xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

d15aa90cf8b146f10fcd1838f8fa2f846261f835

1,912

py

Python

nicos_demo/vrefsans/setups/nok/b2.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

null

nicos_demo/vrefsans/setups/nok/b2.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

null

nicos_demo/vrefsans/setups/nok/b2.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

null

description = 'at samplecamper [slit k1]' group = 'lowlevel' devices = dict( b2 = device('nicos_mlz.refsans.devices.slits.DoubleSlit', description = 'b2 at sample pos', fmtstr = 'opening: %.3f mm, zpos: %.3f mm', unit = '', slit_r = 'b2r', slit_s = 'b2s', ), b2r = device('nicos_mlz.refsans.devices.slits.SingleSlit', # length: 13.0 mm description = 'b2 slit, reactor side; 220 full access, 74 for upper srcews', motor = 'b2_r', nok_start = 11049.50, nok_end = 11064.50, nok_gap = 1.0, masks = { 'slit': 0.0, 'point': -4.067, 'gisans': -218.645, }, visibility = (), unit = 'mm', ), b2s = device('nicos_mlz.refsans.devices.slits.SingleSlit', # length: 13.0 mm description = 'b2 slit, sample side; -291 full access, -182 low row', motor = 'b2_s', nok_start = 11049.50, nok_end = 11064.50, nok_gap = 1.0, masks = { 'slit': 0.0, 'point': -0.233, 'gisans': 206.4, }, unit = 'mm', visibility = (), ), b2_r = device('nicos.devices.generic.Axis', description = 'b2, reactorside', motor = device('nicos.devices.generic.VirtualMotor', abslimits = (-1294, 1222), speed = 3., unit = 'mm', ), backlash = 0, precision = 0.02, visibility = (), ), b2_s = device('nicos.devices.generic.Axis', description = 'b2, sampleside', motor = device('nicos.devices.generic.VirtualMotor', abslimits = (-2960, 2130), speed = 3., unit = 'mm', ), backlash = 0, precision = 0.02, visibility = (), ), ) alias_config = { 'last_aperture': {'b2': 100}, }

27.314286

84

0.486925

203

1,912

4.502463

0.413793

0.084245

0.078775

0.109409

0.602845

0.56674

0.363239

0

0.097279

0.365586

1,912

69

85

27.710145

0.656224

0.016213

0

0.515625

0

0.283813

0.13099

0

1

0

false

0

null

0

null

0

1

0

d15dd7f172b63fa664d2c06fe65f7e7984030b80

2,909

py

Python

pentagon.py

tobi08151405/Platonic-bodys

077976d1943a0b834ad9e81b8e6ff9376ef76449

[ "MIT" ]

null

pentagon.py

tobi08151405/Platonic-bodys

077976d1943a0b834ad9e81b8e6ff9376ef76449

[ "MIT" ]

null

pentagon.py

tobi08151405/Platonic-bodys

077976d1943a0b834ad9e81b8e6ff9376ef76449

[ "MIT" ]

null

__author__ = 'tobias' import math as m import turtle as t import rotation_matrix_3D as rm3D def pentagon(): print("\n\n****************************************************************************\n\n") #requesting the variables radius = float(input("prisms radius [mm] : ")) height = float(input("height h [mm] : ")) Volume = float(input("volume [mm^3] : ")) alpha_grad = float(input("angle alpha [°] : ")) beta_grad = float(input("angle beta [°] : ")) gamma_grad = float(input("angle gamma [°] : ")) print("\n\n****************************************************************************\n\n") #calculation if Volume == 0: W = ((((m.sin((m.pi * 2) / 5) * radius) ** 2 + (radius - (m.cos((m.pi * 2) / 5) * radius)) ** 2) ** 0.5) / 2 * ((radius ** 2 - ((((m.sin((m.pi * 2) / 5) * radius) ** 2 + (radius - (m.cos((m.pi * 2) / 5) * radius)) ** 2) ** 0.5) / 2) ** 2) ** 0.5) * 5) * height print("Ergebnis: volume = %.5f" % W, "[mm^3]") print("\n\n****************************************************************************\n\n") elif height == 0: a = Volume / ((((m.sin((m.pi * 2) / 5) * radius) ** 2 + (radius - (m.cos((m.pi * 2) / 5) * radius)) ** 2) ** 0.5) / 2 * ((radius ** 2 - ((((m.sin((m.pi * 2) / 5) * radius) ** 2 + (radius - (m.cos((m.pi * 2) / 5) * radius)) ** 2) ** 0.5) / 2) ** 2) ** 0.5) * 5) print("Ergebnis: height h = %.%f" % a, "[mm]") height = a #transform from degree to radiant alpha = m.radians(alpha_grad) beta = m.radians(beta_grad) gamma = m.radians(gamma_grad) #define the points Ap, Bp, Cp, Dp, Ep, Fp, Gp, Hp, Ip, Jp = [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0] points_calculat = [Ap, Bp, Cp, Dp, Ep, Fp, Gp, Hp, Ip, Jp] corner_pionts = [] k = 0 for point in points_calculat: if k > 4: z = height else: z = 0 corner_pionts.append([(radius * m.sin(m.pi * 2 / 5 * k)), (radius * m.cos(m.pi * 2 / 5 * k)), z]) k = k + 1 #rotate the points corner_pionts3 = rm3D.rotation_matrix_3D(alpha, beta, gamma, corner_pionts) #draw the prism window = t.Screen() t.ht() t.speed(2) t.up() t.goto(corner_pionts3[0][0:2]) t.pd() for pointk1 in corner_pionts3[1:5]: t.goto(pointk1[0:2]) t.goto(corner_pionts3[0][0:2]) for pointk2 in corner_pionts3[5:10]: t.goto(pointk2[0:2]) t.goto(corner_pionts3[5][0:2]) t.pu() t.goto(corner_pionts3[1][0:2]) t.pd() t.goto(corner_pionts3[6][0:2]) t.pu() t.goto(corner_pionts3[2][0:2]) t.pd() t.goto(corner_pionts3[7][0:2]) t.pu() t.goto(corner_pionts3[3][0:2]) t.pd() t.goto(corner_pionts3[8][0:2]) t.pu() t.goto(corner_pionts3[4][0:2]) t.pd() t.goto(corner_pionts3[9][0:2]) window.exitonclick()

40.402778

268

0.475421

457

2,909

2.960613

0.214442

0.045824

0.062084

0.079823

0.411678

0.390244

0.367332

0.325203

0.189209

0

0.069369

0.236851

2,909

72

269

40.402778

0.538739

0.039532

0

0.215385

0

0.151309

0.090355

0

1

0.015385

false

0

0.046154

0

0.061538

0.076923

0

null

0

null

0

1

0

d1608f7400945f8fca0e8f7dfc05612ae0e8b662

11,102

py

Python

coordinator.py

vascoalramos/distributed-map-reduce

315711489b75929c7f7c80527265a2c7f3d20af5

[ "MIT" ]

null

coordinator.py

vascoalramos/distributed-map-reduce

315711489b75929c7f7c80527265a2c7f3d20af5

[ "MIT" ]

null

coordinator.py

vascoalramos/distributed-map-reduce

315711489b75929c7f7c80527265a2c7f3d20af5

[ "MIT" ]

null

# coding: utf-8 from socket import socket, AF_INET, SOCK_STREAM from backup import Backup import csv import logging import argparse import json import asyncio import sys import queue logging.basicConfig(level=logging.INFO, format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s', datefmt='%m-%d %H:%M:%S') logger = logging.getLogger('Coordinator') # Asyncio class (we used callback asyncio) class EchoProtocol(asyncio.BaseProtocol): def __init__(self, coordinator): self.coordinator = coordinator def connection_made(self, transport): self.transport = transport self.socket = transport.get_extra_info('socket') self.addr = transport.get_extra_info('peername') logger.info('New connection established: %s', self.addr) def data_received(self, data): self.coordinator.receive(self.socket, data) def eof_received(self): self.coordinator.redistributeWork(self.socket) # Coordinator class class Coordinator: def __init__(self, datastore, datastoreIndex=0, maps=[], msgBuffer=""): self.datastore = datastore # Array with all of the blobs if len(self.datastore) == 1: self.singleBlob = True # Control variable used to force a reduce if we only have 1 blob else: self.singleBlob = False # Index that points to what blob we're treating self.datastoreIndex = datastoreIndex self.lostWork = queue.Queue() # Queue with work lost when a worker crashes self.sentWork = {} # Dictionary with all work messages sent and to whom self.workers = {} # Dictionary with worker's id-connection self.tasksCount = 0 self.msgBuffer = msgBuffer # Incoming message buffer self.maps = maps # Maps we're treating logger.debug("Map : %s", self.maps) logger.debug(self.datastoreIndex) # Backup: # Backup connection (Backup-Coordinator address) self.backupConn = None self.backupAddr = () # Backup address (Backup socket address) # Receive function. Used to receive and treat incoming data def receive(self, connection, data): dataReceived = data.decode('UTF-8') if '\x04' not in dataReceived: # If we haven't received a message with the break char self.msgBuffer += dataReceived # Keep appending it to our msgBuffer else: splitBuf = dataReceived.split('\x04') auxBuf = self.msgBuffer + splitBuf[0] self.msgBuffer = splitBuf[1] self.handle(connection, auxBuf) # Send function. Used to send messages def send(self, connection, data): connection.sendall(data.encode( 'UTF-8') + ('\x04').encode('UTF-8')) self.sentWork[connection] = data ################ SYNC FUNCS ############################################ # Sends current maps and index values to backup def syncData(self): msg = {"task": "update", "value": self.maps, "index": self.datastoreIndex} updateMsg = json.dumps(msg) try: self.backupConn.sendall(updateMsg.encode( 'UTF-8') + ('\x04').encode('UTF-8')) except OSError: pass ####################################################################### # Function used to register work that had been sent to a worker that died def redistributeWork(self, connection): if (connection != self.backupConn) and (connection in list(self.workers.values())): for workerID, workerConn in self.workers.items(): if workerConn == connection: del self.workers[workerID] self.lostWork.put(self.sentWork[connection]) break # Function used to register a new worker def regWorker(self, connection, workerID): self.workers[workerID] = connection # Add it to our worker dict logger.info('Worker registered with id %s', workerID) if self.backupConn is not None: # If we have a backup, give the worker a viable address to connect to it workMsg = json.dumps( {"task": "reg_backup", "value": self.backupAddr}) self.send(connection, workMsg) self.giveWork(connection) # Function used to write a csv with the resulting final map def writeToCSV(self): with args.out as f: csv_writer = csv.writer( f, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) for w, c in self.maps[0]: csv_writer.writerow([w, c]) # Function used to give work to a worker def giveWork(self, connection): if (len(self.maps) < 2): # If we only have 1 map in our maps # And still have blobs in the datastore, get a new one and send it to be mapped (either from the lost works or the datastore) if (self.datastoreIndex < len(self.datastore)): if (self.lostWork.qsize() == 0): workMsg = json.dumps( {"task": "map_request", "blob": self.datastore[self.datastoreIndex]}) self.send(connection, workMsg) self.datastoreIndex += 1 if self.backupConn is not None: self.syncData() # Update backup data else: workMsg = self.lostWork.get() self.send(connection, workMsg) if self.backupConn is not None: self.syncData() # Update backup data else: if self.backupConn is not None: self.syncData() # Update backup data self.tasksCount += 1 logger.debug(str(self.tasksCount) + " | " + str(len(self.workers))) if (self.tasksCount == len(self.workers)): if self.singleBlob == True: # In case we only have 1 blob we have to force the reduce! self.singleBlob = False self.tasksCount -= 1 self.maps.append([]) workMsg = json.dumps( {"task": "reduce_request", "value": [self.maps[0], self.maps[1]]}) self.send(connection, workMsg) del self.maps[1] del self.maps[0] else: logger.info('Map complete: %s', self.maps) if self.backupConn is not None: self.syncData() # Update backup data self.writeToCSV() # Store final histogram into a CSV file sys.exit() else: # Otherwise, reduce the 2 maps we've got OR send work that had been lost if (self.lostWork.qsize() == 0): workMsg = json.dumps( {"task": "reduce_request", "value": [self.maps[0], self.maps[1]]}) self.send(connection, workMsg) if self.backupConn is not None: self.syncData() # Update backup data del self.maps[1] del self.maps[0] else: workMsg = self.lostWork.get() self.send(connection, workMsg) if self.backupConn is not None: self.syncData() # Update backup data # Function used to handle incoming requests def handle(self, connection, data): msg = json.loads(data) logger.info('Handling task %s', msg["task"]) if msg['task'] == 'register': # Register new worker self.regWorker(connection, msg['id']) elif msg['task'] == 'reg_backup': # Register new backup self.backupConn = connection self.backupAddr = msg['addr'] workMsg = json.dumps( {"task": "reg_backup", "value": self.backupAddr}) for workerID, workerConn in self.workers.items(): # Register new backup at all workers self.send(workerConn, workMsg) logger.debug("Registered backup!") elif msg['task'] == 'map_reply' or msg['task'] == 'reduce_reply': # Receive a work reply self.maps.append(msg["value"]) self.giveWork(connection) # Main process initializing function async def main(args): datastore = [] # Build blobs with args.file as f: while True: blob = f.read(args.blob_size) if not blob: break # This loop is used to not break word in half while not str.isspace(blob[-1]): ch = f.read(1) if not ch: break blob += ch logger.debug('Blob: %s\n\n', blob) datastore.append(blob) ############################################# # Create Coordinator coordinator = Coordinator(datastore) failCounter = 0 try: # Its a coordinator! loop = asyncio.get_event_loop() server = await loop.create_server(lambda: EchoProtocol(coordinator), "127.0.0.1", args.port) logger.info("Coordinator created!") await server.serve_forever() except: # Its a backup! port = args.port + 1 # Backup port, used to communicate with workers while True: try: backup_coord = Backup( "127.0.0.1", args.port, datastore, "127.0.0.1", port) failCounter = 0 break except: failCounter += 1 port += 1 if failCounter >= 10: break pass logger.info("Backup created!") backup_coord.start_backup() # When the coordinator dies, backup becomes the new coordinator by launching a server coordinator = Coordinator( datastore, backup_coord.indexDatastore, backup_coord.maps) loop = asyncio.get_event_loop() server = await loop.create_server(lambda: EchoProtocol(coordinator), "127.0.0.1", args.port) logger.info("Coordinator created!") await server.serve_forever() if __name__ == '__main__': parser = argparse.ArgumentParser(description='MapReduce Coordinator') parser.add_argument('-p', dest='port', type=int, help='coordinator port', default=8765) parser.add_argument('-f', dest='file', type=argparse.FileType('r'), help='file path') parser.add_argument('-o', dest='out', type=argparse.FileType('w', encoding='UTF-8'), help='output file path', default='output.csv') parser.add_argument('-b', dest='blob_size', type=int, help='blob size', default=1024) args = parser.parse_args() loop = asyncio.get_event_loop() loop.run_until_complete(main(args)) loop.close()

36.045455

137

0.555756

1,229

11,102

4.971522

0.227828

0.020949

0.016039

0.020622

0.232242

0.205074

0.198691

0.178396

0.144354

0

0.011148

0.3294

11,102

308

138

36.045455

0.809537

0.168888

0

0.365385

0

0.07465

0

1

0.0625

false

0.009615

0.043269

0

0.115385

0

null

0

null

0

1

0

d160afe29ca98b897f73981e72be75b8dff2b9ff

2,554

py

Python

batch_merge.py

rmukh/abanalysis

5f75aa7562a47ea8304be8fa1ccf6720f6e5e77d

[ "MIT" ]

null

batch_merge.py

rmukh/abanalysis

5f75aa7562a47ea8304be8fa1ccf6720f6e5e77d

[ "MIT" ]

null

batch_merge.py

rmukh/abanalysis

5f75aa7562a47ea8304be8fa1ccf6720f6e5e77d

[ "MIT" ]

null

#!/usr/bin/python # filename: batch_merge.py ########################################################################### # # Copyright (c) 2013 Bryan Briney. All rights reserved. # Copyright (c) 2021 Rinat Mukhometzianov. # @version: 1.0.0 # @author: Bryan Briney, Rinat Mukhometzianov # @props: IgBLAST team (http://www.ncbi.nlm.nih.gov/igblast/igblast.cgi) # @license: MIT (http://opensource.org/licenses/MIT) # ########################################################################### import os import glob import shutil import argparse import pandaseq parser = argparse.ArgumentParser("Batch merging of paired-end reads with PANDAseq") parser.add_argument('-i', '--in', dest='input', required=True, help="The input directory, containing paired FASTQ files" " (uncompressed or gzip compressed). Required.") parser.add_argument('-o', '--out', dest='output', required=True, help="The output directory, will contain merged FASTA files. Required.") parser.add_argument('-n', '--nextseq', dest='nextseq', default=False, action='store_true', help="Use flag if run was performed on a NextSeq sequencer.") args = parser.parse_args() def make_direc(d): if not os.path.exists(d): os.mkdir(d) def remove_direc(d): shutil.rmtree(d) def list_files(d): return sorted([f for f in glob.glob(d + '/*') if os.path.isfile(f)]) def bin_files(files): file_bins = {} for f in files: f_pre = '_'.join(os.path.basename(f).split('_')[:-1]) if f_pre in file_bins: file_bins[f_pre].append(f) else: file_bins[f_pre] = [f, ] return file_bins def concat(d): files = list_files(d) file_bins = bin_files(files) for file_bin in file_bins: outfile = os.path.join(args.output, '{}.fasta'.format(file_bin)) with open(outfile, 'w') as o: for f in file_bins[file_bin]: with open(f) as i: for line in i: o.write(line) def main(): make_direc(args.output) if args.nextseq: temp = os.path.join(args.output, 'temp') make_direc(temp) o = temp else: o = args.output pandaseq.run(args.input, o, args.nextseq) if args.nextseq: print('') print('Concatenating NextSeq lane files for each sample...') concat(o) remove_direc(o) print('Done.') print('') if __name__ == '__main__': main()

28.696629

120

0.564996

324

2,554

4.330247

0.41358

0.045617

0.036351

0.027085

0.02851

0

0.006266

0.250196

2,554

88

121

29.022727

0.726371

0.124902

0

0.105263

0

0.189007

0

1

0.105263

false

0

0.087719

0.017544

0.22807

0.070175

0

null

0

null

0

1

0

d160e05e12200ca4b5c97430d3fdfce6f5aa5dd3

8,350

py

Python

globus_automate_client/action_client.py

seren/globus-automate-client

e12314911bdf4ef62d2ca533d9de4dd3b3d1ad2c

[ "Apache-2.0" ]

null

globus_automate_client/action_client.py

seren/globus-automate-client

e12314911bdf4ef62d2ca533d9de4dd3b3d1ad2c

[ "Apache-2.0" ]

null

globus_automate_client/action_client.py

seren/globus-automate-client

e12314911bdf4ef62d2ca533d9de4dd3b3d1ad2c

[ "Apache-2.0" ]

null

import uuid from typing import Any, Dict, Iterable, Mapping, Optional, Type, TypeVar, Union from globus_sdk import ( AccessTokenAuthorizer, ClientCredentialsAuthorizer, GlobusHTTPResponse, RefreshTokenAuthorizer, ) from globus_sdk.base import BaseClient from .helpers import merge_lists _ActionClient = TypeVar("_ActionClient", bound="ActionClient") class ActionClient(BaseClient): allowed_authorizer_types = ( AccessTokenAuthorizer, RefreshTokenAuthorizer, ClientCredentialsAuthorizer, ) AllowedAuthorizersType = Union[ AccessTokenAuthorizer, RefreshTokenAuthorizer, ClientCredentialsAuthorizer ] def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) @property def action_scope(self) -> str: """ This property can be used to determine an ``ActionClient``'s ``action_scope``. Internally, this property will introspect the Action Provider at the URL for which the ``ActionClient`` was created. If the ``Action Provider`` is not public, a valid ``Globus Authorizer`` will have to have been provided on initialization to the ``ActionClient``. Otherwise, this call will fail. """ if not hasattr(self, "_action_scope"): resp = self.introspect() if resp.data is None: self._action_scope = "" else: self._action_scope = resp.data.get("globus_auth_scope", "") return self._action_scope def introspect(self, **kwargs) -> GlobusHTTPResponse: """ Introspect the details of an Action Provider to discover information such as its expected ``action_scope``, its ``input_schema``, and who to contact when there's trouble. """ return self.get("") def run( self, body: Mapping[str, Any], request_id: Optional[str] = None, manage_by: Optional[Iterable[str]] = None, monitor_by: Optional[Iterable[str]] = None, label: Optional[str] = None, force_path: Optional[str] = None, **kwargs ) -> GlobusHTTPResponse: """ Invoke the Action Provider to execute an Action with the given parameters. :param body: The Action Provider specific input required to execute an Action payload :param request_id: An optional identifier that serves to de-duplicate requests to the Action Provider :param manage_by: A series of Globus identities which may alter this Action's execution. The principal value is the user's or group's UUID prefixed with either 'urn:globus:groups:id:' or 'urn:globus:auth:identity:' :param monitor_by: A series of Globus identities which may view the state of this Action. The principal value is the user's or group's UUID prefixed with either 'urn:globus:groups:id:' or 'urn:globus:auth:identity:' :param force_path: A URL to use for running this action, ignoring any previous configuration :param label: Set a label for the Action that is run. :param run_monitors: May be used as an alias for ``monitor_by`` :param run_managers: May be used as an alias for ``manage_by`` """ if request_id is None: request_id = str(uuid.uuid4()) path = self.qjoin_path("run") if force_path: path = force_path body = { "request_id": str(request_id), "body": body, "monitor_by": merge_lists(monitor_by, kwargs, "run_monitors"), "manage_by": merge_lists(manage_by, kwargs, "run_managers"), "label": label, } # Remove None items from the temp_body body = {k: v for k, v in body.items() if v is not None} return self.post(path, body) def status(self, action_id: str) -> GlobusHTTPResponse: """ Query the Action Provider for the status of executed Action :param action_id: An identifier that uniquely identifies an Action executed on this Action Provider. """ path = self.qjoin_path(action_id, "status") return self.get(path) def resume(self, action_id: str) -> GlobusHTTPResponse: """ Resume an INACTIVE action. Corrective action must have been taken prior to invoking this method, including the possibility of consenting to additional permissions and using tokens issued by those consents when creating this client. These consents would commonly be required when an Action is INACTIVE and shows the code ConsentRequired. :param action_id: An identifier that uniquely identifies an Action executed on this Action Provider. """ path = self.qjoin_path(action_id, "resume") return self.post(path) def cancel(self, action_id: str) -> GlobusHTTPResponse: """ Cancel a currently executing Action on an Action Provider :param action_id: An identifier that uniquely identifies an Action executed on this Action Provider. """ path = self.qjoin_path(action_id, "cancel") return self.post(path) def release(self, action_id: str) -> GlobusHTTPResponse: """ Remove the history of an Action's execution from an Action Provider :param action_id: An identifier that uniquely identifies an Action executed on this Action Provider. """ path = self.qjoin_path(action_id, "release") return self.post(path) def log( self, action_id: str, limit: int = 10, reverse_order: bool = False, marker: Optional[str] = None, per_page: Optional[int] = None, ) -> GlobusHTTPResponse: """ Retrieve an Action's execution log history. Not all ``Action Providers`` support this operation. :param action_id: An identifier that uniquely identifies an Action executed on this Action Provider. :param limit: A integer specifying how many log records to return :param reverse_order: Display the Action states in reverse- chronological order :param marker: A pagination_token indicating the page of results to return and how many entries to return. Not all ActionProviders will support this parameter. :param per_page: The number of results to return per page. If supplied a pagination_token, this parameter has no effect. Not all ActionProviders will support this parameter. """ params: Dict[str, Union[int, str]] = { "reverse_order": reverse_order, "limit": limit, } if marker is not None: params["pagination_token"] = marker if per_page is not None and marker is None: params["per_page"] = per_page path = self.qjoin_path(action_id, "log") return self.get(path, params=params) @classmethod def new_client( cls: Type[_ActionClient], action_url: str, authorizer: AllowedAuthorizersType, http_timeout: int = 10, ) -> _ActionClient: """ Classmethod to simplify creating an ActionClient. Use this method when attemping to create an ActionClient with pre-existing credentials or authorizers. :param action_url: The url at which the target Action Provider is located. :param authorizer: The authorizer to use for validating requests to the Action Provider. :param http_timeout: The amount of time to wait for connections to the Action Provider to be made. **Examples** >>> authorizer = ... >>> action_url = "https://actions.globus.org/hello_world" >>> ac = ActionClient.new_client(action_url, authorizer) >>> print(ac.run({"echo_string": "Hello from SDK"})) """ return cls( "action_client", app_name="Globus Automate SDK - ActionClient", base_url=action_url, authorizer=authorizer, http_timeout=http_timeout, )

38.302752

91

0.628862

983

8,350

5.23296

0.267548

0.046268

0.026439

0.019829

0.250194

0.202566

0.185264

0.159603

0.145995

0

0.000849

0.29497

8,350

217

92

38.479263

0.87294

0.465389

0

0.128713

0

0.063049

0

1

0.09901

false

0

0.049505

0

0.267327

0

null

0

null

0

1

0

d16327d6f6de6412d5ee3afdf6424723bafa7c97

8,995

py

Python

number_plate_redaction.py

Hashim-Ali-Zaidi/https-github.com-parkpow-deep-license-plate-recognition

01ebc5090923c0cc959f4d8ce55e5cac06b2117f

[ "MIT" ]

21

2022-01-05T03:05:35.000Z

2022-03-31T19:28:27.000Z

number_plate_redaction.py

Hashim-Ali-Zaidi/https-github.com-parkpow-deep-license-plate-recognition

01ebc5090923c0cc959f4d8ce55e5cac06b2117f

[ "MIT" ]

10

2022-01-18T14:34:31.000Z

2022-03-14T07:43:38.000Z

number_plate_redaction.py

Hashim-Ali-Zaidi/https-github.com-parkpow-deep-license-plate-recognition

01ebc5090923c0cc959f4d8ce55e5cac06b2117f

[ "MIT" ]

2

2022-01-24T22:45:03.000Z

2022-01-27T19:13:23.000Z

import io import json import math import re from itertools import combinations from pathlib import Path from PIL import Image, ImageFilter, ImageDraw, ImageFont from plate_recognition import parse_arguments, recognition_api def draw_bb(im, data, new_size=(1920, 1050), text_func=None): draw = ImageDraw.Draw(im) font_path = Path('assets/DejaVuSansMono.ttf') if font_path.exists(): font = ImageFont.truetype(str(font_path), 10) else: font = ImageFont.load_default() rect_color = (0, 255, 0) for result in data: b = result['box'] coord = [(b['xmin'], b['ymin']), (b['xmax'], b['ymax'])] draw.rectangle(coord, outline=rect_color) draw.rectangle(((coord[0][0] - 1, coord[0][1] - 1), (coord[1][0] - 1, coord[1][1] - 1)), outline=rect_color) draw.rectangle(((coord[0][0] - 2, coord[0][1] - 2), (coord[1][0] - 2, coord[1][1] - 2)), outline=rect_color) if text_func: text = text_func(result) text_width, text_height = font.getsize(text) margin = math.ceil(0.05 * text_height) draw.rectangle( [(b['xmin'] - margin, b['ymin'] - text_height - 2 * margin), (b['xmin'] + text_width + 2 * margin, b['ymin'])], fill='white') draw.text((b['xmin'] + margin, b['ymin'] - text_height - margin), text, fill='black', font=font) if new_size: im = im.resize(new_size) return im def blur(im, blur_amount, api_res, ignore_no_bb=False, ignore_list=None): for res in api_res.get('results', []): if ignore_no_bb and res['vehicle']['score'] == 0.0: continue if ignore_list: skip_blur = False for ignore_regex in ignore_list: if re.search(ignore_regex, res['plate']): skip_blur = True break if skip_blur: continue b = res['box'] width, height = b['xmax'] - b['xmin'], b['ymax'] - b['ymin'] crop_box = (b['xmin'], b['ymin'], b['xmax'], b['ymax']) ic = im.crop(crop_box) # Increase amount of blur with size of bounding box blur_image = ic.filter( ImageFilter.GaussianBlur(radius=math.sqrt(width * height) * .3 * blur_amount / 10)) im.paste(blur_image, crop_box) return im def bb_iou(a, b): # determine the (x, y)-coordinates of the intersection rectangle x_a = max(a["xmin"], b["xmin"]) y_a = max(a["ymin"], b["ymin"]) x_b = min(a["xmax"], b["xmax"]) y_b = min(a["ymax"], b["ymax"]) # compute the area of both the prediction and ground-truth # rectangles area_a = (a["xmax"] - a["xmin"]) * (a["ymax"] - a["ymin"]) area_b = (b["xmax"] - b["xmin"]) * (b["ymax"] - b["ymin"]) # compute the area of intersection rectangle area_inter = max(0, x_b - x_a) * max(0, y_b - y_a) return area_inter / float(max(area_a + area_b - area_inter, 1)) def clean_objs(objects, threshold=.1): # Only keep the ones with best score or no overlap for o1, o2 in combinations(objects, 2): if 'remove' in o1 or 'remove' in o2 or bb_iou(o1['box'], o2['box']) <= threshold: continue if o1['score'] > o2['score']: o2['remove'] = True else: o1['remove'] = True return [x for x in objects if 'remove' not in x] def merge_results(images): result = dict(results=[]) for data in images: for item in data['prediction']['results']: result['results'].append(item) for b in [item['box'], item['vehicle'].get("box", {})]: b['ymin'] += data['y'] b['xmin'] += data['x'] b['ymax'] += data['y'] b['xmax'] += data['x'] result['results'] = clean_objs(result['results']) return result def inside(a, b): return (a["xmin"] > b["xmin"] and a["ymin"] > b["ymin"] and a["xmax"] < b["xmax"] and a["ymax"] < b["ymax"]) def post_processing(results): new_list = [] for item in results['results']: if item['score'] < .2 and any([ inside(x['box'], item['box']) for x in results['results'] if x != item ]): continue new_list.append(item) results['results'] = new_list return results def process_image(path, args, i): config = dict(threshold_d=args.detection_threshold, threshold_o=args.ocr_threshold, mode='redaction') # Predictions source_im = Image.open(path) if source_im.mode != 'RGB': source_im = source_im.convert('RGB') images = [((0, 0), source_im)] # Entire image # Top left and top right crops if args.split_image: y = 0 win_size = .55 width, height = source_im.width * win_size, source_im.height * win_size for x in [0, int((1 - win_size) * source_im.width)]: images.append(((x, y), source_im.crop( (x, y, x + width, y + height)))) # Inference results = [] for (x, y), im in images: im_bytes = io.BytesIO() im.save(im_bytes, 'JPEG', quality=95) im_bytes.seek(0) im_results = recognition_api(im_bytes, args.regions, args.api_key, args.sdk_url, config=config) results.append(dict(prediction=im_results, x=x, y=y)) results = post_processing(merge_results(results)) results['filename'] = Path(path).name # Set bounding box padding for item in results['results']: # Decrease padding size for large bounding boxes b = item['box'] width, height = b['xmax'] - b['xmin'], b['ymax'] - b['ymin'] padding_x = int( max(0, width * (.3 * math.exp(-10 * width / source_im.width)))) padding_y = int( max(0, height * (.3 * math.exp(-10 * height / source_im.height)))) b['xmin'] = b['xmin'] - padding_x b['ymin'] = b['ymin'] - padding_y b['xmax'] = b['xmax'] + padding_x b['ymax'] = b['ymax'] + padding_y if args.show_boxes or args.save_blurred: im = blur(source_im, 5, results, ignore_no_bb=args.ignore_no_bb, ignore_list=args.ignore_regexp) if args.show_boxes: im.show() if args.save_blurred: filename = Path(path) im.save(filename.parent / ('%s_blurred%s' % (filename.stem, filename.suffix))) if 0: draw_bb(source_im, results['results']).show() return results def custom_args(parser): parser.epilog += 'To analyse the image for redaction: python number_plate_redaction.py --api-key MY_API_KEY --split-image /tmp/car.jpg' parser.add_argument( '--split-image', action='store_true', help= 'Do extra lookups on parts of the image. Useful on high resolution images.' ) parser.add_argument('--show-boxes', action='store_true', help='Display the resulting blurred image.') parser.add_argument( '--save-blurred', action='store_true', help='Blur license plates and save image in filename_blurred.jpg.') parser.add_argument( '--ignore-regexp', action='append', help='Plate regex to ignore during blur. Usually invalid plate numbers.' ) parser.add_argument( '--ignore-no-bb', action='store_true', help='Ignore detections without a vehicle bounding box during blur.') parser.add_argument( '--detection-threshold', type=float, default=.2, help='Keep all detections above this threshold. Between 0 and 1.') parser.add_argument( '--ocr-threshold', type=float, default=.5, help= 'Keep all plates if the characters reading score is above this threshold. Between 0 and 1.' ) def main(): args = parse_arguments(custom_args) result = [] for i, path in enumerate(args.files): if Path(path).is_file(): result.append(process_image(path, args, i)) if 0: for im_result in result: for i, x in enumerate(im_result['results']): im_result['results'][i] = dict(dscore=x['dscore'], score=x['score'], box=x['box']) print(json.dumps(result, indent=2)) if __name__ == '__main__': main()

34.596154

140

0.531184

1,139

8,995

4.060579

0.217735

0.014054

0.02573

0.016432

0.086486

0.067459

0.043243

0.014703

0

0.015431

0.329961

8,995

259

141

34.72973

0.75195

0.045359

0

0.150235

0

0.004695

0.143457

0.01073

0

1

0.046948

false

0

0.037559

0.004695

0.122066

0.004695

0

null

0

null

0

1

0

d163f1d2396b5d8d3b6886c2d5299e1f66284e91

7,229

py

Python

events/admin.py

roberzguerra/rover

14b6a7a47e75d6b6f8ca44fc0eb1cca500e0eecb

[ "BSD-3-Clause" ]

2

2015-12-02T17:26:12.000Z

2015-12-03T00:43:14.000Z

events/admin.py

roberzguerra/rover

14b6a7a47e75d6b6f8ca44fc0eb1cca500e0eecb

[ "BSD-3-Clause" ]

1

2015-12-02T17:26:43.000Z

2016-03-15T00:01:20.000Z

events/admin.py

roberzguerra/rover

14b6a7a47e75d6b6f8ca44fc0eb1cca500e0eecb

[ "BSD-3-Clause" ]

null

# -*- coding:utf-8 -*- from copy import deepcopy from django.db.models import Q from django.core.urlresolvers import reverse from django.utils.safestring import mark_safe from django.utils.translation import ugettext_lazy as _ from django.contrib import admin from mezzanine.core.admin import DisplayableAdmin, TabularDynamicInlineAdmin from ajax_select.admin import AjaxSelectAdminTabularInline from ajax_select.fields import autoselect_fields_check_can_add from events.forms import EventForm, \ BlockForm, \ EventBlockInlineForm, \ ProgramationForm, \ EventProgramationInlineForm from events.models import Event, Block, EventBlock, Programation, EventProgramation from ajax_select import register, LookupChannel @register('event_blocks') class EventBlockLookup(LookupChannel): """ Lookup para EventBlock """ model = Block def get_query(self, q, request): teste return self.model.objects.filter(title__icontains=q) def format_item_display(self, item): return u"%s" % item.title @register('event_programations') class EventProgramationLookup(LookupChannel): """ Lookup para EventProgramation """ model = Programation def get_query(self, q, request): return self.model.objects.filter(Q(title__icontains=q) | Q(date_time__icontains=q)) def format_item_display(self, item): return u"%s" % (item) programation_fieldsets = deepcopy(DisplayableAdmin.fieldsets) programation_fieldsets[0][1]["fields"].extend(['date_time','image','content']) programation_list_display = ["title", "status", "description", "events_using"] # "admin_link"] class ProgramationAdmin(DisplayableAdmin): """ Admin dos Eventos """ form = ProgramationForm fieldsets = programation_fieldsets list_display = programation_list_display # def link_event_change(self, obj): # html = u' - ' # if obj.event: # html = u'<a href="%s">%s</a>' % (obj.event.get_admin_url(), obj.event) # return html # link_event_change.allow_tags = True # link_event_change.short_description = _(u"Evento") def get_form(self, request, obj=None, **kwargs): form = super(ProgramationAdmin, self).get_form(request, obj, **kwargs) autoselect_fields_check_can_add(form, self.model, request.user) return form def events_using(self, obj): """ monta um link com os eventos utilizando a programação :param obj: :return: """ html = '' event_programations = obj.eventprogramation_set.all() event_ids = [] for event_programation in event_programations: event_ids.append(event_programation.event.id) if event_ids: events = Event.objects.filter(id__in=event_ids) for event in events: html += "<a href=\"%s\">%s</a>, " % (event.get_admin_url(), event) return mark_safe(html) events_using.allow_tags = True events_using.short_description = _(u"Utilizando nos eventos") block_fieldsets = deepcopy(DisplayableAdmin.fieldsets) block_fieldsets[0][1]["fields"].extend(['content']) block_list_display = ["title", "status", "description", "events_using"] # "admin_link"] class BlockAdmin(DisplayableAdmin): """ Admin dos Eventos """ form = BlockForm fieldsets = block_fieldsets list_display = block_list_display # def link_event_change(self, obj): # html = u' - ' # if obj.event: # html = u'<a href="%s">%s</a>' % (obj.event.get_admin_url(), obj.event) # return html # link_event_change.allow_tags = True # link_event_change.short_description = _(u"Evento") def get_form(self, request, obj=None, **kwargs): form = super(BlockAdmin, self).get_form(request, obj, **kwargs) autoselect_fields_check_can_add(form, self.model, request.user) return form def events_using(self, obj): """ monta um link com os eventos utilizando o Bloco :param obj: :return: """ html = '' event_blocks = obj.eventblock_set.all() event_ids = [] for event_block in event_blocks: event_ids.append(event_block.event.id) if event_ids: events = Event.objects.filter(id__in=event_ids) for event in events: html += "<a href=\"%s\">%s</a>, " % (event.get_admin_url(), event) return mark_safe(html) events_using.allow_tags = True events_using.short_description = _(u"Utilizando nos eventos") class EventBlockInline(TabularDynamicInlineAdmin, AjaxSelectAdminTabularInline): model = EventBlock form = EventBlockInlineForm ordering = ('_order',) fieldsets = ( (None, { #"fields": ["name", "status", "image", "date_time", "content"], "fields": ["block", "type", "link_menu", "status", "_order"], }), ) # Teste de personalizacao do Admin template = "admin/includes/event_dynamic_inline_tabular.html" def get_form(self, request, obj=None, **kwargs): form = super(EventBlockInline, self).get_form(request, obj, **kwargs) autoselect_fields_check_can_add(form, self.model, request.user) return form class EventProgramationInline(TabularDynamicInlineAdmin, AjaxSelectAdminTabularInline): model = EventProgramation form = EventProgramationInlineForm ordering = ('_order',) fieldsets = ( (None, { #"fields": ["name", "status", "image", "date_time", "content"], "fields": ["programation", "status", "_order"], }), ) # Teste de personalizacao do Admin template = "admin/includes/event_dynamic_inline_tabular.html" def get_form(self, request, obj=None, **kwargs): form = super(EventBlockInline, self).get_form(request, obj, **kwargs) autoselect_fields_check_can_add(form, self.model, request.user) return form event_fieldsets = deepcopy(DisplayableAdmin.fieldsets) event_fieldsets[0][1]["fields"].extend([ 'event_title_menu','event_description_short', 'event_logo', 'event_title', 'event_image_background', 'event_social_image', 'code', ]) event_list_display = ["title", "status", "preview_link"] class EventAdmin(DisplayableAdmin): """ Admin dos Eventos """ form = EventForm fieldsets = event_fieldsets list_display = event_list_display #filter_horizontal = ("categories",) inlines = [ EventBlockInline, EventProgramationInline, ] def get_form(self, request, obj=None, **kwargs): form = super(EventAdmin, self).get_form(request, obj, **kwargs) autoselect_fields_check_can_add(form, self.model, request.user) return form def preview_link(self, obj): return u'<a target="_blank" href="%s">%s</a>' % (reverse('events:event-preview', args=(obj.slug,)), _(u"Pré-visualizar")) preview_link.allow_tags = True preview_link.short_description = _(u"Pré-visualizar") admin.site.register(Event, EventAdmin) admin.site.register(Block, BlockAdmin) admin.site.register(Programation, ProgramationAdmin)

33.467593

129

0.670632

823

7,229

5.673147

0.190765

0.014993

0.026987

0.030842

0.529235

0.464339

0.445063

0

0.001223

0.208466

7,229

216

130

33.467593

0.81475

0.142343

0

0.386364

0

0.110023

0.030368

0

1

0.090909

false

0

0.090909

0.030303

0.492424

0

null

0

null

0

1

0

d1640c3248a566d8c4b0b2e5d95f52de1ad31f75

4,904

py

Python

api/calculate_frequencies.py

GTJuniorDesign0100-2020/anti-malarial-MCMC-bayesian-algorithm

8ab95c9b65275096dd86268fbb99bb37b6806e05

[ "MIT" ]

1

2020-10-28T18:19:21.000Z

api/calculate_frequencies.py

GTJuniorDesign0100-2020/anti-malarial-MCMC-bayesian-algorithm

8ab95c9b65275096dd86268fbb99bb37b6806e05

[ "MIT" ]

45

2020-09-03T22:17:36.000Z

2020-12-06T02:51:46.000Z

api/calculate_frequencies.py

GTJuniorDesign0100-2020/anti-malarial-MCMC-bayesian-algorithm

8ab95c9b65275096dd86268fbb99bb37b6806e05

[ "MIT" ]

1

2020-12-07T16:47:54.000Z

import pandas as pd import numpy as np import math import statistics import api.recrudescence_utils as recrudescence_utils def calculate_frequencies3(genotypedata, alleles_definitions): ''' Calculate frequencies of alleles Using the input data table and alleles_definition which contains the lower and upper break values of the allele data, this method calculates the amount (frequency) and the variability of raw allele data in each lower and upper break values. Returns a list that that contains the following: - index[0] type: numpy array description: the length of each list of frequencies - index[1] type: numpy matrix description: the matrix (number of locinames by number of alleles) that contains the frequency values - index[2] type: numpy array description: mean SD of within allele length :param genotypedata type: pandas dataframe description: genetic data, where first column (name 'Sample ID') has the id of the sample, and rest of columns have the format nameoflocus_X, where X is the xth allele detected :param alleles_definitions type: list that contains dataframe description: list of length number of loci each entry is a number of alleles by 2 matrix (1st column = lower bound, 2nd column = upper bound) ''' locinames = recrudescence_utils.get_locinames(genotypedata) nloci = len(locinames) frequencies = [] variability = [] n = 0 for j in range(nloci): # retrieve raw alleles (each index contains every raw alleles data with the same locinames) # ex. all data with X313 prefix lociname in index 0 loci_name_prefix, last_index = locinames.get(j) raw_alleles, n = recrudescence_utils.get_RawAlleles(genotypedata, n, last_index) # lower = list of lower bound values # high = list of upper bound values low = alleles_definitions[j]["0"] high = alleles_definitions[j]["1"] # length of the lower bound and upper bound list nrows = len(alleles_definitions[j]) sum_list, meanSD = _get_sumList(nrows, raw_alleles, low, high) frequencies.append(sum_list) variability.append(meanSD) frequencies[j] = frequencies[j] / len(raw_alleles) # switch freq_length and variability list to numpy array freq_length = np.asarray([len(frequencies[j]) for j in range(len(frequencies))]) variability = np.asarray(variability) ncol = max(freq_length) # create matrix with frequency values from frequencies list freqmatrix = _create_frequencyMatrix(nloci, ncol, frequencies) # final result ret = _pack_result(freq_length, freqmatrix, variability) return ret def _get_sumList(nrows: int, raw_alleles: list, low: pd.core.series.Series, high: pd.core.series.Series): ''' Returns a numpy array of the number of allele values that is between lower and upper bound values Also returns a mean of standard deviation of that numpy array. :param nrows: The number of rows of the alleles_definition :param raw_alleles: The allele values retrieved from the input file :param low: The list of the lower bound values from the alleles_definition :param high: The list of the upper bound values from the alleles_definition ''' sum_list = [] # needed for storing frequency values sd_list = [] # standard deviation for i in range(nrows): tf_table = [] result_sum = 0 for allele in raw_alleles: eval = allele > low[i] and allele <= high[i] tf_table.append(eval) if eval: result_sum += 1 sum_list.append(result_sum) true_items = [] for eval_i in range(len(tf_table)): if tf_table[eval_i]: true_items.append(raw_alleles[eval_i]) if len(true_items) > 1: sd_list.append(statistics.stdev(true_items)) sum_list = np.array(sum_list) # mean of standard deviation meanSD = 0 if (len(sd_list) > 0): meanSD = np.mean(sd_list) return sum_list, meanSD def _create_frequencyMatrix(nloci: int, ncol: np.int64, frequencies: list): ''' Turn 1D frequencies list into 2D numpy matrix :param nloci: The number of rows :param ncol: The number of columns :param frequencies: The 1D list that contains the frequency values ''' # initialize frequency matrix with zeros freqmatrix = np.zeros([nloci, ncol]) # fill out each box in the frequency matrix with frequency values from frequencies list for j in range(nloci): for i in range(len(frequencies[j])): freqmatrix[j][i] = frequencies[j][i] return freqmatrix def _pack_result(freq_lengths: np.ndarray, freqmatrix: np.ndarray, variability: np.ndarray): ''' Returns a Frequency object that contains all frequency-related matrices and arrays ''' frequency_result = Frequencies(freq_lengths, freqmatrix, variability) return frequency_result class Frequencies: ''' Holds the related results of calculated frequencies ''' def __init__(self, freq_lengths: np.ndarray, freqmatrix: np.ndarray, variability: np.ndarray): self.lengths = freq_lengths self.matrix = freqmatrix self.variability = variability

32.263158

105

0.753263

720

4,904

5.020833

0.231944

0.024896

0.012172

0.009129

0.115076

0.076349

0.056985

0.032642

0

0.005908

0.171697

4,904

151

106

32.476821

0.884047

0.523654

0

0.03125

0

0.000831

0

1

0.078125

false

0

0.078125

0

0.234375

0

null

0

null

0

1

0

d165298f9d6c2dd4e54aa2831a62b33e2abb9ed6

305

py

Python

linked_lists/linked_list_middle.py

MrCsabaToth/IK

713f91c28af7b4a964ba854ede9fec73bf0c4682

[ "Apache-2.0" ]

null

linked_lists/linked_list_middle.py

MrCsabaToth/IK

713f91c28af7b4a964ba854ede9fec73bf0c4682

[ "Apache-2.0" ]

null

linked_lists/linked_list_middle.py

MrCsabaToth/IK

713f91c28af7b4a964ba854ede9fec73bf0c4682

[ "Apache-2.0" ]

null

#Reference: #LinkedListNode { # int val # LinkedListNode next #} def find_middle_node(head): if not head: return None node = head mid = node i = 0 while node.next: if not i % 2: mid = mid.next node = node.next i += 1 return mid

14.52381

27

0.521311

39

305

4.025641

0.512821

0.101911

0

0.016304

0.396721

305

20

28

15.25

0.836957

0.2

0

1

0.083333

false

0

0.25

0

null

0

null

0

1

0

d1657091800903e794906206a91e8aff42673361

178

py

Python

beginner_contest/172/D.py

FGtatsuro/myatcoder

25a3123be6a6311e7d1c25394987de3e35575ff4

[ "MIT" ]

null

beginner_contest/172/D.py

FGtatsuro/myatcoder

25a3123be6a6311e7d1c25394987de3e35575ff4

[ "MIT" ]

null

beginner_contest/172/D.py

FGtatsuro/myatcoder

25a3123be6a6311e7d1c25394987de3e35575ff4

[ "MIT" ]

null

import sys input = sys.stdin.readline sys.setrecursionlimit(10 ** 7) n = int(input()) ans = 0 for i in range(1, n+1): j = n // i ans += (j * (j+1) * i) // 2 print(ans)

14.833333

31

0.55618

33

178

3

0.606061

0

0.059701

0.247191

178

11

32

16.181818

0.679104

0

1

0

false

0

0.111111

0

0.111111

0

null

0

null

0

1

0

d165bc6f340cc6a3b2581ecbbfc90108635787e6

2,056

py

Python

demo/writing_xml.py

zepheira/amara

d3ffe07d6e2266b34d72b012a82d572c8edbf1e7

[ "Apache-2.0" ]

6

2015-01-30T03:50:36.000Z

2022-03-20T16:09:58.000Z

demo/writing_xml.py

zepheira/amara

d3ffe07d6e2266b34d72b012a82d572c8edbf1e7

[ "Apache-2.0" ]

2

2015-02-04T17:18:47.000Z

2019-09-27T23:39:52.000Z

demo/writing_xml.py

zepheira/amara

d3ffe07d6e2266b34d72b012a82d572c8edbf1e7

[ "Apache-2.0" ]

6

2015-02-04T16:16:18.000Z

2019-10-30T20:07:48.000Z

#Import the basic writer class for users from amara import writer w = writer(indent=u"yes") #Operates in streaming mode w.start_document() w.start_element(u'xsa') w.start_element(u'vendor') #Element with simple text (#PCDATA) content w.simple_element(u'name', content=u'Centigrade systems') #Note writer.text(content) still works w.simple_element(u'email', content=u"info@centigrade.bogus") w.end_element(u'vendor') #Element with an attribute w.start_element(u'product', attributes={u'id': u"100\u00B0"}) #Note w.attribute(name, value, namespace=None) still works w.simple_element(u'name', content=u"100\u00B0 Server") #XML fragment #w.xml_fragment('<version>1.0</version><last-release>20030401</last-release>') #Empty element w.simple_element(u'changes') w.end_element(u'product') w.end_element(u'xsa') w.end_document() print #Now an HTML example w = writer(method=u"html") #indent=u"yes" is default in this mode w.start_document() w.start_element(u'html') w.start_element(u'head') w.simple_element(u'title', content=u'Hello') w.end_element(u'head') w.start_element(u'body') #w.start_element(u'body', attributes={u'id': u"100\u00B0"}) w.simple_element(u'p', content=u"World") #XML fragment #w.xml_fragment('<version>1.0</version><last-release>20030401</last-release>') #Empty element w.simple_element(u'br') w.end_element(u'html') w.end_document() print from amara.writers.struct import * w = structwriter(indent=u"yes").feed( ROOT( E(u'doc', E(u'a', u'hello'), #E('float-content', 3.14), E((None, u'b'), u'this is unicode: \u221e'), #E(u'list-content', [E('child', 'a'), RAW('<raw-node message="hello"/>'), E('child', 'b')]), E(u'c', {u'parrot': u'dead', u'spam': u'eggs'}), E((None, u'c'), {u'parrot': u'dead', (None, u'spam'): u'eggs'}, u'again'), E(u'gen-content', (E('node', x) for x in range(6))), E(u'monty', E('spam', 'eggs')), E(u'empty'), E(u'func', lambda: u'this is a func'), #E(u'raw-xml-content', RAW('<a>b</a>', '<c>d</c>')) #The multiple raw text bits are just concatenated ) )) print

31.630769

105

0.683366

361

2,056

3.822715

0.307479

0.110145

0.065942

0.071014

0.364493

0.302174

0.224638

0.185507

0.13913

0

0.024523

0.10749

2,056

64

106

32.125

0.72752

0.368677

0

0.166667

0

0.229444

0.016445

0

1

0

false

0

0.047619

0

0.047619

0.071429

0

null

0

null

0

1

0

d16615251ad54e500022f66f41091dcdb069f334

4,295

py

Python

opencood/utils/eval_utils.py

YuanYunshuang/OpenCOOD

98e07eb45f7fdcd32518b2cf8f9052f73ca80bec

[ "Apache-2.0" ]

null

opencood/utils/eval_utils.py

YuanYunshuang/OpenCOOD

98e07eb45f7fdcd32518b2cf8f9052f73ca80bec

[ "Apache-2.0" ]

null

opencood/utils/eval_utils.py

YuanYunshuang/OpenCOOD

98e07eb45f7fdcd32518b2cf8f9052f73ca80bec

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Author: Runsheng Xu <rxx3386@ucla.edu> # License: TDG-Attribution-NonCommercial-NoDistrib import os import numpy as np import torch from opencood.utils import common_utils from opencood.hypes_yaml import yaml_utils def voc_ap(rec, prec): """ VOC 2010 Average Precision. """ rec.insert(0, 0.0) rec.append(1.0) mrec = rec[:] prec.insert(0, 0.0) prec.append(0.0) mpre = prec[:] for i in range(len(mpre) - 2, -1, -1): mpre[i] = max(mpre[i], mpre[i + 1]) i_list = [] for i in range(1, len(mrec)): if mrec[i] != mrec[i - 1]: i_list.append(i) ap = 0.0 for i in i_list: ap += ((mrec[i] - mrec[i - 1]) * mpre[i]) return ap, mrec, mpre def caluclate_tp_fp(det_boxes, det_score, gt_boxes, result_stat, iou_thresh): """ Calculate the true positive and false positive numbers of the current frames. Parameters ---------- det_boxes : torch.Tensor The detection bounding box, shape (N, 8, 3) or (N, 4, 2). det_score :torch.Tensor The confidence score for each preditect bounding box. gt_boxes : torch.Tensor The groundtruth bounding box. result_stat: dict A dictionary contains fp, tp and gt number. iou_thresh : float The iou thresh. """ # fp, tp and gt in the current frame fp = [] tp = [] gt = gt_boxes.shape[0] if det_boxes is not None: # convert bounding boxes to numpy array det_boxes = common_utils.torch_tensor_to_numpy(det_boxes) det_score = common_utils.torch_tensor_to_numpy(det_score) gt_boxes = common_utils.torch_tensor_to_numpy(gt_boxes) # sort the prediction bounding box by score score_order_descend = np.argsort(-det_score) det_polygon_list = list(common_utils.convert_format(det_boxes)) gt_polygon_list = list(common_utils.convert_format(gt_boxes)) # match prediction and gt bounding box for i in range(score_order_descend.shape[0]): det_polygon = det_polygon_list[score_order_descend[i]] ious = common_utils.compute_iou(det_polygon, gt_polygon_list) if len(gt_polygon_list) == 0 or np.max(ious) < iou_thresh: fp.append(1) tp.append(0) continue fp.append(0) tp.append(1) gt_index = np.argmax(ious) gt_polygon_list.pop(gt_index) result_stat[iou_thresh]['fp'] += fp result_stat[iou_thresh]['tp'] += tp result_stat[iou_thresh]['gt'] += gt def calculate_ap(result_stat, iou): """ Calculate the average precision and recall, and save them into a txt. Parameters ---------- result_stat : dict A dictionary contains fp, tp and gt number. iou : float """ iou_5 = result_stat[iou] fp = iou_5['fp'] tp = iou_5['tp'] assert len(fp) == len(tp) gt_total = iou_5['gt'] cumsum = 0 for idx, val in enumerate(fp): fp[idx] += cumsum cumsum += val cumsum = 0 for idx, val in enumerate(tp): tp[idx] += cumsum cumsum += val rec = tp[:] for idx, val in enumerate(tp): rec[idx] = float(tp[idx]) / gt_total prec = tp[:] for idx, val in enumerate(tp): prec[idx] = float(tp[idx]) / (fp[idx] + tp[idx]) ap, mrec, mprec = voc_ap(rec[:], prec[:]) return ap, mrec, mprec def eval_final_results(result_stat, save_path): dump_dict = {} ap_30, mrec_30, mpre_30 = calculate_ap(result_stat, 0.30) ap_50, mrec_50, mpre_50 = calculate_ap(result_stat, 0.50) ap_70, mrec_70, mpre_70 = calculate_ap(result_stat, 0.70) dump_dict.update({'ap30': ap_30, 'ap_50': ap_50, 'ap_70': ap_70, 'mpre_50': mpre_50, 'mrec_50': mrec_50, 'mpre_70': mpre_70, 'mrec_70': mrec_70, }) yaml_utils.save_yaml(dump_dict, os.path.join(save_path, 'eval.yaml')) print('The Average Precision at IOU 0.3 is %.2f, ' 'The Average Precision at IOU 0.5 is %.2f, ' 'The Average Precision at IOU 0.7 is %.2f' % (ap_30, ap_50, ap_70))

27.532051

77

0.589523

628

4,295

3.826433

0.224522

0.049938

0.032459

0.031627

0.240533

0.195589

0.184353

0.066583

0.042447

0

0.037904

0.293597

4,295

155

78

27.709677

0.75412

0.208382

0

0.081395

0

0.057082

0

0.011628

1

0.046512

false

0

0.05814

0

0.127907

0.011628

0

null

0

null

0

1

0

d166cf6c9589c4871225d45b81518e6b37bcc726

1,568

py

Python

caj2pdf.py

ElonH/caj2pdf_gui

48fdab29144f77bd2360dce7457a252f859c13e4

[ "Naumen", "Condor-1.1", "MS-PL" ]

127

2018-11-08T08:19:39.000Z

2022-03-12T15:19:26.000Z

caj2pdf.py

kennylx/caj2pdf_gui

48fdab29144f77bd2360dce7457a252f859c13e4

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

caj2pdf.py

kennylx/caj2pdf_gui

48fdab29144f77bd2360dce7457a252f859c13e4

[ "Naumen", "Condor-1.1", "MS-PL" ]

23

2019-04-01T02:54:31.000Z

2022-02-26T06:06:07.000Z

#!/usr/bin/env python3 import os import argparse from cajparser import CAJParser from utils import add_outlines if __name__ == "__main__": parser = argparse.ArgumentParser() subparsers = parser.add_subparsers(help="commands", dest="command") show_parser = subparsers.add_parser("show", help="Show the information of the CAJ file.") show_parser.add_argument("input", help="Path to the CAJ file.") convert_parser = subparsers.add_parser("convert", help="Convert the CAJ file to PDF file.") convert_parser.add_argument("input", help="Path to the CAJ file.") convert_parser.add_argument("-o", "--output", help="Output path to the PDF file.", required=True) outlines_parser = subparsers.add_parser("outlines", help="Extract outlines from the CAJ file and add it to PDF file.") outlines_parser.add_argument("input", help="Path to the CAJ file.") outlines_parser.add_argument("-o", "--output", help="Path to the PDF file.", required=True) args = parser.parse_args() if args.command == "show": caj = CAJParser(args.input) print("File: {0}\nType: {1}\nPage count: {2}\nOutlines count: {3}\n".format( args.input, caj.format, caj.page_num, caj.toc_num )) if args.command == "convert": caj = CAJParser(args.input) caj.convert(args.output) if args.command == "outlines": caj = CAJParser(args.input) toc = caj.get_toc() add_outlines(toc, args.output, "tmp.pdf") os.replace("tmp.pdf", args.output)

36.465116

122

0.657526

212

1,568

4.716981

0.283019

0.054

0.06

0.052

0.289

0.258

0.208

0.152

0

0.004023

0.20727

1,568

42

123

37.333333

0.800483

0.013393

0

0.09375

0

0.03125

0.265201

0

1

0

false

0

0.125

0

0.125

0.03125

0

null

0

null

0

1

0

d169e15fc76abd672102835ffb60d42da63ce07b

3,764

py

Python

razor/pool.py

lahiri-phdworks/OCCAM

21919b0819606b8f76a391965151fba6df86cee7

[ "BSD-3-Clause" ]

1

2021-04-27T01:33:01.000Z

razor/pool.py

lahiri-phdworks/OCCAM

21919b0819606b8f76a391965151fba6df86cee7

[ "BSD-3-Clause" ]

1

2020-07-22T21:59:54.000Z

razor/pool.py

lahiri-phdworks/OCCAM

21919b0819606b8f76a391965151fba6df86cee7

[ "BSD-3-Clause" ]

1

2020-11-25T12:24:36.000Z

""" OCCAM Copyright (c) 2011-2017, SRI International All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of SRI International nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Thread pool for processing modules in parallel. """ from Queue import Queue import threading import traceback import sys class Worker(threading.Thread): """ A daemon worker thread. """ def __init__(self, q): """ Initializes a thread in the queue q. """ threading.Thread.__init__(self) self.daemon = True self.queue = q def run(self): """ The thread main. """ while True: f = self.queue.get(True) f() class ThreadPool(object): """ A pool of daemon worker threads. """ def __init__(self, count=3): """ Initializes a pool queue. """ self.queue = Queue() self.workers = None self.count = count def _start(self): if self.workers is None: self.workers = [Worker(self.queue)] for w in self.workers: w.start() def map(self, f, args): self._start() result = [None for i in range(0, len(args))] sem = threading.Semaphore(0) def func(i): def rf(): try: result[i] = f(args[i]) except Exception: seperator = '-' * 60 print("Exception in worker for {0}:".format(f.func_doc)) print(seperator) traceback.print_exc(file=sys.stderr) print(seperator) sys.exit(1) #iam: was _exit; but are we really that low level? finally: sem.release() return rf for i in range(0, len(args)): self.queue.put(func(i)) for _ in args: sem.acquire(True) return result def shutdown(self): pass POOL = ThreadPool(3) def getDefaultPool(): return POOL def InParallel(f, args, pool=None): import datetime dt = datetime.datetime.now ().strftime ('%d/%m/%Y %H:%M:%S') sys.stderr.write("[%s] Starting %s...\n" % (dt, f.func_doc)) if pool is None: pool = getDefaultPool() result = pool.map(f, args) sys.stderr.write("done\n") return result def shutdownDefaultPool(): POOL.shutdown()

31.366667

83

0.632837

486

3,764

4.86214

0.434156

0.019044

0.014388

0.019467

0.093948

0.073635

0.057554

0

0.00632

0.285335

3,764

119

84

31.630252

0.872119

0.472635

0

0.064516

0

0.037981

0

1

0.177419

false

0.016129

0.080645

0.016129

0.354839

0.064516

0

null

0

null

0

1

0

d16a87fa6f7d9f74b352a27443e5a31a5a09e5e7

6,729

py

Python

cplusplus/level1_single_api/4_op_dev/1_custom_op/tbe/impl/conv2d_tik.py

coldenheart/123

798768bba7dfaef051a46d8e1df48bc671de5213

[ "Apache-2.0" ]

25

2020-11-20T09:01:35.000Z

2022-03-29T10:35:38.000Z

cplusplus/level1_single_api/4_op_dev/1_custom_op/tbe/impl/conv2d_tik.py

coldenheart/123

798768bba7dfaef051a46d8e1df48bc671de5213

[ "Apache-2.0" ]

5

2021-02-28T20:49:37.000Z

2022-03-04T21:50:27.000Z

cplusplus/level1_single_api/4_op_dev/1_custom_op/tbe/impl/conv2d_tik.py

coldenheart/123

798768bba7dfaef051a46d8e1df48bc671de5213

[ "Apache-2.0" ]

16

2020-12-06T07:26:13.000Z

2022-03-01T07:51:55.000Z

""" Copyright (C) 2019. Huawei Technologies Co., Ltd. All rights reserved. This program is free software; you can redistribute it and/or modify it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License. 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 at http://www.apache.org/licenses/LICENSE-2.0 conv2d_tik """ from __future__ import absolute_import import numpy as np from tbe import tik DTYPE_SIZE = { 'bool': 1, 'uint8': 1, 'int8': 1, 'uint16': 2, 'int16': 2, 'int24': 3, 'uint32': 4, 'int32': 4, 'float16': 2, 'float32': 4, 'int48': 6, 'int64': 8, 'uint64': 8, 'float64':8 } def conv2d_tik_compute(params): """ conv2d tik compute @param params: conv2d data @return: tik instance """ tik_instance = tik.Tik() # get shape of feature map and weight n, c1, h, w, c0 = params["fm_shape"] c1, kh, kw, cout, c0 = params["weight_shape"] # get value of stride, dilation, pad stride_h, stride_w = params["stride_list"] dilation_h, dilation_w = params["dilation_list"] pad_top, pad_bot, pad_left, pad_right = params["pad_list"] # calculate height and width kh_dilation = (kh - 1) * dilation_h + 1 kw_dilation = (kw - 1) * dilation_w + 1 ho = int(np.ceil((h + pad_top + pad_bot - kh_dilation + 1) / stride_h)) wo = int(np.ceil((w + pad_right + pad_left - kw_dilation + 1) / stride_w)) round_howo = ((ho * wo + 16 - 1) // 16) * 16 fm_gm = tik_instance.Tensor(params['fm_dtype'], (n, c1, h, w, c0), name='fm_gm', scope=tik.scope_gm) weight_gm = tik_instance.Tensor(params['weight_type'], (c1, kh, kw, cout, c0), name='weight_gm', scope=tik.scope_gm) dst_gm = tik_instance.Tensor(params['dst_gm_type'], [n, cout // 16, ho, wo, 16], name='dst_gm', scope=tik.scope_gm) core_num = params['core_num'] pre_core_cout = cout // core_num cout_iter_num = pre_core_cout // params["cout_split_factor"] Cin_blocks = c1 with tik_instance.for_range(0, core_num, block_num=core_num) as cout_o: with tik_instance.for_range(0, cout_iter_num, thread_num=1) as cout_i: weight_L1 = tik_instance.Tensor( params['weight_type'], (Cin_blocks, kh, kw, params["cout_split_factor"], c0), name='weight_l1', scope=tik.scope_cbuf) tik_instance.data_move( weight_L1, weight_gm.flatten()[cout_o * pre_core_cout * c0 + params["cout_split_factor"] * cout_i * c0], 0, Cin_blocks * kh * kw, params["cout_split_factor"], (cout - params["cout_split_factor"]), 0) with tik_instance.for_range(0, n, thread_num=2) as n_index: feature_map_l1 = tik_instance.Tensor(params['fm_dtype'], (c1, h, w, c0), name='feature_map_l1', scope=tik.scope_cbuf) tik_instance.data_move(feature_map_l1, fm_gm[n_index, :, :, :, :], 0, 1, c1 * h * w, 0, 0) dst_l0c = tik_instance.Tensor( params['dst_l0c_type'], [params["cout_split_factor"] // 16, round_howo, 16], name='dst_l0c', scope=tik.scope_cbuf_out) tik_instance.conv2d(dst_l0c, feature_map_l1, weight_L1, (c1, h, w, c0), (Cin_blocks, kh, kw, params["cout_split_factor"], c0), params['stride_list'], [pad_left, pad_right, pad_top, pad_bot], params['dilation_list'], params['pad_value']) tik_instance.fixpipe( dst_gm[n_index, (cout_o * pre_core_cout + params["cout_split_factor"] * cout_i) // (32 // DTYPE_SIZE[params['dst_gm_type']]), 0, 0, 0], dst_l0c, params["cout_split_factor"] // 16, ho * wo * 16 * DTYPE_SIZE[params['dst_l0c_type']] // 32, 0, 0, extend_params={"bias": None, "quantize_params": params["quantize_params"]}) tik_instance.BuildCCE(kernel_name=params["kernel_name"], inputs=[fm_gm, weight_gm], outputs=[dst_gm], config={'l2_mode': 1}) return tik_instance def conv2d_tik(inputs, weights, outputs, strides, pads, dilations, kernel_name="conv2d_tik"): in_dtype = inputs.get("dtype") w_dtype = weights.get("dtype") res_dtype = outputs.get("dtype") in_shape = inputs.get("shape") w_shape = weights.get("ori_shape") if len(strides) != 4: raise RuntimeError("strides shape should be 4d.") if len(dilations) != 4: raise RuntimeError("dilations shape should be 4d.") if len(pads) != 4: raise RuntimeError("pads shape should be 4d.") if in_dtype != "float16" or w_dtype != "float16" or res_dtype != "float16": raise RuntimeError("dtype shape should be float16.") if weights.get("ori_format") != "NCHW": raise RuntimeError("format should be NCHW.") loc_dtype = "float32" quantize_params = {"mode": "fp322fp16", "mode_param": None} stride_list = [strides[2], strides[3]] dilation_list = [dilations[2], dilations[3]] w5hd_shape = [w_shape[1] // 16, w_shape[2], w_shape[3], w_shape[0], 16] params = { "fm_shape": in_shape, "weight_shape": w5hd_shape, "fm_dtype": in_dtype, "weight_type": w_dtype, "dst_l0c_type": loc_dtype, "dst_gm_type": res_dtype, "quantize_params": quantize_params, "pad_list": pads, "pad_value": 0, "stride_list": stride_list, "dilation_list": dilation_list, "cout_split_factor": 64, "core_num": 2, "kernel_name": kernel_name} conv2d_tik_compute(params)

40.293413

102

0.539605

836

6,729

4.077751

0.230861

0.054855

0.044001

0.055441

0.231446

0.151071

0.072162

0.053388

0.043414

0

0.039229

0.344628

6,729

166

103

40.536145

0.733787

0.104622

0

0.01626

0

0.150033

0

1

0.01626

false

0

0.02439

0

0.04878

0

null

0

null

0

1

0

d16ad1765d12c4ab3d586ee47e803dea6e2400a1

4,589

py

Python

core/src/zeit/cms/clipboard/clipboard.py

rickdg/vivi

16134ac954bf8425646d4ad47bdd1f372e089355

[ "BSD-3-Clause" ]

5

2019-05-16T09:51:29.000Z

2021-05-31T09:30:03.000Z

core/src/zeit/cms/clipboard/clipboard.py

rickdg/vivi

16134ac954bf8425646d4ad47bdd1f372e089355

[ "BSD-3-Clause" ]

107

2019-05-24T12:19:02.000Z

2022-03-23T15:05:56.000Z

core/src/zeit/cms/clipboard/clipboard.py

rickdg/vivi

16134ac954bf8425646d4ad47bdd1f372e089355

[ "BSD-3-Clause" ]

3

2020-08-14T11:01:17.000Z

2022-01-08T17:32:19.000Z

import zope.annotation import zope.component import zope.interface import zope.proxy import zope.publisher.interfaces import zope.security.interfaces import zope.traversing.api import zope.container.interfaces import zope.container.contained import zope.container.ordered import z3c.traverser.interfaces import zeit.cms.workingcopy.interfaces import zeit.cms.clipboard.interfaces @zope.component.adapter(zeit.cms.workingcopy.interfaces.IWorkingcopy) @zope.interface.implementer(zeit.cms.clipboard.interfaces.IClipboard) class Clipboard(zope.container.ordered.OrderedContainer): title = 'Clipboard' def addContent(self, reference_object, add_object, name=None, insert=False): """Add unique_id to obj.""" if not zeit.cms.clipboard.interfaces.IClipboardEntry.providedBy( reference_object): raise ValueError( "`reference_object` does not provide IClipboardEntry (%r)" % reference_object) if insert: container = reference_object position = 0 else: container = reference_object.__parent__ position = list(container.keys()).index( reference_object.__name__) + 1 if not zope.container.interfaces.IOrderedContainer.providedBy( container): raise ValueError('`reference_object` must be a Clip to insert.') entry = zeit.cms.clipboard.interfaces.IClipboardEntry(add_object) entry = zope.proxy.removeAllProxies(entry) order = list(container.keys()) chooser = zope.container.interfaces.INameChooser(container) name = chooser.chooseName(name, entry) container[name] = entry order.insert(position, name) container.updateOrder(order) def addClip(self, title): clip = zeit.cms.clipboard.entry.Clip(title) chooser = zope.container.interfaces.INameChooser(self) name = chooser.chooseName(title, clip) self[name] = clip return self[name] def moveObject(self, obj, new_container, insert=False): if not zeit.cms.clipboard.interfaces.IClipboardEntry.providedBy(obj): raise TypeError("obj must provided IClipboardEntry. Got %r." % obj) if obj == new_container: return if obj in zope.traversing.api.getParents(new_container): raise ValueError( "`obj` must not be an ancestor of `new_container`.") old_container = obj.__parent__ old_name = obj.__name__ del old_container[old_name] self.addContent(new_container, obj, old_name, insert) def __setitem__(self, key, value): if not zeit.cms.clipboard.interfaces.IClipboardEntry.providedBy(value): raise ValueError("Can only contain IClipboardEntry objects. " "Got %r instead." % value) super(Clipboard, self).__setitem__(key, value) clipboardFactory = zope.annotation.factory(Clipboard) @zope.interface.implementer(zeit.cms.clipboard.interfaces.IClipboard) @zope.component.adapter(zope.security.interfaces.IPrincipal) def principalAdapter(principal): """Shortcut adapter from principal to clipboard.""" workingcopy = zeit.cms.workingcopy.interfaces.IWorkingcopy(principal) return zeit.cms.clipboard.interfaces.IClipboard(workingcopy) @zope.component.adapter( zeit.cms.workingcopy.interfaces.IWorkingcopy, zope.publisher.interfaces.IPublisherRequest) @zope.interface.implementer(z3c.traverser.interfaces.IPluggableTraverser) class WorkingcopyTraverser(object): """Traverses to clipboard through a workingcopy.""" def __init__(self, context, request): self.context = context self.request = request def publishTraverse(self, request, name): clipboard = zeit.cms.clipboard.interfaces.IClipboard( self.context, None) if clipboard is not None and clipboard.__name__ == name: return clipboard raise zope.publisher.interfaces.NotFound(self.context, name, request) @zope.component.adapter(zeit.cms.clipboard.interfaces.IClipboard) class ClipboardNameChooser(zope.container.contained.NameChooser): """A namechooser removing invalid characters.""" def chooseName(self, name, object): name = name.replace('/', '') while name.startswith('+'): name = name.replace('+', '', 1) while name.startswith('@'): name = name.replace('@', '', 1) return super(ClipboardNameChooser, self).chooseName(name, object)

37.308943

79

0.687296

483

4,589

6.42029

0.248447

0.03386

0.056756

0.083844

0.253144

0.170268

0.155434

0.13286

0.041277

0

0.001662

0.213336

4,589

122

80

37.614754

0.857341

0.033994

0

0.042553

0

0.059384

0

1

0.085106

false

0

0.138298

0

0.319149

0

null

0

null

0

1

0

d16c1e89b2ab8da6e931b84bf07afa7c43410c07

1,640

py

Python

attendees/persons/serializers/attendingmeet_etc_serializer.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

null

attendees/persons/serializers/attendingmeet_etc_serializer.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

5

2022-01-21T03:26:40.000Z

2022-02-04T17:32:16.000Z

attendees/persons/serializers/attendingmeet_etc_serializer.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

null

from rest_framework import serializers from attendees.persons.models import AttendingMeet class AttendingMeetEtcSerializer(serializers.ModelSerializer): assembly = serializers.IntegerField(read_only=True) class Meta: model = AttendingMeet fields = "__all__" def create(self, validated_data): """ Create or update `AttendingMeet` instance, given the validated data. """ attendingmeet_id = self._kwargs["data"].get("id") obj, created = AttendingMeet.objects.update_or_create( id=attendingmeet_id, defaults=validated_data, ) return obj def update(self, instance, validated_data): """ Update and return an existing `AttendingMeet` instance, given the validated data. """ if ( True ): # need validations such as if the assembly matching meet, it's better to validate on UI first instance.meet = validated_data.get("meet", instance.meet) # instance.meet.assembly = validated_data.get('assembly', instance.meet.assembly) instance.meet.save() instance.attending = validated_data.get("attending", instance.attending) instance.start = validated_data.get("start", instance.start) instance.finish = validated_data.get("finish", instance.finish) instance.character = validated_data.get("character", instance.character) instance.category = validated_data.get("category", instance.category) instance.team = validated_data.get("team", instance.team) instance.save() return instance

36.444444

105

0.664634

172

1,640

6.209302

0.372093

0.15824

0.11985

0.054307

0.078652

0

0.241463

1,640

44

106

37.272727

0.858521

0.196951

0

0.045741

0

1

0.071429

false

0

0.071429

0

0.321429

0

null

0

null

0

1

0

d16c5eccf5ae33abe7cfa19ea89759066337ca25

6,475

py

Python

CDMouth/TextToSpeech.py

okcd00/CDAuto

d2c90062d537bad8c3749ae35542b5e50cb37db0

[ "MIT" ]

3

2020-03-05T10:09:57.000Z

2021-12-11T09:32:00.000Z

CDMouth/TextToSpeech.py

okcd00/CDAlter

43486591d2e5ae3d93ebfc21949894c5c8c8cd94

[ "MIT" ]

null

CDMouth/TextToSpeech.py

okcd00/CDAlter

43486591d2e5ae3d93ebfc21949894c5c8c8cd94

[ "MIT" ]

null

# coding: utf-8 # ========================================================================== # Copyright (C) 2018-2020 All rights reserved. # # filename : TextToSpeech.py # author : chendian / okcd00@qq.com # origin : junzew / HanTTS # date : 2020-03-09 # desc : TTS class # ========================================================================== import os import time import wave import json import _thread import pyaudio import CDMouth.atc as atc from pathlib import Path from pypinyin import lazy_pinyin, TONE3 from pydub import AudioSegment from pydub.silence import split_on_silence class TextToSpeech: CHUNK = 1024 punctuation = [ '，', '。', '？', '！', '“', '”', '；', '：', '（', "）", ":", ";", ",", ".", "?", "!", "\"", "\'", "(", ")"] def __init__(self): self.delay = 0.450 self.root_path = '../' self.source_dir = os.path.join( self.root_path, 'CDMouth', 'syllables/') pass def speak(self, text): syllables = lazy_pinyin(text, style=TONE3) print(syllables) delay = 0 def pre_process(_syl): temp = [] for _s in _syl: for p in TextToSpeech.punctuation: _s = _s.replace(p, "") if _s.isdigit(): _s = atc.num2chinese(_s) new_sounds = lazy_pinyin(_s, style=TONE3) for e in new_sounds: temp.append(e) else: temp.append(_s) return temp syllables = pre_process(syllables) for syllable in syllables: path = self.source_dir + syllable + ".wav" _thread.start_new_thread(TextToSpeech._play_audio, (path, delay)) delay += self.delay @staticmethod def mp3_to_wav(source_file_path, dest_path=None): if dest_path is None: dest_path = source_file_path.replace('.mp3', '.wav') sound = AudioSegment.from_mp3(source_file_path) sound.export(dest_path, format='wav') @staticmethod def split_wav(path, syllables=None, key='a', debug=False): # syllables in form of [['a1', 'a2', 'a3', 'a4', 'a'], ...] file = Path(path) if not file.is_file(): raise Exception(path + " doesn't exist") if syllables is None: data = json.load(open('mapping.json')) syllables = data.get(key) sound_file = AudioSegment.from_wav(path) audio_chunks = split_on_silence( sound_file, min_silence_len=333, # must be silent for at least 333ms silence_thresh=-32 # consider it silent if quieter than -32 dBFS ) # from mapping.json in HanTTS for i, chunk in enumerate(audio_chunks): if debug: # debug mode, ignore syllables list. out_file = "./pre/test{:03}".format(i) + '.wav' elif isinstance(syllables[0], list): # nested list of 5 tones if i // 5 >= syllables.__len__(): # over-capacity chunks syllable = 'oth{}'.format(i) out_file = "./pre/" + syllable + '.wav' else: syllable = syllables[i // 5] print(syllable) j = i % 5 if j != 4: # 1st, 2nd, 3rd, 4th tone out_file = "./pre/" + syllable + str(j + 1) + ".wav" else: # neutrual tone out_file = "./pre/" + syllable + ".wav" else: # a list of single tones if i >= syllables.__len__(): # over-capacity chunks syllable = 'oth{}'.format(i) out_file = "./pre/" + syllable + '.wav' else: syllable = syllables[i] print(syllable) out_file = "./pre/" + syllable + ".wav" print("exporting", out_file) chunk.export(out_file, format="wav") return audio_chunks def synthesize(self, text, src, dst): """ Synthesize .wav from text src is the folder that contains all syllables .wav files dst is the destination folder to save the synthesized file """ print("Synthesizing ...") delay = 0 increment = self.delay * 1000 # milliseconds pause = 500 # pause for punctuation syllables = lazy_pinyin(text, style=TONE3) # initialize to be complete silence, each character takes up ~500ms result = AudioSegment.silent(duration=500 * len(text)) for syllable in syllables: path = src + syllable + ".wav" sound_file = Path(path) # insert 500 ms silence for punctuation marks if syllable in TextToSpeech.punctuation: short_silence = AudioSegment.silent(duration=pause) result = result.overlay(short_silence, position=delay) delay += increment continue # skip sound file that doesn't exist if not sound_file.is_file(): continue segment = AudioSegment.from_wav(path) result = result.overlay(segment, position=delay) delay += increment directory = dst if not os.path.exists(directory): os.makedirs(directory) result.export(directory + "generated.wav", format="wav") print("Exported.") @staticmethod def _play_audio(path, delay): try: time.sleep(delay) wf = wave.open(path, 'rb') p = pyaudio.PyAudio() stream = p.open(format=p.get_format_from_width(wf.getsampwidth()), channels=wf.getnchannels(), rate=wf.getframerate(), output=True) data = wf.readframes(TextToSpeech.CHUNK) while data: stream.write(data) data = wf.readframes(TextToSpeech.CHUNK) stream.stop_stream() stream.close() p.terminate() return except Exception as e: print(e) pass if __name__ == '__main__': tts = TextToSpeech() while True: _t = input('输入中文：') if str(_t).lower().startswith('exit'): break tts.speak(_t)

35.576923

78

0.51166

674

6,475

4.768546

0.347181

0.017424

0.018668

0.028002

0.136279

0.084941

0.056627

0

0.01924

0.357838

6,475

181

79

35.773481

0.753728

0.154595

0

0.20979

0

0.044379

0

1

0.048951

false

0.013986

0.076923

0

0.167832

0.048951

0

null

0

null

0

1

0

d1701b96fd7a92f7df5c07d7aab9cf3f631d9646

635

py

Python

deprecated/rcbu/utils/bytes.py

nloadholtes/python-cloudbackup-sdk

1866e23aaaac41c35be4cb6ab964fcd0ba9a8fe6

[ "Apache-2.0" ]

4

2015-02-10T14:28:12.000Z

2016-12-26T22:52:07.000Z

deprecated/rcbu/utils/bytes.py

nloadholtes/python-cloudbackup-sdk

1866e23aaaac41c35be4cb6ab964fcd0ba9a8fe6

[ "Apache-2.0" ]

17

2015-01-22T21:58:36.000Z

2018-01-25T19:47:43.000Z

deprecated/rcbu/utils/bytes.py

nloadholtes/python-cloudbackup-sdk

1866e23aaaac41c35be4cb6ab964fcd0ba9a8fe6

[ "Apache-2.0" ]

9

2015-01-26T19:25:45.000Z

2018-11-01T20:14:12.000Z

"""Utilities for handling byte quantities and strings.""" def dehumanize_bytes(human_bytes): """Convert a string in the format '2.23 GB' -> 2.23 * 10**30""" packed = human_bytes.split() amount, magnitude = packed[0], None if len(packed) == 2: magnitude = packed[1].upper() prefixes = ['YB', 'ZB', 'EB', 'PB', 'TB', 'GB', 'MB', 'KB'] multipliers = [2**(i*10) for i in range(8, 0, -1)] magnitude_to_multiplier = {ma: mult for ma, mult in zip(prefixes, multipliers)} multiplier = magnitude_to_multiplier.get(magnitude, 1) return int(float(amount) * multiplier)

39.6875

67

0.60315

86

635

4.372093

0.616279

0.053191

0.111702

0

0.041237

0.23622

635

15

68

42.333333

0.734021

0.171654

0

0.031068

0

1

0.090909

false

0

0.181818

0

null

0

null

0

1

0

d17126b678901eaff2294ed14ac2e19ccefc75d6

3,002

py

Python

ptreeopt/plotting.py

quaquel/ptreeopt

d4df26ecd877185b0a8c02c8ecbd3c73e54f6f52

[ "MIT" ]

26

2017-02-27T01:30:19.000Z

2022-02-23T07:26:46.000Z

ptreeopt/plotting.py

quaquel/ptreeopt

d4df26ecd877185b0a8c02c8ecbd3c73e54f6f52

[ "MIT" ]

8

2018-06-28T15:52:49.000Z

2021-09-27T15:49:50.000Z

ptreeopt/plotting.py

quaquel/ptreeopt

d4df26ecd877185b0a8c02c8ecbd3c73e54f6f52

[ "MIT" ]

5

2018-03-31T12:48:00.000Z

2021-09-22T16:36:59.000Z

import numpy as np import matplotlib.pyplot as plt import os, subprocess import pandas as pd def graphviz_export(P, filename, colordict=None, animation=False, dpi=300): ''' Export policy tree P to filename (SVG or PNG) colordict optional. Keys must match actions. Example: colordict = {'Release_Demand': 'cornsilk', 'Hedge_90': 'indianred', 'Flood_Control': 'lightsteelblue'} Requires pygraphviz.''' import pygraphviz as pgv G = pgv.AGraph(directed=True) G.node_attr['shape'] = 'box' G.node_attr['style'] = 'filled' if animation: G.graph_attr['size'] = '2!,2!' # use for animations only G.graph_attr['dpi'] = str(dpi) parent = P.root G.add_node(str(parent), fillcolor='white') S = [] while parent.is_feature or len(S) > 0: if parent.is_feature: S.append(parent) child = parent.l label = 'T' else: parent = S.pop() child = parent.r label = 'F' if child.is_feature or not colordict: c = 'white' else: c = colordict[child.value] G.add_node(str(child), fillcolor=c) G.add_edge(str(parent), str(child), label=label) parent = child G.layout(prog='dot') G.draw(filename) def animate_trees(snapshots, filename, colordict=None, max_nfe=None): os.makedirs('temp') for i, P in enumerate(snapshots['best_P']): nfe = snapshots['nfe'][i] if max_nfe and nfe > max_nfe: break nfestring = 'nfe-' + '%10d' % nfe + '.png' graphviz_export(P, 'temp/%s-%s' % (filename, nfestring), colordict, dpi=150) subprocess.call(['./ptreeopt/stitch-animations.sh', filename, '']) subprocess.call(['rm', '-r', 'temp']) def ts_color(ts_actions, colordict=None): for pol in set(ts_actions): first = ts_actions.index[(ts_actions == pol) & (ts_actions.shift(1) != pol)] last = ts_actions.index[(ts_actions == pol) & (ts_actions.shift(-1) != pol)] for f, l in zip(first, last): plt.axvspan(f, l + pd.Timedelta('1 day'), facecolor=colordict[pol], edgecolor='none', alpha=0.4) def animate_objfxn(snapshots, filename, max_nfe=None): os.makedirs('temp') for i, P in enumerate(snapshots['best_P']): if max_nfe and snapshots['nfe'][i] > max_nfe: break plt.plot(snapshots['nfe'][:i + 1], snapshots['best_f'] [:i + 1], linewidth=2, color='steelblue') L = [max_nfe, snapshots['nfe'][-1]] plt.xlim([0, min(i for i in L if i is not None)]) plt.ylim([0, np.max(snapshots['best_f'])]) plt.ylabel('Objective Function') plt.xlabel('NFE') plt.tight_layout() nfestring = 'nfe-' + '%10d' % snapshots['nfe'][i] + '.png' plt.savefig('temp/%s-%s' % (filename, nfestring), dpi=150) plt.close() subprocess.call(['./ptreeopt/stitch-animations.sh', filename, '-layers optimize']) subprocess.call(['rm', '-r', 'temp'])

28.590476

84

0.596269

406

3,002

4.315271

0.362069

0.041096

0.02968

0.012557

0.216895

0.166667

0.111872

0

0.012753

0.242505

3,002

104

85

28.865385

0.757696

0.087941

0

0.147059

0

0.099631

0.022878

0.029412

0

1

0.058824

false

0

0.073529

0

0.132353

0

null

0

null

0

1

0

d171d9e66a91c717237db741b180e1ba5317644f

3,541

py

Python

will/webapp.py

rgorsuch/will

ebfc0d2953b4dcf5a4acc1118811cab5aec3bd17

[ "MIT" ]

1

2018-11-19T15:34:07.000Z

will/webapp.py

rgorsuch/will

ebfc0d2953b4dcf5a4acc1118811cab5aec3bd17

[ "MIT" ]

null

will/webapp.py

rgorsuch/will

ebfc0d2953b4dcf5a4acc1118811cab5aec3bd17

[ "MIT" ]

1

2019-02-26T02:17:32.000Z

#!/usr/bin/env python # # export REDISCLOUD_URL=redis://localhost:6379/7 # FLASK_APP=manage.py flask run # FLASK_DEBUG=1 python manage.py runserver # gunicorn manage:app from flask_script import Server, Manager from flask import Flask from flask import jsonify from flask import send_from_directory from flask import request from flask import render_template from pprint import pformat import os import time import json import urlparse import redis import logging import gevent import settings keep_alive_url = "/keep-alive" logger = logging.getLogger(__name__) url = urlparse.urlparse(os.environ.get('REDISCLOUD_URL')) r = redis.Redis(host=url.hostname, port=url.port, password=url.password) pubsub = redis.Redis(host=url.hostname, port=url.port, password=url.password) logger.info("type of pics is " + r.type("pics")) if not r.exists("pics"): # First ever startup -- load some default images defaultpics = [ "https://s3.amazonaws.com/uploads.hipchat.com/398524/2959249/Fv0U8jU47Z1RWQt/20151211_235234.jpg", "https://s3.amazonaws.com/uploads.hipchat.com/398524/2973098/mX8h75W4A17wm8a/upload.jpg", "https://s3.amazonaws.com/uploads.hipchat.com/398524/2856310/qwTHxLZQA1uVrEw/upload.png", "https://s3.amazonaws.com/uploads.hipchat.com/398524/2973989/YTonrDGuXGngIDM/upload.png"] now = time.time() for index, pic in enumerate(defaultpics): r.zadd("pics", pic, now - index) elif r.type("pics") == "list": # Data migration from list to sorted-set all = [p for p in r.lrange("pics", 0, -1)] r.delete("pics") for index, pic in enumerate(all): r.zadd("pics", pic, index+1) app = Flask(__name__, static_folder=os.path.join(os.path.dirname(__file__), 'static'), static_url_path='/static') app.config['SECRET_KEY'] = 'TOPsecret!' def bootstrap_flask(): from will.sockets import get_socketio_app logger.info("Starting flask server on port " + settings.HTTPSERVER_PORT) socketioapp = get_socketio_app() socketioapp.run(app, host="0.0.0.0", port=int(settings.HTTPSERVER_PORT)) # # Just Flask # app.run(host="0.0.0.0", port=int(settings.HTTPSERVER_PORT)) @app.route('/') def slideshow(): return send_from_directory(os.path.join(os.path.dirname(__file__), 'static'), "slideshow.html") @app.route('/pics', methods=['GET']) def pics(): logger.info("Handling GET /pics with " + request.method) logger.info(" Headers:" + pformat(request.headers)) logger.info(" Form: " + pformat(request.form)) logger.info(" Data: " + pformat(request.data)) # Get photo URLs from Redis urls = r.zrange("pics", 0, -1) return jsonify(list(reversed(urls))) @app.route('/pics', methods=['POST']) def add_pic(): logger.info("POSTed pic") image = request.form['image'] if image: logger.info("Publishing new image: " + image) logger.info(pformat(request.form)) r.zadd("pics", image, time.time()) pubsub.publish("updates", json.dumps(image)) return jsonify([image]) else: return jsonify([]) @app.route('/pics', methods=['DELETE']) def delete_pic(): image = request.form['image'] logger.info("Deleting pic: " + image) r.zrem("pics", image) return jsonify("deleted " + image) @app.route('/reset') def reset_pics(): r.delete("pics") return "Pics have been reset" @app.route('/keep-alive') def keep_alive(): return "I'm alive!" @app.route("/ping") def ping(): return "PONG" if __name__ == "__main__": manager.run()

28.556452

113

0.684552

489

3,541

4.848671

0.335378

0.042176

0.031632

0.032054

0.21763

0.178828

0.115563

0.077604

0

0.034401

0.162666

3,541

123

114

28.788618

0.765261

0.096583

0

0.048193

0

0.048193

0.235719

0

1

0.096386

false

0.024096

0.192771

0.036145

0.385542

0.012048

0

null

0

null

0

1

0

66f37010bee3fc9dd18822a66b9dc83e5b71b409

1,429

py

Python

pwstat/processor.py

yenarhee/pwstat

67d465d2806ae35ec1a39de867549d3a3f363192

[ "MIT" ]

null

pwstat/processor.py

yenarhee/pwstat

67d465d2806ae35ec1a39de867549d3a3f363192

[ "MIT" ]

null

pwstat/processor.py

yenarhee/pwstat

67d465d2806ae35ec1a39de867549d3a3f363192

[ "MIT" ]

null

# Processor class with static methods # : gets headers, body, timestamp # : returns header and body data # e.g. POST form variables, cookies, keyword parameters import re from Cookie import SimpleCookie as cookie class Processor(object): def __init__(self): return # main function @staticmethod def process(headers, body, timestamp): # process return Processor.process_headers(headers), Processor.process_body(body), timestamp # helper functions @staticmethod def process_headers(headers): # process header data and return useful info as a dictionary headers_dict = dict(headers) # parse cookie try: cookiestring = headers_dict['cookie'] c = cookie() cookie_dict = {} c.load(cookiestring) for key in c: cookie_dict[key] = c[key].value headers_dict['cookie'] = cookie_dict except KeyError: # there is no cookie pass return headers_dict @staticmethod def process_body(body): # process body data and return POST form variables as a dictionary result = {} regex = r"^(\w*)=(\w*)(?:&(\w*)=(\S*))*" match = re.match(regex, body) if match: it = iter(match.groups()) for key in it: result[key] = next(it) return result

28.019608

90

0.585724

160

1,429

5.1375

0.43125

0.053528

0.080292

0.07056

0

0.325402

1,429

50

91

28.58

0.852697

0.244927

0

0.09375

0

0.038425

0.027179

0

1

0.125

false

0.03125

0.0625

0.34375

0

null

0

null

0

1

0

66f529e3e1847f546b2fe48ed349c1cb515916c6

1,424

py

Python

shadowbot/sql/__init__.py

shadowmoose/Discord-Bot

39db07233f23b43a8e15fdaf53de890ad2fe2866

[ "MIT" ]

null

shadowbot/sql/__init__.py

shadowmoose/Discord-Bot

39db07233f23b43a8e15fdaf53de890ad2fe2866

[ "MIT" ]

null

shadowbot/sql/__init__.py

shadowmoose/Discord-Bot

39db07233f23b43a8e15fdaf53de890ad2fe2866

[ "MIT" ]

null

""" The SqlAlchemy static wrapper class. The Sessions created are Thread-safe, but Thread-local in scope. Its objects should not be shared across Processes or Threads. """ import sqlalchemy from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker, scoped_session import os Base = declarative_base() _engine = None _Session = None def init(db_path=":memory:"): """ Initialize the DB, a required function to access the database. Creates the DB file if it does not already exist. :param db_path: :return: """ global _engine, _Session if _Session and _engine: return create_new = False if db_path != ':memory:': db_path = os.path.abspath(db_path) create_new = not os.path.exists(db_path) _engine = sqlalchemy.create_engine('sqlite:///%s' % db_path) session_factory = sessionmaker(bind=_engine) _Session = scoped_session(session_factory) if create_new: _create() def _create(): from sql.message import UserMessageDB, BotMessageDB Base.metadata.create_all(_engine) print("\tCreated Database file.") session().execute("PRAGMA journal_mode=WAL") print("\t+Activated WAL Mode.") def session(): """ Create a Thread-local Session object, the entrypoint to the Database. :return: """ if not _Session or not _engine: raise Exception("SQL Session cannot be created if the DB is not initialized!") # noinspection PyCallingNonCallable return _Session()

24.135593

80

0.754213

197

1,424

5.279188

0.467005

0.040385

0.023077

0

0.149579

1,424

58

81

24.551724

0.858794

0.291433

0

0.159672

0

1

0.1

false

0

0.166667

0

0.333333

0.066667

0

null

0

null

0

1

0

66fb7669cb49911cdfab9cbef121c812ac9aaf5f

519

py

Python

tools/libari/tests/test_libari.py

seemoo-lab/aristoteles

092c746d2a211bb4edc1b60072487a94e8a97c99

[ "MIT" ]

21

2021-08-30T13:25:08.000Z

2021-12-09T16:48:25.000Z

tools/libari/tests/test_libari.py

seemoo-lab/aristoteles

092c746d2a211bb4edc1b60072487a94e8a97c99

[ "MIT" ]

5

2021-09-03T20:33:37.000Z

2021-11-28T21:01:00.000Z

tools/libari/tests/test_libari.py

seemoo-lab/aristoteles

092c746d2a211bb4edc1b60072487a94e8a97c99

[ "MIT" ]

3

2021-09-03T20:08:47.000Z

2021-11-05T21:10:02.000Z

from libari.packet import Packet from libari.tlv import TLV import binascii def test_default_header_only_all_zero(): pkt = Packet() assert(pkt.getHexString() == 'dec07eab0000000000000000') def test_default_header_only_all_zero_and_zero_tlv(): pkt = Packet() pkt.addTLV(TLV(id=0, version=0)) assert(pkt.getHexString() == 'dec07eab000008000000000000000000') reversePkt = Packet.fromBytes(binascii.unhexlify(pkt.getHexString())) assert(reversePkt.getHexString() == pkt.getHexString())

23.590909

73

0.747592

60

519

6.25

0.433333

0.16

0.074667

0.106667

0.165333

0

0.102679

0.136802

519

21

74

24.714286

0.734375

0

0.166667

0

0.1079

0

0.25

1

0.166667

false

0

0.25

0

0.416667

0

null

0

null

0

1

0

66fe695bec9a53f95c6444cdfa497c1f3778ce6b

78,263

py

Python

napalm_iosxr/iosxr.py

ktbyers/napalm-iosxr

dddd96118c20775163299fd0634e177598cc910f

[ "Apache-2.0" ]

1

2021-07-15T18:13:32.000Z

napalm_iosxr/iosxr.py

ktbyers/napalm-iosxr

dddd96118c20775163299fd0634e177598cc910f

[ "Apache-2.0" ]

null

napalm_iosxr/iosxr.py

ktbyers/napalm-iosxr

dddd96118c20775163299fd0634e177598cc910f

[ "Apache-2.0" ]

null

# Copyright 2015 Spotify AB. All rights reserved. # # The contents of this file are 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. # python std lib import re import copy from collections import defaultdict # third party libs from lxml import etree as ETREE import xml.etree.ElementTree as ET from netaddr import IPAddress from netaddr.core import AddrFormatError from pyIOSXR import IOSXR from pyIOSXR.exceptions import ConnectError from pyIOSXR.exceptions import TimeoutError from pyIOSXR.exceptions import InvalidInputError # napalm_base from napalm_base.helpers import convert, find_txt, mac, ip from napalm_base.base import NetworkDriver from napalm_base.utils import string_parsers from napalm_base.exceptions import ConnectionException, MergeConfigException, ReplaceConfigException,\ CommandErrorException, CommandTimeoutException class IOSXRDriver(NetworkDriver): def __init__(self, hostname, username, password, timeout=60, optional_args=None): self.hostname = hostname self.username = username self.password = password self.timeout = timeout self.pending_changes = False self.replace = False if optional_args is None: optional_args = {} self.port = optional_args.get('port', 22) self.lock_on_connect = optional_args.get('config_lock', True) self.device = IOSXR(hostname, username, password, timeout=timeout, port=self.port, lock=self.lock_on_connect) def open(self): try: self.device.open() except ConnectError as conn_err: raise ConnectionException(conn_err.message) def close(self): self.device.close() def load_replace_candidate(self, filename=None, config=None): self.pending_changes = True self.replace = True if not self.lock_on_connect: self.device.lock() try: self.device.load_candidate_config(filename=filename, config=config) except InvalidInputError as e: self.pending_changes = False self.replace = False raise ReplaceConfigException(e.message) def load_merge_candidate(self, filename=None, config=None): self.pending_changes = True self.replace = False if not self.lock_on_connect: self.device.lock() try: self.device.load_candidate_config(filename=filename, config=config) except InvalidInputError as e: self.pending_changes = False self.replace = False raise MergeConfigException(e.message) def compare_config(self): if not self.pending_changes: return '' elif self.replace: return self.device.compare_replace_config().strip() else: return self.device.compare_config().strip() def commit_config(self): if self.replace: self.device.commit_replace_config() else: self.device.commit_config() self.pending_changes = False if not self.lock_on_connect: self.device.unlock() def discard_config(self): self.device.discard_config() self.pending_changes = False if not self.lock_on_connect: self.device.unlock() def rollback(self): self.device.rollback() # perhaps both should be moved in napalm_base.helpers at some point @staticmethod def _find_txt(xml_tree, path, default = ''): try: return xml_tree.find(path).text.strip() except Exception: return default @staticmethod def _convert(to, who, default = u''): if who is None: return default try: return to(who) except: return default def get_facts(self): facts = { 'vendor': u'Cisco', 'os_version': u'', 'hostname': u'', 'uptime': -1, 'serial_number': u'', 'fqdn': u'', 'model': u'', 'interface_list': [] } facts_rpc_request = ( '<Get>' '<Operational>' '<SystemTime/>' '<PlatformInventory/>' '</Operational>' '</Get>' ) facts_rpc_reply = ETREE.fromstring(self.device.make_rpc_call(facts_rpc_request)) system_time_xpath = './/SystemTime/Uptime' platform_attr_xpath = './/RackTable/Rack/Attributes/BasicInfo' system_time_tree = facts_rpc_reply.xpath(system_time_xpath)[0] platform_attr_tree = facts_rpc_reply.xpath(platform_attr_xpath)[0] hostname = convert(unicode, find_txt(system_time_tree, 'Hostname')) uptime = convert(int, find_txt(system_time_tree, 'Uptime'), -1) serial = convert(unicode, find_txt(platform_attr_tree, 'SerialNumber')) os_version = convert(unicode, find_txt(platform_attr_tree, 'SoftwareRevision')) model = convert(unicode, find_txt(platform_attr_tree, 'ModelName')) interface_list = self.get_interfaces().keys() facts.update({ 'os_version': os_version, 'hostname': hostname, 'model': model, 'uptime': uptime, 'serial_number': serial, 'fqdn': hostname, 'interface_list': interface_list }) return facts def get_interfaces(self): interfaces = {} INTERFACE_DEFAULTS = { 'is_enabled': False, 'is_up': False, 'mac_address': u'', 'description': u'', 'speed': -1, 'last_flapped': -1.0 } interfaces_rpc_request = '<Get><Operational><Interfaces/></Operational></Get>' interfaces_rpc_reply = ETREE.fromstring(self.device.make_rpc_call(interfaces_rpc_request)) for interface_tree in interfaces_rpc_reply.xpath('.//Interfaces/InterfaceTable/Interface'): interface_name = find_txt(interface_tree, 'Naming/InterfaceName') if not interface_name: continue is_up = (find_txt(interface_tree, 'LineState') == 'IM_STATE_UP') is_enabled = (find_txt(interface_tree, 'LineState') == 'IM_STATE_UP') mac_address = mac(find_txt(interface_tree, 'MACAddress/Address')) speed = int(convert(int, find_txt(interface_tree, 'Bandwidth'), 0) * 1e-3) description = find_txt(interface_tree, 'Description') interfaces[interface_name] = copy.deepcopy(INTERFACE_DEFAULTS) interfaces[interface_name].update({ 'is_up': is_up, 'speed': speed, 'is_enabled': is_enabled, 'mac_address': mac_address, 'description': description }) return interfaces def get_interfaces_counters(self): rpc_command = "<Get><Operational><Interfaces><InterfaceTable></InterfaceTable></Interfaces></Operational></Get>" result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) interface_counters = dict() for interface in result_tree.iter('Interface'): interface_name = interface.find('InterfaceHandle').text interface_stats = dict() if interface.find('InterfaceStatistics') is None: continue else: interface_stats = dict() interface_stats['tx_multicast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/MulticastPacketsSent').text) interface_stats['tx_discards'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/OutputDrops').text) interface_stats['tx_octets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/BytesSent').text) interface_stats['tx_errors'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/OutputErrors').text) interface_stats['rx_octets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/BytesReceived').text) interface_stats['tx_unicast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/PacketsSent').text) interface_stats['rx_errors'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/InputErrors').text) interface_stats['tx_broadcast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/BroadcastPacketsSent').text) interface_stats['rx_multicast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/MulticastPacketsReceived').text) interface_stats['rx_broadcast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/BroadcastPacketsReceived').text) interface_stats['rx_discards'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/InputDrops').text) interface_stats['rx_unicast_packets'] = int(interface.find( 'InterfaceStatistics/FullInterfaceStats/PacketsReceived').text) interface_counters[interface_name] = interface_stats return interface_counters def get_bgp_neighbors(self): def generate_vrf_query(vrf_name): """ Helper to provide XML-query for the VRF-type we're interested in. """ if vrf_name == "global": rpc_command = """<Get> <Operational> <BGP> <InstanceTable> <Instance> <Naming> <InstanceName> default </InstanceName> </Naming> <InstanceActive> <DefaultVRF> <GlobalProcessInfo> </GlobalProcessInfo> <NeighborTable> </NeighborTable> </DefaultVRF> </InstanceActive> </Instance> </InstanceTable> </BGP> </Operational> </Get>""" else: rpc_command = """<Get> <Operational> <BGP> <InstanceTable> <Instance> <Naming> <InstanceName> default </InstanceName> </Naming> <InstanceActive> <VRFTable> <VRF> <Naming> %s </Naming> <GlobalProcessInfo> </GlobalProcessInfo> <NeighborTable> </NeighborTable> </VRF> </VRFTable> </InstanceActive> </Instance> </InstanceTable> </BGP> </Operational> </Get>""" % vrf_name return rpc_command """ Initial run to figure out what VRF's are available Decided to get this one from Configured-section because bulk-getting all instance-data to do the same could get ridiculously heavy Assuming we're always interested in the DefaultVRF """ active_vrfs = ["global"] rpc_command = """<Get> <Operational> <BGP> <ConfigInstanceTable> <ConfigInstance> <Naming> <InstanceName> default </InstanceName> </Naming> <ConfigInstanceVRFTable> </ConfigInstanceVRFTable> </ConfigInstance> </ConfigInstanceTable> </BGP> </Operational> </Get>""" result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for node in result_tree.iter('ConfigVRF'): active_vrfs.append(str(node.find('Naming/VRFName').text)) result = dict() for vrf in active_vrfs: rpc_command = generate_vrf_query(vrf) result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) this_vrf = dict() this_vrf['peers'] = dict() if vrf == "global": this_vrf['router_id'] = unicode(result_tree.find( 'Get/Operational/BGP/InstanceTable/Instance/InstanceActive/DefaultVRF/GlobalProcessInfo/VRF/RouterID').text) else: this_vrf['router_id'] = unicode(result_tree.find( 'Get/Operational/BGP/InstanceTable/Instance/InstanceActive/VRFTable/VRF/GlobalProcessInfo/VRF/RouterID').text) neighbors = dict() for neighbor in result_tree.iter('Neighbor'): this_neighbor = dict() this_neighbor['local_as'] = int(neighbor.find('LocalAS').text) this_neighbor['remote_as'] = int(neighbor.find('RemoteAS').text) this_neighbor['remote_id'] = unicode(neighbor.find('RouterID').text) if neighbor.find('ConnectionAdminStatus').text is "1": this_neighbor['is_enabled'] = True try: this_neighbor['description'] = unicode(neighbor.find('Description').text) except AttributeError: this_neighbor['description'] = u'' this_neighbor['is_enabled'] = str(neighbor.find('ConnectionAdminStatus').text) is "1" if str(neighbor.find('ConnectionAdminStatus').text) is "1": this_neighbor['is_enabled'] = True else: this_neighbor['is_enabled'] = False if str(neighbor.find('ConnectionState').text) == "BGP_ST_ESTAB": this_neighbor['is_up'] = True this_neighbor['uptime'] = int(neighbor.find('ConnectionEstablishedTime').text) else: this_neighbor['is_up'] = False this_neighbor['uptime'] = -1 this_neighbor['address_family'] = dict() if neighbor.find('ConnectionRemoteAddress/AFI').text == "IPv4": this_afi = "ipv4" elif neighbor.find('ConnectionRemoteAddress/AFI').text == "IPv6": this_afi = "ipv6" else: this_afi = neighbor.find('ConnectionRemoteAddress/AFI').text this_neighbor['address_family'][this_afi] = dict() try: this_neighbor['address_family'][this_afi][ "received_prefixes"] = int(neighbor.find('AFData/Entry/PrefixesAccepted').text) + int( neighbor.find('AFData/Entry/PrefixesDenied').text) this_neighbor['address_family'][this_afi][ "accepted_prefixes"] = int(neighbor.find('AFData/Entry/PrefixesAccepted').text) this_neighbor['address_family'][this_afi][ "sent_prefixes"] = int(neighbor.find('AFData/Entry/PrefixesAdvertised').text) except AttributeError: this_neighbor['address_family'][this_afi]["received_prefixes"] = -1 this_neighbor['address_family'][this_afi]["accepted_prefixes"] = -1 this_neighbor['address_family'][this_afi]["sent_prefixes"] = -1 try: neighbor_ip = unicode(neighbor.find('Naming/NeighborAddress/IPV4Address').text) except AttributeError: neighbor_ip = unicode(neighbor.find('Naming/NeighborAddress/IPV6Address').text) neighbors[neighbor_ip] = this_neighbor this_vrf['peers'] = neighbors result[vrf] = this_vrf return result def get_environment(self): def get_module_xml_query(module,selection): return """<Get> <AdminOperational> <EnvironmentalMonitoring> <RackTable> <Rack> <Naming> <rack>0</rack> </Naming> <SlotTable> <Slot> <Naming> <slot>%s</slot> </Naming> %s </Slot> </SlotTable> </Rack> </RackTable> </EnvironmentalMonitoring> </AdminOperational> </Get>""" % (module,selection) environment_status = dict() environment_status['fans'] = dict() environment_status['temperature'] = dict() environment_status['power'] = dict() environment_status['cpu'] = dict() environment_status['memory'] = int() # finding slots with equipment we're interested in rpc_command = """<Get> <AdminOperational> <PlatformInventory> <RackTable> <Rack> <Naming> <Name>0</Name> </Naming> <SlotTable> </SlotTable> </Rack> </RackTable> </PlatformInventory> </AdminOperational> </Get>""" result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) active_modules = defaultdict(list) for slot in result_tree.iter("Slot"): for card in slot.iter("CardTable"): #find enabled slots, figoure out type and save for later if card.find('Card/Attributes/FRUInfo/ModuleAdministrativeState').text == "ADMIN_UP": slot_name = slot.find('Naming/Name').text module_type = re.sub("\d+", "", slot_name) if len(module_type) > 0: active_modules[module_type].append(slot_name) else: active_modules["LC"].append(slot_name) # # PSU's # for psu in active_modules['PM']: if psu in ["PM6", "PM7"]: # Cisco bug, chassis difference V01<->V02 continue rpc_command = get_module_xml_query(psu,'') result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) psu_status = dict() psu_status['status'] = False psu_status['capacity'] = float() psu_status['output'] = float() for sensor in result_tree.iter('SensorName'): if sensor.find('Naming/Name').text == "host__VOLT": this_psu_voltage = float(sensor.find('ValueBrief').text) elif sensor.find('Naming/Name').text == "host__CURR": this_psu_current = float(sensor.find('ValueBrief').text) elif sensor.find('Naming/Name').text == "host__PM": this_psu_capacity = float(sensor.find('ValueBrief').text) if this_psu_capacity > 0: psu_status['capacity'] = this_psu_capacity psu_status['status'] = True if this_psu_current and this_psu_voltage: psu_status['output'] = (this_psu_voltage * this_psu_current) / 1000000.0 environment_status['power'][psu] = psu_status # # Memory # rpc_command = "<Get><AdminOperational><MemorySummary></MemorySummary></AdminOperational></Get>" result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for node in result_tree.iter('Node'): print if node.find('Naming/NodeName/Slot').text == active_modules['RSP'][0]: # first enabled RSP available_ram = int(node.find('Summary/SystemRAMMemory').text) free_ram = int(node.find('Summary/FreeApplicationMemory').text) break # we're only looking at one of the RSP's if available_ram and free_ram: used_ram = available_ram - free_ram memory = dict() memory['available_ram'] = available_ram memory['used_ram'] = used_ram environment_status['memory'] = memory # # Fans # for fan in active_modules['FT']: rpc_command = get_module_xml_query(fan,'') result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for module in result_tree.iter('Module'): for sensortype in module.iter('SensorType'): for sensorname in sensortype.iter('SensorNameTable'): if sensorname.find('SensorName/Naming/Name').text == "host__FanSpeed_0": environment_status['fans'][fan] = {'status': int(sensorname.find( 'SensorName/ValueDetailed/Status').text) is 1} # # CPU # cpu = dict() rpc_command = "<Get><Operational><SystemMonitoring></SystemMonitoring></Operational></Get>" result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for module in result_tree.iter('CPUUtilization'): this_cpu = dict() this_cpu["%usage"] = float(module.find('TotalCPUFiveMinute').text) rack = module.find('Naming/NodeName/Rack').text slot = module.find('Naming/NodeName/Slot').text instance = module.find('Naming/NodeName/Instance').text position = "%s/%s/%s" % (rack,slot,instance) cpu[position] = this_cpu environment_status["cpu"] = cpu # # Temperature # temperature = dict() slot_list = set() for category, slot in active_modules.iteritems(): slot_list |= set(slot) for slot in slot_list: rpc_command = get_module_xml_query(slot,'') result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for sensor in result_tree.findall(".//SensorName"): if not sensor.find('Naming/Name').text == "host__Inlet0": continue this_reading = dict() this_reading['temperature'] = float(sensor.find('ValueBrief').text) threshold_value = [float(x.text) for x in sensor.findall("ThresholdTable/Threshold/ValueBrief")] this_reading['is_alert'] = threshold_value[2] <= this_reading['temperature'] <= threshold_value[3] this_reading['is_critical'] = threshold_value[4] <= this_reading['temperature'] <= threshold_value[5] this_reading['temperature'] = this_reading['temperature']/10 environment_status["temperature"][slot] = this_reading return environment_status def get_lldp_neighbors(self): # init result dict lldp = {} sh_lldp = self.device.show_lldp_neighbors().splitlines()[5:-3] for n in sh_lldp: local_interface = n.split()[1] if local_interface not in lldp.keys(): lldp[local_interface] = list() lldp[local_interface].append({'hostname': unicode(n.split()[0]), 'port': unicode(n.split()[4]), }) return lldp def get_lldp_neighbors_detail(self, interface = ''): lldp_neighbors = dict() rpc_command = '<Get><Operational><LLDP></LLDP></Operational></Get>' result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for neighbor in result_tree.findall('.//Neighbors/DetailTable/Detail/Entry'): if neighbor is None: continue try: interface_name = unicode(neighbor.find('ReceivingInterfaceName').text) parent_interface = unicode(neighbor.find('ReceivingParentInterfaceName').text) device_id = unicode(neighbor.find('DeviceID').text) chassis_id = unicode(neighbor.find('ChassisID').text) port_id = unicode(neighbor.find('PortIDDetail').text) port_descr = unicode(neighbor.find('Detail/PortDescription').text) system_name = unicode(neighbor.find('Detail/SystemName').text) system_descr = unicode(neighbor.find('Detail/SystemDescription').text) system_capabilities = unicode(neighbor.find('Detail/SystemCapabilities').text) enabled_capabilities= unicode(neighbor.find('Detail/EnabledCapabilities').text) # few other optional... # time_remaining = neighbor.find('Detail/TimeRemaining').text # media_attachement_unit_type = neighbor.find('Detail/MediaAttachmentUnitType').text # port_vlan_id = neighbor.find('Detail/PortVlanID').text if interface_name not in lldp_neighbors.keys(): lldp_neighbors[interface_name] = list() lldp_neighbors[interface_name].append({ 'parent_interface' : parent_interface, 'remote_chassis_id' : chassis_id, 'remote_port' : port_id, 'remote_port_description' : port_descr, 'remote_system_name' : system_name, 'remote_system_description' : system_descr, 'remote_system_capab' : system_capabilities, 'remote_system_enable_capab' : enabled_capabilities }) except Exception: continue # jump to next neighbor return lldp_neighbors def cli(self, commands = None): cli_output = dict() if type(commands) is not list: raise TypeError('Please enter a valid list of commands!') for command in commands: try: cli_output[unicode(command)] = unicode(self.device._execute_show(command)) except TimeoutError: cli_output[unicode(command)] = 'Execution of command "{command}" took too long! Please adjust your params!'.format( command = command ) raise CommandTimeoutException(str(cli_output)) except Exception as e: cli_output[unicode(command)] = 'Unable to execute command "{cmd}": {err}'.format( cmd = command, err = e ) raise CommandErrorException(str(cli_output)) return cli_output def get_bgp_config(self, group = '', neighbor = ''): bgp_config = {} # a helper def build_prefix_limit(af_table, limit, prefix_percent, prefix_timeout): prefix_limit = dict() inet = False inet6 = False preifx_type = 'inet' if 'IPV4' in af_table: inet = True if 'IPv6' in af_table: inet6 = True preifx_type = 'inet6' if inet or inet6: prefix_limit = { preifx_type: { af_table[4:].lower(): { 'limit': limit, 'teardown': { 'threshold': prefix_percent, 'timeout' : prefix_timeout } } } } return prefix_limit # here begins actual method... rpc_command = ''' <Get> <Configuration> <BGP> <Instance> <Naming> <InstanceName> default </InstanceName> </Naming> </Instance> </BGP> </Configuration> </Get> ''' result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) group = group.lower() neighbor = neighbor.lower() if not group: neighbor = '' bgp_group_neighbors = {} for bgp_neighbor in result_tree.iter('Neighbor'): group_name = self._find_txt(bgp_neighbor, 'NeighborGroupAddMember') peer = self._find_txt(bgp_neighbor, 'Naming/NeighborAddress/IPV4Address') or self._find_txt(bgp_neighbor, 'Naming/NeighborAddress/IPV6Address') if neighbor and peer != neighbor: continue description = unicode(self._find_txt(bgp_neighbor, 'Description')) peer_as = int(self._find_txt(bgp_neighbor, 'RemoteAS/AS_YY', 0)) local_as = int(self._find_txt(bgp_neighbor, 'LocalAS/AS_YY', 0)) af_table = self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/Naming/AFName') prefix_limit = int(self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/MaximumPrefixes/PrefixLimit', 0)) prefix_percent = int(self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/MaximumPrefixes/WarningPercentage', 0)) prefix_timeout = int(self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/MaximumPrefixes/RestartTime', 0)) import_policy = unicode(self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/RoutePolicyIn')) export_policy = unicode(self._find_txt(bgp_neighbor, 'NeighborAFTable/NeighborAF/RoutePolicyOut')) local_address = unicode(self._find_txt(bgp_neighbor, 'LocalAddress/LocalIPAddress/IPV4Address') or self._find_txt(bgp_neighbor, 'LocalAddress/LocalIPAddress/IPV6Address')) password = unicode(self._find_txt(bgp_neighbor, 'Password/Password/Password')) nhs = False route_reflector= False if group_name not in bgp_group_neighbors.keys(): bgp_group_neighbors[group_name] = dict() bgp_group_neighbors[group_name][peer] = { 'description' : description, 'remote_as' : peer_as, 'prefix_limit' : build_prefix_limit(af_table, prefix_limit, prefix_percent, prefix_timeout), 'export_policy' : export_policy, 'import_policy' : import_policy, 'local_address' : local_address, 'local_as' : local_as, 'authentication_key' : password, 'nhs' : nhs, 'route_reflector_client': route_reflector } if neighbor and peer == neighbor: break for bgp_group in result_tree.iter('NeighborGroup'): group_name = self._find_txt(bgp_group, 'Naming/NeighborGroupName') if group and group != group_name: continue bgp_type = 'external' # by default external # must check description = unicode(self._find_txt(bgp_group, 'Description')) import_policy = unicode(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/RoutePolicyIn')) export_policy = unicode(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/RoutePolicyOut')) multipath = eval(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/Multipath', 'false').title()) peer_as = int(self._find_txt(bgp_group, 'RemoteAS/AS_YY', 0)) local_as = int(self._find_txt(bgp_group, 'LocalAS/AS_YY', 0)) multihop_ttl = int(self._find_txt(bgp_group, 'EBGPMultihop/MaxHopCount', 0)) local_address = unicode(self._find_txt(bgp_group, 'LocalAddress/LocalIPAddress/IPV4Address') or self._find_txt(bgp_group, 'LocalAddress/LocalIPAddress/IPV6Address')) af_table = self._find_txt(bgp_group, 'NeighborAFTable/NeighborAF/Naming/AFName') prefix_limit = int(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/MaximumPrefixes/PrefixLimit', 0)) prefix_percent= int(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/MaximumPrefixes/WarningPercentage', 0)) prefix_timeout= int(self._find_txt(bgp_group, 'NeighborGroupAFTable/NeighborGroupAF/MaximumPrefixes/RestartTime', 0)) remove_private= True # is it specified in the XML? bgp_config[group_name] = { 'apply_groups' : [], # on IOS-XR will always be empty list! 'description' : description, 'local_as' : local_as, 'type' : unicode(bgp_type), 'import_policy' : import_policy, 'export_policy' : export_policy, 'local_address' : local_address, 'multipath' : multipath, 'multihop_ttl' : multihop_ttl, 'remote_as' : peer_as, 'remove_private_as' : remove_private, 'prefix_limit' : build_prefix_limit(af_table, prefix_limit, prefix_percent, prefix_timeout), 'neighbors' : bgp_group_neighbors.get(group_name, {}) } if group and group == group_name: break return bgp_config def get_bgp_neighbors_detail(self, neighbor_address=''): bgp_neighbors_detail = {} active_vrfs = ['default'] active_vrfs_rpc_request = ( '<Get>' '<Operational>' '<BGP>' '<ConfigInstanceTable>' '<ConfigInstance>' '<Naming>' '<InstanceName>' 'default' '</InstanceName>' '</Naming>' '<ConfigInstanceVRFTable/>' '</ConfigInstance>' '</ConfigInstanceTable>' '</BGP>' '</Operational>' '</Get>' ) active_vrfs_rpc_reply = ETREE.fromstring(self.device.make_rpc_call(active_vrfs_rpc_request)) active_vrfs_tree = active_vrfs_rpc_reply.xpath('.//ConfigVRF') for active_vrf_tree in active_vrfs_tree: active_vrfs.append(find_txt(active_vrf_tree, 'Naming/VRFName')) unique_active_vrfs = set(active_vrfs) bgp_neighbors_vrf_all_rpc = ( '<Get>' '<Operational>' '<BGP>' '<InstanceTable>' '<Instance>' '<Naming>' '<InstanceName>' 'default' '</InstanceName>' '</Naming>' ) for active_vrf in unique_active_vrfs: vrf_rpc = ( '<InstanceActive>' '<VRFTable>' '<VRF>' '<Naming>' '{vrf_name}' '</Naming>' '<GlobalProcessInfo/>' '<NeighborTable/>' '</VRF>' '</VRFTable>' '</InstanceActive>' ) bgp_neighbors_vrf_all_rpc += vrf_rpc.format(vrf_name=active_vrf) bgp_neighbors_vrf_all_rpc += ( '</Instance>' '</InstanceTable>' '</BGP>' '</Operational>' '</Get>' ) bgp_neighbors_vrf_all_tree = ETREE.fromstring(self.device.make_rpc_call(bgp_neighbors_vrf_all_rpc)) _BGP_STATE_ = { '0': 'Unknown', '1': 'Idle', '2': 'Connect', '3': 'OpenSent', '4': 'OpenConfirm', '5': 'Active', '6': 'Established' } instance_active_list = bgp_neighbors_vrf_all_tree.xpath('.//InstanceTable/Instance/InstanceActive/VRFTable/VRF') for vrf_tree in instance_active_list: vrf_name = find_txt(vrf_tree, 'Naming/VRFName') vrf_keepalive = convert(int, find_txt(instance_active_list, 'GlobalProcessInfo/VRF/KeepAliveTime')) vrf_holdtime = convert(int, find_txt(instance_active_list, 'GlobalProcessInfo/VRF/HoldTime')) if vrf_name not in bgp_neighbors_detail.keys(): bgp_neighbors_detail[vrf_name] = {} for neighbor in vrf_tree.xpath('NeighborTable/Neighbor'): up = (find_txt(neighbor, 'ConnectionState') == 'BGP_ST_ESTAB') local_as = convert(int, find_txt(neighbor, 'LocalAS', 0)) remote_as = convert(int, find_txt(neighbor, 'RemoteAS', 0)) router_id = ip(find_txt(neighbor, 'RouterID')) remote_address = ip(find_txt(neighbor, 'Naming/NeighborAddress/IPV4Address')) \ or ip(find_txt(neighbor, 'Naming/NeighborAddress/IPV6Address')) local_address_configured = eval(find_txt(neighbor, 'IsLocalAddressConfigured', 'false').title()) local_address = ip(find_txt(neighbor, 'ConnectionLocalAddress/IPV4Address')) \ or ip(find_txt(neighbor, 'ConnectionLocalAddress/IPV6Address')) local_port = convert(int, find_txt(neighbor, 'ConnectionLocalPort')) remote_address = ip(find_txt(neighbor, 'ConnectionRemoteAddress/IPV4Address')) \ or ip(find_txt(neighbor, 'ConnectionRemoteAddress/IPV6Address')) remote_port = convert(int, find_txt(neighbor, 'ConnectionRemotePort')) multihop = eval(find_txt(neighbor, 'IsExternalNeighborNotDirectlyConnected', 'false').title()) remove_private_as = eval(find_txt(neighbor, 'AFData/Entry/RemovePrivateASFromUpdates', 'false').title()) multipath = eval(find_txt(neighbor, 'AFData/Entry/SelectiveMultipathEligible', 'false').title()) import_policy = find_txt(neighbor, 'AFData/Entry/RoutePolicyIn') export_policy = find_txt(neighbor, 'AFData/Entry/RoutePolicyOut') input_messages = convert(int, find_txt(neighbor, 'MessgesReceived', 0)) output_messages = convert(int, find_txt(neighbor, 'MessagesSent', 0)) connection_up_count = convert(int, find_txt(neighbor, 'ConnectionUpCount', 0)) connection_down_count = convert(int, find_txt(neighbor, 'ConnectionDownCount', 0)) messages_queued_out = convert(int, find_txt(neighbor, 'MessagesQueuedOut', 0)) connection_state = find_txt(neighbor, 'ConnectionState').replace('BGP_ST_', '').title() if connection_state == u'Estab': connection_state = u'Established' previous_connection_state = unicode(_BGP_STATE_.get(find_txt(neighbor, 'PreviousConnectionState', '0'))) active_prefix_count = convert(int, find_txt(neighbor, 'AFData/Entry/NumberOfBestpaths', 0)) accepted_prefix_count = convert(int, find_txt(neighbor, 'AFData/Entry/PrefixesAccepted', 0)) suppressed_prefix_count = convert(int, find_txt(neighbor, 'AFData/Entry/PrefixesDenied', 0)) received_prefix_count = accepted_prefix_count + suppressed_prefix_count # not quite right... advertised_prefix_count = convert(int, find_txt(neighbor, 'AFData/Entry/PrefixesAdvertised', 0)) suppress_4byte_as = eval(find_txt(neighbor, 'Suppress4ByteAs', 'false').title()) local_as_prepend = not eval(find_txt(neighbor, 'LocalASNoPrepend', 'false').title()) holdtime = convert(int, find_txt(neighbor, 'HoldTime', 0)) or vrf_holdtime configured_holdtime = convert(int, find_txt(neighbor, 'ConfiguredHoldTime', 0)) keepalive = convert(int, find_txt(neighbor, 'KeepAliveTime', 0)) or vrf_keepalive configured_keepalive = convert(int, find_txt(neighbor, 'ConfiguredKeepalive', 0)) flap_count = connection_down_count / 2 if up: flap_count -= 1 if remote_as not in bgp_neighbors_detail[vrf_name].keys(): bgp_neighbors_detail[vrf_name][remote_as] = [] bgp_neighbors_detail[vrf_name][remote_as].append({ 'up': up, 'local_as': local_as, 'remote_as': remote_as, 'router_id': router_id, 'local_address': local_address, 'routing_table': vrf_name, 'local_address_configured': local_address_configured, 'local_port': local_port, 'remote_address': remote_address, 'remote_port': remote_port, 'multihop': multihop, 'multipath': multipath, 'import_policy': import_policy, 'export_policy': export_policy, 'input_messages': input_messages, 'output_messages': output_messages, 'input_updates': 0, 'output_updates': 0, 'messages_queued_out': messages_queued_out, 'connection_state': connection_state, 'previous_connection_state': previous_connection_state, 'last_event': u'', 'remove_private_as': remove_private_as, 'suppress_4byte_as': suppress_4byte_as, 'local_as_prepend': local_as_prepend, 'holdtime': holdtime, 'configured_holdtime': configured_holdtime, 'keepalive': keepalive, 'configured_keepalive': configured_keepalive, 'active_prefix_count': active_prefix_count, 'received_prefix_count': received_prefix_count, 'accepted_prefix_count': accepted_prefix_count, 'suppressed_prefix_count': suppressed_prefix_count, 'advertised_prefix_count': advertised_prefix_count, 'flap_count': flap_count }) return bgp_neighbors_detail def get_arp_table(self): arp_table = list() rpc_command = '<Get><Operational><ARP></ARP></Operational></Get>' result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for arp_entry in result_tree.findall('.//EntryTable/Entry'): try: interface = unicode(arp_entry.find('.//InterfaceName').text) ip = unicode(arp_entry.find('.//Address').text) age = float(arp_entry.find('.//Age').text) mac_raw = arp_entry.find('.//HardwareAddress').text mac_all = mac_raw.replace('.', '').replace(':', '') mac_format= unicode(':'.join([mac_all[i:i+2] for i in range(12)[::2]])) arp_table.append( { 'interface' : interface, 'mac' : mac_format, 'ip' : ip, 'age' : age } ) except Exception: continue return arp_table def get_ntp_peers(self): ntp_peers = {} rpc_command = '<Get><Configuration><NTP></NTP></Configuration></Get>' result_tree = ETREE.fromstring(self.device.make_rpc_call(rpc_command)) for version in ['IPV4', 'IPV6']: for peer in result_tree.findall('.//Peer{version}Table/Peer{version}'.format(version=version)): peer_type = find_txt(peer, 'PeerType{version}/Naming/PeerType'.format(version=version)) if peer_type != 'Peer': continue peer_address = find_txt(peer, 'Naming/Address{version}'.format(version=version)) if not peer_address: continue ntp_peers[peer_address] = {} return ntp_peers def get_ntp_servers(self): ntp_servers = {} rpc_command = '<Get><Configuration><NTP></NTP></Configuration></Get>' result_tree = ETREE.fromstring(self.device.make_rpc_call(rpc_command)) for version in ['IPV4', 'IPV6']: for peer in result_tree.xpath('.//Peer{version}Table/Peer{version}'.format(version=version)): peer_type = find_txt(peer, 'PeerType{version}/Naming/PeerType'.format(version=version)) if peer_type != 'Server': continue server_address =find_txt(peer, 'Naming/Address{version}'.format(version=version)) if not server_address: continue ntp_servers[server_address] = {} return ntp_servers def get_ntp_stats(self): ntp_stats = list() rpc_command = '<Get><Operational><NTP><NodeTable></NodeTable></NTP></Operational></Get>' result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for node in result_tree.findall('.//NodeTable/Node/Associations/PeerSummaryInfo/Entry/PeerInfoCommon'): try: synchronized = eval(self._find_txt(node, 'IsSysPeer', 'false').title()) address = unicode(self._find_txt(node, 'Address')) if address == 'DLRSC node': continue referenceid = unicode(self._find_txt(node, 'ReferenceID')) hostpoll = int(self._find_txt(node, 'HostPoll', '0')) reachability = int(self._find_txt(node, 'Reachability', '0')) stratum = int(self._find_txt(node, 'Stratum', '0')) delay = float(self._find_txt(node, 'Delay', '0.0')) offset = float(self._find_txt(node, 'Offset', '0.0')) jitter = float(self._find_txt(node, 'Dispersion', '0.0')) ntp_stats.append({ 'remote' : address, 'synchronized' : synchronized, 'referenceid' : referenceid, 'stratum' : stratum, 'type' : u'', 'when' : u'', 'hostpoll' : hostpoll, 'reachability' : reachability, 'delay' : delay, 'offset' : offset, 'jitter' : jitter }) except Exception: continue return ntp_stats def get_interfaces_ip(self): interfaces_ip = dict() rpc_command_ipv4 = '<Get><Operational><IPV4Network></IPV4Network></Operational></Get>' ipv4_tree = ET.fromstring(self.device.make_rpc_call(rpc_command_ipv4)) for interface in ipv4_tree.findall('.//InterfaceTable/Interface'): try: interface_name = unicode(interface.find('Naming/InterfaceName').text) primary_ip = unicode(interface.find('VRFTable/VRF/Detail/PrimaryAddress').text) primary_prefix = int(interface.find('VRFTable/VRF/Detail/PrefixLength').text) if interface_name not in interfaces_ip.keys(): interfaces_ip[interface_name] = dict() if u'ipv4' not in interfaces_ip[interface_name].keys(): interfaces_ip[interface_name][u'ipv4'] = dict() if primary_ip not in interfaces_ip[interface_name].get(u'ipv4', {}).keys(): interfaces_ip[interface_name][u'ipv4'][primary_ip] = { u'prefix_length': primary_prefix } for secondary_address in interface.findall('VRFTable/VRF/Detail/SecondaryAddress/Entry'): secondary_ip = unicode(secondary_address.find('Address').text) secondary_prefix = int(secondary_address.find('PrefixLength').text) if secondary_ip not in interfaces_ip[interface_name]: interfaces_ip[interface_name][u'ipv4'][secondary_ip] = { u'prefix_length': secondary_prefix } except Exception: continue rpc_command_ipv6 = '<Get><Operational><IPV6Network></IPV6Network></Operational></Get>' ipv6_tree = ET.fromstring(self.device.make_rpc_call(rpc_command_ipv6)) for interface in ipv6_tree.findall('.//InterfaceData/VRFTable/VRF/GlobalDetailTable/GlobalDetail'): interface_name = unicode(interface.find('Naming/InterfaceName').text) if interface_name not in interfaces_ip.keys(): interfaces_ip[interface_name] = dict() if u'ipv6' not in interfaces_ip[interface_name].keys(): interfaces_ip[interface_name][u'ipv6'] = dict() for address in interface.findall('AddressList/Entry'): address_ip = unicode(address.find('Address').text) address_prefix = int(address.find('PrefixLength').text) if address_ip not in interfaces_ip[interface_name].get(u'ipv6', {}).keys(): interfaces_ip[interface_name][u'ipv6'][address_ip] = { u'prefix_length': address_prefix } return interfaces_ip def get_mac_address_table(self): mac_table = list() rpc_command = '<Get><Operational><L2VPNForwarding></L2VPNForwarding></Operational></Get>' result_tree = ET.fromstring(self.device.make_rpc_call(rpc_command)) for mac_entry in result_tree.findall('.//L2FIBMACDetailTable/L2FIBMACDetail'): try: mac_raw = mac_entry.find('Naming/Address').text # will throw error in case not found # and jump to next entry mac_str = mac_raw.replace('.', '').replace(':', '') mac_format = unicode(':'.join([ mac_str[i:i+2] for i in range(12)[::2] ])) vlan = int(self._find_txt(mac_entry, 'Naming/Name', '').replace('vlan', '')) interface = unicode(self._find_txt(mac_entry, 'Segment/AC/InterfaceHandle', u'')) mac_table.append( { 'mac' : mac_format, 'interface' : interface, 'vlan' : vlan, 'active' : True, 'static' : False, 'moves' : 0, 'last_move' : 0.0 } ) except Exception: continue return mac_table def get_route_to(self, destination = '', protocol = ''): routes = {} if not isinstance(destination, str): raise TypeError('Please specify a valid destination!') if not isinstance(protocol, str) or protocol.lower() not in ['static', 'bgp', 'isis']: raise TypeError("Protocol not supported: {protocol}.".format( protocol = protocol )) protocol = protocol.lower() dest_split = destination.split('/') network = dest_split[0] prefix_tag = '' if len(dest_split) == 2: prefix_tag = ''' <PrefixLength> {prefix_length} </PrefixLength> '''.format(prefix_length = dest_split[1]) route_info_rpc_command = ''' <Get> <Operational> <RIB> <VRFTable> <VRF> <Naming> <VRFName> default </VRFName> </Naming> <AFTable> <AF> <Naming> <AFName> IPv4 </AFName> </Naming> <SAFTable> <SAF> <Naming> <SAFName> Unicast </SAFName> </Naming> <IP_RIBRouteTable> <IP_RIBRoute> <Naming> <RouteTableName> default </RouteTableName> </Naming> <RouteTable> <Route> <Naming> <Address> {network} </Address> {prefix} </Naming> </Route> </RouteTable> </IP_RIBRoute> </IP_RIBRouteTable> </SAF> </SAFTable> </AF> </AFTable> </VRF> </VRFTable> </RIB> </Operational> </Get> '''.format( network = network, prefix = prefix_tag ) routes_tree = ET.fromstring(self.device.make_rpc_call(route_info_rpc_command)) for route in routes_tree.iter('Route'): route_details = dict() try: address = route.find('Prefix').text length = route.find('PrefixLength').text distance = int(route.find('Distance').text) protocol = unicode(route.find('ProtocolName').text.upper()) priority = int(route.find('Priority').text) age = int(route.find('RouteAge').text) destination = unicode('{prefix}/{length}'.format( prefix = address, length = length )) if destination not in routes.keys(): routes[destination] = list() except Exception: continue route_details = { 'current_active' : False, 'last_active' : False, 'age' : age, 'next_hop' : u'', 'protocol' : protocol, 'outgoing_interface': u'', 'preference' : priority, 'selected_next_hop' : False, 'inactive_reason' : u'', 'routing_table' : u'default', 'protocol_attributes': {} } # from BGP will try to get some more information if protocol.lower() == 'bgp': # looks like IOS-XR does not filter correctly # !IMPORTANT bgp_route_info_rpc_command = ''' <Get> <Operational> <BGP> <Active> <DefaultVRF> <AFTable> <AF> <Naming> <AFName> IPv4Unicast </AFName> </Naming> <PathTable> <Path> <Naming> <Network> <IPV4Address> {network} </IPV4Address> <IPV4PrefixLength> {prefix_len} </IPV4PrefixLength> </Network> </Naming> </Path> </PathTable> </AF> </AFTable> </DefaultVRF> </Active> </BGP> </Operational> </Get> '''.format( network = network, prefix_len = dest_split[-1] ) bgp_route_tree = ET.fromstring(self.device.make_rpc_call(bgp_route_info_rpc_command)) for bgp_path in bgp_route_tree.iter('Path'): try: best_path = eval(self._find_txt(bgp_path,'PathInformation/IsBestPath', 'false').title()) backup = eval(self._find_txt(bgp_path,'PathInformation/IsPathBackup', 'false').title()) local_preference = int( self._find_txt(bgp_path, 'AttributesAfterPolicyIn/CommonAttributes/LocalPreference', '0') ) local_preference = int( self._find_txt(bgp_path, 'AttributesAfterPolicyIn/CommonAttributes/LocalPreference', '0') ) metric = int( self._find_txt(bgp_path, 'AttributesAfterPolicyIn/CommonAttributes/Metric', '0') ) remote_as = int( self._find_txt(bgp_path, 'AttributesAfterPolicyIn/CommonAttributes/NeighborAS', '0') ) remote_address = unicode(self._find_txt(bgp_path, 'PathInformation/NeighborAddress/IPV4Address') \ or self._find_txt(bgp_path, 'PathInformation/NeighborAddress/IPV6Address')) as_path = ' '.join( [bgp_as.text for bgp_as in bgp_path.findall('AttributesAfterPolicyIn/CommonAttributes/NeighborAS/Entry')] ) next_hop = unicode(self._find_txt(bgp_path, 'PathInformation/NextHop/IPV4Address') \ or self._find_txt(bgp_path, 'PathInformation/NextHop/IPV6Address') ) except Exception: continue single_route_details = route_details.copy() single_route_details['current_active'] = best_path single_route_details['next_hop'] = next_hop single_route_details['protocol_attributes'] = { 'local_preference' : local_preference, 'as_path' : as_path, 'remote_as' : remote_as, 'remote_address' : remote_address } routes[destination].append(single_route_details) else: first_route = True for route_entry in route.findall('RoutePath/Entry'): # get all possible entries try: next_hop = unicode(route_entry.find('Address').text) except Exception: continue single_route_details = route_details.copy() single_route_details.update({ 'current_active': first_route, 'next_hop' : next_hop }) routes[destination].append(single_route_details) first_route = False return routes def get_snmp_information(self): snmp_information = dict() snmp_rpc_command = '<Get><Configuration><SNMP></SNMP></Configuration></Get>' snmp_result_tree = ET.fromstring(self.device.make_rpc_call(snmp_rpc_command)) _PRIVILEGE_MODE_MAP_ = { 'ReadOnly': u'ro', 'ReadWrite': u'rw' } snmp_information = { 'chassis_id': unicode(self._find_txt(snmp_result_tree, './/ChassisID')), 'contact': unicode(self._find_txt(snmp_result_tree, './/Contact')), 'location': unicode(self._find_txt(snmp_result_tree, './/Location')), 'community': {} } for community in snmp_result_tree.iter('DefaultCommunity'): name = unicode(self._find_txt(community, 'Naming/CommunityName')) privilege = self._find_txt(community, 'Priviledge') acl = unicode(self._find_txt(community, 'AccessList')) snmp_information['community'][name] = { 'mode': _PRIVILEGE_MODE_MAP_.get(privilege, u''), 'acl' : acl } return snmp_information def get_probes_config(self): sla_config = dict() _PROBE_TYPE_XML_TAG_MAP_ = { 'ICMPEcho': u'icmp-ping', 'UDPEcho': u'udp-ping', 'ICMPJitter': u'icmp-ping-timestamp', 'UDPJitter': u'udp-ping-timestamp' } sla_config_rpc_command = '<Get><Configuration><IPSLA></IPSLA></Configuration></Get>' sla_config_result_tree = ET.fromstring(self.device.make_rpc_call(sla_config_rpc_command)) for probe in sla_config_result_tree.findall('.//Definition'): probe_name = unicode(self._find_txt(probe, 'Naming/OperationID')) operation_type = probe.find('OperationType').getchildren()[0].tag probe_type = _PROBE_TYPE_XML_TAG_MAP_.get(operation_type, u'') operation = probe.find('OperationType').find(operation_type) test_name = unicode(self._find_txt(operation, 'Tag')) source = unicode(self._find_txt(operation, 'SourceAddress')) target = unicode(self._find_txt(operation, 'DestAddress')) test_interval = int(self._find_txt(operation, 'Frequency', '0')) # defined in seconds probe_count = int(self._find_txt(operation, 'History/Buckets', '0')) if probe_name not in sla_config.keys(): sla_config[probe_name] = dict() if test_name not in sla_config[probe_name]: sla_config[probe_name][test_name] = dict() sla_config[probe_name][test_name] = { 'probe_type': probe_type, 'source': source, 'target': target, 'probe_count': probe_count, 'test_interval': test_interval } return sla_config def get_probes_results(self): sla_results = dict() _PROBE_TYPE_XML_TAG_MAP_ = { 'ICMPEcho': u'icmp-ping', 'UDPEcho': u'udp-ping', 'ICMPJitter': u'icmp-ping-timestamp', 'UDPJitter': u'udp-ping-timestamp' } sla_results_rpc_command = '<Get><Operational><IPSLA></IPSLA></Operational></Get>' sla_results_tree = ET.fromstring(self.device.make_rpc_call(sla_results_rpc_command)) probes_config = self.get_probes_config() # need to retrieve also the configuration # source and tag/test_name not provided for probe in sla_results_tree.findall('.//Operation'): probe_name = unicode(self._find_txt(probe, 'Naming/OperationID')) test_name = probes_config.get(probe_name).keys()[0] target = unicode(self._find_txt(probe, 'History/Target/LifeTable/Life/BucketTable/Bucket[0]/TargetAddress/IPv4AddressTarget')) source = probes_config.get(probe_name).get(test_name, {}).get('source', '') probe_type = _PROBE_TYPE_XML_TAG_MAP_.get(self._find_txt(probe, 'Statistics/Latest/Target/SpecificStats/op_type')) test_interval = int(self._find_txt(probe, 'Common/OperationalState/Frequency')) * 1e-3 # here f is defined in miliseconds probe_count = probes_config.get(probe_name).get(test_name, {}).get('probe_count', 0) # rtt = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/ResponseTime')) response_times = probe.findall('History/Target/LifeTable/Life[last()]/BucketTable/Bucket/ResponseTime') response_times = [int(self._find_txt(response_time, '.', '0')) for response_time in response_times] rtt = 0.0 if len(response_times): rtt = sum(response_times, 0.0)/len(response_times) return_codes = probe.findall('History/Target/LifeTable/Life[last()]/BucketTable/Bucket/ReturnCode') return_codes = [self._find_txt(return_code, '.') for return_code in return_codes] last_test_loss = 0.0 if len(return_codes): last_test_loss = int(100*(1-return_codes.count('ipslaRetCodeOK')/float(len(return_codes)))) rms = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/Sum2ResponseTime')) global_test_updates = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/UpdateCount')) jitter = rtt-(rms/global_test_updates)**0.5 # jitter = max(rtt - max(response_times), rtt - min(response_times)) current_test_min_delay = 0.0 # no stats for undergoing test :( current_test_max_delay = 0.0 current_test_avg_delay = 0.0 last_test_min_delay = float(self._find_txt(probe, 'Statistics/Latest/Target/CommonStats/MinResponseTime')) last_test_max_delay = float(self._find_txt(probe, 'Statistics/Latest/Target/CommonStats/MaxResponseTime')) last_test_sum_delay = float(self._find_txt(probe, 'Statistics/Latest/Target/CommonStats/SumResponseTime')) last_test_updates = float(self._find_txt(probe, 'Statistics/Latest/Target/CommonStats/UpdateCount')) last_test_avg_delay = 0.0 if last_test_updates: last_test_avg_delay = last_test_sum_delay/last_test_updates global_test_min_delay = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/MinResponseTime')) global_test_max_delay = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/MaxResponseTime')) global_test_sum_delay = float(self._find_txt(probe, 'Statistics/Aggregated/HourTable/Hour/Distributed/Target/DistributionIntervalTable/DistributionInterval/CommonStats/SumResponseTime')) global_test_avg_delay = 0.0 if global_test_updates: global_test_avg_delay = global_test_sum_delay/global_test_updates if probe_name not in sla_results.keys(): sla_results[probe_name] = dict() sla_results[probe_name][test_name] = { 'target': target, 'source': source, 'probe_type': probe_type, 'probe_count': probe_count, 'rtt': rtt, 'round_trip_jitter': jitter, 'last_test_loss': last_test_loss, 'current_test_min_delay': current_test_min_delay, 'current_test_max_delay': current_test_max_delay, 'current_test_avg_delay': current_test_avg_delay, 'last_test_min_delay': last_test_min_delay, 'last_test_max_delay': last_test_max_delay, 'last_test_avg_delay': last_test_avg_delay, 'global_test_min_delay': global_test_min_delay, 'global_test_max_delay': global_test_max_delay, 'global_test_avg_delay': global_test_avg_delay } return sla_results def traceroute(self, destination, source='', ttl=0, timeout=0): traceroute_result = dict() ipv = 4 try: ipv = IPAddress(destination).version except AddrFormatError: return {'error': 'Wrong destination IP Address!'} source_tag = '' ttl_tag = '' timeout_tag = '' if source: source_tag = '<Source>{source}</Source>'.format(source = source) if ttl: ttl_tag = '<MaxTTL>{maxttl}</MaxTTL>'.format(maxttl = ttl) if timeout: timout_tag = '<Timeout>{timeout}</Timeout>'.format(timeout = timeout) else: timeout = 5 # seconds traceroute_rpc_command = ''' <Set> <Action> <TraceRoute> <IPV{version}> <Destination> {destination} </Destination> {source_tag} {ttl_tag} {timeout_tag} </IPV{version}> </TraceRoute> </Action> </Set> '''.format( version=ipv, destination=destination, source_tag=source_tag, ttl_tag=ttl_tag, timeout_tag=timeout_tag ) xml_tree_txt = self.device.make_rpc_call(traceroute_rpc_command) traceroute_tree = ET.fromstring(xml_tree_txt) results_tree = traceroute_tree.find('.//Results') results_error = self._find_txt(results_tree, 'Error') if results_error: return {'error': results_error} if results_tree is None or not len(results_tree): return {'error': 'Device returned empty results.'} traceroute_result['success'] = {} last_hop_index = 1 last_probe_index = 1 last_probe_ip_address = '*' last_probe_host_name = '' last_hop_dict = {'probes': {}} for thanks_cisco in results_tree.getchildren(): tag_name = thanks_cisco.tag tag_value = thanks_cisco.text if tag_name == 'HopIndex': new_hop_index = int(self._find_txt(thanks_cisco, '.', '-1')) if last_hop_index and last_hop_index != new_hop_index: traceroute_result['success'][last_hop_index] = copy.deepcopy(last_hop_dict) last_hop_dict = {'probes': {}} last_probe_ip_address = '*' last_probe_host_name = '' last_hop_index = new_hop_index continue tag_value = unicode(self._find_txt(thanks_cisco, '.', '')) if tag_name == 'ProbeIndex': last_probe_index = self._convert(int, tag_value, 0) + 1 if last_probe_index not in last_hop_dict.get('probes').keys(): last_hop_dict['probes'][last_probe_index] = {} if not last_probe_host_name: last_probe_host_name = last_probe_ip_address last_hop_dict['probes'][last_probe_index] = { 'ip_address': unicode(last_probe_ip_address), 'host_name': unicode(last_probe_host_name), 'rtt': timeout * 1000.0 } continue if tag_name == 'HopAddress': last_probe_ip_address = tag_value continue if tag_name == 'HopHostName': last_probe_host_name = tag_value continue if tag_name == 'DeltaTime': last_hop_dict['probes'][last_probe_index]['rtt'] = self._convert(float, tag_value, 0.0) continue if last_hop_index: traceroute_result['success'][last_hop_index] = last_hop_dict return traceroute_result def get_users(self): users = dict() _CISCO_GROUP_TO_CISCO_PRIVILEGE_MAP = { 'root-system': 15, 'operator': 5, 'sysadmin': 1, 'serviceadmin': 1, 'root-lr': 15 } _DEFAULT_USER_DETAILS = { 'level': 0, 'password': '', 'sshkeys': [] } users_xml_req = '<Get><Configuration><AAA></AAA></Configuration></Get>' users_xml_reply = ET.fromstring(self.device.make_rpc_call(users_xml_req)) for user_entry in users_xml_reply.findall('.//Username'): username = unicode(self._find_txt(user_entry, 'Naming/Name')) group = self._find_txt(user_entry, 'UsergroupsUnderUsername/UsergroupUnderUsername/Naming/Name', '') level = _CISCO_GROUP_TO_CISCO_PRIVILEGE_MAP.get(group, 0) password = self._find_txt(user_entry, 'Password/Password') user_details = _DEFAULT_USER_DETAILS.copy() user_details.update({ 'level': level, 'password': password }) users[username] = user_details return users

45.848272

198

0.518572

6,912

78,263

5.601563

0.120226

0.025311

0.023865

0.014102

0.422

0.351749

0.279172

0.227388

0.191384

0.148846

0

0.00528

0.38538

78,263

1,706

199

45.875147

0.799634

0.025644

0

0.271296

0

0.000716

0.309241

0.09473

0

1

0.02577

false

0.005727

0.015032

0.000716

0.067287

0.000716

0

null

0

null

0

1

0

0f01e48d0c802a8abbb9c8391e045c7b8aa15816

411

py

Python

src/calPixels.py

imohamadhoseins/ObjectSegmentCNN

755d7cf80139f48da1accba6e42bea0b381aaa64

[ "MIT" ]

null

src/calPixels.py

imohamadhoseins/ObjectSegmentCNN

755d7cf80139f48da1accba6e42bea0b381aaa64

[ "MIT" ]

null

src/calPixels.py

imohamadhoseins/ObjectSegmentCNN

755d7cf80139f48da1accba6e42bea0b381aaa64

[ "MIT" ]

null

import os import cv2 image_name = 'Binary/ILSVRC2012_test_00096192.jpg' image = cv2.imread(image_name) height, width, channel = image.shape counter = 0 for j in range(height): for k in range(width): color = image[j][k] if color[0] == 0 and color[1] == 0 and color[2] == 0: counter += 1 print('counter', counter) print('area', width * height) print('ratio', counter/(width * height))

22.833333

56

0.654501

63

411

4.206349

0.47619

0.067925

0

0.066869

0.199513

411

18

57

22.833333

0.738602

0

0.129114

0.088608

0

1

0

false

0

0.142857

0

0.142857

0.214286

0

null

0

null

0

1

0

0f09854540cbe2f68e01e0a4c67c7ba05b8bfc38

5,556

py

Python

AI/w2v clustering.py

osamhack2021/APP_AI_MMIS_teamMMIS

6055f6dffda2ec09ed37251a8228e7371a22d206

[ "MIT" ]

2

2021-09-12T13:33:48.000Z

2021-09-13T11:00:53.000Z

AI/w2v clustering.py

osamhack2021/APP_WEB_AI_MMIS_teamMMIS

b39d889126c80416acaeb48ebfa895fbe41321e0

[ "MIT" ]

null

AI/w2v clustering.py

osamhack2021/APP_WEB_AI_MMIS_teamMMIS

b39d889126c80416acaeb48ebfa895fbe41321e0

[ "MIT" ]

2

2021-09-16T10:56:01.000Z

2021-09-29T09:52:34.000Z

#%% #패키지 불러오기 import pandas as pd import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt from pandas.core.frame import DataFrame from gensim.models import Word2Vec #형태소 분석 패키지 from konlpy.tag import Okt from konlpy.tag import Komoran from sklearn.utils.validation import indexable # 데이터 불러오기 data= pd.read_csv("All Menu (Various Versions)/국방부메뉴_v2.1.csv", encoding="UTF-8") # 정규 표현식을 통한 한글 외 문자 제거 data['메뉴이름'] = data['메뉴이름'].str.replace("[^ㄱ-ㅎㅏ-ㅣ가-힣 ]","") data['메뉴이름'] = data['메뉴이름'].str.replace(" ","") # 중복 제거 data = data.drop_duplicates(['메뉴이름'], ignore_index=True) # 정규화 for i in data: if(i in ['계란류', '우유', '메밀', '땅콩', '대두', '밀', '고등어', '게', '새우', '돼지고기', '복숭아', '토마토', '아황산류', '호두', '닭고기', '쇠고기', '오징어', '조개류', '잣']): data[i] = data[i]/100 if i in ['열량', '탄수화물', '지방', '단백질', '나트륨', '콜레스트롤']: data[i] = ((data[i]-data[i].mean())/data[i].std())/500 # # Komoran 사용한 토큰화 작업 # okt, komoran 이 사용 가능(절대적 우위 가리기 불가) & morphs # kkma는 시간이 오래 걸림/ hannanum은 위의 두 개 보다 성능 낮음 komoran = Komoran() okt=Okt() tokenized_data=[] for menu in data['메뉴이름']: temp_X = okt.morphs(menu) #토큰화 tokenized_data.append(temp_X) # word2vec 사용 model = Word2Vec(sentences=tokenized_data, vector_size=200 , window=3, min_count=0, workers=4, sg=0) # # 메뉴별 벡터 구하는 함수 def get_sentence_mean_vector(morphs): vector=[] for i in morphs: try: vector.append(model.wv[i]) except KeyError as e: pass try: return np.mean(vector, axis=0).tolist() except IndexError as e: pass # # sentence vector를 data에 추가 sentence_vector=[] for vectors in tokenized_data: temp_X = get_sentence_mean_vector(vectors) sentence_vector.append(temp_X) data.insert(3, 'wv',sentence_vector) # # clustering -> 추천 잘 될 수 있는지 시각화 용도 dataList=[] for i in range(0, 1550): vectorData=data['wv'][i] for j in ['계란류', '우유', '메밀', '땅콩', '대두', '밀', '고등어', '게', '새우', '돼지고기', '복숭아', '토마토', '아황산류', '호두', '닭고기', '쇠고기', '오징어', '조개류', '잣', '열량', '탄수화물', '지방', '단백질', '나트륨', '콜레스트롤']: vectorData.append(data[j][i]) dataList.append(vectorData) from sklearn.cluster import KMeans num_clusters = 10 k_means_clustering = KMeans(n_clusters=num_clusters) idx = k_means_clustering.fit_predict(dataList) data['category']=idx # # Embedding & 시각화 위해 import from sklearn.manifold import TSNE import os.path import pickle # 차원축소(2차원으로) X = data['wv'].tolist() y = data['category'].tolist() tsne_filepath = 'tnse3000(w2v).pkl' # File Cache if not os.path.exists(tsne_filepath): tsne = TSNE(random_state=42) tsne_points = tsne.fit_transform(X) with open(tsne_filepath, 'wb+') as f: pickle.dump(tsne_points, f) else: #cache hits with open(tsne_filepath, 'rb') as f: tsne_points=pickle.load(f) tsne=TSNE(random_state=42) tsne_points = tsne.fit_transform(X) tsne_df = pd.DataFrame(tsne_points, index=range(len(X)), columns=['x_coord', 'y_coord']) tsne_df['menu_name']=data['메뉴이름'].tolist() tsne_df['cluster_number'] = y #2차원 plotting from bokeh.plotting import figure, show, output_notebook from bokeh.models import HoverTool, ColumnDataSource, value from bokeh.palettes import brewer output_notebook() # Get the number of colors we'll need for the plot. colors = brewer["Spectral"][len(tsne_df['cluster_number'].unique())] # Create a map between factor and color. colormap = {i: colors[i] for i in tsne_df['cluster_number'].unique()} # Create a list of colors for each value that we will be looking at. colors = [colormap[x] for x in tsne_df['cluster_number']] tsne_df['color']=colors # Bokeh Datasouce 만들기 plot_data = ColumnDataSource( data=tsne_df.to_dict(orient='list') ) # Plot 만들기(배경) tsne_plot = figure( # title='TSNE Twitter BIO Embeddings', plot_width = 650, plot_height = 650, active_scroll='wheel_zoom', output_backend="webgl", ) # 해당 Hover 툴팁 만들기 tsne_plot.add_tools( HoverTool( tooltips='@menu_name' ) ) tsne_plot.circle( source=plot_data, x='x_coord', y='y_coord', line_alpha=0.3, fill_alpha=0.2, size=10, fill_color='color', line_color='color', ) # 각 값들 추가해주기 tsne_plot.title.text_font_size = '16pt' tsne_plot.xaxis.visible = False tsne_plot.yaxis.visible = False tsne_plot.grid.grid_line_color = None tsne_plot.outline_line_color = None # 짠! show(tsne_plot) # # 유사 메뉴 추천 from sklearn.metrics.pairwise import cosine_similarity import warnings; warnings.filterwarnings('ignore') # # 코사인 유사도 계산 menuNameSimilarity = cosine_similarity(dataList, dataList) # 유사도 정렬 menu_sim_sorted_idx = menuNameSimilarity.argsort()[:, ::-1] # # 유사 메뉴 추천 함수 def find_sim_menu(data, sorted_idx, name, number=10): title_menu=data[data['메뉴이름']==name] title_menu_idx = title_menu.index.values top_sim_idx = sorted_idx[title_menu_idx, :number] top_sim_idx = top_sim_idx.reshape(-1,) similar_menu = data.iloc[top_sim_idx]['메뉴이름'] similar_menu_list =[] for sim_menu in similar_menu: similar_menu_list.append(sim_menu) return similar_menu_list[1:4] # # 메뉴 추천 Test recommendMenus = ['청양마요치킨', '비엔나소시지찌개','햄치즈버거','탕수육','두부고추장찌개','낙지덮밥','꼬리곰탕','김장김치','콘형아이스크림'] for menu in recommendMenus: print(menu, end=' : ') print(find_sim_menu(data, menu_sim_sorted_idx, menu)) # %% # 서비스 작동을 위한 배열 저장 np.save('/workspaces/APP_AI_MMIS_teamMMIS/AI/server/AI file/w2v_menu_sim_sorted_idx',menu_sim_sorted_idx) data.to_csv('/workspaces/APP_AI_MMIS_teamMMIS/AI/server/AI file/data.csv') # %%

23.948276

180

0.678906

859

5,556

4.222352

0.406286

0.019851

0.006617

0.020954

0.135925

0.118555

0.093741

0.076096

0.053488

0

0.013049

0.172426

5,556

231

181

24.051948

0.77599

0.12023

0

0.062016

0

0.126394

0.029327

0

1

0.015504

false

0.015504

0.139535

0

0.170543

0.015504

0

null

0

null

0

1

0

0f09abf5936e787e6ef87489854c7b6ad3be7773

8,324

py

Python

src/model/efficient_disparity.py

JonasFrey96/FlowPose6D

2297ab5fa0afd0c247d59c2f1c7f899f078e2893

[ "MIT" ]

null

src/model/efficient_disparity.py

JonasFrey96/FlowPose6D

2297ab5fa0afd0c247d59c2f1c7f899f078e2893

[ "MIT" ]

null

src/model/efficient_disparity.py

JonasFrey96/FlowPose6D

2297ab5fa0afd0c247d59c2f1c7f899f078e2893

[ "MIT" ]

null

import torch from efficientnet_pytorch import EfficientNet from torch import nn from torchvision import transforms def deconv(in_planes, out_planes, bias=False): return nn.Sequential( nn.ConvTranspose2d(in_planes, out_planes, kernel_size=4, stride=2, padding=1, bias=bias), nn.LeakyReLU(0.1, inplace=True) ) def predict_flow(in_planes): return nn.Conv2d(in_planes, 2, kernel_size=3, stride=1, padding=1, bias=False) def cat(x, y): if x == None: return y else: return torch.cat( [x,y], dim= 1) class EfficientDisparity(nn.Module): def __init__(self, num_classes = 22, backbone= 'efficientnet-b1', seperate_flow_head= False, pred_flow_pyramid=True, pred_flow_pyramid_add=True, ced_real=1, ced_render=1, ced_render_d=1,ced_real_d=1): # tested with b6 super().__init__() self.feature_extractor = EfficientNet.from_pretrained(backbone) self.size = self.feature_extractor.get_image_size( backbone ) self.seperate_flow_head = seperate_flow_head self.ced_real = ced_real self.ced_render = ced_render self.ced_real_d = ced_real_d self.ced_render_d = ced_render_d self.pred_flow_pyramid_add = pred_flow_pyramid_add self.pred_flow_pyramid = pred_flow_pyramid idxs, feats, res = self.feature_extractor.layer_info( torch.ones( (4,3,self.size, self.size))) if ced_render_d > 0 or ced_real_d > 0: self.depth_backbone = True else: self.depth_backbone = False if self.depth_backbone: self.feature_extractor_depth = EfficientNet.from_name(backbone, in_channels=1) r = res[0] self.idx_extract = [] self.feature_sizes = [] for i in range(len(idxs)): if r != res[i]: self.idx_extract.append(i-1) r = res[i] self.feature_sizes.append( feats[i-1] ) self.idx_extract.append(len(idxs)-1) self.feature_sizes.append( feats[len(idxs)-1] ) self._num_classes = num_classes dc = [] pred_flow_pyramid = [] upsample_flow_layers = [] self.feature_sizes = [8] + self.feature_sizes label_feat = [16,8, num_classes] label_layers = [] label_i = -1 for i in range( 1, len(self.feature_sizes) ): if i == 1: inc_feat_0 = (int(ced_real>0) + int(ced_render>0) + int(ced_render_d>0) + int(ced_real_d>0)) * self.feature_sizes[-i ] else: inc_feat_0 = (int(ced_real>=i) + int(ced_render>=i) + int(ced_render_d>=i) + int(ced_real_d>=i) + 1 ) * self.feature_sizes[-i] if self.pred_flow_pyramid_add and self.pred_flow_pyramid: inc_feat_0 += 2 out_feat = self.feature_sizes[- (i+1) ] #leave this number for now on constant dc.append( deconv( inc_feat_0 , out_feat ) ) print( 'Network inp:', inc_feat_0, ' out: ', out_feat ) if i > len(self.feature_sizes)-len(label_feat): if label_i == -1: inc_feat_label = inc_feat_0 else: inc_feat_label = label_feat[label_i] label_i += 1 out_feat_label = label_feat[label_i] label_layers.append( deconv( inc_feat_label , out_feat_label, bias=True ) ) if self.pred_flow_pyramid: pred_flow_pyramid.append( predict_flow( inc_feat_0 ) ) upsample_flow_layers.append( nn.ConvTranspose2d( 2, 2, 4, 2, 1, bias=False)) label_layers.append( deconv(label_feat[-2], label_feat[-1], bias=True) ) self.label_layers = nn.ModuleList(label_layers) self.deconvs = nn.ModuleList(dc) pred_flow_pyramid.append( predict_flow( self.feature_sizes[0]) ) if self.pred_flow_pyramid: self.pred_flow_pyramid= nn.ModuleList( pred_flow_pyramid ) self.upsample_flow_layers = nn.ModuleList(upsample_flow_layers) self.up_in = torch.nn.UpsamplingBilinear2d(size=(self.size, self.size)) self.input_trafos = transforms.Compose([ transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]) self.norm_depth = transforms.Normalize([0.485,0.485], [0.229,0.229]) self.up_out = torch.nn.UpsamplingNearest2d(size=(480, 640)) self.up_out_bl = torch.nn.UpsamplingBilinear2d(size=(480, 640)) self.up_nn_in= torch.nn.UpsamplingNearest2d(size=(self.size, self.size)) def forward(self, data, idx=False, label=None): """Forward pass Args: data ([torch.tensor]): BS,C,H,W (C=6) if self.depth_backbone: C = 8 else: C = 6 idx ([torch.tensor]): BS,1 starting for first object with 0 endind with num_classes-1 label ([type], optional): [description]. Defaults to None. Returns: flow ([torch.tensor]): BS,2,H,W segmentation ([torch.tensor]): BS,num_classes,H,W """ # is it smart to have the residual skip connections only for the real image of course the information should be given for the real image but therfore the network needs to learn how to fully encode the rendered image correctly # data BS, C, H, W BS,C,H,W = data.shape real = self.up_in(data[:,:3] ) render = self.up_in(data[:,3:6] ) if self.depth_backbone: data[:,6:] = data[:,6:]/10000 for i in range(BS): real[i] = self.input_trafos( real[i] ) render[i] = self.input_trafos( render[i] ) if self.depth_backbone: real_d = self.up_nn_in(data[:,6][:,None,:,:] ) render_d = self.up_nn_in(data[:,7][:,None,:,:] ) feat_real_d = self.feature_extractor_depth.extract_features_layerwise( real_d , idx_extract = self.idx_extract[-(self.ced_real_d):]) feat_render_d = self.feature_extractor_depth.extract_features_layerwise( render_d , idx_extract = self.idx_extract[-(self.ced_render_d):]) feat_real = self.feature_extractor.extract_features_layerwise( real , idx_extract = self.idx_extract) feat_render = self.feature_extractor.extract_features_layerwise( render, idx_extract = self.idx_extract) pred_flow_pyramid_feat = [] x = None for j in range( 1,len( self.deconvs)+1 ): # calculate input: # accumulate input to each layer if j-1 < self.ced_real: x = cat( x, feat_real[-j] ) if j-1 < self.ced_render: x = cat( x, feat_render[-j]) if j-1 < self.ced_real_d: x = cat( x, feat_real_d[-j]) if j-1 < self.ced_render_d: x = cat( x, feat_render_d[-j]) if j > 1 and self.pred_flow_pyramid_add: dim = x.shape[3] # upsample flow f_up = self.upsample_flow_layers[j-2]( pred_flow_pyramid_feat[-1]) [:,:,:dim,:dim] x = cat( x, f_up ) # predict flow at each level if self.pred_flow_pyramid: pred_flow_pyramid_feat.append( self.pred_flow_pyramid[ j-1 ](x) ) try: dim = feat_real[-(j+1)].shape[3] pred_flow_pyramid_feat[-1] = pred_flow_pyramid_feat[-1][:,:,:dim,:dim] except: pass if j == len(self.deconvs) - len(self.label_layers)+2 : # clone features for mask prediction. # here the conv are with bias !!! segmentation = x.clone() # apply upcovn layer x = self.deconvs[j-1](x) try: dim = feat_real[-(j+1)].shape[3] x = x[:,:,:dim,:dim] except: pass # predict label for l in self.label_layers: segmentation = l(segmentation) segmentation = self.up_out(segmentation) # predict flow pred_flow_pyramid_feat.append( self.pred_flow_pyramid[-1](x) ) pred_flow_pyramid_feat.append( self.up_out_bl( pred_flow_pyramid_feat[-1] ) ) if label is None: label = segmentation.argmax(dim=1) return pred_flow_pyramid_feat, segmentation if __name__ == "__main__": model = EfficientDisparity(num_classes = 22, backbone= 'efficientnet-b2', seperate_flow_head= False, pred_flow_pyramid=True, pred_flow_pyramid_add=True, ced_real=3, ced_render=3, ced_render_d=2,ced_real_d=2) BS = 2 H = 480 W = 640 C = 8 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') data = torch.ones( (BS,C,H,W), device=device ) model = model.to(device) idx = torch.linspace(0,BS-1,BS)[:,None] out = model(data, idx = idx) # for i in range(0,7): # model = EfficientDisparity(num_classes = 22, backbone= f'efficientnet-b{i}', connections_encoder_decoder = 2, depth_backbone = True)

38.183486

229

0.652811

1,255

8,324

4.074104

0.163347

0.046939

0.088011

0.040876

0.319382

0.200665

0.132408

0.097203

0.05398

0.036769

0

0.028023

0.224051

8,324

218

230

38.183486

0.763586

0.121696

0

0.115385

0

0.008679

0

1

0.032051

false

0.012821

0.025641

0.012821

0.096154

0.00641

0

null

0

null

0

1

0

0f09cfb8f6847b0ac4050794ebf1bdbab43941f3

843

py

Python

cnap_v2/celery_app.py

qbrc-cnap/cnap

624683e91a64c3b4934b578c59db850242d2f94c

[ "MIT" ]

1

2021-07-08T14:06:04.000Z

cnap_v2/celery_app.py

qbrc-cnap/cnap

624683e91a64c3b4934b578c59db850242d2f94c

[ "MIT" ]

12

2020-02-12T00:10:53.000Z

2021-06-10T21:24:45.000Z

cnap_v2/celery_app.py

qbrc-cnap/cnap

624683e91a64c3b4934b578c59db850242d2f94c

[ "MIT" ]

null

import os from celery import Celery from django.conf import settings from django.apps import apps from celery.schedules import crontab # set the default Django settings module for the 'celery' program. os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'cnap_v2.settings') app = Celery('cnap_v2') # Using a string here means the worker will not have to # pickle the object when using Windows. app.config_from_object('django.conf:settings', namespace='CELERY') app.autodiscover_tasks(lambda: [n.name for n in apps.get_app_configs()]) app.conf.beat_schedule = { 'check_jobs':{ 'task': 'check_job', 'schedule': 60.0 }, 'manage_file': { 'task': 'manage_files', 'schedule': crontab(hour=8, minute=15) } } @app.task(bind=True) def debug_task(self): print('Request: {0!r}'.format(self.request))

26.34375

72

0.705813

121

843

4.793388

0.570248

0.034483

0.068966

0

0.012839

0.168446

843

31

73

27.193548

0.814551

0.185053

0

0.221083

0.032211

0

1

0.045455

false

0

0.227273

0

0.272727

0.045455

0

null

0

null

0

1

0

0f09fa31a27e27c6677b9ba18770a56c391f691a

1,059

py

Python

DecryptLogin/modules/clients/xiaomihealth.py

hedou/DecryptLogin

ff86a5d378c8a42d1caebbb7482658a95053f716

[ "Apache-2.0" ]

null

DecryptLogin/modules/clients/xiaomihealth.py

hedou/DecryptLogin

ff86a5d378c8a42d1caebbb7482658a95053f716

[ "Apache-2.0" ]

null

DecryptLogin/modules/clients/xiaomihealth.py

hedou/DecryptLogin

ff86a5d378c8a42d1caebbb7482658a95053f716

[ "Apache-2.0" ]

null

''' Function: 小米健康客户端 Author: Charles 微信公众号: Charles的皮卡丘更新日期: 2022-03-11 ''' from .baseclient import BaseClient '''小米健康客户端''' class XiaomiHealthClient(BaseClient): def __init__(self, reload_history=True, **kwargs): super(XiaomiHealthClient, self).__init__(website_name='xiaomihealth', reload_history=reload_history, **kwargs) '''检查会话是否已经过期, 过期返回True''' def checksessionstatus(self, session, infos_return): login_token = infos_return['token_info']['login_token'] url = 'https://account-cn.huami.com/v1/client/app_tokens' headers = {'User-Agent': 'Dalvik/2.1.0 (Linux; U; Android 9; MI 6 MIUI/20.6.18)'} params = { 'app_name': 'com.xiaomi.hm.health', 'dn': 'api-user.huami.com%2Capi-mifit.huami.com%2Capp-analytics.huami.com', 'login_token': login_token, } response = self.session.get(url, params=params, headers=headers) if response.json().get('token_info', {}).get('app_token', ''): return False return True

34.16129

118

0.641171

126

1,059

5.206349

0.603175

0.060976

0

0.02506

0.208687

1,059

31

119

34.16129

0.757757

0.080264

0

0.117647

0.292026

0.071121

0

1

0.117647

false

0

0.058824

0

0.352941

0

null

0

null

0

1

0

0f0a17f2452f2173197a297e25bb4a1a971989ed

6,401

py

Python

pbsmmapi/show/models.py

WGBH/django-pbsmmapi

d20d01d2724715379adb2c754ed2537688a1dd1f

[ "MIT" ]

null

pbsmmapi/show/models.py

WGBH/django-pbsmmapi

d20d01d2724715379adb2c754ed2537688a1dd1f

[ "MIT" ]

null

pbsmmapi/show/models.py

WGBH/django-pbsmmapi

d20d01d2724715379adb2c754ed2537688a1dd1f

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from uuid import UUID from django.db import models from django.dispatch import receiver from django.utils.translation import ugettext_lazy as _ from django.urls import reverse from ..abstract.gatekeeper import can_object_page_be_shown from ..abstract.helpers import time_zone_aware_now from ..abstract.models import PBSMMGenericShow from ..api.api import get_PBSMM_record from ..api.helpers import check_pagination from ..asset.ingest_asset import process_asset_record from ..asset.models import PBSMMAbstractAsset from .ingest_show import process_show_record from .ingest_children import process_seasons, process_specials PBSMM_SHOW_ENDPOINT = 'https://media.services.pbs.org/api/v1/shows/' class PBSMMAbstractShow(PBSMMGenericShow): ingest_seasons = models.BooleanField( _('Ingest Seasons'), default=False, help_text='Also ingest all Seasons', ) ingest_specials = models.BooleanField( _('Ingest Specials'), default=False, help_text='Also ingest all Specials', ) ingest_episodes = models.BooleanField( _('Ingest Episodes'), default=False, help_text='Also ingest all Episodes (for each Season)', ) class Meta: verbose_name = 'PBS MM Show' verbose_name_plural = 'PBS MM Shows' db_table = 'pbsmm_show' abstract = True def get_absolute_url(self): return reverse('show-detail', args=[self.slug]) def __unicode__(self): if self.title: return self.title return "ID %d: unknown" % self.id def __object_model_type(self): # This handles the correspondence to the "type" field in the PBSMM JSON # object return 'show' object_model_type = property(__object_model_type) def __available_to_public(self): return can_object_page_be_shown(None, self) available_to_public = property(__available_to_public) class PBSMMShow(PBSMMAbstractShow): pass class PBSMMShowAsset(PBSMMAbstractAsset): show = models.ForeignKey( PBSMMShow, related_name='assets', on_delete=models.CASCADE, # required for Django 2.0 ) class Meta: verbose_name = 'PBS MM Show - Asset' verbose_name_plural = 'PBS MM Shows - Assets' db_table = 'pbsmm_show_asset' def __unicode__(self): return "%s: %s" % (self.show, self.title) def process_show_assets(endpoint, this_show): keep_going = True scraped_object_ids = [] while keep_going: (status, json) = get_PBSMM_record(endpoint) data = json['data'] for item in data: object_id = item.get('id') scraped_object_ids.append(UUID(object_id)) try: instance = PBSMMShowAsset.objects.get(object_id=object_id) except PBSMMShowAsset.DoesNotExist: instance = PBSMMShowAsset() instance = process_asset_record(item, instance, origin='show') # For now - borrow from the parent object instance.last_api_status = status instance.date_last_api_update = time_zone_aware_now() instance.show = this_show instance.ingest_on_save = True # This needs to be here because otherwise it never updates... instance.save() (keep_going, endpoint) = check_pagination(json) for asset in PBSMMShowAsset.objects.filter(show=this_show): if asset.object_id not in scraped_object_ids: asset.delete() ################################ # PBS MediaManager API interface ################################ # The interface/access is done with a 'pre_save' receiver based on the value of 'ingest_on_save' # That way, one can force a reingestion from the Admin OR one can do it from a management script # by simply getting the record, setting ingest_on_save on the record, and calling save(). @receiver(models.signals.pre_save, sender=PBSMMShow) def scrape_PBSMMAPI(sender, instance, **kwargs): if instance.__class__ is not PBSMMShow: return # If this is a new record, then someone has started it in the Admin using # a PBSMM UUID. Depending on which, the retrieval endpoint is slightly different, so this sets # the appropriate URL to access. if instance.pk and instance.slug and str(instance.slug).strip(): # Object is being edited if not instance.ingest_on_save: return # do nothing - can't get an ID to look up! else: # object is being added if not instance.slug: return # do nothing - can't get an ID to look up! url = "{}{}/".format(PBSMM_SHOW_ENDPOINT, instance.slug) # OK - get the record from the API (status, json) = get_PBSMM_record(url) instance.last_api_status = status # Update this record's time stamp (the API has its own) instance.date_last_api_update = time_zone_aware_now() # If we didn't get a record, abort (there's no sense crying over spilled # bits) if status != 200: return # Process the record (code is in ingest.py) instance = process_show_record(json, instance) # continue saving, but turn off the ingest_on_save flag instance.ingest_on_save = False # otherwise we could end up in an infinite loop! # We're done here - continue with the save() operation return @receiver(models.signals.post_save, sender=PBSMMShow) def handle_child_objects(sender, instance, *args, **kwargs): if instance.last_api_status != 200: return this_json = instance.json # ALWAYS GET CHILD ASSETS assets_endpoint = this_json['links'].get('assets') if assets_endpoint: process_show_assets(assets_endpoint, instance) if instance.ingest_seasons: seasons_endpoint = this_json['links'].get('seasons') if seasons_endpoint: process_seasons(seasons_endpoint, instance) if instance.ingest_specials: specials_endpoint = this_json['links'].get('specials') if specials_endpoint: process_specials(specials_endpoint, instance) # This is a tricky way to unset ingest_seasons without calling save() rec = PBSMMShow.objects.filter(pk=instance.id) rec.update(ingest_seasons=False, ingest_specials=False, ingest_episodes=False) return

31.377451

100

0.678488

825

6,401

5.049697

0.294545

0.011522

0.017283

0.011522

0.153385

0.086654

0.073692

0.036006

0.016323

0

0.002037

0.233089

6,401

203

101

31.53202

0.846608

0.204343

0

0.145161

0

0.071586

0

1

0.064516

false

0.008065

0.120968

0.032258

0.379032

0

null

0

null

0

1

0

0f0ef6a186ee50f63722efe4ce641d17f8fe26d8

1,109

py

Python

DeadlockAvoid.py

sid-146/OS_Programs

501b38e9a667590ae5094294dfcd37c0ea851957

[ "MIT" ]

1

2021-12-06T12:06:35.000Z

DeadlockAvoid.py

sid-146/OS_Programs

501b38e9a667590ae5094294dfcd37c0ea851957

[ "MIT" ]

null

DeadlockAvoid.py

sid-146/OS_Programs

501b38e9a667590ae5094294dfcd37c0ea851957

[ "MIT" ]

null

from threading import * import time file = "Sudhanwa Kaveeshwar" s = 1 r = 1 reader_count = 0 def waitc(): global s while s == 0: pass s = 0 def goc(): global s s = 1 def wait_reader(): global r while r == 0: pass r = 0 def go_reader(): global r r = 1 def reader(r): for i in range(3): global reader_count wait_reader() reader_count = reader_count + 1 if reader_count == 1: waitc() go_reader() print("reader {0} reading file : {1} ".format(r, file)) wait_reader() reader_count = reader_count - 1 if reader_count == 0: goc() go_reader() time.sleep(1) def writer(): for i in range(2): global file waitc() file = input("write content in file : ") print("writer writes : ", file) goc() time.sleep(1) writer = Thread(target=writer) reader1 = Thread(target=reader, args=(1,)) reader2 = Thread(target=reader, args=(2,)) reader1.start() reader2.start() writer.start()

14.402597

63

0.536519

146

1,109

3.979452

0.294521

0.151463

0.061962

0.037866

0.158348

0

0.03453

0.34716

1,109

76

64

14.592105

0.767956

0

0.392157

0

0.080252

0

1

0.117647

false

0.039216

0

0.156863

0.039216

0

null

0

null

0

1

0

0f112bc551065f305bd9473b6d2119a4048f2dfe

2,796

py

Python

cka/gram.py

nzw0301/cka

ecc431fcfe273d7a240c9615dc316a80799396d2

[ "Apache-2.0" ]

null

cka/gram.py

nzw0301/cka

ecc431fcfe273d7a240c9615dc316a80799396d2

[ "Apache-2.0" ]

1

2021-11-30T12:42:08.000Z

cka/gram.py

nzw0301/cka

ecc431fcfe273d7a240c9615dc316a80799396d2

[ "Apache-2.0" ]

null

""" The source code comes from https://colab.research.google.com/github/google-research/google-research/blob/master/representation_similarity/Demo.ipynb by Kornblith, Simon and Norouzi, Mohammad and Lee, Honglak and Hinton, Geoffrey. The modifications are as follows: 1. Apply `black` & PyCharm's formatter 2. Rename `center_gram` with `_center_gram` """ import numpy as np def gram_linear(x): """Compute Gram (kernel) matrix for a linear kernel. Args: x: A num_examples x num_features matrix of features. Returns: A num_examples x num_examples Gram matrix of examples. """ return x.dot(x.T) def gram_rbf(x, threshold=1.0): """Compute Gram (kernel) matrix for an RBF kernel. Args: x: A num_examples x num_features matrix of features. threshold: Fraction of median Euclidean distance to use as RBF kernel bandwidth. (This is the heuristic we use in the paper. There are other possible ways to set the bandwidth; we didn't try them.) Returns: A num_examples x num_examples Gram matrix of examples. """ dot_products = x.dot(x.T) sq_norms = np.diag(dot_products) sq_distances = -2 * dot_products + sq_norms[:, None] + sq_norms[None, :] sq_median_distance = np.median(sq_distances) return np.exp(-sq_distances / (2 * threshold ** 2 * sq_median_distance)) def _center_gram(gram, unbiased=False): """Center a symmetric Gram matrix. This is equivalent to centering the (possibly infinite-dimensional) features induced by the kernel before computing the Gram matrix. Args: gram: A num_examples x num_examples symmetric matrix. unbiased: Whether to adjust the Gram matrix in order to compute an unbiased estimate of HSIC. Note that this estimator may be negative. Returns: A symmetric matrix with centered columns and rows. """ if not np.allclose(gram, gram.T): raise ValueError("Input must be a symmetric matrix.") gram = gram.copy() if unbiased: # This formulation of the U-statistic, from Szekely, G. J., & Rizzo, M. # L. (2014). Partial distance correlation with methods for dissimilarities. # The Annals of Statistics, 42(6), 2382-2412, seems to be more numerically # stable than the alternative from Song et al. (2007). n = gram.shape[0] np.fill_diagonal(gram, 0) means = np.sum(gram, 0, dtype=np.float64) / (n - 2) means -= np.sum(means) / (2 * (n - 1)) gram -= means[:, None] gram -= means[None, :] np.fill_diagonal(gram, 0) else: means = np.mean(gram, 0, dtype=np.float64) means -= np.mean(means) / 2 gram -= means[:, None] gram -= means[None, :] return gram

33.686747

121

0.659514

401

2,796

4.516209

0.416459

0.048592

0.033131

0.035892

0.22529

0.154611

0.112645

0

0.018475

0.244993

2,796

82

122

34.097561

0.839413

0.585479

0

0.222222

0

0.03167

0

1

0.111111

false

0

0.037037

0

0.259259

0

null

0

null

0

1

0

0f11ec092d947c7aa54059d8d6ebfb6bd8f528d1

811

py

Python

VB_Classes/PhotoShop_sepia.py

bobdavies2000/OpenCVB

1d339a94643a97e2d34f82dc7776677a8566d71d

[ "MIT" ]

69

2019-07-17T21:20:37.000Z

2022-03-23T08:38:03.000Z

VB_Classes/PhotoShop_sepia.py

bobdavies2000/OpenCVB

1d339a94643a97e2d34f82dc7776677a8566d71d

[ "MIT" ]

5

2021-02-05T05:48:50.000Z

2022-03-12T01:43:15.000Z

VB_Classes/PhotoShop_sepia.py

bobdavies2000/OpenCVB

1d339a94643a97e2d34f82dc7776677a8566d71d

[ "MIT" ]

6

2019-12-24T05:36:52.000Z

2021-02-19T15:55:13.000Z

import cv2 import numpy as np # https://github.com/spmallick/learnopencv/tree/master/ def sepia(img): res = img.copy() res = cv2.cvtColor(res, cv2.COLOR_BGR2RGB) # converting to RGB as sepia matrix is for RGB res = np.array(res, dtype=np.float64) res = cv2.transform(res, np.matrix([[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534, 0.131]])) res[np.where(res > 255)] = 255 # clipping values greater than 255 to 255 res = np.array(res, dtype=np.uint8) res = cv2.cvtColor(res, cv2.COLOR_RGB2BGR) cv2.imshow("original", img) cv2.imshow("Sepia", res) cv2.waitKey(0) cv2.destroyAllWindows() if __name__ == "__main__": img = cv2.imread("../Data/image.jpg") sepia(img)

36.863636

93

0.585697

117

811

3.974359

0.504274

0.077419

0.060215

0.073118

0.193548

0

0.10906

0.265105

811

21

94

38.619048

0.671141

0.17016

0

0.056801

0

1

0.052632

false

0

0.105263

0

0.157895

0

null

0

null

0

1

0

0f1215272d49157aa4f4344e17235518f74e6ff9

15,607

py

Python

plot_cov2ensemble.py

FIDUCEO/FCDR_ST_ensemble

47962346de1db624ee23bfd478fa4f75fb49719a

[ "MIT" ]

null

plot_cov2ensemble.py

FIDUCEO/FCDR_ST_ensemble

47962346de1db624ee23bfd478fa4f75fb49719a

[ "MIT" ]

null

plot_cov2ensemble.py

FIDUCEO/FCDR_ST_ensemble

47962346de1db624ee23bfd478fa4f75fb49719a

[ "MIT" ]

1

2019-08-29T11:23:59.000Z

# !/usr/bin/env python # Code include segment # ======================================== # Version 0.5 # 28 July, 2019 # https://patternizer.github.io/ # michael.taylor AT reading DOT ac DOT uk # ======================================== #--------------------------------------------------------------------------- # PLOT LIST (alphabetical): #--------------------------------------------------------------------------- # plot_crs(): Constrained randing sampling (CRS) demo # plot_eigenspectrum(ev): Eigenspectrum + cumulative relative variance with nPC label # plot_ensemble_closure(da,draws,har): Harmonisation a_cov and a_u versus ensemble-calculated values # plot_ensemble_decile_distribution(Z, decile, npop, nens): Draws with decile per parameter # plot_ensemble_decile_selection(Z_norm, ensemble_idx, nens): Draws with decile selection per parameter # plot_ensemble_deltas(da): Ensemble deltas / parameter uncertainty # plot_ensemble_deltas_an(da,a_u): Ensemble deltas / parameter uncertainty per a(n) # plot_ensemble_deltas_normalised(da,a_u): Ensemble deltas (not normalised) # plot_ensemble_deltas_pc12(da_pc12, a_u): Project ensemble onto PC1 and PC2 # plot_ensemble_diff_BT_scatterplot(BT_ens,BT_mmd): Ensemble BT versus BT_mmd (in 10K bands) # plot_ensemble_diff_BT_timeseries(BT_ens,BT): Ensemble BT minus BT [nens,n] # plot_ensemble_diff_L_timeseries(L_ens,L): Ensemble L minus L [nens,n] # plot_orbit_var(lat, lon, var, vmin, vmax, projection, filestr, titlestr, varstr): Swathe plot of variable with given lat and lon arrays #--------------------------------------------------------------------------- def plot_crs(): ''' Constrained versus unconstrained random sampling demo ''' from ensemble_func import generate_n_single from ensemble_func import generate_n for n in np.array([10,50,100,500,1000,5000,10000,50000]): random_numbers_unconstrained = generate_n_single(n) random_numbers_constrained = generate_n(n) fig,ax = plt.subplots(1,2) labelstr_constrained = 'n=' + str(n) + ': constrained' labelstr_unconstrained = 'n=' + str(n) + ': unconstrained' ax[0].plot(np.sort(np.array(random_numbers_unconstrained)), label=labelstr_unconstrained) ax[0].plot(np.sort(np.array(random_numbers_constrained)), label=labelstr_constrained) ax[0].legend(loc=2, fontsize=8) ax[0].set_ylim(-5,5) ax[0].set_ylabel('z-score') ax[0].set_xlabel('rank') ax[0].set_title(r'Sorted random sample from $erf^{-1}(x)$') ax[1].hist(random_numbers_unconstrained,bins=100,alpha=0.3,label='unconstrained') ax[1].hist(random_numbers_constrained,bins=100,alpha=0.3,label='constrained') ax[1].set_xlim(-5,5) ax[1].set_xlabel('z-score') ax[1].set_ylabel('count') plotstr = 'random_numbers_n_' + str(n) + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_eigenspectrum(ev): ''' Eigenspectrum + cumulative relative variance with nPC label [npar] ''' nPC = ev['nPC'] fig,ax = plt.subplots() plt.plot(ev['eigenvalues_rank'], ev['eigenvalues_norm'], linestyle='-', marker='.', color='b', label=r'$\lambda/sum(lambda)$') plt.plot(ev['eigenvalues_rank'][nPC], ev['eigenvalues_norm'][nPC], marker='o', color='k', mfc='none',label=None) plt.plot(ev['eigenvalues_rank'], ev['eigenvalues_cumsum'], linestyle='-', marker='.', color='r',label='cumulative') labelstr = 'n(PC)='+str(nPC+1)+' var='+"{0:.5f}".format(ev['nPC_variance']) plt.plot(ev['eigenvalues_rank'][nPC], ev['eigenvalues_cumsum'][nPC], marker='o', color='k', mfc='none',label=labelstr) plt.legend(loc='right', fontsize=10) plt.xlabel('rank') plt.ylabel('relative variance') plotstr = 'eigenspectrum' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_closure(da,draws,har): ''' Harmonisation a_cov and a_u versus ensemble-calculated values [npar,npar] & [npar] ''' a_u = np.array(har.parameter_uncertainty) a_cov = np.array(har.parameter_covariance_matrix) da_cov = np.cov(draws.T) # [npar,npar] da_u = np.sqrt(np.diag(da_cov)) # [npar] norm_u = np.linalg.norm(a_u - da_u) norm_cov = np.linalg.norm(a_cov - da_cov) umin = np.min([a_u,da_u]) umax = np.max([a_u,da_u]) covmin = np.min([a_cov,da_cov]) covmax = np.max([a_cov,da_cov]) fig,ax = plt.subplots(2,2) g = sns.heatmap(a_cov - da_cov,ax=ax[0,0]) ax[0,0].set_xlabel('parameter, a(n)') ax[0,0].set_ylabel('parameter, a(n)') ax[0,1].plot(np.arange(1,len(a_u)+1), a_u - da_u,'k.',markersize=10,alpha=0.2) ax[0,1].set_xlabel('parameter, a(n)') ax[0,1].set_ylabel('HAR-MNS: u(n)') ax[1,0].plot(a_cov.ravel(), da_cov.ravel(),'k.',markersize=10,alpha=0.2) ax[1,0].plot([covmin,covmax],[covmin,covmax], '-', color='red') ax[1,0].set_xlabel('HAR: cov(n,n)') ax[1,0].set_ylabel('MNS: cov(n,n)') ax[1,1].plot(a_u, da_u,'k.',markersize=10,alpha=0.2) ax[1,1].plot([umin,umax],[umin,umax], '-', color='red') ax[1,1].set_xlabel('HAR: u(n)') ax[1,1].set_ylabel('MNS: u(n)') plotstr = 'ensemble_closure' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_decile_distribution(Z, decile, npop, nens): ''' Draws with decile per parameter ''' npar = decile.shape[1] if npop > 10000: krange = np.linspace(0,npop-1,10000).astype('int') else: krange = range(npop) fig,ax = plt.subplots() for k in krange: plt.plot(np.arange(1,npar+1),Z[k,:],'.',alpha=0.2) for i in range(nens): plt.plot(np.arange(1,npar+1),decile[i,:],'-',alpha=1.0,label='decile('+\ str(i+1)+')') plt.ylim(-5,5) plt.xlabel('harmonisation parameter') plt.ylabel('multinormal draw z-score') plt.legend(loc=2,fontsize=8, ncol=5) plotstr = 'ensemble_decile_distribution' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_decile_selection(Z_norm, ensemble_idx, nens): ''' Draws with decile selection per parameter ''' fig,ax = plt.subplots() for k in range(nens): labelstr = 'decile('+str(k+1)+')' plt.plot(Z_norm[k,:],label=labelstr) plt.plot(ensemble_idx[k],Z_norm[k,ensemble_idx[k]],marker='o',color='k'\ ,mfc='none',label=None) plt.ylim(0,25) plt.xlabel('multinormal draw') plt.ylabel(r'norm distance of multinormal draw from $k^{th}$ decile') plt.legend(loc=2,fontsize=8, ncol=5) plotstr = 'ensemble_decile_selection.png' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_deltas(da): ''' Ensemble deltas (not normalised) [nens,npar] ''' n = int(da.shape[0]/2) npar = da.shape[1] fig,ax = plt.subplots() for i in range(2*n): labelstr_c = 'ens(' + str(i+1) + ')' plt.plot(np.arange(1,npar+1), da[i,:], lw=2, label=labelstr_c) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.ylim(-0.0020,0.0020) plt.xlabel('parameter, a(n)') plt.ylabel(r'$\delta a(n)$') plotstr = 'npc_deltas' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_deltas_an(da, a_u): ''' Ensemble deltas / parameter uncertainty by parameter a(n) [nens,nsensor] ''' n = int(da.shape[0]/2) nensemble = da.shape[0] nparameters = da.shape[1] if nparameters > 27: for i in range(4): fig,ax = plt.subplots() idx = np.arange(i,nparameters-1,4) # -1 --> MTA:N12 (excl N11) for k in range(len(idx)-1): for l in range(nensemble): labelstr = 'ens('+str(l+1)+')' if k == 0: plt.plot(k, da[l,idx[k]] / a_u[idx[k]],'.',label=labelstr) else: plt.plot(k, da[l,idx[k]] / a_u[idx[k]],'.',label=None) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.ylim(-5,5) plt.ylabel(r'$\delta a(n)/u(n)$') plt.xlabel('sensor') plotstr = 'ensemble_a' + str(i) + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') else: for i in range(3): fig,ax = plt.subplots() idx = np.arange(i,nparameters-1,3) # -1 --> MTA:N12 (excl N11) for k in range(len(idx)-1): for l in range(nensemble): labelstr = 'ens('+str(l+1)+')' if k == 0: plt.plot(k, da[l, idx[k]] / a_u[idx[k]],'.',label=labelstr) else: plt.plot(k, da[l, idx[k]] / a_u[idx[k]],'.',label=None) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.ylim(-5,5) plt.ylabel(r'$\delta a(n)/u(n)$') plt.xlabel('sensor') plotstr = 'ensemble_a' + str(i) + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_deltas_normalised(da, a_u): ''' Ensemble deltas / parameter uncertainty [nens,npar] ''' n = int(da.shape[0]/2) npar = da.shape[1] fig,ax = plt.subplots() for i in range(2*n): labelstr_c = 'ens(' + str(i+1) + ')' plt.plot(np.arange(1,npar+1), da[i,:] / a_u, lw=2, label=labelstr_c) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.ylim(-5,5) plt.xlabel('parameter, a(n)') plt.ylabel(r'$\delta a(n)/u(n)$') plotstr = 'npc_deltas_over_Xu' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_deltas_pc12(da_pc12, a_u): ''' Project ensemble onto PC1 and PC2 ''' n = int(da_pc12['da_pc1'].shape[0]/2) fig,ax = plt.subplots() for i in range(2*n): labelstr = 'PC1: ens(' + str(i+1) + ')' plt.plot(da_pc12['da_pc1'][i,:] / a_u, lw=2, label=labelstr) if n <= 5: plt.legend(loc=2, fontsize=6, ncol=2) plt.xlim(-5,5) plt.ylim(-5,5) plt.xlabel('parameter, a(n)') plt.ylabel(r'$\delta a(n)/u(n)$') plotstr = 'pc1_deltas_over_Xu' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') fig,ax = plt.subplots() for i in range(2*n): labelstr = 'PC1: ens(' + str(i+1) + ')' plt.plot(da_pc12['da_pc1'][i,:] / a_u, lw=2, label=labelstr) if n <= 5: plt.legend(loc=2, fontsize=6, ncol=2) plt.xlim(-5,5) plt.ylim(-5,5) plt.xlabel('parameter, a(n)') plt.ylabel(r'$\delta a(n)/u(n)$') plotstr = 'pc2_deltas_over_Xu' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_diff_BT_scatterplot(BT_ens,BT_mmd): ''' Ensemble BT versus BT_mmd (in 10K bands) [nens,n_mmd] ''' n = int(BT_ens.shape[1]/2) fig,ax = plt.subplots() for i in range(2*n): labelstr = 'ens(' + str(i+1) + ')' gd = BT_ens[:,i] > 0 plt.plot(BT_mmd[gd], BT_ens[gd,i], '.', markersize=2, alpha=0.2, label=labelstr) plt.plot([220,310],[220,310], '--', color='black', label=None) plt.xlim(220,310) plt.ylim(220,310) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.xlabel(r'brightness temperature, BT / $K$') plt.ylabel(r'ensemble brightness temperature, ens(BT) / $K$') plotstr = 'bt_deltas' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') BT_vec = np.arange(230,310,10) for k in range(len(BT_vec)-1): fig,ax = plt.subplots() for i in range(2*n): labelstr = 'ens(' + str(i+1) + ')' domain = (BT_mmd >= BT_vec[k]) & (BT_mmd < BT_vec[k+1]) gd = (BT_ens[:,i] > 0) & domain plt.plot(BT_mmd[gd],BT_ens[gd,i], '.', markersize=2, alpha=0.2, label=labelstr) plt.plot([BT_vec[k],BT_vec[k+1]],[BT_vec[k],BT_vec[k+1]], '--', color='black', label=None) plt.xlim(BT_vec[k],BT_vec[k+1]) plt.ylim(BT_vec[k],BT_vec[k+1]) if n <= 5: plt.legend(loc=2, fontsize=8, ncol=5) plt.xlabel(r'brightness temperature, BT / $K$') plt.ylabel(r'ensemble brightness temperature, ens(BT) / $K$') plotstr = 'bt_deltas' + '_' + str(BT_vec[k]) + '_' + str(BT_vec[k+1]) + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_diff_BT_timeseries(BT_ens,BT): ''' Ensemble BT minus BT [nens,n] ''' n = int(BT_ens.shape[1]/2) fig, ax = plt.subplots() for k in range(2*n): label_str = 'Ens(' + str(k+1) + ')' plt.plot(BT_ens[:,k] - BT, linewidth=1.0, label=label_str) plt.legend(fontsize=10, ncol=1) ax.set_ylabel('BT difference / K', fontsize=12) plotstr = 'bt_deltas' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_ensemble_diff_L_timeseries(L_ens,L): ''' Ensemble L versus L [nens,n] ''' n = int(L_ens.shape[1]/2) fig, ax = plt.subplots() for k in range(2*n): label_str = 'Ens(' + str(k+1) + ')' plt.plot(L_ens[:,k] - L, linewidth=1.0, label=label_str) plt.legend(fontsize=10, ncol=1) ax.set_ylabel('Radiance difference', fontsize=12) plotstr = 'l_deltas' + plotstem plt.tight_layout() plt.savefig(plotstr) plt.close('all') def plot_orbit_var(lat, lon, var, vmin, vmax, projection, filestr, titlestr, varstr): ''' Swathe plot of variable with given lat and lon arrays ''' x = lon[::10,::10] y = lat[::10,::10] z = var[::10,::10] cmap = 'viridis' fig = plt.figure() if projection == 'platecarree': p = ccrs.PlateCarree(central_longitude=0) threshold = 0 if projection == 'mollweide': p = ccrs.Mollweide(central_longitude=0) threshold = 1e6 if projection == 'robinson': p = ccrs.Robinson(central_longitude=0) threshold = 0 ax = plt.axes(projection=p) ax.coastlines() g = ccrs.Geodetic() # trans = ax.projection.transform_points(g, x.values, y.values) trans = ax.projection.transform_points(g, x, y) x0 = trans[:,:,0] x1 = trans[:,:,1] if projection == 'platecarree': ax.set_extent([-180, 180, -90, 90], crs=p) gl = ax.gridlines(crs=p, draw_labels=True, linewidth=1, color='gray', alpha=0.5, linestyle='-') gl.xlabels_top = False gl.ylabels_right = False gl.xlines = True gl.ylines = True gl.xlocator = mticker.FixedLocator([-180,-120,-60,0,60,120,180]) gl.ylocator = mticker.FixedLocator([-90,-60,-30,0,30,60,90]) gl.xformatter = LONGITUDE_FORMATTER gl.yformatter = LATITUDE_FORMATTER # im = ax.pcolor(x, y, z, transform=ax.projection, cmap=cmap) for mask in (x0>threshold,x0<=threshold): im = ax.pcolor(ma.masked_where(mask, x), ma.masked_where(mask, y), ma.masked_where(mask, z), vmin=vmin, vmax=vmax, transform=ax.projection, cmap='seismic') else: for mask in (x0>threshold,x0<=threshold): im = ax.pcolor(ma.masked_where(mask, x0), ma.masked_where(mask, x1), ma.masked_where(mask, z), vmin=vmin, vmax=vmax, transform=ax.projection, cmap='seismic') cb = plt.colorbar(im, orientation="horizontal", extend='both', label=varstr) plt.title(titlestr) plt.savefig(filestr) plt.close('all')

37.426859

169

0.589095

2,316

15,607

3.845423

0.130397

0.00494

0.019762

0.026948

0.658657

0.638783

0.608691

0.572423

0.554233

0.538738

0

0.035726

0.221631

15,607

416

170

37.516827

0.697399

0.155123

0

0.498403

0

0.110657

0.006019

0.00639

0

1

0.041534

false

0

0.00639

0

0.047923

0

null

0

null

0

1

0

0f12a05f3d5e3cccdbc328f63c0a7e69fb06f09c

3,422

py

Python

Day28-Pomodoro_GUI_App/main.py

the-whiz84/Python_Projects

35d6c3cef9b4d90e6cb7cbf1dd88de3a7fe5dd0c

[ "MIT" ]

1

2022-01-05T10:54:06.000Z

Day28-Pomodoro_GUI_App/main.py

the-whiz84/Python_Projects

35d6c3cef9b4d90e6cb7cbf1dd88de3a7fe5dd0c

[ "MIT" ]

null

Day28-Pomodoro_GUI_App/main.py

the-whiz84/Python_Projects

35d6c3cef9b4d90e6cb7cbf1dd88de3a7fe5dd0c

[ "MIT" ]

null

import math from tkinter import * PINK = "#e2979c" RED = "#e7305b" GREEN = "#019267" YELLOW = "#F2FA5A" FONT_NAME = "Courier" WORK_MIN = 50 SHORT_BREAK_MIN = 10 LONG_BREAK_MIN = 30 reps = 0 timer = None def count_down(count): """Create the countdown mechanism inside the canvas. Counts down by each second for the given interval (work, short break or long break). Adds a checkmark for each working interval completed. Args: count (int): Number of minutes to countdown from based on the Constants set. """ count_min = math.floor(count / 60) count_sec = count % 60 if count_sec < 10: count_sec = f"0{count_sec}" if count_min < 10: count_min = f"0{count_min}" canvas.itemconfig(timer_text, text=f"{count_min}:{count_sec}") if count > 0: global timer timer = window.after(1000, count_down, count - 1) else: start_timer() marks = "" work_sessions = math.floor(reps / 2) for _ in range(work_sessions): marks += "✔" checkmark_label.config(text=marks) def start_timer(): """Add the Start Button functionality to start the countdown. Changes the countdown timer between Work interval and Break. Updates the Title label to show which interval is currently on. """ global reps reps += 1 work_sec = WORK_MIN * 60 short_break_sec = SHORT_BREAK_MIN * 60 long_break_sec = LONG_BREAK_MIN * 60 if reps % 8 == 0: title_label.config(text="Break", fg=RED) count_down(long_break_sec) focus_window("on") elif reps % 2 == 0: title_label.config(text="Break", fg=PINK) count_down(short_break_sec) focus_window("on") else: title_label.config(text="Work", fg=GREEN) count_down(work_sec) focus_window("off") def reset_timer(): """Add the Reset Button functionality to reset the countdown and all the text on the GUI. """ global reps reps = 0 window.after_cancel(timer) title_label.config(text="Timer") canvas.itemconfig(timer_text, text="00:00") checkmark_label.config(text="") def focus_window(option): """Enable the Tkinter window to show on top of other windows when minimized. Args: option (str): Set the function to 'on' or 'off' """ if option == "on": window.deiconify() window.focus_force() window.attributes('-topmost', 1) elif option == "off": window.attributes('-topmost', 0) window = Tk() window.title("Pomodoro") window.config(padx=100, pady=50, bg=YELLOW) canvas = Canvas(width=200, height=224, bg=YELLOW, highlightthickness=0) tomato_img = PhotoImage(file="./tomato.png") canvas.create_image(100, 112, image=tomato_img) timer_text = canvas.create_text(100, 130, text="00:00", fill="white", font=(FONT_NAME, 28, "bold")) canvas.grid(column=1, row=1) title_label = Label(text="Timer", fg=GREEN, bg=YELLOW, font=(FONT_NAME, 36, "normal")) title_label.grid(column=1, row=0) start_button = Button(text="Start", font=(FONT_NAME, 16, "normal"), highlightthickness=0, command=start_timer) start_button.grid(column=0, row=2) reset_button = Button(text="Reset", font=(FONT_NAME, 16, "normal"), highlightthickness=0, command=reset_timer) reset_button.grid(column=2, row=2) checkmark_label = Label(fg=GREEN, bg=YELLOW) checkmark_label.grid(column=1, row=3) window.mainloop()

30.553571

110

0.6654

492

3,422

4.477642

0.300813

0.031775

0.040853

0.036314

0.129823

0.067181

0.041761

0

0.039318

0.212157

3,422

111

30.828829

0.777448

0.200175

0

0.101266

0

0.075797

0.00863

0

1

0.050633

false

0

0.025316

0

0.075949

0

null

0

null

0

1

0

0f1339e6f6813e3cd55c4c862dfb0e92d7b3f4a9

1,938

py

Python

src/sentry/utils/pubsub.py

AlexWayfer/sentry

ef935cda2b2e960bd602fda590540882d1b0712d

[ "BSD-3-Clause" ]

1

2022-02-09T22:56:49.000Z

src/sentry/utils/pubsub.py

AlexWayfer/sentry

ef935cda2b2e960bd602fda590540882d1b0712d

[ "BSD-3-Clause" ]

6

2018-10-19T10:04:23.000Z

2019-12-09T20:29:12.000Z

src/sentry/utils/pubsub.py

AlexWayfer/sentry

ef935cda2b2e960bd602fda590540882d1b0712d

[ "BSD-3-Clause" ]

1

2020-07-03T00:52:19.000Z

from __future__ import absolute_import import redis import logging import random from django.conf import settings from threading import Thread from six.moves.queue import Queue, Full class QueuedPublisher(object): """ A publisher that queues items locally and publishes them to a remote pubsub service on a background thread. Maintains a lossy internal queue for posting, will discard the value if the queue is full or not immediately available. Will also drop items if the publish operation to the remote service fails. """ def __init__(self, publisher): self._started = False self.publisher = publisher def _start(self): if self._started: return True self.q = q = Queue(maxsize=100) def worker(): while True: (channel, key, value) = q.get() try: self.publisher.publish(channel, key=key, value=value) except Exception: logger = logging.getLogger('sentry.errors') logger.debug('could not submit event to pubsub') finally: q.task_done() t = Thread(target=worker) t.setDaemon(True) t.start() self._started = True return True def publish(self, channel, value, key=None): if not self._start(): return sample_channel = getattr(settings, 'PUBSUB_SAMPLING', 1.0) if random.random() <= sample_channel: try: self.q.put((channel, key, value), block=False) except Full: return class RedisPublisher(object): def __init__(self, connection): self.rds = None if connection is None else redis.StrictRedis(**connection) def publish(self, channel, value, key=None): if self.rds is not None: self.rds.publish(channel, value)

28.086957

82

0.603199

229

1,938

5.008734

0.436681

0.034002

0.01918

0.036617

0.061029

0

0.003788

0.318885

1,938

68

83

28.5

0.865152

0.156347

0

0.177778

0

0.03743

0

1

0.133333

false

0

0.155556

0

0.422222

0

null

0

null

0

1

0

0f147f9d332c127c0660526475168efc319163b9

960

py

Python

modules/Utils.py

tum-msv/mimo-cnn-est

8915a918c08c5ae61dc2208352ebb9676395b3c8

[ "Unlicense" ]

2

2021-04-28T17:33:07.000Z

2021-09-22T19:35:05.000Z

modules/Utils.py

tum-msv/mimo-cnn-est

8915a918c08c5ae61dc2208352ebb9676395b3c8

[ "Unlicense" ]

null

modules/Utils.py

tum-msv/mimo-cnn-est

8915a918c08c5ae61dc2208352ebb9676395b3c8

[ "Unlicense" ]

null

import time from functools import wraps import numpy as np def crandn(*arg, rng=np.random.random.__self__): #np.random.seed() return np.sqrt(0.5) * (rng.randn(*arg) + 1j * rng.randn(*arg)) def timethis(func): """A decorator that prints the execution time. Example: Write @utils.timethis before a function definition: @utils.timthis def my_function(): pass Then, every time my_function is called, the execution time is printed. """ @wraps(func) def wrapper(*args, **kwargs): tic = time.time() result = func(*args, **kwargs) toc = time.time() # hours h = (toc - tic) // (60 * 60) s = (toc - tic) % (60 * 60) print( 'elapsed time of {}(): ' '{:.0f} hour(s) | {:.0f} minute(s) | {:.5f} second(s).' .format(func.__name__, h, s // 60, s % 60) ) return result return wrapper

24.615385

78

0.536458

121

960

4.173554

0.520661

0.031683

0.043564

0.039604

0

0.027565

0.319792

960

38

79

25.263158

0.745789

0.275

0

0.05

0.113636

0

1

0.15

false

0

0.15

0.05

0.45

0.05

0

null

0

null

0

1

0

0f14c81c5a0498d1d6e6cfa782b064dc1e2a8d46

2,993

py

Python

wordlistgen.py

akumanatt/2600-wordle

5f8d0f76a2db2c06ee59a42106ea3593e735641f

[ "MIT" ]

1

2022-03-13T22:13:41.000Z

wordlistgen.py

akumanatt/2600-wordle

5f8d0f76a2db2c06ee59a42106ea3593e735641f

[ "MIT" ]

null

wordlistgen.py

akumanatt/2600-wordle

5f8d0f76a2db2c06ee59a42106ea3593e735641f

[ "MIT" ]

null

# usage: wordlistgen.py [words.txt] [answers.txt] [wordlist.asm] # words.txt should be sorted by word frequency # since later entries can be removed if there's not enough space import sys ATOZ = "abcdefghijklmnopqrstuvwxyz" BANK_FREES =[0xa3c, 0xfe4, 0xfe4] NUM_BANKS = len(BANK_FREES) fulllist = [i.strip().lower() for i in open(sys.argv[1], "r")] anslist = [i.strip().lower() for i in open(sys.argv[2], "r")] outfile = open(sys.argv[3], "w") output_asm = """ ; generated by wordlistgen.py """ section_format = """ .section wordlist_data_{0} {1} .send """ section_1_format = """ _ptrs := ({0}) wordlist_1_ptrs_lo .byte <(_ptrs) wordlist_1_ptrs_hi .byte >(_ptrs) wordlist_2_ofs """ sizes = None banks = None bins = {} remaining = [] for i in ATOZ: for j in ATOZ: bins[i+j] = [] # first iteration: fit banks for word in fulllist: key = word[:2] bins[key].append(word) # try fitting try_sizes = [0 for i in range(NUM_BANKS)] try_banks = [[] for i in range(NUM_BANKS)] cur_bank = 0 exit = False for i in ATOZ: group_size = sum([len(bins[i+j]) for j in ATOZ]) while (try_sizes[cur_bank] + group_size) > (BANK_FREES[cur_bank] // 2): cur_bank += 1 if cur_bank >= NUM_BANKS: exit = True break if exit: break try_sizes[cur_bank] += group_size try_banks[cur_bank].append(i) if exit: remaining.append(word) bins[key].remove(word) else: sizes = try_sizes banks = try_banks # second iteration: fill gaps for word in remaining: for i in range(NUM_BANKS): if word[0] not in banks[i]: continue if (sizes[i] + 2) <= (BANK_FREES[i] // 2): print(word) bins[word[:2]].append(word) sizes[i] += 2 print(sum([len(bins[i]) for i in bins])) # write results for i in range(NUM_BANKS): stxt = "" if i == 0: stxt += section_1_format.format(", ".join(["wordlist_3_"+i for i in ATOZ])) for j in ATOZ: stxt += " .byte {}\n".format(", ".join(["{:3}".format(len(bins[j+k])*2) for k in ATOZ])) stxt += "\n" for j in banks[i]: stxt += "wordlist_3_"+j linectr = 0 for k in ATOZ: # reverse the list to aid searching, since the game checks from the last member first for word in bins[j+k][::-1]: if linectr % 16 == 0: stxt += "\n .word " else: stxt += ", " c2 = (ord(word[2]) - ord("a") + 1) c3 = (ord(word[3]) - ord("a") + 1) c4 = (ord(word[4]) - ord("a") + 1) il = 0x8000 if word in anslist else 0 stxt += "${:04x}".format(c2 | (c3 << 5) | (c4 << 10) | il) linectr += 1 stxt += "\n" output_asm += section_format.format(i + 1, stxt) outfile.write(output_asm)

27.458716

103

0.537254

428

2,993

3.633178

0.285047

0.025723

0.038585

0.028296

0.141479

0.061736

0.036013

0

0.030303

0.316405

2,993

108

104

27.712963

0.729717

0.111928

0

0.197674

0

0.107588

0.009815

0

0.007928

0

1

0

false

0

0.011628

0

0.011628

0.023256

0

null

0

null

0

1

0

0f14f700cd145b96aa86b15d1a9499221f0c3690

519

py

Python

examples/exampleXeFF.py

ogorton/dmfortfactor

879e747a3c839687a729091f811282fdb9264869

[ "MIT" ]

1

2022-02-28T20:58:51.000Z

examples/exampleXeFF.py

ogorton/dmfortfactor

879e747a3c839687a729091f811282fdb9264869

[ "MIT" ]

1

2022-01-24T20:35:32.000Z

2022-02-28T21:51:53.000Z

examples/exampleXeFF.py

ogorton/dmfortfactor

879e747a3c839687a729091f811282fdb9264869

[ "MIT" ]

null

import sys sys.path.append("../python") import dmfortfactor as dm import numpy as np import matplotlib.pyplot as plt import random cwords = { "wimpmass" : 150.0, "usemomentum": 1} Wfunc = dm.NucFormFactor( Z = 54, N = 77, dres = "../data/Xe/xe131gcn", controlwords = cwords, epmin = 0.001, epmax = 10.0, epstep = 0.001, exec_path='../bin/dmfortfactor') q = 0.001 print("q = %10.5f"%q) print("W_i^{tau,tau_prime}(q) = ") print(Wfunc(q))

19.961538

40

0.568401

71

519

4.112676

0.633803

0.041096

0

0.079787

0.27553

519

25

41

20.76

0.696809

0

0.194605

0.042389

0

1

0

false

0

0.227273

0

0.227273

0.136364

0

null

0

null

0

1

0

0f17142a4a1c75960aa84eea1a7efd1b0957036a

2,166

py

Python

texapi/settings/local.py

blumug/texapi

3caf1dd3f0c641a06964a33f7d3046bdace24eeb

[ "MIT" ]

null

texapi/settings/local.py

blumug/texapi

3caf1dd3f0c641a06964a33f7d3046bdace24eeb

[ "MIT" ]

null

texapi/settings/local.py

blumug/texapi

3caf1dd3f0c641a06964a33f7d3046bdace24eeb

[ "MIT" ]

null

"""Development settings and globals.""" from os.path import join, normpath from base import * ########## DEBUG CONFIGURATION # See: https://docs.djangoproject.com/en/dev/ref/settings/#debug DEBUG = True # See: https://docs.djangoproject.com/en/dev/ref/settings/#template-debug TEMPLATE_DEBUG = DEBUG LOCAL_MODE = True ########## END DEBUG CONFIGURATION ########## EMAIL CONFIGURATION # See: https://docs.djangoproject.com/en/dev/ref/settings/#email-backend EMAIL_BACKEND = 'django.core.mail.backends.smtp.EmailBackend' EMAIL_HOST = 'mailtrap.io' EMAIL_HOST_USER = '4537fd1a8eca5802' EMAIL_HOST_PASSWORD = '0dfa077b609a5a' EMAIL_PORT = '2525' EMAIL_USE_TLS = True ########## END EMAIL CONFIGURATION ########## DATABASE CONFIGURATION # See: https://docs.djangoproject.com/en/dev/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'texapi', 'USER': '', 'PASSWORD': '', 'HOST': '', 'PORT': '', 'ATOMIC_REQUESTS': True, } } ########## END DATABASE CONFIGURATION # ########## CACHE CONFIGURATION # See: https://docs.djangoproject.com/en/dev/ref/settings/#caches CACHES = { 'default': { 'BACKEND': 'django.core.cache.backends.dummy.DummyCache', } } #Activate this cache if you want to use rosetta # CACHES = { # 'default': { # 'BACKEND': 'django.core.cache.backends.locmem.LocMemCache', # 'LOCATION': 'texapi' # } # } ########## END CACHE CONFIGURATION ########## TOOLBAR CONFIGURATION # See: http://django-debug-toolbar.readthedocs.org/en/latest/installation.html#explicit-setup INSTALLED_APPS += ( 'debug_toolbar', ) MIDDLEWARE_CLASSES += ( 'debug_toolbar.middleware.DebugToolbarMiddleware', ) DEBUG_TOOLBAR_PATCH_SETTINGS = False # http://django-debug-toolbar.readthedocs.org/en/latest/installation.html INTERNAL_IPS = ('127.0.0.1', '0.0.0.0', '::1') def custom_show_toolbar(self): return False # True DEBUG_TOOLBAR_CONFIG = { 'SHOW_TOOLBAR_CALLBACK': 'texapi.settings.local.custom_show_toolbar', } ########## END TOOLBAR CONFIGURATION HOST='http://localhost:8009'

23.543478

93

0.668513

244

2,166

5.815574

0.409836

0.05074

0.042283

0.08809

0.336857

0.276251

0.245243

0

0.020675

0.151431

2,166

91

94

23.802198

0.75136

0.435365

0

0.04878

0

0.367701

0.212591

0

1

0.02439

false

0.04878

0.02439

0.097561

0

null

0

null

0

1

0

0f173212856013758f53735b264f6510bc98fc61

658

py

Python

try_json.py

victorai60/Spider

e4f50186a382fa507ca8398af10ca81fb06ddb4a

[ "Apache-2.0" ]

null

try_json.py

victorai60/Spider

e4f50186a382fa507ca8398af10ca81fb06ddb4a

[ "Apache-2.0" ]

null

try_json.py

victorai60/Spider

e4f50186a382fa507ca8398af10ca81fb06ddb4a

[ "Apache-2.0" ]

null

import requests import json url = "https://m.douban.com/rexxar/api/v2/subject_collection/filter_tv_american_hot/items?os=ios&for_mobile=1&start=0&count=18&loc_id=108288&_=0" headers = { "User-Agent": "User-Agent: Mozilla/5.0 (iPhone; CPU iPhone OS 11_0 like Mac OS X) AppleWebKit/604.1.38 (KHTML, like Gecko) Version/11.0 Mobile/15A372 Safari/604.1", "Referer": "https://m.douban.com/tv/american" } response = requests.get(url, headers=headers) json_str = response.content.decode() dict_ret = json.loads(json_str) print(dict_ret) with open("douban.json", "w", encoding="utf-8") as f: f.write(json.dumps(dict_ret, ensure_ascii=False, indent=2))

41.125

168

0.737082

113

658

4.168142

0.654867

0.044586

0.050955

0.063694

0

0.0625

0.100304

658

15

169

43.866667

0.733108

0

0.153846

0.532725

0

1

0

false

0

0.153846

0

0.153846

0.076923

0

null

0

null

0

1

0

0f196729e7a123d28ff556fb7d1a262f4235c43f

715

py

Python

src/models/network.py

schalappe/kenyan_sign_language_classification

a578e55c96e8eced1d23d31bb2019f8be308c899

[ "MIT" ]

null

src/models/network.py

schalappe/kenyan_sign_language_classification

a578e55c96e8eced1d23d31bb2019f8be308c899

[ "MIT" ]

null

src/models/network.py

schalappe/kenyan_sign_language_classification

a578e55c96e8eced1d23d31bb2019f8be308c899

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Set of class for fine tune """ import tensorflow as tf from .addons import models from .head_net import NormHeadNetV2 class FineTuneModel: @staticmethod def build(model_name: str, dims: tuple, num_class: int, hidden_unit): # load reference model head = models[model_name]( input_shape=dims, include_top=False, weights="imagenet", ) # Freeze the pretrained weights head.trainable = False # Add top to reference model outputs = NormHeadNetV2.build( base_model=head, len_class=num_class, dense_unit=hidden_unit ) return tf.keras.Model(head.input, outputs)

23.833333

73

0.627972

85

715

5.141176

0.623529

0.061785

0

0.005882

0.286713

715

29

74

24.655172

0.85098

0.177622

0

0.013865

0

1

0.0625

false

0

0.1875

0

0.375

0

null

0

null

0

1

0

0f1a874facaa326df6344fbfb3ea914616f645d8

7,789

py

Python

scraper/ssb_base.py

VolVox99/OpenCourseAPI

edfe51c8ee050ad0bf99c03f5ed421ce247cc01f

[ "MIT" ]

9

2020-10-02T00:10:46.000Z

2022-01-06T00:48:59.000Z

scraper/ssb_base.py

VolVox99/OpenCourseAPI

edfe51c8ee050ad0bf99c03f5ed421ce247cc01f

[ "MIT" ]

8

2020-09-06T22:13:36.000Z

2020-12-15T20:37:17.000Z

scraper/ssb_base.py

VolVox99/OpenCourseAPI

edfe51c8ee050ad0bf99c03f5ed421ce247cc01f

[ "MIT" ]

4

2020-09-08T02:26:56.000Z

2022-03-11T20:43:55.000Z

from os import makedirs from os.path import join, exists from collections import defaultdict from datetime import datetime import requests from bs4 import BeautifulSoup from tinydb import TinyDB from marshmallow import ValidationError as MarshValidationError from logger import log, log_info, log_err, log_trace from data.models import classDataSchema, classTimeSchema SOUP_PARSER = 'lxml' class BaseHooks: DATE_FORMAT = '%b %d, %Y' # '%d-%b-%Y' @staticmethod def transform_depts(depts): return depts @staticmethod def transform_class(class_data): return class_data @classmethod def parse_date(cls, date_str): return datetime.strftime(datetime.strptime(date_str, cls.DATE_FORMAT), '%m/%d/%Y') @staticmethod def clean_units_str(units_str): if 'TO' in units_str: splitted = units_str.split('TO') return splitted[-1].strip() elif 'OR' in units_str: splitted = units_str.split('OR') return splitted[-1].strip() else: return units_str class BaseSSBScraper: PREFIX = '' def __init__(self, ssb_url, db_dir, cache_dir, hooks=None, login=None, ssb_campus=None, max_terms=-1, start_term=None, use_cache=True, trace=False): self.ssb_url = ssb_url self.db_dir = db_dir self.cache_dir = cache_dir self.login = login self.ssb_campus = ssb_campus self.hooks = hooks or BaseHooks self.max_terms = max_terms self.start_term = start_term self.use_cache = use_cache self.trace = trace self.loggedIn = False self.session = requests.session() def run(self): # Create db dir (ex. 'db/') and cache dir (ex. 'db/.cache/scrape_advanced') for folder in [self.db_dir, self.cache_dir]: if not exists(folder): makedirs(folder, exist_ok=True) # Get all term codes (hits FHDA endpoint) codes = self.mine_term_codes() # Debug utilities to limit the terms mined if self.start_term and codes.index(self.start_term): codes = codes[codes.index(self.start_term):] if self.max_terms > 0 and len(codes) > self.max_terms: codes = codes[:self.max_terms] log_info(f'Loaded {len(codes)} term codes') for term in codes: # Mine department data # Hits FHDA endpoint to get all departments for the term log(term, 'magenta', 'Mining departments... ', end='\r') depts = self.mine_dept_data(term) # Mine and process class data # Hits FHDA endpoint to get all classes for the term log(term, 'magenta', 'Mining classes... ', end='\r') classes = self.mine_campus_term(term, depts) # Create / load a DB for the term log(term, 'magenta', 'Writing data to db... ', end='\r') campus_prefix = f'{self.ssb_campus.lower()}_' if self.ssb_campus else '' db = TinyDB(join(self.db_dir, f'{self.PREFIX}{campus_prefix}{term}_database.json')) with db: # Write the dept and class data to the DB self.save_classes(db, depts, classes) # Get counts of mined data (for logging) dept_count = len(db.table('departments')) course_count = len(db.table('courses')) class_count = len(db.table('classes')) # that's it! move on to the next term code... info = f'Mined {dept_count} depts, {course_count} courses, and {class_count} classes' log(term, 'magenta', f'{info} ') def mine_term_codes(self): ''' Mine term codes will grab all the term IDs. :param use_cache: (bool) whether to use the cache :return data: (list) list of term codes ''' html = self.fetch_and_cache( 'bwckschd.p_disp_dyn_sched', 'all-terms.html', ) soup = BeautifulSoup(html, SOUP_PARSER) term_select = soup.find('select', {'name': 'p_term'}) options = term_select.find_all('option') return [opt['value'] for opt in options if opt['value']] def mine_dept_data(self, term: str): ''' Mine dept data will grab the department IDs for a given quarter. :param term: (str) the term to mine :param use_cache: (bool) whether to use the cache :return data (list(tuple)) the html body ''' data = [('p_calling_proc', 'bwckschd.p_disp_dyn_sched'), ('p_term', term)] html = self.fetch_and_cache( 'bwckgens.p_proc_term_date', f'{term}-depts.html', data=data, ) soup = BeautifulSoup(html, SOUP_PARSER) dept_select = soup.find('select', {'id': 'subj_id'}) options = dept_select.find_all('option') depts = {} for option in options: dept_id = option['value'] if dept_id: depts[dept_id] = option.get_text().strip() or '' return self.hooks.transform_depts(depts) def save_classes(self, db, depts, classes): db_depts = [] db_courses = [] db_classes = [] depts = {k.replace(' ', ''): v for k, v in depts.items()} for dept, t in classes.items(): db_depts.append({ 'id': dept, 'name': depts[dept], }) for course, section in t.items(): course_classes = [] course_titles = set() for cl in section.values(): try: data = classDataSchema.load(cl) classTimes = [classTimeSchema.load(time) for time in cl['times']] except MarshValidationError as e: print(e, cl) continue data['times'] = classTimes db_classes.append(data) course_titles.add(data['title']) course_classes.append(data['CRN']) if len(course_titles) > 1: log_err(f'Multiple course titles for "{dept} {course}" {str(course_titles)}') db_courses.append({ 'dept': dept, 'course': course, 'title': course_titles.pop(), 'classes': course_classes }) db.drop_tables() db.table('departments').insert_multiple(db_depts) db.table('courses').insert_multiple(db_courses) db.table('classes').insert_multiple(db_classes) def fetch_and_cache(self, url: str, filename: str, authenticated=False, data=None): full_filename = join(self.cache_dir, filename) if self.use_cache: try: with open(full_filename, 'r') as f: if self.trace: log_trace(f'Loaded {url} from cache') return f.read() except FileNotFoundError: pass if self.trace: log_trace(f'Loading {url} from network...') if authenticated: self.do_login() obj = self.session if authenticated else requests res = obj.post(self.ssb_url + url, data=data) if data else obj.get(self.ssb_url + url) res.raise_for_status() with open(full_filename, 'wb') as file: file.write(res.content) return res.content def do_login(self): if not self.loggedIn and self.login: self.login(self.session) self.loggedIn = True log_info('Logged in')

33.144681

152

0.563615

948

7,789

4.469409

0.232068

0.013217

0.009441

0.009205

0.144914

0.08119

0.066084

0.024074

0

0.001153

0.331878

7,789

234

153

33.286325

0.813028

0.103222

0

0.094937

0

0.110498

0.021635

0

1

0.06962

false

0.006329

0.063291

0.018987

0.221519

0.006329

0

null

0

null

0

1

0

0f1d969537ae4549e68774c788f1e46159431fb4

2,981

py

Python

backend/apps/recruting/routers.py

RafaelOO/FARM-Intro

14b241353f8d1a2506f6404ba7f09fe373430e33

[ "MIT" ]

null

backend/apps/recruting/routers.py

RafaelOO/FARM-Intro

14b241353f8d1a2506f6404ba7f09fe373430e33

[ "MIT" ]

null

backend/apps/recruting/routers.py

RafaelOO/FARM-Intro

14b241353f8d1a2506f6404ba7f09fe373430e33

[ "MIT" ]

null

from fastapi import APIRouter, Body, Request, HTTPException, status from fastapi.responses import JSONResponse from fastapi.encoders import jsonable_encoder from bson.objectid import ObjectId from .models import Candidate, UpdateCandidateModel router = APIRouter() @router.post("/", response_description="Add new candidate") async def create_task(request: Request, candidate: Candidate = Body(...)): candidate = jsonable_encoder(candidate) new_candidate = await request.app.mongodb["candidates"].insert_one(candidate) created_candidate = await request.app.mongodb["candidates"].find_one( {"_id": new_candidate.inserted_id} ) return JSONResponse(status_code=status.HTTP_201_CREATED, content=created_candidate) @router.get("/", response_description="List all candidates") async def list_candidates(request: Request): candidates = [] for doc in await request.app.mongodb["candidates"].find().to_list(length=100): candidates.append(doc) return candidates @router.get("/{id}", response_description="Get a single candidate from their id") async def show_candidate(id: str, request: Request): if (candidate := await request.app.mongodb["candidates"].find_one({"_id": ObjectId(id)})) is not None: return candidate raise HTTPException(status_code=404, detail=f"Candidate {id} not found") @router.get("/surname/{surname}", response_description="Get a single candidate from their surname") async def show_candidate(surname: str, request: Request): if (candidate := await request.app.mongodb["candidates"].find_one({"name.surname": surname})) is not None: return candidate raise HTTPException(status_code=404, detail=f"Candidate {surname} not found") @router.put("/{id}", response_description="Update a candidate") async def update_candidate(id: str, request: Request, candidate: UpdateCandidateModel = Body(...)): candidate = {k: v for k, v in candidate.dict().items() if v is not None} if len(candidate) >= 1: update_result = await request.app.mongodb["candidates"].update_one( {"_id": id}, {"$set": candidate} ) if update_result.modified_count == 1: if ( updated_candidate := await request.app.mongodb["candidates"].find_one({"_id": id}) ) is not None: return updated_candidate if ( existing_candidate := await request.app.mongodb["candidates"].find_one({"_id": id}) ) is not None: return existing_candidate raise HTTPException(status_code=404, detail=f"Candidate {id} not found") @router.delete("/{id}", response_description="Delete Task") async def delete_task(id: str, request: Request): delete_result = await request.app.mongodb["candidates"].delete_one({"_id": id}) if delete_result.deleted_count == 1: return JSONResponse(status_code=status.HTTP_204_NO_CONTENT) raise HTTPException(status_code=404, detail=f"Candidate {id} not found")

39.746667

110

0.711506

371

2,981

5.568733

0.234501

0.052275

0.065344

0.095837

0.46999

0.450145

0.339303

0.293804

0.268635

0

0.009635

0.164374

2,981

74

111

40.283784

0.819751

0

0.169811

0

0.134854

0

1

0

false

0

0.09434

0

0.226415

0

null

0

null

0

1

0

0f1f36d1e0f9a1ebd133c2aae0975c9487b7d756

3,008

py

Python

Scripts/Wordle_Answers_For_Input.py

krystianpietryka/Wordle_Assistant

caad82fdc780fda50931de7c51fa776ce395ccae

[ "MIT" ]

1

2022-03-18T08:37:14.000Z

Scripts/Wordle_Answers_For_Input.py

krystianpietryka/Wordle_Assistant

caad82fdc780fda50931de7c51fa776ce395ccae

[ "MIT" ]

1

2022-03-18T08:37:00.000Z

2022-03-18T09:30:20.000Z

Scripts/Wordle_Answers_For_Input.py

krystianpietryka/Wordle_Assistant

caad82fdc780fda50931de7c51fa776ce395ccae

[ "MIT" ]

null

import re # checks if values in arguments are the same char at the same index def Same_Place_Letters_Check(green, yellow): for i in range(len(green)): if green[i].isalpha() and yellow[i].isalpha(): return 0 return 1 # checks if values in argument are alphabetic def Valid_Symbol_Check(combined_inputs): for letter in combined_inputs: if not (letter == "." or letter.isalpha()): return 0 return 1 # converts empty letters in string to dots def Convert_Empty_Letters(letters): result = "" for letter in letters: if not letter: result += "." else: result += letter return result # Displays the possible 5 letter answers for given regex pattern def Display_Possible_Answers( possible_answers, excluded_letters, green_letters_input, yellow_letters ): answers_to_delete = [] # Loop through the 5 letter words, filter by green_letters and excluded_letters for line in possible_answers: search_result = re.search(green_letters_input, line) # If search result matches regex, mark for deletion if excluded letters are contained in the word if search_result: for letter in line: if letter in excluded_letters: answers_to_delete.append(line) else: answers_to_delete.append(line) # Loop through filtered answers, mark possible answers for deletion if letters do not contain all of the yellow letters for answer in possible_answers: for letter in yellow_letters: if letter != ".": if letter not in answer: answers_to_delete.append(answer) # If a string contains the same yellow letter and green letter # It must contain 2 of the same letter, so if the answer # does not contain 2 of the same letters, mark it for deletion elif letter in green_letters_input: count = 0 for answer_letter in answer: if answer_letter == letter: count += 1 if count != 2: answers_to_delete.append(answer) # Exclude answers with same letter in the same index as yellow letters for answer in possible_answers: for i in range(0, 5): if yellow_letters[i] == answer[i]: answers_to_delete.append(answer) # mark for deletion wordle answers used in the past with open("Text_Files/past_answers.txt", "r") as past_answers: for past_answer in past_answers: if past_answer in possible_answers: answers_to_delete.append(past_answer) # Deleting answers marked for deletion for marked_answer in answers_to_delete: try: possible_answers.remove(marked_answer) except: pass possible_answers.sort() return possible_answers

34.574713

123

0.627327

386

3,008

4.73057

0.264249

0.082147

0.065717

0.069003

0.159365

0.046002

0

0.006354

0.319814

3,008

86

124

34.976744

0.886119

0.27859

0

0.224138

0

0.014378

0.012523

0

1

0.068966

false

0.017241

0

0.189655

0

null

0

null

0

1

0

0f1fc5d68577311a61dffb534d8ff8b6e87cd185

5,239

py

Python

data/transforms.py

vshipitsin/Ultrasound

deb1e7f0edee023748e675300573656f81e8a5b7

[ "MIT" ]

3

2021-05-12T06:32:06.000Z

2021-06-15T10:58:24.000Z

data/transforms.py

vshipitsin/Ultrasound

deb1e7f0edee023748e675300573656f81e8a5b7

[ "MIT" ]

null

data/transforms.py

vshipitsin/Ultrasound

deb1e7f0edee023748e675300573656f81e8a5b7

[ "MIT" ]

null

import random import math import torch import torchvision import torchvision.transforms.functional as TF class ToTensor(object): def __init__(self, encode_map=False): self.encode_map = encode_map self.transform = torchvision.transforms.ToTensor() @staticmethod def encode_segmentation_map(mask): labels_map = torch.zeros(mask.shape) labels_map[mask > 0] = 1 return labels_map.to(dtype=torch.int64) def __call__(self, sample): image, mask = sample if self.encode_map: return self.transform(image), self.encode_segmentation_map(self.transform(mask)) else: return self.transform(image), self.transform(mask) class Resize(object): def __init__(self, size): self.resize = torchvision.transforms.Resize(size, interpolation=torchvision.transforms.InterpolationMode.BILINEAR) def __call__(self, sample): image, mask = sample return self.resize(image), self.resize(mask) class HorizontalFlip(object): def __init__(self, p=0.5): self.flip = lambda image: TF.hflip(image) if random.random() < p else image def __call__(self, sample): image, mask = sample return self.flip(image), self.flip(mask) class RandomRotation(object): def __init__(self, degrees): angle = torchvision.transforms.RandomRotation.get_params((-degrees, degrees)) self.rotate = lambda image: TF.rotate(image, angle) def __call__(self, sample): image, mask = sample return self.rotate(image), self.rotate(mask) class RandomScale(object): def __init__(self, scale): self.scale = scale def scale(self, image): ret = torchvision.transforms.RandomAffine.get_params((0, 0), None, self.scale, None, image.size) return TF.affine(image, *ret, resample=False, fillcolor=0) def __call__(self, sample): image, mask = sample return self.scale(image), self.scale(mask) class BrightContrastJitter(object): def __init__(self, brightness=0, contrast=0): self.transform = torchvision.transforms.ColorJitter(brightness, contrast, 0, 0) def __call__(self, sample): image, mask = sample return self.transform(image), mask class GaussianNoise(object): def __init__(self, standard_deviation): self.standard_deviation = standard_deviation @staticmethod def noise_overlay(tensor, standard_deviation): if type(standard_deviation) is tuple: min_value = standard_deviation[0] / 255.0 max_value = standard_deviation[1] / 255.0 else: min_value = standard_deviation / 255.0 max_value = standard_deviation / 255.0 return torch.clamp(tensor + torch.empty_like(tensor).normal_(mean=0.0, std=1.0) * torch.empty_like(tensor).uniform_(min_value, max_value), min=0.0, max=1.0) def __call__(self, sample): image, clean_image = sample return self.noise_overlay(image, self.standard_deviation), clean_image class RicianNoise(object): def __init__(self, variance=(0, 0.1)): self.variance = variance @staticmethod def noise_overlay(tensor, variance): if type(variance) is tuple: variance = random.uniform(variance[0], variance[1]) else: variance = variance return torch.clamp(torch.sqrt(torch.pow(tensor + torch.empty_like(tensor).normal_(mean=0.0, std=variance), 2) + torch.pow(torch.empty_like(tensor).normal_(mean=0.0, std=variance), 2)), min=0.0, max=1.0) def __call__(self, sample): image, clean_image = sample return self.noise_overlay(image, self.variance), clean_image class RandomErasing(object): def __init__(self, sl=0.02, sh=0.4, r1=0.3, mean=[0.4914, 0.4822, 0.4465]): self.mean = mean self.sl = sl self.sh = sh self.r1 = r1 def noise_overlay(self, tensor): for attempt in range(100): area = tensor.shape[1] * tensor.shape[2] target_area = random.uniform(self.sl, self.sh) * area aspect_ratio = random.uniform(self.r1, 1 / self.r1) h = int(round(math.sqrt(target_area * aspect_ratio))) w = int(round(math.sqrt(target_area / aspect_ratio))) if w < tensor.shape[2] and h < tensor.shape[1]: x1 = random.randint(0, tensor.shape[1] - h) y1 = random.randint(0, tensor.shape[2] - w) if tensor.shape[0] == 3: tensor[0, x1:x1 + h, y1:y1 + w] = self.mean[0] tensor[1, x1:x1 + h, y1:y1 + w] = self.mean[1] tensor[2, x1:x1 + h, y1:y1 + w] = self.mean[2] else: tensor[0, x1:x1 + h, y1:y1 + w] = self.mean[0] return tensor return tensor def __call__(self, sample): image, clean_image = sample return self.noise_overlay(image), clean_image

33.369427

116

0.60355

646

5,239

4.698142

0.182663

0.032949

0.03855

0.050412

0.336079

0.27084

0.25173

0.241186

0.204942

0.163427

0

0.03237

0.286505

5,239

156

117

33.583333

0.779561

0

0.267241

0

1

0.198276

false

0

0.043103

0

0.456897

0

null

0

null

0

1

0

0f2033a2f3225dea614853557dc3ac6f05fe992a

1,289

py

Python

tests/nutter/test_resultreports.py

cganta/dbtest

37b8020cae9218ce9d9e79e92d2d9419ae62f74c

[ "MIT" ]

130

2020-02-13T17:20:58.000Z

2022-03-29T20:27:49.000Z

tests/nutter/test_resultreports.py

cganta/dbtest

37b8020cae9218ce9d9e79e92d2d9419ae62f74c

[ "MIT" ]

27

2020-02-25T05:04:28.000Z

2022-03-07T23:27:44.000Z

tests/nutter/test_resultreports.py

cganta/dbtest

37b8020cae9218ce9d9e79e92d2d9419ae62f74c

[ "MIT" ]

21

2020-02-13T19:33:42.000Z

2022-03-18T02:36:38.000Z

""" Copyright (c) Microsoft Corporation. Licensed under the MIT license. """ import pytest from common.testresult import TestResults, TestResult from common.resultreports import JunitXMLReportWriter from common.resultreports import TagsReportWriter def test_junitxmlreportwriter_add_result__invalid_params__raises_valueerror(): writer = JunitXMLReportWriter() with pytest.raises(ValueError): writer.add_result(None, None) def test_tagsreportwriter_add_result__invalid_params__raises_valueerror(): writer = TagsReportWriter() with pytest.raises(ValueError): writer.add_result(None, None) def test_tagsreportwriter_add_result__1_test_result__1_valid_row(): writer = TagsReportWriter() test_results = TestResults() test_name = 'case1' duration = 10 tags = ['hello', 'hello'] test_result = TestResult(test_name, True, duration, tags) test_results.append(test_result) notebook_name = 'test_mynotebook' writer.add_result(notebook_name, test_results) assert len(writer._rows) == 1 row = writer._rows[0] assert row.notebook_name == notebook_name assert row.test_name == test_name assert row.passed_str == 'PASSED' assert row.duration == duration assert row.tags == row._to_tag_string(tags)

28.644444

78

0.754849

153

1,289

6.019608

0.339869

0.058632

0.095548

0.062975

0.261672

0.175896

0

0.006475

0.161365

1,289

44

79

29.295455

0.845513

0.052754

0

0.206897

0

0.029678

0

0.206897

1

0.103448

false

0.034483

0.137931

0

0.241379

0

null

0

null

0

1

0

0f242ef44351b6946ec51913b2511ceb3f37212d

648

py

Python

trajectory/management/commands/WayPointsDatabaseLoad.py

RobertPastor/flight-profile

bdc3bb9defeb347db26f96f7accd4d06cad1e33b

[ "MIT" ]

null

trajectory/management/commands/WayPointsDatabaseLoad.py

RobertPastor/flight-profile

bdc3bb9defeb347db26f96f7accd4d06cad1e33b

[ "MIT" ]

null

trajectory/management/commands/WayPointsDatabaseLoad.py

RobertPastor/flight-profile

bdc3bb9defeb347db26f96f7accd4d06cad1e33b

[ "MIT" ]

null

from django.core.management.base import BaseCommand from trajectory.management.commands.WayPoints.WayPointsDatabaseFile import WayPointsDatabase from trajectory.models import WayPoint class Command(BaseCommand): help = 'Reads the Synonym file and load the Aircrafts table' def handle(self, *args, **options): WayPoint.objects.all().delete() wayPointsBD = WayPointsDatabase() if (wayPointsBD.exists()): print("acBD exists") ret = wayPointsBD.read() print ("read wayPoints database result = {0}".format(ret)) else: print("wayPoints database does not exists")

38.117647

93

0.683642

68

648

6.514706

0.691176

0.063205

0

0.001984

0.222222

648

17

94

38.117647

0.876984

0

0.203704

0

1

0.071429

false

0

0.214286

0

0.428571

0.214286

0

null

0

null

0

1

0

0f25e763c359b1bdd3aa8e71bc6771b962bedaf9

938

py

Python

effort/src/datasets/handler.py

rahlk/Bellwether

39e0e63504a6dfdeeb5d6e8d733e708d1485ecd9

[ "Unlicense" ]

9

2017-07-27T10:32:48.000Z

2021-07-01T11:51:51.000Z

effort/src/datasets/handler.py

rahlk/Bellwether

39e0e63504a6dfdeeb5d6e8d733e708d1485ecd9

[ "Unlicense" ]

11

2016-03-15T16:27:47.000Z

2019-09-05T02:25:08.000Z

effort/src/datasets/handler.py

rahlk/Bellwether

39e0e63504a6dfdeeb5d6e8d733e708d1485ecd9

[ "Unlicense" ]

5

2017-01-28T22:45:34.000Z

2019-12-04T13:15:10.000Z

from __future__ import print_function, division from pdb import set_trace from effort import * import pandas import os import sys root = os.path.join(os.getcwd().split('src')[0], 'src') if root not in sys.path: sys.path.append(root) from glob import glob def pytocsv(): for mod in [coc81,Mystery1,Mystery2,cocomo,nasa93]: inst = mod.run() fname = mod.__name__.split('.')[-1]+'.csv' head = inst.indep+[inst.less[0]] print(fname, len(head), " ".join(head)) body = [elem.cells[:24] for elem in inst._rows] dframe = pandas.DataFrame(body, columns = head) dframe.to_csv(fname, index=False) def get_all_datasets(): all = {} files = glob(os.path.abspath(os.path.join(root, 'datasets', "*.csv"))) for f in files: all.update({f.split("/")[-1].split('.')[0]: f}) return all if __name__ == '__main__': get_all_datasets()

26.8

74

0.608742

132

938

4.143939

0.484848

0.032907

0.036563

0

0.018056

0.232409

938

34

75

27.588235

0.741667

0

0.037313

0

1

0.074074

false

0

0.259259

0

0.37037

0.074074

0

null

0

null

0

1

0

0f272a14d6714e39b245a5ca529f31d3ab07a1d7

3,222

py

Python

bot.py

gandalf3/distracticat

22aaa9ecadea4b654f1c2f7c30ed11f10f9472a9

[ "MIT" ]

1

2022-03-08T23:30:40.000Z

bot.py

gandalf3/distracticat

22aaa9ecadea4b654f1c2f7c30ed11f10f9472a9

[ "MIT" ]

1

2022-03-05T21:50:18.000Z

bot.py

gandalf3/distracticat

22aaa9ecadea4b654f1c2f7c30ed11f10f9472a9

[ "MIT" ]

null

#!/usr/bin/env python3 import logging import os import random import sys import discord from dotenv import load_dotenv import sqlalchemy as sa from sqlalchemy import orm from discord.ext import commands from distracticat import chooser, model from distracticat.config import Config from distracticat.emotes import Reactions logging.basicConfig(level=logging.INFO) log = logging load_dotenv() def getenv(key: str) -> str: if (value := os.getenv(key)) is not None: return value else: exit(f"{key} environment variable not specified") database_url = getenv("DATABASE_URL") discord_secret_token = getenv("DISCORD_SECRET_TOKEN") config = Config() bot = commands.Bot(command_prefix=config.command_prefix) engine: sa.engine.Engine = sa.create_engine(database_url, echo=True, future=True) async def add_distraction( channel: discord.PartialMessageable, reply, description: str, guild_id: int, author_id: int, message_id: int | None = None, ): await channel.send(Reactions.reaction()) distraction = model.Distraction( guild_id=guild_id, description=description, author_id=author_id, message_id=message_id, ) embed = discord.Embed( title="new distraction!", description=distraction.description, color=discord.Color.purple(), ) embed.add_field(name="Suggested by", value=f"<@{author_id}>") async with channel.typing(): with orm.Session(engine) as session: session.add(distraction) session.commit() await reply(embed=embed) @bot.command(name="distracticat") async def distracticat_cmd(ctx: commands.Context, *, description: str): await add_distraction( ctx.channel, ctx.reply, description, ctx.guild.id, ctx.author.id, ctx.message.id, ) @bot.slash_command(name="distracticat", guild_ids=config.guild_ids()) async def distracticat_scmd(ctx: discord.ApplicationContext, description: str): await add_distraction( ctx.channel, ctx.respond, description, ctx.guild.id, ctx.author.id, ) @bot.command(name="commitfelicide") async def kill_cmd(ctx: commands.Context): await ctx.reply("how could you do this? (ಡ‸ಡ)") sys.exit() @bot.slash_command(name="commitfelicide", guild_ids=config.guild_ids()) async def kill_scmd(ctx: commands.Context): await ctx.respond("how could you do this? (ಡ‸ಡ)") sys.exit() @bot.command() async def choose(ctx: commands.Context, *, choices_str: str): choices, feedback = chooser.parse_choices(choices_str) if feedback: await ctx.send(feedback) return if len(choices) == 0: await ctx.reply( "That's a tough decision you're asking me to make you know. " "Let me get back to you on that one." ) return if len(choices) == 1: await ctx.reply(f"That's a sound decision {ctx.author}") else: chosen = random.choice(choices) await ctx.reply(f"Hm.. :thinking: I say go with {chosen}.") @bot.event async def on_ready(): log.info(f"logged in as {bot.user}") bot.run(discord_secret_token)

23.347826

81

0.66977

421

3,222

5.030879

0.330166

0.02644

0.033994

0.01983

0.154863

0.130312

0.071766

0.028329

0

0.001194

0.22005

3,222

137

82

23.518248

0.840828

0.006518

0

0.161616

0

0.129375

0

1

0.010101

false

0

0.121212

0

0.161616

0

null

0

null

0

1

0

0f27e3bf932ed138dde63efb1dd8abbc7155fad3

9,666

py

Python

backend/group/views/oj.py

skku-npc/SKKU_Coding_Platform

1d972e8922484cf94f6735fd08b2565e5d3517d0

[ "MIT" ]

1

2022-03-30T14:03:23.000Z

backend/group/views/oj.py

skku-npc/SKKU_Coding_Platform

1d972e8922484cf94f6735fd08b2565e5d3517d0

[ "MIT" ]

56

2022-02-19T08:13:48.000Z

2022-03-25T10:17:07.000Z

backend/group/views/oj.py

skku-npc/SKKU_Coding_Platform

1d972e8922484cf94f6735fd08b2565e5d3517d0

[ "MIT" ]

1

2022-03-25T15:02:46.000Z

from drf_yasg.utils import swagger_auto_schema from drf_yasg import openapi from group.serializers import CreateGroupMemberJoinSerializer, EditGroupMemberPermissionSerializer, GroupMemberJoinSerializer, GroupDetailSerializer, GroupMemberSerializer from group.serializers import GroupRegistrationRequestSerializer, GroupSummarySerializer, CreateGroupRegistrationRequestSerializer from utils.api import APIView, validate_serializer from utils.decorators import check_group_admin from django.db.models import Q from ..models import GroupMemberJoin, GroupMember, GroupRegistrationRequest, Group class GroupRegistrationRequestAPI(APIView): @swagger_auto_schema( request_body=CreateGroupRegistrationRequestSerializer, operation_description="Request to register a group", responses={200: GroupRegistrationRequestSerializer} ) @validate_serializer(CreateGroupRegistrationRequestSerializer) def post(self, request): user = request.user if not user.is_authenticated: return self.error("Login First") data = request.data name = data["name"] if GroupRegistrationRequest.objects.filter(name=name).exists() or Group.objects.filter(name=name).exists(): return self.error("Duplicate group name") registration_request = GroupRegistrationRequest.objects.create( name=name, short_description=data["short_description"], description=data["description"], is_official=data["is_official"], created_by=request.user ) return self.success(GroupRegistrationRequestSerializer(registration_request).data) class GroupAPI(APIView): @swagger_auto_schema( manual_parameters=[ openapi.Parameter( name="id", in_=openapi.IN_QUERY, description="Unique ID of a group. if id is not given, return group list, else return detail of a group", type=openapi.TYPE_INTEGER, required=False ), ], operation_description="Get group list or detail of a group" ) def get(self, request): user = request.user if not user.is_authenticated: return self.error("Login First") group_id = request.GET.get("id") # Group List if not group_id: groups_not_admin = Group.objects.filter(groupmember__is_group_admin=False, groupmember__user=user) groups_admin = Group.objects.filter(groupmember__is_group_admin=True, groupmember__user=user) other_groups = Group.objects.exclude(Q(members=user)) data = {} data["admin_groups"] = GroupSummarySerializer(groups_not_admin, many=True).data data["groups"] = GroupSummarySerializer(groups_admin, many=True).data data["other_groups"] = GroupSummarySerializer(other_groups, many=True).data return self.success(data) # Group Detail try: group = Group.objects.get(id=group_id) except Group.DoesNotExist: return self.error("Group does not exist") data = GroupDetailSerializer(group).data data["members"] = GroupMemberSerializer(GroupMember.objects.filter(group=group_id), many=True).data if GroupMember.objects.filter(is_group_admin=True, group=group, user=user).exists(): group_member_join = GroupMemberJoin.objects.filter(group=group) data["group_member_join"] = GroupMemberJoinSerializer(group_member_join, many=True).data return self.success(data) class GroupMemberAPI(APIView): # Change User Group Permission @swagger_auto_schema( request_body=EditGroupMemberPermissionSerializer, operation_description="Change group member permission. only can change is_group_admin field.", responses={200: GroupMemberSerializer} ) @validate_serializer(EditGroupMemberPermissionSerializer) @check_group_admin() def put(self, request): data = request.data user = request.user if data["is_group_admin"]: try: member = GroupMember.objects.get(user=data["user_id"], group=data["group_id"]) except GroupMember.DoesNotExist: return self.error("Group Member does not exists") member.is_group_admin = data["is_group_admin"] # True member.save() return self.success(GroupMemberSerializer(member).data) # Only group creator can downgrade group admin's permission. try: group = Group.objects.get(id=data["group_id"]) except Group.DoesNotExist: return self.error("Group does not exists") if not (group.created_by.id == user.id): return self.error("Only group creator can change group admin's permission") try: member = GroupMember.objects.get(user=data["user_id"], group=data["group_id"]) except GroupMember.DoesNotExist: return self.error("Group member does not exist") member.is_group_admin = data["is_group_admin"] # False member.save() return self.success(GroupMemberSerializer(member).data) @swagger_auto_schema( manual_parameters=[ openapi.Parameter( name="user_id", in_=openapi.IN_QUERY, description="Unique ID of a user. not member_join(intermediary model) id.", type=openapi.TYPE_INTEGER, required=False ), openapi.Parameter( name="group_id", in_=openapi.IN_QUERY, description="Unique ID of a group", type=openapi.TYPE_INTEGER, required=False ), ], operation_description="Get group list", responses={200: "Member successfully removed from this group."} ) @check_group_admin() def delete(self, request): user_id = request.GET.get("user_id") group_id = request.GET.get("group_id") try: member = GroupMember.objects.get(user=user_id, group=group_id) except GroupMember.DoesNotExist: return self.error("group member does not exist") if member.is_group_admin: return self.error("Cannot remove admin member.") member.delete() return self.success("Member successfully removed from this group.") class GroupMemberJoinAPI(APIView): @swagger_auto_schema( request_body=CreateGroupMemberJoinSerializer, operation_description="Post a group member join", responses={200: GroupMemberJoinSerializer} ) @validate_serializer(CreateGroupMemberJoinSerializer) def post(self, request): user = request.user if not user.is_authenticated: return self.error("Login First") group_id = request.data["group_id"] description = request.data["description"] if Group.objects.filter(id=group_id, members=user).exists(): return self.error("You are already a member of this group.") if GroupMemberJoin.objects.filter(group=group_id, created_by=user).exists(): return self.error("You have already submitted your member join to this group.") group_member_join = GroupMemberJoin.objects.create( group_id=group_id, description=description, created_by=user ) return self.success(GroupMemberJoinSerializer(group_member_join).data) @swagger_auto_schema( manual_parameters=[ openapi.Parameter( name="group_id", in_=openapi.IN_QUERY, type=openapi.TYPE_INTEGER, description="Unique id of group.", required=True ), openapi.Parameter( name="member_join_id", in_=openapi.IN_QUERY, type=openapi.TYPE_INTEGER, description="Unique id of member_join", required=True ), openapi.Parameter( name="accept", in_=openapi.IN_QUERY, type=openapi.TYPE_BOOLEAN, description="true if accept else reject the member_join", required=True ), ], operation_description="Resolve group member join. accept=True -> accept the member to join our group. accept=False or not given -> reject the member", responses={200: GroupDetailSerializer} ) @check_group_admin() def delete(self, request): group_id = request.GET.get("group_id") member_join_id = request.GET.get("member_join_id") accept = request.GET.get("accept") try: group_member_join = GroupMemberJoin.objects.get(id=member_join_id) except GroupMemberJoin.DoesNotExist: self.error("Group member join does not exist") if not accept: group_member_join.delete() return self.success("Successfully rejected a group member join") group_member_join_created_by = group_member_join.created_by try: group = Group.objects.get(id=group_id) except Group.DoesNotExist: self.error("Group does not exist") if group.members.filter(id=group_member_join_created_by.id).exists(): self.error("This user is already a member. This member_join may be already resolved.") group.members.add(group_member_join_created_by) group_member_join.delete() return self.success(GroupDetailSerializer(group).data)

39.292683

171

0.650321

1,035

9,666

5.900483

0.133333

0.040937

0.039299

0.01572

0.457672

0.382184

0.328639

0.282463

0.216473

0.192893

0

0.002106

0.263294

9,666

245

172

39.453061

0.855498

0.012622

0

0.427861

0

0.00995

0.151201

0.002517

0

1

0.029851

false

0

0.039801

0

0.199005

0

null

0

null

0

1

0

0f28c9a7a5cb162604cdc24efd8446cbf75109a5

2,277

py

Python

python/cp1_code/cp1_broadcast_client.py

ntpdrop/ieeesp2021

084ac380774351cb032e9c1f48c5c6f7b58372fa

[ "MIT" ]

null

python/cp1_code/cp1_broadcast_client.py

ntpdrop/ieeesp2021

084ac380774351cb032e9c1f48c5c6f7b58372fa

[ "MIT" ]

null

python/cp1_code/cp1_broadcast_client.py

ntpdrop/ieeesp2021

084ac380774351cb032e9c1f48c5c6f7b58372fa

[ "MIT" ]

null

import logging from scapy.layers.inet import IP, UDP from scapy.packet import Packet from scapy.sendrecv import send from cp1_client import CP1Client from cp1_package import CP1Package from cp1_session import CP1Session from ntp_mode import NTPMode from ntp_utils import init_ntp_client_pck class CP1BroadcastClient(CP1Client): """ OBSOLETE """ def __init__(self, address: str, static_key: str, sniff_interface: str = 'lo', log=logging.getLogger('CP1Client-Logger')): super().__init__(address, static_key, sniff_interface, log) def send_init_pck(self, ip_address, cp1_address): """ Sends an init-package to the desired ip-address and files in the desired cp1-address. :param ip_address: :param cp1_address: :return: """ self.send_session = CP1Session() ntp_pck = self.send_session.generate_init_pck(cp1_address) ntp_pck.orig = None ntp_pck.recv = None ntp_pck.mode = 5 # ntp_pck.show() pck_to_send = IP(dst=ip_address) / UDP() / ntp_pck send(pck_to_send) self.log.debug("Init package successfully send to " + str(ip_address)) return pck_to_send def send_next_pck(self, ip_address, ntp_mode: NTPMode = NTPMode.CLIENT) -> Packet: """ Sends the next chunk of payload bits to the destination. :param ip_address: :param ntp_mode: the mode of the ntp package to send. :return: the bits just send. """ next_bits_to_send = self.send_session.secret_to_send.next_bits(self.payload_size) self.log.debug("Next payload bits to send: " + str(next_bits_to_send)) ntp_pck = CP1Package(ntp_pck=init_ntp_client_pck()) ntp_pck.add_payload(next_bits_to_send) ntp_pck_ntp = ntp_pck.ntp() ntp_pck_ntp.orig = None ntp_pck_ntp.recv = None ntp_pck_ntp.mode = 5 pck_to_send = IP(dst=ip_address) / UDP() / ntp_pck_ntp send(pck_to_send) self.log.debug("Payload package successfully send to " + str(ip_address)) if not self.send_session.secret_to_send.has_next_bits(): self.log.debug("Sending complete. Terminating sending session.") return pck_to_send

33.985075

93

0.669302

323

2,277

4.421053

0.232198

0.063025

0.037815

0.029412

0.212185

0.131653

0.044818

0

0.009889

0.245059

2,277

66

94

34.5

0.820826

0.139218

0

0.105263

0

0.087568

0

1

0.078947

false

0

0.236842

0

0.394737

0

null

0

null

0

1

0

0f2aa8135e4df5892926d93df4dea8a4e0467627

8,103

py

Python

backend/routes.py

ThodoriKapouranis/ECE464-Databases-Final-Quizlet

1231b5a4a683c4dffd354d044dff02100edb9b97

[ "MIT" ]

null

backend/routes.py

ThodoriKapouranis/ECE464-Databases-Final-Quizlet

1231b5a4a683c4dffd354d044dff02100edb9b97

[ "MIT" ]

null

backend/routes.py

ThodoriKapouranis/ECE464-Databases-Final-Quizlet

1231b5a4a683c4dffd354d044dff02100edb9b97

[ "MIT" ]

null

import json import secrets import os from pprint import pprint from bson import json_util from bson.objectid import ObjectId from flask import request, send_from_directory from bson.json_util import dumps, loads from werkzeug.datastructures import FileStorage from main import app from mongodb import users, decks, auths, cards # 200 code :: Good # 400 code :: Bad Request (use as generic error code) # 404 code :: Requested information DNE (good response, but db object DNE) MEDIA_PATH = "media/" @app.route("/") def hello_world(): return "Hello, World!" # Register page @app.route("/register", methods=['POST']) def registerUser(): data = request.json res = users.createUser(data["email"], data["username"], data["password"]) return {"status": 200 } if res!=-1 else {"status": 400 } # Login Page @app.route("/login", methods=["POST"]) def login(): data = request.json res = users.attemptLogin(data["email"], data["password"]) if (res != None): return {"status":200, "username": res[0], "token": res[1] } else: return {"status":400 } # Logout, deletes token from db @app.route("/logout", methods=["POST"]) def logout(): data = request.json res = auths.deleteToken( data["token"] ) return {"status":200} if res else {"status":400} @app.route("/checkToken", methods=["POST"]) def checkToken(): ''' This is called when the header is rerendered and the token hasnt been checked for at least {2} minutes. Checks to see if token is still valid. ''' data = request.json res = auths.checkUserExist( data["token"] ) if ( res != None): return {"status":200} else: return {"status":400} # Get user by name # /search/users/user?=asdfasdf @app.route("/search/users/<username>", methods=["GET"]) def searchUsers(username): res = users.getUsersByName(username) if (res != None): res = json.loads( dumps(res) ) return {"status":200, "users": res} else: return {"status":400} @app.route("/search/decks/", methods=["GET"]) def searchDecks(): name = request.args.get('name') tags = request.args.get('tags').split(",") rating = request.args.get('rating') if rating != "": rating = int(rating) pprint(name) pprint(tags) pprint(rating) res = decks.searchDecks(name=name, tags=tags, rating=rating) if ( res != None): res = json.loads( dumps(res) ) return { "status":200, "decks": res } else: return { "status":400 } @app.route("/search/email/", methods=["GET"]) def searchEmail(): email = request.args.get("email") name = users.getUserByEmail(email) return " email " @app.route("/deck/create", methods=["POST"]) def createDeck(): data = request.json tags = data["tags"].split(" ") did = decks.createDeck(data["name"] , tags, data["token"], data["privacy"]) if (did != -1 and did != None): return {"status":200, "did": str(did)} else: return {"status":400} # https://stackoverflow.com/questions/16586180/typeerror-objectid-is-not-json-serializable # ObjectIDs cannot be sent through JSON easily. # The solution is to use bson.json_util.dump to convert the JSON to a string which breaks up the # object id. Then we rebuild it back to JSON using json.load() @app.route("/user/<username>/decks", methods=["GET"]) def requestUserDecks(username): res = decks.getUsersDecks(username) if (res != None): dids_created = [json.loads(dumps(i)) for i in res[0]] dids_favorited = [json.loads(dumps(i)) for i in res[1]] return {"status" : 200, "created_decks": dids_created, "favorite_decks": dids_favorited } else: return {"status":400} # # Single Deck view (Deck, comments, ratings) # # url: did | json: token @app.route("/deck/<did>", methods=["POST"]) def getDeckInfo(did): # Get the user's tokens to figure out their authorization level # so that the proper things are returned to the frontend # for better user-specific rendering. data = request.json utoken = data["token"] uid = auths.getUid(utoken) deck = decks.getDeck( ObjectId(did) ) if (deck != None and uid != None): # Write the code to average the ratings to display on frontend # ratingAverage = 0 # listOfRatings = res["ratings"] # for i in listOfRatings: # ... authLevel = decks.userAuthorizationLevel(ObjectId(did), uid) deckJson = json.loads( dumps(deck) ) avgRating = decks.getRating( ObjectId(did) ) return {"status":200, "deck": deckJson, "authLevel":authLevel, "rating": avgRating} else: return {"status":400} @app.route("/deck/<did>/comment", methods=["POST"]) def addComment(did): data = request.json comments = data["comment"] token = request.headers["token"] # def addComment ( did:str, utoken:str, content:str ): res = decks.addComment(ObjectId(did), token, comments) return {"status": res} @app.route("/deck/<did>/favorite", methods=["POST"]) def addToFavorite(did): data = request.json token = data["token"] res = users.toggleFavorite(ObjectId(did), token) if (res != -1): return {"status":200} else: return {"status":400} # # Add comment (visible on single deck page) # url: did | json: comment, token # @app.route("/deck/<did>/comment", methods=["POST"]) # def addDeckComment(): # # Add rating (visible on single deck page) # # url: did | json: comment, token @app.route("/deck/<did>/rate", methods=["POST"]) def addDeckRating(did): data = request.json token = data["token"] rating = data["rating"] res = decks.addRating(ObjectId(did), token, rating) return {"status": res} # # Promote someone's auth lv @app.route("/deck/<did>/authorize", methods = ["POST"]) def authorizeUser(did): data = request.json token = data["token"] user = data["username"] level = data["level"] res = decks.authorizeUser(ObjectId(did), token, user, level) if (res != -1): return {"status": 200} else: return {"status": 400} #ftxt0 #fimg34 class Tag: def __init__(self, tag): self.side = tag[0] self.type = tag[1:4] self.id = tag[4:] @app.route("/deck/<did>/add", methods=["POST"]) def addCard(did): data = request.form files = request.files token = request.headers["token"] front = {} back = {} pprint(token) pprint(data) # These are all the text fields for key in data: tag = Tag(key) field = {tag.type: data[key]} # {"img", URL} if (tag.side == "f"): front[tag.id] = field # {0 : {"img", URL}} elif (tag.side == "b"): back[tag.id] = field for key in files: tag = Tag(key) secret = secrets.token_hex() file = files[key] field = {tag.type: secret} file.save(MEDIA_PATH + secret) if (tag.side == "f"): front[tag.id] = field # {0 : {"img", URL}} elif (tag.side == "b"): back[tag.id] = field pprint(front) pprint(back) # Use ORM function to actually create this object res = cards.createCard( ObjectId(did), token, front, back) if res != -1: return {"status": 200} else: return {'status': 400} @app.route('/media/<path:path>') def send_media(path): return send_from_directory( MEDIA_PATH, path, as_attachment=True ) @app.route("/deck/<did>/study", methods=["GET"]) def getFullDeck(did): token = request.headers["token"] # res[0] user auth # res[1] cursor object res = cards.getDecksCards(ObjectId(did), token) if (res[1] != -1): res[1] = json.loads( dumps(res[1]) ) return {"status": 200, "auth": res[0], "cards": res[1]} else : return {"status": 400} @app.route("/deck/<did>", methods = ["DELETE"]) def deckDelete(did): utoken = request.headers ["token"] uid = auths.getUid(utoken) res = decks.deleteDeck( ObjectId(did), uid ) if (res == 0 ): # res = json_util.loads( dumps(res) ) return {"status": 200} else: return {"status": res} @app.route("/deck/<did>/card/<cid>", methods=["DELETE"]) def cardDelete(did, cid): utoken = request.headers["token"] uid = auths.getUid(utoken) res = cards.deleteCard(ObjectId(did), ObjectId(cid), uid) if (res == 0): return {"status": 200} else: return {"status": 400}

27.75

97

0.642972

1,095

8,103

4.73516

0.23379

0.069431

0.043394

0.043973

0.261909

0.218322

0.191707

0.148505

0.104147

0.085632

0

0.020325

0.186351

8,103

292

98

27.75

0.766116

0.192398

0

0.364078

0

0.128585

0.013722

0

1

0.101942

false

0.009709

0.053398

0.009709

0.320388

0.038835

0

null

0

null

0

1

0

0f2c193c99e6c3da6c18f1b4d2444bb931a8ef76

2,087

py

Python

tests/test_guild.py

tylerbutler/battlenet

5394d648c4562a711f21720499fb12ebfaf2de1d

[ "MIT" ]

null

tests/test_guild.py

tylerbutler/battlenet

5394d648c4562a711f21720499fb12ebfaf2de1d

[ "MIT" ]

null

tests/test_guild.py

tylerbutler/battlenet

5394d648c4562a711f21720499fb12ebfaf2de1d

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os import battlenet import datetime from battlenet import Guild try: import unittest2 as unittest except ImportError: import unittest as unittest PUBLIC_KEY = os.environ.get('BNET_PUBLIC_KEY') PRIVATE_KEY = os.environ.get('BNET_PRIVATE_KEY') battlenet.Connection.setup(public_key=PUBLIC_KEY, private_key=PRIVATE_KEY) class GuildTest(unittest.TestCase): def test_general(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence') self.assertEqual(guild.name, 'Excellence') self.assertEqual(str(guild), 'Excellence') self.assertEqual(guild.get_realm_name(), 'Nazjatar') self.assertEqual(guild.realm.name, 'Nazjatar') self.assertEqual(str(guild.realm), 'Nazjatar') def test_len(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence', fields=[Guild.MEMBERS]) self.assertGreater(len(guild), 1) def test_leader(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence', fields=[Guild.MEMBERS]) character = guild.get_leader() self.assertEqual(character.name, 'Clí') def test_lazyload_member_character(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence') character = guild.get_leader() self.assertRegexpMatches(character.get_full_class_name(), r'^(Holy|Protection|Retribution) Paladin$') def test_achievements(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence', fields=[Guild.ACHIEVEMENTS]) for id_, completed_ts in guild.achievements.items(): self.assertIsInstance(id_, int) self.assertIsInstance(completed_ts, datetime.datetime) def test_perks(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence') self.assertGreater(len(guild.perks), 1) def test_rewards(self): guild = Guild(battlenet.UNITED_STATES, 'Nazjatar', 'Excellence') self.assertGreater(len(guild.rewards), 1) if __name__ == '__main__': unittest.main()

30.691176

109

0.695256

237

2,087

5.932489

0.28692

0.034851

0.069701

0.114509

0.446657

0.335704

0.298009

0.257468

0

0.002929

0.18208

2,087

67

110

31.149254

0.820738

0.010062

0

0.186047

0

0.121609

0.014535

0

0.27907

1

0.162791

false

0

0.162791

0

0.348837

0

null

0

null

0

1

0

0f2c8fc217036dfe9c29102e972d0fbdddbef0ca

7,954

py

Python

src/RestrictedPython/Guards.py

rahulbahal7/restricted-python

c39cffe71dfc30630e946977735303d3a65b0383

[ "ZPL-2.1" ]

null

src/RestrictedPython/Guards.py

rahulbahal7/restricted-python

c39cffe71dfc30630e946977735303d3a65b0383

[ "ZPL-2.1" ]

null

src/RestrictedPython/Guards.py

rahulbahal7/restricted-python

c39cffe71dfc30630e946977735303d3a65b0383

[ "ZPL-2.1" ]

null

############################################################################## # # Copyright (c) 2002 Zope Foundation and Contributors. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED # WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS # FOR A PARTICULAR PURPOSE # ############################################################################## # This tiny set of safe builtins is extended by users of the module. # AccessControl.ZopeGuards contains a large set of wrappers for builtins. # DocumentTemplate.DT_UTil contains a few. from RestrictedPython import _compat if _compat.IS_PY2: import __builtin__ as builtins else: # Do not attempt to use this package on Python2.7 as there # might be backports for this package such as future. import builtins safe_builtins = {} _safe_names = [ 'None', 'False', 'True', 'abs', 'bool', 'callable', 'chr', 'complex', 'divmod', 'float', 'hash', 'hex', 'id', 'int', 'isinstance', 'issubclass', 'len', 'oct', 'ord', 'pow', 'range', 'repr', 'round', 'slice', 'str', 'tuple', 'zip' ] _safe_exceptions = [ 'ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException', 'BufferError', 'BytesWarning', 'DeprecationWarning', 'EOFError', 'EnvironmentError', 'Exception', 'FloatingPointError', 'FutureWarning', 'GeneratorExit', 'IOError', 'ImportError', 'ImportWarning', 'IndentationError', 'IndexError', 'KeyError', 'KeyboardInterrupt', 'LookupError', 'MemoryError', 'NameError', 'NotImplementedError', 'OSError', 'OverflowError', 'PendingDeprecationWarning', 'ReferenceError', 'RuntimeError', 'RuntimeWarning', 'StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError', 'TypeError', 'UnboundLocalError', 'UnicodeDecodeError', 'UnicodeEncodeError', 'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserWarning', 'ValueError', 'Warning', 'ZeroDivisionError', ] if _compat.IS_PY2: _safe_names.extend([ 'basestring', 'cmp', 'long', 'unichr', 'unicode', 'xrange', ]) _safe_exceptions.extend([ 'StandardError', ]) else: _safe_names.extend([ '__build_class__', # needed to define new classes ]) for name in _safe_names: safe_builtins[name] = getattr(builtins, name) for name in _safe_exceptions: safe_builtins[name] = getattr(builtins, name) # Wrappers provided by this module: # delattr # setattr # Wrappers provided by ZopeGuards: # __import__ # apply # dict # enumerate # filter # getattr # hasattr # iter # list # map # max # min # sum # all # any # Builtins that are intentionally disabled # compile - don't let them produce new code # dir - a general purpose introspector, probably hard to wrap # execfile - no direct I/O # file - no direct I/O # globals - uncontrolled namespace access # input - no direct I/O # locals - uncontrolled namespace access # open - no direct I/O # raw_input - no direct I/O # vars - uncontrolled namespace access # There are several strings that describe Python. I think there's no # point to including these, although they are obviously safe: # copyright, credits, exit, help, license, quit # Not provided anywhere. Do something about these? Several are # related to new-style classes, which we are too scared of to support # <0.3 wink>. coerce, buffer, and reload are esoteric enough that no # one should care. # buffer # bytes # bytearray # classmethod # coerce # eval # intern # memoryview # object # property # reload # staticmethod # super # type def _write_wrapper(): # Construct the write wrapper class def _handler(secattr, error_msg): # Make a class method. def handler(self, *args): try: f = getattr(self.ob, secattr) except AttributeError: raise TypeError(error_msg) f(*args) return handler class Wrapper(object): def __init__(self, ob): self.__dict__['ob'] = ob __setitem__ = _handler( '__guarded_setitem__', 'object does not support item or slice assignment') __delitem__ = _handler( '__guarded_delitem__', 'object does not support item or slice assignment') __setattr__ = _handler( '__guarded_setattr__', 'attribute-less object (assign or del)') __delattr__ = _handler( '__guarded_delattr__', 'attribute-less object (assign or del)') return Wrapper def _full_write_guard(): # Nested scope abuse! # safetypes and Wrapper variables are used by guard() safetypes = {dict, list} Wrapper = _write_wrapper() def guard(ob): # Don't bother wrapping simple types, or objects that claim to # handle their own write security. if type(ob) in safetypes or hasattr(ob, '_guarded_writes'): return ob # Hand the object to the Wrapper instance, then return the instance. return Wrapper(ob) return guard full_write_guard = _full_write_guard() def guarded_setattr(object, name, value): setattr(full_write_guard(object), name, value) safe_builtins['setattr'] = guarded_setattr def guarded_delattr(object, name): delattr(full_write_guard(object), name) safe_builtins['delattr'] = guarded_delattr def safer_getattr(object, name, default=None, getattr=getattr): """Getattr implementation which prevents using format on string objects. format() is considered harmful: http://lucumr.pocoo.org/2016/12/29/careful-with-str-format/ """ if isinstance(object, _compat.basestring) and name == 'format': raise NotImplementedError( 'Using format() on a %s is not safe.' % object.__class__.__name__) if name.startswith('_'): raise AttributeError( '"{name}" is an invalid attribute name because it ' 'starts with "_"'.format(name=name) ) return getattr(object, name, default) safe_builtins['_getattr_'] = safer_getattr def guarded_iter_unpack_sequence(it, spec, _getiter_): """Protect sequence unpacking of targets in a 'for loop'. The target of a for loop could be a sequence. For example "for a, b in it" => Each object from the iterator needs guarded sequence unpacking. """ # The iteration itself needs to be protected as well. for ob in _getiter_(it): yield guarded_unpack_sequence(ob, spec, _getiter_) def guarded_unpack_sequence(it, spec, _getiter_): """Protect nested sequence unpacking. Protect the unpacking of 'it' by wrapping it with '_getiter_'. Furthermore for each child element, defined by spec, guarded_unpack_sequence is called again. Have a look at transformer.py 'gen_unpack_spec' for a more detailed explanation. """ # Do the guarded unpacking of the sequence. ret = list(_getiter_(it)) # If the sequence is shorter then expected the interpreter will raise # 'ValueError: need more than X value to unpack' anyway # => No childs are unpacked => nothing to protect. if len(ret) < spec['min_len']: return ret # For all child elements do the guarded unpacking again. for (idx, child_spec) in spec['childs']: ret[idx] = guarded_unpack_sequence(ret[idx], child_spec, _getiter_) return ret safe_globals = {'__builtins__': safe_builtins}

24.934169

78

0.642318

902

7,954

5.482262

0.436807

0.019414

0.0091

0.010111

0.072396

0.056623

0.016582

0

0.003323

0.2434

7,954

318

79

25.012579

0.818378

0.386849

0

0.10241

0

0.265864

0.010066

0

0.006024

1

0.066265

false

0

0.03012

0

0.174699

0

null

0

null

0

1

0

0f2d2dbffe32c783e2898f2f8436bb00cc24fbbd

1,896

py

Python

tests/integration/generic/config.py

evsmithx/cosmpy

7dfc81528b287f90190d6d4387942340f8ab88cf

[ "Apache-2.0" ]

15

2021-09-08T05:27:14.000Z

2022-03-29T06:48:08.000Z

tests/integration/generic/config.py

evsmithx/cosmpy

7dfc81528b287f90190d6d4387942340f8ab88cf

[ "Apache-2.0" ]

36

2021-09-01T08:58:33.000Z

2022-03-30T11:40:56.000Z

tests/integration/generic/config.py

evsmithx/cosmpy

7dfc81528b287f90190d6d4387942340f8ab88cf

[ "Apache-2.0" ]

4

2021-10-04T09:29:56.000Z

2022-03-18T15:43:06.000Z

# -*- coding: utf-8 -*- # ------------------------------------------------------------------------------ # # Copyright 2018-2021 Fetch.AI Limited # # 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. # # ------------------------------------------------------------------------------ """Module with config used in Fetchd integration tests.""" import inspect import os from pathlib import Path from cosmpy.crypto.address import Address from cosmpy.crypto.keypairs import PrivateKey from cosmpy.protos.cosmos.base.v1beta1.coin_pb2 import Coin # Denomination and amount of transferred tokens DENOM = "stake" AMOUNT = 1 COINS = [Coin(amount=str(AMOUNT), denom=DENOM)] # Node config GRPC_ENDPOINT_ADDRESS = "localhost:9090" REST_ENDPOINT_ADDRESS = "http://localhost:1317" CHAIN_ID = "testing" # Private key of sender account VALIDATOR_PK = PrivateKey( bytes.fromhex("0ba1db680226f19d4a2ea64a1c0ea40d1ffa3cb98532a9fa366994bb689a34ae") ) VALIDATOR_ADDRESS = Address(VALIDATOR_PK) # Private key of recipient account BOB_PK = PrivateKey( bytes.fromhex("439861b21d146e83fe99496f4998a305c83cfbc24717c77e32b06d224bf1e636") ) BOB_ADDRESS = Address(BOB_PK) # Cosmwasm CUR_PATH = os.path.dirname(inspect.getfile(inspect.currentframe())) # type: ignore CONTRACT_FILENAME = Path( os.path.join(CUR_PATH, "..", "..", "..", "contracts", "cw_erc1155.wasm") ) TOKEN_ID = "444" # nosec

32.689655

85

0.691456

226

1,896

5.725664

0.615044

0.046368

0.020093

0.02473

0

0.069682

0.137131

1,896

57

86

33.263158

0.721271

0.506857

0

0.229834

0.141436

0

1

0

false

0

0.24

0

0.24

0

null

0

null

0

1

0

0f2dd08990b19e27a9643081b1bf9f583649ad3e

505

py

Python

__scraping__/thaitrade.com/main.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

140

2017-02-21T22:49:04.000Z

2022-03-22T17:51:58.000Z

__scraping__/thaitrade.com/main.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

5

2017-12-02T19:55:00.000Z

2021-09-22T23:18:39.000Z

__scraping__/thaitrade.com/main.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

79

2017-01-25T10:53:33.000Z

2022-03-11T16:13:57.000Z

# date: 2020.12.30 # https://stackoverflow.com/questions/65503481/scraping-hidden-link-using-selenium-or-requests#65503481 from selenium import webdriver import time link = 'https://www.thaitrade.com/store/9chemical' driver = webdriver.Chrome()#executable_path=r"C:/chromedriver.exe") #, options=chrome_options) driver.maximize_window() driver.get(link) #soup = BeautifulSoup(driver.page_source, 'html.parser') time.sleep(5) website = driver.find_element_by_id('seller_website').text print(website)

31.5625

103

0.786139

69

505

5.637681

0.753623

0

0.055437

0.071287

505

15

104

33.666667

0.773987

0.475248

0

0.214008

0

1

0

false

0

0.222222

0

0.222222

0.111111

0

null

0

null

0

1

0

0f303dbb7b5651e32ad52ebcac0ace31970f110f

3,128

py

Python

S4/S4 Library/simulation/interactions/jig_part_constraint_interaction.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

1

2021-05-20T19:33:37.000Z

S4/S4 Library/simulation/interactions/jig_part_constraint_interaction.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

S4/S4 Library/simulation/interactions/jig_part_constraint_interaction.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

from interactions.base.interaction import Interaction from interactions.base.mixer_interaction import MixerInteraction from interactions.base.super_interaction import SuperInteraction from interactions.constraints import Transform, Nowhere from sims4.tuning.tunable import Tunable, TunableSet, TunableEnumWithFilter from sims4.utils import flexmethod from tag import Tag import services import sims4 logger = sims4.log.Logger('JigPartConstraintInteraction', default_owner='cjiang') class JigPartConstraintInteraction(SuperInteraction): def __init__(self, *args, jig_object=None, jig_part_index=0, **kwargs): super().__init__(*args, **kwargs) self._jig_object = jig_object self._jig_part_index = jig_part_index @flexmethod def _constraint_gen(cls, inst, sim, *args, **kwargs): yield from super()._constraint_gen(sim, *args, **kwargs) if inst is not None and inst._jig_object is not None: jig = inst._jig_object parts = jig.parts part_index = inst._jig_part_index if parts is None: logger.error("{} doesn't have part tuned", jig) yield Nowhere('Exception while trying to get routing slot on the jig part.') return if part_index >= len(parts): logger.error('{} only have {} parts, out of index {}', jig, len(parts), part_index) yield Nowhere('Exception while trying to get routing slot on the jig part.') return part = parts[part_index] yield Transform(part.transform, routing_surface=jig.routing_surface) class SynchMixerInteraction(MixerInteraction): INSTANCE_TUNABLES = {'virtual_actor_name': Tunable(description='\n The name of the virtual actor sims will be put in.\n ', tunable_type=str, default='x')} def get_asm(self, *args, **kwargs): asm = super().get_asm(*args, **kwargs) asm.remove_virtual_actors_by_name(self.virtual_actor_name) for sim in self.get_sims(): if self.sim is not sim: asm.add_virtual_actor(self.virtual_actor_name, sim) return asm def _get_required_sims(self, *args, **kwargs): sims = super()._get_required_sims(*args, **kwargs) sims.update(self.get_sims()) return sims def get_sims(self): raise NotImplementedError class SynchInSituationMixerInteraction(SynchMixerInteraction): INSTANCE_TUNABLES = {'situation_tags': TunableSet(description='\n Tags for arbitrary groupings of situation types.\n ', tunable=TunableEnumWithFilter(tunable_type=Tag, filter_prefixes=['situation'], default=Tag.INVALID, pack_safe=True))} def get_sims(self): sim_list = [] situation_manager = services.get_zone_situation_manager() situation_list = situation_manager.get_situations_by_tags(self.situation_tags) for situation in situation_list: if situation.is_sim_in_situation(self.sim): sim_list.extend(situation.all_sims_in_situation_gen()) return sim_list

46.686567

263

0.685742

380

3,128

5.405263

0.3

0.035054

0.023369

0.025316

0.064265

0

0.002066

0.226343

3,128

66

264

47.393939

0.846694

0

0.105263

0

0.131714

0.008951

0

1

0.105263

false

0

0.157895

0

0.438596

0

null

0

null

0

1

0

0f30b70b3f021de85c5431ed22d59f28be1101bb

10,633

py

Python

paxes_cinder/k2aclient/exceptions.py

windskyer/k_cinder

000ee539ee4842a158071d26ee99d12c7c0a87da

[ "Apache-2.0" ]

null

paxes_cinder/k2aclient/exceptions.py

windskyer/k_cinder

000ee539ee4842a158071d26ee99d12c7c0a87da

[ "Apache-2.0" ]

null

paxes_cinder/k2aclient/exceptions.py

windskyer/k_cinder

000ee539ee4842a158071d26ee99d12c7c0a87da

[ "Apache-2.0" ]

null

# # # All Rights Reserved. # Copyright 2010 Jacob Kaplan-Moss # 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. """ Exception definitions. """ from paxes_cinder.k2aclient import _ from paxes_k2.k2operator import K2Error from paxes_k2.k2operator import K2ConnectionError from paxes_k2.k2operator import K2SSLError from paxes_k2.k2operator import K2TimeoutError class K2aException(Exception): """Base class for exceptions for all k2aclient exceptions""" def __init__(self, msg): self.msg = msg super(K2aException, self).__init__(msg) def __unicode__(self): return unicode(self.msg) class K2aCrudException(K2aException): """Exception due to issue with K2 response""" def __init__(self, msg, k2resp, exclogger=None): diagfspec = None if exclogger is not None: diagfspec = exclogger.emit("CRUD", msg, k2resp) msg = (_("%(msg)s, exception diagnostics have" " been written to: >%(diagfspec)s<") % {"msg": msg, "diagfspec": diagfspec, }) super(K2aCrudException, self).__init__(msg) self.k2resp = k2resp self.diagfspec = diagfspec class K2aK2Other(K2aException): def __init__(self, e, addmsg=None): msg = _("Other Exception off of K2: >%s<") % e if addmsg is not None: msg = (_("%(msg)s, during: >%(addmsg)s<") % {"msg": msg, "addmsg": addmsg, }) super(K2aK2Other, self).__init__(msg) self.e = e class K2aK2SslError(K2aException): """Exceptions due to k2 SSL processing""" def __init__(self, k2error, addmsg=None): msg = _("SSL exception off of K2: >%s<") % k2error if addmsg is not None: msg = (_("%(msg)s, during: >%(addmsg)s<") % {"msg": msg, "addmsg": addmsg, }) super(K2aK2SslError, self).__init__(msg) self.k2error = k2error class K2aK2ConnectionError(K2aException): """Exceptions due to k2 connection processing""" def __init__(self, k2error, addmsg=None): msg = _("Connection exception off of K2: >%s<") % k2error if addmsg is not None: msg = (_("%(msg)s, during: >%(addmsg)s<") % {"msg": msg, "addmsg": addmsg, }) super(K2aK2ConnectionError, self).__init__(msg) self.k2error = k2error class K2aK2TimeoutError(K2aException): """Exceptions due to k2 timeout""" def __init__(self, k2error, addmsg=None): msg = _("Timeout exception off of K2: >%s<") % k2error if addmsg is not None: msg = (_("%(msg)s, during: >%(addmsg)s<") % {"msg": msg, "addmsg": addmsg, }) super(K2aK2TimeoutError, self).__init__(msg) self.k2error = k2error # TODO get list of status codes that can come off of K2 class K2aK2Error(K2aException): """ Base class for K2Error w/ response codes exceptions coming off of K2 """ def __init__(self, status, k2error, addmsg=None, k2msg=None, diagfspec=None): msg = (_("K2Error off of K2: >%(msg)s<," " Status: >%(status)d<, k2Error: >%(k2error)s<") % {"msg": self.__class__.msg, "status": status, "k2error": k2error, }) if addmsg is not None: msg = (_("%(msg)s, during: >%(addmsg)s<") % {"msg": msg, "addmsg": addmsg, }) super(K2aK2Error, self).__init__(msg) self.status = status self.k2error = k2error self.k2msg = k2msg self.diagfspec = diagfspec class K2aK2ErrorBadRequest(K2aK2Error): """ K2aK2Error HTTP 400 - The request was missing required input, had errors in the provided input, or included extraneous input. Additional information regarding the error is provided in an error response body that includes a reason code with additional information. """ http_status = 400 msg = _("Bad Request") class K2aK2ErrorUnauthorized(K2aK2Error): """ K2aK2Error HTTP 401 - Unauthorized: bad credentials. """ http_status = 401 msg = _("Unauthorized") class K2aK2ErrorForbidden(K2aK2Error): """ K2aK2Error HTTP 403 - Multiple error conditions result in this status code: - The request requires authentication but no X-API-Session header was provided, or one was provided but the session ID was invalid. - The user under which the API request was authenticated is not authorized to perform the requested operation. """ http_status = 403 msg = _("Forbidden") class K2aK2ErrorNotFound(K2aK2Error): """ K2aK2Error HTTP 404 - Multiple error conditions result in this status code: - The URI does not designate an extant resource, or designates a resource for which the API user does not have object-access permission. - The URI designates a resource or operation that is not supported by the MC because it is currently the alternate MC. """ http_status = 404 msg = _("Not Found") class K2aK2ErrorMethodNotAllowed(K2aK2Error): """ K2aK2Error HTTP 405 - The request specifies an HTTP method that is not valid for the designated URI. """ http_status = 405 msg = _("Method Not Allowed") class K2aK2ErrorNotAcceptable(K2aK2Error): """ K2aK2Error HTTP 406 - The Accept header for the request does not include at least one content representation supported by the Web Services API. """ http_status = 406 msg = _("Not Acceptable") class K2aK2ErrorConflict(K2aK2Error): """ K2aK2Error HTTP 409 - The managed resource is in an incorrect state (status) for performing the requested operation. Additional information regarding the error is provided in an error response body that includes a reason code with additional information. """ http_status = 409 msg = _("Conflict") class K2aK2ErrorPreConditionFailed(K2aK2Error): """ K2aK2Error HTTP 412 - PreCondition failed """ http_status = 412 msg = _("PreCondition failed") class K2aK2ErrorRequestBodyTooLarge(K2aK2Error): """ K2aK2Error HTTP 413 - The request includes a request body that is too large. """ http_status = 413 msg = _("Request Body Too Large") class K2aK2ErrorUnsupportedMediaType(K2aK2Error): """ K2aK2Error HTTP 415 - The Content-Type header for the request specifies a representation that is not supported by the Web Services API. """ http_status = 415 msg = _("Unsupported Media Type") class K2aK2ErrorInternaServerError(K2aK2Error): """ K2aK2Error HTTP 500 - A server error occurred during processing of the request. """ http_status = 500 msg = _("Internal Server Error") class K2aK2ErrorNotImplemented(K2aK2Error): """ K2aK2Error HTTP 501 - The request specifies an HTTP method that is not recognized by the server (for any resource). """ http_status = 501 msg = _("Not Implemented") class K2aK2ServiceUnavailable(K2aK2Error): """ K2aK2Error HTTP 503 - The request could not be carried out by the MC due to some temporary condition. """ http_status = 503 msg = _("Service Unavailable") class K2aK2HttpVersionNotSupported(K2aK2Error): """ K2aK2Error HTTP 505 - The request specifies an HTTP protocol version that is not supported by the Web Services API. """ http_status = 505 msg = _("HTTP Version Not Supported") class K2aK2ErrorUnclassified(K2aK2Error): """ HTTP ??? - Unclassified K2Error """ http_status = -1 msg = _("Not Classified") _code_to_exception_map = dict((c.http_status, c) for c in K2aK2Error.__subclasses__()) _EXCLUDED_EXCEPTIONS = [412] def create_k2a_exception_from_k2o_exception(e, addmsg=None, exclogger=None): """ Return an instance of an K2aK2Error or subclass based on an requests response. Optionally add additional message. Optionally log details of the exception. """ if not isinstance(e, K2Error): return K2aK2Other(e, addmsg) if isinstance(e, K2SSLError): return K2aK2SslError(e, addmsg) if isinstance(e, K2ConnectionError): return K2aK2ConnectionError(e, addmsg) if isinstance(e, K2TimeoutError): return K2aK2TimeoutError(e, addmsg) k2response = e.k2response # If non status_code then use -1 status = -1 if k2response is not None and k2response.status is not None: status = k2response.status # if activated place k2response in exception log diagfspec = None if (k2response is not None and exclogger is not None and status not in _EXCLUDED_EXCEPTIONS): category = "UNC" if status > -1: category = str(status) diagfspec = exclogger.emit(category, addmsg, k2response, exc=e) addmsg += (_(", exception diagnostics have been written to: >%s<") % diagfspec) cls = _code_to_exception_map.get(status, K2aK2ErrorUnclassified) k2msg = None if hasattr(k2response, 'k2err'): m = k2response.k2err.find('./Message') if m is not None: k2msg = m.text return cls(status, e, addmsg, k2msg=k2msg, diagfspec=diagfspec) ################# class K2JobFailure(K2aException): """Raised when a K2 Job fails""" def __init__(self, msg, k2resp, diagfspeci=None, diagfspec=None): super(K2JobFailure, self).__init__(msg) self.k2resp = k2resp self.diagfspeci = diagfspeci self.diagfspec = diagfspec ################# class UnsupportedVersion(K2aException): """Raised whan an unsupported version of the k2aclient is requested.""" pass class CommandError(K2aException): pass class NotFound(K2aException): pass class NoUniqueMatch(K2aException): pass

29.372928

77

0.641117

1,214

10,633

5.497529

0.252883

0.012736

0.050345

0.015733

0.253971

0.203476

0.177405

0.153281

0.135301

0.10893

0

0.040808

0.264836

10,633

361

78

29.454294

0.812972

0.32512

0

0.241176

0

0.119593

0

0.00277

0

1

0.058824

false

0.023529

0.029412

0.005882

0.458824

0

null

0

null

0

1

0

0f32f2246845e937b93ff16ba2dea08cdfb5f192

16,378

py

Python

misc/util.py

NirDiamant/pytorch-glow

2ab11f3a8486b86a279fe4fa64f25aa91226ee8a

[ "MIT" ]

null

misc/util.py

NirDiamant/pytorch-glow

2ab11f3a8486b86a279fe4fa64f25aa91226ee8a

[ "MIT" ]

null

misc/util.py

NirDiamant/pytorch-glow

2ab11f3a8486b86a279fe4fa64f25aa91226ee8a

[ "MIT" ]

1

2020-04-29T15:27:39.000Z

import os import re import cv2 import sys import glob import json import shutil import numpy as np import torch from PIL import Image from easydict import EasyDict from torchvision.transforms import transforms # Profile def load_profile(filepath): """ Load experiment profile as EasyDict :param filepath: path to profile :type filepath: str :return: hyper-parameters :rtype: EasyDict """ if os.path.exists(filepath): with open(filepath) as f: return EasyDict(json.load(f)) # Device def get_devices(devices, verbose=True): """ Get devices for running model :param devices: list of devices from profile :type devices: list :param verbose: print log :type verbose: bool :return: list of usable devices according to desired and available hardware :rtype: list[str] """ def parse_cuda_device(device): """ Parse device into device id :param device: given device :type device: str or int :return: device id :rtype: int """ origin = str(device) if isinstance(device, str) and re.search('cuda:([\d]+)', device): device = int(re.findall('cuda:([\d]+)', device)[0]) if isinstance(device, int): if 0 <= device <= torch.cuda.device_count() - 1: return device _print('[Builder] Incorrect device "{}"'.format(origin), verbose=verbose) return use_cpu = any([d.find('cpu') >= 0 for d in devices]) use_cuda = any([(d.find('cuda') >= 0 or isinstance(d, int)) for d in devices]) assert not (use_cpu and use_cuda), 'CPU and GPU cannot be mixed.' if use_cuda: devices = [parse_cuda_device(d) for d in devices] devices = [d for d in devices if d is not None] if len(devices) == 0: _print('[Builder] No available GPU found, use CPU only', verbose=verbose) devices = ['cpu'] return devices # Logger class OutputLogger(object): """Output logger""" def __init__(self): self.file = None self.buffer = '' def set_log_file(self, filename, mode='wt'): assert self.file is None self.file = open(filename, mode) if self.buffer is not None: self.file.write(self.buffer) self.buffer = None def write(self, data): if self.file is not None: self.file.write(data) if self.buffer is not None: self.buffer += data def flush(self): if self.file is not None: self.file.flush() class TeeOutputStream(object): """Redirect output stream""" def __init__(self, child_streams, autoflush=False): self.child_streams = child_streams self.autoflush = autoflush def write(self, data): if isinstance(data, bytes): data = data.decode('utf-8') for stream in self.child_streams: stream.write(data) if self.autoflush: self.flush() def flush(self): for stream in self.child_streams: stream.flush() output_logger = None def init_output_logging(): """ Initialize output logger """ global output_logger if output_logger is None: output_logger = OutputLogger() sys.stdout = TeeOutputStream([sys.stdout, output_logger], autoflush=True) sys.stderr = TeeOutputStream([sys.stderr, output_logger], autoflush=True) def set_output_log_file(filename, mode='wt'): """ Set file name of output log :param filename: file name of log :type filename: str :param mode: the mode in which the file is opened :type mode: str """ if output_logger is not None: output_logger.set_log_file(filename, mode) # Result directory def create_result_subdir(result_dir, desc, profile): """ Create and initialize result sub-directory :param result_dir: path to root of result directory :type result_dir: str :param desc: description of current experiment :type desc: str :param profile: profile :type profile: dict :return: path to result sub-directory :rtype: str """ result_dir = 'results' # determine run id run_id = 0 for fname in glob.glob(os.path.join(result_dir, '*')): fbase = os.path.basename(fname) finds = re.findall('^([\d]+)-', fbase) if len(finds) != 0: ford = int(finds[0]) run_id = max(run_id, ford + 1) # create result sub-directory result_subdir = os.path.join(result_dir, '{:03d}-{:s}'.format(run_id, desc)) if not os.path.exists(result_subdir): os.makedirs(result_subdir) set_output_log_file(os.path.join(result_subdir, 'log.txt')) print("[Builder] Saving results to {}".format(result_subdir)) # export profile with open(os.path.join(result_subdir, 'config.json'), 'w') as f: json.dump(profile, f) return result_subdir def locate_result_subdir(result_dir, run_id_or_result_subdir): """ Locate result subdir by given run id or path :param result_dir: path to root of result directory :type result_dir: str :param run_id_or_result_subdir: run id or subdir path :type run_id_or_result_subdir: int or str :return: located result subdir :rtype: str """ # if isinstance(run_id_or_result_subdir, str) and os.path.isdir(run_id_or_result_subdir): # return run_id_or_result_subdir # # searchdirs = ['', 'results', 'networks'] # # for searchdir in searchdirs: # d = result_dir if searchdir == '' else os.path.join(result_dir, searchdir) # # search directly by name # d = os.path.join(d, str(run_id_or_result_subdir)) # if os.path.isdir(d): # return d # # search by prefix # if isinstance(run_id_or_result_subdir, int): # prefix = '{:03d}'.format(run_id_or_result_subdir) # else: # prefix = str(run_id_or_result_subdir) # dirs = sorted(glob.glob(os.path.join(result_dir, searchdir, prefix + '-*'))) # dirs = [d for d in dirs if os.path.isdir(d)] # if len(dirs) == 1: # return dirs[0] # print('[Builder] Cannot locate result subdir for run: {}'.format(run_id_or_result_subdir)) # return None return result_dir def format_time(seconds): """ Format seconds into desired format :param seconds: number of seconds :type seconds: float :return: formatted time :rtype: str """ s = int(np.rint(seconds)) if s < 60: return '{:d}s'.format(s) elif s < 60 * 60: return '{:d}m {:02d}s'.format(s // 60, s % 60) elif s < 24 * 60 * 60: return '{:d}h {:02d}m {:02}ds'.format(s // (60 * 60), (s // 60) % 60, s % 60) else: return '{:d}d {:02d}h {:02d}m'.format(s // (24 * 60 * 60), (s // (60 * 60)) % 24, (s // 60) % 60) # Model def get_model_name(step): """ Return filename of model snapshot by step :param step: global step of model :type step: int :return: model snapshot file name :rtype: str """ return 'network-snapshot-{:06d}.pth'.format(step) def get_best_model_name(): """ Return filename of best model snapshot by step :return: filename of best model snapshot :rtype: str """ return 'network-snapshot-best.pth' def get_last_model_name(result_subdir): """ Return filename of best model snapshot by step :param result_subdir: path to result sub-directory :type result_subdir: str :return: filename of last model snapshot :rtype: str """ latest = -1 for f in os.listdir(result_subdir): if os.path.isfile(os.path.join(result_subdir, f)) and \ re.search('network-snapshot-([\d]+).pth', f): f_step = int(re.findall('network-snapshot-([\d]+).pth', f)[0]) if latest < f_step: latest = f_step return get_model_name(latest) def save_model(result_subdir, step, graph, optimizer, seconds, is_best, criterion_dict=None): """ Save model snapshot to result subdir :param result_subdir: path to result sub-directory :type result_subdir: str :param step: global step of model :type step: int :param graph: model graph :type graph: torch.nn.Module :param optimizer: optimizer :type optimizer: torch.optim.Optimizer :param seconds: seconds of running time :type seconds: float :param is_best: whether this model is best :type is_best: bool :param criterion_dict: dict of criterion :type criterion_dict: dict """ # construct state state = { 'step': step, # DataParallel wraps model in `module` attribute. 'graph': graph.module.state_dict() if hasattr(graph, "module") else graph.state_dict(), 'optimizer': optimizer.state_dict(), 'criterion': {}, 'seconds': seconds } if criterion_dict is not None: state['criterion'] = {k: v.state_dict() for k, v in criterion_dict.items()} # save current state save_path = os.path.join(result_subdir, get_model_name(step)) torch.save(state, save_path) # save best state if is_best: best_path = os.path.join(result_subdir, get_best_model_name()) shutil.copy(save_path, best_path) def load_model(result_subdir, step_or_model_path, graph, optimizer=None, criterion_dict=None, device=None): """ lOad model snapshot from esult subdir :param result_subdir: path to result sub-directory :type result_subdir: str :param step_or_model_path: step or model path :type step_or_model_path: int or str :param graph: model graph :type graph: torch.nn.Module :param optimizer: optimizer :type optimizer: torch.optim.Optimizer :param criterion_dict: dict of criterion :type criterion_dict: dict :param device: device to run mode :type device: str :return: state :rtype: dict """ # check existence of model file model_path = step_or_model_path if isinstance(step_or_model_path, int): model_path = get_model_name(step_or_model_path) if step_or_model_path == 'best': model_path = get_best_model_name() if step_or_model_path == 'latest': model_path = None if not os.path.exists(model_path): model_path = os.path.join(result_subdir, model_path) if not os.path.exists(model_path): raise FileNotFoundError('Failed to find model snapshot with {}'.format(step_or_model_path)) # load model snapshot if isinstance(device, int): device = 'cuda:{}'.format(device) state = torch.load(model_path, map_location=device) step = state['step'] graph.load_state_dict(state['graph']) graph.set_actnorm_inited() if optimizer is not None: optimizer.load_state_dict(state['optimizer']) if criterion_dict is not None: for k in criterion_dict.keys(): criterion_dict[k].load_state_dict(state['criterion'][k]) print('[Builder] Load model snapshot successfully from {}'.format(model_path)) return state # Dataset def is_image(filepath): """ Determine whether file is an image or not :param filepath: file path :type filepath: str :return: whether file is an image :rtype: bool """ image_extensions = ['.png', '.jpg', '.jpeg'] basename = os.path.basename(filepath) _, extension = os.path.splitext(basename) return extension.lower() in image_extensions def tensor_to_ndarray(tensor): """ Convert float tensor into numpy image :param tensor: input tensor :type tensor: torch.Tensor :return: numpy image :rtype: np.ndarray """ tensor_np = tensor.permute(1, 2, 0).cpu().numpy() tensor_np = tensor_np.astype(np.float32) tensor_np = (tensor_np * 255).astype(np.uint8) return tensor_np def tensor_to_pil(tensor): """ Convert float tensor into PIL image :param tensor: input tensor :type tensor: torch.Tensor :return: PIL image :rtype: Image.Image """ transform = transforms.ToPILImage() tensor = tensor.cpu() return transform(tensor) def ndarray_to_tensor(img, shape=(128, 128, 3), bgr2rgb=True): """ Convert numpy image to float tensor :param img: numpy image :type img: np.ndarray :param shape: image shape in (H, W, C) :type shape: tuple or list :param bgr2rgb: convert color space from BGR to RGB :type bgr2rgb: bool :return: tensor :rtype: torch.Tensor """ if bgr2rgb: img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) img = cv2.resize(img, (shape[0], shape[1])) img = (img / 255.0).astype(np.float32) img = torch.Tensor(img).permute(2, 0, 1) return img def pil_to_tensor(img, shape=(128, 128, 3), transform=None): """ Convert PIL image to float tensor :param img: PIL image :type img: Image.Image :param shape: image shape in (H, W, C) :type shape: tuple or list :param transform: image transform :return: tensor :rtype: torch.Tensor """ if transform is None: transform = transforms.Compose(( transforms.Resize(shape[0]), transforms.ToTensor() )) return transform(img) def image_to_tensor(img, shape=(128, 128, 3), bgr2rgb=True): """ Convert image to torch tensor :param img: image :type img: Image.Image or np.ndarray :param shape: image shape in (H, W, C) :type shape: tuple or list :param bgr2rgb: convert color space from BGR to RGB :type bgr2rgb: bool :return: image tensor :rtype: torch.Tensor """ if isinstance(img, Image.Image): return pil_to_tensor(img, shape) if isinstance(np.ndarray, img): return ndarray_to_tensor(img, shape, bgr2rgb) else: raise NotImplementedError('Unsupported image type: {}'.format(type(img))) def save_deltaz(deltaz, save_dir): """ Save deltaz as numpy :param deltaz: delta vector of attributes in latent space :type deltaz: np.ndarray :param save_dir: directory to save :type save_dir: str """ check_path(save_dir) np.save(os.path.join(save_dir, 'deltaz.npy'), deltaz) def load_deltaz(path): """ Load deltaz as numpy :param path: path to numpy file :type path: str :return: delta vector of attributes in latent space :rtype: np.ndarray """ if os.path.exists(path): return np.load(path) # Misc def manual_seed(seed): """ Set manual random seed :param seed: random seed :type seed: int """ np.random.seed(seed) torch.manual_seed(seed) # torch.cuda.manual_seed_all(seed) def _print(*args, verbose=True, **kwargs): """ Print with condition :param verbose: whether to verbose or not :type verbose: bool """ if verbose: print(*args, **kwargs) def check_path(path): """ Check existence of directory path. If not, then create it. :param path: path to directory :type path: str """ if not os.path.exists(path): os.makedirs(path) def make_batch(tensor, batch_size): """ Generate fake batch :param tensor: input tensor :type tensor: torch.Tensor :param batch_size: batch size :type batch_size: int :return: fake batch :rtype: torch.Tensor """ assert len(tensor.shape) == 3, 'Assume 3D input tensor' return tensor.unsqueeze(0).repeat(batch_size, 1, 1, 1) def make_interpolation_vector(num_classes, step=0.25, minimum=-1., maximum=1.): """ Generate interpolation vector :param num_classes: number of classes :type num_classes: int :param step: increasing step :type step: float :param minimum: minimum value :type minimum: float :param maximum: maximum value :type maximum: float :return: interpolation vector :rtype: np.ndarray """ num_levels = int((maximum - minimum) / step) + 1 levels = [-1. + step * i for i in range(num_levels)] interpolation_vector = np.zeros([num_classes, num_levels, num_classes]) for cls in range(num_classes): for lv in range(num_levels): interpolation_vector[cls, lv, cls] = levels[lv] return interpolation_vector

27.665541

107

0.634632

2,221

16,378

4.550203

0.135525

0.045122

0.009005

0.01415

0.304176

0.229765

0.177123

0.133881

0.116564

0.110133

0

0.011561

0.255343

16,378

591

108

27.712352

0.817071

0.368665

0

0.081081

0

0.069106

0.011589

0

0.013514

1

0.148649

false

0

0.054054

0

0.31982

0.027027

0

null

0

null

0

1

0

0f331a2bbebd94fbbed32bbf0c22269547b1ac25

5,096

py

Python

icinga2api/base.py

wftech/python-icinga2api

f47b8e5903f5035353082f07f8d5077fecdbd5c9

[ "BSD-2-Clause" ]

null

icinga2api/base.py

wftech/python-icinga2api

f47b8e5903f5035353082f07f8d5077fecdbd5c9

[ "BSD-2-Clause" ]

null

icinga2api/base.py

wftech/python-icinga2api

f47b8e5903f5035353082f07f8d5077fecdbd5c9

[ "BSD-2-Clause" ]

1

2020-05-05T11:37:12.000Z

# -*- coding: utf-8 -*- ''' Copyright 2017 fmnisme@gmail.com Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Icinga 2 API client base ''' from __future__ import print_function import logging import sys import requests # pylint: disable=import-error,no-name-in-module if sys.version_info >= (3, 0): from urllib.parse import urljoin else: from urlparse import urljoin # pylint: enable=import-error,no-name-in-module from icinga2api.exceptions import Icinga2ApiException LOG = logging.getLogger(__name__) class Base(object): ''' Icinga 2 API Base class ''' base_url_path = None # 继承 def __init__(self, manager): ''' initialize object ''' self.manager = manager self.stream_cache = "" def _create_session(self, method='POST'): ''' create a session object ''' session = requests.Session() # prefer certificate authentification if self.manager.certificate and self.manager.key: # certificate and key are in different files session.cert = (self.manager.certificate, self.manager.key) elif self.manager.certificate: # certificate and key are in the same file session.cert = self.manager.certificate elif self.manager.username and self.manager.password: # use username and password session.auth = (self.manager.username, self.manager.password) session.headers = { 'User-Agent': 'Python-icinga2api/{0}'.format(self.manager.version), 'X-HTTP-Method-Override': method.upper(), 'Accept': 'application/json' } return session def _request(self, method, url_path, payload=None, stream=False): ''' make the request and return the body :param method: the HTTP method :type method: string :param url_path: the requested url path :type url_path: string :param payload: the payload to send :type payload: dictionary :returns: the response as json :rtype: dictionary ''' request_url = urljoin(self.manager.url, url_path) LOG.debug("Request URL: %s", request_url) # create session session = self._create_session(method) # create arguments for the request request_args = { 'url': request_url, 'timeout': self.manager.timeout, } if payload: request_args['json'] = payload if self.manager.ca_certificate: request_args['verify'] = self.manager.ca_certificate else: request_args['verify'] = False if stream: request_args['stream'] = True # do the request response = session.post(**request_args) if not stream: session.close() # # for debugging # from pprint import pprint # pprint(request_url) # pprint(payload) # pprint(response) if not 200 <= response.status_code <= 299: raise Icinga2ApiException( 'Request "{}" failed with status {}: {}'.format( response.url, response.status_code, response.text, )) if stream: return response else: return response.json() @staticmethod def _get_message_from_stream(stream): ''' make the request and return the body :param stream: the stream :type method: request :returns: the message :rtype: dictionary ''' # TODO: test iter_lines() message = [] for char in stream.iter_content(): if char == b'\n': yield b''.join(message) message = [] else: message.append(char)

31.652174

79

0.634419

596

5,096

5.347315

0.385906

0.058676

0.027612

0.014434

0.129903

0.080326

0.064638

0.042673

0

0.006061

0.287677

5,096

160

80

31.85

0.871901

0.431515

0

0.117647

0

0.062196

0.016111

0

0.00625

0

1

0.058824

false

0.029412

0.102941

0

0.235294

0.014706

0

null

0

null

0

1

0

0f36583faead235efbf9e5d323d62677a00d5973

1,866

py

Python

decode.py

somdipdey/SmartNoshWaste

77150e7a3d308ae466fd1bbc676f3e1f4a39fb2e

[ "MIT" ]

1

2021-04-27T18:01:09.000Z

decode.py

somdipdey/SmartNoshWaste

77150e7a3d308ae466fd1bbc676f3e1f4a39fb2e

[ "MIT" ]

null

decode.py

somdipdey/SmartNoshWaste

77150e7a3d308ae466fd1bbc676f3e1f4a39fb2e

[ "MIT" ]

null

# pip install pyzbar from pyzbar.pyzbar import decode from PIL import Image import hashlib # function to return key for any value def get_key(val, dict): for key, value in dict.items(): if val == value: return key return "key doesn't exist" #create the Food class class Food: def __init__(self, name, variety, farm, size, production_date, expiry_date): self.name = name self.variety = variety self.farm = farm self.size = size self.production_date = production_date self.expiry_date = expiry_date self.info = name + ";" + variety + ";" + farm + ";" + size + ";" + production_date + ";" + expiry_date #create a dictionary of framers with their unique has code farmers_dict = { "BOYDELLS DAIRY FARM": str(hashlib.sha256("BOYDELLS DAIRY FARM".encode()).hexdigest()), "Foxes Farm Produce": str(hashlib.sha256("Foxes Farm Produce".encode()).hexdigest()), "Spinningdale Farm (Essex) Ltd": str(hashlib.sha256("Spinningdale Farm (Essex) Ltd".encode()).hexdigest()) } #qr = qrtools.QR() #qr.decode("qrcode_apple.png") qr = decode(Image.open('qrcode_milk.png')) print(qr[0].data) #data = "apple;gala apple;640bf572c70d06fd1d92137c5b6f69bf6f098842993032f0ca7585323407387a;2020-07-11;2020-08-10;f23f6da1e096620df2db706f55e5d9f4a59ec30f8eb3580b23a68ca15157930e" decoded_item = str(qr[0].data).split(";") farm = get_key(decoded_item[2], farmers_dict) food_item = Food(decoded_item[0], decoded_item[1], farm, decoded_item[3], decoded_item[4], decoded_item[5]) #print info of the food items print("Item name: " + food_item.name + "\n") print("Variety: " + food_item.variety + "\n") print("Farm: " + food_item.farm + "\n") print("Size: " + food_item.size + "\n") print("Production date: " + food_item.production_date + "\n") print("Expiry date: " + food_item.expiry_date + "\n")

37.32

178

0.692926

250

1,866

5.036

0.352

0.06116

0.03336

0.030183

0.068308

0

0.076874

0.163451

1,866

49

179

38.081633

0.72966

0.205788

0

0.165648

0

1

0.060606

false

0

0.090909

0

0.242424

0.212121

0

null

0

null

0

1

0

0f3998d39a2c170485e2967bb1cce29713b51dd3

2,528

py

Python

tests/inverse_kinematics_solutions.py

dmklee/nuro-arm

78a21e17e0140ed73c022bd5e5caef8a71470f21

[ "MIT" ]

4

2021-12-29T20:34:39.000Z

2022-01-30T22:41:33.000Z

tests/inverse_kinematics_solutions.py

dmklee/learning-robotics

bd8f6d3db97f3f6db78c16e228a4b8e7770554d5

[ "MIT" ]

19

2021-05-02T00:34:18.000Z

2021-07-16T21:19:51.000Z

tests/inverse_kinematics_solutions.py

dmklee/nuro-arm

78a21e17e0140ed73c022bd5e5caef8a71470f21

[ "MIT" ]

4

2021-08-24T18:25:04.000Z

2022-02-27T19:54:16.000Z

import pybullet as pb import time from neu_ro_arm.robot.robot_arm import RobotArm from neu_ro_arm.constants import cube_size PI = 3.141592653589793 robot = RobotArm('sim') robot.set_gripper_state(0.5) client = robot.controller._client pb.setGravity(0,0,0,client) # create id_ = pb.createVisualShape(pb.GEOM_BOX, halfExtents=3*[cube_size/2], rgbaColor=[0.1,0.1,0.8,0.5]) pos_body = [0, 0, 0] body = pb.createMultiBody(1, -1, id_, pos_body) d_toggle = pb.addUserDebugParameter('toggle orientation specification', 1, 0, 0, physicsClientId=client) dbg_params = { 'pitch': pb.addUserDebugParameter('gripper_pitch', rangeMin=0, rangeMax=PI, startValue= 2*PI, physicsClientId=client), 'roll' : pb.addUserDebugParameter('gripper_roll', rangeMin=-PI/2, rangeMax= PI/2, startValue= 0.0, physicsClientId=client), 'x' : pb.addUserDebugParameter('cube_x', rangeMin=0., rangeMax= 0.25, startValue= 0.15, physicsClientId=client), 'y' : pb.addUserDebugParameter('cube_y', rangeMin=-0.15, rangeMax= 0.15, startValue= 0.0, physicsClientId=client), 'z' : pb.addUserDebugParameter('cube_z', rangeMin=cube_size/2, rangeMax= 0.45, startValue= 0.2, physicsClientId=client), } dbg_values = {d:pb.readUserDebugParameter(i, physicsClientId=client) for d,i in dbg_params.items()} while True: button_val = pb.readUserDebugParameter(d_toggle, physicsClientId=client) reset_cube = False move_arm = False for name, prm in dbg_params.items(): new_val = pb.readUserDebugParameter(prm, physicsClientId=client) if abs(new_val-dbg_values[name]) > 1e-4: dbg_values[name] = new_val if name in 'xyz': reset_cube = True move_arm = True elif name in ('pitch', 'roll') and button_val % 2 == 1: move_arm = True pos = (dbg_values['x'],dbg_values['y'],dbg_values['z']) if reset_cube: pb.resetBasePositionAndOrientation(body, pos, (0,0,0,1),physicsClientId=client) if move_arm: if button_val % 2 == 0: robot.move_hand_to(pos) else: robot.move_hand_to(pos, (dbg_values['pitch'],dbg_values['roll'])) time.sleep(1) print('done') time.sleep(0.1)

38.892308

87

0.599288

310

2,528

4.722581

0.283871

0.143443

0.006148

0.047131

0.069672

0

0.04355

0.282437

2,528

64

88

39.5

0.763506

0.002373

0

0.072727

0

0.046825

0

1

0

false

0

0.072727

0

0.072727

0.018182

0

null

0

null

0

1

0

0f3c5bd2ec280fd81609df6042a1145ce063d8ea

3,360

py

Python

komadu_client/models/model_creator.py

Data-to-Insight-Center/CKN

8cb8f54119061386f016535612f290a0dee86b02

[ "Apache-2.0" ]

null

komadu_client/models/model_creator.py

Data-to-Insight-Center/CKN

8cb8f54119061386f016535612f290a0dee86b02

[ "Apache-2.0" ]

null

komadu_client/models/model_creator.py

Data-to-Insight-Center/CKN

8cb8f54119061386f016535612f290a0dee86b02

[ "Apache-2.0" ]

null

from komadu_client.models.ingest_models import entityType, fileType, activityType, serviceInformationType, \ instanceOfType, \ usageType, activityEntityType, generationType, addAttributesType from komadu_client.util.association_enums import AssociationEnum from komadu_client.util.util import get_node_id, get_attributes from komadu_client.util.constants import DUMMY_MD5 from datetime import datetime def create_file_entity(filename, file_uri, attributes=None, location=None, created_date=None, owner=None, size=None): entity = entityType() file = fileType() file.fileName = filename file.fileURI = str(file_uri) file.md5sum = DUMMY_MD5 if created_date is not None: file.createDate = created_date else: file.createDate = datetime.now() if owner is not None: file.ownerDN = owner if size is not None: file.size = size entity.file = file if location is not None: entity.location = location if attributes is not None: entity.attributes = attributes return entity def create_workflow_activity(workflow_id, node_id, service_id, instance_workflow, instance_version, instance_creation_time, location, attributes=None): activity = activityType() activity.location = location instance_of = instanceOfType() instance_of.creationTime = instance_creation_time instance_of.instanceOfID = instance_workflow instance_of.version = instance_version service_info = serviceInformationType() service_info.instanceOf = instance_of service_info.serviceID = service_id service_info.workflowID = workflow_id service_info.workflowNodeID = node_id if attributes is not None: service_info.attributes = attributes activity.serviceInformation = service_info return activity def get_activity_entity(activity, entity, timestamp, activity_id, entity_id, type=AssociationEnum.USAGE, attributes=None): relationship = activityEntityType() relationship.activity = activity relationship.entity = entity if type is AssociationEnum.GENERATION: generation = generationType() __populate_relation(activity_id, entity_id, generation, timestamp, attributes) relationship.generation = generation elif type is AssociationEnum.USAGE: usage = usageType() __populate_relation(activity_id, entity_id, usage, timestamp, attributes) relationship.usage = usage return relationship def __populate_relation(activity_id, entity_id, relation, timestamp, attributes=None): relation.activityID = activity_id relation.entityID = entity_id relation.timestamp = timestamp if attributes is not None: relation.attributes = attributes def add_attributes_activity(workflow_id, node_id, key, value, attributes=None): workflow_node_id = get_node_id(workflow_id, node_id) new_attr_doc = addAttributesType() new_attr_doc.objectID = workflow_node_id new_attr_doc.objectType = "ACTIVITY" new_attr_doc.notificationTimestamp = datetime.now() if attributes is None: new_attributes = {key: value} new_attr_doc.attributes = get_attributes(new_attributes) else: new_attr_doc.attributes = attributes return new_attr_doc

35

108

0.732738

379

3,360

6.242744

0.224274

0.020287

0.026627

0.030431

0.10355

0.043111

0

0.001122

0.204464

3,360

95

109

35.368421

0.884025

0

0.064935

0

0.002381

0

1

0.064935

false

0

0.064935

0

0.181818

0

null

0

null

0

1

0

0f3d939e1f04e87cf10ce18e1ac2a71fb2a8f407

2,204

py

Python

tests/test_docs.py

TimSimpson/frontdoor

b4770ed6c66366383b479975ff53abd50d2acd96

[ "CC0-1.0", "MIT" ]

null

tests/test_docs.py

TimSimpson/frontdoor

b4770ed6c66366383b479975ff53abd50d2acd96

[ "CC0-1.0", "MIT" ]

null

tests/test_docs.py

TimSimpson/frontdoor

b4770ed6c66366383b479975ff53abd50d2acd96

[ "CC0-1.0", "MIT" ]

1

2017-02-23T18:20:35.000Z

import os import sys import pytest ROOT = os.path.dirname(os.path.realpath(__file__)) if sys.version_info[0] >= 3: def from_root(path): # type: (str) -> str """Returns a path relative to the root directory.""" if os.name == 'nt': path = path.replace('/', '\\') return os.path.join(ROOT, path) def get_code_text_from_in_readme_md(ext): result = [] record = False with open(from_root('../README.md'), 'r') as f: for line in f.readlines(): if '```' in line: if '```{}'.format(ext) in line: record = True else: record = False elif record: result.append(line.strip()) return '\n'.join(result) def get_ci_py_code_in_readme_md(): return get_code_text_from_in_readme_md('py3') def read_ci_py(): with open(from_root('../ci.py'), 'r') as file: return '\n'.join(line.strip() for line in file.readlines()) def test_readme_python_snippet_is_correct(): """ The stand alone ci.py is run through pep8 and mypy, so it's best to make sure README.md matches it. """ expected = read_ci_py() actual = get_ci_py_code_in_readme_md() assert expected == actual def get_ci_py_no_arg_output_in_readme_md(): return get_code_text_from_in_readme_md('bash') def get_actual_ci_py_no_arg_output(monkeypatch, capsys): import ci monkeypatch.setattr(sys, 'argv', ['ci.py']) with pytest.raises(SystemExit): ci.main() out, err = capsys.readouterr() return '\n'.join( ['$ python ci.py'] + [line.strip() for line in out.split('\n')] ) def test_readme_example_output_is_correct(monkeypatch, capsys): """ This runs the actual ci.py script with no args to make sure the output matches what's shown in README.md. """ expected = get_ci_py_no_arg_output_in_readme_md() actual = get_actual_ci_py_no_arg_output(monkeypatch, capsys) assert expected == actual

31.042254

78

0.57441

296

2,204

4.006757

0.344595

0.043845

0.067454

0.030354

0.255481

0.225126

0.177066

0.06914

0

0.002635

0.311252

2,204

70

79

31.485714

0.778656

0.123412

0

0.086957

0

0.039163

0

0.043478

1

0.173913

false

0

0.086957

0.043478

0.391304

0

null

0

null

0

1

0

0f3d9e11e63c47d832dad04123d10ac7e6934e64

2,065

py

Python

private_sdk/signature.py

teambge/bge-private-sdk

b27d4a6caf35bcb89a260938260fd75dba173311

[ "MIT" ]

null

private_sdk/signature.py

teambge/bge-private-sdk

b27d4a6caf35bcb89a260938260fd75dba173311

[ "MIT" ]

null

private_sdk/signature.py

teambge/bge-private-sdk

b27d4a6caf35bcb89a260938260fd75dba173311

[ "MIT" ]

null

#-*- coding: utf-8 -*- from base64 import b64encode from datetime import datetime, timezone, timedelta from uuid import uuid4 try: from urllib import quote, quote_plus except ImportError: from urllib.parse import quote, quote_plus import string import hmac class Signature(object): salt = string.ascii_letters def __init__(self, client_secret, expiration_time=300): self.client_secret = client_secret self.expiration_time = expiration_time def get_timestamp(self): return datetime.now(tz=timezone.utc).strftime('%Y-%m-%dT%H:%M:%SZ') def is_expired(self, timestamp): now = datetime.now(tz=timezone.utc) timestamp = datetime.strptime( timestamp, '%Y-%m-%dT%H:%M:%SZ').replace(tzinfo=timezone.utc) return now > (timestamp + timedelta(seconds=self.expiration_time)) def get_sign_nonce(self): return uuid4().hex def _get_stringtosign(self, params): t = [] items = list(params.items()) items.sort(key=lambda i: i[0]) for key, value in items: if value is None: continue key = quote_plus(key) value = quote_plus(str(value)) value = value.replace('%7E', '~').replace('+', '%20') t.append('%s=%s' % (key, value)) qs = '&'.join(t) qs = quote_plus(qs).replace('%7E', '~').replace('+', '%20') return qs def _make_signed_string(self, params): text = self._get_stringtosign(params) message = '&'.join([self.salt, text]) key = (self.client_secret + '&').encode('utf-8') message = message.encode('utf-8') h = hmac.new(key, message, digestmod='sha1') return b64encode(h.digest()).decode('utf-8') def sign(self, params): return self._make_signed_string(params) def verify(self, params, signed_string): timestamp = params['timestamp'] if self.is_expired(timestamp): return False return self._make_signed_string(params) == signed_string

31.287879

75

0.614528

257

2,065

4.789883

0.354086

0.036556

0.038993

0.032494

0.103981

0.064988

0

0.014848

0.249879

2,065

65

76

31.769231

0.779858

0.010169

0

0.043074

0

1

0.156863

false

0

0.156863

0.058824

0.509804

0

null

0

null

0

1

0

0f3e7e1d153c48efd2c180d30f0e1eb79462c023

1,610

py

Python

src/post_comment/app.py

datasetu/eventbridge-integration-solution-zendesk-attachment-processing

d3bf1d69154adfe6acc8b44cb0d8d27bc1eef95f

[ "MIT-0" ]

2

2020-11-23T16:35:13.000Z

2021-10-30T17:42:25.000Z

src/post_comment/app.py

datasetu/eventbridge-integration-solution-zendesk-attachment-processing

d3bf1d69154adfe6acc8b44cb0d8d27bc1eef95f

[ "MIT-0" ]

null

src/post_comment/app.py

datasetu/eventbridge-integration-solution-zendesk-attachment-processing

d3bf1d69154adfe6acc8b44cb0d8d27bc1eef95f

[ "MIT-0" ]

3

2020-06-27T04:49:03.000Z

2021-10-30T17:42:13.000Z

import os import json from zenpy.lib.api_objects import Comment from zenpy import Zenpy #importing zenpy (https://github.com/facetoe/zenpy) def lambda_handler(event, context): output = merge_branch_output(event) text_detected_body, images_detected_body = assemble_message_body(output) zenpy_update_ticket(output, text_detected_body, images_detected_body) return def merge_branch_output(event): text_branch_output = event[0] image_branch_output = event[1] output = {**text_branch_output, **image_branch_output} return output def assemble_message_body(output): if output['image_labels_detected'] == True: images_detected_body = f"Main images detected: {output['attachment_images']}" else: images_detected_body = "No images detected" if output['text_detected'] == True: text_detected_body = f"Text detected: {output['attachment_text']}" else: text_detected_body = "No text detected" return text_detected_body, images_detected_body def zenpy_update_ticket(output, text_detected_body, images_detected_body): credentials = { 'email': os.environ['ZENDESK_EMAIL'], 'token': os.environ['ZENDESK_TOKEN'], 'subdomain': os.environ['ZENDESK_SUBDOMAIN'] } zenpy_client = Zenpy(**credentials) ticket = zenpy_client.tickets(id=output['attachment_data']['ticket_id']) ticket.comment = Comment(body=text_detected_body, html_body='<h4>Attachment processed by Amazon Textract & Amazon Rekognition</h4>{}{}'.format(images_detected_body, text_detected_body), public=False) zenpy_client.tickets.update(ticket) return

29.272727

214

0.754037

211

1,610

5.440758

0.298578

0.156794

0.111498

0.076655

0.200348

0.158537

0.099303

0

0.002872

0.134783

1,610

55

215

29.272727

0.821249

0.031056

0

0.114286

0

0.028571

0.213462

0.070513

0

1

0.114286

false

0

0.114286

0

0.342857

0

null

0

null

0

1

0

0f3eb5d4fbfa76e8121ceb71f9823d54a1848d77

4,031

py

Python

ytutils/Video.py

SanjayDevTech/ytutils

775aa5dfa5552ad165086d08e5a0bdd2c06a167c

[ "MIT" ]

null

ytutils/Video.py

SanjayDevTech/ytutils

775aa5dfa5552ad165086d08e5a0bdd2c06a167c

[ "MIT" ]

null

ytutils/Video.py

SanjayDevTech/ytutils

775aa5dfa5552ad165086d08e5a0bdd2c06a167c

[ "MIT" ]

null

import requests import urllib.parse import re class Video: """Video class for accessing YouTube video information.""" def __init__(self, api_key): self.__pattern__ = r"^(?:http(?:s)?:\/\/)?(?:www\.)?(?:m\.)?(?:youtu\.be\/|youtube\.com\/(?:(?:watch)?\?(?:.*&)?v(?:i)?=|(?:embed)\/))([^\?&\"'>]+)" self.api_key = api_key self.__dictChart = {} def set_key(self, api_key): """To change the api_key that is used for fetch details""" self.api_key= api_key def start(self, video_url=None, video_id=None): """Pass video_url or video_id, two is not mandatory but atleast one should be given. It will raise SyntaxError => if none of the parameters were given KeyError => if video url is not matching the pattern ConnectionError => if network connection failed""" if video_url is None and video_id is None: raise SyntaxError('There must be given video_url or video_id') elif video_url is None: self.video_id = video_id else: id_pattern = re.search(self.__pattern__, video_url) if id_pattern is None: raise KeyError('Invalid Video Url') self.video_id = id_pattern[1] self.__URL ='https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&id='+self.video_id+'&key='+self.api_key try: self.__response = requests.get(self.__URL) except: raise ConnectionError('Network connection failed') self.__json = self.__response.json() if 'error' not in self.__json: if int(self.__json['pageInfo']['totalResults']) > 0: self.__dictChart['result'] = 'OK' self.__dictChart['code'] = 200 self.__dictChart['message'] = '' self.__dictChart['reason'] = '' self.__dictChart['extended_help'] = '' self.__dictChart['title'] = self.__json['items'][0]['snippet']['title'] self.__dictChart['des'] = self.__json['items'][0]['snippet']['description'] self.__dictChart['thumbnails'] = self.__json['items'][0]['snippet']['thumbnails'] self.__dictChart['channelId'] = self.__json['items'][0]['snippet']['channelId'] self.__dictChart['publishedAt'] = self.__json['items'][0]['snippet']['publishedAt'] self.__dictChart['channelTitle'] = self.__json['items'][0]['snippet']['channelTitle'] self.__dictChart['viewCount'] = self.__json['items'][0]['statistics']['viewCount'] self.__dictChart['commentCount'] = self.__json['items'][0]['statistics']['commentCount'] self.__dictChart['likeCount'] = self.__json['items'][0]['statistics']['likeCount'] self.__dictChart['dislikeCount'] = self.__json['items'][0]['statistics']['dislikeCount'] else: self.__dictChart['result'] = 'FAILURE' self.__dictChart['code'] = 0 self.__dictChart['message'] = 'Please check your video id' self.__dictChart['reason'] = 'emptyResult' self.__dictChart['extended_help'] = '' else: self.__dictChart['result'] = 'FAILURE' self.__dictChart['code'] = int(self.__json['error']['code']) self.__dictChart['message'] = self.__json['error']['message'] self.__dictChart['reason'] = self.__json['error']['errors'][0]['reason'] self.__dictChart['extended_help'] = 'Use this link to know the meaning of the error code:- https://developers.google.com/youtube/v3/docs/videos/list?hl=en-US#errors_1' def result(self): """Returns the YT video details""" return self.__dictChart

48.566265

180

0.554701

424

4,031

4.95283

0.316038

0.167143

0.061905

0.066667

0.235238

0.044762

0

0.007022

0.293476

4,031

83

181

48.566265

0.730337

0.09551

0

0.157895

0

0.017544

0.273116

0.034247

0

1

0.070175

false

0

0.052632

0

0.157895

0

null

0

null

0

1

0

0f3efcbaeed1949a3f0c19cb7137d4131273fc97

9,761

py

Python

smlcs/training/classifier.py

AnandBhatUpb/smlcs-final-submission

54d810d2ed1dc5907973ce55d93d318bec0d4011

[ "Apache-2.0" ]

null

smlcs/training/classifier.py

AnandBhatUpb/smlcs-final-submission

54d810d2ed1dc5907973ce55d93d318bec0d4011

[ "Apache-2.0" ]

null

smlcs/training/classifier.py

AnandBhatUpb/smlcs-final-submission

54d810d2ed1dc5907973ce55d93d318bec0d4011

[ "Apache-2.0" ]

null

"""This script trains --clf classifier for multiclass classification. Usage: classifier.py --env=<run_environment> --job=<jobid> --subjob=<subjobid> --clf=<classifier> --cw=<classweight> classifier.py (-h | --help) classifier.py Options: -h --help Show this screen. --env=<run_environment> specifies the running environment cluster/PC --job=<jobid> specifies cluster job id --subjob=<subjobid> specifies cluster subjob id --clf=<classifier> specifies classifier to train --cw=<classweight> specifies class weight strategy applied """ import datetime import logging import json from docopt import docopt import numpy as np from joblib import dump from smlcs.helper.read_data import ReadData from smlcs.evaluation.metrics import CalculateMetrics from smlcs.evaluation.plotters import PlotResults from smlcs.helper.preprocessing import Preprocessing from smlcs.helper.write_training_result import WriteToCSV #from imblearn.over_sampling import SMOTE from collections import Counter from sklearn.preprocessing import StandardScaler from sklearn import svm, ensemble from skopt import BayesSearchCV class Classifier: def local_training(environment, clf, X, Y, outercv, logger): try: print('Not Implemented') except Exception as e: print('Error') #logger.error('Failed in local training: ' + str(e)) def cluster_training(environment, clf, job_id, subjob_id, cw, logger): try: logger.info('Training environment: {}'.format(environment)) logger.info('Classifier selected: {}'.format(clf)) logger.info('Class balance strategy selected: {}'.format(cw)) with open('../configurations/outer_fold_data_clf.txt') as json_file: data = json.load(json_file) datasource = data['datasource'] outer_split_strategy = data['outer_split_strategy'] logger.info('Data source selected for training: {}'.format(datasource)) X, Y, pgm_features = ReadData(datasource, logger).read_clf_data(logger) # Read data from local/remote X[:, 0:42], imputerobject = Preprocessing().handle_missing_data(X[:, 0:42], logger) # Handle missing data onehotcoded_data, config_features = Preprocessing().encode_categorical_data(X[:, 42:51], logger) # OneHotCode categorical data feature_names = pgm_features + config_features X = np.delete(X, np.s_[42:51], axis=1) logger.info('Shape of the onehotcoded data: {}'.format(onehotcoded_data.shape)) logger.info('Shape of the program feature data: {}'.format(X.shape)) logger.info('Feature names after onehotencoding: {}'.format(feature_names)) X = np.concatenate((X, onehotcoded_data), axis=1) logger.info('Shape of the final processed data: {}'.format(X.shape)) Y = Preprocessing().encode_labels(Y, logger) # Encoding class labels for f in data['folds']: if int(subjob_id) == int(f['foldId']): X_train, X_test = X[f['outer_train_index']], X[f['outer_test_index']] y_train, y_test = Y[f['outer_train_index']], Y[f['outer_test_index']] #if cw == 'smote': # logger.info('Original dataset shape before smote: {}'.format(Counter(y_train))) # sm = SMOTE(random_state=42) # X_train, y_train = sm.fit_resample(X_train, y_train) # logger.info('Dataset shape after smote: {}'.format(Counter(y_train))) scaler = StandardScaler() X_train = scaler.fit_transform(X_train) X_test = scaler.transform(X_test) dump(scaler, '../../models_persisted/clf_scalar_' + clf + '_' + job_id + '_' + subjob_id + '.joblib') dump(imputerobject, '../../models_persisted/clf_imputer_' + clf + '_' + job_id + '_' + subjob_id + '.joblib') with open('../configurations/clf_config.txt') as json_file: clf_config = json.load(json_file) innercvfolds = int(clf_config['innercv_folds']) logger.info('Inner cross validation number of folds: {}'.format(innercvfolds)) estimator = None tuning_parameters = None if cw == 'imbalanced': class_weight = None elif cw == 'balanced': class_weight = 'balanced' elif cw == 'classweight': class_weight = {0: 5.0, 1: 1.0 } for c in clf_config['classifiers']: if clf == c['clf_name']: if clf == 'rf': if cw == 'smote': estimator = ensemble.RandomForestClassifier(random_state=0) else: estimator = ensemble.RandomForestClassifier(class_weight=class_weight, random_state=1) tuning_parameters = c['clf_parameters'] break elif clf == 'svc': if cw == 'smote' or cw == 'imbalanced': estimator = svm.SVC(random_state=0) else: estimator = svm.SVC(class_weight=class_weight, random_state=1) tuning_parameters = c['clf_parameters'] break else: estimator = ensemble.GradientBoostingClassifier(random_state=1) tuning_parameters = c['clf_parameters'] break logger.info('estimator is : {}'.format(estimator)) logger.info('Tunning parameters are: {}'.format(tuning_parameters)) start_time = datetime.datetime.now() logger.info('Started Skopt CV at: {}'.format(start_time)) opt_clf = BayesSearchCV(estimator, tuning_parameters, cv=innercvfolds) opt_clf.fit(X_train, y_train) end_time = datetime.datetime.now() logger.info('Ended Skopt CV at: {}'.format(end_time)) logger.info('Total time for parameter search: {}'.format(end_time-start_time)) metrics = CalculateMetrics(opt_clf) metrics.grid_models_metrics(logger, job_id, subjob_id) best_params = metrics.grid_best_params(logger) best_estimator = metrics.grid_best_estimator(logger) grid_score = metrics.grid_score(logger) test_score = metrics.test_score(X_test, y_test, logger) important_features = [] if clf == 'rf': important_features = metrics.get_imprtant_features(logger) log_path = './logs/log_'+str(job_id)+'_'+str(subjob_id)+'.log' cm_path = './plots/cm_'+str(job_id)+'_'+str(subjob_id)+'.png' fi_path = './plots/fi_' + str(job_id) + "_" + str(subjob_id) + '.png' # dump all results into the training_result.csv file writer = WriteToCSV() writer.write_result_to_csv(logger, job_id, subjob_id, subjob_id, datetime.datetime.now(), clf, best_params, grid_score, test_score, innercvfolds, outer_split_strategy, 'none', datasource, start_time, end_time, end_time-start_time, X_train.shape, X_test.shape, log_path, cm_path, fi_path) logger.info('Saving trained model') dump(opt_clf, '../../models_persisted/clf_'+clf+'_'+job_id+'_'+subjob_id+'.joblib') logger.info('Saved model: {}'.format('clf_'+clf+'_'+job_id+'_'+subjob_id+'.joblib')) if environment == 'local': plot = PlotResults(opt_clf) plot.plot_confusion_matrix(X_test, y_test, logger, job_id, subjob_id) if clf == 'rf': plot.plot_feature_imp(feature_names, logger, job_id, subjob_id) logger.info('Done') except Exception as e: logger.error('Failed in cluster training: ' + str(e)) if __name__ == '__main__': try: arguments = docopt(__doc__, version=None) if arguments['--env'] is None: environment = 'cluster' else: environment = arguments['--env'] if arguments['--job'] is None: job_id = -1 else: job_id = arguments['--job'] if arguments['--subjob'] is None: subjob_id = -1 else: subjob_id = arguments['--subjob'] if arguments['--clf'] is None: clf = 'rf' else: clf = arguments['--clf'] if arguments['--cw'] is None: cw = 'balanced' else: cw = arguments['--cw'] logging.basicConfig(filename='../../logs/log_' + str(job_id) + '_' + str(subjob_id) + '.log', filemode='w', format='%(name)s - %(levelname)s - %(message)s', level=logging.INFO) logger = logging.getLogger('Clf_training') logger.info('Cluster job ID: {}'.format(job_id)) logger.info('Cluster sub job ID: {}'.format(subjob_id)) cluster_training(environment, clf, job_id, subjob_id, cw, logger) except Exception as e: logger.error('Failed in the main of classifier.py: ' + str(e))

45.826291

126

0.564184

1,056

9,761

5.004735

0.224432

0.039735

0.022895

0.024598

0.16859

0.126963

0.106149

0.078903

0.064901

0.045033

0

0.004684

0.321996

9,761

212

127

46.042453

0.793895

0.11925

0

0.149351

0

0.146305

0.019702

0

1

0.012987

false

0

0.11039

0

0.12987

0.012987

0

null

0

null

0

1

0

0f3f65e11551758b33fce5afba522f25f1619d03

758

py

Python

examples/sharepoint/connect_with_azure_app.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

examples/sharepoint/connect_with_azure_app.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

examples/sharepoint/connect_with_azure_app.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

import os from office365.sharepoint.client_context import ClientContext from settings import settings app_settings = { 'url': settings.get('team_site_url'), 'client_id': '51d03106-4726-442c-86db-70b32fa7547f', 'thumbprint': "6B36FBFC86FB1C019EB6496494B9195E6D179DDB", 'certificate_path': '{0}/selfsigncert.pem'.format(os.path.dirname(__file__)) } ctx = ClientContext.connect_with_certificate(app_settings['url'], app_settings['client_id'], app_settings['thumbprint'], app_settings['certificate_path']) current_web = ctx.web ctx.load(current_web) ctx.execute_query() print("{0}".format(current_web.url))

34.454545

80

0.635884

76

758

6.052632

0.513158

0.119565

0.06087

0

0.093146

0.24934

758

21

81

36.095238

0.71529

0

0.248021

0.100264

0

1

0

false

0

0.176471

0

0.176471

0

null

0

null

0

1

0

0f3f6efc75fc8212e5ff0fedb24746071b27e2d1

2,933

py

Python

apps/configuration/api/views.py

sotkonstantinidis/testcircle

448aa2148fbc2c969e60f0b33ce112d4740a8861

[ "Apache-2.0" ]

3

2019-02-24T14:24:43.000Z

2019-10-24T18:51:32.000Z

apps/configuration/api/views.py

sotkonstantinidis/testcircle

448aa2148fbc2c969e60f0b33ce112d4740a8861

[ "Apache-2.0" ]

17

2017-03-14T10:55:56.000Z

2022-03-11T23:20:19.000Z

apps/configuration/api/views.py

sotkonstantinidis/testcircle

448aa2148fbc2c969e60f0b33ce112d4740a8861

[ "Apache-2.0" ]

2

2016-02-01T06:32:40.000Z

2019-09-06T04:33:50.000Z

from collections import OrderedDict from django.http import Http404 from rest_framework.generics import GenericAPIView from rest_framework.response import Response from api.views import PermissionMixin, LogUserMixin from configuration.structure import ConfigurationStructure from configuration.models import Configuration class ConfigurationStructureView(PermissionMixin, LogUserMixin, GenericAPIView): """ Get the structure of the configuration of a questionnaire. Return information about the categories, questiongroups and questions that build a questionnaire. ``code``: The code of the configuration (e.g. "technologies"). ``edition``: The edition of the configuration (e.g. "2018"). Optional request params: ``flat``: If present, the structure will be a flat list of questions. """ def get(self, request, *args, **kwargs) -> Response: flat = request.GET.get('flat', False) structure_obj = ConfigurationStructure( code=kwargs['code'], edition=kwargs['edition'], flat=flat, ) if structure_obj.error: # No configuration was found for this code and edition. raise Http404() return Response(structure_obj.structure) class ConfigurationView(PermissionMixin, LogUserMixin, GenericAPIView): """ Get available configurations. Return the available configurations codes. Optional request params: ``flat``: If present, the structure will be a flat list of configurations. """ def get(self, request) -> Response: flat = request.GET.get('flat', False) configurations_obj = Configuration.objects.all() if not configurations_obj: # No configurations were found raise Http404() configurations_obj = configurations_obj.values_list('code', flat=flat).distinct().order_by('code') data = {"configurations": list(configurations_obj)} # Return all available configurations return Response(data) class ConfigurationEditionView(PermissionMixin, LogUserMixin, GenericAPIView): """ Get available editions for the configuration. Return the available editions in the configuration. ``code``: The code of the configuration (e.g. "technologies"). Optional request params: ``flat``: If present, the structure will be a flat list of questions. """ def get(self, request, *args, **kwargs) -> Response: flat = request.GET.get('flat', False) editions_obj = Configuration.objects.filter(code=kwargs['code']) if not editions_obj: # No editions were found for the code raise Http404() editions_obj = editions_obj.values_list('edition', flat=flat).distinct().order_by('edition') data = {"editions": list(editions_obj)} # Return all available configurations return Response(data)

31.537634

106

0.685646

320

2,933

6.225

0.253125

0.048193

0.036145

0.066265

0.36496

0.278614

0.261546

0.208333

0.165161

0

0.007039

0.225026

2,933

92

107

31.880435

0.869336

0.342994

0

0.277778

0

0.038904

0

1

0.083333

false

0

0.194444

0

0.444444

0

null

0

null

0

1

0

0f40804db63c1af07a13fce826b215bb90285b4b

3,209

py

Python

script/build.py

Jeket/electron

f41cce96a3afa8c4cf6fe57f9ec904502abed524

[ "MIT" ]

2

2019-07-17T08:09:02.000Z

2021-10-04T04:44:42.000Z

script/build.py

Jeket/electron

f41cce96a3afa8c4cf6fe57f9ec904502abed524

[ "MIT" ]

1

2018-04-03T23:04:37.000Z

script/build.py

Jeket/electron

f41cce96a3afa8c4cf6fe57f9ec904502abed524

[ "MIT" ]

1

2021-10-04T04:47:00.000Z

#!/usr/bin/env python import argparse import os import subprocess import sys from lib.config import MIPS64EL_GCC, get_target_arch, build_env, \ enable_verbose_mode, is_verbose_mode from lib.util import electron_gyp, import_vs_env CONFIGURATIONS = ['Release', 'Debug'] SOURCE_ROOT = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) VENDOR_DIR = os.path.join(SOURCE_ROOT, 'vendor') LIBCC_SOURCE_ROOT = os.path.join(SOURCE_ROOT, 'vendor', 'libchromiumcontent') LIBCC_DIST_MAIN = os.path.join(LIBCC_SOURCE_ROOT, 'dist', 'main') GCLIENT_DONE = os.path.join(SOURCE_ROOT, '.gclient_done') def main(): os.chdir(SOURCE_ROOT) args = parse_args() if args.verbose: enable_verbose_mode() # Update the VS build env. import_vs_env(get_target_arch()) # decide which ninja executable to use ninja_path = args.ninja_path if not ninja_path: ninja_path = os.path.join('vendor', 'depot_tools', 'ninja') if sys.platform == 'win32': ninja_path += '.exe' # decide how to invoke ninja ninja = [ninja_path] if is_verbose_mode(): ninja.append('-v') if args.libcc: if ('D' not in args.configuration or not os.path.exists(GCLIENT_DONE) or not os.path.exists(os.path.join(LIBCC_DIST_MAIN, 'build.ninja'))): sys.stderr.write('--libcc should only be used when ' 'libchromiumcontent was built with bootstrap.py -d ' '--debug_libchromiumcontent' + os.linesep) sys.exit(1) script = os.path.join(LIBCC_SOURCE_ROOT, 'script', 'build') subprocess.check_call([sys.executable, script, '-D', '-t', get_target_arch()]) subprocess.check_call(ninja + ['-C', LIBCC_DIST_MAIN]) env = build_env() for config in args.configuration: build_path = os.path.join('out', config[0]) ret = subprocess.call(ninja + ['-C', build_path, args.target], env=env) if ret != 0: sys.exit(ret) def parse_args(): parser = argparse.ArgumentParser(description='Build project') parser.add_argument('-c', '--configuration', help='Build with Release or Debug configuration', nargs='+', default=CONFIGURATIONS, required=False) parser.add_argument('-v', '--verbose', action='store_true', default=False, help='Verbose output') parser.add_argument('-t', '--target', help='Build specified target', default=electron_gyp()['project_name%'], required=False) parser.add_argument('--libcc', help=( 'Build libchromiumcontent first. Should be used only ' 'when libchromiumcontent as built with boostrap.py ' '-d --debug_libchromiumcontent.' ), action='store_true', default=False) parser.add_argument('--ninja-path', help='Path of ninja command to use.', required=False) return parser.parse_args() if __name__ == '__main__': sys.exit(main())

34.138298

78

0.603615

382

3,209

4.861257

0.311518

0.042003

0.04308

0.025848

0.145396

0.054927

0

0.003007

0.27454

3,209

93

79

34.505376

0.794674

0.033967

0

0.041096

0

0.190245

0.017119

0

1

0.027397

false

0

0.09589

0

0.136986

0

null

0

null

0

1

0

0f40b30ac69c7da5a7f9a164e6b58dd814dda554

8,496

py

Python

edit/datasets/base_sr_dataset.py

tpoisonooo/basicVSR_mge

53df836a7dcc075083ef7c9ff7cabea69fec3192

[ "Apache-2.0" ]

28

2021-03-23T09:00:33.000Z

2022-03-10T03:55:00.000Z

edit/datasets/base_sr_dataset.py

tpoisonooo/basicVSR_mge

53df836a7dcc075083ef7c9ff7cabea69fec3192

[ "Apache-2.0" ]

2

2021-04-17T20:08:55.000Z

2022-02-01T17:48:55.000Z

edit/datasets/base_sr_dataset.py

tpoisonooo/basicVSR_mge

53df836a7dcc075083ef7c9ff7cabea69fec3192

[ "Apache-2.0" ]

5

2021-05-19T07:35:56.000Z

2022-01-13T02:11:50.000Z

import shutil from collections import defaultdict import matplotlib.pyplot as plt import numpy as np import os import os.path as osp import copy from collections import defaultdict from .base_dataset import BaseDataset from pathlib import Path from edit.utils import scandir, is_list_of, mkdir_or_exist, is_tuple_of, imread, imwrite IMG_EXTENSIONS = ('.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP') class BaseSRDataset(BaseDataset): """Base class for image super resolution Dataset. """ def __init__(self, pipeline, scale, mode="train"): super(BaseSRDataset, self).__init__(pipeline, mode) self.scale = scale @staticmethod def scan_folder(path): """Obtain image path list (including sub-folders) from a given folder. Args: path (str | :obj:`Path`): Folder path. Returns: list[str]: image list obtained form given folder. """ if isinstance(path, (str, Path)): path = str(path) else: raise TypeError("'path' must be a str or a Path object, " f'but received {type(path)}.') images = sorted(list(scandir(path, suffix=IMG_EXTENSIONS, recursive=True))) images = [osp.join(path, v) for v in images] assert images, f'{path} has no valid image file.' return images def __getitem__(self, idx): """Get item at each call. Args: idx (int): Index for getting each item. """ results = copy.deepcopy(self.data_infos[idx]) results['scale'] = self.scale return self.pipeline(results) def evaluate(self, results): """Evaluate with different metrics. Args: results (list of dict): for every dict, record metric -> value for one frame Return: dict: Evaluation results dict. """ assert is_list_of(results, dict), f'results must be a list of dict, but got {type(results)}' assert len(results) >= len(self), "results length should >= dataset length, due to multicard eval" self.logger.info("eval samples length: {}, dataset length: {}, only select front {} results".format(len(results), len(self), len(self))) results = results[:len(self)] eval_results = defaultdict(list) # a dict of list for res in results: for metric, val in res.items(): eval_results[metric].append(val) for metric, val_list in eval_results.items(): assert len(val_list) == len(self), ( f'Length of evaluation result of {metric} is {len(val_list)}, ' f'should be {len(self)}') # average the results eval_results = { metric: sum(values) / len(self) for metric, values in eval_results.items() } return eval_results class BaseVSRDataset(BaseDataset): """Base class for video super resolution Dataset. """ def __init__(self, pipeline, scale, mode="train"): super(BaseVSRDataset, self).__init__(pipeline, mode) self.scale = scale def __getitem__(self, idx): """Get item at each call. Args: idx (int): Index for getting each item. """ results = copy.deepcopy(self.data_infos[idx]) results['scale'] = self.scale return self.pipeline(results) def test_aggre(self, save_path, padding_len = 4, start_index = 1): clip_names = sorted(self.frame_num.keys()) # e.g. [`city`, `walk`] frame_nums = [ self.frame_num[clip] for clip in clip_names ] do_frames = 0 now_clip_idx = 0 total_deal = 0 for _ in range(len(self)): do_frames += 1 if do_frames == frame_nums[now_clip_idx]: clip_name = clip_names[now_clip_idx] # move images to dir use shutil save_dir_path = osp.join(save_path, clip_name) mkdir_or_exist(save_dir_path) # index from [total_deal, total_deal + do_frames) for idx in range(total_deal, total_deal + do_frames): ensemble_path_1 = osp.join(save_path, "idx_{}_epoch_1.png".format(idx)) desti_path = osp.join(save_dir_path, str(idx - total_deal + start_index).zfill(padding_len) + ".png") if osp.exists(ensemble_path_1): # get the content path = osp.join(save_path, "idx_{}.png".format(idx)) sum_result = imread(path, flag='unchanged').astype(np.float32) os.remove(path) for e in range(1, 8): path = osp.join(save_path, "idx_{}_epoch_{}.png".format(idx, e)) sum_result = sum_result + imread(path, flag='unchanged').astype(np.float32) os.remove(path) sum_result = sum_result / 8 # 四舍五入 sum_result = sum_result.round().astype(np.uint8) # save imwrite(sum_result, desti_path) else: # move shutil.move(osp.join(save_path, "idx_" + str(idx) + ".png"), desti_path) total_deal += do_frames do_frames = 0 now_clip_idx += 1 def evaluate(self, results, save_path): """ Evaluate with different metrics. Args: results (list of dict): for every dict, record metric -> value for one frame Return: dict: Evaluation results dict. """ save_SVG_path = osp.join(save_path, "SVG") mkdir_or_exist(save_SVG_path) assert is_list_of(results, dict), f'results must be a list of dict, but got {type(results)}' assert len(results) >= len(self), "results length should >= dataset length, due to multicard eval" self.logger.info("eval samples length: {}, dataset length: {}, only select front {} results".format(len(results), len(self), len(self))) results = results[:len(self)] clip_names = sorted(self.frame_num.keys()) # e.g. [`city`, `walk`] frame_nums = [ self.frame_num[clip] for clip in clip_names ] eval_results = defaultdict(list) # a dict of list do_frames = 0 now_clip_idx = 0 eval_results_one_clip = defaultdict(list) for res in results: for metric, val in res.items(): eval_results_one_clip[metric].append(val) do_frames += 1 if do_frames == frame_nums[now_clip_idx]: # 处理一个clip clip_name = clip_names[now_clip_idx] self.logger.info("{}: {} is ok".format(now_clip_idx, clip_name)) for metric, values in eval_results_one_clip.items(): # metric clip_name values to save an svg average = sum(values) / len(values) save_filename = clip_name + "_" + metric title = "{} for {}, length: {}, average: {:.4f}".format(metric, clip_name, len(values), average) plt.figure(figsize=(len(values) // 4 + 1, 8)) plt.plot(list(range(len(values))), values, label=metric) # promise that <= 10000 plt.title(title) plt.xlabel('frame idx') plt.ylabel('{} value'.format(metric)) plt.legend() fig = plt.gcf() fig.savefig(osp.join(save_SVG_path, save_filename + '.svg'), dpi=600, bbox_inches='tight') # plt.show() plt.clf() plt.close() eval_results[metric].append(average) do_frames = 0 now_clip_idx += 1 eval_results_one_clip = defaultdict(list) for metric, val_list in eval_results.items(): assert len(val_list) == len(clip_names), ( f'Length of evaluation result of {metric} is {len(val_list)}, ' f'should be {len(clip_names)}') # average the results eval_results = { metric: sum(values) / len(values) for metric, values in eval_results.items() } return eval_results

39.516279

144

0.555791

1,020

8,496

4.447059

0.209804

0.038801

0.019841

0.576279

0.559965

0.526455

0.468254

0.452822

0.43254

0

0.006384

0.336276

8,496

214

145

39.700935

0.798014

0.125824

0

0.455882

0

0.120095

0

0.051471

1

0.058824

false

0

0.080882

0

0.191176

0

null

0

null

0

1

0

0f40db84d7bca7d0656befc3d3837a41b5c794b2

13,400

py

Python

rbotreborn.py

Bobscorn/rbotreborn

4a16e577c349b1a3461e12643dbb583a35af50f5

[ "MIT" ]

null

rbotreborn.py

Bobscorn/rbotreborn

4a16e577c349b1a3461e12643dbb583a35af50f5

[ "MIT" ]

null

rbotreborn.py

Bobscorn/rbotreborn

4a16e577c349b1a3461e12643dbb583a35af50f5

[ "MIT" ]

null

import discord import asyncio from discord.ext import commands import praw import logging import config from gfycat import Gfycat from custom_embeds import * from reddit import * from exceptions import * from processors import * Config = config.Config('config.ini') bot = commands.Bot(command_prefix=Config.bot_prefix, description='R-BotReborn\n https://github.com/colethedj/rbotreborn') @bot.command(pass_context=True, description="Get x amount of comments from the last post") async def rcl(ctx, *comment_count:int): await bot.delete_message(ctx.message) if comment_count: comment_count = comment_count[0] if comment_count > Config.r_max_comment_count: comment_count = Config.r_max_comment_count else: comment_count = Config.r_default_comment_count loading_message = RedditLoadingEmbed() loading_message.create_embed(subreddit='unknown', post_count=1, comment_count=comment_count, custom_message="Getting comments... This will take a moment") bot_message = await bot.send_message(ctx.message.channel, embed=loading_message.get_embed()) try: post_id = Config.r_last_post_url[ctx.message.server.id][ctx.message.channel.id] getcomments = Reddit(reddit2) comments = getcomments.get_comments(post_id, comment_count) embed = RedditCommentEmbed() embed.create_embed(comments=comments) except KeyError: embed = RedditErrorEmbed() embed.create_embed(title=":warning: There is no last post from this channel saved", ) except UnknownException as e: embed = RedditErrorEmbed() embed.create_embed(title=":warning: Error getting comments from that post: " + str(e), ) # no saved post from this channel await bot.edit_message(bot_message, embed=embed.get_embed()) @bot.command(pass_context=True, description="Get posts from a Reddit comments link. " "Can also grab comments from that post") async def ru(ctx, url: str, *comment_count:int): if comment_count: comment_count = comment_count[0] if comment_count > Config.r_max_comment_count: comment_count = Config.r_max_comment_count else: comment_count = 0 await reddit_handler(ctx, url=url, comment_num=comment_count) @bot.command(pass_context=True, description="Get posts with comments from Reddit") async def rc(ctx, subreddit: str, *comment_count: int): if comment_count: comment_count = comment_count[0] if comment_count > Config.r_max_comment_count: comment_count = Config.r_max_comment_count else: comment_count = Config.r_default_comment_count await reddit_handler(ctx, subreddit=subreddit, post_count=Config.r_postcount, comment_num=comment_count) @bot.command(pass_context=True, description="Get posts from reddit (any type)") async def r(ctx, subreddit: str, *post_count: int): if post_count: post_count = post_count[0] else: post_count = Config.r_postcount await reddit_handler(ctx, subreddit=subreddit, post_count=post_count, image=None) @bot.command(pass_context=True, description="Get image-only posts from reddit") async def ri(ctx, subreddit: str, *post_count: int): if post_count: post_count = post_count[0] else: post_count = Config.r_postcount await reddit_handler(ctx, subreddit=subreddit, post_count=post_count, image=True) @bot.command(pass_context=True, description="Get text-only posts from reddit") async def rt(ctx, subreddit: str, *post_count: int): # TODO if post_count: post_count = post_count[0] else: post_count = Config.r_postcount await reddit_handler(ctx, subreddit=subreddit, post_count=post_count, image=False) # where all the reddit commands use # REQUEST TYPES: 'default', 'url' async def reddit_handler(ctx, **kwargs): subreddit = kwargs.get('subreddit', None) url = kwargs.get('url', None) post_count = int(kwargs.get('post_count', 1)) image = kwargs.get('image', None) comment_num = int(kwargs.get('comment_num', 0)) request_type = 'default' if subreddit is not None: subreddit = subreddit.lower() if url is not None: request_type = 'url' # this is already done in reddit.py but we want to show how much posts we are getting in chat if post_count is not None: if post_count > Config.r_maxpostcount: post_count = Config.r_maxpostcount else: post_count = 1 # delete the request message await bot.delete_message(ctx.message) # send a message to show the requester whats happening loading_message = RedditLoadingEmbed() loading_message.create_embed(subreddit=('unknown' if subreddit is None else subreddit), post_count=post_count, comment_count=comment_num) bot_message = await bot.send_message(ctx.message.channel, embed=loading_message.get_embed()) # check if discord channel is marked as NSFW if str(ctx.message.channel.id) in Config.nsfw_channels[ctx.message.server.id]: nsfw = True else: nsfw = False # start off with getting posts red = Reddit(reddit2) error_embed = None try: post, comments = await red.get(subreddit=subreddit, post_count=post_count, nsfw=nsfw, get_image=image, comment_count=comment_num, request_type=request_type, url=url) except SubredditNotExist: error_embed = RedditErrorEmbed() error_embed.create_embed(title="r/" + str(subreddit) + " does not exist.", description="check your spelling") except SubredditIsNSFW: error_embed = RedditErrorEmbed() error_embed.create_embed(title="r/" + str(subreddit) + " is a NSFW subreddit", description="This channel is not set as a NSFW channel. " "If you want to add this channel as a NSFW channel, " "use the command -addnsfw.") except NoPostsReturned: error_embed = RedditErrorEmbed() error_embed.create_embed(title="No Posts Returned", description="Maybe try again with larger post count. " "If you are getting only images or only text," " some subreddits may not have e.g only images.") except InvalidRedditURL: error_embed = RedditErrorEmbed() error_embed.create_embed(title="Invalid Reddit Submission URL entered", description="Make sure the URL you entered is correct and links " "to a post.") except RedditOAuthException as e: error_embed = RedditErrorEmbed() error_embed.create_embed(title="Reddit Authentication Failure", description="Make sure you have enter credentials and that they are correct" "in the config file. Also make sure only application using your " "API credentials at once. " + str(e)) except UnknownException as e: error_embed = RedditErrorEmbed() error_embed.create_embed(title="Unknown Error", description="""R-BOT has not been programmed to handle this error. Error Output: """ + str(e)) finally: if error_embed is not None: await bot.edit_message(bot_message, embed=error_embed.get_embed()) return # TODO: ERROR HANDLERS # handle the post types post_type = post.get('post_type') post_text = post.get('post_text') post_id = post.get('post_id') image_url = "NONE" # had issues with None being turned to a str type for some reason if post_type != "link" and post_type != "reddit": if post_type != "gif" and post_type != "image": if post_type == "gfycat": post_gfycat = Gfycat(Config.gfycat_client_id, Config.gfycat_client_secret) gfyjson = await post_gfycat.get_gfy_info(str(post.get('post_url'))[19:(len(str(post.get('post_url'))))]) print(gfyjson) # TODO: fails if starts with http:// image_url = gfyjson['gfyItem']['max5mbGif'] # TODO: maybe some error handling here? elif post_type == "imgur": post['post_text'] = "R-BotReborn: Imgur Links are not supported yet" else: processing_embed = GfycatLoadingEmbed() await bot.edit_message(bot_message, embed=processing_embed.get_embed()) image_url = await gfycat_url_handler(post.get('post_url')) if image_url is GfycatErrorEmbed: # time to send error to channel await bot.edit_message(bot_message, embed=error_embed.get_embed()) image_url = None return elif post_type == "gif" or post_type == "image": # either gif or image image_url = post.get('post_url') elif post_type == "link": if Config.enable_sumy: # tldrify if user wants # TODO: add this function # we are going to TLDRify the link (but only if there is not text to start with) if post_text == "": post_text = "**TL;DR:** " + await sumy_url(post.get('post_url')) # create reddit embed comment_embed = None if len(comments) > 0: comment_embed = RedditCommentEmbed() comment_embed.create_embed(comments=comments) post_embed = RedditPostEmbed() post_embed.create_embed(title=str(post.get('post_title')), url=str(post.get('post_permalink')), author=str(post.get('post_author')), nsfw=bool(post.get('nsfw')), score=int(post.get('post_score')), description=str(post_text), image=str(image_url), time=str(post.get('created_utc')) + " UTC", subreddit=str(post.get('post_subreddit')) ) await bot.edit_message(bot_message, embed=post_embed.get_embed()) if comment_embed is not None: await bot.send_message(ctx.message.channel, embed=comment_embed.get_embed()) # now we will save the post id if str(ctx.message.server.id) in Config.r_last_post_url: Config.r_last_post_url[str(ctx.message.server.id)][str(ctx.message.channel.id)] = post_id else: Config.r_last_post_url[str(ctx.message.server.id)] = {str(ctx.message.channel.id): post_id} @bot.command(pass_context=True, description="Allow NSFW on current channel") async def addnsfw(ctx): new_channels, message = config.UpdateConfig('config.ini').add_nsfw_channels(str(ctx.message.server.id), str(ctx.message.channel.id)) Config.nsfw_channels = new_channels if message is None: embed = discord.Embed(title=":underage: Added this channel as a NSFW Channel") else: embed = discord.Embed(title=":warning:" + str(message)) await bot.send_message(ctx.message.channel, embed=embed) @bot.command(pass_context=True, description="Allow NSFW on current channel") async def removensfw(ctx): new_channels, message = config.UpdateConfig('config.ini').remove_nsfw_channels(str(ctx.message.server.id), str(ctx.message.channel.id)) Config.nsfw_channels = new_channels if message is None: embed = discord.Embed(title=":wastebasket: Removed this channel as a NSFW Channel") else: embed = discord.Embed(title=":warning: " + str(message)) await bot.send_message(ctx.message.channel, embed=embed) @bot.event # when ready display this shit async def on_ready(): logging.info('Logged into discord as:') logging.info(bot.user.name) logging.info(bot.user.id) print(vars(reddit2)) print(dir(reddit2)) logging.info("Logged into reddit as:") #logging.info(reddit2.user.me()) logging.info('------') await bot.change_presence(game=discord.Game(name=Config.bot_game)) # main method run when starting def start(): # connect to discord print(Config.discord_token) bot.run(Config.discord_token) # connect to reddit (instance) # connect to reddit (instance) def connect_reddit(): reddit = praw.Reddit(client_id=Config.r_client_id, client_secret=Config.r_client_secret, user_agent=Config.r_user_agent, ) return reddit if __name__ == '__main__': logging.basicConfig( level=logging.DEBUG, format='%(asctime)s %(levelname)-8s %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) reddit2 = connect_reddit() start()

37.535014

141

0.623731

1,646

13,400

4.899757

0.176792

0.053565

0.020831

0.024551

0.451457

0.409423

0.380657

0.344947

0.303162

0.278611

0

0.00229

0.28306

13,400

356

142

37.640449

0.837202

0.068433

0

0.271255

0

0.146816

0

0.002809

0

1

0.008097

false

0.032389

0.044534

0

0.064777

0.016194

0

null

0

null

0

1

0

0f429fee86ffe0485046fceb6efe8634730b1750

2,954

py

Python

eventbusk/brokers/base.py

Airbase/eventbusk

704d50a4c9c1f7d332dba93ee04ab07afa59d216

[ "BSD-3-Clause" ]

null

eventbusk/brokers/base.py

Airbase/eventbusk

704d50a4c9c1f7d332dba93ee04ab07afa59d216

[ "BSD-3-Clause" ]

1

2021-06-13T18:08:50.000Z

eventbusk/brokers/base.py

Airbase/eventbusk

704d50a4c9c1f7d332dba93ee04ab07afa59d216

[ "BSD-3-Clause" ]

null

""" Base interface for event consumer and producers. """ from __future__ import annotations import logging from abc import ABC, abstractmethod from contextlib import ContextDecorator from types import TracebackType from typing import Callable, Optional, Type, Union from confluent_kafka import cimpl # type: ignore logger = logging.getLogger(__name__) __all__ = [ "BaseBrokerURI", "BaseConsumer", "BaseProducer", ] # Type hints # callback method `on_delivery` on the producer DeliveryCallBackT = Callable[..., None] MessageT = Union[str, bytes, cimpl.Message] class BaseBrokerURI(ABC): """ Base class that defines the interface for all broker URIs """ @classmethod @abstractmethod def from_uri(cls, uri: str) -> BaseBrokerURI: """ Return a instance created from a URI """ class BaseConsumer(ContextDecorator, ABC): """ Base class for consumers All event consumers are exposed as a ContextDecorator, so it can be used via a `with` statement and any connections are automatically closed on exit. """ broker: BaseBrokerURI topic: str group: str def __repr__(self) -> str: return ( f"<{self.__class__.__name__}(" f"broker=*, " f"topic={self.topic}, " f"group='{self.group}')>" ) def __enter__(self) -> BaseConsumer: return self def __exit__( self, exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], exc_traceback: Optional[TracebackType], ) -> None: pass @abstractmethod def poll(self, timeout: int) -> Optional[MessageT]: # type: ignore """ Poll for a specified time in seconds for new messages """ @abstractmethod def ack(self, message: str) -> None: """ Acknowledge successful consumption of a message. """ class BaseProducer(ABC): """ Base class for producers """ def __repr__(self) -> str: return f"<{self.__class__.__name__}(" f"broker=*>" @abstractmethod def __init__(self, broker: str): super().__init__() @abstractmethod def produce( # type: ignore # pylint: disable=too-many-arguments self, topic: str, value: MessageT, flush: bool = True, on_delivery: DeliveryCallBackT = None, fail_silently: bool = False, ) -> None: """ Send a message on the specific topic. Arguments ---------- topic: The name of the topic value: Serialized message to send. on_delivery: Callback function on delivery of a message. flush: Flush any pending messages after every send. Useful for brokers like Kafka which do batches. fail_silently: If True, ignore all delivery errors. """

23.822581

82

0.61002

315

2,954

5.52381

0.419048

0.048851

0.02069

0.017241

0.047126

0

0.296886

2,954

123

83

24.01626

0.837747

0.317197

0

0.189655

0

0.08661

0.043305

0

1

0.155172

false

0.017241

0.12069

0.051724

0.431034

0

null

0

null

0

1

0

0f44d6bc8334ac97aa9e714bc57dd06d1424b56c

11,558

py

Python

mw4/gui/mainWmixin/tabSettDome.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

16

2020-01-11T22:32:26.000Z

2022-03-31T15:18:14.000Z

mw4/gui/mainWmixin/tabSettDome.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

196

2020-01-16T13:56:01.000Z

2022-03-29T02:06:51.000Z

mw4/gui/mainWmixin/tabSettDome.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

6

2019-12-01T19:39:33.000Z

2021-05-27T13:14:20.000Z

############################################################ # -*- coding: utf-8 -*- # # # # # # # # # ## ## # ## # # # # # # # # # # # # # # # ## # ## ## ###### # # # # # # # # # Python-based Tool for interaction with the 10micron mounts # GUI with PyQT5 for python # # written in python3, (c) 2019-2021 by mworion # Licence APL2.0 # ########################################################### # standard libraries # external packages # local import class SettDome(object): """ """ def __init__(self): self.ui.domeRadius.valueChanged.connect(self.setUseGeometry) self.ui.offGEM.valueChanged.connect(self.setUseGeometry) self.ui.offLAT.valueChanged.connect(self.setUseGeometry) self.ui.domeEastOffset.valueChanged.connect(self.setUseGeometry) self.ui.domeNorthOffset.valueChanged.connect(self.setUseGeometry) self.ui.domeZoffGEM.valueChanged.connect(self.setZoffGEMInMount) self.ui.domeZoff10micron.valueChanged.connect(self.setZoff10micronInMount) self.ui.domeClearOpening.valueChanged.connect(self.setUseGeometry) self.ui.domeOpeningHysteresis.valueChanged.connect(self.setUseGeometry) self.ui.domeClearanceZenith.valueChanged.connect(self.setUseGeometry) self.ui.useOvershoot.clicked.connect(self.setUseGeometry) self.ui.settleTimeDome.valueChanged.connect(self.setDomeSettlingTime) self.ui.useDomeGeometry.clicked.connect(self.setUseGeometry) self.ui.useDynamicFollowing.clicked.connect(self.setUseGeometry) self.ui.copyFromDomeDriver.clicked.connect(self.updateDomeGeometryToGui) self.app.mount.signals.firmwareDone.connect(self.setUseGeometry) self.app.mount.signals.firmwareDone.connect(self.setZoffGEMInMount) self.ui.domeRadius.valueChanged.connect(self.tab1) self.ui.domeNorthOffset.valueChanged.connect(self.tab2) self.ui.domeEastOffset.valueChanged.connect(self.tab3) self.ui.domeZoffGEM.valueChanged.connect(self.tab4) self.ui.domeZoff10micron.valueChanged.connect(self.tab5) self.ui.offGEM.valueChanged.connect(self.tab6) self.ui.offLAT.valueChanged.connect(self.tab7) self.ui.domeClearOpening.valueChanged.connect(self.tab8) self.ui.domeOpeningHysteresis.valueChanged.connect(self.tab9) self.ui.domeClearanceZenith.valueChanged.connect(self.tab10) self.app.update1s.connect(self.updateShutterStatGui) self.ui.domeAbortSlew.clicked.connect(self.domeAbortSlew) self.ui.domeOpenShutter.clicked.connect(self.domeOpenShutter) self.ui.domeCloseShutter.clicked.connect(self.domeCloseShutter) def tab1(self): self.ui.tabDomeExplain.setCurrentIndex(0) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab2(self): self.ui.tabDomeExplain.setCurrentIndex(1) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab3(self): self.ui.tabDomeExplain.setCurrentIndex(2) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab4(self): self.ui.tabDomeExplain.setCurrentIndex(3) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab5(self): self.ui.tabDomeExplain.setCurrentIndex(4) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab6(self): self.ui.tabDomeExplain.setCurrentIndex(5) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab7(self): self.ui.tabDomeExplain.setCurrentIndex(6) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab8(self): self.ui.tabDomeExplain.setCurrentIndex(7) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab9(self): self.ui.tabDomeExplain.setCurrentIndex(8) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def tab10(self): self.ui.tabDomeExplain.setCurrentIndex(9) self.ui.tabDomeExplain.setStyleSheet(self.getStyle()) def initConfig(self): """ initConfig read the key out of the configuration dict and stores it to the gui elements. if some initialisations have to be proceeded with the loaded persistent data, they will be launched as well in this method. :return: True for test purpose """ config = self.app.config['mainW'] self.ui.domeClearOpening.setValue(config.get('domeClearOpening', 0.4)) self.ui.domeOpeningHysteresis.setValue(config.get('domeOpeningHysteresis', 0.0)) self.ui.domeClearanceZenith.setValue(config.get('domeClearanceZenith', 0.2)) self.ui.useOvershoot.setChecked(config.get('useOvershoot', False)) self.ui.domeNorthOffset.setValue(config.get('domeNorthOffset', 0)) self.ui.domeEastOffset.setValue(config.get('domeEastOffset', 0)) self.ui.domeZoffGEM.setValue(config.get('domeZoffGEM', 0)) self.ui.offGEM.setValue(config.get('offGEM', 0)) self.ui.offLAT.setValue(config.get('offLAT', 0)) self.ui.domeRadius.setValue(config.get('domeRadius', 1.5)) self.ui.useDomeGeometry.setChecked(config.get('useDomeGeometry', False)) self.ui.autoDomeDriver.setChecked(config.get('autoDomeDriver', False)) self.ui.useDynamicFollowing.setChecked(config.get('useDynamicFollowing', False)) self.ui.settleTimeDome.setValue(config.get('settleTimeDome', 0)) self.setUseGeometry() return True def storeConfig(self): """ storeConfig writes the keys to the configuration dict and stores. if some saving has to be proceeded to persistent data, they will be launched as well in this method. :return: True for test purpose """ config = self.app.config['mainW'] config['domeRadius'] = self.ui.domeRadius.value() config['domeClearOpening'] = self.ui.domeClearOpening.value() config['domeOpeningHysteresis'] = self.ui.domeOpeningHysteresis.value() config['domeClearanceZenith'] = self.ui.domeClearanceZenith.value() config['useOvershoot'] = self.ui.useOvershoot.isChecked() config['domeNorthOffset'] = self.ui.domeNorthOffset.value() config['domeEastOffset'] = self.ui.domeEastOffset.value() config['domeZoffGEM'] = self.ui.domeZoffGEM.value() config['offGEM'] = self.ui.offGEM.value() config['offLAT'] = self.ui.offLAT.value() config['useDomeGeometry'] = self.ui.useDomeGeometry.isChecked() config['autoDomeDriver'] = self.ui.autoDomeDriver.isChecked() config['useDynamicFollowing'] = self.ui.useDynamicFollowing.isChecked() config['settleTimeDome'] = self.ui.settleTimeDome.value() return True def setZoffGEMInMount(self): """ :return: """ self.app.mount.geometry.offVertGEM = self.ui.domeZoffGEM.value() self.ui.domeZoff10micron.setValue(self.app.mount.geometry.offVert) self.app.updateDomeSettings.emit() return True def setZoff10micronInMount(self): """ :return: """ self.app.mount.geometry.offVert = self.ui.domeZoff10micron.value() self.ui.domeZoffGEM.setValue(self.app.mount.geometry.offVertGEM) self.app.updateDomeSettings.emit() return True def setUseGeometry(self): """ setUseGeometry updates the mount class with the new setting if use geometry for dome calculation should be used or not. :return: true for test purpose """ if self.ui.autoDomeDriver.isChecked(): self.updateDomeGeometryToGui() self.app.mount.geometry.domeRadius = self.ui.domeRadius.value() self.app.dome.radius = self.ui.domeRadius.value() self.app.mount.geometry.offGEM = self.ui.offGEM.value() self.app.mount.geometry.offLAT = self.ui.offLAT.value() self.app.mount.geometry.offNorth = self.ui.domeNorthOffset.value() self.app.mount.geometry.offEast = self.ui.domeEastOffset.value() clearOpening = self.ui.domeClearOpening.value() self.app.dome.clearOpening = clearOpening self.ui.domeOpeningHysteresis.setMaximum(clearOpening / 2.1) self.app.dome.openingHysteresis = self.ui.domeOpeningHysteresis.value() self.app.dome.clearanceZenith = self.ui.domeClearanceZenith.value() useGeometry = self.ui.useDomeGeometry.isChecked() self.app.dome.useGeometry = useGeometry useDynamicFollowing = self.ui.useDynamicFollowing.isChecked() self.app.dome.useDynamicFollowing = useDynamicFollowing self.app.dome.overshoot = self.ui.useOvershoot.isChecked() self.app.updateDomeSettings.emit() return True def updateDomeGeometryToGui(self): """ :return: true for test purpose """ value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_OTA_OFFSET', 0)) self.ui.offGEM.setValue(value) value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_DOME_RADIUS', 0)) self.ui.domeRadius.setValue(value) value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_SHUTTER_WIDTH', 0)) self.ui.domeClearOpening.setValue(value) value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_NORTH_DISPLACEMENT', 0)) self.ui.domeNorthOffset.setValue(value) value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_EAST_DISPLACEMENT', 0)) self.ui.domeEastOffset.setValue(value) value = float(self.app.dome.data.get('DOME_MEASUREMENTS.DM_UP_DISPLACEMENT', 0)) self.ui.domeZoffGEM.setValue(value) return True def setDomeSettlingTime(self): """ :return: true for test purpose """ self.app.dome.settlingTime = self.ui.settleTimeDome.value() return True def updateShutterStatGui(self): """ :return: True for test purpose """ value = self.app.dome.data.get('DOME_SHUTTER.SHUTTER_OPEN', None) if value is True: self.changeStyleDynamic(self.ui.domeOpenShutter, 'running', True) self.changeStyleDynamic(self.ui.domeCloseShutter, 'running', False) elif value is False: self.changeStyleDynamic(self.ui.domeOpenShutter, 'running', False) self.changeStyleDynamic(self.ui.domeCloseShutter, 'running', True) else: self.changeStyleDynamic(self.ui.domeOpenShutter, 'running', False) self.changeStyleDynamic(self.ui.domeCloseShutter, 'running', False) value = self.app.dome.data.get('Status.Shutter', None) if value: self.ui.domeShutterStatusText.setText(value) return True def domeAbortSlew(self): """ :return: """ suc = self.app.dome.abortSlew() if not suc: self.app.message.emit('Dome slew abort could not be executed', 2) return suc def domeOpenShutter(self): """ :return: """ suc = self.app.dome.openShutter() if not suc: self.app.message.emit('Dome open shutter could not be executed', 2) return suc def domeCloseShutter(self): """ :return: """ suc = self.app.dome.closeShutter() if not suc: self.app.message.emit('Dome close shutter could not be executed', 2) return suc

41.278571

91

0.661447

1,209

11,558

6.303557

0.160463

0.085028

0.063378

0.045663

0.577352

0.433539

0.240257

0.123737

0.098281

0

0.009336

0.212234

11,558

279

92

41.426523

0.827677

0.090587

0

0.186441

0

0.080084

0.027694

0

1

0.124294

false

0

0.19209

0

null

0

null

0

1

0

0f468cd48e78952f7f0e78c7dfbb72964775a0d2

2,179

py

Python

lib/mixer.py

voc/multiview-monitor

b1435d6613882e3ebbc05589e5265fe596fbfed2

[ "MIT" ]

51

2016-02-02T00:51:24.000Z

2022-02-03T21:46:20.000Z

lib/mixer.py

voc/multiview-monitor

b1435d6613882e3ebbc05589e5265fe596fbfed2

[ "MIT" ]

null

lib/mixer.py

voc/multiview-monitor

b1435d6613882e3ebbc05589e5265fe596fbfed2

[ "MIT" ]

5

2017-02-03T11:23:18.000Z

2021-06-21T15:49:28.000Z

#!/usr/bin/python3 import os, logging, gi, math from gi.repository import Gst # import library components from lib.config import Config class Mixer(object): output_width = 0 output_height = 0 def __init__(self): self.log = logging.getLogger('Mixer') self.sources = [] def append(self, source): self.sources.append(source) def configure(self): grid = Config.get('output', 'grid') grid_width, grid_height = [int(n) for n in grid.split('x', 1)] self.log.info('Configuring grid of %ux%u tiles', grid_width, grid_height) # intervideosrc(es) -> videomixer -> intervideosink pipeline = """ compositor name=mix """ pos_x = 0 pos_y = 0 col_w = 0 for tile_x in range(0, grid_width): pos_y = 0 pos_x += col_w col_w = 0 self.log.debug('') for tile_y in range(0, grid_height): index = tile_x * grid_height + tile_y source = self.sources[index] self.log.debug('Placing tile #%2u %u/%u of type %10s (size: %4u/%4upx) at %4u/%4upx in the viewport', index, tile_x, tile_y, source.type, source.width, source.height, pos_x, pos_y) pipeline += """ sink_{index}::xpos={x} sink_{index}::ypos={y} sink_{index}::width={width} sink_{index}::height={height} """.format( index=index, x=pos_x, y=pos_y, width=source.width, height=source.height, ) pos_y += source.height col_w = max(col_w, source.width) self.log.debug('') self.output_width = pos_x + col_w self.output_height = pos_y self.log.info('Calculated final grid-size to be %ux%upx', self.output_width, self.output_height) pipeline += """ ! intervideosink channel=out """.format( ) for source in self.sources: pipeline += """ intervideosrc channel=in_{name} ! video/x-raw,width={width},height={height} ! textoverlay text={name} font-desc="Normal 40" ! mix. """.format( name=source.name, width=source.width, height=source.height, ) self.log.debug('Configured Mix-Pipeline:\n%s', pipeline) self.pipeline = Gst.parse_launch(pipeline) def start(self): self.log.debug('Starting Mix-Pipeline') self.pipeline.set_state(Gst.State.PLAYING)

22.936842

108

0.654429

320

2,179

4.309375

0.315625

0.040609

0.04351

0.027556

0.049311

0

0.011448

0.198256

2,179

94

109

23.180851

0.777905

0.04268

0

0.231884

0

0.028986

0.263082

0.067691

0

1

0.057971

false

0

0.043478

0

0.144928

0

null

0

null

0

1

0

0f471508739ee756f36bead1b4722b0b4521114d

2,747

py

Python

src/parse/city_extractor.py

hse-ml-da/drink_cider

96e76c8f1429b7776b3b9055ed98b4835dd2b6a9

[ "Apache-2.0" ]

1

2021-06-20T17:29:16.000Z

src/parse/city_extractor.py

hse-ml-da/drink_cider

96e76c8f1429b7776b3b9055ed98b4835dd2b6a9

[ "Apache-2.0" ]

null

src/parse/city_extractor.py

hse-ml-da/drink_cider

96e76c8f1429b7776b3b9055ed98b4835dd2b6a9

[ "Apache-2.0" ]

null

from os.path import join from typing import Optional from natasha import Doc from natasha.grammars.addr import Settlement, INT, DOT, TITLE, NOUN, ADJF, DASH from yargy import Parser, or_, rule, and_ from yargy.pipelines import morph_pipeline from yargy.predicates import in_caseless, caseless, normalized, dictionary from yargy.rule import InterpretationRule class CityExtractor: __city_abbreviations = { "Москва": ["мск"], "Санкт-Петербург": ["спб", "питер", "петербург", "расчленинград"], "Новосибирск": ["нск"], "Екатеринбург": ["екб"], } __simple_city_names_file = join("src", "resources", "simple_city_names.txt") __complex_city_names_file = join("src", "resources", "complex_city_names.txt") def __init__(self): yargi_interpolation_rule = self.__rebuild_yargi_parser_rules() self.__yargi_parser = Parser(yargi_interpolation_rule) def extract_city(self, message: Doc) -> Optional[str]: for span in message.spans: if span.type == "LOC": return self.__back_translation(span.normal) for token in message.tokens: if self.__yargi_parser.match(token.lemma) is not None: return self.__back_translation(token.lemma) return None def __back_translation(self, city: str) -> str: for name, abbreviation in self.__city_abbreviations.items(): if city.lower() in abbreviation: return name return city def __rebuild_yargi_parser_rules(self) -> InterpretationRule: with open(self.__simple_city_names_file, "r") as f: simple_city_names = dictionary([name.strip() for name in f]) with open(self.__complex_city_names_file, "r") as f: complex_city_names = morph_pipeline([name.strip() for name in f]) city_abbreviations = in_caseless(sum(self.__city_abbreviations.values(), [])) city_name = or_(rule(simple_city_names), complex_city_names, rule(city_abbreviations)).interpretation( Settlement.name ) simple_name = and_(TITLE, or_(NOUN, ADJF)) complex_name = or_( rule(simple_name, DASH.optional(), simple_name), rule(TITLE, DASH.optional(), caseless("на"), DASH.optional(), TITLE), ) name = or_(rule(simple_name), complex_name) maybe_city_name = or_(name, rule(name, "-", INT)).interpretation(Settlement.name) city_words = or_(rule(normalized("город")), rule(caseless("г"), DOT.optional())).interpretation( Settlement.type.const("город") ) city = or_(rule(city_words, maybe_city_name), rule(city_words.optional(), city_name)).interpretation(Settlement) return city

42.261538

120

0.666545

329

2,747

5.243161

0.303951

0.052174

0.043478

0.027826

0.129855

0.075362

0

0.220604

2,747

64

121

42.921875

0.805698

0

0.037037

0

0.061522

0.015653

0

1

0.074074

false

0

0.148148

0

0.407407

0

null

0

null

0

1

0

0f475cd22072cd673e6e509fb236783e4554da6a

13,336

py

Python

TEmarker_utils/TM_genos_combine_ref_close_loci.py

yanhaidong1/TEmarker

120a9555d075c14db8b2c6a409d8df96e4acfead

[ "BSD-3-Clause" ]

2

2022-01-17T19:29:58.000Z

2022-02-23T02:03:12.000Z

TEmarker_utils/TM_genos_combine_ref_close_loci.py

yanhaidong1/TEmarker

120a9555d075c14db8b2c6a409d8df96e4acfead

[ "BSD-3-Clause" ]

1

2022-03-30T06:43:20.000Z

2022-03-30T12:22:42.000Z

TEmarker_utils/TM_genos_combine_ref_close_loci.py

yanhaidong1/TEmarker

120a9555d075c14db8b2c6a409d8df96e4acfead

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python ##updation 122120 change the c and s cover case ##updation 121920 add the case when first line is the last one ##updation 110220this version did not consider the s or c is covered by the reference we need to have a check ##we need to generate a dic to store the s or c TEs that are covered by the o type and finally, we will filter out these locations ##this script we will combine the close loci with the overlapped regions ##import modules import re def combine_close_loci (genotype_fl,working_dir): ######## ##step 1: store the id line and store the same o to one dic ##generate a temp genotype file with id information store_id_line_list = [] count = 0 with open (genotype_fl,'r') as ipt: for eachline in ipt: count += 1 eachline = eachline.strip('\n') new_line = str(count) + '\t' + eachline store_id_line_list.append(new_line) with open (working_dir + '/temp_te_genotype_annot_add_id.txt','w+') as opt: for eachline in store_id_line_list: opt.write(eachline + '\n') ##initial a list contain all the TE situations dic_list = [] ##initial a dictionary to store the target lines dic_te = {} ##get the last id with open(working_dir + '/temp_te_genotype_annot_add_id.txt', 'r') as ipt_rmk_out: last_line = ipt_rmk_out.readlines()[-1] last_col = last_line.strip().split() last_id = last_col[0] ##updation 110220 store_covered_c_with_o_loc_dic = {} ##store the te infor with open(working_dir + '/temp_te_genotype_annot_add_id.txt', 'r') as ipt_rmk_out: for line in ipt_rmk_out: col = line.strip().split() chr = col[1] #te_nm = col[4] id = col[0] bg = col[2] ed = col[3] #dir = col[3] #lib_bg = col[5] #lib_ed = col[6] #lib_left = col[7] comb_type = col[4] if id == str(1): ##if the id is 1, it will directly store in the dic_te dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type':comb_type, 'line':line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) else: ##if the id is over 1 ##if the chr is the same as the previous one if dic_te[str(int(id) - 1)]['chr'] == chr: if dic_te[str(int(id) - 1)]['comb_type'] == comb_type: ##if the comb_type is the same if comb_type == 'o': ##detect whether they are overlapped pre_st = dic_te[str(int(id) - 1)]['begin'] pre_ed = dic_te[str(int(id) - 1)]['end'] ##it means there is a overlap if int(ed) >= int(pre_st) and int(bg) <= int(pre_ed): dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type': comb_type, 'line': line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) else: ##if there is no overlap we will store the previous dic and assign a new dic id dic_list.append(dic_te) dic_te = {} dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type': comb_type, 'line': line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) else: ##directly store the previous dic and assign a new dic id dic_list.append(dic_te) dic_te = {} dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type': comb_type, 'line': line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) ##if the comb_type is not the same ##we also need to store else: ##updation 110520 ##it means the pre comb_type is o and current is c or s pre_comb_type = dic_te[str(int(id) - 1)]['comb_type'] if pre_comb_type == 'o': ##the current is s or c ##or the pre comb_type is c or s and current o ##updation 110220 we need to check whether the c is covered with the o ##detect whether they are overlapped pre_st = dic_te[str(int(id) - 1)]['begin'] pre_ed = dic_te[str(int(id) - 1)]['end'] ##it means there is a overlap if int(ed) >= int(pre_st) and int(bg) <= int(pre_ed): loc_str = chr + '_' + bg + '_' + ed store_covered_c_with_o_loc_dic[loc_str] = 1 else: ##updation 122120 ##if the pre is s or c ##the current could be o ##or could be s or c if comb_type == 'o': ##if the pre is s or c ##the current is o pre_st = dic_te[str(int(id) - 1)]['begin'] pre_ed = dic_te[str(int(id) - 1)]['end'] if int(ed) >= int(pre_st) and int(bg) <= int(pre_ed): loc_str = chr + '_' + pre_st + '_' + pre_ed store_covered_c_with_o_loc_dic[loc_str] = 1 ##if current is not o so it would be c or s ##the reason to case this case is because we enlarge the searching range from s and c case ##and allow there are some overlapping ##in this case, we need to follow the single case TE since the combined case ##there is no else since we will modify the searching range that allows there is no cover for the s and c #else: dic_list.append(dic_te) dic_te = {} dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type': comb_type, 'line': line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) else: ##if the chr is not the same as the previous one ##store the dic_te which has been stored the te informations dic_list.append(dic_te) dic_te = {} dic_te[id] = {'chr': chr, 'begin': bg, 'end': ed, 'comb_type': comb_type, 'line': line} if id == last_id: ##should be out of the previous loop dic_list.append(dic_te) #print(dic_list) print(store_covered_c_with_o_loc_dic) ######## ##step 2: combine the overlapped o ref loci store_final_line_list = [] ##updation 110220 write a file to show whether we remove some locations for the c and s store_remove_c_s_line_list = [] #comb_count = 0 for each_te_dic in dic_list: if len(each_te_dic.keys()) == 1: final_line_no_id_str = '' for eachid in each_te_dic: ##key is id 1,2,3,4,5 line = each_te_dic[eachid]['line'] col_line = line.strip().split() first_item = col_line[1] final_line_no_id_str = first_item for eachid in each_te_dic: ##key is id 1,2,3,4,5 line = each_te_dic[eachid]['line'] col_line = line.strip().split() for i in range (2,len(col_line)): final_line_no_id_str = final_line_no_id_str + '\t' + col_line[i] ##updation 110220 check location of c or s TE wrong_count = 0 for eachid in each_te_dic: chr = each_te_dic[eachid]['chr'] bg = each_te_dic[eachid]['begin'] ed = each_te_dic[eachid]['end'] loc_infor = chr + '_' + bg + '_' + ed if loc_infor in store_covered_c_with_o_loc_dic: wrong_count += 1 if wrong_count == 0: store_final_line_list.append(final_line_no_id_str) else: store_remove_c_s_line_list.append(final_line_no_id_str) else: #comb_count += 1 #print(len(each_te_dic.keys()) ) #print(each_te_dic) ##it means we need to decide a new o locus ##first we need to select the smallest bg bg_list = [] ed_list = [] chr = '' ##since we need to generate a new genotype line we need to extract the the first several col information ori_id = '' #ori_num = '' #ori_total = '' #ori_pro = '' ori_geno = 'o' #ori_sap_infor_str = '' ori_te_nm = '' for eachid in each_te_dic: bg = int(each_te_dic[eachid]['begin']) bg_list.append(bg) ed = int(each_te_dic[eachid]['end']) ed_list.append(ed) chr = each_te_dic[eachid]['chr'] ori_line = each_te_dic[eachid]['line'] ori_line_col = ori_line.split() ori_id = ori_line_col[0] #ori_num = ori_line_col[4] #ori_total = ori_line_col[5] #ori_pro = ori_line_col[6] ori_te_nm = ori_line_col[5] #ori_sap_infor_str = ori_line_col[8] smallest_bg = min(bg_list) largest_ed = max(ed_list) ##second we need to store the name of the sample store_sp_name_dic = {} for eachid in each_te_dic: loc_line = each_te_dic[eachid]['line'] loc_col = loc_line.split() for i in range(6,len(loc_col)): mt = re.match('(.+):.+',loc_col[i]) sp_nm = mt.group(1) store_sp_name_dic[sp_nm] = 1 #print(store_sp_name_dic) ##third we need analyze on each sample store_sp_str = '' ##DRR054229:0.0;0/15;0/0;Unknown_TE DRR054234:0.0;0/4;0/0;Unknown_TE for eachsp in store_sp_name_dic: #store_geno_value_list = [] ##1/1: 2, 0/1:1, 0/0:0 ##then we need to compare the value of them and select the largest one sp_id = 0 ## store_same_sp_loc_dic = {} ##key is the sp_id (0 or 1 or 2...) and value has two part, first is the geno line (eg. DRR054241:0.0;0/7;0/0;Unknown_TE) and second is geno_value for eachid in each_te_dic: loc_line = each_te_dic[eachid]['line'] loc_col = loc_line.split() for i in range(6, len(loc_col)): mt = re.match('(.+):.+', loc_col[i]) sp_nm = mt.group(1) if eachsp == sp_nm: sp_id += 1 ##so the sp_id is the location id since if we allow the eachsp == sp_nm so there is only one value from 6 to len(loc_col) ##since this is the genos file so there is no missing information geno_line = loc_col[i] geno_col = geno_line.split(';') geno = geno_col[2] geno_value = '' if geno == '0/0': geno_value = 0 if geno == '0/1': geno_value = 1 if geno == '1/1': geno_value = 2 #store_geno_value_list.append(geno_value) store_same_sp_loc_dic[str(sp_id) + '_' + geno_line] = geno_value ##eg 1_DRR054229:0.0;0/15;0/0;LTR max_geno_id = max(store_same_sp_loc_dic, key=store_same_sp_loc_dic.get) #print(max_geno_id) mt = re.match('.+?_(.+)',max_geno_id) real_id = mt.group(1) ##DRR054229:0.0;0/15;0/0;LTR #print(real_id) store_sp_str = store_sp_str + '\t' + real_id ##generate the final line final_line = chr + '\t' + str(smallest_bg) + '\t' + str(largest_ed) + '\t' + 'o' + '\t' + ori_te_nm + store_sp_str store_final_line_list.append(final_line) return (store_final_line_list,store_remove_c_s_line_list)

40.907975

162

0.484253

1,792

13,336

3.364397

0.128906

0.026538

0.031348

0.027368

0.458119

0.40073

0.354288

0.329574

0.322276

0.296401

0

0.026367

0.42269

13,336

325

163

41.033846

0.756722

0.270021

0

0.436364

0

0.04192

0.01069

0

1

0.006061

false

0

0.006061

0

0.018182

0.006061

0

null

0

null

0

1

0

0f4b04a45100aa19af536e46188a9406fa130b44

15,027

py

Python

MATTS/runner.py

mwesleyj/geo-deep-learning

9bb8942156fc1a19f8f5ac911e237daa30740ca9

[ "MIT" ]

null

MATTS/runner.py

mwesleyj/geo-deep-learning

9bb8942156fc1a19f8f5ac911e237daa30740ca9

[ "MIT" ]

null

MATTS/runner.py

mwesleyj/geo-deep-learning

9bb8942156fc1a19f8f5ac911e237daa30740ca9

[ "MIT" ]

null

import argparse, io, sys, os, h5py from pathlib import Path from ruamel_yaml import YAML import csv from PIL import Image import numpy as np from rich.console import Console, RenderGroup from rich.panel import Panel from rich.text import Text from rich.table import Table from rich.tree import Tree from rich.columns import Columns from rich import box from torchsummary import summary as torch_summary # from ray import tune # from ray.tune import CLIReporter # from ray.tune.schedulers import ASHAScheduler # from utils.tracker import Tracker from models.model_choice import net from images_to_samples import main as IM_TO_SAMPLES_main from train_segmentation import main as TRAIN_main def make_csv_trckr(csv_filename): """ Open csv file and parse it, returning a list of dict. - tif full path - metadata yml full path (may be empty string if unavailable) - gpkg full path - attribute_name - dataset (trn or tst) """ list_values = [] with open(csv_filename, 'r') as f: reader = csv.reader(f) for index, row in enumerate(reader): row_length = len(row) if index == 0 else row_length assert len(row) == row_length, "Rows in csv should be of same length" row.extend([None] * (5 - len(row))) # fill row with None values to obtain row of length == 5 list_values.append({'tif': row[0], 'meta': row[1], 'gpkg': row[2], 'attribute_name': row[3], 'dataset': row[4]}) assert Path(row[0]).is_file(), f'Tif raster not found "{row[0]}"' if row[2]: assert Path(row[2]).is_file(), f'Gpkg not found "{row[2]}"' assert isinstance(row[3], str) try: # Try sorting according to dataset name (i.e. group "train", "val" and "test" rows together) list_values = sorted(list_values, key=lambda k: k['dataset']) except TypeError: list_values return list_values def read_params(param_file): yaml = YAML() yaml.preserve_quotes = True with open('./config/travis_CI/config_ci_segmentation_local.yaml') as fp: data = yaml.load(fp) fp.close() return data def write_params(param_file, data): yaml = YAML() with open('./config/travis_CI/config_ci_segmentation_local.yaml', 'w') as fp: yaml.dump(data, fp) fp.close() def save_samp_ims(data_location, experiment_dir, set): dataset_ims_to_show = ('map_img', 'sat_img') f = h5py.File(data_location + '\\' + experiment_dir + '\\' + set + '_samples.hdf5', 'r') for dataset_name in dataset_ims_to_show: dataset = f[dataset_name] for imN in range(dataset.shape[0]): print(dataset_name) print(dataset[imN,...].shape[0]) sample_html = open('hello.html', 'w+') sample_html.close() if __name__ == '__main__': # 0) read in params parser = argparse.ArgumentParser(description='Sample preparation') parser.add_argument('ParamFile', metavar='DIR',help='Path to training parameters stored in yaml') args = parser.parse_args() param_path = Path(args.ParamFile) print(args.ParamFile) params = read_params(args.ParamFile) # 1) options #----------------------------------------------------------------------------------------------------------------------- OPTS = {'HPC' : False, 'show model layers' : False, 'vis_samples' : True, 'output_html' : 'test', 'out_html_dir' : ''} # config = {"l1": tune.sample_from(lambda _: 2**np.random.randint(2, 9)), # "l2": tune.sample_from(lambda _: 2**np.random.randint(2, 9)), # "lr": tune.loguniform(1e-4, 1e-1), # "batch_size": tune.choice([2, 4, 8, 16])} path_name = 'samples'+ \ str(params['global']['samples_size'])+ \ '_overlap'+ \ str(params['sample']['overlap'])+ \ '_min-annot'+ \ str(params['sample']['sampling_method']['min_annotated_percent'])+ \ '_'+\ str(params['global']['number_of_bands'])+ \ 'bands_'+ \ str(params['global']['mlflow_experiment_name']) # 2) set up console #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - console = Console(record=True) # width=... if OPTS['HPC']: sys.stdout = open(os.devnull, "w") # 3) run im-samp & prints #----------------------------------------------------------------------------------------------------------------------- console.print(' DEBUG = ', params['global']['debug_mode'], style='bold purple', justify='left') console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='left',style='bold #FFFFFF on #000000') console.print('STEP 1:',justify='center',style='bold #FFFFFF on #000000') console.print('MAKE SAMPLES',justify='center',style='bold #FFFFFF on #000000') console.print(' ',justify='left',style='bold #FFFFFF on #000000') console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='center',style='on #FFFFFF') # info Panel txt = Text('parent dir =\t') txt.append(params['global']['data_path']) txt.append('\nsmples dir =\t') txt.append(path_name) txt.append('\ncsv =\t') txt.append(params['sample']['prep_csv_file']) params['sample']['prep_csv_file'] = 'C:/Users/muzwe/Documents/GitHub' if os.path.isdir(Path(params['global']['data_path']+'/'+path_name)): console.print(Panel(txt,title='NOT, prcessing new Samples', style='red')) else: console.print(Panel(txt,title='YES, prcessing new Samples', style='green')) IM_TO_SAMPLES_main(params, console) # output data panel trees = [] num_samples = {} for sN, set in enumerate(['trn', 'tst', 'val']): trees.append(Tree(set, style='color('+str(sN+2)+')')) with h5py.File(params['global']['data_path'] + '/' + path_name + '/' + set + '_samples.hdf5', 'r') as f: for dataset_name in ('map_img', 'sat_img'): dataset = f[dataset_name] new = trees[sN].add(dataset_name) new.add('[white]'+str(dataset.shape[0])) new.add(str(dataset.shape)) num_samples[set] = dataset.shape[0] console.print(Panel(Columns((trees[0], trees[1], trees[2]), equal=True, expand=True), title='Smples output')) # 4) run training # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='left',style='bold #FFFFFF on #000000') console.print('STEP 2:',justify='center',style='bold #FFFFFF on #000000') console.print('TRAIN',justify='center',style='bold #FFFFFF on #000000') console.print(' ',justify='left',style='bold #FFFFFF on #000000') console.print(' ',justify='center',style='on #FFFFFF') console.print(' ',justify='center',style='on #FFFFFF') # assert model info # console.print(' ',justify='center',style='on #FFFFFF') # console.print(' model = ',params['global']['model_name'],justify='center',style='bold #FFFFFF on #000000') # console.print(' ',justify='center',style='on #FFFFFF') # # if params['global']['model_name'] == 'deeplabv3_resnet101': # table = Table(title='[bold]deeplabv3_resnet101', show_lines=True, expand=True) # table.add_column('required stat',justify="center", style="cyan", no_wrap=True) # table.add_column('[#787878]op', justify="center", style="cyan", no_wrap=True) # table.add_column('requirement',justify="center", style="cyan", no_wrap=True) # table.add_column('assert',justify="center", style="cyan", no_wrap=True) # # table.add_row('range', '=', str([0, 1]), str([0, 1]==params['global']['scale_data'])) # table.add_row('mean', '=', str([0.485, 0.456, 0.406]))#, str(np.equal([0.485, 0.456, 0.406], params['global']['scale_data']))) # table.add_row('std', '=', str([0.229, 0.224, 0.225]))#, str(np.equal([0.229, 0.224, 0.225], params['global']['scale_data']))) # table.add_row('min_pixel_res', '>=', str(224))#,str(224>=0)) # # console.print(table) # console.print(' ',justify='center',style='on #FFFFFF') # info Panel list = Table(expand=True, show_lines=True, style="orchid1") list.add_column('[bold]catagory',justify='center', no_wrap=False) list.add_column('[bold]path',justify='center', no_wrap=False) list.add_column('[bold]exists?',justify='center', no_wrap=False) list.add_row('parent dir', str(params['global']['data_path']), str(Path(params['global']['data_path']).is_dir())) list.add_row('samples dir', str(path_name), str(Path(params['global']['data_path']).joinpath(path_name).is_dir())) list.add_row('model dir', 'model_' + str(params['global']['model_output_dir']), str(Path(params['global']['data_path']).joinpath(path_name).joinpath('model_' + str(params['global']['model_output_dir'])).is_dir())) txt = Text(justify='center') # txt.append_text(Text('model = ' + str(params['global']['model_name']) + '\n', style='bold cyan2')) # txt.append_text(Text('loss = ' + str(params['training']['loss_fn']) + '\n', style='bold cyan2')) # txt.append_text(Text('optmzr = ' + str(params['training']['optimizer']) + '\n', style='bold cyan2')) def list_layers(model, count): modules = dict(model.named_modules()) keys = [] for key in modules: if key == '': continue console.print(key, justify='right')#, style='color('+str(count)+')') console.print(modules[key], justify='left')#, style='color('+str(count)+')') # console.print(dict(modules[key].named_modules()), justify='center', style='color('+str(count)+')') console.print(count, justify='center', style='on color('+str(count)+')') list_layers(modules[key], count+1) console.print(count, justify='center', style='on color('+str(count)+')') # model layers if OPTS['show model layers']: txt.append('\n\n') model, model_name, criterion, optimizer, lr_scheduler = net(params, params['global']['num_classes']+1) # console.print(len(dict(model.named_modules()))) # console.print(dict(model.named_modules())) # console.print() list_layers(model, 0) sys.exit() try: summary = torch_summary(model, (params['global']['number_of_bands'], params['global']['samples_size'], params['global']['samples_size'])) table = Table(title=params['global']['model_name'], expand=True) table.add_column("Layer (type)", justify="center", style="bright_cyan", no_wrap=True) table.add_column("Output Shape", justify="center", style="bright_cyan", no_wrap=True) table.add_column("Param #", justify="center", style="bright_cyan", no_wrap=True) for layer in summary: table.add_row(layer, str(summary[layer]["output_shape"]), "{0:,}".format(summary[layer]["nb_params"])) console.print(Panel(RenderGroup(txt,table, summary['final_summary']), title='pre-training info', box=box.DOUBLE_EDGE, style="magenta1")) console.print(str(model)) except AttributeError: console.print(Panel(RenderGroup(txt,Text('model = ' + str(params['global']['model_name']))), title='pre-training info', box=box.DOUBLE_EDGE, style="magenta1")) console.print(str(model)) else: console.print(Panel(RenderGroup(list, txt), title='pre-training info', box=box.DOUBLE_EDGE, style="magenta1")) changes = {} changes['learning_rate'] = [0.0001] changes['weight_decay'] = [0] changes['step_size'] = [4] changes['gamma'] = [0.9] experiments = Table('exp. num.', 'model', 'optimzier', 'loss func', 'learning_rate', 'weight_decay', 'step_size', 'gamma', title='experiments', expand=True, style='purple') experiments.add_row(str(1), str(params['training']['learning_rate']), str(params['training']['weight_decay']), str(params['training']['step_size']), str(params['training']['gamma'])) console.print(experiments) for change in changes: params['training'][change] = changes[change][0] # if params['training']['loss_fn'] == 'Lovasz': # params['training']['class_weights'] = None trckr = h5py.File('output_path', 'w') # for set in ['trn', 'tst', 'val']: # trckr.create_group(set) trckr.create_dataset('acc') trckr.create_dataset('pers') trckr.create_dataset('iou') trckr.create_dataset('fscore') write_params(args.ParamFile, params) TRAIN_main(params, param_path, console, trckr) # TODO: make sure model_NAME doesnt exist already #----------------------------------------------------------------------------------------------------------------------- # console.export_html(clear=False) # console.save_html(OPTS['output_html']+'.html', clear=False) # #----------------------------------------------------------------------------------------------------------------------- # # from rich.tree import Tree # tree = Tree("Rich Tree") # baz_tree = tree.add("baz") # tree.add("baz") # baz_tree.add("[red]Red").add("[green]Green").add("[blue]Blue") # # console.print(tree) # # #----------------------------------------------------------------------------------------------------------------------- # # from rich.columns import Columns # columns = Columns((tree, tree), equal=True, expand=True) # # console.print(columns) # # #----------------------------------------------------------------------------------------------------------------------- # # from rich.panel import Panel # panel = Panel(columns, title='[bold]just an example') # # console.print(panel) # # #----------------------------------------------------------------------------------------------------------------------- # # from rich.table import Table # table = Table(title="[bold]\nThe Worst Star Wars[/bold] Movies", show_lines=True) # table.add_column("Released", justify="center", style="cyan", no_wrap=True) # # table.add_row("Dec 20, 2019", "Star Wars: The Rise of Skywalker") # table.add_row("May 25, 2018", "Solo: A Star Wars Story", "$393,151,347") # console.print(table)

43.68314

150

0.562854

1,780

15,027

4.620225

0.202247

0.062743

0.059095

0.031615

0.366367

0.307758

0.266537

0.234801

0.222398

0.177408

0

0.018736

0.211486

15,027

344

151

43.68314

0.675331

0.320689

0

0.151042

0

0.21223

0.017786

0

0.002907

0.020833

1

0.026042

false

0

0.088542

0

0.125

0.171875

0

null

0

null

0

1

0

0f4fe424e452a2068dbc9a4317c9b75f67f3c367

1,157

py

Python

vaegan/utils/progress.py

amirjaber/vaegan

6b8f89f9c70b384d88158822f1a9beeaba5802f0

[ "MIT" ]

101

2016-03-20T04:29:16.000Z

2022-02-16T05:00:43.000Z

vaegan/utils/progress.py

amirjaber/vaegan

6b8f89f9c70b384d88158822f1a9beeaba5802f0

[ "MIT" ]

4

2017-02-14T01:20:49.000Z

2018-06-04T04:17:33.000Z

vaegan/utils/progress.py

amirjaber/vaegan

6b8f89f9c70b384d88158822f1a9beeaba5802f0

[ "MIT" ]

19

2016-07-29T12:32:39.000Z

2021-03-04T11:53:17.000Z

#coding : utf-8 import sys class Progress( object ): def __init__( self, max_count, size ): if size <= max_count: self.__size = size else: self.__size = max_count self.__max_count = max_count self.__sep = int(max_count/size) + 1 self.__count = 0 def prog( self ): if int( self.__count % self.__sep ) != 0: self.__count += 1 return p = int( self.__count / self.__sep ) + 1 s = u'|' + u'=' * p + u' ' * (self.__size-p) + u'| %d/%d' \ % (self.__count,self.__max_count) sys.stdout.write("\r%s" % s) sys.stdout.flush() self.__count += 1 def end( self ): self.__count = 0 p = self.__size s = u'|' + u'=' * p + u' ' * (self.__size-p) + u'| %d/%d' \ % (self.__max_count ,self.__max_count) sys.stdout.write("\r%s" % s) sys.stdout.flush() print >>sys.stdout if __name__ == '__main__': a = range(1000000) prog = Progress(len(a),50) for e in range(10): for i,v in enumerate(a): prog.prog() prog.end()

25.711111

67

0.491789

154

1,157

3.311688

0.298701

0.141176

0.117647

0.1

0.390196

0.270588

0

0.025435

0.354365

1,157

44

68

26.295455

0.657296

0.0121

0

0.285714

0

0.031524

0

1

0.085714

false

0

0.028571

0

0.171429

0.028571

0

null

0

null

0

1

0

0f5147d3f4e60c38090cf067509503b19803e937

1,124

py

Python

metadata-ingestion/tests/unit/stateful_ingestion/state/test_sql_common_state.py

bskim45/datahub

c10456d2bcc0f41d4b8361768e1e07ad0eb79f37

[ "Apache-2.0" ]

1,603

2016-03-03T17:21:03.000Z

2020-01-22T22:12:02.000Z

metadata-ingestion/tests/unit/stateful_ingestion/state/test_sql_common_state.py

bskim45/datahub

c10456d2bcc0f41d4b8361768e1e07ad0eb79f37

[ "Apache-2.0" ]

1,157

2016-03-03T19:29:22.000Z

2020-01-20T14:41:59.000Z

metadata-ingestion/tests/unit/stateful_ingestion/state/test_sql_common_state.py

bskim45/datahub

c10456d2bcc0f41d4b8361768e1e07ad0eb79f37

[ "Apache-2.0" ]

570

2016-03-03T17:21:05.000Z

2020-01-21T06:54:10.000Z

from datahub.emitter.mce_builder import make_container_urn, make_dataset_urn from datahub.ingestion.source.state.sql_common_state import ( BaseSQLAlchemyCheckpointState, ) def test_sql_common_state() -> None: state1 = BaseSQLAlchemyCheckpointState() test_table_urn = make_dataset_urn("test_platform", "db1.test_table1", "test") state1.add_table_urn(test_table_urn) test_view_urn = make_dataset_urn("test_platform", "db1.test_view1", "test") state1.add_view_urn(test_view_urn) test_container_urn = make_container_urn("test_container") state1.add_container_guid(test_container_urn) state2 = BaseSQLAlchemyCheckpointState() table_urns_diff = list(state1.get_table_urns_not_in(state2)) assert len(table_urns_diff) == 1 and table_urns_diff[0] == test_table_urn view_urns_diff = list(state1.get_view_urns_not_in(state2)) assert len(view_urns_diff) == 1 and view_urns_diff[0] == test_view_urn container_urns_diff = list(state1.get_container_urns_not_in(state2)) assert ( len(container_urns_diff) == 1 and container_urns_diff[0] == test_container_urn )

38.758621

86

0.774021

160

1,124

4.96875

0.25

0.090566

0.05283

0.064151

0.260377

0.181132

0.090566

0

0.021583

0.134342

1,124

28

87

40.142857

0.795478

0

0.068505

0

0.142857

1

0.047619

false

0

0.095238

0

0.142857

0

null

0

null

0

1

0

0f5202b60405893a1a16c170a0706a914d313c0f

2,636

py

Python

inn/inn_hotels/doctype/ar_city_ledger_invoice/ar_city_ledger_invoice.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

4

2021-08-19T03:33:36.000Z

2021-08-28T16:37:52.000Z

inn/inn_hotels/doctype/ar_city_ledger_invoice/ar_city_ledger_invoice.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

98

2020-02-24T08:12:47.000Z

2021-08-21T07:54:03.000Z

inn/inn_hotels/doctype/ar_city_ledger_invoice/ar_city_ledger_invoice.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

13

2021-01-24T18:08:43.000Z

2022-03-29T09:23:25.000Z

# -*- coding: utf-8 -*- # Copyright (c) 2020, Core Initiative and contributors # For license information, please see license.txt from __future__ import unicode_literals import frappe from frappe.model.document import Document class ARCityLedgerInvoice(Document): pass @frappe.whitelist() def get_payments_accounts(mode_of_payment): account = frappe.db.get_value('Mode of Payment Account', {'parent': mode_of_payment, 'company': frappe.get_doc( "Global Defaults").default_company}, "default_account") against = frappe.db.get_list('Account', filters={'account_number': '1133.001'})[0].name return account, against @frappe.whitelist() def make_payment(id): doc = frappe.get_doc('AR City Ledger Invoice', id) arc_id = [] folio_list = doc.folio if len(folio_list) == 0: frappe.msgprint("Please add the Folio to be Collected first before making payment") else: for folio in folio_list: arc_id.append(folio.ar_city_ledger_id) payments = doc.get('payments') return_status = 1 for payment in payments: remark = 'AR City Ledger Invoice Payments: ' + payment.name doc_je = frappe.new_doc('Journal Entry') doc_je.title = payment.name doc_je.voucher_type = 'Journal Entry' doc_je.naming_series = 'ACC-JV-.YYYY.-' doc_je.posting_date = payment.payment_reference_date doc_je.company = frappe.get_doc('Global Defaults').default_company doc_je.total_amount_currency = frappe.get_doc('Global Defaults').default_currency doc_je.remark = remark doc_je.user_remark = remark doc_jea_debit = frappe.new_doc('Journal Entry Account') doc_jea_debit.account = payment.account doc_jea_debit.debit = payment.payment_amount doc_jea_debit.debit_in_account_currency = payment.payment_amount doc_jea_debit.party_type = 'Customer' doc_jea_debit.party = doc.customer_id doc_jea_debit.user_remark = remark doc_jea_credit = frappe.new_doc('Journal Entry Account') doc_jea_credit.account = payment.account_against doc_jea_credit.credit = payment.payment_amount doc_jea_credit.credit_in_account_currency = payment.payment_amount doc_jea_credit.party_type = 'Customer' doc_jea_credit.party = doc.customer_id doc_jea_credit.user_remark = remark doc_je.append('accounts', doc_jea_debit) doc_je.append('accounts', doc_jea_credit) doc_je.save() doc_je.submit() if frappe.db.get_value('Journal Entry', {'title': payment.name}, 'remark') == remark: return_status = 2 if return_status == 1: doc.status = 'Paid' doc.save() for arc in arc_id: doc_arc_ledger = frappe.get_doc('AR City Ledger', arc) doc_arc_ledger.is_paid = 1 doc_arc_ledger.save() return return_status

34.233766

112

0.76214

393

2,636

4.811705

0.272265

0.050767

0.046536

0.048652

0.328398

0.268112

0.13432

0

0.007871

0.132398

2,636

77

113

34.233766

0.818977

0.046282

0

0.032258

0

0.162485

0

1

0.032258

false

0.016129

0.048387

0

0.129032

0.016129

0

null

0

null

0

1

0

0f541dfb90c1bf063d05a6e72bfe89bac2f84a44

1,572

py

Python

examples/maths/__init__.py

tryal-ai/mnkytw

28d78d0f378a985e4c5601bd28f8f5d2df57848e

[ "Apache-2.0" ]

null

examples/maths/__init__.py

tryal-ai/mnkytw

28d78d0f378a985e4c5601bd28f8f5d2df57848e

[ "Apache-2.0" ]

null

examples/maths/__init__.py

tryal-ai/mnkytw

28d78d0f378a985e4c5601bd28f8f5d2df57848e

[ "Apache-2.0" ]

null

import mnkytw from examples.maths.IntegerMatch import IntegerMatch from examples.maths.FloatMatch import FloatMatch # Create a single unified matcher that attempts to identify # an integer or a float Constants = mnkytw.MatchAlternation([ FloatMatch(), IntegerMatch() ]) # symbols Symbols = mnkytw.MatchAlternation([ mnkytw.LiteralMatch("+"), mnkytw.LiteralMatch("-"), mnkytw.LiteralMatch("*"), mnkytw.LiteralMatch("/") ]) class OperationMatch: def __init__(self): self.matcher = mnkytw.MatchAlternation([ # Either this is a chain of operations mnkytw.MatchJoin([ Constants, Symbols, self ]), # Or a constant Constants ]) def parser(self, body : str, hard_fail = True): result = self.matcher.parser(body, hard_fail) if not result: return result #we can infer that it matched the "MatchJoin" if it's a list if type(result[0]) is list: # make a dictionary that shows the lhs and rhs and the symbol return [{ 'lhs': result[0][0], 'symbol': result[0][1], 'rhs': result[0][2] }, result[1]] else: #Otherwise it matched the constant so just return the constant return result Operation = OperationMatch() print(mnkytw.peg_parse("3+4", Operation)) print(mnkytw.peg_parse("3+4+5", Operation)) print(mnkytw.peg_parse("3+4*5-6", Operation))

28.071429

74

0.585878

175

1,572

5.211429

0.445714

0.078947

0.118421

0.169956

0.067982

0

0.015712

0.311705

1,572

56

75

28.071429

0.827172

0.20229

0

0.128205

0

0.02488

0

1

0.051282

false

0

0.076923

0

0.230769

0.076923

0

null

0

null

0

1

0

0f5698174d653f570858341752fa6fba2fa609e8

354

py

Python

WEEKS/CD_Sata-Structures/general/practice/BeautifulText/solution.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/CD_Sata-Structures/general/practice/BeautifulText/solution.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/CD_Sata-Structures/general/practice/BeautifulText/solution.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

def beautifulText(inputString, l, r): for w in range(l, r + 1): i = w while i < len(inputString): if inputString[i] != " ": break i += w + 1 if i == len(inputString): return True return False s = "Look at this example of a correct text" print(beautifulText(s, 5, 15))

23.6

44

0.50565

47

354

3.808511

0.638298

0.022346

0.167598

0

0.022936

0.384181

354

14

45

25.285714

0.798165

0

0.110169

0

1

0.083333

false

0

0.25

0.083333

0

null

0

null

0

1

0

0f591d0adbc9428bd5196057d6b311feb4ee4e6e

20,015

py

Python

api/stacking/stacking.py

ruizca/rapidxmm

4b2dacefcb73464ad4dfd6d404b5795a15046ffc

[ "MIT" ]

3

2021-06-24T07:53:15.000Z

2022-03-18T12:03:26.000Z

api/stacking/stacking.py

ruizca/rapidxmm

4b2dacefcb73464ad4dfd6d404b5795a15046ffc

[ "MIT" ]

null

api/stacking/stacking.py

ruizca/rapidxmm

4b2dacefcb73464ad4dfd6d404b5795a15046ffc

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Fri Apr 16 16:13:39 2021 @author: ruizca """ import matplotlib.pyplot as plt import numpy as np from astropy import units as u from astropy.coordinates import SkyCoord, FK5 from astropy.table import Table, unique, join from astropy.utils.console import color_print from astropy_healpix import HEALPix from matplotlib.collections import PatchCollection from matplotlib.colors import Normalize from matplotlib.patches import Polygon from mocpy import MOC from mocpy.mocpy import flatten_pixels from scipy.stats import median_abs_deviation from tqdm.auto import tqdm from .. import rapidxmm from .ecf import ECF plt.rc('font', family='serif') plt.rc('xtick', labelsize='x-small') plt.rc('ytick', labelsize='x-small') #plt.rc('text', usetex=True) plt.rcParams['mathtext.fontset'] = "stix" plt.rcParams['mathtext.rm'] = "STIXGeneral" plt.rcParams['font.family'] = "STIXGeneral" plt.rcParams["axes.formatter.use_mathtext"] = True # Numpy random number generator rng = np.random.default_rng() def get_neighbours(npixel, hp, level=5): # The central pixel is the first one # The output of hp.neighbours always follows the # same order, starting SW and rotating clockwise neighbours_level = [None] * (level + 1) neighbours_level[0] = [npixel] npixel_neighbours = [npixel] for i in range(1, level + 1): neighbours_level[i] = hp.neighbours(neighbours_level[i - 1]).flatten() npixel_neighbours += list(neighbours_level[i]) sorted_neighbours = Table() sorted_neighbours["npixel"] = npixel_neighbours sorted_neighbours["order"] = range(len(npixel_neighbours)) sorted_neighbours = unique(sorted_neighbours, keys=["npixel"]) sorted_neighbours.sort("order") return sorted_neighbours def get_bkg_npixels(src_center, nside, npixels=100): order = np.log2(nside).astype(int) bkg_moc_outer = MOC.from_cone(src_center.ra, src_center.dec, 120*u.arcsec, order) bkg_moc_inner = MOC.from_cone(src_center.ra, src_center.dec, 60*u.arcsec, order) bkg_moc = bkg_moc_outer.difference(bkg_moc_inner) bkg_npixels = flatten_pixels(bkg_moc._interval_set._intervals, order) return rng.choice(bkg_npixels, size=npixels, replace=False).tolist() def get_bkg_data(npixel, obsid, hp): src_center = hp.healpix_to_skycoord(npixel) bkg_npixels = get_bkg_npixels(src_center, hp.nside, npixels=100) bkg_data = rapidxmm.query_npixels( bkg_npixels, obstype="pointed", instrum="PN" ) mask = bkg_data["obsid"] == obsid bkg_data = bkg_data[mask] if len(bkg_data) < 15: bkg_data = None return bkg_data def stats_bootstrap(src, bkg, exp, eef, ecf, ac=None, nbkg=None, nsim=1000): # Calculate median and MAD for the stack using bootstraping nstack, npixels, nbands = src.shape cr = np.zeros((nsim, npixels, nbands)) cr_err = np.zeros((nsim, npixels, nbands)) snr = np.zeros((nsim, npixels, nbands)) texp = np.zeros((nsim, npixels, nbands)) ecf_sample = np.zeros((nsim, nbands)) # msrc = np.zeros((nsim, npixels, nbands)) # mbkg = np.zeros((nsim, npixels, nbands)) # mexp = np.zeros((nsim, npixels, nbands)) for i in range(nsim): idx_sample = np.random.randint(nstack, size=nstack) S = np.sum(src[idx_sample, :, :], axis=0) B = np.sum(bkg[idx_sample, :, :], axis=0) t = np.sum(exp[idx_sample, :, :], axis=0) if ac is None: Bcorr = np.sum(bkg[idx_sample, :, :] / nbkg[idx_sample, :, :], axis=0) ac = np.ones_like(bkg) else: Bcorr = np.sum(ac[idx_sample, :, :] * bkg[idx_sample, :, :], axis=0) cr[i, :, :] = ( np.sum(src[idx_sample, :, :] / eef[idx_sample, :, :], axis=0) - np.sum(bkg[idx_sample, :, :] / eef[idx_sample, :, :], axis=0) ) / t cr_err[i, :, :] = np.sqrt( np.sum(src[idx_sample, :, :] / eef[idx_sample, :, :]**2, axis=0) + np.sum(ac[idx_sample, :, :] * bkg[idx_sample, :, :] / eef[idx_sample, :, :]**2, axis=0) ) / t snr[i, :, :] = (S - B) / np.sqrt(S + Bcorr) #snr[i, :, :] = cr[i, :, :] / cr_err[i, :, :] ecf_sample[i, :] = np.mean(ecf[idx_sample, :], axis=0) # msrc[i, :, :] = np.sum(src[idx_sample, :, :], axis=0) # mbkg[i, :, :] = np.sum(bkg[idx_sample, :, :], axis=0) # mexp[i, :, :] = np.sum(exp[idx_sample, :, :], axis=0) texp[i, :, :] = t cr_median = np.nanmedian(cr, axis=0) snr_median = np.nanmedian(snr, axis=0) ecf_median = np.nanmedian(ecf_sample, axis=0) texp_median = np.nanmedian(texp, axis=0) #cr_median = np.mean(cr, axis=0) #snr_median = np.mean(snr, axis=0) # src_median = np.median(msrc, axis=0) # bkg_median = np.median(mbkg, axis=0) # exp_median = np.median(mexp, axis=0) # kk1 = (src_median - bkg_median) / exp_median # kk2 = np.sqrt(src_median + bkg_median) / exp_median # kk3 = (src_median - bkg_median) / np.sqrt(src_median) cr_mad = np.zeros((npixels, nbands)) snr_mad = np.zeros((npixels, nbands)) for i in range(nbands): cr_mad[:, i] = median_abs_deviation(cr[:, :, i], axis=0, nan_policy="omit", scale="normal") snr_mad[:, i] = median_abs_deviation(snr[:, :, i], axis=0, nan_policy="omit", scale="normal") return cr_median, cr_mad, snr_median, snr_mad, ecf_median, texp_median def flux_bootstrap(src_flux, src_flux_err, bkg_flux, bkg_flux_err, nsim=1000): nstack, nbands = src_flux.shape flux = np.zeros((nsim, nbands)) flux_err = np.zeros((nsim, nbands)) for i in range(nsim): idx_sample = np.random.randint(nstack, size=nstack) ngood = np.zeros(nbands, dtype=int) for j in range(nbands): good_idx = np.where(np.isfinite(src_flux[idx_sample, j])) ngood[j] = len(good_idx[0]) flux[i, :] = ( np.nansum(src_flux[idx_sample, :], axis=0) - np.nansum(bkg_flux[idx_sample, :], axis=0) ) / ngood flux_err[i, :] = np.sqrt( np.nansum( src_flux_err[idx_sample, :]**2 + bkg_flux_err[idx_sample, :]**2, axis=0 ) ) / ngood flux_median = np.median(flux, axis=0) flux_err_median = np.median(flux_err, axis=0) flux_mad = median_abs_deviation(flux, axis=0, scale="normal") return flux_median, flux_mad def print_stats(cr, cr_err, snr, snr_err, texp, flux, flux_err, ebands=["6", "7", "8"]): color_print("\nStatistics", "yellow") color_print("----------", "yellow") for i, eband in enumerate(ebands): idx_max = np.argmax(cr[:, i]) cr_peak = cr[idx_max, i] cr_peak_mad = cr_err[idx_max, i] texp_peak = texp[idx_max, i] idx_max = np.argmax(snr[:, i]) snr_peak = snr[idx_max, i] snr_peak_mad = snr_err[idx_max, i] color_print(f"Energy band {eband}:", "white") print(f"Median net CR at peak: {cr_peak:.01e} ± {cr_peak_mad:.01e} counts/s") print(f"Median exposure time at peak: {texp_peak:.01e} s") if flux is not None: f, ferr = flux[i], flux_err[i] print(f"Median flux: {f:.01e} ± {ferr:.01e} erg/s/cm-2") print(f"Median SNR at peak: {snr_peak:.01f} ± {snr_peak_mad:.01f}\n") def print_params(parnames, params): color_print("\nAverage parameters", "yellow") color_print("------------------", "yellow") color_print("Weighted by number of repetitions in the stack") average_params = np.median(params, axis=0) for name, par in zip(parnames, average_params): color_print(f"{name}: {par:.04f}", "white") return average_params def plot_stack(npixels, hp, cr, snr, filename=None, scale=None): lon, lat = hp.healpix_to_lonlat(npixels) boundaries = hp.boundaries_lonlat(npixels, 1) patches = [] for blon, blat in zip(*boundaries): patches.append(Polygon(np.array([blon.value, blat.value]).T, closed=True)) if not scale: vmin_cr, vmax_cr = cr.flatten().min(), cr.flatten().max() vmin_snr, vmax_snr = snr.flatten().min(), snr.flatten().max() scale = [vmin_cr, vmax_cr, vmin_snr, vmax_snr] else: vmin_cr, vmax_cr = scale[0], scale[1] vmin_snr, vmax_snr = scale[2], scale[3] norm_cr = Normalize(vmin=vmin_cr, vmax=vmax_cr) norm_snr = Normalize(vmin=vmin_snr, vmax=vmax_snr) fig, axs = plt.subplots(2, 3, constrained_layout=False, figsize=(5.5, 4)) for i, eband in enumerate(["6", "7", "8"]): # Count-rate "images" pcm_cr = axs[0, i].scatter( lon, lat, c=cr[:, i], s=1, vmin=vmin_cr, vmax=vmax_cr ) p = PatchCollection(patches, alpha=1) p.set_array(cr[:, i]) p.set_norm(norm_cr) axs[0, i].add_collection(p) axs[0, i].set_title(f"Energy band {eband}") axs[0, i].set_xticks([]) axs[0, i].set_yticks([]) # signal-to-noise ratio "images" pcm_snr = axs[1, i].scatter( lon, lat, c=snr[:, i], s=1, vmin=vmin_snr, vmax=vmax_snr ) p = PatchCollection(patches, alpha=1) p.set_array(snr[:, i]) p.set_norm(norm_snr) axs[1, i].add_collection(p) axs[1, i].set_xticks([]) axs[1, i].set_yticks([]) if i == 0: axs[0, i].set_ylabel("Stack net CR (median)") axs[1, i].set_ylabel("Stack SNR (median)") plt.tight_layout() fig.colorbar(pcm_cr, ax=axs[0, :], shrink=0.6, location='bottom', pad=0.02) fig.colorbar(pcm_snr, ax=axs[1, :], shrink=0.6, location='bottom', pad=0.02) if filename: fig.savefig(filename, bbox_inches='tight', pad_inches=0) plt.close() else: plt.show() return scale def plot_radial(npixels, level, hp, cr, cr_err, snr, snr_err, filename=None): radius = list(range(level + 1)) cr_radial = np.zeros((level + 1, 3)) cr_err_radial = np.zeros((level + 1, 3)) snr_radial = np.zeros((level + 1, 3)) snr_err_radial = np.zeros((level + 1, 3)) cr_radial[0, :] = cr[0, :] cr_err_radial[0, :] = cr_err[0, :] snr_radial[0, :] = snr[0, :] snr_err_radial[0, :] = snr_err[0, :] npixel_neighbours = [npixels[0]] for i in range(1, level + 1): npixel_neighbours = list(set(hp.neighbours(npixel_neighbours).flatten())) mask = [p in npixel_neighbours for p in npixels] cr_radial[i] = np.sum(cr[mask], axis=0) / len(npixels[mask]) cr_err_radial[i] = np.sqrt(np.sum(cr_err[mask]**2, axis=0)) / len(npixels[mask]) snr_radial[i] = np.sum(snr[mask], axis=0) / len(npixels[mask]) snr_err_radial[i] = np.sqrt(np.sum(snr_err[mask]**2, axis=0)) / len(npixels[mask]) cr_min = np.nanmin(cr_radial - 1.1*cr_err_radial) cr_max = np.nanmax(cr_radial + 1.1*cr_err_radial) snr_min = np.nanmin(snr_radial - 1.1*snr_err_radial) snr_max = np.nanmax(snr_radial + 1.1*snr_err_radial) # filename_npz = filename.parent.joinpath(filename.stem + "_radial.npz") # np.savez( # filename_npz, # cr_radial=cr_radial, # cr_err_radial=cr_err_radial, # snr_radial=snr_radial, # snr_err_radial=snr_err_radial, # ) fig, axs = plt.subplots( 2, 3, sharex=True, constrained_layout=False, figsize=(5.5, 3.5) ) for i, eband in enumerate(["6", "7", "8"]): axs[0, i].errorbar( radius, cr_radial[:, i], yerr=cr_err_radial[:, i], fmt="o", capsize=2 ) axs[0, i].set_title(f"Energy band {eband}", size="x-small") axs[0, i].set_ylim(cr_min, cr_max) axs[0, i].ticklabel_format( axis="y", style="sci", scilimits=(0,0), useMathText=True ) axs[0, i].xaxis.offsetText.set_fontsize(8) axs[0, i].grid(color='gray', linestyle=':') axs[1, i].errorbar( radius, snr_radial[:, i], yerr=snr_err_radial[:, i], fmt="o", capsize=2 ) axs[1, i].set_ylim(snr_min, snr_max) axs[1, i].grid(color='gray', linestyle=':') if i == 0: axs[0, i].set_ylabel("net counts / s / pixel") axs[1, i].set_ylabel("SNR / pixel") fig.add_subplot(111, frameon=False) plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False) plt.xlabel("Distance to central npixel") plt.tight_layout() if filename: filename = filename.parent.joinpath(filename.stem + "_radial" + filename.suffix) fig.savefig(filename, bbox_inches='tight', pad_inches=0) plt.close() else: plt.show() def stack_npixels( npixels, level_neighbours=5, params=None, max_data=1000, calc_flux=True, use_flagged_pixels=False, skip_detections=False, custom_bkg=False, moc_masked_sources=None, order=16, with_plots=False, plotfile=None, scale=None, ): ecf_pn = { "6": ECF.ecf_det_eband("PN", "6"), "7": ECF.ecf_det_eband("PN", "7"), "8": ECF.ecf_det_eband("PN", "8"), } num_neighbours = sum([8*k for k in range(level_neighbours + 1)]) + 1 ebands = ["6", "7", "8"] src_stack = np.zeros((max_data, num_neighbours, len(ebands))) bkg_stack = np.zeros((max_data, num_neighbours, len(ebands))) exp_stack = np.zeros((max_data, num_neighbours, len(ebands))) eef_stack = np.ones((max_data, num_neighbours, len(ebands))) ac_stack = np.zeros((max_data, num_neighbours, len(ebands))) npixels_bkg_stack = np.ones((max_data, num_neighbours, len(ebands))) ecf_stack = np.zeros((max_data, len(ebands))) if calc_flux: src_flux_center = np.full((max_data, len(ebands)), np.nan) bkg_flux_center = np.full((max_data, len(ebands)), np.nan) src_flux_err_center = np.full((max_data, len(ebands)), np.nan) bkg_flux_err_center = np.full((max_data, len(ebands)), np.nan) if params: params_stack = np.zeros((max_data, len(params.colnames))) hp = HEALPix(nside=2 ** order, order="nested", frame=FK5()) n, nsrc = 0, 0 for j, npixel in enumerate(tqdm(npixels)): sorted_neighbours = get_neighbours(npixel, hp, level=level_neighbours) data = rapidxmm.query_npixels( sorted_neighbours["npixel"], obstype="pointed", instrum="PN" ) if len(data) == 0: continue nsrc += 1 data = data.group_by(["obsid", "instrum"]) for group in data.groups: data_obs_order = join( sorted_neighbours, group, keys=["npixel"], join_type="left" ) data_obs_order.sort("order") if skip_detections: if np.any(data_obs_order["band8_flags"] >= 8): continue if custom_bkg: bkg_data = get_bkg_data(npixel, group["obsid"][0], hp) if bkg_data is None: # We couldn't find a good background region for this npixel, # so it's rejected from the stack continue for i, eband in enumerate(ebands): if use_flagged_pixels: mask = [True] * len(sorted_neighbours) else: mask = data_obs_order[f"band{eband}_flags"] == 0 src_stack[n, mask, i] = data_obs_order[f"band{eband}_src_counts"][mask] exp_stack[n, mask, i] = data_obs_order[f"band{eband}_exposure"][mask] eef_stack[n, mask, i] = data_obs_order["eef"][mask] ac_stack[n, mask, i] = data_obs_order["area_ratio"][mask] if custom_bkg: mask_bkg = bkg_data[f"band{eband}_flags"] == 0 # The same average bkg value is assigned to all npixels in the detection bkg_counts = bkg_data[f"band{eband}_bck_counts"][mask_bkg] bkg_stack[n, mask, i] = np.mean(bkg_counts) npixels_bkg_stack[n, mask, i] = len(bkg_counts) else: bkg_stack[n, mask, i] = data_obs_order[f"band{eband}_bck_counts"][mask] if calc_flux and np.any(mask): ecf_stack[n, i] = ecf_pn[eband][group["filt"][0]].get_ecf(params["NHGAL"][j], 1.9) exp = np.mean(exp_stack[n, mask, i]) ngood = len(exp_stack[n, mask, i]) src_flux_center[n, i] = ( np.sum(src_stack[n, mask, i]) / exp / ecf_stack[n, i] / 1e11 / ngood ) src_flux_err_center[n, i] = ( np.sqrt(np.sum(src_stack[n, mask, i])) / exp / ecf_stack[n, i] / 1e11 / ngood ) if custom_bkg: exp_bkg = np.mean(bkg_data[f"band{eband}_exposure"][mask_bkg]) ngood_bkg = len(bkg_data[f"band{eband}_exposure"][mask_bkg]) bkg_flux_center[n, i] = ( np.sum(bkg_counts) / exp_bkg / ecf_stack[n, i] / 1e11 / ngood_bkg ) bkg_flux_err_center[n, i] = ( np.sqrt(np.sum(bkg_counts)) / exp_bkg / ecf_stack[n, i] / 1e11 / ngood_bkg ) else: bkg_flux_center[n, i] = ( np.sum(bkg_stack[n, mask, i]) / exp / ecf_stack[n, i] / 1e11 / ngood ) bkg_flux_err_center[n, i] = ( np.sqrt(np.sum(bkg_stack[n, mask, i])) / exp / ecf_stack[n, i] / 1e11 / ngood ) if params: for i, col in enumerate(params.colnames): params_stack[n, i] = params[col][j] n += 1 src_stack = src_stack[:n, :, :] bkg_stack = bkg_stack[:n, :, :] exp_stack = exp_stack[:n, :, :] ecf_stack = ecf_stack[:n, :] if custom_bkg: # No need to take into account the area correction when using custom # backgrounds, since counts are extracted in regions with the same size ac_stack = None npixels_bkg_stack = npixels_bkg_stack[:n, :] else: ac_stack = ac_stack[:n, :] npixels_bkg_stack = None if n < 2: return None, None, None, None, None, None, None cr, cr_mad, snr, snr_mad, ecf, texp = stats_bootstrap( src_stack, bkg_stack, exp_stack, eef_stack, ecf_stack, ac_stack, npixels_bkg_stack, nsim=1000 ) flux, flux_mad = None, None flux2, flux2_mad = None, None if calc_flux: src_flux_center = src_flux_center[:n, :] src_flux_err_center = src_flux_err_center[:n, :] bkg_flux_center = bkg_flux_center[:n, :] bkg_flux_err_center = bkg_flux_err_center[:n, :] flux, flux_mad = flux_bootstrap( src_flux_center, src_flux_err_center, bkg_flux_center, bkg_flux_err_center, nsim=1000 ) flux2 = np.mean(cr, axis=0) / ecf / 1e11 flux2_mad = np.sqrt(np.mean(cr_mad**2, axis=0)) / ecf / 1e11 if with_plots: scale = plot_stack( sorted_neighbours["npixel"], hp, cr, snr, plotfile, scale ) plot_radial( sorted_neighbours["npixel"], level_neighbours, hp, cr, cr_mad, snr, snr_mad, plotfile ) print_stats( cr, cr_mad, snr, snr_mad, texp, flux, flux_mad ) if params: average_params = print_params(params.colnames, params_stack[:n, :]) else: average_params = None return flux, flux_mad, flux2, flux2_mad, average_params, scale, n, nsrc

35.299824

102

0.579216

2,814

20,015

3.911869

0.142502

0.016806

0.01399

0.016533

0.375908

0.27589

0.206577

0.16379

0.108648

0.073129

0

0.019578

0.277792

20,015

566

103

35.362191

0.74175

0.077242

0

0.143902

0

0.002439

0.057422

0.006187

0

1

0.02439

false

0

0.039024

0

0.085366

0.039024

0

null

0

null

0

1

0

0f59d5843303a8468919fb4b9547b41d7cdf2bb8

2,575

py

Python

saas/data_bean.py

yongli82/CodeGenerator

4ca9255c3c4c5392e45815fd20f605ccbbfd2325

[ "MIT" ]

null

saas/data_bean.py

yongli82/CodeGenerator

4ca9255c3c4c5392e45815fd20f605ccbbfd2325

[ "MIT" ]

null

saas/data_bean.py

yongli82/CodeGenerator

4ca9255c3c4c5392e45815fd20f605ccbbfd2325

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding:utf-8 -*- import sys reload(sys) sys.path.append("..") sys.setdefaultencoding('utf-8') from project_util import * ################################################################################ # 业务函数 ################################################################################ ############# # 扫描API函数 ############# def is_sql_map_xml(file_path, arguments): return file_path.endswith(".xml") and "/sqlmap/" in file_path def handle_sql_map_xml(file_path, arguments): content = read_file(file_path) class_set = arguments[0] if "</sqlMap>" not in content: return logger.info(file_path) # result map class_list = re.findall(r"""<typeAlias\s+.*?\s*type="([\w\.]+)"/>""", content, flags=re.I) for class_name in class_list: logger.info(class_name) class_set.add(class_name) class_list = re.findall(r"""<resultMap\s+.*?\s*class="([\w\.]+)">""", content, flags=re.I) for class_name in class_list: if "." in class_name: logger.info(class_name) class_set.add(class_name) def is_data_bean(file_path, arguments): if file_path.endswith(".java"): start_pos = file_path.find("com/dianping/ba/") if start_pos < 0: return False class_set = arguments[0] class_name = file_path[start_pos:-5].replace("/", ".") if class_name in class_set: logger.info("[DATA_BEAN] %s" % class_name) return True else: return False return False def handle_data_bean(file_path, arguments): content = read_file(file_path) if "extends DataBase" in content: return logger.info("**************Handle %s " % file_path) matched = re.findall("((public\s+class\s+\w+)([\s\w]+\{))", content)[0] line = matched[0] content = content.replace(line, "%s extends DataBase %s" % (matched[1], matched[2])) content = content.replace("implements Serializable", "") content = content.replace("\n", "\n\nimport com.dianping.ba.finance.expense.api.base.DataBase;\n", 1) write_file(file_path, content) ############# # main ############# if __name__ == "__main__": data_bean_set = set() scan_module(module_name="expense", func_match_pattern=is_sql_map_xml, func_handler=handle_sql_map_xml, args=(data_bean_set,)) scan_module(module_name="expense", func_match_pattern=is_data_bean, func_handler=handle_data_bean, args=(data_bean_set,))

31.402439

105

0.568544

318

2,575

4.336478

0.292453

0.081218

0.026106

0.034808

0.35388

0.266135

0.240754

0.182741

0.126178

0

0.005416

0.211262

2,575

81

106

31.790123

0.67356

0.027184

0

0.339286

0

0.017857

0.151727

0.070398

0

1

0.071429

false

0

0.053571

0.017857

0.25

0

null

0

null

0

1

0

0f5ba763d8dc076a6f987c5dcaf800e5147fe387

2,187

py

Python

classes/gaussian.py

Vbtesh/easy_EM

5b8e2dc07f7c63c74e4e3bf641a92ef0814ae622

[ "MIT" ]

null

classes/gaussian.py

Vbtesh/easy_EM

5b8e2dc07f7c63c74e4e3bf641a92ef0814ae622

[ "MIT" ]

null

classes/gaussian.py

Vbtesh/easy_EM

5b8e2dc07f7c63c74e4e3bf641a92ef0814ae622

[ "MIT" ]

null

import numpy as np class Gaussian_mean: def __init__(self, name, num_clusters, data, variance=None, means=None): self.name = name self.c = num_clusters self.type = 'gaussian_mean' self.n_iter = 0 if variance: self.std = np.sqrt(variance) else: # Default is standard error self.std = np.sqrt(np.var(data.flatten())) / np.sqrt(len(data.flatten())) # Can be a single parameter or a vector of parameters, usually the latter if not isinstance(means, np.ndarray): # If none are given generate a vector of rate normally distributed around the sample mean with sample variance self.params_init = np.random.normal(loc=np.mean(data), scale=self.std, size=self.c) self.params = self.params_init else: self.initial_params = means self.params = means # Observation of the normal random variable, should be a length n column vector where n is the number of observations self.data = data.reshape((len(data), 1)) # Compute likelihood and log likelihood self.update() def get_likelihood(self, obs): # obs must be an integer or a column vector return 1 / np.sqrt(2 * np.pi * self.std**2) * np.exp(- (1/(2 * self.std**2)) * (obs - self.params)**2) def get_log_likelihood(self, obs): # obs must be an integer or a column vector return - 1 / (2 * self.std**2) * (obs - self.params)**2 def maximise(self, q_h): self.params_old = self.params # Optimise the energy w.r.t to mean parameters, q_h is the optimmised variational distribution output from the expectation step self.params = np.sum(q_h * self.data, axis=0) / np.sum(q_h, axis=0) self.update() self.n_iter += 1 def update(self): # Likelihood of each observation given the current rates self.likelihood = self.get_likelihood(self.data) # Log likelihood, up to proportionality, of each observation given the current rates self.log_likelihood = self.get_log_likelihood(self.data)

32.161765

135

0.622314

310

2,187

4.309677

0.36129

0.067365

0.050898

0.019461

0.186377

0.125

0

0.010224

0.284408

2,187

67

136

32.641791

0.84345

0.323731

0

0.129032

0

0.008874

0

1

0.16129

false

0

0.032258

0.064516

0.290323

0

null

0

null

0

1

0

0f5dd0b94acf376ad82df1f237683a4b69b1bdd7

3,451

py

Python

prioritize_health.py

bryanhpchiang/Twilio-Backend

b1fc70e8404c211a2a39fd3f5f024ad738edbbe2

[ "Apache-2.0" ]

null

prioritize_health.py

bryanhpchiang/Twilio-Backend

b1fc70e8404c211a2a39fd3f5f024ad738edbbe2

[ "Apache-2.0" ]

null

prioritize_health.py

bryanhpchiang/Twilio-Backend

b1fc70e8404c211a2a39fd3f5f024ad738edbbe2

[ "Apache-2.0" ]

null

import nltk nltk.download('averaged_perceptron_tagger') nltk.download('punkt') import gensim from ibm_watson import NaturalLanguageUnderstandingV1 from ibm_watson.natural_language_understanding_v1 import Features, KeywordsOptions from ibm_key import * def is_useless(word): pos=nltk.pos_tag([word])[0][1] if pos in ["DT","IN","WRB","RB"]: return True return False def prioritize_health(sentence,model): priority_dict={} with open("priority_dict.csv","r") as f: for line in f: # print(line.strip().split(",")) comma_split=line.strip().split(",") symptom=",".join(comma_split[:-1]) priority=int(comma_split[-1]) print(symptom,priority) priority_dict[symptom]=priority symptoms=priority_dict.keys() natural_language_understanding = NaturalLanguageUnderstandingV1( version='2019-07-12', iam_apikey=ibm_key, url='https://gateway.watsonplatform.net/natural-language-understanding/api' ) result=natural_language_understanding.analyze( language="en", text=sentence, features=Features(keywords=KeywordsOptions())).get_result() print(result) keywords=[x['text'] for x in result['keywords']] print(keywords) #find key words in the sentence. for each word, find nearest keywords based on the avg cosine score # print(symptoms) closest_symptoms=[] #add one for each keyword best_symptom=None for cur_keyword in keywords: best_avg_sim=0 print("Finding closest match for keyword={}".format(cur_keyword)) test_keyword=cur_keyword.split(" ")[-1] print("Test keyword={}".format(test_keyword)) for cur_symptom in symptoms: symptom_tokens=[x.lower() for x in nltk.word_tokenize(cur_symptom) if not is_useless(x) and x.isalpha()] total_sim=0 total_cnt=0 # print("Symptom={}".format(cur_symptom)) # print("Symptom tokens={}".format(symptom_tokens)) for token in symptom_tokens: # print("Token={}".format(token)) if token not in model.vocab or token==test_keyword: # print("Token not found in vocab, skipping") continue #compute similarity of keyword and otken cur_sim=model.similarity(test_keyword,token) # print("cur_sim={}".format(cur_sim)) if cur_sim<-0.2 or cur_sim>0.2: total_sim+=cur_sim total_cnt+=1 if total_cnt: avg_sim=float(total_sim)/total_cnt print("total_sim={},total_cnt={},avg_sim={}".format(total_sim,total_cnt,avg_sim)) if avg_sim>best_avg_sim: best_avg_sim=avg_sim best_symptom=cur_symptom print(best_avg_sim,best_symptom) if best_symptom is not None: priority_score=priority_dict[best_symptom] else: priority_score=0 res=(keywords,priority_score) print("Result={}".format(res)) return res def main(): sentence="i have a small wound and broken leg" model = gensim.models.KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300-SLIM.bin', binary=True) # print("hello" in model.vocab) result=prioritize_health(sentence,model) # print(result) if __name__ == '__main__': main()

38.775281

116

0.63286

427

3,451

4.899297

0.330211

0.025813

0.053537

0.020076

0.033461

0.021033

0

0.011288

0.255578

3,451

89

117

38.775281

0.803036

0.131266

0

0.111186

0.033825

0

1

0.041667

false

0

0.069444

0

0.152778

0.111111

0

null

0

null

0

1

0

0f5f6c43c0a2b98dab6270e3ab4c4138890053eb

9,266

py

Python

dev/phonts/visualization/visualize_freq_vs_lifetime_Ar.py

eragasa/pypospack

21cdecaf3b05c87acc532d992be2c04d85bfbc22

[ "MIT" ]

4

2018-01-18T19:59:56.000Z

2020-08-25T11:56:52.000Z

dev/phonts/visualization/visualize_freq_vs_lifetime_Ar.py

eragasa/pypospack

21cdecaf3b05c87acc532d992be2c04d85bfbc22

[ "MIT" ]

1

2018-04-22T23:02:13.000Z

dev/phonts/visualization/visualize_freq_vs_lifetime_Ar.py

eragasa/pypospack

21cdecaf3b05c87acc532d992be2c04d85bfbc22

[ "MIT" ]

1

2019-09-14T07:04:42.000Z

import os,copy import pandas as pd import numpy as np import matplotlib.pyplot as plt from collections import OrderedDict class PhontsBteData(object): """ Args: directory(str): the directory where the phonts simulation output files exist natoms(int):number of atoms in the simulation cel Attributes: directory(str): the directory where the phonts simulation output files exist ph_lt_file(pypospack.io.phonts.PhononLifetimeFile) ph_freq_file(pypospack.io.phonts.PhononFrequencyFile) natoms(int):number of atoms in the simulation cel """ def __init__(self,directory,natoms): self.directory =directory self.ph_lt_file = None self.ph_freq_file = None self.ph_lt_filename = 'phon_lifetime.dat' self.ph_freq_filename = 'freq.dat' self.natoms = natoms self.data = None def read(self,directory=None): if directory is not None: self.directory = directory self.ph_lt_file = PhononLifetimeFile( natoms=self.natoms, filename=os.path.join( self.directory, self.ph_lt_filename)) self.ph_freq_file = PhononFrequencyFile( natoms=self.natoms, filename=os.path.join( self.directory, self.ph_freq_filename)) self.ph_lt_file.read() self.ph_freq_file.read() def build_data(self): self.data = OrderedDict() for temp in self.ph_lt_file.temp: print('temp={}'.format(temp)) self.data[temp] = None self.build_data_at_temp(temp) def build_data_at_temp(self,temp): """ This method consolidates the data contained in two different files so that we can compare phonon frequencies with with phonon lifetimes. Args: temp(int): the temperature from the BTE calculation, this value must be in list of values contained in the list ph_lt_file.temp """ if self.data is None: self.data = OrderedDict() self.data[temp] = [] # initialize our list self.kpoint_keys_format = "{kp1:.6f}_{kp2:.6f}_{kp3:.6f}" freq_n_rows, freq_n_cols = self.ph_freq_file.data.shape lt_n_rows, lt_n_cols = self.ph_lt_file.data[temp].shape #these indices are the column index for the columns kp1,kp2,kp3 in #phonon frequency file (ph_fr_file) freq_kp1_idx = self.ph_freq_file.col_names.index('kp1') freq_kp2_idx = self.ph_freq_file.col_names.index('kp2') freq_kp3_idx = self.ph_freq_file.col_names.index('kp3') # these indices are the the column indices for the columns kp1,kp2,kp3 # in the lifetime frequency file (ph_lt_file) lt_kp1_idx = self.ph_lt_file.col_names.index('kp1') lt_kp2_idx = self.ph_lt_file.col_names.index('kp2') lt_kp3_idx = self.ph_lt_file.col_names.index('kp3') for i in range(freq_n_rows): freq_kpoint_key = self.kpoint_keys_format.format( kp1 = self.ph_freq_file.data[i,freq_kp1_idx], kp2 = self.ph_freq_file.data[i,freq_kp2_idx], kp3 = self.ph_freq_file.data[i,freq_kp3_idx]) for j in range(lt_n_rows): lt_kpoint_key = self.kpoint_keys_format.format( kp1 = self.ph_lt_file\ .data[temp][j,lt_kp1_idx], kp2 = self.ph_lt_file\ .data[temp][j,lt_kp2_idx], kp3 = self.ph_lt_file\ .data[temp][j,lt_kp3_idx]) if freq_kpoint_key == lt_kpoint_key: for k in range(3*self.natoms): # here we are building the row for the phonon frequency # and the associated limetime with that phonon # ph_id(int) - unique integer assigned to a phonon for # identification # kp1,kp2,kp3 - the location of the kpoint associated with # phonon frequency represented in the basis of the # reciprocal lattice # fr - this is the frequency of the phonon in meV # lt - this is the phonon lifetime in ps ph_id = len(self.data[temp]) kp1 = self.ph_lt_file\ .data[temp][j,lt_kp1_idx] kp2 = self.ph_lt_file\ .data[temp][j,lt_kp2_idx] kp3 = self.ph_lt_file\ .data[temp][j,lt_kp3_idx] # we need the index associated with the phonon freq fr_idx = self.ph_freq_file.col_names.index( "freq{}".format(k+1)) # wew need the index associated with the phonon lifetime lt_idx = self.ph_lt_file.col_names.index( "lt{}".format(k+1)) fr = self.ph_freq_file.data[i,fr_idx] lt = self.ph_lt_file.data[temp][j,lt_idx] self.data[temp].append([ ph_id, kp1,kp2,kp3, fr,lt]) self.data[temp] = np.array(self.data[temp]) class PhononLifetimeFile(object): def __init__(self,natoms,filename='phon_lifetime.dat'): self.col_names = ['index','kp1','kp2','kp3']\ + ['lt{}'.format(i+1) for i in range(3*natoms)] self.natoms = natoms self.filename = filename self.data = read_phon_lifetime(self.filename) self.temp = [k for k,v in self.data.items()] def read(self): self.data = read_phon_lifetime(self.filename) def print(self): for k,v in self.data.items(): print(k,v.shape) class PhononFrequencyFile(object): def __init__(self,natoms,filename='freq.dat'): self.col_names = ['index','kp1','kp2','kp3']\ + ['freq{}'.format(i+1) for i in range(3*natoms)] self.filename = filename self.data = None self.natoms = natoms def read(self,filename=None): if filename is not None: self.filename = filename try: with open(self.filename,'r') as f: lines = f.readlines() except FileNotFoundErr as e: raise values_all = [] for i,line in enumerate(lines): args = line.strip().split() values_all.append([float(arg) for arg in args]) self.data = np.array(values_all) def print(self): print(self.data.shape) def get_data_from_phonts_file(filename): #def process_first_line(line): # args = line.strip().split() # args = [arg.strip() for arg in args] # args = args[1:] # return args #labels = None data = None data_all = None with open(filename) as f: lines = f.readlines() # except FileNotFoundErr #initialize variables values_all = [] for i,line in enumerate(lines): # if i == 0: # labels = process_first_line(line) # else: args = line.strip().split() values_all.append([float(arg) for arg in args]) data_all = np.array(values_all) return data_all def get_freq_data(filename='freq.dat'): freq_data = get_data_from_phonts_file(filename) return freq_data def read_phon_lifetime(filename='phon_lifetime.dat'): """ Reads phonon lifetime information """ def subselect_table_block(i_start,lines): i=i_start+1 table = [] while(lines[i].strip() !=""): args = lines[i].split() args = [arg.strip() for arg in args] args = [float(arg) for arg in args] table.append(args) i += 1 return np.array(table) line = None #initialize with open(filename,'r') as f: lines = f.readlines() lines = [s.strip() for s in lines] temperatures = [] phon_lifetime = OrderedDict() for il,line in enumerate(lines): if line.startswith('# Temp:'): args = line.split(':') T = int(float(args[1].strip())) temperatures.append(T) phon_lifetime[T] = subselect_table_block(il,lines) return {k:v.copy() for k,v in phon_lifetime.items()} if __name__ == "__main__": phonts_sim_dir = 'Ar_result' freq_data_filename = os.path.join( phonts_sim_dir, 'freq.dat') phon_lifetime_data_filename = os.path.join( phonts_sim_dir, 'phon_lifetime.dat') bte_data = PhontsBteData(natoms=4,directory=phonts_sim_dir) bte_data.read() bte_data.build_data_at_temp(temp=400) ph_freq = bte_data.data[400][:,4] ph_lt = bte_data.data[400][:,5] idx_not_zero = np.where(ph_lt != 0)[0] ph_freq = bte_data.data[400][idx_not_zero,4] ph_inv_lt = 1/bte_data.data[400][idx_not_zero,5]

34.70412

81

0.564213

1,200

9,266

4.143333

0.16

0.038616

0.030571

0.038616

0.441875

0.4107

0.359413

0.254224

0.16432

0.134956

0

0.014479

0.336607

9,266

266

82

34.834586

0.794371

0.185625

0

0.252941

0

0.031013

0.003927

0

1

0.082353

false

0

0.029412

0

0.152941

0.029412

0

null

0

null

0

1

0

0f5ffb83eb270ebe0264b1392d0c080b2974987c

3,828

py

Python

leprikon/forms/refundrequest.py

leprikon-cz/leprikon

b1bec36fb6bcf0220bffccca53b6f200f9e95910

[ "BSD-3-Clause" ]

4

2018-10-29T17:46:09.000Z

2021-12-16T08:57:48.000Z

leprikon/forms/refundrequest.py

leprikon-cz/leprikon

b1bec36fb6bcf0220bffccca53b6f200f9e95910

[ "BSD-3-Clause" ]

68

2016-07-11T07:48:54.000Z

2022-03-18T01:32:06.000Z

leprikon/forms/refundrequest.py

leprikon-cz/leprikon

b1bec36fb6bcf0220bffccca53b6f200f9e95910

[ "BSD-3-Clause" ]

2

2016-07-12T20:39:53.000Z

2020-10-10T03:14:42.000Z

from django import forms from django.utils.translation import ugettext_lazy as _ from ..models.courses import CourseRegistration from ..models.events import EventRegistration from ..models.orderables import OrderableRegistration from ..models.refundrequest import RefundRequest from ..models.transaction import Transaction from ..utils import comma_separated, currency, first_upper from .fields import ReadonlyField from .form import FormMixin class RefundRequestBaseForm(FormMixin, forms.ModelForm): def __init__(self, registration, *args, **kwargs): super().__init__(*args, **kwargs) self.registration = registration self.readonly_fields = [ ReadonlyField(label=first_upper(registration.subject.subject_type.name), value=registration.subject.name) ] if registration.subject.registration_type_participants: if len(registration.all_participants) > 1: label = _("Participants") else: label = _("Participant") self.readonly_fields.append( ReadonlyField(label=label, value=comma_separated(registration.all_participants)) ) elif registration.subject.registration_type_groups: self.readonly_fields.append(ReadonlyField(label=_("Contact person"), value=registration.group.full_name)) if registration.group.name: self.readonly_fields.append(ReadonlyField(label=_("Group name"), value=registration.group.name)) self.readonly_fields.append( ReadonlyField(label=_("Overpaid amount"), value=currency(registration.payment_status.overpaid)) ) class RefundRequestForm(RefundRequestBaseForm): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.instance.registration = self.registration self.instance.requested_by_id = self.registration.user_id class Meta: model = RefundRequest fields = ["bank_account"] class PaymentTransferForm(RefundRequestBaseForm): instance: Transaction def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) valid_target_registration_ids = [ registration.id for Registration in (CourseRegistration, EventRegistration, OrderableRegistration) for registration in Registration.objects.filter(user_id=self.registration.user_id) if registration.payment_status.amount_due ] registration_choices = self.fields["target_registration"].widget.choices registration_choices.queryset = registration_choices.queryset.filter(id__in=valid_target_registration_ids) self.instance.source_registration = self.registration self.instance.accounted_by_id = self.registration.user_id self.instance.transaction_type = Transaction.TRANSFER def clean(self): self.cleaned_data = super().clean() target_registration = self.cleaned_data.get("target_registration") if target_registration: self.instance.amount = min( self.registration.payment_status.overpaid, target_registration.payment_status.amount_due, ) return self.cleaned_data class Meta: model = Transaction fields = ["target_registration"] class DonationForm(RefundRequestBaseForm): instance: Transaction def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.instance.source_registration = self.registration self.instance.accounted_by_id = self.registration.user_id self.instance.transaction_type = Transaction.DONATION_TRANSFER self.instance.amount = self.registration.payment_status.overpaid class Meta: model = Transaction fields = []

40.723404

117

0.702456

379

3,828

6.831135

0.248021

0.06798

0.034762

0.029355

0.405176

0.286983

0.244496

0.23175

0.183082

0

0.000331

0.210554

3,828

93

118

41.16129

0.856387

0

0.25641

0

0.034222

0

1

0.064103

false

0

0.128205

0

0.320513

0

null

0

null

0

1

0

0f62c371e97016904243e582e0e0941f4163bf85

1,922

py

Python

tests/integration/states/service.py

pass-by-value/salt

2ede44fe54516242e10fe428629d5f5a18e5f7ea

[ "Apache-2.0", "MIT" ]

null

tests/integration/states/service.py

pass-by-value/salt

2ede44fe54516242e10fe428629d5f5a18e5f7ea

[ "Apache-2.0", "MIT" ]

1

2019-09-06T13:57:28.000Z

tests/integration/states/service.py

pass-by-value/salt

2ede44fe54516242e10fe428629d5f5a18e5f7ea

[ "Apache-2.0", "MIT" ]

1

2020-09-30T16:09:48.000Z

# -*- coding: utf-8 -*- ''' Tests for the service state ''' # Import python libs from __future__ import absolute_import # Import Salt Testing libs from salttesting import skipIf from salttesting.helpers import ( ensure_in_syspath, destructiveTest ) ensure_in_syspath('../../') # Import salt libs import integration import salt.utils INIT_DELAY = 5 SERVICE_NAME = 'crond' @destructiveTest @skipIf(salt.utils.which('crond') is None, 'crond not installed') class ServiceTest(integration.ModuleCase, integration.SaltReturnAssertsMixIn): ''' Validate the service state ''' def check_service_status(self, exp_return): ''' helper method to check status of service ''' check_status = self.run_function('service.status', name=SERVICE_NAME) if check_status is not exp_return: self.assertFalse('status of service is not returning correctly') def test_service_dead(self): ''' test service.dead state module ''' start_service = self.run_state('service.running', name=SERVICE_NAME) self.assertSaltTrueReturn(start_service) self.check_service_status(True) ret = self.run_state('service.dead', name=SERVICE_NAME) self.assertSaltTrueReturn(ret) self.check_service_status(False) def test_service_dead_init_delay(self): ''' test service.dead state module with init_delay arg ''' start_service = self.run_state('service.running', name=SERVICE_NAME) self.assertSaltTrueReturn(start_service) self.check_service_status(True) ret = self.run_state('service.dead', name=SERVICE_NAME, init_delay=INIT_DELAY) self.assertSaltTrueReturn(ret) self.check_service_status(False) if __name__ == '__main__': from integration import run_tests run_tests(ServiceTest)

28.686567

77

0.67898

223

1,922

5.591928

0.304933

0.052927

0.072173

0.060946

0.384924

0.336808

0.2502

0

0.00135

0.229448

1,922

66

78

29.121212

0.840648

0.135796

0

0.27027

0

0.098978

0

0.162162

1

0.081081

false

0

0.162162

0

0.27027

0

null

0

null

0

1

0

0f63dc2f21bee87e13f8d7f4d271327d23cf44c1

763

py

Python

6.py

msatuqi/homework

c6110ce26cba4e279622667f02b06edb4308d26d

[ "MIT" ]

null

6.py

msatuqi/homework

c6110ce26cba4e279622667f02b06edb4308d26d

[ "MIT" ]

null

6.py

msatuqi/homework

c6110ce26cba4e279622667f02b06edb4308d26d

[ "MIT" ]

null

import sys import os if __name__ == "__main__": files = [] if len(sys.argv) > 1: for i in range(1, len(sys.argv)): file = sys.argv[i] if os.path.isfile(file): files.append(file) continue print(f"File {file} doesn't exist") else: print("Not enough arguments!") sys.exit() funcs = [] for i in files: with open(i, "r", encoding="utf-8") as f: a = f.readlines() for j in range(len(a)): if a[j].startswith("def "): if not a[j - 1].startswith("#"): funcs.append(f"file name: {i}, line: {j} function name: {a[j][4:]}") for i in funcs: print(i)

29.346154

89

0.454784

101

763

3.356436

0.445545

0.061947

0.053097

0

0.01087

0.397117

763

26

90

29.346154

0.726087

0

0.041667

0.156969

0

1

0

false

0

0.083333

0

0.083333

0.125

0

null

0

null

0

1

0

0f6443bcf6ed89d7221f462318c15bab9a25357c

2,107

py

Python

mobilecoind/clients/python/cli/get_public_address.py

jgreat/mobilecoin

7df58d88f67e3b92122b814acae9c08498429092

[ "Apache-2.0" ]

1

2022-01-17T21:12:44.000Z

mobilecoind/clients/python/cli/get_public_address.py

jgreat/mobilecoin

7df58d88f67e3b92122b814acae9c08498429092

[ "Apache-2.0" ]

292

2020-10-22T00:34:35.000Z

2022-03-29T09:29:14.000Z

mobilecoind/clients/python/cli/get_public_address.py

eranrund/mobilecoin

ef19480f5a2c5dd7f79aba5650138e0f730735b4

[ "Apache-2.0" ]

1

2022-03-26T20:34:00.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # Copyright (c) 2018-2021 The MobileCoin Foundation """ displays the b58 public address and URI that correspond to a master key """ import argparse import os,sys sys.path.insert(1, os.path.realpath(os.path.join(os.path.pardir, "lib"))) import mobilecoin if __name__ == '__main__': # Connect to mobilecoind mobilecoind = mobilecoin.Client("localhost:4444", ssl=False) # Parse the arguments parser = argparse.ArgumentParser( description='Displays public address information for a provided master key, or for a random master key if no key is provided.') parser.add_argument('-k', '--key', help='account master key', type=str) parser.add_argument('-m', '--mnemonic', help='account key as mnemonic string', type=str) parser.add_argument('-s', '--subaddress', help='(optional) subaddress', nargs='?', const=mobilecoin.DEFAULT_SUBADDRESS_INDEX, type=int, default=mobilecoin.DEFAULT_SUBADDRESS_INDEX) args = parser.parse_args() # create a monitor and use it to calculate the public address if args.key: entropy_bytes = bytes.fromhex(args.key) if args.key else mobilecoind.generate_entropy() account_key = mobilecoind.get_account_key(entropy_bytes).account_key entropy_display = entropy_bytes.hex() else: mnemonic = args.mnemonic if args.mnemonic else mobilecoind.generate_mnemonic() account_key = mobilecoind.get_account_key_from_mnemonic(mnemonic) entropy_display = mnemonic monitor_id = mobilecoind.add_monitor(account_key, first_subaddress=args.subaddress).monitor_id public_address = mobilecoind.get_public_address(monitor_id, subaddress_index=args.subaddress).public_address # print the public address information print("\n") print(" {:<18}{}".format("Master Key:", entropy_display)) print(" {:<18}{}".format("Subaddress Index:", args.subaddress)) print(" {:<18}{}".format("Address Code:", public_address.b58_code)) print(" {:<18}{}".format("Address URL:", "mob58://"+ public_address.b58_code)) print("\n")

46.822222

184

0.712862

271

2,107

5.365314

0.376384

0.080468

0.035763

0.022008

0.114168

0.046768

0

0.017465

0.15757

2,107

44

185

47.886364

0.80169

0.14523

0

0.071429

0

0.035714

0.197427

0

1

0

false

0

0.107143

0

0.107143

0.214286

0

null

0

null

0

1

0

0f66c650220248159eeb9079ee30655ab1b2a320

1,200

py

Python

qichacha/crawler.py

johnson7788/webinfo-crawler

42a1194b32d600a2c41c8eccab9afa1bcb61d053

[ "MIT" ]

null

qichacha/crawler.py

johnson7788/webinfo-crawler

42a1194b32d600a2c41c8eccab9afa1bcb61d053

[ "MIT" ]

null

qichacha/crawler.py

johnson7788/webinfo-crawler

42a1194b32d600a2c41c8eccab9afa1bcb61d053

[ "MIT" ]

null

#!/usr/bin/python3 # -*-: coding: utf-8 -*- """ :author: lubosson :date: 2019-04-15 :desc: """ import logging as log from qichacha.client import QichachaClient from qichacha.manager import QichachaManager from db.model.model import Company from db.mysql_connector import insert as save # 企查查客户端 qcc_client = QichachaClient() manager = QichachaManager() def start(): keywords = globals().get('keywords') for keyword in keywords: raw_companies = qcc_client.search(keyword) cost_time = 2 * raw_companies.__len__() + 4 log.info('正在处理爬取[%s]，大概需要%s秒' % (keyword, cost_time)) # company对象 company = Company() for raw_company in raw_companies: company.keyword = keyword # 组装公司信息 manager.assembly(company, raw_company) raw_company_detail = qcc_client.search_detail(raw_company.get('KeyNo')) # 补充公司详细信息 manager.assembly_detail(company, raw_company_detail) # 保存到数据库 # save(company.__dict__) log.info(company) company.clear() log.info('completed') def load_keys(keys: list): globals().setdefault('keywords', keys)

22.641509

83

0.640833

137

1,200

5.416058

0.489051

0.067385

0.068733

0.061995

0

0.013333

0.25

1,200

52

84

23.076923

0.811111

0.121667

0

0.046647

0

1

0.083333

false

0

0.208333

0

0.291667

0

null

0

null

0

1

0

0f67013369c20b543aea358f0f79f4d5815f4539

961

py

Python

sources/Entities/BackgroundScrolling.py

rsoultan/Pygame-shoot-them-up

0ae41522253b7405e6d00a8c4094de7480846535

[ "Apache-2.0" ]

null

sources/Entities/BackgroundScrolling.py

rsoultan/Pygame-shoot-them-up

0ae41522253b7405e6d00a8c4094de7480846535

[ "Apache-2.0" ]

null

sources/Entities/BackgroundScrolling.py

rsoultan/Pygame-shoot-them-up

0ae41522253b7405e6d00a8c4094de7480846535

[ "Apache-2.0" ]

null

import pygame from sources.Entities.Entity import Entity from sources.Settings import SETTINGS class BackgroundScrolling(pygame.sprite.Sprite, Entity): def __init__(self): super().__init__() self.music = pygame.mixer.music.load("assets/sounds/game.ogg") pygame.mixer.music.play() self.image = pygame.image.load("assets/images/game_background.png").convert_alpha() self.rect = self.image.get_rect() self.rect.x = 0 self.rect.y = 0 self.rel_x = self.rect.x % self.rect.width def event(self, event): pass def update(self, elapsed_time): self.rect.x -= 1 self.rel_x = self.rect.x % self.rect.width if self.rect.x < -self.rect.width: self.rect.x = 0 def draw(self, window): window.blit(self.image, (self.rel_x - self.rect.width, 0)) if self.rel_x < SETTINGS['WIDTH']: window.blit(self.image, (self.rel_x, 0))

32.033333

91

0.626431

136

961

4.301471

0.330882

0.164103

0.092308

0.095727

0.246154

0.232479

0.194872

0.102564

0

0.008219

0.240375

961

29

92

33.137931

0.793151

0

0.166667

0

0.062435

0.057232

0

1

0.166667

false

0.041667

0.125

0

0.333333

0

null

0

null

0

1

0

0f6bbd07c06394980185670c03f5513e2f6231c0

2,573

py

Python

src/tinkoff/client.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

1

2021-03-03T19:51:24.000Z

src/tinkoff/client.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

null

src/tinkoff/client.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

null

import requests from collections import OrderedDict from django.conf import settings from hashlib import sha256 from urllib.parse import urljoin from app.banking import Bank from tinkoff.exceptions import TinkoffRequestException class TinkoffBank(Bank): def get_initial_payment_url(self): return self.Init()['PaymentURL'] def Init(self) -> dict: return self.call('Init', payload={ 'Amount': self.price, 'OrderId': self.order.id, 'CustomerKey': self.user.id, 'SuccessURL': self.success_url, 'FailURL': self.fail_url, 'Receipt': self.get_receipt(), 'NotificationURL': self.get_notification_url(), }) def call(self, method: str, payload: dict) -> dict: """Query Tinkoff API """ payload.update({'TerminalKey': settings.TINKOFF_TERMINAL_KEY}) r = requests.post(f'https://securepay.tinkoff.ru/v2/{method}/', json={ 'Token': self._get_token(payload), **payload, }) if r.status_code != 200: raise TinkoffRequestException(f'Incorrect HTTP-status code for {method}: {r.status_code}') parsed = r.json() if not parsed['Success']: raise TinkoffRequestException(f'Non-success request for {method}: {parsed["ErrorCode"]}, {parsed["Message"]} ({parsed["Details"]}') return parsed def get_receipt(self): return { 'Email': self.user.email, 'Taxation': 'usn_income', 'Items': self.get_items(), } def get_items(self): return [{ 'Name': self.order.item.name_receipt, 'Price': self.price, 'Quantity': 1, 'Amount': self.price, 'PaymentObject': 'service', 'Tax': "none", # fuck }] @staticmethod def _get_token(request: dict) -> str: """Get request signature based on https://oplata.tinkoff.ru/landing/develop/documentation/request_sign""" _request = request.copy() for key_to_ignore in ['DATA', 'Receipt']: _request.pop(key_to_ignore, None) _request['Password'] = settings.TINKOFF_TERMINAL_PASSWORD sorted_request = OrderedDict(sorted(_request.items(), key=lambda key, *args: key)) return sha256(''.join(str(value) for value in sorted_request.values()).encode()).hexdigest().upper() @staticmethod def get_notification_url(): return urljoin(settings.ABSOLUTE_HOST, '/api/v2/banking/tinkoff-notifications/')

32.1625

143

0.609405

278

2,573

5.507194

0.435252

0.019595

0

0.006299

0.259619

2,573

79

144

32.56962

0.797375

0.051302

0

0.103448

0

0.017241

0.176543

0.024691

0

1

0.12069

false

0.017241

0.12069

0.086207

0.37931

0

null

0

null

0

1

0

0f6c0bb22a1598a62cc05707e29dda3aac3c16ed

4,564

py

Python

policy_sentry/command/initialize.py

cclauss/policy_sentry

98e46f5c785b2845b2971e3c8c484f3e2355d756

[ "MIT" ]

null

policy_sentry/command/initialize.py

cclauss/policy_sentry

98e46f5c785b2845b2971e3c8c484f3e2355d756

[ "MIT" ]

null

policy_sentry/command/initialize.py

cclauss/policy_sentry

98e46f5c785b2845b2971e3c8c484f3e2355d756

[ "MIT" ]

null

""" Create the Policy Sentry config folder (~/.policy_sentry/) and the contents within Create the SQLite database and fill it with the tables scraped from the AWS Docs """ import shutil import click from policy_sentry.configuration.access_level_overrides import create_default_overrides_file from policy_sentry.configuration.analysis import create_default_report_config_file from policy_sentry.configuration.config_directory import create_policy_sentry_config_directory, \ create_audit_directory, create_policy_analysis_directory, create_html_docs_directory from policy_sentry.querying.all import get_all_service_prefixes from policy_sentry.scraping.awsdocs import update_html_docs_directory, get_list_of_service_prefixes_from_links_file, \ create_service_links_mapping_file from policy_sentry.shared.database import connect_db, create_database from policy_sentry.shared.constants import HOME, CONFIG_DIRECTORY, HTML_DIRECTORY_PATH, LINKS_YML_FILE_LOCAL, \ BUNDLED_DATABASE_FILE_PATH @click.command( short_help='Create a local database to store AWS IAM information.' ) @click.option( '--access-level-overrides-file', type=str, required=False, help='Path to access level overrides file, used to override the Access Levels per action provided by AWS docs' ) @click.option( '--fetch', is_flag=True, required=False, default=False, help='Specify this flag to fetch the HTML Docs directly from the AWS website. This will be helpful if the docs ' 'in the Git repository are behind the live docs and you need to use the latest version of the docs right ' 'now.' ) @click.option( '--build', is_flag=True, required=False, default=False, help='Build the SQLite database from the HTML files rather than copying the SQLite database file from ' 'the python package. Defaults to false' ) def initialize(access_level_overrides_file, fetch, build): """ Initialize the local database to store AWS IAM information, which can be used to generate IAM policies, and for querying the database. """ if not access_level_overrides_file: overrides_file = HOME + CONFIG_DIRECTORY + 'access-level-overrides.yml' else: overrides_file = access_level_overrides_file # Create the config directory database_path = create_policy_sentry_config_directory() # Copy over the html docs, which will be used to build the database create_html_docs_directory() # Create the directory to download IAM policies to create_policy_analysis_directory() # Create audit directory to host list of permissions for analyze_iam_policy create_audit_directory() # Create overrides file, which allows us to override the Access Levels # provided by AWS documentation create_default_overrides_file() # Create the default reporting configuration file. This is used by # analyze_iam_policy create_default_report_config_file() if not build and not fetch: # copy from the bundled database location to the destination path shutil.copy(BUNDLED_DATABASE_FILE_PATH, database_path) # Connect to the database at that path with SQLAlchemy db_session = connect_db(database_path, initialization=True) # --fetch: wget the AWS IAM Actions, Resources and Condition Keys pages and store them locally. # if --build and --fetch are both supplied, just do --fetch if fetch: # `wget` the html docs to the local directory update_html_docs_directory(HTML_DIRECTORY_PATH) # Update the links.yml file prefix_list = create_service_links_mapping_file( HTML_DIRECTORY_PATH, LINKS_YML_FILE_LOCAL) print(f"Services: {prefix_list}") # initialize --build if build or access_level_overrides_file or fetch: # Use the list of services that were listed in the links.yml file all_aws_services = get_list_of_service_prefixes_from_links_file( LINKS_YML_FILE_LOCAL) print(f"Services to build for: ${LINKS_YML_FILE_LOCAL}") # Fill in the database with data on the AWS services create_database(db_session, all_aws_services, overrides_file) print("Created tables for all services!") # Query the database for all the services that are now in the database. all_aws_service_prefixes = get_all_service_prefixes(db_session) total_count_of_services = str(len(all_aws_service_prefixes)) print(f"{total_count_of_services} AWS services in the database. \nServices: {all_aws_service_prefixes}")

43.466667

118

0.758107

642

4,564

5.137072

0.249221

0.047301

0.048514

0.043663

0.213159

0.10279

0.046089

0

0.18624

4,564

104

119

43.884615

0.887991

0.27213

0

0.151515

0

0.030303

0.233679

0.039353

0

1

0.015152

false

0

0.136364

0

0.151515

0.060606

0

null

0

null

0

1

0

0f6ca83e6f6ee2952775de43a42c712196dbdb99

4,128

py

Python

tests/flake8_integration/test_formatter.py

s-weigand/flake8-nb

39c6cf6158cc231c420ff783a550b09ee5f7e4c7

[ "Apache-2.0" ]

23

2019-12-05T06:02:43.000Z

2022-03-11T18:17:19.000Z

tests/flake8_integration/test_formatter.py

s-weigand/flake8-nb

39c6cf6158cc231c420ff783a550b09ee5f7e4c7

[ "Apache-2.0" ]

191

2019-10-04T06:22:14.000Z

2022-03-29T04:02:28.000Z

tests/flake8_integration/test_formatter.py

s-weigand/flake8-nb

39c6cf6158cc231c420ff783a550b09ee5f7e4c7

[ "Apache-2.0" ]

6

2020-06-13T13:35:15.000Z

2021-11-28T19:50:12.000Z

import os from optparse import Values from typing import List import pytest from flake8.style_guide import Violation from flake8_nb.flake8_integration.formatter import IpynbFormatter from flake8_nb.flake8_integration.formatter import map_notebook_error from flake8_nb.parsers.notebook_parsers import NotebookParser TEST_NOTEBOOK_PATH = os.path.join("tests", "data", "notebooks", "notebook_with_flake8_tags.ipynb") def get_test_intermediate_path(intermediate_names): return [ filename for filename in intermediate_names if filename.endswith("notebook_with_flake8_tags.ipynb_parsed") ][0] def get_mocked_option(notebook_cell_format: str, formatter="default_notebook") -> Values: return Values( {"output_file": "", "format": formatter, "notebook_cell_format": notebook_cell_format} ) def get_mocked_violation(filename: str, line_number: int) -> Violation: return Violation( filename=os.path.normpath(filename), line_number=line_number, physical_line=0, column_number=2, code="AB123", text="This is just for the coverage", ) @pytest.mark.parametrize( "line_number,cell_nr,expected_line_number", [ (8, 1, 2), (15, 2, 2), (29, 4, 2), (30, 4, 3), (38, 5, 3), ], ) @pytest.mark.parametrize( "notebook_cell_format,cell_format_str", ( ("{nb_path}#In[{exec_count}]", "#In[{}]"), ("{nb_path}:code_cell#{exec_count}", ":code_cell#{}"), ), ) def test_IpynbFormatter__map_notebook_error( notebook_parser: NotebookParser, notebook_cell_format: str, cell_format_str: str, line_number: int, cell_nr: int, expected_line_number: int, ): expected_filename = f"{TEST_NOTEBOOK_PATH}{cell_format_str.format(cell_nr)}" filename = get_test_intermediate_path(notebook_parser.intermediate_py_file_paths) mock_error = get_mocked_violation(filename, line_number) map_result = map_notebook_error(mock_error, notebook_cell_format) assert map_result is not None filename, input_cell_line_number = map_result assert input_cell_line_number == expected_line_number assert filename == expected_filename @pytest.mark.parametrize( "format_str,file_path_list,expected_result_str", [ ( "default_notebook", [], "{expected_filename}:2:2: AB123 This is just for the coverage", ), ( "%(path)s:%(row)d: %(text)s", [], "{expected_filename}:2: This is just for the coverage", ), ( "default_notebook", ["tests", "data", "notebooks", "falsy_python_file.py"], "{expected_filename}:8:2: AB123 This is just for the coverage", ), ( "default_notebook", [ "tests", "data", "intermediate_py_files", "notebook_with_flake8_tags.ipynb_parsed", ], "{expected_filename}:8:2: AB123 This is just for the coverage", ), ], ) @pytest.mark.parametrize( "notebook_cell_format,cell_format_str", ( ("{nb_path}#In[{exec_count}]", "#In[1]"), ("{nb_path}:code_cell#{exec_count}", ":code_cell#1"), ), ) def test_IpynbFormatter__format( notebook_cell_format: str, cell_format_str: str, notebook_parser: NotebookParser, file_path_list: List[str], format_str: str, expected_result_str: str, ): mocked_option = get_mocked_option(notebook_cell_format, format_str) formatter = IpynbFormatter(mocked_option) # type: ignore if file_path_list: filename = expected_filename = os.path.join(*file_path_list) else: expected_filename = f"{TEST_NOTEBOOK_PATH}{cell_format_str}" filename = get_test_intermediate_path(notebook_parser.intermediate_py_file_paths) mock_error = get_mocked_violation(filename, 8) result = formatter.format(mock_error) expected_result = expected_result_str.format(expected_filename=expected_filename) assert result == expected_result

31.51145

98

0.664244

494

4,128

5.188259

0.200405

0.058525

0.063207

0.025361

0.415139

0.404604

0.353102

0.318767

0.253999

0.200546

0

0.016614

0.227229

4,128

130

99

31.753846

0.786834

0.002907

0

0.273504

0

0.239912

0.142197

0

0.034188

1

0.042735

false

0

0.068376

0.025641

0.136752

0

null

0

null

0

1

0