm(np.array((img_y/2, img_x/2)) - np.array(r.weighted_centroid))) for i, r in enumerate(rprops) ] select_region = min(distances, key=lambda x: x[1])[0] # Pick first closest region y_min, x_min, y_max, x_max = [p for p in rprops[select_region].bbox] return image[y_min:y_max, x_min:x_max] def nearest_neighbors(neighbors): """group k best scores for each class average to construct graph""" projection_knn = {} order_scores = {avg: [] for avg in range(num_class_avg)} for d in drop: order_scores.pop(d, None) #projection_knn[projection_1] = [projection_2, angle_1, angle_2, score] for pair, values in scores_update.items(): p1, p2 = [p for p in pair] a1, a2, s = [v for v in values] c = [p2, a1, a2, s] order_scores[p1].append(c) # Zscore per class avg for edge for projection, scores in order_scores.items(): all_scores = [v[3] for v in scores] u = np.mean(all_scores) s = np.std(all_scores) for v in scores: zscore = (v[3] - u)/s v[3] = zscore for avg, scores in order_scores.items(): sort = sorted(scores, reverse=False, key=lambda x: x[3])[:neighbors] projection_knn[avg] = sort return projection_knn def remove_outliers(clusters): """ Use median absolute deviation to remove outliers Boris Iglewicz and David Hoaglin (1993) """ pixel_sums = {} outliers = [] for cluster, nodes in clusters.items(): if len(nodes) > 1: pixel_sums[cluster] = [] for node in nodes: pixel_sums[cluster].append(sum(sum(extract_2D[node]))) for cluster, psums in pixel_sums.items(): med = np.median(psums) m_psums = [abs(x - med) for x in psums] mad = np.median(m_psums) if mad == 0: next else: for i, proj in enumerate(psums): z = 0.6745*(proj - med)/mad if abs(z) > 3.5: outliers.append((cluster, clusters[cluster][i])) clusters["outliers"] = [o[1] for o in outliers] for outlier in outliers: cluster, node = outlier[0], outlier[1] clusters[cluster].remove(node) print('class_avg node {0} was removed from cluster {1} as an outlier'.format(node, cluster)) def random_color(): return tuple(np.random.rand(1,3)[0]) def get_plot_colors(clusters, graph): color_list = [] preset_colors = [color for colors in [cm.Set3.colors] for color in colors] for i in range(len(clusters)): if i < len(preset_colors): color_list.append(preset_colors[i]) else: color_list.append(random_color()) colors = [] for i, node in enumerate(graph.nodes): for cluster, projections in clusters.items(): if cluster == 'singles': if node in projections: colors.append((0.85, 0.85, 0.85)) elif cluster == 'outliers': if node in projections: colors.append((0.35, 0.35, 0.35)) elif cluster == 'removed': if node in projections: colors.append((0.9, 0, 0)) elif node in projections: colors.append((color_list[cluster])) return colors def make_equal_square_images(ref, comp): ry, rx = np.shape(ref) cy, cx = np.shape(comp) max_dim = max(rx, ry, cx, cy) # Max dimension ref = adjust_image_size(ref, max_dim) comp = adjust_image_size(comp, max_dim) return ref, comp def adjust_image_size(img, max_dim): y, x = np.shape(img) y_pad = int((max_dim-y)/2) if y % 2 == 0: img = np.pad(img, pad_width=((y_pad,y_pad), (0,0)), mode='constant') else: img = np.pad(img, pad_width=((y_pad+1,y_pad), (0,0)), mode='constant') x_pad = int((max_dim-x)/2) if x % 2 == 0: img = np.pad(img, pad_width=((0,0), (x_pad,x_pad)), mode='constant') else: img = np.pad(img, pad_width=((0,0), (x_pad+1,x_pad)), mode='constant') return img class Projection: """for 1D projection vectors""" def __init__(self, class_avg, angle, vector): self.class_avg = class_avg self.angle = angle self.vector = vector def size(self): return len(self.vector) def make_1D(projection, angle): proj_1D = transform.rotate(projection, angle, resize=True).sum(axis=0) trim_1D = np.trim_zeros(proj_1D, trim='fb') p = Projection(class_avg=projection, angle=angle, vector=trim_1D) return p def slide_score(a, b): """ finds minimum pairwise score for translations of 1D projections a, b are instances of the Projection class modified from main for plotting """ scores = [] if a.size() > b.size(): l, s = a.vector, b.vector else: l, s = b.vector, a.vector l_size, s_size = len(l), len(s) pad_l = np.pad(l, pad_width=(s_size-1, s_size-1)) diff_of_len = abs(len(pad_l) - s_size) for i in range(s_size+l_size-1): shift_s = np.pad(s, pad_width=(i, diff_of_len-i)) scores.append(np.linalg.norm(pad_l - shift_s)) score = min(scores) loc = np.argwhere(scores == np.amin(scores)) loc = loc[0][0].astype('int') # If multiple minimum occur pick the first if a.size() > b.size(): ref_intensity = pad_l comp_intensity = np.pad(s, pad_width=(loc, diff_of_len-loc)) else: ref_intensity = np.pad(s, pad_width=(loc, diff_of_len-loc)) comp_intensity = pad_l #Crop lines for plotting if loc < s_size-1: ref_intensity = ref_intensity[loc:s_size-1+l_size] comp_intensity = comp_intensity[loc:s_size-1+l_size] elif loc >= s_size-1 and loc+s_size < s_size-1+l_size: ref_intensity = ref_intensity[s_size-1:s_size+l_size] comp_intensity = comp_intensity[s_size-1:s_size+l_size] elif loc >= s_size-1 and loc+s_size >= s_size-1+l_size: ref_intensity = ref_intensity[s_size-1:loc+s_size] comp_intensity = comp_intensity[s_size-1:loc+s_size] return score, ref_intensity, comp_intensity def parse_star(f): """ functions to parse star file adapted from Tristan Bepler https://github.com/tbepler/topaz https://www.nature.com/articles/s41592-019-0575-8 """ return parse(f) def parse(f): lines = f.readlines() for i in range(len(lines)): line = lines[i] if line.startswith('data_'): return parse_star_body(lines[i+1:]) def parse_star_body(lines): #data_images line has been read, next is loop for i in range(len(lines)): if lines[i].startswith('loop_'): lines = lines[i+1:] break header,lines = parse_star_loop(lines) #parse the body content = [] for i in range(len(lines)): line = lines[i].strip() if line.startswith('data'): # done with image block break if line.startswith('#') or line.startswith(';'): # comment lines continue if line != '': tokens = line.split() content.append(tokens) table = pd.DataFrame(content, columns=header) return table def parse_star_loop(lines): columns = [] for i in range(len(lines)): line = lines[i].strip() if not line.startswith('_'): break name = line[1:] #strip trailing comments from name loc = name.find('#') if loc >= 0: name = name[:loc] #strip 'rln' prefix if name.startswith('rln'): name = name[3:] name = name.strip() columns.append(name) return columns, lines[i:] app = SLICEM_GUI() app.geometry('900x750') app.mainloop()

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0.553282

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40,276

4.290753

0.127541

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0.015605

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0

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0.011222

0

null

0

null

0

1

0

2cc537735a2d67e707923633b8c5359a8e975af1

650

py

Python

src/openprocurement/tender/openeu/procedure/state/bid.py

ProzorroUKR/openprocurement.api

2855a99aa8738fb832ee0dbad4e9590bd3643511

[ "Apache-2.0" ]

10

2020-02-18T01:56:21.000Z

2022-03-28T00:32:57.000Z

src/openprocurement/tender/openeu/procedure/state/bid.py

quintagroup/openprocurement.api

2855a99aa8738fb832ee0dbad4e9590bd3643511

[ "Apache-2.0" ]

26

2018-07-16T09:30:44.000Z

2021-02-02T17:51:30.000Z

src/openprocurement/tender/openeu/procedure/state/bid.py

ProzorroUKR/openprocurement.api

2855a99aa8738fb832ee0dbad4e9590bd3643511

[ "Apache-2.0" ]

15

2019-08-08T10:50:47.000Z

2022-02-05T14:13:36.000Z

from openprocurement.api.utils import error_handler from openprocurement.tender.core.procedure.state.bid import BidState as BaseBidState class BidState(BaseBidState): def status_up(self, before, after, data): assert before != after, "Statuses must be different" # this logic moved here from validate_update_bid_status validator # if request.authenticated_role != "Administrator": if after not in ("pending", "active"): self.request.errors.add("body", "bid", "Can't update bid to ({}) status".format(after)) self.request.errors.status = 403 raise error_handler(self.request)

40.625

99

0.695385

80

650

5.5625

0.6625

0.074157

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0

0.005803

0.204615

650

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1

0.111111

false

0

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0

0.444444

0

null

0

null

0

1

0

2cc54c1983960e2959f4569eed5ba54d8ffadc15

4,903

py

Python

api/serializers.py

apigram/jade-api

1aece29c3109db68897fdf854be431554e7f2863

[ "Apache-2.0" ]

null

api/serializers.py

apigram/jade-api

1aece29c3109db68897fdf854be431554e7f2863

[ "Apache-2.0" ]

null

api/serializers.py

apigram/jade-api

1aece29c3109db68897fdf854be431554e7f2863

[ "Apache-2.0" ]

null

from rest_framework_nested.serializers import NestedHyperlinkedModelSerializer from rest_framework_nested.relations import NestedHyperlinkedRelatedField from rest_framework import serializers from api.models import User, Company, CompanyContact, Order, Item, Contact, OrderItem import copy class UserSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = User fields = ('url', 'username', 'contact', 'email') class CompanyContactsSerializer(NestedHyperlinkedModelSerializer): parent_lookup_kwargs = { 'company_pk': 'company__pk' } contact = serializers.HyperlinkedRelatedField( view_name='contact-detail', many=False, read_only=True ) class Meta: model = CompanyContact fields = ('contact',) class CompanySerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Company fields = ('url', 'name', 'business_number', 'type', 'contacts') contacts = CompanyContactsSerializer(many=True, read_only=False) def create(self, validated_data): client_data = copy.deepcopy(validated_data) del client_data['contacts'] contact_list_data = validated_data['contacts'] company = Company(**client_data) company.save() for contact_data in contact_list_data: contact = Contact(**contact_data) contact.save() companycontact = CompanyContact() companycontact.company = company companycontact.contact = contact companycontact.save() return company class ClientSerializer(CompanySerializer): url = serializers.HyperlinkedIdentityField( view_name='client-detail', lookup_field='pk' ) class SupplierSerializer(CompanySerializer): url = serializers.HyperlinkedIdentityField( view_name='supplier-detail', lookup_field='pk' ) class OrderItemSerializers(NestedHyperlinkedModelSerializer): parent_lookup_kwargs = { 'order_pk': 'order__pk' } order = serializers.HyperlinkedRelatedField( view_name='order-detail', many=False, read_only=True ) item = serializers.HyperlinkedRelatedField( view_name='item-detail', many=False, read_only=True ) class Meta: model = OrderItem fields = ('order', 'item', 'quantity', 'unit_price', 'comments') class ItemOrderSerializers(NestedHyperlinkedModelSerializer): parent_lookup_kwargs = { 'item_pk': 'item__pk' } order = serializers.HyperlinkedRelatedField( view_name='order-detail', many=False, read_only=True ) item = serializers.HyperlinkedRelatedField( view_name='item-detail', many=False, read_only=True ) class Meta: model = OrderItem fields = ('order', 'item', 'quantity', 'price', 'comments') class OrderCompanySerializer(NestedHyperlinkedModelSerializer): parent_lookup_kwargs = { 'order_pk': 'order__pk' } class Meta: model = Company fields = ('url', 'name', 'contacts', 'business_number', 'type') contacts = CompanyContactsSerializer(many=True, read_only=True) class OrderSerializer(serializers.HyperlinkedModelSerializer): client = serializers.HyperlinkedRelatedField( view_name="client-detail", many=False, read_only=False, queryset=Company.objects.filter(type='CLIENT') ) supplier = serializers.HyperlinkedRelatedField( view_name="supplier-detail", many=False, read_only=False, queryset=Company.objects.filter(type='SUPPLIER') ) class Meta: model = Order fields = ( 'url', 'items', 'client', 'supplier', 'received_date', 'scheduled_deliver_date', 'delivered_date', 'status', 'comments' ) items = OrderItemSerializers(many=True, read_only=False) def create(self, validated_data): order_data = copy.deepcopy(validated_data) del order_data['items'] item_list_data = validated_data['items'] order = Order(**order_data) order.save() for item_data in item_list_data: order_item = OrderItem(**item_data) order_item.order = order order_item.save() return order class ItemSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Item fields = ('url', 'orders', 'label', 'quantity', 'unit_price') orders = OrderItemSerializers(many=True, read_only=True) class ContactSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Contact fields = ('first_name', 'last_name', 'role', 'phone', 'email', 'address')

27.544944

85

0.646543

442

4,903

6.9819

0.208145

0.028516

0.04083

0.095269

0.466948

0.376863

0.277706

0.255671

0.214841

0.201555

0

0.255354

4,903

177

86

27.700565

0.845248

0

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0

0.112176

0.004487

0

1

0.014388

false

0

0.035971

0

0.330935

0

null

0

null

0

1

0

2cc5625c16ac62cef1a16f88ef8ee506d837539a

1,703

py

Python

kanga/management/commands/add-origins.py

deptofdefense/kanga

9c8d926a4828e2fca528915ddf35759d1c328c85

[ "MIT" ]

1

2022-03-05T01:17:59.000Z

kanga/management/commands/add-origins.py

deptofdefense/kanga

9c8d926a4828e2fca528915ddf35759d1c328c85

[ "MIT" ]

null

kanga/management/commands/add-origins.py

deptofdefense/kanga

9c8d926a4828e2fca528915ddf35759d1c328c85

[ "MIT" ]

null

# ================================================================= # # Work of the U.S. Department of Defense, Defense Digital Service. # Released as open source under the MIT License. See LICENSE file. # # ================================================================= import json import sys from django.core.management.base import BaseCommand from django.forms.models import model_to_dict from kanga.models import Account, Origin from kanga.encoder import KangaEncoder from kanga.utils import clean_phone_number class Command(BaseCommand): help = 'Add origins' def add_arguments(self, parser): parser.add_argument( '--account', type=str, default=None, required=True, help='Name') parser.add_argument( '--path', type=str, default=None, required=True, help='Path') def handle(self, *args, **options): # account = options['account'] p = options['path'] # a = Account.objects.get(id=account) # Origin.objects.all().delete() # with open(p, 'r') as file: text = clean_phone_number(file.read()) for line in text.splitlines(): Origin.objects.create( account=a, phone_number="+1{}".format(line), voice=True, sms=True, mms=True, fax=True, active=True) # origins = [o for o in Origin.objects.all()] json.dump([model_to_dict(o) for o in origins], sys.stdout, cls=KangaEncoder)

28.864407

84

0.500881

174

1,703

4.833333

0.511494

0.032105

0.026159

0.042806

0.080856

0

0.000875

0.328831

1,703

58

85

29.362069

0.734908

0.153846

0

0.2

0

0.03499

0

1

0.05

false

0

0.175

0

0.275

0

null

0

null

0

1

0

2cc813a4b5a65446f5e51d5a31e50f0a7569413f

692

py

Python

examples/joost/grammarator.py

wilkeraziz/grasp

95f5135fd3711eed32cddce2049dd595314fb1f4

[ "Apache-2.0" ]

9

2015-07-22T18:07:44.000Z

2021-11-08T11:21:11.000Z

examples/joost/grammarator.py

wilkeraziz/grasp

95f5135fd3711eed32cddce2049dd595314fb1f4

[ "Apache-2.0" ]

null

examples/joost/grammarator.py

wilkeraziz/grasp

95f5135fd3711eed32cddce2049dd595314fb1f4

[ "Apache-2.0" ]

1

2021-01-12T10:00:22.000Z

#!/usr/bin/env python3 import argparse parser = argparse.ArgumentParser(description='Process some integers.') parser.add_argument('k', metavar='k', type=int, nargs='?', help='number of classes of terminals (terminal-generating non-terminals)') args = parser.parse_args() # print("k = %d" % args.k) print("""[A] ||| [S] [VT] [O] ||| 1.0 [S] ||| [S] [S] ||| 0.2 [S] ||| [S] 'rpi' [S] [VT] ||| 0.2 [S] ||| [ST] ||| 0.6 [O] ||| [O] [O] ||| 0.2 [O] ||| [S] 'rpi' [S] [VT] ||| 0.2 [O] ||| [OT] ||| 0.6""") p = 1.0 / float(args.k) for i in range(1, args.k + 1): print("[ST] ||| 'si%d' ||| %f" % (i, p)) print("[OT] ||| 'oi%d' ||| %f" % (i, p)) print("[VT] ||| 'vi%d' ||| %f" % (i, p))

26.615385

76

0.492775

115

692

2.947826

0.452174

0.023599

0.026549

0.035398

0.106195

0.053097

0

0.033451

0.179191

692

25

77

27.68

0.56338

0.066474

0

0.535714

0

1

0

false

0

0.058824

0

0.058824

0.235294

0

null

0

null

0

1

0

2ccbbcd205dc73323b99918be9662a57635d2a3f

5,924

py

Python

app/sims/method/fields.py

DeepanshS/mrsimulator-ui

42f1a85f1cb76896cde2a3c8d4e38fe2c989b710

[ "BSD-3-Clause" ]

2

2019-11-21T16:14:13.000Z

2020-10-17T21:36:00.000Z

app/sims/method/fields.py

DeepanshS/mrsimulator-ui

42f1a85f1cb76896cde2a3c8d4e38fe2c989b710

[ "BSD-3-Clause" ]

32

2021-07-07T20:16:29.000Z

2022-03-29T14:09:23.000Z

app/sims/method/fields.py

DeepanshS/mrsimulator-ui

42f1a85f1cb76896cde2a3c8d4e38fe2c989b710

[ "BSD-3-Clause" ]

2

2019-10-23T18:23:57.000Z

2021-03-25T00:13:10.000Z

# -*- coding: utf-8 -*- import dash_core_components as dcc import dash_html_components as html from dash.dependencies import Input from dash.dependencies import Output from app import app from app.custom_widgets import collapsable_card from app.custom_widgets import container from app.custom_widgets import custom_button from app.custom_widgets import custom_input_group # from dash.dependencies import State __author__ = "Deepansh J. Srivastava" __email__ = "srivastava.89@osu.edu" def experiment_ui(): # upload experiment dataset tooltip = ( "Click to attach a measurement file to the selected method. " "Alternatively, drag and drop the file onto the Simulation area." ) icon = html.I(className="fas fa-paperclip fa-lg", title=tooltip) clip_btn = html.Button(icon, className="icon-button") upload = dcc.Upload(clip_btn, id="import-measurement-for-method") # label = dbc.InputGroupAddon("Measurement data", addon_type="prepend") # upload_ui = dbc.InputGroup([label, upload], className="input-form") # standard deviation calc_tooltip = ( "Click to calculate the noise standard deviation from the selected region of ∂" "the experiment spectrum." ) calc_icon = html.I(className="fas fa-calculator", title=calc_tooltip) calc_btn = html.Button(calc_icon, id="calc-sigma-button", className="icon-button") sigma = custom_input_group( prepend_label="Noise standard deviation (σ)", # Text overwraps the input field append_label=calc_btn, value=1.0, min=1e-6, id="measurement-sigma", debounce=True, ) return container( text=["Experiment", upload], featured=[sigma], ) # app.clientside_callback( # """ # function(index, data) { # console.log(data); # if (data == null) { throw window.dash_clientside.PreventUpdate; } # if (data.methods[index] == null){throw window.dash_clientside.PreventUpdate;} # if (data.methods[index].experiment == null) { # return [false, false, false, false, false, false]; # } # else { return [true, true, true, true, true, true]; } # } # """, # [ # *[Output(f"count-{i}", "disabled") for i in range(2)], # *[Output(f"spectral_width-{i}", "disabled") for i in range(2)], # *[Output(f"reference_offset-{i}", "disabled") for i in range(2)], # ], # Input("select-method", "value"), # Input("local-mrsim-data", "data"), # prevent_initial_call=True, # ) def spectral_dimension_ui(i): """Return a list of widgets whose entries are used in evaluating the dimension coordinates along the i^th dimension. The widgets includes number of points (count), spectral width, and reference offset. Args: i: An integer with the dimension index. """ # count count = custom_input_group( prepend_label="Number of points", value=512, min=2, id=f"count-{i}", debounce=True, pattern="[0-9]*", ) # spectral width spectral_width = custom_input_group( prepend_label="Spectral width", append_label="kHz", value=25.0, min=1e-6, id=f"spectral_width-{i}", debounce=True, ) # reference offset reference_offset = custom_input_group( prepend_label="Reference offset", append_label="kHz", value=0.0, id=f"reference_offset-{i}", debounce=True, ) # origin offset # origin_offset = custom_input_group( # prepend_label="Origin offset", # append_label="MHz", # value=0.0, # id=f"origin_offset-{i}", # debounce=True, # ) # origin offset label = custom_input_group( prepend_label="Label", append_label="", input_type="text", value="frequency", id=f"label-{i}", debounce=True, ) return collapsable_card( text=f"Spectral Dimension - {i}", id_=f"dim-{i}", featured=[count, spectral_width, reference_offset], hidden=[label], message="Show/Hide", outer=True, ) def global_environment(): """Generate a list of widgets whose entries are the sample global environment parameter. The widgets includes flux density, rotor frequency, and rotor angle.""" flux_density = custom_input_group( prepend_label="Magnetic flux density (B₀)", append_label="T", value=9.4, id="magnetic_flux_density", min=0.0, debounce=True, ) # rotor frequency rotor_frequency = custom_input_group( prepend_label="Rotor frequency (𝜈ᵣ)", append_label="kHz", value=0.0, id="rotor_frequency", min=0.0, debounce=True, ) # rotor angle magic_angle = custom_button( icon_classname="fas fa-magic", tooltip="Set value to the magic angle.", id="set-to-magic-angle", className="icon-button", module="html", ) # dbc.Button( # html.I(className="fas fa-magic"), # color="light", # id="set-to-magic-angle", # size="sm", # ) # datalist = html.Datalist([0, 54.7356103172, 90], id="datalist-magic-angle") rotor_angle = custom_input_group( prepend_label=html.Div(["Rotor angle (θᵣ)", magic_angle]), append_label="deg", value=54.7356103172, id="rotor_angle", max=90, min=0, debounce=True, # list="datalist-magic-angle", ) app.clientside_callback( """function(n) { return 54.7356103172; }""", Output("rotor_angle", "value"), Input("set-to-magic-angle", "n_clicks"), ) return container( text="Global Environment Parameters", featured=[flux_density, rotor_frequency, rotor_angle], )

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88

0.61293

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5,924

4.997167

0.273371

0.031179

0.045351

0.058673

0.27466

0.165816

0.085317

0.049887

0.034014

0

0.017348

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5,924

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null

0

null

0

1

0

2ccee2fa8c8ba625dd902253db0db5b0a2526b08

563

py

Python

class2/exercises/exercise2/exercise2c.py

EndlessDynamics/Fork_nornir_course

04bf7e3819659f481a4e04059152877b795177b2

[ "Apache-2.0" ]

60

2019-05-11T05:23:10.000Z

2022-03-30T08:03:43.000Z

class2/exercises/exercise2/exercise2c.py

EndlessDynamics/Fork_nornir_course

04bf7e3819659f481a4e04059152877b795177b2

[ "Apache-2.0" ]

14

2021-03-31T19:08:08.000Z

2021-09-15T17:29:40.000Z

class2/exercises/exercise2/exercise2c.py

EndlessDynamics/Fork_nornir_course

04bf7e3819659f481a4e04059152877b795177b2

[ "Apache-2.0" ]

21

2019-08-08T21:30:46.000Z

2022-03-28T06:22:25.000Z

from rich import print from nornir import InitNornir from nornir.core.filter import F from nornir_netmiko import netmiko_send_command def main(): nr = InitNornir(config_file="config.yaml") filt = F(groups__contains="ios") nr = nr.filter(filt) my_results = nr.run( task=netmiko_send_command, command_string="show run | i hostname" ) host_results = my_results["cisco3"] print() print(type(host_results)) print(repr(host_results[0])) print(host_results.__iter__) print() if __name__ == "__main__": main()

22.52

73

0.694494

76

563

4.789474

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0.120879

0.098901

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0.004425

0.197158

563

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false

0

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0.315789

0

null

0

null

0

1

0

e2ba3189a471ae4c5fad168efa534a2e6749bec4

13,265

py

Python

portality/api/current/data_objects/application.py

DOAJ/doaj

b11f163c48f51f9e3ada2b02c617b50b847dcb4c

[ "Apache-2.0" ]

47

2015-04-24T13:13:39.000Z

2022-03-06T03:22:42.000Z

portality/api/current/data_objects/application.py

DOAJ/doaj

b11f163c48f51f9e3ada2b02c617b50b847dcb4c

[ "Apache-2.0" ]

1,215

2015-01-02T14:29:38.000Z

2022-03-28T14:19:13.000Z

portality/api/current/data_objects/application.py

DOAJ/doaj

b11f163c48f51f9e3ada2b02c617b50b847dcb4c

[ "Apache-2.0" ]

14

2015-11-27T13:01:23.000Z

2021-05-21T07:57:23.000Z

import uuid from datetime import datetime from portality.api.current.data_objects.common import _check_for_script from portality.lib import swagger, seamless, coerce, dates, dataobj from portality import models from copy import deepcopy from portality.api.current.data_objects.common_journal_application import OutgoingCommonJournalApplication, _SHARED_STRUCT # both incoming and outgoing applications share this struct # "required" fields are only put on incoming applications from portality.lib.coerce import COERCE_MAP from portality.lib.seamless import SeamlessMixin from portality.models import JournalLikeBibJSON from portality.ui.messages import Messages OUTGOING_APPLICATION_STRUCT = { "fields": { "id": {"coerce": "unicode"}, # Note that we'll leave these in for ease of use by the "created_date": {"coerce": "utcdatetime"}, # caller, but we'll need to ignore them on the conversion "last_updated": {"coerce": "utcdatetime"}, # to the real object "last_manual_update": {"coerce": "utcdatetime"} }, "objects": ["admin", "bibjson"], "structs": { "admin" : { "fields" : { "application_status" : {"coerce" : "unicode"}, "current_journal" : {"coerce" : "unicode"}, "date_applied" : {"coerce" : "unicode"}, "owner" : {"coerce" : "unicode"} } } } } INTERNAL_APPLICATION_STRUCT = { "fields": { "id": {"coerce": "unicode"}, # Note that we'll leave these in for ease of use by the "created_date": {"coerce": "utcdatetime"}, # caller, but we'll need to ignore them on the conversion "last_updated": {"coerce": "utcdatetime"}, # to the real object "last_manual_update": {"coerce": "utcdatetime"}, "es_type": {"coerce": "unicode"} }, "objects": ["admin", "bibjson"], "structs": { "admin" : { "fields" : { "related_journal" : {"coerce" : "unicode"}, "editor_group" : {"coerce" : "unicode"}, "editor" : {"coerce" : "unicode"}, "owner" : {"coerce" : "unicode"}, "seal" : {"coerce" : "unicode"} }, "lists": { "notes" : {"contains" : "object"}, } } } } INCOMING_APPLICATION_REQUIREMENTS = { "required" : ["admin", "bibjson"], "structs": { "bibjson": { "required": [ "copyright", "deposit_policy", "editorial", "eissn", "keywords", "language", "license", "ref", "pid_scheme", "pissn", "plagiarism", "preservation", "publication_time_weeks", "publisher", "ref", "oa_start", "other_charges", "waiver", "title" ], "structs": { "copyright": { "required" : ["url"] }, "editorial": { "required" : ["review_process", "review_url"] }, "plagiarism": { "required": ["detection","url"] }, "publisher": { "required": ["name"] }, "ref": { "required" : ["journal"] } } } } } class IncomingApplication(SeamlessMixin, swagger.SwaggerSupport): """ ~~APIIncomingApplication:Model->Seamless:Library~~ """ __type__ = "application" __SEAMLESS_COERCE__ = COERCE_MAP __SEAMLESS_STRUCT__ = [ OUTGOING_APPLICATION_STRUCT, # FIXME: should this be here? It looks like it allows users to send administrative data to the system # I have removed it as it was exposing incorrect data in the auto-generated documentation # INTERNAL_APPLICATION_STRUCT, _SHARED_STRUCT, # FIXME: can we live without specifying required fields, since the form validation will handle this? INCOMING_APPLICATION_REQUIREMENTS ] def __init__(self, raw=None, **kwargs): if raw is None: super(IncomingApplication, self).__init__(silent_prune=False, check_required_on_init=False, **kwargs) else: super(IncomingApplication, self).__init__(raw=raw, silent_prune=False, **kwargs) @property def data(self): return self.__seamless__.data def custom_validate(self): # only attempt to validate if this is not a blank object if len(list(self.__seamless__.data.keys())) == 0: return if _check_for_script(self.data): raise dataobj.ScriptTagFoundException(Messages.EXCEPTION_SCRIPT_TAG_FOUND) # extract the p/e-issn identifier objects pissn = self.data["bibjson"]["pissn"] eissn = self.data["bibjson"]["eissn"] # check that at least one of them appears and if they are different if pissn is None and eissn is None or pissn == eissn: raise seamless.SeamlessException("You must specify at least one of bibjson.pissn and bibjson.eissn, and they must be different") # normalise the ids if pissn is not None: pissn = self._normalise_issn(pissn) if eissn is not None: eissn = self._normalise_issn(eissn) # check they are not the same if pissn is not None and eissn is not None: if pissn == eissn: raise seamless.SeamlessException("P-ISSN and E-ISSN should be different") # A link to the journal homepage is required # if self.data["bibjson"]["ref"]["journal"] is None or self.data["bibjson"]["ref"]["journal"] == "": raise seamless.SeamlessException("You must specify the journal homepage in bibjson.ref.journal") # if plagiarism detection is done, then the url is a required field if self.data["bibjson"]["plagiarism"]["detection"] is True: url = self.data["bibjson"]["plagiarism"]["url"] if url is None: raise seamless.SeamlessException("In this context bibjson.plagiarism.url is required") # if licence_display is "embed", then the url is a required field #TODO: what with "display" art = self.data["bibjson"]["article"] if "embed" in art["license_display"] or "display" in art["license_display"]: if art["license_display_example_url"] is None or art["license_display_example_url"] == "": raise seamless.SeamlessException("In this context bibjson.article.license_display_example_url is required") # if the author does not hold the copyright the url is optional, otherwise it is required if self.data["bibjson"]["copyright"]["author_retains"] is not False: if self.data["bibjson"]["copyright"]["url"] is None or self.data["bibjson"]["copyright"]["url"] == "": raise seamless.SeamlessException("In this context bibjson.copyright.url is required") # check the number of keywords is no more than 6 if len(self.data["bibjson"]["keywords"]) > 6: raise seamless.SeamlessException("bibjson.keywords may only contain a maximum of 6 keywords") def _normalise_issn(self, issn): issn = issn.upper() if len(issn) > 8: return issn if len(issn) == 8: if "-" in issn: return "0" + issn else: return issn[:4] + "-" + issn[4:] if len(issn) < 8: if "-" in issn: return ("0" * (9 - len(issn))) + issn else: issn = ("0" * (8 - len(issn))) + issn return issn[:4] + "-" + issn[4:] def to_application_model(self, existing=None): nd = deepcopy(self.data) if existing is None: return models.Suggestion(**nd) else: nnd = seamless.SeamlessMixin.extend_struct(self._struct, nd) return models.Suggestion(**nnd) @property def id(self): return self.__seamless__.get_single("id") def set_id(self, id=None): if id is None: id = self.makeid() self.__seamless__.set_with_struct("id", id) def set_created(self, date=None): if date is None: date = dates.now() self.__seamless__.set_with_struct("created_date", date) @property def created_date(self): return self.__seamless__.get_single("created_date") @property def created_timestamp(self): return self.__seamless__.get_single("created_date", coerce=coerce.to_datestamp()) def set_last_updated(self, date=None): if date is None: date = dates.now() self.__seamless__.set_with_struct("last_updated", date) @property def last_updated(self): return self.__seamless__.get_single("last_updated") @property def last_updated_timestamp(self): return self.__seamless__.get_single("last_updated", coerce=coerce.to_datestamp()) def set_last_manual_update(self, date=None): if date is None: date = dates.now() self.__seamless__.set_with_struct("last_manual_update", date) @property def last_manual_update(self): return self.__seamless__.get_single("last_manual_update") @property def last_manual_update_timestamp(self): return self.__seamless__.get_single("last_manual_update", coerce=coerce.to_datestamp()) def has_been_manually_updated(self): lmut = self.last_manual_update_timestamp if lmut is None: return False return lmut > datetime.utcfromtimestamp(0) def has_seal(self): return self.__seamless__.get_single("admin.seal", default=False) def set_seal(self, value): self.__seamless__.set_with_struct("admin.seal", value) @property def owner(self): return self.__seamless__.get_single("admin.owner") def set_owner(self, owner): self.__seamless__.set_with_struct("admin.owner", owner) def remove_owner(self): self.__seamless__.delete("admin.owner") @property def editor_group(self): return self.__seamless__.get_single("admin.editor_group") def set_editor_group(self, eg): self.__seamless__.set_with_struct("admin.editor_group", eg) def remove_editor_group(self): self.__seamless__.delete("admin.editor_group") @property def editor(self): return self.__seamless__.get_single("admin.editor") def set_editor(self, ed): self.__seamless__.set_with_struct("admin.editor", ed) def remove_editor(self): self.__seamless__.delete('admin.editor') def add_note(self, note, date=None, id=None): if date is None: date = dates.now() obj = {"date": date, "note": note, "id": id} self.__seamless__.delete_from_list("admin.notes", matchsub=obj) if id is None: obj["id"] = uuid.uuid4() self.__seamless__.add_to_list_with_struct("admin.notes", obj) def remove_note(self, note): self.__seamless__.delete_from_list("admin.notes", matchsub=note) def set_notes(self, notes): self.__seamless__.set_with_struct("admin.notes", notes) def remove_notes(self): self.__seamless__.delete("admin.notes") @property def notes(self): return self.__seamless__.get_list("admin.notes") @property def ordered_notes(self): notes = self.notes clusters = {} for note in notes: if note["date"] not in clusters: clusters[note["date"]] = [note] else: clusters[note["date"]].append(note) ordered_keys = sorted(list(clusters.keys()), reverse=True) ordered = [] for key in ordered_keys: clusters[key].reverse() ordered += clusters[key] return ordered def bibjson(self): bj = self.__seamless__.get_single("bibjson") if bj is None: self.__seamless__.set_single("bibjson", {}) bj = self.__seamless__.get_single("bibjson") return JournalLikeBibJSON(bj) def set_bibjson(self, bibjson): bibjson = bibjson.data if isinstance(bibjson, JournalLikeBibJSON) else bibjson self.__seamless__.set_with_struct("bibjson", bibjson) class OutgoingApplication(OutgoingCommonJournalApplication): """ ~~APIOutgoingApplication:Model->APIOutgoingCommonJournalApplication:Model~~ ~~->Seamless:Library~~ """ __SEAMLESS_COERCE__ = COERCE_MAP __SEAMLESS_STRUCT__ = [ OUTGOING_APPLICATION_STRUCT, _SHARED_STRUCT ] def __init__(self, raw=None, **kwargs): super(OutgoingApplication, self).__init__(raw, silent_prune=True, **kwargs) @classmethod def from_model(cls, application): assert isinstance(application, models.Suggestion) return super(OutgoingApplication, cls).from_model(application) @property def data(self): return self.__seamless__.data

35.467914

140

0.603166

1,462

13,265

5.214774

0.192886

0.055089

0.025708

0.040399

0.390346

0.320698

0.247639

0.195042

0.119753

0.084601

0

0.001893

0.283302

13,265

373

141

35.563003

0.800042

0.104109

0

0.216028

0

0.170979

0.013699

0

0.002681

0.003484

1

0.135889

false

0

0.038328

0.04878

0.278746

0

null

0

null

0

1

0

e2bd7c8a213c65827af43039aa4e15d0d27034d2

4,086

py

Python

app.py

joumanarahime/sqlalchemy-challenge

e86c3a05443a6d2664b2f9ab8145565c7fbce24b

[ "ADSL" ]

null

app.py

joumanarahime/sqlalchemy-challenge

e86c3a05443a6d2664b2f9ab8145565c7fbce24b

[ "ADSL" ]

null

app.py

joumanarahime/sqlalchemy-challenge

e86c3a05443a6d2664b2f9ab8145565c7fbce24b

[ "ADSL" ]

null

import numpy as np import pandas as dp import datetime as dt import sqlalchemy from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine, func from flask import Flask, jsonify #engine = create_engine("sqlite:///Resources/hawaii.sqlite") engine = create_engine("sqlite:////Users/joumanarahime/Documents/Vanderbilt BootCamp/sqlalchemy-challenge/Resources/hawaii.sqlite") Base=automap_base() Base.prepare(engine, reflect=True) Base.classes.keys() Measurement = Base.classes.measurement Station = Base.classes.station session=Session(engine) max_date = session.execute('select MAX(date) from measurement').fetchall() max_date = max_date[0][0] # Calculate the date 1 year ago from the last data point in the database date_stamp = dt.datetime.strptime(max_date,'%Y-%m-%d') year = date_stamp.year month = date_stamp.month day = date_stamp.day prior_year = f'{year-1}-{month:02d}-{day:02d}' #Create the app app = Flask(__name__) # index route @app.route("/") def home(): """List of all available api routes.""" return ( f"Available Routes: " f"------------------------ " f"/api/v1.0/precipitation " f"/api/v1.0/stations " f"/api/v1.0/tobs " f"/api/v1.0/2016-01-30 " f"/api/v1.0/2016-01-30/2017-01-30" ) # 4. /api/v1.0/precipitation @app.route("/api/v1.0/precipitation") def prec(): session=Session(engine) results = session.query(Measurement.prcp, Measurement.date).filter(Measurement.date > prior_year).all() session.close() prec_data=[] for result in results: prec_dict = {result.date: result.prcp } prec_data.append(prec_dict) return jsonify(prec_data) @app.route("/api/v1.0/stations") def stations(): session=Session(engine) results= session.execute('select station, count(*) as count from measurement group by station order by count(station) desc ').fetchall() station_data=[] for result in results: station_dict = {result.station: result.count} station_data.append(station_dict) return jsonify(station_data) @app.route("/api/v1.0/tobs") def tobs(): session=Session(engine) cal_temp = session.execute(f"select date, min(tobs), avg(tobs), max(tobs) from measurement where date> '{prior_year}'").fetchall() temp_dict= { "Date": cal_temp[0][0], "Low Temp": cal_temp[0][1], "Avg Temp": cal_temp[0][2], "Highest Temp": cal_temp[0][3] } return jsonify(temp_dict) @app.route("/api/v1.0/<start>") def start_date(start): session=Session(engine) sel= [func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)] results= (session.query(*sel) .filter(func.strftime("%Y-%m-%d", Measurement.date)>=start) .all()) dates=[] for result in results: start_dict={ "Date": start, "Low Temp": result[0], "Avg Temp": result[1], "Highest Temp": result[2] } dates.append(start_dict) return jsonify(dates) @app.route("/api/v1.0/<start>/<end>") def start_end_date(start, end): session=Session(engine) sel= [func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)] results= (session.query(*sel) .filter(func.strftime("%Y-%m-%d", Measurement.date)>=start) .filter(func.strftime("%Y-%m-%d", Measurement.date)<=end) .all()) dates=[] for result in results: startEnd_dict={} startEnd_dict={ "Start Date": start, "End Date": end, "Low Temp": result[0], "Avg Temp": result[1], "Highest Temp": result[2] } dates.append(startEnd_dict) return jsonify(dates) if __name__ == "__main__": app.run(debug=True)

27.986301

140

0.610622

526

4,086

4.642586

0.226236

0.022523

0.027027

0.01638

0.314087

0.251433

0.199836

0.171171

0

0.022172

0.238375

4,086

146

141

27.986301

0.762532

0.053108

0

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0

0.009709

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0

1

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false

0

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